1 Rush Institute for Healthy Aging, Rush-Presbyterian-St. Lukes Medical Center, Chicago, IL.
2 Department of Internal Medicine, Rush-Presbyterian-St. Lukes Medical Center, Chicago, IL.
3 Department of Preventive Medicine, Rush-Presbyterian-St. Lukes Medical Center, Chicago, IL.
4 Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
5 The Center on Aging and Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
6 Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA.
7 Department of Epidemiology, Harvard School of Public Health, Boston, MA.
Received for publication February 20, 2002; accepted for publication October 28, 2002.
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ABSTRACT |
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aging; disabled persons; longitudinal studies; social behavior; social support
Abbreviations: Abbreviations: ADL, activities of daily living; EPESE, Established Populations for Epidemiologic Studies of the Elderly.
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INTRODUCTION |
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Recent studies suggest that participation in leisure activities unrelated to fitness increases survival and has other positive health effects for older adults (1118). Some of these studies have focused on social and productive activity, the latter usually being defined as activity that represents an intrinsic economic value, such as paid employment, volunteer work, or gardening. For example, social and productive activity has been associated with a reduced mortality risk (13, 14, 19) and a reduced risk of cognitive decline and dementia (12, 15, 18). The purpose of this investigation was to build on these findings and evaluate the effect of social and productive activity on functional decline and disability. Disability is generally considered a good indicator of overall health status in older populations. It is thought to arise from the cumulative damage of the chronic disease processes that affect humans throughout life and that become manifest in older age (20, 21).
There have been few systematic studies to date of the relation between social and productive activity and disability. One study found a significant cross-sectional association between social activities and disability in a relatively small sample (22). Another study reported a prospective association between social activity and disability, but this finding was limited to church attendance (23). In this paper, we test the degree to which participation in social and productive activity, which we refer to as social engagement, is associated with a reduced risk of disability in a community-based population of adults aged 65 years or older.
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MATERIALS AND METHODS |
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Data collection and measures
Baseline data collection took place during face-to-face interviews conducted in 1982 and included questions on sociodemographic, psychosocial, and health-related characteristics. Follow-up assessment consisted of in-home interviews in 1985 and 1988 and brief telephone interviews in the intervening years (1983, 1984, 1986, and 1987) as well as in the 2 years (1989 and 1990/1991) following the last in-home interview, yielding a total of nine waves of data. Disability status was ascertained at each yearly interview, while questions on social engagement were included in face-to-face interviews only.
Social engagement
Social engagement was measured by asking a series of questions during the baseline interview on frequency of participation in social and productive activity. These questions were designed not to refer to some underlying "latent" construct of social engagement but rather to provide a broad characterization of the types of activities common among older persons. Hence, there were no a priori assumptions about the intercorrelations between the items. Information on 11 types of social or productive activities was included. Eight items (visits to theaters, sporting events; shopping; gardening; meal preparation; card, game playing; day or overnight trips; paid community work; and unpaid community work) were rated according to frequency of participation (0, never; 1, sometimes; 2, often). Church attendance was rated on a six-point frequency scale (from never/almost never to more than once a week), which was recoded into three categories comparable to the other eight activity items. Questions about participation in groups and paid employment were asked in a yes/no format. Participation in groups was recoded to a value of 1, whereas paid employment was recoded to a value of 2. A summary measure of social engagement was derived by summing the responses across the items. Total social engagement scores were set to missing if responses were missing for more than three items (n = 51, 2 percent); otherwise, missing responses were recoded as 0 (no participation) for that activity. The baseline interview also included three questions on fitness activity (active sports or swimming, walking, physical exercise), which were coded in the same way as the other activity items. Higher scores on the social engagement and fitness activity measures represented higher levels of activity, and each measure was centered at the mean for use in the longitudinal analysis.
Disability status
The New Haven EPESE study included three self-reported measures of disability representing separate, but complementary aspects of disability. The first focused on the ability to perform essential self-care tasks (e.g., bathing, dressing, eating) and was derived from the Katz activities of daily living (ADL) scale (25). Consistent with previous studies (2628), task-specific disability was defined as a self- or proxy report of presently needing help from a person, needing special equipment or a device, or being unable to perform the activity. A summary score was computed by adding the number of tasks a person was able to perform without help (range, 06). The second measure focused on tasks requiring a certain degree of strength and basic mobility, derived from the Rosow-Breslau Functional Health Scale measure (29). The three items assessed the ability (without help) to do heavy work around the house, to walk up and down the stairs, and to walk half a mile (1 mile = 1.61 km). A summary score was formed by adding the three items (range, 03). The third measure evaluated basic upper- and lower-extremity function and was based on the work by Nagi (30). It determined the degree of difficulty in pulling or pushing large objects, stooping, crouching, or kneeling; reaching or extending the arms above shoulder level, and writing or handling small objects. Responses indicating no or little difficulty were added across items to create a summary score (range, 04). Disability questions were included in each yearly interview, yielding a maximum of nine waves of disability data per subject.
Covariates
In addition to age (in years) and gender, we selected three sets of covariates that are known to be related to disability outcomes and might influence the association of social engagement with disability. The first set consists of indicators of socioeconomic status, represented by measures of education and income. The second set includes measures of health and the third set a measure of the overall number and extent of social relationships.
Education was measured in number of years completed. Income was categorized into two dummy variables (<$5,000/year for low income; $5,000$9,999/year for middle income). To retain subjects who failed to report income (13 percent), a separate dummy variable was created for missing values. The high income level ($10,000/year) served as the referent group. In the analysis, adjustment for income meant including all three dummy variables in the model.
Health measures included information on relative weight and chronic conditions. Relative weight was assessed by determining body mass index and was then divided into approximate tertiles to create dummy variables for low (<23 kg/m2), middle (2327 kg/m2), and high (>27 kg/m2). As for income, a dummy variable for missing body mass index values was created to permit inclusion of subjects for whom values were missing (6 percent). Prevalent chronic conditions were ascertained by using self-reported information on seven physician-diagnosed medical conditions: myocardial infarction, high blood pressure, stroke, cancer, diabetes, hip fracture, and arthritis. A summary measure was created by adding the number of self-reported conditions. Cognitive health status was assessed by using the 10-item Short Portable Mental Status Questionnaire (31). To examine the influence of poor cognition on the results, analyses were repeated after excluding subjects whose performance on this questionnaire was poor, conventionally defined as three or more incorrect responses (32).
Social networks were measured with a composite index by using information on the number of social ties that included visual and nonvisual contact and the proximity of four groups of ties: children, relatives, friends, and confidants. A total social network score was constructed by summing the scores for each of the tie-specific measures. Additional details of this measure have been described previously (33), and this measure has been found to be associated with disability transitions in the same cohort (28). Race was self-reported and was coded as Black or non-Black (<1 percent of subjects reported another racial/ethnic identity).
Statistical analysis
Generalized linear modeling was used to fit the nine yearly waves of disability data. Because of their skewed distributions, each disability outcome was modeled by using a logistic link function, and a binomial error structure was specified. To express each outcome as a proportion, we recoded the disability variables by dividing the number of items a subject was able to perform by the total number of items. The regression coefficients of the predictor variables in these models represent the linear effect on the log odds of the proportion of tasks a subject is able to perform on each measure. A generalized estimating equations approach was used to account for the correlated structure of disability data within sampling clusters (24) as well as within subjects across repeated measurements (34).
A series of models was fitted to test the cross-sectional and longitudinal effects of social engagement on disability. To that end, the sequential disability data were modeled as a function of baseline age, gender, and race, representing the cross-sectional association of these variables with disability. Longitudinal effects were represented by follow-up time (in years since baseline) itself as well as the interactions between follow-up time and age, follow-up time and gender, and follow-up time and race. Separate models were constructed for each disability outcome. We then tested the main or "cross-sectional" effect of social engagement on disability by adding baseline social engagement to these models. The cross-sectional effect represents the degree to which social engagement is associated with level of disability, averaged across all yearly follow-up interviews. We also included fitness activity in each model to adjust for the effect of this variable. In the second series of models, we added a term for the interaction between social engagement and follow-up time to test the longitudinal effect of social engagement on disability. In these models, the main (or cross-sectional) effect represents the baseline association of social engagement with disability, whereas the longitudinal effect represents the degree to which the effect of baseline social engagement changes during follow-up.
Sets of covariates representing socioeconomic status, health status, and social networks were added to these models one at a time to examine the influence of these variables on the association of social engagement with disability. An additional model was fitted that was restricted to those subjects without significant cognitive impairment at baseline. Finally, to test the influence of mortality on the estimated relation between social engagement and disability, a separate model was fitted for those who survived the entire follow-up period. Only baseline information was used for each of the predictor variables, including social engagement. All results were based on weighted analysis, unless otherwise specified. All longitudinal analyses were performed by using Statistical Analysis Software (SAS), version 8 (35).
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RESULTS |
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The generalized estimating equations coefficients (table 2) represent the effect on the ratio of the number of items or tasks a person is able to perform to the number that he or she is unable to perform, expressed on a log scale. Hence, the coefficients lack a direct linear interpretation, especially at the extremes of each disability measure. To graphically illustrate the longitudinal effect of social engagement on disability, we computed predicted disability scores, based on the second series of models, at the 25th and 75th percentiles of the social engagement measure. Graphs were plotted for a Black female and a White male, both aged 70 years (figure 1). Disability levels at baseline, that is, at age 70 years, were markedly higher (lower scores) for those whose levels of social engagement were lower, but differences remained fairly stable during follow-up. In this figure, the almost-parallel curves of decline for each group reflect the finding that the negative interaction between social engagement and follow-up time was small relative to the main effect. In fact, disability differences between high and low social engagement tended to increase slightly for ADL disability, the measure for which the predicted scores were closest to the upper limit (ceiling). Differences in predicted disability levels for a White male and a Black female aged 70 years are a combination of both the gender and race effects.
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DISCUSSION |
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Our findings revealed a strong and robust cross-sectional association between social engagement and disability. When the data were averaged across all years of observation, more socially active persons reported considerably lower levels of disability than their counterparts. The association was consistent across gender and race and across all three measures of disability, suggesting that social engagement affects a relatively broad spectrum of this process. The results also indicate that the protective effect of social engagement diminishes slowly over time, suggesting that social engagement is not necessarily associated with a slower rate of functional decline. However, the differential changes in effects were very small relative to the substantial protective effect at baseline for the more socially active, yielding a pattern of mostly constant disability differences during follow-up. In fact, predicted ADL scores suggested a slight increase in absolute differences in ADL disability between the more and less socially active.
The lack of a clearer positive longitudinal effect may in part have been due to the ordinal scaling of the disability measures, which may have limited their ability to adequately capture progression of disability over time. For example, longitudinal effect estimates may be biased to the degree that differences between individual scores at higher levels of each measure represent smaller gradations in underlying disability than equivalent differences at lower levels. Some evidence exists that specific task difficulties, or the patterns in which subjects become disabled, do not follow strictly linear patterns. Losses at lower levels of functional status, compared with higher levels, may indicate greater progression of disability (43, 44). However, we know of no uniformly accepted methods for either rescaling disability measures or differentially weighting individual items according to underlying level of disability, which precluded us from systematically investigating this possibility.
Overall, however, our findings are not consistent with a clear direct or "causal" effect of social engagement on disability. An important issue is the temporal order of the association. One consideration is that social engagement may be as much a consequence of disability as it is a cause. However, in a separate analysis, disability at baseline had only a weak and nonsignificant effect on changes in social engagement (data not shown). This finding raises the possibility that the association between social engagement and disability is more complex than a unidirectional causal effect one way or the other. For example, the findings may be consistent with a pattern of reciprocal causation, similar to what has been observed in other studies of psychosocial factors and change in disability (45). Reciprocal causation could arise from a process of multiple system deactivation; that is, losses in physical function and self-care capacities lead to reduced social engagement, which in turn accelerates functional decline (also known as "use it or lose it"). This theme is common in the gerontologic literature, described as changes in everyday competence and adaptation that follow a dynamic and recursive process in interaction with age-related declines in physical or cognitive function (4549).
Although social engagement may enable older persons to help maintain their functional abilities, our data do not provide clear evidence that it leads to a significant slowing of the disability process itself. The fact that this process is driven mostly by the progression and acute clinical manifestation of age-related chronic conditions suggests that social engagement may not be directly involved in these disease processes. In fact, little evidence to date suggests that social engagement or related psychosocial factors play a significant etiologic role in common, age-related chronic diseases (50, 51). Instead, it may be more likely that social engagement is related to the ability to modify the functional consequences of these diseases. Social engagement, or more generally the extent to which persons are meaningfully involved in their social environment, may provide a sense of purpose and a sense of control over ones life and efficacy in ones abilities (46, 5254). A greater sense of control and self-efficacy, in turn, has been shown to enable older persons to attenuate the impact of declining physical health on everyday function and disability (5557). In other words, social engagement may promote or reinforce the personal resources that enhance resilience in the face of disease processes that become more severe over time. The exact mechanisms involved in this process remain poorly understood but likely consist of a combination of psychosocial and physiologic pathways that require further study.
Our study may have several weaknesses. For example, we relied on ad hoc measures of social engagement, assembled from items designed to cover a broad array of activities that older adults commonly engage in. Confirmation of these findings with better validated measures of social engagement will be necessary. Another issue is that some aspects of social engagement may be conceptually related to functional abilities, leading to potential measurement confounding. Some of the items in our social engagement measure (e.g., shopping, preparing meals) may be particularly vulnerable to overlap with measures of instrumental ADL, but this measure of disability was not used in the present analysis. There was no content overlap with any of the items related to the three disability measures used in our study. In addition, disability is commonly defined in terms of the ability to complete self-care tasks and other basic functions, whereas social engagement is defined as actual participation in activity. Nevertheless, the exact boundaries between lack of social engagement and onset of disability remain difficult to define precisely
An important strength of this analysis was the availability of nine waves of sequential disability data. This design feature enabled us to estimate the effect of social engagement on change in disability status over time with greater precision than is possible in studies with fewer data points and longer intervals between observations. Our analysis focused on the average, or marginal, disability effects, but it did not directly address the heterogeneity in change in disability over time that exists among older adults. Another limitation of our analytic approach is that it did not take into account the problem of competing risk. We found previously that low levels of social engagement are associated with greater mortality risk (19). Therefore, selective mortality may have influenced our findings, especially in view of the high mortality in this cohort during follow-up (48 percent). However, selective mortality is unlikely to account for the observed effect of social engagement on disability, given that the association was only slightly reduced among those who survived the entire follow-up period. Disability can be viewed as a stage in the course of chronic disease processes that will ultimately lead to death. It is possible that the same mechanisms that enable older adults to reduce the disability associated with chronic diseases, such as greater resilience, also allow them to prolong life in the face of declining health.
Another strength of our study is that we were able to consider a broad set of other factors that might have accounted for an association between social engagement and disability. For example, persons reporting higher levels of social engagement may also engage in more fitness activities. Although such activities are strongly related to disability (3, 68), the effect of social engagement was found to be independent of this type of activity. We further investigated the potentially confounding effects of socioeconomic status, poor physical or mental health, and social network ties, all of which were found to be correlated with social engagement and are also known to be related to disability and functional decline (20, 49, 5863). However, the effect of social engagement was either unaffected or only slightly reduced after adjustment for these variables.
The present findings are generally consistent with a health benefit related to social engagement in older populations. A number of studies have indicated a clear survival advantage for older adults who are more socially active or who participate in specific social or productive activities (13, 14, 16, 19), although not all studies have observed a clear survival benefit (64). Others have reported that social engagement is associated with reduced levels of depressive symptoms (54) and might be protective against decline in cognitive function and onset of dementia (15, 65). These findings suggest that social engagement forms an integral part of a constellation of characteristics that have substantial significance for the overall health, well-being, and functional independence of older adults. As such, social engagement may be a critical aspect of successful aging (66, 67).
In sum, we found that higher levels of social engagement are associated with reduced disability and that this effect was consistent across three different measures of disability as well as across gender and racial subgroups. However, the longitudinal data failed to provide evidence for a clear causal effect on rate of functional decline. This finding does not necessarily diminish its potential significance for preventing disability. Promotion of social and productive activity may provide both clinicians and policy makers with an additional strategy to maintain the health and independence of seniors and to postpone the disabling consequences of age-related chronic diseases. For most people, being socially engaged, having meaningful social and productive activity in ones life, is a worthy goal in and of itself.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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