Poor housing conditions and evictions are both associated with poor physical and mental health outcomes, such as increased risks for cardiovascular disease, depression, and injuries. However, the relationship between these two negative housing outcomes has received little quantitative study, including in public housing where exposure to these factors and to negative health outcomes are elevated. We therefore sought to examine the relationship between evictions and formal housing safety inspections triggered by tenant complains about poor conditions. We estimated a hierarchical logistic regression model assessing associations between housing quality inspections and evictions using data from January 2017 and March 2020 on 3,746 residential buildings within 299 New York City Housing Authority (NYCHA) developments, adjusting for development size, funding type, and area-level social vulnerability indicators. The average Social Vulnerability Index percentile for the buildings included in this study was 0.90 (SD = 0.12), indicating that these buildings were in areas with greater social vulnerability than 90% of other census tracts in the state. Adjusted predicted probabilities of an eviction increased from 34 to 43% in the presence of a rodent inspection and from 34 to 46% in the presence of an indoor environmental inspection (p < 0.001 for both), indicating that inspections for unsafe housing conditions were associated with evictions at the building level. Substandard housing quality and evictions are important public health concerns. Policies to enhance protections for tenants against both of these social ills simultaneously may be needed to improve community health outcomes.
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http://dx.doi.org/10.1007/s10900-022-01114-3 | DOI Listing |
Nat Med
January 2025
Environment & Health Modelling (EHM) Lab, Department of Public Health Environment & Society, London School of Hygiene & Tropical Medicine, London, UK.
Previous health impact assessments of temperature-related mortality in Europe indicated that the mortality burden attributable to cold is much larger than for heat. Questions remain as to whether climate change can result in a net decrease in temperature-related mortality. In this study, we estimated how climate change could affect future heat-related and cold-related mortality in 854 European urban areas, under several climate, demographic and adaptation scenarios.
View Article and Find Full Text PDFGeospat Health
January 2025
Environmental Agenda, Universidad Autónoma de San Luis Potosí, San Luis Potosí.
This study aimed to estimate a socio-spatial vulnerability index for type 2 diabetes mellitus (T2DM) at the municipal level in Mexico for 2020. It incorporated factors such as poverty, social backwardness, marginalization index, and human development index. This retrospective ecological study analyzed 317,011 incident cases of T2DM in 2020.
View Article and Find Full Text PDFPlant Cell Environ
January 2025
CREAF, Cerdanyola del Vallès, Barcelona (Catalonia), Spain.
Water storage capacity and capacitance in trees regulate hydration levels, providing water reserves during drought. However, the effects of varying traits, tissue fractions and of different water pools on the allometry of branch-/sample-level properties have not been systematically investigated. We analyse the relationships between branch size and branch capacity and capacitance with respect to wood density, xylem vulnerability to embolism, and tissue fractions.
View Article and Find Full Text PDFCities
February 2025
Department of Geography & Environmental Studies, University of New Mexico, Albuquerque, New Mexico, 87131, USA.
Historical redlining practices in the United States date back to the 1930s and have continued to impact cities socially, environmentally, and economically since then. This study explores current social vulnerability inequity among former HOLC (Home Owners' Loan Corporation) neighborhoods with four color-coded grades in 196 U.S.
View Article and Find Full Text PDFEnviron Res
January 2025
Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Air-pollution monitoring is sparse across most of the United States, so geostatistical models are important for reconstructing concentrations of fine particulate air pollution (PM) for use in health studies. We present XGBoost-IDW Synthesis (XIS), a daily high-resolution PM machine-learning model covering the contiguous US from 2003 through 2023. XIS uses aerosol optical depth from satellites and a parsimonious set of additional predictors to make predictions at arbitrary points, capturing near-roadway gradients and allowing the estimation of address-level exposures.
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