self-reported disability performance-based disability social integration chronic conditions home environment

Abstract

Objectives. To examine the differences of self-reported versus performance- based disability on social integration among older adults, as well as the direct and potential moderating role of the physical and social environment on these relationships.
Methods. Using data from the 2015 National Health and Aging Trends Study (n = 2,700), two indicators of disability (self-reported, performance- based), chronic health conditions, and home environment were examined as predictors of social integration using multinomial logistic regression.
Results. Compared to older adults with self-reported disabilities, older adults with performance-based disabilities were less likely to be nonintegrated. The presence of chronic conditions moderated these associations. Home environment had a direct effect on social integration, although it did not account for disability-related differences in outcomes.
Discussion. Careful selection of disability measures and the inclusion of physical and social environmental factors is important when investigating determinants of social integration among older adults.

Social integration refers to the degree to which an individual is connected to others and to the community 1, including activities with friends, family, and/or other individuals such as supporting neighbors, joining in informal groups, using the phone, and visiting a church 2. In the United States (U.S.), lack of social integration is a major concern for older adults 3. Research suggests that approximately 28% of older adults report being lonely and 11 million older adults live alone 4, both of which contribute to high rates of morbidity and mortality 5,6. Numerous studies have shown that social integration is associated with better cognitive function, less depression, higher self-rated health, and improved sense of belonging 7,8. As such, the World Health Organization (WHO) recognizes social integration as a vital issue for aging (WHO, 2002). Understanding factors that promote social integration among older adults can help individuals achieve better outcomes and more successful aging.

The WHO disability model 9 define disability as the interplay between participation restriction, disruptions to the normal functioning of movement, and social relationships. Research has shown that, compared to the general population, older adults and those with disabilities are less likely to be socially integrated 10,11. However, other studies have added complexity to our understanding of the relationship between disability and social integration 8. For example, numerous independent studies indicate that people with disabilities experience unique barriers that could reduce the opportunities to be socially integrated into daily life such as negative attitude toward disabilities 12, functional limitations 13, lack of transportation 14, unemployment 15, and lack of adequate social support systems and geographic barriers 16. Additionally, the presence of chronic health conditions 17 and demographic characteristics such as gender 18, and race/ethnicity 19 influence social integration. These results suggest that older adults with disabilities, in particular those with chronic conditions, may be at greater risk for social isolation.

Studies have defined disability in a variety of ways. The majority of nationally representative surveys in the U.S. (e.g., Behavioral Risk Factor Surveillance System, American Community Survey) utilize the self-reported activities of daily living (ADL) 20 to indicate the presence of disability 21. By this measure, findings between studies tend to be inconsistent. For example, some studies with older adults have found a strong connection between social integration and ADL function 22-25, while other studies show that ADL function and social integration are not always associated 26. These inconsistencies may be attributable to the influence of the availability of social support. For example, married older men report better ADL function while unmarried older men report worse ADL function 27-29.

Clinical researchers often use objective, performance-based measures such as gait speed and standing balance to represent whether or not an individual has the capacity to perform certain necessary actions 30,31. These objective measures reflect physical decline or functional limitation, in anticipation of future disability 32,33. As with studies based upon self-reported disability measures, findings based upon performance-based disability measures also tend to be mixed. For example, in a longitudinal study, Buchman and colleagues 34 found that poor global motor function was associated with less social integration. In a separate study, however, they also found that social network size was not associated with either baseline motor function nor the rate of decline 35. In a cross-sectional study, better gait speed was associated with having a social network and strong social ties 36. However, unlike with some studies based upon self-reported disability measures 28, gender did not mediate these relationships 36, perhaps due to socio-economic factors 6. den Ouden and colleagues 37 found that better ADL scores were longitudinally associated with leg extensor strength and handgrip strength only, after adjusting for covariates. In a separate study 38, this group also found that markers of subclinical vascular abnormalities indicated greater performance-based disability. However, markers of vascular abnormalities were not associated with self-reported disability longitudinally. Taken together, this body of research suggests that performance-based disability and self-reported disability, while related, may in fact be separate constructs.

Environmental gerontology has argued that the physical environments in which older adults live influence well-being, self-reported and performance-based disability status, and social integration 39,40. Older adults tend to spend much of their time at home 41. When the home environment, including the physical layout and condition of the home, does not support their functional limitation, they experience a lower functional ability 42, which can impede social integration 40. Given this, when older adults indicate having a disability, this may in part be attributable to inadequate interior conditions at home. Previous studies argue that the home environment, including clutter and disrepair, contribute to mobility difficulties 43 and reflect general social disadvantage 44. Several independent studies also examine factors associated with disordered living conditions, social isolation 45 and high demand for housekeeping 44,45. However, few studies to date have investigated the extent to which disability and conditions of the home environment, independently as well as in conjunction with one another, are essential to social integration.

The purpose of this study is to examine the differential impact of self-reported versus performance-based disability on social integration among older adults, as well as the direct and potential moderating role of the physical and social environment on these relationships. The identification of people with disabilities varies across federally and state-sponsored publically available data sets. Putnam et al. 20 have shown that, although most data sets had a measure of self-reported disability (the ADL limitation), several data sets used the presence of at least one specific diagnosis condition to represent the presence of disability (e.g., performance-based disability). These different disability measures have been utilized interchangeably in disability and health studies. However, few studies have examined the relative relationships of the two disability measures and home environment on social integration. Using a measure of self-reported and performance-based disability simultaneously in the same study allows us to contrast their unique impacts on social integration. This study is significant because findings could reinforce the importance of social integration for older adults with disabilities, regardless of how disability may be defined. Findings also provide critical information focused on the development of tailored interventions to promote social integration among older adults with both self-reported and performance-based disabilities, because the disability measures themselves may skew findings related to social integration.

Based upon the studies described before, we hypothesize that:

H1. The degree of association between two different disability measures and social integration will be different; H2. Home interior conditions will explain some of the differences in social integration between those with self-reported versus performance-based disabilities. METHODS

The Institutional Review Board of the first author’s university approved this study (HUM00184720).

DATA AND SAMPLE

Data are drawn from the 2017 National Health and Aging Trends Study (NHITS) 46, a nationally representative sample of Medicare recipients aged 65 or older. The purpose of NHATS is to assess disability experiences, social circumstances, and general health and well-being in later life. The Institutional Review Board at Johns Hopkins University approved the NHATS. NHATS utilizes a stratified, three-stage sampling method and oversamples those who are aged 90 or older and those who were African American. Details of the sampling strategy and design are available elsewhere 47. A total of 8,245 older adults participated in NHATS 2017 with a response rate of 71%.

MEASURES

For the current study, social integration was measured with five dichotomous (0/1) items reflecting social activities in the previous month: 1) visiting family and friends; 2) attending religious services; 3) participating in clubs, classes, or other organized activities; 4) going out for enjoyment, and; 5) doing volunteer work. We developed three classifications of social integration, consistent with previous studies 48,49. Participants with a total score of zero were classified as nonintegrated, those with a total score of 1 were classified as partially integrated, and those with a total score of 2 or more were classified as fully integrated. We recognize that previous studies based upon the NHATS included both social integration and social network size to represent social isolation 49,50. We treated them separately and included social integration only in this analysis because social network and social integration may impact differently upon people with disabilities due to their unique physical and social barriers 51.

Disability was assessed with two measures: the 6-item Activities of Daily Living scale (ADL) 52 and the 3-item Short Physical Performance Battery (SPPB) 30. Participant ADL limitations served as a measure of self-reported disability for the present study. The ADL measure included self-reported difficulty with six activities in the previous month: 1) eating; 2) dressing; 3) toileting; 4) bathing/washing; 5) moving inside by oneself, and; 6) effort required to go outside by oneself. For each item, participants indicated “no difficulty,” “a little”, “some”, or “a lot”. Similar to a previous study using ADL limitations as an indicator of disability 53, those with at least a little difficulty on any item were classified as having a self-reported disability and those with no difficulty on any item were classified as not having a self-reported disability.

The SPPB is a clinician-rated assessment of lower extremity functioning in older adults and served as a measure of performance-based disability for the present study. It includes gait speed, standing balance, and time to stand up from a chair. NHATS performed the standardized scoring procedure, which is explained in more detail elsewhere 54. SPPB total scores may range from 0 to 12. Based on previous research 30,55, participants with a score of 8 or greater were classified as having a performance-based disability and those with a score of 7 or lower were classified as not having a performance-based disability. Lastly, we developed a single dichotomous variable, with discreet categories, for which those with self-reported disabilities but without performance-based disabilities were classified as 0 and those with performance-based disabilities but without self-reported disabilities were classified as 1.

The presence of chronic conditions was assessed according to whether participants had been diagnosed by a doctor with any of six conditions: 1) a heart attack or myocardial infarction; 2) heart disease including angina or congestive heart failure; 3) diabetes; 4) lung disease such as emphysema, asthmas, or chronic bronchitis; 5) stroke, or; 6) cancer. We coded the responses as Yes (1) if a respondent reported at least one chronic condition, or No (0) if a respondent reported no chronic conditions.

The presence of disrepair inside participants’ homes was measured through direct observations by NHATS interviewers about the presence of flooring disrepair (no/yes), broken furniture (no/yes), and trip hazards (no/yes). Affirmation of at least one indicator was coded as presence. Clutter inside the home also was assessed by interviewer observation and was classified into no clutter or clutter.

Age was obtained at the time of the interview and only available categorically. For this study, age was dichotomized as 65-74 years old versus greater than 75 years old. Gender was categorized into male or female. Race/ethnicity was dichotomized into two groups: White, not Hispanic or other. Education was originally assessed in NHATS by nine categorical responses ranging from “no schooling completed” to “master’s professional, or doctoral”. We dichotomized this variable into “less than or equal to high school graduate” versus “greater than high school”.

DATA ANALYSIS

Frequencies, means, and standard deviations were calculated as appropriate for demographic variables, disability, and other independent variables. Items were coded so that higher scores indicated the presence of a condition. Multinomial logistic regression analyses with interaction effects were performed using the Mplus 8.2 56, NOMINAL option to examine the relationships of the binary independent variables with three levels of the social integration dependent variable. The analyses used a maximum likelihood robust method with the fully socially integrated group as the reference group. This yielded comparisons of a nonintegrated group with a fully integrated group and of a partially integrated group with a fully integrated group. For the interaction terms, Mplus produced single estimates for the model parameters instead of class-specific estimates (e.g., the use of 1.00 as the reference value) in the multinomial logistic regression 56. We utilized a 95% confidence interval to identify significant predictors.

RESULTS

We included older adults with self-reported disabilities only and those with a performance-based disability only in this current study to meet the study objectives. Respondents with missing data on the required variables (i.e., who did not indicate responses) were excluded from this study. Thus, we analyzed 2,700 out of 8,245 participants from the 2017 NHATS dataset. Descriptive analyses showed that participants with both self-reported and performance-based disabilities who were excluded from this study were more likely to be old, Caucasian, and have an associate degree or higher. Those without either disability who were excluded from this study were more likely to be young, have disrepair but no clutter inside the home, and be socially integrated.

As summarized in Table I, the characteristics of the participants showed that older adults with performance-based disabilities were more likely to be educated, Caucasian, and less likely to be non-integrated, have at least one chronic condition, and have disrepair or clutter inside the home.

H1. TWO DISABILITY MEASURES AND SOCIAL INTEGRATION

In the comparisons between the nonintegrated group and the fully integrated group (reference group) (Tab. II), all main independent variables except chronic conditions and disrepair significantly differed between the two groups. The relative odds ratio for performance-based disability (SPPB) was 0.03, indicating that, compared with those with self-reported disabilities (ADL), people with performance-based disabilities were less likely to be classified as nonintegrated. Additionally, the relative odds ratio for the two-way interaction between performance-based disability and chronic condition was 0.30, revealing that those with performance-based disabilities, as well as chronic conditions, were less likely to be classified as nonintegrated.

H2. HOME INTERIOR CONDITIONS AND SOCIAL INTEGRATION

The relative odds ratios for clutter were 0.31 (severe) and 0.01 (partial), respectively, indicating that, compared to those without clutter, people with clutter were less likely to be classified into the nonintegrated and the partially integrated groups. However, the relative odds ratios for the interaction between disability and clutter were not significant (Tab. III).

Because the relative odds ratios of the interactions between performance-based disability and chronic conditions and between performance-based disability and social network were contradictory, we examined the bivariate relationships of these variables using descriptive statistics. The results indicated that, although older adults in the non-integrated group were more likely to perceive difficulties in activities such as eating, dressing, toileting, bathing/washing, moving about independently inside the home, and having to make an effort to go outside (p < .05).

We also conducted a simple logistic regression analysis with a dichotomous outcome, comparing the nonintegrated group with the combined partially and fully integrated group. The interaction between having a disability and chronic conditions was similar to the multinomial logistic model comparing partially integrated to fully integrated. This result shows that the unique differences between two disability measures in the degree of social integration could not be detected with a simple logistic regression analysis.

DISCUSSION

Identifying the association of self-reported versus performance-based disability, as well as environmental factors, on older adults’ experiences of social integration has the potential to enhance our understanding of past and future research in this field. This enhanced understanding may allow us to more appropriately allocate resources and develop targeted programs to best meet the needs of older adults with disabilities in the community. In this study, we found that two different disability measures differently impacted social integration, with older adults with performance-based disabilities reporting better social integration compared to older adults with self-reported disabilities. This association was moderated by the presence of chronic conditions (in the model comparing nonintegrated to fully integrated). The home environment (disrepair, clutter) did not interact with disability to explain differences in social integration.

Our results generally confirm previous research showing that having a disability is associated with less social integration 8. We expanded on this research by including both self-reported and performance-based disability measures in the same study to examine the relative impact of each. Consistent with our hypothesis, we found differences in the effect of the disability measures on social integration. In our study, older adults with performance-based disabilities were more likely than those with self-reported disabilities to be socially integrated, providing support for previous research showing that certain components of the two disability types may be overlapping but that, overall, they are distinct from one another 57. Additionally, compared to performance-based measures, self-reported ADL function may be related to psychosocial factors such as depressive symptoms 57, pain 58, and care dependence 59. Older adults with self-reported disabilities could have more psychological and social challenges in their lives than those with performance-based disabilities only in this study.

It is also important to recognize that different disability measures are based upon samples of individuals experiencing different types of disabilities, which influence the study findings. This study purposefully restricted the analytic sample to those who reported either self-reported disability or performance-based disability. Those with self-reported disabilities but without performance-based disabilities could include frail older adults without any medical diagnoses who may not have adequate social support systems. Those with performance-based disabilities but without self-reported disabilities could include individuals with congenital disabilities. Although their unmet needs are highly prevalent 60,61, those with congenital disabilities may utilize their support systems to engage in ADLs. Further studies are needed to identify the characteristics of these disability groups in order to more fully interpret results. The current study provides further evidence for researchers and clinicians and underscores the importance of clearly defining different disability populations.

We considered the direct impact of the home environment on social integration, as well as the potential moderating effect of these factors with disability on integration. Similar to previous studies 62, we found that physical barriers in the form of clutter in the home were associated with less social integration. This finding is consistent with the basic understanding put forth by environmental gerontology. Previous studies have shown that clutter links to cognitive and other physiological declines. For example, older adults with hoarding disorder have shown deficits in memory, attention, and executive functioning 63. Other factors associated with less social integration include loneliness 64, depression and distress 65, lack of sleep and fatigue 66, and lack of social support 48. Therefore, future research and intervention development projects should include the mental health status of participants and other similar considerations when working to promote social integration.

Our study found that older adults with performance-based disabilities and chronic health conditions are less likely to be nonintegrated, compared to older adults with performance-based disabilities and no chronic health conditions. Previous research suggests that having a chronic health condition increases one’s utilization of social support (e.g., friends, family, caregivers), resulting in increased social integration 67 The impact of having a chronic condition on social integration for people with performance-based disabilities would be an essential topic to investigate in future studies.

LIMITATIONS

This study has several limitations. First, we used a cross-sectional design. Thus, our results cannot be interpreted as causal. Second, this study did not assess the same activities between self-reported disability and performance-based disability, nor did we have available in NHATS an objective, third-party measure of self-reported disability, both of which limit our ability to compare the predictive value of self-reported and performance-based disability 68. Thirdly, we followed the previous studies to define self-reported disability and performance-based disability, another study used a different cut-off point 69. Our findings cannot generalize other disability studies. Finally, although clutter and home arrangement have been linked to mental health conditions, our findings cannot generalized to these studies. NHATS includes limited psychosocial variables to assess stress, coping, and psychological function. It is crucial to consider these factors when examining social integration.

CONCLUSIONS

This study demonstrated that two different disability measures characterize older adults and suggest substantial differences in predicting social integration. This calls for recognizing the impact of the selection of disability measures on social integration and similar psychosocial outcomes in future studies. It also is vital to examine factors associated with these differences and to develop interventions covering the characteristics of self-reported disability, performance-based disability, and ADL support systems. People with self-reported disabilities may need support to expand social contacts and social engagement beyond their existing social network. By applying a more comprehensive approach to study disability and aging, environment, and social integration, it may be possible to identify additional moderating and mediating factors. This will provide clearer guidance for how to intervene to improve social integration in later life.

Conflict of interest statement

The authors declare no conflict of interest.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author contributions

The authors contribuited equally to the work.

Ethical consideration

This study was approved by the Institutional Review Board at the University of Michigan (HUM00184720).

The research was conducted ethically, with all study procedures being performed in accordance with the requirements of the World Medical Association’s Declaration of Helsinki.

Figures and tablesDisability type Performance-based Self-reported P-value** Variable Total raw sample 1885 815   Social integration     < .000 0= severe 2% 10%   1= partial 6% 27%   2= full 92% 63%   Disability     < .052 1. SPPB limitation 100% 0   0. ADL limitation 0 100%   Chronic conditions       Means (S.D.)* 2.29 (1.34) 3.27 (1.53) < .000 1= present 51% 68% < .000 0= not present 49% 32%   Disrepair     < .002 1= present 5% 10%   0= not present 95% 90%   Clutter     < .006 1= present 16% 32%   0= not present 84% 68%   Age     < 0.81 0= 65-74 90% 90%   1= 75-79 10% 10%   Education     < .004 0= <= High school or GED 27% 49%   1= > High school 63% 51%   Gender     <.062 0= male 44% 46%   1= female 56% 54%   Race     <.000 1= Caucasian 79% 62%   0= African American/Hispanic/Others 21% 38%   * indicates the standard deviation; ** indicates statistically significance of the chi square test at < .05. Table I.Participants’ characteristics. Predictor No Integration vs Full Integration(reference) Estimate (E.E.) Odds ratio 95% CL Lower Upper Performance-based disability -3.56(0.96) 0.03 0.01 0.01, 0.17 Chronic condition -1.84(1.92) 0.16 0.03 1.92 Disrepair 5.39(3.39) 3.56 0.13 8.70 Clutter -5.88(2.71) 0.01 0.00 0.44 Age 0.35(0.28) 1.41 0.73 2.77 Education -0.64(0.28) 0.53 0.37 1.11 Gender 0.32(0.29) 1.38 0.77 2.39 Race -1.10(0.31) 0.33 0.21 0.68           Interactions (1 x 1)Disability x chronic conditions 1.18(0.76) 0.30 0.11 0.57 Disability x disrepair -0.84(1.24) 0.43 0.08 4.91 Disability x clutter 1.98(0.92) 7.26 0.95 9.42 Abbreviations. CL: confidence intervals; EE: the error of the estimate. The main analysis and the interaction analysis were conducted separately. Table II.Parameter estimates, relative odds ratios, and 95% confidence intervals for the final multinomial logistic regression analysis; No integration versus full integration. Predictor Partial integration vs Full integration (reference) Estimate (E.E.) Odds ratio 95% CL Lower Upper Performance-based disability -1.56(0.41) 0.21 0.02 0.46 Chronic conditions 0.83(1.03) 0.44 0.73 1.43 Disrepair -0.49(1.86) 0.62 0.02 10.16 Clutter -2.04(1.19) 0.31 0.02 0.48 Age -0.06(0.17) 0.94 0.56 1.13 Education -0.73(0.16) 0.48 0.34 0.65 Gender 0.01(0.17) 1.00 0.72 1.37 Race -0.60(0.17) 0.55 0.57 0.79 Interactions (1 x 1)   Disability x chronic conditions 0.37(0.35) 1.45 0.32 1.07 Disability x disrepair 0.38(0.63) 1.46 0.86 1.62 Disability x clutter 0.65(0.39) 1.92 0.11 1.41 Abbreviations. CL: confidence intervals; EE: the error of the estimate. The main analysis and the interaction analysis were conducted separately. Table III.Parameter estimates, relative odds ratios, and 95% confidence intervals for the final multinomial logistic regression analysis; partial integration versus full integration. ReferencesHooyman N, Kiyak HA. Social gerontology: a multidisciplinary perspective. 9. Allyn &amp; Bacon: Boston, MA; 2011. Levasseur M, Richard L, Gauvin L. Inventory and analysis of definitions of social participation found in the aging literature: proposed taxonomy of social activities. Soc Sci Med. 2010; 71:2141-2149. DOI U.S. Department of Health and Human Services. Healthy People 2020. 2012. Publisher Full Text Roberts AW, Ogunwole SU, Blakeslee L. The population 65 years and older in the United States: 2016-American Community survey reports. 2018. Publisher Full Text Khazem LR. Physical disability and suicide: recent advancements in understanding and future directions for consideration. Curr Opin Psychol. 2018; 22:18-22. DOI Shankar A, McMunn A, Demakakos P. Social isolation and loneliness: prospective associations with functional status in older adults. Health Psychol. 2017; 36:179. DOI Tomaka J, Thompson S, Palacios R. The relation of social isolation, loneliness, and social support to disease outcomes among the elderly. J Aging Health. 2006; 18:359-384. Courtin E, Knapp M. Social isolation, loneliness and health in old age: a scoping review. Health Soc Care Community. 2017; 25:799-812. DOI Nagi SZ. A study in the evaluation of Disabil Rehabil potential: concepts, methods, and procedures. American Journal of Public Health and the Nations Health. 1964; 54:1568-1579. Cacioppo JT, Hawkley LC, Norman GJ. Social isolation. Ann N Y Acad Sci. 2011; 1231:17. DOI Malcolm M, Frost H, Cowie J. Loneliness and social isolation causal association with health-related lifestyle risk in older adults: a systematic review and meta-analysis protocol. Syst Rev. 2019; 8:48. DOI Simonsick EM, Kasper JD, Phillips CL. Physical disability and social interaction: factors associated with low social contact and home confinement in disabled older women (The Women’s Health and Aging Study). J Gerontol B Psychol Sci Soc Sci. 1998; 53:S209-S217. DOI Kenyon S, Lyons G, Rafferty J. Transport and social exclusion: investigating the possibility of promoting inclusion through virtual mobility. J Transp Geogr. 2002; 10:207-219. DOI Bezyak JL, Sabella SA, Gattis RH. Public transportation: an investigation of barriers for people with disabilities. J Disabil Policy Stud. 2017; 28:52-60. DOI United States Department of Labor Bureau of Labor Statistics. Persons with a disability: labor force characteristics summary 2019. 2020. Publisher Full Text Tittman SM, Harteau C, Beyer K. The effects of geographic isolation and social support on the health of Wisconsin women. WMJ. 2016; 115:65-69. Griffith LE, Raina P, Levasseur M. Functional disability and social participation restriction associated with chronic conditions in middle-aged and older adults. J Epidemiol Community Health. 2017; 71:381-389. DOI Ang S. Social participation and health over the adult life course: does the association strengthen with age?. Soc Sci Med. 2018; 206:51-59. DOI Taylor RJ, Chatters LM, Taylor HO. Race and objective social isolation: older African Americans, Black Caribbeans, and Non-Hispanic Whites. J Gerontol B Psychol Sci Soc Sci. 2019; 74:1429-1440. DOI Putnam M, Molton IR, Truitt AR. Measures of aging with disability in US secondary data sets: Results of a scoping review. Disabil Health J. 2016; 9:5-10. DOI Wiener JM, Hanley RJ, Clark R. Measuring the activities of daily living: comparisons across national surveys. J Gerontol. 1990; 45:S229-S237. DOI de Jong Gierveld J, Van Tilburg T, Dykstra PA. Cambridge handbook of personal relationships. University Press: Cambridge, UK; 2006. Holt-Lunstad J, Smith TB, Baker M. Loneliness and social isolation as risk factors for mortality: a meta-analytic review. Perspect Psychol Sci. 2015; 10:227-237. DOI James BD, Boyle PA, Buchman AS. Relation of late-life social activity with incident disability among community-dwelling older adults. J Gerontol A Biol Sci Med Sci. 2011; 66:467-473. DOI Kotian DB, Mathews M, Parsekar SS. Factors associated with social isolation among the older people in india. J Geriatr Psychiatry Neurol. 2018; 31:271-278. DOI Rubio E, Lázaro A, Sánchez-Sánchez A. Social participation and independence in activities of daily living: a cross sectional study. BMC Geriatrics. 2009; 9:26. DOI Avlund K, Lund R, Holstein BE. The impact of structural and functional characteristics of social relations as determinants of functional decline. J Gerontol B Psychol Sci Soc Sci. 2004; 59:S44-S51. DOI Antonucci TC, Akiyama H. An examination of sex differences in social support among older men and women. Sex Roles. 1987; 17:737-749. DOI Smith GL, Banting L, Eime R. The association between social support and physical activity in older adults: a systematic review. Int J Behav Nutr Phys Act. 2017; 14:56. DOI Vasunilashorn S, Coppin AK, Patel KV. Use of the Short Physical Performance Battery Score to predict loss of ability to walk 400 meters: analysis from the InCHIANTI study. J Gerontol A Biol Sci Med Sci. 2009; 64:223-229. DOI Peel NM, Kuys SS, Klein K. Gait speed as a measure in geriatric assessment in clinical settings: a systematic review. J Gerontol A Biol Sci Med Sci. 2013; 68:39-46. DOI Guralnik JM, Ferrucci L. Assessing the building blocks of function: utilizing measures of functional limitation. Am J Prev Med. 2003; 25:112-121. DOI Nagi SZ. An epidemiology of disability among adults in the United States. Milbank Mem Fund Q Health Soc. 1976;439-467. Buchman AS, Boyle PA, Wilson RS. Association between late-life social activity and motor decline in older adults. Arch Intern Med. 2009; 169:1139-1146. DOI Buchman AS, Boyle PA, Wilson RS. Loneliness and the rate of motor decline in old age: the Rush Memory and Aging Project, a community-based cohort study. BMC Geriatrics. 2010; 10:77. DOI Merchant RA, Liu SG, Lim JY. Factors associated with social isolation in community-dwelling older adults: a cross-sectional study. Qual Life Res. 2020;1-7. DOI den Ouden ME, Schuurmans MJ, Brand JS. Physical functioning is related to both an impaired physical ability and ADL disability: a ten year follow-up study in middle-aged and older persons. Maturitas. 2013; 74:89-94. DOI den Ouden ME, Schuurmans MJ, Mueller-Schotte S. Do subclinical vascular abnormalities precede impaired physical ability and ADL disability?. Exp Gerontol. 2014; 58:1-7. DOI Wahl H-W, Weisman GD. Environmental gerontology at the beginning of the new millennium: reflections on its historical, empirical, and theoretical development. Gerontologist. 2003; 43:616-627. Wahl H-W, Iwarsson S, Oswald F. Aging well and the environment: toward an integrative model and research agenda for the future. Gerontologist. 2012; 52:306-316. Krantz-Kent R, Stewart J. How do older Americans spend their time. Monthly Lab Rev. 2007; 130:8. Wahl H-W, Fänge A, Oswald F. The home environment and disability-related outcomes in aging individuals: what is the empirical evidence?. Gerontologist. 2009; 49:355-367. DOI Keeney T, Jette AM. Individual and Environmental determinants of late-life community disability for persons aging with cardiovascular disease. Am J Phys Med Rehabil. 2019; 98:30. Cornwell EY. Social resources and disordered living conditions: evidence from a national sample of community-residing older adults. Res Aging. 2014; 36:399-430. Cornwell EY. Household disorder, network ties, and social support in later life. J Marriage Fam. 2016; 78:871-889. DOI Johns Hopkins University. National Health and Aging Trends Study (NHATS). 2011. Publisher Full Text Montaquila J, Freedman VA, Spillman B. Development of round 1 survey weights. Johns Hopkins University School of Public Health: Baltimore, MD; 2012. Publisher Full Text Cornwell EY, Waite LJ. Social disconnectedness, perceived isolation, and health among older adults. J Health Soc Behav. 2009; 50:31-48. DOI Cudjoe TK, Roth DL, Szanton SL. The epidemiology of social isolation: National Health &amp; Aging Trends study. J Gerontol B Psychol Sci Soc Sci. 2018;gby037. DOI Pohl JS, Cochrane BB, Schepp KG. Measuring social isolation in the national health and aging trends study. Res Gerontol Nurs. 2017; 10:277-287. DOI Shandra CL. Disability as inequality: social disparities, health disparities, and participation in daily activities. Soc Forces. 2018; 97:157-192. DOI Freedman VA, Kasper JD, Cornman JC. Validation of new measures of disability and functioning in the National Health and Aging Trends Study. J Gerontol A Biol Sci Med Sci. 2011; 66:1013-1021. DOI Frochen S, Mehdizadeh S. Functional status and adaptation: measuring activities of daily living and device use in the National Health and Aging Trends study. J Aging Health. 2018; 30:1136-1155. DOI Guralnik JM, Simonsick EM, Ferrucci L. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 1994; 49:M85-M94. DOI Sun DQ, Huang J, Varadhan R. Race and fall risk: data from the National Health and Aging Trends study (NHATS). Age Ageing. 2016; 45:120-127. Mplus version 8.2 [computer program]. Muthén & Muthén. 2018. Kempen GI, Steverink N, Ormel J. The assessment of ADL among frail elderly in an interview survey: self-report versus performance-based tests and determinants of discrepancies. J Gerontol B Psychol Sci Soc Sci. 1996; 51:P254-P260. DOI Connolly D, Garvey J, McKee G. Factors associated with ADL/IADL disability in community dwelling older adults in the Irish longitudinal study on ageing (TILDA). Disabil Rehabil. 2017; 39:809-816. DOI Millán-Calenti JC, Tubío J, Pita-Fernández S. Prevalence of functional disability in activities of daily living (ADL), instrumental activities of daily living (IADL) and associated factors, as predictors of morbidity and mortality. Arch Gerontol Geriatr. 2010; 50:306-310. DOI Noreau L, Noonan V, Cobb J. Spinal Cord Injury Community survey: understanding the needs of Canadians with SCI. Top Spinal Cord Inj Rehabil. 2014; 20:265-276. DOI Casey R. Disability and unmet health care needs in Canada: a longitudinal analysis. Disabil Health J. 2015; 8:173-181. DOI Brenner AB, Clarke PJ. Understanding socioenvironmental contributors to racial and ethnic disparities in disability among older Americans. Res Aging. 2018; 40:103-130. DOI Roane DM, Landers A, Sherratt J. Hoarding in the elderly: a critical review of the recent literature. Int Psychogeriatr. 2017; 29:1077-1084. DOI Petersen J, Kaye J, Jacobs PG. Longitudinal relationship between loneliness and social isolation in older adults: results from the cardiovascular health study. J Aging Health. 2016; 28:775-795. DOI Taylor HO, Taylor RJ, Nguyen AW. Social isolation, depression, and psychological distress among older adults. J Aging Health. 2018; 30:229-246. DOI Cho JH-J, Olmstead R, Choi H. Associations of objective versus subjective social isolation with sleep disturbance, depression, and fatigue in community-dwelling older adults. Aging Ment Health. 2019; 23:1130-1138. DOI Koch G, Wakefield BJ, Wakefield DS. Barriers and facilitators to managing multiple chronic conditions: a systematic literature review. West J Nurs Res. 2015; 37:498-516. DOI Shulman LM, Pretzer-Aboff I, Anderson KE. Subjective report versus objective measurement of activities of daily living in Parkinson’s disease. Mov Disord. 2006; 21:794-799. DOI Leonardi M, Bickenbach J, Ustun TB. The definition of disability: what is in a name?. Lancet. 2006; 368:1219-1221. DOI