ArticleEnvironmental science and pollution research international2022
Spatial heterogeneity of human lifespan in relation to living environment and socio-economic polarization: a case study in the Beijing-Tianjin-Hebei region, China.
Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 5 citations in OpenAlex.
- Hainan Longevity Model, Senile Degeneration, Cognitive Disability and Healthy Longevity.Aging medicine (Milton (N.S.W)) · 2026Review
- Older adults life expectancy in China: Bayesian mortality estimation and spatially heterogeneous determinants.Frontiers in public health · 2026Article
- Spatiotemporal patterns and social determinants of county life expectancy in the Yangtze River Economic Belt.Frontiers in public health · 2025Article
- Factors Associated with Elderly Health-Related Quality of Life in Tibet: A Cross-Sectional Study from a Health Ecological Perspective.Journal of multidisciplinary healthcare · 2024Article
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3 authors at 1 institution in 1 country.
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Abstract
The spatial heterogeneity and influence factors of public lifespan have been reported worldwide at the national level or typical longevous areas. However, few sub-national studies considering the living environment and socio-economic level together have been explored in the imbalanced developed region with a huge population base and deteriorated air quality. In this paper, spatial heterogeneity of lifespan integrating environment and socio-economic influence factors was investigated in the Beijing-Tianjin-Hebei (BTH) region of China using geographically weighted regression (GWR). Five indicators were constructed to determine the lifespan based on the three national censuses (1990-2010) in the BTH region. The results showed that the areas with higher CH (centenarians per 100,000 inhabitants) and centenarity index (CI) exhibited changing distribution in the BTH region, whereas those with lower CH and CI and extreme value of the ultra-octogenarian index (UOI) and LI (> 90/ > 65) maintained a relatively stable feature through time. But as lifespan indicators increase overall, the differences between the counties/districts widen. Furthermore, remarkable spatial heterogeneity was detected for the associations between the significant environmental and socio-economic variables and lifespan indicators. Although the natural geographic condition (altitude) still exhibited a negative influence on the longevity of the population, the socio-economic factors (GDP
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