AUTHOR=Fan Mingyuan , Yuan Jiushu , Zhang Sai , Fu Qingqing , Lu Dingyi , Wang Qiangyan , Xie Hongyan , Gao Hong TITLE=Association between outdoor artificial light at night and metabolic diseases in middle-aged to older adults—the CHARLS survey JOURNAL=Frontiers in Public Health VOLUME=Volume 13 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1515597 DOI=10.3389/fpubh.2025.1515597 ISSN=2296-2565 ABSTRACT=IntroductionArtificial light at night (LAN) is associated with metabolic diseases, but its precise relationship is still not fully understood. This study explores the association between LAN and metabolic diseases.MethodsA cross-sectional study involving 11,729 participants conducted in 2015 was selected from the China Health and Retirement Longitudinal Study. Diabetes, metabolic syndrome (MetS), overweight, obesity, dyslipidemia, and hyperuricemia (HUA) were defined according to established guidelines. Using satellite data, we estimated LAN exposure for 2015 and matched each participant’s address with the corresponding annual mean LAN value. Multivariate logistic regression models were used to assess the relationship between LAN and metabolic diseases. To investigate possible non-linear associations and visualize the dose–response relationship between LAN and metabolic diseases, we used the restricted cubic splines (RCS) regression model.ResultsWe found that higher levels of LAN significantly correlate with metabolic diseases. In the final adjusted model, participants in the highest LAN quartile group (Q4) showed the highest risk for metabolic diseases: diabetes [odds ratio (OR): 1.03, 95% confidence interval (CI): 1.01, 1.05], MetS (OR: 1.04, 95% CI: 1.02, 1.06), overweight (OR: 1.08, 95% CI: 1.06, 1.11), obesity (OR: 1.03, 95% CI: 1.01, 1.05), and dyslipidemia (OR: 1.03, 95% CI: 1.01, 1.05). In the RCS regression model, there was a non-linear association between LAN and risk of MetS, overweight, obesity, dyslipidemia, and HUA (for non-linear: p < 0.05).ConclusionLAN is associated with an increased risk of metabolic diseases. This highlights the urgent need to address LAN pollution in public health strategies; reducing LAN exposure may help mitigate the risk of metabolic diseases.