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1.  Estimating Causal Associations of Fine Particles With Daily Deaths in Boston 
American Journal of Epidemiology  2015;182(7):644-650.
Many studies have reported associations between daily particles less than 2.5 µm in aerodynamic diameter (PM2.5) and deaths, but they have been associational studies that did not use formal causal modeling approaches. On the basis of a potential outcome approach, we used 2 causal modeling methods with different assumptions and strengths to address whether there was a causal association between daily PM2.5 and deaths in Boston, Massachusetts (2004–2009). We used an instrumental variable approach, including back trajectories as instruments for variations in PM2.5 uncorrelated with other predictors of death. We also used propensity score as an alternative causal modeling analysis. The former protects against confounding by measured and unmeasured confounders and is based on the assumption of a valid instrument. The latter protects against confounding by all measured covariates, provides valid estimates in the case of effect modification, and is based on the assumption of no unmeasured confounders. We found a causal association of PM2.5 with mortality, with a 0.53% (95% confidence interval: 0.09, 0.97) and a 0.50% (95% confidence interval: 0.20, 0.80) increase in daily deaths using the instrumental variable and the propensity score, respectively. We failed to reject the null association with exposure after the deaths (P =0.93). Given these results, prior studies, and extensive toxicological support, the association between PM2.5 and deaths is almost certainly causal.
PMCID: PMC4692977  PMID: 26346544
causal model; instrumental variables; mortality; particulate pollution; propensity score
2.  Rising atmospheric CO2 increases global threat of zinc deficiency 
The Lancet. Global health  2015;3(10):e639-e645.
Increasing concentrations of atmospheric carbon dioxide (CO2) lower the content of zinc and other nutrients in important food crops. Zinc deficiency is currently responsible for large burdens of disease globally, and those populations who are at highest risk for zinc deficiency also receive most of their dietary zinc from crops. By modeling dietary intake of bioavailable zinc for the populations of 188 countries under both an ambient CO2 and elevated CO2 scenario, we sought to estimate the impact of anthropogenic CO2 emissions on the global risk of zinc deficiency.
We used established methods of estimating per capita per day bioavailable intake of zinc for the populations of 188 countries at ambient CO2 concentrations. We then modeled zinc intake at elevated and ambient CO2 concentrations and estimated the risk for inadequate zinc intake among the populations of different nations under the two scenarios (ambient and elevated CO2) by calculating population-weighted estimated average requirements (EARs), and using the EAR cut-point based method. We then compared the size of the populations at risk under the two scenarios in each country.
Anthropogenic emissions of CO2 are likely to place between 132 million—180 million people at new risk of zinc deficiency by around 2050. The people likely to be most affected live in Africa and South Asia, with nearly 48 million residing in India alone. Global maps of increased risk show significant heterogeneity and can be used to help guide interventions aimed at reducing this vulnerability.
Our results indicate that one heretofore unquantified human health impact associated with anthropogenic CO2 emissions will be a significant increase in the human population at risk for zinc deficiency.
PMCID: PMC4784541  PMID: 26189102
3.  Temperature Variability and Mortality: A Multi-Country Study 
Environmental Health Perspectives  2016;124(10):1554-1559.
The evidence and method are limited for the associations between mortality and temperature variability (TV) within or between days.
We developed a novel method to calculate TV and investigated TV-mortality associations using a large multicountry data set.
We collected daily data for temperature and mortality from 372 locations in 12 countries/regions (Australia, Brazil, Canada, China, Japan, Moldova, South Korea, Spain, Taiwan, Thailand, the United Kingdom, and the United States). We calculated TV from the standard deviation of the minimum and maximum temperatures during the exposure days. Two-stage analyses were used to assess the relationship between TV and mortality. In the first stage, a Poisson regression model allowing over-dispersion was used to estimate the community-specific TV-mortality relationship, after controlling for potential confounders. In the second stage, a meta-analysis was used to pool the effect estimates within each country.
There was a significant association between TV and mortality in all countries, even after controlling for the effects of daily mean temperature. In stratified analyses, TV was still significantly associated with mortality in cold, hot, and moderate seasons. Mortality risks related to TV were higher in hot areas than in cold areas when using short TV exposures (0–1 days), whereas TV-related mortality risks were higher in moderate areas than in cold and hot areas when using longer TV exposures (0–7 days).
The results indicate that more attention should be paid to unstable weather conditions in order to protect health. These findings may have implications for developing public health policies to manage health risks of climate change.
Guo Y, Gasparrini A, Armstrong BG, Tawatsupa B, Tobias A, Lavigne E, Coelho MS, Pan X, Kim H, Hashizume M, Honda Y, Guo YL, Wu CF, Zanobetti A, Schwartz JD, Bell ML, Overcenco A, Punnasiri K, Li S, Tian L, Saldiva P, Williams G, Tong S. 2016. Temperature variability and mortality: a multi-country study. Environ Health Perspect 124:1554–1559;
PMCID: PMC5047764  PMID: 27258598
4.  Long-Term Exposure to Ambient Fine Particulate Matter and Renal Function in Older Men: The Veterans Administration Normative Aging Study 
Environmental Health Perspectives  2016;124(9):1353-1360.
It is unknown if ambient fine particulate matter (PM2.5) is associated with lower renal function, a cardiovascular risk factor.
We investigated whether long-term PM2.5 exposure was associated with estimated glomerular filtration rate (eGFR) in a cohort of older men living in the Boston Metropolitan area.
This longitudinal analysis included 669 participants from the Veterans Administration Normative Aging Study with up to four visits between 2000 and 2011 (n = 1,715 visits). Serum creatinine was measured at each visit, and eGFR was calculated according to the Chronic Kidney Disease Epidemiology Collaboration equation. One-year exposure to PM2.5 prior to each visit was assessed using a validated spatiotemporal model that utilized satellite remote-sensing aerosol optical depth data. eGFR was modeled in a time-varying linear mixed-effects regression model as a continuous function of 1-year PM2.5, adjusting for important covariates.
One-year PM2.5 exposure was associated with lower eGFRs; a 2.1-μg/m3 interquartile range higher 1-year PM2.5 was associated with a 1.87 mL/min/1.73 m2 lower eGFR [95% confidence interval (CI): –2.99, –0.76]. A 2.1 μg/m3-higher 1-year PM2.5 was also associated with an additional annual decrease in eGFR of 0.60 mL/min/1.73 m2 per year (95% CI: –0.79, –0.40).
In this longitudinal sample of older men, the findings supported the hypothesis that long-term PM2.5 exposure negatively affects renal function and increases renal function decline.
Mehta AJ, Zanobetti A, Bind MC, Kloog I, Koutrakis P, Sparrow D, Vokonas PS, Schwartz JD. 2016. Long-term exposure to ambient fine particulate matter and renal function in older men: the VA Normative Aging Study. Environ Health Perspect 124:1353–1360;
PMCID: PMC5010417  PMID: 26955062
5.  The impact of nitrogen oxides concentration decreases on ozone trends in the USA 
Ozone (O3) has harmful effects on human health and ecosystems. In the USA, significant reductions of O3 precursors—nitrogen oxides (NOx) and volatile organic compounds (VOCs)—have not yielded proportionate decreases in O3. NOx is a major precursor of O3 as well as a quencher of O3 through NOx titration, which is especially important during the night and wintertime. In this study, we investigated the potential dual impact of NOx concentration decreases on recent O3 trends by season and time of day. We analyzed hourly O3 and NOx measurement data between 1994 and 2010 in the continental USA. Nationally, hourly O3 concentrations decreased by as much as −0.38 ppb/year with a standard error of 0.05 ppb/year during the warm season midday, but increased by as much as +0.30±0.04 ppb/year during the cold season. High O3 concentrations (≥75th percentile) during the warm season decreased significantly, however, there were notable increases in the cold season as well as warm season nighttime; we found that these increases were largely attributable to NOx decreases as less O3 is quenched. These O3 increases, or “penalties”, related to NOx reductions remained robust at a wide range of O3 concentrations (5th to 99th percentile), and even after accounting for VOC reductions and meteorological parameters, including temperature, wind speed, and water vapor pressure. In addition, we observed O3 penalties across rural, suburban, and urban areas. Nonetheless, peak O3 concentrations (99.9th percentile) were mitigated by NOx reductions. In addition, there was some suggestive evidence that VOC reductions have been more effective in reducing O3.
PMCID: PMC4988408  PMID: 27547271
Ozone; Nitrogen oxides; Air pollution; Trends
6.  Changing patterns of the temperature-mortality association by time and location in the US, and implications for climate change 
Environment international  2015;81:80-86.
The shape of the non-linear relationship between temperature and mortality varies among cities with different climatic conditions. There has been little examination of how these curves change over space and time. We evaluated the short-term effects of hot and cold temperatures on daily mortality over six 7-years periods in 211 US cities, comprising over 42 million deaths. Cluster analysis was used to group the cities according to similar temperatures and relative humidity. Temperature-mortality functions were calculated using B-splines to model the heat effect (lag 0) and the cold effect on mortality (moving average lag 1-5). The functions were then combined through meta-smoothing and subsequently analyzed by meta-regression. We identified eight clusters. At lag 0, Cluster 5 (West Coast) had a RR of 1.14 (95% CI: 1.11,1.17) for temperatures of 27°C vs 15.6 °C, and Cluster 6 (Gulf Coast) has a RR of 1.04 (95% CI: 1.03,1.05), suggesting that people are acclimated to their respective climates. Controlling for cluster effect in the multivariate-meta regression we found that across the US, the excess mortality from a 24-hr temperature of 27°C decreased over time from 10.6% to 0.9%. We found that the overall risk due to the heat effect is significantly affected by summer temperature mean and air condition usage, which could be a potential predictor in building climate-change scenarios.
PMCID: PMC4780576  PMID: 25965185
climate change; health effects; temperature; meta-smoothing
7.  Estimating Causal Effects of Long-Term PM2.5 Exposure on Mortality in New Jersey 
Environmental Health Perspectives  2016;124(8):1182-1188.
Many studies have reported the associations between long-term exposure to PM2.5 and increased risk of death. However, to our knowledge, none has used a causal modeling approach or controlled for long-term temperature exposure, and few have used a general population sample.
We estimated the causal effects of long-term PM2.5 exposure on mortality and tested the effect modifications by seasonal temperatures, census tract–level socioeconomic variables, and county-level health conditions.
We applied a variant of the difference-in-differences approach, which serves to approximate random assignment of exposure across the population and hence estimate a causal effect. Specifically, we estimated the association between long-term exposure to PM2.5 and mortality while controlling for geographical differences using dummy variables for each census tract in New Jersey, a state-wide time trend using dummy variables for each year from 2004 to 2009, and mean summer and winter temperatures for each tract in each year. This approach assumed that no variable changing differentially over time across space other than seasonal temperatures confounded the association.
For each interquartile range (2 μg/m3) increase in annual PM2.5, there was a 3.0% [95% confidence interval (CI): 0.2, 5.9%] increase in all natural-cause mortality for the whole population, with similar results for people > 65 years old [3.5% (95% CI: 0.1, 6.9%)] and people ≤ 65 years old [3.1% (95% CI: –1.8, 8.2%)]. The mean summer temperature and the mean winter temperature in a census tract significantly modified the effects of long-term exposure to PM2.5 on mortality. We observed a higher percentage increase in mortality associated with PM2.5 in census tracts with more blacks, lower home value, or lower median income.
Under the assumption of the difference-in-differences approach, we identified a causal effect of long-term PM2.5 exposure on mortality that was modified by seasonal temperatures and ecological socioeconomic status.
Wang Y, Kloog I, Coull BA, Kosheleva A, Zanobetti A, Schwartz JD. 2016. Estimating causal effects of long-term PM2.5 exposure on mortality in New Jersey. Environ Health Perspect 124:1182–1188;
PMCID: PMC4977041  PMID: 27082965
8.  Chronic effects of temperature on mortality in the Southeastern USA using satellite-based exposure metrics 
Scientific Reports  2016;6:30161.
Climate change may affect human health, particularly for elderly individuals who are vulnerable to temperature changes. While many studies have investigated the acute effects of heat, only a few have dealt with the chronic ones. We have examined the effects of seasonal temperatures on survival of the elderly in the Southeastern USA, where a large fraction of subpopulation resides. We found that both seasonal mean temperature and its standard deviation (SD) affected long-term survival among the 13 million Medicare beneficiaries (aged 65+) in this region during 2000–2013. A 1 °C increase in summer mean temperature corresponded to an increase of 2.5% in death rate. Whereas, 1 °C increase in winter mean temperature was associated with a decrease of 1.5%. Increases in seasonal temperature SD also influence mortality. We decomposed seasonal mean temperature and its temperature SD into long-term geographic contrasts between ZIP codes and annual anomalies within ZIP code. Effect modifications by different subgroups were also examined to find out whether certain individuals are more vulnerable. Our findings will be critical to future efforts assessing health risks related to the future climate change.
PMCID: PMC4951799  PMID: 27436237
10.  Changes in Susceptibility to Heat During the Summer: A Multicountry Analysis 
American Journal of Epidemiology  2016;183(11):1027-1036.
Few studies have examined the variation in mortality risk associated with heat during the summer. Here, we apply flexible statistical models to investigate the issue by using a large multicountry data set. We collected daily time-series data of temperature and mortality from 305 locations in 9 countries, in the period 1985–2012. We first estimated the heat-mortality relationship in each location with time-varying distributed lag non-linear models, using a bivariate spline to model the exposure-lag-response over lag 0–10. Estimates were then pooled by country through multivariate meta-analysis. Results provide strong evidence of a reduction in risk over the season. Relative risks for the 99th percentile versus the minimum mortality temperature were in the range of 1.15–2.03 in early summer. In late summer, the excess was substantially reduced or abated, with relative risks in the range of 0.97–1.41 and indications of wider comfort ranges and higher minimum mortality temperatures. The attenuation is mainly due to shorter lag periods in late summer. In conclusion, this multicountry analysis suggests a reduction of heat-related mortality risk over the summer, which can be attributed to several factors, such as true acclimatization, adaptive behaviors, or harvesting effects. These findings may have implications on public health policies and climate change health impact projections.
PMCID: PMC4887574  PMID: 27188948
adaptation; climate change; distributed lag models; heat; mortality; temperature
11.  Impacts of Temperature and its Variability on Mortality in New England 
Nature climate change  2015;5:988-991.
Rapid buildup of greenhouse gases is expected to increase the Earth surface mean temperature, with unclear effects on temperature variability1–3. This adds urgency to better understand the direct effects of the changing climate on human health. However, the effects of prolonged exposures to temperatures, which are important for understanding the public health burden, are unclear. Here we demonstrate that long-term survival was significantly associated with both seasonal mean values and standard deviations (SDs) of temperature among the Medicare population (aged 65+) in New England, and break that down into long-term contrasts between ZIP codes and annual anomalies. A rise in summer mean temperature of 1 °C was associated with 1.0% higher death rate whereas an increase in winter mean temperature corresponded to 0.6% lower mortality. Increases in temperature SDs for both summer and winter were harmful. The increased mortality in warmer summers was entirely due to anomalies, while it was long term average differences in summer SD across ZIP codes that drove the increased risk. For future climate scenarios, seasonal mean temperatures may in part account for the public health burden, but excess public health risk of climate change may also stem from changes of within season temperature variability.
PMCID: PMC4666547  PMID: 26640524
12.  PM2.5 and survival among older adults: Effect modification by particulate composition 
Epidemiology (Cambridge, Mass.)  2015;26(3):321-327.
Fine particulate (PM2.5) air pollution has been consistently linked to survival, but reported effect estimates are geographically heterogeneous. Exposure to different types of particle mixtures may explain some of this variation.
We used k-means cluster analyses to identify cities with similar pollution profiles, (i.e. PM2.5 composition) across the US. We examined the impact of PM2.5 on survival, and its variation across clusters of cities with similar PM2.5 composition, among Medicare enrollees in 81 US cities (2000–2010). We used time-varying annual PM2.5 averages, measured at ambient central monitoring sites, as the exposure of interest. We ran by-city Cox models, adjusting for individual data on previous cardiopulmonary-related hospitalizations and stratifying by follow-up time, age, gender and race. This eliminates confounding by factors varying across cities and long-term trends, focusing on year-to-year variations of air pollution around its city-specific mean and trend. We then pooled the city-specific effects using a random effects meta-regression. In this second stage, we also assessed effect modification by cluster membership and estimated cluster-specific PM2.5 effects.
We followed more than 19 million subjects and observed more than 6 million deaths. We found a harmful impact of annual PM2.5 concentrations on survival (HR = 1.11 [95% confidence interval = 1.01–1.23] per 10 µg/m3). This effect was modified by particulate composition, with higher effects observed in clusters containing high concentrations of nickel, vanadium and sulfate. For instance, our highest effect estimate was observed in cities with harbors in the Northwest, characterized by high nickel, vanadium and elemental carbon concentrations (1.9 [1.1–3.3]). We observed null or negative associations in clusters with high oceanic and crustal particles.
To our knowledge, this is the first study to examine the association between PM2.5 composition and survival. Our findings indicate that long-term exposure to fuel oil combustion and power plant emissions have the highest impact on survival.
PMCID: PMC4675621  PMID: 25738903
13.  Cardiorespiratory treatments as modifiers of the relationship between particulate matter and health: a case-only analysis on hospitalized patients in Italy 
Environmental research  2014;136:491-499.
A few panel and toxicological studies suggest that health effects of particulate matter (PM) might be modified by medication intake, but whether this modification is confirmed in the general population or for more serious outcomes is still unknown.
We carried out a population-based pilot study in order to assess how pre-hospitalization medical treatments modify the relationship between PM < 10 µm in aerodynamic diameter (PM10) and the risk of cardiorespiratory admission.
We gathered information on hospitalizations for cardiorespiratory causes, together with pre-admission pharmacological treatments, that occurred during 2005 in seven cities located in Lombardy (Northern Italy). City-specific PM10 concentrations were measured at fixed monitoring stations. Each treatment of interest was analyzed separately through a case-only approach, using generalized additive models accounting for sex, age, comorbidities, temperature and simultaneous intake of other drugs. Analyses were stratified by season and, if useful, by age and sex.
Our results showed a higher effect size for PM10 on respiratory admissions in subjects treated with theophylline (Odds Ratio (OR) of treatment for an increment of 10 µg/m3 in PM10 concentration: 1.119; 95% Confidence Interval (CI), 1.013 – 1.237), while for cardiovascular admissions treatment with cardiac therapy (OR: 0.967, 95% CI, 0.940 – 0.995) and lipid modifying agents (OR: 0.962, 95% CI, 0.931 – 0.995) emerged as a protective factor, especially during the warm season. Evidence of a protective effect against the pollutant was found for glucocorticoids and respiratory admissions.
Our study showed that the treatment with cardiac therapy and lipid modifying agents might mitigate the effect of PM10 on cardiovascular health, while the use of theophylline seems to enhance the effect of the pollutant, possibly due to confounding by indication. It is desirable to extend the analyses to a larger population.
PMCID: PMC4822335  PMID: 25460671
particulate matter; pharmacological treatments; effect modification; case-only analysis
15.  Ambient air pollution, lung function and airway responsiveness in children with asthma 
Although ambient air pollution has been linked to reduced lung function in healthy children, longitudinal analyses of pollution effects in asthma are lacking.
To investigate pollution effects in a longitudinal asthma study and effect modification by controller medications.
We examined associations of lung function and methacholine responsiveness (PC20) with ozone, carbon monoxide (CO), nitrogen dioxide (NO2) and sulfur dioxide (SO2) levels in 1,003 asthmatic children participating in a 4-year clinical trial. We further investigated whether budesonide and nedocromil modified pollution effects. Daily pollutant concentrations were linked to zip/postal code of residence. Linear mixed models tested associations of within-subject pollutant concentrations with FEV1 and FVC %predicted, FEV1/FVC and PC20, adjusting for seasonality and confounders.
Same-day and 1-week average CO levels were negatively associated with post-bronchodilator %predicted FEV1 (change(95%CI) per IQR: −0.33(−0.49, −0.16), −0.41(−0.62, −0.21), respectively) and FVC (−0.19(−0.25, −0.07), −0.25(−0.43, −0.07)). Longer-term four-month averages of CO were negatively associated with prebronchodilator %predicted FEV1 and FVC (−0.36(−0.62, −0.10), −0.21(−0.42, −0.01)). Four-month averaged CO and ozone levels were negatively associated with FEV1/FVC (p<0.05). Increased four-month average NO2 levels were associated with reduced post-bronchodilator FEV1 and FVC %predicted. Long-term exposures to SO2 were associated with reduced PC20 (%change(95%CI) per IQR:-6(-11,-1.5)). Treatment augmented the negative short-term CO effect on PC20.
Air pollution adversely influences lung function and PC20 in asthmatic children. Treatment with controller medications may not protect but worsens the CO effects on PC20. This clinical trial design evaluates modification of pollution effects by treatment without confounding by indication.
PMCID: PMC4742428  PMID: 26187234
asthma; ambient air pollution; airway hyperresponsiveness; inhaled corticosteroids; lung function
16.  Effect of daily temperature range on respiratory health in Argentina and its modification by impaired socio-economic conditions and PM10 exposures 
Epidemiological investigations regarding temperature influence on human health have focused on mortality rather than morbidity. In addition, most information comes from developed countries despite the increasing evidence that climate change will have devastating impacts on disadvantaged populations living in developing countries. In the present study, we assessed the impact of daily temperature range on upper and lower respiratory infections in Cordoba, Argentina, and explored the effect modification of socio-economic factors and influence of airborne particles We found that temperature range is a strong risk factor for admissions due to both upper and lower respiratory infections, particularly in elderly individuals, and that these effects are more pronounced in sub-populations with low education level or in poor living conditions. These results indicate that socio-economic factors are strong modifiers of the association between temperature variability and respiratory morbidity, thus they should be considered in risk assessments.
PMCID: PMC4739786  PMID: 26164202
daily temperature range; respiratory infections; socio-economic conditions; education; morbidity
17.  Ozone Trends and their Relationship to Characteristic Weather Patterns 
Local trends in ozone concentration may differ by meteorological conditions. Furthermore, the trends occurring at the extremes of the Ozone distribution are often not reported even though these may be very different than the trend observed at the mean or median and they may be more relevant to health outcomes.
Classify days of observation over a 16 year period into broad categories that capture salient daily local weather characteristics. Determine the rate of change in mean and median O3 concentrations within these different categories to assess how concentration trends are impacted by daily weather. Further examine if trends vary for observations in the extremes of the O3 distribution.
We used k-means clustering to categorize days of observation based on the maximum daily temperature, standard deviation of daily temperature, mean daily ground level wind speed, mean daily water vapor pressure and mean daily sea-level barometric pressure. The five cluster solution was determined to be the appropriate one based on cluster diagnostics and cluster interpretability. Trends in cluster frequency and pollution trends within clusters were modeled using Poisson regression with penalized splines as well as quantile regression.
There were five characteristic groupings identified. The frequency of days with large standard deviations in hourly temperature decreased over the observation period, whereas the frequency of warmer days with smaller deviations in temperature increased. O3 trends were significantly different within the different weather groupings. Furthermore, the rate of O3 change for the 95th percentile and 5th percentile was significantly different than the rate of change of the median for several of the weather categories.
We found that O3 trends vary between different characteristic local weather patterns. O3 trends were significantly different between the different weather groupings suggesting an important interaction between changes in prevailing weather conditions and O3 concentration.
PMCID: PMC4739788  PMID: 25004934
18.  Associations of Inter- and Intraday Temperature Change With Mortality 
American Journal of Epidemiology  2016;183(4):286-293.
In this study we evaluated the association between temperature variation and mortality and compared it with the contribution due to mean daily temperature in 6 cities with different climates. Quasi-Poisson time series regression models were applied to estimate the associations (relative risk and 95% confidence interval) of mean daily temperature (99th and 1st percentiles, with temperature of minimum mortality as the reference category), interday temperature variation (difference between the mean temperatures of 2 neighboring days) and intraday temperature variation (diurnal temperature range (DTR)) (referred to as median variation) with mortality in 6 cities: London, United Kingdom; Madrid, Spain; Stockholm, Sweden; New York, New York; Miami, Florida; and Houston, Texas (date range, 1985–2010). All cities showed a substantial increase in mortality risk associated with mean daily temperature, with relative risks reaching 1.428 (95% confidence interval (CI): 1.329, 1.533) for heat in Madrid and 1.467 (95% CI: 1.385, 1.555) for cold in London. Inconsistent results for inter-/intraday change were obtained, except for some evidence of protective associations on hot and cold days (relative risk (RR) = 0.977 (95% CI: 0.955, 0.999) and RR = 0.981 (95% CI: 0.971, 0.991), respectively) in Madrid and on cold days in Stockholm (RR = 0.989, 95% CI: 0.980, 0.998). Our results indicate that the association between mortality and temperature variation is generally minimal compared with mean daily temperatures, although further research on intraday changes is needed.
PMCID: PMC4753281  PMID: 26811244
ambient temperature; diurnal temperature range; mortality; temperature variation
19.  Prenatal Exposure to Traffic Pollution: Associations with Reduced Fetal Growth and Rapid Infant Weight Gain 
Prenatal air pollution exposure inhibits fetal growth, but implications for postnatal growth are unknown.
We assessed weights and lengths of US infants in the Project Viva cohort at birth and 6 months. We estimated third-trimester residential air pollution exposures using spatiotemporal models. We estimated neighborhood traffic density and roadway proximity at birth address using geographic information systems. We performed linear and logistic regression adjusted for sociodemographic variables, fetal growth, and gestational age at birth.
Mean birth weight-for-gestational age z-score (fetal growth) was 0.17 (SD = 0.97; n=2,114), 0-6 month weight-for-length gain was 0.23 z-units (SD = 1.11; n=689), and 17% had weight-for-length ≥95th percentile at 6 months of age. Infants exposed to the highest (vs. lowest) quartile of neighborhood traffic density had lower fetal growth (−0.13 units [95% confidence interval (CI) = −0.25 to −0.01]), more rapid 0-6 month weight-for-length gain (0.25 units [95% CI = 0.01 to 0.49]), and higher odds of weight-for-length ≥95th percentile at 6 months (1.84 [95% CI = 1.11 to 3.05]). Neighborhood traffic density was additionally associated with an infant being in both the lowest quartile of fetal growth and highest quartile of 0-6 month weight-for-length gain (Q4 vs. Q1, OR = 3.01 [95% CI = 1.08 to 8.44]). Roadway proximity and third-trimester black carbon exposure were similarly associated with growth outcomes. For third-trimester PM2.5, effect estimates were in the same direction, but smaller and imprecise.
Infants exposed to higher traffic-related pollution in early life may exhibit more rapid postnatal weight gain in addition to reduced fetal growth.
PMCID: PMC4285344  PMID: 25437317
20.  Low-Concentration PM2.5 and Mortality: Estimating Acute and Chronic Effects in a Population-Based Study 
Both short- and long-term exposures to fine particulate matter (≤ 2.5 μm; PM2.5) are associated with mortality. However, whether the associations exist at levels below the new U.S. Environmental Protection Agency (EPA) standards (12 μg/m3 of annual average PM2.5, 35 μg/m3 daily) is unclear. In addition, it is not clear whether results from previous time series studies (fit in larger cities) and cohort studies (fit in convenience samples) are generalizable.
We estimated the effects of low-concentration PM2.5 on mortality.
High resolution (1 km × 1 km) daily PM2.5 predictions, derived from satellite aerosol optical depth retrievals, were used. Poisson regressions were applied to a Medicare population (≥ 65 years of age) in New England to simultaneously estimate the acute and chronic effects of exposure to PM2.5, with mutual adjustment for short- and long-term exposure, as well as for area-based confounders. Models were also restricted to annual concentrations < 10 μg/m3 or daily concentrations < 30 μg/m3.
PM2.5 was associated with increased mortality. In the study cohort, 2.14% (95% CI: 1.38, 2.89%) and 7.52% (95% CI: 1.95, 13.40%) increases were estimated for each 10-μg/m3 increase in short- (2 day) and long-term (1 year) exposure, respectively. The associations held for analyses restricted to low-concentration PM2.5 exposure, and the corresponding estimates were 2.14% (95% CI: 1.34, 2.95%) and 9.28% (95% CI: 0.76, 18.52%). Penalized spline models of long-term exposure indicated a larger effect for mortality in association with exposures ≥ 6 μg/m3 versus those < 6 μg/m3. In contrast, the association between short-term exposure and mortality appeared to be linear across the entire exposure distribution.
Using a mutually adjusted model, we estimated significant acute and chronic effects of PM2.5 exposure below the current U.S. EPA standards. These findings suggest that improving air quality with even lower PM2.5 than currently allowed by U.S. EPA standards may benefit public health.
Shi L, Zanobetti A, Kloog I, Coull BA, Koutrakis P, Melly SJ, Schwartz JD. 2016. Low-concentration PM2.5 and mortality: estimating acute and chronic effects in a population-based study. Environ Health Perspect 124:46–52;
PMCID: PMC4710600  PMID: 26038801
21.  Long-term PM2.5 Exposure and Neurological Hospital Admissions in the Northeastern United States 
Long-term exposure to fine particles (particulate matter ≤ 2.5 μm; PM2.5) has been consistently linked to heart and lung disease. Recently, there has been increased interest in examining the effects of air pollution on the nervous system, with evidence showing potentially harmful effects on neurodegeneration.
Our objective was to assess the potential impact of long-term PM2.5 exposure on event time, defined as time to first admission for dementia, Alzheimer’s (AD), or Parkinson’s (PD) diseases in an elderly population across the northeastern United States.
We estimated the effects of PM2.5 on first hospital admission for dementia, AD, and PD among all Medicare enrollees ≥ 65 years in 50 northeastern U.S. cities (1999–2010). For each outcome, we first ran a Cox proportional hazards model for each city, adjusting for prior cardiopulmonary-related hospitalizations and year, and stratified by follow-up time, age, sex, and race. We then pooled the city-specific estimates by employing a random effects meta-regression.
We followed approximately 9.8 million subjects and observed significant associations of long-term PM2.5 city-wide exposure with all three outcomes. Specifically, we estimated a hazard ratio (HR) of 1.08 (95% CI: 1.05, 1.11) for dementia, an HR of 1.15 (95% CI: 1.11, 1.19) for AD, and an HR of 1.08 (95% CI: 1.04, 1.12) for PD admissions per 1-μg/m3 increase in annual PM2.5 concentrations.
To our knowledge, this is the first study to examine the relationship between long-term exposure to PM2.5 and time to first hospitalization for common neurodegenerative diseases. We found strong evidence of association for all three outcomes. Our findings provide the basis for further studies, as the implications of such exposures could be crucial to public health.
Kioumourtzoglou MA, Schwartz JD, Weisskopf MG, Melly SJ, Wang Y, Dominici F, Zanobetti A. 2016. Long-term PM2.5 exposure and neurological hospital admissions in the northeastern United States. Environ Health Perspect 124:23–29;
PMCID: PMC4710596  PMID: 25978701
22.  Temporal Variation in Heat–Mortality Associations: A Multicountry Study 
Environmental Health Perspectives  2015;123(11):1200-1207.
Recent investigations have reported a decline in the heat-related mortality risk during the last decades. However, these studies are frequently based on modeling approaches that do not fully characterize the complex temperature–mortality relationship, and are limited to single cities or countries.
We assessed the temporal variation in heat–mortality associations in a multi-country data set using flexible modelling techniques.
We collected data for 272 locations in Australia, Canada, Japan, South Korea, Spain, the United Kingdom, and the United States, with a total 20,203,690 deaths occurring in summer months between 1985 and 2012. The analysis was based on two-stage time-series models. The temporal variation in heat–mortality relationships was estimated in each location with time-varying distributed lag nonlinear models, expressed through an interaction between the transformed temperature variables and time. The estimates were pooled by country through multivariate meta-analysis.
Mortality risk due to heat appeared to decrease over time in several countries, with relative risks associated to high temperatures significantly lower in 2006 compared with 1993 in the United States, Japan, and Spain, and a nonsignificant decrease in Canada. Temporal changes are difficult to assess in Australia and South Korea due to low statistical power, and we found little evidence of variation in the United Kingdom. In the United States, the risk seems to be completely abated in 2006 for summer temperatures below their 99th percentile, but some significant excess persists for higher temperatures in all the countries.
We estimated a statistically significant decrease in the relative risk for heat-related mortality in 2006 compared with 1993 in the majority of countries included in the analysis.
Gasparrini A, Guo Y, Hashizume M, Kinney PL, Petkova EP, Lavigne E, Zanobetti A, Schwartz JD, Tobias A, Leone M, Tong S, Honda Y, Kim H, Armstrong BG. 2015. Temporal variation in heat–mortality associations: a multicountry study. Environ Health Perspect 123:1200–1207;
PMCID: PMC4629745  PMID: 25933359
23.  Prenatal and Childhood Traffic-Related Pollution Exposure and Childhood Cognition in the Project Viva Cohort (Massachusetts, USA) 
Environmental Health Perspectives  2015;123(10):1072-1078.
Influences of prenatal and early-life exposures to air pollution on cognition are not well understood.
We examined associations of gestational and childhood exposure to traffic-related pollution with childhood cognition.
We studied 1,109 mother–child pairs in Project Viva, a prospective birth cohort study in eastern Massachusetts (USA). In mid-childhood (mean age, 8.0 years), we measured verbal and nonverbal intelligence, visual motor abilities, and visual memory. For periods in late pregnancy and childhood, we estimated spatially and temporally resolved black carbon (BC) and fine particulate matter (PM2.5) exposures, residential proximity to major roadways, and near-residence traffic density. We used linear regression models to examine associations of exposures with cognitive assessment scores, adjusted for potential confounders.
Compared with children living ≥ 200 m from a major roadway at birth, those living < 50 m away had lower nonverbal IQ [–7.5 points; 95% confidence interval (CI): –13.1, –1.9], and somewhat lower verbal IQ (–3.8 points; 95% CI: –8.2, 0.6) and visual motor abilities (–5.3 points; 95% CI: –11.0, 0.4). Cross-sectional associations of major roadway proximity and cognition at mid-childhood were weaker. Prenatal and childhood exposure to traffic density and PM2.5 did not appear to be associated with poorer cognitive performance. Third-trimester and childhood BC exposures were associated with lower verbal IQ in minimally adjusted models; but after adjustment for socioeconomic covariates, associations were attenuated or reversed.
Residential proximity to major roadways during gestation and early life may affect cognitive development. Influences of pollutants and socioeconomic conditions on cognition may be difficult to disentangle.
Harris MH, Gold DR, Rifas-Shiman SL, Melly SJ, Zanobetti A, Coull BA, Schwartz JD, Gryparis A, Kloog I, Koutrakis P, Bellinger DC, White RF, Sagiv SK, Oken E. 2015. Prenatal and childhood traffic-related pollution exposure and childhood cognition in the Project Viva cohort (Massachusetts, USA). Environ Health Perspect 123:1072–1078;
PMCID: PMC4590752  PMID: 25839914
24.  Exposure to Traffic and Early Life Respiratory Infection: A Cohort Study 
Pediatric pulmonology  2014;10.1002/ppul.23029.
We examined whether proximity to a major roadway and traffic density around the home during pregnancy are associated with risk of early life respiratory infection in a pre-birth cohort in the Boston area. We geocoded addresses for 1,263 mother-child pairs enrolled during the first trimester of pregnancy in Project Viva during 1999-2002. We calculated distance from home to nearest major roadway and traffic density in a 100 m buffer around the home. We defined respiratory infection as maternal report of >1 doctor-diagnosed pneumonia, bronchiolitis, croup or other respiratory infection from birth until the early childhood visit (median age 3.3). We used relative risk regression models adjusting for potential confounders to estimate associations between traffic exposures and risk of respiratory infection. Distance to roadway during pregnancy was associated with risk of respiratory infection. In fully adjusted models, relative risks (95% CI) for respiratory infection were: 1.30 (1.08, 1.55) for <100 m, 1.15 (0.93, 1.41) for 100 to <200 m, and 0.95 (0.84, 1.07) for 200 to <1000 m compared with living ≥1000 m away from a major roadway. Each interquartile range increase in distance to roadway was associated with an 8% (95% CI 0.87, 0.98) lower risk, and each interquartile range increase in traffic density was associated with a 5% (95% CI 0.98, 1.13) higher risk of respiratory infection. Our findings suggest that living close to a major roadway during pregnancy may predispose the developing lung to infection in early life.
PMCID: PMC4177521  PMID: 24678045
Epidemiology; Environmental Lung Disease; Air pollution; Traffic; Prenatal exposures; Respiratory Infection
25.  Mortality risk attributable to high and low ambient temperature: a multicountry observational study 
Lancet (London, England)  2015;386(9991):369-375.
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.
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.
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.
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.
UK Medical Research Council.
PMCID: PMC4521077  PMID: 26003380

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