Gaps and linkages between biometeorological research across the Global South: a call for new efforts to advance biometeorology in the Global South.

Biometeorology research continues to grow and accelerate in terms of productivity (papers produced, studies conducted, etc.) as well as its direct impact on society and policy. Simultaneously, the scientific community is increasingly acknowledging that research has predominantly focused on the Global North. Additionally, work conducted in the Global South often follows extractive practices that primarily advance the careers and scientific knowledge of researchers from the Global North, offering minimal benefit to the communities studied in the Global South. This short communication intends to serve as a call to the biometeorology community to work collaboratively across continents to understand the current knowledge of biometeorology research in the Global South in addition to identifying the gaps, challenges, and opportunities of conducting grounded research in the Global South led by Global South researchers to support societies equitably.

Sociodemographic Determinants of Extreme Heat and Ozone Risk Among Older Adults in 3 Sun Belt Cities.

BACKGROUND: Vulnerable populations across the United States are frequently exposed to extreme heat, which is becoming more intense due to a combination of climate change and urban-induced warming. Extreme heat can be particularly detrimental to the health and well-being of older citizens when it is combined with ozone. Although population-based studies have demonstrated associations between ozone, extreme heat, and human health, few studies focused on the role of social and behavioral factors that increase indoor risk and exposure among older adults. METHODS: We conducted a household survey that aimed to understand how older adults are affected by extreme heat and ozone pollution inside and outside of their homes across Houston, Phoenix, and Los Angeles. We examine contributing factors to the risk of self-reported health effects using a generalized linear mixed-effects regression model of telephone survey data of 909 older adults in 2017. RESULTS: We found an increased occurrence of self-reported symptoms for extreme heat with preexisting respiratory health conditions and a lack of air conditioning access; self-reported ozone symptoms were more likely with preexisting respiratory health conditions. The risk of heat-related symptoms was slightly higher in Los Angeles than Houston and Phoenix. We found several demographic, housing, and behavioral characteristics that influenced the risk of heat- and ozone-related symptoms. CONCLUSIONS: The increased risk among older adults based on specific social and behavioral factors identified in this study can inform public health policy and help cities tailor their heat and ozone response plans to the specific needs of this vulnerable population.

Mental health and air temperature: Attributable risk analysis for schizophrenia hospital admissions in arid urban climates.

Health researchers have examined the physiological impacts of extreme air temperature on the human body. Yet, the mental health impacts of temperature have been understudied. Research has shown that the environment can create circumstances that exacerbate mental health issues. This may be particularly challenging for some of the fastest growing cities, located in hot, dry climates. Given the theoretical relationship between air temperature and mental health, we seek to measure the association between temperature and schizophrenia hospital admissions in an arid urban climate and quantify the associated public health burden. We collected 86,672 hospitalization records for schizophrenia from 2006 to 2014 in Maricopa County, Arizona, USA. Using a distributed lag non-linear model (DLNM), we tested for a statistical association between temperature and schizophrenia hospital admissions after controlling for year, season, weekends, and holidays. We calculated the cumulative attributable risk of nighttime temperature on schizophrenia for the entire dataset as well as among demographic subgroups. The relative risk of schizophrenia hospital admissions increased with both high and low temperatures. Statistical models using daily minimum temperature were more strongly associated with hospitalization than those using mean or maximum. Schizophrenia hospital admissions increased on days with minimum temperatures above 30 °C and below 3 °C, with some subgroups experiencing higher rates of hospitalization. The total fraction of schizophrenia hospital admissions attributable to non-optimal minimum temperature is 3.45 % (CI: -4.91-10.80 %) and high minimum temperature is 0.28 % (CI: -1.18-1.78 %). We found that non-whites and males appear to be at a slightly increased risk than the general population, although there did not appear to be a statistically significant difference. A conservative estimate of healthcare costs annually from non-optimal temperature attributed schizophrenia hospitalization is $1.95 million USD. Therefore, nighttime cooling strategies and efforts could increase the accessibility of shelters to reduce overnight exposure to extreme air temperature.

A Case-Crossover Analysis of Indoor Heat Exposure on Mortality and Hospitalizations among the Elderly in Houston, Texas.

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.

Validation of seasonal mean radiant temperature simulations in hot arid urban climates.

We validated seasonal RayMan and ENVI-met mean radiant temperature (TMRT) simulations to assess model performance in a sensitivity analysis from cold to extremely hot conditions. Human-biometeorological validation data were collected in Tempe, Arizona via transects during five field campaigns between 2014 and 2017. Transects were conducted across seven locations in two to three-hour intervals from 6:00 to 23:00 LST with a Kestrel meter and thermal camera (2014-2015) and the mobile instrument platform MaRTy (2017). Observations across diverse urban forms, sky view factors, and seasons covered a wide range of solar radiation regimes from a minimum TMRT of 8.7 °C to a maximum of 84.9 °C. Both models produced large simulation errors across regimes with RMSE ranging from 8 °C to 12 °C (RayMan) and 11.2 °C to 16.1 °C (ENVI-met), exceeding a suggested TMRT accuracy of ±5 °C for heat stress studies. RayMan model errors were largest for engineered enclosed spaces, complex urban forms, and extreme heat conditions. ENVI-met was unable to resolve intra-domain spatial variability of TMRT and exhibited large errors with RMSE up to 25.5 °C for engineered shade. Both models failed to accurately simulate TMRT for hot conditions. Errors varied seasonally with overestimated TMRT in the summer and underestimated TMRT in the winter and shoulder seasons. Results demonstrate that models should not be used under micrometeorological or morphological extremes without in-situ validation to quantify errors and assess directional bias due to model limitations.

Urban heat and air pollution: A framework for integrating population vulnerability and indoor exposure in health risk analyses.

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.