Confounding Effects in Spatial Epidemiology

This lecture discusses the importance of controlling for confounding variables in spatial epidemiology to isolate the effect of specific factors on human health, such as sugar sweetened beverages, pesticides, and income. It covers topics like the distribution and determinants of health, the impact of space in public health, and the masking of true effects of exposure. Specific confounding factors for diseases like sleep troubles and BMI are explored, along with methods for adjusting for confounders such as restriction, matching, stratification, and multivariate analysis. The lecture also addresses the criteria for confounding variables and the challenges in observational studies.