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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;in press
Published online January 18, 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.

 

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SENSOR-BASED FRAILTY ASSESSMENT IN SURVIVORS OF CHILDHOOD CANCER: A PILOT STUDY

 

N.J. Krnavek1, S. Ajasin2, E.C. Arreola2, M. Zahiri1, M. Noun1, P.J. Lupo2, B. Najafi1, M.M. Gramatges2

1. Baylor College of Medicine, Department of Surgery, Division of Vascular Surgery and Endovascular Therapy, USA; 2. Baylor College of Medicine, Department of Pediatrics, Section of Hematology and Oncology, USA
Corresponding author: Maria Monica Gramatges, Baylor College of Medicine, Department of Pediatrics, Feigin Center, 1102 Bates St, Suite 1200, Houston, Texas, 77030, (p) 832-824-4678; (f) 832-825-4651, gramatge@bcm.edu

J Frailty Aging 2020;in press

Published online December 23, 2020, http://dx.doi.org/10.14283/jfa.2020.71

 


Abstract

Background: Survivors of childhood cancer (CCS) are at risk for early aging and frailty. Frailty in CCS has been assessed with established clinical criteria, a time-intensive approach requiring specialized training. There is an unmet need for cost-effective, rapid methods for assessing frailty in at-risk adolescent and young adult (AYA) CCS, which are scalable to large populations. Objectives: To validate a sensor-based frailty assessment tool in AYA CCS, compare frailty status between CCS and controls, and assess the correlation between frailty and number of CCS comorbidities. Design, Setting, and Participants: Mean frailty index (MFI) was assessed by a frailty wrist sensor in 32 AYA CCS who were ≥1 year off therapy and in remission. Results were compared with 32 AYA controls without cancer or chronic disease. Measurements: Frailty assessments with and without a simultaneous cognitive task were performed to obtain MFI. Results were compared between cases and controls using a Student t test, and the number of pre-frail/frail subjects by Chi Square test. The contribution of radiation therapy (RT) exposure to MFI was assessed in a sub-analysis, and the correlation between the number of comorbidities and MFI was measured using the Pearson method. Results: MFI was strongly correlated with gait speed in AYA CCS. CCS were more likely to be pre-frail than controls without cancer history (p=0.032), and CCS treated with RT were more likely to be pre-frail than CCS not treated with RT (p<0.001). The number of comorbidities was strongly correlated with MFI (ρ=0.65), with a 0.028 increase in MFI for each added condition (p<0.001). Conclusions: Results from this study support higher risk for frailty among CCS, especially those with multiple comorbidities or who were treated with RT. A wrist-worn sensor-based method is feasible for application in AYA CCS, and provides an opportunity for cost-effective, rapid screening of at-risk AYA CCS who may benefit from early interventions.

Key words: Survivorship, frailty, slowness, weakness.


 

Introduction

Over 80% of children diagnosed with cancer survive their disease (1), but survivors of childhood cancer (CCS) are at risk for late effects including early onset aging and frailty (2-10). An increase in frailty accompanies physiologic aging, affecting ~9% of persons >65 years (11) and 25-40% of persons >80 years (12). Frailty identifies individuals more vulnerable to adverse health outcomes (13) and predicts risk for early mortality (14, 15). Compared with sibling controls, CCS are more likely to report poor general health, functional impairment, and activity limitations with a prevalence that increases with age (16, 4, 3). Among 1,922 adult CCS with a mean age of 33.6 +/- 8.1 years, up to 13.1% were frail and up to 31.5% were pre-frail when assessed by the Fried clinical criteria, similar to the frailty prevalence in the general population that is at least three decades older (5). Frailty in CCS has been associated with exposure to cranial radiation and higher doses of abdominal or pelvic radiation (17).
In addition to the Fried clinical criteria, a number of methods assess frailty by clinical or survey-based assessment of factors such as weight loss, exhaustion, poor grip strength, slow gait speed, low physical activity, chronic health conditions, functional impairments, clinical symptoms, and behavior/psychological factors such as poor sleep quality or mood (18). These methods were largely developed for the frail older patient and validated in geriatric populations. Given the high prevalence of frailty in adolescent and young adult (AYA) CCSs, there is an unmet need for efficient, reliable, and low-cost methods that assess frailty across the lifespan.
We conducted a pilot study in AYA CCS leveraging a sensor-based upper extremity frailty assessment tool that has a strong correlation with well-established clinical and survey-based methods of frailty assessment in adults (sensitivity and specificity of 85% and 93% for predicting pre-frailty and 100% sensitivity and specificity for predicting frailty compared with the Fried criteria, sensitivity and specificity of 78% and 82% compared with a validated modified Rockwood questionnaire, and good correlation (ρ = 0.78) with the 6 minute walk test) (19-22). The Fried criteria and Rockwood questionnaire are considered gold standards for measuring frailty in elderly populations, but include components that are not appropriate for application to AYA populations. Therefore, our first objective was to validate the frailty assessment tool by determining correlation between mean frailty index and gait speed, a component of the Fried criteria, in AYA CCS. We then 1) tested feasibility of applying the frailty assessment tool in AYA CCS in an outpatient setting, 2) compared mean frailty index and frailty status between CCS and controls and CCS with or without high-risk treatment exposures (i.e. radiation), and 3) assessed the correlation between mean frailty index and the number of comorbidities present at the time of enrollment.

 

Methods

Study Population

For the frailty meter validation, eligible cases were recruited from the Texas Children’s Cancer and Hematology Centers (TCCC), and included CCS who were ≥15 years old, English-speaking, ≥1 year off therapy, and in remission.
For the feasibility assessment and comparisons between cases and controls, cases were recruited from CCS who met the same above-described eligibility criteria, but were non-overlapping with subjects recruited to the validation step. Controls were ≥15 years old, without cancer history, and recruited from routine well visit patients at a Texas Children’s Pediatric Clinic or Baylor Clinic. For CCS, comorbidities present at the time of enrollment were abstracted from the electronic medical record (EMR). Comorbidities were defined as chronic health conditions listed as an active problem in the EMR Problem List, present for at least one year (determined by problem start date) and requiring ongoing medical care (determined by scheduled subspecialty clinic visits). All cases and controls provided informed consent, as well as assent when applicable, for participation and were enrolled to an IRB-approved research protocol. This research was conducted in accordance with the ethical standards of the Baylor College of Medicine Institutional Review Board (H-38994) and with the 1964 Helsinki declaration and its later amendments.

Frailty Assessment

Mean frailty index (MFI) was determined for each arm by trained personnel using a wrist-worn frailty meter (Figure 1) (26). A wearable sensor is placed on the patient’s wrist, and, while seated, the participant performs a repetitive elbow flexion and extension task as quick and steadily as possible for 20 seconds (single task assessment). The dual task assessment adds a cognitive load to the single task, and in older adults leads to worse performance and higher MFI scores, an effect that is most pronounced among adults with cognitive impairment (27). During the dual task assessment, the subject counts down from a random number provided by the test administrator while performing the task (27). The sensor contains a tri-axial gyroscope that estimates three-dimensional angular velocity of the upper arm and forearm segments. Outcomes measures representing the kinematics and kinetics of elbow flexion, including speed, rise time, and flexion number per 20-second interval (indicators of slowness); flexibility (indicator of rigidity); power and moment (indicators of weakness); speed variability (indicator of steadiness); and speed reduction (indicator of exhaustion) are derived from the angular velocity, anthropometric data, and sex, and captured wirelessly through a tablet device (BioSensics, LLC, Newton, MA, USA). MFI is derived from these outcome measures using an optimized linear regression model previously described by Lee et al., with a numeric output on a continuous scale between 0 and 1 (26). In addition to the MFI, these outcome measures quantify slowness, weakness, and exhaustion (20). Participants completed the single and dual task assessments for both the dominant and non-dominant upper extremities in an average time of just under 5 minutes.

Figure 1
Upper extremity frailty meter sensor and example output. Mean frailty index (MFI) is derived from the measures obtained, in the context of sex, BMI, height, and weight.

 

Gait Speed Assessment

For the validation step, gait speed was determined by the Timed Up and Go (TUG) test (23), which is both reliable and reproducible in AYAs and for which normative values in this age range are available (24, 25). Briefly, the time (in seconds) required for a subject to rise from a standard armchair, walk a distance of 3 meters, turn, walk back to the chair, and sit down again is measured for each subject.

Quality of Life Assessment

Given the well-described inverse relationship between frailty and quality of life (28), and evidence for impact of frailty on quality of life among CCS (29), we included the PROMIS measure to assess this outcome in conjunction with frailty assessment in our case-control comparisons. Each participant completed the PROMIS questionnaire, a reliable measure of patient-reported health status for mental and physical well-being that has been validated in both children and adults (30). Metrics included in this study were the PROMIS Global Physical Health, Global Mental Health, and Global Health.

Data Analysis

For the validation step, the relationship between MFI and TUG time was determined by the Pearson correlation test. For the subsequent comparisons, participants were classified based on pre-defined MFI thresholds obtained from the dominant arm as robust (MFI <0.20), pre-frail (0.20≤ MFI <0.35), or frail (MFI ≥0.35), using the benchmarks proposed by Rockwood et al (31). After confirming that the data were normally distributed, the mean MFI and MFI subcomponents were compared between cases and controls using a Student t test, and the number of pre-frail/frail subjects by a Chi Square test. For CCS, the relationship between the number of comorbidities and MFI was determined by linear regression, and correlation was tested using the Pearson method. Factors previously associated with frailty include any exposure to cranial radiation in both sexes and abdominal/pelvic radiation in excess of 34Gy/40Gy, respectively, in males) (17). Therefore, we conducted a sub-analysis to compare outcomes between CCS who met criteria for at-risk RT exposure to CCS who did not meet criteria for at-risk RT. PROMIS data were categorized by T score and established cut points for excellent, very good, good, fair, and poor, and then analyzed by the Chi Square test (32).

 

Results

Seven CCS were recruited for the validation step (two females and five males), mean age of 22.8 years (15-30 years). The mean for the Timed Up and Go (TUG) was 7.87 seconds (range, 5.23-10.12 seconds). Results were comparable to age-normative values for all but two subjects, who each exceeded the upper bound of the 95% confidence interval for the mean by 0.68 seconds and by 1.15 seconds. MFI was 0.19, range 0.13-0.25, and a strong correlation was observed between MFI and TUG time (ρ =0.83, p=0.02).
There were 48 potentially eligible CCS seen for an office visit in the TCCC Late Effects Clinic between June 29 and July 31, 2019. Subjects were recruited four days per week, so that 34 CCS were approached for participation, of which 32 consented and two declined (94% participation rate). All controls who were approached consented to study, so that there were 32 CCS and 32 age-comparable controls that were enrolled. The distribution of primary diagnoses among CCS were as follows: leukemia/lymphoblastic lymphoma, 20; germ cell tumor, 1; Hodgkin/non-Hodgkin lymphoma, 2; rhabdomyosarcoma, 2; Wilm’s tumor, 2; central nervous system tumor, 3; retinoblastoma, 1; ovarian cancer, 1. Participants were a mean of 9.8 years since completion of cancer treatment (median 8.0 years, range 1-36 years). Table 1 shows the distribution of baseline characteristics among CCS and controls.

Table 1
Distribution of demographic characteristics in CCSs and controls

 

The mean MFI for the dominant arm, both single and dual tasks, was higher among CCS than controls (p=0.002 and p<0.001, respectively, Table 2). The difference in MFI was primarily driven by the weakness and slowness components of MFI, rather than exhaustion. For both the single and dual task assessments in the dominant arm, CCS were more likely to be pre-frail than controls (p=0.032 and p=0.003, respectively). None of the participants met the pre-determined MFI cutoff criteria for frailty.

Table 2
Mean Frailty Index, frailty subcomponents, quality of life, fatigue assessment in CCSs compared with controls

* MFI thresholds for pre-frail and frail were pre-determined from the benchmarks proposed by Rockwood et al, (31) i.e. robust: MFI <0.20, pre-frail: 0.20≤ MFI <0.35, and frail: MFI ≥0.35. All results are displayed as a mean score ± SD

 

Out of 32 CCS, 13 had at-risk RT exposures: 12 were treated with cranial radiation (12-55.8 Gy), and one male was treated with pelvic RT (50.4 Gy). No females were treated with abdominal or pelvic RT. In the single task assessment, CCS with at-risk RT exposures had a higher MFI (p<0.001) and were more likely to be pre-frail (p<0.001) than CCS without RT exposure (Table 2). As expected, the 12 CCS whose treatment included CRT had a significantly higher MFI than CCS not exposed to CRT, and though there was some evidence of dose-dependence, this difference was not statistically significant (p=0.15, Table 3). No substantial difference in MFI was noted after the addition of a cognitive load (dual task assessment) in controls and cases, regardless of CRT exposure (Tables 2 and 3).

Table 3
Dominant arm, single and dual task MFI determined in controls compared with CCSs without (n=20) and with (n=12) history of exposure to cranial radiation (CRT). Mean MFI increased with increasing dose of CRT

All results are displayed as mean score ± SD

 

Eleven CCS had no comorbidities, 10 had one condition, 5 had two conditions, 4 had three conditions, 1 had four conditions, and 1 had six conditions, described in more detail in Figure 2. The number of comorbidities was correlated with MFI (ρ = 0.65), with a 0.028 increase in MFI for each added condition (p<0.001).
No significant differences in the proportion of subjects reporting ‘poor’ or ‘fair’ vs. ‘good,’ very good,’ or ‘excellent’ global health, global mental, or global physical health status were observed between controls and CCS.

Figure 2
Distribution of chronic health conditions by system among CCS (n=32)

Cardiometabolic: congestive heart failure (1), hypertension (2), obesity (6); Endocrine: hypogonadism (1), hypothyroidism (2), primary ovarian failure (2), growth hormone deficiency (3); Vision/hearing: cataracts (2), severe visual impairment (2), hearing loss or tinnitus (3); Peripheral/Central nervous system: peripheral neuropathy (1), hemiparesis (1), chronic migraine (1), epilepsy (2); Musculoskeletal: arthritis (1), osteopenia/osteonecrosis (4); Neuropsychological: generalized anxiety disorder (2) major depressive disorder (2); Pulmonary: chronic lung disease (1), obstructive sleep apnea (1); Renal: chronic kidney disease (1); Hematological: chronic pancytopenia (1)

 

Discussion

There is considerable need for methods that rapidly, effectively, and inexpensively screen CCS for evidence of pre-frailty or frailty conferred by cancer treatment. To date, studies conducted in CCS have used the clinical Fried criteria, which is both time-consuming and requires training to administer. In elderly persons, the wrist-worn sensor-based method for frailty status determination has a strong correlation with frailty status determined by both the Fried criteria and the Rockwood Frailty Index (19-22), and is a strong predictor of adverse outcomes such as prolonged hospitalizations and prospective falls (35, 36, 27, 37). Given that this tool has largely been applied in older adult populations, we first validated its use in AYA CCS by demonstrating correlation between frailty status determined by wrist-worn sensor and gait speed.
Our study suggests that this method is feasible for application in the outpatient setting. In our pilot study, CCS were more likely to have a higher MFI and be pre-frail than controls, and CCS with at-risk RT exposures were more likely to have a higher MFI and be pre-frail than CCS without a history of at-risk RT, in line with prior reports (5). Of note, the mean age of CCS in this study was 20.5 years, so it is not surprising that no CCS met thresholds for frailty. CRT-exposed CCS showed no discernible difference in MFI with the addition of a cognitive load (dual task) compared with the single task, and compared with non-CRT-exposed CCS. The absence of an effect on MFI observed with addition of a cognitive load suggests that the dual task may be of less importance when assessing frailty in CCS. MFI in CCS was strongly correlated with the number of comorbidities, but the study was not powered to detect associations with diagnosis, treatment dose, or modality other than RT exposure.
Detection of pre-frailty is important, because it offers an opportunity for early intervention in an anticipated trajectory of continued physical decline. The frailty assessment tool described here is a safe, low cost, and time-efficient method, requiring less than 5 minutes to complete compared with the 10-20 minutes required for the Fried method (33, 34). Moreover, it is a stand-alone tool that requires minimal training to use, and does not require additional equipment such as a dynamometer, stopwatch, or 15 foot floor tape. Our pilot data suggest higher MFI in CCS, especially CCS treated with RT compared with controls, and support prospective application of this method to predict risk for morbidity and mortality in CCS, correlated with objective functional and biological measures.

 

Acknowledgements: The authors would like to thank the patients who participated in this study as well as their families.
Funding: This work was supported by the Texas Children’s Cancer and Hematology Centers.
Conflicts of Interest: None declared by the Authors.
Ethical Standards: This study was approved by the Baylor College of Medicine institutional review board, and conducted in accordance with the Helsinki Declaration of 1975, as revised in 2000.

 

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11. 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.
12. 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.
13. Macklai NS, Spagnoli J, Junod J, Santos-Eggimann B. Prospective association of the SHARE-operationalized frailty phenotype with adverse health outcomes: evidence from 60+ community-dwelling Europeans living in 11 countries. BMC Geriatr. 2013;13:3.
14. Chang SF, Lin PL. Frail phenotype and mortality prediction: a systematic review and meta-analysis of prospective cohort studies. Int J Nurs Stud. 2015;52(8):1362-74.
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17. Hayek S, Gibson TM, Leisenring WM, Guida JL, Gramatges MM, Lupo PJ et al. Prevalence and Predictors of Frailty in Childhood Cancer Survivors and Siblings: A Report From the Childhood Cancer Survivor Study. J Clin Oncol. 2019:JCO1901226.
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LETTER TO THE EDITOR: FRAILTY PHENOTYPE OF HOMEBOUND MONTREAL OLDER COMMUNITY DWELLERS DURING THE COVID-19 PANDEMIC: RESULTS OF A CROSS-SECTIONAL POPULATION STUDY

 

C.P. Launay1,2, L. Cooper-Brown2,3, V. Ivensky2,4, O. Beauchet1,2,5,6

1. Department of Medicine, Division of Geriatric Medicine, Sir Mortimer B. Davis – Jewish General Hospital and Lady Davis Institute for Medical Research, McGill University, Montreal, Quebec, Canada; 2. Centre of Excellence on Longevity of McGill integrated University Health and social services Network, Quebec, Canada; 3. Faculty of Medicine, McGill University, Montreal, Quebec, Canada; 4. Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada; 5. Dr. Joseph Kaufmann Chair in Geriatric Medicine, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; 6. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore

Corresponding Author: Olivier Beauchet, MD, PhD; Department of Medicine, Division of Geriatric Medicine, Sir Mortimer B. Davis – Jewish General Hospital, McGill University, 3755 chemin de la Côte-Sainte-Catherine, Montréal, QC H3T 1E2, Canada; E-mail: olivier.beauchet@mcgill.ca; Phone: (+1) 514-340-8222, #24741; Fax: (+1) 514-340-7547
J Frailty Aging 2020;
Published online December 22, 2020, http://dx.doi.org/10.14283/jfa.2020.69

 


Dear Editor,
Recently, Aubertin-Leheurdre & Rolland underscored issues and challenges related to the insufficient physical activity levels observed in the frail older population due to social distancing during the Coronavirus disease 2019 (COVID-19) pandemic (1). Social distancing is an effective intervention to limit the spread of COVID-19 (2). However, for older community dwellers social distancing implies homebound which may lead to a decline in physical activity, increased gait and balance disorders, cardiovascular disease burden and morality risk (1, 3, 4).
Frailty refers to a condition of vulnerability to physical and psychological stressors that exposes individuals to incident adverse health events, disabilities and death (5-7). There are two frailty phenotypes: physical and mental (6, 7). We suggested that frailty phenotypes may confer distinct risks for adverse outcomes to homebound older community dwellers. To explore this research hypothesis, there is a need to first gather information about homebound older adults’ physical and mental frailty phenotypes at the onset of confinement. Montreal (Quebec, Canada) is an urban area that is particularly affected by the COVID-19 pandemic, being, as of May 2020, the city with the highest number of confirmed COVID-19 cases in Canada (8). The confinement of Montreal’s older adults will be therefore lasting longer than initially anticipated.
A short assessment tool, known as “Évaluation SOcio-GÉRiatrique” (ESOGER), for Montreal’s older community-dwelling population has been designed in March 2020. ESOGER allows to screen both physical and mental frailty. The objective of the present study is to describe the clinical characteristics and frailty phenotype of Montreal’s older community dwellers, assessed with ESOGER after one month of being homebound.
Between April 20 and May 08, 2020, 879 older community dwellers were recruited to participate in this cross-sectional study. Selection criteria were: age ≥70 years, being homebound, understanding French and/or English and agreeing to participate in the study. ESOGER is a clinical assessment consisting of a digital questionnaire that includes close-ended questions exploring five complementary subdomains, including: 1) COVID-19 clinical symptomatology (i.e., fever ≥38°C/100F, cough, shortness of breath and other symptoms); 2) a frailty assessment performed using the 6-item brief geriatric assessment (BGA), 3) psychological stress using a verbal analogue scale (VAS) of anxiety ranging from 0 (i.e., no anxiety) to 10 (i.e., severe anxiety) (9). ESOGER can be filled out by health and social professionals, as well as by trained volunteers, through a phone call with older community dwellers or their caregivers. Participants were separated into 4 groups based on their frailty phenotype as per the 6-item BGA: no frailty, physical frailty (i.e., use of a walking aid), mental frailty (i.e., temporal disorientation associated with anxiety), and a combination of physical and mental frailty. Participants’ characteristics were summarized using frequencies and percentages. Between-group comparisons were performed using Chi-squared tests. P-values less than 0.001 were considered statistically significant because of multiple comparisons (n = 42). All statistics were performed using SPSS (version 24.0; SPSS, Inc., Chicago, IL). The study was approved by the Ethics Committee Of thé Jewish General Hospital (Montreal, Quebec, Canada).
The overall prevalence of frailty was 65.0%; the most prevalent type was physical frailty 38.3%, whereas the prevalence of mental frailty was 12.5%, and that of both frailties combined was 14.1% (Table 1). Participants identified as physically frail were older, used home support, and experienced polypharmacy at a higher rate than those with no frailty (P≤0.001) and those with mental frailty (P≤0.001). Participants combining both types of frailty took more medications compared to those with no frailty (P≤0.001) and had home support more often than those with mental frailty only (P≤0.001). There were no significant differences between groups for the other characteristics.

Table 1
Characteristics of participants separated into four groups based on their frailty phenotype (n=879)

*: based on Chi-squared test; †: Formal (i.e., health and/or social professionals) or informal (i.e., family and/or friends); ‡: Number of different medications taken daily ≥5; §: Older adults with at least 3 COVID-19 symptoms among fever ≥ 38°C /100°F, cough, shortness of breath and other symptoms; ¶: cane and rolling walker; #: Inability to give the month and/or year; **: Highest tertile of the verbal analogue anxiety scale score ranging from 0 (no anxiety) to 10 (severe anxiety).

 
These findings illustrate the high prevalence of frailty, especially of the physical phenotype, among homebound older community dwellers in Montreal. This result provides insight into the importance of prioritising preventive interventions that target insufficient physical activity in times of social distancing. Indeed, it is well known that older community dwellers with physical frailty are at increased risk for motor deconditioning and related adverse outcomes, which include muscle mass decline and increasingly unstable gait and balance, ultimately increasing the risk of falls and fractures (1). In this population, patient-centred care should include offering physical activity programs that take into account physical distancing measures (10). As suggested by Aubertin-Leheurdre & Rolland, innovative gerontechnology solutions such as exergames or web-based exercise programs may address the risk being homebound poses to older community dwellers (1).

Conflict of interest: The authors CPL, LCB, VI and OB report no disclosures relevant to the manuscript.

 

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6. 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:M146-156.
7. Kelaiditi E, Cesari M, Canevelli M, van Kan GA, Ousset PJ, Gillette-Guyonnet S, et al. Cognitive frailty: rational and definition from an (I.A.N.A./I.A.G.G.) international consensus group. J Nutr Health Aging. 2013;17:726-734.
8. Coronavirus Disease 2019 (COVID-19). Daily Epidemiology Update (Updated May 15, 2020, 2:00 PM ET). https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection.html?utm_campaign=gc-hc-sc-coronavirus2021-ao-2021-0005-9834796012&utm_medium=search&utm_source=google_grant-ads-107802327544&utm_content=text-en-434601690158&utm_term=%2Bcoronavirus#a1
9. Beauchet O, Chabot J, Fung S, Launay CP. Update of the 6-Item Brief Geriatric Assessment Screening Tool of Older Inpatients at Risk for Long Length of Hospital Stay: Results From a Prospective and Observational Cohort Study. J Am Med Dir Assoc. 2018;19:720-721.
10. Bonadias Gadelha A, Lima RM. Letter to the Editor: COVID-19 Quarantine in Older People: The Need to Think about Sarcopenia-Related Phenotypes. J Frailty Aging. 2020;9(4):244-245.

RELATIONSHIP BETWEEN SERUM FATTY ACIDS AND COMPONENTS OF PHYSICAL FRAILTY IN COMMUNITY-DWELLING JAPANESE OLDER ADULTS

 

K. Kinoshita1,2, R. Otsuka3, C. Tange3, Y. Nishita1, M. Tomida3, F. Ando3,4, H. Shimokata3,5, H. Arai6
 
1. Department of Epidemiology of Aging, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, Aichi Japan; 2. Department of Community Healthcare and Geriatrics, Nagoya University Graduate School of Medicine, Aichi, Japan; 3. Section of NILS-LSA, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, Aichi, Japan; 4. Faculty of Health and Medical Sciences, Aichi Shukutoku University, Aichi, Japan; 5. Graduate School of Nutritional Sciences, Nagoya University of Arts and Sciences, Aichi, Japan; 6. National Center for Geriatrics and Gerontology, Aichi, Japan
Corresponding author: Rei Otsuka, Section of NILS-LSA, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka, Obu, Aichi 474-8511, Japan, Tel: +81-562-46-2311; FAX: +81-562-46-2373; E-mail: otsuka@ncgg.go.jp

J Frailty Aging 2020;in press
Published online December 22, 2020, http://dx.doi.org/10.14283/jfa.2020.67

 


Abstract

Polyunsaturated fatty acids help maintain insulin sensitivity, mitochondrial function, and anti-inflammation. It is well known that deterioration in these areas can cause frailty. However, little is known about the differences in serum polyunsaturated fatty acid levels among frailty components. We investigated the cross-sectional relationship between frailty and serum fatty acids in 1,033 community-dwelling older adults aged 60–88 years. Polyunsaturated fatty acid concentrations were measured from fasting blood samples. The modified phenotype criteria defined frailty. Polyunsaturated fatty acid levels were compared among each component using general linear modeling after controlling for sex, age, body mass index, smoking status, household income, and medical history. Lower polyunsaturated fatty acid levels were associated with the modified frailty criteria, including shrinking and weakness (p < 0.05). Our findings suggest that serum polyunsaturated fatty acid levels differ depending on the frailty status of older adults.

Key words: Cross-sectional study, polyunsaturated fatty acids, n-3 polyunsaturated fatty acids.


 

Introduction

Fatty acids, especially polyunsaturated fatty acids (PUFA), have gained attention from many researchers and clinicians because they may have beneficial effects on the health of older adults (1). Besides being produced from food intake, some fatty acids are synthesized in the body. Previous studies have reported that the serum levels of fatty acids are affected by age and are independent of their intake (2).
PUFA can help maintain insulin sensitivity, mitochondrial function, and anti-inflammation (1). This is significant, since deterioration in these areas is known to cause frailty (3). Thus, frail older adults may have lower PUFA serum levels than healthy older adults. However, little is known about differences in fatty acid serum levels associated with frailty in community-dwelling older adults.
Investigating the relationship between serum fatty acids and frailty signs could be useful for future research and medical treatments, especially towards maintaining the health of older adults. Therefore, we aimed to verify the differences of fatty acid serum levels associated with frailty components in community-dwelling older adults.

 

Methods

Study participants

This study was conducted as a part of the National Institute for Longevity Sciences – Longitudinal Study of Aging (NILS-LSA) (4). Participants were recruited using a stratified random sampling method, by age (≥ 40 years) and sex, from the community-dwelling population of Obu City and Higashiura Town in Aichi Prefecture, Japan (4).
We cross-sectionally analyzed the fifth study wave data (between July 2006 and July 2008). Of the 2,419 participants in the fifth study, we excluded participants who: were aged < 60 years (n = 1,140), had incomplete frailty diagnoses (n = 178), had missing data for serum samples (n = 38), and had missing data for covariates (n = 30). Finally, 1,033 participants (males, n = 513, 49.7%) were analyzed in this study.
All participants provided written informed consent before participation. This study protocol was approved by the Ethics Committee of Human Research of the National Center for Geriatrics and Gerontology, Japan (No. 1115-3).

Blood sampling and fatty acid measurement

Blood samples were collected in the morning after fasting at least 12 hours. The NILS-LSA measurement details for fatty acids have been reported elsewhere (2). This study assessed total fatty acids (TFA), saturated fatty acids (SFA), monosaturated fatty acids (MUFA), and PUFA. Regarding PUFA, the n-3 series PUFA (n-3 PUFA) including alpha-linoleic acid (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA); and the n-6 series PUFA (n-6 PUFA) including gamma-linoleic acid (GLA), linoleic acid (LA), arachidonic acid (AA) were also assessed.

Physical frailty assessment

Frailty was assessed using frailty phenotype modified for Japanese, based on the original criteria outlined by Fried (5, 6). Frailty was indicated if participants met three or more components; meeting one or two components indicated pre-frailty. Shrinking was defined by ≥ 5% weight loss in the prior two years, since the NILS-LSA survey is biennial (4, 6). Weakness was defined by a maximum grip strength of < 26 kg in males and < 18 kg in females (6). Slowness was defined by a 10-m general gait speed of < 1.0 m/sec (6). Low activity was defined as scoring in the lower 20% for physical activity on a modified Minnesota Leisure-time Physical Activity Questionnaire (6). Exhaustion was assessed by determining whether participants experienced either of the following conditions: “I felt that everything I did was an effort” and “I could not get ‘going,’” The responses, with regard to the previous week, were: “less than 1 day,” “1-2 days,” “3-4 days,” and “5-7 days.” Participants were defined as exhausted if they did not answer “less than 1 day” for either of these questions (6).

Covariates

Body mass index (BMI, kg/m2) was calculated from anthropometric data. Smoking status (current smoker or not), annual household income (less than 5.5 million yen or more), and medical history (hypertension, ischemic heart disease, dyslipidemia, diabetes mellitus, and stroke) were assessed using self-report questionnaires.

Statistical analysis

Serum fatty acid levels were estimated with logarithmic conversion. Mean and standard deviations were calculated for continuous variables.
Participant characteristics, according to frailty status, were analyzed using the Chi-squared test and analysis of variance.
Using general linear modeling after controlling for covariates, we compared serum fatty acid levels between participants in three categories according to frailty phenotype (i.e., robust, pre-frail, and frail), and in participants with or without each of the five frailty components.
In the additional analysis, we included the overall energy intake (kcal/day) as covariates. The energy intake was assessed using a three-day dietary record that has been reported in detail elsewhere (7).
All analyses were performed using the Statistical Analysis System version 9.3 (SAS Institute, Cary, NC, USA); a two-sided p-value < 0.05 indicated statistical significance.

 

Results

Table 1 shows participant characteristics. Participant age ranged from 60 to 88 years. There were 68 (6.6%) frail, 561 (54.3%) pre-frail, and 404 (39.1%) robust participants.

Table 1
Characteristics of participants according to physical frailty (n=1,033)

*Chi-squared test for proportion variables and ANOVA for continuous variables; †5.5 million yen = $51,882.32 USD, which was calculated according to the mean conversion rate during the study period (i.e., July 2006 to July 2008); SD, standard deviation; BMI, body mass index; ANOVA, analysis of variance.

 

In comparing fatty acid serum levels in robust, pre-frail, and frail participants, PUFA levels (μg/ml) were highest in the robust group and lowest in the frail group (least squares mean ± standard error; 1416.1 ± 1.0, 1378.1 ± 1.0, and 1341.5 ± 1.0; in respectively, p = 0.020 for between-group difference, p = 0.026 for trend).
Table 2 shows fatty acid serum levels according to the five frailty components. Participants with shrinking had significantly lower levels of TFA, SFA, MUFA, and PUFA than those without (p < 0.01 in all). Those with weakness had significantly lower EPA and DHA levels, than those without (p < 0.05 in all). Those with slowness had significantly lower EPA levels (p = 0.032); those with low activity had significantly lower DHA levels (p = 0.048). However, we found no significant differences in fatty acid serum levels for participants with and without exhaustion.

Table 2
Serum levels of fatty acids according to the five components of physical frailty (n=1,033)

Values are least squares mean (standard error). General linear modeling was performed after controlling for sex, age, BMI, current smoker, annual household income (< 5.5 million yen), and history of stroke, ischemic heart disease, hypertension, dyslipidemia, diabetes mellitus. Serum fatty acids levels were estimated after logarithmic conversion. TFA, total fatty acids; SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; ALA, alpha-linoleic acid; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid, GLA, gamma-linoleic acid; LA, linoleic acid; AA, arachidic acid.

 

Discussion

This study investigated the serum fatty acid levels according to frailty components in community-dwelling older adults. Our findings suggest that serum fatty acid concentrations, especially PUFA levels, differ depending on the frailty signs in older adults.
Both PUFA and MUFA are suggested to be effective in preventing muscle loss through suppressing reductions in insulin sensitivity (1). This may be because insulin accelerates muscle synthesis by activating the mammalian target of rapamycin complex 1 (8). PUFA is believed to prevent muscle atrophy and physical dysfunction by improving mitochondrial function and anti-inflammatory effects (1, 9). Mitochondrial dysfunction overproduces reactive oxygen species, leading to muscle atrophy due to induced protein degradation through the accelerated ubiquitin-proteasome system (10). Inflammation is suggested to be associated with components of frailty; however, this needs to be further explored in future studies (9, 3).
Participants with shrinking had significantly lower serum SFA levels. SFA may have an association with muscle loss (1). However, participants with shrinking also showed significantly lower TFA levels. Previous research observed that TFA serum levels were significantly lower in thin people compared with obese people (11). To account for the effect of consumption on shrinking, we additionally analyzed and controlled participants’ energy intake (kcal/day); however, this association remained even after the adjustment (data not shown).
We determined that lower PUFA levels, especially n-3 PUFA, were associated with signs of frailty. Based on a review article, randomized controlled trials (RCTs) of n-3 PUFA supplementation for muscle function were conducted with healthy older adults. However, the beneficial effects were shown only during sufficient supplementation (12). Intriguingly, Guerville and colleagues conducted an RCT in community-dwelling older adults with regard to slow gait speeds or any limitations in the activities of daily living; they reported that the n-3 PUFA supplementation and lifestyle intervention resulted in a lower frailty incidence than the placebo group, when they excluded participants who became frail within one year (13). They suggested that earlier intervention may be crucial (13). Considering our findings together, PUFA requirements might vary according to the conditions of frailty.
There are several limitations to this study. First, the participants may have been healthier than those in other cohorts because the mean frailty prevalence is 11.2% in Japan, as reported from seven community-based studies (14). However, our study participants were younger than in those seven studies. Second, although shrinking status was measured as the change after two years, whether these weight losses were intentional was not clarified. The original criteria measured the weight change during one year (5). Thus, it is possible that some participants with shrinking displayed more gradual weight loss than the original criteria accounted for, or they lost weight intentionally (5). Third, we repeated the analysis for each component; thus, the possibility of an alpha error cannot be ruled out. However, we judged this according to the statistical results, and our interpretation coincides with the view of the American Statistical Association (15).
In conclusion, our findings suggest that older adults with frailty components show lower serum levels of PUFA, especially EPA and DHA. PUFA may prevent frailty signs, such as skeletal muscle catabolism and physical dysfunction, through the beneficial effects of suppressing insulin resistance, maintaining the mitochondrial function, and anti-inflammation. These results can be useful for designing studies and treatment strategies regarding the improvement of physical frailty in older age.

 

Acknowledgments: We truly appreciate all participants and staff of the NILS-LSA for their cooperation and contributions to this study. We would like to thank Editage (www.editage.com) for English language editing.
Funding: This study was supported in part by the Food Science Institute Foundation, and Research Funding for Longevity Sciences from the National Center for Geriatrics and Gerontology, Japan (19-10 to R.O.); and the Japanese Ministry of Education, Culture, Sports, Science and Technology (20H04114 to H.S.).
Author contributions: Kaori Kinoshita conceived the study design, performed the data analysis, interpreted the results, and drafted the initial manuscript; Rei Otsuka collected data, conceived the study design, performed the data analysis, interpreted the results, and contributed to discussions; Chikako Tange collected data, interpreted the results and contributed to discussions; Yukiko Nishita collected data, interpreted the results, and contributed to discussions; Makiko Tomida collected data, interpreted the results, and contributed to discussions; Fujiko Ando designed the NILS-LSA, collected data, interpreted the results, and contributed to discussions; Hiroshi Shimokata designed the NILS-LSA, collected data, interpreted the results, and contributed to discussions; and Hidenori Arai supervised the study, conceived the study design, interpreted the results, and contributed to discussions.
Conflict of Interest: None declared by the authors.
Ethical standards: This study was carried out in accordance with the ethical standards.

 

References

1. Lipina C, Hundal HS. Lipid modulation of skeletal muscle mass and function. J Cachexia Sarcopenia Muscle 2017;8(2):190-201.
2. Otsuka R, Kato Y, Imai T, Ando F, Shimokata H. Higher serum EPA or DHA, and lower ARA compositions with age independent fatty acid intake in Japanese aged 40 to 79. Lipids 2013;48(7):719-727.
3. Rodriguez-Mañas L, Araujo de Carvalho I, Bhasin S, et al. ICFSR Task Force perspective on biomarkers for sarcopenia and frailty. J Frailty Aging 2020;9(1):4-8.
4. 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(1 Suppl):S1-9.
5. 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.
6. Yuki A, Otsuka R, Tange C, et al. Epidemiology of frailty in elderly Japanese. J Phys Fit Sports Med 2016;5(4):301-307.
7. 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(1 Suppl):S70-76.
8. Laplante M, Sabatini DM. mTOR signaling at a glance. J Cell Sci 2009;122(Pt 20):3589-3594.
9. Ferrucci L, Fabbri E. Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nat Rev Cardiol 2018;15(9):505-522.
10. Jang YC, Lustgarten MS, Liu Y, et al. Increased superoxide in vivo accelerates age-associated muscle atrophy through mitochondrial dysfunction and neuromuscular junction degeneration. FASEB J 2010;24(5):1376-1390.
11. Mittendorfer B, Magkos F, Fabbrini E, Mohammed BS, Klein S. Relationship between body fat mass and free fatty acid kinetics in men and women. Obesity 2009;17(10):1872-1877.
12. Tessier AJ, Chevalier S. An update on protein, leucine, omega-3 fatty acids, and vitamin D in the prevention and treatment of sarcopenia and functional decline. Nutrients 2018;10(8).
13. Guerville F, de Souto Barreto P, Giudici KV, Rolland Y, Vellas B. Association of 3-Year multidomain intervention and omega-3 supplementation with frailty incidence. J Am Geriatr Soc 2019;67(8):1700-1706.
14. Satake S, Shimada H, Yamada M, et al. Prevalence of frailty among community-dwellers and outpatients in Japan as defined by the Japanese version of the Cardiovascular Health Study criteria. Geriatr Gerontol Int 2017;17(12):2629-2634.
15. Wasserstein RL, Lazar NA. The ASA Statement on p-Values: context, process, and purpose. Am Stat 2016;70(2):129-133.

 

OLDER PEOPLE FACING THE CRISIS OF COVID-19: BETWEEN FRAGILITY AND RESILIENCE

 

H. Amieva, J.-A. Avila-Funes, S. Caillot-Ranjeva, J.-F. Dartigues, M. Koleck, L. Letenneur, M. Pech, K. Pérès, N. Raoux, N. Rascle, C. Ouvrard, M. Tabue-Teguo, R. Villeneuve, V. Bergua

INSERM, Bordeaux Population Health Research Center, UMR 1219, Univ. Bordeaux, F-33000 Bordeaux, France
Corresponding author: Professor Helene Amieva, Inserm U 1219 Bordeaux Population Health, University of Bordeaux, 146 Rue Léo Saignant, 33076 Bordeaux cedex, France, Phone: +33 5 57 57 15 10 / Fax: +33 5 57 57 14 86, Helene.Amieva@u-bordeaux.fr
J Frailty Aging 2020;in press
Published online November 18, 2020, http://dx.doi.org/10.14283/jfa.2020.60

 


Abstract

The health crisis we are facing is challenging seniors’ resources and capacities for adaptation and resilience. The PACOVID survey, set up a few days after containment, investigates their psychological and social experiences with regard to the COVID-19 crisis and to what extent these characteristics, representations and attitudes have an impact on health and mortality. A telephone survey is being carried out on 935 people already followed up in the framework of ongoing epidemiological studies. As we are writing this article, the interviews conducted during the containment have just ended. Even though we will have to wait for the analysis of the results to draw conclusions, words collected by the psychologists during the interviews already illustrate a great heterogeneity in the way older adults lived this experience: social isolation, anxiety, the importance of family and the difficulty of being deprived of it, but also remarkable coping skills and resilience capacities.

Key words: Containment, behaviors, vulnerability, coping, resilience.


In the face of health crises, the older population is one of the most vulnerable. The heat wave episode in France in August 2003 exceptional in terms of intensity, duration and geographical extent, clearly demonstrated this. The excess mortality related to this episode (15,000 additional deaths compared to the usual mortality) was explained by an increase in excess mortality with age particularly marked among people living alone at home or in nursing homes (1). While the world is still facing the COVID-19 epidemic, there is every reason to believe that older people will once again be the most affected, as shown by the mortality curves provided by the countries affected by the pandemic. This excess mortality can be explained by the physiological particularities of the older persons (a greater state of immuno-depression, a propensity to over-activate the inflammatory response, and the frequent co-morbidities such as heart failure or chronic obstructive bronchopneumopathy, favoring complications), but the specificities related to the psychological and social functioning of the older adults also contribute to this issue. Apart from any crisis situation, the consequences of a disease are very different from one older person to another depending on psychological resources, lifestyle, level of social support, home facilities, accessibility of services and shops, etc. Numerous studies have shown that socially isolated older adults present higher mortality, independently of many confounding factors (2–4). Depression also has a major impact on mortality of the older persons suffering from diseases such as cancer (5), as depressed people adhere less to preventive screening procedures, good health behaviors, and treatments. In a major health crisis, do these factors carry more weight? As few studies explored in depth this question, it is difficult to answer this question.
In the days following the containment measures in China, a literature review was undertaken to take stock of what is known about the psychological impact of quarantine (6). Based on 24 studies, the conclusions highlight the psychological impact, the most frequent consequences being post-traumatic stress symptoms, confusion and anger. These symptoms persist for several months or even years after quarantine. For example, in Wu et al.’s study (7) conducted during the SARS epidemic, quarantine predicted post-traumatic stress up to 3 years later Brooks et al. (6) also highlight the factors that contribute to the negative impact: duration of quarantine, level of fear of infection, feelings of frustration, boredom, supply problems, lack of information, loss of income, and stigmatization.
No study specifically focused on the older population particularly at risk at least at three levels: with regard to the response to the infectious agent itself because of the physiological characteristics of this population; with regard to the psycho-social characteristics of the older persons which make part of this population even more exposed to the risk of severe repercussions of the infection (elders with dependency, cognitive disorders, depression, social isolation or living in institutions); and possibly with regard to the situation of containment due to reduced adjustment capacities (8,9).
The PACOVID (Personnes Agées face au COVID-19) survey was set up in Bordeaux region a few days after containment. Through a 2-step telephone survey carried out during and after the confinement on 935 people (living at home or in institutions) already followed up in the framework of ongoing epidemiological studies, this project addresses the following questions:
1) What are the attitudes, psychological and social experiences of the older persons with regard to the COVID-19 crisis and the containment measures: level of stress, coping strategies, social support, access to information, instructions and measures put in place by government authorities, understanding and compliance to such measures, representations of the epidemic, access to digital communication tools?
2) To what extent do these characteristics, representations and attitudes have an impact on mortality and health events related and unrelated to COVID-19?
As we are writing this article, the first wave of the survey conducted during the period of containment has just ended (the second wave will take place away from the containment). Even though we will have to wait for the analysis of the results to draw conclusions, words collected by the psychologists during the interviews already illustrate a great heterogeneity in the way older adults live this experience. First of all, this survey reminds us to what extent loneliness and social isolation are worrying issues among the older persons, such as this 98-year-old woman, pleasantly surprised by our telephone call and who told us that she had not seen anyone since Christmas, «I lost my husband at the beginning of the year, I’ve been in conflict with my only son for many years, I don’t have any friends left, your call is very touching to me». For those who have more people around them, the importance of family and the difficulty of being deprived of it come out from numerous comments: «Usually, my children and grandchildren visit me at lunchtime, but now I feel alone and I miss them, we lose our appetite with my husband,» said one participant. Actually, several people told us that they apply the containment measures very strictly, even though it turned out during the interview that they continued to receive regular visits from their family, «Containment is for outsiders, the family is not the same. My children come to see me every day to bring me groceries, watch TV, help me with household chores. By the way, today my daughter-in-law is coming to mow the lawn!» says one participant. As we expected, anxiety was very present, as in this 103-year-old woman who told us: «I suffer from rheumatism to the legs, my physiotherapist doesn’t come anymore, I would have to walk but nobody can accompany me, I can’t do anything!». This other 98-year-old participant even tells us: «You know, I pray every day, maybe I won’t wake up tomorrow». Although frequent, these examples do not cover the whole range of experiences. Older people are not only vulnerable, they also have remarkable coping skills and resilience. A striking fact is that many people spontaneously referred to the parallel between this crisis and the war. «We old people know what it’s like, we’ve been through war! It’s the young people we worry about; they’re not used to it». Another participant said: «When I see the long queues in front of the shops, the difficulty in finding certain foods, I feel like I am back in wartime! But you know, we know what it’s like, we’ll survive!». Another man makes the connection with his past as a soldier: «You know, this epidemic reminds me of the time when I was in the trenches, there was a huge epidemic, I fell through the cracks, I hope I will do it again this time!». For some, this containment is lived in the greatest serenity, like this older man, passionate about flowers, a former nurseryman who spends his days in his garden where he grows more than 50 varieties of rare flowers to the admiration of his neighbours. «COVID-19 has no impact on me, I’ve been confined to my garden since I retired, and I’m very happy that way!». In the same vein, this woman says: «I have my chickens, my garden, cleaning, knitting, I don’t have time to be bored!». Another interesting testimony is that of a 97-year-old man who has settled for the confinement at his niece’s house: «I live the best of my life, I enjoy it, I am taken care of, I eat delicious meals, I hope the containment will keep going for a while yet!» As may be seen here, lifestyle, self-esteem and the meaning one gives to one’s life are determining factors in the way one experiences this confinement. In addition to the use of the telephone to keep in touch with beloved ones, digital tools equipped with simultaneous vision seem to have been new allies for some seniors during containment. For example, an older lady who was hosted in her daughter’s home tolds us: «I have a great-granddaughter who was just born, my daughter hooked us up to the camera, you know with the phone, if you had seen how she looked at me, I’m so happy to be able to see her». Other participants told us that they wished they had known how to use these tools like this centenary lady: «You know if my children showed me how it works, I would have liked to use these tools, I’m not against these things, it would have helped me.»
The crisis we are facing is challenging seniors’ resources and capacities for adaptation and resilience. While for some, maintaining balance seems easy, for others, containment will have serious consequences for psychological, cognitive and physical health. Isolation, anxiety and the absence of certain home care professionals may have increased certain risk situations such as frailty, falls, cognitive decline or lack of care. Thanks to the follow-up of participants enrolled in prospective cohorts, the results gathered from PACOVID will help characterizing the most vulnerable people, which is important to anticipate in the future medico-social actions to be implemented rapidly to support them.

 

Conflict of Interest: The authors declare they have no conflict of interest
Funding: The PACOVID study is supported by the National Agency Research « Agence Nationale de la Recherche » [ANR-20-COVI-0010-01]. The sponsor 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.
Ethical standards: This study is in accordance with the international ethical standards of research and with the 1964 Helsinki Declaration.

 

References

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2. Rubin R. Loneliness Might Be a Killer, but What’s the Best Way to Protect Against It? JAMA. 2017; 318(19):1853‑5.
3. Tabue Teguo M, Simo-Tabue N, Stoykova R, Meillon C, Cogne M, Amieva H, et al. Feelings of Loneliness and Living Alone as Predictors of Mortality in the Elderly: The PAQUID Study. Psychosom Med. 2016;78(8):904‑9.
4. Tanskanen J, Anttila T. A Prospective Study of Social Isolation, Loneliness, and Mortality in Finland. Am J Public Health. 2016;106(11):2042‑8.
5. Pinquart M, Duberstein PR. Depression and cancer mortality: a meta-analysis. Psychol Med. 2010;40(11):1797‑810.
6. Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. The Lancet. 2020;395(10227):912‑20.
7. Wu P, Fang Y, Guan Z, Fan B, Kong J, Yao Z, et al. The psychological impact of the SARS epidemic on hospital employees in China: exposure, risk perception, and altruistic acceptance of risk. Can J Psychiatry Rev Can Psychiatr. 2009;54(5):302‑11.
8. Charles ST. Strength and vulnerability integration: a model of emotional well-being across adulthood. Psychol Bull. 2010;136(6):1068‑91.
9. Rothermund K, Brandstädter J. Coping With Deficits and Losses in Later Life: From Compensatory Action to Accommodation. Psychol Aging. 2003;18(4):896‑905.

INTEGRATED CARE AND GERIATRICS: A CALL TO RENOVATION FROM THE COVID-19 PANDEMIC

 
P. Astrone1, M. Cesari2
 
1. Subacute Care Unit, Codogno Hospital, ASST Lodi, Lodi, Italy; 2. Geriatric Unit, IRCCS Istituti Clinici Scientifici Maugeri, University of Milan, Milan, Italy
Corresponding author: Paolo Astrone, MD. Viale Guglielmo Marconi, 1, 26845 Codogno, Lodi, Italy. Email: paolo.astrone@outlook.com.
J Frailty Aging 2020;in press
Published online October 28, 2020, http://dx.doi.org/10.14283/jfa.2020.59
 


In recent decades, we have witnessed the progressive aging of the world population. According to the latest global demographic estimates by the Population Division of the Department of Economic and Social Affairs of the United Nations, people aged 65 years or older represented 9% of the entire population in 2019 (1). It is well-established that the risk of severe health-related events increases with age. Thus it is not surprising that the COVID-19 pandemic has shown once more how the older adults and the frailest subjects are particularly exposed to adverse outcomes (2). The often neglected problems of geriatrics are today evident (at least, for those who want to see them), and indicate the need to reshape our healthcare systems according to characteristics of the older population.
Besides soliciting the adoption of preventive measures to limit the spread of the SARS-CoV-2 virus (e.g., social distancing, personal protection equipment, PPE), the pandemic has mainly been counteracted by strengthening the centrality of the hospital setting through the reinforcement of intensive care units and emergency departments. The priority has been to isolate COVID patients (and/or suspect cases) as soon as possible, hospitalize them, and offer prompt respiratory support when symptoms appear and start to dramatically worsen (3). Such an approach might appear reasonable in a period of emergency. However, it becomes less logical if considering the widespread unpreparedness in front of this catastrophic event. In particular, everything may appear frustrating thinking that 1) previous pandemics (e.g., SARS) have taught nothing (but luckily exceptions do exist! (4, 5)), and 2) many countries have been found not adequately organized even after months from the first cases. In this context, the evident fragmentation of our healthcare systems, unadapted primarily to the needs of older and frail persons, represents a critical point to discuss, with a view to implementing the management of possible future waves of COVID-19.
A paradigmatic example comes from long-term care facilities (LTCFs). This setting of geriatric care has been traditionally marginalized within healthcare networks. LTCFs have constantly been living in the ambiguity that their residential nature does not fit with the relevant clinical burden of care of their frail and complex residents. Not surprisingly, during the pandemic, the undefined/neglected role of nursing homes has been translated into a high tool of fatalities among their residents. A similar situation has been observed for primary and community healthcare services, which have suffered in terms of death of many professionals found themselves unprepared on the frontline, and have experienced a decrease in home care, outpatient care, and caregivers’ support.
These problems are mainly related to the hospital-centered approach of our healthcare systems, a perspective that implicitly tends to reduce resources to other settings of care that are equally important for the proper functioning of the healthcare network. In the aging population, prevention of hospitalization is crucial, but the current primary healthcare services are often unable to ensure safety and continuity of care for older persons. Moreover, geriatricians still have limited visibility in the system, playing a marginal role in the planning and organization of care. Paradoxically, during the current pandemic, while geriatricians have often been employed at the frontline against COVID-19 given their background as internists, concepts of major importance for geriatric medicine (e.g., biological age, multidimensionality, frailty, functional ability, continuity of care) have frequently been put aside on the pretext of the emergency. In this context, the poor diffusion of geriatric knowledge concurs with feeding rampant ageism, affecting capacities of all those settings that are traditionally devoted to the care of older persons. In fact, in daily clinical practice, older persons are frequently discriminated against due to their chronological age, which has been used as the main criterion for the allocation of care resources.
In its immense tragedy, the COVID-19 pandemic may become an opportunity to prove the weaknesses of the healthcare system and may indicate which parts are at the most urgent need of reorganization (6–9). It is evident that a restructuring according to more modern models of care based on integration of healthcare services, multidimensional assessment, and person-centered approach is needed, especially for the most vulnerable individuals. There is a pressing need to strengthen primary care to prevent, slow, or even reverse declines in intrinsic capacity (10). Such adaptation of the system to the new needs is clearly explained by the World Health Organization in its guidelines to Integrated Care for Older PEople (ICOPE). Important elements for delivering ICOPE and guaranteeing continuity of care include the comprehensive assessment of the older person, personalized interventions, self-management support, community engagement and caregivers’ support… (10), all aspects that have traditionally been promoted by geriatricians and presented as the only way of dealing with the complexities of the frail older person. In this general reorganization of the system towards models that are more careful at the basic principles of geriatric medicine (11), it might be important to foresee a more formal engagement of geriatricians in institutional decisions. Given its transversal nature, geriatric medicine should be reinforced across all the healthcare settings, both inside the hospital setting (for example, through the generation of more frequent collaborations/exchanges with other specialties) and the territory (for example, creating links with primary care). Under this perspective, geriatricians may assume a relevant responsibility, playing the critical role in connecting the two souls of the healthcare system, the hospital one and the other based on the community.
Hopefully, public health authorities will become better aware of the urgent need to guide our society towards a cultural renovation that starts from the reorganization of the healthcare system. A more modern system, together with the promotion of ad hoc training for healthcare professionals and the educative role of mass communications, may result decisive in giving value to geriatric medicine and fighting the diffusion of age stigma.

Disclosure statement: The authors declare no conflict of interest.

 

References

1. United Nations, Department of Economic and Social Affairs, Population Division (2019). World Population Prospects 2019: Highlights (ST/ESA/SER.A/423)
2. Boreskie KF, Hay JL, Duhamel TA. Preventing Frailty Progression during the COVID-19 Pandemic. J Frailty Aging. 2020;9(3):130-131. doi:10.14283/jfa.2020.29
3. Cesari M, Proietti M. Editorial: Geriatric medicine in Italy in the time of COVID-19. J Nutr Health Aging. 2020;24(5):459-460. doi:10.1007/s12603-020-1354-z
4. Tan LF, Seetharaman S. Preventing the Spread of COVID-19 to Nursing Homes: Experience from a Singapore Geriatric Centre. J Am Geriatr Soc. 2020;68(5):942. doi:10.1111/jgs.16447
5. Tan LF, Seetharaman SK. COVID-19 Outbreak in Nursing Homes in Singapore. J Microbiol Immunol Infect. Published online May 13, 2020;10.1016/j.jmii.2020.04.018. doi:10.1016/j.jmii.2020.04.018
6. Inzitari M, Risco E, Cesari M, et al. Nursing Homes and Long Term Care after COVID-19: A New Era? J Nutr Heal Aging. (2020). https://doi.org/10.1007/s12603-020-1447-8
7. Chen LK. Older adults and COVID-19 pandemic: Resilience matters. Arch Gerontol Geriatr. 2020;89:104124. doi:10.1016/j.archger.2020.104124
8. Merchant RA. COVID-19: Role of Integrated Regional Health System Towards Controlling Pandemic in the Community, Intermediate and Long-Term Care. J Frailty Aging (2020). http://dx.doi.org/10.14283/jfa.2020.39
9. Wee SL, Yap PLK. Timely Lessons from a Pandemic on the Benefits of Person Centric Care in Long Term Care Facilities. J Frailty Aging. 2020;9(3):132-133. doi:10.14283/jfa.2020.28
10. World Health Organization. (2017). Integrated Care for Older People: Guidelines on Community-Level Interventions to Manage Declines in Intrinsic Capacity. World Health Organization. https://apps.who.int/iris/handle/10665/258981
11. Aprahamian I, Cesari M. Geriatric Syndromes and SARS-Cov-2: More than Just Being Old. J Frailty Aging. 2020;9(3):127-129. doi:10.14283/jfa.2020.17

COGNITIVE FUNCTION AND AMYLOID MARKER IN FRAIL OLDER ADULTS: THE COGFRAIL COHORT STUDY

 

S. Sourdet1, G. Soriano1,2, J. Delrieu1,2, Z. Steinmeyer1, S. Guyonnet1,2, L. Saint-Aubert3,4, P. Payoux3,4, P.J. Ousset1,2, A. Ghisolfi1, B. Chicoulaa1,5, S. Dardenne1, T. Gemar1, M. Baziard1, F. Guerville6, S. Andrieu1,2, B. Vellas1,2

 

1. Gérontopôle, Department of Internal Medicine and Geriatrics, Toulouse University Hospital, La Cité de la Santé, Hôpital La Grave, Place Lange, TSA 60033, 31059 TOULOUSE Cedex 9, France; 2. UMR Inserm Unit 1027, University of Toulouse III, Toulouse, France; 3. Department of Nuclear Medicine, Imaging Center, Toulouse University Hospital, Toulouse, France; 4. Toulouse NeuroImaging Center, Inserm UMR1214, Toulouse University, UPS, Toulouse, France; 5. University Department of General Medicine, Paul Sabatier University, Toulouse; 6. Gérontopôle of Toulouse, Institute of Aging, Toulouse University Hospital, Toulouse, France.
Corresponding author: Sandrine Sourdet, MD – Hôpital de jour d’évaluation des fragilités, Service de Médecine Interne et Gérontologie Clinique, La Cité de la Santé, Hôpital La Grave, Place Lange, TSA 60033, 31059 Toulouse cedex 9, France, Phone: (33) 5 61 77 79 29, Fax: (33) 5 61 77 79 27, E-mail: sourdet.s@chu-toulouse.fr

J Frailty Aging 2020;in press
Published online October 13, 2020, http://dx.doi.org/10.14283/jfa.2020.57

 

 


Abstract

Background: Frailty and cognitive impairment are common manifestations of the ageing process and are closely related. But the mechanisms linking aging, physical frailty, and cognitive disorders, are complex and remain unclear. Objectives: We aim to explore the role of cerebral amyloid pathology, but also a range of nutritional, physical, biological or brain-aging marker in the development of cognitive frailty. Method: COGFRAIL study is a monocentric prospective study of frail older patients with an objective cognitive impairment (Clinical Dementia Rating Scale global score at 0.5 or 1). Three-hundred-and-twenty-one patients are followed up every 6 months, for 2 years. Clinical assessment at baseline and during follow-up included frailty, physical, mood, sensory, nutritional, and cognitive assessment (with a set of neuropsychological tests). Cerebral amyloid pathology is measured by amyloid Positron Emission Tomography (PET) or amyloid-β-1-42 level in cerebrospinal fluid. Brain magnetic resonance imaging, measurement of body composition using Dual X Ray Absorptiometry and blood sampling are performed. The main outcome of the study is to assess the prevalence of positive cerebral amyloid status according to amyloid PET or amyloid-β-1-42 level CSF. Secondary outcomes included biological, nutritional, MRI imaging, cognitive, clinical, physical and body composition markers to better understand the mechanisms of cognitive frailty. Perspective: COGFRAIL study will give the opportunity to better understand the link between Gerosciences, frailty, cognitive impairment, and Alzheimer’s disease, and to better characterize the physical and cognitive trajectories of frail older adults according to their amyloid status. Understanding the relationship between physical frailty and cognitive impairment is a prerequisite for the development of new interventions that could prevent and treat both conditions.

Key words: Cognitive decline, frailty, older adults, Alzheimer’s disease, geroscience, amyloid, neuroimaging.


 

Introduction

With population ageing, frailty has received growing interest from scientific and clinical communities, as well as by the public health authorities (1). Frailty is best defined as an acceleration of the aging process, a condition of homeostatic degradation across physiological systems leaving the individual at high risk of negative health-related outcomes, including disability, hospitalization and mortality. More recently, a number of cross-sectional and longitudinal studies have suggested that physical frailty was associated with late-life cognitive disorders, including mild cognitive impairment (MCI), non Alzheimer’s disease (AD) dementia, and AD (2, 3). Several mechanisms, known for playing a role in both cognitive impairment and frailty have been proposed to explain this link (4). Vascular risk factors, for example, are known to increase the risk of stroke, cerebrovascular lesions, but also sarcopenia, which are involved in the development of frailty on one hand and the development of vascular dementia but also AD on the other hand (5). Several nutritional factors, such as undernutrition, weight loss, reduced caloric or specific nutrients intake, are also associated with a higher risk of both frailty and cognitive impairment (6–8). Genetic and environmental stressor, depression, hormonal dysfunctions may also play a role (4, 8). Another hypothesis is the existence of a direct link between brain pathology and frailty. Several neuropathological studies, using brain autopsies from the Religious Orders Study and the Rush Memory and Aging Project, have explored the association between physical frailty, cognitive decline and the presence of postmortem neuropathologies (9–11). They reported an association between progressive frailty before death and common brain pathologies including AD pathology, Lewy Body pathology, macroinfarcts and nigral neuronal loss, in older adults with but also without dementia. Focusing on AD biomarkers, PET amyloid imaging studies have also suggested an association between regional brain β-amyloid deposition and frailty parameters (12–14).
Despite mounting evidence that cognitive impairment and frailty are closely connected, and that AD pathology could play a role in their co-expression (15), there are still insufficient data exploring this pathological pathway and their potential confounders, especially in vivo. Moreover, longitudinal data are still lacking to understand the evolution of cognitive impairment in the frail and pre-frail population. The COGFRAIL study is a large clinic-based cohort of frail older adults with cognitive impairment. Investigations include regular clinical, cognitive, physical, nutritional, biological assessment and neuroimaging (amyloid PET and Magnetic Resonance Imaging, MRI). In this study, we seek to better understand the proportion of cognitive decline, which can be explained by an AD pathology in frail older adults. It will also allow us to study the role of a range of aging biomarkers with a geroscience approach.

 

Methods and analysis

Aim and objectives

The main objective of the study is to examine the prevalence of subjects with a positive cerebral amyloid status according to amyloid PET or amyloid-β-1-42 level cerebrospinal fluid (CSF), among frail and pre-frail individuals presenting an objective cognitive impairment. The key secondary objectives are to examine changes in cognitive function, physical function, frailty status and body composition during follow-up. We also aim to explore the relationship between these parameters (at baseline and their change during follow-up) and 1/MRI markers, 2/food intake, and 3/nutritional and aging biomarkers (including APOE genotype). Other secondary objectives are to explore the association between cognitive decline during follow-up and changes in physical function, sensory impairments, frailty and body composition, These objectives will be explored in the total population, and also according to the amyloid status. A last objective is to estimate costs related to the management of frail and pre-frail older patients presenting an objective cognitive impairment.

Study design

COGFRAIL is a monocentric observational prospective study. The participants are followed up every 6 months, during 2 years after enrolment.

Study population and eligibility criteria

Three hundred twenty-one participants were recruited for this study, between January 2017 and February 2020. Participants were invited to participate during a routine frailty or cognitive assessment, at the Gerontopôle, University of Toulouse Hospital Center, at the Frailty Clinic, Memory Clinic, or during community-care assessment.
The frailty clinic is a geriatric day hospital unit, dedicated to the assessment and follow-up of frail older adults. Patients were referred after having been identified as frail by their general practitioner using the Gerontopôle Frailty Screening Tool (16). Its functioning is well described elsewhere (17). Most of the participants were recruited at the frailty clinic, as the study is designed following the standardized clinical assessment and follow-up implemented in this unit. The enrollment was also extended to community care, through frailty promotion program developed locally (18) and during usual cognitive assessment at the memory clinic.

Inclusion criteria are:
• Having an objective memory impairment defined by a Clinical Dementia Rating (CDR) global score at 0.5 or 1 (19)
• Age ≥ 70 years
• Having at least 1 frailty criteria according to Fried’s criteria (20)
• Having an informant accompanying or available by phone
• Being affiliated to a healthcare security system.

Exclusion criteria are:
• Presence of any pathology or severe clinical or psychological condition that, based on medical judgment, might interfere with study results or may expose the participants to additional risks
• Dependency (Activities of Daily Living (ADL) <4) (21)
• A major deterioration in global cognitive function (Mini Mental State Examination (MMSE<20) at inclusion (22)
• Adults legally protected (under judicial protection, guardianship or supervision).

Study outcomes and data collection

The study protocol consists of six visits (figure 1): three annual frailty assessment (baseline visit, visit at year 1 and 2), one neuroimaging visit within 4 months after inclusion, and two follow-up visits for medical consultation at 6 and 18 months.

Figure 1
Participant’s follow-up during the study

 

Table 1 and 2 shows the details of study outcomes and data collection time points.

Table 1
COGFRAIL study outcomes and other assessments

PET : Positron Emission Tomography , CSF : Cerebrospinal Fluid, MMSE : Mini-Mental State Examinatino, CDR : Clinical Dementia Rating MRI : Magnetic Resonance Imaging

Table 2
Data collection time-points of the COGFRAIL study

* if non evaluated during screening visit; † Associated pathologies, Treatments, family history of disease; ‡ MMSE, CDR, FCSRT, DSST, COWAT, CNT, TMT; § NPI, GDS, EQ-5D-5L; || IADL, ADL, SPPB; { MNA, BMI, weight; # Fatty acid profile, Vitamin D, B6, B9, B12, homocystein; ** optional

 

Cognition

The Mini-mental State Examination (MMSE) and CDR scale are used to assess global cognitive impairment at baseline. For cognitive outcomes, MMSE is repeated every 6 months and CDR each year. A neuropsychological battery is performed by a neuropsychologist at baseline, 12 and 24 months and is detailed in table 1.
Four of these cognitive tests are used to create a « composite z score » previously used in MAPT study (23).

Physical function

Frailty is evaluated according to Fried phenotype, based on the five physical criteria developed by Fried and colleagues: weight loss, exhaustion, weakness, low physical activity and slowness (20). Weight loss is defined by an unintentional weight loss of more than 4.5 kg in the previous year. Self-reported exhaustion is assessed using two questions from Center for Epidemiological Studies Depression (CES-D) scale: “How often did you feel that everything you did was an effort?” and “How often did you feel that you could not get going” (24). Participants that answered “most of the time” or “often” to one of the questions were categorized as frail for this item. Weakness / hand grip strength is measured with a dynamometer: interpretation of results takes into account sex and body mass index [BMI]). Slow gait speed is defined by walking time over a distance of 4 meters: interpretation of results takes into account sex and height. Physical activity is evaluated using a scale developed by Saltin and Grimby and modified by Mattiasson-Nilo et al. (25). This Classification system of physical activity includes physical training/ exercises and domestic activities and consists of 6 grades: 1/ Hardly any physical activity, 2/ Mostly sitting, sometimes a walk, light gardening or similar tasks, sometimes light household activities such as heating up food, dusting or clearing up 3/ Light physical exercise around 2–4 h a week such as walks, fishing, dancing, and ordinary gardening, including walks to and from shops. Main responsibility for light domestic work such as cooking, clearing up and making beds. Performs or takes part inweekly cleaning, 4/ Moderate exercise 1–2 h a week, e.g., jogging, swimming, gymnastics, heavy gardening, home-repairing, or light physical activity more than 4 h a week. Responsible for all domestic activities, light as well as heavy. Weekly cleaning with vacuum cleaning, washing floors and window-cleaning, 5/ Moderate exercise at least 3 h a week, e.g., tennis, swimming, and jogging, 6/ Hard or very hard exercise regularly and several times a week, where physical exertion is great, e.g., jogging and skiing. The “low physical activity” criteria is met if the participant is graded 1 or 2. According to these criteria, subjects were categorized as non-frail (=0 criteria), pre-frail (=1 or 2 criteria), or frail (≥3 criteria) (20). Physical performance is evaluated with the Short Physical Performance Battery (SPPB) scale, a tool combining gait speed, chair stand and balance tests (26). To explore the existence of Parkinson’s signs, the Unified Parkinson’s Disease Rating scale will be evaluated at the second visit at 6 months (27).
Moreover, a dual energy X-ray absorptiometry (DEXA) is be performed optionally at baseline, 12 and 24 months (system Lunar iDXA), to measure the whole body composition (fat mass, muscle mass, bone mass) and identify sarcopenia.

Food intake and nutritional status

Nutritional status is assessed using baseline body weight, change in body weight, Body Mass Index (BMI, in kg/m2) and the Mini Nutritional Assessment-Long Form (28). Depending on total MNA score, patients are classified as well nourished (>23.5 points), at risk of malnutrition (17–23.5 points) or malnourished (<17 points).
The dietary macronutrient and micronutrient intake of the participants is assessed using diet history interviews performed annually with the clinics dietitian. Diet history is a detailed interview (lasting about 45 min) on the usual dietary intake of the subject including all meals, drinks (including alcohol consumption) and snacks. This interview will collect a typical daily intake pattern, including amount, frequencies and methods of preparation. The resulting data are then analyzed using Nutrilog software (SAS, France) to calculate the nutrient intake.

Beta amyloid-level: PET imaging and CSF amyloid level

The primary outcome of this study is the prevalence of subjects with a positive amyloid status as corroborated with amyloid Positron Emission Tomography (PET) or amyloid-β-1-42 level in CSF. Amyloid PET imaging is a relatively non-invasive technique to detect brain beta-amyloid pathology, and has proven to be effective in the early diagnosis of AD (29). To date, only a few studies have explored cerebral amyloid pathology using amyloid PET scans in frail patients (13, 14).
Participants receive an intravenous injection of the following radiotracers, depending on their availability: Amyvid (18F-Florbetapir), Neuraceq (18F-Florbetaben) or Vizamyl (18F-Flutemetamol). A systematic review and meta-analysis exploring the diagnostic accuracy of these biomarkers for AD did not find differences between these 3 amyloid radiotracers (30). The injected dose depends on the radiotracer selected: 4Mbq/kg for florbetapir, 300 Mbq for florbetapen and 185 Mbq for flutemetamol. PET Scans were acquired at the PET facility of Toulouse University Hospital using a BiographTM 6 TruePointTM (Siemens Medical Solutions, Munich, Germany) high-resolution hybrid PET/CT scanner. Following the Euratom Directive 96/29 and its implementation in France by Decree 2002-460 for healthy volunteers and patients, the injected dose and the parameters of brain scanner are adapted to a quality examination with the least irradiation possible. Image emission starts 90 (+5) minutes after radiotracer injection, for a 10 minutes acquisition period. The PET images are reconstructed iteratively and attenuation corrected according to the Hounsfield unit scale from the brain scan.
Amyloid positivity is determined by visual reading: 2 independent nuclear medicine physicians, highly trained to amyloid PET reading and blind to all clinical and diagnostic informations, review all PET scans in a randomized order. They use a binary scale to classify each scan as “amyloid negative” in absence of significant cortical retention, and “amyloid positive” in presence of significant cortical retention. In case of disagreement, the two reviewers review the images again until a consensus is reached.
Global as well as regional standardized uptake volume ratios (SUVRs) will also be obtained by semi-quantitative analyses, using the whole cerebellum as reference region. Determination of SUVRs cut-off will be determined according to the literature, and others cut-off will be explored.
Depending on the patient’s acceptablity and the clinical context, a lumbar puncture with CSF amyloid-β-1-42 measurement can be proposed, as a second option to measure beta-amyloid level. If CSF is collected, CSF level of total tau and phosphorylated tau are also measured. While not always interchangeable, PET amyloid imaging and CSF amyloid level show high correlation, with good concordance using dichotomized variables (31, 32). A lumbar puncture is performed following standardized conditions to collect 5 to 10 mL of CSF sample in 2 polypropylene tubes. The quantitative determination of beta-amyloid peptide in CSF will be performed at the Toulouse Bio Ressources (Centre de Ressources Biologique CRB) using the INNOTEST B-amyloid (1-42) enzyme immunoassay (FUJIREBIO). A cut-off of 500 pg/mL will be applied for the determination of the amyloid status.

Magnetic Resonance imaging

Only a few neuroimaging studies have investigated the association between frailty and structural neuroimaging markers (33, 34). One of the main finding was the positive association between a higher burden of white matter lesions and the prevalence of frailty but also slow gait speed. A positive association between slow gait speed and brain atrophy, smaller gray matter volume, smaller total hippocampal volume and resting state connectivity were also suggested in some studies (35–37), but these results remain scarce.
Our objective is a better understanding of brain imaging modifications associated with frailty and cognitive impairment and to identify potential biomarkers of cognitive frailty. A MRI is performed once, within 4 months of the inclusion. All MRI data are collected on a 3-Tesla MRI scanner with a multi-channel head coil. The imaging analyses rely on the CATI (a platform dedicated to multicenter neuroimaging). The protocol is partly derived from the ADNI (Alzheimer Disease Neuroimaging Initiative) study and includes a scan with the following sequences: 3DT1, T2FLAIR, T2FSE, T2GRE, resting-state functional MRI and diffusion MRI. Quality controls will rely on the CATI. MRI analysis include: whole brain volumetry (and total grey and white matter volume), hippocampal volumetry, white matter hyperintensities volume, connectivity indexes, cortical thickness, indices derived from diffusion imagin in region of interests and sulcal morphology.
This examination is not mandatory, depending on compatibility for MRI examination and medical pertinence (patients who underwent a cerebral routine MRI scan for cognitive investigation on the year preceding inclusion were not asked systematically to undergo a second examination).

Blood sampling

Blood samples are collected at 2 times point during the study (at 6 months and 24 months) to obtain longitudinal data on biomarkers. A 22 ml blood sample is taken in fasting condition each time: 2 clot activator tubes (2x 6 mL), 1 ethylenediaminetetraacetic (EDTA) tube (6 mL) and 1 lithium heparin tube (4 mL). Right after blood drawing, the samples are transferred directly at 4°C to the CRB (Centre de Ressources Biologiques) Toulouse Bio Ressources. One milliliter of blood is taken to measure immediately a series of nutritional biomarkers (Vitamin D, B6, B9, B12, homocysteine and fatty acids including EPA and DHA), due to their instability. The rest of the blood sample (plasma, serum and pellet) is aliquoted in 500 µL cryotubes and frozen at -20°C to constitute a biobank. All aliquots are in a second time transferred in a freezer at -80°C. The biobank will permit to measure a range of biological marker of aging potentially linking frailty to cognitive impairment (e.g inflammatory, metabolomics, nutritional, oxidative stress or genomic markers). A biobank scientific committee will be set up, in collaboration with the one of the INSPIRE study (38), to determine the scientific directions and research priorities in this cohort.
Additionally, results from the standard blood tests usually done in clinical routine at the Frailty or Memory Clinic at the time of inclusion are extracted from patients medical record: they include CRP, creatinine, hemoglobin, platelets, leukocytes, and TSH.

Biological ancillary studies

An ancillary study to explore the link between peripheral blood mononuclear cells (PBMC) and neurodegeneration was submitted 20 march 2020. Two additional EDTA tubes (2×6 mL) will be collected at 6, 12 and 24 months for immunological assessment. The samples will be transferred at room temperature to CRB where PBMC will be collected after density gradient-based separation, counted and frozen at 10 millions/cells per vials. Frozen vials will be stored in liquid nitrogen by the immune monitoring platform at the Center for Pathophysiology of Toulouse-Purpan (CPTP).

Health Economic

Costs examined are those related to the management of patients enrolled in the study. Cost estimates are performed from the health insurance perspective and more broadly from the societal perspective (i.e. patients and families). Costs taken into account are direct medical costs (inpatient, outpatient, and medication), direct non-medical costs (transportation, formal care) and informal costs. The expenses incurred in the management of patients are recorded over a 2 years period from the French health insurance databases and from questionnaires for formal and informal costs.

Ethical approval

Ethical approval was obtained from the institutional research committee (CPP SOOM II) on 02 December 2016 ((Registration Number: RC31/16/8753). The protocol was registered on ClinicalTrials.gov (NCT03129269).

 

Discussion

The COGFRAIL study will give the opportunity to determine for the first time the prevalence of cerebral amyloid pathology in frail older adults with cognitive impairment, to assess their cognitive and physical progression over a 2 years follow-up period, and to explore the impact of a range of nutritional, imaging, biological marker in the development and progression of cognitive frailty.
Many Alzheimer drug trials have failed through the last several years. We stressed that frailty and dementia could be closely interrelated, but frailty is not taken into account in AD trials and could be a new axis of intervention(39). COGFRAIL will give a unique opportunity to better understand the links between AD, aging, and frailty.
First, this study is an opportunity to better understand the links between amyloid pathology and frailty. Recently, with the perspective to explore the discrepancy between brain level of AD pathology and cognitive decline, Wallace et al. suggested that frailty could moderate the relationship between AD pathology and the expression of dementia (40). They suggested that frailty could modulate the expression of AD pathology: subjects with a low degree of frailty were less prone to express AD dementia in presence of AD pathology, and inversely subjects with a high degree of frailty are more likely to express AD dementia even with low burden of AD pathology. The COGFRAIL study could allow to assess the impact of physical frailty on brain areas involved in cognitive resilience (with brain baseline MRI) and to study brain mechanisms involved in the clinical expression of frailty and amyloid pathology.
Secondarily, this study will focus on the role of nutrition in the development and progression of cognitive frailty. There is growing evidence that vitamins B6, B12, B9, polyphenol, carotenoid and omega-3 PUFA (polyunsaturated fatty acids) may play a protective role in cognitive decline (41, 42). Deficiencies in these micronutrients are common in older adults, particularly those who are frail or cognitively impaired (43, 44). They may represent a population of interest on which nutritional strategies could be targeted to slow down neurodegenerative progression. However, certain studies have provided controversial results on the effect of dietary regimens or nutritional supplementation on cognitive decline (including study of cognitive functions, and brain imaging biomarkers). One of the potential reason is the lack of data supporting probable synergies between nutrients or food groups (45, 46) because they were focused on single nutrients. Moreover, interactions with others factors such as health behaviours, ApoE genotype, or other personal characteristics (46, 47) must be taken in account to better understand direct and indirect relationships between nutrition and cognitive decline. The COGFRAIL study will give us significant information on the impact of nutrition on cognition and physical frailty using a wide range of data including blood measurement of nutritional biomarker, detailed dietary interview, clinical assessment and DEXA measurement.
Gathering blood samples and longitudinal clinical data on cognitive and physical functions (but also mood, nutrition and sensory functions) from older persons at risk of functional decline will allow us to test geroscience hypotheses. Indeed, markers of biological age are needed to better understand the heterogeneity of the aging process among individuals, to implement interventions to promote healthy aging, and to monitor the response to these interventions. To date, putative biomarkers of aging were proposed mainly for their association(s) with mortality or age-related disease, but none of them are validated for their ability to predict the decline of several functions (e.g. cognition and locomotion) (48–50). For this purpose, we will combine « omics » and hypothesis-driven approaches focused on putative biomarkers related to hallmarks of biological aging (e.g. loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, or inflammaging) (51,52). The COGFRAIL study is associated to the Inspire Research Platform on Healhty Aging and Gerosciences, a translational geriatric program (53–55).

 

Conclusion

Results of the study will help characterize the cognitive decline in frail and pre-frail patients, with important implications for the identification, management and prevention of neurocognitive disorders among frail old individuals. If mechanistic frailty-cognitive decline links are established, these results may also help optimize the early identification of patients with or even at risk of AD-dementia by taking into account physical parameters that are not conventionally looked at in AD, such as frailty parameters (e.g. gait speed) or muscle composition. Such an outcome might also open a window to novel prevention and treatment strategies in AD.

 

Funding: The COGFRAIL study has obtained funding from MSDAVENIR.
Potential Conflicts of Interest: All authors declare to have no financial relationship with any organisations that might have an interest in the submitted work, and no other relationships or activities that could appear to have influenced the submitted work.
Acknowledgement: The authors thank MSD AVENIR and its support from the beginning of the study, but also all the health professionals participating in the COGFRAIL study.
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.

 

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EFFICACY OF A COMPREHENSIVE DYSPHAGIA INTERVENTION PROGRAM TAILORED FOR THE RESIDENTS OF NURSING HOMES

 

R. Fong1,2, S.W.K. Wong3, J.K.L. Chan3, M.C.F. Tong1,2, K.Y.S. Lee1,2

 

1. Department of Otorhinolaryngology, Head and Neck Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong; 2. Institute of Human Communicative Research, The Chinese University of Hong Kong, Hong Kong; 3. Hong Kong Christian Service, Hong Kong.
Corresponding author: Raymond Fong, Rm 303, Academic Building No. 2, The Chinese University of Hong Kong, Tel: +85239439602, Email: raymondfong@ent.cuhk.edu.hk

J Frailty Aging 2020;in press
Published online October 13, 2020, http://dx.doi.org/10.14283/jfa.2020.56

 


Abstract

Oropharyngeal dysphagia is a widespread condition in older people and thus poses a serious health threat to the residents of nursing homes. The management of dysphagia relies mainly on compensatory strategies, such as diet and environmental modification. This study investigated the efficacy of an intervention program using a single-arm interventional study design. Twenty-two participants from nursing homes were included and had an average of 26 hours of intervention, including oromotor exercises, orosensory stimulation and exercises to target dysphagia and caregiver training. Four of the 22 participants exhibited improvement in functional oral intake scale (FOIS) but was not statistically significant as a group. All oromotor function parameters, including the range, strength, and coordination of movements, significantly improved. These results indicate that this intervention program could potentially improve the oromotor function, which were translated into functional improvements in some participants’ recommended diets. The validity of this study could be improved further by using standardized swallowing and feeding assessment methods or an instrumental swallowing assessment.

Key words: Dysphagia, swallowing treatment, aspiration.


 

Introduction

Oropharyngeal dysphagia is widespread in older adults (1). The risk of diseases that may lead to dysphagia increases with age and so does dysphagia (2). With aging, there is a progressive decline of muscle mass and strength as well as a decrease in connective tissue elasticity resulting in a diminishment in range of movements (3). This change with aging has been termed as primary sarcopenia whereas secondary sarcopenia refers to the same phenomenon due to diseases or a lack of nutrition (3). Swallowing dysfunction can be aggravated by sarcopenia (4). Dysphagia has adverse effects on self-esteem, socialization, and the quality of life (5). Dysphagia also has a significant impact on the nutritional status, because with difficulty in food/liquid intake, the individual is more at risk of having lowered nutritional status (2, 6). A close association has been identified between dysphagia and aspiration pneumonia (7, 8). Langmore, Skarupski (9) concluded that swallowing difficulty is a predictor of pneumonia in residents of nursing home. These findings indicate that clinicians should aim to prevent declines in swallowing in older adults to prevent nutritional and respiratory complications.
The high prevalence and fatal consequences of dysphagia in older adults have led to investigations intended to improve the prevention and management of dysphagia. One focus of swallowing rehabilitation is to improve the swallow through exercises (10). Numerous exercises targeting different structures and subsystems of the swallow have been proposed, including lingual resistance exercises, exercises on the suprahyoid muscle group and expiratory muscle strength training (2). Physiological benefit and functional gain with a reduction of frequency of malnutrition and pneumonia have been reported in older people with dysphagia after doing these exercises (2). The use of multidisciplinary interventions provides another perspective. In one study, Arahata, Oura (11) provided an average of 4.3 interventional strategies to 90 patients, including range-of-movement oromotor and swallowing structures, feeding and swallowing foods or liquids (11). The 1-year artificial nutrition-free rate was significantly higher than the historical control rates. However, that study also used interventional strategies besides swallowing therapy, including oral hygiene and other nursing interventions. The current prospective pilot study was designed to investigate the effectiveness of a set of direct swallowing therapies intended to target the swallowing functions of residents in nursing homes. The effectiveness was determined by two outcomes: Functional oral intake scale (FOIS) and a self-devised oromotor function scale.

 

Methods

Ethical approval was received from the Joint Chinese University of Hong Kong – New Territories East Cluster Clinical Research Ethics Committee (CREC Ref. No. 2019.699). All participants provided informed consent. This study was conducted at two nursing homes and two daycare centers from April 2018 to March 2019. Participants were included if their FOIS score was at 3-6 and was able to provide consent. Twenty-five participants meeting the inclusion criteria were recruited.
The pre-intervention assessment included a clinical swallowing evaluation for determining the FOIS score and devising the personalized treatment. The clinical swallowing evaluation consisted of communication ability screening, physical examination and swallow trials (10). The recommendation of diet was a clinical decision based on the components of the evaluation as above. The diets available in the nursing homes include puree, minced, soft and regular diet, which corresponded to IDDSI Level 4, 5, 6 and 7 respectively. The FOIS is a 7-point ordinal scale that documents the patient’s functional eating status, with 1 being fully dependent on tube feeding and 7 indicating no restriction or special preparation (10). The participants were assessed by four qualified speech therapists with 2–10 years of clinical experience in dysphagia management. These therapists also performed the intervention.
The FOIS score was the primary outcome of treatment, as the goal of the intervention was to improve the overall swallowing competence of the participants. The secondary outcome of treatment was an improvement in oromotor function. The range of movement, strength and rate of the tongue, lips, and jaw were measured. Individual scores were assigned for the measured range of movement (jaw, lips protrusion and spreading, tongue protrusion, lateralization, elevation/depression, and elevation of the velum), strength (jaw opening and closing, lip seal, tongue protrusion, lateralization, and elevation/depression), and rate of movement (jaw, lips, tongue protrusion, lateralization, and elevation/depression). Each structure was rated in each domain (range, strength and rate) using a 0 (no abnormality) – 5 (severe impairment) scale. A higher score indicated greater impairment of that domain. After excluding three more participants at this stage, the data analysis included 22 participants. The study population included 16 female and 6 male participants with a mean age of 86.13 (standard deviation, S.D.: 8.91) years. The demographics, medical conditions, pre- and post-treatment diet and the FOIS scores of the participants are listed in Table 1.

Table 1
Details of the participants

 

After the initial assessment, the participants were provided with a personalized intervention program targeted three main areas: oromotor exercises (range of movement, strength and coordination), dysphagia intervention (orosensory stimulation and exercises) and caregiver training. The three main areas and examples of treatment goals are detailed in Table 2. The exercises were based on the principles of resistance loading, as advocated by Sura, Madhavan (2). Although the use of thermal-tactile stimulation and its effectiveness for dysphagia management remain controversial, especially in stroke patients (12), this study applied a combination of thermal, mechanical, and chemical sensory stimuli based on the reported conclusion of Rofes, Cola (13). Each participant received an average of 26.23 hours of therapy in weekly sessions. The post-intervention assessment was conducted within 2 weeks after treatment completion and the FOIS score was calculated. The investigator who performed the post-intervention assessment was blinded to the initial FOIS score and the treatment received. Statistical analyses were performed using SPSS software ver. 23.0 (IBM, Armonk, NY, USA). The pre-treatment and post-treatment data were compared using the Wilcoxon signed rank test. A p value of <0.05 was considered to indicate statistical significance.

Table 2
Content of the tailored comprehensive intervention program

 

Results

Of the 22 participants, 4 (18.2%) had a change of FOIS score, 16 (73.7%) remained unchanged and 2 (9.1%) regressed from the pre-intervention period. The changes in FOIS was not statistically significant (Z = -1.000, p = 0.317). For the secondary outcomes, a significant change in the range of movement (Z = -3.933, p < 0.001) with the mean difference of -4.59 (S.D. = 2.82). For strength, the mean difference was -4.57 (S.D. = 4.78) and this was also significant (Z = -3.712, p < 0.001). For rate of movement, mean difference was -4.68 (S.D. = 4.00) and this was also significant (Z = -3.830, p < 0.001).

 

Discussion

Dysphagia management strategies for older adults, particularly residents of nursing homes, have focused largely on the use of compensatory strategies. The results of this pilot study demonstrate that a personalized treatment program could improve the function of underlying structures needed for swallowing. However, the effect on the overall swallowing function was not significant.
Although not all participants exhibited positive changes in terms of functional swallowing outcomes, significant improvements were observed in all three domains measured for the secondary outcome of the intervention program. Previous studies have supported the use of oromotor exercises for improving the swallowing mechanism (10). Specifically, lip and tongue resistive training has been shown to improve both the strengths of these structures and the swallowing ability (10). In most participants, improvements were noted across all three domains of oromotor function. This result indicates that participation in a robust weekly therapy program for six months could induce changes in the oromotor functioning of the treatment recipients. However, sensory aspects and the pharyngeal phase of swallowing also contribute to the overall swallowing competence. Therefore, a significant improvement in oromotor function alone may not induce adequate changes in the overall swallowing competence of the participants, as reflected by a change in the FOIS score.
In this study cohort, most of the participants were older than 90 years, and over half of the participants had a background of dementia. Therefore, the participants may have found it difficult to comprehend and retain the instructions for daily active swallowing exercises. Some of the exercises may have been performed only once per week during the therapy session. In other cases, some exercises might not have been possible, and only passive exercises would have been performed. Treatment compliance and issues with exercise selection due to limited cognitive ability might also explain why this treatment did not lead to changes in diet recommendations and FOIS scores, despite improvements in oromotor functioning. However, this study could not determine whether this type of intervention would only be efficacious for patients without dementia because of the small participant cohort.

Limitations

The degree of cognitive impairment due to dementia, or other medical conditions, could have affected the exercise selection, treatment compliance and ultimately treatment outcome. However, no uniform documentation of the cognitive ability could be retrieved across participants for a valid comparison. In the future, all participants should undergo a cognitive screening with validated tools such as the Hong Kong Brief Cognitive Test (14). The validity of this study could be improved by the inclusion of outcome measures such as the Iowa Oral Performance Instrument (IOPI Medical LLC, Redmond, WA), videofluoroscopy, endoscopy, which would enable investigators to delineate changes in the swallowing physiology and function more objectively. However, these measures were not routinely applied to people living in local nursing homes, and therefore this analysis could not be performed. To improve the validity and reliability of future studies involving residential care homes, a standardized clinical assessment such as the Mann Assessment of Swallowing Ability or the McGill Ingestive Skills Assessment (10) could be used to standardize the documentation of changes in swallowing and related functions.

 

Conclusions and implications

Few studies have investigated the treatment efficacies of swallowing and feeding intervention programs designed for residents in aged-care facilities. This study provides a good foundation for further studies of larger cohorts. The ability to extrapolate the study findings to a more general population of residents in nursing homes would enable better management of the risks associated with dysphagia and the associated quality of life. Future studies could focus on investigating the treatment efficacy in patients who can comply with all prescribed active oromotor and swallowing exercises. Alternatively, dysphagic individuals may require a more intensive intervention program or a protocol involving more passive forms of treatment. The efficacies of these alternative treatment options also require further investigation.

 

Conflict of interest: The authors declare that there is no conflict of interest.
Acknowledgments: The authors gratefully acknowledge the input from staff members at the Cheung Fat Home for the Elderly, Shun Lee Home for the Elderly, Chin Wah Day Care Centre for the Elderly, and Sham Shui Po Day Care Centre for the Elderly, as well as the speech therapists affiliated with the Hong Kong Christian Service.
Funding: This study was based on a pilot project, the “Good to Taste: Swallowing Enhancement Project for Elderly,” carried out by the Hong Kong Christian Service. This pilot project was supported financially by The Community Chest of Hong Kong. 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.

 

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FAT MASS IS NEGATIVELY ASSOCIATED WITH MUSCLE STRENGTH AND JUMP TEST PERFORMANCE

 

B.A. Moore1, D.A. Bemben2, D.H. Lein3, M.G. Bemben2, H. Singh2,3

 

1. Department of Nutrition Sciences, University of Alabama at Birmingham, Birmingham, AL, USA; 2. Department of Health and Exercise Science, University of Oklahoma, Norman, OK, USA; 3. Department of Physical Therapy, University of Alabama at Birmingham, Birmingham, AL, USA.
Corresponding author: Harshvardhan Singh, PT, PhD, Department of Physical Therapy, University of Alabama at Birmingham, 1716 9th Avenue South, SHPB#384, Birmingham, AL 35211, Telephone:  205-996-1413, Fax: 205-975-7787, Email: hsingh@uab.edu
J Frailty Aging 2020;9(4)214-218
Published online March 16, 2020, http://dx.doi.org/10.14283/jfa.2020.11

 


Abstract

Background: It is known that maintenance of muscle mass cannot prevent loss of muscle strength in older adults. Recent evidence suggests that fat mass can weaken the relationship between muscle mass and functional performance. No information exists if fat mass can independently affect muscle strength and jump test performance in middle-aged and older adults. Objective: To assess the independent relationships between fat mass, leg muscle mass, lower extremity muscle strength, and jump test performance in adults, 55-75 years of age. Design: Cross-sectional. Setting: University laboratory. Participants: Fifty-nine older adults (men, n = 27, age = 64.8 + 6.5 years; women, n = 32, age = 62.5 + 5.1 years) participated in this study. Measurements: Dual energy X-ray absorptiometry was used to measure fat mass and leg muscle mass. An average of 3 maximal countermovement jumps was used to calculate jump power and jump height. Two leg press and hip abduction strength were assessed by 1-repetition maximum testing. Results: Stepwise sequential regression analysis of fat mass and leg muscle mass versus jump test performance and measures of muscle strength after adjusting for age, height, and physical activity revealed that fat mass was negatively associated with jump height (p = 0.047, rpartial = -0.410) in men. In women, fat mass was negatively associated with jump height (p = 0.003, rpartial = -0.538), leg press (p = 0.002, rpartial = -0.544), and hip abduction strength (p < 0.001, rpartial = -0.661). Leg muscle mass was positively associated with jump power in women (p = 0.047, rpartial = 0.372) only. Conclusions: Fat mass has an independent negative relationship with jump test performance in middle-aged and older men and women. This has clinical implications for rehabilitating neuromuscular performance in middle-aged and older adults.

Key words: Body composition, muscle power, aging, muscle strength, neuromuscular performance.


 

Introduction

Aging is associated with changes in body composition such as reduced muscle mass and increased fat mass (1), which can ultimately have an adverse effect on muscle performance. For example, older adults with reduced muscle mass have lower muscle strength (2) and jump power (3). Typically, these deficits in muscle performance accelerate after the fifth decade at a rate of ~15% per decade (4). Evidence indicates that the deficits in muscle power may be greater than deficits in muscle strength (5), both of which can lead to clinically relevant implications such as decreased physical activity, functional declines, and lower quality of life. Notably, the degree of loss of muscle mass and muscle strength with aging is sex-specific with men showing greater rate of loss of muscle mass and muscle strength than women (6).
The interaction of fat mass with muscle mass and its effects on muscle performance is an area of active research interest. Previous data suggests that the maintenance of muscle mass cannot prevent  loss of muscle strength in older adults (7). A recent meta-analysis article suggested that fat mass can weaken the relationship between muscle mass and functional performance, such as mobility in older adults (8). It is known that adiposity can lead to non-optimal muscle shortening (9) and attenuated calcium signaling (10) which can adversely affect muscle force generation. Accordingly, it can be postulated that fat mass could attenuate the relationship between muscle mass and muscle performance. This is supported by reports of lower muscle strength and power in obese individuals (11).
Jump test performance is a popular technique to assess muscle power in older individuals (3,12). Specifically, the use of a mobile contact mat to assess jump performance which is reliable (13), valid (14), user friendly, and easily administered in various settings such as the home, clinics, and community gymnasium settings provides an excellent low cost opportunity to assess muscle function. To our knowledge, relationships between fat mass, muscle mass, lower extremity muscle strength, and jump test performance independent of factors including age, body weight, height, and physical activity are unknown in older adults. Specifically, the effect of sex on these relationships is unknown. Understanding these relationships could provide insight into the relative role of fat mass on muscle performance in older men and women.
Thus, the aim of this investigation was to assess sex-based differences in the independent relationships between fat mass, leg muscle mass, lower extremity muscle strength, and jump test performance in adults, aged 55-75 years of age. We hypothesized that jump test performance and lower extremity muscle strength will be negatively related to fat mass in our study participants and that its degree would be greater from women versus men.

 

Methods

Participants

Participants aged 55 – 75 years of age were recruited from the Oklahoma City metro general community and were deemed medically cleared by their personal physician prior to enrolling in the study. An a priori power analysis was used to estimate the required sample size for the study. The statistical analysis was set for a linear regression: fixed model, single regression coefficient with an effect size (f2) of 0.35, alpha error probability at 0.05, and power at 0.8. The calculated sample size was found to be 25 participants per group.
Prior to participation, volunteers obtained medical clearance from their personal physician to ensure medical stability and capability of undergoing the strength and jump testing safely. Individuals were excluded from the study if they had any condition that did not allow them to fully perform the physical tests of the study. Participants were also excluded if they had any thyroid disorders, cardiovascular diagnoses, metal in their body, any recent surgery or fracture, used tobacco within the previous 10 years, body weight greater than 136kg (because of the equipment limit) or were on steroid or hormone therapy. The local institutional review board approved this study. All participants provided written informed consent for participation in this study.

Study Design

Participants made three visits to the laboratory. In the first visit, participants gave informed consent and completed a health status questionnaire to determine study eligibility. During the second visit, participants completed physical activity and menstrual history questionnaires (women only), a total body dual energy X-ray absorptiometry (DXA) scan and familiarization with strength and jump testing. At the third visit, participants underwent jump test and muscle strength testing. Detailed explanations of the methods used can be found in our previous studies (3, 12).

Anthropometric Measurements

A wall stadiometer (Novel Products Inc, Rockton, Illinois) was used to measure height in centimeters. A digital body weight scale (Tanita Corporation of America, Arlington Heights, Illinois) was used to measure body weight in kilograms. Body mass index (BMI) was calculated using the formula, weight divided by height squared (kg/m2).

Questionnaires

All participants completed medical history and physical activity questionnaire. International Physical Activity Questionnaire, which is a valid and reliable measure of physical activity, was chosen to estimate the physical activity levels in METs/week (15). A customized menstrual history questionnaire was completed by all female participants to confirm their postmenopausal status and not taking any hormone replacement therapy.

Bone Densitometry and Body Composition

A single technician measured body composition using DXA (GE Lunar Prodigy, enCORE 2010 Software, Version 13.31.016, GE Medical Systems, Madison, Wisconsin). A quality assurance check of the DXA was performed before any data collection. Percent total body fat, fat mass, bone free lean body mass, leg muscle mass, and fat free mass were determined using a total body scan with the participant in supine, lying position. Universally acceptable cut-off values of BMI, recommended by bodies such as Center for Disease Control and Prevention/World Health Organization (16, 17) were used to categorize our participants into normal weight, overweight, and obesity. Per these cut-off values, a BMI between a) 18.5 and 24.9 is considered as normal weight, b) 25 and 29.9 is categorized as overweight, and c) greater than 30 is considered obese (16,17).  The short-term in vivo precision coefficients of variation (CV%) were as follows: 1.24% for percent total body fat, 0.64% for bone free lean body mass, 1.16% for fat mass, and 0.83% for fat free mass.

Muscle Strength Testing

Muscle strength testing has been described in our previous studies (3, 12). In short, prior to muscle strength testing, participants were familiarized to the testing procedures. On the testing day, participants pedaled a Monark 828E stationary bicycle ergometer as warm-up prior to determining 1-repetition maximum (1RM) on Cybex weight machines (Cybex International, Medway, Massachusetts) for two-legged leg press (LP), right, and left hip abduction. 1RM was determined by increasing weight progressively in increments of 9.1 to 18.2kg for LP and 2.8 to 5.6kg for hip abduction until participants failed to lift weight through the full range of motion. Participants were provided 90 seconds of rest between each lift attempt.

Jump Test Measurement

Jump power (JPow) and jump height (JHt) were assessed by Tendo FiTRODYNE power and speed analyzer (Tendo Sports Machines, Trencin, Slovak Republic) and “Just Jump” contact mat (Probotics Inc, Huntsville, Alabama), respectively. In short, the Tendo unit measures jump velocity which is then used to estimate jump power (3, 12). The “Just Jump” contact mat and accompanied handheld equipment was used to measure JHt (Probotics Inc, Huntsville, Alabama). Moreover, use of the contact mat rather than force platforms has been shown to provide reliable vertical JPow results in older adults (13). Tendo FiTRODYNE power and speed analyzer is a reliable device for measuring movement velocity (18). It is a valid and reliable technique to assess muscle power in older adults (19). Our laboratory determined CV% for JPow and JHt are 4.0% and 3.3%, respectively (3, 12).
We have described jump test performance measurement in our previous studies (3, 12). Briefly, participants moved from a standing position, flexed their knees and hips, and were instructed to jump as high and as fast as possible without tucking the legs and instructed to land with both feet on the jump mat. Each participant performed 3 successful jumps, the average of which was used for data analyses. Participants rested for 60 seconds or longer if needed between each successive jump. All the testing was done by the same tester.

Statistical Analysis

Data from a previous study were used for secondary analysis for this investigation (3, 12). Statistical Package for Social Sciences SPSS 24.0 software (SPSS Inc., Chicago, IL) to perform data analysis. All descriptive statistics are reported as mean ± standard error (SE). Independent t-tests were computed to assess sex-based differences in physical characteristics, muscle strength, jump test performance, and physical activity. Bonferroni corrections were used for multiple comparisons. Data normality was checked using skewness, kurtosis, and Shapiro-Wilk test. The average of the right and left hip abduction (HipAbd) values were used for analysis. JPow, LP and HipAbd were normalized for body mass, meaning values of JPow, LP, and HipAbd of participants were divided by their respective body mass (kg), for all calculations. JHt was corrected prior to analysis in order to account for the overestimation of JHt by the Just Jump system.(20) We split our data based on sex and then stepwise sequential linear regression analyses were used to examine which independent variables (fat mass, leg muscle mass) correlated with the outcome measures (JPow, JHt, LP and HipAbd strength) after adjusting for age, height, and physical activity in men and women. Block one of the regression model contained the independent variables of age, height, and PA. Block two was set as stepwise and contained fat mass and leg muscle mass. The alpha level was set at p < 0.05 for all the significance tests.  The magnitude of effects was measured by using Cohen’s d, with values of 0.2, 0.5, and 0.8 demonstrating small, medium, and large effects respectively.

 

Results

Physical characteristics of participants based on sex are shown in Table 1. There were no differences in age, body mass index (BMI), and fat mass (all p > 0.112). Body weight and leg muscle mass were greater in men versus women (both p < 0.001). Measures of jump test performance and muscle strength were also greater in men versus women. Men had greater JPow (p = 0.003), JHt (p < 0.001), and LP (p = 0.002) versus women. There was a trend toward greater physical activity (p = 0.08) and hip abduction (p = 0.037) in men versus women. Based on the Center for Disease Control and Prevention/World Health Organization classification of BMI(16) 54% (32/59) of the study participants were overweight or obese. A greater percentage of men (20/27 = 74%) versus women (12/32 = 39%) were overweight or obese.

Table 1 Physical characteristics, muscle strength, and jump test performance of study participants

Table 1
Physical characteristics, muscle strength, and jump test performance of study participants

Abbreviations: BMI, body mass index; PA, physical activity; MET, metabolic equivalent; JPow, jump power; JHt, jump height; HipAbd, hip abduction strength; LP, two-legged leg press strength; * Significant sex difference after Bonferroni correction with p < 0.0125.

 

Results from the step-wise sequential regression analysis are displayed in Table 2. Fat mass was negatively associated with JHt (p = 0.047) in men (a) and  JHt (p = 0.003), LP (p = 0.002), and HipAbd (p < 0.001) in women (b). Leg muscle mass was a significant predictor of JPow (p = 0.047) in women only.

Table 2 Stepwise sequential regression analyses of fat mass and leg muscle mass versus JPow, JHt, LP, and Hip Abd in men (A) and women (B). All the models were adjusted for age, height, and physical activity

Table 2
Stepwise sequential regression analyses of fat mass and leg muscle mass versus JPow, JHt, LP, and Hip Abd in men (A) and women (B). All the models were adjusted for age, height, and physical activity

Abbreviations: JPow, jump power; JHt, jump height; LP, 2-leg press strength; HipAbd, hip abduction strength. Normalized values of JPow, LP, and HipAbd to body weight were used for all calculations. β-coefficients represent changes in SD in dependent variables per SD change in predictor variable; *Significant at p < 0.05; There were no significant predictors for JPow, LP, and HipAbd in men.

 

Discussion

To our knowledge, this is the first study to report negative relationships between fat mass and i) jump test performance and ii) muscle strength independent of age, height, physical activity, and leg muscle mass in men and women, 55-75 years of age. Positive association between leg muscle mass and jump power in women only was another main finding of this study.
Muscle activation capacity could be one of the critical factors that could explain negative relationships between fat mass and muscle performance in our population (21). There is some evidence that adiposity can adversely affect muscle activation capacity in young adults (22). Specifically, higher fat mass can markedly reduce agonist muscle activation (22). Thus, in addition to the typical aging-related loss in muscle activation capacity (23), a higher adiposity can further increase the degree of loss of muscle activation in older adults. A lower muscle activation capacity could result in lower muscle fiber recruitment and thus a lower net force generation. This is supported by our findings of negative relationships between fat mass and measures of muscle strength and power. These findings are in line with previous studies of lower muscle torques in individuals with obesity (11) even with greater fat free mass (11). Thus, fat mass versus leg muscle mass can play a critical role in dictating muscle performance in individuals with greater adiposity. Interestingly, visceral adiposity is associated with increased neural drive (24) but we did not collect any data on visceral adiposity in our population. Future studies should examine the interplay of visceral adiposity and muscle performance.
Muscle morphology is a critical factor which, in part, dictates muscle performance. Adiposity has been linked to a greater adipose tissue infiltration of skeletal muscles (ATSM) (25). ATSM is associated with reduced capacity for force and power generation by muscles leading to poor muscle quality (9,26). Moreover, there is some emerging evidence that ATSM can increase the stiffness of muscle and can adversely affect muscle shortening (9). This may explain the negative association of muscle strength with fat mass in our study. A negative relationship between muscle and neuromuscular performance, and fat mass in our study can also be explained by a synergistic effect of adiposity and aging which can result in greater degree of reduction in anabolic hormones such as insulin-like growth factor-1 (27) and chronic elevation  of inflammatory cytokine such asinterleukin-6 (28)  which could decrease voluntary muscle activation and thus, can decrease muscle performance in adults with greater fat mass. A positive relationship between JPow and leg muscle mass only in women was surprising. There is some evidence (28, 29) that women compared to men have greater muscle lengthening force production. A greater muscle lengthening force production mainly dictates jump power and may explain the positive relationship between JPow and leg muscle mass in women. Men and women display unique mechanisms for aging-associated muscle atrophy (31). The loss in total number of muscle fibers with aging is lower in women versus men (30) and the degree of loss of muscle mass and  muscle strength is markedly greater in older men than women (6). This may be related to greater loss of muscle mass in men versus women seen with aging (7).  Also, greater percent of men were obese than women in our study which may have conferred biomechanical disadvantage to men for jump test performance. However, we normalized JPow for body mass which may have attenuated, in part, effect of body mass on jump test performance. Thus, an interaction of various factors such as greater muscle lengthening force production, lower rate of loss of muscle mass, and lower rate of total number of muscle fiber loss in women versus men could explain the positive relationship between JPow and leg muscle mass in women only.
We did not use force plates for jump test performance in our study which may be considered a study limitation, however, we used a jump mat which has been shown to be a valid and reliable estimate for measures of jump test performance (13, 14). Jump mat is a user-friendly, cost-effective, and mobile piece of equipment which can be used to assess jump test performance in clinics or field settings. Thus, its translation to the rehabilitation community or field settings may be more feasible than using a force plate to assess jump test performance.
Taken together, the data from our current investigation provides earliest evidence of independent, negative relationships between fat mass and 1) jump test performance, and 2) muscle strength in both men and women between 55-75 years of age. For the same age group, leg muscle mass may dictate jump power in women but not in men. This knowledge is important for designing future intervention studies to inform evidence-based musculoskeletal rehabilitation in older adults with sarcopenia and increased adiposity, and in the decision-making process regarding weight loss in obese individuals.

 

Acknowledgements: We are thankful to all the participants without which this study would not have been possible.
Conflicts of interest: None declared by the Authors.

SUPPLEMENTARY MATERIAL

 

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