Spatial Patterning of Spontaneous and Medically Indicated Preterm Birth in Philadelphia.

Preterm birth (PTB) remains a key public health issue that disproportionately affects Black individuals. Since spontaneous PTB (sPTB) and medically indicated PTB (mPTB) may have different causes and interventions, we quantified racial disparities for sPTB and mPTB, and we characterized the geographic patterning of these phenotypes, overall and according to race/ethnicity. We examined a pregnancy cohort of 83,952 singleton births at 2 Philadelphia hospitals from 2008-2020, and classified each PTB as sPTB or mPTB. We used binomial regression to quantify the magnitude of racial disparities between non-Hispanic Black and non-Hispanic White individuals, then generated small area estimates by applying a Bayesian model that accounts for small numbers and smooths estimates of PTB risk by borrowing information from neighboring areas. Racial disparities in both sPTB and mPTB were significant (relative risk of sPTB = 1.83, 95% confidence interval: 1.70, 1.98; relative risk of mPTB = 2.20, 95% confidence interval: 2.00, 2.42). The disparity was 20% greater in mPTB than sPTB. There was substantial geographic variation in PTB, sPTB, and mPTB risks and racial disparity. Our findings underscore the importance of distinguishing PTB phenotypes within the context of public health and preventive medicine. Future work should consider social and environmental exposures that may explain geographic differences in PTB risk and disparities.

Do neighborhood attributes moderate the relationship between alcohol establishment density and crime?

Although numerous studies have found a positive association between the density of alcohol establishments and various types of crime, few have examined how neighborhood attributes (e.g., schools, parks) could moderate this association. We used data from Minneapolis, MN with neighborhood as the unit of analysis (n = 83). We examined eight types of crime (assault, rape, robbery, vandalism, nuisance crime, public alcohol consumption, driving while intoxicated, underage alcohol possession/consumption) and measured density as the total number of establishments per roadway mile. Neighborhood attributes assessed as potential moderators included non-alcohol businesses, schools, parks, religious institutions, neighborhood activism, neighborhood quality, and number of condemned houses. Using Bayesian techniques, we created a model for each crime outcome (accounting for spatial auto-correlation and controlling for relevant demographics) with an interaction term (moderator × density) to test each potential moderating effect. Few interaction terms were statistically significant. The presence of at least one college was the only neighborhood attribute that consistently moderated the density-crime association, with the presence of a college attenuating the association between the density and three types of crime (assaults, nuisance crime, and public consumption). However, caution should be used when interpreting the moderating effect of college presence because of the small number of colleges in our sample. The lack of moderating effects of neighborhood attributes, except for presence of a college, suggests that the addition of alcohol establishments to any neighborhood, regardless of its other attributes, could result in an increase in a wide range of crime.

The association between density of alcohol establishments and violent crime within urban neighborhoods.

BACKGROUND: Numerous studies have found that areas with higher alcohol establishment density are more likely to have higher violent crime rates, but many of these studies did not assess the differential effects of type of establishments or the effects on multiple categories of crime. In this study, we assess whether alcohol establishment density is associated with 4 categories of violent crime and whether the strength of the associations varies by type of violent crime and by on-premise establishments (e.g., bars, restaurants) versus off-premise establishments (e.g., liquor and convenience stores). METHODS: Data come from the city of Minneapolis, Minnesota in 2009 and were aggregated and analyzed at the neighborhood level. Across the 83 neighborhoods in Minneapolis, we examined 4 categories of violent crime: assault, rape, robbery, and total violent crime. We used a Bayesian hierarchical inference approach to model the data, accounting for spatial auto-correlation and controlling for relevant neighborhood demographics. Models were estimated for total alcohol establishment density as well as separately for on-premise establishments and off-premise establishments. RESULTS: Positive, statistically significant associations were observed for total alcohol establishment density and each of the violent crime outcomes. We estimate that a 3.9 to 4.3% increase across crime categories would result from a 20% increase in neighborhood establishment density. The associations between on-premise density and each of the individual violent crime outcomes were also all positive and significant and similar in strength as for total establishment density. The relationships between off-premise density and the crime outcomes were all positive but not significant for rape or total violent crime, and the strength of the associations was weaker than those for total and on-premise density. CONCLUSIONS: Results of this study, combined with earlier findings, provide more evidence that community leaders should be cautious about increasing the density of alcohol establishments within their neighborhoods.

Is the density of alcohol establishments related to nonviolent crime?

OBJECTIVE: We examined the associations between the density of alcohol establishments and five types of nonviolent crime across urban neighborhoods. METHOD: Data from the city of Minneapolis, MN, in 2009 were aggregated and analyzed at the neighborhood level. We examined the association between alcohol establishment density and five categories of nonviolent crime: vandalism, nuisance crime, public alcohol consumption, driving while intoxicated, and underage alcohol possession/consumption. A Bayesian approach was used for model estimation accounting for spatial auto-correlation and controlling for relevant neighborhood demographics. Models were estimated for total alcohol establishment density and then separately for off-premise establishments (e.g., liquor and convenience stores) and on-premise establishments (e.g., bars and restaurants). RESULTS: We found positive associations between density and each crime category. The association was strongest for public consumption and weakest for vandalism. We estimated that a 3.3%-10.9% increase across crime categories would result from a 20% increase in neighborhood establishment density. Similar results were seen for on- and off-premise establishments, although the strength of the associations was lower for off-premise density. CONCLUSIONS: Our results indicate that communities should consider the potential increase in nonviolent crime associated with an increase in the number of alcohol establishments within neighborhoods.