ArticleSociology of health & illness2025
A Political-Economic Model of Community and Societal Health Resources: A 92-Country Global Analysis.
Article in Sociology of health & illness, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- The impact of health risks on healthcare expenditure in European countries.The European journal of health economics : HEPAC : health economics in prevention and care · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The quality and access to healthcare systems depend on community health resources, infrastructure, and funding; however, a significant disparity in these resources persists globally. The effectiveness of national health systems depends on a balanced approach to health spending, access to facilities and a skilled local health workforce. What accounts for country-level differences in those critical community and societal health resources? We proposed and tested a model that leverages political and socioeconomic factors to predict various health resources and services in countries. Data, including community health training, research, and support, universal health coverage, healthcare infrastructure, and per capita health expenditure, were collected and analysed by statistical methods, like bivariate correlations and hierarchical multiple linear regressions from 105 countries. Countries with more grassroots activism, fiscal decentralisation, freedom, and globalisation and less perceived corruption and inequality had more community and societal health resources. In multivariate analyses, stronger community health training and research is associated with the globalisation index, freedom score, government fiscal decentralisation, and income inequality. The strongest predictor of health insurance coverage and hospital beds was the country's population education index, and of nurses and midwives-per-capita and health expenditures-per-capita was GDP-per-capita. These insights could guide policymaking to reduce global health inequalities.
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