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Socio-economic inequalities in diabetes and prediabetes among Bangladeshi adults

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Abstract

Diabetes and prediabetes are overwhelming public health concerns in Bangladesh. However, there is a paucity of the literature examining and measuring socioeconomic inequalities in the prevalence of diabetes in Bangladesh. To provide reliable data and contribute to a nationwide scenario analysis, this study aims to estimate the inequality in prevalence of diabetes and prediabetes and to identify factors potentially contributing to socioeconomic inequalities in Bangladesh. This study used data from the latest Bangladesh Demographic and Health Survey (BDHS) 2017–18, a nationally representative survey. A regression-based decomposition method was applied to assess the socioeconomic contributors to inequality. The prevalence of diabetes and prediabetes were about 10 and 15% among Bangladeshi adults, respectively. Both diabetes and prediabetes were significantly associated with age, wealth status, suffering from overweight or obesity and administrative divisions of the respondents (p < 0.001). Respondents’ household wealth status accounted for about 74 and 81% of the total inequality in diabetes and prediabetes in Bangladesh, respectively. Administrative region contributed 24.85% of the inequality in prediabetes and 12.26% of the inequality in diabetes. In addition, overweight or obesity status contributed 11.37% and exposure to television contributed 5.17% of the inequality in diabetes. Diabetes and prediabetes affect a substantial proportion of the Bangladeshi adult population. Therefore, these findings should be considered in the context of current and proposed policy decision making and for tracking its progression with economic development in Bangladesh.

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Data availability

The electronic datasets can be freely downloaded from the DHS’s website through the following link: https://dhsprogram.com/data.

References

  1. IDF. Diabetes atlas. Lancet. 2019. https://doi.org/10.1016/S0140-6736(55)92135-8.

    Article  Google Scholar 

  2. IDF. Diabetes in South-East Asia. In: The International Diabetes Federation-the prevalence of diabetes [Internet]. 2019 [cited 10 Mar 2020]. Available: https://idf.org/our-network/regions-members/south-east-asia/diabetes-in-sea.html. Accessed 3 June 2021.

  3. Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for diabetes development. Lancet. 2012;379:2279–90. https://doi.org/10.1016/S0140-6736(12)60283-9.

    Article  PubMed  PubMed Central  Google Scholar 

  4. ADA. Classification and diagnosis of diabetes: standards of medical care in diabetes. Diabetes Care. 2018;41:S13–27. https://doi.org/10.2337/dc18-S002.

    Article  Google Scholar 

  5. IHME. What causes the most death and disability combined? In: Measuring what matters- Bangladesh [Internet]. 2020 [cited 18 Mar 2021]. Available: http://www.healthdata.org/bangladesh. Accessed 13 May 2021.

  6. Bommer C, Heesemann E, Sagalova V, Manne-Goehler J, Atun R, Bärnighausen T, et al. The global economic burden of diabetes in adults aged 20–79 years: a cost-of-illness study. Lancet Diabetes Endocrinol. 2017. https://doi.org/10.1016/S2213-8587(17)30097-9.

    Article  PubMed  Google Scholar 

  7. Barua L, Faruque M, Chowdhury HA, Banik PC, Ali L. Health-related quality of life and its predictors among the type 2 diabetes population of Bangladesh: a nation-wide cross-sectional study. J Diabetes Investig. 2021. https://doi.org/10.1111/jdi.13331.

    Article  PubMed  Google Scholar 

  8. Rapoport M, Chetrit A, Cantrell D, Novikov I, Roth J, Dankner R. Years of potential life lost in pre-diabetes and diabetes mellitus: data from a 40-year follow-up of the Israel study on glucose intolerance, obesity and hypertension. BMJ Open Diabetes Res Care. 2021;9:1–8. https://doi.org/10.1136/bmjdrc-2020-001981.

    Article  Google Scholar 

  9. Sarker AR, Sultana M. Health and economic burden of diabetes in Bangladesh: priorities for attention and control. J Diabetes. 2017;12:1118–9. https://doi.org/10.1111/1753-0407.12587.

    Article  Google Scholar 

  10. Afroz A, Hird TR, Zomer E, Owen A, Chen L, Ademi Z, et al. The impact of diabetes on the productivity and economy of Bangladesh. BMJ Glob Heal. 2020;5:1–8. https://doi.org/10.1136/bmjgh-2020-002420.

    Article  Google Scholar 

  11. Akhtar S, Nasir JA, Sarwar A, Nasr N, Javed A, Majeed R, et al. Prevalence of diabetes and pre-diabetes in Bangladesh: a systematic review and meta-analysis. BMJ Open. 2020;10: e036086. https://doi.org/10.1136/bmjopen-2019-036086.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Dhaka Tribune. Over 8 million people have diabetes in Bangladesh. Tribune Health Desk. 13 Nov 2020. Available: https://www.dhakatribune.com/health/2020/11/13/over-8-million-people-have-diabetes-in-bangladesh. Accessed 12 July 2021.

  13. Islam SMS, Biswas T, Bhuiyan FA, Mustafa K, Islam A. Patients’ perspective of disease and medication adherence for type 2 diabetes in an urban area in Bangladesh: a qualitative study. BMC Res Notes. 2017;10:131. https://doi.org/10.1186/s13104-017-2454-7.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Akter S, Rahman MM, Abe SK, Sultana P. Prevalence of diabetes and prediabetes and their risk factors among Bangladeshi adults: a nationwide survey. Bull World Health Organ. 2014;92:204-213A. https://doi.org/10.2471/BLT.13.128371.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Ali N, Akram R, Sheikh N, Sarker ARAR, Sultana M. Sex-specific prevalence, inequality and associated predictors of hypertension, diabetes, and comorbidity among Bangladeshi adults: results from a nationwide cross-sectional demographic and health survey. BMJ Open. 2019. https://doi.org/10.1136/bmjopen-2019-029364.

    Article  PubMed  PubMed Central  Google Scholar 

  16. De Silva AP, De Silva SHP, Haniffa R, Liyanage IK, Jayasinghe S, Katulanda P, et al. Inequalities in the prevalence of diabetes mellitus and its risk factors in Sri Lanka: a lower middle income country. Int J Equity Health. 2018. https://doi.org/10.1186/s12939-018-0759-3.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Espelt A, Borrell C, Palència L, Goday A, Spadea T, Gnavi R, et al. Socioeconomic inequalities in the incidence and prevalence of type 2 diabetes mellitus in Europe. Gac Sanit. 2013. https://doi.org/10.1016/j.gaceta.2013.03.002.

    Article  PubMed  Google Scholar 

  18. Hosseinpoor AR, Bergen N, Kunst A, Harper S, Guthold R, Rekve D, et al. Socioeconomic inequalities in risk factors for non communicable diseases in low-income and middle-income countries: results from the world health survey. BMC Public Health. 2012. https://doi.org/10.1186/1471-2458-12-912.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Espelt A, Kunst AE, Palència L, Gnavi R, Borrell C. Twenty years of socio-economic inequalities in type 2 diabetes mellitus prevalence in Spain, 1987–2006. Eur J Public Health. 2012. https://doi.org/10.1093/eurpub/ckr158.

    Article  PubMed  Google Scholar 

  20. National Institute of Population Research and Training (NIPORT), and ICF. Bangladesh demographic and health survey 2017–18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF. 2020.

  21. Duc Son LENT, Kusama K, Hung NTK, Loan TTH, Van Chuyen N, Kunii D, et al. Prevalence and risk factors for diabetes in Ho Chi Minh City, Vietnam. Diabet Med. 2004. https://doi.org/10.1111/j.1464-5491.2004.01159.x.

    Article  PubMed  Google Scholar 

  22. Khambalia A, Phongsavan P, Smith BJ, Keke K, Dan L, Fitzhardinge A, et al. Prevalence and risk factors of diabetes and impaired fasting glucose in Nauru. BMC Public Health. 2011. https://doi.org/10.1186/1471-2458-11-719.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Unwin N, Shaw J, Zimmet P, Alberti K. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med. 2002;19:708–23.

    Article  CAS  Google Scholar 

  24. Rutstein SO, Johnson K. The DHS wealth index. DHS comparative reports No. 6. Calverton, Maryland, USA: ORC Macro, Maryland; 2004. Available: https://dhsprogram.com/pubs/pdf/cr6/cr6.pdf. Accessed 20 July 2021.

  25. WHO. Obesity and overweight. In: Facts about overweight and obesity [Internet]. 2021 [cited 20 Mar 2021]. Available: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight. Accessed 15 July 2021.

  26. Hasan MM, Tasnim F, Tariqujjaman M, Ahmed S. Socioeconomic inequalities of undiagnosed diabetes in a resource-poor setting: insights from the cross-sectional Bangladesh demographic and health survey 2011. Int J Environ Res Public Health. 2019;16:1–12. https://doi.org/10.3390/ijerph16010115.

    Article  Google Scholar 

  27. Sarker ARAR, Akram R, Ali N, Sultana M. Coverage and factors associated with full immunisation among children aged 12–59 months in Bangladesh: insights from the nationwide cross-sectional demographic and health survey. BMJ Open. 2019;9: e028020. https://doi.org/10.1136/bmjopen-2018-028020.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Kakwani NC. Income inequality and poverty: methods of estimation and policy applications. Popul Dev Rev. 1980. https://doi.org/10.2307/1972940.

    Article  Google Scholar 

  29. O’Donnell O, van Doorslaer E, Wagstaff A, Lindelow M, O’Donnell O, van Doorslaer E, et al. Analyzing health equity using household survey data. A guide to techniques and their implementation. Washington: The World Bank; 2008.

    Google Scholar 

  30. Shifti DM, Chojenta C, Holliday EG, Loxton D. Socioeconomic inequality in short birth interval in Ethiopia: a decomposition analysis. BMC Public Health. 2020;20:1–13. https://doi.org/10.1186/s12889-020-09537-0.

    Article  Google Scholar 

  31. Chandrupatla SG, Khalid I, Muthuluri T, Dantala S, Tavares M. Diabetes and prediabetes prevalence among young and middle-aged adults in India, with an analysis of geographic differences: findings from the National Family Health Survey. Epidemiol Health. 2021. https://doi.org/10.4178/epih.e2020065.

    Article  Google Scholar 

  32. Talukder A, Hossain MZ. Prevalence of diabetes mellitus and its associated factors in Bangladesh: application of two-level logistic regression model. Sci Rep. 2020;10:1–7. https://doi.org/10.1038/s41598-020-66084-9.

    Article  CAS  Google Scholar 

  33. Latif ZA, Jain A, Rahman MM. Evaluation of management, control, complications and psychosocial aspects of diabetics in Bangladesh: DiabCare Bangladesh 2008. Bangladesh Med Res Counc Bull. 2011. https://doi.org/10.3329/bmrcb.v37i1.7793.

    Article  PubMed  Google Scholar 

  34. Manne-Goehler J, Atun R, Stokes A, Goehler A, Houinato D, Houehanou C, et al. Diabetes diagnosis and care in sub-Saharan Africa: pooled analysis of individual data from 12 countries. Lancet Diabetes Endocrinol. 2016. https://doi.org/10.1016/S2213-8587(16)30181-4.

    Article  PubMed  Google Scholar 

  35. Jayawardena R, Ranasinghe P, Byrne NM, Soares MJ, Katulanda P, Hills AP. Prevalence and trends of the diabetes epidemic in South Asia: a systematic review and meta-analysis. BMC Public Health. 2012. https://doi.org/10.1186/1471-2458-12-380.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Tandon N, Anjana RM, Mohan V, Kaur T, Afshin A, Ong K, et al. The increasing burden of diabetes and variations among the states of India: the Global Burden of Disease Study 1990–2016. Lancet Glob Health. 2018. https://doi.org/10.1016/S2214-109X(18)30387-5.

    Article  Google Scholar 

  37. Feng L, Naheed A, De Silva HA, Jehan I, Raqib R, Islam MT, et al. Regional variation in comorbid prediabetes and diabetes and associated factors among hypertensive individuals in rural Bangladesh, Pakistan, and Sri Lanka. J Obes. 2019. https://doi.org/10.1155/2019/4914158.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Aung WP, Bjertness E, Htet AS, Stigum H, Kjøllesdal MKR. Trends in diabetes prevalence, awareness, treatment and control in Yangon region, Myanmar, between 2004 and 2014, two cross-sectional studies. Int J Environ Res Public Health. 2019. https://doi.org/10.3390/ijerph16183461.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Andrade FCD, López-Ortega M. The magnitude of health inequalities among older adults in Brazil and Mexico. In: Contextualizing health and aging in the Americas: effects of space, time and place. Springer; 2018. p. 181–98.

    Google Scholar 

  40. Mahumud RA, Sarker AR, Sultana M, Islam Z, Khan J, Morton A. Distribution and determinants of out-of-pocket healthcare expenditures in Bangladesh. J Prev Med Public Health. 2017;50:91–9. https://doi.org/10.3961/jpmph.16.089.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Khan JAM, Ahmed S, Maclennan M, Sarker AR, Sultana M, Rahman H. Benefit incidence analysis of healthcare in Bangladesh – equity matters for universal health coverage. Health Policy Plan. 2016;32:1–7. https://doi.org/10.1093/heapol/czw131.

    Article  Google Scholar 

  42. Espelt A, Borrell C, Roskam AJ, Rodríguez-Sanz M, Stirbu I, Dalmau-Bueno A, et al. Socioeconomic inequalities in diabetes mellitus across Europe at the beginning of the 21st century. Diabetologia. 2008. https://doi.org/10.1007/s00125-008-1146-1.

    Article  PubMed  Google Scholar 

  43. Al-Hanawi MK, Chirwa GC, Pulok MH. Socio-economic inequalities in diabetes prevalence in the Kingdom of Saudi Arabia. Int J Health Plan Manag. 2020. https://doi.org/10.1002/hpm.2899.

    Article  Google Scholar 

  44. Blakely T, Hales S, Kieft C, Wilson N, Woodward A. The global distribution of risk factors by poverty level. Bull World Health Organ. 2005;83:118–26.

    PubMed  PubMed Central  Google Scholar 

  45. Byron RK. Bangladesh gets UN recommendation for graduating from LDC status. The Daily Star. 27 Feb 2021. Available: https://www.thedailystar.net/business/news/bangladesh-gets-un-recommendation-graduating-ldc-status-2051857. Accessed 25 July 2021.

  46. Mutyambizi C, Booysen F, Stokes A, Pavlova M, Groot W. Lifestyle and socio-economic inequalities in diabetes prevalence in South Africa: a decomposition analysis. PLoS ONE. 2019. https://doi.org/10.1371/journal.pone.0211208.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Corsi DJ, Subramanian SV. Socioeconomic gradients and distribution of diabetes, hypertension, and obesity in India. JAMA Netw Open. 2019. https://doi.org/10.1001/jamanetworkopen.2019.0411.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Adekanmbi VT, Uthman OA, Erqou S, Echouffo-Tcheugui JB, Harhay MN, Harhay MO. Epidemiology of prediabetes and diabetes in Namibia, Africa: a multilevel analysis. J Diabetes. 2019. https://doi.org/10.1111/1753-0407.12829.

    Article  PubMed  Google Scholar 

  49. Mirhadyan L, Moradi L, Saeid P, Afsaneh K, Nejad LE. Junk food consumption and its associated factors in high school students in Rasht in 2017. J Res Dev Nurs Midwifery. 2020;17:52–66. https://doi.org/10.29252/jgbfnm.17.1.52.

    Article  Google Scholar 

  50. Yin H, Wu Q, Cui Y, Hao Y, Liu C, Li Y, et al. Socioeconomic status and prevalence of chronic non-communicable diseases in Chinese women: a structural equation modelling approach. BMJ Open. 2017. https://doi.org/10.1136/bmjopen-2016-014402.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Sarker AR, Sultana M, Sheikh N, Akram R, Ali N, Alam R, et al. Inequality of childhood undernutrition in Bangladesh: a decomposition approach. Int J Heal Plann Manag. 2019. https://doi.org/10.1002/hpm.2918.

    Article  Google Scholar 

  52. Hasan E, Khanam M, Shimul SN. Socio-economic inequalities in overweight and obesity among women of reproductive age in Bangladesh: a decomposition approach. BMC Womens Health. 2020;20:1–11. https://doi.org/10.1186/s12905-020-01135-x.

    Article  Google Scholar 

  53. Banik S, Rahman M. Prevalence of overweight and obesity in Bangladesh: a systematic review of the literature. Curr Obes Rep. 2018. https://doi.org/10.1007/s13679-018-0323-x.

    Article  PubMed  Google Scholar 

  54. Chowdhury MAB, Adnan MM, Hassan MZ. Trends, prevalence and risk factors of overweight and obesity among women of reproductive age in Bangladesh: a pooled analysis of five national cross-sectional surveys. BMJ Open. 2018. https://doi.org/10.1136/bmjopen-2017-018468.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Ghose B. Frequency of TV viewing and prevalence of overweight and obesity among adult women in Bangladesh: a cross-sectional study. BMJ Open. 2017. https://doi.org/10.1136/bmjopen-2016-014399.

    Article  PubMed  PubMed Central  Google Scholar 

  56. ADA. Physical activity/exercise and diabetes. Diabetes Care. 2004;27:S73–7.

    Google Scholar 

  57. Pulok MH, Uddin J, Enemark U, Hossin MZ. Socioeconomic inequality in maternal healthcare: an analysis of regional variation in Bangladesh. Health Place. 2018. https://doi.org/10.1016/j.healthplace.2018.06.004.

    Article  PubMed  Google Scholar 

  58. Sarker AR, Sheikh N, Mahumud RA, Sultana M. Determinants of adolescent maternal healthcare utilization in Bangladesh. Public Health. 2018;157:94–103. https://doi.org/10.1016/j.puhe.2018.01.010.

    Article  CAS  PubMed  Google Scholar 

  59. Vakharia JD, Agrawal S, Molino J, Topor LS. Family history of diabetes is associated with increased risk of recurrent diabetic ketoacidosis in pediatric patients. Endocr Pract. 2020. https://doi.org/10.4158/ep-2019-0351.

    Article  PubMed  Google Scholar 

  60. Molla GJ, Ismail-Beigi F, Larijani B, Khaloo P, Moosaie F, Alemi H, et al. Smoking and diabetes control in adults with type 1 and type 2 diabetes: a nationwide study from the 2018 National Program for Prevention and Control of Diabetes of Iran. Can J Diabetes. 2020. https://doi.org/10.1016/j.jcjd.2019.07.002.

    Article  PubMed  Google Scholar 

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ARS conducted the design of the study, interpretation of data, and writing of the initial manuscript. ARS and MK contributed to the statistical analysis plan and wrote the statistical methods section. ARS and MK reviewed the manuscript. ARS is the guarantor of this paper. All authors reviewed, contributed to, and approved the manuscript.

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Correspondence to Abdur Razzaque Sarker.

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This study did not require ethical approval as it used unidentifiable secondary DHS dataset. According to the DHS, written informed consent was obtained from mothers/caretakers on behalf of the children enrolled in the survey. The DHS data are publicly accessible and were made available to us upon request by Measure DHS. No identifiable information was included in the dataset and no attempt was made to identify any individual interviewed in the survey.

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Sarker, A.R., Khanam, M. Socio-economic inequalities in diabetes and prediabetes among Bangladeshi adults. Diabetol Int 13, 421–435 (2022). https://doi.org/10.1007/s13340-021-00556-9

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