Evidence map›Paper›PMID 40727627›Full record

ArticleJournal of public health research2025

Exploring the spatial and temporal dynamics of the health index of Bangladesh using Bayesian framework.

Afroza Sultana, Akher Ali, Sifat Ar Salan, Mohammad Alamgir Kabir

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Article in Journal of public health research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Afroza SultanaDepartment of Statistics and Data Science, Jahangirnagar University, Savar, Dhaka, Bangladesh.ORCID https://orcid.org/0009-0006-4136-5753
Akher AliDepartment of Statistics and Data Science, Jahangirnagar University, Savar, Dhaka, Bangladesh.
Sifat Ar SalanDepartment of Statistics and Data Science, Jahangirnagar University, Savar, Dhaka, Bangladesh.
Mohammad Alamgir KabirDepartment of Statistics and Data Science, Jahangirnagar University, Savar, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Health is vital for survival and societal well-being, with global goals focusing on improved access and achieving progress in public health. In Bangladesh, investigating health determinants and disparities is crucial for effective interventions. Objective: This study investigates spatial and temporal variations in the influence of socioeconomic and health-related factors on the health index at a detailed district level in Bangladesh, aiming to discern disparities in health indicators among districts. Based on 21 years of secondary data across 64 districts in Bangladesh, this research deploys four Bayesian spatial-temporal models to analyze the health index and relevant variables. Design and methods: The study identifies the optimal model by evaluating linear, analysis of variance, and autoregressive models of orders one and two. Comparative analysis utilizing the WAIC and DIC aids model selection. The MCMC method enhances precision in determining health index determinants, providing valuable insights for policymakers and researchers. Results: Our findings reveal that the AR (2) model demonstrated superior performance among all the spatiotemporal models. The health index demonstrated a consistent upward trend overall, but regional variations in residents' health indices were noted. Positive spatial autocorrelation was identified in the health index, emphasizing interconnected health outcomes. Spatiotemporal models underscored the significance of the income index, child mortality, life expectancy, and the proportion of the active population as crucial factors shaping the health index in Bangladesh. Conclusions: This study provides actionable insights for targeted health interventions in districts with specific needs, emphasizing focused policies on poverty, education, and healthcare to enhance overall well-being in Bangladesh.

Indexed as

BangladeshBayesian inferencechild mortalityhealth indexlife expectancyMCMCspatial-temporal approach

Identifiers

PMID40727627
PMCPMC12301593

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