Lifestyle and socio-economic disparities in the prevalence of diabetes among the elderly population (aged 60+) in India: a decomposition analysis using longitudinal aging study in India data
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20233788Keywords:
Diabetes, Prevalence, Comorbidities, Healthy Ageing, ElderlyAbstract
Background: This study aimed to determine the prevalence of self-reported diabetes by sex and investigate the socio-economic, demographic, and lifestyle risk factors associated with diabetes. Additionally, it aimed to understand the coexistence of diabetes with other morbid conditions.
Methods: The study design used in this research is a cross-sectional study design. This study utilized data from the longitudinal aging study in India (LASI), a nationally representative survey of older adults. The sample included 15,098 males and 16,366 females aged 60 years and above.
Results: The prevalence of diabetes in India varies by state, zone, and rural/urban areas. Kerala has the highest prevalence among both men (33%) and women (28.5%). Urban areas have a higher prevalence (20%) compared to rural areas (8.5%). Hypertension and cancer are strongly associated with diabetes. Other morbid conditions like heart disease, high cholesterol, and vision problems also show significant links with diabetes.
Conclusions: Diabetes in India is a significant health concern, with variations across regions and associations with comorbidities like hypertension, cancer, heart disease, high cholesterol, and vision problems. To address this, comprehensive preventive measures and health promotion campaigns are needed, targeting high-risk groups and improving healthcare access. Early detection, effective management, and promoting healthy lifestyles are crucial for diabetes prevention and control in India.
Metrics
References
Goli S, Arokiasamy P. Demographic Transition in India: An Evolutionary Interpretation of Population and Health Trends Using ‘Change-Point Analysis.’ Schooling CM, editor. PLoS One. 2013;8(10):e76404.
Mason A, Lee SH, Park D. Demographic Change, Economic Growth, and Old-Age Economic Security: Asia and the World. Asian Development Review. 2022;39(01):131-67.
Medhi GK, Dutta G, Borah P, Lyngdoh M, Sarma A. Prevalence of Diabetes and Its Relationship With Body Mass Index Among Elderly People in a Rural Area of Northeastern State of India. Cureus. 2021;13:1.
Department of Economic and Social Affairs, Population Division. World population ageing, 2019 highlights. United Nations New York. 2019. Available at: https://digitallibrary.un.org/record/ 3846855?ln=en. Accessed on 09 September 2023.
Gu D, Andreev K, E. Dupre M, United Nations Population Division, New York, USA, Department of Population Health Sciences & Department of Sociology, Duke University, North Carolina, USA. Major Trends in Population Growth Around the World. China CDC Weekly. 2021;3(28):604-13.
Doddamani A, Ballala ABK, Madhyastha SP, Kamath A, Kulkarni MM. A cross-sectional study to identify the determinants of non-communicable diseases among fishermen in Southern India. BMC Public Health. 2021;21(1):414.
Kohler IV, Sudharsanan N, Bandawe C, Kohler HP. Aging and hypertension among the global poor—Panel data evidence from Malawi. Invitation PE, editor. PLOS Glob Public Health. 2022;2(6):e0000600.
Khan MAB, Hashim MJ, King JK, Govender RD, Mustafa H, Al Kaabi J. Epidemiology of Type 2 Diabetes – Global Burden of Disease and Forecasted Trends. JEGH. 2019;10(1):107.
Geldsetzer P, Manne-Goehler J, Theilmann M, Davies JI, Awasthi A, Vollmer S, et al. Diabetes and Hypertension in India: A Nationally Representative Study of 1.3 Million Adults. JAMA Intern Med. 2018;178(3):363.
Pradeepa R, Mohan V. Epidemiology of type 2 diabetes in India. Indian J Ophthalmol. 2021;69(11):2932.
Arokiasamy P. India’s escalating burden of non-communicable diseases. The Lancet Global Health. 2018;6(12):e1262-3.
Galicia-Garcia U, Benito-Vicente A, Jebari S, Larrea-Sebal A, Siddiqi H, Uribe KB, et al. Pathophysiology of Type 2 Diabetes Mellitus. IJMS. 2020;21(17):6275.
Budreviciute A, Damiati S, Sabir DK, Onder K, Schuller-Goetzburg P, Plakys G, et al. Management and Prevention Strategies for Non-communicable Diseases (NCDs) and Their Risk Factors. Front Public Health. 2020;8:574111.
Galaviz KI, Narayan KMV, Lobelo F, Weber MB. Lifestyle and the Prevention of Type 2 Diabetes: A Status Report. Am J Lifestyle Med. 2018;12(1):4-20.
Nolan CJ, Damm P, Prentki M. Type 2 diabetes across generations: from pathophysiology to prevention and management. The Lancet. 2011;378(9786):169-81.
Teo ZL, Tham YC, Yu M, Chee ML, Rim TH, Cheung N, et al. Global Prevalence of Diabetic Retinopathy and Projection of Burden through 2045. Ophthalmology. 2021;128(11):1580-91.
Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Research and Clinical Practice. 2019;157:107843.
Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Research and Clinical Practice. 2022;183:109119.
Liu J, Ren ZH, Qiang H, Wu J, Shen M, Zhang L, et al. Trends in the incidence of diabetes mellitus: results from the Global Burden of Disease Study 2017 and implications for diabetes mellitus prevention. BMC Public Health. 2020;20(1):1415.
Lin X, Xu Y, Pan X, Xu J, Ding Y, Sun X, et al. Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025. Sci Rep. 2020;10(1):14790.
Wu Y, Ding Y, Tanaka Y, Zhang W. Risk Factors Contributing to Type 2 Diabetes and Recent Advances in the Treatment and Prevention. Int J Med Sci. 2014;11(11):1185-200.
Hill-Briggs F, Adler NE, Berkowitz SA, Chin MH, Gary-Webb TL, Navas-Acien A, et al. Social Determinants of Health and Diabetes: A Scientific Review. Diabetes Care. 2021;44(1):258-79.
Bhagyalaxmi A, Atul T, Shikha J. Prevalence of Risk Factors of Non-communicable Diseases in a District of Gujarat, India. J Health Popul Nutr. 2013;31(1):78-85.
Zhang J, Xu L, Li J, Sun L, Qin W, Ding G, et al. Gender differences in the association between body mass index and health-related quality of life among adults:a cross-sectional study in Shandong, China. BMC Public Health. 2019;19(1):1021.
Teufel F, Seiglie JA, Geldsetzer P, Theilmann M, Marcus ME, Ebert C, et al. Body-mass index and diabetes risk in 57 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 685 616 adults. The Lancet. 2021;398(10296):238-48.
Bays HE, Chapman RH, Grandy S, SHIELD Investigators’ Group. The relationship of body mass index to diabetes mellitus, hypertension and dyslipidaemia: comparison of data from two national surveys. Int J Clin Pract. 2007;61(5):737-47.
Aggarwal H, Kaur H, Saklani R, Saba N, Choudhary S, Dogra S, et al. Prevalence of obesity and associated hypertension and diabetes in Delhi, metropolitan city of India. Indian J Med Specialities. 2015;6(3):82-7.
Hajar R. Risk factors for coronary artery disease: Historical perspectives. Heart Views. 2017;18(3):109.
Hruby A, Hu FB. The Epidemiology of Obesity: A Big Picture. PharmacoEconomics. 2015;33(7):673-89.
Yang J, Qian F, Chavarro JE, Ley SH, Tobias DK, Yeung E, et al. Modifiable risk factors and long term risk of type 2 diabetes among individuals with a history of gestational diabetes mellitus: prospective cohort study. BMJ. 2022;e070312.
Majumdar S, Gangopadhyay KK, Chowdhuri N, Majumder A, Ghoshdastidar B, Bhattacharjee K, et al. Barriers to Exercise in Type 2 DM Patients: An Institutional Cross-Sectional Descriptive Study. JDMC. 2019;1-6.
Quarti Machado Rosa M, dos Santos Rosa R, Correia M, Araujo D, Bahia L, Toscano C. Disease and Economic Burden of Hospitalizations Attributable to Diabetes Mellitus and Its Complications: A Nationwide Study in Brazil. IJERPH. 2018;15(2):294.
Booth FW, Roberts CK, Laye MJ. Lack of Exercise Is a Major Cause of Chronic Diseases. In: Terjung R, editor. Comprehensive Physiology. 1st ed. Wiley. 2012;1143-211.
Bavuma CM, Niyibizi JB, Bitunguhari L, Musafi S, McQuillan R, Wild S. Prevalence and characteristics associated with diabetes mellitus and impaired fasting glucose among people aged 15 to 64 years in rural and urban Rwanda: secondary data analysis of World Health Organization surveillance data. Pan Afr Med J. 2022;41.
Pandey AR, Aryal KK, Shrestha N, Sharma D, Maskey J, Dhimal M. Burden of Diabetes Mellitus in Nepal: An Analysis of Global Burden of Disease Study 2019. Cardoso C, editor. J Diabet Res. 2022;2022:1-15.
Hu FB. Globalization of Diabetes. Diabetes Care. 2011;34(6):1249-57.
Tabish SA. Is Diabetes Becoming the Biggest Epidemic of the Twenty-first Century? Int J Health Sci (Qassim). 2007;1(2):V-VIII.
World Health Organization. Global report on diabetes. Geneva: World Health Organization. 2016. Available at: https://apps.who.int/iris/handle/ 10665/204871. Accessed on 09 September 2023.
Longitudinal Ageing Study in India (LASI) | International Institute for Population Sciences (IIPS). Longitudinal Ageing Study in India (LASI) | International Institute for Population Sciences (IIPS). 2022. Available at: https://www.iipsindia.ac.in/lasi. Accessed on 09 September 2023.
Bloom DE, Sekher TV, Lee J. Longitudinal Aging Study in India (LASI): new data resources for addressing aging in India. Nat Aging. 2021;1(12):1070-2.
Perianayagam A, Bloom D, Lee J, Parasuraman S, Sekher TV, Mohanty SK, et al. Cohort Profile: The Longitudinal Ageing Study in India (LASI). Int J Epidemiol. 2022;51(4):e167-76.
Gateway to Global Aging Data. Gateway to Global Aging Data. 2023. Available at: https://g2aging.org/. Accessed on 09 September 2023.
O’Donnell O, O’Neill S, Van Ourti T, Walsh B. conindex: Estimation of concentration indices. Stata J. 2016;16(1):112-38.
Ataguba JE. A short note revisiting the concentration index: Does the normalization of the concentration index matter? Health Economics. 2022;31(7):1506-12.
Sudharsanan N, Bijlsma MJ. Educational note: causal decomposition of population health differences using Monte Carlo integration and the g-formula. Int J Epidemiol. 2022;50(6):2098-107.
Hwang J, Lee EY, Lee CG. Measuring Socioeconomic Inequalities in Obesity among Korean Adults, 1998–2015. IJERPH. 2019;16(9):1617.
Megari K. Quality of life in chronic disease patients. Health Psych Res. 2013;1(3):27.
Olanrewaju TO, Aderibigbe A, Popoola AA, Braimoh KT, Buhari MO, Adedoyin OT, et al. Prevalence of chronic kidney disease and risk factors in North-Central Nigeria: a population-based survey. BMC Nephrol. 2020;21(1):467.
Kapil U, Khandelwal R, Ramakrishnan L, Khenduja P, Gupta A, Pandey R, et al. Prevalence of hypertension, diabetes, and associated risk factors among geriatric population living in a high-altitude region of rural Uttarakhand, India. J Family Med Prim Care. 2018;7(6):1527.
Cohen AK, Nussbaum J, Weintraub MLR, Nichols CR, Yen IH. Association of Adult Depression With Educational Attainment, Aspirations, and Expectations. Prev Chronic Dis. 2020;17:E94.
Ramezankhani A, Azizi F, Hadaegh F. Associations of marital status with diabetes, hypertension, cardiovascular disease and all-cause mortality: A long term follow-up study. Shimosawa T, editor. PLoS One. 2019;14(4):e0215593.
Vlassoff C. Gender differences in determinants and consequences of health and illness. J Health Popul Nutr. 2007;25(1):47-61.
Anjana RM, Pradeepa R, Das AK, Deepa M, Bhansali A, Joshi SR, et al. Physical activity and inactivity patterns in India – results from the ICMR-INDIAB study (Phase-1) [ICMR-INDIAB-5]. Int J Behav Nutr Phys Act. 2014;11(1):26.
Kriska AM. Physical Activity, Obesity, and the Incidence of Type 2 Diabetes in a High-Risk Population. Am J Epidemiol. 2003;158(7):669-75.
Downloads
Published
How to Cite
Issue
Section
