ArticleFrontiers in public health2025
Spatiotemporal heterogeneity of the association between socioeconomic development and birth rate: a geographically and temporally weighted regression modeling study in China.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The birth rate is an important indicator of the health of the population. However, persistently low birth rate has become a pressing demographic challenge for many countries, including China. This has significant implications for sustainable population planning. Methods: This study applied hot spot analysis and the spatiotemporal geographically weighted regression (GTWR) modeling, used panel data of 286 cities in China from 2012 to 2021 to explore the spatiotemporal heterogeneity of the relationship between the socioeconomic development and birth rate. Results: The research has found that 2017 was an important turning point in China's demographic transition. The hot spot analysis reveals that the birth rate hot spots are characterized by a multipolar kernel distribution, shifting from spatial diffusion to convergence, with the cold spots mainly located in the northeast. And the GTWR modeling found that the relationship between socioeconomic development and birth rate varies and change dynamically over space and time. Key findings include: (1) the negative impact of GDP per capita on birth rates has intensified; (2) housing prices exhibit both wealth and crowding-out effects on birth rates, and there are obvious regional differences between the north and the south; (3) fiscal education expenditure on birth rates has the most pronounced income effect in the eastern region. Conclusion: This study adopts spatiotemporal perspective to reveal the spatiotemporal heterogeneity of the association between socioeconomic development and birth rate. It provides new evidence on the influence of macro factors on fertility in China. And emphasizes the importance of incorporating regional variations into population policy design.
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