jfa journal

AND option

OR option

FREQUENCY OF CONDITIONS ASSOCIATED WITH DECLINES IN INTRINSIC CAPACITY ACCORDING TO A SCREENING TOOL IN THE CONTEXT OF INTEGRATED CARE FOR OLDER PEOPLE

 

E. González-Bautista1, P. de Souto Barreto1,2, K. Virecoulon Giudici1, S. Andrieu1,2, Y. Rolland1,2, B. Vellas1,2, for the MAPT/DSA group*

 

1. Gerontopole of Toulouse, Institute of Aging, Toulouse University Hospital (CHU Toulouse), Toulouse, France; 2. UPS/Inserm UMR1027, University of Toulouse III, Toulouse, France; *The members are listed at the end of the manuscript.
Corresponding author: Emmanuel González-Bautista. Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), 37 Allée Jules Guesde, 31000 Toulouse, France. Mobile 06 22 10 14 96 emmanuel.scout@gmail.com

J Frailty Aging 2020;in press
Published online August 7, 2020, http://dx.doi.org/10.14283/jfa.2020.42

 


Abstract

Background: The screening tool of the Integrated Care for Older People (ICOPE Step 1), designed to detect declines in the domains of intrinsic capacity, has been incipiently investigated in older adult populations. Objectives: To retrospectively estimate the frequency of priority conditions associated with declines in intrinsic capacity according to an adaptation of the screening tool ICOPE Step 1 among participants of the Multidomain Alzheimer Preventive Trial (MAPT). Design: A cross-sectional retrospective analysis from the baseline assessment of the MAPT. Setting: The data was gathered during a preventive consultation for cardiovascular risk factors in memory clinics in France. Participants : Seven hundred fifty-nine older adults aged 70-89 years with memory complaints, allocated to the multidomain groups of the MAPT study. Measurements: Five domains of intrinsic capacity (cognition, locomotion, nutrition, sensorial, and psychological) were assessed using a screening tool similar to the ICOPE Step 1 (MAPT Step 1). The frequency of six conditions associated with declines in intrinsic capacity (cognitive decline, limited mobility, malnutrition, visual impairment, hearing loss, and depressive symptoms) was obtained for older adults with memory complaints participating in the MAPT study. Results: Overall, 89.3% of the participants had one or more conditions associated with declines in intrinsic capacity. The overall frequency of each condition was: 52.2% for cognitive decline, 20.2% for limited mobility, 6.6% for malnutrition, 18.1% for visual impairment, 56.2% for hearing loss, and 39% for depressive symptoms. Conclusion: After being screened with an adaptation of the ICOPE step 1 (MAPT step 1) tool, 9/10 older adults had one or more conditions associated with declines in intrinsic capacity. The relative frequency differs across conditions and could probably be lower in a population without memory complaints. The frequency of screened conditions associated with declines in IC highlights how relevant it is to develop function-centered care modalities to promote healthy aging.

Key words: Intrinsic capacity, screening, physical functions, integrated care, older adults.

Abbreviations: CCHA: Clinical Consortium for Healthy Ageing; COPD: Chronic obstructive pulmonary disease; FA: Functional ability; IC: Intrinsic capacity; ICOPE: Integrated Care for Older People; MAPT: Multidomain Alzheimer Preventive Trial; NCD: Non-communicable disease; OA: Older adults; WHO: World Health Organization.


 

Background

Screening for early declines of intrinsic capacity (IC) is crucial for the implementation of the Integrated Care for Older People (ICOPE)(1). The World Health Organization (WHO) Clinical Consortium for Healthy Ageing (CCHA) and other public health and aging experts developed the ICOPE guidelines. The objective of the ICOPE guidelines is to help key stakeholders in the health and social care arenas to design and implement integrated person-centered models of care (1–3).
The ICOPE approach might prevent care-dependency by timely detecting and managing conditions associated with declines in intrinsic capacity (IC). IC is the composite of all physical and mental capacities of an individual, organized in five domains: cognition, mobility, nutrition, sensorial, and psychological. The interaction between the IC and the environment determines functional ability and healthy aging (4,5). The WHO ICOPE approach has, thus, the goal of helping health systems support healthy aging (4) through the maintenance of optimal functional ability levels during aging.
The clinical care pathways proposed by the ICOPE (1) start with a screening process (ICOPE Step 1). The purpose of the screening is to detect conditions associated with declines in IC at the community level, namely cognitive decline, limited mobility, malnutrition, visual impairment, hearing loss, and depressive symptoms. People identified as having normal IC levels will receive general health advice (i.e., physical activity, nutrition). In contrast, those with IC declines will receive an in-depth assessment (ICOPE Step 2) to confirm or rule such declines. Afterward, they will follow the next steps in the care pathway (i.e., searching the causes of low IC levels, designing a person-centered care plan).
For health service providers, ICOPE Step 1 has a strategic role because it opens the door for the subsequent steps in the healthcare pathway. By managing the adequate «filter» to identify the individuals who can benefit the most from health and social interventions, the healthcare system could enhance the effective use of the available resources.
We have recently reviewed the literature on the topic (in press) and observed only ten original studies on the topic. None of those studies investigated the frequency of low levels of IC according to the screening tool. To our knowledge, measurements of conditions associated with declines in intrinsic capacity, according to ICOPE Step 1 have not been reported so far. Therefore, this study aimed to retrospectively estimate the frequency of conditions associated with declines in intrinsic capacity according to an adaptation of the screening tool ICOPE Step 1 among participants of the Multidomain Alzheimer Preventive Trial (MAPT).

 

Methods

This study uses cross-sectional data to describe the baseline frequency of conditions associated with IC declines among the participants of the Multidomain Alzheimer Preventive Trial (MAPT). The MAPT was not designed to assess the ICOPE screening; thus, we used a retrospective approach to define the variables of interest according to the availability of data. The detailed methodology of MAPT has been described elsewhere(6, 7). Briefly, MAPT was a 3-year randomized controlled trial on the effect of a multidomain intervention (nutritional and physical activity counseling, cognitive training, and annual preventive consultations for the management of cardiovascular risk factors and the detection of functional impairments) with and without supplementation of omega-3 polyunsaturated fatty acids (PUFA) on the prevention of cognitive decline among community-dwelling adults aged 70 years and older. The trial protocol (ClinicalTrials.gov identifier: NCT00672685) was approved by the French Ethical Committee located in Toulouse (CPP SOOM II) and was authorized by the French Health Authority. All participants signed their consent before any study assessment.

Participants

Inclusion criteria for the MAPT study were meeting at least one of three conditions: a) spontaneous memory complaint expressed to their physician, b) limitation in one instrumental activity of daily living (IADL), or c) slow gait speed (≤0.8 m/s). Exclusion criteria comprised participants with a Mini-Mental State Examination (MMSE) score < 24, diagnosis of dementia, the limitation for any of the basic activities of daily living, and those taking PUFA supplements at baseline.
The 759 subjects allocated to the multidomain intervention groups of MAPT constitute our study sample. Data on the five domains of IC was available only for them because they underwent a preventive consultation with a physician who assessed for the hearing and vision capacities. The rest of the 1,679 participants initially enrolled in MAPT were lacking data on the sensorial domain.

IC domains assessment – Step 1 (screening)

We followed the recommendations from the WHO ICOPE Handbook to operationalize the ICOPE Step 1 tool(1). To be consistent with the terms used in the Handbook, we used «cognitive decline,» «limited mobility,» «malnutrition,» «visual impairment,» «hearing loss» and «depressive symptoms» to refer to the conditions associated with declines in IC. These terms are not equivalent to clinical diagnoses.
The same items recommended by the WHO were used to evaluate three domains: cognition, locomotion, and vitality/nutrition. Nevertheless, due to data availability, we adapted the operationalization of the following conditions associated with declines in IC: visual impairment: was assessed by self-reported visual acuity items; hearing loss: was measured with item number 3 of the screening version of the hearing handicap inventory for the elderly (HHSE-S(8,9)); depressive symptoms: were defined according to items 2 and 7 of the Geriatric Depression Scale (GDS-15) (10), which were judged by three experts (one geriatrician, one general practitioner, and one researcher in clinical gerontology) as being the most similar items compared to those recommended by WHO. This resulting adapted screening tool was then called «MAPT Step 1» (Table 1).
Specifically, for hearing loss, we used the validated HHIE-S(8) because studies have validated this instrument against pure tone audiometry. Sindhusake et al. (11) concluded that HHIE-S has adequate sensitivity and specificity for detecting moderate hearing loss (audiometry hearing threshold of >40 dB). The HHIE-S cut-off >8 points is established in the guidelines of the American Speech-Language-Hearing Association(12) as a criterion for a referral to further audiological testing.
More sophisticated measurements of IC have been published but are not feasible in a clinical routine setting(13,14). A screening procedure like ICOPE Step 1 may help to target an at-risk population that would, then, receive in-depth assessments and a closer follow-up.

Table 1
Comparison of the operationalization of the conditions associated with declines in IC between the ICOPE handbook and the definitions applied in MAPT study

*Participants were explicitly asked for each of the items in the time and spatial orientation, and not only an open-ended question. The participant was recorded as with cognitive decline if he/she was wrong to tell the date (number and name of the day, month, year), or wrong to tell the name of the hospital, the level of the building, department and region.
†We used item number 3 of the HHIE-S because of its similarity with the whisper test.

 

IC domains in-depth assessment

The following tests were performed for an in-depth assessment of the IC domains:
• Cognition: Mini-Mental State Examination (MMSE) (15).
• Locomotion: Short Performance Physical Battery (SPPB) (16)
• Vitality/nutrition: Mini Nutritional Assessment (full version MNA)(17).
• Vision: Monoyer vision chart (18).
• Hearing: Hearing Handicap Inventory for the Elderly – Screening version (HHIE-S) (8).
• Psychological: 15-item Geriatric Depression Scale (GDS-15) (10).

Statistical Analysis

We used percentages to report the frequency of the declines in IC in our study population and by age and sex subgroups. Scores of the in-depth assessments were described using means and standard deviation (SD). Data were analyzed using STATA 14®.

 

Results

The mean age of our study population was 75.2 years (SD=4.3), 63.6% of them were women, and 28.9% reported 12 years or more of formal education (Table 2). Overall, 89.3% of the population presented one or more conditions associated with declines in IC (87.4% among females, 92.8% among males). Table 3 shows the frequency of conditions associated with declines in IC by domain. Relative frequency of the conditions of interest and mean scores of the tests used for in-depth assessment for sex and age-groups are reported in Supplementary Table S1.

Table 2
Sex, frailty status, number of instrumental activities impaired and mean values of functional performance tests by age group among participants of the MAPT Study

MMSE= mini-mental state examination. SPPB= short performance physical battery. MNA= mini nutritional assessment full version. HHIE-S= Hearing Handicap Inventory for the Elderly – Screening version. GDS= Geriatric Depression Scale; * provided in decimal acuity. For reference, 0.8 decimal = 20/25 imperial= 6/7.5 metric = 0.1 LogMAR.

Table 3
Frequency of conditions associated with declines in IC according to the ICOPE step 1 screening tool by age group among participants of the MAPT Study

*Maximum of possible conditions is six because the sensorial domain includes visual impairment and hearing loss

 

Cognitive domain

Half of the studied population presented signs of cognitive decline. Table 4 shows the details of the cognitive items of MAPT Step 1. Failing in the word recall section of the MMSE was three times more frequent than failing in the orientation section. In all age groups, the most frequently mistaken word recall was for the last word in the list given to the participants (i.e., cigarette, flower, door – participants less often recalled the word «door»).

Table 4
Prevalence of cognitive sub-domains and mistaken item from the Mini-Mental State Examination (MMSE) including alternative definitions for cognitive decline by age group among participants of the MAPT Study

* Areas of political division. †MAPT participants used the French version during the study.

 

Mobility domain

Overall, the mean of the time to perform five chair rises was 11.9 seconds (SD=4.5), with age-specific averages ranging from 11.0 (70-74 years) to 16.0 seconds (85-89 years). For the group aged 85-89 years (n=22), the cut-off of 14 seconds proposed by ICOPE Step 1 was at the percentile 52. Further details about the distribution of the sex- and age-specific chair rise times are provided in Supplementary Table S1.

Vitality/Nutrition domain

The mean score in the MNA was 27.6 points, ranging from 27.7 in the youngest group to 26.8 in the oldest group. The frequency of self-reported weight loss or appetite loss was lower than 5% for all the age groups, except for the appetite loss in those aged 80-84 years (7.3%).

Sensorial domain

Vision. In our study population, 92.1% of participants used glasses, contact glasses, implants, or magnifiers at the time of the interview. Even with their supportive devices, up to 14.5% of the participants found it hard to read a newspaper or watch television.
Hearing. Among the participants, 18.2% were using a hearing assistive device at the time of the interview. The screening question for hearing loss identified 55% of those aged 70-74 years and 68% of those aged 85-89 years as positive for hearing loss.

 

Discussion

Our study is the first to describe the frequency of the IC declines according to an adaptation of the ICOPE Step 1 screening tool (MAPT step 1) in a selected cohort of memory clinic attendees. Overall, 89.3% of the participants had one or more conditions associated with declines in IC, according to MAPT Step 1 (87.4% among females, 92.8% among males). Nine in every ten screened older adults would be referred to a specialized, in-depth evaluation. It should be noted, however, that MAPT participants expressed memory complaints at recruitment.
We found a high demand for an in-depth assessment. Consider that the MAPT population is more fit than others reported in French studies (except perhaps for cognitive function due to the inclusion criteria). Compared to a random sample used in the French Three-City Study published by Avila-Funes et al. (19), our population was slightly older (mean age 74.1, SD=5.2 vs. 75.2 years, SD=4.3), reported higher levels of educational attainment (>12 years: 17.0% vs. 28.9%) and a lower frequency of frailty (7.0% vs. 3.2%). Therefore, our findings might be underestimating the frequency of IC declines detected by MAPT Step 1 in a real-world population of users of the healthcare system (except for cognitive decline). Our results highlight the need for adapting our health care system to improve the assessment of functions to prevent functional decline. For example, people detected with signs of cognitive decline using the screening tool ICOPE Step 1 could benefit from multidomain interventions (20–22).
Half of the study population showed signs of cognitive decline. Interestingly, participants more frequently failed in selected items (i.e., recalling the name of the day or the last word in a list of three). Therefore, it will be interesting to explore the domain and item’s capacity to predict health events such as frailty incidence in future studies.
Regarding locomotion, the cut-off time to perform five chair rises deserves further investigation (the ICOPE handbook suggests 14 seconds). A cut-off of 15 sec was used in a study measuring the time to complete ten rather than five chair-rises (23). A meta-analysis by Bohannon concluded that 11.4 and 12.7 seconds are suitable cut-off values among subjects aged 60-69 and 80-89, respectively (24). In the SPPB validation study, Guralnik et al. (16) found that 13.7 sec corresponded to the 50th percentile of performance in the chair rise test in a population of more than 5,000 American people aged 71 years or older in 1981. However, current generations might have a better physical performance than those assessed 30 years ago. Establishing age- tailored cut-offs for the chair rise test would allow for a better classification of the performance levels. They would not add difficulty to the implementation of the ICOPE care pathway.
Malnutrition was the least frequent condition. The average score for the full MNA was 27.6, which is higher than the cut-off often used to define the risk of malnutrition (23.5) (17). We think that clinicians should address anorexia and weight loss even if the MNA test if above the cut-off designed for malnutrition. According to the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition in adults (25), reduced food intake/assimilation and weight loss are sufficient to integrate the diagnosis of malnutrition. Also, the Beck depression inventory (26) and by the Center for Epidemiologic Studies Depression (CES-D) scale (27) consider the loss of appetite as a depressive symptom. Moreover, those who leave alone are at higher nutritional risk (28).
For the psychological domain, we did not use the exact questions suggested in the ICOPE screening tool Step 1 because they were not available in MAPT Study. Therefore, we selected from the GDS-15 the two items that more closely matched the ICOPE definition (Table 1). The frequency of depressive symptoms in our study was high (39%), compared to a previous investigation among French older adults (13.8% evaluated with the CES-D in people aged 75 years; SD=6.8) (29). Shared risk factors for cognitive decline and depressive symptoms can explain this difference. Due to MAPT inclusion criteria, participants were at increased risk for cognitive decline, and more than 40% presented mild cognitive impairment (MCI). For instance, using the MAPT Step 1 tool resulted in an overlap of 72% of the participants according to their cognitive decline and depressive symptoms status (7 out of 10 were simultaneously free from or afflicted by both conditions). The connexions across the IC domains are a hallmark of the ICOPE approach (30, 31). Timely interventions targeting these interactions can prevent further losses of ADL ADLs (32).
In the visual domain, we used three questions related to self-reported problems for vision, even when using correction devices (Table 1). Of note, the frequency of visual impairment in our study may have been underestimated because the questions used in MAPT are more specific than the general question proposed in ICOPE Step 1. Furthermore, we did not consider if the person had hypertension or diabetes, as suggested in the ICOPE tool. Evidence suggests that more than half of the cases of visual impairment in older ages are due to cataract and refractive errors, with less than 5% due to diabetic retinopathy (33–35). Perceived difficulty in reading a journal or watching television was reported in 15% of the population wearing vision aids. We consider this ratio as an indicator of unsatisfied demand for visual correction adjustment.
Our hearing loss estimates show that the age-specific frequency of hearing handicap was higher than the ones reported in the study of Wiley et al. performed with 3,471 non-Hispanic whites in Wisconsin, USA. Our figures were similar to those reported by Tomioka et al. (36), with 1,731 community-dwelling older adults from Nara and Osaka, Japan. The different age distribution could explain the dissimilarities.
Our study has strengths, such as being among the first to report the frequency of conditions associated with declines in the five IC domains in a selected cohort of memory clinic attendees. Moreover, the MAPT Step 1 and the ICOPE Step 1 use the same items for most of the IC domains. Therefore, the frequency of declines on visual, hearing, and psychological domains might have been different from our findings if the WHO ICOPE screening tool had been used. On the other hand, some limitations should be mentioned. There was a potential selection bias towards cognitive decline, given that having a spontaneous memory complaint was one of the inclusion criteria in MAPT. However, in a sensitivity analysis removing participants with a cognitive decline in the MAPT Step 1, 78% of the remaining population still had one or more conditions associated with declines in IC (Supplementary Table S2). Our data should not be generalized to other populations. Compared to the age and sex distribution of French older adults, our population overrepresented women (57.1% vs. 63.6%) and adults aged 70-79 years (39.1% vs. 49.8%) (37).
In summary, almost 90% of adults aged 70 years and older in a selected cohort of memory clinic attendees had at least one condition associated with declines in IC. Frequencies varied from 52.2% in the cognitive domain to 6.2% in the nutrition domain. These findings suggest that implementing the ICOPE Step 1 at the community level will help screen for conditions associated with declines in intrinsic capacity. The frequency of declines in IC can provide health systems managers with an estimation of the amount and the type of resources needed to implement the ICOPE clinical pathways. For example, satisfying the demand for visual aids adjustment, or recruitment of health workforce with psychological training. Interesting questions emerged from this descriptive study. For example, should some items be changed to increase the chances of detecting most of the people at risk? Also, are age-specific cut-offs the most suitable approach for some IC domains in the ICOPE screening tool (notably, locomotion)?

 

MAPT/DSA group: Principal investigator: Bruno Vellas (Toulouse); Coordination: Sophie Guyonnet; Project leader: Isabelle Carrié; CRA: Lauréane Brigitte; Investigators: Catherine Faisant, Françoise Lala, Julien Delrieu, Hélène Villars; Psychologists: Emeline Combrouze, Carole Badufle, Audrey Zueras; Methodology, statistical analysis and data management: Sandrine Andrieu, Christelle Cantet, Christophe Morin; Multidomain group: Gabor Abellan Van Kan, Charlotte Dupuy, Yves Rolland (physical and nutritional components), Céline Caillaud, Pierre-Jean Ousset (cognitive component), Françoise Lala (preventive consultation) (Toulouse). The cognitive component was designed in collaboration with Sherry Willis from the University of Seattle, and Sylvie Belleville, Brigitte Gilbert and Francine Fontaine from the University of Montreal. Co-Investigators in associated centres: Jean-François Dartigues, Isabelle Marcet, Fleur Delva, Alexandra Foubert, Sandrine Cerda (Bordeaux); Marie-Noëlle-Cuffi, Corinne Costes (Castres); Olivier Rouaud, Patrick Manckoundia, Valérie Quipourt, Sophie Marilier, Evelyne Franon (Dijon); Lawrence Bories, Marie-Laure Pader, Marie-France Basset, Bruno Lapoujade, Valérie Faure, Michael Li Yung Tong, Christine Malick-Loiseau, Evelyne Cazaban-Campistron (Foix); Françoise Desclaux, Colette Blatge (Lavaur); Thierry Dantoine, Cécile Laubarie-Mouret, Isabelle Saulnier, Jean-Pierre Clément, Marie-Agnès Picat, Laurence Bernard-Bourzeix, Stéphanie Willebois, Iléana Désormais, Noëlle Cardinaud (Limoges); Marc Bonnefoy, Pierre Livet, Pascale Rebaudet, Claire Gédéon, Catherine Burdet, Flavien Terracol (Lyon), Alain Pesce, Stéphanie Roth, Sylvie Chaillou, Sandrine Louchart (Monaco); Kristelle Sudres, Nicolas Lebrun, Nadège Barro-Belaygues (Montauban); Jacques Touchon, Karim Bennys, Audrey Gabelle, Aurélia Romano, Lynda Touati, Cécilia Marelli, Cécile Pays (Montpellier); Philippe Robert, Franck Le Duff, Claire Gervais, Sébastien Gonfrier (Nice); Yannick Gasnier and Serge Bordes, Danièle Begorre, Christian Carpuat, Khaled Khales, Jean-François Lefebvre, Samira Misbah El Idrissi, Pierre Skolil, Jean-Pierre Salles (Tarbes). MRI group: Carole Dufouil (Bordeaux), Stéphane Lehéricy, Marie Chupin, Jean-François Mangin, Ali Bouhayia (Paris); Michèle Allard (Bordeaux); Frédéric Ricolfi (Dijon); Dominique Dubois (Foix); Marie Paule Bonceour Martel (Limoges); François Cotton (Lyon); Alain Bonafé (Montpellier); Stéphane Chanalet (Nice); Françoise Hugon (Tarbes); Fabrice Bonneville, Christophe Cognard, François Chollet (Toulouse). PET scans group: Pierre Payoux, Thierry Voisin, Julien Delrieu, Sophie Peiffer, Anne Hitzel, (Toulouse); Michèle Allard (Bordeaux); Michel Zanca (Montpellier); Jacques Monteil (Limoges); Jacques Darcourt (Nice). Medico-economics group: Laurent Molinier, Hélène Derumeaux, Nadège Costa (Toulouse). Biological sample collection: Bertrand Perret, Claire Vinel, Sylvie Caspar-Bauguil (Toulouse). Safety management: Pascale Olivier-Abbal. DSA Group: Sandrine Andrieu, Christelle Cantet, Nicola Coley.
Funding: The present work was performed in the context of the Inspire Program, a research platform supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856). 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.
Acknowledgements: NA
Authors contributions: PB, BV and EG conceived the study. EG, statistics and manuscript writing. KV, PB, LM, BV and SA provided inputs and reviewed the manuscript. BV and SA are PIs in MAPT.
Funding section: The present work was performed in the context of the Inspire Program, a research platform supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856). 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. “This study received funds from Alzheimer Prevention in Occitania and Catalonia (APOC Chair of Excellence – Inspire Program). The MAPT study was supported by grants from the Gérontopôle of Toulouse, the French Ministry of Health (PHRC 2008, 2009), Pierre Fabre Research Institute (manufacturer of the omega-3 supplement), ExonHit Therapeutics SA, and Avid Radiopharmaceuticals Inc. The promotion of this study was supported by the University Hospital Center of Toulouse. The data sharing activity was supported by the Association Monegasque pour la Recherche sur la maladie d’Alzheimer (AMPA) and the INSERM-University of Toulouse III UMR 1027 Unit».
Conflict of interest: The authors declare no competing interest relevant to this article.
Ethical standard: This study did not include any experiments involving humans or other animals.

 

SUPPLEMENTARY MATERIAL

 

References

1. World Health Organization. Integrated care for older people (ICOPE): Guidance for person-centred assessment and pathways in primary care. [Internet]. Geneva: WHO; 2019 [cited 2019 Nov 14]. 87 p. Available from: https://apps.who.int/iris/bitstream/handle/10665/326843/WHO-FWC-ALC-19.1-eng.pdf?sequence=17
2. Thiyagarajan JA, Araujo de Carvalho I, Peña-Rosas JP, Chadha S, Mariotti SP, Dua T, et al. Redesigning care for older people to preserve physical and mental capacity: WHO guidelines on community-level interventions in integrated care. PLOS Med [Internet]. 2019 Oct 18 [cited 2020 Jan 8];16(10):e1002948. Available from: http://dx.plos.org/10.1371/journal.pmed.1002948
3. World Health Organisation. WHO Clinical Consortium on Healthy Ageing. Report of consortium meeting 1-2 December 2016 in Geneva, Switzerland. 2017;(December).
4. World Health Organization. World Report on Ageing and Health. Geneva: WHO Press; 2015.
5. Cesari M, De Carvalho IA, Thiyagarajan JA, Cooper C, Martin FC, Reginster JY, et al. Evidence for the domains supporting the construct of intrinsic capacity. Vol. 73, Journals of Gerontology – Series A Biological Sciences and Medical Sciences. Oxford University Press; 2018. p. 1653–60.
6. Vellas B, Carrie I, Gillette-Guyonnet S, Touchon J, Dantoine T, Dartigues JF, et al. MAPT study: A multidomain approach for preventing Alzheimer’s disease: design and baseline data. J Prev Alzheimer’s Dis [Internet]. 2014 Jun [cited 2020 Feb 5];1(1):13–22. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26594639
7. Andrieu S, Guyonnet S, Coley N, Cantet C, Bonnefoy M, Bordes S, et al. Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): a randomised, placebo-controlled trial. Lancet Neurol. 2017 May 1;16(5):377–89.
8. Ventry IM, Weinstein BE. The hearing handicap inventory for the elderly: A new tool. Ear Hear. 1982;3(3):128–34.
9. Bagai A. Does This Patient Have Hearing Impairment ? JAMA. 2008;295(4):416–28.
10. Yesavage JA, Sheikh JI. Geriatric Depression Scale (GDS). Clin Gerontol [Internet]. 1986 Nov 18;5(1–2):165–73. Available from: https://doi.org/10.1300/J018v05n01_09
11. Sindhusake D, Mitchell P, Smith W, Golding M, Newall P, Hartley D, et al. Validation of self-reported hearing loss. The blue mountainshearing study. Int J Epidemiol. 2001;30(6):1371–8.
12. Association AS-L-H. Guidelines for Audiologic Screening. www.asha.org/policy [Internet]. 1997 [cited 2020 Feb 7];1–64. Available from: http://www.asha.org/policy/GL1997-00199/
13. Beard JR, Jotheeswaran AT, Cesari M, Araujo de Carvalho I. The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open [Internet]. 2019 Nov 2 [cited 2019 Nov 7];9(11):e026119. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31678933
14. Gutiérrez-Robledo LM, García-Chanes RE, Pérez-Zepeda MU. Allostatic Load as a Biological Substrate to Intrinsic Capacity: A Secondary Analysis of CRELES. J Nutr Health Aging [Internet]. 2019 [cited 2019 Nov 5];23(9):788–95. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31641727
15. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98.
16. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A short physical performance battery assessing lower extremity function: Association with self-reported disability and prediction of mortality and nursing home admission. Journals Gerontol. 1994;49(2).
17. Vellas B, Guigoz Y, Garry PJ, Nourhashemi F, Bennahum D, Lauque S, et al. The mini nutritional assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition. 1999 Feb;15(2):116–22.
18. World Health Organization. World report on vision. Vol. 214, World report on vision. Geneva: WHO Press; 2019. 180–235 p.
19. Ávila-Funes JA, Helmer C, Amieva H, Barberger-Gateau P, Le Goff M, Ritchie K, et al. Frailty among community-dwelling elderly people in france: The three-city study. Journals Gerontol – Ser A Biol Sci Med Sci. 2008;63(10):1089–96.
20. Rosenberg A, Mangialasche F, Ngandu T, Solomon A, Kivipelto M. Multidomain Interventions to Prevent Cognitive Impairment, Alzheimer’s Disease, and Dementia: From FINGER to World-Wide FINGERS. J Prev Alzheimer’s Dis [Internet]. 2020 [cited 2020 Mar 23];7(1):29–36. Available from: http://www.ncbi.nlm.nih.gov/pubmed/32010923
21. Cherian L, Wang Y, Fakuda K, Leurgans S, Aggarwal N, Morris M. Mediterranean-Dash Intervention for Neurodegenerative Delay (MIND) Diet Slows Cognitive Decline After Stroke. J Prev Alzheimer’s Dis [Internet]. 2019 [cited 2020 Mar 23];6(4):267–73. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31686099
22. Udeh-Momoh C, Price G, Ropacki MT, Ketter N, Andrews T, Arrighi HM, et al. Prospective Evaluation of Cognitive Health and Related Factors in Elderly at Risk for Developing Alzheimer’s Dementia: A Longitudinal Cohort Study. J Prev Alzheimer’s Dis [Internet]. 2019 [cited 2020 Mar 23];6(4):256–66. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31686098
23. Hardy R, Cooper R, Shah I, Harridge S, Guralnik J, Kuh D. Is chair rise performance a useful measure of leg power? Aging Clin Exp Res. 2010;22(5–6):412–8.
24. BOHANNON RW. Reference Values for the Five-Repetition Sit-To-Stand Test: a Descriptive Meta-Analysis of Data From Elders. Percept Mot Skills. 2006;103(5):215.
25. Cederholm T, Jensen GL, Correia MITD, Gonzalez MC, Fukushima R, Higashiguchi T, et al. GLIM criteria for the diagnosis of malnutrition – A consensus report from the global clinical nutrition community. J Cachexia Sarcopenia Muscle [Internet]. 2019 Feb 1 [cited 2020 Feb 27];10(1):207–17. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/jcsm.12383
26. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An Inventory for Measuring Depression. Arch Gen Psychiatry. 1961;4(6):561–71.
27. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401.
28. Suthutvoravut U, Tanaka T, Takahashi K, Akishita M, Iijima K. Living with Family yet Eating Alone is Associated with Frailty in Community-Dwelling Older Adults: The Kashiwa Study. J frailty aging [Internet]. 2019 [cited 2020 Mar 23];8(4):198–204. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31637406
29. Montagnier D, Barberger-Gateau P, Jacqmin-Gadda H, Dartigues JF, Rainfray M, Pérès K, et al. Evolution of prevalence of depressive symptoms and antidepressant use between 1988 and 1999 in a large sample of older French people: Results from the personnes agées quid study. J Am Geriatr Soc [Internet]. 2006 Dec [cited 2020 Feb 13];54(12):1839–45. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17198488
30. Kiiti Borges M, Oiring de Castro Cezar N, Silva Santos Siqueira A, Yassuda M, Cesari M, Aprahamian I. The Relationship between Physical Frailty and Mild Cognitive Impairment in the Elderly: A Systematic Review. J frailty aging [Internet]. 2019 [cited 2020 Mar 23];8(4):192–7. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31637405
31. Kwan RYC, Leung AYM, Yee A, Lau LT, Xu XY, Dai DLK. Cognitive Frailty and Its Association with Nutrition and Depression in Community-Dwelling Older People. J Nutr Health Aging [Internet]. 2019 Dec 1 [cited 2020 Mar 23];23(10):943–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/31781723
32. McGrath R, Erlandson KM, Vincent BM, Hackney KJ, Herrmann SD, Clark BC. Decreased Handgrip Strength is Associated With Impairments in Each Autonomous Living Task for Aging Adults in the United States. J frailty aging. 2019;8(3):141–5.
33. Zhu RR, Shi J, Yang M, Guan HJ. Prevalences and causes of vision impairment in elderly chinese: A socioeconomic perspective of a comparative report nested in Jiangsu Eye Study. Int J Ophthalmol. 2016 Jul 18;9(7):1051–6.
34. Murthy GVS, Vashist P, John N, Pokharel G, Ellwein LB. Prevalence and causes of visual impairment and blindness in older adults in an area of India with a high cataract surgical rate. Ophthalmic Epidemiol. 2010 Aug;17(4):185–95.
35. Bourne RRA, Jonas JB, Bron AM, Cicinelli MV, Das A, Flaxman SR, et al. Prevalence and causes of vision loss in high-income countries and in Eastern and Central Europe in 2015: Magnitude, temporal trends and projections. Br J Ophthalmol. 2018 May 1;102(5):575–85.
36. Tomioka K, Ikeda H, Hanaie K, Morikawa M, Iwamoto J, Okamoto N, et al. The Hearing Handicap Inventory for Elderly-Screening (HHIE-S) versus a single question: reliability, validity, and relations with quality of life measures in the elderly community, Japan. Qual Life Res [Internet]. 2013 Jun [cited 2020 Feb 12];22(5):1151–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22833152
37. United Nations Department of Economic and Social Affairs. Population Division. Ageing Profiles [Internet]. Ageing Profiles. 2019 [cited 2020 Feb 13]. Available from: https://population.un.org/ProfilesOfAgeing2019/index.html