WHO South-East Asia Journal of Public Health
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Year : 2013  |  Volume : 2  |  Issue : 3  |  Page : 156-164

Effects of education and income on cognitive functioning among Indians aged 50 years and older: evidence from the Study on Global Ageing and Adult Health (SAGE) Wave 1 (2007-2010)

Department of Internal Medicine, Scott & White Healthcare/Texas A&M Health Science Center College of Medicine, Temple TX, United States of America

Correspondence Address:
Rashmita Basu
Assistant Professor, Department of Internal Medicine, Scott&White Healthcare, Texas A&M University Health Science Center College of Medicine, 2401 South 31st Street, 501 Brindley Circles (#540), Temple, Texas 76508
United States of America
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2224-3151.206762

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Objectives: Relatively little is known about socioeconomic predictors of cognitive health among middle-aged and elderly Indians. The primary objective of this study was to examine the extent to which education and income influence cognitive functioning after adjusting for demographic characteristics, health risk factors and transgenerational factors such as parental education. The study also examined gender disparities in cognitive functioning across geographic regions in India. Methods: Using cross-sectional data from the World Health Organization Study on Global Ageing and Adult Health (SAGE) Wave 1 (2007–2010) in a national sample of adults aged 50 years or older, a generalized linear model was used to examine the impacts of education and per-capita income on overall cognitive functioning. The generalized estimating equation approach was utilized to quantify these impacts on respondents’ overall cognitive performance score. This technique accounted for any correlation of responses of individuals within the same household. Results: Respondents with primary or secondary education and those with education above secondary level scored 3.8 and 6 points (P < 0.001) respectively more than respondents who had no formal education. In a similar vein, individuals in higher per-capita income quartiles scored 0.4,1.0 and 1.8 (P < 0.001) more than respondents in the lowest income quartile. Although respondents in northern states scored 1.8 points higher than those from other geographic locations (P < 0.001), females in northern states had the worst cognitive performance (1.9 points lower) compared with females in other Indian states. In addition, early and adult life characteristics such as parental education, physical activity and a history of depression were found to be significant predictors of overall cognitive functioning. Conclusion: Education and income play important roles in influencing overall cognitive performance among middle-aged and elderly Indians. In addition, cognitive performance scores varied across geographic regions, and female disadvantage was observed in northern Indian states. Policies directed towards greater educational opportunities, particularly for women in northern Indian states, or promotion of physical activity programmes, have potential to improve cognitive performance and enhance cognitive health among middle-aged and older adults in India.

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