Neighborhoods, Racism, Stress, and Preterm Birth Among African American Women: A Review

African American women are more likely to experience preterm birth (<37 completed weeks gestation) compared with White women. African American women are also more likely to live in neighborhoods characterized as disadvantaged (i.e., exhibiting higher rates of vacant housing, poorer property conditions, and more litter and crime) and to experience racial discrimination compared with White women. These chronic stressors have been related to preterm birth (PTB) among African American women. This review focuses on potential stress-related pathways by which neighborhood disadvantage and racial discrimination increase the risk for PTB among African American women. Specifically, we propose cortisol, systemic inflammation, proteome and lipidome profiles, and telomere shortening as potential mediators linking these social determinants of health with PTB among African American women. Examination of these factors and the signaling pathways they contribute to will increase our knowledge of the effects of social determinants of health on PTB for African American women.

Neighborhood Inequities in Tobacco Retailer Density and the Presence of Tobacco-Selling Pharmacies and Tobacco Shops

Studies document inequitable tobacco retailer density by neighborhood sociodemographics, but these findings may not be robust to different density measures. Policies to reduce density may be less equitable depending on how the presence of store types differs by neighborhood characteristics. We built a 2018 list of probable tobacco retailers in the United States and calculated four measures of density for all census tracts ( N = 71,495), including total count, and number of retailers per 1,000 people, square mile, and kilometers of roadway. We fit multivariable regression models testing associations between each density measure and tract-level sociodemographics. We fit logistic regression models testing associations between sociodemographics and the presence of a tobacco-selling pharmacy or tobacco shop. Across all measures, tracts with a greater percentage of residents living below 150% of the federal poverty level (FPL) had higher density. A higher percentage of Black residents, Hispanic or Latino residents, and vacant housing was inconsistently associated with density across measures. Neighborhoods with a greater percentage of Black residents had a lower odds of having a pharmacy (adjusted odds ratio [a OR] = 0.96, 95% confidence interval [CI; 0.95, 0.97]) and tobacco shop (a OR = 0.87, CI [0.86, 0.89]), while those with a greater percentage of residents living below 150% FPL had greater odds of having a tobacco shop (a OR = 1.18, CI [1.16, 1.20]). Researchers and policymakers should consider how various measures of retailer density may capture different aspects of the environment. Furthermore, there may be an inequitable impact of retailer-specific policies on tobacco availability.

Medium-sized cities in decline in France: between urban shrinkage and city centre devitalisation

Since the end of the 2000s, the question of the decline of French medium-sized towns has become central within the scientific and public debate. More specifically, two processes are underlined: the devitalisation of city centres on the one hand, and urban shrinkage on the other hand. The devitalisation of city centres has been studied in several institutional reports. It is characterised by high rates of vacant housing and high street shops vacancies, a fall in visits to the city centre, an impoverishment of residents and population losses. In geography, urban studies and planning, the dynamics of urban shrinkage have been discussed since the 1990s. They comprise a multidimensional urban crisis, triggered and characterised by job and population losses. This paper attempts to explore the relationships between these processes by underlining their similarities and differences with data analysis and multivariate clustering methods. By comparing medium-sized cities with small and large cities, the specificities of urban decline in medium-sized cities are explored. It appears that cities are not homogeneously affected by urban decline. More particularly, a large number of weakened medium-sized cities display a distinctive feature: markers of decline are concentrated in their urban core.

A Census Tract–Level Examination of Differences in Social Determinants of Health Among People With HIV, by Race/Ethnicity and Geography, United States and Puerto Rico, 2017

Objective Social and structural factors, referred to as social determinants of health (SDH), create pathways or barriers to equitable sexual health, and information on these factors can provide critical insight into rates of diseases such as HIV. Our objectives were to describe and identify differences, by race/ethnicity and geography, in SDH among adults with HIV. Methods We conducted an ecological study to explore SDH among people with HIV diagnosed in 2017, by race/ethnicity and geography, at the census-tract level in the United States and Puerto Rico. We defined the least favorable SDH as the following: low income (<$40 000 in median annual household income), low levels of education (≥18% of residents have <high school diploma), high levels of poverty (≥19% of residents live below the federal poverty level), unemployment (≥6% of residents in the workface do not have a job), lack of health insurance (≥16% of residents lack health insurance), and vacant housing (≥15% of housing units are vacant). Results HIV diagnosis rates increased 1.4 to 4.0 times among men and 1.5 to 5.5 times among women as census-tract poverty levels increased, education levels decreased, income decreased, unemployment increased, lack of health insurance increased, and vacant housing increased. Among racial/ethnic groups by region and SDH, we observed higher HIV diagnosis rates per 100 000 population among non-Hispanic Black (49.6) and non-Hispanic White (6.5) adults in the South and among Hispanic/Latino (27.4) adults in the Northeast than in other regions. We observed higher HIV diagnosis rates per 100 000 population among non-Hispanic Black (44.3) and Hispanic/Latino (21.1) adults than among non-Hispanic White (5.1) adults. Conclusion Our findings highlight the importance of SDH in HIV infection and support the need for effective, targeted local interventions to specific populations based on HIV diagnoses and prevalence to prevent infection and reduce racial/ethnic disparities.

LEARNING GEOGRAPHICAL DISTRIBUTION OF VACANT HOUSES USING CLOSED MUNICIPAL DATA: A CASE STUDY OF WAKAYAMA CITY, JAPAN

Vacant housing detection is an urgent problem that needs to be addressed. It is also a suitable example to promote utilisation of smart data that are stored in municipalities. This study proposes a vacant housing detection model that uses closed municipal data and considers accelerating the use of public data to promote smart cities. Employing a machine learning technique, this study ensures high predictive power for vacant housing detection. The model enables us to handle complex municipal data that include non-linear feature characteristics and substantial missing data. In particular, handling missing data is important in the practical use of closed municipal data because not all of the data are necessarily absorbed to a building unit. Consequently, the model in this analysis showed that the accuracy and false positive rate are 95.4 percent and 3.7 percent, respectively, which are high enough to detect vacant houses. However, the true positive rate is 77.0 percent. Although the rate is not low to some extent, selection of features and further collection of extra samples may improve the rate. Geographic distribution of vacant houses further enabled us to check the difference between the actual and estimated number of vacant houses, and more than 80 percent of 500-meter grid data are with below 10 errors, which we think, provides city planners with informative data to roughly grasp geographical tendencies.

Fixing Up after Tearing Down: The Impact of Demolitions on Residential Investment

Does the presence of deteriorating housing affect nearby property owner’s decision to maintain their units? Does demolishing these distressed houses increase nearby homeowner’s maintenance investment? In this paper, I examine these questions by testing whether exposure to targeted demolitions of abandoned and distressed housing affects changes in the external condition of nearby houses. Using two waves of a property inventory in Cleveland, Ohio, my models suggest that, compared with a control group of houses located near vacant housing, proximity to demolitions decreases the likelihood that a property’s condition deteriorated between 2015 and 2018 and increases the likelihood that it improved.