ArticleBiological trace element research2026
Soil Selenium and Longevity: A Multi-scale Spatial Analysis in China.
Article in Biological trace element research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
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.
Indexed as
Identifiers
42509495What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.