Syndemic analysis of stroke in Indonesia

Stroke is the first leading cause of mortality in Indonesia, yet no national study has applied a comprehensive syndemic approach that integrates co-occurring diseases and socio-economic conditions to assess the determinant of this cerebrovascular disease. To address this gap, we analyzed the ten most prevalent clinical conditions and major socio-economic indicators to identify the interacting factors that contribute to stroke incidence.

We analyzed national health insurance data from over 12 million patients, integrated with provincial socio-economic indicators. All variables were aggregated and analyzed at the provincial level from 2018 to 2023. Multiple advanced statistical approaches were leveraged to identify syndemic patterns.

Stroke, diabetes mellitus (DM), chronic kidney disease (CKD), and poverty showed consistent increases across Indonesian provinces. Correlation analysis identified strong associations between stroke and CKD, DM, and cirrhosis, with poverty demonstrating a moderate correlation. Bayesian Gaussian Network Analysis indicated that stroke was the most probable downstream outcome (51.85%) within this interconnected system. Path analysis showed that DM had strong direct associations with CKD (75.88%) and cirrhosis (61.27%), indicating a major upstream role of diabetes in the network. CKD in turn showed substantial direct associations with both poverty (48.67%) and stroke (19.18), while poverty and cirrhosis also demonstrated indirect associations with stroke. Geographically and Temporally Weighted Regression revealed marked spatial and temporal heterogeneity in the strength of these determinants across provinces. Principal Component Analysis consistently clustered several provinces in high-burden syndemic profiles.

Stroke in Indonesia emerges as the convergent outcome of interconnected metabolic, hepatic, and socio-economic factors, rather than isolated clinical conditions. These findings underscore the importance of a syndemic framework to effectively reduce the national stroke burden.

This study was funded by Indonesian Ministry of Higher Education, Science and Technology's BIMA Research Program under grant number 050/E5/PG.02.00.PL/2024 and 02035/UN4.22.2/PT.01.03/2024.