Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jul 1;83(1):169.
doi: 10.1186/s13690-025-01613-4.

The major risk factor of stroke across Indonesia; a nationwide geospatial analysis of universal health coverage program

Andi Alfian Zainuddin  1 , Rais Reskiawan A Kadir  2   3 , Hedi Kuswanto  2 , Jumraini Tammasse  4 , Nurul Qalby  2 , Andi Afdal Abdullah  5 , Ari Andini Junaidi  2 , Al Asyary  6
Affiliations

The major risk factor of stroke across Indonesia; a nationwide geospatial analysis of universal health coverage program

Andi Alfian Zainuddin et al. Arch Public Health. .

Abstract

Background: Stroke is the leading cause of mortality in Indonesia, with hypertension and diabetes mellitus (DM) recognized as well-established risk factors. Moreover, recent epidemiological studies have documented rising incidence, morbidity and mortality of these conditions. Understanding their spatial distribution and interrelationships is crucial for developing targeted public health interventions. This study aims to analyze the geographic distribution of stroke, DM, and hypertension across Indonesia's provinces, evaluate their spatial correlations, and explore their interconnections using advanced spatial modeling techniques.

Methods: The data were collected from the Social Health Insurance Administration Body, which manages Indonesia's universal health coverage, between 2017 and 2022. Crude incidence rates for the diseases were calculated and spatial distribution patterns were analyzed using Global and local Moran analysis. A spatial autoregressive (SAR) model was employed to assess the spatial dependence and interrelationships between these diseases.

Results: The crude incidence rates of stroke, hypertension, and DM were 158.47, 2716.34, and 1503.06 per 100,000 population, respectively. Significant spatial heterogeneity was observed, with certain provinces consistently appearing as high-risk areas across all three diseases. Through SAR analysis, our study identified a significant positive spatial association between DM and stroke incidence, indicating that provinces with higher DM rates also tend to experience elevated stroke burden.

Conclusion: This study mapped the geographical and spatial distribution of stroke, DM, and hypertension across Indonesia and found the pivotal role of DM in driving stroke incidence. By prioritizing high-incidence regions and addressing specific risk factors, targeted interventions can significantly reduce stroke cases and enhance public health outcomes in Indonesia.

Keywords: Diabetes mellitus; Epidemiology; Geospatial; Hypertension; Stroke.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was reviewed and approved by Ethics Committee of Hasanuddin University (869/UN4.6.4.5.31/PP35/2024). Informed consent was waived by the Ethics Committee. Consent for publication: This manuscript has been approved by all authors and is solely the work of the authors named. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Stroke incidence across Indonesia from 2017–2022. Aceh (1), North Sumatera (2), Riau Islands (3), Riau (4), West Sumatera (5), Jambi (6), Bangka Belitung Islands (7), South, Sumatera (8). Bengkulu (9), Lampung (10), Banten (11), Jakarta (12), West Java (13), Central Java (14), Yogyakarta (15), East Java (16), Bali (17), West Nusa Tenggara (18), East Nusa, Tenggara (19), West Kalimantan (20), Central Kalimantan (21), North Kalimantan (22), East Kalimantan (23), South Kalimantan (24), West Sulawesi (25), Central Sulawesi (26), South Sulawesi (27), Southeast Sulawesi (28), Gorontalo (29), North Sulawesi (30), North Maluku (31), Maluku (32), West Papua (33), Papua (34)
Fig. 2
Fig. 2
Hypertension incidence across Indonesia from 2017 to 2022
Fig. 3
Fig. 3
Incidence of DM across Indonesia for the years 2017–2022
Fig. 4
Fig. 4
Local Moran analysis identifying specific geographical locations with similar stroke rates
Fig. 5
Fig. 5
Local Moran analysis was conducted to identify geographic regions with similar hypertension rates
Fig. 6
Fig. 6
Local Moran analysis identified regions with similar DM rates
Fig. 7
Fig. 7
The Gaussian model of stroke, hypertension, and DM incidence across Indonesia revealed a strong correlation between both DM and hypertension with cerebrovascular diseases
See this image and copyright information in PMC

References

    1. Riskesdas. Laporan Riset Kesehatan Dasar Kementrian Kesehatan republik Indonesia. Kemenkes RI: Badan Litbangkes; 2018.
    1. Pandian JD, Padma Srivastava MV, Aaron S, et al. The burden, risk factors and unique etiologies of stroke in South-East Asia region (SEAR). Lancet Reg Health Southeast Asia. 2023;17:100290. 10.1016/j.lansea.2023.100290 - DOI - PMC - PubMed
    1. Venketasubramanian N, Yoon BW, Pandian J, et al. Stroke epidemiology in South, East, and South-East Asia: a review. J Stroke. 2017;19(3):286–94. 10.5853/jos.2017.00234 - DOI - PMC - PubMed
    1. Tan KS, Pandian JD, Liu L, et al. Stroke in Asia. Cerebrovasc Dis Extra. 2024;14(1):58–75. 10.1159/000538928 - DOI - PMC - PubMed
    1. Rochmah TN, Rahmawati IT, Dahlui M, et al. Economic burden of stroke disease: a systematic review. Int J Environ Res Public Health. 2021;18(14). 10.3390/ijerph18147552 - PMC - PubMed

LinkOut - more resources