Fan Mingyuan, Yuan Jiushu, Zhang Sai, Fu Qingqing, Lu Dingyi, Wang Qiangyan, Xie Hongyan, Gao Hong
Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Front Public Health. 2025 Mar 6;13:1515597. doi: 10.3389/fpubh.2025.1515597. eCollection 2025.
Artificial 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.
A 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.
We 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: < 0.05).
LAN 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.
夜间人工照明（LAN）与代谢性疾病有关，但其确切关系仍未完全明确。本研究探讨LAN与代谢性疾病之间的关联。
从中国健康与养老追踪调查中选取了一项2015年进行的涉及11729名参与者的横断面研究。糖尿病、代谢综合征（MetS）、超重、肥胖、血脂异常和高尿酸血症（HUA）均根据既定指南进行定义。利用卫星数据，我们估算了2015年的LAN暴露情况，并将每位参与者的住址与相应的年平均LAN值进行匹配。采用多因素逻辑回归模型评估LAN与代谢性疾病之间的关系。为研究可能的非线性关联并直观呈现LAN与代谢性疾病之间的剂量反应关系，我们使用了受限立方样条（RCS）回归模型。
我们发现，较高水平的LAN与代谢性疾病显著相关。在最终调整模型中，LAN最高四分位数组（Q4）的参与者患代谢性疾病的风险最高：糖尿病[比值比（OR）：1.03，95%置信区间（CI）：1.01，1.05]、MetS（OR：1.04，95%CI：1.02，1.06）、超重（OR：1.08，95%CI：1.06，1.11）、肥胖（OR：1.03，95%CI：1.01，1.05）和血脂异常（OR：1.03，95%CI：1.01，1.05）。在RCS回归模型中，LAN与MetS、超重、肥胖、血脂异常和HUA风险之间存在非线性关联（非线性检验：<0.05）。
LAN与代谢性疾病风险增加有关。这凸显了在公共卫生策略中解决LAN污染问题的迫切需求；减少LAN暴露可能有助于降低代谢性疾病的风险。
