Physical activity, functional abilities, and health: Results of a WHO SAGE sub-study among older adults in an urban setting in India. Tyler M. Barrett1, Melissa A. Liebert1, Tara J. Cepon-Robins1, Arvind Mathur2, Paul Kowal3,4, and J. Josh Snodgrass1 1Department of Anthropology, University of Oregon, USA; 2Dr SN Medical College, Jodhpur, India; 3World Health Organization (WHO), Geneva, Switzerland; 4University of Newcastle Research Centre for Gender, Health and Ageing, Australia. Introduction Recent research in wealthy nations suggests that decreased physical activity in old age is detrimental to health, yet few studies have examined the relationships among physical activity, functional abilities, and health among older adults in developing nations. Therefore, understanding cross-cultural variation in physical activity patterns among aging populations is central to interpreting known links between sedentary behavior and chronic health conditions such as obesity and cardiovascular disease. Further, little is known about patterns of functional decline among aging populations in developing nations. While recent research has demonstrated a link between greater levels of physical activity and the reduction of physical disability among older adults in wealthy nations, little is known about this relationship in developing nations (Pahor et al., 2014). Preserving functional ability is therefore an integral aspect of ensuring quality of life among older adults, especially in low and middle-income countries that lack infrastructure and resources for aging populations. In order to gain a comprehensive understanding of these associations, a method for objectively measuring physical activity is necessary. Recent technological advances in accelerometry allow for the collection of reliable data on physical activity variation at the population level. Methods Accelerometry: Participants wore ActiGraph GT3X accelerometers at the hip (~1 cm from the iliac crest) for 7 consecutive days; data were recorded for all three axes at 60 second epochs (Figure 3a). Data Processing: Raw data were downloaded using ActiLife software (Figure 3b) and processed by two analysts to determine periods of inactivity. Table 1. Partial correlations (controlling for age) between activity measures and function measures among women. Correlations are statistically significant at *p ≤ 0.001; **p ≤ 0.01; ***p ≤ 0.05. Table 2. Partial correlations (controlling for age) between activity measures and function measures among men. Figure 3. (a) Actigraph accelerometer with demonstration of placement; (b) Graphic preview of daily activity counts recorded with the Actigraph accelerometer. Methods Continued Accelerometry Variables: Total Daily Energy Expenditure (TDEE) was estimated and Physical Activity Level (PAL) calculated based on TDEE/Basal Metabolic Rate (BMR; based on the Oxford equations, Henry, 2005). Daily Average Activity Counts (AC) were measured based on the frequency and intensity of acceleration events that occurred during each epoch; Activity Energy Expenditure (AEE) was determined using a combination of Freedson and Work Energy Theorem equations. Tests of Physical Function: Grip Strength was measured twice for both hands using a dynometer (grip strength/body mass). A four meter Timed Walk on a flat, straight surface was recorded by an interviewer. Daily Average Sit Time and Average Sleep Time were measured with self-report data. Self-Report Health Conditions: A short face-to-face interview provided information regarding diagnosed health conditions including diabetes, hypertension, arthritis, and depression. Statistical Analysis: T-tests and partial correlations (controlling for age) were performed using SPSS 21.0; all analyses used log10-transformed data. Objectives The present study was conducted among older adults in an urban setting in India with the following three objectives: Objective One: Evaluate links among measures of physical activity and self-report health conditions. Objective Two: Investigate links among measures of physical activity and measures of physical function. STUDY ON GLOBAL AGEING AND ADULT HEALTH (SAGE) PROJECT The present study was a sub-study of the World Health Organization’s Study on Global Ageing and Adult Health (SAGE). SAGE is a longitudinal, multi-country project designed to gather information on the health of adult populations and the aging process from nationally representative samples in six countries (China, Ghana, India, Mexico, Russian Federation, and South Africa). Correlations are statistically significant at *p ≤ 0.001; **p ≤ 0.01; ***p ≤ 0.05. Discussion This study documented a relationship between higher levels of physical activity and better health (i.e. lower rates of hypertension) as well as a relationship between higher levels of physical activity and greater functional ability among women. The lack of significant associations among men may be due to a limited sample size, but it also indicates the need for a more comprehensive approach to understanding functional decline and health among older men in developing nations. However, significant findings among women further support the use of physical activity intervention as a means for prolonging functional abilities and reducing chronic disease burden in older ages. Aging is not a phenomenon unique to wealthy nations; it is universal. This study contributes to a cross-cultural understanding of the aging process. STUDY POPULATION This SAGE sub-study (Figure 1) was a face-to-face household interview among urban adults in Jodhpur, Rajasthan, India (Figure 2). Data were collected in 2010 from 200 adults (72 men, 128 women) aged 49-90 years old. 113 participants (33 men, 80 women) were young older adults (49-60 years old); 87 (39 men, 48 women) were considered old older adults (>60 years old). Two participants were excluded due to corrupt data files. Key Findings Continued Objective One (Physical Activity & Self-Report Health Conditions): Women diagnosed with hypertension had significantly lower PAL (p<0.05) and AC (p<0.05) than women without hypertension. Physical activity was not significantly associated with self-report health conditions among men. Objective Two (Physical Activity & Physical Function): Among women, there was a significant negative correlation between PAL and walking speed (p<0.05), a significant positive correlation between AC and grip strength (p<0.01), and a significant negative correlation between TDEE and grip strength (p<0.01) (Table 1). Among men, there was also a significant negative correlation between TDEE and grip strength (p<0.001) but no other significant associations (Table 2). Since TDEE and grip strength are closely related to body size, the negative associations between the two variables among both men and women may be a result of body size signals interfering with the analysis. Acknowledgements We thank study participants as well as Paul Kowal and Somnath Chatterji for overseeing the SAGE project, Sunit Mathur for organizing the accelerometry study, and Alex Halmi for his assistance with data analysis. Support: WHO, NIH. Jodhpur References Henry CJK. 2005. Basal metabolic rate studies in humans: Measurement and development of new equations. Pub Health Nutr 8: 1133. Pahor M. et al. 2014. Effect of structured physical activity on prevention of major mobility disability in older adults: The LIFE Study Randomized Clinical Trial. The Journal of the American Medical Association doi: 10.1001/jama.2014.5616. Figure 2. Map of India, showing study location. (http://en.wikipedia.org/wiki/File:India Rajasthan locator map.svg) Figure 1. SAGE team members in India.