Preprint
Article

This version is not peer-reviewed.

Participation and the Well-Being of Older Adults with ADL Disabilities: A Longitudinal Application of the International Classification of Functioning, Health, and Disability

Submitted:

17 April 2026

Posted:

20 April 2026

You are already at the latest version

Abstract
Applying the International Classification of Functioning, Disability, and Health (ICF) framework, this study examined longitudinal associations among activities of daily living (ADL) limitations, participation, and well-being among community-dwelling older adults with ADL difficulty. We used five waves (2015–2019; Waves 5–9) of the National Health and Aging Trends Study (NHATS; baseline n = 5,346). Well-being was measured using 11 NHATS items spanning affect, life satisfaction, and perceived control/self-efficacy. Participation was operationalized using five dichotomous indicators of engagement in common social and community activities. Autoregressive cross-lagged structural equation models were estimated using full-information maximum likelihood, and indirect associations were assessed with bootstrap standard errors. We found that ADL limitations were associated with lower subsequent participation, while greater participation predicted higher subsequent well-being across waves. Indirect associations linking ADL limitations to later well-being through participation were small and time-dependent. Overall, the findings are consistent with an ICF-informed perspective in which participation plays a dynamic role in linking activity limitations and well-being over time, although effect sizes were modest.
Keywords: 
;  ;  ;  ;  ;  ;  
Abstract
Applying the International Classification of Functioning, Disability, and Health (ICF) framework, this study examined longitudinal associations among activities of daily living (ADL) limitations, participation, and well-being among community-dwelling older adults with ADL difficulty. We used five waves (2015–2019; Waves 5–9) of the National Health and Aging Trends Study (NHATS; baseline n = 5,346). Well-being was measured using 11 NHATS items spanning affect, life satisfaction, and perceived control/self-efficacy. Participation was operationalized using five dichotomous indicators of engagement in common social and community activities. Autoregressive cross-lagged structural equation models were estimated using full-information maximum likelihood, and indirect associations were assessed with bootstrap standard errors. We found that ADL limitations were associated with lower subsequent participation, while greater participation predicted higher subsequent well-being across waves. Indirect associations linking ADL limitations to later well-being through participation were small and time-dependent. Overall, the findings are consistent with an ICF-informed perspective in which participation plays a dynamic role in linking activity limitations and well-being over time, although effect sizes were modest.
As population aging accelerates worldwide, the number of older adults living with limitations in everyday functioning is projected to increase substantially in coming decades (Chatterji et al., 2015; United Nations, 2017). At the same time, policy and research attention has increasingly shifted toward aging in community settings, as most older adults prefer to remain in their own homes rather than institutional care (Wick, 2017; Rosenwohl-Mack et al., 2020). Within this context, understanding how older adults with activity limitations maintain well-being while aging in place has become a central concern for gerontology and public health research (Vanleerberghe et al., 2017).
Difficulty performing activities of daily living (ADLs), such as eating, bathing, dressing, toileting, or basic mobility, represents a common form of activity limitation in later life. ADL limitations reflect difficulty performing routine self-care and mobility activities rather than the presence of specific diseases, and they are among the most frequently reported forms of disability among older adults in the United States (Courtney-Long et al., 2015; Okoro et al., 2018). Because ADL limitations can constrain independence and daily activities, they are consistently associated with lower levels of participation and poorer well-being (Boslaugh & Andresen, 2006; Dunlop et al., 2015; Li et al., 2020).
Traditional models of successful aging have often emphasized the avoidance of disease and disability, implicitly positioning older adults with functional impairments as aging “unsuccessfully” (Rowe & Kahn, 1997). Although influential, this perspective has been critiqued for marginalizing a growing segment of the older population for whom aging with chronic conditions and activity limitations has become normative rather than exceptional (Boudiny, 2013; Vanleerberghe et al., 2017). These critiques have prompted calls for alternative frameworks that emphasize functioning, adaptation, and quality of life within social and environmental contexts rather than disease avoidance alone.
One such framework is the World Health Organization’s International Classification of Functioning, Disability, and Health (ICF), which conceptualizes disability as a dynamic process shaped by interactions among body functions and structures, activities, participation, and contextual factors (World Health Organization, 2001; Kostanjsek, 2011). Within the ICF, activity limitations (such as ADL difficulty) and participation (involvement in life situations) are conceptually distinct but interrelated components of functioning (Rejeski et al., 2008; Whiteneck & Dijkers, 2009). This distinction has been widely adopted in gerontological research to examine how activity limitations translate into restrictions in social and community engagement (Freedman, 2009; Liu, 2017).
Figure 1. Interactions between the components of ICF (WHO 2001:18).
Figure 1. Interactions between the components of ICF (WHO 2001:18).
Preprints 209042 g001
Participation is a central construct within the ICF framework and refers to involvement in social, community, and civic life. In this study, the term community participation is used to describe observable indicators of the broader ICF construct of participation, operationalized using engagement in common social and community activities. Prior research has consistently shown that higher levels of participation are associated with better psychosocial outcomes among older adults, including greater life satisfaction and lower loneliness (Pinquart & Sörensen, 2000; Fokkema et al., 2012). Among older adults with activity limitations, participation may provide opportunities to maintain social roles, autonomy, and a sense of meaning despite physical constraints (Freedman et al., 2012; Hammel et al., 2015).
Although well-being is not a discrete domain within the ICF taxonomy, it is commonly treated in ICF-informed aging research as a distal subjective outcome reflecting individuals’ evaluations of their lives and psychological functioning in context (Freedman et al., 2011; Graybill et al., 2014). Subjective well-being encompasses emotional experiences, life evaluation, and perceived control or self-efficacy, all of which have been shown to be associated with participation and community engagement in later life (Pinquart & Sörensen, 2000; Freedman et al., 2012). From this perspective, participation may be prospectively associated with well-being by supporting social connectedness, role fulfillment, and adaptive coping, whereas activity limitations may indirectly undermine well-being by constraining opportunities for engagement.
Despite extensive cross-sectional evidence linking ADL limitations, participation, and well-being, longitudinal research examining how these constructs unfold over time remains limited, particularly among older adults with established activity limitations (Anaby et al., 2011; Li et al., 2020). Much of the existing literature relies on cross-sectional designs that cannot assess temporal ordering or examine whether participation is prospectively associated with subsequent well-being after accounting for prior levels of functioning and psychosocial status.
Guided by an ICF-informed perspective emphasizing the distinction between activity limitation and participation, the present study uses five waves of data from the National Health and Aging Trends Study (NHATS) to examine longitudinal associations among ADL limitations, participation, and well-being among community-dwelling older adults with ADL difficulty. Specifically, this study assesses whether participation is prospectively associated with well-being over time and whether participation constitutes a statistical pathway linking ADL limitations and later well-being.

Methods

Data and Sample

Data were drawn from the National Health and Aging Trends Study (NHATS), an ongoing, nationally representative longitudinal study of Medicare beneficiaries aged 65 years and older in the United States. NHATS has conducted annual in-person interviews since 2011 using a stratified sampling design and oversampling of the oldest-old and non-Hispanic Black older adults to enhance national representativeness.
The present study used data from Waves 5 through 9 (2015–2019). This analytic window was selected for two reasons. First, Wave 5 introduced a replenishment cohort, providing a refreshed nationally representative baseline for subsequent longitudinal analyses. Second, the five-wave period offers sufficient repeated observations for cross-lagged modeling while limiting complexity and instability associated with attrition in later waves.
Participants were included if they were aged 65 or older, resided in community settings, and reported at least one activity of daily living (ADL) limitation at baseline (Wave 5). The analytic sample sizes across waves were 5,346 (2015), 4,316 (2016), 3,578 (2017), 3,013 (2018), and 2,588 (2019). The study was exempt from Institutional Review Board review because it used publicly available, deidentified data.

Measurements

Subjective Well-Being

Well-being was assessed using 11 NHATS items commonly used to capture subjective well-being. These items reflect multiple components of subjective well-being, including emotional well-being (4 items), life satisfaction (4 items), and perceived control or self-efficacy (3 items). Together, these items capture individuals’ emotional experiences and evaluations of their lives, as well as psychological resources relevant to adaptation in later life.
Items assessing emotional well-being and life satisfaction were rated on 5-point frequency scales, whereas items assessing perceived control or self-efficacy were rated on 3-point agreement scales, consistent with NHATS survey design. Prior to scale construction, items were harmonized to ensure consistent directionality and comparability, and then averaged to create a composite well-being score, with higher values indicating greater subjective well-being. Internal consistency of the composite measure was acceptable (Cronbach’s α = .78).

Participation

Participation was operationalized using five NHATS indicators reflecting engagement in common social and community activities: visiting friends or family in person, attending religious services, participating in clubs or organized activities, going out for enjoyment (e.g., dinner, movies, concerts), and engaging in volunteer work. Each activity was dichotomously coded (1 = yes, 0 = no), and responses were summed and averaged, with higher scores indicating participation in a broader range of activities.
NHATS includes follow-up items assessing whether health or functioning limited participation in some activities. Although these items are substantively relevant to the ICF framework, they were not incorporated into the current participation measure to maintain consistency across indicators and parsimony in longitudinal modeling. The implications of this measurement decision are addressed in the Limitations section.

ADL Limitations (Activity Limitation)

ADL limitations were defined based on self-reported difficulty performing one or more basic self-care or mobility activities, including eating, bathing, toileting, dressing, getting out of bed, walking outside, and walking inside the home. Consistent with NHATS measurement, ADL limitation was defined based on reported difficulty with the activity and does not distinguish whether respondents used assistive devices or received help from others to complete the task.
A dichotomous indicator was used to reflect the presence of any ADL limitation (1 = at least one ADL with reported difficulty; 0 = no reported difficulty). This operationalization aligns with the study’s baseline inclusion criterion and facilitates comparability across waves, though it does not capture heterogeneity in how activities are completed. This limitation is discussed below.

Analytic Strategy

The analytic goal of this study was to examine longitudinal associations among ADL limitations, participation, and well-being over time within an ICF-informed framework. Because these constructs were expected to show temporal stability while also exhibiting cross-domain associations across repeated measurements, a longitudinal autoregressive structural equation modeling (SEM) approach was employed.
Autoregressive SEMs allow each construct to be predicted by its own prior value while simultaneously estimating cross-lagged associations among constructs across adjacent waves (Cole & Maxwell, 2003; Little et al., 2007). This approach permits assessment of whether ADL limitations at time t are associated with participation at time t+1 and whether participation at time t is associated with well-being at time t+1, after accounting for prior levels of each construct.
Model specification was guided by the ICF-informed distinction between activity limitation and participation. Accordingly, paths were specified from ADL limitations at time t to participation at time t+1, and from participation at time t to well-being at time t+1, along with autoregressive paths for each construct.
As an initial exploratory step, cross-sectional decomposition analyses were conducted separately for each wave using the paramed command in Stata to assess whether participation statistically accounted for the contemporaneous association between ADL limitations and well-being. These analyses were used as a diagnostic tool to evaluate whether the direction and magnitude of associations were consistent with the hypothesized longitudinal pathways, rather than to establish causal mediation.
In the longitudinal SEM, correlated residuals among ADL limitations, participation, and well-being within the same wave were included to account for shared variance attributable to unmeasured time-specific factors (Anderson & Williams, 1992). Selected wave-skipping autoregressive paths (e.g., predicting a construct at wave t+2 from wave t) were added when theoretically plausible and empirically supported, to capture longer-term stability not fully explained by adjacent autoregression. These paths were restricted to within-construct associations and did not represent additional cross-domain causal assumptions.
Model modifications were evaluated using modification indices and expected parameter change values, with priority given to theoretically defensible adjustments. Model fit was evaluated using multiple indices, including the chi-square test, RMSEA (< .08), and comparative fit indices (CFI and TLI > .90). Information criteria (AIC and BIC) were used to compare nested models. Missing data were addressed using full-information maximum likelihood estimation. Indirect associations were estimated using bootstrapping with 500 replications to obtain standard errors for total, direct, and indirect effects. All analyses were conducted using Stata version 17.

Results

Descriptive Statistics

Table 1 presents baseline demographic characteristics of the analytic sample in 2015 (n = 5,346) and 2019 n = 2,588). The age distribution shifted modestly over time, with a decrease in the proportion of participants aged 90 years and older (from 10.06% in 2015 to 6.53% in 2019). The proportion of female participants increased slightly from 58.45% to 61.55%. Racial composition remained relatively stable across waves, with White participants comprising the majority (64.61% in 2015; 65.73% in 2019), followed by Black (22.95% to 23.92%) and Hispanic participants (6.60% to 6.49%). Approximately 55% of participants were married at both time points.
Table 2 summarizes descriptive statistics for ADL limitations, participation, and well-being from 2015 through 2019. The proportion of respondents reporting at least one ADL limitation increased over time, from 0.17 (SD = 0.26) in 2015 to 0.31 (SD = 0.33) in 2019. Mean participation scores remained relatively stable across waves, ranging from 0.51 to 0.53. Mean well-being scores showed a gradual decline over time, decreasing from 6.55 (SD = 0.87) in 2015 to 6.34 (SD = 0.90) in 2019.

Structural Equation Models

Longitudinal structural equation modeling was used to examine temporal associations among ADL limitations, participation, and well-being. Consistent with prior recommendations for longitudinal modeling (Cole & Maxwell, 2003), correlations among repeated measures indicated substantial temporal stability across constructs. Correlations between ADL limitations measured at Wave 5 and Wave 9 ranged from .64 to .67; correlations for participation ranged from .70 to .72; and correlations for well-being ranged from .69 to .72.
A baseline autoregressive model was first estimated to assess stability of each construct over time. Standardized autoregressive coefficients indicated moderate to strong stability across adjacent waves for ADL limitations (.66–.73), participation (.70–.72), and well-being (.71–.73).
Cross-lagged paths were then added to examine associations between ADL limitations and subsequent participation, as well as between participation and subsequent well-being, consistent with the ICF-informed analytic framework (Figure 2). Across waves, reporting an ADL limitation was consistently associated with lower participation at the subsequent wave (β = −.048 to −.089, all p < .001). Participation was positively associated with subsequent well-being across waves (β = .033 to .081, all p < .001).
To account for shared variance attributable to unmeasured time-specific factors, correlated residuals among ADL limitations, participation, and well-being within the same wave were included. The inclusion of these correlations improved overall model fit while leaving the magnitude and direction of the primary cross-lagged associations largely unchanged.
The final model incorporated covariates and selected wave-skipping autoregressive paths to capture longer-term stability within constructs. Model fit indices indicated good fit to the data (CFI = .935; TLI = .912; RMSEA = .056, 95% CI [.052, .054]). Standardized autoregressive coefficients remained moderate across constructs, and cross-lagged associations between ADL limitations and participation, as well as between participation and well-being, were retained (ADL → participation β = −.047 to −.085; participation → well-being β = .014 to .061).

Indirect Associations

Indirect associations linking earlier ADL limitations to later well-being through participation were examined across three temporal sequences: Wave 5 → Wave 7, Wave 6 → Wave 8, and Wave 7 → Wave 9. One indirect path (participation at Wave 6 to well-being at Wave 7) was not statistically significant and was excluded from the final model to maintain parsimony.
Time-specific indirect associations varied in magnitude and statistical significance. The indirect association from ADL limitations at Wave 5 to well-being at Wave 7 through participation was small and not statistically significant (β = −.001, SE = .002, p = .273). Indirect associations from Wave 6 to Wave 8 (β = −.004, SE = .004, p = .001) and from Wave 7 to Wave 9 (β = −.003, SE = .004, p = .017) were statistically significant but modest in magnitude. The cumulative indirect association from ADL limitations at Wave 5 to well-being at Wave 9 through participation was −.005 (SE = .005, p < .001). The corresponding total association between ADL limitations at Wave 5 and well-being at Wave 9 was not statistically significant (p = .237), indicating that the indirect pathway accounted for a modest portion of an overall weak long-term association.
For comparison, cross-sectional decomposition analyses conducted at each wave indicated that participation statistically accounted for approximately 16.0% to 21.4% of the contemporaneous association between ADL limitations and well-being (Table 3; Figure 3). These results are descriptive and are presented to contextualize the longitudinal findings rather than to support causal mediation.

Discussion

This study examined longitudinal associations among ADL limitations, participation, and well-being among community-dwelling older adults with ADL difficulty using a nationally representative, multi-wave dataset. Guided by an ICF-informed perspective, the analyses focused on temporal patterns linking activity limitation, participation, and well-being rather than on causal inference. Overall, the findings indicate that ADL limitations, participation, and well-being exhibit substantial temporal stability, while also showing consistent associations across adjacent waves.
Across the five-year period, the proportion of older adults reporting ADL difficulty increased modestly, participation levels remained relatively stable, and well-being declined slightly. Each construct was strongly predicted by its prior value, highlighting the importance of historical status in shaping subsequent functioning and well-being in later life. These patterns are consistent with prior longitudinal research demonstrating that functional status, social engagement, and subjective well-being tend to show persistence over time among older adults.
Consistent with previous studies, ADL limitations were negatively associated with well-being, and participation was positively associated with well-being among older adults with activity limitations (Li et al., 2020; Phelan et al., 2004). Extending prior work, the present study examined these associations longitudinally and found that participation was prospectively associated with subsequent well-being across multiple waves, even after accounting for prior participation and well-being. Although the magnitude of these associations was modest, the pattern was largely consistent over time.
The analyses also indicated that participation statistically accounted for a portion of the longitudinal association between ADL limitations and well-being. Indirect associations linking earlier ADL limitations to later well-being through participation were small and varied across waves, with some pathways reaching statistical significance and others not. These findings suggest that participation may play a partial and time-dependent role in linking activity limitations and well-being rather than serving as a strong or uniform explanatory mechanism. The modest size and inconsistency of the indirect associations underscore the need for cautious interpretation and align with the complexity of aging processes in community settings.
From a theoretical perspective, the observed temporal patterns are broadly consistent with the ICF framework, which emphasizes interactions among activity limitation, participation, and broader indicators of health and functioning within specific environmental contexts. Rather than treating disability as a static outcome, the findings illustrate how activity limitations and participation are dynamically related over time among community-dwelling older adults. While the results do not establish causal pathways, they provide empirical support for applying an ICF-informed perspective to longitudinal research on aging and well-being.

Implications

Well-being is a central component of quality of life in later adulthood, particularly for older adults aging in place with activity limitations. The present findings highlight stable longitudinal associations among ADL limitations, participation, and well-being, suggesting that both activity limitation and social engagement are relevant for understanding well-being trajectories among community-dwelling older adults.
Although ADL limitations were relatively stable over time, they were consistently associated with lower subsequent participation. This pattern suggests that activity limitations may constrain opportunities for engagement in social and community activities. Efforts aimed at supporting mobility, accessibility, or adaptive functioning may therefore be relevant for maintaining participation among older adults with ADL difficulty, though such implications should be interpreted cautiously given the observational nature of the data.
Participation levels remained relatively consistent across waves and were positively associated with subsequent well-being. While the observed associations were modest, they suggest that participation may be an important correlate of well-being among older adults with ADL limitations. Community-based approaches that facilitate social contact, transportation, or accessible activities—such as senior centers or community programs—may help support engagement among older adults with activity limitations. Importantly, these implications are suggestive rather than prescriptive and warrant further evaluation using intervention or quasi-experimental designs.

Limitations

Several limitations should be acknowledged. Participation was measured using a limited set of dichotomous indicators capturing observable engagement in common social and community activities rather than the full conceptual scope of participation as defined in the ICF, and follow-up items assessing participation restriction due to health or functioning were not incorporated. ADL limitation was operationalized as a binary indicator of any reported difficulty, which does not distinguish between individuals who complete activities independently, use assistive devices, or rely on help from others, despite NHATS providing richer information on activity performance. Although longitudinal data and autoregressive modeling were used, the analyses remain observational and focus on temporal associations rather than causal inference, and the models specified unidirectional cross-lagged paths without incorporating potential reciprocal feedback processes among activity limitation, participation, and well-being that are explicitly acknowledged within the ICF framework. In addition, well-being was measured as a composite construct encompassing emotional well-being, life satisfaction, and perceived control or self-efficacy; although this approach demonstrated acceptable internal consistency and aligns with prior NHATS-based research, these components represent related but distinct psychological domains. Finally, attrition and selective survival may have influenced observed associations despite the use of full-information maximum likelihood estimation.

Conclusion

Using five waves of nationally representative NHATS data, this study examined longitudinal associations among ADL limitations, participation, and subjective well-being among community-dwelling older adults with ADL difficulty. The findings indicate that participation is prospectively associated with subsequent well-being over time and constitutes a modest, time-dependent statistical pathway linking activity limitation and later well-being. Although effect sizes were small and the analyses do not support causal inference, the results are consistent with an ICF-informed perspective emphasizing the distinction between activity limitation and participation. Together, these findings underscore the importance of considering participation as part of the broader context in which older adults with functional limitations experience and maintain well-being while aging in place, and they highlight the value of longitudinal approaches for understanding dynamic processes in later life.

Author Contributions

Conceptualization, Q.L.; Methodology, Q.L.; software, Q.L.; validation, C.Y., and X.L.; formal analysis, Q.L.; investigation, Q.L.; data curation, Q.L.; writing—original draft preparation, Q.L.; writing—review and editing, Q.L., X.L., and C.Y.; visualization, Q.L.; supervision, Q.L.; project administration, Q.L.; All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to that the data set is publicly available and are de-identified.

Data Availability Statement

Publicly Available.

Conflicts of Interest

The authors declare no conflicts of interest.

Use of Artificial Intelligence

Chat-GPT 5 was used for language and readability checks. The authors take full responsibility of conceptualization, data analyses, reporting, and writing.

References

  1. Anaby, D.; Miller, W. C.; Eng, J. J.; Jarus, T.; Noreau, L. Participation and well-being among older adults living with chronic conditions. Soc Indic Res 2011, 100(1), 171–183. [Google Scholar] [CrossRef] [PubMed]
  2. Boslaugh, S. E.; Andresen, E. M. Correlates of physical activity for adults with disability. Prev Chronic Dis 2006, 3(3), 1–14. [Google Scholar]
  3. Chatterji, S.; Byles, J.; Cutler, D.; Seeman, T.; Verdes, E. Health, functioning, and disability in older adults - Present status and future implications. Lancet 2015, 385(9967), 563–575. [Google Scholar] [CrossRef] [PubMed]
  4. Cole, D. A.; Maxwell, S. E. Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling. Journal of abnormal psychology 2003, 112(4), 558. [Google Scholar] [CrossRef]
  5. Courtney-Long, E. A.; Carroll, D. D.; Zhang, Q. C.; et al. Prevalence of Disability and Disability Type Among Adults — United States, 2013. MMWR Morb Mortal Wkly Rep 2015, 64(29), 777–782. [Google Scholar] [CrossRef]
  6. Dunlop, D. D.; Song, J.; Arntson, E. K.; et al. Sedentary time in US older adults associated with disability in activities of daily living independent of physical activity. J Phys Act Heal 2015, 12(1), 93–101. [Google Scholar] [CrossRef]
  7. Fokkema, T.; De Jong Gierveld, J.; Dykstra, P. A. Cross-national differences in older adult loneliness. J Psychol Interdiscip Appl 2012, 146(1-2), 201–228. [Google Scholar] [CrossRef]
  8. Fong, J. H. Disability Incidence and Functional Decline among Older Adults with Major Chronic Diseases. BMC Geriatr 2019, 19(1), 323. [Google Scholar] [CrossRef]
  9. Freedman, V. A. Adopting the ICF language for studying late-life disability: a field of dreams? Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences 2009, 64(11), 1172–1174. [Google Scholar] [CrossRef]
  10. Freedman, V. A.; Kasper, J. D. Cohort Profile: The National Health and Aging Trends Study (NHATS). Int J Epidemiol 2019, 48(4), 1044–1045G. [Google Scholar] [CrossRef]
  11. Freedman, V. A.; Stafford, F.; Schwarz, N.; Conrad, F. Disability, participation, and subjective well-being among older couples. Soc Sci Med 2011, 74(4). [Google Scholar]
  12. Freedman, V. A.; Stafford, F.; Schwarz, N.; Conrad, F.; Jennifer; Cornman, C. Disability, participation, and subjective well-being among older couples. Soc Sci Med 2012, 74(4), 588–596. [Google Scholar] [CrossRef]
  13. Graybill, E. M.; McMeekin, P.; Wildman, J. Can aging in place be cost effective? A systematic review. PLoS One 2014, 9(7). [Google Scholar] [CrossRef] [PubMed]
  14. Hammel, J.; Magasi, S.; Heinemann, A.; Gray, D. B.; Stark, S.; Kisala, P.; Hahn, E. A. Environmental barriers and supports to everyday participation: A qualitative insider perspective from people with disabilities. Archives of Physical Medicine and Rehabilitation 2015, 96(4), 578–588. [Google Scholar] [CrossRef] [PubMed]
  15. O’Rourke, H. M.; Collins, L.; Sidani, S. Interventions to address social connectedness and loneliness for older adults: a scoping review. BMC geriatrics 2018, 18(1), 214. [Google Scholar] [CrossRef] [PubMed]
  16. Hausman, J. A. Specification tests in econometrics. Econometrica: Journal of the econometric society 1978, 1251–1271. [Google Scholar] [CrossRef]
  17. Hinton, P. R.; McMurray, I.; Brownlow, C. SPSS explained; Routledge, 2014. [Google Scholar]
  18. Kostanjsek, N. Use of the International Classification of Functioning, Disability and Health (ICF) as a conceptual framework and common language for disability statistics and health information systems. BMC Public Health 2011, 11 (SUPPL. 4), S3. [Google Scholar] [CrossRef]
  19. Li, X.; Wang, J.; Dong, S.; Fu, J.; Liu, J. The influence of disabilities in activities of daily living on successful aging: the role of well-being and residence location. Frontiers in Public Health 2020, 7, 417. [Google Scholar] [CrossRef]
  20. Liu, J. Y. W. The severity and associated factors of participation restriction among community-dwelling frail older people: an application of the International Classification of Functioning, Disability and Health (WHO-ICF). BMC geriatrics 2017, 17(1), 1–11. [Google Scholar] [CrossRef]
  21. Motamed-Jahromi, M.; Kaveh, M. H. Effective interventions on improving elderly’s independence in activity of daily living: a systematic review and logic model. Frontiers in Public Health 2021, 8, 516151. [Google Scholar] [CrossRef]
  22. Okoro, C. A.; Hollis, N. D.; Cyrus, A. C.; Griffin-Blake, S. Prevalence of Disabilities and Health Care Access by Disability Status and Type Among Adults — United States, 2016. MMWR Morb Mortal Wkly Rep 2018, 67(32), 882–887. [Google Scholar] [CrossRef]
  23. Phelan, E. A.; Williams, B.; Penninx, B. W.; LoGerfo, J. P.; Leveille, S. G. Activities of daily living function and disability in older adults in a randomized trial of the health enhancement program. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 2004, 59(8), M838–M843. [Google Scholar] [CrossRef]
  24. Pinquart, M.; Sörensen, S. Influences of Socioeconomic Status, Social Network, and Competence on Subjective Well-Being in Later Life: A Meta-Analysis. Psychol Aging 2000, 15(2), 187–224. [Google Scholar] [CrossRef] [PubMed]
  25. Rejeski, W. J.; Ip, E. H.; Marsh, A. P.; Miller, M. E.; Farmer, D. F. Measuring disability in older adults: the International Classification System of Functioning, Disability and Health (ICF) framework. Geriatrics & gerontology international 2008, 8(1), 48–54. [Google Scholar]
  26. Rosenwohl-Mack, A.; Schumacher, K.; Fang, M. L.; Fukuoka, Y. A new conceptual model of experiences of aging in place in the United States: Results of a systematic review and meta-ethnography of qualitative studies. Int J Nurs Stud 2020, 103, 103496. [Google Scholar] [CrossRef] [PubMed]
  27. Rowe, J. W.; Kahn, R. L. The Forum The Forum. Gerontologist 1997, 37(4), 433–440. [Google Scholar] [CrossRef]
  28. Steeves, J.; Shiroma, E.; Conger, S. A.; Van Domelen, D.; Harris, T. Physical activity patterns and multimorbidity burden of older adults with different levels of functional status: NHANES 2003-2006. Disabil Health J 2019, 12(3), 495–502. [Google Scholar] [CrossRef]
  29. United Nations; Department of Economic and Social Affairs PD. World Population Prospects: The 2017 Revision, Key Findings and Advance Tables; 2017. [Google Scholar]
  30. Vanleerberghe, P.; De Witte, N.; Claes, C.; Schalock, R. L.; Verté, D. The quality of life of older people aging in place: a literature review. Qual Life Res 2017, 26(11), 2899–2907. [Google Scholar] [CrossRef]
  31. Whiteneck, G.; Dijkers, M. P. Difficult to measure constructs: Conceptual and methodological issues concerning participation and environmental factors. Archives of Physical Medicine and Rehabilitation 2009, 90(11), S22–S35. [Google Scholar] [CrossRef]
  32. Wick, J. Y. Aging in Place: Our House Is a Very, Very, Very Fine House. Consult Pharm 2017, 32(10), 566–574. [Google Scholar] [CrossRef]
  33. World Health Organization G. International classification of functioning, disability and health: ICF; World Rep Child Inj Prev, 2001. [Google Scholar]
  34. Zhang, M.; Pan, Y. Design of Sustainable Senior-Friendly Community Transportation Services. Sustainability 2021, 13(23), 13078. [Google Scholar] [CrossRef]
Figure 2. Autoregressive mediation model framework.
Figure 2. Autoregressive mediation model framework.
Preprints 209042 g002
Figure 3. Final SEM Diagram.
Figure 3. Final SEM Diagram.
Preprints 209042 g003
Table 1. Sample characteristics.
Table 1. Sample characteristics.
2015 (N= 5346) 2019 (N=2588)
Age n % n %
65-69 679 12.7 322 12.44
70-74 1,146 21.44 622 24.03
75-79 1,115 20.86 585 22.6
80-84 1,064 19.9 535 20.67
85-89 804 15.04 355 13.72
90+ 538 10.06 169 6.53
Gender
Male 2,221 41.55 995 38.45
Female 3,125 58.45 1,593 61.55
Race
White 3,454 64.61 1,701 65.73
Black 1,227 22.95 619 23.92
Hispanic 353 6.6 168 6.49
Other 312 5.84 100 3.86
Marital status
Married 2,946 55.11 1,421 54.91
Not married 2,400 44.89 1,167 45.09
Table 2. Descriptive Statistics of ADL, Participation, and Well-being From 2015 to 2019.
Table 2. Descriptive Statistics of ADL, Participation, and Well-being From 2015 to 2019.
2015 2016 2017 2018 2019
M(SD) M(SD) M(SD) M(SD) M(SD)
ADL .17(.26) .22(.30) .24(.31) .27(.32) .31(.33)
Participation .53(.27) .53(.27) .52(.27) .51(.27) .51(.27)
Well-being 6.55(.87) 6.46(.89) 6.43(.89) 6.37(.90) 6.34(.90)
Table 3. Iterations of SEM and Model Fits.
Table 3. Iterations of SEM and Model Fits.
χ2 CFI TLI RMSEA
M1: theory model 4252.72 .862 .829 .098
M2: added covariance of residual 3804.33 .880 .839 .094
M3: added covariates 3409.74 .890 .844 .074
M4: Additional autoregression paths added 2122.18 .935 .911 .056
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

Disclaimer

Terms of Use

Privacy Policy

Privacy Settings

© 2026 MDPI (Basel, Switzerland) unless otherwise stated