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1.
Appl Geogr ; 152: 102876, 2023 Mar.
Article in English | MEDLINE | ID: mdl-36686332

ABSTRACT

Extreme heat is a major health hazard that is exacerbated by ongoing human-caused climate change. However, how populations perceive the risks of heat in the context of other hazards like COVID-19, and how perceptions vary geographically, are not well understood. Here we present spatially explicit estimates of worry among the U.S. public about the risks of heat and COVID-19 during the summer of 2020, using nationally representative survey data and a multilevel regression and poststratification (MRP) model. Worry about extreme heat and COVID-19 varies both across states and across demographic groups, in ways that reflect disparities in the impact of each risk. Black or African American and Hispanic or Latino populations, who face greater health impacts from both COVID-19 and extreme heat due to institutional and societal inequalities, also tend to be much more worried about both risks than white, non-Hispanic populations. Worry about heat and COVID-19 were correlated at the individual and population level, and patterns tended to be related to underlying external factors associated with the risk environment. In the face of a changing climate there is an urgent need to address disparities in heat risk and develop responses that ensure the most at-risk populations are protected.

2.
Environ Health Perspect ; 128(12): 127007, 2020 12.
Article in English | MEDLINE | ID: mdl-33300819

ABSTRACT

BACKGROUND: Despite the substantial role indoor exposure has played in heat wave-related mortality, few epidemiological studies have examined the health effects of exposure to indoor heat. As a result, knowledge gaps regarding indoor heat-health thresholds, vulnerability, and adaptive capacity persist. OBJECTIVE: We evaluated the role of indoor heat exposure on mortality and morbidity among the elderly (≥65 years of age) in Houston, Texas. METHODS: Mortality and emergency hospital admission data were obtained through the Texas Department of State Health Services. Summer indoor heat exposure was modeled at the U.S. Census block group (CBG) level using building energy models, outdoor weather data, and building characteristic data. Indoor heat-health associations were examined using time-stratified case-crossover models, controlling for temporal trends and meteorology, and matching on CBG of residence, year, month, and weekday of the adverse health event. Separate models were fitted for three indoor exposure metrics, for individual lag days 0-6, and for 3-d moving averages (lag 0-2). Effect measure modification was explored via stratification on individual- and area-level vulnerability factors. RESULTS: We estimated positive associations between short-term changes in indoor heat exposure and cause-specific mortality and morbidity [e.g., circulatory deaths, odds ratio per 5°C increase=1.16 (95% CI: 1.03, 1.30)]. Associations were generally positive for earlier lag periods and weaker across later lag periods. Stratified analyses suggest stronger associations between indoor heat and emergency hospital admissions among African Americans compared with Whites. DISCUSSION: Findings suggest excess mortality among certain elderly populations in Houston who are likely exposed to high indoor heat. We developed a novel methodology to estimate indoor heat exposure that can be adapted to other U.S. LOCATIONS: In locations with high air conditioning prevalence, simplified modeling approaches may adequately account for indoor heat exposure in vulnerable neighborhoods. Accounting for indoor heat exposure may improve the estimation of the total impact of heat on health. https://doi.org/10.1289/EHP6340.


Subject(s)
Environmental Exposure/statistics & numerical data , Heat-Shock Response , Hot Temperature , Aged , Aged, 80 and over , Female , Hospitalization/statistics & numerical data , Humans , Male , Mortality/trends , Texas
3.
Sci Total Environ ; 660: 715-723, 2019 Apr 10.
Article in English | MEDLINE | ID: mdl-30743957

ABSTRACT

Urban growth and climate change will exacerbate extreme heat events and air pollution, posing considerable health challenges to urban populations. Although epidemiological studies have shown associations between health outcomes and exposures to ambient air pollution and extreme heat, the degree to which indoor exposures and social and behavioral factors may confound or modify these observed effects remains underexplored. To address this knowledge gap, we explore the linkages between vulnerability science and epidemiological conceptualizations of risk to propose a conceptual and analytical framework for characterizing current and future health risks to air pollution and extreme heat, indoors and outdoors. Our framework offers guidance for research on climatic variability, population vulnerability, the built environment, and health effects by illustrating how health data, spatially resolved ambient data, estimates of indoor conditions, and household-level vulnerability data can be integrated into an epidemiological model. We also describe an approach for characterizing population adaptive capacity and indoor exposure for use in population-based epidemiological models. Our framework and methods represent novel resources for the evaluation of health risks from extreme heat and air pollution, both indoors and outdoors.


Subject(s)
Air Pollution, Indoor/statistics & numerical data , Environmental Exposure/statistics & numerical data , Hot Temperature , Air Pollution , Cities , Climate Change , Humans , Urban Health , Urban Population
4.
Sci Total Environ ; 655: 1-12, 2019 Mar 10.
Article in English | MEDLINE | ID: mdl-30469055

ABSTRACT

Urban populations are typically subject to higher outdoor heat exposure than nearby rural areas due to the urban heat island (UHI) effect. Excessive Heat Events (EHEs) further amplify heat stress imposed on city dwellers. Heat exposure largely depends on the spatial and temporal distribution of temperature and population, however, few studies considered their concurrent variations. To better characterize exposure to heat in the context of long-term urban climatology and during excessive heat events, this study focuses on the dynamics of ambient temperature and population and proposes an open-data-based approach for spatiotemporal analysis of urban exposure to heat by using air temperature estimated from satellite observations and commute-adjusted diurnal population calculated primarily on the Census Transportation Planning Products. We use the metropolitan area of Chicago, U.S.A. as a case study to analyze the urban heat pattern changes during EHEs and their influence on population heat exposure diurnally. The intra-urban spatiotemporal analysis reveals that the population's exposure to heat changes fast as the nighttime temperature increases and the EHEs increase the spatial exposure impact due to the ubiquitous higher nocturnal temperature over the Chicago metropolitan area. "Hotspots" associated with a higher temperature and greater number of urban residents are identified in the heat exposure map. Meanwhile, the spatial extent of high ambient exposure areas varies diurnally. Our study contributes to a better understanding of the dynamic heat exposure patterns in urban areas. The approaches presented in this article can be used for informing heat mitigation as well as emergency response strategies at specific times and locations.


Subject(s)
Climate Change , Environmental Monitoring/methods , Heat Stress Disorders , Heat-Shock Response , Urban Population/trends , Chicago , Heat Stress Disorders/epidemiology , Heat Stress Disorders/prevention & control , Hot Temperature , Humans , Satellite Imagery , Spatio-Temporal Analysis
5.
Spat Spatiotemporal Epidemiol ; 8: 23-33, 2014 Apr.
Article in English | MEDLINE | ID: mdl-24606992

ABSTRACT

Identifying and characterizing urban vulnerability to heat is a key step in designing intervention strategies to combat negative consequences of extreme heat on human health. This study combines excess non-accidental mortality counts, numerical weather simulations, US Census and parcel data into an assessment of vulnerability to heat in Houston, Texas. Specifically, a hierarchical model with spatially varying coefficients is used to account for differences in vulnerability among census block groups. Socio-economic and demographic variables from census and parcel data are selected via a forward selection algorithm where at each step the remaining variables are orthogonalized with respect to the chosen variables to account for collinearity. Daily minimum temperatures and composite heat indices (e.g. discomfort index) provide a better model fit than other ambient temperature measurements (e.g. maximum temperature, relative humidity). Positive interactions between elderly populations and heat exposure were found suggesting these populations are more responsive to increases in heat.


Subject(s)
Heat Stress Disorders , Hot Temperature/adverse effects , Urban Population/statistics & numerical data , Age Factors , Environmental Exposure/adverse effects , Environmental Exposure/statistics & numerical data , Heat Stress Disorders/etiology , Heat Stress Disorders/mortality , Humans , Models, Statistical , Risk Assessment , Risk Factors , Socioeconomic Factors , Spatio-Temporal Analysis , Texas/epidemiology
6.
Health Place ; 17(2): 498-507, 2011 Mar.
Article in English | MEDLINE | ID: mdl-21216652

ABSTRACT

Extreme heat is an important weather hazard associated with excess mortality and morbidity. We determine the relative importance of heat exposure and the built environment, socioeconomic vulnerability, and neighborhood stability for heat mortality (Philadelphia, PA, USA) or heat distress (Phoenix, AZ, USA), using an ecologic study design. We use spatial Generalized Linear and Mixed Models to account for non-independence (spatial autocorrelation) between neighboring census block groups. Failing to account for spatial autocorrelation can provide misleading statistical results. Phoenix neighborhoods with more heat exposure, Black, Hispanic, linguistically and socially isolated residents, and vacant households made more heat distress calls. Philadelphia heat mortality neighborhoods were more likely to have low housing values and a higher proportion of Black residents. Our methodology can identify important risk factors and geographic areas to target interventions.


Subject(s)
Environmental Exposure , Extreme Heat , Heat Stress Disorders/mortality , Residence Characteristics , Vulnerable Populations , Arizona/epidemiology , Climate , Heat Stress Disorders/prevention & control , Housing , Humans , Linear Models , Philadelphia/epidemiology , ROC Curve , Risk Factors , Socioeconomic Factors , Urban Population
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