ArticleGeroScience2026
Estimation of biological age and age-related outcomes with easily accessible parameters in Chinese.
Article in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Seven routine blood markers predict five-year mortality in older Indians: a risk score from the LASI-DAD cohort.Research square · 2026Article
- Artificial intelligence approaches in biological age prediction: current status and challenges.British journal of biomedical science · 2026Review
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Authors and funding
8 authors.
Funding
Abstract
Biological aging exhibits significant heterogeneity across individuals, and a precise evaluation at scale is urgently needed. Here, we developed a PCAge, based on common clinical, physiological, and laboratory indices routinely collected in primary healthcare, in the CHARLS. PCAge demonstrated strong correlations with chronological age (r = 0.86-0.88, P < 0.001) and robust performance in the prediction of mortality (C-index = 0.798) over a 10-year follow-up. Biologically older individuals (PCAge > chronological age) suffered from substantially higher risk of age-related diseases, including cardiovascular disease (HR = 1.30, P < 0.001), heart disease (HR = 1.35, P = 0.003), stroke (HR = 2.38, P < 0.001), hypertension (HR = 1.28, P = 0.007), and diabetes (HR = 1.51, P < 0.001). Furthermore, the generalizability of PCAge was validated in the South China Cohort (SCC, n = 68,920). Biologically older individuals were more likely to have hypertension, diabetes, cardiovascular disease, and respiratory diseases. Being female (proportion ratios [PR] = 1.94, P < 0.001), lower education attainment (PR = 1.18, P < 0.001), higher income (PR = 1.47, P < 0.001), and unfavorable lifestyles (PR = 1.41, P < 0.001) were associated with a higher probability of having accelerated aging. PCAge identified aging trajectories up to a decade before clinical disease onset, offering a cost-effective tool for population-level aging surveillance. Our findings underscore the potential of PCAge as a highly accessible tool for the evaluation of aging status, especially in resource-limited areas.
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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.