esc

Type at least two characters to start searching.

↑↓ select↵ openesc close

Share

Export Citation

APA
MLA
Chicago
Harvard
Vancouver
BIBTEX
RIS
Universitas Hasanuddin
Research output:Contribution to journal›Article›peer-review

Geographic Variations and Determinants of Prediabetes and Type 2 Diabetes Among Indonesian Adults: Evidence From the 2023 Indonesian Health Survey

Adnan Y.

Tropical Medicine and International Health

Q1
Published: 2026

Abstract

OBJECTIVES: The rising burden of prediabetes and Type 2 diabetes (T2D) in Indonesia, along with geographic disparities and age-related risk patterns, remain inadequately understood. The present study used nationally representative data to examine determinants, geographic variations and age and sex related glycaemic probability patterns. METHODS: A cross-sectional study using data from the Indonesian Health Survey 2023 on individuals aged ≥ 15 years (n = 37,157). Analysis was performed using survey weighting and multinomial logistic regression. Non-linear age relationships were modelled using generalized additive models (GAM), and regional variations were visualized using choropleth maps. RESULTS: A total of 37.4% of respondents were classified as normoglycaemia, 41.6% as prediabetic and 20.9% as having T2D. The main determinants of prediabetes included age ≥ 45 years (aOR = 1.48; 95% CI: 1.40-1.57), males (aOR = 1.55; 95% CI: 1.44-1.67), obesity (aOR = 1.46; 95% CI: 1.37-1.55), hypertension (aOR = 1.35; 95% CI: 1.27-1.43) and dyslipidemia (aOR = 1.31; 95% CI: 1.24-1.38). The main determinants of T2D were age ≥ 45 years (aOR = 7.13; 95% CI: 5.63-9.04), dyslipidemia (aOR = 2.51; 95% CI: 2.10-3.00), hypertension (aOR = 1.77; 95% CI: 1.50-2.09) and obesity (aOR = 1.65; 95% CI: 1.35-2.01). The GAM showed a non-linear and accelerated increase in the probability of T2D in older age. Geographically, the burden of dysglycaemia is more concentrated in western Indonesia, indicating regional disparities in risk distribution. CONCLUSIONS: These findings demonstrate significant geographic variation and key determinants of prediabetes and T2D, supporting region-specific prevention strategies, risk-based screening and equitable public health policies to strengthen diabetes prevention and control in Indonesia.

Access to Document

10.1111/tmi.70247

Other files and links

Fingerprint

PrediabetesSciences
MedicineSciences
DyslipidemiaSciences
Type 2 diabetesSciences
DemographySciences
Environmental healthSciences
ObesitySciences
IndonesianSciences
Logistic regressionSciences
Public healthSciences
Multinomial logistic regressionSciences
GerontologySciences
Cross-sectional studySciences
Socioeconomic statusSciences
OverweightSciences
Diabetes mellitusSciences
PopulationSciences
Type 2 Diabetes MellitusSciences
Social determinants of healthSciences
Metabolic syndromeSciences
National Health and Nutrition Examination SurveySciences
Survey data collectionSciences
GeographySciences
PovertySciences
Impaired fasting glucoseSciences
QuartileSciences