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. 2025 Jun 16;23(1):26.
doi: 10.1186/s12963-025-00372-2.

The role of education composition in shaping the burden of obesity and diabetes in Indonesia: a microsimulation-based projection study

Lilipramawanty K Liwin  1   2 , Tianyu Shen  2   3 , Collin F Payne  4   5   6
Affiliations

The role of education composition in shaping the burden of obesity and diabetes in Indonesia: a microsimulation-based projection study

Lilipramawanty K Liwin et al. Popul Health Metr. .

Abstract

Background: Diabetes prevalence is increasing worldwide, particularly in developing countries and disadvantaged groups. Alongside this phenomenon, the expansion of educational attainment has led to changes in population educational composition, which can significantly influence social disparities in diabetes and its risk factors, including obesity. This paper explores the role of changing educational composition in shaping the future burden of excess body weight and diabetes in Indonesia, a country with a rapidly growing prevalence of both diabetes and obesity.

Methods: We utilise three data sources as the inputs for our projection model. Panel data from the Indonesia Family Life Survey (IFLS) for 2007 and 2014 were used to compute health transition probabilities by age, sex, and education status using a multinomial logit model. Results from a dried blood test were used to adjust for undiagnosed diabetes in the projection model. The Indonesian National Health Surveys (Riskesdas) in 2007, 2013, and 2018 were used to estimate the prevalence of excess body weight and diabetes by age, sex, and education. Finally, we used projections of Indonesia's population size and composition by age, sex and education level for the period 2010 to 2060 from the Wittgenstein Centre Human Capital Data Explorer version WIC2018 v2. We employ a cohort component model with microsimulation to project the population forward.

Results: The estimated prevalence of diabetes from our projection model incorporating population education composition is 7.8% in 2010 and is expected to reach 16.7% by 2060. The most rapid increase in prevalence (14% growth in 50 years) is estimated among people with primary education, while other groups show smaller rises.

Conclusion: Incorporating population educational composition into projections of the burden of excess body weight and diabetes provides valuable insights into social disparities in diabetes over time. This can inform policy decisions by helping to prioritise healthcare budgets, targeted disease prevention programs, and diabetes treatment for high-risk groups based on educational status.

Keywords: Diabetes; Education; Obesity; Projection.

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Conflict of interest statement

Declarations. Ethical approval: The Indonesian Family Life Surveys were reviewed and approved by Institutional Review Boards (IRBs) in the United States at RAND and in Indonesia by University of Indonesia for waves 1 and 2, and University of Gadjah Mada for waves 3 to 5. Written informed consent was obtained from all respondents prior to data collection. The analysis in this study has received ethics approval from the Humanities and Social Sciences DERC at The Australian National University with the protocol number: 2022/004. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Transition probability diagram from health status in time 0 to time 1
Fig. 2
Fig. 2
Prevalence of overweight and diabetes based on Risksesdas
Fig. 3
Fig. 3
Prevalence of self-reported diabetes and the projections taking account of population education structure and without education
Fig. 4
Fig. 4
The proportion of under/normal BMI, excess weight and diabetes, (a) before adjustment for undiagnosed diabetes, and (b) after adjustment for undiagnosed diabetes
Fig. 5
Fig. 5
Prevalence of diagnosed diabetes and the projection taking account of population education structure using self-reported diabetes and after adjustment undiagnosed diabetes based on HbA1c diagnosis
Fig. 6
Fig. 6
Prevalence of diabetes and the projection by education level comparing before and after adjustment undiagnosed diabetes
Fig. 7
Fig. 7
Projection the number of male and female by health status from 2010–2060
See this image and copyright information in PMC

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