The Negative Correlation Between Nighttime Light Pollution and the Prevalence of Depressive Disorders: A Medical Image-Processing Study on 35 US Cities

Background: Growing evidence suggests potential links between artificial nighttime illumination and neurological health outcomes. This study introduces an innovative satellite image analysis technique to quantify light pollution while investigating its association with depressive disorders across urban populations. Methods: We developed a PHP-based image processing algorithm to estimate relative light pollution levels from high-resolution nighttime satellite imagery. Applying this method to 35 U.S. metropolitan areas, we correlated the findings with depression prevalence data from the CDC's Behavioral Risk Factor Surveillance System (Pickens et al., 2018). Our analysis incorporated multiple mental health indicators, including depression diagnoses, smoking rates, and binge drinking patterns. Results: Our analysis revealed three key findings: (1) a positive correlation between urban population density and light pollution intensity (p=0.03), (2) an inverse relationship between light pollution levels and both depression prevalence (p=0.01) and smoking rates (p=0.02), and (3) a positive association between light pollution and binge drinking reports (p=0.04). These patterns remained significant after controlling for population variables. Conclusion: The proposed satellite image analysis method provides a cost-effective approach for large-scale light pollution assessment in neuroepidemiological research. Our findings suggest complex relationships between artificial nighttime lighting and mental health indicators that warrant further investigation, particularly regarding potential mediating factors in urban environments.