How Blackouts during Heat Waves Amplify Mortality and Morbidity Risk.

The recent concurrence of electrical grid failure events in time with extreme temperatures is compounding the population health risks of extreme weather episodes. Here, we combine simulated heat exposure data during historical heat wave events in three large U.S. cities to assess the degree to which heat-related mortality and morbidity change in response to a concurrent electrical grid failure event. We develop a novel approach to estimating individually experienced temperature to approximate how personal-level heat exposure changes on an hourly basis, accounting for both outdoor and building-interior exposures. We find the concurrence of a multiday blackout event with heat wave conditions to more than double the estimated rate of heat-related mortality across all three cities, and to require medical attention for between 3% (Atlanta) and more than 50% (Phoenix) of the total urban population in present and future time periods. Our results highlight the need for enhanced electrical grid resilience and support a more spatially expansive use of tree canopy and high albedo roofing materials to lessen heat exposures during compound climate and infrastructure failure events.

Indoor apparent temperature, cognition, and daytime sleepiness among low-income adults in a temperate climate.

The burden of temperature-associated mortality and hospital visits is significant, but temperature's effects on non-emergency health outcomes is less clear. This burden is potentially greater in low-income households unable to afford efficient heating and cooling. We examined short-term associations between indoor temperatures and cognitive function and daytime sleepiness in low-income residents of Detroit, Michigan. Apparent temperature (AT, based on temperature and humidity) was recorded hourly in 34 participant homes between July 2019-March 2020. Between July-October 2019, 18 participants were administered word list immediate (WLL) and delayed (WLD) recall tests (10-point scales) and the Epworth Sleepiness Scale (24-point scale) 2-4 times. We applied longitudinal models with nonlinear distributed lags of temperature up to 7 days prior to testing. Indoor temperatures ranged 8-34°C overall and 15-34°C on survey days. We observed a 0.4 (95% CI: 0.0, 0.7) point increase in WLL and 0.4 (95% CI: 0.0, 0.9) point increase in WLD scores per 2°C increase in AT. Results suggested decreasing sleepiness scores with decreasing nighttime AT below 22°C. Low-income Detroit residents experience uncomfortably high and low indoor temperatures. Indoor temperature may influence cognitive function and sleepiness, although we did not observe deleterious effects of higher temperatures.

Compound Climate and Infrastructure Events: How Electrical Grid Failure Alters Heat Wave Risk.

The potential for critical infrastructure failures during extreme weather events is rising. Major electrical grid failure or "blackout" events in the United States, those with a duration of at least 1 h and impacting 50,000 or more utility customers, increased by more than 60% over the most recent 5 year reporting period. When such blackout events coincide in time with heat wave conditions, population exposures to extreme heat both outside and within buildings can reach dangerously high levels as mechanical air conditioning systems become inoperable. Here, we combine the Weather Research and Forecasting regional climate model with an advanced building energy model to simulate building-interior temperatures in response to concurrent heat wave and blackout conditions for more than 2.8 million residents across Atlanta, Georgia; Detroit, Michigan; and Phoenix, Arizona. Study results find simulated compound heat wave and grid failure events of recent intensity and duration to expose between 68 and 100% of the urban population to an elevated risk of heat exhaustion and/or heat stroke.

Short-term exposures to atmospheric evergreen, deciduous, grass, and ragweed aeroallergens and the risk of suicide in Ohio, 2007-2015: Exploring disparities by age, gender, and education level.

BACKGROUND: Seasonal trends in suicide mortality are observed worldwide, potentially aligning with the seasonal release of aeroallergens. However, only a handful of studies have examined whether aeroallergens increase the risk of suicide, with inconclusive results thus far. The goal of this study was to use a time-stratified case-crossover design to test associations of speciated aeroallergens (evergreen, deciduous, grass, and ragweed) with suicide deaths in Ohio, USA (2007-2015). METHODS: Residential addresses for 12,646 persons who died by suicide were linked with environmental data at the 4-25 km grid scale including atmospheric aeroallergen concentrations, maximum temperature, sunlight, particulate matter <2.5 µm, and ozone. A case-crossover design was used to examine same-day and 7-day cumulative lag effects on suicide. Analyses were stratified by age group, gender, and educational level. RESULTS: In general, associations were null between aeroallergens and suicide. Stratified analyses revealed a relationship between grass pollen and same-day suicide for women (OR = 3.84; 95% CI = 1.44, 10.22) and those with a high school degree or less (OR = 2.03; 95% CI = 1.18, 3.49). CONCLUSIONS: While aeroallergens were generally not significantly related to suicide in this sample, these findings provide suggestive evidence for an acute relationship of grass pollen with suicide for women and those with lower education levels. Further research is warranted to determine whether susceptibility to speciated aeroallergens may be driven by underlying biological mechanisms or variation in exposure levels.

Association between temperature exposure and cognition: a cross-sectional analysis of 20,687 aging adults in the United States.

BACKGROUND: Older adults are particularly vulnerable to the adverse health effects of extreme temperature-related events. A growing body of literature highlights the importance of the natural environment, including air pollution and sunlight, on cognitive health. However, the relationship between exposure to outdoor temperatures and cognitive functioning, and whether there exists any differences across climate region, remains largely unexplored. We address this gap by examining the temperature-cognition association, and whether there exists any variation across climate regions in a national cohort of aging adults. METHODS: In this cross-sectional study, we obtained data on temperature exposure based on geocoded residential location of participants in the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. For each participant, this information was linked to their cognitive scores from Word List Learning and Recall tests to assess cognitive functioning. We used distributed lag non-linear models (dlnm) to model temperature effects over 2 days. Multivariable linear regression was used to compute temperature-cognitive functioning associations, adjusted for important covariates. Region-specific ("Dry", "Mediterranean/oceanic", "Tropical" and "Continental") associations were examined by including an interaction term between climate region and temperature. RESULTS: Amongst 20,687 individuals (mean age = 67.8; standard deviation = 9.2), exposure to region-specific extreme cold temperatures in the "dry" region (e.g., Arizona) over 2 days was associated with lower cognitive scores (Mean Difference [MD]: -0.76, 95% Confidence Interval [CI]: - 1.45, - 0.07). Associations remained significant for cumulative effects of temperature over 2 days. Extremely cold exposure in the "Mediterranean/oceanic" region (e.g., California) over 2 days was also associated with significantly lower cognitive performance (MD: -0.25, 95% CI: - 0.47, - 0.04). No significant associations were observed for exposure to hot temperatures. Cognitive performance was slightly higher in late summer and fall compared to early summer. CONCLUSION: We noted adverse cognitive associations with cold temperatures in traditionally warmer regions of the country and improved cognition in summer and early fall seasons. While we did not observe very large significant associations, this study deepens understanding of the impact of climate change on the cognitive health of aging adults and can inform clinical care and public health preparedness plans.

Particulate matter exposure, dietary inflammatory index and preterm birth in Mexico city, Mexico.

BACKGROUND: Particulate matter ≤10 µm in aerodynamic diameter (PM10) and diet quality are risk factors for systemic inflammation, which is associated with preterm birth (PTB). PM10 and a pro-inflammatory diet (assessed by the Dietary Inflammatory Index [DII®]) have been individually evaluated as causes of PTB and differences by offspring sex have been reported for the DII. However, additional studies are needed to evaluate joint effects of these associations to inform intervention efforts. OBJECTIVES: To evaluate the independent and joint effects of PM10 and energy-adjusted DII (E-DII) on PTB risks. METHODS: PM10 estimates were generated from daily citywide averages for 1216 pregnant women from three subcohorts of the Early Life Exposures in Mexico to Environmental Toxicants study using data from the Mexico City Outdoor Air Monitoring Network. Among a subset of participants (N = 620), E-DII scores were calculated using a validated food frequency questionnaire. Cox Proportional Hazards models were run for select periods during pregnancy and entire pregnancy averages for E-DII and PM10. We assessed for potential non-linear associations using natural splines. RESULTS: In adjusted models, PM10 exposure was associated with increased risks of PTB for a range of values (58-72 µg/m3) during the second trimester, while negative associations were seen during the second (≥74 µg/m3) and third trimesters (55-65 µg/m3). Analyses conducted using distributed lag models for periods closer to delivery (max lag = 90) did not show negative associations between PM10 exposure and preterm birth, and indeed positive significant associations were observed (estimates and figures). E-DII was not associated with PTB and there was no evidence of effect modification by infant sex. There was no evidence of interaction between PM10 and E-DII and the risk of preterm birth. DISCUSSION: Associations between PM10 and PTB in Mexico City varied over time and across levels of PM10. Our findings of negative associations in the second and third trimesters, which are contrary to the hypothesized relationship between PM10 and PTB, may be due to a number of factors, including live birth bias and the exposure period evaluated. Differences in results for the periods evaluated suggest that PM10 from shorter exposure windows may play a more proximal role in initiating preterm labor.

Repeated Measures of Cervicovaginal Cytokines during Healthy Pregnancy: Understanding "Normal" Inflammation to Inform Future Screening.

OBJECTIVE: This study aimed to describe characteristics of cervicovaginal cytokines obtained during pregnancy from women who subsequently delivered at term. STUDY DESIGN: We used repeated measures of 20 cervicovaginal cytokines, collected on average on a monthly basis, from the second to the ninth month of gestation among 181 term pregnancies in the Mexico City Pregnancy Research on Inflammation, Nutrition, & City Environment: Systematic Analyses cohort (2009-2014). Cytokines were quantified using multiplex assay. RESULTS: Cytokine distributions differed more between than within cytokines. Across trimesters, cytokines interleukin (IL)-1Ra, IL-1α, and IL-8 consistently had high concentrations compared with other measured cytokines. Cytokine intraclass correlation coefficients ranged from 0.41 to 0.82. Spearman's correlation coefficients among cytokine pairs varied but correlation directions were stable; 95.3% of the 190 correlation pairs remained either negative or positive across trimesters. Mean longitudinal patterns of log-transformed cytokines from Tobit regression varied across but less within cytokines. CONCLUSION: Although mean concentrations of cervicovaginal cytokines among term pregnancies were high, they were largely stable over time. The high cytokine concentrations corroborate that pregnancy is associated with an active inflammatory state. These characterizations may serve as a baseline for comparison to other obstetric outcomes, which may be helpful in understanding deviations from normal gestational inflammation.

Assessing the magnitude and uncertainties of the burden of selected diseases attributable to extreme heat and extreme precipitation under a climate change scenario in Michigan for the period 2041-2070.

BACKGROUND: Extreme heat (EH) and extreme precipitation (EP) events are expected to increase with climate change in many parts of the world. Characterizing the potential future morbidity and mortality burden of EH and EP and associated costs, as well as uncertainties in the estimates, can identify areas for public health intervention and inform adaptation strategies. We demonstrate a burden of disease and uncertainty assessment using data from Michigan, USA, and provide approaches for deriving these estimates for locations lacking certain data inputs. METHODS: Case-crossover analysis adapted from previous Michigan-specific modeling was used to characterize the historical EH-mortality relationship by county poverty rate and age group. Historical EH-associated hospitalization and emergency room visit risks from the literature were adapted to Michigan. In the U.S. Environmental Protection Agency's BenMAP software, we used a novel approach, with multiple spatially-varying exposures, to estimate all non-accidental mortality and morbidity occurring on EH days (EH days; days where maximum temperature 32.2-35 C or > 35 C) and EP days. We did so for two time periods: the "historical" period (1971-2000), and the "projected" period (2041-2070), by county. RESULTS: The rate of all non-accidental mortality associated with EH days increased from 0.46/100,000 persons historically to 2.9/100,000 in the projected period, for 240 EH-attributable deaths annually. EH-associated ED visits increased from 12/100,000 persons to 68/100,000 persons, for 7800 EH-attributable emergency department visits. EP-associated ED visits increased minimally from 1.7 to 1.9/100,000 persons. Mortality and morbidity were highest among those aged 65+ (91% of all deaths). Projected health costs are dominated by EH-associated mortality ($280 million) and EH-associated emergency department visits ($14 million). A variety of sources contribute to a moderate-to-high degree of uncertainty around the point estimates, including uncertainty in the magnitude of climate change, population composition, baseline health rates, and exposure-response estimates. CONCLUSIONS: The approach applied here showed that health burden due to climate may significantly rise for all Michigan counties by midcentury. The costs to health care and uncertainties in the estimates, given the potential for substantial attributable burden, provide additional information to guide adaptation measures for EH and EP.

Vulnerability to the Cardiovascular Effects of Ambient Heat in Six US Cities: Results from the Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: With climate change, temperatures are increasing. Heat-associated health events disproportionately affect certain subpopulations. However, prior research has often lacked information on individual-level health and air conditioning and neighborhood stressors/protections. OBJECTIVES: To assess whether (1) heat (2-day mean temperature above local 75th percentiles) is associated with increased heart rate and decreased blood pressure, controlling for age, time, season, daily ozone, and daily particulate matter (PM2.5) and (2) associations differ by antihypertensive medication use, renal function, fasting glucose, emotional support, air conditioning ownership and use, normalized difference vegetation index, neighborhood safety, and residence- specific oxides of nitrogen and PM2.5. METHODS: Health and behavioral characteristics were obtained repeatedly on participants of the Multi-Ethnic Study of Atherosclerosis in six US sites (2000-2010). These were linked with airport temperature, air quality, and satellite- and survey-derived neighborhood characteristics. We used a fixed-effects design, regressing health outcomes on linear temperature splines with knots at the 75th percentiles, interaction terms for each characteristic, and adjustment for month of year, age, PM2.5, and ozone. RESULTS: Overall, heat was not associated with heart rate. However, for a 2°C increase in heat, systolic blood pressure decreased by 1.1 mmHg (95% CI = -1.6, -0.6) and diastolic blood pressure by 0.3 mmHg (95% CI = -0.6, -0.1). Among nonusers of antihypertensive medications, heat-associated decreases in SBP were 2.1 mmHg greater among individuals with central air conditioning versus those without. Confidence intervals around the remaining modifiers were wide after multiple-comparisons corrections or sensitivity analyses. CONCLUSIONS: Outdoor heat is associated with decreasing blood pressure, and cardiovascular vulnerability may vary primarily by ownership of central air conditioning.

Vulnerability to extreme-heat-associated hospitalization in three counties in Michigan, USA, 2000-2009.

With climate change, extreme heat (EH) events are increasing, so it is important to understand who is vulnerable to heat-associated morbidity. We determined the association between EH and hospitalizations for all natural causes; cardiovascular, respiratory, and renal diseases; diabetes mellitus; and acute myocardial infarction in Michigan, USA, at different intensities and durations. We assessed confounding by ozone and how individual characteristics and health insurance payer (a proxy for income) modified these associations. We obtained Michigan Inpatient Database, National Climatic Data Center, and US Environmental Protection Agency ozone data for May-September, 2000-2009 for three Michigan counties. We employed a case-crossover design and modeled EH as an indicator for temperature above the 95th, 97th, or 99th percentile thresholds for 1, 2, 3, or 4 days. We examined effect modification by patient age, race, sex, and health insurance payer and pooled the county results. Among non-whites, the pooled odds ratio for hospitalization on EH (97th percentile threshold) vs. non-EH days for renal diseases was 1.37 (95 % CI = 1.13-1.66), which increased with increasing EH intensity, but was null among whites (OR = 1.00, 95 % CI = 0.81, 1.25). We observed a null association between EH and cardiovascular hospitalization. EH (99th percentile threshold) was associated with myocardial infarction hospitalizations. Confounding by ozone was minimal. EH was associated with hospitalizations for renal disease among non-whites. This information on vulnerability to heat-associated morbidity helps characterize the public health burden of EH and target interventions including patient education.

Vulnerability to extreme heat by socio-demographic characteristics and area green space among the elderly in Michigan, 1990-2007.

OBJECTIVES: We examined how individual and area socio-demographic characteristics independently modified the extreme heat (EH)-mortality association among elderly residents of 8 Michigan cities, May-September, 1990-2007. METHODS: In a time-stratified case-crossover design, we regressed cause-specific mortality against EH (indicator for 4-day mean, minimum, maximum or apparent temperature above 97th or 99 th percentiles). We examined effect modification with interactions between EH and personal marital status, age, race, sex and education and ZIP-code percent "non-green space" (National Land Cover Dataset), age, race, income, education, living alone, and housing age (U.S. Census). RESULTS: In models including multiple effect modifiers, the odds of cardiovascular mortality during EH (99 th percentile threshold) vs. non-EH were higher among non-married individuals (1.21, 95% CI=1.14-1.28 vs. 0.98, 95% CI=0.90-1.07 among married individuals) and individuals in ZIP codes with high (91%) non-green space (1.17, 95% CI=1.06-1.29 vs. 0.98, 95% CI=0.89-1.07 among individuals in ZIP codes with low (39%) non-green space). Results suggested that housing age may also be an effect modifier. For the EH-respiratory mortality association, the results were inconsistent between temperature metrics and percentile thresholds of EH but largely insignificant. CONCLUSIONS: Green space, housing and social isolation may independently enhance elderly peoples' heat-related cardiovascular mortality vulnerability. Local adaptation efforts should target areas and populations at greater risk.

Summer temperature variability and long-term survival among elderly people with chronic disease.

Time series studies show that hot temperatures are associated with increased death rates in the short term. In light of evidence of adaptation to usual temperature but higher deaths at unusual temperatures, a long-term exposure relevant to mortality might be summertime temperature variability, which is expected to increase with climate change. We investigated whether the standard deviation (SD) of summer (June-August) temperatures was associated with survival in four cohorts of persons over age 65 y with predisposing diseases in 135 US cities. Using Medicare data (1985-2006), we constructed cohorts of persons hospitalized with chronic obstructive pulmonary disease, diabetes, congestive heart failure, and myocardial infarction. City-specific yearly summer temperature variance was linked to the individuals during follow-up in each city and was treated as a time-varying exposure. We applied a Cox proportional hazard model for each cohort within each city, adjusting for individual risk factors, wintertime temperature variance, yearly ozone levels, and long-term trends, to estimate the chronic effects on mortality of long-term exposure to summer temperature SD, and then pooled results across cities. Mortality hazard ratios ranged from 1.028 (95% confidence interval, 1.013- 1.042) per 1 °C increase in summer temperature SD for persons with congestive heart failure to 1.040 (95% confidence interval, 1.022-1.059) per 1 °C increase for those with diabetes. Associations were higher in elderly persons and lower in cities with a higher percentage of land with green surface. Our data suggest that long-term increases in temperature variability may increase the risk of mortality in different subgroups of susceptible older populations.

Susceptibility to mortality in weather extremes: effect modification by personal and small-area characteristics.

BACKGROUND: Extremes of temperature have been associated with short-term increases in daily mortality. We identified subpopulations with increased susceptibility to dying during temperature extremes, based on personal demographics, small-area characteristics, and preexisting medical conditions. METHODS: We examined Medicare participants in 135 US cities and identified preexisting conditions based on hospitalization records before their deaths, from 1985 to 2006. Personal characteristics were obtained from the Medicare records, and area characteristics were assigned based on zip code of residence. We conducted a case-only analysis of over 11 million deaths and evaluated modification of the risk of dying associated with extremely hot days and extremely cold days, continuous temperatures, and water vapor pressure. Modifiers included preexisting conditions, personal characteristics, zip code-level population characteristics, and land cover characteristics. For each effect modifier, a city-specific logistic regression model was fitted and then an overall national estimate was calculated using meta-analysis. RESULTS: People with certain preexisting conditions were more susceptible to extreme heat, with an additional 6% (95% confidence interval = 4%-8%) increase in the risk of dying on an extremely hot day in subjects with previous admission for atrial fibrillation, an additional 8% (4%-12%) in subjects with Alzheimer disease, and an additional 6% (3%-9%) in subjects with dementia. Zip code level and personal characteristics were also associated with increased susceptibility to temperature. CONCLUSIONS: We identified several subgroups of the population who are particularly susceptible to temperature extremes, including persons with atrial fibrillation.

Staying cool in a changing climate: Reaching vulnerable populations during heat events.

The frequency and intensity of hot weather events are expected to increase globally, threatening human health, especially among the elderly, poor, and chronically ill. Current literature indicates that emergency preparedness plans, heat health warning systems, and related interventions may not be reaching or supporting behavior change among those most vulnerable in heat events. Using a qualitative multiple case study design, we comprehensively examined practices of these populations to stay cool during hot weather ("cooling behaviors") in four U.S. cities with documented racial/ethnic and socio-economic disparities and diverse heat preparedness strategies: Phoenix, Arizona; Detroit, Michigan; New York City, New York; and Philadelphia, Pennsylvania. Based on semi-structured in-depth interviews we conducted with 173 community members and organizational leaders during 2009-2010, we assessed why vulnerable populations do or do not participate in health-promoting behaviors at home or in their community during heat events, inquiring about perceptions of heat-related threats and vulnerability and the role of social support. While vulnerable populations often recognize heat's potential health threats, many overlook or disassociate from risk factors or rely on experiences living in or visiting warmer climates as a protective factor. Many adopt basic cooling behaviors, but unknowingly harmful behaviors such as improper use of fans and heating and cooling systems are also adopted. Decision-making related to commonly promoted behaviors such as air conditioner use and cooling center attendance is complex, and these resources are often inaccessible financially, physically, or culturally. Interviewees expressed how interpersonal, intergenerational relationships are generally but not always protective, where peer relationships are a valuable mechanism for facilitating cooling behaviors among the elderly during heat events. To prevent disparities in heat morbidity and mortality in an increasingly changing climate, we note the implications of local context, and we broadly inform heat preparedness plans, interventions, and messages by sharing the perspectives and words of community members representing vulnerable populations and leaders who work most closely with them.

Associations between Air Pollution Exposure and Blood Pressure during Pregnancy among PRINCESA Cohort Participants.

High blood pressure (BP) is a risk factor for hypertensive disease during pregnancy. Exposure to multiple toxic air pollutants can affect BP in pregnancy but has been rarely studied. We evaluated trimester-specific associations between air pollution exposure and systolic (SBP) and diastolic BP (DBP). Ozone (O3), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), and particulate matter less than 10 and 2.5 µm in aerodynamic diameter (PM10, PM2.5) in the Pregnancy Research on Inflammation, Nutrition, & City Environment: Systematic Analyses (PRINCESA) study. Multipollutant generalized linear regression models with each pollutant and O3 were fit. Due to nonlinear pollution/BP associations, results are presented for "below the median" or "above the median", where the beta estimate is the change in BP at a pollutant's median versus BP at the pollutant's minimum or maximum, respectively. Associations varied across trimesters and pollutants, and deleterious associations (higher blood pressure with higher pollution) were found only at pollutant values below the median: for SBP with NO2 in the second and third trimesters, and PM2.5 during the third trimester, and for DBP, PM2.5, and NO2 in the second and third trimesters. Findings suggest that minimizing prenatal exposure to air pollution may reduce the risks of changes in BP.

Geostatistical exploration of spatial variation of summertime temperatures in the Detroit metropolitan region.

BACKGROUND: Because of the warming climate urban temperature patterns have been receiving increased attention. Temperature within urban areas can vary depending on land cover, meteorological and other factors. High resolution satellite data can be used to understand this intra-urban variability, although they have been primarily studied to characterize urban heat islands at a larger spatial scale. OBJECTIVE: This study examined whether satellite-derived impervious surface and meteorological conditions from multiple sites can improve characterization of spatial variability of temperature within an urban area. METHODS: Temperature was measured at 17 outdoor sites throughout the Detroit metropolitan area during the summer of 2008. Kriging and linear regression were applied to daily temperatures and secondary information, including impervious surface and distance-to-water. Performance of models in predicting measured temperatures was evaluated by cross-validation. Variograms derived from several scenarios were compared to determine whether high-resolution impervious surface information could capture fine-scale spatial structure of temperature in the study area. RESULTS: Temperatures measured at the sites were significantly different from each other, and all kriging techniques generally performed better than the two linear regression models. Impervious surface values and distance-to-water generally improved predictions slightly. Restricting models to days with lake breezes and with less cloud cover also somewhat improved the predictions. In addition, incorporating high-resolution impervious surface information into cokriging or universal kriging enhanced the ability to characterize fine-scale spatial structure of temperature. CONCLUSIONS: Meteorological and satellite-derived data can better characterize spatial variability in temperature across a metropolitan region. The data sources and methods we used can be applied in epidemiological studies and public health interventions to protect vulnerable populations from extreme heat events.

Modeling and comparing central and room air conditioning ownership and cold-season in-home thermal comfort using the American Housing Survey.

Household-level information on central air conditioning (cenAC) and room air conditioning (rmAC) air conditioning and cold-weather thermal comfort are often missing from publicly available housing databases hindering research and action on climate adaptation and air pollution exposure reduction. We modeled these using information from the American Housing Survey for 2003-2013 and 140 US core-based statistical areas employing variables that would be present in publicly available parcel records. We present random-intercept logistic regression models with either cenAC, rmAC or "home was uncomfortably cold for 24 h or more" (tooCold) as outcome variables and housing value, rented vs. owned, age, and multi- vs. single-family, each interacted with cooling- or heating-degree days as predictors. The out-of-sample predicted probabilities for years 2015-2017 were compared with corresponding American Housing Survey values (0 or 1). Using a 0.5 probability threshold, the model had 63% specificity (true negative rate), and 91% sensitivity (true positive rate) for cenAC, while specificity and sensitivity for rmAC were 94% and 34%, respectively. Area-specific sensitivities and specificities varied widely. For tooCold, the overall sensitivity was effectively 0%. Future epidemiologic studies, heat vulnerability maps, and intervention screenings may reliably use these or similar AC models with parcel-level data to improve understanding of health risk and the spatial patterning of homes without AC.

Mapping Human Vulnerability to Extreme Heat: A Critical Assessment of Heat Vulnerability Indices Created Using Principal Components Analysis.

BACKGROUND: Extreme heat poses current and future risks to human health. Heat vulnerability indices (HVIs), commonly developed using principal components analysis (PCA), are mapped to identify populations vulnerable to extreme heat. Few studies critically assess implications of analytic choices made when employing this methodology for fine-scale vulnerability mapping. OBJECTIVE: We investigated sensitivity of HVIs created by applying PCA to input variables and whether training input variables on heat-health data produced HVIs with similar spatial vulnerability patterns for Detroit, Michigan, USA. METHODS: We acquired 2010 Census tract and block group level data, land cover data, daily ambient apparent temperature, and all-cause mortality during May-September, 2000-2009. We used PCA to construct HVIs using: a) "unsupervised"-PCA applied to variables selected a priori as risk factors for heat-related health outcomes; b) "supervised"-PCA applied only to variables significantly correlated with proportion of all-cause mortality occurring on extreme heat days (i.e., days with 2-d mean apparent temperature above month-specific 95th percentiles). RESULTS: Unsupervised and supervised HVIs yielded differing spatial vulnerability patterns, depending on selected land cover input variables. Supervised PCA explained 62% of variance in the input variables and was applied on half the variables used in the unsupervised method. Census tract-level supervised HVI values were positively associated with increased proportion of mortality occurring on extreme heat days; supervised PCA could not be applied to block group data. Unsupervised HVI values were not associated with extreme heat mortality for either tracts or block groups. DISCUSSION: HVIs calculated using PCA are sensitive to input data and scale. Supervised HVIs may provide marginally more specific indicators of heat vulnerability than unsupervised HVIs. PCA-derived HVIs address correlation among vulnerability indicators, although the resulting output requires careful contextual interpretation beyond generating epidemiological research questions. Methods with reliably stable outputs should be leveraged for prioritizing heat interventions. https://doi.org/10.1289/EHP4030.

Heat-Related Illness Is Associated with Lack of Air Conditioning and Pre-Existing Health Problems in Detroit, Michigan, USA: A Community-Based Participatory Co-Analysis of Survey Data.

The objective of the study was to investigate, using academic-community epidemiologic co-analysis, the odds of reported heat-related illness for people with (1) central air conditioning (AC) or window unit AC versus no AC, and (2) fair/poor vs. good/excellent reported health. From 2016 to 2017, 101 Detroit residents were surveyed once regarding extreme heat, housing and neighborhood features, and heat-related illness in the prior 5 years. Academic partners selected initial confounders and, after instruction on directed acyclic graphs, community partners proposed alternate directed acyclic graphs with additional confounders. Heat-related illness was regressed on AC type or health and co-selected confounders. The study found that heat-related illness was associated with no-AC (n = 96, odds ratio (OR) = 4.66, 95% confidence interval (CI) = 1.22, 17.72); living ≤5 years in present home (n = 57, OR = 10.39, 95% CI = 1.13, 95.88); and fair/poor vs. good/excellent health (n = 97, OR = 3.15, 95% CI = 1.33, 7.48). Co-analysis suggested multiple built-environment confounders. We conclude that Detroit residents with poorer health and no AC are at greater risk during extreme heat. Academic-community co-analysis using directed acyclic graphs enhances research on community-specific social and health vulnerabilities by identifying key confounders and future research directions for rigorous and impactful research.

Physical Activity in the Summer Heat: How Hot Weather Moderates the Relationship Between Built Environment Features and Outdoor Physical Activity of Adults.

BACKGROUND: Research has not yet examined how hot weather moderates the relationship between the built environment and outdoor physical activity levels. The authors posited that hot days will increase the magnitude of the expected directional effect of built environment features on physical activity. METHODS: This longitudinal study included 134 US adults from the Three city Heat and Electrical failure AdapTation study. Adults self-reported physical activity for multiple summer days (nstudy-days = 742) in 2016. Hot days were defined as ≥90th percentile of daily maximum heat index. Built environment features included density, safety, trees, hilliness, connectivity, access to parks, and access to shops + services. Separate growth curve models with interaction terms (ie, hot day × built environment feature) were run for daily minutes of outdoor physical activity (ie, any activity and recommended activity). RESULTS: Neither hot days nor built environment features impacted outdoor physical activity significantly, and hot days did not moderate the relationship between built environment features and physical activity (P > .05). CONCLUSIONS: With adults failing to modify behavior on hot days, cities may be placing adults at increased risk of exertional heat illness. The authors recommend incorporating the risk of exertional heat illness in health impact assessments and deploying heat management strategies.