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Light pollution and risk of diabetes: a systematic review and meta-analysis of observational studies
Mengxiang Zhang1,2,3, Yafei Xie4, Dexuan Hu5
1The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
Background:
Light pollution, characterized by excessive artificial light at night (LAN), is an emerging environmental risk factor with widespread impacts on human health. While its disruption of circadian rhythms is well-documented, its specific link to metabolic disorders like diabetes remains poorly synthesized.
Objective:
To systematically evaluate and quantify the association between light pollution exposure (both indoor and outdoor) and the risk of diabetes mellitus based on existing observational studies.
Methods:
We searched PubMed, Web of Science, Scopus, Embase, and CINAHL on January 9, 2024, and manually supplemented with citation searches. Two researchers independently screened literature and extracted data. Study quality was evaluated using the AHRQ and NOS scales. Random-effects meta-analyses synthesized risk estimates, with heterogeneity measured by I2. Publication bias was assessed using funnel plots and Beeg's test. Subgroup analyses were conducted based on the severity and type of light pollution. The GRADE method assessed evidence credibility.
Results:
Out of 2,115 identified studies, six were included in the quantitative synthesis. Light pollution exposure was associated with a 31% increase in diabetes risk (OR: 1.31, 95% CI: 1.13-1.33; GRADE: moderate). Subgroup analyses showed significant correlations with severe light pollution (OR: 1.19, 95% CI: 1.14-1.24; GRADE: moderate), low to moderate light pollution (OR: 1.10, 95% CI: 1.06-1.14; GRADE: moderate), and indoor light pollution (OR: 1.66, 95% CI: 1.15-2.39; GRADE: moderate). Heterogeneity sources included sample size, light pollution type, and study quality.
Conclusion:
Exposure to light pollution is positively associated with increased diabetes risk, particularly with indoor light pollution. However, the limited number of included studies underscores the need for more prospective cohort studies with standardized exposure assessment and covariate adjustment.
Systematic Review Registration:
PROSPERO https://www.crd.york.ac.uk/prospero/, identifier CRD42024551969.
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