Environmental Epidemiology最新文献

Volatile organic compounds (VOCs) are components of the complex mixture of air pollutants within cities and can cause various adverse health effects. Therefore, it is necessary to understand their spatial distribution for exposure assessment in epidemiological studies.

Objectives: The objective was to model measured concentrations of five VOCs within the city of Montreal, Canada, developing spatial prediction models that can be used in health studies.

Methods: We measured concentrations using 3M 3500 Organic Vapor Monitors, over 2-week periods, for three monitoring campaigns between 2005 and 2006 in over 130 locations in the city. Using GC/MSD (Gas Chromatography/Mass Selective Detector), we measured concentrations of benzene, n-decane, ethylbenzene, hexane, and trimethylbenzene. We fitted four different models that combine land-use regression and geostatistical methods to account for the potential spatial structure that remains after accounting for the land-use variables. The fitted models also accounted for possible variations in the concentration of air pollutants across campaigns.

Results: The highest concentrations for all VOCs were found in December with hexane being the most abundant followed by ethylbenzene. We obtained predicted surfaces for the VOCs for the three campaigns and mean surfaces across campaigns. We found higher concentrations of some VOCs along highways and in the Eastern part of Montreal, which is a highly industrialized area.

Conclusions: Each of the fitted models captured the spatial and across-campaigns variability for each VOC, and we found that different VOCs required different model structures.

Hawai'i has the highest prevalence of nontuberculous mycobacterial (NTM) pulmonary disease in the United States. Previous studies indicate that certain trace metals in surface water increase the risk of NTM infection.

Objective: To identify whether trace metals influence the risk of NTM infection in O'ahu, Hawai'i.

Methods: A population-based ecologic cohort study was conducted using NTM infection incidence data from patients enrolled at Kaiser Permanente Hawai'i during 2005-2019. We obtained sociodemographic, microbiologic, and geocoded residential data for all Kaiser Permanente Hawai'i beneficiaries. To estimate the risk of NTM pulmonary infection from exposure to groundwater constituents, we obtained groundwater data from three data sources: (1) Water Quality Portal; (2) the Hawai'i Department of Health; and (3) Brigham Young University, Department of Geological Science faculty. Data were aggregated by an aquifer and were associated with the corresponding beneficiary aquifer of residence. We used Poisson regression models with backward elimination to generate models for NTM infection risk as a function of groundwater constituents. We modeled two outcomes: Mycobacterium avium complex (MAC) species and Mycobacterium abscessus group species.

Results: For every 1-unit increase in the log concentration of vanadium in groundwater at the aquifer level, infection risk increased by 22% among MAC patients. We did not observe significant associations between water-quality constituents and infection risk among M. abscessus patients.

Conclusions: Concentrations of vanadium in groundwater were associated with MAC pulmonary infection in O'ahu, Hawai'i. These findings provide evidence that naturally occurring trace metals influence the presence of NTM in water sources that supply municipal water systems.

Although parental preconception exposure to some phenols and phthalates have been associated with reduced birthweight, few studies have examined these chemicals as complex mixtures.

Methods: We included 384 mothers and 211 fathers (203 couples) who gave birth to 384 singletons from a prospective cohort of couples seeking fertility evaluation. Urinary concentrations of bisphenol A (BPA), parabens, and 11 phthalate metabolites including those of di(2-ethylhexyl) phthalate (DEHP) were examined. Birthweight was abstracted from delivery records. We used principal component analysis and Bayesian Kernel Machine Regression (BKMR) to examine maternal and paternal preconception mixtures in relation to singleton birthweight. We also fit couple-based BKMR with hierarchical variable selection to assess couples' joint mixtures in relation to birthweight.

Results: PC scores of maternal and paternal preconception low molecular weight phthalates factor, and paternal preconception DEHP-BPA factor were associated with reduced birthweight. In BKMR models, we found that maternal preconception monoethyl phthalate and BPA concentrations, and paternal preconception mono-n-butyl phthalate concentrations were inversely associated with birthweight when the remaining mixture components were held at their median concentrations. In couple-based BKMR models, paternal preconception biomarkers contributed more to couples' joint effect on birthweight compared with maternal preconception biomarkers. A decreasing trend of birthweight was observed across quantiles of maternal, paternal, and couples' total preconception mixture concentrations, respectively.

Conclusions: Results from this preconception cohort of subfertile couples suggest a complex interplay between paternal and maternal preconception exposure to mixtures of nonpersistent chemicals, with both parental windows of exposure jointly contributing to reduced birthweight.

Evidence is emerging that preterm birth (PTB, birth before 37 completed weeks of gestation), a risk factor for neonatal mortality and future morbidity, may be induced by maternal nitrate ( ${NO}_3^{-}$ ) exposure from drinking water. The objective of this study is to assess the association between maternal exposure to nitrate and the risk of PTB in a nationwide study of liveborn singletons.

Methods: We estimated maternal nitrate exposure from household tap water for 1,055,584 births in Denmark to Danish-born parents during 1991-2015 by linkage of individual home address(es) with nitrate concentrations from a national monitoring database. Nitrate exposure during pregnancy was modeled using four categories and continuously. Logistic models adjusted for sex, birth year, birth order, urbanicity, and maternal age, smoking, education, income, and employment, with generalized estimating equations were used to account for sibling clusters.

Results: A total of 1,009,189 births were included, comprising 51,747 PTB. An increase in the risk of PTB was seen across categories of exposure (P < 0.001) with an odds ratio (OR) in the uppermost category (>25 mg/L nitrate) of 1.05 (95% confidence interval [CI] = 1.00, 1.10). Evidence of an exposure-response relationship was observed in models using continuous nitrate (OR = 1.01 [95% CI = 1.00, 1.03] per 10 mg/L nitrate). In sensitivity analyses, results were robust to the addition of variables for short inter-pregnancy interval (<1 year between births), maternal pre-pregnancy body mass index, paternal socioeconomic status and age, season of birth, and inclusion of post-term births. Results were virtually unchanged when the analysis was restricted to women exposed to less than the current European Union standard of 50 mg/L.

Conclusion: We observed an increasing risk of PTB with increases in nitrate in household tap water. These findings add to a growing body of evidence of adverse effects from nitrate in drinking water at levels below current regulatory levels.

Ambient air pollution is a human carcinogen and a possible risk factor for prostate cancer.

Methods: We investigated associations between ambient concentrations particulate matter 2.5 (PM_2.5) and nitrogen dioxide (NO₂) and incident prostate cancer in a Canadian case-control study. Between 1994 and 1997, cases were identified from provincial cancer registries, and a population-based series of controls was recruited. Among men 50 years of age or older, risk factor and residential history data (1975 to 1994) were collected from 1,420 prostate cancer cases and 1,424 controls. Three methods were used to estimate the residential mean exposure to PM_2.5 and NO₂ during this period: (1) satellite-derived observations; (2) satellite-derived observations scaled with historical fixed-site measurements; and (3) a national land-use regression (LUR) model. Odds ratios (ORs) and their 95% confidence intervals (CIs) in relation to interquartile range (IQR) increases in PM_2.5 and NO₂ were estimated using logistic regression, adjusting for personal and contextual factors.

Results: We found positive associations between exposure to PM_2.5 and NO₂ over the previous 20 years and prostate cancer. An IQR increase in PM_2.5 (3.56 µg/m³ for satellite and 4.48 µg/m³ for scaled satellite observations) yielded ORs of 1.28 (95% CI = 1.07, 1.52) and 1.20 (95% CI = 1.03, 1.40), respectively. For NO₂, IQR increases (1.45 ppb for satellite, 15.18 ppb for scaled satellite-derived information, and 15.39 ppb for the national LUR) were associated with ORs of 1.09 (95% CI = 0.95, 1.24), 1.21 (95% CI = 1.02, 1.43), and 1.19 (95% CI = 1.03, 1.38), respectively.

Conclusions: Our findings support the hypothesis that ambient air pollution increases the risk of prostate cancer.

The prevalence of type 2 diabetes (T2D) has increased in the United States, and recent studies suggest that environmental factors contribute to T2D risk. We sought to understand if environmental factors were associated with the rate and magnitude of increase in diabetes prevalence at the county level.

Methods: We obtained age-adjusted diabetes prevalence estimates from the CDC for 3,137 US counties from 2004 to 2017. We applied latent growth mixture models to these data to identify classes of counties with similar trends in diabetes prevalence over time, stratified by Rural Urban Continuum Codes (RUCC). We then compared mean values of the US EPA Environmental Quality Index (EQI) 2006-2010, overall and for each of the five domain indices (air, water, land, sociodemographic, and built), with RUCC-specific latent class to examine associations of environmental factors and class of diabetes prevalence trajectory.

Results: Overall diabetes prevalence trends between 2004 and 2017 were similar across all RUCC strata. We identified two classes among metropolitan urbanized (RUCC 1) counties; four classes among non-metro urbanized (RUCC 2) counties; and three classes among less urbanized (RUCC 3) and thinly populated (RUCC 4) counties. Associations with overall EQI values and class of diabetes prevalence trends differed by RUCC strata, with the clearest association between poor air EQI and steeper increases in diabetes prevalence among rural counties (RUCC 3 and 4).

Conclusions: Similarities in county-level diabetes prevalence trends between 2004 and 2017 were identified for each RUCC strata, although associations with environmental factors varied by rurality.

Background: Prenatal exposure to organochlorine compounds (OCs) has been associated with increased childhood body mass index (BMI); however, only a few studies have focused on longitudinal BMI trajectories, and none of them used multiple exposure mixture approaches.

Aim: To determine the association between in-utero exposure to eight OCs and childhood BMI measures (BMI and BMI z-score) at 4 years and their yearly change across 4-12 years of age in 279 Rhea child-mother dyads.

Methods: We applied three approaches: (1) linear mixed-effect regressions (LMR) to associate individual compounds with BMI measures; (2) Bayesian weighted quantile sum regressions (BWQSR) to provide an overall OC mixture association with BMI measures; and (3)Bayesian varying coefficient kernel machine regressions (BVCKMR) to model nonlinear and nonadditive associations.

Results: In the LMR, yearly change of BMI measures was consistently associated with a quartile increase in hexachlorobenzene (HCB) (estimate [95% Confidence or Credible interval] BMI: 0.10 [0.06, 0.14]; BMI z-score: 0.02 [0.01, 0.04]). BWQSR results showed that a quartile increase in mixture concentrations was associated with yearly increase of BMI measures (BMI: 0.10 [0.01, 0.18]; BMI z-score: 0.03 [0.003, 0.06]). In the BVCKMR, a quartile increase in dichlorodiphenyldichloroethylene concentrations was associated with higher BMI measures at 4 years (BMI: 0.33 [0.24, 0.43]; BMI z-score: 0.19 [0.15, 0.24]); whereas a quartile increase in HCB and polychlorinated biphenyls (PCB)-118 levels was positively associated with BMI measures yearly change (BMI: HCB:0.10 [0.07, 0.13], PCB-118:0.08 [0.04, 012]; BMI z-score: HCB:0.03 [0.02, 0.05], PCB-118:0.02 [0.002,04]). BVCKMR suggested that PCBs had nonlinear relationships with BMI measures, and HCB interacted with other compounds.

Conclusions: All analyses consistently demonstrated detrimental associations between prenatal OC exposures and childhood BMI measures.