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Introduction: Historical maps of racialized evaluation of mortgage lending risk (i.e., redlined neighborhoods) have been linked to adverse health outcomes. Little research has examined whether living in historically redlined neighborhoods is associated with obesity, differentially by race or gender. Methods: This is a cross-sectional study to examine whether living in historically redlined neighborhoods is associated with BMI and waist circumference among Black and White adults in 1985–1986. Participants’ addresses were linked to the 1930s Home Owners’ Loan Corporation maps that evaluated mortgage lending risk across neighborhoods. The authors used multilevel linear regression models clustered on Census tract, adjusted for confounders to estimate main effects, and stratified, and interaction models by (1) race, (2) gender, and (3) race by gender with redlining differentially for Black versus White adults and men versus women. To better understand strata differences, they compared Census tract–level median household income across race and gender groups within Home Owners’ Loan Corporation grade. Results: Black adults (n=2,103) were more likely than White adults (n=1,767) to live in historically rated hazardous areas and to have higher BMI and waist circumference. Redlining and race and redlining and gender interactions for BMI and waist circumference were statistically significant (p

Background: The burden of cancer in Africa is growing. Although cancer outcomes are understood as the product of influences at multiple socioecological levels, population-based studies of geographical factors and cancer outcomes in Africa are scarce. The objective of this study was to identify parish-level social factors associated with cervical cancer incidence in the Kampala Cancer Registry catchment area, using a novel linkage between population-based cancer registry data and small-area census data from Uganda. Methods: Kampala Cancer Registry cervical cancer records (2008–15) were augmented to add the parish of residence at diagnosis. Parish-level population and housing profile data (2014) were obtained from the Uganda Bureau of Statistics and linked to Kampala Cancer Registry records. Stepwise forward Poisson regression modelling was used to estimate incidence ratios (IR) assessing associations between social factors and incidence. Housing tenure, infrastructure, gender equality, economic status, and employment were examined, controlling for population density. The significance level was set at α=0·05. Findings: Factors related to higher incidence included a higher girl-to-boy ratio of 6–12-year-olds not attending school (IR 1·33 [95% CI 1·15–1·54]; p