Is employment status cross-culturally associated with cognitive function among older adults: Results from the Study on global AGEing and adult health.

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Is employment status cross-culturally associated with cognitive function among older adults: Results from the Study on global AGEing and adult health (SAGE) Theresa E. Gildner1, Melissa A. Liebert1, Paul Kowal2,3, and J. Josh Snodgrass1 1Department of Anthropology, University of Oregon, Eugene, OR; 2World Health Organization, Geneva, Switzerland; 3University of Newcastle Research Centre for Gender, Health and Ageing, Newcastle, NSW, Australia Introduction The global population is currently experiencing a rapid transition characterized by an increased proportion of older adults (UN Population Division, 2013). At the same time, individuals in many countries are retiring at earlier ages (Bonsang et al., 2012); yet, the ability to perform daily activities during this period of life may be compromised by age-related declines in mental and physical faculties. Retirement is traditionally thought to increase leisure time and reduce stress, thus improving health (Ekerdt et al., 1983). However, ceasing work at an earlier age may also decrease daily social and mental stimulation in older adults (Salthouse, 2006). Previous research in high-income nations indicates that the loss of work-related problem-solving tasks and social interactions may exacerbate cognitive decline in retired individuals (Börsch-Supan & Schuth, 2013; Dave et al., 2006). Still, this relationship appears to vary by sex (Bound and Waidmann, 2007), and it is unclear whether this relationship is present in lower income countries. Discussion The present study found mixed support for the hypothesis: As expected, individuals who had never worked for wages mostly exhibited significantly lower cognitive performance scores compared to currently employed older adults (in both sexes). Similarly, participants who were currently not working generally displayed significantly lower cognitive function scores (in both sexes); however, the opposite pattern was observed in Chinese men and women. Interestingly, these significant patterns were most apparent in Russia and South Africa, perhaps due to earlier ages of retirement or less social engagement among retirees in these populations. Still, adding employment status to the models explained a very small amount of additional variance in cognitive function. Retirement may therefore have less impact on mental decline in these populations compared to higher income nations. Still, further biocultural work is needed to test these associations in diverse settings and at different levels of economic development. Thus, although the effects of employment status on cognitive performance are modest, the uniform nature of these results suggest that the mental and social stimulation associated with working may slow cognitive decline in older adults. Figure 2. SAGE participants in India at work Key Findings: Men In China, India, Russia, and South Africa participants who had never worked for wages exhibited significantly lower cognitive performance scores compared to currently employed individuals (p < 0.01) (Table 1). In Russia and South Africa participants who were not currently employed exhibited significantly lower cognitive performance scores compared to currently employed individuals (p < 0.001). Conversely, currently unemployed individuals in China displayed significantly higher cognitive function scores than currently employed participants (p = 0.033) (Table 1). Hypothesis This study focused on older adults and tested the following hypothesis: In both sexes, current employment will be positively associated with cognitive function. Study on global AGEing and adult health (SAGE) participants Data were drawn from the first wave of the World Health Organization’s SAGE project. SAGE is a longitudinal study of nationally-representative samples of older adults (>50 years old) in six middle-income countries (China, Ghana, India, Mexico, Russian Federation, and South Africa) (Fig. 1). A household questionnaire administered to participants was used to obtain measures of current employment status (n = 33,353; Fig 2) and cognitive function (n = 31,813). Table 2. Linear regression assessing if current employment status significantly predicts composite cognitive performance score in women, by country; “currently employed” served as the reference group in each comparison. The number of asterisks indicates the level of significance of the final model (*= p < 0.05, **= p < 0.01, ***= p < 0.001). Key Findings: Women   R2 Change Employment Dummy Codes B (S.E.) p-value China (n=6,416)*** 0.007 Never worked for wages -0.657 (0.114) < 0.001 Not currently employed 0.232 (0.090) = 0.010 Ghana (n=1,822)** 0.005 -0.277 (0.531) 0.602 -0.508 (0.141) India (n=3,027)*** 0.003 -0.355 (0.109) = 0.001 -0.049 (0.121) 0.686 Mexico (n=1,202)* 0.004 -0.488 (0.220) 0.027 -0.200 (0.244) 0.413 Russia (n=2,006)*** 0.013 -1.031 (0.600) 0.086 -1.056 (0.165) South Africa (n=1,653)*** 0.020 -1.516 (0.242) -0.424 (0.193) 0.028 In China, India, Mexico, and South Africa participants who had never worked for wages demonstrated significantly lower cognitive performance scores compared to currently employed individuals (p < 0.05) (Table 2). In Ghana, Russia, and South Africa participants who were not currently employed exhibited significantly lower cognitive performance scores compared to currently employed individuals (p < 0.05). Similar to the men, currently unemployed Chinese women displayed significantly higher cognitive function scores than currently employed participants (p = 0.010) (Table 2). Table 1. Linear regression assessing if current employment status significantly predicts composite cognitive performance score in men, by country; “currently employed” served as the reference group in each comparison. The number of asterisks indicates the level of significance of the final model (*= p < 0.05, **= p < 0.01, ***= p < 0.001). Figure 1. Map of six SAGE countries, showing study locations. http://www.who.int/healthinfo/systems/sage/en/ Acknowledgments We thank Nirmala Naidoo for her efforts in data analysis. Support for the research was provided by NIH NIA Interagency Agreement YA1323-08-CN-0020; NIH R01-AG034479.   R2 Change Employment Dummy Codes B (S.E.) p-value China (n=5,496)*** 0.009 Never worked for wages -1.054 (0.150) < 0.001 Not currently employed 0.206 (0.097) 0.033 Ghana (n=2,040) 0.002 0.286 (0.510) 0.576 -0.285 (0.152) 0.061 India (n=3,147)* -0.614 (0.221) 0.006 -0.134 (0.099) 0.174 Mexico (n=775) 0.001 -0.102 (0.255) 0.690 0.204 (0.222) 0.359 Russia (n=1,103)*** -1.881 (0.526) -0.839 (0.222) South Africa (n=1,056)*** 0.019 -1.940 (0.394) -0.784 (0.208) Methods Employment Variables: Participants reported whether they had ever worked for wages, and if so, whether they had worked at least two days during the previous week (measure of current employment). This variable was dummy coded using “currently employed” as the reference group. Cognitive Variables: Five cognitive performance tests were used to create a summary z-score of cognitive function for each participant: immediate and delayed verbal recall, forward and backward digit span, and verbal fluency. Higher z-scores corresponded to higher cognitive function. Statistics: Linear regressions were used to examine the relationship between cognitive function and employment status by sex and country while controlling for age, education level, level of social engagement (martial status and self-reported difficulty maintaining personal relationships), and activities and health conditions known to affect mental acuity (BMI, physical activity level, drinking and smoking frequency, angina, stroke, depression). References Bonsang, E., Adam, S., & Perelman, S. (2012). Does retirement affect cognitive functioning?. Journal of health economics, 31(3), 490-501. Börsch-Supan, A., & Schuth, M. (2013). 29 Early retirement, mental health and social networks. Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis, 337. Bound, J., & Waidmann, T. (2007). Estimating the health effects of retirement. Michigan Retirement Research Center Research Paper No. UM WP, 168. Ekerdt, D. J., Bosse, R., & LoCastro, J. S. (1983). Claims that retirement improves health. Journal of Gerontology, 38(2), 231-236. Dave, D., Rashad, I., & Spasojevic, J. (2006). The effects of retirement on physical and mental health outcomes (No. w12123). National Bureau of Economic Research. Salthouse, T. A. (2006). Mental exercise and mental aging evaluating the validity of the “use it or lose it” hypothesis. Perspectives on Psychological Science, 1(1), 68-87. United Nations Population Division. World Population Prospects: The 2012 Revision. New York: United Nations. 2013.