Environmental Epidemiology最新文献

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.

Living in a disadvantaged neighborhood has been associated with adverse birth outcomes. Most prior studies have conceptualized neighborhoods using census boundaries and few have examined the role of neighborhood perceptions, which may better capture the neighborhood environment. In the present study, we examined associations between extrinsic and perceived neighborhood quality measures and adverse birth outcomes.

Methods: Participants resided in the San Francisco Bay Area of California and were enrolled in Chemicals in Our Bodies, a prospective birth cohort (N = 817). The Index of Concentration at the Extremes (ICE) for income, Area Deprivation Index (ADI), and the Urban Displacement Project's measure of gentrification were included as census block group-level extrinsic neighborhood quality measures. Poor perceived neighborhood quality was assessed using an interview questionnaire. Linear regression models were utilized to examine associations between extrinsic and perceived neighborhood quality measures, and gestational age and birthweight for gestational age z-scores. Covariates in adjusted models were chosen via a directed acyclic graph (DAG) and included maternal age, education, and marital status.

Results: In adjusted models, having poor perceived neighborhood quality was associated with higher birthweight z-scores, relative to those who did not perceive their neighborhood as poor quality (β = 0.21, 95% confidence intervals = 0.01, 0.42). Relative to the least disadvantaged tertile, the upper tertile of the ADI was associated with a modest reduction in gestational age (β = -0.35, 95% confidence intervals = -0.67, -0.02).

Conclusions: In the Chemicals in Our Bodies study population, extrinsic and perceived neighborhood quality measures were inconsistently associated with adverse birth outcomes.

Inverse associations between natural vegetation exposure (i.e., greenness) and breast cancer risk have been reported; however, it remains unknown whether greenness affects breast tissue development or operates through other mechanisms (e.g., body mass index [BMI] or physical activity). We examined the association between greenness and mammographic density-a strong breast cancer risk factor-to determine whether greenness influences breast tissue composition independent of lifestyle factors.

Methods: Women (n = 2,318) without a history of breast cancer underwent mammographic screening at Brigham and Women's Hospital in Boston, Massachusetts, from 2006 to 2014. Normalized Difference Vegetation Index (NDVI) satellite data at 1-km² resolution were used to estimate greenness at participants' residential address 1, 3, and 5 years before mammogram. We used multivariable linear regression to estimate differences in log-transformed volumetric mammographic density measures and 95% confidence intervals (CIs) for each 0.1 unit increase in NDVI.

Results: Five-year annual average NDVI was not associated with percent mammographic density in premenopausal (β = -0.01; 95% CI = -0.03, 0.02; P = 0.58) and postmenopausal women (β = -0.02; 95% CI = -0.04, 0.01; P = 0.18). Results were similar for 1-year and 3-year NDVI measures and in models including potential mediators of BMI and physical activity. There were also no associations between greenness and dense volume and nondense volume.

Conclusions: Greenness exposures were not associated with mammographic density.

Impact: Prior observations of a protective association between greenness and breast cancer may not be driven by differences in breast tissue composition, as measured by mammographic density, but rather other mechanisms.

Studies have revealed a link between aberrant levels of maternal C-reactive protein (CRP) and cell adhesion molecules (CAMs) with adverse birth outcomes. Some epidemiologic studies have indicated that long-term metal exposures can modulate the levels of CRP and CAMs, but the associations between prenatal metal exposures and the levels of CRP and CAMs have yet to be studied more extensively. In this study, we assessed associations between maternal blood metal levels and CRP/CAMs among 617 pregnant women in the Puerto Rico PROTECT birth cohort.

Methods: Blood samples were collected from participants at 16-20 (visit 1) and 24-28 (visit 3) weeks gestation. We measured concentrations of 11 metals using inductively coupled plasma mass spectrometry (ICP-MS). From the blood samples, CRP and CAMs intercellular adhesion molecule (ICAM) and vascular cell adhesion molecule (VCAM) were also quantified using a customized Luminex assay. Linear-mixed effects models (LMEs) were used to regress CRP and CAMs on metals and included random intercepts for study participants to account for correlated repeated outcome measures. Fetal sex and visit effects were estimated using interaction terms between metal exposure variables and fetal sex, as well as visit indicators, respectively.

Results: We observed significant positive associations between nickel and CRP (Δ: 7.04, 95% CI = 0.75, 13.73) and between lead and VCAM (Δ: 4.57, 95% CI = 1.36, 7.89). The positive associations were mainly driven by mothers carrying male fetuses. We also observed various visit-specific associations. The significant associations between metals and CRP were predominantly driven by visit 3; however, the significant associations between metals and VCAM were mainly driven by visit 1.

Conclusion: Certain maternal blood metal levels were significantly associated with CRP and CAMs and most of these associations were differentially driven by fetal sex, as well as by timing in pregnancy. Future studies should further explore metal-CRP/CAMs associations for a better understanding of the underlying mechanism of metal-induced adverse birth outcomes.

Per and polyfluoroalkyl substances (PFAS) are associated with health outcomes ranging from cancer to high cholesterol. However, there has been little examination of how PFAS exposure might impact the development of multiple chronic diseases, known as multimorbidity. Here, we associated the presence of one or more PFAS in water systems serving the zip code of residence with chronic disease and multimorbidity.

Methods: We used data from the unregulated contaminant monitoring rule 3 to estimate exposure to PFAS for a random sample of 10,168 patients from the University of North Carolina Healthcare System. The presence of 16 chronic diseases was determined via. their electronic health records. We used a logistic regression model in a cross-sectional study design to associate the presence of one or more PFAS with multimorbidity. Models were adjusted for age, race, sex, smoking status, socioeconomic status, and 20 county-level confounders.

Results: There were four PFAS found in water systems that served at least one zip code represented in our patient data: PFOA, PFHpA, PFOS, and PFHxS. Exposure to any PFAS was associated with a odds ratio of 1.25 for multimorbidity (95% confidence interval = 1.09, 1.45). Among the chronic diseases with at least 300 cases, we observed associations with dyslipidemia, hypertension, ischemic heart disease, and osteoporosis.

Conclusion: Exposure to PFAS is associated with a range of chronic diseases as well as multimorbidity. Accounting for the joint impacts of PFAS on multiple chronic conditions may give an increasingly clear picture of the public health impacts of PFAS.

Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with substantial morbidity and mortality. Short-term exposure to fine particulate matter (PM_2.5) has been causally linked to higher risk of cardiovascular disease, but the association with atrial fibrillation (AF) is less clear.

Methods: We conducted a time-stratified case-crossover study to estimate the association between short-term air pollution levels and risk of AF episodes. The episodes were identified among patients with paroxysmal AF and an intracardiac devices able to register and store AF episodes. We obtained air pollution and temperature data from fixed monitoring stations and used conditional logistic regression to quantify the association of PM_2.5, particulate matter (PM₁₀), nitrogen dioxide (NO₂) and ozone (O₃) with onset of AF episodes, adjusting for temperature and public holidays.".

Results: We analyzed 584 episodes of AF from 91 participants and observed increased risk of AF episodes with PM_2.5 levels for the 48-72 hours lag (OR 1.05; CI [1.01,1.09] per IQR)] and 72-96 hours (OR 1.05 CI [1.00,1.10] per IQR). Our results were suggestive of an association between O₃ levels and AF episodes during the warm season. We did not observe any statistically significant associations for PM₁₀ nor NO₂.

Conclusion: Short-term increases in PM_2.5 in a low-pollution level environment were associated with increased risk of AF episodes in a population with intracardiac devices. Our findings add to the evidence of a potential triggering of AF by short-term increases in air pollution levels, well below the new WHO air quality guidelines.

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.