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Beyond METs: types of physical activity and depression among older adults SPRUHA JOSHI1, STEPHEN J. MOONEY2, GARY J. KENNEDY3,4, EBELE O. BENJAMIN5, DANIELLE OMPAD6, ANDREW G. RUNDLE2, JOHN R. BEARD7, MAGDALENA CERDÁ8 1

Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA Department of Epidemiology, Columbia University, New York, NY 10032, USA 3 Geriatric Psychiatry, Montefiore Medical Center, New York, NY, USA 4 Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, New York, NY, USA 5 Center for Evaluation and Applied Research, The New York Academy of Medicine, New York, NY, USA 6 NYU College of Global Public Health, New York, NY, USA 7 School of Public Health, University of Sydney, Australia 8 Department of Emergency Medicine, University of California, Davis, Sacramento, CA, USA 2

Address correspondence to: M. Cerdá. Tel: (+1) 916 734 3539. Email: [email protected]

Abstract Background/Objectives: physical activity may be beneficial in reducing depression incidence among the elderly. A key unanswered question is whether certain types of physical activity are particularly associated with decreased depression incidence. We examined the relationship between quantity and type of physical activity and subsequent depression using longitudinal data from elderly adults in New York City (NYC). 103

S. Joshi et al. Methods: we followed 3,497 adults aged 65–75 living in NYC for three years. Total physical activity was measured using the Physical Activity Scale for the Elderly (PASE) and type of physical activity was measured using a latent class analysis of PASE item responses. We used generalised estimating equations to measure the relationship between quantity and latent class of physical activity at waves 1–2 and depression at waves 2–3, controlling for wave-1 depression. Results: individuals in the second highest quartile (50–75%) (odds ratio (OR) = 0.45; 95% confidence interval (CI) = 0.23, 0.88) and highest quartile of activity (OR = 0.31; 95% CI = 0.16, 0.63) had lower odds of depression. Among all subjects, athletic types (OR = 0.25; 95% CI = 0.12, 0.51) and walker types (OR = 0.58; 95% CI = 0.34, 0.99) had lower odds of depression. Among non-disabled participants, walkers (OR = 0.36; 95% CI = 0.18, 0.73), athletic types (OR = 0.14; 95% CI = 0.06, 0.32), domestic/gardening types (OR = 0.29; 95% CI = 0.12, 0.73) and domestic/gardening athletic types (OR = 0.13; 95% CI = 0.02, 0.75) had lower odds of depression. Conclusion: respondents who practised the highest levels of physical activity and who performed athletic activities were at lower risk for depression. Interventions aimed at promoting athletic physical activity among older adults may generate benefits for mental health. Keywords: depression, physical activity, latent classes, older people

Introduction Depression is a common cause of morbidity and disability among older adults [1–3, 4]. The high prevalence of depression among older adults is particularly concerning due to its related consequences, which include cognitive decline, reduced overall quality of life and satisfaction, and suicide [5–7]. Physical activity may be beneficial in reducing depression and depressive symptoms, but studies have yielded mixed results [8–13]. A recent review examining the effectiveness of exercise as a treatment for adults with depression compared to those with no intervention found a moderate association between exercise and reduction of depressive symptoms [14]. The review focused on randomised control trials of athletic exercise among adults of all ages. However, different types of physical activity may have an impact on depression; some types of physical activity may be protective against depression while others may not provide any benefit. Few studies have compared the relationship between different types of physical activity, such as domestic-related and leisure-time activity, and depression [15], and fewer still have focused on older adults [15]. Understanding the contribution of specific types of physical activity on depression is important to develop appropriate public health recommendations. High correlation between types of physical activity (e.g. people who do domestic chores may also be more likely to garden) makes it challenging to compare specific benefits of each activity. Person-centred approaches such as latent class analysis (LCA) offer a promising tool to identify latent homogeneous subgroups engaged in distinct types of physical activity [16, 17]. LCA has been used to assess physical activity [18–20], but to our knowledge, no other study has examined the relationship between latent classes of physical activity and subsequent depression among older adults. We examined the independent contribution that quantity and type of physical activity have on subsequent depression using longitudinal data from the New York City Neighborhood and Mental Health in the Elderly Study II. We conducted a sensitivity analysis restricting the sample to

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the non-disabled in order to address potential confounding by physical limitation.

Methods Study participants

The New York City Neighborhood and Mental Health in the Elderly Study II is a 3-year longitudinal study of New York City (NYC) residents 65 to 75 years old at baseline, conducted from June 2011 to November 2013. Census tracts were divided into 16 strata, which represented varying degrees of racial-ethnic mix, household income, and walkability. Participants were sampled from a stratified geocoded telephone list from InfoUSA. In each participating household, interviewers asked how many people between 65 and 75 years of age lived in the household. In the case of two or more eligible household members, a computer-assisted telephone-interviewing programme randomly selected a household member based on age and sex, e.g. the oldest female in the household. Each telephone number in each neighbourhood had an equal probability of being selected. At baseline, there were 3,497 respondents. The response rate for Wave-1 was 17% and the cooperation rate was 30%. At wave-2, 2,455 were successfully re-interviewed (follow-up rate of 78%) and at wave-3 2,355 were successfully re-interviewed (follow-up rate of 67%). Respondents were offered $10 for participating. The study was approved by the Institutional Review Boards of Columbia University, New York Academy of Medicine, and Abt SRBI. Additional details regarding the methods are available in Appendix Text 1 in the supplementary data on the journal website (http://www.ageing.oxfordjournals.org/). Measures

Past month probable depression was measured using the Patient Health Questionnaire (PHQ-9), a 9-item symptom severity rating scale for depression [21]. The PHQ-9 has excellent internal consistency, test–retest reliability, and construct

Types of physical activity and depression validity [22]. The PHQ-9 has also produces similar results whether administered in person or on the telephone [23]. For analysis, baseline, wave 2, and wave 3 depression were dichotomised as probable depression (PHQ-9 score of 10 or higher) and no depression (PHQ-9 score of 9 and lower). Physical activity was measured at baseline using the Physical Activity Scale for the Elderly (PASE). The PASE is a 10-item instrument designed to assess physical activity levels in older adults [24]. It covers physical activity domains including, leisure time activities, housework, sports and recreational activities. Specifically, these include: walking, light recreational activities, moderate recreational activities, strenuous recreational activities, exercise specifically to increase muscle strength and endurance, light housework, heavy housework, home repairs, lawn work or yard care, outdoor gardening, and caring for another person. The PASE also includes an item assessing physical activity from employment, but it was excluded in this mostly retired sample; the majority of the participants (88.3%) reported they were either retired, unable to work, unemployed or a student; only 11.7% of the survey participants were employed. The total PASE score is calculated by the average number of hours per day over a one-week period spent on each activity multiplied by a specific weight for each activity. Higher scores indicate higher levels of physical activity. The PASE has been shown to be a reliable and valid measure of physical activity among older adults [25]. Latent class analysis was used to identify groups of subjects with homogeneous patterns of activity: specific details on the methods used to create these classes have been described elsewhere [26]. Model Fit statistics are available in Supplementary data, Appendix Table S1, available in Age and Ageing online. Five classes of physical activity were examined: least active class (little to no activity), walker class (walking only and a little housework), domestic/gardening class (gardening, lawn/yard work, and home repairs), athletic class (mainly sports and/or recreational activities), and domestic/gardening athletic class (sports and recreational activities and home-related activities). We also accounted for measures of demographic, psychosocial and physical health characteristics that are associated with physical activity and depression, including neuroticism, stressful life events, chronic health conditions, and disability [10, 11, 27]. Demographics variables included age, sex, race (Non-Hispanic White, Non-Hispanic Black, Hispanic, and Other) education (less than high school, high school/GED, some college, Bachelors or more) and household income (less than or equal to $20,000, more than $20,000 to $40,000, more than $40,000 to $80,000, and more than $80,000). Neuroticism was measured by the short neuroticism arm of the Eysenck Personality Questionnaire Brief Version, which has demonstrated high reliability (α: 78) and test–retest reliability (r: 0.92) [28]. Life stress events were measured with a seven-item survey asking respondents if they experienced various stressful events in the past 12 months (e.g. divorce/separation, serious illness in spouse or partner, major financial loss) [29]. Chronic conditions included the self-reported prevalence in the last 12 months (e.g. high blood pressure, stroke, heart problem, diabetes,

cancer). Disability was measured using the Basic Activity of Living section of the Functional Status Questionnaire (FSQ); respondents were classified into no disability (score: 0–87) and warning zones of disability (score: 88–100) [30]. Data analysis

Generalised estimating equations with a logit link function was used to estimate the odds of depression at waves-2 or 3 associated with physical activity at waves-1 or 2. Main analyses were conducted first among the total sample using the PASE score and second among the total sample using the latent classes of physical activity. Two sensitivity analyses were conducted: (1) restricting analyses to the non-disabled sample to address potential confounding due to disability; and (2) excluding participants with depression at wave 1, to address potential directionality issues. We estimated four models: (M1) covariates included physical activity, baseline depression levels (i.e. moderate/severe and mild, versus no depression), and demographic characteristics (i.e. age, sex, race, income and education); (M2) M1 + psychosocial covariates (i.e. neuroticism and life stress events); (M3): M2 + physical health covariates (i.e. disability and chronic health conditions); (M4) included all significant covariates. For analyses utilising the latent classes, models also controlled for the total PASE score. Multiple imputation was used to address missing data in the covariates, as implemented in IVEWARE [31, 32]. Rubin’s rules were used to compile findings across five imputed datasets [33]. Sample weights were created based on the 2006–2010 American Community Survey 5-Year Estimates to align the total sample to the population benchmarks for gender, race/ethnicity, education and geographic location. All analyses accounted for weights and clustering, and were conducted using SAS version 9.3 [34].

Results The respondents (n = 2,023) were representative of the 2010 U.S. Census population aged 65 to 75 in New York City after the use of sample weights (Supplementary data, Appendix Table S2, available in Age and Ageing online). Depressed individuals at wave 2 or wave 3 were more likely to be younger, female, have a lower household income, and education level than non-depressed individuals (Table 1). Depressed individuals were also more likely to be disabled, have a higher BMI, more chronic conditions, more life stress events, have higher levels of neuroticism, and lower levels of physical activity (Table 1). The association between overall physical activity, measured using quartiles of the total PASE score, and probable depression at wave 2 or 3 is shown in Table 2. In the final model, controlling for demographics, stressful life events, neuroticism, and number of chronic conditions, individuals in the second highest quartile (50–75%) (odds ratio (OR) = 0.45; 95% confidence interval (CI) = 0.23, 0.88) and highest quartile of activity (OR = 0.31; 95% CI = 0.16, 0.63) had lower odds of probable depression at wave 2 or 3 than individuals in the lowest quartile. Among the non-disabled subsample only the highest quartile of PASE remained significant (OR for highest quartile of PASE = 0.26; 95% CI = 0.10, 0.64).

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S. Joshi et al. Table 1. Selected characteristics by probable depression at wave 2 or wave 3 of NYCNAMES respondents Probable depression M (SE)

No probable depression M (SE)

152 (7.51) 70.05 (3.07)

1,871 (92.49) 70.16 (2.95)

P-value (χ 2/F)

.................................................................................... Age (n (%)) Gender Male Female Race Non-Hispanic White Non-Hispanic Black Hispanic Other Income Less than or equal to $20,000 More than $20,000 to $40,000 More than $40,000 to $80,000 More than $80,000 Education

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