Light at night exposure and risk of breast cancer: a meta-analysis of observational studies
Bibliographic record
Abstract
Objective The aim of this meta-analysis is to evaluate the impact of light at night (LAN) exposure on the risk of breast cancer across varying factors. Method We conducted a systematic search of literature up to July 15, 2023, including PubMed, Cochrane Library, and Embase databases, using keywords related to breast cancer and LAN exposure. Cohort study and case–control study literature on night light exposure and breast cancer risk were included. Statistical analyses were performed using Stata software version 17.0. To address heterogeneity among different studies, we employed a random-effects model for analysis and assessed publication bias using funnel plots and Egger’s test. Results We included 13 case–control and 8 cohort studies with 734,372 participants worldwide. In the Newcastle-Ottawa Scale (NOS) assessments, the average score was 7.43 (ranging from 5 to 9). The overall meta-analysis demonstrated a significant association between exposure to LAN and risk of breast cancer (RR = 1.12; 95% CI: 1.06–1.17; I 2 = 31.3%, p < 0.001). In the subgroup analysis, the results of the analysis for study types (case–control studies: RR = 1.16; 95% CI: 1.06–1.27; I 2 = 40.4%, p = 0.001; cohort studies: RR = 1.08; 95% CI: 1.04–1.14; I 2 = 0.0%, p < 0.001) and the results for light exposure types (outdoor LAN: RR = 1.07; 95% CI: 1.02–1.13; I 2 = 30.9%, p = 0.004) are presented. In the analysis conducted for continents, the highest breast cancer risk was observed in the Asian population (Asian: RR = 1.24; 95% CI: 1.15–1.34; I 2 = 0.0%, p < 0.001) and in the analysis of estrogen receptor status (ER+: RR = 1.10; 95% CI: 1.03–1.18; I 2 = 17.0%, p = 0.005;). We also conducted an analysis on menopausal status and various lifestyles but did not find any statistically significant findings. Conclusion Our study demonstrates that LAN exposure is associated with an increased risk of breast cancer, particularly in the Asian population. Among the existing hypotheses, the idea that LAN exposure leads to a decrease in melatonin is widely accepted. However, until the mechanism of this effect is clearly elucidated, it is not recommended to take melatonin supplements for breast cancer prevention without medical advice. We hope to conduct more high-quality research, especially concerning the investigation of other environmental confounding factors, to further advance this field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".