1 Human Population Laboratory, Public Health Institute, Berkeley, CA.
2 School of Public Health, University of Texas, Houston, TX.
3 Department of Epidemiology, University of Michigan, Ann Arbor, MI.
Received for publication October 1, 2001; accepted for publication April 24, 2002.
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ABSTRACT |
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aged; disabled persons; exercise; mental health; prospective studies
Abbreviations: Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio.
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INTRODUCTION |
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Increased levels of physical activity are known to reduce morbidity and mortality (810), but the impact on depression is not clear. Three community-based longitudinal studies concluded that physical activity was not protective for subsequent depression (1113). However, two of these (11, 12) studied only middle-aged males. Although the third study (13) did include both men and women as well as older subjects, physical activity was defined as exercise during sports, which would fail to capture other activities such as walking or jogging that are normally included in assessments of physical activity. One of these studies (12) also involved only 47 subjects. Three large, community-based studies did report a protective effect. One (14) was limited to male college students, but the other two included a very broad age range as well as both men and women (15, 16). One of these reported a longitudinal protective effect of physical activity on depression for both men and women (15), while the other (16) reported an effect only for women.
Citing such inconsistent results, a recent longitudinal analysis of older subjects based on data from the Rancho Bernardo Study argued that these longitudinal studies erred by failing to exclude physically disabled subjects at baseline (17). Physical disability represents a potentially powerful confounding variable because it is associated with both a higher risk of depression and lower levels of physical activity. In the Rancho Bernardo analyses, with physically disabled subjects (6.7 percent of the initial sample) removed, there were no statistically significant longitudinal effects of physical activity on depression (measured as depressed mood).
Results from intervention trials involving physical activity and depression have been equally inconsistent; a recent meta-analysis concluded that the reviewed results were contradictory and had serious methodological difficulties such as lack of concealment for treatment allocation, blinding of results, and intention-to-treat analyses (18).
The analyses reported here attempt to clarify the relation between physical activity and depression by utilizing a broad-based community sample that included both men and women over a wide age range. Follow-up was for 5 years, and likely confounders were included in statistical models. Both cross-sectional and longitudinal associations were examined, and longitudinal analyses were made with and without exclusion of physically disabled subjects at baseline.
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MATERIALS AND METHODS |
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Of the 2,123 subjects in the initial sample frame, 2,061 were age 50 years or older in 1994; of these, 114 were missing responses on one or more of the variables in the analyses reported here and so were excluded. The mean age of the remaining 1,947 in 1994 was 63 years; 56 percent were female. Ethnicity was 84 percent White, 7 percent African American, 4 percent Asian, 3 percent Hispanic, and 2 percent other groups.
Measures
Except for the inclusion of 1999 depression, all measures reflect 1994 values.
Physical activity.
We constructed a physical activity scale based on four questions: usual frequency of physical exercise, taking part in active sports, taking long walks, and swimming. The response set for each item was never, sometimes, or often; scoring was zero, one, or two, respectively. The resulting scale had a range of 08 with a mean of 3.4; reliability (standardized Cronbachs alpha) was 0.64. This scale has been used in previous analyses to demonstrate a protective effect for physical activity on all-cause and cardiovascular mortality for both men and women (20, 21) and as a 5-year predictor of successful aging (22).
Depression
. The measure of depression was a set of 12 items that operationalized the diagnostic criteria for a major depressive episode outlined in Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (23). Designated the DSM12D, the items or symptom queries were adapted from the PRIME-MD mood disorders section of the Manual. Cases of major depressive episode were subjects who had experienced five or more symptoms of depression almost every day for the previous 2 weeks, including disturbed mood or anhedonia. There were 145 cases of depression in 1994, for a prevalence of 7.4 percent. This number is within the range of results reported in other community studies of older persons for major depression but is probably lower than that which would have been obtained with symptom scales specifically designed to capture those older persons with significant depressive symptoms who do not otherwise meet diagnostic criteria for major depression (2427). Incident cases in 1999 totaled 98 (5.4 percent) among the 1,802 subjects who were not scored as depressed in 1994.
Disability
. Four variables common to many data sets were used to assess disability: walking a quarter mile (0.4 km); walking up 10 stairs without resting; getting up from a stooping, kneeling, or crouching position; and standing up after sitting in a chair (2830). Those who reported having a lot of difficulty or needing help to do any of the four items were scored as disabled.
Covariates
. Covariates included demographic variables, financial problems, neighborhood problems, chronic conditions, health behaviors, and social relations. Each factor can be categorized as a status attribute, a psychosocial resource, or a stressor and has been shown to predict depression in Alameda County Study analyses and elsewhere (3134). Demographic variables included age (5069, 7079, and 80 years), sex, ethnicity (White vs. other), and education (<12 years vs.
12 years of education). Financial problems included any one of the following: not having enough money in the previous 12 months to buy clothing, fill a prescription, see a doctor, pay rent or mortgage, or (in the previous 30 days) buy food. Neighborhood problems included responding that any of the following conditions constituted a very serious problem: crime, traffic, noise, trash and litter, night lighting, and availability of public transportation. Chronic conditions included the prevalence in the previous 12 months of arthritis, asthma, bronchitis, diabetes, emphysema, heart disease, and high blood pressure. These were collapsed into three variables of zero, one, or two or more conditions. Health behaviors included cigarette smoking (current, former, never), alcohol consumption (0, 160, and >60 drinks per month), and body mass index (BMI) (weight (kg)/height (m)2), which was used to divide subjects into three categories: underweight (BMI, <18.5), normal/overweight (BMI, 18.5<30), and obese (BMI,
30) using recent guidelines from the National Heart, Lung, and Blood Institute (35). Social relations included fewer than three close friends versus three or more, fewer than three close relatives versus three or more, and being somewhat or not satisfied with friendships and relations with others versus being very satisfied.
Data analyses
The relation between each independent variable used in the analyses and both prevalent and incident depression was first examined for all 1,947 subjects using percentages and unadjusted odds ratios. To test the physical activity scale for linearity, we plotted the log odds of depression against the physical activity scale (data not shown); results did not depart substantially from linearity, so physical activity was used as a linear scale in subsequent analyses.
Four sequential logistic models were then used to analyze associations between physical activity and depression. The first model included only physical activity along with age, sex, and ethnicity. The second model added education, financial problems, and neighborhood problems as covariates. The third model added disability, chronic conditions, and health behaviors, while the fourth added the social relation variables.
Three sets of analyses were conducted by using the sequential models. In the cross-sectional analyses, 1994 physical activity was used to predict prevalent depression in 1994 for all 1,947 subjects. In the longitudinal analyses, 1994 physical activity was first used to predict incident depression in 1999 after the exclusion of the 145 subjects with prevalent depression in 1994. Finally, as a test of the Rancho Bernardo Study recommendation, the longitudinal models were rerun after excluding 151 additional subjects who reported physical disability in 1994. Because the incidence rate of depression was low (5.4 percent after exclusion of subjects with prevalent depression), the resulting odds ratios from the logistic analyses for the longitudinal models closely approximate relative risks.
All calculations were performed using SAS, version 6.12 (SAS Institute, Inc., Cary, North Carolina).
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RESULTS |
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Associations between depression and age as well as ethnicity were not statistically significant. Females and subjects with fewer than 12 years of education were more likely to be depressed, as were those who reported financial strain or neighborhood problems. Compared with those with no alcohol consumption, those who consumed 160 drinks per month were less likely to be depressed, while current smokers were more likely to be depressed than were nonsmokers.
Reporting one or two or more chronic conditions compared with no condition was associated with depression, as was obesity. Subjects who reported fewer than three close friends or relatives were more likely to be depressed, as were those who reported being somewhat satisfied or not satisfied with friendships.
The two right columns of table 1 present the associations between baseline risk factors and incident depression in 1999. With only several exceptions, associations with depression are similar to those for the prevalent associations. Major differences involve age, where the increased rate for those in their 70s was statistically significant, and the social relation variables, where only satisfaction with friendships was statistically significant.
Cross-sectional association between physical activity and depression in 1994
When adjusted for age, gender, and ethnicity, 1994 physical activity was associated cross-sectionally with 1994 depression (table 2, columns 2 and 3). The relative likelihood of being depressed associated with a one-point increment in the physical activity scale was 0.75 (95 percent CI: 0.68, 0.84) in model 1. Subsequent adjustments reduced the relation, but even with all of the adjustments in model 4, the relation between physical activity and depression was still marginally significant (OR = 0.90, 95 percent CI: 0.79, 1.01).
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The right columns of table 2 present the relative risks and confidence intervals for incident depression in 1999 associated with 1994 physical activity scale after exclusion of an additional 151 subjects with prevalent 1994 disability. In all four models, physical activity remained protective for subsequent depression, and the exclusion of disabled subjects did not attenuate the observed protective effects (OR = 0.79, 95 percent CI: 0.67, 0.92).
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DISCUSSION |
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These results lend support to those other longitudinal studies that have previously reported a protective effect for physical activity against incident depression. Unlike the Rancho Bernardo findings (17), our study found a relatively strong longitudinal protective effect for physical activity that was not attenuated when physically disabled subjects were excluded. Physicians generally counsel physically disabled patients to avoid inactivity for fear that their condition will worsen. Because the prevalence of disability increases rapidly with age and because disability is strongly associated with depression, excluding older persons with disabilities would both render studies that excluded subjects less representative and possibly involve removing those who might benefit the most. Although we concur that physical disability represents a potentially powerful confounder, our recommendation is to continue including such subjects in research studies involving older persons but to ascertain their influence on the results by adjustment as we did in our first set of longitudinal analyses.
The measure of disability used in the analyses presented here involved difficulty in four lower-body tasks, whereas in the Rancho Bernardo Study, disability was defined as being largely or extremely physically limited during the previous month. The prevalence of disability in their study was 6.7 percent, whereas our measure yielded 9.8 percent. Other researchers might want to explore the issue of including or excluding disabled subjects by using other measures of dis-ability.
A variety of mechanisms have been proposed by which physical activity might reduce the incidence of depression, but research to date is not definitive (36). Two mechanisms often discussed include increased levels of two types of brain neurotransmitters after exercise: monoamines and endorphins (36, 37). The preventive aspects of physical activity for development of serious chronic conditions such as diabetes or heart disease could be important as well because of the strong link between physical health and depression in old age (38). Other plausible mechanisms include improved fitness and increased self-esteem as a result of greater physical activity (39).
Two additional mechanisms question adjusting for social relations and chronic conditions in analyses of physical activity and depression. Physically active older persons may interact more and form relations with those with whom they come into contact as a result of their physical activity. If this is true, social relations constitute an intervening variable between physical activity and depression rather than a confounder and should not be included as adjustment variables. Because of the strong linkage between physical activity and onset of chronic conditions, adjustment for chronic conditions could raise the same issue. We adjusted for both sets of variables in our analyses (models 3 and 4). Readers concerned about possible overadjustment should focus on our results for model 2.
Finally, although studies of the impact of physical activity on depression try to measure independent effects, it is plausible that persons with high levels of physical activity are also more likely to engage in other beneficial health behaviors such as not smoking, avoiding obesity, and not drinking to excess. The potential impact of one beneficial health behavior on adoption of others deserves further research.
Further research with representative community samples and more exact measures of physical activity is needed to definitively answer the question of how strong a protective effect physical activity has on the risk of subsequent depression and to clarify further the role of disability in any observed relation. If results continue to be positive, such findings would be the most helpful for practitioners advising patients about the benefits of physical activity for both somatic and psychologic well-being.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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