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Socioeconomic Disadvantage, Chronic Diseases and their Association with Cognitive Functioning of Adults in India: A Multilevel Analysis

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Abstract

Cognitive functioning is an important factor in determining overall well-being in adults. The research conducted in this area has mainly focused on dementia and gender differentials in cognitive ability. Using data from WHO’s Study on global AGEing and adult health (SAGE), this study examines the association of individual, household, contextual socioeconomic status, and chronic morbidities with cognitive abilities of younger (18-49) and older adults (50+) in India. Multilevel linear hierarchical model was used to examine this association. Results show that the years of schooling and household income were positively and significantly associated with cognitive abilities in younger and older adults. Community level socioeconomic status was positively associated with cognition in adults. Females had significantly lower cognitive abilities than male counterparts. Further, chronic morbidites and edentulism were negatively associated with cognition, especially the association of chronic morbidities was stronger in younger adults (β = −0.11; p < .001). Measures to prevent chronic health conditions and edentulism are mportant to improve the quality of aging in India.

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References

  • Abegunde, D. O., Mathers, C. D., Adam, T., Ortegon, M., & Strong, K. (2007). The burden and costs of chronic diseases in low-income and middle-income countries. The Lancet, 370(9603), 1929–1938.

    Google Scholar 

  • Aneshensel, C. S., Ko, M. J., Chodosh, J., & Wight, R. G. (2011). The urban neighborhood and cognitive functioning in late middle age. Journal of Health and Social Behavior, 52(2), 163–179.

    Google Scholar 

  • Arokiasamy, P. (2018). India’s escalating burden of non-communicable diseases. The Lancet Global Health, 6(12), e1262–e1263.

  • Arokiasamy, P., & Selvamani, Y. (2018). Age, socioeconomic patterns and regional variations in grip strength among older adults (50+) in India: Evidence from WHO’s study on global ageing and adult health (SAGE). Archives of Gerontology and Geriatrics, 76, 100–105.

    Google Scholar 

  • Arokiasamy, P., Uttamacharya, & Jain, K. (2015a). Multi-morbidity, functional limitations, and self-rated health among older adults in India: Cross-sectional analysis of LASI pilot survey, 2010. SAGE Open, 5(1), 2158244015571640.

    Google Scholar 

  • Arokiasamy, P., Uttamacharya, U., Jain, K., Biritwum, R. B., Yawson, A. E., Wu, F., Guo, Y., Maximova, T., Espinoza, B. M., Salinas Rodríguez, A., Afshar, S., Pati, S., Ice, G., Banerjee, S., Liebert, M. A., Snodgrass, J. J., Naidoo, N., Chatterji, S., & Kowal, P. (2015b). The impact of multimorbidity on adult physical and mental health in low-and middle-income countries: What does the study on global ageing and adult health (SAGE) reveal? BMC Medicine, 13(1), 178.

    Google Scholar 

  • Arokiasamy, P., Kowal, P., Capistrant, B. D., Gildner, T. E., Thiele, E., Biritwum, R. B., et al. (2017). Chronic noncommunicable diseases in 6 low-and middle-income countries: Findings from wave 1 of the World Health Organization's study on global ageing and adult health (SAGE). American Journal of Epidemiology, 185(6), 414–428.

    Google Scholar 

  • Banjare, P., & Pradhan, J. (2014). Socio-economic inequalities in the prevalence of multi-morbidity among the rural elderly in Bargarh District of Odisha (India). PLoS One, 9(6), e97832.

    Google Scholar 

  • Banjare, P., Dwivedi, R., & Pradhan, J. (2015). Factors associated with the life satisfaction amongst the rural elderly in Odisha, India. Health and Quality of Life Outcomes, 13(1), 201.

    Google Scholar 

  • Barnes, L. L., Cagney, K. A., & Mendes, D. L. C. F. (2008). Social resources and cognitive function in older persons. In S. M. Hofer & D. F. Alwin (Eds.), Handbook of cognitive aging: Interdisciplinary perspectives (pp. 603–613). Los Angeles: Sage.

    Google Scholar 

  • Basta, N. E., Matthews, F. E., Chatfield, M. D., Brayne, C., & MRC-CFAS. (2007). Community-level socio-economic status and cognitive and functional impairment in the older population. European Journal of Public Health, 18(1), 48–54.

    Google Scholar 

  • Chaix, B., Veugelers, P. J., Boëlle, P. Y., & Chauvin, P. (2005). Access to general practitioner services: The disabled elderly lag behind in underserved areas. The European Journal of Public Health, 15(3), 282–287.

    Google Scholar 

  • Conroy, R. M., Golden, J., Jeffares, I., O’Neill, D., & McGee, H. (2010). Boredom-proneness, loneliness, social engagement and depression and their association with cognitive function in older people: A population study. Psychology, Health & Medicine, 15(4), 463–473.

    Google Scholar 

  • Curry, A., Latkin, C., & Davey-Rothwell, M. (2008). Pathways to depression: The impact of neighborhood violent crime on inner-city residents in Baltimore, Maryland, USA. Social Science & Medicine, 67(1), 23–30.

    Google Scholar 

  • Ellaway, A., Macintyre, S., & Bonnefoy, X. (2005). Graffiti, greenery, and obesity in adults: Secondary analysis of European cross sectional survey. Bmj, 331(7517), 611–612.

    Google Scholar 

  • Emami, E. S., Raphael F., Kabawat, M., & Feine, J. S. (2013). The impact of edentulism on oral and general health. International Journal of Dentistry, 2013(2013), 498305.

  • Fabbri, E., An, Y., Zoli, M., Tanaka, T., Simonsick, E. M., Kitner-Triolo, M. H., & Ferrucci, L. (2016). Association between accelerated multimorbidity and age-related cognitive decline in older Baltimore longitudinal study of aging participants without dementia. Journal of the American Geriatrics Society, 64(5), 965–972.

    Google Scholar 

  • Glass, T. A., & Balfour, J. L. (2003). Neighborhoods, aging, and functional limitations. Neighborhoods and Health, 1, 303–334.

    Google Scholar 

  • Ingle, G. K., & Nath, A. (2008). Geriatric health in India: Concerns and solutions. Indian journal of community medicine: official publication of Indian Association of Preventive & Social Medicine, 33(4), 214–218.

    Google Scholar 

  • Jindai, K., Nielson, C. M., Vorderstrasse, B. A., & Quiñones, A. R. (2016). Multimorbidity and functional limitations among adults 65 or older, NHANES 2005–2012. Preventing Chronic Disease, 13.

  • Joshi, S., Mooney, S. J., Rundle, A. G., Quinn, J. W., Beard, J. R., & Cerdá, M. (2017). Pathways from neighborhood poverty to depression among older adults. Health & Place, 43, 138–143.

    Google Scholar 

  • Jotheeswaran, A. T., Williams, J. D., & Prince, M. J. (2010). The predictive validity of the 10/66 dementia diagnosis in Chennai, India–a three year follow-up study of cases identified at baseline. Alzheimer Disease and Associated Disorders, 24(3), 296–302.

    Google Scholar 

  • Kailembo, A., Preet, R., & Williams, J. S. (2017). Common risk factors and edentulism in adults, aged 50 years and over, in China, Ghana, India and South Africa: Results from the WHO study on global AGEing and adult health (SAGE). BMC Oral Health, 17(1), 29.

    Google Scholar 

  • Kastor, A., & Mohanty, S. K. (2016). Associated covariates of functional limitation among older adults in India: An exploration. Ageing International, 41(2), 178–192.

    Google Scholar 

  • Krall, E., Hayes, C., & Garcia, R. (1998). How dentition status and masticatory function affect nutrient intake. The Journal of the American Dental Association, 129(9), 1261–1269.

  • Kubo, K. Y., Ichihashi, Y., Kurata, C., Iinuma, M., Mori, D., Katayama, T., & TAMURA, Y. (2010). Masticatory function and cognitive function. Okajimas Folia Anatomica Japonica, 87(3), 135–140.

    Google Scholar 

  • Kumar, K., Shukla, A., Singh, A., Ram, F., & Kowal, P. (2016). Association between wealth and health among older adults in rural China and India. The Journal of the Economics of Ageing, 7, 43–52.

    Google Scholar 

  • Lee, J., Shih, R., Feeney, K., & Langa, K. M. (2014). Gender disparity in late-life cognitive functioning in India: Findings from the longitudinal aging study in India. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 69(4), 603–611.

    Google Scholar 

  • Lee, J. T., Hamid, F., Pati, S., Atun, R., & Millett, C. (2015a). Impact of noncommunicable disease multimorbidity on healthcare utilisation and out-of-pocket expenditures in middle-income countries: Cross sectional analysis. PLoS One, 10(7), e0127199.

    Google Scholar 

  • Lee, J., McGovern, M. E., Bloom, D. E., Arokiasamy, P., Risbud, A., O’Brien, J., Kale, V., & Hu, P. (2015b). Education, gender, and state-level disparities in the health of older Indians: Evidence from biomarker data. Economics and Human Biology, 19, 145–156.

    Google Scholar 

  • Li, J., Xu, H., Pan, W., & Wu, B. (2017). Association between tooth loss and cognitive decline: A 13-year longitudinal study of Chinese older adults. PLoS One, 12(2).

  • Lloyd-Sherlock, P., Agrawal, S., & Minicuci, N. (2016). Fear of crime and older people in low-and middle-income countries. Ageing and Society, 36(5), 1083–1108.

    Google Scholar 

  • Luo, J., Wu, B., Zhao, Q., Guo, Q., Meng, H., Yu, L., & Ding, D. (2015). Association between tooth loss and cognitive function among 3063 Chinese older adults: A community-based study. PLoS One, 10(3).

  • Maass, R., Kloeckner, C. A., Lindstrøm, B., & Lillefjell, M. (2016). The impact of neighborhood social capital on life satisfaction and self-rated health: A possible pathway for health promotion? Health & Place, 42, 120–128.

    Google Scholar 

  • Mini, G. K., & Thankappan, K. R. (2017). Pattern, correlates and implications of non-communicable disease multimorbidity among older adults in selected Indian states: A cross-sectional study. BMJ Open, 7(3), e013529.

    Google Scholar 

  • Mitoku, K., Masaki, N., Ogata, Y., & Okamoto, K. (2016). Vision and hearing impairments, cognitive impairment and mortality among long-term care recipients: A population-based cohort study. BMC Geriatrics, 16(1), 112.

    Google Scholar 

  • Mollaoglu, N., & Alpar, R. (2005). The effect of dental profile on daily functions of the elderly. Clinical Oral Investigations, 9(3), 137–140.

    Google Scholar 

  • Oksuzyan, A., Singh, P. K., Christensen, K., & Jasilionis, D. (2017). A cross-national study of the gender gap in health among older adults in India and China: Similarities and disparities. The Gerontologist, 58(6), 1156–1165

  • Onur, I., & Velamuri, M. (2016). A life course perspective on gender differences in cognitive functioning in India. Journal of Human Capital, 10(4), 520–563.

    Google Scholar 

  • Pati, S., Agrawal, S., Swain, S., Lee, J. T., Vellakkal, S., Hussain, M. A., & Millett, C. (2014). Non communicable disease multimorbidity and associated health care utilization and expenditures in India: Cross-sectional study. BMC Health Services Research, 14(1), 451.

    Google Scholar 

  • Pati, S., Swain, S., Hussain, M. A., Van Den Akker, M., Metsemakers, J., Knottnerus, J. A., & Salisbury, C. (2015). Prevalence and outcomes of multimorbidity in South Asia: a systematic review. BMJ Open, 5(10), e007235.

  • Remes, O., Wainwright, N., Surtees, P., Lafortune, L., Khaw, K. T., & Brayne, C. (2017). Sex differences in the association between area deprivation and generalised anxiety disorder: British population study. BMJ Open, 7(5), e013590.

    Google Scholar 

  • Rodriguez, J. J. L., Ferri, C. P., Acosta, D., Guerra, M., Huang, Y., Jacob, K. S., et al. (2008). Prevalence of dementia in Latin America, India, and China: A population-based cross-sectional survey. The Lancet, 372(9637), 464–474.

    Google Scholar 

  • Saito, S., Ohi, T., Murakami, T., Komiyama, T., Miyoshi, Y., Endo, K., et al. (2018). Association between tooth loss and cognitive impairment in community-dwelling older Japanese adults: A 4-year prospective cohort study from the Ohasama study. BMC Oral Health, 18(1), 142.

    Google Scholar 

  • Samal, S., Panigrahi, P., & Dutta, A. (2015). Social epidemiology of excess weight and central adiposity in older Indians: Analysis of study on global AGEing and adult health (SAGE). BMJ Open, 5(11), e008608.

    Google Scholar 

  • Santabárbara, J., Lopez-Anton, R., Marcos, G., De-la-Cámara, C., Lobo, E., Saz, P., et al. (2015). Degree of cognitive impairment and mortality: A 17-year follow-up in a community study. Epidemiology and Psychiatric Sciences, 24(6), 503–511.

    Google Scholar 

  • Schneeweis, N. E., Skirbekk, V., & Winter-Ebmer, R. (2012). Does schooling improve cognitive functioning at older ages? IZA DP, (6958).

  • Selvamani, Y., & Singh, P. (2018). Socioeconomic patterns of underweight and its association with self-rated health, cognition and quality of life among older adults in India. PLoS One, 13(3), e0193979.

    Google Scholar 

  • Singh, P., Govil, D., Kumar, V., & Kumar, J. (2017). Cognitive impairment and quality of life among elderly in India. Applied Research in Quality of Life, 12(4), 963–979.

    Google Scholar 

  • Sosa, A. L., Albanese, E., Stephan, B. C., Dewey, M., Acosta, D., Ferri, C. P., & Rodriguez, J. J. L. (2012). Prevalence, distribution, and impact of mild cognitive impairment in Latin America, China, and India: A 10/66 population-based study. PLoS Medicine, 9(2), e1001170.

    Google Scholar 

  • Srivastava, A., & Mohanty, S. K. (2012). Poverty among elderly in India. Social Indicators Research, 109(3), 493–514.

    Google Scholar 

  • United Nations (2017). World Population Ageing 2017. (ST/ESA/SER.A/397). New York, NY: Department of Economic and Social Affairs, Population Division. Available online at: https://www.un.org/en/development/desa/population/publications/pdf/ageing/WPA2017_Highlights.pdf.

  • Vassilaki, M., Aakre, J. A., Cha, R. H., Kremers, W. K., St. Sauver, J. L., Mielke, M. M., & Roberts, R. O. (2015). Multimorbidity and risk of mild cognitive impairment. Journal of the American Geriatrics Society, 63(9), 1783–1790.

  • Vellakkal, S., Subramanian, S. V., Millett, C., Basu, S., Stuckler, D., & Ebrahim, S. (2013). Socioeconomic inequalities in non-communicable diseases prevalence in India: Disparities between self-reported diagnoses and standardized measures. PLoS One, 8(7), e68219.

    Google Scholar 

  • Villeneuve, S., Belleville, S., Massoud, F., Bocti, C., & Gauthier, S. (2009). Impact of vascular risk factors and diseases on cognition in persons with mild cognitive impairment. Dementia and Geriatric Cognitive Disorders, 27(4), 375–381.

    Google Scholar 

  • Weir, D., Lay, M., & Langa, K. (2014). Economic development and gender inequality in cognition: A comparison of China and India, and of SAGE and the HRS sister studies. The Journal of the Economics of Ageing, 4, 114–125.

    Google Scholar 

  • Whitley, R., & Prince, M. (2005). Fear of crime, mobility and mental health in inner-city London, UK. Social science & medicine, 61(8), 1678–1688.

  • Wu, F., Guo, Y., Zheng, Y., Ma, W., Kowal, P., Chatterji, S., & Wang, L. (2016). Social-economic status and cognitive performance among Chinese aged 50 years and older. PLoS One, 11(11), e0166986.

    Google Scholar 

  • Yen, I. H., Michael, Y. L., & Perdue, L. (2009). Neighborhood environment in studies of health of older adults: A systematic review. American Journal of Preventive Medicine, 37(5), 455–463.

    Google Scholar 

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Table 4 Mean of cognition parameters by various background characteristics in 18–49 years age group
Table 5 Mean of cognition parameters by various background characteristics in 50+ years age group

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Kumar, H., Arokiasamy, P. & Selvamani, Y. Socioeconomic Disadvantage, Chronic Diseases and their Association with Cognitive Functioning of Adults in India: A Multilevel Analysis. Population Ageing 13, 285–303 (2020). https://doi.org/10.1007/s12062-019-09243-9

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