Marie S. O’Neill

Diabetes Enhances Vulnerability to Particulate Air Pollution–Associated Impairment in Vascular Reactivity and Endothelial Function

Background—Epidemiological studies suggest that people with diabetes are vulnerable to cardiovascular health effects associated with exposure to particle air pollution. Endothelial and vascular function is impaired in diabetes and may be related to increased cardiovascular risk. We examined whether endothelium-dependent and -independent vascular reactivity was associated with particle exposure in individuals with and without diabetes. Methods and Results—Study subjects were 270 greater-Boston residents. We measured 24-hour average ambient levels of air pollution (fine particles [PM2.5], particle number, black carbon, and sulfates [SO42−]) ≈500 m from the patient examination site. Pollutant concentrations were evaluated for associations with vascular reactivity. Linear regressions were fit to the percent change in brachial artery diameter (flow mediated and nitroglycerin mediated), with the particulate pollutant index, apparent temperature, season, age, race, sex, smoking history, and body mass index as predictors. Models were fit to all subjects and then stratified by diagnosed diabetes versus at risk for diabetes. Six-day moving averages of all 4 particle metrics were associated with decreased vascular reactivity among patients with diabetes but not those at risk. Interquartile range increases in SO42− were associated with decreased flow-mediated (−10.7%; 95% CI, −17.3 to −3.5) and nitroglycerin-mediated (−5.4%; 95% CI, −10.5 to −0.1) vascular reactivity among those with diabetes. Black carbon increases were associated with decreased flow-mediated vascular reactivity (−12.6%; 95% CI, −21.7 to −2.4), and PM2.5 was associated with nitroglycerin-mediated reactivity (−7.6%; 95% CI, −12.8 to −2.1). Effects were stronger in type II than type I diabetes. Conclusions—Diabetes confers vulnerability to particles associated with coal-burning power plants and traffic.

Disparities by race in heat-related mortality in four US cities: The role of air conditioning prevalence

Daily mortality is typically higher on hot days in urban areas, and certain population groups experience disproportionate risk. Air conditioning (AC) has been recommended to mitigate heat-related illness and death. We examined whether AC prevalence explained differing heat-related mortality effects by race. Poisson regression was used to model daily mortality in Chicago, Detroit, Minneapolis, and Pittsburgh. Predictors included natural splines of time (to control seasonal patterns); mean daily apparent temperature on the day of death, and averaged over lags 1–3; barometric pressure; day of week; and a linear term for airborne particles. Separate, city-specific models were fit to death counts stratified by race (Black or White) to derive the percent change in mortality at 29°C, relative to 15°C (lag 0). Next, city-specific effects were regressed on city-and race-specific AC prevalence. Combined effect estimates across all cities were calculated using inverse variance-weighted averages. Prevalence of central AC among Black households was less than half that among White households in all four cities, and deaths among Blacks were more strongly associated with hot temperatures. Central AC prevalence explained some of the differences in heat effects by race, but room-unit AC did not. Efforts to reduce disparities in heat-related mortality should consider access to AC.

HFE Genotype, Particulate Air Pollution, and Heart Rate Variability A Gene-Environment Interaction

Background— Particulate air pollution has been associated with cardiovascular mortality and morbidity. Transition metals such as iron bound to the particles may be responsible for those associations. The protein product of the hemochromatosis (HFE) gene modulates uptake of iron and divalent cations from pulmonary sources and reduces their toxicity. Two HFE polymorphisms (C282Y and H63D) associated with increased iron uptake may modify the effect of metal-rich particles on the cardiovascular system. Methods and Results— We investigated the association between particulate matter ≤2.5 &mgr;m in aerodynamic diameter and heart rate variability in 518 older men from the Normative Aging Study who were examined between November 2000 and December 2004. Linear regression models were fit to evaluate interactions between HFE genotype and particulate matter ≤2.5 &mgr;m in aerodynamic diameter in relation to heart rate variability, controlling for potential confounders. A 10-&mgr;g/m3 increase in particulate matter ≤2.5 &mgr;m in aerodynamic diameter during the 48 hours before heart rate variability measurement was associated with a 31.7% (95% CI, 10.3% to 48.1%) decrease in the high-frequency component of heart rate variability in persons with the wild-type genotype, whereas no relationship in the high-frequency component was observed in persons with either HFE variant. The difference in effect of particulate matter ≤2.5 &mgr;m in aerodynamic diameter on the high-frequency component between persons with and without HFE variants was significant (P for interaction=0.02). Conclusions— The effect of particles on cardiac autonomic function was shielded in subjects with at least 1 copy of an HFE variant compared with wild-type subjects. Transition metals, including iron, bound to ambient particles and the related oxidative stress may play an important role in cardiac toxicity of particles.

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. Citation: Gronlund CJ, Zanobetti A, Schwartz JD, Wellenius GA, O’Neill MS. 2014. Heat, heat waves, and hospital admissions among the elderly in the United States, 1992–2006. Environ Health Perspect 122:1187–1192; http://dx.doi.org/10.1289/ehp.1206132

Preventing cold-related morbidity and mortality in a changing climate.

Winter weather patterns are anticipated to become more variable with increasing average global temperatures. Research shows that excess morbidity and mortality occurs during cold weather periods. We critically reviewed evidence relating temperature variability, health outcomes, and adaptation strategies to cold weather. Health outcomes included cardiovascular-, respiratory-, cerebrovascular-, and all-cause morbidity and mortality. Individual and contextual risk factors were assessed to highlight associations between individual- and neighborhood-level characteristics that contribute to a persons vulnerability to variability in cold weather events. Epidemiologic studies indicate that the populations most vulnerable to variations in cold winter weather are the elderly, rural and, generally, populations living in moderate winter climates. Fortunately, cold-related morbidity and mortality are preventable and strategies exist for protecting populations from these adverse health outcomes. We present a range of adaptation strategies that can be implemented at the individual, building, and neighborhood level to protect vulnerable populations from cold-related morbidity and mortality. The existing research justifies the need for increased outreach to individuals and communities for education on protective adaptations in cold weather. We propose that future climate change adaptation research couple building energy and thermal comfort models with epidemiological data to evaluate and quantify the impacts of adaptation strategies.

Socioeconomic Disparities and Air Pollution Exposure: a Global Review

The existing reviews and meta-analyses addressing unequal exposure of environmental hazards on certain populations have focused on several environmental pollutants or on the siting of hazardous facilities. This review updates and contributes to the environmental inequality literature by focusing on ambient criteria air pollutants (including NOx), by evaluating studies related to inequality by socioeconomic status (as opposed to race/ethnicity) and by providing a more global perspective. Overall, most North American studies have shown that areas where low-socioeconomic-status (SES) communities dwell experience higher concentrations of criteria air pollutants, while European research has been mixed. Research from Asia, Africa, and other parts of the world has shown a general trend similar to that of North America, but research in these parts of the world is limited.

Air pollution, inflammation and preterm birth: A potential mechanistic link

Preterm birth is a public health issue of global significance, which may result in mortality during the perinatal period or may lead to major health and financial consequences due to lifelong impacts. Even though several risk factors for preterm birth have been identified, prevention efforts have failed to halt the increasing rates of preterm birth. Epidemiological studies have identified air pollution as an emerging potential risk factor for preterm birth. However, many studies were limited by study design and inadequate exposure assessment. Due to the ubiquitous nature of ambient air pollution and the potential public health significance of any role in causing preterm birth, a novel focus investigating possible causal mechanisms influenced by air pollution is therefore a global health priority. We hypothesize that air pollution may act together with other biological factors to induce systemic inflammation and influence the duration of pregnancy. Evaluation and testing of this hypothesis is currently being conducted in a prospective cohort study in Mexico City and will provide an understanding of the pathways that mediate the effects of air pollution on preterm birth. The important public health implication is that crucial steps in this mechanistic pathway can potentially be acted on early in pregnancy to reduce the risk of preterm birth.

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.

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.

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 kilogram 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 US metropolitan areas, consistent with the US 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 US burden of 2,000,000 DALY, slightly lower than previous US estimates. The annual US health burden estimated from PM emissions and characterization factors was 2.2 times higher.