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ASSOCIATION OF DIETARY INTAKE WITH THE TRANSITIONS OF FRAILTY AMONG JAPANESE COMMUNITY-DWELLING OLDER ADULTS

 

R. Otsuka1, S. Zhang1, C. Tange1, Y. Nishita1, M. Tomida1, K. Kinoshita2, Y. Kato1,3, F. Ando1,3, H. Shimokata1,4, H. Arai5

 

1. Department of Epidemiology of Aging, Research Institute, National Center for Geriatrics and Gerontology, Aichi, Japan; 2. Department of Frailty Research, Research Institute, National Center for Geriatrics and Gerontology, Aichi, Japan; 3. Faculty of Health and Medical Sciences, Aichi Shukutoku University, Aichi, Japan; 4. Graduate School of Nutritional Sciences, Nagoya University of Arts and Sciences, Aichi, Japan; 5. National Center for Geriatrics and Gerontology, Aichi, Japan.

Corresponding Author: Rei Otsuka, Department of Epidemiology of Aging, Research Institute, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, Aichi 474-8511, Japan, E-mail: otsuka@ncgg.go.jp, Tel: +81-562-46-2311

J Frailty Aging 2021;in press
Published online October 7, 2021, http://dx.doi.org/10.14283/jfa.2021.42

 


Abstract

Background: Frailty is a dynamic process, with frequent transitions between frailty, prefrailty, and robust statuses over time. The effect of dietary intake on frailty transitions is unknown.
Objective: To examine the association between dietary intake and frailty transitions.
Design: Survey-based retrospective analysis of the National Institute for Longevity Sciences-Longitudinal Study of Aging data.
Setting: Areas neighboring the National Center for Geriatrics and Gerontology in Aichi Prefecture, Japan.
Participants: We included 469 prefrail community dwellers aged 60–87 years who participated both in the baseline (2008–2010) and 2-year follow-up (2010–2012) surveys of the National Institute for Longevity Sciences-Longitudinal Study of Aging.
Measurements: Transitions of frailty were categorized by changes in status from baseline to follow-up: “deterioration (prefrail to frail),” “persistence (persistent prefrail),” and “reversal (prefrail to robust).” Estimated dietary (nutrients and food) intakes assessed by 3-day dietary records in each frailty transition were analyzed with a multivariate-adjusted general linear model after adjusting for sex, age, education, family income, smoking, and chronic disease.
Results: At the 2-year follow-up, 28%, 7%, and 65% of participants had robust, frail, and pre-frail status, respectively. Among 13 food groups, only milk and dairy product intake was positively associated with frailty reversal even after adjusting for all frailty criteria at baseline. Despite insignificant differences in the estimated mean intakes, the baseline intake of saturated fatty acids, potassium, and vitamin B1 tended to be the highest in the reversal group. The estimated mean (standard error) for milk and dairy product intake (g/day) was 79.1 (28.6), 129.3 (19.9), and 161.7 (21.7) for the deterioration, persistence, and reversal groups, respectively (P=0.0036, P-trend=0.0019).
Conclusions: Daily consumption of dairy products may contribute to frailty reversal and frailty prevention among older community dwellers who consume small amounts of dairy products. Other food groups showed no association with frailty status transitions.

Key words: Frailty, reversibility, diet, retrospective study.


 

Introduction

Frailty is an emerging global burden among the older population (1) and is characterized by a decline in functioning across multiple physiological systems that is accompanied by an increased vulnerability to stressors. Frailty is a dynamic process, with frequent transitions between frailty, prefrailty, and robust statuses over time. As an intermediate state between robust and frailty, those with prefrailty have a high risk of progressing to frailty (2, 3). Pre-frailty naturally tends to rapidly worsen and transit to frailty. However, previous studies have shown that prefrail individuals may reverse toward a robust state if appropriate interventions are taken (for example, improving nutritional intake or increasing physical activity) (4-7). Considering the high prevalence (approximately 50%) of prefrail individuals in the older population (8, 9), identifying potentially modifiable risk factors for prefrail transitions is needed.
Review studies have shown that dietary factors, such as macronutrients (e.g., protein), micronutrients [e.g., carotenoids and 25(OH)D], food groups (e.g., low-fat dairy products), and dietary patterns (e.g., the Mediterranean diet), are related to frailty syndrome or frail criteria (10-12). However, the subjects of these studies were predominantly non-frail individuals. Meanwhile, interventional studies on frail participants suggested similar promising effects of dietary factors on frailty improvement. Nevertheless, the duration in most of the interventional studies was too short (from a few weeks to 6 months) to yield long-term outcomes (10, 12). Therefore, the effect of dietary intake on frail transitions is unknown.
In this retrospective study, we focused on prefrail individuals at baseline and examined changes in their status at the 2-year follow-up. We aimed to evaluate the association between baseline dietary intake and 2-year frailty transitions to clarify the dietary/nutritional factors that are related to frailty deterioration and reversal among older community dwellers.

 

Methods

Study design and participants

Data for this survey were obtained from the National Institute for Longevity Sciences-Longitudinal Study of Aging (NILS-LSA), which used detailed questionnaires, medical checkups, anthropometric measurements, physical fitness tests, and nutritional examinations to assess the normal aging process over time. NILS-LSA participants comprised randomly selected age- and sex-stratified individuals from a pool of community-dwelling residents of Obu City and Higashiura Town, which are in the neighborhood of the National Center for Geriatrics and Gerontology in Aichi Prefecture, Japan. The initial survey of the NILS-LSA involved 2,267 men and women aged between 40 and 79 years, including approximately 280 men and 280 women in each decade of age. These subjects were followed-up every 2 years from the first wave (November 1997–April 2000) to the second wave (April 2000–May 2002), third wave (May 2002–May 2004), fourth wave (June 2004–July 2006), fifth wave (July 2006–July 2008), sixth wave (July 2008–July 2010), and seventh wave (July 2010–July 2012). When participants could not be followed up (e.g., moved to another area, dropped out for personal reasons, or died), except for those aged 80 years or older, new decade- and sex-matched participants were randomly recruited from the second to seventh waves. Moreover, participants aged ≥40 years were newly recruited every year. Each wave included approximately 2300 men and women. The Committee on the Ethics of Human Research of the National Center for Geriatrics and Gerontology approved the study protocol (No. 899-6), and written informed consent was obtained from all participants. Details of the NILS-LSA have been reported previously (13).
Given the small number of older adults in the first to fifth waves of the NILS-LSA, the sixth wave was used as the baseline, and the seventh wave was used as the follow-up survey (Figure 1). The main study of NILS-LSA sixth wave included participants aged 40 to 89 years, but this study focused on older adults aged ≥60 years. We considered individuals aged ≥60 years as older adults.
The baseline included 1,173 men and 1,129 women (age range: 40–89 years), and the exclusion criteria (shown in Figure 1) were as follows: 1) age <60 years at baseline (n = 1,042), 2) non-participation in the follow-up (n = 205), 3) lack of body weight measurement at the fifth wave (n = 53; this was important because shrinking at baseline could not be assessed otherwise), 4) incomplete data of any frailty criterion at baseline (n = 11), 5) definition as frail (n = 57) or robust (n = 416) at baseline, and 6) incomplete data on nutritional assessments (n = 29) or self-reported questionnaires (n = 20) at baseline.
Ultimately, the data of 469 Japanese older adults (232 men and 237 women, aged 60–87 years) were available for analysis. The mean (standard deviation) interval between baseline and follow-up for all participants was 2.0 (0.1) years.

Figure 1. Participant flow chart and variables used in the analyses

Frailty assessment and transitions

Frailty was assessed using five criteria—slowness, weakness, exhaustion, low activity, and shrinking—based on a modified set of criteria established by the Cardiovascular Health Study (14). Details of the modified criteria have been reported previously (15).
In brief, slowness was defined as gait disturbance or a gait speed <1.0 m/s in a 10-m walk test using a comfortable gait. Weakness was defined as a maximum grip strength <26 and <18 kg for men and women, respectively. Exhaustion was assessed through self-reports based on responses to two statements in the Center for Epidemiologic Studies Depression Scale (16): the statements included “I felt that everything I did was an effort,” and “I could not get ‘going.’” The responses included “Rarely or none of the time (less than 1 day during the past week),” “Some or a little of the time (1–2 days),” “Occasionally or a moderate amount of time (3–4 days),” and “Most or all of the time (5–7 days).” Participants who did not answer “Rarely or none of the time” for both statements were identified as showing exhaustion. Low activity was defined as the lowest 20% metabolic equivalents of leisure-time physical activity based on sex, assessed using the modified Minnesota Leisure-time Physical Activity Questionnaire (17). Shrinking was defined as a ≥5% weight loss within the preceding 2 years (during the fifth to sixth [baseline] and sixth to seventh [follow-up] waves).
Frailty was defined as meeting 3 or more criteria, prefrailty was defined as meeting 1–2 criteria, and robustness was defined as not meeting any of the prespecified frailty criteria. Thus, transitions of frailty among prefrail participants at baseline (n = 469) were categorized into three groups according to changes in status from baseline to follow-up: “deterioration (prefrail to frail),” “persistence (persistent prefrail),” and “reversal (prefrail to robust).”
Supplemental Table 1 shows the prevalence of each frailty criterion at baseline and follow-up according to frailty transitions.

Nutritional assessments

On the day they participated in the baseline survey, trained dietitian staff explained the purpose and methods of the dietary record survey during lunchtime. The participants were instructed to take the survey on days when they ate normal meals as much as possible, avoiding special days such as anniversaries, because the dietary survey assessed their normal dietary habits. During this time, a 1-kg kitchen scale (Sekisui Jushi, Tokyo, Japan) and one and/or more disposable camera (27 shots; Fuji Film, Tokyo, Japan) were provided to all participants, and a practice session on taking pictures with the disposable camera was also conducted (Appendix Figure 1).
After participation in the baseline study, subjects completed a 3-day dietary record to assess dietary intake, including supplement use. The dietary record was completed over 3 consecutive days (2 weekdays and 1 day in the weekend) since food habits differed on weekdays and weekends; 3 consecutive days were selected based on the same method used by the National Health and Nutrition Examination Survey in Japan (18, 19).
All food items, including spices and seasonings, were weighed/measured separately on the 1-kg kitchen scale with a lightweight cup or spoon before being cooked, or the portion sizes were estimated. During the 3 days, all activities of eating and drinking, including consuming snacks, were noted in detail. In addition, subjects used the disposable camera to take photos of their meals before and after eating. When taking the photos, they were asked to place a scale paper on the dining table so that we could estimate the size of the plates and foods. If it was difficult for the subjects to write detailed records (i.e., if they were not in charge of cooking), the cooks conducted the recording. Subjects completed the dietary record at home, and most returned it within 1 month.
The films in the returned disposable cameras were developed. Dietitians then used these photos to complete the missing information in each subject’s dietary record and assigned a code number from the Standard Tables of Food Composition in Japan 2010 (20) for every food (the number of codes in each subject’s records was around a few hundreds). Based on the code number and weight records, we used the Statistical Analysis System software version 9.3 (SAS Institute, Cary, NC, USA) to calculate the average food and nutrient intake (including alcohol intake) over 3 days from the nutrient intakes included in the Standard Tables of Food Composition in Japan 2010 (20), without using any dietary assessment software. There are 17 food groups in the Japanese food composition table (14): cereals, potatoes, sugars and sweeteners, beans, nuts and seeds, vegetables (non-green-yellow/green-yellow), fruits, mushrooms, seaweed, fish and shellfish, meats, eggs, milk and dairy products, fats and oils, confectionaries, beverages, and seasoning and spices. In this study, we included 13 food groups: cereals, potatoes, beans, nuts and seeds, non-green-yellow vegetables, green-yellow vegetables, fruits, mushrooms, seaweed, fish and shellfish, meats, eggs, milk and dairy products, and excluded sugars and sweeteners, fats and oils, confectionaries, beverages, and seasoning and spices. Each food group contains dozens or hundreds of foods, for example, the milk and dairy products group contains the nutritional values of 52 different foods, including natural milk, low-fat milk, yogurt, cheese, and butter.
Calculating the nutrient values for each subject based on the coding chart took several hours even for a trained dietitian, and the values were checked by two or more other trained dietitians to prevent coding errors. Information on any discrepancies and any requisite additional information was obtained via telephone calls to the subjects. However, if the records were still insufficient, the dietary survey data were considered missing.

Other measurements

Weight and height were measured in the fasting state (around 9–10 am) to the nearest 0.1 kg and 0.1 cm, respectively, with participants wearing light clothing and no shoes. The body mass index was calculated as the body weight in kilograms divided by the square of the height in meters. Data on years of education (≤12 or ≥13 years of school), annual family income (<5.5 or ≥5.5 million yen per year), smoking status (current, never/former), and chronic disease history (past and present stroke, heart disease, hypertension, dyslipidemia, and diabetes mellitus; yes/no, for each) were collected using a self-administered questionnaire and confirmed by medical doctors or trained staff.

Statistical analysis

According to frailty transitions, differences in proportions and means of baseline characteristics were assessed using the chi-squared test and general linear model, respectively. As for dietary variables, we selected the parametric test (general linear model) because each variable is a continuous quantity and the distribution was close to a normal distribution. A general linear model adjusted for sex, baseline age, years of education, annual family income, smoking status, and history of chronic disease was applied to compare baseline nutrient intakes according to the frailty transitions. Moreover, to compare baseline food intakes according to frailty transitions, general linear regression was performed again. Model 1 was adjusted for sex, baseline age, years of education, annual family income, smoking status, and chronic disease history. Model 2 was further adjusted for the total number of frailty criteria at baseline. BMI and physical activity were not treated as an adjustment factor because 1) the weight used in the BMI calculation was used to determine the weight loss (shrinking) of the frailty component, 2) the leisure-time physical activity was used to determine the low activity of the frailty component.
To test any trend in the association between dietary intakes and frailty transitions, the trend test of the general linear model was applied with ascending ordinal values −1, 0, and 1 assigned to “deterioration (prefrail to frail),” “persistence (persistent prefrail),” and “reversal (prefrail to robust),” respectively. In sub-analyses, we focused on dairy intakes and estimated the daily mean dairy intakes (including milk, yogurt, and cheese) according to frailty transitions using the general linear model. Adjustments were the same as those in Model 2.
All statistical analyses were performed using the Statistical Analysis System software version 9.3 (SAS Institute, Cary, NC, USA). All reported P-values were two-sided, and a P-value <0.05 was considered significant.

 

Results

At the 2-year follow-up, 28% (n = 130) of participants had reversed to robust status, whereas 7% (n = 32) and 65% (n = 307) had deteriorated to frail and remained at prefrail statuses, respectively. Participants in the reversal group were younger than those in the other two groups. Although the prevalence of chronic disease (except dyslipidemia) tended to be high in the deterioration group, no significant differences were observed (Table 1).

Table 1. Baseline characteristics of subjects according to the transitions of frailty

*General linear model used for continuous variables; χ2 test used for the categorical variables; †Trend test of the general linear model used with ascending ordinal values −1, 0, and 1 assigned to “deterioration,” “persistence,” and “reversal,” respectively.

 

Table 2 shows the multivariate-adjusted baseline nutrient intakes according to transitions of frailty. After adjusting for sex, baseline age, years of education, annual family income, smoking status, and chronic disease history, the baseline intake of saturated fatty acids, potassium, and vitamin B1 tended to be high in the reversal group (P-trend: 0.03, 0.04, and 0.02, respectively), although the differences in estimated mean intakes were not significant among the three groups.

Table 2. Baseline nutrient intakes according to the transitions of frailty *

*General linear model used. Adjusted for sex, baseline age, years of education, annual family income, smoking status, and chronic disease history; †Trend test of the general linear model used with ascending ordinal values −1, 0, and 1 assigned to “deterioration,” “persistence,” and “reversal,” respectively; ‡Estimated mean (standard error), all such values.

 

Table 3 shows the baseline food intakes according to the transitions of frailty. After multivariate adjustment, milk and dairy product intake were positively associated with frailty reversal. The corresponding estimated mean (standard error) values for milk and dairy products intake (g/day) for “frailty deterioration,” “frailty persistence,” and “frailty reversal” were 79.1 (28.6), 129.3 (19.9), and 161.7 (21.7), respectively (P-value 0.0036, P-trend 0.0019; Model 1). Even after adjusting for the total number of frailty criteria at baseline, the positive association remained (P-value 0.0028, P-trend 0.0014; Model 2). No other food intake was associated with frailty reversal.
In sub-analyses (Supplemental Table 2), milk and yogurt intake, but not cheese intake, were positively associated with frailty reversal.

Table 3. Baseline food intakes according to transitions of frailty *

*General linear model was used; †Adjusted for sex, baseline age, years of education, annual family income, smoking status, and chronic disease history. ‡Adjusted for Model 1 + total number of frailty criteria at baseline; §Trend test of the general linear model used with ascending ordinal values −1, 0, 1 assigned to “deterioration,” “persistence,” and “reversal,” respectively; ||Estimated mean (standard error), for all such values.

 

Discussion

This retrospective study indicated that dairy product intake was positively associated with frailty reversal among older community dwellers. To our best knowledge, this is the first study to investigate the association between dietary intake and frailty transitions.
Cuesta-Triana et al. (21) reviewed the effect of milk and other dairy products on the risk of frailty, sarcopenia, and cognitive performance decline in older adults. They concluded that dairy product consumption might reduce the risk of frailty, especially high consumption of low-fat milk and yogurt. In our study, milk and yogurt intake, but not low-fat milk or cheese intake, were associated with frailty reversal. This may be because our participants consumed relatively low amounts of low-fat dairy products (mean 21.1 g/day) and cheese (mean 2.5 g/day); therefore, the association between the intake of these products and frailty transitions was difficult to determine. Although the mean value of dairy product intake in our study was smaller than reports from previous (Spain) studies (306 g vs. 141 g per day) among robust community-dwelling older adults (21, 22), both studies observed benefits of high dairy product intake on frailty prevention. A recent study indicated that dairy consumption was associated with a lower risk of mortality and major cardiovascular disease events in a diverse multinational cohort in 21 countries (23). This suggests that daily dairy product consumption may protect frailty development both in robust and prefrail older adults.
Dairy products are good sources of protein, vitamins, and minerals (24), and these nutrients are considered to play an important role in the prevention of frailty. Although the differences in the estimated mean intakes were not significant, the intake of saturated fatty acids, potassium, and vitamin B1 tended to be highest in the reversal group among the frailty transition groups. A higher percentage of saturated fatty acid intake was associated with both higher frailty and mortality (25), even after considering the degree of nutritional deficits. However, the mean total fatty acid and saturated fatty acid intakes were higher in that study (25) compared to our sample (total fatty acid: 75.65 g vs. 46.3–50.8 g per day, saturated fatty acid: 24.77 g vs. 12.2–14.4 g per day; Table 2). Therefore, while excessive intake of saturated fatty acids is detrimental to frailty, the moderate intake of saturated fatty acids among older adults who consume small amounts of saturated fatty acid may be effective in preventing frailty.
Potassium exerts beneficial effects on cardiovascular diseases (26). The salt intake of the Japanese people is extremely high compared to the rest of the world, and in our sample, the sodium intake was 3809.2, 3976.7, and 3891.4 mg, the potassium intake was 2415.8, 2615.3, and 2676.7 mg, and the sodium/potassium ratio was 1.58, 1.52, and 1.54 for the deterioration, persistence, and reversal groups, respectively. Therefore, in a population that has a high salt intake, the high potassium intake may partly modify the frailty status through a reduction in the risk of cardiovascular disease because high sodium intake is a strong risk factor for cardiovascular disease (27). The results of this study indicate frailty reversal in older adults with high potassium intake. Among Japanese cohorts, vitamin B1, potassium, and other micronutrient intake were cross-sectionally lower in the prefrailty group (26, 28). These nutrients, including saturated fatty acids, potassium, and vitamin B1, are found abundantly in vegetables, fruits, meat, and/or fish; thus, dairy product intake may not be solely responsible for the improved nutritional status. As the nutritional status of our subjects was relatively good compared to the results of the National Health and Nutrition Examination Survey in Japan (29), the difference in the dairy intake may have affected their prognosis in terms of the frailty status.
Furthermore, the differences in the estimated mean total protein intakes were not significant among the transitions of frailty groups. Therefore, health awareness and accessibility to dairy products may play a role in improving prefrail status by promoting physical and mental health rather than simply relying on protein intake. In our previous study, the intake of dairy products and fruits decreased with age (30). These foods need to be fresh and are difficult for Japanese families and communities to procure and grow at home. Furthermore, these foods are usually heavy and difficult to carry home from the store, which may cause prefrail older adults to refrain from purchasing them. Therefore, our findings indicate that health awareness and actions may be key factors for frailty reversal.
The proportion of transitions among our prefrail participants was similar to that of a previous study. Corresponding proportions for “reversal,” “persistence,” and “deterioration” were 35%, 55%, and 7% over 1.6 years (31) (28%, 65%, and 7% over 2 years in our study). Considering that there are many prefrail older adults in the community and that frailty reversal is highly achievable, advocating dairy intake may be an important nutritional strategy to promote health and prevent frailty.
The strengths of our study are as follows: (1) this was the first study that investigated the association between dietary intake and frailty transitions among prefrail older participants; (2) dietary and nutritional intake was assessed by 3-day dietary records and photographs, which may introduce less recall bias than other methods (e.g., dietary recall and self-reported questionnaires); (3) the estimated mean consumptions of milk and yogurt were 96.5 g/day and 36.4 g/day in the “frailty reversal” group, which are almost half a cup of milk and yogurt. Therefore, if accessed sustainably, even older adults could easily consume these volumes. In other words, at the level of public health policy formulation and advocacy, our findings provide more feasible evidence for frailty prevention and health promotion.
Our study has a few limitations that warrant consideration. First, dietary and nutritional intake was only assessed at baseline. Diet naturally changes over time, and it is affected by various factors related to aging. Second, a 3-day dietary record was not enough to accurately assess long-term eating habits. In addition, the Japanese intake of dairy products is relatively lower than the average global intake (29, 32). Therefore, our findings may not be generalizable to Western populations who consume larger amounts of dairy products. However, even among Western populations, the consumption of dairy products would decline with age; thus, our findings may be valuable for those populations.
In conclusion, consumption of dairy products, including milk and yogurt, might be beneficial for promoting frailty reversal and frailty prevention among older community dwellers who consume small amounts of dairy products. Our findings might be applicable for robust and frail individuals. Future studies are needed to address this hypothesis.

 

Funding: This work was supported in part by grants from the Food Science Institute Foundation and Research Funding for Longevity Sciences from the National Center for Geriatrics and Gerontology, Japan (grant number 19-10,21-18). The sponsors had no role in the design and conduct of the study; in the data collection, analysis, and interpretation; in the preparation of the manuscript; or in the review or approval of the manuscript.

Acknowledgments: We wish to express our sincere appreciation to the study participants and our colleagues in the NILS-LSA for completing the surveys in this study.

Conflicts of interest: All authors declare no conflicts of interest.

Ethical Standards: This study was carried out in accordance with the ethical standards.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

SUPPLEMENTARY MATERIAL1

SUPPLEMENTARY MATERIAL2

 

References

1. Hoogendijk EO, Afilalo J, Ensrud KE, Kowal P, Onder G, Fried LP. Frailty: implications for clinical practice and public health. Lancet 2019;394:1365-1375. doi: 10.1016/S0140-6736(19)31786-6.
2. Xue QL. The frailty syndrome: definition and natural history. Clin Geriatr Med 2011;27:1-15. doi: 10.1016/j.cger.2010.08.009.
3. Fallah N, Mitnitski A, Searle SD, Gahbauer EA, Gill TM, Rockwood K. Transitions in frailty status in older adults in relation to mobility: a multistate modeling approach employing a deficit count. J Am Geriatr Soc 2011;59:524-529. doi: 10.1111/j.1532-5415.2011.03300.x.
4. Michel JP, Cruz-Jentoft AJ, Cederholm T. Frailty, Exercise and Nutrition. Clin Geriatr Med 2015;31:375-387. doi: 10.1016/j.cger.2015.04.006.
5. Kojima G, Taniguchi Y, Iliffe S, Jivraj S, Walters K. Transitions between frailty states among community-dwelling older people: A systematic review and meta-analysis. Ageing Res Rev 2019;50:81-88. doi: 10.1016/j.arr.2019.01.010.
6. Gill TM, Gahbauer EA, Allore H, Han L. Transitions between frailty states among community-living older persons. Arch Intern Med 2006;166:418-423. doi: 10.1001/archinte.166.4.418.
7. Mendonça N, Kingston A, Yadegarfar M, et al. Transitions between frailty states in the very old: the influence of socioeconomic status and multi-morbidity in the Newcastle 85+ cohort study. Age Ageing 2020;49:974-981. doi: 10.1093/ageing/afaa054.
8. Hanlon P, Nicholl BI, Jani BD, Lee D, McQueenie R, Mair FS. Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants. Lancet Public Health 2018;3:e323-e332. doi: 10.1016/S2468-2667(18)30091-4.
9. Siriwardhana DD, Hardoon S, Rait G, Weerasinghe MC, Walters KR. Prevalence of frailty and prefrailty among community-dwelling older adults in low-income and middle-income countries: a systematic review and meta-analysis. BMJ Open 2018;8:e018195. doi: 10.1136/bmjopen-2017-018195.
10. Yannakoulia M, Ntanasi E, Anastasiou CA, Scarmeas N. Frailty and nutrition: From epidemiological and clinical evidence to potential mechanisms. Metabolism 2017;68:64-76. doi: 10.1016/j.metabol.2016.12.005.
11. Lorenzo-López L, Maseda A, de Labra C, Regueiro-Folgueira L, Rodríguez-Villamil JL, Millán-Calenti JC. Nutritional determinants of frailty in older adults: A systematic review. BMC Geriatr 2017;17:108. doi: 10.1186/s12877-017-0496-2.
12. Morante JJH, Martínez CG, Morillas-Ruiz JM. Dietary factors associated with frailty in old adults: a review of nutritional interventions to prevent frailty development. Nutrients 2019;11:102. doi: 10.3390/nu11010102.
13. Shimokata H, Ando F, Niino N. A new comprehensive study on aging–the National Institute for Longevity Sciences, Longitudinal Study of Aging (NILS-LSA). J Epidemiol 2000;10:S1-S9. doi: 10.2188/jea.10.1sup_1.
14. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146-M156. doi: 10.1093/gerona/56.3.m146.
15. Yuki A, Otsuka R, Tange C, et al. Epidemiology of frailty in elderly Japanese. J Sports Med Phys Fitness 2016;5:301-307.
16. Radloff LS. The CES-D Scale: a self-report depression scale for research in the general population. Appl Psychol Meas 1977;1:385-401.
17. Kozakai R, Doyo W, Tsuzuku S, et al. Relationships of muscle strength and power with leisure-time physical activity and adolescent exercise in middle-aged and elderly Japanese women. Geriatr Gerontol Int 2005;5:182-188.
18. Imai T, Sakai S, Mori K, Ando F, Niino N, Shimokata H. Nutritional assessments of 3-day dietary records in National Institute for Longevity Sciences–Longitudinal Study of Aging (NILS-LSA). J Epidemiol 2000;10:S70-S76. doi: 10.2188/jea.10.1sup_70.
19. Yoshiike N, Matsumura Y, Iwaya M, Sugiyama M, Yamaguchi M. National Nutrition Survey in Japan. J Epidemiol 1996;6:S189-200. doi: 10.2188/jea.6.3sup_189.
20. Ministry of Education Culture, Sports, Science and Technology. Standard Tables of Foods Composition in Japan 2010. Ishiyaku-syuppan.
21. Cuesta-Triana F, Verdejo-Bravo C, Fernández-Pérez C, Martín-Sánchez FJ. Effect of milk and other dairy products on the risk of frailty, sarcopenia, and cognitive performance decline in the elderly: a systematic review. Adv Nutr 2019;10:S105-S119. doi: 10.1093/advances/nmy105.
22. Lana A, Rodriguez-Artalejo F, Lopez-Garcia E. Dairy consumption and risk of frailty in older adults: a prospective cohort study. J Am Geriatr Soc 2015;63:1852-1860. doi: 10.1111/jgs.13626. doi: 10.1111/jgs.13626.
23. Dehghan M, Mente A, Rangarajan S, et al. Association of dairy intake with cardiovascular disease and mortality in 21 countries from five continents (PURE): a prospective cohort study. Lancet 2018;392:2288-2297. doi: 10.1016/S0140-6736(18)31812-9.
24. Thorning TK, Raben A, Tholstrup T, Soedamah-Muthu SS, Givens I, Astrup A. Milk and dairy products: good or bad for human health? An assessment of the totality of scientific evidence. Food Nutr Res 2016;60:32527. doi: 10.3402/fnr.v60.32527.
25. Jayanama K, Theou O, Godin J, Cahill L, Rockwood K. Association of fatty acid consumption with frailty and mortality among middle-aged and older adults. Nutrition 2020;70:110610. doi: 10.1016/j.nut.2019.110610.
26. Liu F, Zhang R, Zhang W, et al. Potassium supplementation blunts the effects of high salt intake on serum retinol-binding protein 4 levels in healthy individuals. J Diabetes Investig 2021;12:658-663. doi: 10.1111/jdi.13376.
27. Cook NR, Appel LJ, Whelton PK. Lower levels of sodium intake and reduced cardiovascular risk. Circulation 2014;129:981-989. doi: 10.1161/CIRCULATIONAHA.
28. Kaimoto K, Yamashita M, Suzuki T, et al. Association of protein and magnesium intake with prevalence of prefrailty and frailty in community-dwelling older Japanese women. J Nutr Sci Vitaminol (Tokyo) 2021;67:39-47. doi: 10.3177/jnsv.67.39.
29. Ministry of Health, Labour and Welfare. The National Health and Nutrition Survey in Japan. 2009. http://www.mhlw.go.jp/bunya/kenkou/eiyou/h21-houkoku.html. Accessed [17 April 2021].
30. Otsuka R, Nishita Y, Tange C, et al. Dietary diversity decreases the risk of cognitive decline among Japanese older adults. Geriatr Gerontol Int 2017;17:937-944. doi: 10.1111/ggi.12817.
31. Gill TM, Gahbauer EA, Allore HG, Han L. Transitions between frailty states among community-living older persons. Arch Intern Med 2006;166:418-423. doi: 10.1001/archinte.166.4.418.
32. Micha R, Khatibzadeh S, Shi P, et al. Global, regional, and national consumption levels of dietary fats and oils in 1990 and 2010: a systematic analysis including 266 country-specific nutrition surveys. BMJ 2014;348:g2272. doi: 10.1136/bmj.g2272.

OLDER PERSONS “LOST” TO THE COVID-19 VACCINATION: WHERE ARE THEY?

 

M. Cesari1, B. Vellas2

 

1. Geriatric Unit, IRCCS Istituti Clinici Scientifici Maugeri, University of Milan, Milan, Italy; 2. Gerontopole – Inspire Program, UMR INSERM 1295, Toulouse University Hospital, University of Toulouse Paul Sabatier, Toulouse, France

Corresponding Author: Matteo Cesari, MD, PhD. IRCCS Istituti Clinici Scientifici Maugeri; via Camaldoli 64, 20138 Milan – Italy. Email: macesari@gmail.com; Twitter: @macesari

J Frailty Aging 2021;10(4)308-309
Published online September 17, 2021, http://dx.doi.org/10.14283/jfa.2021.37

 


Key words: Vaccines, geriatrics, frailty, integrated care, social care.


 

The COVID-19 pandemic has substantially changed our lives. It has also acted as a sort of stress test for care systems, letting emerge all the inconsistencies, weaknesses, and contradictions of them. In particular, frail persons have shown to be those paying the most severe consequences of the general disservices (1). To date, in the absence of specific drugs against the SARS-CoV-2, preventive measures against infection and vaccination represent the only available weapons. Social distancing, hand hygiene, and protective personal equipment have been immediately put in place since the very first phases of the pandemic. Starting in December 2020, vaccines against the SARS-CoV2 infection have been made available and mass campaigns of vaccinations have started worldwide.
Given the high-risk profile exhibited by older persons with frailty, these have been usually prioritized in the vaccination campaigns. Today, the vaccine administration is primarily focused to adults and young persons. Whereas it is generally assumed that the older population has now been vaccinated, a recent survey has suggested that many persons aged 80 years and older (almost 20%) are not yet (2). Indeed, as reported, “statistics from the Centers for Disease Control and Prevention showed this population’s vaccination rates soaring through the spring, then hitting a plateau”.
Which are the barriers precluding the vaccination of so many persons at risk of the most severe consequences of COVID-19? Several reasons can be hypothesized:
– Older persons may refuse the vaccination for personal opinions or because influenced by their proxies. In this context, the presence of cognitive impairment and difficulties in judgment might affect the capacity to decide, relying on what younger persons (potentially less concerned by the severity of the virus and more exposed to fake news) choose for them. In this context, it is important to consider that the many no-vax messages might have, directly and indirectly, influenced the most vulnerable ones (due to their frail status and/or low socio-cultural conditions).
– The frailty status of many older persons can complicate the access to the vaccination. Difficulties in the use of technologies for scheduling an appointment, mobility impairment and/or social isolation hampering the possibility to reach the vaccination site, cognitive disorders affecting the capacity to take and retain the appointment… are all examples of potential underestimated barriers.
– The pandemic has made clear that the hospital-centered design of our healthcare systems is not suitable for many persons living with frailty (3). Their protection implies the adoption of a more comprehensive approach, leaving the traditional standalone disease-model in favor of a holistic vision of the individual inclusive of his/her environment. In this context, it cannot be ignored how most of the vaccination campaigns are centered on hubs in the community where persons can go to receive their vaccine dose. However, relatively low interest has been put for supporting primary care and facilitate the vaccination of the frailest individuals who are home-bound. Indeed, the COVID-19 pandemic has exposed the extreme paucity of resources and infrastructures devoted to older persons where they live and age (i.e., in the community). More research is needed to better understand how many and why older persons are still “lost” to our care systems. This is pivotal to develop future strategies allowing the provision of preventive care in the community to the most vulnerable persons.

Access to care has been extremely difficult for many persons over the past months, not only because of the restrictions and lockdowns applied by governments during the hardest moments of the pandemic. Older persons have specially suffered the fragmentation of care and the prolonged disruptions of services (often motivated by the need of facing the COVID-19 emergency). The procrastination of routine clinical evaluations, often combined with the older person’s fear of being infected, has uphold many interventions that were instead needed (4). Furthermore, the lifestyle modifications forcedly brought by the pandemic have negatively impacted on the health status of the most vulnerable persons, worsening their functions and clinical conditions (5,6). The functional loss and social isolation developed by older persons over the past months will likely result in major consequences in the next future, both in terms of 1) frailer and more complex patients, and 2) incapacity of services to adequately address the increasing demands.
Interestingly, a recent study by Ankuda and colleagues (7) has recently described an exponential increase of community-dwelling older persons who have become home-bound (i.e., leaving the house once a week or less) during these months of pandemics. These persons are exposed to particularly high risk of negative outcomes. Their risk profile is further enhanced by their social isolation preventing them from prompt access to care. A further example is coming from Italy. During the vaccination campaign, almost 500-thousand persons (that is about 1% of the Italian population) were untraceable and difficult to reach. They are socially isolated, tend to live in rural areas, have no internet/phone connection, and/or move frequently across the country. In other words, the COVID-19 pandemic is showing the existence of a population of frail individuals for which a completely different model of care is needed. The usual reactive approach is evidently not working for them, and proactive/preventive strategies are needed.
Under the current COVID-19 situation, we would like to stress the importance of the following points:
1. With the aging of our population and the increasing number of socially isolated individuals, the system cannot anymore just wait for the incoming request. The continuation of this obsolete approach will contribute at accelerating the collapse of the systems which are designed for late interventions. It is necessary to reshape our clinical and public health strategies for anticipating the problems and act when the case is still reversible (for the benefit of the person and the community)(8).
2. Instead of waiting that the problem arrives to the attention of clinical and social services, it is necessary to identify the early signs of future issues to preventively intervene. This means the building of multidisciplinary bridges facilitating the sharing of relevant information across settings for the development of person-centered actions.
3. In this context, it is noteworthy the work conducted by the World Health Organization (WHO) to promote the integration and continuum of care (9). The WHO has repeatedly recommended over the past years to modify the approach to older persons by implementing preventive strategies and personalization of interventions (e.g., ICOPE Program)(10). Every point of contact between the individual and the care system should become an opportunity for estimating the residual reserves (i.e., intrinsic capacity) and abilities (i.e., functional ability) (11). The resulting information may then be used to track his/her trajectories and identify deviations from the normality.
4. Finally, the adoption of shared technologies is not an option anymore. Indeed, in a world dominated by technologies, it is not anymore acceptable that persons are “lost” to the care system. It is time to take advantage of technologies as exemplified by the ICOPE Monitor, an innovative digital healthcare program designed for community-dwelling older persons with frailty with the final aim of remote monitoring their health status (via nurse assistance) and facilitating access to preventive services (including COVID-19 vaccination) (12, 13).

 

References

1. Merchant R. COVID-19: role of integrated regional health system towards controlling pandemic in the community, intermediate and long-term care. J Frailty Aging. 2020:1-2. doi:10.14283/jfa.2020.39.
2. Span P. More Than 80 Percent of Seniors Are Vaccinated. That’s ‘Not Safe Enough.’ The New York Times. https://www.nytimes.com/2021/09/02/health/covid-vaccines-seniors.html. Published September 2, 2021. Accessed September 3, 2021.
3. Astrone P, Cesari M. Integrated Care and Geriatrics: A Call to Renovation from the COVID-19 Pandemic. J Frailty Aging. October 2020:1-2. doi:10.14283/jfa.2020.59.
4. Briguglio M, Giorgino R, Dell’Osso B, et al. Consequences for the Elderly After COVID-19 Isolation: FEaR (Frail Elderly amid Restrictions). Front Psychol. 2020;11:565052. doi:10.3389/fpsyg.2020.565052.
5. Kirwan R, McCullough D, Butler T, Perez de Heredia F, Davies IG, Stewart C. Sarcopenia during COVID-19 lockdown restrictions: long-term health effects of short-term muscle loss. Geroscience. 2020;42(6):1547-1578. doi:10.1007/s11357-020-00272-3.
6. Canevelli M, Valletta M, Toccaceli Blasi M, et al. Facing Dementia During the COVID-19 Outbreak. J Am Geriatr Soc. 2020;68(8):1673-1676. doi:10.1111/jgs.16644.
7. Ankuda CK, Leff B, Ritchie CS, Siu AL, Ornstein KA. Association of the COVID-19 Pandemic With the Prevalence of Homebound Older Adults in the United States, 2011-2020. JAMA Internal Medicine. August 2021. doi:10.1001/jamainternmed.2021.4456.
8. Barusch A, Waters D. Social engagement of frail elders. J Frailty Aging. 2012;1(4):189-194.
9. World Health Organization, Department of Ageing and Life Course. Integrated Care for Older People.; 2017. http://www.ncbi.nlm.nih.gov/books/NBK488250/. Accessed March 1, 2019.
10. Integrated Care for Older People (ICOPE): Guidance for Person-Centred Assessment and Pathways in Primary Care. World Health Organization; 2019.
11. World Health Organization (WHO). Decade of Healthy Ageing.; 2020. https://www.youtube.com/watch?v=ShmemfpkVLQ&list=PL1F160112BFDBC1D5&index=2. Accessed April 27, 2021.
12. González-Bautista E, De Souto Barreto P, Virecoulon Giudici K, et al. Frequency of Conditions Associated with Declines in Intrinsic Capacity According to a Screening Tool in the Context of Integrated Care for Older People. J Frailty Aging. August 2020. doi:10.14283/jfa.2020.42.
13. Tavassoli N, Piau A, Berbon C, et al. Framework Implementation of the INSPIRE ICOPE-CARE Program in Collaboration with the World Health Organization (WHO) in the Occitania Region. J Frailty Aging. 2021;10(2):103-109. doi:10.14283/jfa.2020.26.

LONG-TERM ASPIRIN USE AND SELFREPORTED WALKING SPEED IN OLDER MEN: THE PHYSICIANS’ HEALTH STUDY

 

A.R. Orkaby1,2, A.B. Dufour3, L. Yang3, H.D. Sesso2, J.M. Gaziano1,2, L. Djousse1,2, J.A. Driver1,2, T.G. Travison3

 

1. New England GRECC, VA Boston Healthcare System, Boston, MA, USA; 2. Brigham & Women’s Hospital and Harvard Medical School, Boston, MA, USA; 3. Marcus Institute for Aging Research, Hebrew Senior Life, and Harvard Medical School, Boston, MA, USA.

Corresponding Author: Ariela Orkaby, MD MPH, Assistant Professor of Medicine, Harvard Medical School, Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, 150 South Huntington St, Boston, MA 02130, USA, aorkaby@bwh.harvard.edu

J Frailty Aging 2021;in press
Published online September 17, 2021, http://dx.doi.org/10.14283/jfa.2021.36

 


Abstract

Background: Mobility limitation is a component of frailty that shares a bidirectional relationship with cardiovascular disease (CVD). Data are limited on the role of established CVD prevention therapies, such as aspirin, for prevention of frailty and mobility limitation.
Objectives: Examine the association between long-term aspirin use and walking speed.
Design, Setting, Participants: Prospective cohort of 14,315 men who participated in the Physicians’ Health Study I, a completed randomized controlled trial of aspirin (1982-1988), with extended post-trial follow-up.
Measurements: Annual questionnaires collected data on aspirin use, lifestyle and other factors. Average annual aspirin use was categorized for each participant: ≤60 days/year and >60 days/year. Mobility was defined according to self-reported walking pace, categorized as: don’t walk regularly (reference), easy/casual <2mph, normal ≥2-2.9mph, or brisk/very brisk ≥3mph. Propensity scoring balanced covariates between aspirin categories. Multinomial logistic regression models estimated odds of being in each self-reported walking category.
Results: Mean age was 70±8 years; mean aspirin use 11 years. There were 2,056 (14.3%) participants who reported aspirin use ≤60 days/year. Aspirin use >60 days/year was associated with drinking alcohol, smoking, hypertension, heart disease and stroke, while ≤60 days/year was associated with anticoagulation use and bleeding history. In all, 13% reported not walking regularly, 12% walked <2 mph, 44% walked ≥2-2.9 mph, and 31% walked ≥3 mph. After propensity score adjustment, regular aspirin use was associated with a faster walking speed. Odds ratios (95% confidence intervals) were 1.16 (0.97 to 1.39), 1.24 (1.08 to 1.43), and 1.40 (1.21 to 1.63) for <2 mph, ≥2-2.9 mph and ≥3 mph, respectively, compared to not walking regularly (p-trend<0.001).
Conclusions: In this cohort of older men, long-term aspirin use is associated with a greater probability of faster walking speed later in life.

Key words: Aspirin, mobility, gait speed, frailty.


 

Introduction

One of the most feared consequences of aging is loss of function and resultant loss of independence (1). Mobility is a critical aspect of function (l) independence, and limitations in mobility – specifically as measured by usual walking speed – are associated with an increased risk of morbidity and mortality (2-4). To date, the only proven therapy to prevent mobility limitation is exercise and leisure-time activity (5).
Mobility limitation is often considered a component of frailty, a state of decreased resilience to stressors that is more common in older adults (6) We have previously demonstrated that slow walking speed is associated with cardiovascular disease (CVD) events (7), and it is thought that frailty and dismobility have a bidirectional relationship with CVD, including peripheral vascular disease (PVD) (8-10). This suggests that pharmacologic therapies targeting CVD may prevent frailty and, specifically, mobility limitation, but this has yet to be investigated.
Among such therapies, aspirin is an intriguing option as it has both anti-inflammatory and anti-thrombotic properties which can improve large and small vessel blood flow and muscle function (11-13). Data from the ASPirin in Reducing Events in the Elderly (ASPREE) trial, demonstrated a reduction in persistent ADL disability among older adults randomized to aspirin vs placebo (14). However, in older adults, data on aspirin are limited and conflicting, with increasing risks of major bleeding largely outweighing benefit for those without a history of CVD (15, 16). In prior work we have shown that long term aspirin use in men is associated with a lower risk of frailty (17). We hypothesized that long term aspirin use, especially if started in middle age when risks of aspirin are minimal, would be associated with a lower risk of mobility limitation measured according to walking speed. We used 15-year follow-up data from men enrolled in the extended observational phases of the Physician’s Health Study (PHS) I.

 

Methods

Cohort

PHS I is a completed double-blind, 2×2 factorial placebo-controlled trial that randomized 22,071 male physicians to either aspirin or placebo, and to beta-carotene or placebo, beginning in 1982 (18-20). At the start of the trial, participants were free of cancer and CVD. The aspirin intervention component of the trial ended early in 1988 at the recommendation of the PHS Data Safety Monitoring Board, due to the highly significant reduction in the rate of total myocardial infarctions among those assigned to aspirin versus placebo (19). Observational follow-up was extended after completion of the trial with annual questionnaires.
Detailed questionnaires were sent to participants annually to collect information on clinical variables, medications, and lifestyle from 1982 through 2012. Questions regarding walking speed were added to the annual questionnaire returned from 2001-2003. Participants responding to this questionnaire were eligible for the cross-sectional analyses described here, which compares participants to one another on the basis of cumulative aspirin exposure irrespective of randomized beta-carotene assignment. Of 14,896 participants who responded to the self-reported walking speed question, 581 were excluded due to missing covariate data. All participants were aged ≥58 years at the time of the walking speed assessment.
All participants executed written informed consent, and the PHS trial and subsequent follow-up were approved by the Institutional Review Board at Brigham and Women’s Hospital in Boston, MA, USA.

Exposure

For the duration of the aspirin trial, participants were randomized to 325 mg aspirin or placebo every other day. The aspirin arm of the trial was stopped after an average of 60 months of follow-up (19). Once the aspirin arm of the trial ended, treatment crossover to aspirin use among those who had been assigned to placebo was greater than 70% (21). Ongoing use of aspirin was asked on every annual questionnaire, with the following question: “Over the past 12 months, on how many days have you taken aspirin or medication containing aspirin? 0 days, 1-13 days, 14-30 days, 31-60 days, 61-90 days, 91-120 days, 121-180 days, 180+days.” For the analyses reported here, aspirin exposure was computed from responses to the questionnaires sent out 1988-2001, corresponding to the year that walking pace was added. Average annual use of aspirin was summed and categorized for each participant as follows: ≤60 days/year (low use), >61 days/year (regular use) for the follow up years post-trial, as has been done previously in PHS (22). Information on the actual dose of aspirin was not available once the trial had ended.

Outcome

A previously validated self-assessment of average walking speed was added to the questionnaire in 2001 (23, 24). The question was asked as follows: “What is your usual walking pace?” with the following possible responses: “Don’t walk regularly; Easy, casual (<2 mph); Normal, average (2-2.9mph); Brisk pace (3-3.9mph); Very brisk, striding (4mph or faster)”. After examining the data distribution, we categorized walking pace into 4 categories: don’t walk regularly, easy casual <2mph, normal ≥2-2.9mph, and brisk or very brisk ≥3mph.

Other Baseline Covariates

Information on demographics, comorbidities, and health, including history of bleeding, heart disease, stroke, peripheral artery disease, arthritis, migraine or headache, atrial fibrillation, or anticoagulation use, was drawn from all prior questionnaires to ensure complete capture of data. Smoking status was quantified as “never, past, or current”. Alcohol consumption was categorized as “daily, weekly, monthly, or rarely”. Cumulative non-aspirin non-steroidal anti-inflammatory drug use (NSAID) was quantified as the average number of years of self-reported NSAID use that were >60 days per year.

Statistical Analysis

Because of significant crossover to aspirin after completion of the intervention phase of the trial and dissolution of its randomized groupings, we developed a propensity score to balance the degree of aspirin exposure over a maximum 15 years of the post-intervention follow-up by relevant covariates. Estimation of the propensity score accounted for the initial PHS trial randomization; other variables that might be related to post-intervention aspirin use (e.g. history of bleeding, heart disease) and health-related risk factors and outcomes (e.g. smoking history). Exercise and other potential mediators or moderators of the influence of aspirin on walking speed were excluded from the propensity scoring model. We examined the distribution of propensity scores using kernel density plots to determine whether there was sufficient overlap between exposed vs unexposed (25, 26). We initially considered aspirin exposure in 2 or 3 categories of use (≤60 days vs >60 days or ≤60 days vs 61-180 vs >180 days per years). Two categories had the best overlap and were used for all analyses, as in our prior work (17, 22). Estimation employed inverse probability of treatment weighting (27-29). We compared the standardized differences between baseline covariates before and after propensity score adjustment to ensure <10% difference (25).
Descriptive characteristics were obtained after adjustment for propensity scores. Multinomial logistic regression models estimated the odds of prevalent mobility defined according to self-reported walking speed category among aspirin users relative to non-users (≤60 d/yr) while contrasting each level of walking speed to “Don’t walk regularly” category. Potential effect modification by age, history of heart disease, arthritis, bleeding and exercise frequency were examined by inspection and application of interaction tests, stratification and subgroup analysis.
Model-based estimates of association were accompanied by 95% confidence intervals (95% CI). Prespecified hypothesis testing was performed at an α=0.05 level. All analyses were conducted in SAS version 9.4 (SAS Institute, Cary, NC, USA) and R version 3.3.2 (R Foundation for Statistical Computing, Vienna, Austria).

 

Results

In total, 14,315 male, predominantly white (93%), physicians were included in this study. At time of walking speed assessment, the mean (standard deviation; SD) age was 70 (8) years with range 58-100 years; mean (SD) duration of aspirin use was 11 (5) years (range 0-18 years). Aspirin use was reported as ≤60 days/year by 2,056 (14.4%) participants. For walking speed, 13.1% reported not walking regularly, 12.2% walked <2 mph, 44.1% walked ≥2-2.9 mph, and 30.7% walked ≥3 mph.
Prior to propensity score adjustment, those who reported greater aspirin use were more likely to report drinking alcohol daily, prior smoking, and a history of atrial fibrillation, diabetes, hypertension, coronary heart disease (CHD), and stroke. Lower frequency of aspirin use was associated with greater anticoagulation use and bleeding history such as gastritis and melena. Following propensity score IPTW adjustment, there were no significant differences between groups (Table 1). With adjustment for propensity score, we found a graded association between regular aspirin use and faster walking speed. The multiplicative increase (95% CI) attributable to high aspirin use in odds of faster walking speed as compared to not regularly walking was 1.16 (0.97 to 1.39), 1.24 (1.08 to 1.43), and 1.40 (1.21 to 1.63) for those reporting walking speeds of <2 mph, ≥2-2.9 mph and ≥3 mph, respectively, (p-trend<0.001) (Table 2). In a sensitivity analysis, after adjusting for the propensity score in the crude model, results were unchanged.

Table 1. Cohort characteristics of 14,315 PHS participants according to average annual aspirin use, before and after propensity score adjustment

Table 2. Association between regular aspirin use and self-reported walking pace in 14,315 PHS participants before and after propensity score weighting

Legend: Sample sizes are provided for each category to allow for calculation of the raw ORs. For example, comparing “normal” walkers with those who “don’t walk” the estimated unadjusted OR is 1.18, as shown in the table. This is interpreted as: for an individual in the high-aspirin group, the relative odds of being in the “normal» walking group than the «don’t walk” group are18% greater with high aspirin exposure vs low aspirin exposure.

 

Subgroup analyses generally showed little evidence of differential effects across pre-specified categories of risk factors, including age, arthritis, bleeding or exercise frequency. The only subgroup in which there was a statistically significant interaction was among those with history of CHD (p<0.0008). The OR (95% CI) for those with prior CHD and high aspirin use (vs low) was 1.15 (0.80 to 1.64), 1.72 (1.26 to 2.35), and 2.84 (1.93 to 4.16) for those reporting <2 mph, ≥2-2.9 mph and 3+ mph, respectively, compared to 1.18 (0.96 to 1.45), 1.15 (0.98 to 1.34), and 1.24 (1.05 to 1.46) for those without CHD. (Figures 1 and 2).

Figure 1. Forest plot showing the relative odds of increased mobility according to level of aspirin use, stratifying by age and and history of heart disease. The referent mobility group is those who do not engage in regular walking

Figure 2. Forest plot showing the relative odds of increased mobility according to level of aspirin, stratifying on history of arthritis, bleeding, and weekly exercise. The referent mobility group is those who do not engage in regular walking

 

Discussion

In this 15-year post-trial follow up study of 14,315 male physicians, long term aspirin use, started in middle age, was associated with a greater probability of faster walking speed in late life. Our results suggest that decreased walking speed might be prevented through regular aspirin use, independent of medical history and health behaviors. Importantly, however, results suggest that after consideration of these factors, the associations due to aspirin exposure are more strongly manifested among older individuals with a history of heart disease. This observation is in line with the hypothesis that those cardiovascular morbidity and frailty have shared underlying pathophysiology and may be targeted by regular aspirin use.
Aspirin lowers the risk of cardiovascular events by both preventing platelet aggregation and reducing inflammation. In patients with PVD, aspirin is an established part of the treatment plan, either alone or in combination with other antiplatelets or anticoagulants (30, 31). However, clinical trial data has not consistently demonstrated a benefit of aspirin of intermittent claudication. Although aspirin has anti-inflammatory and vasodilatory properties which might improve walking speed, prior clinical data in those with PVD does not support this hypothesis. While most older adults do not have clinical PVD, the microvascular changes that occur with aging contribute to decreased blood flow to leg muscles and may explain in part the natural slowing in walking and increased sarcopenia that is seen with physiologic aging (3, 32). We hypothesize that regular use of aspirin over years, in late middle age and early old age, may improve blood flow and circulation to distal muscles particularly in those with CVD, and therefore lead to less mobility limitation in later decades, in those with heart disease in particular. This is likely mediated by the vasodilatory and anti-inflammatory properties of aspirin.Randomized trials of aspirin for mobility are limited. The ASPREE trial examined the effect of aspirin on disability-free survival, CV events, and mortality in adults aged 70 and older, over 5-years (15, 33, 34). In secondary analyses there was a signal for a lower rate of persistent physical disability (HR 0.85, 95% CI 0.70 to 1.03) (33). and possible benefit for mobility. However, there are serious concerns regarding the safety of aspirin that need to be considered, particularly related to fatal bleeding events (15). It is possible that any benefit of aspirin for prevention of mobility limitation would need to begin earlier in life, however we found that the association between long-term use of aspirin and lower risk of slow walking remained even after accounting for age.
In subgroup analyses we explored whether aspirin use is more effective in certain disease states which may be impacted by aspirin use. Although overall results were similar, there was a statistically significant interaction for those with a history of CHD and a non-significant suggestion of greater benefit among those who do not exercise regularly. Cardiovascular disease has multiple causes, including increased inflammation and thrombotic milieu. That those with CHD had evidence of greater benefit from aspirin may suggest that those using aspirin for secondary prevention of CVD might improve walking speed later in life by reducing their burden of CVD over the lifespan by preventing future CV events and resultant disability. On the other hand, those who exercise may have sufficient benefit from improving blood flow to extremities (35) that the addition of aspirin does not further improve walking. Exercise has been shown to be one of the few modalities that can improve function and frailty at all stages (36), and it is possible that the benefits of aspirin are most beneficial in those who are inactive or who have biologically active CVD.
There are several important limitations to consider. First, this cohort is entirely male and largely made up of individuals identifying as white within a US context, and the study should be repeated in a cohort of women. However, women are also more likely to outlive men by 6-8 years and data that is sex specific is needed in aging research. Second, walking speed was assessed using self-report which could either over or under estimate actual walking pace, although the question used has been well validated (23, 24). Although the end-point mixes aspects of physical activity, function, and ability or disability, we interpret this as an important measure of actualized functional capacity in the real-world setting (21). Third, even though we used propensity score methods to address confounding by indication, reverse causality remains possible. Fourth, information on dose of aspirin was not available after completion of the trial and we are unable to examine the role of aspirin dose on the outcome. Future work to understand the relationship between aspirin and mobility could include plasma analysis for inflammatory biomarkers and mediation analysis to understand what role aspirin may play in reducing inflammation and preventing frailty.
In conclusion, in this cohort of older men, we found that long-term aspirin use started in late midlife was associated with lower odds of mobility limitation, as defined by self-reported walking speed. Future work should replicate these findings in women and further explore the protentional role of aspirin as a preventive strategy for frailty and mobility limitation.

 

Acknowledgments: The authors gratefully acknowledge the patients and research staff who participated in the Physicians’ Health Study. We are grateful for Natalya Gomelskaya for her statistical support. All authors contributed to study conception, writing, and editing the manuscript. L.Y., A.B.D., and T.G.T. conducted the statistical analysis. The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.

Funding: This work was supported by a Career Development award to A.R.O. from the Boston Claude D. Pepper Older Americans Independence Center, National Institute on Aging grant P30-AG013679. A.R.O. is also supported by Veterans Affairs CSR&D CDA-2 IK2-CX001800 and National Institute on Aging grant R03-AG060169. The Physicians’ Health Study is funded by grants CA-34944, CA-40360, and CA-097193 from the National Cancer Institute and grants HL-26490 and HL-34595 from the National Heart, Lung, and Blood Institute, Bethesda, MD.

Conflicts of Interest: J.M.G. reports serving as a consultant and receiving honoraria for speaking for Bayer.

Ethical standards: All participants provided written informed consent. The trial was approved by the Institutional Review Board at Brigham and Women’s Hospital.

 

References

1. Parry SW, Finch T and Deary V. How should we manage fear of falling in older adults living in the community? BMJ (Clinical research ed). 2013;346:f2933. doi: 10.1136/bmj.f2933
2. Studenski S, Perera S, Patel K, Rosano C, Faulkner K, Inzitari M, Brach J, Chandler J, Cawthon P, Connor EB, Nevitt M, Visser M, Kritchevsky S, Badinelli S, Harris T, Newman AB, Cauley J, Ferrucci L and Guralnik J. Gait speed and survival in older adults. Jama. 2011;305:50-8. doi: 10.1001/jama.2010.1923
3. Fritz S and Lusardi M. White paper: «walking speed: the sixth vital sign». Journal of geriatric physical therapy (2001). 2009;32:46-9.
4. Middleton A, Fritz SL and Lusardi M. Walking speed: the functional vital sign. Journal of aging and physical activity. 2015;23:314-22. doi: 10.1123/japa.2013-0236
5. Brown CJ and Flood KL. Mobility limitation in the older patient: a clinical review. Jama. 2013;310:1168-77. doi: 10.1001/jama.2013.276566
6. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G and McBurnie MA. Frailty in older adults: evidence for a phenotype. The journals of gerontology Series A, Biological sciences and medical sciences. 2001;56:M146-56. doi: 10.1093/gerona/56.3.M146
7. Imran TF, Orkaby A, Chen J, Selvaraj S, Driver JA, Gaziano JM and Djoussé L. Walking pace is inversely associated with risk of death and cardiovascular disease: The Physicians’ Health Study. Atherosclerosis. 2019;289:51-56. doi: 10.1016/j.atherosclerosis.2019.08.001
8. Afilalo J, Alexander KP, Mack MJ, Maurer MS, Green P, Allen LA, Popma JJ, Ferrucci L and Forman DE. Frailty assessment in the cardiovascular care of older adults. Journal of the American College of Cardiology. 2014;63:747-62. doi: 10.1016/j.jacc.2013.09.070
9. Bouillon K, Batty GD, Hamer M, Sabia S, Shipley MJ, Britton A, Singh-Manoux A and Kivimaki M. Cardiovascular disease risk scores in identifying future frailty: the Whitehall II prospective cohort study. Heart (British Cardiac Society). 2013;99:737-42. doi: 10.1136/heartjnl-2012-302922
10. Newman AB, Gottdiener JS, McBurnie MA, Hirsch CH, Kop WJ, Tracy R, Walston JD and Fried LP. Associations of subclinical cardiovascular disease with frailty. The journals of gerontology Series A, Biological sciences and medical sciences. 2001;56:M158-66. doi: 10.1093/gerona/56.3.M158
11. Vane JR and Botting RM. The mechanism of action of aspirin. Thrombosis research. 2003;110:255-8. doi: 10.1016/S0049-3848(03)00379-7
12. Oh J, Sinha I, Tan KY, Rosner B, Dreyfuss JM, Gjata O, Tran P, Shoelson SE and Wagers AJ. Age-associated NF-kappaB signaling in myofibers alters the satellite cell niche and re-strains muscle stem cell function. Aging. 2016;8:2871-2896. doi: 10.18632/aging.101098
13. Morris T, Stables M, Hobbs A, de Souza P, Colville-Nash P, Warner T, Newson J, Bellingan G and Gilroy DW. Effects of low-dose aspirin on acute inflammatory responses in humans. Journal of immunology (Baltimore, Md : 1950). 2009;183:2089-96. doi: 10.4049/jimmunol.0900477
14. Woods RL, Espinoza S, Thao LTP, Ernst ME, Ryan J, Wolfe R, Shah RC, Ward SA, Storey E, Nelson MR, Reid CM, Lockery JE, Orchard SG, Trevaks RE, Fitzgerald SM, Stocks NP, Williamson JD, McNeil JJ, Murray AM and Newman AB. Effect of Aspirin on Activities of Daily Living Disability in Community-Dwelling Older Adults. The journals of gerontology Series A, Biological sciences and medical sciences. 2020. doi: 10.1093/gerona/glaa316
15. McNeil JJ, Wolfe R, Woods RL, Tonkin AM, Donnan GA, Nelson MR, Reid CM, Lockery JE, Kirpach B, Storey E, Shah RC, Williamson JD, Margolis KL, Ernst ME, Abhayaratna WP, Stocks N, Fitzgerald SM, Orchard SG, Trevaks RE, Beilin LJ, Johnston CI, Ryan J, Radziszewska B, Jelinek M, Malik M, Eaton CB, Brauer D, Cloud G, Wood EM, Mahady SE, Satterfield S, Grimm R and Murray AM. Effect of Aspirin on Cardiovascular Events and Bleeding in the Healthy Elderly. The New England journal of medicine. 2018;379:1509-1518. doi: 10.1056/NEJMoa1805819
16. Bibbins-Domingo K. Aspirin Use for the Primary Prevention of Cardiovascular Disease and Colorectal Cancer: U.S. Preventive Services Task Force Recommendation Statement. Annals of internal medicine. 2016;164:836-45. doi: 10.7326/M16-0577
17. Orkaby AR, Yang L, Dufour AB, Travison TG, Sesso HD, Driver JA, Djousse L and Gaziano JM. Association Between Long-Term Aspirin Use and Frailty in Men: The Physicians’ Health Study. The journals of gerontology Series A, Biological sciences and medical sciences. 2020. doi: 10.1093/gerona/glaa233
18. Findings from the aspirin component of the ongoing Physicians’ Health Study. The New England journal of medicine. 1988;318:262-4. doi: 10.1056/NEJM198801283180431
19. Final report on the aspirin component of the ongoing Physicians’ Health Study. Steering Committee of the Physicians’ Health Study Research Group. The New England journal of medicine. 1989;321:129-35. doi: 10.1056/NEJM198907203210301
20. Hennekens CH, Buring JE, Manson JE, Stampfer M, Rosner B, Cook NR, Belanger C, LaMotte F, Gaziano JM, Ridker PM, Willett W and Peto R. Lack of effect of long-term supplementation with beta carotene on the incidence of malignant neoplasms and cardiovascular disease. The New England journal of medicine. 1996;334:1145-9. doi: 10.1056/NEJM199605023341801
21. Sturmer T, Glynn RJ, Lee IM, Manson JE, Buring JE and Hennekens CH. Aspirin use and colorectal cancer: post-trial follow-up data from the Physicians’ Health Study. Annals of internal medicine. 1998;128:713-20. doi:10.7326/0003-4819-128-9-199805010-00003
22. Driver JA, Logroscino G, Lu L, Gaziano JM and Kurth T. Use of non-steroidal anti-inflammatory drugs and risk of Parkinson’s disease: nested case-control study. BMJ (Clinical research ed). 2011;342:d198. doi: 10.1136/bmj.d198
23. Wolf AM, Hunter DJ, Colditz GA, Manson JE, Stampfer MJ, Corsano KA, Rosner B, Kriska A and Willett WC. Reproducibility and validity of a self-administered physical activity questionnaire. International journal of epidemiology. 1994;23:991-9. doi: 10.1093/ije/23.5.991
24. Hu FB, Sigal RJ, Rich-Edwards JW, Colditz GA, Solomon CG, Willett WC, Speizer FE and Manson JE. Walking compared with vigorous physical activity and risk of type 2 diabetes in women: a prospective study. Jama. 1999;282:1433-9. doi: 10.1001/jama.282.15.1433
25. Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Statistics in medicine. 2009;28:3083-107. doi: 10.1002/sim.3697
26. Crump RK, Hotz VJ, Imbens GW and Mitnik OA. Dealing with limited overlap in estimation of average treatment effects. 2009;96:187-199. doi: 10.1093/biomet/asn055
27. Elze MC, Gregson J, Baber U, Williamson E, Sartori S, Mehran R, Nichols M, Stone GW and Pocock SJ. Comparison of Propensity Score Methods and Covariate Adjustment: Evaluation in 4 Cardiovascular Studies. Journal of the American College of Cardiology. 2017;69:345-357. doi: 10.1016/j.jacc.2016.10.060
28. Curtis LH, Hammill BG, Eisenstein EL, Kramer JM and Anstrom KJ. Using inverse probability-weighted estimators in comparative effectiveness analyses with observational databases. Medical care. 2007;45:S103-7. doi: 10.1097/MLR.0b013e31806518ac
29. Kim DH, Pieper CF, Ahmed A and Colon-Emeric CS. Use and Interpretation of Propensity Scores in Aging Research: A Guide for Clinical Researchers. Journal of the American Geriatrics Society. 2016;64:2065-2073. doi: 10.1111/jgs.14253
30. Gerhard-Herman MD, Gornik HL, Barrett C, Barshes NR, Corriere MA, Drachman DE, Fleisher LA, Fowkes FG, Hamburg NM, Kinlay S, Lookstein R, Misra S, Mureebe L, Olin JW, Patel RA, Regensteiner JG, Schanzer A, Shishehbor MH, Stewart KJ, Treat-Jacobson D and Walsh ME. 2016 AHA/ACC Guideline on the Management of Patients With Lower Extremity Peripheral Artery Disease: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2017;135:e686-e725. doi: 10.1161/CIR.0000000000000470
31. Hess CN and Hiatt WR. Antithrombotic Therapy for Peripheral Artery Disease in 2018. Jama. 2018;319:2329-2330. doi: 10.1001/jama.2018.5422
32. Proctor DN, Shen PH, Dietz NM, Eickhoff TJ, Lawler LA, Ebersold EJ, Loeffler DL and Joyner MJ. Reduced leg blood flow during dynamic exercise in older endurance-trained men. J Appl Physiol (1985). 1998;85:68-75. doi: 10.1152/jappl.1998.85.1.68
33. McNeil JJ, Woods RL, Nelson MR, Reid CM, Kirpach B, Wolfe R, Storey E, Shah RC, Lockery JE, Tonkin AM, Newman AB, Williamson JD, Margolis KL, Ernst ME, Abhayaratna WP, Stocks N, Fitzgerald SM, Orchard SG, Trevaks RE, Beilin LJ, Donnan GA, Gibbs P, Johnston CI, Ryan J, Radziszewska B, Grimm R and Murray AM. Effect of Aspirin on Disability-free Survival in the Healthy Elderly. The New England journal of medicine. 2018;379:1499-1508. doi: 10.1056/NEJMoa1800722
34. McNeil JJ, Nelson MR, Woods RL, Lockery JE, Wolfe R, Reid CM, Kirpach B, Shah RC, Ives DG, Storey E, Ryan J, Tonkin AM, Newman AB, Williamson JD, Margolis KL, Ernst ME, Abhayaratna WP, Stocks N, Fitzgerald SM, Orchard SG, Trevaks RE, Beilin LJ, Donnan GA, Gibbs P, Johnston CI, Radziszewska B, Grimm R and Murray AM. Effect of Aspirin on All-Cause Mortality in the Healthy Elderly. The New England journal of medicine. 2018;379:1519-1528. doi: 10.1056/NEJMoa1803955
35. Hildebrandt W, Schwarzbach H, Pardun A, Hannemann L, Bogs B, König AM, Mahnken AH, Hildebrandt O, Koehler U and Kinscherf R. Age-related differences in skeletal muscle microvascular response to exercise as detected by contrast-enhanced ultrasound (CEUS). PLoS One. 2017;12:e0172771. doi: 10.1371/journal.pone.0172771
36. Clegg A, Young J, Iliffe S, Rikkert MO and Rockwood K. Frailty in elderly people. Lancet. 2013;381:752-62. doi: 10.1016/S0140-6736(12)62167-9

EFFECTS OF TIMING OF MEDIUM-CHAIN TRIGLYCERIDES (8:0 AND 10:0) SUPPLEMENTATION DURING THE DAY ON MUSCLE MASS, FUNCTION AND COGNITION IN FRAIL ELDERLY ADULTS

 

S. Abe1, O. Ezaki2, M. Suzuki1

 

1. Day Care SKY, Yokohama, Japan; 2. Institute of Women’s Health Science, Showa Women’s University, Tokyo, Japan

Corresponding Author: Osamu Ezaki, M.D. Institute of Women’s Health Science, Showa Women’s University, 1-7-57 Taishido, Setagaya-ku, Tokyo 154-8533, Japan, Tel: +81-3-3411-7450; Fax: +81-3-3411-7450, E-mail: ezaki1952@yahoo.co.jp

J Frailty Aging 2021;in press
Published online September 2, 2021, http://dx.doi.org/10.14283/jfa.2021.33

 


Abstract

Objectives: Supplementation with 6 g/day of medium-chain triglycerides (MCTs) at dinnertime increases muscle function and cognition in frail elderly adults relative to supplementation with long-chain triglycerides. However, suitable timing of MCT supplementation during the day is unknown.
Design: We enrolled 40 elderly nursing home residents (85.9 ± 7.7 years) in a 1.5-month randomized intervention trial. Participants were randomly allocated to two groups: one received 6 g/day of MCTs at breakfast (breakfast group) as a test group and the other at dinnertime (dinner group) as a positive control group.
Measurements: Muscle mass, strength, function, and cognition were monitored at baseline and 1.5 months after initiation of intervention.
Results: Thirty-seven participants completed the study and were included in the analysis. MCT supplementation in breakfast and dinner groups respectively increased right arm muscle area from baseline by 1.1 ± 0.8 cm2 (P<0.001) and 1.6 ± 2.5 cm2 (P<0.001), left arm muscle area by 1.1 ± 0.7 cm2 (P<0.001) and 0.9 ± 1.0 cm2 (P<0.01), right knee extension time by 39 ± 42 s (P<0.01) and 20 ± 32 s (P<0.05), leg open and close test time by 1.74 ± 2.00 n/10 s (P<0.01) and 1.67 ± 2.01 n/10 s (P<0.01), and Mini-Mental State Examination score by 1.5 ± 3.0 points (P=0.06) and 1.0 ± 2.1 points (P=0.06). These increases between two groups did not differ statistically significantly.
Conclusion: Supplementation with 6 g MCTs/day for 1.5 months, irrespective of ingestion at breakfast or dinnertime, could increase muscle mass and function, and cognition in frail elderly adults.

Key words: FIM, frailty, MCT oil, MMSE, sarcopenia.


Introduction

Sarcopenia (loss of skeletal muscle mass, strength, and function) and dementia (or cognitive impairment) are common in elderly adults but difficult to treat. Previously, in a randomized, controlled trial with a time course, we found that supplementation with medium-chain triglycerides (MCTs) (6 g/day) at dinnertime for 3 months in frail elderly adults increased their muscle strength, function, activities of daily living (ADL) (1), and cognition (2) relative to supplementation with long-chain triglycerides (LCTs). The muscle and cognitive functions in the LCT group gradually decreased with time, whereas those in the MCT group increased (1, 2). However, suitable timing of MCT supplementation during the day is unknown.
Our previous studies (1, 2) suggested that O-n-octanoylation of ghrelin by C8:0 in MCTs could be a mechanism by which dietary MCTs increase muscle function and cognition , rather than in its role as a ketogenic meal (3). O-n-octanoylation by ghrelin o-acyltransferase in the stomach is essential for the activation of ghrelin, which stimulates the release of growth hormone (GH) in rats (4). Also, the injection of acyl-ghrelin in humans released GH in a dose-dependent manner (5, 6). A decrease in GH secretion accompanies aging and may contribute to the sarcopenia that develops in older adults (7). Ingestion of MCTs leads to the activation (i.e., acylation) of ghrelin in mice (8), which may lead to an increase in the level of GH secretion and a subsequent increase in muscle mass (the MCTs/Ghrelin/GH hypothesis). In humans, ingestion of MCTs also leads to an increase in blood acyl-ghrelin concentration (9-11). However, it has not been shown that ingestion of MCTs can increase GH secretion.
Both ghrelin and GH are secreted with circadian rhythmicity. Plasma ghrelin levels rise before a meal and drop after feeding (12). Inter-meal ghrelin levels displayed a diurnal rhythm, rising throughout the day to a zenith at 1:00 a.m., then falling overnight to a nadir at 9:00 a.m. (12). This circadian rhythm of ghrelin secretion may affect GH secretion. The stimulatory actions of GH-releasing hormone and ghrelin on GH secretion from pituitary and the tonic inhibitory influence of somatostatin generate a pulsatile pattern of GH secretion (13), which is stimulated during sleep (14). A major secretory episode occurs shortly after sleep onset, in association with the first period of slow-wave sleep (15). However, during aging, slow-wave sleep and GH secretion decrease with the same chronology (16). Therefore, to increase GH secretion during sleep, the timing of MCT supplementation may be important.
In our previous studies (1, 2, 17, 18), MCTs were given at dinnertime. If MCTs are given at breakfast time, the favorable effects of MCTs might not be observed because the effects of MCTs might not be long enough to increase ghrelin and GH secretion during sleep. In the present study, to determine suitable timing of MCT supplementation during the day, we compared the effects of MCTs given either at breakfast or dinnertime for 1.5 months, as both times are suitable to add MCTs in served foods for most elderly adults.

 

Materials and methods

Participants

This trial was announced in early April 2019 at the Day Care SKY facility in Yokohama, Japan. All participants who resided in this nursing home and who required special care from a helper were targeted (n = 68; mean age, 86.1 ± 7.7 years) (Figure 1). The registration was started on April 6, 2019 and ended on April 18, 2019. During this interval, 21 participants were excluded by the criteria of a body mass index (BMI) of >23 kg/m2 (to avoid a further increase in body weight); <65 years of age; parenteral nutrition; difficulty in swallowing; severe heart failure, lung, liver, kidney, or blood disease; a fasting blood glucose level of ≥200 mg/dL; a blood creatinine level of ≥1.5 mg/dL; or a CRP level of ≥2.0 mg/dL, and 7 participants were moved to other facilities, as described in Figure 1. Thus, 40 participants (5 men, 35 women; mean age, 85.9 ± 7.7 years) were enrolled and allocated to each group on April 18, 2019. Data collection at baseline was started on April 19, 2019 and ended by May 2, 2019. The intervention took place from May 3, 2019 to June 14, 2019 at Day Care SKY. Data collection after the intervention was started on June 16, 2019 and ended by June 20, 2019.

Figure 1. Trial profile

Participants (n = 40) were randomly allocated to two groups: the breakfast group (6 g/day of medium-chain triglycerides at breakfast time, n =20) and dinner group (6 g/day of medium-chain triglycerides at dinnertime, n =20). Thirty-seven participants completed the study and were included in the analysis. FIM = Functional Independence Measure; MCT = medium-chain triglycerides; RSST = repetitive saliva swallowing test.

 

The participants and their family members were informed of the nature of the experimental procedures before their written informed consent was obtained. In patients with cognitive decline or difficulty in writing (n = 12), informed consent was obtained from the patient’s family members. The present study was approved by the Human Ethics Committee of Japan Society of Nutrition and Food Science (Approval No. 87). The procedures were conducted in accordance with either the ethical standards of the institutional committee on human experimentation or the Helsinki Declaration of 1975 (as revised in 2000).

Study design

We performed a 1.5-month randomized, single blinded, parallel group intervention trial in which the 40 participants were randomly allocated into two groups (Figure 1). Sealed envelopes containing the written informed consent of the individual participants (or their family members) were thoroughly shuffled. Twenty participants (envelopes) each were allocated to the group that received 6 g/day MCTs at breakfast time (7:30~8:15 a.m.) and the group that received 6 g/day MCTs at dinnertime (6:00~6:45 p.m.). Allocation was conducted by a non-member of this study.
The intervention duration was 1.5 months, which was half that of the previous trial design (3 months) (1, 2, 17, 18), because significant dropouts in participants had been expected after the 1.5-month intervention. Due to legal limitations on the period of residency in this nursing home, some of the participants were required to leave this nursing home during the study period.
The participants’ body weight, appendicular muscle mass, strength, function, cognition, and ADL as described previously (1, 2) were assessed at baseline and 1.5 months after the initiation of the intervention. To avoid the possible acute effects of MCTs, assessment of the MCT intervention was conducted 2 days after the last MCT supplementation. Additionally in the present study, body composition (body fat percentage, fat mass, and muscle mass) in the whole body was measured by bioelectrical impedance method (ONE SMARTDIET, South Korea).

Blinding

The participants in both groups were blinded for group allocation. They did not know whether they belonged to the breakfast or dinner group because they could not detect the foods containing MCTs. This might be due to the faint smell of the MCTs oil itself, the relatively small amounts of MCTs added to the foods, or the decreased sense of taste in the elderly participants.
To assess the outcomes, the examiners who oversaw the walking speed test and undertook the Functional Independence Measure (FIM) and the Nishimura geriatric rating scale for mental status (NM scale) were unaware of each participant’s group (blinded). Other assessments (anthropometric measurements, hand grip strength, knee leg extension time, leg open and close test, peak expiratory flow [PEF] test, repetitive saliva swallowing test [RSST], and Mini-Mental State Examination [MMSE]) were conducted by an expert with a certificate of training but who was aware of the participant’s group assignment (unblinded).

Study products

The MCTs (75% 8:0 and 25% 10:0 from total fatty acids) were purchased from Nisshin OilliO Group Ltd. (Kanagawa, Japan). Six grams of MCTs (50 kcal; 8.3 kcal/g) per day was mixed with foods such as steamed rice or miso soup at breakfast or dinnertime.

Daily time schedule of the participants

The daily time schedule in this nursing home was as follows: hour of rising, 5:30~6:30 a.m.; breakfast, 7:30~8:15 a.m.; lunch, 12:00~12:45 p.m.; snack, 3:00~3:30 p.m.; dinner, 6:00~6:45 p.m.; bedtime, 8:00~9:00 p.m.

Dietary intake

Breakfast, lunch, and dinner were served daily in the nursing care home. The habitual daily energy and nutrient intake of the individual participants during the baseline and intervention periods was measured as described previously (17). Then, the mean daily energy and macronutrient intakes of the two groups were calculated based on the daily energy and nutrient intakes of the individual participants (Table 1).

Table 1. Habitual energy and macronutrients intake at baseline and during the 1.5-month intervention and their changes in the breakfast and dinner groups (excluding MCT supplement)

Values are mean + SD. †P values represent the differences in the changes of variables between the two groups as assessed by 1-factor ANCOVA adjusted by each baseline value. MCFA = medium-chain fatty acid.

 

Daily activity and rehabilitation/exercise

Daily activities of this nursing care home were follows: at 7:15 a.m., exercises for the mouth were started for 10 min. At 10:00 a.m., exercises for the arms and fingers were started for 20 min. At 3:30 p.m., recreational therapy was started for 1 hour as described previously (1). At other times, residents spent their free time watching TV, lying in bed, and doing other activities. In addition, rehabilitation/exercise protocols were individually conducted. Several types of exercises such as walking, resistance training, leg stretches, stair stepping, or balance training were individually conducted for 20 min twice a week. The individual daily activities and rehabilitation/exercise were not changed during the baseline and intervention periods. The conductors of the daily activity and individual rehabilitation/exercise were unaware of the group to which each participant was assigned.

Medications

Medical drugs (antihypertensive, antiplatelet, antipsychotic, antilipemic, antidiabetic, antiosteoporosis, laxative, and hypnotic drugs), which were used by some of the participants, were not changed during the baseline or intervention periods.

Participants excluded from the analysis

Two participants in the breakfast group had paralysis of the right hand and another participant suffered from Parkinson’s disease and were excluded from the analysis of right-hand grip strength (Figure 1). One participant in the breakfast group had paralysis of the right leg and was excluded from the analysis of right knee extension time. One participant in the breakfast group had paralysis of the left leg and was excluded from the analysis of left knee extension time.
Three participants in the breakfast group had right foot paralysis, a fourth participant had low-back pain, and another participant refused to undergo the analysis of walking speed. One participant from the dinner group had difficulty in standing up due to increased body weight. All 6 participants were excluded from this test.
Three participants in the breakfast group and one from the dinner group had difficulty in understanding how to perform the PEF test and were excluded from the analysis of PEF. One participant in the breakfast group had motor apraxia and was excluded from the analysis of RSST. One participant in the dinner group changed from use of a walker to use of a wheelchair during the intervention (i.e., ADL were changed) and was excluded from the analysis of the FIM score.

Primary and secondary outcome variables

The primary outcome of the trial was the result of right knee extension time, which showed the largest increase (26 s, 43.3%, P < 0.001) in the 1.5-month intervention from baseline in the MCT group among the muscle tests conducted in our previous study (1). The other test results were considered the secondary outcomes. For the primary efficacy measure of right knee extension time, 36 participants were required in one group (n = 72 in two groups) for a power of 80% at a two-sided P of 0.05 to detect a treatment difference of 26 s with an SD of 39 s between the two groups by t-test.

Statistical analysis

All data are expressed as the mean + SD. In the within-group analysis, values at baseline and at the end of the intervention in each group were compared by Wilcoxon signed-rank test.
In the between-group analysis, to compare the groups with respect to the effects of MCTs on the measurements, differences in the change (change value = intervention value – baseline value) between the groups were assessed with analysis of covariance (ANCOVA), with adjustment for the baseline values in each measurement, age, sex, and BMI as covariates. The variances of change in all measurements were homogeneous between the groups by Levene’s test.
The percentage of relative change (% change) was calculated as follows: % change = (mean of the intervention value – mean of the baseline value) / mean of baseline value × 100. This value was then used to describe the degree of effect.
Missing data (data that could not be collected at baseline and/or after the intervention due to difficulty in performing tests) were not included in the analyses. A P level of 0.05 was used to determine statistical significance. All statistical analyses were performed with the SPSS 20.0 software program (IBM, Chicago, IL).

 

Results

Participants and compliance

We enrolled 40 participants in the trial (Figure 1). Three participants dropped out during the study: one participant in the breakfast group due to bone fracture following a fall and 2 participants in the dinner group due to signs of acute heart failure. Thus, the remaining 37 participants (breakfast group: n = 19; 2 men, 17 women; mean age, 85.6 ± 7.9 years and the dinner group: n = 18; 2 men, 16 women; mean age, 86.4 ± 8.3 years) completed the study, and their data were used for the following analysis. No side effects, including diarrhea, or any other claims were reported.

Dietary intake (excluding supplemental MCTs)

Habitual intakes of energy and macronutrients at baseline and during the intervention period for the two groups are shown in Table 1. The MCTs that were administered are not included in this table. No differences between the baseline and intervention period were observed in either group with regard to the habitual intake of energy, protein, fat, and carbohydrate.

Anthropometric measures

Table 2 shows the anthropometric measures obtained at baseline and at the end of the 1.5-month intervention and their changes from baseline in the two groups. MCT supplementation did not affect body weight and BMI in either group. However, MCTs increased whole-body muscle mass from baseline by 0.3 ± 0.7 kg (non-significant, P = 0.11) in the breakfast group and 0.4 ± 0.5 kg (P < 0.01) in the dinner group and decreased whole-body fat mass by -0.9 ± 1.4 kg (P < 0.01) and –1.0 ± 1.5 kg (P < 0.01), respectively. In both groups, in agreement with the changes in body composition, increases in calculated right/left arm muscle area (AMA) and decreases in right/left triceps skinfold thickness (TSF) were noted. However, the increase in the right calf circumference (CC) was significant in the dinner group (0.4 ± 0.5 cm, P < 0.01) but not in the breakfast group (0.1 ± 0.6 cm, P = 0.23), whereas the increase in the left CC was significant in the breakfast group (0.2 ± 0.4 cm, P < 0.05) but not in the dinner group (0.3 ± 0.5 cm, P = 0.06). These changes between the two groups did not differ statistically significantly.

Table 2. Anthropometric measurements at baseline and 1.5-month intervention and their changes from baseline in the breakfast and dinner groups

Values are expressed as the mean ± SD. Asterisks indicate a statistically significant difference from baseline *P < 0.05, **P < 0.01, ***P < 0.001 by Wilcoxon signed-rank test. †P value represents the difference in the change in a variable between the two groups as assessed by a 1-factor ANCOVA adjusted for the baseline value in each measurement, age, sex, and BMI. AC = arm circumference; AMA = arm muscle area; BMI = body mass index; CC = calf circumference; TSF = triceps skinfold thickness.

 

Muscle strength and function

Muscle strength and function at baseline and at the end of the 1.5-month intervention and their changes from baseline in the two groups are shown in Table 3. MCT supplementation in the breakfast and dinner groups increased the right knee extension time from baseline by 39 ± 42 s (P < 0.01) and 20 ± 32 s (P < 0.05); the left knee extension time by 37 ± 36 s (P < 0.01) and 28 ± 32 s (P < 0.01); and the leg open and close test results by 1.74 ± 2.00 n/10s (P < 0.01) and 1.67 ± 2.01 n/10s (P < 0.01), respectively. However, the increase in the right-hand grip strength was significant only in the dinner group (0.9 ± 1.8 kg, P < 0.05) and not in the breakfast group (0.9 ± 2.3 kg, P = 0.24). These increases between the two groups did not differ statistically significantly.

Table 3. Muscle strength and function at baseline and 1.5-month intervention and their changes from baseline in the breakfast and dinner groups

Values are expressed as the mean ± SD. Asterisks indicate a statistically significant difference from baseline *P < 0.05, **P < 0.01 by Wilcoxon signed-rank test. †P value represents the difference in the change in a variable between the two groups as assessed by a 1-factor ANCOVA adjusted for the baseline values in each measurement, age, sex, and BMI. RSST = repetitive saliva swallowing test.

 

ADL and cognition

The FIM, MMSE, and NM scale scores at baseline and at the end of the 1.5-month intervention and their changes from baseline in the two groups are shown in Table 4. In these tests, a high score indicates better function. MCT supplementation in the breakfast and dinner groups increased the FIM score from baseline by 5.1 ± 6.0 points (P < 0.01) and 3.7 ± 5.0 points (P < 0.01); the MMSE score by 1.5 ± 3.0 points (P = 0.06) and 1.0 ± 2.1 points (P = 0.06); and the NM scale score by 3.5 ± 2.7 points (P < 0.01) and 2.2 ± 2.8 points (P < 0.01), respectively. These increases between the two groups also did not differ statistically significantly.

Table 4. FIM, MMSE, and NM scale scores at baseline and 1.5-month intervention and their changes from baseline in the breakfast and dinner groups

Values are means ± SD. In these tests, a high score indicates better function. Asterisks indicate a statistically significant difference from baseline *P < 0.05, **P < 0.01, ***P < 0.001 by Wilcoxon signed-rank test. †P values represent the differences in the changes of variables between the two groups as assessed by 1-factor ANCOVA adjusted for the baseline values in each measurement, age, sex, and BMI. FIM = Functional Independence Measure; MMSE = Mini-Mental State Examination; NM scale = Nishimura geriatric rating scale for mental status.

 

Discussion

The present study showed that irrespective of the timing of MCT supplementation during the day (either at breakfast or at dinnertime), supplementation with 6 g MCTs/day for 1.5 months increased muscle mass and function, cognition, and ADL of frail elderly adults from baseline measurements. These results suggested that ingestion of MCT at either time could lead to similar activation of the MCTs/Ghrelin/GH axis.
A negative control (or placebo) group could not be included due to the small number of participants in the present trial. However, because our previous studies included an unsupplemented control group (inert control group) (17, 18) or negative placebo group (LCT group) (1, 2), it is clear that 6 g/day MCT supplementation increased muscle strength, function, ADL, and cognition relative to the control groups (inert or placebo).
The results are promising, but a future larger randomized study is needed. In addition, considering the reported adverse effects of the administration of ghrelin (19) and GH (20), long-term studies of MCT supplementation will be required to examine potential adverse effects, including risks of diabetes mellitus, cancer, and hyperplasia in some tissues.

Effects of MCTs on dietary intake

We did not observe any differences in habitual energy or nutritional intake between baseline and the intervention period in either group (Table 1), in agreement with our previous studies (1, 17). These results suggest that intakes of other daily nutrients did not alter the effects of MCT supplementation.
MCTs have been shown to be more satiating (i.e., decrease appetite) and promote weight loss compared with LCTs (21, 22), whereas ghrelin administration increases appetite (19). We speculated that either the dose of 6 g/day MCTs in our studies was not enough to promote weight loss, or an increase in appetite generated by ghrelin might counteract the effect of MCTs to decrease appetite.

Possible reasons for similar effects of MCT supplementation at either breakfast or dinnertime

The circadian profile of acyl-ghrelin and GH concentrations in blood after MCT supplementation, in which frequent blood sampling (i.e., more than 30 times throughout a 24-h period) was required (12, 16), have not been examined. However, blood acyl-ghrelin concentration after acute or chronic MCT supplementation, in which blood sampling is required several times throughout a 24-h period, has been reported in several human studies (9-11).
A time lag from oral MCT supplementation to an increase in ghrelin concentration was observed in two studies (8, 9). In one study in mice, the n-octanoyl ghrelin concentration in the stomach increased significantly at 3 h after glyceryl trioctanoate supplementation (8). In another experiment in mice from the same study, plasma acyl-ghrelin, which does not naturally occur in mammals, appeared after 4 h following supplementation of either glyceryl triheptanoate or n-heptanoic acid (7:0) (8). In a clinical study, 2–5 h was required to observe an increase in acyl-ghrelin concentration after the single oral ingestion of 3.0 g of a MCT supplement in an energy-containing formula in cachectic patients relative to patients without administration of the formula (9). Surprisingly, this increase in blood acyl-ghrelin concentration was maintained for at least another 10 h (9). Considering the shorter half-life of acyl-ghrelin in blood (10 min) (23), the longer activation of ghrelin by MCT supplementation suggested that medium-chain fatty acids (MCFAs), which are stored as triglyceride (TG) in X/A-like cells of the stomach, might be used for the production of acyl-ghrelin.
Although a part of ingested MCFAs and MCTs are directly used for ghrelin acyl modification in X/A-like cells of the stomach (8), the fate of MCFAs in these cells is not clear. Most MCFAs entering the cells may be used for ATP production in mitochondria or synthesis of TG in cytosol (24, 25). MCFAs stored as TG in cells and MCFAs directly entering from the circulation could also be used for acyl-ghrelin synthesis. Therefore, a time lag to the increase in acyl-ghrelin concentration in blood is expected after MCT supplementation due to the time necessary for formation of acyl-ghrelin, and the duration of this increased acyl-ghrelin concentration in blood may depend on the bio-availability of MCFAs (mostly from storage in the TG form) in the X/A-like cells of the stomach.
In the present study, MCTs were given in the dinner group at 6:00~6:45 p.m., which was 1–3 h before sleeping time (8:00~9:00 p.m.). Blood acyl-ghrelin concentration may increase at the initiation of sleeping time when GH secretion also increases. MCTs in the breakfast group were given at 7:30~8:15 a.m., which was 11–14 h before sleeping time (8:00~9:00 p.m.), and blood acyl-ghrelin concentrations that derived from TG in cells of the stomach, may still be elevated at this time. Therefore, irrespective of the timing of MCT supplementation during the day (at breakfast or dinner), supplementation with 6 g MCTs/d for 1.5 months could increase muscle mass and function, cognition, and ADL of the frail elderly adults from baseline.

Limitations

Limitations of the present study are as follows. 1) The number of participants might be too small to observe significant effects of MCTs in some measures and non-significant differences in measures between the breakfast and dinner groups due to a lack of statistical power. A large-scale intervention study or meta-analysis may clarify these issues. 2) The examiners were not completely blinded to treatment allocation, which could bias the results. There was a chance that the examiner might favorably judge cognition in some groups, although the examiner kept in mind the responsibility of precisely assessing cognition. 3) Changes in the circadian rhythm of ghrelin and GH after MCT supplementation were not measured. However, frequent blood sampling will be necessary to elucidate the mechanisms of the effects of MCTs in the future. 4) Because this study targeted only frail elderly Japanese individuals, we did not address whether similar favorable effects of MCTs would be observed in western populations with a larger body size or in non-frail subjects.

 

Conclusions

Whether 6 g MCTs/day was supplemented either at breakfast or dinnertime, the increases in muscle mass and muscle function, cognition, and ADL of frail elderly individuals by MCT supplementation did not differ. MCTs are promising nutrients for elderly frail adults.

 

Acknowledgements: The authors thank all our study participants and all personnel at the Day Care SKY nursing home for collaborating with us.

Author contributions: SA, OE, and MS designed the research; SA and MS conducted the research; SA and OE analyzed the data or performed the statistical analysis; OE wrote the manuscript; and SA has the primary responsibility for the final content. All of the authors read and approved the final manuscript.

Funding sources: This study was supported by a grant from the Policy-Based Medical Services Foundation, 2019 (to SA).

Author disclosures: SA, OE, and MS have nothing to disclose.

Ethical Standards: The authors declare that the study procedures comply with the current ethical standards for investigation involving human participants in Japan.

 

References

1. Abe, S.; Ezaki, O.; Suzuki, M. Medium-chain triglycerides (8:0 and 10:0) are promising nutrients for sarcopenia: a randomized controlled trial. The American journal of clinical nutrition 2019, 110, 652-665, doi:10.1093/ajcn/nqz138.
2. Abe, S.; Ezaki, O.; Suzuki, M. Medium-Chain Triglycerides (8:0 and 10:0) Increase Mini-Mental State Examination (MMSE) Score in Frail Elderly Adults in a Randomized Controlled Trial. J Nutr 2020, 150, 2383-2390, doi:10.1093/jn/nxaa186.
3. Cunnane, S.C.; Courchesne-Loyer, A.; Vandenberghe, C.; St-Pierre, V.; Fortier, M.; Hennebelle, M.; Croteau, E.; Bocti, C.; Fulop, T.; Castellano, C.A. Can Ketones Help Rescue Brain Fuel Supply in Later Life? Implications for Cognitive Health during Aging and the Treatment of Alzheimer’s Disease. Frontiers in molecular neuroscience 2016, 9, 53, doi:10.3389/fnmol.2016.00053.
4. Kojima, M.; Hosoda, H.; Date, Y.; Nakazato, M.; Matsuo, H.; Kangawa, K. Ghrelin is a growth-hormone-releasing acylated peptide from stomach. Nature 1999, 402, 656-660, doi:10.1038/45230.
5. Takaya, K.; Ariyasu, H.; Kanamoto, N.; Iwakura, H.; Yoshimoto, A.; Harada, M.; Mori, K.; Komatsu, Y.; Usui, T.; Shimatsu, A., et al. Ghrelin strongly stimulates growth hormone release in humans. J Clin Endocrinol Metab 2000, 85, 4908-4911, doi:10.1210/jcem.85.12.7167.
6. Hataya, Y.; Akamizu, T.; Takaya, K.; Kanamoto, N.; Ariyasu, H.; Saijo, M.; Moriyama, K.; Shimatsu, A.; Kojima, M.; Kangawa, K., et al. A low dose of ghrelin stimulates growth hormone (GH) release synergistically with GH-releasing hormone in humans. J Clin Endocrinol Metab 2001, 86, 4552, doi:10.1210/jcem.86.9.8002.
7. Liu, H.; Bravata, D.M.; Olkin, I.; Nayak, S.; Roberts, B.; Garber, A.M.; Hoffman, A.R. Systematic review: the safety and efficacy of growth hormone in the healthy elderly. Ann Intern Med 2007, 146, 104-115, doi:10.7326/0003-4819-146-2-200701160-00005.
8. Nishi, Y.; Hiejima, H.; Hosoda, H.; Kaiya, H.; Mori, K.; Fukue, Y.; Yanase, T.; Nawata, H.; Kangawa, K.; Kojima, M. Ingested medium-chain fatty acids are directly utilized for the acyl modification of ghrelin. Endocrinology 2005, 146, 2255-2264, doi:10.1210/en.2004-0695.
9. Ashitani, J.; Matsumoto, N.; Nakazato, M. Effect of octanoic acid-rich formula on plasma ghrelin levels in cachectic patients with chronic respiratory disease. Nutr J 2009, 8, 25, doi:10.1186/1475-2891-8-25.
10. Kawai, K.; Nakashima, M.; Kojima, M.; Yamashita, S.; Takakura, S.; Shimizu, M.; Kubo, C.; Sudo, N. Ghrelin activation and neuropeptide Y elevation in response to medium chain triglyceride administration in anorexia nervosa patients. Clin Nutr ESPEN 2017, 17, 100-104, doi:10.1016/j.clnesp.2016.10.001.
11. Yoshimura, Y.; Shimazu, S.; Shiraishi, A.; Nagano, F.; Tominaga, S.; Hamada, T.; Kudo, M.; Yamasaki, Y.; Noda, S.; Bise, T. GHRELIN ACTIVATION BY INGESTION OF MEDIUM-CHAIN TRIGLYCERIDES IN HEALTHY ADULTS: A PILOT TRIAL. Journal of Aging Research & Clinical Practice 2018, 7.
12. Cummings, D.E.; Purnell, J.Q.; Frayo, R.S.; Schmidova, K.; Wisse, B.E.; Weigle, D.S. A preprandial rise in plasma ghrelin levels suggests a role in meal initiation in humans. Diabetes 2001, 50, 1714-1719, doi:10.2337/diabetes.50.8.1714.
13. Murray, P.G.; Higham, C.E.; Clayton, P.E. 60 YEARS OF NEUROENDOCRINOLOGY: The hypothalamo-GH axis: the past 60 years. The Journal of endocrinology 2015, 226, T123-140, doi:10.1530/JOE-15-0120.
14. Veldhuis, J.D.; Keenan, D.M.; Pincus, S.M. Motivations and methods for analyzing pulsatile hormone secretion. Endocrine reviews 2008, 29, 823-864, doi:10.1210/er.2008-0005.
15. Van Cauter, E.; Plat, L.; Copinschi, G. Interrelations between sleep and the somatotropic axis. Sleep 1998, 21, 553-566.
16. Van Cauter, E.; Leproult, R.; Plat, L. Age-related changes in slow wave sleep and REM sleep and relationship with growth hormone and cortisol levels in healthy men. Jama 2000, 284, 861-868, doi:10.1001/jama.284.7.861.
17. Abe, S.; Ezaki, O.; Suzuki, M. Medium-Chain Triglycerides in Combination with Leucine and Vitamin D Increase Muscle Strength and Function in Frail Elderly Adults in a Randomized Controlled Trial. J Nutr 2016, 146, 1017-1026, doi:10.3945/jn.115.228965.
18. Abe, S.; Ezaki, O.; Suzuki, M. Medium-Chain Triglycerides in Combination with Leucine and Vitamin D Benefit Cognition in Frail Elderly Adults: A Randomized Controlled Trial. J Nutr Sci Vitaminol (Tokyo) 2017, 63, 133-140, doi:10.3177/jnsv.63.133.
19. Yanagi, S.; Sato, T.; Kangawa, K.; Nakazato, M. The Homeostatic Force of Ghrelin. Cell metabolism 2018, 27, 786-804, doi:10.1016/j.cmet.2018.02.008.
20. Colon, G.; Saccon, T.; Schneider, A.; Cavalcante, M.B.; Huffman, D.M.; Berryman, D.; List, E.; Ikeno, Y.; Musi, N.; Bartke, A., et al. The enigmatic role of growth hormone in age-related diseases, cognition, and longevity. Geroscience 2019, 41, 759-774, doi:10.1007/s11357-019-00096-w.
21. St-Onge, M.P.; Jones, P.J. Physiological effects of medium-chain triglycerides: potential agents in the prevention of obesity. J Nutr 2002, 132, 329-332, doi:10.1093/jn/132.3.329.
22. French, S.; Robinson, T. Fats and food intake. Curr Opin Clin Nutr Metab Care 2003, 6, 629-634, doi:10.1097/00075197-200311000-00004.
23. Tong, J.; Dave, N.; Mugundu, G.M.; Davis, H.W.; Gaylinn, B.D.; Thorner, M.O.; Tschop, M.H.; D’Alessio, D.; Desai, P.B. The pharmacokinetics of acyl, des-acyl, and total ghrelin in healthy human subjects. Eur J Endocrinol 2013, 168, 821-828, doi:10.1530/EJE-13-0072.
24. Friedman, M.I.; Ramirez, I.; Bowden, C.R.; Tordoff, M.G. Fuel partitioning and food intake: role for mitochondrial fatty acid transport. Am J Physiol 1990, 258, R216-221, doi:10.1152/ajpregu.1990.258.1.R216.
25. Papamandjaris, A.A.; MacDougall, D.E.; Jones, P.J. Medium chain fatty acid metabolism and energy expenditure: obesity treatment implications. Life Sci 1998, 62, 1203-1215.

 

FRUIT AND VEGETABLE CONSUMPTION AND INCIDENT FRAILTY IN OLDER ADULTS: A SYSTEMATIC REVIEW AND META-ANALYSIS

 

G. Kojima1, Y. Taniguchi2, T. Urano3

 

1. Department of Research, Dr. AGA Clinic, Tokyo, Japan; 2. Center for Health and Environmental Risk Research, National Institute for Environmental Studies, Tsukuba, Japan; 3. Department of Geriatric Medicine, International University of Health and Welfare, Chiba, Japan

Corresponding Author: Tomohiko Urano, MD, PhD, Department of Geriatric Medicine, International University of Health and Welfare, Kozunomori 4-3, Narita City, Chiba Prefecture, 286-8686, Japan, Phone: +81 (0)476-20-7701, Fax: +81 (0)476-20-7702, Email: turano@iuhw.ac.jp

J Frailty Aging 2021;in press
Published online September 2, 2021, http://dx.doi.org/10.14283/jfa.2021.32

 


Abstract

Background: There is limited evidence regarding associations between fruit and vegetable consumption and incident frailty risk among older people.
Objectives: The objective of this study was to conduct a systematic review and meta-analysis regarding the association between fruit and vegetable consumption and incident frailty risk among older adults.
Methods: A systematic search of the literature was conducted according to the PRISMA guidelines using PubMed in January 2021 for studies that prospectively examined risk of incident frailty in relation to fruit and vegetable consumption in older adults aged 60 and older. Methodological quality and heterogeneity were assessed. Odds ratios (OR) were pooled using random-effects or fixed-effects meta-analysis, depending on the presence of heterogeneity.
Results: Among three studies included in this review, data of four cohorts were provided by two studies and used in meta-analysis. The highest fruit and vegetable consumption was significantly associated with lower risk of incident frailty compared with the lowest consumption (pooled OR=0.38, 95%CI=0.24-0.59, p=<0.001).
Conclusions: This study provided the pooled evidence that high fruit and vegetable consumption may be beneficial for preventing the development of frailty in older adults. Increasing fruit and vegetable consumption can be a relevant strategy to prevent frailty.

Key words: Frailty, fruit, vegetables, diet, Nutrition, meta-analysis.


 

Introduction

Fruit and vegetables contain various nutrients, including micronutrients with anti-inflammatory and antioxidant properties and are important parts of healthy diet (1). Their benefits for human health have been extensively studied and well documented in the literature (1). Sufficient intake of fruit and vegetables is associated with reduced risk of cardiovascular diseases, certain cancers, and premature death (1, 2). Therefore, fruit and vegetables are widely recommended by most authorities and nutritional guidelines (1, 2). A joint report by The World Health Organization and The Food and Agriculture Organization of the United Nations recommends at least 400g of fruit and vegetables a day to prevent chronic diseases (3). Unfortunately, these health benefits of fruit and vegetable consumption are relatively understudied in the older adults (4).
Frailty is a state of vulnerability to stressors and age-related decreased functioning of various physiological systems (5). It is considered as one of the problematic expression of aging. Previous studies showed approximately 10% of older adults aged 65 or more are affected by frailty and the prevalence increases with age (6). Those who are frail are susceptible to multiple negative health outcomes, including falls (7), disabilities (8), dementia (9), and death (10). Frailty have also been shown to increase the use of healthcare resources, such as hospitalization (11), institutionalization (12), and emergency department visits (13). Given these detrimental negative impacts of frailty on older people as well as on societies, frailty has been recognized as one of the most important public health priorities (14, 15).
Inadequate intake of fruit and vegetable is common among older people due to various reasons (4), such as age-related physiological and social changes (16), and may be related to increased inflammation and oxidative stress. Evidence suggests that oxidative stress and inflammation play important roles in pathogenesis of sarcopenia, which is the decline in muscle mass and function with age and a core feature of frailty (17). Therefore, increasing fruit and vegetable consumption may be effective for preventing frailty. However, few studies focused specifically on fruit and vegetables in relation to frailty (18), although multiple studies have investigated associations between certain dietary patterns and frailty risk, i.e., Mediterranean diet (19). Although a previous systematic review on associations between fruit and vegetable intake and frailty found little evidence (18), there have been more evidence published in the literature since then. Therefore, the objectives of the current study were to perform an updated systematic literature search and to attempt to conduct a meta-analysis to pool the evidence regarding the association between fruit and vegetable consumption and incident frailty risk among community-dwelling older adults.

 

Methods

Search strategy and study selection

The protocol of this systematic review was developed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statements (20) and registered at PROSPERO (https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021225161). The PubMed was searched by one investigator (KG) in January 2021 using prespecified search terms, which included Fruit (MeSH) OR Vegetables (MeSH) OR Fruit and Vegetable Juices (MeSH) OR Antioxidants (MeSH) OR Diet (MeSH) OR Diet Therapy (MeSH) OR Nutrition Therapy (MeSH) OR fruit* OR vegetable* OR anti-oxidant* OR antioxidant* OR diet* OR nutrition* AND Frailty (MeSH) OR Frail Elderly (MeSH) OR OR frailty. Study may have been eligible if they were prospectively cohort studies examining baseline fruit and/or vegetable consumption and subsequent risk of developing frailty in community-dwelling older people with a mean age of 60 or over. Reference lists of included and relevant articles were also examined. The search period was from 2000 or later, since the most widely used frailty criteria, the Cardiovascular Health Study (CHS) criteria were published in 2001 (21). No language restriction was applied.
For meta-analysis, eligible studies prospectively examined risk of incident frailty in relation to consumption of fruit, vegetables, or both at baseline in samples of older adults with a mean age of 60 or over. Studies including selected samples, such as patients with dementia or hospitalized patients, or focusing on dietary patterns were not considered. Frailty should be defined by validated criteria designed to measure frailty. Studies defining frailty status as a continuous score or index, such as the Frailty Index, were not included. Reviews, conference abstracts, editorials, comments, or letters were not included.
Two investigators (GK, YT) screened the titles, abstracts, and full-texts of the identified studies for eligibility. Any disagreement was solved by discussion.

Data Extraction

The data extracted from the included studies were first author, publication year, cohort name, location, sample size, proportion of women in the cohort, mean age, age range, dietary assessment tool, frailty criteria, follow-up period, and findings.

Methodological Quality Assessment

The methodological quality of the included studies was assessed using the Newcastle-Ottawa scale for cohort studies (22). This tool has nine criteria and a study meeting five or more criteria was considered to have adequate methodological quality.

Statistical Analysis

If two or more prospective studies provided the same effect measures, such as odds ratio (OR) or hazard ratio (HR), they were pooled by meta-analysis using the inverse variance method. The heterogeneity across the studies were examined using chi-square, and the degree of heterogeneity was assessed using the I2 statistic. A random-effects model was used when significant heterogeneity was present, and a fixed-effects model was used when absent. If a study provided both unadjusted and adjusted effect measures, the ones with full adjustment were used for meta-analysis. Publication bias was assessed by visually inspecting the funnel plots. Sensitivity and subgroup analyses were not possible due to the small number of included studies.

 

Results

Selection Processes

The results of the systematic review and the study selection processes were presented in Figure 1. The systematic search of the literature found 290 studies, of which 278 studies were excluded by title screening. Among twelve studies left, 8 studies and 1 study were further excluded due to not providing sufficient data and using the same cohort, respectively. Finally, three studies were included for this review, among which two studies were used for meta-analysis. One study was excluded since it used frequency of fruit and vegetable consumption.

Figure 1. Flow chart of systematic literature review

 

Study Characteristics

Table 1 presents the summary of included studies. Three studies used quantity of fruit and vegetable consumption. A recent US study used data of 78,336 older female nurses from the Nurses’ Health Study in the US and examined risk of incident frailty (23). They found that those who consumed 7 or more servings of fruit and vegetables per day had a significantly decreased risk than those who consumed less than 3 servings per day over 20 years (23). Another study from the England investigated the associations between fruit and vegetable consumption at baseline and risk of developing frailty 4 years later in 2,634 non-frail older men and women, however, failed to find any significant associations (24). The third study used three cohorts of older adults (1 from Spain and 2 from France), and two of them showed that those consuming 5 or more portions of fruit and vegetables a day had a significantly higher risk of developing frailty compared with those consuming less than 1 portions a day, and the other showed non-significant results (25). The food assessments were either self-administered questionnaires (23-25) or questionnaires with a help of trained research assistant (25).

Table 1. Summary of included studies on associations between fruit and vegetable consumption and incident frailty risk

aHR: Adjusted hazard ratio; aOR: Adjusted odds ratio; BMI: Body mass index; ELSA: English Longitudinal Study of Ageing; FFQ: Food Frequency Questionnaire; MMSE: Mini-Mental State Examination; Senior-ENRICA: Study on Nutrition and Cardiovascular Risk Factors in Spain

 

Methodological quality assessment

Three studies (23-25) were evaluated using the Newcastle-Ottawa scale for cohort studies and were considered to have adequate methodological quality, with the mean score of 6.8 (range=6-8).

Fruit and vegetable consumption and incident frailty risk

OR of incident frailty risk according to fruit and vegetable consumption (combined) were provided from four cohorts (3 cohorts in 1 study (25) and 1 cohort in another study (24); Figure 2A). The OR for the highest category of fruit and vegetable consumption compared with the lowest category were combined using the fixed-effects meta-analysis. The highest fruit and vegetable consumption was significantly associated with lower risk of incident frailty (pooled OR=0.38, 95%CI=0.24-0.59, p=<0.001) than the lowest consumption. The degree of heterogeneity across the included cohort data was low (I2=0%).

Figure 2. Forest plots of incident frailty risk according to A: fruit and vegetables, B: fruit only, and C: vegetables only

AMI: Integrated Multidisciplinary Approach cohort, CI: confidence interval, IV: inverse variance, SE: standard error

 

The meta-analysis was repeated for fruit and vegetable alone separately (Figures 2B and 2C). Although the highest vegetable consumption was significantly associated with decreased risk of incident frailty (pooled OR=0.54, 95%CI=0.32-0.91, p=0.02; Figure 2C), there was no significant association observed between fruit and incident frailty risk (pooled OR=0.75, 95%CI=0.35-1.60, p=0.46; Figure 2B). It was not possible to properly assess the publication bias due to the small number of the included cohorts.

 

Discussion

This study systematically searched the literature for associations between fruit and vegetable consumption and incident frailty risk and was able to provide the pooled evidence that higher fruit and vegetable consumption is associated with lower risk of incident frailty among community-dwelling older adults.
We found a few studies focusing on frequency of consuming fruit and vegetable, or vegetable alone (26-28). Two studies using the British Whitehall II study cohort, consisting of middle-aged civil servants aged 35-55 at recruitment showed similar results. In the first study, consuming fruit and vegetables at least twice a day when 50 years old was associated with a decreased risk of frailty 20 years later compared with consuming less than once a day (adjusted HR=0.70, 95%CI=0.53-0.92) (26). It should be noted that this study did not examine frailty status at baseline, although prevalence of frailty at the age of 50 would have been very low (26). The second study of the Whitehall II cohort showed that those consuming fruit and vegetables less than daily at the age of 45-55 had significantly higher risk of developing frailty approximately 18 years later compared with those consuming more than daily (adjusted OR=1.29, 95%CI=1.05-1.58). A Swedish study conducted a secondary data analysis of 371 independent community-dwelling Swedish men and women aged 80 years or older who participated in a randomized trial designed to evaluate the effects of a preventive home visit and multi-professional senior group meetings (28). According to this study, frequency of vegetable intake at baseline was not significantly associated with frailty risk at any time points: baseline, 12 months, or 24 months (Unadjusted OR=1.22, 95%CI=0.86-1.73 at 1 year, unadjusted OR=1.03, 95%CI=0.71-1.49 at 2 years) (28). Potential limitations of the discussed studies may include a small sample size, unadjusted effect measures, selection bias, and a relatively short study period.
“Inflammaging” is referred to an age-related low-grade chronic inflammation status and has been considered to be associated with the development of frailty (29). Multiple studies showed that those who are frail have significantly higher levels of inflammatory markers than those who are not (29). Another possible cause of frailty is oxidative stress. The oxidative stress plays an important role in the aging process and is associated with accelerated aging. Previous studies showed that frailty was associated with higher oxidative stress and lower anti-oxidative parameters (30). Fruit and vegetables are rich in flavonoids, which form a group of natural products with various phenolic structures and are known for their health-beneficial effects, including anti-inflammatory and anti-oxidative characteristics (31). These properties may be attributed to the decreased risk of developing frailty.
In the meta-analysis, fruit consumption only was not associated with incident frailty. Since high degree of heterogeneity was observed, a random-effect meta-analysis was used. In a sensitivity analysis, excluding one study showing very high OR (24) significantly decreased the heterogeneity from 69% to 0%. A meta-analysis involving the remaining three cohorts showed that the highest fruit consumption group had a significantly lower risk of incident frailty (pooled OR=0.51, 95%CI=0.31-0.83, p<0.01). These findings suggest that the results of the meta-analysis of the fruit consumption and incident frailty may not be robust and that it is not necessarily true that fruit is not associated with a lower incident frailty risk.
The current review has potential limitations. First, the number of cohorts included in the meta-analysis were relatively small. However, the result of the meta-analysis showed the significant inverse association between fruit and vegetable consumption and incident frailty risk was persistent and that the degree of heterogeneity was low. Second, a systematic search of the literature was conducted using PubMed only, therefore, some important studies may have been missed. Nonetheless, the chance may be limited since the comprehensive search strategy with an extensive array of search terms, including MeSH terms, was applied and the reference list of the relevant papers was scrutinized.
This study has multiple strengths. First, the robust search protocol was developed following the PRISMA statements. Second, the comprehensive search strategy, including screening done by two researchers independently, assessment of heterogeneity and methodological quality. In addition, it was possible to perform the meta-analysis and show the significant inverse association between fruit and vegetable consumption and incident frailty risk.

 

Conclusion/Relevance

This systematic review and meta-analysis provided the pooled evidence that high fruit and vegetable consumption may be beneficial for preventing the development of frailty in older adults. As increasing fruit and vegetable consumption is feasible and relatively cheap without significant side effects, this can be a relevant strategy to prevent frailty. Randomized controlled trials are warranted to confirm the positive effects against frailty (32, 33).

 

Funding: We had no specific funding to support this study.

Conflict of interests: All authors declare no conflict of interest.

Acknowledgment: We are grateful to the authors who provided additional data.

Ethical standards: This systematic review and meta-analysis study was conducted according to the PRISMA guidelines and the prespecified protocol was registered at PROSPERO.

 

SUPPLEMENTARY MATERIAL

 

References

1. Fruit and Vegetables for Health Initiative, Fruit and Vegetables for Health Initiative; 2018. http://www.fao.org/3/i6807e/i6807e.pdf. Accessed 21 March 2021.
2. Slavin, JL, Lloyd, B. Health benefits of fruits and vegetables. Adv Nutr 2012;3(4):506-516.
3. Who, J, Consultation, FE. Diet, nutrition and the prevention of chronic diseases. World Health Organ Tech Rep Ser 2003;916(i-viii).
4. Nicklett, EJ, Kadell, AR. Fruit and vegetable intake among older adults: a scoping review. Maturitas 2013;75(4):305-312.
5. Clegg, A, Young, J, Iliffe, S, et al. Frailty in elderly people. Lancet 2013;381(9868):752-762.
6. Collard, RM, Boter, H, Schoevers, RA, et al. Prevalence of frailty in community-dwelling older persons: a systematic review. J Am Geriatr Soc 2012;60(8):1487-1492.
7. Kojima, G. Frailty as a Predictor of Future Falls Among Community-Dwelling Older People: A Systematic Review and Meta-Analysis. J Am Med Dir Assoc 2015;16(12):1027-1033.
8. Kojima, G. Frailty as a predictor of disabilities among community-dwelling older people: a systematic review and meta-analysis. Disabil Rehabil 2017;39(19):1897-1908.
9. Kojima, G, Taniguchi, Y, Iliffe, S, et al. Frailty as a Predictor of Alzheimer Disease, Vascular Dementia, and All Dementia Among Community-Dwelling Older People: A Systematic Review and Meta-Analysis. J Am Med Dir Assoc 2016;17(10):881-888.
10. Vermeiren, S, Vella-Azzopardi, R, Beckwée, D, et al. Frailty and the Prediction of Negative Health Outcomes: A Meta-Analysis. J Am Med Dir Assoc 2016;17(12):1163.e1161-1163.e1117.
11. Kojima, G. Frailty as a predictor of hospitalisation among community-dwelling older people: a systematic review and meta-analysis. J Epidemiol Community Health 2016;70(7):722-729.
12. Kojima, G. Frailty as a Predictor of Nursing Home Placement Among Community-Dwelling Older Adults: A Systematic Review and Meta-analysis. J Geriatr Phys Ther 2018;41(1):42-48.
13. Kojima, G. Frailty as a Predictor of Emergency Department Utilization among Community-Dwelling Older People: A Systematic Review and Meta-Analysis. J Am Med Dir Assoc 2019;20(1):103-105.
14. Cesari, M, Prince, M, Thiyagarajan, JA, et al. Frailty: An Emerging Public Health Priority. J Am Med Dir Assoc 2016;17(3):188-192.
15. Kojima, G, Liljas, AEM, Iliffe, S. Frailty syndrome: implications and challenges for health care policy. Risk Manag Healthc Policy 2019;12:23-30.
16. Azzolino, D, Passarelli, PC, De Angelis, P, et al. Poor Oral Health as a Determinant of Malnutrition and Sarcopenia. Nutrients 2019;11(12).
17. Meng, SJ, Yu, LJ. Oxidative stress, molecular inflammation and sarcopenia. Int J Mol Sci 2010;11(4):1509-1526.
18. Kojima, G, Avgerinou, C, Iliffe, S, et al. Fruit and Vegetable Consumption and Frailty: A Systematic Review. J Nutr Health Aging 2018;22(8):1010-1017.
19. Kojima, G, Avgerinou, C, Iliffe, S, et al. Adherence to Mediterranean Diet Reduces Incident Frailty Risk: Systematic Review and Meta-Analysis. J Am Geriatr Soc 2018;66(4):783-788.
20. Moher, D, Liberati, A, Tetzlaff, J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Bmj 2009;339:b2535.
21. Fried, LP, Tangen, CM, Walston, J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56(3):M146-156.
22. Wells, G, Shea, B, O’connell, D, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Ottawa: Ottawa Hospital Research Institute. oxford. asp; 2011.
23. Fung, TT, Struijk, EA, Rodriguez-Artalejo, F, et al. Fruit and vegetable intake and risk of frailty in women 60 years old or older. Am J Clin Nutr 2020;112(6):1540-1546.
24. Kojima, G, Iliffe, S, Jivraj, S, et al. Fruit and Vegetable Consumption and Incident Prefrailty and Frailty in Community-Dwelling Older People: The English Longitudinal Study of Ageing. Nutrients 2020;12(12).
25. García-Esquinas, E, Rahi, B, Peres, K, et al. Consumption of fruit and vegetables and risk of frailty: a dose-response analysis of 3 prospective cohorts of community-dwelling older adults. Am J Clin Nutr 2016;104(1):132-142.
26. Gil-Salcedo, A, Dugravot, A, Fayosse, A, et al. Healthy behaviors at age 50 years and frailty at older ages in a 20-year follow-up of the UK Whitehall II cohort: A longitudinal study. PLoS Med 2020;17(7):e1003147.
27. Brunner, EJ, Shipley, MJ, Ahmadi-Abhari, S, et al. Midlife contributors to socioeconomic differences in frailty during later life: a prospective cohort study. Lancet Public Health 2018;3(7):e313-e322.
28. Johannesson, J, Rothenberg, E, Gustafsson, S, et al. Meal frequency and vegetable intake does not predict the development of frailty in older adults. Nutr Health 2019;25(1):21-28.
29. Marcos-Pérez, D, Sánchez-Flores, M, Proietti, S, et al. Association of inflammatory mediators with frailty status in older adults: results from a systematic review and meta-analysis. Geroscience 2020;42(6):1451-1473.
30. Soysal, P, Isik, AT, Carvalho, AF, et al. Oxidative stress and frailty: A systematic review and synthesis of the best evidence. Maturitas 2017;99:66-72.
31. Panche, AN, Diwan, AD, Chandra, SR. Flavonoids: an overview. J Nutr Sci 2016;5:e47.
32. Goisser, S, Guyonnet, S, Volkert, D. The Role of Nutrition in Frailty: An Overview. J Frailty Aging 2016;5(2):74-77.
33. Manal, B, Suzana, S, Singh, DK. Nutrition and Frailty: A Review of Clinical Intervention Studies. J Frailty Aging 2015;4(2):100-106.

 

SOCIAL PARTICIPATION’S ASSOCIATION WITH FALLS AND FRAILTY IN MALAYSIA: A CROSS-SECTIONAL STUDY

 

S. Risbridger1, R. Walker1,2, W.K. Gray2, S.B. Kamaruzzaman3, C. Ai-Vyrn3, N.N. Hairi4, P.L. Khoo5, T.M.Pin3

 

1. Faculty of Medical Sciences, Newcastle University, UK; 2. Northumbria Healthcare NHS Foundation Trust, UK; 3. Department of Medicine, Faculty of Medicine, University of Malaya, Malaysia; 4. Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia; .5. Sports Centre, University of Malaya, Malaysia

Corresponding Author: Tan Maw Pin, Department of Medicine, Faculty of Medicine, University of Malaya, Malaysia, mptan@ummc.edu.my

J Frailty Aging 2021;in press
Published online August 27, 2021, http://dx.doi.org/10.14283/jfa.2021.31

 


Abstract

Background: The global population is ageing rapidly, with the most dramatic increases in developing countries like Malaysia. Older people are at increased risk of multimorbidity, frailty and falls.
Objectives: In this study we aimed to determine the relationship between social participation, frailty and falls in Malaysia.
Design, Setting, and Participants: This was a cross-sectional study of individuals aged 55 years and above selected from the electoral rolls of three Klang Valley parliamentary constituencies through stratified random sampling. They were invited to take part in a questionnaire and physical assessment as part of the Malaysian Elders Longitudinal Research (MELoR) study.
Measurements: Fallers were individuals who had fallen in the previous year. Frailty was defined as meeting ≥3 of: low body mass index, reduced cognition, low physical activity, low hand-grip strength, and slow walking speed. Social participation was determined from employment status, social network, and community activity. Binomial logistic regression multivariant analysis was performed to identify links between the measures of social participation and falls and frailty.
Results: The mean age of the 1383 participants was 68.5 years, with 57.1% female. Within the population, 22.9% were fallers and 9.3% were frail. Social isolation (OR= 2.119; 95% CI=1.351-3.324), and non-engagement in community activities (OR=2.548; 95% CI=1.107-5.865) were associated with increased frailty. Falls increased with social isolation (OR=1.327; 95% CI=1.004-1.754).
Conclusions: Previous studies have shown social participation to be linked to frailty and falls risk, and social isolation to be a predictor of falls. In this study frailty was associated with all three social participation measures and history of falls was associated with social isolation.

Key words: Healthy ageing, frailty, falls, social isolation, community.


 

Introduction

The world’s population is ageing rapidly and Asian countries are expected to see a much greater increase than their more developed counterparts (1). Already, the proportion of over-65s in the Malaysian population rose from 3.9% in 2000 to 6.7% in 2018This demographic transition is likely to lead to increased dependency, due to frailty, falls, and other age-related conditions, and requires a shift in health and social care provision (2-4).
Advancing age is associated with frailty as the result of global, cumulative, cyclical physiological decline. There is no single concept or phenotype to describe frailty due to its complex mixture of increasing vulnerability, decreasing cognition causing confusion and restricted mental capacity, and reduced physical abilities. Frailty can be completely reversible or improved through intervention (5). Frailty-related syndromes include falls, delirium, lack of mobility, incontinence and susceptibility to medication side effects (6). The prevalence of frailty in Malaysia has been reported as being between 5.7- 9.4% in the over 65s (3, 7-9). The longer individuals live, the greater their risk developing age-related conditions, with the population aged 80 years and above increasing the most rapidly and representing individuals at highest risk of falls and frailty (10).
A bidirectional relationship is likely to exist between falls and frailty. As one of the frailty-related syndromes, falls have multiple associated risk factors including: sarcopenia, impaired sensorimotor function, environmental factors such as home hazards, medication side effects, and cardiovascular diseases (11-13). Falls have been identified as the second leading cause of unintentional death globally (14). The prevalence of falls in over 55’s in Malaysia was reported as 18.9%, with many studies in South-East Asia reporting comparatively lower prevalence than in more developed countries (2). In their discussion on healthy ageing, the World Health Organization highlighted the multifactorial causes of falls; social interaction and community support was highlighted as an area for helping prevent falls (15). They described social participation as one of the key pillars of ‘Active Ageing’ and highlighted its necessity for healthy ageing (16, 15).
Whilst no universal definition of social participation exists it is often described as ‘a person’s involvement in activities providing interactions with others in society or the community’ (17, 18). The continuum of participation ranges from those with ‘active’ roles running organisations, to solely participating in these activities, and extends to employment. These active roles often require higher levels of interaction with the local community (19). This social participation is recognised as a major contributor to health with evidence demonstrating reduction in all-cause mortality (18).
Social participation may be reduced with increasing age (20). Social isolation is associated with mortality, hospitalisation, mild cognitive impairment (MCI), dementia, and many other health conditions (21-24). Protective mechanisms such as social inclusion and cohesion may decrease frailty prevalence and reduce the incidence of falls (25).
Social participation, frailty, and falls are related and in turn may influence healthy ageing and quality of life for older adults (26). In this study we aimed to gain insights into the relationship between social participation, frailty, and falls in the elderly Malaysian population.

 

Methods

Design

This was an exploratory analysis using cross sectional data.

Participants

The MELoR study is a longitudinal cohort study based in Klang Valley, Kuala Lumpur. The initial study consisted of a 14-section questionnaire, which was undertaken at the participant’s home, and a clinical assessment completed at the University of Malaya Medical Centre. The questionnaire was administered by trained interviewers in English, Malay, Chinese, or Tamil, as appropriate to the participant.
Data collection occurred between November 2013 and October 2015. The electoral rolls of the Parliamentary constituencies of Petaling Jaya North, Petaling Jaya South, and Pantai Valley were used to determine the base population for the study. Individuals aged 55 years and above in 2013 were selected through simple random sampling, stratified by age deciles and ethnicity, and were included if they could provide informed consent. An age cut-off of 55 years was used as this was the mandatory retirement age in Malaysia at study initiation, though it has since increased to 60 years.
Stratification by ethnicity was for the three main ethnic groups in Malaysia: Malay, Chinese, and Indian. The exclusion criteria included those who were institutionalised, bed-bound, unable to access the research centre, or those who had communication difficulties, including severe cognitive impairment meaning they lacked the ability to answer the questionnaire. These initial cross-sectional data were used for this study, as the longitudinal follow up data were not yet available.
A total of 8769 individuals were invited to take part in the study, of whom 5815 were initially contactable, and 3334 met all the eligibility criteria.

Measurements

An adapted version of the Fried frailty phenotype was operationalised based on the available data. The ‘shrinking’ element was defined in line with the HAALSI cohort study (27), using body mass index (BMI); a BMI lower than the WHO recommended 18.5k/m2 was given a positive score (28). The ‘poor endurance and energy’ element was replaced by a measure of cognitive impairment, the Montreal cognitive assessment (MoCA); any individual scoring ≤18 on the MoCA after educational adjustment was determined to have MCI, in line with the validation of the Bahasa Malaysia MoCA (29). The ‘low physical activity’ element was measured using the international physical activity questionnaire (IPAQ); the bottom quintile were given a positive score, ≤292.68 for males and ≤216.00 for females. The ‘slowness’ element was a test of walking 15ft; a cut-off of ≥7 seconds was used for males and females as this included all the bottom quintile. The ‘weakness’ element was a test of hand-grip strength (HGS); the bottom quintile was any male with right-handed HGS ≤21.83kg and any female with right-handed HGS ≤14.50kg. In keeping with the original methods, a score of three or more out of five was considered to signify a diagnosis of frailty (5). Adjustments to the original frailty phenotype were undertaken partly due to data availability. The decision to include the MoCA as a measure of cognitive frailty was in recognition of the fact that cognition does have a major effect on frailty. Lack of measurement of cognition is a key issue with Fried’s original score (27, 30). Participants were determined to be a faller if they had reported at least one fall in the previous 12 months.
Social participation was measured in three ways; as these do not form a coherent score, each were analysed separately and discussed individually where appropriate. Employment status was self-disclosed within the questionnaire: whether they had ever worked, and whether they were currently working. ‘Working’ included self-employment, family businesses, and private or governmental employment We wanted to highlight the difference within the population between those who were retired, as is common in this age group in Malaysia, and those who were unemployed and have never worked who may be at greater risk of conditions associated with ageing. The Lubben Social Network Scale-6 (LSNS-6) was used to determine which individuals were at risk of social isolation, as per the published guidelines (31). Levels of community activities (such as sports groups, clubs, societies, and involvement with non-governmental/ voluntary organisations) were separated into three groups: those who had no community activities ‘none’, those who had relatively ‘inactive roles’ or simply stated membership with no role attached, and those with ‘active roles’ in positions of responsibility such as a committee member or tutor. In the discussion, ‘social participation’ is used as an overarching concept of inclusion in society, measured through these three scales.

Statistical methods and data analysis

Data were analysed using SPSS Version 26 with the significance threshold set at p <0.05. Univariate analysis was performed using Pearson’s chi-squared statistical test of homogeneity. Significant results were then taken on to post hoc analysis with multiple z-tests of two proportions, with Bonferroni corrections, and binomial logistic regression multivariant analysis.
Participants missing demographic data were excluded from analysis as they could not be correctly differentiated within populations. Individuals missing data either for frailty or falls, but not both, were included in the analysis for the sections they had completed. The same process was applied for the three measures of social participation. Participants who did not have every item completed for the frailty score fell into two categories: those with enough data to assign ‘frail’ or ‘not frail’; those without enough available data who were therefore excluded from this part of the analysis. Assignment to a category was determined according to one of three criteria: they had already scored three so were ‘frail’; they had scored zero and were missing one or two items of data so were ‘not frail’; they had scored one and were missing one piece of data so were ‘not frail’.

 

Results

The total study population was 1383 after removal of incomplete entries, duplications, and those who did not meet eligibility criteria. The cohort which were excluded in data cleaning had similar age, sex, ethnicities, levels of social isolation and participation, and number of fallers to the final sample used, according to the data available.
As shown in Table 1, the average age was 68.5 years, with the eldest participant aged 93 years. The largest ethnic group was Chinese. Only 2.9% had no formal education, and 73.9% had secondary education or higher. The mean BMI was 25.33 kg/m2, ranging from 13.62 to 59.63. Most of the population were not currently employed, although they had been previously. 28% were found to be at risk of social isolation. 33.1% reported being a member of a society, 10.6% were members of Non-Governmental Organisations or charities, and 18% had active roles in either activity.

Table 1. Basic characteristics and outcome data from the study population

 

As shown in Table 1, 126 (9.3%) of the study population were identified as ‘frail’, while for 2% of the population there were not enough data to determine their status. According to the specific frailty score calculated, 591 (45.1%) were deemed non-frail, 603 (46.0%) were pre-frail, and 117 (9%) frail. 311 (22.9%) were identified as a ‘faller’ (1.8% of the sample not completing this section) of whom 201 (66.8%) had only fallen once in the preceding 12 months.
117 (8.5%) participants had never worked, of whom 33 (28.9%) were fallers and 26 (23.2%) were frail. Of the 284 (20.7%) participants who were still currently employed, 53 (18.9%) were fallers and 12 (4.2%) were frail. There was a statistically significant difference in proportions of those who were frail when grouped by employment status, Χ2= 34.949, p <0.001. Regression analysis showed employment status no longer had a statistically significant effect on diagnosis of frailty when other variables had been considered, mainly educational attainment.
382 (28%) participants were deemed to be at risk of social isolation when using the LSNS-6; 101 (26.9%) were identified as fallers and 60 (16.3%) were frail. There was a statistically significant difference in frailty between the isolation classes, Χ2= 31.436, p <0.001. Regression analysis showed those at risk of social isolation had 2.119 (95% CI 1.351-3.324) times higher odds of being classed as frail, p =0.001, as shown in Fig 1.

Figure 1. Adjusted regression analysis for frailty. Odds ratio showing increased frailty compared to index category. Error bars representing 95% CI

 

In relation to social isolation, there was a statistically significant difference in the proportion of those who fell compared to those who did not, Χ2= 4.579, p=0.032. Regression analysis showed those at risk of social isolation had 1.327 (95% CI 1.004-1.754) times higher odds of falling, p =0.047, as shown in Fig 2.

Figure 2. Adjusted regression analysis for falls. Odds ratio showing increased falls compared to index category. Error bars representing 95% CI

 

843 (62%) participants were not involved in community groups; 201 (24.1) of these were fallers and 99 (12%) were frail. 244 (28%) had at least one active role with 48 (19.9%) of these being fallers and 7 (2.9) being frail. There was a statistically significant difference in proportions of those who were frail when grouped by involvement in community groups, Χ2= 26.139, p <0.001. Regression analysis showed that those not participating in community groups had 2.548 (95% CI 1.107-5.865) times higher odds of being frail than those with active roles, p =0.028 (seen in Fig 1).

 

Discussion

Reduced social participation, measured through social isolation according to the LSNS-6 and absence of participation in community groups, was associated with frailty in this study. Falls were also associated with reduced social participation in this study specifically through the measure of increased social isolation.
The prevalence of frailty in this cohort was 9.3%, in keeping with prevalence estimates of between 5.7% and 9.4% from other studies (3, 7-9, 32). As this cohort included individuals aged 55 years and over, rather than the usually employed lower age cut-offs of 60 or 65 years, the prevalence was expected to be lower than previously reported. The relatively high prevalence may be due to the high proportion of both females and those aged ≥75 in the study, and the way in which Fried’s criteria were operationalised in our adapted assessment. As expected, age had a large impact on the diagnosis of frailty; 24.5% of those aged ≥75 were frail, with only 8.5% of individuals aged 70 to 74 years being considered frail. Badrasawi et al in 2016 studied a demographically similar population in Klang Valley, in people ≥60. They found a frailty prevalence of 8.9% in a smaller sample of 473 participants[8].
Frailty was found to be significantly associated with social isolation, according to the LSNS-6, and lack of participation in community groups. These both caused the odds of being frail to be two times higher in the adjusted models. Once adjusted for education, the relationship between employment status and frailty was no longer statistically significant. Community activities are often physically or mentally stimulating, which appears to maintain healthier levels of activity and cognitive function (18, 33).
Being involved in the community and maintaining social ties will provide a support system for older people, improve their mental wellbeing, and allow them to stay active; having objectives and a purpose in life has been shown to improve happiness and health (24, 23). The link between social activity and frailty has not been as well studied as other aspects of frailty. Few studies exist globally, but the positive nature of social participation is shown often (18, 34, 35). Developing systems to increase social participation, particularly in the oldest age groups, is likely to improve the lives of Malaysia’s ageing population.
Social isolation was associated with increased reported falls after adjusting for age, gender, and ethnicity. This fits with research by Pohl et al in the USA who determined that social isolation is a good predictor of falls, though participants had an average age 10 years older than in this study (22). No similar studies have been performed in Malaysia or within South-East Asia. Although our cross-sectional study does not suggest a causal link between social isolation and falling, social isolation may increase fear of falling or the consequences of a fall may be more severe, making the experience easier to recall. Many studies have highlighted the chain effect of falling, fearing falling, decreasing social activities, increasing isolation, and then having a greater risk of falling again[36]. An improved social circle, and regular contact with friends and family, could mean the individuals have better quality of life and reduced healthcare burden (34, 35).
The importance of the effects of social participation, and the risks of social isolation could not be more relevant to the current global situation. COVID-19 has led to many countries introducing social-distancing and ‘lockdown’ measures; it was estimated that in March 2020 over one-third of the global population had some form of restricted movement (37). Individuals who are older, have chronic health conditions, or are otherwise vulnerable are most likely to be facing the longest periods of isolation; social isolation in the elderly is already known to put them at risk of neurocognitive decline, cardiovascular disease, autoimmune problems, depression and anxiety, as well as an increase in mortality of nearly one-third (37-39). To add to that, an increase in frailty and falls will place increased demands on services. However, COVID-19 was not the trigger for social isolation of the older populations (but definitely worsened the problem), insights into the root causes of disintegration within communities and lack of opportunities for participation in the older age groups may inform future interventions and improve all aspects of health for the older population. Protecting this population from the future health risks caused by the social isolation from this pandemic would allow health systems to better prepare for similar future challenges. The WHO Global Network for Age-friendly Cities and Communities is an important example of current policy striving to better provide for our older populations in this way, and more initiatives such as this could have a major impact in improving quality of life (40).

Limitations

Due to the retrospective nature of the study questionnaire, falls prevalence may have been underestimated, as recall bias can underestimate falls by 13-32% (12). This bias would also limit recall of engagement in community activities. As this study was performed cross-sectionally, reverse causation cannot be assessed, and so temporal relationships can be suggested but not proved.
We used an adapted Fried frailty score which has not been validated, and this may mean that the predictive value demonstrated by the original score is not reflected in this study. The frailty phenotype has several documented limitations including its reliance on physical traits and ignoring psychological and cognitive decline (41). The lack of availability of data about ‘exhaustion’ is the most limiting aspect of this operationalisation. Previous researchers have suggested links between the physical frailty described in Fried’s phenotype and cognitive decline, and the usefulness of adding a cognitive test to the phenotype, but there is no evidence that this could replace the missing element (42).
The younger cohorts included in this study may also have biased our findings. The older an individual is, the more likely they are to be affected by falls and frailty, and so including down to the ages of 55 may have hidden some key details.

Recommendations for future work

A longitudinal cohort study could help determine whether social isolation in fact leads to frailty or if frail individuals are less able to participate in current society. Whether greater participation in society before a person retires could reduce their future risk of frailty and falls is an important link to the multifactorial aetiology of frailty.
Creation of a universally agreed measurement of social participation and frailty would make research more relatable to the global population. A score which identifies the key areas of social participation, while being accessible to countries with poor healthcare infrastructure and funding, would best provide a global measurement of participation to allow results to be directly compared between populations. A universal consensus for the diagnosis of frailty would also mean results could be directly compared globally.

 

Conclusions

Reduced social participation, measured with reduced social network and absence of participation in community groups, is associated with the frailty phenotype in individuals aged 55 years and over included in this study. Falls, as an outcome of frailty, also shows an association with reduced social participation through increased social isolation. Within developing nations, social participation may be an affordably modifiable risk factor for frailty and its associated syndromes, which would in turn improve quality of life and support healthy ageing.

 

Ethics approval: The MELoR study was approved by the University of Malaya Medical Centre Medical Ethics Committee (Ref: 925.4).

Authors’ contributions: Material preparation and data collection were performed by Shahrul B Kamaruzzaman, Chin Ai-Vyrn, Noran N Hairi, Phaik Lin Khoo, and Tan Maw Pin. Analysis was performed by Sophie Risbridger, under the guidance of Richard Walker and William Keith Gray. The manuscript was written by Sophie Risbridger and all authors commented on versions of the manuscript.

Funding: This work was supported by the Ministry of Health, Malaysia, Long-term Research Grant Scheme [grant LR005-2019]. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

 

References

1. United Nations Department of Economic and Social Affairs. World Population Ageing 2017- Highlights2017 2017.
2. Alex D, Khor HM, Chin AV, Hairi NN, Othman S, Khoo SPK et al. Cross-sectional analysis of ethnic differences in fall prevalence in urban dwellers aged 55 years and over in the Malaysian Elders Longitudinal Research study. BMJ Open. 2018;8(7):e019579. doi:10.1136/bmjopen-2017-019579.
3. Ahmad NS, Hairi NN, Said MA, Kamaruzzaman SB, Choo WY, Hairi F et al. Prevalence, transitions and factors predicting transition between frailty states among rural community-dwelling older adults in Malaysia. PLoS One. 2018;13(11):Online. doi:10.1371/journal.pone.0206445.
4. Crome P, Lally F. Frailty: joining the giants. Canadian Medical Association Journal. 2011;183(8):889-90. doi:10.1503/cmaj.110626.
5. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J et al. Frailty in Older Adults: Evidence for a Phenotype. The Journals of Gerontology: Series A. 2001;56(3):M146-57. doi:10.1093/gerona/56.3.M146.
6. British Geriatrics Society, Age UK, Royal College of General Practitioners. Fit for frailty- Consensus best practice guidance for the care of older people living in community and outpatient settings. London2014.
7. Sathasivam J, Kamaruzzaman SB, Hairi F, Ng CW, Chinna K. Frail Elders in an Urban District Setting in Malaysia: Multidimensional Frailty and Its Correlates. Asia Pacific Journal of Public Health. 2015;27(8 Suppl):52S-61S. doi:10.1177/1010539515583332.
8. Badrasawi M, Shahar S, Singh DKA. Risk Factors of Frailty Among Multi-Ethnic Malaysian Older Adults. International Journal of Gerontology. 2017;11(3):154-60. doi:10.1016/j.ijge.2016.07.006.
9. Siriwardhana DD, Hardoon S, Rait G, Weerasinghe MC, Walters KR. Prevalence of frailty and prefrailty among community-dwelling older adults in low-income and middle-income countries: a systematic review and meta-analysis. BMJ Open. 2018;8(3):e018195. doi:10.1136/bmjopen-2017-018195.
10. Tinetti M, Huang A, Molnar F. The Geriatrics 5M’s: A New Way of Communicating What We Do. J Am Geriatr Soc. 2017;65(9):2115. doi:10.1111/jgs.14979.
11. Caird FI, Andrews GR, Kennedy RD. Effect of posture on blood pressure in the elderly. British Heart Journal. 1973;35(5):527-30. doi:10.1136/hrt.35.5.527.
12. Masud T, Morris RO. Epidemiology of falls. Age and Ageing. 2001;30 Suppl 4:3-7. doi:10.1093/ageing/30.suppl_4.3.
13. Goh CH, Ng SC, Kamaruzzaman SB, Chin AV, Poi PJ, Chee KH et al. Evaluation of Two New Indices of Blood Pressure Variability Using Postural Change in Older Fallers. Medicine (Baltimore). 2016;95(19):e3614. doi:10.1097/MD.0000000000003614.
14. WHO. Falls. In: Fact Sheet. World Health Organisation, Online. 2018. https://www.who.int/news-room/fact-sheets/detail/falls. Accessed 08/04/2020 2020.
15. WHO. World Report on Ageing and Health. Geneva: World Health Organisation; 2015 30/09/2015.
16. WHO. Active Ageing: A Policy Framework. Geneva: World Health Organisation;2002 04/2002.
17. Eriksson BG. Ordinal dispersion of ratings of social participation as a function of age from 70 years of age among the H-70 panel, Gothenburg, Sweden. Archives of Gerontology and Geriatrics. 2008;47(2):229-39. doi:10.1016/j.archger.2007.08.007.
18. Okura M, Ogita M, Yamamoto M, Nakai T, Numata T, Arai H. Community activities predict disability and mortality in community-dwelling older adults. Geriatrics and Gerontology International. 2018;18(7):1114-24. doi:10.1111/ggi.13315.
19. Aw S, Koh G, Oh YJ, Wong ML, Vrijhoef HJM, Harding SC et al. Explaining the continuum of social participation among older adults in Singapore: from ‘closed doors’ to active ageing in multi-ethnic community settings. Journal of Aging Studies. 2017;42:46-55. doi:10.1016/j.jaging.2017.07.002.
20. Liu JY. The severity and associated factors of participation restriction among community-dwelling frail older people: an application of the International Classification of Functioning, Disability and Health (WHO-ICF). BMC Geriatriatrics. 2017;17(1):43. doi:10.1186/s12877-017-0422-7.
21. Rawtaer I, Gao Q, Nyunt MS, Feng L, Chong MS, Lim WS et al. Psychosocial Risk and Protective Factors and Incident Mild Cognitive Impairment and Dementia in Community Dwelling Elderly: Findings from the Singapore Longitudinal Ageing Study. Journal of Alzheimer’s Disease. 2017;57(2):603-11. doi:10.3233/JAD-160862.
22. Pohl JS, Cochrane BB, Schepp KG, Woods NF. Falls and Social Isolation of Older Adults in the National Health and Aging Trends Study. Research in Gerontological Nursing. 2018;11(2):61-70. doi:10.3928/19404921-20180216-02.
23. Courtin E, Knapp M. Social isolation, loneliness and health in old age: a scoping review. Health and Social Care in the Community. 2017;25(3):799-812. doi:10.1111/hsc.12311.
24. Uchino BN. Social support and health: a review of physiological processes potentially underlying links to disease outcomes. Journal of Behavioural Medicine. 2006;29(4):377-87. doi:10.1007/s10865-006-9056-5.
25. Chon D, Lee Y, Kim J, Lee KE. The Association between Frequency of Social Contact and Frailty in Older People: Korean Frailty and Aging Cohort Study (KFACS). Journal of Korean Medical Sciences. 2018;33(51):e332. doi:10.3346/jkms.2018.33.e332.
26. Hayashi T, Umegaki H, Makino T, Huang CH, Inoue A, Shimada H et al. Combined Impact of Physical Frailty and Social Isolation on Rate of Falls in Older Adults. The journal of nutrition, health & aging. 2020;24(3):312-8. doi:10.1007/s12603-020-1316-5.
27. Payne CF, Wade A, Kabudula CW, Davies JI, Chang AY, Gomez-Olive FX et al. Prevalence and correlates of frailty in an older rural African population: findings from the HAALSI cohort study. BMC Geriatriatrics. 2017;17(1):293. doi:10.1186/s12877-017-0694-y.
28. Global Health Observatory. Mean Body Mass Index (BMI). In: GHO Data. World Health Organisation. 2009. https://www.who.int/gho/ncd/risk_factors/bmi_text/en/. Accessed 01/04/2020 2020.
29. Normah CD, Shahar S, Zulkifli BH, Razali R, Chin A, Omar A. Validation and Optimal Cut-Off Scores of the Bahasa Malaysia Version of the Montreal Cognitive Assessment (MoCA-BM) for Mild Cognitive Impairment among Community Dwelling Older Adults in Malaysia. Sains Malaysiana. 2016;45(9):1337-43.
30. Lewis EG, Coles S, Howorth K, Kissima J, Gray WK, Urasa S et al. The prevalence and characteristics of frailty by frailty phenotype in rural Tanzania. BMC Geriatrics. 2018;18(1). doi:10.1186/s12877-018-0967-0.
31. Lubben J, Blozik E, Gillmann G, Iliffe S, von Renteln Kruse W, Beck JC et al. Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. The Gerontologist,. 2006;46(4):503-13. doi:10.1093/geront/46.4.503.
32. Gray WK, Richardson J, McGuire J, Dewhurst F, Elder V, Weeks J et al. Frailty Screening in Low- and Middle-Income Countries: A Systematic Review. Journal of the American Geriatrics Society. 2016;64(4):806-23. doi:10.1111/jgs.14069.
33. Okura M, Ogita M, Yamamoto M, Nakai T, Numata T, Arai H. The relationship of community activities with cognitive impairment and depressive mood independent of mobility disorder in Japanese older adults. Arch Gerontol Geriatr. 2017;70:54-61. doi:10.1016/j.archger.2016.12.010.
34. Pereira GN, Morsch P, Lopes DG, Trevisan MD, Ribeiro A, Navarro JH et al. Social and environmental factors associated with the occurrence of falls in the elderly. Ciencia and Saude Coletiva. 2013;18(12):3507-14. doi:10.1590/s1413-81232013001200007.
35. Hajek A, Konig HH. The association of falls with loneliness and social exclusion: evidence from the DEAS German Ageing Survey. BMC Geriatriatrics. 2017;17(1):204. doi:10.1186/s12877-017-0602-5.
36. Petersen N, König H-H, Hajek A. The link between falls, social isolation and loneliness: A systematic review. Archives of gerontology and geriatrics. 2020;88:104020.
37. Lippi G, Henry BM, Bovo C, Sanchis-Gomar F. Health risks and potential remedies during prolonged lockdowns for coronavirus disease 2019 (COVID-19). Diagnosis (Berlin). 2020;7(2):85-90. doi:10.1515/dx-2020-0041.
38. Armitage R, Nellums LB. COVID-19 and the consequences of isolating the elderly. Lancet Public Health. 2020;5(5):e256. doi:10.1016/S2468-2667(20)30061-X.
39. Douglas M, Katikireddi SV, Taulbut M, McKee M, McCartney G. Mitigating the wider health effects of covid-19 pandemic response. BMJ. 2020;369:m1557. doi:10.1136/bmj.m1557.
40. WHO. WHO Global Network for Age-friendly Cities and Communities. World Health Organisation; , Online. 2016. https://www.who.int/ageing/projects/age_friendly_cities_network/en/. Accessed 07/01/2021 2021.
41. Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. The Lancet. 2013;381(9868):752-62. doi:10.1016/S0140-6736(12)62167-9.
42. Ma L, Zhang L, Sun F, Li Y, Tang Z. Cognitive function in Prefrail and frail community-dwelling older adults in China. BMC Geriatrics. 2019;19(1):53. doi:10.1186/s12877-019-1056-8.

 

FRAILTY IN CAREGIVERS AND ITS RELATIONSHIP WITH PSYCHOLOGICAL STRESS AND RESILIENCE: A CROSS-SECTIONAL STUDY BASED ON THE DEFICIT ACCUMULATION MODEL

 

M. Canevelli1,2,*, F.S. Bersani1,*, F. Sciancalepore1, M. Salzillo1, M. Cesari3,4, L. Tarsitani1, M. Pasquini1, S. Ferracuti1, M. Biondi1, G. Bruno1

 

1. Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy; 2. National Center for Disease Prevention and Health Promotion, Italian National Institute of Health, Rome, Italy; 3. Geriatric Unit, IRCCS Istituti Clinici Scientifici Maugeri, Milan, Italy; 4. Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy; *These authors contributed equally to the work.

Corresponding Author: Marco Canevelli, Francesco Saverio Bersani, Department of Human Neurosciences, Sapienza University of Rome, Viale dell’Università 30, 00185, Rome, Italy, marco.canevelli@uniroma1.it, francescosaverio.bersani@uniroma1.it

J Frailty Aging 2021;in press
Published online June 25, 2021, http://dx.doi.org/10.14283/jfa.2021.29

 


Abstract

Background: Studies increasingly suggest that chronic exposure to psychological stress can lead to health deterioration and accelerated ageing, thus possibly contributing to the development of frailty. Recent approaches based on the deficit accumulation model measure frailty on a continuous grading through the “Frailty Index” (FI), i.e. a macroscopic indicator of biological senescence and functional status.
OBJECTIVES: The study aimed at testing the relationship of FI with caregiving, psychological stress, and psychological resilience.
DESIGN: Cross-sectional study, with case-control and correlational analyses.
PARTICIPANTS: Caregivers of patients with dementia (n=64), i.e. individuals a priori considered to be exposed to prolonged psychosocial stressors, and matched controls (n=64) were enrolled.
MEASUREMENTS: The two groups were compared using a 38-item FI condensing biological, clinical, and functional assessments. Within caregivers, the association of FI with Perceived Stress Scale (PSS) and Brief Resilience Scale (BRS) was tested.
RESULTS: Caregivers had higher FI than controls (F=8.308, p=0.005). FI was associated directly with PSS (r=0.660, p<0.001) and inversely with BRS (r=-0.637, p<0.001). Findings remained significant after adjusting for certain confounding variables, after excluding from the FI the conditions directly related to psychological stress, and when the analyses were performed separately among participants older and younger than 65 years.
CONCLUSIONS: The results provide insight on the relationship of frailty with caregiving, psychological stress, and resilience, with potential implications for the clinical management of individuals exposed to chronic emotional strain.

Key words: Frailty, stress, resilience, caregiving, psychopathology, comorbidity.


 

Introduction

Frailty has been originally conceptualized in the context of geriatric research to describe a condition of reduced homeostatic reserves and increased vulnerability to exogenous and endogenous stimuli often characterizing older adults (1). Although a definition of frailty has long been debated, it has recently been defined by the World Health Organization as “a progressive age-related decline in physiological systems that results in decreased reserves of intrinsic capacity, which confers extreme vulnerability to stressors and increases the risk of a range of adverse health outcomes” (2), and by an international consensus group as “a medical syndrome with multiple causes and contributors that is characterized by diminished strength, endurance, and reduced physiologic function that increases an individual’s vulnerability for developing increased dependency and/or death” (3).
Overall, frailty is considered to represent an estimate of organism’s biological age and, as such, it is increasingly explored in several medical areas to account for the interindividual variability in health trajectories and outcomes (4-6). Recent approaches measure frailty on a continuous grading according to the model of deficit accumulation, which postulates that the individual’s degree of frailty is related to the amount of health deficits accumulated with aging; accordingly, one’s biological and clinical complexity can be estimated by condensing such negative attributes in a single continuous variable, the Frailty Index (FI) (5, 7-11).
The concept of psychological stress is nowadays increasingly explored in virtually all fields of health-related research. It has been shown that exposure to psychological and social stress in childhood and adulthood, as well as the cumulation of psychosocial stressors over time, can have a significant negative impact on health mediated by a range of molecular mechanisms including, but not limited to, alterations in hypothalamic–pituitary–adrenal axis functioning and inflammatory responses (12).
Exposure to chronic psychological stress has been associated with increased vulnerability and worse outcomes related to cardiovascular, mental, metabolic, oncological, and infectious diseases, as well as to disability and earlier mortality (12). As a consequence, it seems possible that chronic psychological stress represents a factor contributing to the development of frailty. Such possibility is supported by the evidence linking psychological stress to the molecular mediators of biological age: while the condition of frailty has been proposed to represent a product of senescent biological age (4-6, 9, 13), studies have suggested that chronic exposure to psychological stress play a role in accelerating biological aging, i.e. leading to premature senescence, as documented, for example, by the widely replicated association of perceived psychological stress and stress-related psychiatric disorders with shorter telomere length (TL) in leukocytes (14-16).
Relatively few research has been performed so far to test the association between psychological stress and frailty. Further, to the best of our knowledge, no studies have explored such relationship among caregivers of patients with dementia, i.e. individuals exposed to severe and prolonged psychological burden (17), and operationalizing frailty through the FI as deficit accumulation. It can be hypothesized that caregiving, intended as a condition of chronic psychological stress exposure, is associated with accelerated senescence and higher accrual of health deficits, and that, among caregivers, frailty levels are directly related to the intensity of perceived psychological stress and inversely related to the individual’s capacity of psychological resilience, i.e. the capacity of maintaining positive emotional responses in the presence of psychosocial stressors. Therefore, the aim of the present study was (i) to compare biological age and functional status assessed through the FI in caregivers and matched controls, and (ii) within caregivers, to test the association of FI with measures of perceived psychological stress and resilience.

 

Methods

Sample

A total of 128 individuals were enrolled in the study: 64 caregivers of patients with dementia (i.e. individuals a priori considered as exposed to prolonged psychosocial stressors) and 64 non-caregiver matched controls. Such amount of participants was selected as a sample size calculation performed with the G*Power 3.1 software (18) indicated that 64 subjects in each group are needed to achieve an effect size of 0.5 with power=0.80 and alpha=0.05 (two-tailed) in between-group comparisons.
Caregivers were consecutively recruited through their carereceiver’s healthcare professionals at the Memory Clinic of Policlinico Umberto I University Hospital of Rome (Italy). Non-caregiver controls were recruited among volunteers in order to be age- and sex-matched with caregivers. Inclusion criteria for caregivers were (i) being spouse, child, sibling, or parent of a patient with a major neurocognitive disorder diagnosed according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM5) (19), (ii) living with the carereceiver, and (iii) having the role of principal caregiver from at least two years. Caregivers and controls were not included if they had a clinically unstable and disabling medical condition at the time of the evaluation.
Participants received a complete explanation of the procedures of the study and provided consent for allowing the utilization of the collected data for research purposes. Participants were not compensated for the participation to the study.

Procedures and assessments

The frailty status of all participants (caregivers and controls, n=128) was evaluated using a 38-item FI designed according to the model of Rockwood and Mitniski, following a standard procedure (5, 9-11). As mentioned above, the FI is a health-state measure, condensing information from multiple physiological systems; it is thought to reflect individual’s biological age and vulnerability to adverse outcomes. The FI is defined as the ratio between the deficits presented by the subject and the number of deficits explored in the context of a comprehensive clinical assessment. Candidate variables include symptoms, signs, comorbidities, and disabilities meeting standardized criteria (11). Each composing item is coded as “0” or “1” depending on whether the corresponding health deficit is absent or present, respectively. The FI thus provides a continuous measure of frailty potentially ranging between 0 and 1 for each individual. A cut-off of 0.25 has been adopted to identify frail and non-frail subjects (20-22). The deficits considered for the computation of the FI used in the present study emerged from biological (e.g. oxygen saturation, systolic blood pressure, body mass index [BMI], heart rate), clinical (e.g. current and past pathologies, chronic conditions, comorbidities) and functional (e.g. difficulties in transportations, money management, household keeping) evaluations, and they are listed in Table 1. In the present study the Cronbach’s α for the overall sample (caregivers and controls) was 0.76.

Table 1. Deficits considered in the computation of the Frailty Index

 

In addition to the FI, 62 of the caregivers were also evaluated with the 10 Items Perceived Stress Scale (PSS) (23-24), and with the Brief Resilience Scale (BRS) (25-27). In the PSS, respondents are asked to rate how often they experienced psychological stress in the past month on a 5-point Likert-type scale ranging from “Never = 0” to “Very Often = 4”, and a total score is calculated such that higher score reflects higher perceived psychological stress (23-24). In the present study, the Italian version of the scale was used (24), and the Cronbach’s α was 0.85. In the BRS, respondents are asked to rate their ability to recover from psychosocial stress by answering to 6 questions on a 5-point Likert-type scale ranging from “strongly disagree=1” to “strongly agree= 5”, and a total score is calculated such that higher score reflects higher resilience (25-27). Further, the authors of BRS proposed the following scores to qualitatively differentiate levels of resilience: below 3.00=low resilience, above 4.30=high resilience (27). In the present study, the Italian version of the scale was used (25), and the Cronbach’s α was 0.89.

Statistical methods

The Statistical Package for the Social Sciences (SPSS) was used for statistical calculations. All tests were 2-tailed with alpha=0.05. Quantitative data are expressed as means ± standard deviations (SD).
Parametric tests were performed as data were normally distributed (skewness and kurtsosis between -2 and 2). Analysis of variance (ANOVA) was used to test inter-group differences in FI between caregivers and controls, while analysis of covariance (ANCOVA) was used to control for confounding variables. Pearson correlations and partial correlations were performed to test the association of PSS and BRS with FI within caregivers.
ANOVA, Pearson correlation, and chi-square (Χ²) tests were also used to perform the following sensitivity analyses: (i) analyses performed using a modified FI computed after the exclusion of variables directly related to psychological stress; (ii) analyses performed separately among participants older and younger than 65 years; and (iii) analyses performed to further stratify/investigate the characteristics of the enrolled sample).

 

Results

Almost all caregivers were spouses/partners (n=42, 65.6%) or children (n=20, 31.2%) of their carereceivers. The duration of their role as caregivers ranged between six and ten years in almost a half of cases (48.3%) and was lower than five years in 33.3% of cases. There were no significant differences between caregivers and non-caregiver controls by age, BMI, sex, and use of medications (Table 2).

Table 2. Characteristics of caregivers and controls

Abbreviations: BMI=Body Mass Index; ANOVA= Analysis of variance; X²=Chi squared; BMI data were available for 54 caregivers and 51 controls, information on medications was available for 33 caregivers and 34 controls.

 

Consistently with previous studies, the distribution of the adopted 38-item FI showed right skewness with a maximal score below 0.7 (scores ranged between 0 and 0.58).

In the overall study population, the adopted 38-item FI had a characteristic (11) right-skewed distribution with scores ranging between 0 and 0.58 (Figure 1). The mean FI value was 0.19±0.12, the median value was 0.16 (interquartile range [IQR] 0.11-0.26), and the 99th percentile was 0.56. The FI scores were higher in women than in men (0.20±0.12 vs. 0.16±0.09; F=5.708, p=0.018). Across all participants, FI scores were positively correlated with chronological age (r=0.419, p<0.001) (Figure 2). Based on the above-mentioned qualitative FI cut-off of 0.25, 28.1% (n=36) of participants could be classified as frail.

Figure 1. Distribution of FI values in caregivers and controls. Data are shown as %. FI scores are on the X-axis

Consistently with previous studies, the distribution of the adopted 38-item FI showed right skewness with a maximal score below 0.7 (scores ranged between 0 and 0.58).

 

The mean FI value was 0.21±0.12 in caregivers and 0.16±0.11 in controls. One-way ANOVA determined highly significant group differences between caregivers and controls (F[1, 127] = 8.308, p = 0.005) (Figure 3), and an extended model using age and sex as covariates did not alter the significance of this result (F[1, 124] = 11.247, p = 0.001). Using the above-mentioned FI cut-off, higher frailty prevalence was observed among caregivers compared with controls (24 vs 12, i.e. 37.5% vs. 18.8%; Χ²=5.565; p=0.018). Resilient caregivers (n=17), i.e. those with high resilience according to the above-mentioned BRS cut-off, had mean FI similar (non significantly lower) than controls (0.11±0.06 vs 0.16±0.11, F=2.247; p=0.138).

Figure 2. Scatterplot showing the significant (r=0.419, p<0.001) association of FI with age across all participants (caregivers are in black, controls are in white)

Figure 3. Graph showing the significant difference in FI between caregivers and controls (F=8.308, p=0.005). Bars indicate standard error

 

Within caregivers, mean scores of PSS and BRS were 17.94±8.90 and 3.36±1.07, respectively. FI was significantly positively associated with PSS (r=0.660, p<0.001), and it was significantly negatively associated with BRS (r=-0.637, p<0.001) (Figure 4). These correlations remained statistically significant (both p≤0.001) when age, sex, education, BMI, years of caregiving, and type of relationship with the carereceiver (i.e. being spouses/partners, children, siblings, or parents of carereceivers) were included as covariates. The FI was not significantly different between caregivers who were spouses/partners of the carereceivers (n=42) and caregivers who were children of the carereceivers (n=20) (F=0.866; p=0.356).

Figure 4. Scatterplots showing the significant association of FI with perceived psychological stress (PSS, r=0.660, p<0.001) and resilience (BRS, r=-0.637, p<0.001) within caregivers

 

As four of the 38 variables included in the FI are directly related to psychological stress (i.e. irritability, anhedonia, fatigue, sleep disorders), we created a second modified FI (defined as 34-item FI) excluding such variables from the computation of the score to be tested in sensitivity analyses. Performing between-group comparisons (caregivers vs controls) on 34-item FI and correlation analyses between 34-item FI, PSS and BRS within caregivers still gave significant findings (data not shown).
For further sensitivity, we performed between-group and within-group analyses (i) only including participants with an age higher than 64 years (caregivers n=38, controls n=39), and (ii) only including participants with an age in the range of 18-64 years (caregivers n=26, controls n=25). The mean FI values were again significantly higher in caregivers than in controls (older adults: 0.25±0.12 vs 0.19±0.11, F=4.090, p=0.047; adults: 0.17±0.10 vs 0.10±0.07, F=7.216, p=0.010), and, within caregivers, they were again significantly directly associated with PSS and inversely associated BRS in both groups (all p ≤0.003 by zero-order correlations).

 

Discussion

Consistently with the hypotheses, in the present research we observed that caregivers had more pronounced frailty, as assessed by the FI, than controls (Figure 3), and that within caregivers the degree of frailty was directly associated with the degree of perceived psychological stress and inversely associated with the degree of resilience capacity (Figure 4). The statistical significance of such findings remained when certain potentially confounding variables were controlled for, when certain conditions directly related to psychological stress (irritability, anhedonia, fatigue, sleep disorders) were excluded from the computation of FI, and when the analyses were performed separately among participants older and younger than 65 years.
Previous evidence suggested that caregivers can show more pronounced health deficits and biological senescence than non-caregivers as a consequence of the prolonged psychological burden of caregiving (17, 28), that psychological stress has a deteriorating effect on health (12), that resilience skills can contribute to reduce the negative impact of psychological stress on health (17, 29), and that frail older adults have more stress-related psychological symptoms than non-frail older adults (30). Further, studies suggested that psychological stress is associated with accelerated/premature biological senescence measured through molecular indicators of ageing, i.e. molecular systems which are thought to reflect, mediate or promote cellular ageing and biological senescence (e.g. TL, mitochondrial DNA copy number, epigenetic signatures), while psychological resilience can have a protective role (9, 14, 16, 31-33). The findings of the present research are consistent with such data, and add novelty and specificity to the field as (i) the enrolled sample had a mean age of 67.71±11.57 with ages ranging between 34 and 89, while previous studies linking FI with psychopathology were mainly focused on older adults (i.e. individuals with age ≥65) (34-37); (ii) the health and biological measures were conceptualized within the multidimensional construct of frailty evaluated on a continuous grading (FI) rather that dichotomously (i.e. frail vs non frail subjects); (iii) information was collected multimodally, i.e. by integrating senescence- and health-related dimensions emerging from biological (e.g. oxygen saturation, systolic blood pressure, BMI, heart rate), clinical (e.g. current and past pathologies, chronic conditions, comorbidities) and functional (e.g. difficulties in transportations, money management, household keeping) evaluations (Table 1).
In relation to frailty, the findings of the present study are in line with previous observations emerging from studies based on FI in which different health deficits were considered: FI scores were significantly associated with chronological age (Figure 2) (7); significantly higher FI values were observed in women than in men, consistently with previous observations of sex-specific differences in FI scores, which are often defined in the literature as the “male-female health-survival paradox” (38); the FI exhibited a right-skewed distribution with a maximal value of 0.58 (Figure 1), consistently with previous data showing that FI had an upper limit of 0.7, which have been explained by the fact that people cannot tolerate and survive health deficits above a certain threshold (39).
In relation to the health status of caregivers, our results support the relevance of resilience to psychosocial stress for such at-risk individuals: (i) among caregivers, higher levels of frailty were significantly associated with higher perceived psychological stress and with lower capacity of psychological resilience; (ii) across all subjects, while the FI of caregivers was significantly higher than that of controls, the FI of those caregivers with high levels of resilience was similar (non significantly lower) than that of controls. Such data can contribute to extend to psychological resilience the evidence suggesting that physical resilience (which has been defined as the capacity of function maintenance or recovery following biomedical or pathological challenges) plays a protecting role towards the development of frailty (40). Further, consistently with previous studies (17, 41), these findings support the possibility that being the caregiver of a chronically ill person does not inevitably lead to a more deteriorated health profile, and that the way caregivers respond to adversities play a relevant role in determining how psychosocial stressors affect health. From a clinical perspective, it is thus possible that interventions on caregivers focused on decreasing perceived psychological stress and increasing psychological resilience skills can play a role in the improvement of their frailty and general health status. Of relevance, as this was a cross-sectional study, longitudinal and causal relationships between such variables cannot be established, and both directions of causality are potentially possible.
Overall, while the study of the relationship between psychological stress, health and ageing through the analysis of molecular markers of ageing is closely related to pathophysiology, the study of such link through a FI can be more closely related to clinical and functional state, thus possibly expanding the knowledge originating from such area of investigation (9). Relatedly, recent studies in older adults have observed FI to be significantly associated with TL and epigenetic clocks in leukocytes (9, 42-44), and preliminary studies have integrated various mlecular indicators of ageing within a biomarker-based FI (45). Among the molecular indicators of ageing, increasing attentions is nowadays given to the so-called “inflammaging”, i.e. chronically increased levels of inflammatory cytokines which are thought to underlie the progression of senescence-related processes (9, 46). While the FI adopted in the current study did not incude the assessment of cytokine levels, it did consider certain conditions which are tightly related to increased inflammation, such as cancer, osteoporosis, diabetes, and previous episodes of transient ischemic attack or stroke; subsequently, the adopted deficit accumulation approach may capture certain aspects of inflammation even in absence of molecular measures of inflammatory processes.
The present study has several limitations, among which: (i) the cross sectional nature of the research does not allow to establish causal relationships , if any, between correlated variables and the potential direction of causality; (ii) some pieces of information were not fully collected for all participants: complete BMI data were available for 54 caregivers and 51 controls, data on medication use were available for 33 caregivers and 34 controls, information on PSS, BRS, and education was collected in 62 of the 64 caregivers and not in controls, information on years of caregiving was collected in 60 of the 64 caregivers; (iii) the reliability of self-report measures (such as PSS and BRS) can be affected by several biases (e.g. social desirability bias, response bias) (47); (iv) mean age of caregivers and controls was 67.72 ± 11.59 and 67.70 ± 11.63, so the findings may not be applicable to cohorts of different ages, although when the analyses were performed separately among participants older and younger than 65 years the significance of the main results did not change; (v) the study sample size (n = 128) was adequate to test between-group differences on FI (as indicated by an a priori power analysis), but not to test within group correlations, although the observed significant associations of FI with PSS and BRS had large effect sizes (r=0.660 and -0.637 respectively); (vi) a selection bias may have occurred as recruiting caregivers through their carereceiver’s healthcare professionals may have favoured the inclusion of caregivers with higher levels of psychological stress; (vii) we performed a 1:1 match between cases and controls, while epidemiological studies suggest to enrol more than one control for every case to obtain the best methodology (48); (viii) although we statistically controlled for certain potential confounders, other residual confounding factors may have influenced the results of the study. Among the strengths, (i) participants of both groups were in good general health at the moment of the evaluation, i.e. they were not included if they currently had a clinically unstable and disabling medical condition; (ii) the FI was developed according to a well established procedure (11), it showed adequate reliability (Cronbach’s α=0.76), and it comprehensively assessed information arising from biological, clinical, and functional evaluations (the participants were thus assessed multimodally); (iii) we used PSS and BRS, which are extensively used and validated assessment instruments for psychological stress and resilience, and showed satisfactory Cronbach’s α was in the current sample (0.85 and 0.89 respectively).
In conclusions, our findings provide pieces of insight on the complex relationships of frailty, conceptualized as a measure of deficit accumulation and an indicator of functional status and biological age, with caregiving, psychological stress and resilience, with potential implications for the psychological and medical management of individuals exposed to chronic emotional strain.

 

Conflicts of Interest: The authors do not have conflicts of interest to declare.

Ethical standards: Participants provided consent for allowing the utilization of the collected data for research purposes.

 

References

1. Clegg, A., et al., Frailty in elderly people. Lancet, 2013. 381(9868): p. 752-62.
2. World Health Organization, World report on ageing and health. 2015: World Health Organization.
3. Morley, J.E., et al., Frailty consensus: a call to action. J Am Med Dir Assoc, 2013. 14(6): p. 392-7.
4. Hoogendijk, E.O., et al., Frailty: implications for clinical practice and public health. Lancet, 2019. 394(10206): p. 1365-1375.
5. Mitnitski, A.B., A.J. Mogilner, and K. Rockwood, Accumulation of deficits as a proxy measure of aging. ScientificWorldJournal, 2001. 1: p. 323-36.
6. Cesari, M., B. Vellas, and G. Gambassi, The stress of aging. Exp Gerontol, 2013. 48(4): p. 451-6.
7. Rockwood, K. and S.E. Howlett, Age-related deficit accumulation and the diseases of ageing. Mech Ageing Dev, 2019. 180: p. 107-116.
8. Cesari, M., et al., The frailty phenotype and the frailty index: different instruments for different purposes. Age Ageing, 2014. 43(1): p. 10-2.
9. Bersani, F.S., et al., Frailty Index as a clinical measure of biological age in psychiatry. J Affect Disord, 2020. 268: p. 183-187.
10. Canevelli, M., et al., Promoting the Assessment of Frailty in the Clinical Approach to Cognitive Disorders. Front Aging Neurosci, 2017. 9: p. 36.
11. Searle, S.D., et al., A standard procedure for creating a frailty index. BMC Geriatr, 2008. 8: p. 24.
12. Epel, E.S., et al., More than a feeling: A unified view of stress measurement for population science. Front Neuroendocrinol, 2018. 49: p. 146-169.
13. Junius-Walker, U., et al., The essence of frailty: A systematic review and qualitative synthesis on frailty concepts and definitions. Eur J Intern Med, 2018. 56: p. 3-10.
14. Bersani, F.S., et al., Accelerated aging in serious mental disorders. Curr Opin Psychiatry, 2019. 32(5): p. 381-387.
15. Mathur, M.B., et al., Perceived stress and telomere length: A systematic review, meta-analysis, and methodologic considerations for advancing the field. Brain Behav Immun, 2016. 54: p. 158-169.
16. Puterman, E. and E. Epel, An intricate dance: Life experience, multisystem resiliency, and rate of telomere decline throughout the lifespan. Soc Personal Psychol Compass, 2012. 6(11): p. 807-825.
17. Harmell, A.L., et al., A review of the psychobiology of dementia caregiving: a focus on resilience factors. Curr Psychiatry Rep, 2011. 13(3): p. 219-24.
18. Faul, F., et al., Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods, 2009. 41(4): p. 1149-60.
19. American Psychiatric Association, Diagnostic and statistical manual of mental disorders (5th ed.). 2013: American Psychiatric Publishing.
20. Song, X., A. Mitnitski, and K. Rockwood, Prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation. J Am Geriatr Soc, 2010. 58(4): p. 681-7.
21. Hoogendijk, E.O., et al., Operationalization of a frailty index among older adults in the InCHIANTI study: predictive ability for all-cause and cardiovascular disease mortality. Aging Clin Exp Res, 2020. 32(6): p. 1025-1034.
22. Rockwood, K., M. Andrew, and A. Mitnitski, A comparison of two approaches to measuring frailty in elderly people. J Gerontol A Biol Sci Med Sci, 2007. 62(7): p. 738-43.
23. Cohen, S. and G. Williamson, Perceived stress in a probability sample of the United States, in The social psychology of health: Claremont Symposium on applied social psychology, S. Spacapan and S. Oskamp, Editors. 1988, Sage.
24. Mondo, M., C. Sechi, and C. Cabras, Psychometric evaluation of three versions of the Italian Perceived Stress Scale. Curr Psychol, 2019.
25. Laudadio, A., L. Mazzocchetti, and F.J. Fìz Perez, Gli stumenti disponibili in lingua italiana, in Valutare la resilienza: teorie, modelli e strumenti. 2011, Carocci Editore.
26. Smith, B.W., et al., The brief resilience scale: assessing the ability to bounce back. Int J Behav Med, 2008. 15(3): p. 194-200.
27. Smith, B.W., et al., The Foundations of Resilience: What Are the Critical Resources for Bouncing Back from Stress?, in Resilience in Children, Adolescents, and Adults, S. Prince-Embury and D.H. Saklofske, Editors. 2013, Springer.
28. Damjanovic, A.K., et al., Accelerated telomere erosion is associated with a declining immune function of caregivers of Alzheimer’s disease patients. J Immunol, 2007. 179(6): p. 4249-54.
29. Palacio, G.C., et al., Resilience in Caregivers: A Systematic Review. Am J Hosp Palliat Care, 2020. 37(8): p. 648-658.
30. Desrichard, O., et al., Frailty in aging and its influence on perceived stress exposure and stress-related symptoms: evidence from the Swiss Vivre/Leben/Vivere study. Eur J Ageing, 2018. 15(4): p. 331-338.
31. Bersani, F.S., et al., Association of dimensional psychological health measures with telomere length in male war veterans. J Affect Disord, 2016. 190: p. 537-542.
32. Epel, E.S., et al., Accelerated telomere shortening in response to life stress. Proc Natl Acad Sci U S A, 2004. 101(49): p. 17312-5.
33. Verner, G., et al., Maternal Psychological Resilience During Pregnancy and Newborn Telomere Length: A Prospective Study. Am J Psychiatry, 2021. 178(2): p. 183-192.
34. Benraad, C.E.M., et al., Frailty, multimorbidity and functional status as predictors for health outcomes of acute psychiatric hospitalisation in older adults. Aging Ment Health, 2018: p. 1-10.
35. Benraad, C.E.M., et al., Frailty as a Predictor of Mortality in Older Adults within 5 Years of Psychiatric Admission. Int J Geriatr Psychiatry, 2020.
36. Lohman, M., L. Dumenci, and B. Mezuk, Depression and Frailty in Late Life: Evidence for a Common Vulnerability. J Gerontol B Psychol Sci Soc Sci, 2016. 71(4): p. 630-40.
37. Aprahamian, I., et al., Frailty in geriatric psychiatry inpatients: a retrospective cohort study. Int Psychogeriatr, 2020: p. 1-9.
38. Gordon, E.H., et al., Sex differences in frailty: A systematic review and meta-analysis. Exp Gerontol, 2017. 89: p. 30-40.
39. Rockwood, K. and A. Mitnitski, Limits to deficit accumulation in elderly people. Mech Ageing Dev, 2006. 127(5): p. 494-6.
40. Whitson, H.E., et al., Physical Resilience: Not Simply the Opposite of Frailty. J Am Geriatr Soc, 2018. 66(8): p. 1459-1461.
41. Biondi, M., F.S. Bersani, and M. Pasquini, The Role of Integrated Interventions in Psychosomatic Diseases, in Person Centered Approach to Recovery in Medicine, L. Grassi, M.B. Riba, and T. Wise, Editors. 2019, Springer.
42. Araujo Carvalho, A.C., et al., Telomere length and frailty in older adults-A systematic review and meta-analysis. Ageing Res Rev, 2019. 54: p. 100914.
43. Kim, S., et al., The frailty index outperforms DNA methylation age and its derivatives as an indicator of biological age. Geroscience, 2017. 39(1): p. 83-92.
44. Breitling, L.P., et al., Frailty is associated with the epigenetic clock but not with telomere length in a German cohort. Clin Epigenetics, 2016. 8: p. 21.
45. Mitnitski, A., et al., Age-related frailty and its association with biological markers of ageing. BMC Med, 2015. 13: p. 161.
46. Franceschi, C., et al., Inflammaging: a new immune-metabolic viewpoint for age-related diseases. Nat Rev Endocrinol, 2018. 14(10): p. 576-590.
47. Demetriou, C., B.U. Ozer, and C.A. Essau, Self-Report Questionnaires, in The Encyclopedia of Clinical Psychology, R.L. Cautin and S.O. Lilienfeld, Editors. 2015, John Wiley & Sons.
48. Lewallen, S. and P. Courtright, Epidemiology in practice: case-control studies. Community Eye Health, 1998. 11(28): p. 57-8.

OSTEOPOROSIS IN FRAIL OLDER ADULTS: RECOMMENDATIONS FOR RESEARCH FROM THE ICFSR TASK FORCE 2020

 

Y. Rolland1, M. Cesari2, R.A. Fielding3, J.Y. Reginster4,5, B. Vellas7, A.J. Cruz-Jentoft6 and the ICFSR Task Force

 

1. Service de Médecine Interne et Gérontologie Clinique, Gérontopôle, CHU Toulouse, INSERM 1027, France; 2. IRCCS Istituti Clinici Scientifici Maugeri, University of Milan, Milan, Italy; 3. Tufts University, Boston, MA, USA; 4. Division of Epidemiology, Public Health and Health Economics, University of Liege, Liege, Belgium; 5. Chair for Biomarkers of Chronic Diseases, Biochemistry Department, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia; 6. Servicio de Geriatría, Hospital Universitario Ramón y Cajal (IRYCIS), Madrid, Spain; 7. Gerontopole, INSERM U1027, Alzheimer’s Disease Research and Clinical Center, Toulouse University Hospital, Toulouse, France
Corresponding author: Yves Rolland, Service de Médecine Interne et Gérontologie Clinique, Gérontopôle, CHU Toulouse, INSERM 1027, France, rolland.y@chu-toulouse.fr

 

Task Force members: Samuel Agus (Paris); Sandrine Andrieu (Toulouse, France); Mylène Aubertin-Leheudre (Montréal, Canada); Amos Baruch (South San Francisco, USA); Shalender Bhasin (Boston, USA); Louis Casteilla (Toulouse, France); Peggy Cawthon (San Francisco, USA) ; Manu Chakravarthy (Cambridge, USA); Rafael De Cabo (Baltimore, USA); Carla Delannoy (Vevey, Switzerland); Philipe De Souto Barreto (Toulouse, France) ; Waly Dioh (Paris, France); Luigi Ferrucci (Baltimore, USA); Françoise Forette (Paris, USA); Sophie Guyonnet (Toulouse); Joshua Hare (Miami) ; Darren Hwee (South San Francisco); Kala Kaspar (Vevey); Nathan LeBrasseur (Rochester, USA); Valérie Legrand (Nanterre, France); Roland Liblau (Toulouse, France); Yvette Luiking (Utrecht, The Netherland) ; Bradley Morgan (South San Francisco, USA) ; Eric Morgen (Richmond, USA); John Morley (St Louis, USA) ; Angelo Parini (Toulouse, USA); Suzette Pereira (Columbus, USA); Alfredo Ramirez (Cologne, USA); Leocadio Rodriguez Manas (Getafe (Madrid), Spain); Ricardo Rueda (Columbus, USA); Jorge Ruiz (Miami, USA); Peter Schüler (Langen, Germany); Alan Sinclair (London, United Kingdom); Nicolas Thevenet (Nanterre, France); Janneke Van Wijngaarden (Utrecht, The Netherlands); Bruno Vellas (Toulouse, France) ; José Viña (Valencia, Spain); Jeremy Walston (Baltimore, USA); Debra Waters (Dunedin, New Zealand)

J Frailty Aging 2021;in press
Published online February 7, 2021, http://dx.doi.org/10.14283/jfa.2021.4


 

Abstract

Interactions among physiological pathways associated with osteoporosis and sarcopenia are thought to contribute to the onset of frailty. The International Conference on Frailty and Sarcopenia Research Task Force thus met in March 2020 to explore how emerging interventions to manage fracture and osteoporosis in older adults may reduce frailty, disability, morbidity, and mortality in the older population. Both pharmacological and non-pharmacological interventions (including nutritional intervention, exercise, and other lifestyle changes) were discussed, including nutritional intervention, exercise, and other lifestyle changes. Pharmacological treatments for osteoporosis include bone-forming and antiresorptive agents, which may optimally be used in sequential or combination regimens. Since similar mechanisms related to resorption underlie physiological changes in muscle and bone, these interventions may provide benefits beyond treating osteoporosis. Clinical trials to test these interventions, however, often exclude frail older persons because of comorbidities (such as mobility disability and cognitive impairment) or polypharmacy. The Task Force recommended that future clinical trials use harmonized protocols, including harmonized inclusion criteria and similar outcome measures; and that they test a range of multidomain therapies. They further advocated more high-quality research to develop interventions specifically for people who are frail and old. The ICOPE program recommended by WHO appears to be highly recommended to frail older adults with osteoporosis.

Key words: Frailty, osteoporosis, prevention, ICOPE.


 

Introduction

All organisms show biologically driven declines in motor function as they age and these declines are closely linked to mortality (1, 2). In humans, these declines manifest as the frailty syndrome, which is defined by the overlapping characteristics of low physical activity, slowed motor performance, weakness, fatigue or exercise intolerance, and unintentional weight loss (3). Physiologically, frailty reflects a lowered resistance to stressors resulting from multi-systemic decline. Clinically, frailty is associated with diagnoses of sarcopenia, the age-related loss of muscle mass and strength, and osteoporosis, the loss of bone mass and the deterioration of bone tissue (4). When they occur together, the syndrome may be referred to as “osteosarcopenia” (5). Moreover, interactions between bone and muscle through multiple physiological pathways, including hormonal and inflammatory pathways, are thought to result in the frailty syndrome (6).
As it has done every year since 2014, the International Conference of Frailty and Sarcopenia Research (ICFSR) Task Force brought together researchers from academia and industry to discuss challenges and opportunities for managing frailty and sarcopenia. In 2020 the Task Force met in Toulouse, France, where it focused attention on emerging interventions to manage fracture and osteoporosis in frail older adults. This population group has often been excluded from recent osteoporosis drug trials due to comorbidities and polypharmacy, despite the fact that they may potentially benefit more from a treatment since they are more likely to have falls, fractures, disability and a poor prognosis.

 

Associations of frailty with osteoporosis, fragility fracture, and malnutrition

Bone fragility caused by osteoporosis occurs commonly in older adults and results in increased risk of fragility fracture (7). A systematic review of worldwide studies estimated that 9 million osteoporotic fractures occurred in 2000, resulting in substantial disability, morbidity, and mortality (8). However, osteoporosis may not be diagnosed until an individual has experienced multiple fragility fractures; and studies show that after diagnosis, treatment for osteoporosis is not routinely given in older adults and adherence to medical regimens is poor (9).
One of the most common and disabling fractures sustained by older persons is hip fracture, which may result in long-term mobility impairment, reduced ability to care for oneself or participate in everyday activities, pain, anxiety, and depression (10). Nutrition plays an important role in bone health and sarcopenia (11, 12), and malnutrition is common in individuals with hip fracture (13). Sarcopenia is also associated with an increased rate fractures in older adults (14, 15).
Most patients with hip fracture complain of pain and resulting functional limitations six months after the fracture (16), which can lead to a vicious cycle of self-medication and mistrust of clinicians (17). Recovery from hip fracture may be delayed in the presence of sarcopenia (18), and hip fracture may be particularly disabling in individuals with frailty (19). Nearly 30 years ago, Marottoli and colleagues showed that physical function before the fracture predicts functional recovery (20). Comorbidities, fear of falling, and other age-related conditions may further exacerbate hip fracture and its associated functional consequences (21, 22). Moreover, individuals over age 80 years, in addition to meeting the frailty phenotype proposed by Fried and colleagues (i.e., weight loss, fatigue, slow gait speed, weakness, sedentary lifestyle), often live alone, and often experience cognitive decline (23); thus they need special management for frailty. However, frail older persons are often excluded from clinical trials of fragility fracture interventions, in part because of comorbidities, sarcopenia, cognitive impairment, and polypharmacy (24).
The substantial impact of fragility fractures on functioning in frail older persons thus requires dedicated and multidisciplinary care pathways, which have been shown to improve quality of life and physical function and limit excessive costs (25,26). Intensive interventions including exercise and physical therapy immediately following hip fracture is essential. Preventive strategies also need to be widely implemented, including early identification of those at risk, increased prescribing of bone loss prevention treatments, and the introduction of care models based on the comprehensive geriatric assessment and personalization of interventions. Recently multidisciplinary, evidence-based guidelines for the management of osteoporosis and fragility fractures have been published (27–29).
Given the association of poor nutrition with sarcopenia and frailty (30, 31), assessment of the nutritional status of older adults provides a potential pathway to interventions that could delay or prevent these disabling conditions of aging (32). The Mini Nutritional Assessment (MNA) is a tool designed to rapidly assess nutritional status though a series of simple measurements and brief questions (33). The MNA has been validated in frail older persons (34) and in community-dwelling older adults, demonstrating that frailty and malnutrition are distinct but related conditions (35–37).
Using the MNA short form (MNA-SF), investigators showed that poor nutrition in combination with frailty was associated with an increased prevalence and incidence of poor functional outcomes in the Singapore Longitudinal Aging Study (32). In cancer patients, a low MNA score combined with a high Groningen Frailty Index (GFI) score was associated with an increased mortality risk (38). MNA score has also been used as a prognostic factor of adverse outcomes after hip fracture (39). Yet while there is mounting evidence about the importance of stratifying research populations for frailty, impaired nutritional status at baseline has been associated with greater benefits from the interventions (40, 41). The new ESPEN guidelines on the treatment of malnutrition in older people include a section on hip fracture, with the recommendation to incorporate nutrition intervention into a multidisciplinary approach (42).
As a screening tool in outpatients, the MNA-SF has been shown to have a sensitivity of 71.2% and specificity of 92.8% (AUC 0.906) for the detection of frailty, and a 45.7% sensitivity and 78.3% specificity (AUC 0.687) for the detection of pre-frailty (43). In hospitalized patients, the MNA-SF predicted frailty with good sensitivity but only marginal specificity (44). There is no evidence that the MNA can be used as an outcome measure in trials.

 

Pharmacological treatment for osteoporosis, sarcopenia, and frailty

Better targeting of therapeutic interventions for the management of osteoporosis starts with diagnosis, identification of risk factors, and an assessment of fracture risk (45). The International Osteoporosis Foundation and European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis published guidance for the diagnosis and management of osteoporosis in 2013, and recently updated such guidance (46). Diagnostic criteria for sarcopenia have also been recommended by other different groups. The European Working Group on Sarcopenia in Older People (EWGSOP) published a definition in 2010 and updated it in 2019 based on a better understanding of the condition (47,48); and the ICFSR published guidelines on the management of sarcopenia in 2018 (49). In 2017, sarcopenia also was assigned a diagnostic code in the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code book, indicating recognition of sarcopenia as a separately reportable disease condition for clinical practice and drug development (50).
A fracture may trigger a downward spiral of recurrent fractures known as the “fracture cascade” (51). A study in Iceland showed that the first fracture dramatically increases the risk of a subsequent fractures, particularly during the first year following the first event and regardless of the site of it. The authors concluded that treatment should be started immediately to prevent recurrence of the problem (52). Bone fragility, determined by assessing bone mineral density (BMD) at the hip or spine by DXA scan, is associated with high fracture risk (53), suggesting that restoring bone density may significantly reduce the risk of a second fracture. Low muscle strength and low physical function (sarcopenia) also increase the risk of injurious falls and fractures after a first hip fracture (54).
Several bone-forming drugs are clinically available, including anti-resorptive agents such as denosumab (55–57); romosozumab, a monoclonal antibody that both increases bone formation and inhibits bone resorption (58,59); anabolic agents such as teriparatide (60) and abaloparatide (61–63); biphosphonates such as alendronate and zoledronic acid (64); and myostatin inhibitors, which are also under research as potential drugs to treat sarcopenia (65, 66).
Optimal treatment of osteoporosis may require sequential or combination therapies, for example starting with a bone forming agent then add an antiresorptive agent for maintenance. For example, in the phase 2 FRActure study in postmenopausal woMen with ostEoporosis (FRAME), romosuzumab followed by denosumab reduced the risk of fracture in postmenopausal women (67). Other sequential regimens that have shown promise in lowering fracture risk and/or increasing bone density include romosozumab followed by alendronate (68), abaloparatide followed by alendronate (69,70), and combination denosumab/teriparatide followed by denosumab alone (71).

 

Preventing frailty and its consequences through nutrition and exercise

The concept of frailty facilitates a better understanding of heterogeneity in the older population and promotes study of the aging process. It provides a possible target for preventive measures aimed at reducing the functional decline and the occurrence of negative events such as falls and fractures (72, 73). Frail patients present with weakness, fatigue, a sedentary lifestyle and mobility impairment. They may have anorexia and recent weight loss. All of these clinical signs increase the risk of falls and fractures. They are also accessible to interventions such as nutritional management and/or physical exercise (focused on strength training and balance), which reduce the risk of falling (74, 75).
Several mechanisms responsible for both growth and decline of muscles and bones are shared. It has been hypothesized that pharmacological, nutritional, and/or exercise-based interventions may also overlap and provide mutual/dual benefits (76). For example, both skeletal muscle and bone respond to treatment with androgens, and exercise is an essential element of treatment regimens for osteoporosis, sarcopenia, and frailty. Malnutrition plays an important role in the development of both sarcopenia and frailty (31). Decreased dietary protein intake has been shown to result in decreased lean muscle mass in the Health Aging and Body Composition (ABC) Study (77). The Vitality, Independence and Vigor Study (VIVE2) showed that a high protein, high vitamin D nutritional supplement added to a physical activity intervention led to improvements in muscle density and a loss of intermuscular fat in mobility-limited older adults (78), although these benefits seemed insufficient to improve functional measures such as gait speed (79). Other studies have shown that a combination of resistance exercise and increased protein intake prevented muscle wasting in older adults (80, 81).
Obesity is known to contribute to functional declines and frailty in older adults. Sarcopenia in combination with obesity – a condition known as sarcopenic obesity – increases the risk of functional decline through multiple synergistic pathways. Intervention strategies to combat sarcopenic obesity include weight reduction, calorie restriction, and exercise. Pharmacological strategies may also prove useful (82). Weight reduction through calorie restriction has been shown to have positive effects on longevity, yet it also may result in a loss of fat and lean mass and bone density (83,84). In a study of older frail obese adults, an intervention that combined weight loss and aerobic plus resistance exercise, Villareal and colleagues showed that in comparison to either approach alone, the combination resulted in greater physical function and aerobic capacity and attenuated the loss of bone mineral density (85, 86).
The mechanisms by which dietary changes and exercise influence muscle and bone provide clues that may help design better and more targeted intervention strategies. For example, evidence implicates age-related declines in muscle insulin-like growth factor 1 (IGF-1) in sarcopenia; and both exercise and injury increase IGF-1, IGF-1 receptors, and IGF-1 activated signaling pathways. Aging muscle may have less ability to synthesize IGF-1 or may be resistant to IGF-1, and aging may also be associated with attenuation of the ability of exercise to induce IGF-1 (87).
A small study of healthy older women fed with a low-protein diet for 10 weeks showed a decline in both muscle mass and IGF-1 (88). More than 20 years ago, Rizzoli and colleagues showed that protein supplementation in frail individuals post hip fracture restored levels of IGF-1 in the plasma and attenuated loss in bone mineral density compared to placebo (89). Supplementation with selenium and coenzyme Q10 have also been shown to increase levels of IGF-1 in older adults (90).
Skeletal muscle cells express the vitamin D receptor (VDR), and low levels of vitamin D have been associated with lower muscle strength, mobility impairments, and disability (91). In mobility-impaired older women, vitamin D supplementation increased VDR expression and improved skeletal muscle fiber size (92). However, another study in older adults with low baseline levels of serum 25(OH)D showed that while supplementation increased serum levels to more normal levels, there was no effect on lean mass, lower-extremity power, or strength (93).
Nutritional supplements that target inflammation have also been proposed as a strategy for improving muscle function in older adults. For example, omega-3 fatty acids derived from fish oil have also been shown to slow decline in muscle mass and function in older adults (94). However, a recent clinical trial, the ENabling Reduction of low-Grade Inflammation in SEniors (ENRGISE) Pilot study, which tested the efficacy of fish oil and the angiotensin receptor blocker losartan in older, mobility-impaired adults, showed no improvement of walking speed or serum level of the inflammatory marker IL-6 (95).
Demonstrating the efficacy of nutritional interventions is challenging for many reasons, including the difficulty of determining whether the baseline level of dietary intake is inadequate and capturing subtle effects of change from baseline. These challenges are exacerbated when nutritional interventions are superimposed on other interventions.

 

Designing clinical trials to target bone fracture in frail older adults

The burden of fracture is expected to increase worldwide as the population ages, yet few trials have assessed the benefit of treatments in the oldest old and even less in the frail population (96, 97). Thus, fracture prevention and optimizing bone health represent important public health goals. Interventions that target the frail population offer the potential for the greatest benefit, as was demonstrated in a study by Rolland and colleagues, which tested the ability of strontium ranelate to reduce vertebral fractures in osteoporotic women, independently of frailty status (98). Beyond pharmacological interventions, nutrition and exercise have been shown to act synergistically to improve bone and muscle health and thus should be incorporated into randomized clinical trials (99).
To increase the efficiency and maximizing learnings from clinical studies, sponsors and researchers should use harmonized protocols with similar outcome measures. The ICFSR Task Force suggested the following:

Possible Study Design

The placebo-controlled, parallel-arm, double-blind trial is the gold standard for assessing efficacy and effectiveness. Other elements of an optimal trial design include:
• A long run-in phase before initiating treatment, during which activity diaries could be monitored and dietary inadequacies or anemia corrected to ensure a stable baseline.
• 2 x 2 designs for studies testing multimodal approaches such as resistance exercise and/or combination of resistance and aerobic exercise and nutrition.
• Using assessment time points that have been harmonized with other studies to enable data pooling and meta-analyses of data.
• Use the gold standard of collecting falls incidence using monthly calendars.
• At least one-year of follow up. If studies aim to target bone fracture or prevent the progression from pre-sarcopenia to sarcopenia, long follow-up will be necessary.

Proposed Outcomes

• Primary outcome: fragility fractures at 24 months (hip and spine).
• Secondary outcomes:
o Physical performance and disability as measures of functional decline
o Injurious falls
o Patient-reported outcomes, including mobility assessments and quality of life
o Nursing home admissions
o Bone turnover biomarkers
o BMD assessment (hip and spine)
• Exploratory outcomes
o Cognitive function
o Comorbidities
o Survival

Note that Fragility fractures or injurious falls as the primary outcome will require a very large sample size. Benefit of pharmacological treatment has also needed a large sample size.

Potential Target Population

• Patients with low BMD, high rate of falls (such as ≥2 self-reported falls/year), and frailty.
• Inclusion criteria: ≥ 75 years old with osteoporosis defined by low BMD, FRAX, and/or history of osteoporotic fracture, and with frailty defined by variable proven predictive of falls (100). Patients in nursing homes and those with dementia should be included where possible.
• Exclusions: Projected life expectancy < 2 years or estimated glomerular filtration rate < 30 mL/min/1.73 m2, individuals who are bedridden or who have contraindications related to the drug being tested

Design of Interventions

Frailty is a complex syndrome requiring multidimensional interventions. Interventions should target two or more risk factors for falls. For example, polypharmacy and some specific medications have been associated with increase fracture risk (101, 102). The European Geriatric Medicine Society (EuGMS) Task and Finish group on Fall-Risk-Increasing Drugs (FRIDs) recently proposed practical recommendation and strategies to reduce the use of FRIDs (103). The increase risk of falls related to the use of psychotropics drugs (104), cardiovascular drugs (105) and other medications (106) is now well-known. As the field of geroscience continues to emerge, it may become possible to target aging itself (107). For example, cellular senescence represents a promising therapeutic paradigm for potentially preventing or even reversing age-related osteoporosis and simultaneously treating multiple aging comorbidities (108).
Multidomain interventions for preventing falls in older people living in the community typically include physical activity (strength and balance classes with walking practice), and deprescribing. A systematic review and meta-analysis concluded that such multidomain interventions may reduce the rate of falls and recurrent falls, although the impact on fracture reduction has not been clearly demonstrated (109).
To test an osteoporosis drug in combination with a multidomain intervention, four parallel groups are recommended: 1) osteoporosis drug alone, 2) multidomain intervention alone, 3) osteoporosis drug plus multidomain intervention, 4) placebo or active comparator.
The Multidomain Alzheimer’s Prevention Trial (MAPT) study is an example of a multidomain trial in frail older adults (110). This three-year, multicenter, randomized, placebo-controlled superiority trial enrolled community-dwelling persons aged 70 or older with spontaneous memory complaints, absence of dementia, and limitations in one instrumental activity of daily living or slow gait speed. They were randomly assigned to one of four groups: 1) a multidomain intervention comprising cognitive training, physical activity, and nutritional counseling plus omega-3 polyunsaturated fatty acids with a total daily dose of 800 mg docosahexaenoic acid and 225 mg eicosapentaenoic acid, 2) the multidomain intervention plus placebo, 3)omega-3 polyunsaturated fatty acids alone, or 4) placebo alone. The trial was registered with ClinicalTrials. gov (NCT00672685).

 

Conclusions and next steps

The ICFSR Task Force reached several conclusions. First, it recognized that the traditional care system is inadequate for dealing with complex health disorders of aging such as frailty, where multidisciplinarity is required (111, 112). Cognitive impairment is often associated with frailty and must be taken into consideration (113, 114). The links between frailty and cognition are now well described (115–117) and integrated care like the ICOPE program have to be promoted to prevent and treat fractures in frail older persons (118–121).
Second, the Task Force suggested that reducing fracture risk among older adults requires first intervening with a powerful agent to restore the strength of bone, and then switching to an anti-resorptive agent to maintain bone health. The need for treatment is especially true after a first major hip fracture. The high cost of many of these drugs imposes a barrier to such an approach and payers will require studies that document efficacy; yet fractures themselves are costly and health economics studies show that bone forming agents are cost-effective even over short time periods. Combination therapies were also recommended, not just for treating the bone but for other factors as well, particularly in individuals who are frail. Benefits of these drugs in frail populations with high risk of fracture, short life expectancy, and high risk of adverse events such as nursing home residents should be investigated. One problem is that these frail older adults often take many drugs due to co-morbidities, including cognitive impairment, undernutrition, depression, and loneliness, raising questions about the value of further adding drugs to treat osteoporosis versus decreasing drug consumption in frail older adults. Advances in the field of geroscience may help in the future to answer these questions by introducing new biomarkers and better targeted therapies (122–124).
Third, the Task Force noted that while pathophysiology of bone fracture is the same in frail and non-frail adults, the mechanisms that lead to bone fracture – poor balance, sarcopenia, poor physical performance, sedentary lifestyle, and poor nutritional status – differ. Given these differences, specific recommendations may be needed for interventions in people who are frail, for example by more routinely adopting multidimensional and comprehensive interventions (125). To develop these interventions, more studies are needed in people who are frail and old. In addition, high-quality research is needed to confirm the role of nutrition in reversing or preventing frailty and adverse outcomes in frail persons (126, 127). Moreover the ICOPE program developed by WHO appears to be most useful for the frail older adults with osteoporosis to maintain Intrinsic capacities, monitor functions with ICOPE MONITOR (119) and prevent further disabilities (Table 1).

Table 1
Screening Tool for the “Integrated Care for Older Persons” (ICOPE)

 

Acknowledgements: The authors thank Lisa J. Bain for assistance in the preparation of this manuscript.
Conflicts of interest: ACJ reports grants or personal fees from Fresenius Kabi, Abbott Nutrition, Nestlé, Nutricia, Sanofi, and Pfizer, all unrelated to the submitted article. MC is member of Advisory Board for Nestlé.
Ethical Standards: None
Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

References

1. Dickinson MH, Farley CT, Full RJ, Koehl MA, Kram R, Lehman S. How animals move: an integrative view. Science. 2000 Apr 7;288(5463):100–6.
2. Studenski S, Perera S, Patel K, Rosano C, Faulkner K, Inzitari M, et al. Gait speed and survival in older adults. JAMA. 2011 Jan 5;305(1):50–8.
3. Fried LP, Xue Q-L, Cappola AR, Ferrucci L, Chaves P, Varadhan R, et al. Nonlinear multisystem physiological dysregulation associated with frailty in older women: implications for etiology and treatment. J Gerontol A Biol Sci Med Sci. 2009 Oct;64(10):1049–57.
4. Frisoli A, Chaves PH, Ingham SJM, Fried LP. Severe osteopenia and osteoporosis, sarcopenia, and frailty status in community-dwelling older women: results from the Women’s Health and Aging Study (WHAS) II. Bone. 2011 Apr 1;48(4):952–7.
5. Kirk B, Al Saedi A, Duque G. Osteosarcopenia: A case of geroscience. Aging Med (Milton). 2019 Sep;2(3):147–56.
6. Greco EA, Pietschmann P, Migliaccio S. Osteoporosis and Sarcopenia Increase Frailty Syndrome in the Elderly. Front Endocrinol (Lausanne). 2019;10:255.
7. Li G, Thabane L, Papaioannou A, Ioannidis G, Levine MAH, Adachi JD. An overview of osteoporosis and frailty in the elderly. BMC Musculoskelet Disord [Internet]. 2017 Jan 26 [cited 2020 Apr 24];18. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5270357/
8. Johnell O, Kanis JA. An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int. 2006 Dec;17(12):1726–33.
9. Hiligsmann M, Cornelissen D, Vrijens B, Abrahamsen B, Al-Daghri N, Biver E, et al. Determinants, consequences and potential solutions to poor adherence to anti-osteoporosis treatment: results of an expert group meeting organized by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) and the International Osteoporosis Foundation (IOF). Osteoporos Int. 2019 Nov;30(11):2155–65.
10. Magaziner J, Hawkes W, Hebel JR, Zimmerman SI, Fox KM, Dolan M, et al. Recovery from hip fracture in eight areas of function. J Gerontol A Biol Sci Med Sci. 2000 Sep;55(9):M498-507.
11. Cashman KD. Diet, Nutrition, and Bone Health. J Nutr. 2007 Nov 1;137(11):2507S-2512S.
12. Beaudart C, Sanchez-Rodriguez D, Locquet M, Reginster J-Y, Lengelé L, Bruyère O. Malnutrition as a Strong Predictor of the Onset of Sarcopenia. Nutrients [Internet]. 2019 Nov 27 [cited 2020 Apr 28];11(12). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6950107/
13. Díaz de Bustamante M, Alarcón T, Menéndez-Colino R, Ramírez-Martín R, Otero Á, González-Montalvo JI. Prevalence of malnutrition in a cohort of 509 patients with acute hip fracture: the importance of a comprehensive assessment. European Journal of Clinical Nutrition. 2018 Jan;72(1):77–81.
14. Yeung SSY, Reijnierse EM, Pham VK, Trappenburg MC, Lim WK, Meskers CGM, et al. Sarcopenia and its association with falls and fractures in older adults: A systematic review and meta-analysis. J Cachexia Sarcopenia Muscle. 2019;10(3):485–500.
15. Kirk B, Phu S, Brennan-Olsen SL, Bani Hassan E, Duque G. Associations between osteoporosis, the severity of sarcopenia and fragility fractures in community-dwelling older adults. Eur Geriatr Med. 2020 Jun;11(3):443–50.
16. Sale JEM, Frankel L, Thielke S, Funnell L. Pain and fracture-related limitations persist 6 months after a fragility fracture. Rheumatol Int. 2017 Aug;37(8):1317–22.
17. Gheorghita A, Webster F, Thielke S, Sale JEM. Long-term experiences of pain after a fragility fracture. Osteoporos Int. 2018 May 1;29(5):1093–104.
18. Landi F, Calvani R, Ortolani E, Salini S, Martone AM, Santoro L, et al. The association between sarcopenia and functional outcomes among older patients with hip fracture undergoing in-hospital rehabilitation. Osteoporos Int. 2017;28(5):1569–76.
19. Kua J, Ramason R, Rajamoney G, Chong MS. Which frailty measure is a good predictor of early post-operative complications in elderly hip fracture patients? Arch Orthop Trauma Surg. 2016 May;136(5):639–47.
20. Marottoli RA, Berkman LF, Cooney LM. Decline in physical function following hip fracture. J Am Geriatr Soc. 1992 Sep;40(9):861–6.
21. Kerr C, Bottomley C, Shingler S, Giangregorio L, de Freitas HM, Patel C, et al. The importance of physical function to people with osteoporosis. Osteoporos Int. 2017;28(5):1597–607.
22. Ong T, Yong BKA, Shouter T, Shahrokhi N, Sahota O. Optimising bone health among older people with hip fractures and co-existing advanced chronic kidney disease. Eur Geriatr Med. 2020 Jun 1;
23. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-156.
24. European Medicines Agency. Reflection paper on physical frailty: Instruments for baseline characterisation of older populations in clinical trials [Internet]. 2015. Report No.: EMA/CHMP/778709/2015. Available from: https://www.ema.europa.eu/en/documents/scientific-guideline/reflection-paper-physical-frailty-instruments-baseline-characterisation-older-populations-clinical_en.pdf
25. Talevski J, Sanders KM, Duque G, Connaughton C, Beauchamp A, Green D, et al. Effect of Clinical Care Pathways on Quality of Life and Physical Function After Fragility Fracture: A Meta-analysis. J Am Med Dir Assoc. 2019 Jul;20(7):926.e1-926.e11.
26. Hawley S, Javaid MK, Prieto-Alhambra D, Lippett J, Sheard S, Arden NK, et al. Clinical effectiveness of orthogeriatric and fracture liaison service models of care for hip fracture patients: population-based longitudinal study. Age Ageing. 2016 Mar;45(2):236–42.
27. Nuti R, Brandi ML, Checchia G, Di Munno O, Dominguez L, Falaschi P, et al. Guidelines for the management of osteoporosis and fragility fractures. Intern Emerg Med. 2019 Jan;14(1):85–102.
28. Lems WF, Dreinhöfer KE, Bischoff-Ferrari H, Blauth M, Czerwinski E, da Silva J, et al. EULAR/EFORT recommendations for management of patients older than 50 years with a fragility fracture and prevention of subsequent fractures. Ann Rheum Dis. 2017 May;76(5):802–10.
29. Compston J, Cooper A, Cooper C, Gittoes N, Gregson C, Harvey N, et al. UK clinical guideline for the prevention and treatment of osteoporosis. Arch Osteoporos. 2017 Dec;12(1):43.
30. Landi F, Sieber C, Fielding RA, Rolland Y, Guralnik J, the ICFSR Task Force A. Nutritional intervention in sarcopenia: report from the international conference on frailty and sarcopenia research task force. Journal of Frailty & Aging. 2018 Dec 1;J Frailty Aging 20187(4):247–52.
31. Cruz-Jentoft AJ, Kiesswetter E, Drey M, Sieber CC. Nutrition, frailty, and sarcopenia. Aging Clin Exp Res. 2017 Feb;29(1):43–8.
32. Wei K, Thein FS, Nyunt MSZ, Gao Q, Wee SL, Ng TP. Nutritional and Frailty State Transitions in the Singapore Longitudinal Aging Study. J Nutr Health Aging. 2018;22(10):1221–7.
33. Vellas B, Guigoz Y, Garry PJ, Nourhashemi F, Bennahum D, Lauque S, et al. The mini nutritional assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition. 1999 Feb 1;15(2):116–22.
34. Lilamand M, Kelaiditi E, Cesari M, Raynaud-Simon A, Ghisolfi A, Guyonnet S, et al. Validation of the Mini Nutritional Assessment-Short Form in a Population of Frail Elders without Disability. Analysis of the Toulouse Frailty Platform Population in 2013. J Nutr Health Aging. 2015 May;19(5):570–4.
35. Lorenzo-López L, Maseda A, de Labra C, Regueiro-Folgueira L, Rodríguez-Villamil JL, Millán-Calenti JC. Nutritional determinants of frailty in older adults: A systematic review. BMC Geriatr. 2017 15;17(1):108.
36. Wei K, Nyunt MSZ, Gao Q, Wee SL, Ng T-P. Frailty and Malnutrition: Related and Distinct Syndrome Prevalence and Association among Community-Dwelling Older Adults: Singapore Longitudinal Ageing Studies. J Am Med Dir Assoc. 2017 Dec 1;18(12):1019–28.
37. Verlaan S, Ligthart-Melis GC, Wijers SLJ, Cederholm T, Maier AB, de van der Schueren MAE. High Prevalence of Physical Frailty Among Community-Dwelling Malnourished Older Adults-A Systematic Review and Meta-Analysis. J Am Med Dir Assoc. 2017 May 1;18(5):374–82.
38. Aaldriks AA, Maartense E, le Cessie S, Giltay EJ, Verlaan H a. CM, van der Geest LGM, et al. Predictive value of geriatric assessment for patients older than 70 years, treated with chemotherapy. Crit Rev Oncol Hematol. 2011 Aug;79(2):205–12.
39. Malafarina V, Reginster J-Y, Cabrerizo S, Bruyère O, Kanis JA, Martinez JA, et al. Nutritional Status and Nutritional Treatment Are Related to Outcomes and Mortality in Older Adults with Hip Fracture. Nutrients. 2018 Apr 30;10(5).
40. Kim CO. Predicting the Efficacy of Protein-Energy Supplementation in Frail Older Adults Living in Community. J Frailty Aging. 2014;3(2):126–31.
41. Luger E, Dorner TE, Haider S, Kapan A, Lackinger C, Schindler K. Effects of a Home-Based and Volunteer-Administered Physical Training, Nutritional, and Social Support Program on Malnutrition and Frailty in Older Persons: A Randomized Controlled Trial. J Am Med Dir Assoc. 2016 01;17(7):671.e9-671.e16.
42. Volkert D, Beck AM, Cederholm T, Cruz-Jentoft A, Goisser S, Hooper L, et al. ESPEN guideline on clinical nutrition and hydration in geriatrics. Clin Nutr. 2019;38(1):10–47.
43. Soysal P, Veronese N, Arik F, Kalan U, Smith L, Isik AT. Mini Nutritional Assessment Scale-Short Form can be useful for frailty screening in older adults. Clin Interv Aging. 2019;14:693–9.
44. Dent E, Visvanathan R, Piantadosi C, Chapman I. Use of the Mini Nutritional Assessment to detect frailty in hospitalised older people. J Nutr Health Aging. 2012;16(9):764–7.
45. Kanis JA, Harvey NC, McCloskey E, Bruyère O, Veronese N, Lorentzon M, et al. Algorithm for the management of patients at low, high and very high risk of osteoporotic fractures. Osteoporos Int. 2020 Jan;31(1):1–12.
46. Kanis JA, Cooper C, Rizzoli R, Reginster J-Y, Scientific Advisory Board of the European Society for Clinical and Economic Aspects of Osteoporosis (ESCEO) and the Committees of Scientific Advisors and National Societies of the International Osteoporosis Foundation (IOF). European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int. 2019 Jan;30(1):3–44.
47. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010 Jul;39(4):412–23.
48. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019 Jul;48(4):601.
49. Dent E, Morley JE, Cruz-Jentoft AJ, Arai H, Kritchevsky SB, Guralnik J, et al. International Clinical Practice Guidelines for Sarcopenia (ICFSR): Screening, Diagnosis and Management. J Nutr Health Aging. 2018;22(10):1148–61.
50. Vellas B, Fielding RA, Bens C, Bernabei R, Cawthon PM, Cederholm T, et al. Implications of icd-10 for sarcopenia clinical practice and clinical trials: report by the international conference on frailty and sarcopenia research task force. Journal of Frailty & Aging. 2018 Mar 1;J Frailty Aging 20187(1):2–9.
51. Broy SB. The Vertebral Fracture Cascade: Etiology and Clinical Implications. Journal of Clinical Densitometry. 2016 Jan 1;19(1):29–34.
52. Kanis JA, Johansson H, Odén A, Harvey NC, Gudnason V, Sanders KM, et al. Characteristics of recurrent fractures. Osteoporos Int. 2018 Aug;29(8):1747–57.
53. Kopperdahl DL, Aspelund T, Hoffmann PF, Sigurdsson S, Siggeirsdottir K, Harris TB, et al. Assessment of incident spine and hip fractures in women and men using finite element analysis of CT scans. J Bone Miner Res. 2014 Mar;29(3):570–80.
54. Lloyd BD, Williamson DA, Singh NA, Hansen RD, Diamond TH, Finnegan TP, et al. Recurrent and injurious falls in the year following hip fracture: a prospective study of incidence and risk factors from the Sarcopenia and Hip Fracture study. J Gerontol A Biol Sci Med Sci. 2009 May;64(5):599–609.
55. Dempster DW, Chines A, Bostrom MP, Nieves JW, Zhou H, Chen L, et al. Modeling-Based Bone Formation in the Human Femoral Neck in Subjects Treated With Denosumab. J Bone Miner Res. 2020 Mar 12;
56. Ferrari S, Libanati C, Lin CJF, Brown JP, Cosman F, Czerwiński E, et al. Relationship Between Bone Mineral Density T-Score and Nonvertebral Fracture Risk Over 10 Years of Denosumab Treatment. J Bone Miner Res. 2019 Jun;34(6):1033–40.
58. McClung MR, Grauer A, Boonen S, Bolognese MA, Brown JP, Diez-Perez A, et al. Romosozumab in postmenopausal women with low bone mineral density. N Engl J Med. 2014 Jan 30;370(5):412–20.
59. Cosman F, Crittenden DB, Adachi JD, Binkley N, Czerwinski E, Ferrari S, et al. Romosozumab Treatment in Postmenopausal Women with Osteoporosis. N Engl J Med. 2016 20;375(16):1532–43.
60. Cosman F, Nieves JW, Roimisher C, Neubort S, McMahon DJ, Dempster DW, et al. Administration of teriparatide for four years cyclically compared to two years daily in treatment Naïve and alendronate treated women. Bone. 2019;120:246–53.
61. Watts NB, Hattersley G, Fitzpatrick LA, Wang Y, Williams GC, Miller PD, et al. Abaloparatide effect on forearm bone mineral density and wrist fracture risk in postmenopausal women with osteoporosis. Osteoporos Int. 2019 Jun;30(6):1187–94.
62. McClung MR, Harvey NC, Fitzpatrick LA, Miller PD, Hattersley G, Wang Y, et al. Effects of abaloparatide on bone mineral density and risk of fracture in postmenopausal women aged 80 years or older with osteoporosis. Menopause. 2018;25(7):767–71.
63. Reginster J-Y, Bianic F, Campbell R, Martin M, Williams SA, Fitzpatrick LA. Abaloparatide for risk reduction of nonvertebral and vertebral fractures in postmenopausal women with osteoporosis: a network meta-analysis. Osteoporos Int. 2019 Jul;30(7):1465–73.
64. Kim TY, Bauer DC, McNabb BL, Schafer AL, Cosman F, Black DM, et al. Comparison of BMD Changes and Bone Formation Marker Levels 3 Years After Bisphosphonate Discontinuation: FLEX and HORIZON-PFT Extension I Trials. Journal of Bone and Mineral Research. 2019;34(5):810–6.
65. Wallner C, Jaurich H, Wagner JM, Becerikli M, Harati K, Dadras M, et al. Inhibition of GDF8 (Myostatin) accelerates bone regeneration in diabetes mellitus type 2. Sci Rep [Internet]. 2017 Aug 29 [cited 2020 May 2];7. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575348/
66. Rooks D, Praestgaard J, Hariry S, Laurent D, Petricoul O, Perry RG, et al. Treatment of Sarcopenia with Bimagrumab: Results from a Phase II, Randomized, Controlled, Proof-of-Concept Study. J Am Geriatr Soc. 2017 Sep;65(9):1988–95.
67. Cosman F, Crittenden DB, Ferrari S, Lewiecki EM, Jaller-Raad J, Zerbini C, et al. Romosozumab FRAME Study: A Post Hoc Analysis of the Role of Regional Background Fracture Risk on Nonvertebral Fracture Outcome. J Bone Miner Res. 2018;33(8):1407–16.
68. Saag KG, Petersen J, Brandi ML, Karaplis AC, Lorentzon M, Thomas T, et al. Romosozumab or Alendronate for Fracture Prevention in Women with Osteoporosis. N Engl J Med. 2017 12;377(15):1417–27.
69. Bone HG, Cosman F, Miller PD, Williams GC, Hattersley G, Hu M-Y, et al. ACTIVExtend: 24 Months of Alendronate After 18 Months of Abaloparatide or Placebo for Postmenopausal Osteoporosis. J Clin Endocrinol Metab. 2018 01;103(8):2949–57.
70. Cosman F, Miller PD, Williams GC, Hattersley G, Hu M-Y, Valter I, et al. Eighteen Months of Treatment With Subcutaneous Abaloparatide Followed by 6 Months of Treatment With Alendronate in Postmenopausal Women With Osteoporosis: Results of the ACTIVExtend Trial. Mayo Clin Proc. 2017 Feb;92(2):200–10.
71. Leder BZ, Tsai JN, Uihlein AV, Wallace PM, Lee H, Neer RM, et al. Denosumab and teriparatide transitions in postmenopausal osteoporosis (the DATA-Switch study): extension of a randomised controlled trial. Lancet. 2015 Sep 19;386(9999):1147–55.
72. Kojima G. Frailty as a Predictor of Future Falls Among Community-Dwelling Older People: A Systematic Review and Meta-Analysis. Journal of the American Medical Directors Association. 2015 Dec;16(12):1027–33.
73. Dent E, Morley JE, Cruz-Jentoft AJ, Woodhouse L, Rodríguez-Mañas L, Fried LP, et al. Physical Frailty: ICFSR International Clinical Practice Guidelines for Identification and Management. J Nutr Health Aging. 2019;23(9):771–87.
74. Kritchevsky SB, Lovato L, Handing EP, Blair S, Botoseneanu A, Guralnik JM, et al. Exercise’s effect on mobility disability in older adults with and without obesity: The LIFE study randomized clinical trial. Obesity (Silver Spring). 2017;25(7):1199–205.
75. Marzetti E, Cesari M, Calvani R, Msihid J, Tosato M, Rodriguez-Mañas L, et al. The “Sarcopenia and Physical fRailty IN older people: multi-componenT Treatment strategies” (SPRINTT) randomized controlled trial: Case finding, screening and characteristics of eligible participants. Exp Gerontol. 2018;113:48–57.
76. Lebrasseur NK, Achenbach SJ, Melton LJ, Amin S, Khosla S. Skeletal muscle mass is associated with bone geometry and microstructure and serum insulin-like growth factor binding protein-2 levels in adult women and men. J Bone Miner Res. 2012 Oct;27(10):2159–69.
77. Houston DK, Nicklas BJ, Ding J, Harris TB, Tylavsky FA, Newman AB, et al. Dietary protein intake is associated with lean mass change in older, community-dwelling adults: the Health, Aging, and Body Composition (Health ABC) Study. Am J Clin Nutr. 2008 Jan;87(1):150–5.
78. Englund DA, Kirn DR, Koochek A, Zhu H, Travison TG, Reid KF, et al. Nutritional Supplementation With Physical Activity Improves Muscle Composition in Mobility-Limited Older Adults, The VIVE2 Study: A Randomized, Double-Blind, Placebo-Controlled Trial. J Gerontol A Biol Sci Med Sci. 2017 Dec 12;73(1):95–101.
79. Fielding RA, Travison TG, Kirn DR, Koochek A, Reid KF, von Berens Å, et al. Effect of Structured Physical Activity and Nutritional Supplementation on Physical Function in Mobility-Limited Older Adults: Results from the VIVE2 Randomized Trial. J Nutr Health Aging. 2017;21(9):936–42.
80. Breen L, Phillips SM. Interactions between exercise and nutrition to prevent muscle waste during ageing. Br J Clin Pharmacol. 2013 Mar;75(3):708–15.
81. Deutz NEP, Bauer JM, Barazzoni R, Biolo G, Boirie Y, Bosy-Westphal A, et al. Protein intake and exercise for optimal muscle function with aging: recommendations from the ESPEN Expert Group. Clin Nutr. 2014 Dec;33(6):929–36.
82. Batsis JA, Villareal DT. Sarcopenic obesity in older adults: aetiology, epidemiology and treatment strategies. Nat Rev Endocrinol. 2018;14(9):513–37.
83. Das SK, Roberts SB, Bhapkar MV, Villareal DT, Fontana L, Martin CK, et al. Body-composition changes in the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE)-2 study: a 2-y randomized controlled trial of calorie restriction in nonobese humans. Am J Clin Nutr. 2017;105(4):913–27.
84. Villareal DT, Fontana L, Weiss EP, Racette SB, Steger-May K, Schechtman KB, et al. Bone Mineral Density Response to Caloric Restriction–Induced Weight Loss or Exercise-Induced Weight Loss: A Randomized Controlled Trial. Arch Intern Med. 2006 Dec 11;166(22):2502–10.
85. Villareal DT, Chode S, Parimi N, Sinacore DR, Hilton T, Armamento-Villareal R, et al. Weight loss, exercise, or both and physical function in obese older adults. N Engl J Med. 2011 Mar 31;364(13):1218–29.
86. Shah K, Armamento-Villareal R, Parimi N, Chode S, Sinacore DR, Hilton TN, et al. Exercise training in obese older adults prevents increase in bone turnover and attenuates decrease in hip bone mineral density induced by weight loss despite decline in bone-active hormones. J Bone Miner Res. 2011 Dec;26(12):2851–9.
87. Adamo ML, Farrar RP. Resistance training, and IGF involvement in the maintenance of muscle mass during the aging process. Ageing Res Rev. 2006 Aug;5(3):310–31.
88. Castaneda C, Gordon PL, Fielding RA, Evans WJ, Crim MC. Marginal protein intake results in reduced plasma IGF-I levels and skeletal muscle fiber atrophy in elderly women. J Nutr Health Aging. 2000;4(2):85–90.
89. Schürch MA, Rizzoli R, Slosman D, Vadas L, Vergnaud P, Bonjour JP. Protein supplements increase serum insulin-like growth factor-I levels and attenuate proximal femur bone loss in patients with recent hip fracture. A randomized, double-blind, placebo-controlled trial. Ann Intern Med. 1998 May 15;128(10):801–9.
90. Alehagen U, Johansson P, Aaseth J, Alexander J, Brismar K. Increase in insulin-like growth factor 1 (IGF-1) and insulin-like growth factor binding protein 1 after supplementation with selenium and coenzyme Q10. A prospective randomized double-blind placebo-controlled trial among elderly Swedish citizens. PLoS One [Internet]. 2017 Jun 13 [cited 2020 May 4];12(6). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5469470/
91. Houston DK, Tooze JA, Davis CC, Chaves PHM, Hirsch CH, Robbins JA, et al. Serum 25-hydroxyvitamin D and physical function in older adults: the Cardiovascular Health Study All Stars. J Am Geriatr Soc. 2011 Oct;59(10):1793–801.
92. Ceglia L, Niramitmahapanya S, da Silva Morais M, Rivas DA, Harris SS, Bischoff-Ferrari H, et al. A randomized study on the effect of vitamin D3 supplementation on skeletal muscle morphology and vitamin D receptor concentration in older women. J Clin Endocrinol Metab. 2013 Dec;98(12):E1927-1935.
93. Shea MK, Fielding RA, Dawson-Hughes B. The effect of vitamin D supplementation on lower-extremity power and function in older adults: a randomized controlled trial. Am J Clin Nutr. 2019 01;109(2):369–79.
94. Smith GI, Julliand S, Reeds DN, Sinacore DR, Klein S, Mittendorfer B. Fish oil-derived n-3 PUFA therapy increases muscle mass and function in healthy older adults. Am J Clin Nutr. 2015 Jul;102(1):115–22.
95. Pahor M, Anton SD, Beavers DP, Cauley JA, Fielding RA, Kritchevsky SB, et al. Effect of Losartan and Fish Oil on Plasma IL-6 and Mobility in Older Persons. The ENRGISE Pilot Randomized Clinical Trial. J Gerontol A Biol Sci Med Sci. 2019 Sep 15;74(10):1612–9.
96. Cole ZA, Dennison EM, Cooper C. Osteoporosis epidemiology update. Curr Rheumatol Rep. 2008 Apr;10(2):92–6.
97. Cooper C, Campion G, Melton LJ. Hip fractures in the elderly: a world-wide projection. Osteoporos Int. 1992 Nov;2(6):285–9.
98. Rolland Y, Abellan Van Kan G, Gillette-Guyonnet S, Roux C, Boonen S, Vellas B. Strontium ranelate and risk of vertebral fractures in frail osteoporotic women. Bone. 2011 Feb;48(2):332–8.
99. Laskou F, Dennison E. Interaction of Nutrition and Exercise on Bone and Muscle. Eur Endocrinol. 2019 Apr;15(1):11–2.
100. Sambrook PN, Cameron ID, Chen JS, Cumming RG, Lord SR, March LM, et al. Influence of fall related factors and bone strength on fracture risk in the frail elderly. Osteoporos Int. 2007 May;18(5):603–10.
101. Lai S-W, Cheng K-C, Lin C-L, Liao K-F. Furosemide use and acute risk of hip fracture in older people: A nationwide case-control study in Taiwan. Geriatr Gerontol Int. 2017 Dec;17(12):2552–8.
102. Torstensson M, Hansen AH, Leth-Møller K, Jørgensen TSH, Sahlberg M, Andersson C, et al. Danish register-based study on the association between specific cardiovascular drugs and fragility fractures. BMJ Open. 2015 Dec 29;5(12):e009522.
103. Seppala LJ, van der Velde N, Masud T, Blain H, Petrovic M, van der Cammen TJ, et al. EuGMS Task and Finish group on Fall-Risk-Increasing Drugs (FRIDs): Position on Knowledge Dissemination, Management, and Future Research. Drugs Aging. 2019;36(4):299–307.
104. Seppala LJ, Wermelink AMAT, de Vries M, Ploegmakers KJ, van de Glind EMM, Daams JG, et al. Fall-Risk-Increasing Drugs: A Systematic Review and Meta-Analysis: II. Psychotropics. J Am Med Dir Assoc. 2018;19(4):371.e11-371.e17.
105. de Vries M, Seppala LJ, Daams JG, van de Glind EMM, Masud T, van der Velde N, et al. Fall-Risk-Increasing Drugs: A Systematic Review and Meta-Analysis: I. Cardiovascular Drugs. J Am Med Dir Assoc. 2018;19(4):371.e1-371.e9.
106. Seppala LJ, van de Glind EMM, Daams JG, Ploegmakers KJ, de Vries M, Wermelink AMAT, et al. Fall-Risk-Increasing Drugs: A Systematic Review and Meta-analysis: III. Others. J Am Med Dir Assoc. 2018;19(4):372.e1-372.e8.
107. Tchkonia T, Zhu Y, van Deursen J, Campisi J, Kirkland JL. Cellular senescence and the senescent secretory phenotype: therapeutic opportunities. J Clin Invest. 2013 Mar;123(3):966–72.
108. Khosla S, Farr JN, Kirkland JL. Inhibiting Cellular Senescence: A New Therapeutic Paradigm for Age-Related Osteoporosis. J Clin Endocrinol Metab. 2018 01;103(4):1282–90.
109. Hopewell S, Copsey B, Nicolson P, Adedire B, Boniface G, Lamb S. Multifactorial interventions for preventing falls in older people living in the community: a systematic review and meta-analysis of 41 trials and almost 20 000 participants. Br J Sports Med. 2019 Aug 21;
110. Andrieu S, Guyonnet S, Coley N, Cantet C, Bonnefoy M, Bordes S, et al. Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): a randomised, placebo-controlled trial. Lancet Neurol. 2017 May;16(5):377–89.
111. Pérez LM, Enfedaque-Montes MB, Cesari M, Soto-Bagaria L, Gual N, Burbano MP, et al. A Community Program of Integrated Care for Frail Older Adults: +AGIL Barcelona. J Nutr Health Aging. 2019;23(8):710–6.
112. Kito N, Matsuo K, Ogawa K, Izumi A, Kishima M, Itoda M, et al. Positive Effects of “Textured Lunches” Gatherings and Oral Exercises Combined with Physical Exercises on Oral and Physical Function in Older Individuals: A Cluster Randomized Controlled Trial. J Nutr Health Aging. 2019;23(7):669–76.
113. Ruan Q, Xiao F, Gong K, Zhang W, Zhang M, Ruan J, et al. Prevalence of Cognitive Frailty Phenotypes and Associated Factors in a Community-Dwelling Elderly Population. J Nutr Health Aging. 2020;24(2):172–80.
114. Ge M, Zhang Y, Zhao W, Yue J, Hou L, Xia X, et al. Prevalence and Its Associated Factors of Physical Frailty and Cognitive Impairment: Findings from the West China Health and Aging Trend Study (WCHAT). J Nutr Health Aging. 2020;24(5):525–33.
115. Chye L, Wei K, Nyunt MSZ, Gao Q, Wee SL, Ng TP. Strong Relationship between Malnutrition and Cognitive Frailty in the Singapore Longitudinal Ageing Studies (SLAS-1 and SLAS-2). J Prev Alzheimers Dis. 2018;5(2):142–8.
116. Shimada H, Makizako H, Tsutsumimoto K, Doi T, Lee S, Suzuki T. Cognitive Frailty and Incidence of Dementia in Older Persons. J Prev Alzheimers Dis. 2018;5(1):42–8.
117. Halil M, Cemal Kizilarslanoglu M, Emin Kuyumcu M, Yesil Y, Cruz Jentoft AJ. Cognitive aspects of frailty: mechanisms behind the link between frailty and cognitive impairment. J Nutr Health Aging. 2015 Mar;19(3):276–83.
118. Vellas B, Scrase D, Rosenberg GA, Andrieu S, Araujo de Carvalho I, Middleton LT. Editorial: WHO Guidelines on Community-Level Interventions to Manage Declines in Intrinsic Capacity: The Road for Preventing Cognitive Declines in Older Age? J Prev Alzheimers Dis. 2018;5(3):165–7.
119. Tavassoli N, Piau A, Berbon C, De Kerimel J, Lafont C, De Souto Barreto P, et al. Framework implementation of the inspire icope-care program in collaboration with the world health organization (who) in the occitania region. Journal of Frailty & Aging [Internet]. 2019 Mar 1 [cited 2020 May 28]; Available from: https://www.jfrailtyaging.com/all-issues.html
120. Takeda, C., Guyonnet, S., Sumi, Y., Vellas. B., Araujo De Carvalho, I. Integrated Care for Older People and the Implementation in the INSPIRE Study. 2020;7(2):70-74.doi: 10.14283/jpad.2020.8.
121. Beard JR. Editorial: Linking Geroscience and Integrated Care to Reinforce Prevention. J Prev Alzheimers Dis. 2020;7(2):68–9.
122. Guerville F, de Souto Barreto P, Giudici KV, Rolland Y, Vellas B, MAPT/DSA Group. Association of 3-Year Multidomain Intervention and Omega-3 Supplementation with Frailty Incidence. J Am Geriatr Soc. 2019 Aug;67(8):1700–6.
123. Muscedere J, Kim PM, Afilalo J, Balion C, Baracos VE, Bowdish D, et al. Proceedings of the Canadian Frailty Network Workshop: Identifying Biomarkers of Frailty to Support Frailty Risk Assessment, Diagnosis and Prognosis. Toronto, January 15, 2018. J Frailty Aging. 2019;8(3):106–16.
124. Rodriguez-Mañas L, Araujo de Carvalho I, Bhasin S, Bischoff-Ferrari HA, Cesari M, Evans W, et al. ICFSR Task Force Perspective on Biomarkers for Sarcopenia and Frailty. J Frailty Aging. 2020;9(1):4–8.
125. Bray NW, Jones GJ, Rush KL, Jones CA, Jakobi JM. Multi-Component Exercise with High-Intensity, Free-Weight, Functional Resistance Training in Pre-Frail Females: A Quasi-Experimental, Pilot Study. J Frailty Aging. 2020;9(2):111–7.
126. Cruz-Jentoft AJ, Woo J. Nutritional interventions to prevent and treat frailty. Curr Opin Clin Nutr Metab Care. 2019;22(3):191–5.
127. Dicks ND, Kotarsky CJ, Trautman KA, Barry AM, Keith JF, Mitchell S, et al. Contribution of Protein Intake and Concurrent Exercise to Skeletal Muscle Quality with Aging. J Frailty Aging. 2020;9(1):51–6.

MULTICOMPONENT EXERCISE PROGRAM IN OLDER ADULTS WITH LUNG CANCER DURING ADJUVANT/PALLIATIVE TREATMENT: A SECONDARY ANALYSIS OF AN INTERVENTION STUDY

 

N. Martínez-Velilla1,2,3, M.L. Saez de Asteasu1,2, R. Ramírez-Vélez1, I.D. Rosero1, A. Cedeño-Veloz1,3, I. Morilla1,4, R.V. García1,4, F. Zambom-Ferraresi1,2, A. García-Hermoso1,5, M. Izquierdo1,2

1. Navarrabiomed, Complejo Hospitalario de Navarra (CHN)-Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain; 2. CIBER of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain; 3. Department of Geriatric Medicine, Complejo Hospitalario de Navarra, Irunlarrea 3, Pamplona, Spain; 4. Department of Medical Oncology, Complejo Hospitalario de Navarra, Pamplona, Spain; 5. Laboratorio de Ciencias de la Actividad Física, el Deporte y la Salud, Facultad de Ciencias Médicas, Universidad de Santiago de Chile, USACH, Santiago, Chile.
Corresponding author: Mikel Izquierdo, PhD, Department of Health Sciences, Public University of Navarra, Av. De Barañain s/n 31008 Pamplona (Navarra) Spain, Tel + 34 948 417876, mikel.izquierdo@gmail.com

J Frailty Aging 2021;10(3)247-253
Published online February 7, 2021, http://dx.doi.org/10.14283/jfa.2021.2

 


Abstract

Background: Lung cancer is the second most prevalent common cancer in the world and predominantly affects older adults. This study aimed to examine the impact of an exercise programme in the use of health resources in older adults and to assess their changes in frailty status. Design: This is a secondary analysis of a quasi-experimental study with a non-randomized control group. Setting: Oncogeriatrics Unit of the Complejo Hospitalario de Navarra, Spain. Participants: Newly diagnosed patients with NSCLC stage I–IV. Intervention: Multicomponent exercise programme that combined resistance, endurance, balance and flexibility exercises. Each session lasted 45–50 minutes, and the exercise protocol was performed twice a week over 10 weeks. Measurements: Mortality, readmissions and Visits to the Emergency Department. Change in frailty status according to Fried, VES-13 and G-8 scales. Results: 26 patients completed the 10-weeks intervention (IG). Mean age in the control group (CG) was 74.5 (3.6 SD) vs 79 (3 SD) in the IG, and 78,9% were male in the IG vs 71,4% in the CG. No major adverse events or health-related issues attributable to the testing or training sessions were noted. Significant between-group differences were obtained on visits to the emergency department during the year post-intervention (4 vs 1; p:0.034). No differences were found in mortality rate and readmissions, where an increasing trend was observed in the CG compared with the IG in the latter (2 vs 0; p 0.092). Fried scale was the unique indicator that seemed to be able to detect changes in frailty status after the intervention. Conclusions: A multicomponent exercise training programme seems to reduce the number of visits to the emergency department at one-year post-intervention in older adults with NSCLC during adjuvant therapy or palliative treatment, and is able to modify the frailty status when measured with the Fried scale.

Key words: Lung cancer, frailty, exercise, health-care resources.


 

Introduction

Lung cancer is the second most prevalent common cancer in the world and predominantly affects older adults; 50% of the diagnoses are in patients aged 70 or older, and about 14% in over 80 years old (1, 2). Overall, the survival rate at 5 years is lower in the very old, and patients aged 80 years or older are less likely to receive local therapy than younger patients (2). Additionally, the incidence and mortality from lung cancer have decreased among individuals aged 50 years and younger but have increased among those aged 70 years and older (3). However, geriatric patients may be undertreated, and are routinely underrepresented on clinical trials for many reasons including frailty, doubts about the usefulness of therapy, or lower patient willingness to pursue aggressive therapy (4, 5).
The standard-of-care therapy for patients with stage III Non-small cell lung cancer (NSCLC) is concurrent chemotherapy and radiotherapy (CRT), but there is a lack of data regarding the use of CRT in octogenarians and nonagenarians. The goal for the treatment of patients with stage IV NSCLC is palliation, both through improvement in their quality of life (QOL) and in prolongation of survival. Few comparative studies have been conducted that are limited to older patients, and even in very recent research of older adults with NSCLC, the cut-off age was 65 or 70 years (6), and in some studies, even 62.7% of patients aged ≥80 years with stage III NSCLC received no cancer-directed care (7). Patient selection is a key factor in order to administer some treatments in older adults because they are more likely to have a poor performance status with comorbidities, which can lead to little benefit (8).
There is a growing interest in non-invasive interventions for patients with lung cancer, with the goal of maximising physical performance. Physical exercise can be beneficial at any stage of the disease through increasing strength, endurance and decreasing emotional issues (9). Multicomponent exercise programmes have demonstrated to be well tolerated and safe in patients with lung cancer, but there is still a paucity of data to draw conclusive and precise exercise guidelines. A recent Cochrane review failed to establish any conclusive evidence regarding efficiency of exercise training on physical fitness in patients with advanced lung cancer (10–12), and there is little information on what kind of benefits an exercise intervention can provide in the use of health-related resources or the impact on the ability to reverse frailty in the older population. To date, the clinical effectiveness of physical exercise in advanced cancer remains inconclusive.
This study aimed to examine the impact of this exercise programme in the use of health resources and its ability to reduce the number of visits to an emergency department at one-year post-intervention and to assess the changes in frailty status.

 

Methods

Study design, setting and ethical considerations

This is a secondary analysis of a non-randomised, opportunistic control, longitudinal trial designed to examine the effects of a multicomponent exercise programme on surrogate measures of health status in patients with lung cancer in real-world settings (12). Patients were treated at the Oncogeriatrics Unit of the Complejo Hospitalario de Navarra (CHN), Pamplona, Spain. The study ran from May 2018 to November 2019 and was approved by the CHN Research Ethics Committee (25 April, 2018, reference number Pyto2018/5#214) according to the World Medical Association Declaration of Helsinki Declaration.

Patient population

Newly diagnosed patients with NSCLC stage I–IV (TNM classification) were enrolled after histologically confirmation and screening for eligibility by their oncologist. The study included an initial exam at the first visit (baseline) and a final exam after 10-weeks. The inclusion criteria were: aged 70 years or older, have a diagnosis of confirmed lung cancer, with a life expectancy exceeding 3 months (prognosis), with multimorbidity, a Barthel score ≥60 points, and to be able to communicate and collaborate with the research team. Exclusion criteria were clinically unstable patients defined medically as having received active treatment (chemotherapy or radiotherapy) before inclusion in the study, moderate–severe cognitive impairment considered as a score ≥5 in the Reisberg Global Deterioration Scale, and contraindications to exercise or already engaged in high levels of physical training.

Outcome assessment

The primary outcomes of this study were mortality rate, readmissions and visits to the emergency department during the year after the intervention. The secondary outcomes were the changes in the level of frailty measured with G8 (14, 15), Vulnerable Elders Survey-13 (VES-13) (16, 17) and Fried scales (17). The G8 is an eight-item screening tool, developed for older cancer patients. The tool covers multiple domains usually assessed by the geriatrician when performing the geriatric assessment. A score of ≤14 is considered abnormal. The VES-13 is a 13-item self-administered tool, developed for identifying older people at increased risk of health deterioration in the community. A score of ≥3 identifies individuals as “vulnerable”, which is defined as an increased risk of functional decline or death over 2 years. The Fried Frailty Criteria includes five items: weight loss, handgrip strength, gait speed, exhaustion and physical performance and a score of ≥3 indicates “frailty”.
Members of the research team were able to access the medical records of each patient. The same assessments were repeated at 10-weeks after intervention or usual care, and we checked the medical records in order to assess the mortality, number of readmissions and visits to the emergency department during the year posterior to the intervention.

Intervention

The intervention is described elsewhere (12). Briefly, the control group (CG) did not perform any kind of supervised physical exercises/activities during the intervention period but received habitual outpatient care, including comprehensive geriatric assessment and physical rehabilitation when needed.
The intervention group (IG) received a multicomponent exercise programme that combined resistance, endurance, balance and flexibility exercises. Each session lasted 45–50 minutes, and the exercise protocol was performed twice a week over 10 weeks (Table 1). EGYM Smart strength machines (eGym® GmbH, München, Germany) were used for both resistance training and maximum strength measurements of the lower and upper extremity muscles. Muscle power training including motivational gamification and maximum acceleration of constant weight from 30% to 60% of the maximun strength measurements were used during training (Explonic eGym® intelligent training program). The exercise programme was individualised and included measurements of vital signs at the beginning and end of each session. Patients were advised to carry out the «Vivifrail» programme (18) at home during the entire study period. The control group received the usual medical treatment and was advised to continue their usual activities without restriction in physical activity throughout the study period.

Table 1
Multi-component exercise program

Abbreviations: HR: Heart Rate; RM: Repetition Maximum.

 

Statistical analyses

All analyses were performed by a researcher who was not involved in the study’s participant assessments and interventions. The statistical data analysis was performed with the commercial software SPSS Statistics version 25.0 (IBM Corp., Chicago, IL, USA). The Shapiro–Wilk test was used to determine whether parametric tests were appropriate, and the normality of data was checked graphically. In the present study, descriptive data, including frequencies for categorical variables and means and standard deviation (SD) for continuous variables, were reported. Baseline differences and use of health resources (readmission and visits to the emergency department) were analysed using the chi-squared test and Mann–Whitney U test for nominal data and the Kruskal–Wallis test for ordinal data. A significance level of 5% (p <0.05) was adopted for all statistical analyses.

 

Results

Characteristics of participants

Of the 42 volunteers, 34 attended the oncologic and geriatric clinics screening. Of these, 26 completed the 10-weeks intervention. Two patients from the IG did not complete the programme due to death or oesophagal surgery. Data from the 19 remaining patients from the IG were analysed. A total of 6 of the 13 CG subjects dropped out of the study and did not take the final exam due to the progression of the disease (n = 3) or death (n = 3). Data from the 7 remaining CG participants were analysed. A total of 19 participants (4 females, 15 males) were eligible for analysis in the IG and 7 participants (2 females, 5 males) in the CG (Figure 1). All subjects in the IG completed at least 86% of the planned training sessions. No major adverse events or health-related issues attributable to the testing or training sessions were noted.
Table 2 displays the baseline characteristics by group. No significant differences were found between the two groups, except for age. Patients in the IG had a mean (SD) age of 74.5 (3.6) years, range 70–81 years (78.9% males) and BMI 26.8 (4.5) kg/m2. In total, 41% underwent surgery, and 78.9% received adjuvant chemotherapy alone or in combination with other therapies. Participants in the CG had a mean (SD) age of 79.0 (3.0) years, range 75–83 years (71.4% males), and BMI 25.5 (2.5) kg/m2. Within this group, 14% were submitted to surgery, and 85.7% were receiving adjuvant chemotherapy alone or in combination with other therapies.

Figure 1
CONSORT Flow Diagram – modified for non-randomized
trial design

Table 2
Baseline characteristics of the participants

Abbreviations: BMI, body mass index; COPD, chronic obstructive pulmonary disease; TNM, tumor node metastasis; VATS, video-assisted thoracic surgery; VES-13, Vulnerable Elders Survey-13. aData are reported as mean ± standard deviation or number (%).

 

Mortality, readmissions and Visits to the Emergency Department

Significant between-group differences were obtained on visits to the emergency department during the year post-intervention (4 vs 1; p:0.034). Furthermore, no differences were found in mortality rate and readmissions, where an increasing trend was observed in the CG compared with the IG in the latter (2 vs 0; p 0.092) (Table 3).

Table 3
Mortality rate, readmissions and visits to the Emergency Department at one year post-intervention

Abbreviations: ED, Emergency Department; IQR, interquartile range.

 

Change in frailty status according to Fried, VES-13 and G-8

Although no significant between-group differences were obtained on frailty status changes assessed with the G-8, VES-13 and Fried scale, the unique indicator that seems to be able to detect changes in frailty status is the Fried Index after the intervention (Table 4).

Table 4
Changes in frailty status according to G-8, VES-13
and Frailty Index after the intervention

Abbreviations: VES, Vulnerable Elders Survey.

 

Discussion

The main finding of this study was that supervised multicomponent exercise training can be beneficial for patients with lung cancer, by decreasing the number of visits to the emergency department. Previously, we showed that a multicomponent exercise programme in older patients with NSCLC under adjuvant therapy or palliative treatment positively affected measures of functional performance and quality of life (i.e., pain symptoms and dyspnea) (12), but this secondary analysis goes a step further, and analyses additional outcomes that may help when making decisions in relation to the use of healthcare resources.
Non-oncologic causes of readmission and death predominate in the first 90 days after pneumonectomy, after which oncologic causes prevail (19). Most previous studies have been related to readmissions after pulmonary resection (21, 22), but there is hardly any data on the influence of exercise programmes on the number of visits to the emergency department or on the influence of frailty in the use of health resources in cancer patients (17, 23). Older adults have been traditionally excluded from clinical trials, and clinical data obtained in a younger population cannot be automatically extrapolated to older patients with lung cancer (23). Older patients have more comorbidities and tend to tolerate aggressive chemotherapy and radiotherapy worse than younger patients. Much of the data available currently is based on retrospective studies of trials that included patients with good performance status and patients of all ages. Nonetheless, retrospective analyses of ordinary trials without age-specific entry criteria are potentially biased by the intrinsic selection that governs enrollment. In the present study, we did not find differences in the mortality rate, but this factor is very difficult to modify, especially in an older population as complex and frail as the one that participated in the study. However, we found that the IG had a non-significant lower number of readmissions (p = 0.09) and a lower number of visits to the emergency department (p = 0.034) at one-year post-intervention, which had at least a moderate impact on aspects related to the quality of life and use of health resources.
Chronological age alone should not be the only factor in the cancer treatment plan. Other factors should be taken into account and frailty assessment in older patients with primary lung cancer is increasingly being recognised as a very important tool (24), and it could be used even to prevent under- or overtreatment (25). In fact, a comprehensive geriatric assessment should be used together with an evaluation of the toxicity profile of each drug to guide the choice of the best treatment (26).
There is a big dilemma regarding the scales and the models to select the patients who most benefit of specific oncogeriatric approaches (15). Some studies suggest the VES-13 scale or G-8 scale, nevertheless, the only scale in our study that identified a possible reversal of the frailty status was the Fried Index. This could be because physical exercise modifies more parameters that are taken into account in Fried model of frailty (physical activity, grip strength and gait speed) compared to the G8 model (which has a vague and generic question about mobility), or the VES-13 (which has questions related more to basic activity rather than functional capacity). This has implications for future studies and helps to clarify which indices we should use in this population sector. In our study, a supervised exercise training programme was able to reverse frailty in 21.1% of patients (vs 0% in CG) using the Fried scale. This scale includes many functional aspects such as handgrip strength and gait velocity that could benefit from a physical exercise programme in comparison with G-8 and VES-13 scales.
The management of the older person with cancer should be based on the risk/benefit assessment, and in the multidisciplinary interventions (medical, psychological and social) it may improve the tolerance of the treatments (27). Exercise should be part of this multidisciplinary approach because it provides physiological and psychological benefits for cancer survivors Cancer rehabilitation as a part of clinical management is still underutilised, but older adults with lung cancer would welcome a proactive intervention. There are some barriers due to the psychosocial impact of diagnosis and the effects of cancer treatment, but the intervention must be tailored to individual need and address physical limitations, psychological and social welfare in addition to physical activity and nutritional advice (28). In this regard, the present study shows that these kind of programmes are feasible and may improve the quality of life of older patients with NSCLC.
This study had several limitations that should be considered. The most important was that the number of participants in our study was relatively small, but there are not many related studies with more patients, and so more extensive multicentre studies are encouraged to reinforce our findings. However, our study based on a supervised and individualized multicomponent physical exercise intervention including muscle power training and motivational gamification was beneficial and safe for patients with advanced NSCLC, under adjuvant therapy or palliative treatment. To our knowledge, none of the previous studies that have evaluated physical training in older adults with lung cancer reported serious adverse events, which is consistent with the findings of our study. We believe that the present study represents an important addition to the current body of knowledge on the safety of exercise interventions, particularly in the elderly with NSCLC under adjuvant therapy or palliative treatment. Well-designed randomized clinical trials should be performed to corroborate the current findings, with a larger sample size to detect a significant difference in the components studied.
In conclusion, a multicomponent exercise training programme seems to reduce the number of visits to the emergency department at one-year post-intervention in older adults with NSCLC during adjuvant therapy or palliative treatment for their disease, and is able to modify the frailty status measured with the Fried scale.

 

Funding: M.I. is funded in part by a research grant PI17/01814 from the Ministerio de Economía, Industria, y Competitividad (ISCIII, FEDER). R.R.-V. is funded in part by a Postdoctotal fellowship grant ID 420/2019 of the Universidad Pública de Navarra, Spain. N.M.-V. is funded in part by a research grant from Gobierno de Navarra: «Project prevención de deterioro funcional del anciano frágil con cáncer de pulmón mediante un programa de ejercicio tras valoración geriátrica integral” (Expediente 43/18), promovido por el Departamento de Salud.
Acknowledgments: We thank Fundacion Miguel Servet (Navarrabiomed) for its support during the implementation of the study, as well as Fundacion Caja Navarra and Fundacion La Caixa. Finally, we thank our patients and their families for their confidence in the research team.
Conflicts of Interest: The authors declare no conflicts of interest.
Ethical Standards: The study was approved by the CHN Research Ethics Committee (25 April, 2018, reference number Pyto2018/5#214) according to the World Medical Association Declaration of Helsinki Declaration.

 

References

1. Casaluce F, Sgambato A, Maione P, Spagnuolo A, Gridelli C. Lung cancer, elderly and immune checkpoint inhibitors. J Thorac Dis. 2018;10(1):S1474-S1481. doi:10.21037/jtd.2018.05.90.
2. Owonikoko TK, Ragin CC, Belani CP, et al. Lung cancer in elderly patients: An analysis of the surveillance, epidemiology, and end results database. J Clin Oncol. 2007;25(35):5570-5577. doi:10.1200/JCO.2007.12.5435.
3. Wingo PA, Cardinez CJ, Landis SH, et al. Long-term trends in cancer mortality in the United States, 1930-1998. Cancer. 2003;97(12 SUPPL.):3133-3275. doi:10.1002/cncr.11380.
4. Hutchins LF, Unger JM, Crowley JJ, Coltman C. A. J, Albain KS. Underrepresentation of patients 65 years of age or older in cancer-treatment trials. N Engl J Med. 1999;341(27):2061-2067. doi:10.1056/NEJM199912303412706.
5. Sacher AG, Le LW, Leighl NB, Coate LE. Elderly patients with advanced NSCLC in phase III clinical trials: Are the elderly excluded from practice-changing trials in advanced NSCLC? J Thorac Oncol. 2013;8(3):366-368. doi:10.1097/JTO.0b013e31827e2145.
6. Carmichael JA, Wing-San Mak D, O’Brien M. A review of recent advances in the treatment of elderly and poor performance NSCLC. Cancers (Basel). 2018;10(7). doi:10.3390/cancers10070236.
7. Cassidy RJ, Zhang X, Switchenko JM, et al. Health care disparities among octogenarians and nonagenarians with stage III lung cancer. Cancer. 2018;124(4):775-784. doi:10.1002/cncr.31077.
8. Takigawa N, Ochi N, Nakagawa N, et al. Do elderly lung cancer patients aged ≥75 years benefit from immune checkpoint inhibitors? Cancers (Basel). 2020;12(7):1-12. doi:10.3390/cancers12071995.
9. Michaels C. The importance of exercise in lung cancer treatment. Transl Lung Cancer Res. 2016;5(3):235-238. doi:10.21037/tlcr.2016.03.02.
10. Peddle-McIntyre CJ, Singh F, Thomas R, Newton RU, Galvao DA, Cavalheri V. Exercise training for advanced lung cancer. Cochrane Database Syst Rev. 2019;2019(2). doi:10.1002/14651858.CD012685.pub2.
11. Rosero ID, Ramírez-Vélez R, Lucia A, et al. Systematic review and meta-analysis of randomized, controlled trials on preoperative physical exercise interventions in patients with non-small-cell lung cancer. Cancers (Basel). 2019;11(7). doi:10.3390/cancers11070944.
12. Rosero ID, Ramírez-Vélez R, Martínez-Velilla N, Cedeño-Veloz BA, Morilla I, Izquierdo M. Effects of a Multicomponent Exercise Program in Older Adults with Non-Small-Cell Lung Cancer during Adjuvant/Palliative Treatment: An Intervention Study. J Clin Med. 2020;9(3):862. doi:10.3390/jcm9030862.
13. Soubeyran P, Bellera C, Goyard J, et al. Screening for Vulnerability in Older Cancer Patients: The ONCODAGE Prospective Multicenter Cohort Study. PLoS One. 2014;9(12):e115060. doi:10.1371/journal.pone.0115060.
14. Bellera CA, Rainfray M, Mathoulin-Pélissier S, et al. Screening older cancer patients: First evaluation of the G-8 geriatric screening tool. Ann Oncol. 2012;23(8):2166-2172. doi:10.1093/annonc/mdr587.
15. Decoster L, Van Puyvelde K, Mohile S, et al. Screening tools for multidimensional health problems warranting a geriatric assessment in older cancer patients: an update on SIOG recommendations†. Ann Oncol. 2015;26(2):288-300. doi:10.1093/annonc/mdu210.
16. Saliba D, Elliott M, Rubenstein LZ, et al. The vulnerable elders survey: A tool for identifying vulnerable older people in the community. J Am Geriatr Soc. 2001;49(12):1691-1699. doi:10.1046/j.1532-5415.2001.49281.x.
17. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-56. https://www.ncbi.nlm.nih.gov/pubmed/11253156.
18. Izquierdo M, Casas-Herrero A, Zambom-Ferraresi F, Martínez-Velilla N, Alonso-Bouzón C, Rodriguez-Mañas L. Multicomponent physical exercise program vivifrail. A practical guide for prescribing a Multicomponent Physical training program to prevent weakness and falls in people over 70 [Internet]. 2017 [cited 2019 Aug 4]. Available from: http://vivifrail.com/wp-content/uploads/2019/11/VIVIFRAIL-ENG-Interactivo.pdf
19. Jones GD, Tan KS, Caso R, et al. Time-varying analysis of readmission and mortality during the first year after pneumonectomy. In: Journal of Thoracic and Cardiovascular Surgery. Vol 160. Mosby Inc.; 2020:247-255.e5. doi:10.1016/j.jtcvs.2020.02.086.
20. Handy JR, Child AI, Grunkemeier GL, et al. Hospital readmission after pulmonary resection: Prevalence, patterns, and predisposing characteristics. Ann Thorac Surg. 2001;72(6):1855-1860. doi:10.1016/S0003-4975(01)03247-7.
21. Hu Y, McMurry TL, Isbell JM, Stukenborg GJ, Kozower BD. Readmission after lung cancer resection is associated with a 6-fold increase in 90-day postoperative mortality. J Thorac Cardiovasc Surg. 2014;148(5):2261-2267.e1. doi:10.1016/j.jtcvs.2014.04.026.
22. Min L, Yoon W, Mariano J, et al. The vulnerable elders-13 survey predicts 5-year functional decline and mortality outcomes in older ambulatory care patients. J Am Geriatr Soc. 2009;57(11):2070-2076. doi:10.1111/j.1532-5415.2009.02497.x.
23. Ludmir EB, Subbiah IM, Mainwaring W, et al. Decreasing incidence of upper age restriction enrollment criteria among cancer clinical trials. J Geriatr Oncol. 2020;11(3):451-454. doi:10.1016/j.jgo.2019.11.001.
24. Wang Y, Zhang R, Shen Y, Su L, Dong B, Hao Q. Prediction of chemotherapy adverse reactions and mortality in older patients with primary lung cancer through frailty index based on routine laboratory data. Clin Interv Aging. 2019;14:1187-1197. doi:10.2147/CIA.S201873.
25. Tsubata Y, Shiratsuki Y, Okuno T, et al. Prospective clinical trial evaluating vulnerability and chemotherapy risk using geriatric assessment tools in older patients with lung cancer. Geriatr Gerontol Int. 2019;19(11):1108-1111. doi:10.1111/ggi.13781.
26. Gridelli C, Aapro M, Ardizzoni A, et al. Treatment of advanced non-small-cell lung cancer in the elderly: Results of an International Expert Panel. J Clin Oncol. 2005;23(13):3125-3137. doi:10.1200/JCO.2005.00.224.
27. Balducci L, Extermann M. Management of Cancer in the Older Person: A Practical Approach. Oncologist. 2000;5(3):224-237. doi:10.1634/theoncologist.5-3-224.
28. Swan F, Chen H, Forbes CC, Johnson MJ, Lind M. CANcer BEhavioural nutrition and exercise feasibility trial (CanBenefit); phase I qualitative interview findings. J Geriatr Oncol. 2020. doi:10.1016/j.jgo.2020.09.026.

TRENDS IN THE PREVALENCE OF FRAILTY IN JAPAN: A META-ANALYSIS FROM THE ILSA-J

 

H. MAKIZAKO1, Y. NISHITA2, S. JEONG3, R. OTSUKA4, H. SHIMADA5, K. IIJIMA6, S. OBUCHI7, H. KIM8, A. KITAMURA9, Y. OHARA8, S. AWATA8, N. YOSHIMURA10, M. YAMADA11, K. TOBA12, T. SUZUKI13

1. Department of Physical Therapy, Faculty of Medicine, School of Health Sciences, Kagoshima University, Kagoshima, Japan; 2. Department of Epidemiology, National Center for Geriatrics and Gerontology, Obu, Japan; 3. Department Community Welfare, Niimi University, Niimi, Japan; 4. Section of NILS-LSA, National Center for Geriatrics and Gerontology, Obu, Japan; 5. Department of Preventive Gerontology, National Center for Geriatrics and Gerontology, Obu, Japan; 6. Institute of Gerontology, The University of Tokyo, Bunkyo-ku, Japan; 7. Research Team for Human Care, Tokyo Metropolitan Institute of Gerontology, Itabashi-ku, Japan; 8. Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute of Gerontology, Itabashi-ku, Japan; 9. Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Itabashi-ku, Japan; 10. Department of Joint Disease Research, 22nd Century Medical and Research Center, The University of Tokyo, Bunkyo-ku, Japan; 11. Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Japan; 12. Tokyo Metropolitan Institute of Gerontology, Itabashi-ku, Japan; 13. National Center for Geriatrics and Gerontology, Obu, Japan & Institute of Gerontology, J.F. Oberlin University, Machida, Japan.
Corresponding author: Hyuma Makizako, epartment of Physical Therapy, Faculty of Medicine, School of Health Sciences, Kagoshima University, Kagoshima, Japan, makizako@health.nop.kagoshima-u.ac.jp

J Frailty Aging 2021;10(3)211-218
Published online December 22, 2020, http://dx.doi.org/10.14283/jfa.2020.68

 


Abstract

Objective: To examine whether age-specific prevalence of frailty in Japan changed between 2012 and 2017. Design: This study performed meta-analyses of data collected from 2012 to 2017 using the Integrated Longitudinal Studies on Aging in Japan (ILSA-J), a collection of representative Japanese cohort studies. Setting: The ILSA-J studies were conducted on community-living older adults. Participants: ILSA-J studies were considered eligible for analysis if they assessed physical frailty status and presence of frailty in the sample. Seven studies were analyzed for 2012 (±1 year; n = 10312) and eight studies were analyzed for 2017 (±1 year; n = 7010). Five studies were analyzed for both 2012 and 2017. Measurements: The study assessed the prevalence of frailty and frailty status according to 5 criteria: slowness, weakness, low activity, exhaustion, and weight loss.Results: The overall prevalence of physical frailty was 7.0% in 2012 and 5.3% in 2017. The prevalence of frailty, especially in people 70 years and older, tended to decrease in 2017 compared to 2012. Slight decreases were found in the prevalence of frailty subitems including weight loss, slowness, exhaustion, and low activity between 2012 and 2017, but change in the prevalence of weakness was weaker than other components. Conclusions: The prevalence of physical frailty decreased from 2012 to 2017. There are age- and gender-related variations in the decrease of each component of frailty.

Key words: Frailty, aging, cohort study, older.


 

Introduction

Frailty is defined as a clinically recognizable state of increased vulnerability in older adults resulting from age-associated declines in physiologic reserves and function across multiple organ systems (1). Although it is recognized as a multidimensional construct, comprising psychological and social conditions and symptoms in addition to physical, the physical frailty phenotype is well defined and its impact on adverse health outcomes such as disability, hospitalization, and death has been examined in many prior studies (2-5). Clinical practice guidelines based on the current evidence base provide recommendations for identifying and managing frailty in older adults (6). Reducing the risk and prevalence of frailty may play an important role in extending healthy life expectancy in the aged population.
The most common components used to assess physical frailty are the frailty phenotype proposed by Fried et al. using data from the Cardiovascular Health Study (CHS) (2). Based on the Fried criteria, a wide prevalence of frailty has been reported among community-dwelling people aged 65 years and older, ranging from 4% to 27% (7, 8). In Japan, with a rapidly increasing aging population, the overall prevalence of frailty was 7.4%, with a similar prevalence in men (7.6%) and women (8.1%) (9). These prevalence rates increased with advancing age (1.9%, 3.8%, 10.0%, 20.4%, and 35.1% for people aged 65 to 69, 70 to 74, 75 to 79, 80 to 84, and 85 or older, respectively) (9).
In the past several decades, both life and health expectancy have increased in many countries. In Japan, the average life expectancy was 81.3 years for men and 87.3 years for women in 2018, according to data from the Ministry of Health. There may be improvement in physical health status among older adults based on increased life and health expectancy. Although previous studies indicated the prevalence of frailty in a large cohort or meta-analysis, no studies focused on trends in the prevalence of frailty and assessment years.
This study performed meta-analyses using data from the National Center for Geriatrics and Gerontology’s Integrated Longitudinal Studies on Aging in Japan (ILSA-J), a collection of 13 longitudinal cohort studies on aging in Japan involving community-dwelling older adults, to test whether the age-specific prevalence of frailty changed in Japan between 2012 and 2017.

 

Methods

Data Sources

This study performed meta-analyses using ILSA-J data on frailty. The ILSA-J included a total of 13 longitudinal cohort studies conducted throughout Japan (Table 1). Studies were considered eligible for inclusion in the present analysis if they assessed physical frailty status and prevalence of frailty in the sample using the Fried criteria (2) (e.g., slowness, weakness, exhaustion, low activity, and weight loss). Of the 13 cohort studies, 7 (total n = 10312; 4611 men and 5701 women) were analyzed for 2012 (±1 year), and 8 (total n = 7010; 2662 men and 4348 women) were analyzed for 2017 (±1 year). Finally, only 10 of the 13 cohort studies in the ILSA-J project were included in this meta-analysis, because 3 cohort studies did not provide data on frailty status in 2012 and 2017.

Table1
Characteristics of the cohort studies included in the meta-analysis

 

Main Outcome Measures and Operational Definition of Frailty

The main outcome measures in this study were the prevalence of frailty status and the five frailty sub-items (%). This study determined physical frailty status according to the 5 criteria of physical frailty suggested by the Japanese version of the CHS (J-CHS) (10, 11) and a slightly revised criterion: weight loss, slowness, weakness, exhaustion, and low activity. Participants whose responses did not correspond to any of these target criteria were considered to be robust; those who responded positively for 1 or 2 criteria were considered pre-frail; and those with 3 or more positive criteria responses were considered frail.
Although all the cohort studies included in the current meta-analysis used the same 5 criteria to assess frailty status, there were differences in the subcriteria (Appendix table 1). The 5 criteria defining physical frailty were assessed as follows. Weight loss was identified by a response of “yes” to the question (12), “Have you lost 2 kg or more in the past 6 months?” Slowness was identified by a normal walking speed of <1.0 m/s (10). Weakness was identified according to grip strength of the subject’s dominant hand: <26 kg for men and <18 kg for women (13). Exhaustion was identified by a response of “yes” to the question (12), “In the last 2 weeks, have you felt tired for no reason?” Low activity was identified by a response of “no” to both the following questions (10): “Do you engage in moderate levels of physical exercise or sports aimed at health?” and “Do you engage in low levels of physical exercise aimed at health?”

Data Collection

All ILSA-J cohort studies were approved by the ethics committee of the relevant university or institute. Among the 13 total cohort studies, those that assessed frailty provided data on the prevalence of frailty status (frailty, pre-frailty, and robust) and the 5 frailty subitems for meta-analyses. Thus, no author of the present study could access participants’ individual data.

Statistical Analysis

A two-step approach was used in the current study. First, we obtained the frailty prevalence in each cohort study separately, then, we calculated the combined prevalence using meta-analysis. The prevalence rates of frailty and pre-frailty for the years 2012 and 2017 were calculated by age group and gender. The 5 frailty items were also included to calculate prevalence. The present meta-analysis used a two-step approach. First, Cochran’s Q test was used to assess the presence of heterogeneity across cohorts, indicated by p<0.05, and I2 statistic values of 25%, 50%, and 75% indicated low, moderate, and high degrees of heterogeneity, respectively (14). Then, prevalence and 95% confidence intervals (CIs) were calculated for frailty and pre-frailty using a random-effects model if heterogeneity was present (p<0.05) and a fixed-effects model if heterogeneity was absent based on Cochran’s Q test (9). In addition, we performed a sensitivity analysis restricting the meta-analysis to surveys performed at both time-points, 2012 and 2017. Statistical analyses were completed using Comprehensive Meta-Analysis software (Version 3; Biostat, Englewood, NJ, USA).

 

Results

Table 2 presents the data on the presence of heterogeneity across cohorts and the prevalence of physical frailty among each age group in 2012 and 2017. There was a slight decrease (1.7%) in overall prevalence of physical frailty between 2012 and 2017. The overall prevalence of physical frailty was 7.0% (95% CI 5.4-9.0%) in 2012 and 5.3% (95% CI 4.3-6.6%) in 2017. The sensitivity analysis restricted to surveys with data at both time-points (2012 and 2017) provided similar results to the main analysis (Appendix table 2). Greater decreases in the prevalence of frailty were found in adults aged 75 years and older. Specifically, in 2012, the prevalence of frailty was 7.4% in the 75-79 age group, 12.6% in the 80-84 group, and 23.2% in the 85-89 group. In 2017, a 3.0% decrease was found in the 75-79 age group, a 4.2% decrease in the 80-84 group, and a 6.2% decrease in the 85-89 group.

Table 2
Prevalence of physical frailty by age group

 

Among men, frailty prevalence increased with advancing age in both 2012 and 2017. In 2012, prevalence was 6.3% in the 75-79 age group, 9.9% in the 80-84 group, and 24.6% in the 85-89 group ; in 2017, a decrease of 3.1% was found in the 75-79 age group (prevalence of 3.2%), 3.1% in the 80-84 group (prevalence of 6.8%), and 8.2% in the 85-89 group (prevalence of 16.4%).
Similar trends were observed in women. The prevalence of frailty in 2012 was 8.1% in the 75-79 age group, 14.8% in the 80-84 group, and 26.3% in the 85-89 group. In 2017, a decrease of 3.1% was found in the 75-79 age group (prevalence of 5.0%), 5.4% in the 80-84 group (prevalence of 9.4%), and 8.7% in the 85-89 group (prevalence of 17.6%).
The gender-stratified prevalence of physical frailty subitems is shown in Tables 3 and 4. Regardless of gender, slight decreases (less than 5%) in the subitems were found between 2012 and 2017 among young old groups (ages 65-69 and 70-74), with the exception of low activity in men aged 65-69 and women aged 70-74. Differing trends between men and women were found among old groups (ages 75-79, 80-84, and 85-89). In men, subitems with greater decreases (more than 5%) included exhaustion, which decreased 6.0% in the 75-79 age group, 5.2% in the 80-84 group, and 8.9% in the 85-89 group; slowness, which decreased 7.7% in the 85-59 group; and low activity, which decreased 7.2% in the 85-89 group).

Table 3
Prevalence of physical frailty components (Men)

Note. Sample sizes for 2012 age groups were as follows: 65-69, n=1540 (6 studies); 70-74, n=1434 (6 studies); 75-79, n=942 (6 studies); 80-84, n=519 (6 studies); 85-89, n=176 (6 studies). Sample sizes for 2017 age groups were as follows: 65-69, n=357 (5 studies); 70-74, n=629 (6 studies); 75-79, n=882 (7 studies); 80-84, n=565 (7 studies); 85-89, n=229 (7 studies).

Table 4
Prevalence of physical frailty components (Women)

Note. Sample sizes for 2012 age groups were as follows: 65-69, n=1808 (6 studies); 70-74, n=1518 (6 studies); 75-79, n=1205 (7 studies); 80-84, n=892 (7 studies); 85-89, n=278 (7 studies). Sample sizes for 2017 age groups were as follows: 65-69, n=835 (6 studies); 70-74, n=1115 (7 studies); 75-79, n=1400 (8 studies); 80-84, n=756 (8 studies); 85-89, n=242 (7 studies).

 

Compared with men, women were found to have decreased prevalence in many components. In the 75-79 age group, all components expect for weakness decreased (weight loss, 9.7%; slowness, 5.8%; exhaustion, 7.3%; low activity, 6.4%). All components decreased in the 80-84 and 85-89 groups (weight loss, 7.5% and 8.1%, respectively; slowness, 12.1% and 16.6%; weakness, 6.1% and 5.5%; exhaustion, 9.3% and 5.8%; low activity, 5.4% and 5.9%).

 

Discussion

This study performed meta-analyses using data from ILSA-J cohort studies and showed that the prevalence of frailty tended to decrease in 2017 compared to 2012, especially in adults 75 years and older. The sensitivity analysis confirmed the main findings and indicates that this increases the robustness of the findings.
A recent systematic review of articles published in 28 countries estimated the global incidence of frailty among community-dwelling adults (15). Among robust individuals who survived a median follow-up of 3.0 years, 13.6% became frail, with a pooled incidence rate of 43.4 cases per 1000 person-years (15); incidence rates varied by diagnostic criteria and country income level. Previous systematic review and meta-analysis studies have also suggested variation in the prevalence of frailty based on diagnostic criteria (16), country income level (17), and residential environment (18, 9). Additionally, the prevalence of frailty among community-dwelling older adults has been reported to differ based on race (9, 19). Therefore, the influences of those characteristics should be considered when discussing the prevalence of frailty and prevention strategies.
Most systematic review and meta-analysis studies that examine the prevalence of frailty include articles published after 2000. Worldwide, there were 901 million people aged 60 years or over in 2015, an increase of 48% over the global total of 607 million older people in 2000 (20). The global number of people aged 60 years or over increased by 68% in urban areas, compared to 25% in rural areas, from 2000 to 2015 (20). In Japan, approximately 12% of the population was 65 years or older in 1990, about the same as the total in the USA in 1990 (21). By 2010, the 65 and older population in Japan doubled, rising from 15 million to 29 million and comprising 23% of the total population, the highest proportion in the world (21). The percentage rose to over 28% in 2019. Although the number of older people in Japan is increasing rapidly, their latent capabilities and background factors can be changed. Health-related measures among Japanese community-dwelling older adults from 2007 to 2017 indicate that a phenomenon of “rejuvenation” is occurring among the new generation of older Japanese adults (22). In the United States, dementia declined significantly between 2000 and 2012, and one associated factor was an increase in educational attainment (23). Thus, better change in older adults’ latent capabilities and background factors may lead to a decrease in the prevalence of frailty.

Several important factors, such as comorbidities, low socioeconomic position, poor diet, and sedentary lifestyle, increase the risks of frailty (24). Some of these are modifiable. Therefore, it may be possible to reduce the prevalence of frailty by controlling or improving risk factors. Although this study’s meta-analyses had a relatively short observational term of 5 years, decreasing trends in the prevalence of frailty may become clearer based on long-term observation.
Among 5 components of frailty, weakness and slowness may have greater impacts on increased risk of disability (11, 25). In this study, there was a decreasing trend in the prevalence of almost all items, however there was less change in the prevalence of weakness compared with other items. No change or a slight increase in the prevalence of weakness was observed in men in all age groups, whereas for women, only a decrease in the 80 years and older group was observed.
This study found significant differences in frailty prevalence between men and women. Older women, especially in the old-old population (aged 75 years and over), were found to have decreased prevalence in almost all frailty items. Recently, the ILSA-J reported differences between the years 2007 (± 2 years) and 2017 (± 2 years) in several indices (e.g., body composition, walking speed, and grip strength) that are related to the health and functioning of older adults (22). Better health status and a slower decline in most of the health-related measures were observed in 2017 compared with a decade ago. Japanese older adults living in the community have been consistently increasing their walking speed over the past 25 years, and the improvement in walking speed is especially striking in women (26, 27). In a previous study that analyzed IADL performance in 17,680 older adults with dependency in basic ADL, the men were found to have 3 times higher prevalence of poor performance of IADL compared with the women (28). Older adult women may reduce age-related decline in functional level by increasing or maintaining the multidimensional aspects of their lives, such as social and leisure time activities. In addition, our data showed higher study participation rates in women than in men for both 2012 and 2017. These findings may indicate that women have more interest in their health compared with men. Increased interest in personal health may prevent or delay the progression of frailty.
Consistent “female disadvantage” in physical performance among older adults has been demonstrated (29). One previous study with 4683 Japanese nondisabled community-dwelling older adults demonstrated increasing significant gender differences in one-legged stance performance and gait speed with age. In contrast, gender differences significantly decreased in hand-grip strength with increasing age (30). In other words, strength may be more affected by advancing age in older adult men than in older adult women. Thus, preventing or delaying the progression of weakness with age may be difficult in men. Weakness was determined according to grip strength of the subject’s dominant hand, with cutoff values of 26 kg for men and 18 kg for women. Although the average values of grip strength may decrease slightly in new generation of Japanese older adults (22), the changes may not reach sufficient levels, indicating that this component is less susceptible to generation changes than the others.
Several limitations of the present study should be noted. First, the meta-analyses in the present study used cross-sectional data from 7 cohort studies in 2012 (±1 year) and 8 cohort studies in 2017 (±1 year). Therefore, the study design was not longitudinal, following the same individuals and cohorts. Second, the current study used data from 2012 and 2017, analyzing the trends in prevalence over a period of 5 years. This may be too short to fully examine trends of change. Third, the number of participants varied widely by age group, especially participants in the 85 and older group, which had a relatively small sample size (fewer than 200 men in 2012). Finally, assessment protocols were dependent on each cohort study, not unified across all cohorts. We believe that the cohort studies included in the current meta-analysis had high data quality, but not all of the studies were designed using probabilistic samples. For instance, recruitment methods (e.g., random sampling, direct mail to all citizen, and volunteers) varied. In addition, more knowledge on the prevalence of the risk factors for frailty and those components, such as comorbidities, nutritional status, and cognitive function will support the phenomenon of decreasing frailty in the new generation of Japanese older adults.
Although this study examines a relatively short period of time (5 years), it has several strengths. First, it is, to our knowledge, the first study to describe trends in the prevalence of frailty. Second, the prevalence of frailty and subitems were assessed through a meta-analysis of 10 Japanese cohort studies, which provided data from 287 to 4779 older adults. Third, frailty status was assessed not only by questionnaires but also by objective measures such as grip strength and walking speed; therefore, are results may reflect functional status.
In conclusion, the current meta-analyses suggested that the prevalence of frailty has shown a decreasing trend in the new generation of Japanese older adults, especially in adults aged 75 years and older. This finding may indicate physical rejuvenation in older adults. Progression of this trend may improve health expectancy and shorten the gap between life expectancy and health expectancy. Future studies with more long-term follow-up period and a larger sample will be needed to clarify the trends in the prevalence of frailty among community-dwelling older adults.

 

Acknowledgement: This work was funded by the National Center for Geriatrics and Gerontology (Choujyu 29-42). We are grateful to all the participants for their valuable contribution to this study. The authors thank Dr. Katsunori Kondo of the National Center for Geriatrics and Gerontology & Chiba University, Dr. Yoshinori Fujiwara of the Tokyo Metropolitan Institute of Gerontology, and Dr. Shuichiro Watanabe of J.F. Oberlin University who are members of the ILSA-J project for their contributions in study progression. We also thank to Dr. Takehiko Doi of the National Center for Geriatrics and Gerontology, Dr. Tomoki Tanaka of the Institute of Gerontology, The University of Tokyo, Dr. Hisashi Kawai, Dr. Yu Nofuji, Dr. Takumi Abe and Dr. Susumu Ogawa of the Tokyo Metropolitan Institute of Gerontology, Dr. Yu Taniguchi of National Institute for Environmental Studies, and Dr. Yutaka Watanabe of the Faculty of Dental Medicine, Hokkaido University for their helpful supporting data sharing process and Ms. Shiho Fujii of the National Center for Geriatrics and Gerontology for her help in preparing the tables.
Conflicts of Interest: None declared.
Ethics Statement: This study was conducted in compliance with the current laws of Japan.
Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

SUPPLEMENTARY MATERIAL1

SUPPLEMENTARY MATERIAL2

References

1. Chen X, Mao G, Leng SX. Frailty syndrome: an overview. Clin Interv Aging 2014;9:433-41. doi: 10.2147/CIA.S45300
2. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-56. doi: 10.1093/gerona/56.3.m146
3. Ensrud KE, Ewing SK, Taylor BC, Fink HA, Cawthon PM, Stone KL, et al. Comparison of 2 frailty indexes for prediction of falls, disability, fractures, and death in older women. Arch Intern Med 2008;168(4):382-9. doi: 10.1001/archinternmed.2007.113
4. Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9868):752-62. doi: 10.1016/S0140-6736(12)62167-9
5. Pereira AA, Borim FSA, Aprahamian I, Neri AL. Comparison of two models of frailty for the prediction of mortality in Brazilian community-dwelling older adults: The FIBRA study. J Nutr Health Aging 2019;23(10):1004-10. doi: 10.1007/s12603-019-1264-0
6. Dent E, Morley JE, Cruz-Jentoft AJ, Woodhouse L, Rodriguez-Manas L, Fried LP, et al. Physical frailty: ICFSR international clinical practice guidelines for identification and management. J Nutr Health Aging 2019;23(9):771-87. doi: 10.1007/s12603-019-1273-z
7. Collard RM, Boter H, Schoevers RA, Oude Voshaar RC. Prevalence of frailty in community-dwelling older persons: A systematic review. J Am Geriatr Soc. 2012;60(8):1487-92. doi: 10.1111/j.1532-5415.2012.04054.x
8. Choi J, Ahn A, Kim S, Won CW. Global prevalence of physical frailty by Fried’s criteria in community-dwelling elderly with national population-based surveys. J Am Med Dir Assoc 2015;16(7):548-50. doi: 10.1016/j.jamda.2015.02.004
9. Kojima G, Iliffe S, Taniguchi Y, Shimada H, Rakugi H, Walters Prevalence of frailty in Japan: A systematic review and meta-analysis. J Epidemiol 2017;27(8):347-53. doi: 10.1016/j.je.2016.09.008
10. Shimada H, Makizako H, Doi T, Yoshida D, Tsutsumimoto K, Anan Y, et al. Combined prevalence of frailty and mild cognitive impairment in a population of elderly Japanese people. J Am Med Dir Assoc 2013;14(7):518-24. doi: 10.1016/j.jamda.2013.03.010
11. Makizako H, Shimada H, Doi T, Tsutsumimoto K, Suzuki T. Impact of physical frailty on disability in community-dwelling older adults: A prospective cohort study. BMJ open 2015;5(9):e008462. doi: 10.1136/bmjopen-2015-008462
12. Fukutomi E, Okumiya K, Wada T, Sakamoto R, Ishimoto Y, Kimura Y, et al. Relationships between each category of 25-item frailty risk assessment (Kihon Checklist) and newly certified older adults under Long-Term Care Insurance: A 24-month follow-up study in a rural community in Japan. Geriatr Gerontol Int 2015;15(7):864-71. doi: 10.1111/ggi.12360
13. Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: Consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc 2014;15(2):95-101. doi: 10.1016/j.jamda.2013.11.025
14. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003;327(7414):557-60. doi: 10.1136/bmj.327.7414.557
15. Ofori-Asenso R, Chin KL, Mazidi M, Zomer E, Ilomaki J, Zullo AR, et al. Global incidence of frailty and prefrailty among community-dwelling older adults: A systematic review and meta-analysis. JAMA Netw Open 2019;2(8):e198398. doi: 10.1001/jamanetworkopen.2019.8398
16. He B, Ma Y, Wang C, Jiang M, Geng C, Chang X, et al. Prevalence and risk factors for frailty among community-dwelling older people in China: A systematic review and meta-analysis. J Nutr Health Aging 2019;23(5):442-50. doi: 10.1007/s12603-019-1179-9
17. Siriwardhana DD, Hardoon S, Rait G, Weerasinghe MC, Walters KR. Prevalence of frailty and prefrailty among community-dwelling older adults in low-income and middle-income countries: A systematic review and meta-analysis. BMJ open 2018;8(3):e018195. doi: 10.1136/bmjopen-2017-018195
18. Kojima G. Prevalence of frailty in nursing homes: A systematic review and meta-analysis. J Am Med Dir Assoc 2015;16(11):940-5. doi: 10.1016/j.jamda.2015.06.025
19. Da Mata FA, Pereira PP, Andrade KR, Figueiredo AC, Silva MT, Pereira MG. Prevalence of frailty in Latin America and the Caribbean: A systematic review and meta-analysis. PLoS One 2016;11(8):e0160019. doi: 10.1371/journal.pone.0160019
20. United Nations. Department of Economic and Social Affaris, Population Dynamics. World Population Prospects. http://esa.un.org/unpd/wpp/DataQuery/ Accessed 18 December 2019.
21. Tamiya N, Noguchi H, Nishi A, Reich MR, Ikegami N, Hashimoto H, et al. Population ageing and wellbeing: Lessons from Japan’s long-term care insurance policy. Lancet 2011;378(9797):1183-92. doi: 10.1016/S0140-6736(11)61176-8
22. Suzuki T, Nishita Y, Jeong S, Shimada H, Otsuka R, Kondo K, et al. Are Japanese older adults rejuvenating? Changes in health-related measures among older community dwellers in the last decade. Rejuvenation Res 2020; in press. doi: 10.1089/rej.2019.2291
23. Langa KM, Larson EB, Crimmins EM, Faul JD, Levine DA, Kabeto MU, et al. A comparison of the prevalence of dementia in the United States in 2000 and 2012. JAMA Intern Med 2017;177(1):51-58. doi: 10.1001/jamainternmed.2016.6807
24. Hoogendijk EO, Afilalo J, Ensrud KE, Kowal P, Onder G, Fried LP. Frailty: implications for clinical practice and public health. Lancet 2019;394(10206):1365-75. doi: 10.1016/S0140-6736(19)31786-6
25. Shimada H, Makizako H, Doi T, Tsutsumimoto K, Suzuki T. Incidence of disability in frail older persons with or without slow walking speed. J Am Med Dir Assoc 2015;16(8):690-6. doi: 10.1016/j.jamda.2015.03.019
26. Suzuki T, Kwon J. Health status of older adults living in the community in Japan: Recent changes and significance in the super-aged society. Geriatr Gerontol Int 2018;18(5):667-677. doi: 10.1111/ggi.1326627. Suzuki T. Health status of older adults living in the community in Japan: Recent changes and significance in the super-aged society. Geriatr Gerontol Int. 2018 May;18(5):667-77.
28. Tomioka K, Kurumatani N, Hosoi H. Age and gender differences in the association between social participation and instrumental activities of daily living among community-dwelling elderly. BMC Geriatr 2017;17(1):99. doi: 10.1186/s12877-017-0491-7
29. Sialino LD, Schaap LA, van Oostrom SH, Nooyens ACJ, Picavet HSJ, Twisk JWR, et al. Sex differences in physical performance by age, educational level, ethnic groups and birth cohort: The Longitudinal Aging Study Amsterdam. PLoS One 2019;14(12):e0226342. doi: 10.1371/journal.pone.0226342
30. Seino S, Shinkai S, Fujiwara Y, Obuchi S, Yoshida H, Hirano H, et al. Reference values and age and sex differences in physical performance measures for community-dwelling older Japanese: A pooled analysis of six cohort studies. PLoS One 2014;9(6):e99487. doi: 10.1371/journal.pone.0099487