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Risk of functional decline among well elders
J Clin Printed
Epidemiol Vol. 42. No. 9, pp. 895-904, in Great Britain. All rights reserved
08954356/89 $3.00 + 0.00 Lc 1989 Pergamon Press plc
1989 Copyright
RISK OF FUNCTIONAL DECLINE WELL ELDERS*
AMONG
VINCENTMoR,’ JOHNMURPHY,’SUSANMASTERSON-ALLEN,’ CYNTHIAWILLEY,‘.~ AHMAD RAZMPOUR,’M. ELIZABETHJACKSON,’ DAVID GREER’and SIDNEYKATZ~ ‘Brown University Center for Gerontology and Health Care Research, Providence, R.I., ‘Memorial Hospital of Rhode Island, Department of Family Medicine, ‘University of Rhode Island, School of Nursing and Pharmacy, Kingston, R.I. and 4Department of Bioarchitechtonics, Case Western University Medical School, Cleveland, OH 44106, U.S.A. (Receked
in revised form 9 December
1988)
Abstract-Active lifestyles may delay the onset of the functional consequences of chronic disease, potentially increasing active life expectancy. We analyzed the Longitudinal Study of Aging (LSOA) to test the hypothesis that elders’ participation in an active lifestyle prevents loss of function. Focusing on the cohort aged 70-74 who reported being able to carry 25 lb, walk l/4 mile, climb 10 steps and do heavy housework without help and without difficulty at baseline, decline was defined as no longer being able to perform these tasks independently and without difficulty 2 years later. Using multivariate logistic regression, results reveal that those who did not report regularly exercising or walking a mile were 1.5 times more likely to decline than those who did, controlling for reported medical conditions and demographic factors. Similar findings (with different models) were observed for both men and women. Findings suggest the potential value of programs oriented toward the primary prevention of functional decline.
Functional health Prevention
Active life expectancy
Longitudinal Study of Aging
Risk appraisal
preventive health practice among the aged [9]. Since age related physiologic changes as well as extended exposure to environmental risks make it unlikely that the major diseases will be eliminated, the most promising approach to prevention in the aged population is to reduce the functional consequences of disease and aging. It is well known that some lifestyle behaviors, such as smoking, place individuals at risk of certain diseases that will ultimately influence functional status. As Patrick notes, “Disease states . , . have consequences for the individual in terms of role functions, activity restrictions and subjective well-being.” [lo, p. 37S]. However, recent evidence suggests that lifestyle behaviors which promote physical activities such as exercise can increase elders’ functioning and physiological test performance even in the face of existing medical conditions [I 1, 121. Active
BACKGROUND
Physical function is widely recognized as a crucial component of quality of life and perhaps the most universally accepted aspect of the definition of health [l-3]. Functional dependence is more prevalent among the aged and those with chronic disease [4, 51. With the aging of the population and continued survival gains among the elderly, the national implications of a growing number of functionally compromised persons in the U.S. are substantial [6]. To avoid enormous increases in the size of the dependent population over the next 50 years, active life expectancy must be extended [7, 81. To achieve this goal, we need to examine the prospects of *Supported in part by Grant No. HSOOOll-02 from the National Center for Health Services Research. 895
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lifestyles may delay the onset of the functional consequences of chronic disease, potentially allowing for the “rectangularization” of the functional morbidity distribution [8]. Such a scenario would provide evidence to support programs aimed at the primary prevention of functional decline. The purpose of this paper is to specifically examine the effect of an active lifestyle on the probability of functional decline, controlling for disease status and impairment level in a nationally representative population of well functioning younger elders. METHODS
Sample and data
The data used in this study were taken from the Longitudinal Study of Aging (LSOA) conducted by the National Center for Health Statistics and the National Institute on Aging. The study is briefly described here. More detailed information about the 1984 Supplement on Aging (SOA), of the National Health Interview Survey is published in greater detail elsewhere [13, 141. Households were selected through a multistage probability sampling procedure based upon the week of the year in which interviews were conducted. Interviews were conducted by trained U.S. Bureau of Census personnel. Proxy responses were allowed if there was a knowledgeable family member available. Of the 16,148 individuals interviewed in 1984, 91.5% responded for themselves. The SOA asked numerous questions about the physical and social functioning of the elderly respondents, i.e. the activities of daily living (ADLs) and the instrumental activities of daily living (IADLs) as well as more difficult functions such as climbing stairs or carrying groceries. The degree of difficulty elders experienced performing these latter activities was also determined. In 1986, a sample of SOA participants who were over age 70 in 1984 was selected for reinterview, oversampling those over 85 and minorities. Of the 7541 eligible individuals interviewed in 1984, 5151 (68.3%) were sampled for reinterview in 1986. A computer assisted telephone interview system was used to gather the interview data. Once again, proxy interviews with family members were permitted. The interview was similar to the 1984 survey with the principle focus on functioning and receipt of formal and informal service assistance in meeting needs arising from functional deficits. Of the
5 151 individuals identified for reinterview, 417 (8.1%) have unknown status, and 604 (11.7%) were deceased. Sample refinement
Consistent with our interest in the prevention of functional decline among well elders, we chose to focus on the risk of functional decline among the youngest respondents in the LSOA; those 7&74 years of age in 1984. This group had the highest proportion of persons who were intact in all ADLs, IADLs and the more difficult functions. It is in this younger group of aged persons that the impact of preventive health services is most likely to be observed. A total of 1745 sample members in the LSOA met this age condition. We further chose to focus upon individuals who were intact in all ADLs, IADLs as well as aforementioned extended function as measured by selected items from the Nagi battery included in the SOA [15, 161. Extended function items included in defining the functionally intact state were: climbing 10 stairs, carrying 25 lb (2 bags of groceries), walking l/4 mile, performing heavy housework or other heavy chores. To be considered “intact” required that the individual perform all four activities independently, without personal assistance. In addition to the independent performance of each activity, we also considered the degree of difficulty respondents had performing an activity alone. Those reporting considerable, or a great deal of difficulty on any one of the four items resembled those who were unable to perform the functions. Consequently, they intact. were classified as not functionally Those reporting only “some” difficulty in performing those activities were classified as independent. Independence in the IADLs and the ADLs were a virtual prerequisite to independence in the four extended function items. Less than 1% of those with difficulty in an IADL were intact in the extended core functions. Although not used as a Guttman scale, we found that the four extended function items when combined with an indicator of IADL dependency and one for ADL dependency, yielded a coefficient of reproducibility of 0.90. Classification “errors” were highest on the household chores item, which is probably more a function of environmental and sex role factors than physical health factors. This extension of the ADL and IADL hierarchy is consistent with work by Katz et al. [ 15, 171 and more recently by Pinsky et al. [ 181.
Risk of Functional Decline
Definition of functional decline and its predictors
The outcome variable was defined as no longer being intact on the extended function items in 1986 among those who survived and were interviewed. Intact was defined in 1986 precisely as in 1984. Thus, decline by 1986 includes any respondent unable to independently climb 10 stairs, walk l/4 mile, carry 25 lb or do heavy housework or who reported “some” difficulty in any of these tasks. Inability to independently perform any ADL or IADL activities was also considered to be decline. We adopted a dichotomous dependent variable for two reasons. First, this approach is similar to the traditional disease prevention and mortality prediction models. We view our research into the determinants of functional decline as earlier researchers who examined the determinants of heart disease and mortality, both of which are dichotomous outcomes. Second, earlier studies of functional decline in smaller populations revealed that the predictors of decline vary as a function of both baseline impairment and degree of decline. Since we focused our analyses on the well elders, the fact of the onset of decline is the relevant outcome. We hypothesized that involvement in the active lifestyle will positively affect an individual’s risk of loss of function, controlling for demographic characteristics and the presence of pre-existing health problems, disease and impairment. The LSOA contains questions measuring standard demographics (such as race, marital status, education etc.). Health risks and conditions (bed days, hospital use, diabetes) were reported by survey respondents, a practice consistent with similar community epidemiology studies. Prior research comparing self reported major medical conditions in a community population has been inconsistent but generally supports reasonable congruence between physician and patient reported health [19-211. The presence of a health condition was measured as merely present or absent without indication of the severity of the condition. However, since manifestation of disease severity is most often expressed as functional limitations, the reported medical conditions of our study subjects are unlikely to be severe since they have no functional limitations. Lifestyle activities were solicited in the LSOA with only a few questions. Those pertaining to social and physical activity were asked in the form: “Have you . . . gone to church or temple
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in last 2 weeks”; “Do you follow a REGULAR routine of physical exercise?“. A single item about respondents’ walking was in the form “How often do you walk a mile or more without resting?” Response options ranged from never to everyday. Analytic approach
The relative risk of functional decline in 2 years was calculated for dichotomized predictor variables along with Taylor series confidence intervals [22]. Multivariate logistic regression models were then estimated separately for each predictor domain (demographic, medical and behavioral) and the adjusted odds ratios of variables in the models were compared. Stepwise logistic regression was utilized to identify those predictors meeting traditional criteria of statistical significance. Significant variables from each domain were incorporated into a single model. The relative risk of decline associated with each lifestyle activity was explored by testing the increase in the log-likelihood ratio resulting from adding each term to the model. In addition, the multivariate adjusted relative risk associated with each activity after controlling for demographic and health related variables was calculated to account for the inherent multicollinearity thought to exist among the lifestyle variables. As has been found so often before, our initial analyses revealed that self-reported health is one of the best predictors of future status, both survival and functional decline [23]. Since selfreported health is correlated with both the presence of medical conditions and lifestyle activities, when it was entered into multivariate logistic models, other variables with more interpretable and policy relevant meaning were supplanted. Given the salience of the activity measures we chose not to include self reported health measures in the final combined models. We examined the bivariate relationship of these self-report measures with our outcome measure to provide a comparison of the effect of the other independent variables on decline. The final analytic step was to estimate separate models of functional decline for males and females. Since our measure of functional decline may have been partially influenced by sex role specific activities (e.g. household chores, regular exercise), separate models were necessary. There were also considerable differences in the proportion of males and females performing selected activities. Additionally, males had significantly
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lower rates of functional decline than females (18.5. vs 31.8%) and they were more likely to have died (6.9 vs 1.6%). All these factors merited the use of separate models for men and women. Due to the exploratory nature of these analyses and our use of only a select subsample of well functioning survivors, no attempt was made to adjust either the bivariate or multivariate analyses for the multistaged sampling frame. All figures presented are based only upon the study sample and no attempt is made to extrapolate results to a known population. FINDINGS
Sample description
Table 1 contrasts sample members in the 70-74 year old age group who were and were not functionally intact in 1984. Over half (55.3%) of this age cohort were intact in the extended core functions. Males were more
prevalent in the well functioning group as were whites, married persons, those who are better educated, and those with family incomes greater than U.S. $25,000. Despite the large differences in these measures, there is virtually no difference in the ages of the two groups (71.90 vs 71.96). Nearly 15% of those with intact functioning were working as compared to only 4.3% of those not functionally intact. On all health related variables, the functionally intact were less likely to report bed days, hospitalization, falls or virtually any of the health conditions included in the interview than were those who are not functionally intact. With respect to perceived health and activity level, functionally intact respondents compared their activity levels favorably to that of their peers, felt they had more control over their health and were less likely to worry over their health than were those who were not functionally intact. Finally, the functionally intact were more likely to exercise, go to church and other social events as well as
Table 1. Description of the study sample by intact functional status: Longitudinal Study of Aging, ages 70-74 Not intact function N = 776
Intact function N =961
Female White Married Family income U.S. $25,000+ Education: some college Living alone
68.0% 80.2% 50.6% 12.7% 14.8% 34.1%
53.4% 86.6% 62.4% 18.6% 21.1% 25.1%
Serf assessed health Self assessed health-fair/poor Not limited in activity Health worse than last year Does not worry about health Activity level less than last year Working is major activity
55.1% 42.9% 25.7% 29.7% 31.1% 4.3%
16.0% 86.8% 5.1% 63.1% 6.8% 14.8%
50.8% 73.7% 37.6% 22.5% 4.3% 6.3% 3.6% 10.5% 9.3% 16.0% 68.6% 28.4% 42.1%
78.3% 88.2% 15.8% 12.6% 2.5% 3.0% 1.7% 3.4% 2.4% 7.3% 41.4% 12.5% 27.6%
13.6% 77.8% 24.4% 50.0% 23.7% 8.4%
22.5% 81.4% 34.5% 60.0% 35.6% 25.4%
Variables Demographics
Health status No bed days past 12 months
No hospitalizations last year Has trouble with vision Has cataracts Has osteoporosis Has coronary heart disease Past myocardial infarction Has angina pecoris Has had stroke/CVA Has diabetes Has arthritis Has fallen in past 12 months Reports frequently getting confused Activity pattern
Did volunteer work last year Got together w/relatives last 2 wk Went to movies, sports last 2 wk Went to church, temple last 2 wk Reports regular exercise routine Walks one mile 4-7 days/week
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Risk of Functional Decline Table 2. Description of the functionally intact study sample by sex: Longitudinal Study of Aging, ages 70-74 Variables
Male N=448
Female N = 513
Demographics
White Married Family income U.S. $25,000+ Education 13+ years Living alone
84.3% 80.8% 23.1% 22.1% 13.4%
78.2% 46.4% 14.1% 20.3% 35.3%
Self assessed health Self assessed health-fair/poor Health worse than last year Not limited in activity Activity level less than last year Does not worry about health Work is major activity
20.1% 7.1% 81.9% 7.5% 60.6% 20.5%
12.3% 3.4% 91.0% 6.2% 65.2% 9.1%
77.4% 85.7% 15.9% 9.7% 0.7% 4.9% 2.9% 4.5% 4.0% 7.6% 35.6% 9.6% 30.4%
79.1% 90.4% 15.8% 15.2% 4.1% 1.4% 0.6% 2.5% 1.0% 7.0% 46.5% 15.0% 25.2%
16.6% 80.0% 33.3% 56.3% 37.0% 31.6%
27.1% 82.6% 35.5% 63.3% 34.4% 20.1%
Health status No bed days past 12 months
No hospitalizations last year Has trouble with vision Has cataracts Has osteoporosis Has coronary heart disease Past myocardial infarction Has angina pecoris Has had stroke/CVA Has diabetes Has arthritis Has fallen in past 12 months Reports frequently getting confused Activity pattern
Did volunteer work last year Got together w/relatives last 2 wk Went to movies, sports last 2 wk Went to church, temple last 2 wk Reports regular exercise routine Walks one mile 4-7 days/week
participate in volunteer activities than were those who were not intact. Table 2 contrasts males and females in the intact group. Women were nearly half as likely to be married and were less likely to have incomes over U.S. $25,000 in 1984. Males were more likely to rate their health as fair or poor, but were less likely to have reported falling or to have arthritis. Males were more likely to report all types of heart disease such as history of an MI than were women; however, these are not prevalent conditions in either sex. With regard to participation in activities, women were somewhat more likely to report doing volunteer work and going to church, but were less likely to regularly walk a mile although they were almost as likely as were men to report having a regular exercise routine. Relative risk of functional decline
Of the 961 fully functionally intact persons interviewed in 1984,4.1% had died and another 7.3% were not interviewed and no proxy data
were available. Of the 852 persons interviewed, 246 (29.0%) were no longer able to perform all four extended core functions without more than some difficulty. The most prevalent area of lost independence was in carrying 25 lb (22.3%) while 10.3% were no longer able to walk l/4 mile without difficulty. Despite the substantial proportion of surviving sample members whose function declined, only a few became dependent in IADLs (1.5% in personal shopping) or ADLs (0.8% m bathing). Table 3 summarizes the relative risk of functional decline and the associated confidence bounds calculated at the 95% confidence limits for each predictor variable. If the confidence bounds do not include “1.00” the relationship between the predictor and functional decline is statistically significant at conventional levels (p < 0.05). The predictor variables are coded such that the negative state is coded as “1” while the positive, or neutral, condition is coded “0”; meaning that relative risk figures greater than 1.0 are indicative of increased risk of
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Table 3. Relative risk of functional decline in two years for selected demographic, health status and volitional life activities: Longitudinal Study of Aging; ages 7&74 (N = 852) Relative risk
Lower limit
Upper limit
1.60 1.45 1.48 1.53 1.80 1.26
1.28 1.12 1.20 1.13 1.39 1.oo
2.01 1.88 1.82 2.07 2.32 1.58
Major activity is keeping house Any bed days in last year Any hospitalizations Trouble with vision Cataracts Osteoporosis Hypertension Any heart disease Past stroke or CVA Arthritis Diabetes Fallen past year Frequently confused
1.47 1.14 1.05 1.57 1.24 1.37 1.20 1.46 1.75 1.64 1.77 1.48 1.08
1.03 0.89 0.76 1.24 0.93 0.81 0.97 0.94 1.09 1.33 1.33 1.14 0.86
2.11 1.45 1.46 1.99 1.65 2.31 1.48 2.29 2.82 2.36 2.36 1.92 1.37
Serf assessed health Perceived health fair/poor Health worse than last year Worries about health Less active than peers Activity level less than last year
1.54 1.88 1.71 1.55 1.81
1.24 1.36 1.33 1.25 1.34
1.91 2.59 2.12 1.92 2.45
1.16 0.95 1.02 1.51 1.56
0.89 0.21 0.82 1.18 1.25
1.45 1.25 1.26 1.94 1.93
Predictors Demographics
Female Nonwhite Unmarried No college Income U.S. <$25,000 Living alone Health status
Activity pattern
Did volunteer work Didn’t get together w/relatives No church or temple No regular exercise Never walks one mile
functional decline. For example, women were 1.6 times more likely to decline in the 2 year period than were men. Women, nonwhites, non-married persons, those living alone, those without a college education or incomes under U.S. $25,000 were more likely to manifest functional decline. Neither bed days in the prior year, nor past hospitalizations were found to be related to decline. On the other hand, all subjective assessments of health were highly related to decline in the expected direction. Those reporting their health to be only “fair”, or “poor”, were 1.54 times more likely to decline than were those with a more optimistic appraisal of their health. Those reporting that their health in 1984 was worse than it was a year before (only 5.1% of the sample) were 1.83 times more likely to have deteriorated functionally by 1986 than were those reporting their health to be stable or improving. Worry over health was also strongly predictive of decline as was individuals’ assessment of their health relative to their
peers. Clearly, individuals’ internal barometer appears to be as accurate as the “objective” determinants of health in predicting decline. Among the lifestyle activities, we see that only those involving physical exertion appear to be predictive of future functioning. Respondents noting that their major activity is keeping house were significantly more likely to have declined than were those whose normal activity was work. On the other hand, volunteer work, social outings, church participation and going to movies or sports events all revealed relative risks of decline that were not different from 1.0. The two more physically active indicators, regular exercise and walking one mile, were very strongly related to decline. Those without an exercise routine were 1.51 times more likely to decline than those who regularly exercised, and those who never walk a mile were 1.56 times more likely to decline than were those who do so at least several times a week. While we observe no evidence in support of the protective value of the social and intellectual dimensions of
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Risk of Functional Decline
lifestyle activities, we do find that an active lifestyle may enable one to be functionally independent longer than a less active one. Multivariate adjusted risk of decline
Within each domain we performed stepwise logistic regression to identify from among all variables in the domain, those that were related to functional decline, controlling for all others in that domain. Not all variables with a significant bivariate relationship to the outcome emerged as significant in the multivariate model. Since family income and respondent education were correlated, we selected education in view of its association with health status and function in previous research [18]. In the demographic domain, sex, education and marital status entered into a logistic model predicting decline. In the medical domain, arthritis, diabetes, past stroke as well as visual impairment, falls and confusion all entered the multivariate model. Among the lifestyle activities, only exercises and walking entered the model; working did not reach significance after controlling for the two physical activities. The final model synthesizing the three domains included those variables found to be significantly related in each domain. We tested several possible interactions among variables across domains and also examined possible suppressor variables. Table 4 presents the summary logistic regression model combining males and females. The adjusted odds ratio of each variable as well as its associated confidence limits are presented. Thus, the indicator variable for sex is clearly highly significant, controlling for other demographic, health and behavioral risk factors, It can be interpreted to mean that women are 1.3 times more likely to decline than are men and this relationship is statistically significant since the lower estimate of the 95% confidence bound is as high as 1.2. All terms in the final model
were significantly related to functional decline. Even fairly skewed variables such as the presence of prior stroke have relatively small confidence intervals. It is interesting to note that the two behavioral factors, lack of regular exercise and not walking were as predictive of decline as were several of the medical and impairment measures. In examining the predictors of decline for males and females separately, we reconstructed separate models beginning with the larger variable pool. Table 5 presents the adjusted odds ratios and their associated confidence intervals for the predictors which entered each sexspecific model. Only a few variables predict decline among men. Medical factors, (history of stroke and the presence of diabetes), were strongly related to decline. We tested a variety of different variables regarding the presence of cardiac conditions but none improved upon the present model. Those whose normal activity is not work are 1.4 times more likely to decline than those who are still working. Even controlling for work status, however, engaging in a regular exercise program is protective; those who do not are nearly 1.6 times more likely to decline in functional independence. Among women the model is somewhat more complex with medical and functional factors such as diabetes, arthritis, visual impairment and having fallen in the past year all being related to decline. Diabetes is comparably predictive of decline among males and females. Table 5. Odds ratios and associated confidence intervals from a multiple logistic regression model predicting functional decline for functionally intact males and females: Longitudinal Study of Aging; ages 70-74 Predictors Not college educated Work not usual activity
Table 4. Odds ratios and associated confidence intervals from multiple logistic regression model predicting functional decline for all functionally intact cases: Longitudinal Study of Aging; ages 7&74 (N = 852) Predictors Sex (female) Unmarried Not college educated Diabetes Arthritis Past stroke Visual impairment No regular exercise Never walks 1 mile
All cases
Confidence intervals
1.321 1.250 1.196 1.648 1.370 1.785 1.305 1.197 1.288
(1,222-l ,404) (1.122-1.320) (1.122-1.346) (1.477-1.779) (1.223-1.393) (I ,358-l .9S6) (1.152-1.371) (1.103-1.299) (1.230-1.470)
Males Females (Confidence intervals)
Diabetes Past stroke
1.426 (1.381-1.571) 1.438 (1.342-1.634) 1.539 (1.322-1.756) 1.964 (1.610-2.318)
Visual impairment
1.260 (1.1241.396) 1.350 (1.24415456) 1.278 (1.1361.420)
Arthritis Fallen in last 12 months No regular exercise Never walks 1 mile
1.563 (1.365-1.661)
1.583 (1.426-1.740) 1.459 (1.3161.602)
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VlNCENT
Women with a lower educational level were more likely to decline than were the more educated women, perhaps reflecting income effects as well as lifestyle patterns that differ as a function of socioeconomic conditions. Controlling for these medical and background characteristics, we see that women who never walk one mile are nearly 1.5 times more likely to decline than are women who walk a mile at any frequency. Thus, for both men and women having a physically active lifestyle appears to be protective of functional decline. Indeed, the adjusted odds ratios for the physical activity variables increase substantially in the models run separately for males and females when compared to the combined model.
DISCUSSION
We analyzed the Longitudinal Study of Aging (LSOA) to identify those factors that were predictive of loss of independent functioning and to test the hypothesis that elders’ participation in an active lifestyle would be protective of functional decline. Results reveal that among functionally intact men and women between the ages of 70 and 74, those who regularly exercised or walked a mile were less likely to lose functional independence over a 2 year period than were those who did not pursue such activities, controlling for the presence of medical problems and impairments. In the discussion which follows, we examine several aspects of the study findings that argue for the viability of and continued need for exploration of the concept of the primary prevention of functional decline. Our analyses revealed that medical problems and dysfunction do not always go hand in hand. Indeed, as many as 40% of the well functioning elderly between 70 and 74 report having arthritis and 16% have vision problems. Morbidity as measured by the presence of disease, does not necessarily mark the onset of disability. Rather, as our research suggests, the presence of disease may be a marker of future loss of functional independence. Disease severity is obviously an important parameter which our study was not able to measure. However, since severity is often measured in relation to the functional consequences of the disease and our study sample was functionally intact, severity is unlikely to account for much mispecification of the model. And while it is true that the relationship
MOR
el a/.
between clinical parameters (e.g. non-HDL cholesterol) and mortality has been established in younger and older populations [24,25], there continues to be a dearth of reported longitudinal studies examining the relationship between such clinical indicators of illness severity and functional decline in the aged population. Physical and laboratory assessment measures have proved to be no more predictive of functional decline among arthritics than have simple patient assessments [26-281. Pinsky and her colleagues found that physiological measures such as blood pressure and vital capacity were unrelated to future functioning after controlling for age, sex and education [ 181. Several longitudinal studies have examined the relationship between active lifestyles and mortality. For example, various reports based on the Alameda County data indicate that engaging in social and physical activities may reduce the risk of mortality among younger and older individuals over periods of 9-17 years [29-311. Analyses of the Techumseh Community Health Study revealed that 10 year death rates from all causes were negatively associated with social activities, and among females, positively associated with sedentary activity such as watching television [32]. Similar results indicating the protective effect of participation in activities outside the home and of aerobic sports have been reported by the Goteberg studies and the Harvard Alumni Study [33,34]. These reports suggest that an active lifestyle improves survival. Survival effects may be translatable into gains in “active” life expectancy [7], notwithstanding the increased likelihood of morbidity with increased age. Several longitudinal studies have found that elders’ functional status at one point in time is a strong indicator of their survival as well as their future functional status. Using Massachusetts Panel data Katz and his colleagues found that elders with functional dependencies were less likely to survive and more likely to decline than were those who functioned independently [7]. Using several data sets, Spector and his colleagues revealed that elders with dependencies in either ADL or IADL were less likely to survive and more likely to become more impaired than were elders without physical functional limitations at the outset [17]. Mortality is often preceded by a period of functional decline. Whether some of this can be avoided even in the face of chronic disease that may eventually lead to death requires more research.
Risk of Functional Decline
The current study, to our knowledge, is the first to specifically examine the relationship between participation in an “active” lifestyle and future functioning. Obviously, a physically active lifestyle presupposes functional independence. Research on physical functioning consistently reveals that loss of independence in the basic and instrumental activities of daily living generally proceeds in a hierarchical manner [ 15, 171. However, individuals engage in a broader range of activity than merely the ADL and IADLs. The most basic functions are defined as the final common pathway of functional loss associated with most progressive disease [30,35]. Extended core functions which have been incorporated into Nagi’s measures of function include climbing stairs and carrying groceries, activities requiring more stamina [16, 361. These have all been combined into a single “Good Function Index” by Pinsky et al. [18]. Differentiating between the extended core functions and those that are reflections of lifestyle choices may appear arbitrary. Participating in a regular exercise routine is a lifestyle choice, whereas climbing stairs is a task frequently encountered as part of daily life. Additionally, while walking a quarter of a mile is frequently demanded of independent persons interacting with their environment, walking a mile in our society is more likely to be a reflection of individual choice. We feel such lifestyle choices are qualitatively different from every day functional demands and as such, represent legitimate predictors of loss of functional independence over a 2 year period in a homogeneous sample of well functioning younger elders. Our analyses suggest that the men and women who regularly walked or engaged in exercise were significantly more likely to remain independent in extended functions as well as in the IADLs and ADLs than were those who did not. Of particular interest was the fact that although functionally intact men and women reported regularly exercising (37.0 vs 34.4%, respectively) at similar levels, walking one mile 4-7 days a week (done by only 20% of women) was protective of decline for women while exercise was protective for men. Since walking a mile is a more explicit description of behavior than is regular exercise, men may have interpreted this item as meaning a more rigorous workout than did women. Based upon our analyses, the clinical significance of the observed lifestyle effects is
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similar to having a diagnosis of diabetes which is a health condition known to affect morbidity and mortality. Additionally, since the adjusted odds ratios associated with the two lifestyle variables actually increase in the separate sex models, it is unlikely that statistical significance is merely attributable to sample size. Other research seeking to determine the effect of lifestyle choices on survival have yielded similar and even smaller (although statistically significant) effects on which many public health recommendations have been based. We did try to test the role of less physically taxing activities such as attending church and mixing socially with family and friends, however, these factors seemed unrelated to future decline, even though they had differentiated the functionally intact and not intact groups at baseline. Whether a broader range of social or intellectual, as opposed to merely physical, activities might prove to be protective of future decline remains to be seen. In the absence of even a bivariate relationship in our analyses, it may be that physically taxing activities will predominate future research as well. Conducting such research using secondary data sets always entails making compromises. The choice of control variables is limited and their validity is open to debate. While the relationships we observed between the presence of medical problems, impairments and future functioning were anticipated, it is not clear whether unmeasured medical problems would have suppressed the observed effect of exercise and walking on functional decline. Given the paucity of measures of current and past lifestyle activities in this data set, it is possible that measures of current lifestyle may already reflect the presence of morbidity that led to a reduction in exercise and walking. Attributing causality to exercise and walking is problematic at this stage. Indeed, it may be that active lifestyle must be ongoing for decades in order to effect future functioning, and that adopting such activities later in life may be ineffective. Nontheless, since small scale trials of exercise programs have been shown to have positive short term effects in the impaired elderly, it is reasonable to expect younger elders who are still functioning to benefit from adopting a more active life style [l 1, 121. Establishing the validity of the primary prevention of functional decline model ultimately requires the same experimental testing to which disease prevention models have been subjected.
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We feel that this study has accomplished the first step of examining the relationship between lifestyle and functional decline using a panel study. Future efforts utilizing more sophisticated data sets, covering longer periods of time, with better clinical information and data on other long term lifestyle behaviors will determine whether active lifestyles are protective or merely predictive of future functioning. REFERENCES 1.
2. 3.
4.
5. 6.
IO.
11.
12. 13.
14.
15.
16.
Patrick DL, Bush JW, Chen MM. Toward an operational definition of health. J Health Sot Behav 1973: 14: 6. Ware JE Jr. Scales for measuring general health perceptions. Health Serv Res 1976; 11: 3988415. Read JL, Quinn RJ, Hoefer MA. Measuring overall health: an evaluation of three important approaches. J Chron Dis 1987; 40 (Suppl. I): 7%21s. Jette AM, Branch LG. The Framingham Disability Study II. Physical disability among the aging. Am J Public Health 1981; 71: 1211-1216. Schick FL. Statistical Handbook on Aging America. Phoenix: The Oryx Press; 1986. Liu K, Manton K. Long term care: current estimates and projections. Proc 1987 Public Health Conference on Records and Statistics, DHHS Pub. No. (PHS) 88-1214. Hyattsville, Md; 1987. Katz S, Branch LG, Branson MH et al. Active life expectancy. N Engl J Med 1983; 309: 1218. Fries JF. Aging, natural death, and the compression of morbidity. N Engl J Med 1980: 303: 130-135. Berg RL. Prevention of Disability in the Aged. In: Last JM, Ed. Maxcy-Rosenau Public Health and Preventative Medicine, 1Ith edn. New York: AppletonCountry-Crofts; 1980; 128331299. Patrick DL. Commentary: patient reports of health status as predictors of physiologic health in chronic disease. J Chron Dis 1987; 40 (Suppl. I): 37S-4OS. Bruce RA. Exercise, functional aerobic capacity and seine. In: Princinles of Geriatric Medicine. Andres R. B&man EL, Haizard WR, Eds. New York: McGraw: Hill; 1985: 87-103. Larson EB, Bruce RA. Exercise and aging (Editorial). Ann Intern Med 1986: 105: 783-785. Kovar MG. The longitudinal study of aging: the 1986 reinterview public-use file. Proc 1987 Public Health Conference on Records and Statistics, DHHS Pub. No. (PHS) 88-1214. Hyattsville, Md; 1987. Feller BA Americans Needing Home Care, United States. Vital and Health Statistics, Series 10, No. 153, DHSS Pub. No. (PHS) 86-1581, Public Health Service. Washington, DC.: U.S. Government Printing Office; March 1986. Katz S, Ford AB, Moskowitz RW et al. Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA 1963; 185: 914. Nagi S. An epidemiology of disability among adults in the United States. Milbank Mem Fund Q 1976: 54: 439-468.
al.
17. Spector WD, Katz S, Murphy JB, Fulton JP. The
18.
19.
20.
21.
22.
23.
24. 25.
26.
27.
28.
29.
30.
31.
32.
33.
34. 35. 36.
hierarchical relationship between activities of daily living and instrumental activities of daily living. J Chron Dis 1987; 40: 481-489. Pinsky JL, Leaverton PE, Stokes J. Predictors of good function: The Framingham Study. J Chron Dis 1987; 40 (Suppl. 1): 159S-167s. Fillenbuam GG. Social contest and health assessments of health among the elderly. J Health Sot Rehav 1979; 20: 45-51. Kaplan GA, Kotter PL. Self reports predictive of mortality from ischemic heart disease: a nine-year follow-up of the human population laboratory cohort. J Chron Dis 1985: 38(2): 195-201. LaRue A, Bank L, J&k L, Hetland M. Health in old age: how do physician ratings and self-ratings compare. J Gerontol 1979; 34: 687-691. Kleinbaum DG. KuDner LL. Moraenstem H. Enidemiological R&ear& Principles &d Quantita&e Methods. Belmont, Cahf.: Lifetime Learning; 1982. Kaplan SH. Patient reports of health status as predictors of physiological health measures in chronic disease. J Chron Dis 1987; 40 (Suppl. 1): 27535s. Consensus Conference. Lowering blood cholesterol to prevent heart disease. JAMA 1985; 253: 208&2086. Anderson K, Castelli W, Levy D. Cholesterol and mortality: thirty years of follow-up from The Framingham Study. JAMA 1987; 257: 21762180. Bellamy N, Buchanan W. Outcome measurement in osteoarthritis clinical trials: the case for standardization. Clin Rheumatol 1984; 3: 293-303. Rasker J, Cosh J. The natural history of rheumatoid arthritis: a fifteen year follow-up study. Ciin Rheumatol 1984; 3: 11-20. Helawa A, Goldsmith C, Smythe H. Independent measurement of functional capacity in rheumatoid arthritis. J Rheumatol 1982; 9: 794-797. Berkman LF, Syme SL. Social networks, host resistance and mortality: a nine year follow-up study of Alameda County residents. Am J Epidemiol 1979; 109: 186-204. Wingard DL, Berkman LF, Brand RJ. A multivariate analysis of health related practices: a nine-year mortality followup of the Alameda County study. Am J Epidemiol 1982; 116: 765-775. Kaplan GA, Seeman TE, Cohen RD, Knudsen LP, Guralnick J. Mortality among the elderly in the Alameda County study: behavioral and demoeranhic risk factors. Am J Public Health 1987: 77: TOi-312. House JS, Robbins C, Metzner HL. The association of social relationships and activities with mortality: prospective evidence from the Tecumseh Community Health Study. Am J Epidemiol 1982; 116: 123-140. Welin L, Svardsudd K, Ander-Peciva S, et al. Prospective study of social influences on mortality: the study of men born in 1913 and 1923. Lancet 1985; 915-918. Paffenbarger RS, Hyde RT, Wing AL, Hsieh C. Physical activity, all cause mortality and longevity of college alumini. N Engl J Med 1986; 314: 605-613. Mor V. Cancer patients’ quality of life over the disease course: lessons from the real world. J Chron Dis 1987; 40: 535-544. Rosow I, Bresalu H. A Guttman health scale for the aged. J Gerontol 1966; 21: 556559.
Epidemiol Vol. 42. No. 9, pp. 895-904, in Great Britain. All rights reserved
08954356/89 $3.00 + 0.00 Lc 1989 Pergamon Press plc
1989 Copyright
RISK OF FUNCTIONAL DECLINE WELL ELDERS*
AMONG
VINCENTMoR,’ JOHNMURPHY,’SUSANMASTERSON-ALLEN,’ CYNTHIAWILLEY,‘.~ AHMAD RAZMPOUR,’M. ELIZABETHJACKSON,’ DAVID GREER’and SIDNEYKATZ~ ‘Brown University Center for Gerontology and Health Care Research, Providence, R.I., ‘Memorial Hospital of Rhode Island, Department of Family Medicine, ‘University of Rhode Island, School of Nursing and Pharmacy, Kingston, R.I. and 4Department of Bioarchitechtonics, Case Western University Medical School, Cleveland, OH 44106, U.S.A. (Receked
in revised form 9 December
1988)
Abstract-Active lifestyles may delay the onset of the functional consequences of chronic disease, potentially increasing active life expectancy. We analyzed the Longitudinal Study of Aging (LSOA) to test the hypothesis that elders’ participation in an active lifestyle prevents loss of function. Focusing on the cohort aged 70-74 who reported being able to carry 25 lb, walk l/4 mile, climb 10 steps and do heavy housework without help and without difficulty at baseline, decline was defined as no longer being able to perform these tasks independently and without difficulty 2 years later. Using multivariate logistic regression, results reveal that those who did not report regularly exercising or walking a mile were 1.5 times more likely to decline than those who did, controlling for reported medical conditions and demographic factors. Similar findings (with different models) were observed for both men and women. Findings suggest the potential value of programs oriented toward the primary prevention of functional decline.
Functional health Prevention
Active life expectancy
Longitudinal Study of Aging
Risk appraisal
preventive health practice among the aged [9]. Since age related physiologic changes as well as extended exposure to environmental risks make it unlikely that the major diseases will be eliminated, the most promising approach to prevention in the aged population is to reduce the functional consequences of disease and aging. It is well known that some lifestyle behaviors, such as smoking, place individuals at risk of certain diseases that will ultimately influence functional status. As Patrick notes, “Disease states . , . have consequences for the individual in terms of role functions, activity restrictions and subjective well-being.” [lo, p. 37S]. However, recent evidence suggests that lifestyle behaviors which promote physical activities such as exercise can increase elders’ functioning and physiological test performance even in the face of existing medical conditions [I 1, 121. Active
BACKGROUND
Physical function is widely recognized as a crucial component of quality of life and perhaps the most universally accepted aspect of the definition of health [l-3]. Functional dependence is more prevalent among the aged and those with chronic disease [4, 51. With the aging of the population and continued survival gains among the elderly, the national implications of a growing number of functionally compromised persons in the U.S. are substantial [6]. To avoid enormous increases in the size of the dependent population over the next 50 years, active life expectancy must be extended [7, 81. To achieve this goal, we need to examine the prospects of *Supported in part by Grant No. HSOOOll-02 from the National Center for Health Services Research. 895
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lifestyles may delay the onset of the functional consequences of chronic disease, potentially allowing for the “rectangularization” of the functional morbidity distribution [8]. Such a scenario would provide evidence to support programs aimed at the primary prevention of functional decline. The purpose of this paper is to specifically examine the effect of an active lifestyle on the probability of functional decline, controlling for disease status and impairment level in a nationally representative population of well functioning younger elders. METHODS
Sample and data
The data used in this study were taken from the Longitudinal Study of Aging (LSOA) conducted by the National Center for Health Statistics and the National Institute on Aging. The study is briefly described here. More detailed information about the 1984 Supplement on Aging (SOA), of the National Health Interview Survey is published in greater detail elsewhere [13, 141. Households were selected through a multistage probability sampling procedure based upon the week of the year in which interviews were conducted. Interviews were conducted by trained U.S. Bureau of Census personnel. Proxy responses were allowed if there was a knowledgeable family member available. Of the 16,148 individuals interviewed in 1984, 91.5% responded for themselves. The SOA asked numerous questions about the physical and social functioning of the elderly respondents, i.e. the activities of daily living (ADLs) and the instrumental activities of daily living (IADLs) as well as more difficult functions such as climbing stairs or carrying groceries. The degree of difficulty elders experienced performing these latter activities was also determined. In 1986, a sample of SOA participants who were over age 70 in 1984 was selected for reinterview, oversampling those over 85 and minorities. Of the 7541 eligible individuals interviewed in 1984, 5151 (68.3%) were sampled for reinterview in 1986. A computer assisted telephone interview system was used to gather the interview data. Once again, proxy interviews with family members were permitted. The interview was similar to the 1984 survey with the principle focus on functioning and receipt of formal and informal service assistance in meeting needs arising from functional deficits. Of the
5 151 individuals identified for reinterview, 417 (8.1%) have unknown status, and 604 (11.7%) were deceased. Sample refinement
Consistent with our interest in the prevention of functional decline among well elders, we chose to focus on the risk of functional decline among the youngest respondents in the LSOA; those 7&74 years of age in 1984. This group had the highest proportion of persons who were intact in all ADLs, IADLs and the more difficult functions. It is in this younger group of aged persons that the impact of preventive health services is most likely to be observed. A total of 1745 sample members in the LSOA met this age condition. We further chose to focus upon individuals who were intact in all ADLs, IADLs as well as aforementioned extended function as measured by selected items from the Nagi battery included in the SOA [15, 161. Extended function items included in defining the functionally intact state were: climbing 10 stairs, carrying 25 lb (2 bags of groceries), walking l/4 mile, performing heavy housework or other heavy chores. To be considered “intact” required that the individual perform all four activities independently, without personal assistance. In addition to the independent performance of each activity, we also considered the degree of difficulty respondents had performing an activity alone. Those reporting considerable, or a great deal of difficulty on any one of the four items resembled those who were unable to perform the functions. Consequently, they intact. were classified as not functionally Those reporting only “some” difficulty in performing those activities were classified as independent. Independence in the IADLs and the ADLs were a virtual prerequisite to independence in the four extended function items. Less than 1% of those with difficulty in an IADL were intact in the extended core functions. Although not used as a Guttman scale, we found that the four extended function items when combined with an indicator of IADL dependency and one for ADL dependency, yielded a coefficient of reproducibility of 0.90. Classification “errors” were highest on the household chores item, which is probably more a function of environmental and sex role factors than physical health factors. This extension of the ADL and IADL hierarchy is consistent with work by Katz et al. [ 15, 171 and more recently by Pinsky et al. [ 181.
Risk of Functional Decline
Definition of functional decline and its predictors
The outcome variable was defined as no longer being intact on the extended function items in 1986 among those who survived and were interviewed. Intact was defined in 1986 precisely as in 1984. Thus, decline by 1986 includes any respondent unable to independently climb 10 stairs, walk l/4 mile, carry 25 lb or do heavy housework or who reported “some” difficulty in any of these tasks. Inability to independently perform any ADL or IADL activities was also considered to be decline. We adopted a dichotomous dependent variable for two reasons. First, this approach is similar to the traditional disease prevention and mortality prediction models. We view our research into the determinants of functional decline as earlier researchers who examined the determinants of heart disease and mortality, both of which are dichotomous outcomes. Second, earlier studies of functional decline in smaller populations revealed that the predictors of decline vary as a function of both baseline impairment and degree of decline. Since we focused our analyses on the well elders, the fact of the onset of decline is the relevant outcome. We hypothesized that involvement in the active lifestyle will positively affect an individual’s risk of loss of function, controlling for demographic characteristics and the presence of pre-existing health problems, disease and impairment. The LSOA contains questions measuring standard demographics (such as race, marital status, education etc.). Health risks and conditions (bed days, hospital use, diabetes) were reported by survey respondents, a practice consistent with similar community epidemiology studies. Prior research comparing self reported major medical conditions in a community population has been inconsistent but generally supports reasonable congruence between physician and patient reported health [19-211. The presence of a health condition was measured as merely present or absent without indication of the severity of the condition. However, since manifestation of disease severity is most often expressed as functional limitations, the reported medical conditions of our study subjects are unlikely to be severe since they have no functional limitations. Lifestyle activities were solicited in the LSOA with only a few questions. Those pertaining to social and physical activity were asked in the form: “Have you . . . gone to church or temple
897
in last 2 weeks”; “Do you follow a REGULAR routine of physical exercise?“. A single item about respondents’ walking was in the form “How often do you walk a mile or more without resting?” Response options ranged from never to everyday. Analytic approach
The relative risk of functional decline in 2 years was calculated for dichotomized predictor variables along with Taylor series confidence intervals [22]. Multivariate logistic regression models were then estimated separately for each predictor domain (demographic, medical and behavioral) and the adjusted odds ratios of variables in the models were compared. Stepwise logistic regression was utilized to identify those predictors meeting traditional criteria of statistical significance. Significant variables from each domain were incorporated into a single model. The relative risk of decline associated with each lifestyle activity was explored by testing the increase in the log-likelihood ratio resulting from adding each term to the model. In addition, the multivariate adjusted relative risk associated with each activity after controlling for demographic and health related variables was calculated to account for the inherent multicollinearity thought to exist among the lifestyle variables. As has been found so often before, our initial analyses revealed that self-reported health is one of the best predictors of future status, both survival and functional decline [23]. Since selfreported health is correlated with both the presence of medical conditions and lifestyle activities, when it was entered into multivariate logistic models, other variables with more interpretable and policy relevant meaning were supplanted. Given the salience of the activity measures we chose not to include self reported health measures in the final combined models. We examined the bivariate relationship of these self-report measures with our outcome measure to provide a comparison of the effect of the other independent variables on decline. The final analytic step was to estimate separate models of functional decline for males and females. Since our measure of functional decline may have been partially influenced by sex role specific activities (e.g. household chores, regular exercise), separate models were necessary. There were also considerable differences in the proportion of males and females performing selected activities. Additionally, males had significantly
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lower rates of functional decline than females (18.5. vs 31.8%) and they were more likely to have died (6.9 vs 1.6%). All these factors merited the use of separate models for men and women. Due to the exploratory nature of these analyses and our use of only a select subsample of well functioning survivors, no attempt was made to adjust either the bivariate or multivariate analyses for the multistaged sampling frame. All figures presented are based only upon the study sample and no attempt is made to extrapolate results to a known population. FINDINGS
Sample description
Table 1 contrasts sample members in the 70-74 year old age group who were and were not functionally intact in 1984. Over half (55.3%) of this age cohort were intact in the extended core functions. Males were more
prevalent in the well functioning group as were whites, married persons, those who are better educated, and those with family incomes greater than U.S. $25,000. Despite the large differences in these measures, there is virtually no difference in the ages of the two groups (71.90 vs 71.96). Nearly 15% of those with intact functioning were working as compared to only 4.3% of those not functionally intact. On all health related variables, the functionally intact were less likely to report bed days, hospitalization, falls or virtually any of the health conditions included in the interview than were those who are not functionally intact. With respect to perceived health and activity level, functionally intact respondents compared their activity levels favorably to that of their peers, felt they had more control over their health and were less likely to worry over their health than were those who were not functionally intact. Finally, the functionally intact were more likely to exercise, go to church and other social events as well as
Table 1. Description of the study sample by intact functional status: Longitudinal Study of Aging, ages 70-74 Not intact function N = 776
Intact function N =961
Female White Married Family income U.S. $25,000+ Education: some college Living alone
68.0% 80.2% 50.6% 12.7% 14.8% 34.1%
53.4% 86.6% 62.4% 18.6% 21.1% 25.1%
Serf assessed health Self assessed health-fair/poor Not limited in activity Health worse than last year Does not worry about health Activity level less than last year Working is major activity
55.1% 42.9% 25.7% 29.7% 31.1% 4.3%
16.0% 86.8% 5.1% 63.1% 6.8% 14.8%
50.8% 73.7% 37.6% 22.5% 4.3% 6.3% 3.6% 10.5% 9.3% 16.0% 68.6% 28.4% 42.1%
78.3% 88.2% 15.8% 12.6% 2.5% 3.0% 1.7% 3.4% 2.4% 7.3% 41.4% 12.5% 27.6%
13.6% 77.8% 24.4% 50.0% 23.7% 8.4%
22.5% 81.4% 34.5% 60.0% 35.6% 25.4%
Variables Demographics
Health status No bed days past 12 months
No hospitalizations last year Has trouble with vision Has cataracts Has osteoporosis Has coronary heart disease Past myocardial infarction Has angina pecoris Has had stroke/CVA Has diabetes Has arthritis Has fallen in past 12 months Reports frequently getting confused Activity pattern
Did volunteer work last year Got together w/relatives last 2 wk Went to movies, sports last 2 wk Went to church, temple last 2 wk Reports regular exercise routine Walks one mile 4-7 days/week
899
Risk of Functional Decline Table 2. Description of the functionally intact study sample by sex: Longitudinal Study of Aging, ages 70-74 Variables
Male N=448
Female N = 513
Demographics
White Married Family income U.S. $25,000+ Education 13+ years Living alone
84.3% 80.8% 23.1% 22.1% 13.4%
78.2% 46.4% 14.1% 20.3% 35.3%
Self assessed health Self assessed health-fair/poor Health worse than last year Not limited in activity Activity level less than last year Does not worry about health Work is major activity
20.1% 7.1% 81.9% 7.5% 60.6% 20.5%
12.3% 3.4% 91.0% 6.2% 65.2% 9.1%
77.4% 85.7% 15.9% 9.7% 0.7% 4.9% 2.9% 4.5% 4.0% 7.6% 35.6% 9.6% 30.4%
79.1% 90.4% 15.8% 15.2% 4.1% 1.4% 0.6% 2.5% 1.0% 7.0% 46.5% 15.0% 25.2%
16.6% 80.0% 33.3% 56.3% 37.0% 31.6%
27.1% 82.6% 35.5% 63.3% 34.4% 20.1%
Health status No bed days past 12 months
No hospitalizations last year Has trouble with vision Has cataracts Has osteoporosis Has coronary heart disease Past myocardial infarction Has angina pecoris Has had stroke/CVA Has diabetes Has arthritis Has fallen in past 12 months Reports frequently getting confused Activity pattern
Did volunteer work last year Got together w/relatives last 2 wk Went to movies, sports last 2 wk Went to church, temple last 2 wk Reports regular exercise routine Walks one mile 4-7 days/week
participate in volunteer activities than were those who were not intact. Table 2 contrasts males and females in the intact group. Women were nearly half as likely to be married and were less likely to have incomes over U.S. $25,000 in 1984. Males were more likely to rate their health as fair or poor, but were less likely to have reported falling or to have arthritis. Males were more likely to report all types of heart disease such as history of an MI than were women; however, these are not prevalent conditions in either sex. With regard to participation in activities, women were somewhat more likely to report doing volunteer work and going to church, but were less likely to regularly walk a mile although they were almost as likely as were men to report having a regular exercise routine. Relative risk of functional decline
Of the 961 fully functionally intact persons interviewed in 1984,4.1% had died and another 7.3% were not interviewed and no proxy data
were available. Of the 852 persons interviewed, 246 (29.0%) were no longer able to perform all four extended core functions without more than some difficulty. The most prevalent area of lost independence was in carrying 25 lb (22.3%) while 10.3% were no longer able to walk l/4 mile without difficulty. Despite the substantial proportion of surviving sample members whose function declined, only a few became dependent in IADLs (1.5% in personal shopping) or ADLs (0.8% m bathing). Table 3 summarizes the relative risk of functional decline and the associated confidence bounds calculated at the 95% confidence limits for each predictor variable. If the confidence bounds do not include “1.00” the relationship between the predictor and functional decline is statistically significant at conventional levels (p < 0.05). The predictor variables are coded such that the negative state is coded as “1” while the positive, or neutral, condition is coded “0”; meaning that relative risk figures greater than 1.0 are indicative of increased risk of
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Table 3. Relative risk of functional decline in two years for selected demographic, health status and volitional life activities: Longitudinal Study of Aging; ages 7&74 (N = 852) Relative risk
Lower limit
Upper limit
1.60 1.45 1.48 1.53 1.80 1.26
1.28 1.12 1.20 1.13 1.39 1.oo
2.01 1.88 1.82 2.07 2.32 1.58
Major activity is keeping house Any bed days in last year Any hospitalizations Trouble with vision Cataracts Osteoporosis Hypertension Any heart disease Past stroke or CVA Arthritis Diabetes Fallen past year Frequently confused
1.47 1.14 1.05 1.57 1.24 1.37 1.20 1.46 1.75 1.64 1.77 1.48 1.08
1.03 0.89 0.76 1.24 0.93 0.81 0.97 0.94 1.09 1.33 1.33 1.14 0.86
2.11 1.45 1.46 1.99 1.65 2.31 1.48 2.29 2.82 2.36 2.36 1.92 1.37
Serf assessed health Perceived health fair/poor Health worse than last year Worries about health Less active than peers Activity level less than last year
1.54 1.88 1.71 1.55 1.81
1.24 1.36 1.33 1.25 1.34
1.91 2.59 2.12 1.92 2.45
1.16 0.95 1.02 1.51 1.56
0.89 0.21 0.82 1.18 1.25
1.45 1.25 1.26 1.94 1.93
Predictors Demographics
Female Nonwhite Unmarried No college Income U.S. <$25,000 Living alone Health status
Activity pattern
Did volunteer work Didn’t get together w/relatives No church or temple No regular exercise Never walks one mile
functional decline. For example, women were 1.6 times more likely to decline in the 2 year period than were men. Women, nonwhites, non-married persons, those living alone, those without a college education or incomes under U.S. $25,000 were more likely to manifest functional decline. Neither bed days in the prior year, nor past hospitalizations were found to be related to decline. On the other hand, all subjective assessments of health were highly related to decline in the expected direction. Those reporting their health to be only “fair”, or “poor”, were 1.54 times more likely to decline than were those with a more optimistic appraisal of their health. Those reporting that their health in 1984 was worse than it was a year before (only 5.1% of the sample) were 1.83 times more likely to have deteriorated functionally by 1986 than were those reporting their health to be stable or improving. Worry over health was also strongly predictive of decline as was individuals’ assessment of their health relative to their
peers. Clearly, individuals’ internal barometer appears to be as accurate as the “objective” determinants of health in predicting decline. Among the lifestyle activities, we see that only those involving physical exertion appear to be predictive of future functioning. Respondents noting that their major activity is keeping house were significantly more likely to have declined than were those whose normal activity was work. On the other hand, volunteer work, social outings, church participation and going to movies or sports events all revealed relative risks of decline that were not different from 1.0. The two more physically active indicators, regular exercise and walking one mile, were very strongly related to decline. Those without an exercise routine were 1.51 times more likely to decline than those who regularly exercised, and those who never walk a mile were 1.56 times more likely to decline than were those who do so at least several times a week. While we observe no evidence in support of the protective value of the social and intellectual dimensions of
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Risk of Functional Decline
lifestyle activities, we do find that an active lifestyle may enable one to be functionally independent longer than a less active one. Multivariate adjusted risk of decline
Within each domain we performed stepwise logistic regression to identify from among all variables in the domain, those that were related to functional decline, controlling for all others in that domain. Not all variables with a significant bivariate relationship to the outcome emerged as significant in the multivariate model. Since family income and respondent education were correlated, we selected education in view of its association with health status and function in previous research [18]. In the demographic domain, sex, education and marital status entered into a logistic model predicting decline. In the medical domain, arthritis, diabetes, past stroke as well as visual impairment, falls and confusion all entered the multivariate model. Among the lifestyle activities, only exercises and walking entered the model; working did not reach significance after controlling for the two physical activities. The final model synthesizing the three domains included those variables found to be significantly related in each domain. We tested several possible interactions among variables across domains and also examined possible suppressor variables. Table 4 presents the summary logistic regression model combining males and females. The adjusted odds ratio of each variable as well as its associated confidence limits are presented. Thus, the indicator variable for sex is clearly highly significant, controlling for other demographic, health and behavioral risk factors, It can be interpreted to mean that women are 1.3 times more likely to decline than are men and this relationship is statistically significant since the lower estimate of the 95% confidence bound is as high as 1.2. All terms in the final model
were significantly related to functional decline. Even fairly skewed variables such as the presence of prior stroke have relatively small confidence intervals. It is interesting to note that the two behavioral factors, lack of regular exercise and not walking were as predictive of decline as were several of the medical and impairment measures. In examining the predictors of decline for males and females separately, we reconstructed separate models beginning with the larger variable pool. Table 5 presents the adjusted odds ratios and their associated confidence intervals for the predictors which entered each sexspecific model. Only a few variables predict decline among men. Medical factors, (history of stroke and the presence of diabetes), were strongly related to decline. We tested a variety of different variables regarding the presence of cardiac conditions but none improved upon the present model. Those whose normal activity is not work are 1.4 times more likely to decline than those who are still working. Even controlling for work status, however, engaging in a regular exercise program is protective; those who do not are nearly 1.6 times more likely to decline in functional independence. Among women the model is somewhat more complex with medical and functional factors such as diabetes, arthritis, visual impairment and having fallen in the past year all being related to decline. Diabetes is comparably predictive of decline among males and females. Table 5. Odds ratios and associated confidence intervals from a multiple logistic regression model predicting functional decline for functionally intact males and females: Longitudinal Study of Aging; ages 70-74 Predictors Not college educated Work not usual activity
Table 4. Odds ratios and associated confidence intervals from multiple logistic regression model predicting functional decline for all functionally intact cases: Longitudinal Study of Aging; ages 7&74 (N = 852) Predictors Sex (female) Unmarried Not college educated Diabetes Arthritis Past stroke Visual impairment No regular exercise Never walks 1 mile
All cases
Confidence intervals
1.321 1.250 1.196 1.648 1.370 1.785 1.305 1.197 1.288
(1,222-l ,404) (1.122-1.320) (1.122-1.346) (1.477-1.779) (1.223-1.393) (I ,358-l .9S6) (1.152-1.371) (1.103-1.299) (1.230-1.470)
Males Females (Confidence intervals)
Diabetes Past stroke
1.426 (1.381-1.571) 1.438 (1.342-1.634) 1.539 (1.322-1.756) 1.964 (1.610-2.318)
Visual impairment
1.260 (1.1241.396) 1.350 (1.24415456) 1.278 (1.1361.420)
Arthritis Fallen in last 12 months No regular exercise Never walks 1 mile
1.563 (1.365-1.661)
1.583 (1.426-1.740) 1.459 (1.3161.602)
902
VlNCENT
Women with a lower educational level were more likely to decline than were the more educated women, perhaps reflecting income effects as well as lifestyle patterns that differ as a function of socioeconomic conditions. Controlling for these medical and background characteristics, we see that women who never walk one mile are nearly 1.5 times more likely to decline than are women who walk a mile at any frequency. Thus, for both men and women having a physically active lifestyle appears to be protective of functional decline. Indeed, the adjusted odds ratios for the physical activity variables increase substantially in the models run separately for males and females when compared to the combined model.
DISCUSSION
We analyzed the Longitudinal Study of Aging (LSOA) to identify those factors that were predictive of loss of independent functioning and to test the hypothesis that elders’ participation in an active lifestyle would be protective of functional decline. Results reveal that among functionally intact men and women between the ages of 70 and 74, those who regularly exercised or walked a mile were less likely to lose functional independence over a 2 year period than were those who did not pursue such activities, controlling for the presence of medical problems and impairments. In the discussion which follows, we examine several aspects of the study findings that argue for the viability of and continued need for exploration of the concept of the primary prevention of functional decline. Our analyses revealed that medical problems and dysfunction do not always go hand in hand. Indeed, as many as 40% of the well functioning elderly between 70 and 74 report having arthritis and 16% have vision problems. Morbidity as measured by the presence of disease, does not necessarily mark the onset of disability. Rather, as our research suggests, the presence of disease may be a marker of future loss of functional independence. Disease severity is obviously an important parameter which our study was not able to measure. However, since severity is often measured in relation to the functional consequences of the disease and our study sample was functionally intact, severity is unlikely to account for much mispecification of the model. And while it is true that the relationship
MOR
el a/.
between clinical parameters (e.g. non-HDL cholesterol) and mortality has been established in younger and older populations [24,25], there continues to be a dearth of reported longitudinal studies examining the relationship between such clinical indicators of illness severity and functional decline in the aged population. Physical and laboratory assessment measures have proved to be no more predictive of functional decline among arthritics than have simple patient assessments [26-281. Pinsky and her colleagues found that physiological measures such as blood pressure and vital capacity were unrelated to future functioning after controlling for age, sex and education [ 181. Several longitudinal studies have examined the relationship between active lifestyles and mortality. For example, various reports based on the Alameda County data indicate that engaging in social and physical activities may reduce the risk of mortality among younger and older individuals over periods of 9-17 years [29-311. Analyses of the Techumseh Community Health Study revealed that 10 year death rates from all causes were negatively associated with social activities, and among females, positively associated with sedentary activity such as watching television [32]. Similar results indicating the protective effect of participation in activities outside the home and of aerobic sports have been reported by the Goteberg studies and the Harvard Alumni Study [33,34]. These reports suggest that an active lifestyle improves survival. Survival effects may be translatable into gains in “active” life expectancy [7], notwithstanding the increased likelihood of morbidity with increased age. Several longitudinal studies have found that elders’ functional status at one point in time is a strong indicator of their survival as well as their future functional status. Using Massachusetts Panel data Katz and his colleagues found that elders with functional dependencies were less likely to survive and more likely to decline than were those who functioned independently [7]. Using several data sets, Spector and his colleagues revealed that elders with dependencies in either ADL or IADL were less likely to survive and more likely to become more impaired than were elders without physical functional limitations at the outset [17]. Mortality is often preceded by a period of functional decline. Whether some of this can be avoided even in the face of chronic disease that may eventually lead to death requires more research.
Risk of Functional Decline
The current study, to our knowledge, is the first to specifically examine the relationship between participation in an “active” lifestyle and future functioning. Obviously, a physically active lifestyle presupposes functional independence. Research on physical functioning consistently reveals that loss of independence in the basic and instrumental activities of daily living generally proceeds in a hierarchical manner [ 15, 171. However, individuals engage in a broader range of activity than merely the ADL and IADLs. The most basic functions are defined as the final common pathway of functional loss associated with most progressive disease [30,35]. Extended core functions which have been incorporated into Nagi’s measures of function include climbing stairs and carrying groceries, activities requiring more stamina [16, 361. These have all been combined into a single “Good Function Index” by Pinsky et al. [18]. Differentiating between the extended core functions and those that are reflections of lifestyle choices may appear arbitrary. Participating in a regular exercise routine is a lifestyle choice, whereas climbing stairs is a task frequently encountered as part of daily life. Additionally, while walking a quarter of a mile is frequently demanded of independent persons interacting with their environment, walking a mile in our society is more likely to be a reflection of individual choice. We feel such lifestyle choices are qualitatively different from every day functional demands and as such, represent legitimate predictors of loss of functional independence over a 2 year period in a homogeneous sample of well functioning younger elders. Our analyses suggest that the men and women who regularly walked or engaged in exercise were significantly more likely to remain independent in extended functions as well as in the IADLs and ADLs than were those who did not. Of particular interest was the fact that although functionally intact men and women reported regularly exercising (37.0 vs 34.4%, respectively) at similar levels, walking one mile 4-7 days a week (done by only 20% of women) was protective of decline for women while exercise was protective for men. Since walking a mile is a more explicit description of behavior than is regular exercise, men may have interpreted this item as meaning a more rigorous workout than did women. Based upon our analyses, the clinical significance of the observed lifestyle effects is
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similar to having a diagnosis of diabetes which is a health condition known to affect morbidity and mortality. Additionally, since the adjusted odds ratios associated with the two lifestyle variables actually increase in the separate sex models, it is unlikely that statistical significance is merely attributable to sample size. Other research seeking to determine the effect of lifestyle choices on survival have yielded similar and even smaller (although statistically significant) effects on which many public health recommendations have been based. We did try to test the role of less physically taxing activities such as attending church and mixing socially with family and friends, however, these factors seemed unrelated to future decline, even though they had differentiated the functionally intact and not intact groups at baseline. Whether a broader range of social or intellectual, as opposed to merely physical, activities might prove to be protective of future decline remains to be seen. In the absence of even a bivariate relationship in our analyses, it may be that physically taxing activities will predominate future research as well. Conducting such research using secondary data sets always entails making compromises. The choice of control variables is limited and their validity is open to debate. While the relationships we observed between the presence of medical problems, impairments and future functioning were anticipated, it is not clear whether unmeasured medical problems would have suppressed the observed effect of exercise and walking on functional decline. Given the paucity of measures of current and past lifestyle activities in this data set, it is possible that measures of current lifestyle may already reflect the presence of morbidity that led to a reduction in exercise and walking. Attributing causality to exercise and walking is problematic at this stage. Indeed, it may be that active lifestyle must be ongoing for decades in order to effect future functioning, and that adopting such activities later in life may be ineffective. Nontheless, since small scale trials of exercise programs have been shown to have positive short term effects in the impaired elderly, it is reasonable to expect younger elders who are still functioning to benefit from adopting a more active life style [l 1, 121. Establishing the validity of the primary prevention of functional decline model ultimately requires the same experimental testing to which disease prevention models have been subjected.
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We feel that this study has accomplished the first step of examining the relationship between lifestyle and functional decline using a panel study. Future efforts utilizing more sophisticated data sets, covering longer periods of time, with better clinical information and data on other long term lifestyle behaviors will determine whether active lifestyles are protective or merely predictive of future functioning. REFERENCES 1.
2. 3.
4.
5. 6.
IO.
11.
12. 13.
14.
15.
16.
Patrick DL, Bush JW, Chen MM. Toward an operational definition of health. J Health Sot Behav 1973: 14: 6. Ware JE Jr. Scales for measuring general health perceptions. Health Serv Res 1976; 11: 3988415. Read JL, Quinn RJ, Hoefer MA. Measuring overall health: an evaluation of three important approaches. J Chron Dis 1987; 40 (Suppl. I): 7%21s. Jette AM, Branch LG. The Framingham Disability Study II. Physical disability among the aging. Am J Public Health 1981; 71: 1211-1216. Schick FL. Statistical Handbook on Aging America. Phoenix: The Oryx Press; 1986. Liu K, Manton K. Long term care: current estimates and projections. Proc 1987 Public Health Conference on Records and Statistics, DHHS Pub. No. (PHS) 88-1214. Hyattsville, Md; 1987. Katz S, Branch LG, Branson MH et al. Active life expectancy. N Engl J Med 1983; 309: 1218. Fries JF. Aging, natural death, and the compression of morbidity. N Engl J Med 1980: 303: 130-135. Berg RL. Prevention of Disability in the Aged. In: Last JM, Ed. Maxcy-Rosenau Public Health and Preventative Medicine, 1Ith edn. New York: AppletonCountry-Crofts; 1980; 128331299. Patrick DL. Commentary: patient reports of health status as predictors of physiologic health in chronic disease. J Chron Dis 1987; 40 (Suppl. I): 37S-4OS. Bruce RA. Exercise, functional aerobic capacity and seine. In: Princinles of Geriatric Medicine. Andres R. B&man EL, Haizard WR, Eds. New York: McGraw: Hill; 1985: 87-103. Larson EB, Bruce RA. Exercise and aging (Editorial). Ann Intern Med 1986: 105: 783-785. Kovar MG. The longitudinal study of aging: the 1986 reinterview public-use file. Proc 1987 Public Health Conference on Records and Statistics, DHHS Pub. No. (PHS) 88-1214. Hyattsville, Md; 1987. Feller BA Americans Needing Home Care, United States. Vital and Health Statistics, Series 10, No. 153, DHSS Pub. No. (PHS) 86-1581, Public Health Service. Washington, DC.: U.S. Government Printing Office; March 1986. Katz S, Ford AB, Moskowitz RW et al. Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA 1963; 185: 914. Nagi S. An epidemiology of disability among adults in the United States. Milbank Mem Fund Q 1976: 54: 439-468.
al.
17. Spector WD, Katz S, Murphy JB, Fulton JP. The
18.
19.
20.
21.
22.
23.
24. 25.
26.
27.
28.
29.
30.
31.
32.
33.
34. 35. 36.
hierarchical relationship between activities of daily living and instrumental activities of daily living. J Chron Dis 1987; 40: 481-489. Pinsky JL, Leaverton PE, Stokes J. Predictors of good function: The Framingham Study. J Chron Dis 1987; 40 (Suppl. 1): 159S-167s. Fillenbuam GG. Social contest and health assessments of health among the elderly. J Health Sot Rehav 1979; 20: 45-51. Kaplan GA, Kotter PL. Self reports predictive of mortality from ischemic heart disease: a nine-year follow-up of the human population laboratory cohort. J Chron Dis 1985: 38(2): 195-201. LaRue A, Bank L, J&k L, Hetland M. Health in old age: how do physician ratings and self-ratings compare. J Gerontol 1979; 34: 687-691. Kleinbaum DG. KuDner LL. Moraenstem H. Enidemiological R&ear& Principles &d Quantita&e Methods. Belmont, Cahf.: Lifetime Learning; 1982. Kaplan SH. Patient reports of health status as predictors of physiological health measures in chronic disease. J Chron Dis 1987; 40 (Suppl. 1): 27535s. Consensus Conference. Lowering blood cholesterol to prevent heart disease. JAMA 1985; 253: 208&2086. Anderson K, Castelli W, Levy D. Cholesterol and mortality: thirty years of follow-up from The Framingham Study. JAMA 1987; 257: 21762180. Bellamy N, Buchanan W. Outcome measurement in osteoarthritis clinical trials: the case for standardization. Clin Rheumatol 1984; 3: 293-303. Rasker J, Cosh J. The natural history of rheumatoid arthritis: a fifteen year follow-up study. Ciin Rheumatol 1984; 3: 11-20. Helawa A, Goldsmith C, Smythe H. Independent measurement of functional capacity in rheumatoid arthritis. J Rheumatol 1982; 9: 794-797. Berkman LF, Syme SL. Social networks, host resistance and mortality: a nine year follow-up study of Alameda County residents. Am J Epidemiol 1979; 109: 186-204. Wingard DL, Berkman LF, Brand RJ. A multivariate analysis of health related practices: a nine-year mortality followup of the Alameda County study. Am J Epidemiol 1982; 116: 765-775. Kaplan GA, Seeman TE, Cohen RD, Knudsen LP, Guralnick J. Mortality among the elderly in the Alameda County study: behavioral and demoeranhic risk factors. Am J Public Health 1987: 77: TOi-312. House JS, Robbins C, Metzner HL. The association of social relationships and activities with mortality: prospective evidence from the Tecumseh Community Health Study. Am J Epidemiol 1982; 116: 123-140. Welin L, Svardsudd K, Ander-Peciva S, et al. Prospective study of social influences on mortality: the study of men born in 1913 and 1923. Lancet 1985; 915-918. Paffenbarger RS, Hyde RT, Wing AL, Hsieh C. Physical activity, all cause mortality and longevity of college alumini. N Engl J Med 1986; 314: 605-613. Mor V. Cancer patients’ quality of life over the disease course: lessons from the real world. J Chron Dis 1987; 40: 535-544. Rosow I, Bresalu H. A Guttman health scale for the aged. J Gerontol 1966; 21: 556559.