Diabetes is increasingly becoming a prevalent disease in developing countries such as India. This has raised great concern among public health practitioners, researchers and policy makers. The present study aims to examine the geographical variations in the prevalence of diabetes and its contextual risk factors including production and consumption of different food groups in the districts of India.
We used state- and district-level data from multiple sources. These include National Family Health Survey-4 (2015–2016), socio-economic data from the census of India (2011), per capita crop production from the Ministry of Agriculture and Farmers and consumption of different food groups from the 68th round of the National Sample Survey. The study adopted advanced spatial statistical analysis including the Moran index and spatial regression to fulfil the objectives of the article.
The study reveals the remarkable geographical variations in diabetes risk in the districts of India. Districts from the coastal area have more diabetes prevalence. Per capita calorie consumption, calorie intake from sugar and production of sugar crops in districts are significantly positively related to diabetes prevalence. On the other hand, protein intake and calorie consumption from pulses and nuts and milk and dairy products reduce the risk of diabetes.
The study recommends that public health programmes target hot-spot districts with high prevalence of diabetes and encourage people to increase consumption of protein-rich diets including pulses, nuts and milk products to reduce diabetes prevalence.
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This article used state/district-level data from multiple sources. State/district factsheets of National Family Health Survey-4 (2015–2016) can be downloaded from the website “http://rchiips.org/nfhs/”. Socio-economic indicators for all districts were compiled from http://www.censusindia.gov.in/2011-Common/CensusData2011.html (census of India, 2011). Furthermore, the article used per capita crop production from the website of the Ministry of Agriculture and Farmers (http://aps.dac.gov.in/APY/Public_Report1.aspx), and consumption of different food groups at the state-level was compiled from the National Sample Survey Office (NSS Report no. 560).
Agrawal S, Millett CJ, Dhillon PK, Subramanian SV, Ebrahim S (2014) Type of vegetarian diet, obesity and diabetes in adult Indian population. Nutr J 13(1):89. https://doi.org/10.1186/1475-2891-13-89
Akhtar SN, Dhillon P (2017) Prevalence of diagnosed diabetes and associated risk factors: evidence from the large-scale surveys in India. J Soc Health and Diabetes 5(1):28. https://doi.org/10.4103/2321-0656.194001
Alkerwi A, Bahi IE, Stranges S, Beissel J, Delagardelle C, Noppe S, Kandala NB (2017) Geographic variations in cardiometabolic risk factors in Luxembourg. Int J Environ Res Public Health 14:648. https://doi.org/10.3390/ijerph14060648
Anjana RM, Ali MK, Pradeepa R, Deepa M, Datta M, Unnikrishnan R, Rema M, Mohan V (2011) The need for obtaining accurate nationwide estimates of diabetes prevalence in India— rationale for a national study on diabetes. Indian J Med Res 133(4):369–380
Anjana RM, Deepa M, Pradeepa R, Mahanta J, Narain K, Das HK et al (2017) Prevalence of diabetes and prediabetes in 15 states of India: results from the ICMR–INDIAB population-based cross-sectional study. Lancet Diabetes Endocrinol 5:585–596. https://doi.org/10.1016/S2213-8587(17)30174-2
Anselin L (1988) Spatial econometrics: methods and models. Springer, Netherlands
Auchincloss AH, Gebreab SY, Mair C, Roux AVD (2012) A review of spatial methods in epidemiology, 2000–2010. Annu Rev Public Health 33:107–122. https://doi.org/10.1146/annurev-publhealth-031811-124655
Borah M, Goswami RK (2017) Sociodemographic and clinical characteristics of a diabetic population at a tertiary care center in Assam, India. Journal of Social Health and Diabetes 5(1):37. https://doi.org/10.4103/2321-0656.193997
Chow CK, Raju PK, Raju R, Reddy KS, Cardona M, Celermajer DS, Bruce C (2006) The prevalence and management of diabetes in rural India. Diabetes Care 29:1717–1718. https://doi.org/10.2337/dc06-0621
Dagogo-Jack S (2006) Primary prevention of type-2 diabetes in developing countries. J Natl Med Assoc 98:415–419
Diamond J (2003) The double puzzle of diabetes. Nature 423(6940):599–602
Food and Agriculture Organisation (2010). FAOSTAT Commodity list http://www.fao.org/economic/ess/ess-standards/commodity/comm-chapters/en/. Accessed 05 January, 2019
Gulati S, Misra A (2014) Sugar intake, obesity, and diabetes in India. Nutrients 6(12):5955–5974. https://doi.org/10.3390/nu6125955
International Diabetes Federation (2013) IDF Diabetes Atlas. In: 6th edition. https://idf.org/e-library/epidemiology-research/diabetes-atlas/19-atlas-6th-edition.html Accessed 05 January 2019
Jayawardena R, Ranasinghe P, Byrne NM, Soares MJ, Katulanda P, Hills AP (2012) Prevalence and trends of the diabetes epidemic in South Asia: a systematic review and meta-analysis. BMC Public Health 12:380
Joner G, Sovik O, Riise T (1998) Clustering of type one diabetes mellitus in Norway. Diabetologia 41(Suppl 1):A21–A75
King H, Aubert RE, Herman WH (1998) Global burden of diabetes, 1995-2025: prevalence, numericl estimates, and projections. Diabetes Care 21(9):1414–1431
Liu S, Manson JE, Stampfer MJ, Hu FB, Giovannucci E, Colditz GA et al (2000) A prospective study of whole-grain intake and risk of type 2 diabetes mellitus in US women. Am J Public Health 90(9):1409–1415
Malik VS, Popkin BM, Bray GA, Després JP, Willett WC, Hu FB (2010) Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care 33(11):2477–2483
Mattei J, Malik V, Wedick NM, Hu FB, Spiegelman D, Willett WC, Campos H (2015) Reducing the global burden of type 2 diabetes by improving the quality of staple foods: the global nutrition and epidemiologic transition initiative. Glob Health 11(1):23. https://doi.org/10.1186/s12992-015-0109-9
Ministry of Agriculture and Farmers Welfare, Govt. of India (2010) Crop production statistics information system 2010–11: District-wise crop production statistics, New Delhi. http://aps.dac.gov.in/APY/Public_Report1.aspx. Accessed on 06 August 2017
Mohan V, Sandeep S, Deepa R, Shah B, Varghese C (2007) Epidemiology of type 2 diabetes: Indian scenario. Indian J Med Res 125(3):217–230
National Sample Survey Organization (NSSO) (2014) Ministry of Statistics and Programme Implementation (MOSPI). Nutritional Intake in India 2011–12. Report No.560. New Delhi
Popkin BM, Horton S, Kim S, Mahal A, Shuigao J (2001) Trends in diet, nutritional status, and diet-related noncommunicable diseases in China and India: the economic costs of the nutrition transition. Nutrition Res 59(12):379–390
Prasad RB, Groop L (2015) Genetics of type 2 diabetes—pitfalls and possibilities. Genes 6(1):87–123. https://doi.org/10.3390/genes6010087
Ramachandran A, Snehalatha C, Kapur A, Vijay V, Mohan V, Das AK et al (2001) High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia 44(9):1094–1101
Samuelsson U, Johansson C, Carstensen J, Ludvigsson J (1994) Space-time clustering in insulin-dependent diabetes mellitus (IDDM) in south-East Sweden. Int J Epidemiol 23(1):138–142
Santos JL, Pérez-Bravo F, Carrasco E, Calvillán M, Albala C (2001) Low prevalence of type 2 diabetes despite a high average body mass index in the Aymara natives from Chile. Nutrition 17(4):305–309
Snowdon DA, Phillips RL (1985) Does a vegetarian diet reduce the occurrence of diabetes? Am J Public Health 75(5):507–512
Somannavar S, Ganesan A, Deepa M, Datta M, Mohan V (2009) Random capillary blood glucose cut points for diabetes and pre-diabetes derived from community-based opportunistic screening in India. Diabetes Care 32(4):641–643. https://doi.org/10.2337/dc08-0403
Tonstad S, Butler T, Yan R, Fraser GE (2009) Type of vegetarian diet, body weight, and prevalence of type 2 diabetes. Diabetes Care 32(5):791–796. https://doi.org/10.2337/dc08-1886
Turi KN, Toussaint DSG (2017) Spatial spillover and the socio-ecological determinants of diabetes-related mortality across US counties. Appl Geogr 85:62–72. https://doi.org/10.1016/j.apgeog.2017.05.005
Vos T, Barber RM, Bell B, Bertozzi-Villa A, Biryukov S, Bolliger I, Duan L (2015) Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the global burden of disease study 2013. Lancet 386(9995):743
World Health Organization (WHO) (2016) Global Report on Diabetes, Geneva http://apps.who.int/iris/bitstream/handle/10665/204871/9789241565257_eng.pdf;jsessionid=683202F3A1F12D05926016C769AB83A0?sequence=1. accessed 06 January 2019
This research received no specific grant from any funding agency, commercial entity or not-for-profit organisation. We thank the reviewers from the journal for giving their useful comments for the improvement of this article.
We declare that no competing interests exist.
Conflict of interests
The authors declare that they have no conflict of interest.
The authors assert that all procedures contributing to this work fulfil the ethical standards of the National Family Health Survey. The protocol for the NFHS-4 survey, including the content of all the survey questionnaires, was approved by the IIPS Institutional Review Board and the ICF Institutional Review Board. The protocol was also reviewed by the US Centers for Disease Control and Prevention (CDC).
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Ghosh, K., Dhillon, P. & Agrawal, G. Prevalence and detecting spatial clustering of diabetes at the district level in India. J Public Health (Berl.) 28, 535–545 (2020). https://doi.org/10.1007/s10389-019-01072-6
- Dietary groups