Journal of Urban Health最新文献

Research on retail food environment (RFE) relies on data availability and accuracy. However, the discrepancies in RFE datasets may lead to imprecision when measuring association with health outcomes. In this research, we present a two-tier hierarchical point of interest (POI) matching framework to compare and triangulate food outlets across multiple geospatial data sources. Two matching parameters were used including the geodesic distance between businesses and the similarity of business names according to Levenshtein distance (LD) and Double Metaphone (DM). Sensitivity analysis was conducted to determine thresholds of matching parameters. Our Tier 1 matching used more restricted parameters to generate high confidence-matched POIs, whereas in Tier 2 we opted for relaxed matching parameters and applied a weighted multi-attribute model on the previously unmatched records. Our case study in San Diego County, California used government, commercial, and crowdsourced data and returned 20.2% matched records from Tier 1 and 18.6% matched from Tier 2. Our manual validation shows a 100% matching rate for Tier 1 and up to 30.6% for Tier 2. Matched and unmatched records from Tier 1 were further analyzed for spatial patterns and categorical differences. Our hierarchical POI matching framework generated highly confident food POIs by conflating datasets and identified some food POIs that are unique to specific data sources. Triangulating RFE data can reduce uncertain and invalid POI listings when representing food environment using multiple data sources. Studies investigating associations between food environment and health outcomes may benefit from improved quality of RFE.

The goal of this study was to examine the effects of racial discrimination, depression, and Black LGBTQ community support on HIV care outcomes among a sample of Black sexually minoritized men living with HIV. We conducted a cross-sectional survey with 107 Black sexually minoritized men living with HIV in Chicago. A path model was used to test associations between racial discrimination, Black LGBTQ community support, depressive symptoms, and missed antiretroviral medication doses and HIV care appointments. Results of the path model showed that men who had experienced more racism had more depressive symptoms and subsequently, missed more doses of HIV antiretroviral medication and had missed more HIV care appointments. Greater Black LGBTQ community support was associated with fewer missed HIV care appointments in the past year. This research shows that anti-Black racism may be a pervasive and harmful determinant of HIV inequities and a critical driver of racial disparities in ART adherence and HIV care engagement experienced by Black SMM. Black LGBTQ community support may buffer against the effects of racial discrimination on HIV care outcomes by providing safe, inclusive, supportive spaces for Black SMM.

Neighborhood deprivation indices are widely used in research, but the performance of these indices has rarely been directly compared in the same analysis. We examined the Area Deprivation Index, Neighborhood Deprivation Index, and Yost index, and compared their associations with breast cancer mortality. Indices were constructed for Georgia census block groups using 2011–2015 American Community Survey data. Pearson correlation coefficients and percent agreement were calculated. Associations between each index and breast cancer mortality were estimated among 36,795 women diagnosed with breast cancer using Cox proportional hazards regression. The indices were strongly correlated (absolute value of correlation coefficients > 0.77), exhibited moderate (41.4%) agreement, and were similarly associated with a 36% increase in breast cancer mortality. The similar associations with breast cancer mortality suggest the indices measure the same underlying construct, despite only moderate agreement. By understanding their correlations, agreement, and associations with health outcomes, researchers can choose the most appropriate index for analysis.

This scoping review of the literature explores the following question: what systematic measures are needed to achieve a healthy city? The World Health Organization (WHO) suggests 11 characteristics of a healthy city. Measures contributing to these characteristics are extracted and classified into 29 themes. Implementation of some of these measures is illustrated by examples from Freiburg, Greater Vancouver, Singapore, Seattle, New York City, London, Nantes, Exeter, Copenhagen, and Washington, DC. The identified measures and examples indicate that a healthy city is a system of healthy sectors. A discussion section suggests healthy directions for nine sectors in a healthy city. These sectors include transportation, housing, schools, city planning, local government, environmental management, retail, heritage, and healthcare. Future work is advised to put more focus on characteristic 5 (i.e., the meeting of basic needs for all the city's people) and characteristic 10 (i.e., public health and sick care services accessible to all) of a healthy city.

Rapid urbanization is likely to be associated with suboptimal access to essential health services. This is especially true in cities from sub-Saharan Africa (SSA), where urbanization is outpacing improvements in infrastructure. We assessed the current situation in regard to several markers of maternal, newborn, and child health, including indicators of coverage of health interventions (demand for family planning satisfied with modern methods, at least four antenatal care visits (ANC4+), institutional birth, and three doses of DPT vaccine[diphtheria, pertussis and tetanus]) and health status (stunting in children under 5 years, neonatal and under-5 mortality rates) among the poor and non-poor in the most populous cities from 38 SSA countries. We analyzed 136 population-based surveys (year range 2000–2019), contrasting the poorest 40% of households (referred to as poor) with the richest 60% (non-poor). Coverage in the most recent survey was higher for the city non-poor compared to the poor for all interventions in virtually all cities, with the largest median gap observed for ANC4+ (13.5 percentage points higher for the non-poor). Stunting, neonatal, and under-5 mortality rates were higher among the poor (7.6 percentage points, 21.2 and 10.3 deaths per 1000 live births, respectively). The gaps in coverage between the two groups were reducing, except for ANC4, with similar median average annual rate of change in both groups. Similar rates of change were also observed for stunting and the mortality indicators. Continuation of these positive trends is needed to eliminate inequalities in essential health services and child survival in SSA cities.

Empirical analyses have demonstrated that individuals exposed to severe air pollution in utero have worse health outcomes during childhood. However, there is little evidence on the long-term health impacts of air pollution exposure. The objective of this paper is to estimate the effect of in utero exposure to the Great London Smog of 1952 (GLS) on five health outcomes identified through a scoping review to be those most likely affected: respiratory, circulatory, neoplasms, mental health, and nervous system conditions. We use the GLS, an extreme air pollution event in December 1952, as a quasi-natural experiment to estimate the effect of exposure to air pollution in utero on adulthood health. Data from the UK Biobank is analysed for a cohort of participants born from December 1952 to July 1956. Differences in health outcomes between adults exposed and not exposed to the GLS due to their birth dates, born inside and outside London, were explored. Our primary focus is hospitalization events between 1997 and 2020 (corresponding to ages 40 to 69), as recorded in linked administrative data from the National Health Service (NHS). Specifically, the five primary outcomes are binary variables indicating that the individual had at least one hospitalization where the main cause of hospitalization is related to respiratory, circulatory, neoplasms, mental health, or nervous system conditions. The analytical sample comprised 36,281 individuals. A positive effect on adulthood hospitalizations due to respiratory conditions was observed. If exposed to the GLS in utero, the probability of at least one respiratory health-related hospitalization between 1997 and 2020 increased by 2.58 percentage points (95% CI 0.08, 4.30, p = 0.03), a 23% increase relative to the sample mean. Small effects were found for all other outcomes, suggesting that these conditions were not affected by the GLS. We do not find heterogeneous effects by sex or childhood socioeconomic status. This study found that a 5-day pollution exposure event while in utero significantly increased respiratory-related hospitalizations at ages 40 to 69 but had no impact on hospitalizations due to circulatory, neoplasms, mental health, and nervous system conditions.