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The impact of diabetes on the productivity and economy of Bangladesh

AIMS: To estimate the impact of type 2 diabetes in terms of mortality, years of life lost (YLL) and productivity-adjusted life years (PALY) lost in Bangladesh. METHODS: A life table model was constructed to estimate the productivity of the Bangladeshi population of current working age (20–59 years)...

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Detalles Bibliográficos
Autores principales: Afroz, Afsana, Hird, Thomas R, Zomer, Ella, Owen, Alice, Chen, Lei, Ademi, Zanfina, Liew, Danny, Magliano, Dianna J, Billah, Baki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295429/
https://www.ncbi.nlm.nih.gov/pubmed/32532757
http://dx.doi.org/10.1136/bmjgh-2020-002420
Descripción
Sumario:AIMS: To estimate the impact of type 2 diabetes in terms of mortality, years of life lost (YLL) and productivity-adjusted life years (PALY) lost in Bangladesh. METHODS: A life table model was constructed to estimate the productivity of the Bangladeshi population of current working age (20–59 years) with diabetes. Follow-up to 60 years (retirement age) was simulated. The life table analysis was then repeated assuming that the cohort did not have diabetes, with subsequent improvement in productivity. Differences in the results of the two analyses reflected the impact of diabetes on health and productivity. Demographic and the prevalence of diabetes data were sourced from the International Diabetes Foundation estimates for 2017 and mortality data were based on the 2017 Global Burden of Disease study. Relative risk and productivity indices were based on an Indian and Bangladeshi study, respectively. The cost of each PALY was assumed to be equivalent to gross domestic product (GDP) per equivalent full-time worker (US$8763). Future costs and years of life, and PALYs lived were discounted at an annual rate of 3%. RESULTS: Assuming a follow-up of this population (aged 20–59 years) until age 60 years or death, an estimated 813 807 excess deaths, loss of 4.0 million life years (5.5%) and 9.2 million PALYs (20.4%) were attributable to having diabetes. This was equivalent to 0.7 YLL, and 1.6 PALYs lost per person. The loss in PALYs equated to a total of US$97.4 billion lost (US$16 987 per person) in GDP. The results of the scenario analysis showed that the estimation was robust. CONCLUSION: In Bangladesh, the impact of diabetes on productivity loss and the broader economy looms large, and poses a substantial risk to the country’s future prosperity. This highlights the critical importance of health strategies aimed at the control of diabetes.