Rationale: The heat-related risk of hospitalization for respiratory diseases among the elderly has not been quantified in the United States on a national scale. With climate change predictions of more frequent and more intense heat waves, it is of paramount importance to quantify the health risks related to heat, especially for the most vulnerable.
Objectives: To estimate the risk of hospitalization for respiratory diseases associated with outdoor heat in the U.S. elderly.
Methods: An observational study of approximately 12.5 million Medicare beneficiaries in 213 United States counties, January 1, 1999 to December 31, 2008. We estimate a national average relative risk of hospitalization for each 10°F (5.6°C) increase in daily outdoor temperature using Bayesian hierarchical models.
Measurements and Main Results: We obtained daily county-level rates of Medicare emergency respiratory hospitalizations (International Classification of Diseases, Ninth Revision, 464–466, 480–487, 490–492) in 213 U.S. counties from 1999 through 2008. Overall, each 10°F increase in daily temperature was associated with a 4.3% increase in same-day emergency hospitalizations for respiratory diseases (95% posterior interval, 3.8, 4.8%). Counties’ relative risks were significantly higher in counties with cooler average summer temperatures.
Conclusions: We found strong evidence of an association between outdoor heat and respiratory hospitalizations in the largest population of elderly studied to date. Given projections of increasing temperatures from climate change and the increasing global prevalence of chronic pulmonary disease, the relationship between heat and respiratory morbidity is a growing concern.
chronic obstructive pulmonary disease; hospitalization; hot temperature; respiratory tract infections; weather
Rationale: The effect of endotoxin on asthma morbidity in urban populations is unclear.
Objectives: To determine if indoor pollutant exposure modifies the relationships between indoor airborne endotoxin and asthma health and morbidity.
Methods: One hundred forty-six children and adolescents with persistent asthma underwent repeated clinical assessments at 0, 3, 6, 9, and 12 months. Home visits were conducted at the same time points for assessment of airborne nicotine, endotoxin, and nitrogen dioxide (NO2) concentrations. The effect of concomitant pollutant exposure on relationships between endotoxin and asthma outcomes were examined in stratified analyses and statistical models with interaction terms.
Measurements and Main Results: Both air nicotine and NO2 concentrations modified the relationships between airborne endotoxin and asthma outcomes. Among children living in homes with no detectable air nicotine, higher endotoxin was inversely associated with acute visits and oral corticosteroid bursts, whereas among those in homes with detectable air nicotine, endotoxin was positively associated with these outcomes (interaction P value = 0.004 and 0.07, respectively). Among children living in homes with lower NO2 concentrations (<20 ppb), higher endotoxin was positively associated with acute visits, whereas among those living in homes with higher NO2 concentrations, endotoxin was negatively associated with acute visit (interaction P value = 0.05). NO2 also modified the effect of endotoxin on asthma symptom outcomes in a similar manner.
Conclusions: The effects of household airborne endotoxin exposure on asthma are modified by coexposure to air nicotine and NO2, and these pollutants have opposite effects on the relationships between endotoxin and asthma-related outcomes.
childhood asthma; endotoxin; indoor pollution; nitrogen dioxide; second-hand smoke
Cockroach and mouse allergens have both been implicated as causes in
inner-city asthma morbidity in multicenter studies, but whether both
allergens are clinically relevant within specific inner-city communities is
unclear. Objective: Our study aimed to identify relevant allergens in
One hundred forty-four children (5–17 years old) with asthma
underwent skin prick tests at baseline and had clinical data collected at
baseline and 3, 6, 9, and 12 months. Home settled dust samples were
collected at the same time points for quantification of indoor allergens.
Participants were grouped based on their sensitization and exposure status
to each allergen. All analyses were adjusted for age, sex, and serum total
Forty-one percent were mouse sensitized/exposed, and 41% were
cockroach sensitized/exposed based on bedroom floor exposure data. Mouse
sensitization/exposure was associated with acute care visits, decreased
FEV1/forced vital capacity percentage values, fraction of
exhaled nitric oxide levels, and bronchodilator reversibility. Cockroach
sensitization/exposure was only associated with acute care visits and
bronchodilator reversibility when exposure was defined by using bedroom
floor allergen levels. Mouse-specific IgE levels were associated with poor
asthma health across a range of outcomes, whereas cockroach-specific IgE
levels were not. The relationships between asthma outcomes and mouse
allergen were independent of cockroach allergen. Although
sensitization/exposure to both mouse and cockroach was generally associated
with worse asthma, mouse sensitization/exposure was the primary contributor
to these relationships.
In a community with high levels of both mouse and cockroach
allergens, mouse allergen appears to be more strongly and consistently
associated with poor asthma outcomes than cockroach allergen.
Community-level asthma interventions in Baltimore should prioritize reducing
mouse allergen exposure.
Inner-city asthma; childhood asthma; mouse allergen; cockroach allergen; indoor allergens
Indoor particulate matter (PM) has been linked to respiratory symptoms in former smokers with COPD. While subjects with COPD and atopy have also been shown to have more frequent respiratory symptoms, whether they exhibit increased susceptibility to PM as compared to their non-atopic counterparts remains unclear. The aim of this study was to determine whether atopic individuals with COPD have greater susceptibility to PM compared to non-atopic individuals with COPD.
Former smokers with moderate to severe COPD were enrolled (n = 77). PM2.5, PM with diameter <2.5 micrometers, was measured in the main living area over three one-week monitoring periods at baseline, 3, and 6 months. Quality of life, respiratory symptoms and medication use were assessed by questionnaires. Serum was analyzed for specific IgE for mouse, cockroach, cat, dog and dust mite allergens. Atopy was established if at least one test was positive. Interaction terms between PM and atopy were tested and generalized estimating equation analysis determined the effect of PM concentrations on health outcomes. Multivariate models were adjusted for age, sex, education, race, season, and baseline lung function and stratified by atopic status.
Among atopic individuals, each 10 μg/m3 increase in PM was associated with higher risk of nocturnal symptoms (OR, 1.95; P = 0.02), frequent wheezing (OR, 2.49; P = 0.02), increased rescue medication use (β = 0.14; P = 0.02), dyspnea (β = 0.23; P < 0.001), higher St. George’s Respiratory Quality of Life score (β = 2.55; P = 0.01), and higher breathlessness, cough, and sputum score (BCSS) (β = 0.44; P = 0.01). There was no association between PM and health outcomes among the non-atopic individuals. Interaction terms between PM2.5 and atopy were statistically significant for nocturnal symptoms, frequency of rescue medication use, and BCSS (all P < 0.1).
Individuals with COPD and atopy appear to be at higher risk of adverse respiratory health effects of PM exposure compared to non-atopic individuals with COPD.
COPD; Atopy; Allergic sensitization; Pollutants; Particulate matter; PM; Indoor air; Susceptibility
Background: In a changing climate, increasing temperatures are anticipated to have profound health impacts. These impacts could be mitigated if individuals and communities adapt to changing exposures; however, little is known about the extent to which the population may be adapting.
Objective: We investigated the hypothesis that if adaptation is occurring, then heat-related mortality would be decreasing over time.
Methods: We used a national database of daily weather, air pollution, and age-stratified mortality rates for 105 U.S. cities (covering 106 million people) during the summers of 1987–2005. Time-varying coefficient regression models and Bayesian hierarchical models were used to estimate city-specific, regional, and national temporal trends in heat-related mortality and to identify factors that might explain variation across cities.
Results: On average across cities, the number of deaths (per 1,000 deaths) attributable to each 10°F increase in same-day temperature decreased from 51 [95% posterior interval (PI): 42, 61] in 1987 to 19 (95% PI: 12, 27) in 2005. This decline was largest among those ≥ 75 years of age, in northern regions, and in cities with cooler climates. Although central air conditioning (AC) prevalence has increased, we did not find statistically significant evidence of larger temporal declines among cities with larger increases in AC prevalence.
Conclusions: The population has become more resilient to heat over time. Yet even with this increased resilience, substantial risks of heat-related mortality remain. Based on 2005 estimates, an increase in average temperatures by 5°F (central climate projection) would lead to an additional 1,907 deaths per summer across all cities.
Citation: Bobb JF, Peng RD, Bell ML, Dominici F. 2014. Heat-related mortality and adaptation to heat in the United States. Environ Health Perspect 122:811–816; http://dx.doi.org/10.1289/ehp.1307392
The “Air Pollution and Health: A Combined European and North American Approach” (APHENA) project is a collaborative analysis of multi-city time-series data on the association between air pollution and adverse health outcomes. The main objective of APHENA was to examine the coherence of findings of time-series studies relating short-term fluctuations in air pollution levels to mortality and morbidity in 125 cities in Europe, the US, and Canada. Multi-city time-series analysis was conducted using a two-stage approach. We used Poisson regression models controlling for overdispersion with either penalized or natural splines to adjust for seasonality. Hierarchical models were used to obtain an overall estimate of excess mortality associated with ozone and to assess potential effect modification. Potential effect modifiers were city-level characteristics related to exposure to other ambient air pollutants, weather, socioeconomic status, and the vulnerability of the population. Regionally pooled risk estimates from Europe and the US were similar; those from Canada were substantially higher. The pooled estimated excess relative risk associated with a 10 µg/m3 increase in 1 h daily maximum O3 was 0.26 % (95 % CI, 0.15 %, 0.37 %). Across regions, there was little consistent indication of effect modification by age or other effect modifiers considered in the analysis. The findings from APHENA on the effects of O3 on mortality in the general population were comparable with previously reported results and relatively robust to the method of data analysis. Overall, there was no indication of strong effect modification by age or ecologic variables considered in the analysis.
Ozone; Mortality; Time-series; Multi-city; Cardiovascular; Respiratory
Rationale: The effect of indoor air pollutants on respiratory morbidity among patients with chronic obstructive pulmonary disease (COPD) in developed countries is uncertain.
Objectives: The first longitudinal study to investigate the independent effects of indoor particulate matter (PM) and nitrogen dioxide (NO2) concentrations on COPD morbidity in a periurban community.
Methods: Former smokers with COPD were recruited and indoor air was monitored over a 1-week period in the participant’s bedroom and main living area at baseline, 3 months, and 6 months. At each visit, participants completed spirometry and questionnaires assessing respiratory symptoms. Exacerbations were assessed by questionnaires administered at clinic visits and monthly telephone calls.
Measurements and Main Results: Participants (n = 84) had moderate or severe COPD with a mean FEV1 of 48.6% predicted. The mean (± SD) indoor PM2.5 and NO2 concentrations were 11.4 ± 13.3 µg/m3 and 10.8 ± 10.6 ppb in the bedroom, and 12.2 ± 12.2 µg/m3 and 12.2 ± 11.8 ppb in the main living area. Increases in PM2.5 concentrations in the main living area were associated with increases in respiratory symptoms, rescue medication use, and risk of severe COPD exacerbations. Increases in NO2 concentrations in the main living area were independently associated with worse dyspnea. Increases in bedroom NO2 concentrations were associated with increases in nocturnal symptoms and risk of severe COPD exacerbations.
Conclusions: Indoor pollutant exposure, including PM2.5 and NO2, was associated with increased respiratory symptoms and risk of COPD exacerbation. Future investigations should include intervention studies that optimize indoor air quality as a novel therapeutic approach to improving COPD health outcomes.
indoor air; chronic obstructive pulmonary disease; particulate matter; nitrogen dioxide; exacerbations
Hierarchical models (HM) have been used extensively in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for other pollutants and other time-varying factors. Recently, Environmental Protection Agency (EPA) has called for research quantifying health effects of simultaneous exposure to many air pollutants. However, straightforward application of HM in this context is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters. Here we introduce reduced HM as a general statistical approach for analyzing correlated data with many nuisance parameters. For reduced HM we first calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants), and we then specify a flexible random-effect distribution directly on this parameter. Simulation studies show that the reduced HM performs comparably to the full HM in many scenarios, and even performs better in some cases, particularly when the multivariate random-effect distribution of the full HM is misspecified. Methods are applied to estimate relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during 1999–2005.
Air pollution; Multilevel models; Multisite time series data; Nuisance parameters; Random effects
Epidemiological findings concerning the seasonal variation in the acute effect of particulate matter (PM) are inconsistent. We investigated the seasonality in the association between PM with an aerodynamic diameter of less than 10 μm (PM10) and daily mortality in 17 Chinese cities. We fitted the “main” time-series model after adjustment for time-varying confounders using smooth functions with natural splines. We established a “seasonal” model to obtain the season-specific effect estimates of PM10, and a “harmonic” model to show the seasonal pattern that allows PM10 effects to vary smoothly with the day in a year. At the national level, a 10 μg/m3 increase in the two-day moving average concentrations (lag 01) of PM10 was associated with 0.45% [95% posterior interval (PI), 0.15% to 0.76%], 0.17% (95% PI, −0.09% to 0.43%), 0.55% (95% PI, 0.15% to 0.96%) and 0.25% (95%PI, −0.05% to 0.56%) increases in total mortality for winter, spring, summer and fall, respectively. For the smoothly-varying plots of seasonality, we identified a two-peak pattern in winter and summer. The observed seasonal pattern was generally insensitive to model specifications. Our analyses suggest that the acute effect of particulate air pollution could vary by seasons with the largest effect in winter and summer in China. To our knowledge, this is the first multicity study in developing countries to analyze the seasonal variations of PM-related health effects.
Seasonality; Air pollution; Particulate matter; Mortality; Time series
Both being overweight and exposure to indoor pollutants, which have been associated with worse health of asthmatic patients, are common in urban minority populations. Whether being overweight is a risk factor for the effects of indoor pollutant exposure on asthma health is unknown.
We sought to examine the effect of weight on the relationship between indoor pollutant exposure and asthma health in urban minority children.
One hundred forty-eight children (age, 5–17 years) with persistent asthma were followed for 1 year. Asthma symptoms, health care use, lung function, pulmonary inflammation, and indoor pollutants were assessed every 3 months. Weight category was based on body mass index percentile.
Participants were predominantly African American (91%) and had public health insurance (85%). Four percent were underweight, 52% were normal weight, 16% were overweight, and 28% were obese. Overweight or obese participants had more symptoms associated with exposure to fine particulate matter measuring less than 2.5 μm in diameter (PM2.5) than normal-weight participants across a range of asthma symptoms. Overweight or obese participants also had more asthma symptoms associated with nitrogen dioxide (NO2) exposure than normal-weight participants, although this was not observed across all types of asthma symptoms. Weight did not affect the relationship between exposure to coarse particulate matter measuring between 2.5 and 10 μm in diameter and asthma symptoms. Relationships between indoor pollutant exposure and health care use, lung function, or pulmonary inflammation did not differ by weight.
Being overweight or obese can increase susceptibility to indoor PM2.5 and NO2 in urban children with asthma. Interventions aimed at weight loss might reduce asthma symptom responses to PM2.5 and NO2, and interventions aimed at reducing indoor pollutant levels might be particularly beneficial in overweight children.
Asthma; overweight; obesity; indoor pollutants childhood asthma; inner-city asthma
Vitamin D; wheeze; asthma; age
Background: Epidemiological studies have demonstrated associations between short-term exposure to PM2.5 and hospital admissions. The chemical composition of particles varies across locations and time periods. Identifying the most harmful constituents and sources is an important health and regulatory concern.
Objectives: We examined pollutant sources for associations with risk of hospital admissions for cardiovascular and respiratory causes.
Methods: We obtained PM2.5 filter samples for four counties in Connecticut and Massachusetts and analyzed them for PM2.5 elements. Source apportionment was used to estimate daily PM2.5 contributions from sources (traffic, road dust, oil combustion, and sea salt as well as a regional source representing coal combustion and other sources). Associations between daily PM2.5 constituents and sources and risk of cardiovascular and respiratory hospitalizations for the Medicare population (> 333,000 persons ≥ 65 years of age) were estimated with time-series analyses (August 2000–February 2004).
Results: PM2.5 total mass and PM2.5 road dust contribution were associated with cardiovascular hospitalizations, as were the PM2.5 constituents calcium, black carbon, vanadium, and zinc. For respiratory hospitalizations, associations were observed with PM2.5 road dust, and sea salt as well as aluminum, calcium, chlorine, black carbon, nickel, silicon, titanium, and vanadium. Effect estimates were generally robust to adjustment by co-pollutants of other constituents. An interquartile range increase in same-day PM2.5 road dust (1.71 μg/m3) was associated with a 2.11% (95% CI: 1.09, 3.15%) and 3.47% (95% CI: 2.03, 4.94%) increase in cardiovascular and respiratory admissions, respectively.
Conclusions: Our results suggest some particle sources and constituents are more harmful than others and that in this Connecticut/Massachusetts region the most harmful particles include black carbon, calcium, and road dust PM2.5.
Citation: Bell ML, Ebisu K, Leaderer BP, Gent JF, Lee HJ, Koutrakis P, Wang Y, Dominici F, Peng RD. 2014. Associations of PM2.5 constituents and sources with hospital admissions: analysis of four counties in Connecticut and Massachusetts (USA) for persons ≥ 65 years of age. Environ Health Perspect 122:138–144; http://dx.doi.org/10.1289/ehp.1306656
There is a need for a readily available, non-invasive source of biomarkers that predict poor asthma control.
We sought to determine if there is an association between the salivary inflammatory profile and disease control in children and adults with asthma.
In this cross-sectional study, we collected demographic and clinical information from two independent populations at different sites, resulting in convenience samples of 58 pediatric and 122 adult urban asthmatics. Control was assessed by symptom questionnaire (children) and by Asthma Control Questionnaire and current exacerbation (adults). Saliva was collected in all subjects. We applied principal component analysis to a 10-plex panel of relevant inflammatory markers to characterize marker profiles and determined if profiles were associated with asthma control.
There were similar, strong correlations amongst biologically related markers in both populations: eosinophil-related: eotaxin-1/CCL11, RANTES/CCL5, and IL-5 (p<.001); myeloid/innate: IL-1β, IL-6, MCP-1/CCL2, and IL-8/CXCL8 (p<.001). The first three principal components captured ≥74% of variability across all ten analytes in both populations. In adults, the Principal Component 1 score, broadly reflective of all markers, but with greater weight given to myeloid/innate markers, was associated with Asthma Control Questionnaire score and exacerbation. The Principal Component 3 score, reflective of IP-10/CXCL10, was associated with current exacerbation. In children, the Principal Component 1, 2, and 3 scores were associated with recent asthma symptoms. The Principal Component 2 score, reflective of higher eosinophil markers, was inversely correlated with symptoms. The Principal Component 3 score was positively associated with all symptom outcomes.
The salivary inflammatory profile is associated with disease control in children and adults with asthma.
Epidemiologic studies have linked tropospheric ozone pollution and human mortality. Although research has shown that this relation is not confounded by particulate matter when measured by mass, little scientific evidence exists on whether confounding exists by chemical components of the particle mixture. Using mortality and particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) component data from 57 US communities (2000–2005), the authors investigate whether the ozone-mortality relation is confounded by 7 components of PM2.5: sulfate, nitrate, silicon, elemental carbon, organic carbon matter, sodium ion, and ammonium. Together, these components constitute most PM2.5 mass in the United States. Estimates of the effect of ozone on mortality were almost identical before and after controlling for the 7 components of PM2.5 considered (mortality increase/10-ppb ozone increase, before and after controlling: ammonium, 0.34% vs. 0.35%; elemental carbon, 0.36% vs. 0.37%; nitrate, 0.27% vs. 0.26%; organic carbon matter, 0.34% vs. 0.31%; silicon, 0.36% vs. 0.37%; sodium ion, 0.21% vs. 0.18%; and sulfate, 0.35% vs. 0.38%). Additionally, correlations were weak between ozone and each particulate component across all communities. Previous research found that the ozone-mortality relation is not confounded by particulate matter measured by mass; this national study indicates that the relation is also robust to control for specific components of PM2.5.
air pollution; confounding factors; mortality; ozone; particulate matter
Background: Although the association between PM2.5 mass and mortality has been extensively studied, few national-level analyses have estimated mortality effects of PM2.5 chemical constituents. Epidemiologic studies have reported that estimated effects of PM2.5 on mortality vary spatially and seasonally. We hypothesized that associations between PM2.5 constituents and mortality would not vary spatially or seasonally if variation in chemical composition contributes to variation in estimated PM2.5 mortality effects.
Objectives: We aimed to provide the first national, season-specific, and region-specific associations between mortality and PM2.5 constituents.
Methods: We estimated short-term associations between nonaccidental mortality and PM2.5 constituents across 72 urban U.S. communities from 2000 to 2005. Using U.S. Environmental Protection Agency (EPA) Chemical Speciation Network data, we analyzed seven constituents that together compose 79–85% of PM2.5 mass: organic carbon matter (OCM), elemental carbon (EC), silicon, sodium ion, nitrate, ammonium, and sulfate. We applied Poisson time-series regression models, controlling for time and weather, to estimate mortality effects.
Results: Interquartile range increases in OCM, EC, silicon, and sodium ion were associated with estimated increases in mortality of 0.39% [95% posterior interval (PI): 0.08, 0.70%], 0.22% (95% PI: 0.00, 0.44), 0.17% (95% PI: 0.03, 0.30), and 0.16% (95% PI: 0.00, 0.32), respectively, based on single-pollutant models. We did not find evidence that associations between mortality and PM2.5 or PM2.5 constituents differed by season or region.
Conclusions: Our findings indicate that some constituents of PM2.5 may be more toxic than others and, therefore, regulating PM total mass alone may not be sufficient to protect human health.
Citation: Krall JR, Anderson GB, Dominici F, Bell ML, Peng RD. 2013. Short-term exposure to particulate matter constituents and mortality in a national study of U.S. urban communities. Environ Health Perspect 121:1148–1153; http://dx.doi.org/10.1289/ehp.1206185
Background: Environmental health research employs a variety of metrics to measure heat exposure, both to directly study the health effects of outdoor temperature and to control for temperature in studies of other environmental exposures, including air pollution. To measure heat exposure, environmental health studies often use heat index, which incorporates both air temperature and moisture. However, the method of calculating heat index varies across environmental studies, which could mean that studies using different algorithms to calculate heat index may not be comparable.
Objective and Methods: We investigated 21 separate heat index algorithms found in the literature to determine a) whether different algorithms generate heat index values that are consistent with the theoretical concepts of apparent temperature and b) whether different algorithms generate similar heat index values.
Results: Although environmental studies differ in how they calculate heat index values, most studies’ heat index algorithms generate values consistent with apparent temperature. Additionally, most different algorithms generate closely correlated heat index values. However, a few algorithms are potentially problematic, especially in certain weather conditions (e.g., very low relative humidity, cold weather). To aid environmental health researchers, we have created open-source software in R to calculate the heat index using the U.S. National Weather Service’s algorithm.
Conclusion: We identified 21 separate heat index algorithms used in environmental research. Our analysis demonstrated that methods to calculate heat index are inconsistent across studies. Careful choice of a heat index algorithm can help ensure reproducible and consistent environmental health research.
Citation: Anderson GB, Bell ML, Peng RD. 2013. Methods to calculate the heat index as an exposure metric in environmental health research. Environ Health Perspect 121:1111–1119; http://dx.doi.org/10.1289/ehp.1206273
Season of birth has been reported as a risk factor for food allergy, but the mechanisms by which it acts are unknown.
Two populations were studied; 5862 children from the National Health and Nutrition Examination Survey (NHANES) III, 1514 well-characterized food allergic children from the Johns Hopkins Pediatric Allergy Clinic (JHPAC). Food allergy was defined as self report of an acute reaction to a food (NHANES), or as milk, egg and peanut allergy. Logistic regression compared fall or non-fall birth between (1) food allergic and non-allergic subjects in NHANES, adjusted for ethnicity, age, income and sex, and (2) JHPAC subjects and the general Maryland population. For NHANES, stratification by ethnicity and for JHPAC, eczema, was examined.
Fall birth was more common among food allergic subjects in both NHANES (OR: 1.91, 95%CI: 1.31–2.77) and JHPAC/Maryland (OR: 1.31, 95%CI: 1.18–1.47). Ethnicity interacted with season (OR 2.34, 95%CI 1.43–3.82 for Caucasians, OR 1.19, 95%CI 0.77–1.86 for non-Caucasians, p=0.04 for interaction), as did eczema (OR 1.47, 95%CI 1.29–1.67 with eczema, OR 1.00, 95%CI 0.80–1.23 without eczema, p=0.002 for interaction).
Fall birth is associated with increased risk of food allergy, and this risk is greatest among those most likely to have seasonal variation in vitamin D during infancy (Caucasians) and those at risk for skin barrier dysfunction (subjects with a history of eczema), suggesting that vitamin D and the skin barrier may be implicated in seasonal associations with food allergy.
food allergy; season of birth; eczema; vitamin D
Evidence on the health risks associated with short-term exposure to fine particles (particulate matter ≤2.5 μm in aerodynamic diameter [PM2.5]) is limited. Results from the new national monitoring network for PM2.5 make possible systematic research on health risks at national and regional scales.
To estimate risks of cardiovascular and respiratory hospital admissions associated with short-term exposure to PM2.5 for Medicare enrollees and to explore heterogeneity of the variation of risks across regions.
Design, Setting, and Participants
A national database comprising daily time-series data daily for 1999 through 2002 on hospital admission rates (constructed from the Medicare National Claims History Files) for cardiovascular and respiratory outcomes and injuries, ambient PM2.5 levels, and temperature and dew-point temperature for 204 US urban counties (population >200 000) with 11.5 million Medicare enrollees (aged >65 years) living an average of 5.9 miles from a PM2.5 monitor.
Main Outcome Measures
Daily counts of county-wide hospital admissions for primary diagnosis of cerebrovascular, peripheral, and ischemic heart diseases, heart rhythm, heart failure, chronic obstructive pulmonary disease, and respiratory infection, and injuries as a control outcome.
There was a short-term increase in hospital admission rates associated with PM2.5 for all of the health outcomes except injuries. The largest association was for heart failure, which had a 1.28% (95% confidence interval, 0.78%–1.78%) increase in risk per 10-μg/m3 increase in same-day PM2.5. Cardiovascular risks tended to be higher in counties located in the Eastern region of the United States, which included the Northeast, the Southeast, the Midwest, and the South.
Short-term exposure to PM2.5 increases the risk for hospital admission for cardiovascular and respiratory diseases.
Computational science has led to exciting new developments, but the nature of the work has exposed limitations in our ability to evaluate published findings. Reproducibility has the potential to serve as a minimum standard for judging scientific claims when full independent replication of a study is not possible.
Estimating the risks heat waves pose to human health is a critical part of assessing the future impact of climate change. In this paper we propose a flexible class of time series models to estimate the relative risk of mortality associated with heat waves and conduct Bayesian model averaging (BMA) to account for the multiplicity of potential models. Applying these methods to data from 105 U.S. cities for the period 1987–2005, we identify those cities having a high posterior probability of increased mortality risk during heat waves, examine the heterogeneity of the posterior distributions of mortality risk across cities, assess sensitivity of the results to the selection of prior distributions, and compare our BMA results to a model selection approach. Our results show that no single model best predicts risk across the majority of cities, and that for some cities heat wave risk estimation is sensitive to model choice. While model averaging leads to posterior distributions with increased variance as compared to statistical inference conditional on a model obtained through model selection, we find that the posterior mean of heat wave mortality risk is robust to accounting for model uncertainty over a broad class of models.
Climate change; Generalized Additive Models; Model Uncertainty; Time series data
As climate continues to change, scientists are left to analyze the effects these changes will have on the public. In this article, a flexible class of distributed lag models are used to analyze the effects of heat on mortality in four major metropolitan areas in the U.S. (Chicago, Dallas, Los Angeles, and New York). Specifically, the proposed methodology uses Gaussian processes as a prior model for the distributed lag function. Gaussian processes are adequately flexible to capture a wide variety of distributed lag functions while ensuring smoothness properties of process realizations. Additionally, the proposed framework allows for probabilistic inference of the maximum lag. Applying the proposed methodology revealed that mortality displacement (or, harvesting) was present for most age groups and cities analyzed suggesting that heat advanced death in some individuals. Additionally, the estimated shape of the DL functions gave evidence that prolonged heat exposure and highly variable temperatures pose a threat to public health.
Climate change; Gaussian process; Public health; Harvesting