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3.
Biostatistics ; 2019 Sep 23.
Artigo em Inglês | MEDLINE | ID: mdl-31545341

RESUMO

We propose a computationally and statistically efficient divide-and-conquer (DAC) algorithm to fit sparse Cox regression to massive datasets where the sample size $n_0$ is exceedingly large and the covariate dimension $p$ is not small but $n_0\gg p$. The proposed algorithm achieves computational efficiency through a one-step linear approximation followed by a least square approximation to the partial likelihood (PL). These sequences of linearization enable us to maximize the PL with only a small subset and perform penalized estimation via a fast approximation to the PL. The algorithm is applicable for the analysis of both time-independent and time-dependent survival data. Simulations suggest that the proposed DAC algorithm substantially outperforms the full sample-based estimators and the existing DAC algorithm with respect to the computational speed, while it achieves similar statistical efficiency as the full sample-based estimators. The proposed algorithm was applied to extraordinarily large survival datasets for the prediction of heart failure-specific readmission within 30 days among Medicare heart failure patients.

5.
Environ Health Perspect ; 127(9): 97007, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31553655

RESUMO

BACKGROUND: There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature. OBJECTIVES: We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset. METHODS: In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. City-specific associations were summarized using meta-analytic techniques. RESULTS: Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1-3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly. DISCUSSION: The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify. https://doi.org/10.1289/EHP5430.

6.
Environ Pollut ; 254(Pt B): 113121, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31493628

RESUMO

There is limited evidence for short-term association between mortality and ambient air pollution in the Middle East and no study has evaluated exposure windows of about a month prior to death. We investigated all-cause non-accidental daily mortality and its association with fine particulate matter (PM2.5), nitrogen dioxide (NO2), and the Air Quality Index (AQI) from March 2011 through March 2014 in the megacity of Tehran, Iran. Generalized additive quasi-Poisson models were used within a distributed lag linear modeling framework to estimate the cumulative effects of PM2.5, NO2, and the AQI up to a lag of 45 days. We further conducted multi-pollutant models and also stratified the analyses by sex, age group, and season. The relative risk (95% confidence interval (CI)) for all seasons, both sexes and all ages at lag 0 for PM2.5, NO2, and AQI were 1.004 (1.001, 1.007), 1.003 (0.999, 1.007), and 1.004 (1.001, 1.007), respectively, per inter-quartile range (IQR) increment (18.8 µg/m3 for PM2.5, 12.6 ppb for NO2, and 31.5 for AQI). In multi-pollutant models, the PM2.5 associations were almost independent from NO2. However, the RRs for NO2 were slightly attenuated after adjustment for PM2.5 but they were still largely independent from PM2.5. The cumulative relative risks (95% CI) per IQR increment reached maximum during the cooler months, including: 1.13 (1.06, 1.20) for PM2.5 at lag 0-31 (for females, all ages); 1.17 (1.10, 1.25) for NO2 at lag 0-45 (for males, all ages); and 1.13 (1.07, 1.20) for the AQI at lag 0-30 (for females, all ages). Generally, the RRs were slightly larger for NO2 than PM2.5 and AQI. We found somewhat larger RRs in females, age group >65 years of age, and in cooler months. In summary, positive associations were found in most models. This is the first study to report short-term associations between all-cause non-accidental mortality and ambient PM2.5 and NO2 in Iran.

7.
Environ Health ; 18(1): 83, 2019 Sep 11.
Artigo em Inglês | MEDLINE | ID: mdl-31511079

RESUMO

BACKGROUND: Short-term geomagnetic disturbances (GMD) driven by the quasi-periodic 11-year cycle of solar activity have been linked to a broad range of adverse health effects, including cardiovascular diseases (CVD) and total deaths. We conducted a large epidemiological study in 263 U.S. cities to assess the effects of GMD on daily deaths of total, CVD, myocardial infarction (MI), and stroke. METHODS: We employed a two-step meta-analysis approach, in which we estimated city-specific and season-stratified mortality risk associated with a GMD parameter (Kp index) in 263 U.S. cities. In addition, sensitivity analysis was performed to assess whether effect modification of particulate matter (PM2.5) in the prior day changed Kp index effects on daily deaths after adjusting for confounders. RESULTS: We found significant association between daily GMD and total, CVD, and MI deaths. The effects were even stronger when we adjusted the models for 24-h PM2.5 for different seasons. For example, in the winter and fall one standard deviation of z-score Kp index increase was associated with a 0.13 and 0.31% increase in total deaths, respectively (Winter: p = 0.01, 95% CI: 0.02 to 0.24; Fall: p = 0.00001; 95% CI: 0.23 to 0.4), without adjusting for PM2.5. The effects of GMD on total deaths were also observed in spring and summer in the models without PM2.5 (p = 0.00001). When the models were adjusted for PM2.5 the total deaths increased 0.47% in winter (p = 0.00001, 95% CI: 0.3 to 0.65) and by 0.23% in fall (p = 0.001, 95% CI: 0.09 to 0.37). The effects of GMD were also significant associated with MI deaths and CVD. No positive significant association were found between Kp and stroke. The GMD effects on deaths were higher than for 24 h-PM2.5 alone, especially in spring and fall. CONCLUSION: Our results suggest that GMD is associated with total, CVD and MI deaths in 263 U. S cities. Increased mortality in the general population during GMD should be further investigated to determine whether those human physiological dynamics driven by variations in solar activity can be related to daily clinical cardiovascular observations.

8.
Epidemiology ; 30(5): 617-623, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31386643

RESUMO

BACKGROUND: Maternal exposure to fine particulate air pollution (PM2.5) during pregnancy is associated with lower newborn birthweight, which is a risk factor for chronic disease. Existing studies typically report the average association related with PM2.5 increase, which does not offer information about potentially varying associations at different points of the birthweight distribution. METHODS: We retrieved all birth records in Massachusetts between 2001 and 2013 then restricted our analysis to full-term live singletons (n = 775,768). Using the birthdate, gestational age, and residential address reported at time of birth, we estimated the average maternal PM2.5 exposure during pregnancy of each birth. PM2.5 predictions came from a model that incorporates satellite, land use, and meteorologic data. We applied quantile regression to quantify the association between PM2.5 and birthweight at each decile of birthweight, adjusted for individual and neighborhood covariates. We considered effect modification by indicators of individual and neighborhood socioeconomic status (SES). RESULTS: PM2.5 was negatively associated with birthweight. An interquartile range increase in PM2.5 was associated with a 16 g [95% confidence interval (CI) = 13, 19] lower birthweight on average, 19 g (95% CI = 15, 23) lower birthweight at the lowest decile of birthweight, and 14 g (95% CI = 9, 19) lower birthweight at the highest decile. In general, the magnitudes of negative associations were larger at lower deciles. We did not find evidence of effect modification by individual or neighborhood SES. CONCLUSIONS: In full-term live births, PM2.5 and birthweight were negatively associated with more severe associations at lower quantiles of birthweight.

9.
N Engl J Med ; 381(8): 705-715, 2019 08 22.
Artigo em Inglês | MEDLINE | ID: mdl-31433918

RESUMO

BACKGROUND: The systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias. METHODS: We evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 µm or less (PM10) and fine PM with an aerodynamic diameter of 2.5 µm or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived. RESULTS: On average, an increase of 10 µg per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations. CONCLUSIONS: Our data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).


Assuntos
Poluição do Ar/efeitos adversos , Exposição Ambiental/análise , Mortalidade , Material Particulado/efeitos adversos , Poluição do Ar/análise , Doenças Cardiovasculares/mortalidade , Causas de Morte , Exposição Ambiental/efeitos adversos , Exposição Ambiental/legislação & jurisprudência , Saúde Global , Humanos , Tamanho da Partícula , Material Particulado/análise , Doenças Respiratórias/mortalidade , Risco
10.
Thorax ; 2019 Aug 07.
Artigo em Inglês | MEDLINE | ID: mdl-31391318

RESUMO

BACKGROUND: Ambient air pollution accelerates lung function decline among adults, however, there are limited data about its role in the development and progression of early stages of interstitial lung disease. AIMS: To evaluate associations of long-term exposure to traffic and ambient pollutants with odds of interstitial lung abnormalities (ILA) and progression of ILA on repeated imaging. METHODS: We ascertained ILA on chest CT obtained from 2618 Framingham participants from 2008 to 2011. Among 1846 participants who also completed a cardiac CT from 2002 to 2005, we determined interval ILA progression. We assigned distance from home address to major roadway, and the 5-year average of fine particulate matter (PM2.5), elemental carbon (EC, a traffic-related PM2.5 constituent) and ozone using spatio-temporal prediction models. Logistic regression models were adjusted for age, sex, body mass index, smoking status, packyears of smoking, household tobacco exposure, neighbourhood household value, primary occupation, cohort and date. RESULTS: Among 2618 participants with a chest CT, 176 (6.7%) had ILA, 1361 (52.0%) had no ILA, and the remainder were indeterminate. Among 1846 with a preceding cardiac CT, 118 (6.4%) had ILA with interval progression. In adjusted logistic regression models, an IQR difference in 5-year EC exposure of 0.14 µg/m3 was associated with a 1.27 (95% CI 1.04 to 1.55) times greater odds of ILA, and a 1.33 (95% CI 1.00 to 1.76) times greater odds of ILA progression. PM2.5 and O3 were not associated with ILA or ILA progression. CONCLUSIONS: Exposure to EC may increase risk of progressive ILA, however, associations with other measures of ambient pollution were inconclusive.

11.
Environ Pollut ; 254(Pt A): 112926, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31404729

RESUMO

BACKGROUND: New evidence suggests that particulate matter less than 2.5 µm in diameter (PM2.5) is associated with late-onset dementia (LOD). However, epidemiological studies for the entire population are lacking. METHODS: We analyzed approximately 94 million follow-up records from fee-for-service Medicare records for 13 million Medicare beneficiaries residing in the southeastern United States (U.S.) from 2000 to 2013. We used spatially and temporally continuous PM2.5 exposure data. To account for time-varying PM2.5 levels, we applied an Andersen-Gill counting process proportional hazard model; we stratified our analyses by subtype of dementia and level of urbanization of residence. RESULTS: During a median follow-up of 6 years, 1,409,599 hospitalizations with dementia occurred. The adjusted hazard ratio (HR) of hospitalization with dementia was 1.049 (95% confidence interval [CI], 1.048 to 1.051) per 1 µg/m3 increase in annual PM2.5. The hazard ratio for vascular dementia was higher (HR, 1.086; 95% CI, 1.082 to 1.090). In large, the magnitude of the effect grew as the level of urbanization increased (HR, 1.036; 95% CI, 1.031 to 1.041 in rural areas versus HR, 1.052; 95% CI, 1.050 to 1.054 in metropolitan areas). CONCLUSIONS: Long-term exposure to higher PM2.5 was associated with increased hospitalizations with dementia.

12.
Environ Sci Technol ; 53(17): 10279-10287, 2019 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-31415154

RESUMO

Nitrogen dioxide (NO2) remains an important traffic-related pollutant associated with both short- and long-term health effects. We aim to model daily average NO2 concentrations in Switzerland in a multistage framework with mixed-effect and random forest models to respectively downscale satellite measurements and incorporate local sources. Spatial and temporal predictor variables include data from the Ozone Monitoring Instrument, Copernicus Atmosphere Monitoring Service, land use, and meteorological variables. We derived robust models explaining ∼58% (R2 range, 0.56-0.64) of the variation in measured NO2 concentrations using mixed-effect models at a 1 × 1 km resolution. The random forest models explained ∼73% (R2 range, 0.70-0.75) of the overall variation in the residuals at a 100 × 100 m resolution. This is one of the first studies showing the potential of using earth observation data to develop robust models with fine-scale spatial (100 × 100 m) and temporal (daily) variation of NO2 across Switzerland from 2005 to 2016. The novelty of this study is in demonstrating that methods originally developed for particulate matter can also successfully be applied to NO2. The predicted NO2 concentrations will be made available to facilitate health research in Switzerland.

13.
Circulation ; 140(8): 645-657, 2019 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-31424985

RESUMO

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

14.
Artigo em Inglês | MEDLINE | ID: mdl-31315297

RESUMO

: Background: Numerous epidemiological studies indicated high levels of particulate matter less than2.5 µm diameter (PM2.5) as a major cardiovascular risk factor. Most of the studies have been conducted in high-income countries (HICs), where average levels of PM2.5 are far less compared to low- and middle- income countries (LMICs), and their socio-economic profile, disease burden, and PM speciation/composition are very different. We systematically reviewed the association of long-term exposure to PM2.5 and cardio-metabolic diseases (CMDs) in LMICs. METHODS: Multiple databases were searched for English articles with date limits until March 2018. We included studies investigating the association of long-term exposure to PM2.5 (defined as an annual average/average measure for 3 more days of PM2.5 exposure) and CMDs, such as hospital admissions, prevalence, and deaths due to CMDs, conducted in LMICs as defined by World Bank. We excluded studies which employed exposure proxy measures, studies among specific occupational groups, and specific episodes of air pollution. RESULTS: A total of 5567 unique articles were identified, of which only 17 articles were included for final review, and these studies were from Brazil, Bulgaria, China, India, and Mexico. Outcome assessed were hypertension, type 2 diabetes mellitus and insulin resistance, and cardiovascular disease (CVD)-related emergency room visits/admissions, death, and mortality. Largely a positive association between exposure to PM2.5 and CMDs was found, and CVD mortality with effect estimates ranging from 0.24% to 6.11% increased per 10 µg/m3 in PM2.5. CVD-related hospitalizations and emergency room visits increased by 0.3% to 19.6%. Risk factors like hypertension had an odds ratio of 1.14, and type 2 diabetes mellitus had an odds ratio ranging from 1.14-1.32. Diversity of exposure assessment and health outcomes limited the ability to perform a meta-analysis. CONCLUSION: Limited evidence on the association of long-term exposure to PM2.5 and CMDs in the LMICs context warrants cohort studies to establish the association.

15.
Aging (Albany NY) ; 11(14): 4970-4989, 2019 Jul 18.
Artigo em Inglês | MEDLINE | ID: mdl-31322503

RESUMO

Evidence indicates associations between higher optimism and reduced risk of age-related conditions and premature mortality. This suggests optimism is a positive health asset, but research identifying potential biological mechanisms underlying these associations remains limited. One potential pathway is slower cellular aging, which may delay age-related deterioration in health. Data were from the Women's Health Initiative (WHI) (N=3,298) and the Veterans Affairs Normative Aging Study (NAS) (N=514), and included dispositional and explanatory style optimism measures. We evaluated whether higher optimism was associated with metrics suggestive of less cellular aging, as indicated by two DNA methylation algorithms, intrinsic (IEAA) and extrinsic epigenetic age acceleration (EEAA); these algorithms represent accelerated biologic aging that exceeds chronological age. We used linear regression models to test our hypothesis while considering several covariates (sociodemographics, depressive symptoms, health behaviors). In both cohorts, we found consistently null associations of all measures of optimism with both measures of DNA methylation aging, regardless of covariates considered. For example, in fully-adjusted models, dispositional optimism was not associated with either IEAA (WHI:ß=0.02; 95% Confidence Interval [CI]:-0.15-0.20; NAS:ß=-0.06; 95% CI:-0.56-0.44) or EEAA (WHI:ß=-0.04; 95% CI: -0.26-0.17; NAS:ß=-0.17; 95% CI: -0.80-0.46). Higher optimism was not associated with reduced cellular aging as measured in this study.

16.
Environ Health Perspect ; 127(7): 77002, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31268361

RESUMO

BACKGROUND: A few studies suggest that air pollution may decrease fertility, but prospective studies and examinations of windows of susceptibility remain unclear. OBJECTIVE: We aimed to examine the association between time-varying exposure to nitrogen dioxide ([Formula: see text]), ozone ([Formula: see text]), fine particulate matter [Formula: see text] ([Formula: see text]), and black carbon (BC) on in vitro fertilization (IVF) outcomes. METHODS: We included 345 women (522 IVF cycles) for the [Formula: see text], [Formula: see text], and [Formula: see text] analyses and 339 women (512 IVF cycles) for the BC analysis enrolled in a prospective cohort at a Boston fertility center (2004­2015). We used validated spatiotemporal models to estimate daily residential exposure to [Formula: see text], [Formula: see text], [Formula: see text], and BC. Multivariable discrete time Cox proportional hazards models with four periods [ovarian stimulation (OS), oocyte retrieval to embryo transfer (ET), ET to implantation, implantation to live birth] estimated odds ratios (OR) and 95% confidence intervals (CI) of failing at IVF. Time-dependent interactions were used to identify vulnerable periods. RESULTS: An interquartile range (IQR) increase in [Formula: see text], [Formula: see text], and BC throughout the IVF cycle was associated with an elevated odds of failing at IVF prior to live birth ([Formula: see text], 95% CI: 0.95, 1.23 for [Formula: see text]; [Formula: see text], 95% CI: 0.88, 1.28 for [Formula: see text]; and [Formula: see text], 95% CI: 0.96, 1.41 for BC). This relationship significantly varied across the IVF cycle such that the association with higher exposure to air pollution during OS was strongest for early IVF failures. An IQR increase in [Formula: see text], [Formula: see text], and BC exposure during OS was associated with 1.42 (95% CI: 1.20, 1.69), 1.26 (95% CI: 0.96, 1.67), and 1.23 (95% CI: 0.96, 1.59) times the odds of failing prior to oocyte retrieval, and 1.32 (95% CI: 1.13, 1.54), 1.27 (95% CI: 0.98, 1.65), and 1.32 (95% CI: 1.10, 1.59) times the odds of failing prior to ET. CONCLUSION: Increased exposure to traffic-related pollutants was associated with higher odds of early IVF failure. https://doi.org/10.1289/EHP4601.

17.
Artigo em Inglês | MEDLINE | ID: mdl-31277270

RESUMO

DNA methylation may play a critical role in aging and age-related diseases. DNA methylation phenotypic age (DNAmPhenoAge) is a new aging biomarker and predictor of chronic disease risk. While smoking is a strong risk factor for chronic diseases and influences methylation, its influence on DNAmPhenoAge is unknown. We investigated associations of self-reported and epigenetic smoking indicators with DNAmPhenoAge acceleration in a longitudinal aging study in eastern Massachusetts. DNA methylation was measured in whole blood samples from multiple visits for 692 male participants in the Veterans Affairs Normative Aging Study during 1999-2013. Acceleration was defined using residuals from linear regression of the DNAmPhenoAge on the chronological age. Cumulative smoking (pack-years) was significantly associated with DNAmPhenoAge acceleration, whereas self-reported smoking status was not. We observed significant validated associations between smoking-related loci and DNAmPhenoAge acceleration for 52 CpG sites, where 18 were hypomethylated and 34 were hypermethylated, mapped to 16 genes. The AHRR gene had the most loci (N = 8) among the 16 genes. We generated a smoking aging index based on these 52 loci, which showed positive significant associations with DNAmPhenoAge acceleration. These epigenetic biomarkers may help to predict age-related risks driven by smoking.

18.
Environ Int ; 130: 104909, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31272018

RESUMO

Various approaches have been proposed to model PM2.5 in the recent decade, with satellite-derived aerosol optical depth, land-use variables, chemical transport model predictions, and several meteorological variables as major predictor variables. Our study used an ensemble model that integrated multiple machine learning algorithms and predictor variables to estimate daily PM2.5 at a resolution of 1 km × 1 km across the contiguous United States. We used a generalized additive model that accounted for geographic difference to combine PM2.5 estimates from neural network, random forest, and gradient boosting. The three machine learning algorithms were based on multiple predictor variables, including satellite data, meteorological variables, land-use variables, elevation, chemical transport model predictions, several reanalysis datasets, and others. The model training results from 2000 to 2015 indicated good model performance with a 10-fold cross-validated R2 of 0.86 for daily PM2.5 predictions. For annual PM2.5 estimates, the cross-validated R2 was 0.89. Our model demonstrated good performance up to 60 µg/m3. Using trained PM2.5 model and predictor variables, we predicted daily PM2.5 from 2000 to 2015 at every 1 km × 1 km grid cell in the contiguous United States. We also used localized land-use variables within 1 km × 1 km grids to downscale PM2.5 predictions to 100 m × 100 m grid cells. To characterize uncertainty, we used meteorological variables, land-use variables, and elevation to model the monthly standard deviation of the difference between daily monitored and predicted PM2.5 for every 1 km × 1 km grid cell. This PM2.5 prediction dataset, including the downscaled and uncertainty predictions, allows epidemiologists to accurately estimate the adverse health effect of PM2.5. Compared with model performance of individual base learners, an ensemble model would achieve a better overall estimation. It is worth exploring other ensemble model formats to synthesize estimations from different models or from different groups to improve overall performance.

19.
Environ Int ; 131: 105018, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31336254

RESUMO

BACKGROUND: Whole-body and thoracic ionizing radiation exposure are both associated with the development of renal dysfunction. However, whether low-level environmental radiation from air pollution affects renal function remains unknown. OBJECTIVES: We investigated the association of particle radioactivity (PR) with renal function defined by the estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD) in the Normative Aging Study. METHODS: This longitudinal analysis included 2491 medical visits from 809 white males enrolled between 1999 and 2013. The eGFR was calculated using the CKD-EPI and MDRD equations, and CKD cases were identified as those with an eGFR <60 mL/min/1.73 m2. Gross ß activity measured by five monitors of the U.S. Environmental Protection Agency's RadNet monitoring network was utilized to represent PR. RESULTS: Ambient PR levels from 1 to 28 days prior to clinical visit demonstrated robust negative associations with both forms of eGFR, but not with the increased odds of CKD. An interquartile range higher 28-day average ambient PR level was significantly associated with 0.83-mL/min/1.73 m2 lower eGFR estimated by the CKD-EPI equation (95% confidence interval: -1.46, -0.20, p-value = 0.01). Controlling for PM2.5 or black carbon in the model slightly attenuated the PR effects on eGFR. However, in individuals with the highest levels (3rd tertile) of C-reactive protein (CRP) or fibrinogen, we observed robust associations of PR with eGFR and CKD, suggesting that systemic inflammation may modify the PR-eGFR and PR-CKD relationships. CONCLUSIONS: Our study reveals adverse health effects of short-term low-level ambient PR on the renal function, providing evidence to guide further study of the interplay between PR, inflammation, and renal health.

20.
Environ Int ; 131: 105027, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31351381

RESUMO

An increase in the global health burden of temperature was projected for 459 locations in 28 countries worldwide under four representative concentration pathway scenarios until 2099. We determined that the amount of temperature increase for each 100 ppm increase in global CO2 concentrations is nearly constant, regardless of climate scenarios. The overall average temperature increase during 2010-2099 is largest in Canada (1.16 °C/100 ppm) and Finland (1.14 °C/100 ppm), while it is smallest in Ireland (0.62 °C/100 ppm) and Argentina (0.63 °C/100 ppm). In addition, for each 1 °C temperature increase, the amount of excess mortality is increased largely in tropical countries such as Vietnam (10.34%p/°C) and the Philippines (8.18%p/°C), while it is decreased in Ireland (-0.92%p/°C) and Australia (-0.32%p/°C). To understand the regional variability in temperature increase and mortality, we performed a regression-based modeling. We observed that the projected temperature increase is highly correlated with daily temperature range at the location and vulnerability to temperature increase is affected by health expenditure, and proportions of obese and elderly population.

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