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.

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.

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.

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.

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.

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.

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.

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.

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.

Time series analysis of total and direct associations between high temperatures and preterm births in Detroit, Michigan

OBJECTIVES

Preterm births (PTBs) represent significant health risks, and several studies have found associations between high outdoor temperatures and PTB. We estimated both the total and natural direct effects (independent of particulate matter, ozone and nitrogen dioxide air pollutants) of the prior 2-day mean apparent temperature (AT) on PTB. We evaluated effect modification by maternal age, race, education, smoking status and prenatal care.

DESIGN AND SETTING

We obtained birth records and meteorological data for the Detroit, Michigan, USA area, for the warm months (May to September), 1991 to 2001. We used a time series Poisson regression with splines of AT, wind speed, solar radiation and citywide average precipitation to estimate total effects. To accommodate multiple mediators and exposure-mediator interactions, AT inverse odds weights, predicted by meteorological and air pollutant covariates, were added in a subsequent model to estimate direct effects.

RESULTS

At 24.9°C relative to 18.6°C, 10.6% (95% CI: 3.8% to 17.2%) of PTBs were attributable to the total effects of AT, and 10.4% (95% CI: 2.2% to 17.5%) to direct effects. Relative excess risks of interaction indicated that the risk of PTB with increasing temperature above 18.6°C was significantly lower among black mothers and higher among mothers less than 19, older than 30, with late or no prenatal care and who smoked.

CONCLUSION

This additional evidence of a direct association between high temperature and PTB may motivate public health interventions to reduce extreme heat exposures among pregnant women, particularly among those who may have enhanced vulnerability.

Shifting from "Community-Placed" to "Community-Based" Research to Advance Health Equity: A Case Study of the Heatwaves, Housing, and Health: Increasing Climate Resiliency in Detroit (HHH) Partnership

Extreme summertime heat is a significant public health threat that disproportionately impacts vulnerable urban populations. Research on health impacts of climate change (including increasing intensity, duration, and frequency of hot weather) is sometimes designed and implemented without the involvement of the communities being studied, i.e., "community-placed" not "community-based." We describe how the Heatwaves, Housing, and Health: Increasing Climate Resiliency in Detroit (HHH) partnership engaged relevant communities by integrating a community-based participatory research (CBPR) approach into an existing, academic-designed research project through a steering committee of community and academic partners. Using a case study approach, we analyze program documentation, partnership evaluation questionnaires, and HHH steering committee meeting notes. We describe the CBPR process by which we successfully collected research data in Detroit during summer 2016, engaged in collaborative analysis of data, and shared results with Detroit residents. Evaluations of the partnership over 2 years show community involvement in research; enhanced capacities; success in securing new grant funding; and ways that CBPR strengthened the validity, relevance, and translation of research. Engaging communities as equal partners using CBPR, even after a study is underway, can strengthen research to understand and address the impacts of extreme heat on health and equity in urban communities.

Air pollution and inflammation: Findings from concurrent repeated measures of systemic and reproductive tract cytokines during term pregnancy in Mexico City

BACKGROUND

Environmental exposures are associated with a number of outcomes including adverse pregnancy outcomes. Although inflammation is hypothesized to play a role, the mechanistic pathways between environmental exposures and adverse health outcomes, including associations between exposures and longitudinal measures of systemic and reproductive tract inflammation, need elucidation.

OBJECTIVES

This study was conducted to evaluate whether exposure to air pollution is associated with immunologic responses in the systemic circulation and lower reproductive tract, and to evaluate whether systemic and reproductive tract immunologic responses are similar.

METHODS

We quantified repeated measures of cytokines from cervico-vaginal exudates and serum obtained concurrently among 104 women with term pregnancies and estimated PM₁₀ and CO exposure using the monitor nearest each participant's residence. Serum and cervico-vaginal cytokines were compared using Wilcoxon signed-ranks test and Spearman rank correlations for select gestational months. We used intraclass correlation coefficients (ICCs) to quantify reproducibility of cytokine measurements, and Tobit regression to estimate associations between air pollution and cytokines.

RESULTS

Median cervico-vaginal levels of IL-6, Eotaxin, IP-10, MCP-1, MIP-1α, MIP-1β, and TNFα were higher than corresponding serum cytokines, significantly so for IL-6 and IP-10. Cervico-vaginal and serum cytokines were not correlated, but cytokines from the same fluid were correlated. ICCs for most serum cytokines were ≤0.40, while ICCs were higher in cervico-vaginal cytokines (range 0.52-0.83). IP-10 and Eotaxin had the highest ICCs for both cytokine sources. In adjusted models, PM₁₀ was positively associated with serum cytokines IL-6, IP-10, MIP-1β and Eotaxin but inversely associated with cervico-vaginal cytokine TNFα, IP-10, MIP-1β, MCP-1 and Eotaxin, controlling for false discovery rate. CO was inversely associated with cervico-vaginal TNFα, IL-6, MIP-1β, MCP-1 and Eotaxin.

CONCLUSIONS

Inflammatory processes are compartment-specific. Systemic inflammatory markers may provide information on immunologic processes and response to environmental exposures, but are not proxies for lower reproductive tract 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.

Climate change and temperature extremes: A review of heat- and cold-related morbidity and mortality concerns of municipalities

Cold and hot weather are associated with mortality and morbidity. Although the burden of temperature-associated mortality may shift towards high temperatures in the future, cold temperatures may represent a greater current-day problem in temperate cities. Hot and cold temperature vulnerabilities may coincide across several personal and neighborhood characteristics, suggesting opportunities for increasing present and future resilience to extreme temperatures. We present a narrative literature review encompassing the epidemiology of cold- and heat-related mortality and morbidity, related physiologic and environmental mechanisms, and municipal responses to hot and cold weather, illustrated by Detroit, Michigan, USA, a financially burdened city in an economically diverse metropolitan area. The Detroit area experiences sharp increases in mortality and hospitalizations with extreme heat, while cold temperatures are associated with more gradual increases in mortality, with no clear threshold. Interventions such as heating and cooling centers may reduce but not eliminate temperature-associated health problems. Furthermore, direct hemodynamic responses to cold, sudden exertion, poor indoor air quality and respiratory epidemics likely contribute to cold-related mortality. Short- and long-term interventions to enhance energy and housing security and housing quality may reduce temperature-related health problems. Extreme temperatures can increase morbidity and mortality in municipalities like Detroit that experience both extreme heat and prolonged cold seasons amidst large socioeconomic disparities. The similarities in physiologic and built-environment vulnerabilities to both hot and cold weather suggest prioritization of strategies that address both present-day cold and near-future heat concerns.

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 Renal, Heat and Respiratory Hospitalizations During Extreme Heat Among U.S. Elderly

BACKGROUND

Extreme heat (EH) is a growing concern with climate change, and protecting human health requires knowledge of vulnerability factors. We evaluated whether associations between EH (maximum temperature > 97th percentile) and hospitalization for renal, heat and respiratory diseases among people ≥ 65 years differed by individual and area-level characteristics.

METHODS

We used Medicare billing records, airport weather data, U.S. Census data and satellite land cover imagery in 109 US cities, May-September, 1992-2006, in a time-stratified case-crossover design. Interaction terms between EH and individual (> 78 years, black race, sex) and home ZIP-code (percentages of non-green space, high school education, housing built before 1940) characteristics were incorporated in a single model. Next, we pooled city-specific effect estimates or regressed them on quartiles of air conditioning prevalence (ACP) in a multivariate random effects meta-analysis.

RESULTS

EH and combined renal/heat/respiratory hospitalization associations were stronger among blacks, the very old, in ZIP codes with lower educational attainment or older housing and in cities with lower ACP. For example, for EH versus non-heat days, we found a 15% (95% CI 11%-19%) increase in renal/heat/respiratory hospitalizations among individuals in ZIP codes with higher percent of older homes in contrast to a 9% (95% CI 6%-12%) increase in hospitalizations in ZIP codes with lower percent older homes.

CONCLUSION

Vulnerability to EH-associated hospitalization may be influenced by age, educational attainment, housing age and ACP.

Evaluating the Appropriateness of Downscaled Climate Information for Projecting Risks of Salmonella

Foodborne diseases have large economic and societal impacts worldwide. To evaluate how the risks of foodborne diseases might change in response to climate change, credible and usable climate information tailored to the specific application question is needed. Global Climate Model (GCM) data generally need to, both, be downscaled to the scales of the application to be usable, and represent, well, the key characteristics that inflict health impacts. This study presents an evaluation of temperature-based heat indices for the Washington D.C. area derived from statistically downscaled GCM simulations for 1971–2000—a necessary step in establishing the credibility of these data. The indices approximate high weekly mean temperatures linked previously to occurrences of Salmonella infections. Due to bias-correction, included in the Asynchronous Regional Regression Model (ARRM) and the Bias Correction Constructed Analogs (BCCA) downscaling methods, the observed 30-year means of the heat indices were reproduced reasonably well. In April and May, however, some of the statistically downscaled data misrepresent the increase in the number of hot days towards the summer months. This study demonstrates the dependence of the outcomes to the selection of downscaled climate data and the potential for misinterpretation of future estimates of Salmonella infections.

Characterizing the burden of disease of particulate matter for life cycle impact assessment

Fine particulate air pollution (PM2.5) is a major environmental contributor to human burden of disease and therefore an important component of life cycle impact assessments. An accurate PM2.5 characterization factor, i.e., the impact per kg of PM2.5 emitted, is critical to estimating "cradle-to-grave" human health impacts of products and processes. We developed and assessed new characterization factors (disability-adjusted life years (DALY)/kgPM2.5 emitted), or the products of dose-response factors (deaths/kgPM2.5 inhaled), severity factors (DALY/death) and intake fractions (kgPM2.5 inhaled/kgPM2.5 emitted). In contrast to previous health burden estimates, we calculated age-specific concentration- and dose-response factors using baseline data, from 63 U.S. metropolitan areas, consistent with the U.S. study population used to derive the relative risk. We also calculated severity factors using 2010 Global Burden of Disease data. Multiplying the revised PM2.5 dose-responses, severity factors and intake fractions yielded new PM2.5 characterization factors that are higher than previous factors for primary PM2.5 but lower for secondary PM2.5 due to NOx. Multiplying the concentration-response and severity factors by 2005 ambient PM2.5 concentrations yielded an annual U.S. burden of 2,000,000 DALY, slightly lower than previous U.S. estimates. The annual U.S. health burden estimated from PM emissions and characterization factors was 2.2 times higher.

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.

Heat, heat waves, and hospital admissions among the elderly in the United States, 1992-2006

BACKGROUND

Heat-wave frequency, intensity, and duration are increasing with global climate change. The association between heat and mortality in the elderly is well documented, but less is known regarding associations with hospital admissions.

OBJECTIVES

Our goal was to determine associations between moderate and extreme heat, heat waves, and hospital admissions for nonaccidental causes among Medicare beneficiaries ≥ 65 years of age in 114 cities across five U.S. climate zones.

METHODS

We used Medicare inpatient billing records and city-specific data on temperature, humidity, and ozone from 1992 through 2006 in a time-stratified case-crossover design to estimate the association between hospitalization and moderate [90th percentile of apparent temperature (AT)] and extreme (99th percentile of AT) heat and heat waves (AT above the 95th percentile over 2-8 days). In sensitivity analyses, we additionally considered confounding by ozone and holidays, different temperature metrics, and alternate models of the exposure-response relationship.

RESULTS

Associations between moderate heat and hospital admissions were minimal, but extreme heat was associated with a 3% (95% CI: 2%, 4%) increase in all-cause hospital admissions over the subsequent 8 days. In cause-specific analyses, extreme heat was associated with increased hospitalizations for renal (15%; 95% CI: 9%, 21%) and respiratory (4%; 95% CI: 2%, 7%) diseases, but not for cardiovascular diseases. An added heat-wave effect was observed for renal and respiratory admissions.

CONCLUSION

Extreme heat is associated with increased hospital admissions, particularly for renal causes, among the elderly in the United States.

Racial and socioeconomic disparities in heat-related health effects and their mechanisms: a review

Adaptation to increasing extreme heat in a changing climate requires a precise understanding of who is most vulnerable to the health effects of extreme heat. The evidence for race, ethnicity, income, education and occupation, at the individual and area levels, as indicators of vulnerability is reviewed. The evidence for the social, behavioral and technological mechanisms by which racial and socioeconomic disparities in vulnerability exist is also reviewed. These characteristics include cardiorespiratory, renal and endocrine comorbidities; cognitive, mental or physical disabilities; medication use; housing characteristics; neighborhood characteristics such as urban heat islands, crime and safety; social isolation; and individual behaviors such as air conditioning use, opening windows and using fans and use of cooler public spaces. Pre-existing and future research identifying these more proximal indicators of vulnerability will provide information that is more generalizable across locations and time to aid in identifying who to target for prevention of heat-associated morbidity and mortality.

Strategies to reduce the harmful effects of extreme heat events: a four-city study

Extreme heat events (EHEs) are becoming more intense, more frequent and longer lasting in the 21st century. These events can disproportionately impact the health of low-income, minority, and urban populations. To better understand heat-related intervention strategies used by four U.S. cities, we conducted 73 semi-structured interviews with government and non-governmental organization leaders representing public health, general social services, emergency management, meteorology, and the environmental planning sectors in Detroit, MI; New York City, NY; Philadelphia, PA and Phoenix, AZ-cities selected for their diverse demographics, climates, and climate adaptation strategies. We identified activities these leaders used to reduce the harmful effects of heat for residents in their city, as well as the obstacles they faced and the approaches they used to evaluate these efforts. Local leaders provided a description of how local context (e.g., climate, governance and city structure) impacted heat preparedness. Despite the differences among study cities, political will and resource access were critical to driving heat-health related programming. Upon completion of our interviews, we convened leaders in each city to discuss these findings and their ongoing efforts through day-long workshops. Our findings and the recommendations that emerged from these workshops could inform other local or national efforts towards preventing heat-related morbidity and mortality.

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.

Validating satellite-derived land surface temperature with in situ measurements: a public health perspective

BACKGROUND

Land surface temperature (LST) and percent surface imperviousness (SI), both derived from satellite imagery, have been used to characterize the urban heat island effect, a phenomenon in which urban areas are warmer than non-urban areas.

OBJECTIVES

We aimed to assess the correlations between LSTs and SI images with actual temperature readings from a ground-based network of outdoor monitors.

METHODS

We evaluated the relationships among a) LST calculated from a 2009 summertime satellite image of the Detroit metropolitan region, Michigan; b) SI from the 2006 National Land Cover Data Set; and c) ground-based temperature measurements monitored during the same time period at 19 residences throughout the Detroit metropolitan region. Associations between these ground-based temperatures and the average LSTs and SI at different radii around the point of the ground-based temperature measurement were evaluated at different time intervals. Spearman correlation coefficients and corresponding p-values were calculated.

RESULTS

Satellite-derived LST and SI values were significantly correlated with 24-hr average and August monthly average ground temperatures at all but two of the radii examined (100 m for LST and 0 m for SI). Correlations were also significant for temperatures measured between 0400 and 0500 hours for SI, except at 0 m, but not LST. Statistically significant correlations ranging from 0.49 to 0.91 were observed between LST and SI.

CONCLUSIONS

Both SI and LST could be used to better understand spatial variation in heat exposures over longer time frames but are less useful for estimating shorter-term, actual temperature exposures, which can be useful for public health preparedness during extreme heat events.

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.

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.

Impacts of climate change on public health in India: future research directions

BACKGROUND

Climate change and associated increases in climate variability will likely further exacerbate global health disparities. More research is needed, particularly in developing countries, to accurately predict the anticipated impacts and inform effective interventions.

OBJECTIVES

Building on the information presented at the 2009 Joint Indo-U.S. Workshop on Climate Change and Health in Goa, India, we reviewed relevant literature and data, addressed gaps in knowledge, and identified priorities and strategies for future research in India.

DISCUSSION

The scope of the problem in India is enormous, based on the potential for climate change and variability to exacerbate endemic malaria, dengue, yellow fever, cholera, and chikungunya, as well as chronic diseases, particularly among the millions of people who already experience poor sanitation, pollution, malnutrition, and a shortage of drinking water. Ongoing efforts to study these risks were discussed but remain scant. A universal theme of the recommendations developed was the importance of improving the surveillance, monitoring, and integration of meteorological, environmental, geospatial, and health data while working in parallel to implement adaptation strategies.

CONCLUSIONS

It will be critical for India to invest in improvements in information infrastructure that are innovative and that promote interdisciplinary collaborations while embarking on adaptation strategies. This will require unprecedented levels of collaboration across diverse institutions in India and abroad. The data can be used in research on the likely impacts of climate change on health that reflect India's diverse climates and populations. Local human and technical capacities for risk communication and promoting adaptive behavior must also be enhanced.

Mapping community determinants of heat vulnerability

BACKGROUND

The evidence that heat waves can result in both increased deaths and illness is substantial, and concern over this issue is rising because of climate change. Adverse health impacts from heat waves can be avoided, and epidemiologic studies have identified specific population and community characteristics that mark vulnerability to heat waves.

OBJECTIVES

We situated vulnerability to heat in geographic space and identified potential areas for intervention and further research.

METHODS

We mapped and analyzed 10 vulnerability factors for heat-related morbidity/mortality in the United States: six demographic characteristics and two household air conditioning variables from the U.S. Census Bureau, vegetation cover from satellite images, and diabetes prevalence from a national survey. We performed a factor analysis of these 10 variables and assigned values of increasing vulnerability for the four resulting factors to each of 39,794 census tracts. We added the four factor scores to obtain a cumulative heat vulnerability index value.

RESULTS

Four factors explained > 75% of the total variance in the original 10 vulnerability variables: a) social/environmental vulnerability (combined education/poverty/race/green space), b) social isolation, c) air conditioning prevalence, and d) proportion elderly/diabetes. We found substantial spatial variability of heat vulnerability nationally, with generally higher vulnerability in the Northeast and Pacific Coast and the lowest in the Southeast. In urban areas, inner cities showed the highest vulnerability to heat.

CONCLUSIONS

These methods provide a template for making local and regional heat vulnerability maps. After validation using health outcome data, interventions can be targeted at the most vulnerable populations.

US local action on heat and health: are we prepared for climate change?

OBJECTIVES

Global climate change is increasing the frequency of heat waves, hot weather, and temperature variability, which contribute to mortality and illness. Baseline information on local efforts to reduce heat vulnerability, including public advisories; minimizing greenhouse gas emissions; and mitigating urban heat islands, is lacking.

METHODS

We designed a survey about local government programs to prevent health problems and reduce heat exposure during heatwaves and administered it to 285 US communities.

RESULTS

Of 70 respondents, 26 indicated that excessive heat events are a significant issue for the local government; 30 had established preventive programs. Local government leadership and public health impacts of heat were cited most frequently as extremely important determinants of preventive programs, followed by implementation costs, economic impacts of hot weather, and greenhouse gas emissions mitigation. Cool paving materials and vegetated roofs were common heat mitigation strategies. Fact sheets and case studies were desired guidance for protecting communities during hot weather.

CONCLUSIONS

New partnerships and financial resources are needed to support more widespread local action to prevent adverse health consequences of climate change and promote environmental sustainability.

Cryptic reproductive isolation in the Drosophila simulans species complex

Forms of reproductive isolation that act after copulation but before fertilization are potentially important components of speciation, but are studied only infrequently. We examined postmating, prezygotic reproductive isolation in three hybridizations within the Drosophila simulans species complex. We allowed females to mate only once, observed and timed all copulations, dissected a subset of the females to track the storage and retention of sperm, examined the number and hatchability of eggs laid after insemination, counted all progeny produced, and measured the longevity of mated females. Each of the three hybridizations is characterized by a different set of cryptic barriers to heterospecific fertilization. When D. simulans females mate with D. sechellia males, few heterospecific sperm are transferred, even during long copulations. In contrast, copulations of D. simulans females with D. mauritiana males are often too short to allow sperm transfer. Those that are long enough to allow insemination, however, involve the transfer of many sperm, but only a fraction of these heterospecific sperm are stored by females, who also lay fewer eggs than do D. simulans females mated with conspecific males. Finally, when D. mauritiana females mate with D. simulans males, sperm are transferred and stored in abundance, but are lost rapidly from the reproductive tract and are therefore used inefficiently. These results add considerably to the list of reproductive isolating mechanisms in this well-studied clade and possibly to the list of evolutionary processes that could contribute to their reproductive isolation.