Research Article

Mapping structural topology of OECD health dynamics: A network analysis of mortality changes

Number: 1 July 13, 2026

Mapping structural topology of OECD health dynamics: A network analysis of mortality changes

Abstract

Objective: Comparative public health research tends to focus on rankings that treat countries as independent units. This approach risks overlooking structural relationships and hidden country clusters arising from policy diffusion and common epidemiological trends. In response to this methodological gap, the main objective of this study is to reveal the underlying structural similarities and differences in mortality change dynamics in OECD countries between 2018 and 2023 through network analysis.
Methods: In this study, social network analysis  was applied to examine health dynamics. Networks were constructed using Pearson correlation coefficients of mortality change data from 37 countries. Sensitivity analysis was performed to determine the optimal thresholds for network stability.
Results: OECD countries do not form a uniform homogeneous bloc. Rather, they coalesce into distinct “health blocs” shaped mainly by geographical proximity, such as the European, Baltic and Latin American clusters. Critically, the male mortality network is much more fragmented than the female network, which calls into question assumptions of sex-based homogeneity in health transitions.
Conclusion: The position of countries within these “networks of similarities” provides a robust framework for evidence-based policy development, suggesting that policy transfer should be guided by spatial and structural proximity, not just formal health system typologies. The observed heterogeneity in male health dynamics necessitates strategies tailored to local risk profiles, rather than a “one-size-fits-all” approach.

Keywords

Mortality, Social Network Analysis, Spatial Analysis, Cause of Death, OECD, Sex Factors

Ethical Statement

This study is based on the analysis of publicly available data obtained from the OECD's “Causes of Death” database. As the study did not involve any interaction with human participants or the use of identifiable personal data, no ethical committee approval was obtained.

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APA
Bulut, T. (2026). Mapping structural topology of OECD health dynamics: A network analysis of mortality changes. Turkish Journal of Public Health, 1. https://doi.org/10.20518/tjph.1830849
AMA
1.Bulut T. Mapping structural topology of OECD health dynamics: A network analysis of mortality changes. TJPH. 2026;(1). doi:10.20518/tjph.1830849
Chicago
Bulut, Tevfik. 2026. “Mapping Structural Topology of OECD Health Dynamics: A Network Analysis of Mortality Changes”. Turkish Journal of Public Health, no. 1. https://doi.org/10.20518/tjph.1830849.
EndNote
Bulut T (July 1, 2026) Mapping structural topology of OECD health dynamics: A network analysis of mortality changes. Turkish Journal of Public Health 1
IEEE
[1]T. Bulut, “Mapping structural topology of OECD health dynamics: A network analysis of mortality changes”, TJPH, no. 1, July 2026, doi: 10.20518/tjph.1830849.
ISNAD
Bulut, Tevfik. “Mapping Structural Topology of OECD Health Dynamics: A Network Analysis of Mortality Changes”. Turkish Journal of Public Health. 1 (July 1, 2026). https://doi.org/10.20518/tjph.1830849.
JAMA
1.Bulut T. Mapping structural topology of OECD health dynamics: A network analysis of mortality changes. TJPH. 2026. doi:10.20518/tjph.1830849.
MLA
Bulut, Tevfik. “Mapping Structural Topology of OECD Health Dynamics: A Network Analysis of Mortality Changes”. Turkish Journal of Public Health, no. 1, July 2026, doi:10.20518/tjph.1830849.
Vancouver
1.Tevfik Bulut. Mapping structural topology of OECD health dynamics: A network analysis of mortality changes. TJPH. 2026 Jul. 1;(1). doi:10.20518/tjph.1830849