Semen quality and cigarette smoking in a cohort of healthy fertile men Background: Numerous health effects of smoking are well-known; associations with semen quality are uncertain. Most previous studies did not adjust for potential confounders and had limited information on age at smoking initiation or smoking cessation. Methods: We investigated 1,631 healthy fertile men in the Nanjing Medical University Longitudinal Investigation of Fertility and the Environment (NMU-LIFE) study. Relationships were examined using multivariable linear regression controlling for potential covariates. Results: We found a significant decrease in semen volume (β = −0.10, P = 0.001) and total sperm count (β = −0.42, P = 0.037), and significant increase in total motility (β = 6.02, P = 0.037) and progressive motility (β = 5.52, P = 0.037) in ever smokers of pack-years ≥10 compared with never smokers. We observed an inverse dose-dependent relation between smoking pack-years and semen volume (P < 0.001) and total sperm count (P = 0.010) and a positive dose-dependent relation between smoking pack-years and both total motility and progressive motility (P = 0.042 and 0.048, respectively). No significant differences in semen quality were detected among ever smokers with different ages at smoking initiation nor in former smokers compared with never smokers. Conclusions: Cigarette smoking was associated with lower semen volume and total sperm count and higher sperm motility. Smoking cessation might have a restorative effect on semen quality. This finding has important implications for public health research and for understanding the development of abnormal semen quality.

Change in PM2.5 exposure and mortality among Medicare recipients: Combining a semi-randomized approach and inverse probability weights in a low exposure population The association between PM2.5 and mortality is well established; however, confounding by unmeasured factors is always an issue. In addition, prior studies do not tell us what the effect of a sudden change in exposure on mortality is. We consider the sub-population of Medicare enrollees who moved residence from one ZIP Code to another from 2000 to 2012. Because the choice of new ZIP Code is unlikely to be related with any confounders, restricting to the population of movers allows us to have a study design that incorporates randomization of exposure. Over 10 million Medicare participants moved. We calculated change in exposure by subtracting the annual exposure at original ZIP Code from exposure at the new ZIP Code using a validated model. We used Cox proportional hazards models stratified on original ZIP Code with inverse probability weights (IPW) to control for individual and ecological confounders at the new ZIP Code. The distribution of covariates appeared to be randomized by change in exposure at the new locations as standardized differences were mostly near zero. Randomization of measured covariates suggests unmeasured covariates may be randomized also. Using IPW, per 10 µg/m3 increase in PM2.5, the hazard ratio was 1.21 (95% confidence interval [CI] = 1.20, 1.22] among whites and 1.12 (95% CI = 1.08, 1.15) among blacks. Hazard ratios increased for whites and decreased for blacks when restricting to exposure levels below the current standard of 12 µg/m3. This study provides evidence of likely causal effects at concentrations below current limits of PM2.5.

Ultraviolet radiation exposure and breast cancer risk in the Nurses’ Health Study II Background: Ultraviolet (UV) radiation exposure, the primary source of vitamin D for most people, may reduce breast cancer risk. To date, epidemiologic studies have shown inconsistent results. Methods: The Nurses’ Health Study II is a U.S. nationwide prospective cohort of female registered nurses. A UV exposure model was linked with geocoded residential address histories. Early-life UV exposure was estimated based on the state of residence at birth, age 15, and age 30. Self-reported breast cancer was confirmed from medical records. Time-varying Cox regression models adjusted for established breast cancer risk factors were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: From 1989 to 2013, 3,959 invasive breast cancer cases occurred among 112,447 participants. Higher UV exposure during adulthood was not associated with invasive breast cancer risk overall (adjusted HR comparing highest to lowest quintile = 1.00; 95% CI = 0.90, 1.11, P for trend = 0.64) or according to estrogen receptor (ER) status. There were suggestive inverse associations between ER− breast cancer and early-life UV exposure at birth (adjusted HR = 0.94; 95% CI = 0.88, 1.01 per interquartile range increase [15.7 mW/m2]), age 15 (adjusted HR = 0.96; 95% CI = 0.89, 1.04 per 18.0 mW/m2), and age 30 (adjusted HR = 0.90; 95% CI = 0.82, 1.00 per 27.7 mW/m2). Conclusions: Ambient UV exposure during adulthood was not associated with risk of invasive breast cancer overall or by ER status. However, we observed suggestive inverse associations between early-life UV exposure and ER− breast cancer risk.

Environmental noise and sleep and mental health outcomes in a nationally representative sample of urban US adolescents Background: Environmental noise has been linked to negative health outcomes, like poor sleep, poor mental health, and cardiovascular disease, and likely accounts for more than 1 million disability-adjusted life years annually in Western Europe. Adolescence may be a particularly sensitive period for noise exposure due to an increased need for sleep, failure to meet sleep guidelines, and increased risk for first onset of some mental health disorders. However, the potential health effects of living in high-noise environments have not been studied in US adolescents, rarely in European adolescents, and mental health outcomes studied have not corresponded to diagnoses from the Diagnostic and Statistical Manual of Mental Disorders (DSM). Methods: Using a US-based nationally representative survey of urban adolescents (N = 4,508), we estimated associations of day-night average sound levels exceeding the US Environmental Protection Agency’s 55 decibel limit with sleep outcomes and lifetime mental health DSM diagnoses. We implemented doubly robust targeted minimum loss-based estimation coupled with propensity score matching to account for numerous potential adolescent, household, and environmental confounders. Results: Living in a high- versus low-noise Census block group was associated with later bedtimes on weeknights (0.48 hours, 95% confidence interval [CI] = –0.15, 1.12) and weekend nights (0.65 hours, 95% CI = 0.37, 0.93), but not with total hours slept. Associations between living in a high- versus low-noise Census block group and mental disorders were mixed, with wide CIs, and not robust to sensitivity analyses. Conclusions: We find evidence for an association between residence in a high-noise area and later bedtimes among urban adolescents but no consistent evidence of such an association with mental health disorders.

Hazardous air pollutants and telomere length in the Sister Study Background: Telomeres are vital for genomic integrity, and telomere length has been linked to many adverse health outcomes. Some hazardous air pollutants or air toxics increase oxidative stress and inflammation, two possible determinants of shortened telomere length. No studies have examined air toxic–telomere length associations in a nonoccupational setting. Methods: This study included 731 Sister Study participants (enrolled 2003–2007) who were randomly selected to assess telomere length in baseline blood samples. Multiplex qPCR was used to determine telomere to single copy gene (T/S) ratios. Census tract concentration estimates of 29 air toxics from the 2005 National Air Toxics Assessment were linked to baseline residential addresses. Air toxics were classified into tertile-based categories of the exposure. Multivariable linear regression was used to estimate β coefficients and 95% confidence intervals (CIs) in single-pollutant models. Multipollutant groups were identified with regression trees. Results: The average T/S ratio was 1.24. Benzidine (T3 versus T1 β = −0.08; 95% CI = −0.14, −0.01) and 1,4-dioxane (T3 versus T1 β = −0.06; 95% CI = −0.13, 0.00) in particular, as well as carbon tetrachloride, chloroprene, ethylene dibromide, and propylene dichloride, were associated with shorter relative telomere length. Benzidine (P = 0.02) and 1,4-dioxane (P = 0.06) demonstrated some evidence of a monotonic trend. The regression tree identified age, BMI, physical activity, ethylene oxide, acrylonitrile, ethylidene dichloride, propylene dichloride, and styrene in multipollutant groups related to telomere length. Conclusions: In this first study of air toxics and telomere length in a nonoccupational setting, several air toxics, particularly 1,4-dioxane and benzidine, were associated with shorter relative telomere length.

Estimating the causal effect of annual PM2.5 exposure on mortality rates in the Northeastern and mid-Atlantic states Background: Dozens of cohort studies have associated particulate matter smaller than 2.5 µm in diameter (PM2.5) exposure with early deaths, and the Global Burden of Disease identified PM2.5 as the fifth-ranking mortality risk factor in 2015. However, few studies have used causal modeling techniques. We assessed the effect of annual PM2.5 exposure on all-cause mortality rates among the Medicare population in the Northeastern and mid-Atlantic states, using the difference-in-differences approach for causal modeling. Methods: We obtained records of Medicare beneficiaries 65 years of age or more who reside in the Northeastern or mid-Atlantic states from 2000 to 2013 and followed each participant from the year of enrollment to the last year of follow-up. We estimated the causal effect of annual PM2.5 exposure on mortality rates using the difference-in-differences approach in the Poisson survival analysis. We controlled for individual confounders, for spatial differences using dummy variables for each ZIP code and for time trends using a penalized spline of year. Results: We included 112,376,805 person-years from 15,401,064 people, of whom 37.4% died during the study period. The interquartile range (IQR) of the annual PM2.5 concentration was 3 µg/m3, and the mean annual PM2.5 concentration ranged between 6.5 and 14.5 µg/m3 during the study period. An IQR incremental increase in PM2.5 was associated with a 4.04% increase (95% CI = 3.49%, 4.59%) in mortality rates. Conclusions: Assuming no omitted predictors changing differently across ZIP codes over time in correlation with PM2.5, we found a causal effect of PM2.5 on mortality incidence rate.

Low birth weight and PM2.5 in Puerto Rico Background: Low birth weight (LBW) has been associated with adverse health outcomes across the lifespan. Among ethnic/racial minority populations, few studies have examined the association between LBW (<2,500 or ≥2,500 g) and prenatal exposure to air pollution, a key modifiable environmental risk factor. Methods: We examined the association between LBW and prenatal exposure to PM2.5 in a Hispanic and black population in Puerto Rico between 1999 and 2013, adjusting for individual and municipality-level confounders. We used modified Poisson regression to estimate the association and performed sensitivity analyses treating birth weight as continuous or polychotomous. In secondary analyses, we applied a 2-stage mixed effects model suitable for longitudinally measured exposures and binary outcomes. Results: Among 332,129 total and 275,814 term births, 12.2% and 6.3% of infants had LBW, respectively. Eighty-eight percent of mothers were Hispanic. Mean (SD) PM2.5 concentrations declined from 9.9 (1.7) µg/m3 in 1999 to 6.1 (1.1) µg/m3 in 2013. Mean birth weights dropped to 3,044 g in 2010 and rose steadily afterward. Among term births, a SD increase in PM2.5 was associated with a 3.2% (95% CI = −1.0%, 6.3%) higher risk of LBW. First (risk ratio, 1.02; 95% CI = 1.00, 1.04) and second (1.02; 95% CI = 1.01, 1.05) trimester exposures were associated with increased LBW risk. In a 2-stage approach that longitudinally modeled monthly prenatal exposure levels, a standard deviation increase in average PM2.5 was associated with higher risk of LBW (odds ratio, 1.04; 95% CI = 1.01, 1.08). Conclusions: In Puerto Rico, LBW is associated with prenatal PM2.5 exposure.

A quantile regression approach to examine fine particles, term low birth weight, and racial/ethnic disparities Background: Exposure to fine particulate matter (PM2.5) during pregnancy has been shown to be associated with reduced birth weight and racial/ethnic minorities have been found to be more vulnerable. Previous studies have focused on the mean value of birth weight associated with PM2.5, which may mask meaningful differences. We applied a quantile regression approach to investigate the variation by percentile of birth weight and compared non-Hispanic (NH) Black, NH White, and Hispanic mothers. Methods: Data for singleton births in California from October 24, 2005 to February 27, 2010 were collected from the birth records accessed from the California Department of Public Health. Air pollution monitoring data collected by the California Air Resources Board and interpolated for each zip code using an inverse-distance weighting approach, and linked to maternal zip code of residence reported on the birth certificate. Multilevel linear regression models were conducted with mother’s residential zip code tabulation area as a random effect. Multilevel quantile regression models were used to analyze the association at different percentiles of birth weight (5th, 10th, 25th, 50th, 75th, 90th, 95th), as well as examine the heterogeneity in this association between racial/ethnic groups. Results: Linear regression revealed that a 10 μg/m3 increase in PM2.5 exposure during pregnancy is associated with a mean birth weight decrease of 7.31 g [95% confidence interval (CI): 8.10, 6.51] and NH Black mothers are the most vulnerable. Results of the quantile regression are not constant across quantiles. For NH Black mothers whose infants had the lowest birthweight of less than 2673 g (5th percentile), a 10 μg/m3 increase in PM2.5 exposure is associated with a decrease of 18.57 g [95% CI: 22.23, 14.91], while it is associated with a decrease of 7.77 g [95% CI: 8.73, 6.79] for NH White mothers and 7.76 [8.52, 7.00] decrease for Hispanic mothers at the same quantile. Conclusion: Results of the quantile regression revealed greater disparities, particularly for infants with the lowest birth weight. By identifying vulnerable populations, we can promote and implement policies to confront these health disparities.

Air pollution-associated changes in biomarkers of diabetes risk Background: Ambient particulate matter (PM) and nitrogen oxide (NOx) air pollution may be diabetogenic. Objective: To examine longitudinal associations of short- and longer-term mean PM ≤10 μm (PM10), PM ≤2.5 μm (PM2.5), and NOx concentrations with five biomarkers of diabetes risk. Methods: We studied a stratified, random minority oversample of nondiabetic Women’s Health Initiative clinical trials participants with biomarkers and geocoded participant address-specific mean air pollution concentrations available at repeated visits (years = 1993–2004; n = 3,915; mean age = 62.7 years; 84% white). We log-transformed the biomarkers, then used multi-level, mixed-effects, longitudinal models weighted for sampling design/attrition and adjusted for sociodemographic, clinical, and meteorological covariates to estimate their associations with air pollutants. Results: Biomarkers exhibited null to suggestively negative associations with short- and longer-term PM10 and NOx concentrations, e.g., −3.1% (−6.1%, 0.1%), lower homeostatic model assessment of insulin resistance per 10 μg/m3 increase in 12-month PM10. A statistically significant interaction by impaired fasting glucose (IFG) at baseline in this analysis indicated potentially adverse effects only among women with versus without IFG, i.e., 1.4% (−3.5%, 6.5%) versus −4.6% (−7.9%, −1.1%), Pinteraction < 0.05. In contrast, longer-term PM2.5 concentrations were largely but not statistically significantly associated with higher biomarkers. Conclusions: Low-level short-term PM10 and NOx concentrations may have negligible adverse effects on biomarkers of diabetes risk. Although longer-term mean PM2.5 concentrations showed primarily null associations with these biomarkers, results suggestively indicated that PM2.5 exposure over the range of concentrations experienced in the United States may adversely affect biomarkers of diabetes risk at the population level, as may longer-term mean PM10 concentrations among women with IFG.