Michelle L. Bell

Weather-related mortality: how heat, cold, and heat waves affect mortality in the United States.

Background: Many studies have linked weather to mortality; however, role of such critical factors as regional variation, susceptible populations, and acclimatization remain unresolved. Methods: We applied time-series models to 107 US communities allowing a nonlinear relationship between temperature and mortality by using a 14-year dataset. Second-stage analysis was used to relate cold, heat, and heat wave effect estimates to community-specific variables. We considered exposure timeframe, susceptibility, age, cause of death, and confounding from pollutants. Heat waves were modeled with varying intensity and duration. Results: Heat-related mortality was most associated with a shorter lag (average of same day and previous day), with an overall increase of 3.0% (95% posterior interval: 2.4%–3.6%) in mortality risk comparing the 99th and 90th percentile temperatures for the community. Cold-related mortality was most associated with a longer lag (average of current day up to 25 days previous), with a 4.2% (3.2%–5.3%) increase in risk comparing the first and 10th percentile temperatures for the community. Mortality risk increased with the intensity or duration of heat waves. Spatial heterogeneity in effects indicates that weather–mortality relationships from 1 community may not be applicable in another. Larger spatial heterogeneity for absolute temperature estimates (comparing risk at specific temperatures) than for relative temperature estimates (comparing risk at community-specific temperature percentiles) provides evidence for acclimatization. We identified susceptibility based on age, socioeconomic conditions, urbanicity, and central air conditioning. Conclusions: Acclimatization, individual susceptibility, and community characteristics all affect heat-related effects on mortality.

A Meta-Analysis of Time-Series Studies of Ozone and Mortality With Comparison to the National Morbidity, Mortality, and Air Pollution Study

Background: Although many time-series studies of ozone and mortality have identified positive associations, others have yielded null or inconclusive results, making the results of these studies difficult to interpret. Methods: We performed a meta-analysis of 144 effect estimates from 39 time-series studies, and estimated pooled effects by lags, age groups, cause-specific mortality, and concentration metrics. We compared results with pooled estimates from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), a time-series study of 95 large U.S. urban centers from 1987 to 2000. Results: Both meta-analysis and NMMAPS results provided strong evidence of a short-term association between ozone and mortality, with larger effects for cardiovascular and respiratory mortality, the elderly, and current-day ozone exposure. In both analyses, results were insensitive to adjustment for particulate matter and model specifications. In the meta-analysis, a 10-ppb increase in daily ozone at single-day or 2-day average of lags 0, 1, or 2 days was associated with an 0.87% increase in total mortality (95% posterior interval = 0.55% to 1.18%), whereas the lag 0 NMMAPS estimate is 0.25% (0.12% to 0.39%). Several findings indicate possible publication bias: meta-analysis results were consistently larger than those from NMMAPS; meta-analysis pooled estimates at lags 0 or 1 were larger when only a single lag was reported than when estimates for multiple lags were reported; and heterogeneity of city-specific estimates in the meta-analysis were larger than with NMMAPS. Conclusions: This study provides evidence of short-term associations between ozone and mortality as well as evidence of publication bias.

Mortality risk attributable to high and low ambient temperature: a multicountry observational study.

Summary Background Although studies have provided estimates of premature deaths attributable to either heat or cold in selected countries, none has so far offered a systematic assessment across the whole temperature range in populations exposed to different climates. We aimed to quantify the total mortality burden attributable to non-optimum ambient temperature, and the relative contributions from heat and cold and from moderate and extreme temperatures. Methods We collected data for 384 locations in Australia, Brazil, Canada, China, Italy, Japan, South Korea, Spain, Sweden, Taiwan, Thailand, UK, and USA. We fitted a standard time-series Poisson model for each location, controlling for trends and day of the week. We estimated temperature–mortality associations with a distributed lag non-linear model with 21 days of lag, and then pooled them in a multivariate metaregression that included country indicators and temperature average and range. We calculated attributable deaths for heat and cold, defined as temperatures above and below the optimum temperature, which corresponded to the point of minimum mortality, and for moderate and extreme temperatures, defined using cutoffs at the 2·5th and 97·5th temperature percentiles. Findings We analysed 74 225 200 deaths in various periods between 1985 and 2012. In total, 7·71% (95% empirical CI 7·43–7·91) of mortality was attributable to non-optimum temperature in the selected countries within the study period, with substantial differences between countries, ranging from 3·37% (3·06 to 3·63) in Thailand to 11·00% (9·29 to 12·47) in China. The temperature percentile of minimum mortality varied from roughly the 60th percentile in tropical areas to about the 80–90th percentile in temperate regions. More temperature-attributable deaths were caused by cold (7·29%, 7·02–7·49) than by heat (0·42%, 0·39–0·44). Extreme cold and hot temperatures were responsible for 0·86% (0·84–0·87) of total mortality. Interpretation Most of the temperature-related mortality burden was attributable to the contribution of cold. The effect of days of extreme temperature was substantially less than that attributable to milder but non-optimum weather. This evidence has important implications for the planning of public-health interventions to minimise the health consequences of adverse temperatures, and for predictions of future effect in climate-change scenarios. Funding UK Medical Research Council.

Heat Waves in the United States: Mortality Risk during Heat Waves and Effect Modification by Heat Wave Characteristics in 43 U.S. Communities

Background Devastating health effects from recent heat waves, and projected increases in frequency, duration, and severity of heat waves from climate change, highlight the importance of understanding health consequences of heat waves. Objectives We analyzed mortality risk for heat waves in 43 U.S. cities (1987–2005) and investigated how effects relate to heat waves’ intensity, duration, or timing in season. Methods Heat waves were defined as ≥ 2 days with temperature ≥ 95th percentile for the community for 1 May through 30 September. Heat waves were characterized by their intensity, duration, and timing in season. Within each community, we estimated mortality risk during each heat wave compared with non-heat wave days, controlling for potential confounders. We combined individual heat wave effect estimates using Bayesian hierarchical modeling to generate overall effects at the community, regional, and national levels. We estimated how heat wave mortality effects were modified by heat wave characteristics (intensity, duration, timing in season). Results Nationally, mortality increased 3.74% [95% posterior interval (PI), 2.29–5.22%] during heat waves compared with non-heat wave days. Heat wave mortality risk increased 2.49% for every 1°F increase in heat wave intensity and 0.38% for every 1-day increase in heat wave duration. Mortality increased 5.04% (95% PI, 3.06–7.06%) during the first heat wave of the summer versus 2.65% (95% PI, 1.14–4.18%) during later heat waves, compared with non-heat wave days. Heat wave mortality impacts and effect modification by heat wave characteristics were more pronounced in the Northeast and Midwest compared with the South. Conclusions We found higher mortality risk from heat waves that were more intense or longer, or those occurring earlier in summer. These findings have implications for decision makers and researchers estimating health effects from climate change.

Hospital Admissions and Chemical Composition of Fine Particle Air Pollution

RATIONALE There are unexplained geographical and seasonal differences in the short-term effects of fine particulate matter (PM(2.5)) on human health. The hypothesis has been advanced to include the possibility that such differences might be due to variations in the PM(2.5) chemical composition, but evidence supporting this hypothesis is lacking. OBJECTIVES To examine whether variation in the relative risks (RR) of hospitalization associated with ambient exposure to PM(2.5) total mass reflects differences in PM(2.5) chemical composition. METHODS We linked two national datasets by county and by season: (1) long-term average concentrations of PM(2.5) chemical components for 2000-2005 and (2) RRs of cardiovascular and respiratory hospitalizations for persons 65 years or older associated with a 10-microg/m(3) increase in PM(2.5) total mass on the same day for 106 U.S. counties for 1999 through 2005. MEASUREMENTS AND MAIN RESULTS We found a positive and statistically significant association between county-specific estimates of the short-term effects of PM(2.5) on cardiovascular and respiratory hospitalizations and county-specific levels of vanadium, elemental carbon, or nickel PM(2.5) content. CONCLUSIONS Communities with higher PM(2.5) content of nickel, vanadium, and elemental carbon and/or their related sources were found to have higher risk of hospitalizations associated with short-term exposure to PM(2.5).

Emergency admissions for cardiovascular and respiratory diseases and the chemical composition of fine particle air pollution.

Background Population-based studies have estimated health risks of short-term exposure to fine particles using mass of PM2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter) as the indicator. Evidence regarding the toxicity of the chemical components of the PM2.5 mixture is limited. Objective In this study we investigated the association between hospital admission for cardiovascular disease (CVD) and respiratory disease and the chemical components of PM2.5 in the United States. Methods We used a national database comprising daily data for 2000–2006 on emergency hospital admissions for cardiovascular and respiratory outcomes, ambient levels of major PM2.5 chemical components [sulfate, nitrate, silicon, elemental carbon (EC), organic carbon matter (OCM), and sodium and ammonium ions], and weather. Using Bayesian hierarchical statistical models, we estimated the associations between daily levels of PM2.5 components and risk of hospital admissions in 119 U.S. urban communities for 12 million Medicare enrollees (≥ 65 years of age). Results In multiple-pollutant models that adjust for the levels of other pollutants, an interquartile range (IQR) increase in EC was associated with a 0.80% [95% posterior interval (PI), 0.34–1.27%] increase in risk of same-day cardiovascular admissions, and an IQR increase in OCM was associated with a 1.01% (95% PI, 0.04–1.98%) increase in risk of respiratory admissions on the same day. Other components were not associated with cardiovascular or respiratory hospital admissions in multiple-pollutant models. Conclusions Ambient levels of EC and OCM, which are generated primarily from vehicle emissions, diesel, and wood burning, were associated with the largest risks of emergency hospitalization across the major chemical constituents of PM2.5.

Spatial and temporal variation in PM2.5 chemical composition in the United States for health effects studies

Background Although numerous studies have demonstrated links between particulate matter (PM) and adverse health effects, the chemical components of the PM mixture that cause injury are unknown. Objectives This work characterizes spatial and temporal variability of PM2.5 (PM with aerodynamic diameter < 2.5 μm) components in the United States; our objective is to identify components for assessment in epidemiologic studies. Methods We constructed a database of 52 PM2.5 component concentrations for 187 U.S. counties for 2000–2005. First, we describe the challenges inherent to analysis of a national PM2.5 chemical composition database. Second, we identify components that contribute substantially to and/or co-vary with PM2.5 total mass. Third, we characterize the seasonal and regional variability of targeted components. Results Strong seasonal and geographic variations in PM2.5 chemical composition are identified. Only seven of the 52 components contributed ≥ 1% to total mass for yearly or seasonal averages [ammonium (NH4+), elemental carbon (EC), organic carbon matter (OCM), nitrate (NO3−), silicon, sodium (Na+), and sulfate (SO42−)]. Strongest correlations with PM2.5 total mass were with NH4+ (yearly), OCM (especially winter), NO3− (winter), and SO42− (yearly, spring, autumn, and summer), with particularly strong correlations for NH4+ and SO42− in summer. Components that co-varied with PM2.5 total mass, based on daily detrended data, were NH4+, SO42−, OCM, NO32−, bromine, and EC. Conclusions The subset of identified PM2.5 components should be investigated further to determine whether their daily variation is associated with daily variation of health indicators, and whether their seasonal and regional patterns can explain the seasonal and regional heterogeneity in PM10 (PM with aerodynamic diameter < 10 μm) and PM2.5 health risks.

The Exposure–Response Curve for Ozone and Risk of Mortality and the Adequacy of Current Ozone Regulations

Time-series analyses have shown that ozone is associated with increased risk of premature mortality, but little is known about how O3 affects health at low concentrations. A critical scientific and policy question is whether a threshold level exists below which O3 does not adversely affect mortality. We developed and applied several statistical models to data on air pollution, weather, and mortality for 98 U.S. urban communities for the period 1987–2000 to estimate the exposure–response curve for tropospheric O3 and risk of mortality and to evaluate whether a “safe” threshold level exists. Methods included a linear approach and subset, threshold, and spline models. All results indicate that any threshold would exist at very low concentrations, far below current U.S. and international regulations and nearing background levels. For example, under a scenario in which the U.S. Environmental Protection Agency’s 8-hr regulation is met every day in each community, there was still a 0.30% increase in mortality per 10-ppb increase in the average of the same and previous days’ O3 levels (95% posterior interval, 0.15–0.45%). Our findings indicate that even low levels of tropospheric O3 are associated with increased risk of premature mortality. Interventions to further reduce O3 pollution would benefit public health, even in regions that meet current regulatory standards and guidelines.

Ambient air pollution and low birth weight in Connecticut and Massachusetts.

Background Several studies have examined whether air pollution affects birth weight; however results vary and many studies were focused on Southern California or were conducted outside of the United States. Objectives We investigated maternal exposure to particulate matter with aerodynamic diameter < 10, < 2.5 μm (PM10, PM2.5), sulfur dioxide, nitrogen dioxide, and carbon monoxide and birth weight for 358,504 births in Massachusetts and Connecticut from 1999 to 2002. Methods Analysis included logistic models for low birth weight (< 2,500 g) and linear models with birth weight as a continuous variable. Exposure was assigned as the average county-level concentration over gestation and each trimester based on mother’s residence. We adjusted for gestational length, prenatal care, type of delivery, child’s sex, birth order, weather, year, and mother’s race, education, marital status, age, and tobacco use. Results An interquartile increase in gestational exposure to NO2, CO, PM10, and PM2.5 lowered birth weight by 8.9 g [95% confidence interval (CI), 7.0–10.8], 16.2 g (95% CI, 12.6–19.7), 8.2 g (95% CI, 5.3–11.1), and 14.7 g (95% CI, 12.3–17.1), respectively. Lower birth weight was associated with exposure in the third trimester for PM10, the first and third trimesters for CO, the first trimester for NO2 and SO2, and the second and third trimesters for PM2.5. Effect estimates for PM2.5 were higher for infants of black mothers than those of white mothers. Conclusions Results indicate that exposure to air pollution, even at low levels, may increase risk of low birth weight, particularly for some segments of the population.

Coarse Particulate Matter Air Pollution and Hospital Admissions for Cardiovascular and Respiratory Diseases Among Medicare Patients

CONTEXT Health risks of fine particulate matter of 2.5 microm or less in aerodynamic diameter (PM2.5) have been studied extensively over the last decade. Evidence concerning the health risks of the coarse fraction of greater than 2.5 microm and 10 microm or less in aerodynamic diameter (PM10-2.5) is limited. OBJECTIVE To estimate risk of hospital admissions for cardiovascular and respiratory diseases associated with PM10-2.5 exposure, controlling for PM2.5. DESIGN, SETTING, AND PARTICIPANTS Using a database assembled for 108 US counties with daily cardiovascular and respiratory disease admission rates, temperature and dew-point temperature, and PM10-2.5 and PM2.5 concentrations were calculated with monitoring data as an exposure surrogate from January 1, 1999, through December 31, 2005. Admission rates were constructed from the Medicare National Claims History Files, for a study population of approximately 12 million Medicare enrollees living on average 9 miles (14.4 km) from collocated pairs of PM10 and PM2.5 monitors. MAIN OUTCOME MEASURES Daily counts of county-wide emergency hospital admissions for primary diagnoses of cardiovascular or respiratory disease. RESULTS There were 3.7 million cardiovascular disease and 1.4 million respiratory disease admissions. A 10-microg/m3 increase in PM10-2.5 was associated with a 0.36% (95% posterior interval [PI], 0.05% to 0.68%) increase in cardiovascular disease admissions on the same day. However, when adjusted for PM2.5, the association was no longer statistically significant (0.25%; 95% PI, -0.11% to 0.60%). A 10-microg/m3 increase in PM10-2.5 was associated with a nonstatistically significant unadjusted 0.33% (95% PI, -0.21% to 0.86%) increase in respiratory disease admissions and with a 0.26% (95% PI, -0.32% to 0.84%) increase in respiratory disease admissions when adjusted for PM2.5. The unadjusted associations of PM2.5 with cardiovascular and respiratory disease admissions were 0.71% (95% PI, 0.45%-0.96%) for same-day exposure and 0.44% (95% PI, 0.06% to 0.82%) for exposure 2 days before hospital admission. CONCLUSION After adjustment for PM2.5, there were no statistically significant associations between coarse particulates and hospital admissions for cardiovascular and respiratory diseases.