ArticleInternational journal of biometeorology2022
Geographical distinctions of longevity indicators and their correlation with climatic factors in the area where most Chinese Yao are distributed.
Article in International journal of biometeorology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Spatial heterogeneity of health care resources: a study of the socioeconomic, demographic, and natural geographic conditions of ethnic minority regions in Southwestern China.BMC public health · 2026Article
- Guangxi Eco-Environmental Health and Aging Study (GEHAS).BMJ open · 2026Article
- Relationship and distribution patterns between geochemical backgrounds of W and MScientific reports · 2026Article
- Patterns of spatial inequality in China's longevity population and its socio-economic influences.BMC public health · 2025Article
- Mortality and immunological indicators of men who have sex with men living with HIV on antiretroviral therapy: a 10-year retrospective cohort study in Southern China.BMC infectious diseases · 2025Article
- The relationship between geochemical background values of MgO and SiO₂ and regional population longevity: evidence from Yunnan, China.Frontiers in public health · 2025Article
- Which Factors Influence Healthy Aging? A Lesson from the Longevity Village of Bama in China.Aging and disease · 2023Review
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11 authors.
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Abstract
Longevity research is a hot topic in the health field. Considerable research focuses on longevity phenomenon in Bama Yao Autonomous County, which has a typical karst landform and is located in Southwest China. This study aims to illustrate the spatial feature of longevity indicators in other Yao areas, to analyze the correlation between climatic factors and longevity indicators, and to provide new clues and targets for further longevity studies. We collect and integrate population, climate, and terrain data into a spatial database. The main analysis methods include spatial autocorrelation, high/low clustering, and multiscale geographically weighted regression (MGWR). Two longevity clusters are identified in Guijiang River Basin (longevity index (LI%): 2.49 ± 0.63) and Liujiang River Basin (LI%: 2.13 ± 0.60). The spatial distribution of longevity indicators is autocorrelative (Moran's I = 0.652, p < 0.001) and clustered significantly (Z score = 4.268, p < 0.001). MGWR shows that the atmospheric pressure significantly affects the spatial distribution of LI% (estimate value (EV) = - 0.566, p = 0.012), centenarity index (CI%) (EV = - 0.425, p = 0.007), UC (EV = - 0.502, p = 0.006), and CH (EV = - 0.497, p = 0.007). Rainfall significantly affects the spatial distribution of LI% (EV = 0.300, p = 0.003) and CI% (EV = - 0.191, p = 0.016). The spatial distribution of the main longevity indicators shows significant heterogeneity and autocorrelation, and they cluster in the Guijiang River and Liujiang River basins. Atmospheric pressure and rainfall may contribute to the longevity phenomenon through complex mechanisms. The longevity phenomenon in the Yao nationality in Guijiang River Basin requires further study to improve our understanding of the health effect of meteorological, environmental, and social conditions on longevity.
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