Soil Selenium and Longevity: A Multi-scale Spatial Analysis in China.

Authors

Ying Mo, Jiasheng Peng, Youfan Wu, Guohuan Zhang, Changyin Dai, Qiangzhong Yu, Yujie Zhang, Linchun Jiao, Yuhang Li, Wenjie Shen

Published in

Biological trace element research. Jul 28, 2026. Epub Jul 28, 2026.

Abstract

Selenium (Se) is an essential trace element for human health and longevity. However, the spatial association between soil Se content and longevity remains poorly understood at different spatial scales. Therefore, this study investigated the relationship between soil Se and longevity at both the national scale in China and at six representative smaller regions (Heilongjiang Province, Liaohe River Basin, Enshi Prefecture in Hubei, Ankang City in Shaanxi, Lianzhou City and Yingde City in Guangdong). Both traditional statistical methods (e.g., Pearson correlation, OLS regression) and spatial statistical methods (e.g., Moran's I, SLM, SEM) were employed. The results revealed that: (1) At the national scale, soil Se and longevity exhibited a highly significant positive correlation and strong spatial clustering. High-Se/high-longevity clusters were mainly located in southern China, while northern provinces were characterized by low-Se/low-longevity clusters. SEM (R² = 0.31) outperformed OLS (R² = 0.22) and SLM (R² = 0.28), and the SEM model parameters indicated that the positive association persists after controlling for spatial error dependence. (2) At the small-scale level, a highly significant positive correlation was only identified in Lianzhou and Yingde. In Lianzhou, clusters of high Se and high longevity were concentrated in the southern region. SLM (R² = 0.87) outperformed OLS (R² = 0.72); the SLM model parameters indicated that the positive effect of soil Se remains after controlling for spatial lag dependence. (3) Spatial error dependence dominated at the broader scale, whereas spatial lag dependence was more prominent in small regions. Linearity and model performance improved substantially at the small scale. Regions with suitable Se levels showed the strongest Se-longevity associations.

PMID:
42509495
Bibliographic data and abstract were imported from PubMed on 28 Jul 2026.

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