Short-term exposures to temperature and risk of sudden cardiac death in women: A case-crossover analysis in the Nurses' Health Study.

Background: Sudden cardiac death (SCD) is a major source of mortality and is the first manifestation of heart disease for most cases. Thus, there is a definite need to identify risk factors for SCD that can be modified on the population level. Short-term exposures to temperature have been implicated as a potential risk factor. Our objective was to determine if short-term temperature exposures were associated with increased risk of SCD in a US-based time-stratified case-crossover study. Methods: A total of 465 cases of SCD were identified among participants of the prospective Nurses' Health Study (NHS). Control days were selected from all other matching days of the week within the same month as the case day. Average ambient temperature on the current day (Lag0) and preceding 27 days (Lags1-27) was determined at the residence level using 800-m resolution estimates. Conditional logistic distributed lag nonlinear models (DLNMs) were used to assess the relative risk (RR) of the full range of temperature exposures over the lag period. Results: Warmer exposures in the days before event and colder temperatures 21-28 days prior were associated with increased risks of SCD. These results were driven by associations in regions other than the Northeast and among married women. Conclusions: Both warm and cold ambient temperatures are suggestively associated with risks of SCD among middle-aged and older women living across the United States.

Using Parametric g-Computation for Time-to-Event Data and Distributed Lag Models to Identify Critical Exposure Windows for Preterm Birth: An Illustrative Example Using PM2.5 in a Retrospective Birth Cohort Based in Eastern Massachusetts (2011-2016).

BACKGROUND: Parametric g-computation is an attractive analytic framework to study the health effects of air pollution. Yet, the ability to explore biologically relevant exposure windows within this framework is underdeveloped. OBJECTIVES: We outline a novel framework for how to incorporate complex lag-responses using distributed lag models (DLMs) into parametric g-computation analyses for survival data. We call this approach "g-survival-DLM" and illustrate its use examining the association between PM2.5 during pregnancy and the risk of preterm birth (PTB). METHODS: We applied the g-survival-DLM approach to estimate the hypothetical static intervention of reducing average PM2.5 in each gestational week by 20% on the risk of PTB among 9,403 deliveries from Beth Israel Deaconess Medical Center, Boston, Massachusetts, 2011-2016. Daily PM2.5 was taken from a 1-km grid model and assigned to address at birth. Models were adjusted for sociodemographics, time trends, nitrogen dioxide, and temperature. To facilitate implementation, we provide a detailed description of the procedure and accompanying R syntax. RESULTS: There were 762 (8.1%) PTBs in this cohort. The gestational week-specific median PM2.5 concentration was relatively stable across pregnancy at ∼7µg/m3. We found that our hypothetical intervention strategy changed the cumulative risk of PTB at week 36 (i.e., the end of the preterm period) by -0.009 (95% confidence interval: -0.034, 0.007) in comparison with the scenario had we not intervened, which translates to about 86 fewer PTBs in this cohort. We also observed that the critical exposure window appeared to be weeks 5-20. DISCUSSION: We demonstrate that our g-survival-DLM approach produces easier-to-interpret, policy-relevant estimates (due to the g-computation); prevents immortal time bias (due to treating PTB as a time-to-event outcome); and allows for the exploration of critical exposure windows (due to the DLMs). In our illustrative example, we found that reducing fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5)] during gestational weeks 5-20 could potentially lower the risk of PTB. https://doi.org/10.1289/EHP13891.

Prenatal air pollution and children's autism traits score: Examination of joint associations with maternal intake of vitamin D, methyl donors, and polyunsaturated fatty acids using mixture methods.

Background: Maternal nutrient intake may moderate associations between environmental exposures and children's neurodevelopmental outcomes, but few studies have assessed joint effects. We aimed to evaluate whether prenatal nutrient intake influences the association between air pollutants and autism-related trait scores. Methods: We included 126 participants from the EARLI (Early Autism Risk Longitudinal Investigation, 2009-2012) cohort, which followed US pregnant mothers who previously had a child with autism. Bayesian kernel machine regression and traditional regression models were used to examine joint associations of prenatal nutrient intake (vitamins D, B12, and B6; folate, choline, and betaine; and total omega 3 and 6 polyunsaturated fatty acids, reported via food frequency questionnaire), air pollutant exposure (particulate matter <2.5 µm [PM2.5], nitrogen dioxide [NO2], and ozone [O3], estimated at the address level), and children's autism-related traits (measured by the Social Responsiveness Scale [SRS] at 36 months). Results: Most participants had nutrient intakes and air pollutant exposures that met US standards. Bayesian kernel machine regression mixture models and traditional regression models provided little evidence of individual or joint associations of nutrients and air pollutants with SRS scores or of an association between the overall mixture and SRS scores. Conclusion: In this cohort with a high familial likelihood of autism, we did not observe evidence of joint associations between air pollution exposures and nutrient intake with autism-related traits. Future work should examine the use of these methods in larger, more diverse samples, as our results may have been influenced by familial liability and/or relatively high nutrient intakes and low air pollutant exposures.

Long-term exposure to air pollution, greenness and temperature and survival after a nonfatal myocardial infarction.

BACKGROUND: Little is known about the impact of environmental exposures on mortality risk after a myocardial infarction (MI). OBJECTIVE: The goal of this study was to evaluate associations of long-term temperature, air pollution and greenness exposures with mortality among survivors of an MI. METHODS: We used data from the US-based Nurses' Health Study to construct an open cohort of survivors of a nonfatal MI 1990-2017. Participants entered the cohort when they had a nonfatal MI, and were followed until death, loss to follow-up, end of follow-up, or they reached 80 years old, whichever came earliest. We assessed residential 12-month moving average fine particulate matter (PM2.5) and nitrogen dioxide (NO2), satellite-based annual average greenness (in a circular 1230 m buffer), summer average temperature and winter average temperature. We used Cox proportional hazard models adjusted for potential confounders to assess hazard ratios (HR and 95% confidence intervals). We also assessed potential effect modification. RESULTS: Among 2262 survivors of a nonfatal MI, we observed 892 deaths during 19,216 person years of follow-up. In single-exposure models, we observed a HR (95%CI) of 1.20 (1.04, 1.37) per 10 ppb NO2 increase and suggestive positive associations were observed for PM2.5, lower greenness, warmer summer average temperature and colder winter average temperature. In multi-exposure models, associations of summer and winter average temperature remained stable, while associations of NO2, PM2.5 and greenness attenuated. The strength of some associations was modified by other exposures. For example, associations of greenness (HR = 0.88 (0.78, 0.98) per 0.1) were more pronounced for participants in areas with a lower winter average temperature. CONCLUSION: We observed associations of air pollution, greenness and temperature with mortality among MI survivors. Some associations were confounded or modified by other exposures, indicating that it is important to explore the combined impact of environmental exposures.

Associations of street-view greenspace with Parkinson's disease hospitalizations in an open cohort of elderly US Medicare beneficiaries.

INTRODUCTION: Protective associations of greenspace with Parkinson's disease (PD) have been observed in some studies. Visual exposure to greenspace seems to be important for some of the proposed pathways underlying these associations. However, most studies use overhead-view measures (e.g., satellite imagery, land-classification data) that do not capture street-view greenspace and cannot distinguish between specific greenspace types. We aimed to evaluate associations of street-view greenspace measures with hospitalizations with a PD diagnosis code (PD-involved hospitalization). METHODS: We created an open cohort of about 45.6 million Medicare fee-for-service beneficiaries aged 65 + years living in core based statistical areas (i.e. non-rural areas) in the contiguous US (2007-2016). We obtained 350 million Google Street View images across the US and applied deep learning algorithms to identify percentages of specific greenspace features in each image, including trees, grass, and other green features (i.e., plants, flowers, fields). We assessed yearly average street-view greenspace features for each ZIP code. A Cox-equivalent re-parameterized Poisson model adjusted for potential confounders (i.e. age, race/ethnicity, socioeconomic status) was used to evaluate associations with first PD-involved hospitalization. RESULTS: There were 506,899 first PD-involved hospitalizations over 254,917,192 person-years of follow-up. We found a hazard ratio (95% confidence interval) of 0.96 (0.95, 0.96) per interquartile range (IQR) increase for trees and a HR of 0.97 (0.96, 0.97) per IQR increase for other green features. In contrast, we found a HR of 1.06 (1.04, 1.07) per IQR increase for grass. Associations of trees were generally stronger for low-income (i.e. Medicaid eligible) individuals, Black individuals, and in areas with a lower median household income and a higher population density. CONCLUSION: Increasing exposure to trees and other green features may reduce PD-involved hospitalizations, while increasing exposure to grass may increase hospitalizations. The protective associations may be stronger for marginalized individuals and individuals living in densely populated areas.

Urinary benzophenone-3 concentrations and ovarian reserve in a cohort of subfertile women.

OBJECTIVE: To evaluate the association between the urinary benzophenone-3 concentrations and measures of ovarian reserve (OR) among women in the Environment and Reproductive Health study seeking fertility treatment at Massachusetts General Hospital (MGH) in Boston, Massachusetts. DESIGN: Prospective cohort study. SETTING: MGH infertility clinic in Boston, Massachusetts. PATIENT(S): Women in the Environment and Reproductive Health cohort seeking fertility treatment. INTERVENTION(S): Women contributed spot urine samples prior to assessment of OR outcomes that were analyzed for benzophenone-3 concentrations. MAIN OUTCOME MEASURE(S): Antral follicle count (AFC) and day 3 follicle-stimulating hormone (FSH) levels were evaluated as part of standard infertility workups during unstimulated menstrual cycles. Quasi-Poisson and linear regression models were used to evaluate the association of the specific gravity-adjusted urinary benzophenone-3 concentrations with AFC and FSH, with adjustment for age and physical activity. In the secondary analyses, models were stratified by age. RESULT(S): This study included 142 women (mean age ± standard deviation, 36.1 ± 4.6 years; range, 22-45 years) enrolled between 2009 and 2017 with both urinary benzophenone-3 and AFC measurements and 57 women with benzophenone-3 and FSH measurements. Most women were White (78%) and highly educated (49% with a graduate degree). Women contributed a mean of 2.7 urine samples (range, 1-10), with 37% contributing ≥2 samples. Benzophenone-3 was detected in 98% of samples. The geometric mean specific gravity-corrected urinary benzophenone-3 concentration was 85.9 µg/L (geometric standard deviation, 6.2). There were no associations of benzophenone-3 with AFC and day 3 FSH in the full cohort. In stratified models, a 1-unit increase in the log geometric mean benzophenone-3 concentration was associated with a 0.91 (95% confidence interval, 0.86-0.97) times lower AFC among women aged ≤35 years and an increase in the FSH concentration of 0.73 (95% confidence interval, 0.12-1.34) IU/L among women aged >35 years. CONCLUSION(S): In the main models, urinary benzophenone-3 was not associated with OR. However, younger patients may be vulnerable to the potential effects of benzophenone-3 on AFC. Further research is warranted.

Association of Residential Exposure to Hazardous Air Pollutants with Risk of Non-Hodgkin Lymphoma and Multiple Myeloma.

BACKGROUND: Certain hazardous air pollutants (HAP) are known or suspected to pose immunological or cancer risk to humans, but evidence is limited from the general population. METHODS: We assessed associations between residential exposure to HAPs at the census tract level and incident non-Hodgkin lymphoma (NHL) and multiple myeloma in the Nurses' Health Study (NHS, 1986-2012) and NHSII (1989-2019). We used the covariate-adjusted proportional hazards model to estimate hazard ratios (HR) of NHL, major NHL subtypes, and multiple myeloma per interquartile range increase in exposure to a given HAP and pooled the cohort-specific estimates using fixed-effects meta-analyses. RESULTS: There were 810 NHL and 158 multiple myeloma cases in NHS (1,700,707 person-years) and 379 NHL and 59 multiple myeloma cases in NHSII (2,820,772 person-years). Most HRs approximated unity. Meta-analyses did not show consistent evidence of associations between any HAP exposure and risk of NHL or multiple myeloma. CONCLUSIONS: Exposure to HAPs was not consistently associated with risks of NHL or multiple myeloma in these nationwide prospective cohorts of women. IMPACT: This is the first nationwide study assessing associations between residential HAP exposures and risk of lymphoid malignances in prospective cohorts and focuses on women, who have frequently been underrepresented in (primarily occupational) studies of exposure to HAPs.

Maternal One-Carbon Nutrient Intake and Risk of Being Overweight or Obese in Their Offspring-A Transgenerational Prospective Cohort Study.

We aimed to investigate the associations between maternal intake of folate, vitamin B12, B6, B2, methionine, choline, phosphatidylcholine and betaine during the period surrounding pregnancy and offspring weight outcomes from birth to early adulthood. These associations were examined among 2454 mother-child pairs from the Nurses' Health Study II and Growing Up Today Study. Maternal energy-adjusted nutrient intakes were derived from food frequency questionnaires. Birth weight, body size at age 5 and repeated BMI measurements were considered. Overweight/obesity was defined according to the International Obesity Task Force (<18 years) and World Health Organization guidelines (18+ years). Among other estimands, we report relative risks (RRs) for offspring ever being overweight with corresponding 95% confidence intervals across quintiles of dietary factors, with the lowest quintile as the reference. In multivariate-adjusted models, higher maternal intakes of phosphatidylcholine were associated with a higher risk of offspring ever being overweight (RRQ5vsQ1 = 1.16 [1.01-1.33] p-trend: 0.003). The association was stronger among offspring born to mothers with high red meat intake (high red meat RRQ5vsQ1 = 1.50 [1.14-1.98], p-trend: 0.001; low red meat RRQ5vsQ1 = 1.05 [0.87-1.27], p-trend: 0.46; p-interaction = 0.13). Future studies confirming the association between a higher maternal phosphatidylcholine intake during pregnancy and offspring risk of being overweight or obese are needed.

Aircraft noise exposure and body mass index among female participants in two Nurses' Health Study prospective cohorts living around 90 airports in the United States.

OBJECTIVE: Aircraft noise exposure is linked to cardiovascular disease risk. One understudied candidate pathway is obesity. This study investigates the association between aircraft noise and obesity among female participants in two prospective Nurses' Health Study (NHS and NHSII) cohorts. METHODS: Aircraft day-night average sound levels (DNL) were estimated at participant residential addresses from modeled 1 dB (dB) noise contours above 44 dB for 90 United States (U.S.) airports in 5-year intervals 1995-2010. Biennial surveys (1994-2017) provided information on body mass index (BMI; dichotomized, categorical) and other individual characteristics. Change in BMI from age 18 (BMI18; tertiles) was also calculated. Aircraft noise exposures were dichotomized (45, 55 dB), categorized (<45, 45-54, ≥55 dB) or continuous for exposure ≥45 dB. Multivariable multinomial logistic regression using generalized estimating equations were adjusted for individual characteristics and neighborhood socioeconomic status, greenness, population density, and environmental noise. Effect modification was assessed by U.S. Census region, climate boundary, airline hub type, hearing loss, and smoking status. RESULTS: At baseline, the 74,848 female participants averaged 50.1 years old, with 83.0%, 14.8%, and 2.2% exposed to <45, 45-54, and ≥55 dB of aircraft noise, respectively. In fully adjusted models, exposure ≥55 dB was associated with 11% higher odds (95% confidence interval [95%CI]: -1%, 24%) of BMIs ≥30.0, and 15% higher odds (95%CI: 3%, 29%) of membership in the highest tertile of BMI18 (ΔBMI 6.7 to 71.6). Less-pronounced associations were observed for the 2nd tertile of BMI18 (ΔBMI 2.9 to 6.6) and BMI 25.0-29.9 as well as exposures ≥45 versus <45 dB. There was evidence of DNL-BMI trends (ptrends ≤ 0.02). Stronger associations were observed among participants living in the West, arid climate areas, and among former smokers. DISCUSSION: In two nationwide cohorts of female nurses, higher aircraft noise exposure was associated with higher BMI, adding evidence to an aircraft noise-obesity-disease pathway.

Associations of fine particulate matter with incident cardiovascular disease; comparing models using ZIP code-level and individual-level fine particulate matter and confounders.

BACKGROUND: PM2.5 has been positively associated with cardiovascular disease (CVD) incidence. Most evidence has come from cohorts and administrative databases. Cohorts typically have extensive information on potential confounders and residential-level exposures. Administrative databases are usually more representative but typically lack information on potential confounders and often only have exposures at coarser geographies (e.g., ZIP code). The weaknesses in both types of studies have been criticized for potentially jeopardizing the validity of their findings for regulatory purposes. METHODS: We followed 101,870 participants from the US-based Nurses' Health Study (2000-2016) and linked residential-level PM2.5 and individual-level confounders, and ZIP code-level PM2.5 and confounders. We used time-varying Cox proportional hazards models to examine associations with CVD incidence. We specified basic models (adjusted for individual-level age, race and calendar year), individual-level confounder models, and ZIP code-level confounder models. RESULTS: Residential- and ZIP code-level PM2.5 were strongly correlated (Pearson r = 0.88). For residential-level PM2.5, the hazard ratio (HR, 95 % confidence interval) per 5 µg/m3 increase was 1.06 (1.01, 1.11) in the basic and 1.04 (0.99, 1.10) in the individual-level confounder model. For ZIP code-level PM2.5, the HR per 5 µg/m3 was 1.04 (0.99, 1.08) in the basic and 1.02 (0.97, 1.08) in the ZIP code-level confounder model. CONCLUSION: We observed suggestive positive, but not statistically significant, associations between long-term PM2.5 and CVD incidence, regardless of the exposure or confounding model. Although differences were small, associations from models with individual-level confounders and residential-level PM2.5 were slightly stronger than associations from models with ZIP code-level confounders and PM2.5.

Nurses' use of 'wellness' supplements during the COVID-19 pandemic in the United States.

AIM: Quantify disparities and identify correlates and predictors of 'wellness' supplement use among nurses during the first year of the pandemic. DESIGN: Longitudinal secondary analysis of Nurses' Health Studies 2 and 3 and Growing Up Today Study data. METHODS: Sample included 36,518 total participants, 12,044 of which were nurses, who completed surveys during the first year of the COVID-19 pandemic (April 2020 to April 2021). Analyses were conducted in March 2023. Modified Poisson models were used to estimate disparities in 'wellness' supplement use between nurses and non-healthcare workers and, among nurses only, to quantify associations with workplace-related predictors (occupational discrimination, PPE access, workplace setting) and psychosocial predictors (depression/anxiety, county-level COVID-19 mortality). Models included race/ethnicity, gender identity, age and cohort as covariates. RESULTS: Nurses were significantly more likely to use all types of supplements than non-healthcare workers. Lacking personal protective equipment and experiencing occupational discrimination were significantly associated with new immune supplement use. Depression increased the risk of using weight loss, energy and immune supplements. CONCLUSION: Nurses' disproportionate use of 'wellness' supplements during the COVID-19 pandemic may be related to workplace and psychosocial stressors. Given well-documented risks of harm from the use of 'wellness' supplements, the use of these products by nurses is of concern. IMPACT: 'Wellness' supplements promoting weight loss, increased energy, boosted immunity and cleansing of organs are omnipresent in today's health-focused culture, though their use has been associated with harm. This is of added concern among nurses given their risk of COVID-19 infection at work. Our study highlighted the risk factors associated with use of these products (lacking PPE and experiencing occupational discrimination). Findings support prior research suggesting a need for greater public health policy and education around the use of 'wellness' supplements. REPORTING METHOD: STROBE guidelines were followed throughout manuscript. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution was involved.

Deployment-related Cigarette Smoking Behaviors and Pulmonary Function Among U.S. Veterans.

INTRODUCTION: The effects of smoking on lung function among post-9/11 Veterans deployed to environments with high levels of ambient particulate matter are incompletely understood. MATERIALS AND METHODS: We analyzed interim data (04/2018-03/2020) from the Veterans Affairs (VA) Cooperative Studies Program #595, "Service and Health Among Deployed Veterans". Veterans with ≥1 land-based deployments enrolled at 1 of 6 regional Veterans Affairs sites completed questionnaires and spirometry. Multivariable linear regression models assessed associations between cigarette smoking (cumulative, deployment-related and non-deployment-related) with pulmonary function. RESULTS: Among 1,836 participants (mean age 40.7 ± 9.6, 88.6% male), 44.8% (n = 822) were ever-smokers (mean age 39.5 ± 9.5; 91.2% male). Among ever-smokers, 86% (n = 710) initiated smoking before deployment, while 11% (n = 90) initiated smoking during deployment(s). Smoking intensity was 50% greater during deployment than other periods (0.75 versus 0.50 packs-per-day; P < .05), and those with multiple deployments (40.4%) were more likely to smoke during deployment relative to those with single deployments (82% versus 74%). Total cumulative pack-years (median [IQR] = 3.8 [1, 10]) was inversely associated with post-bronchodilator FEV1%-predicted (-0.82; [95% CI] = [-1.25, -0.50] %-predicted per 4 pack-years) and FEV1/FVC%-predicted (-0.54; [95% CI] = [-0.78, -0.43] %-predicted per 4 pack-years). Deployment-related pack-years demonstrated similar point estimates of associations with FEV1%-predicted (-0.61; [95% CI] = [-2.28, 1.09]) and FEV1/FVC%-predicted (-1.09; [95% CI] = [-2.52, 0.50]) as non-deployment-related pack-years (-0.83; [95% CI] = [-1.26, -0.50] for FEV1%-predicted; -0.52; [95% CI] = [-0.73, -0.36] for FEV1/FVC%-predicted). CONCLUSIONS: Although cumulative pack-years smoking was modest in this cohort, an inverse association with pulmonary function was detectable. Deployment-related pack-years had a similar association with pulmonary function compared to non-deployment-related pack-years.

Indoor and ambient black carbon and fine particulate matter associations with blood biomarkers in COPD patients.

BACKGROUND: Systemic inflammation contributes to cardiovascular risk and chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between systemic inflammation and exposure to ambient fine particulate matter (PM ≤ 2.5 µm diameter; PM2.5), and black carbon (BC), a PM2.5 component attributable to traffic and other sources of combustion, infiltrating indoors are not well described. METHODS: Between 2012 and 2017, COPD patients completed in-home air sampling over one-week intervals, up to four times (seasonally), followed by measurement of plasma biomarkers of systemic inflammation, C-reactive protein (CRP) and interleukin-6 (IL-6), and endothelial activation, soluble vascular adhesion molecule-1 (sVCAM-1). Ambient PM2.5, BC and sulfur were measured at a central site. The ratio of indoor/ambient sulfur in PM2.5, a surrogate for fine particle infiltration, was used to estimate indoor BC and PM2.5 of ambient origin. Linear mixed effects regression with a random intercept for each participant was used to assess associations between indoor and indoor of ambient origin PM2.5 and BC with each biomarker. RESULTS: 144 participants resulting in 482 observations were included in the analysis. There were significant positive associations between indoor BC and indoor BC of ambient origin with CRP [%-increase per interquartile range (IQR);95 % CI (13.2 %;5.2-21.8 and 11.4 %;1.7-22.1, respectively)]. Associations with indoor PM2.5 and indoor PM2.5 of ambient origin were weaker. There were no associations with IL-6 or sVCAM-1. CONCLUSIONS: In homes of patients with COPD without major sources of combustion, indoor BC is mainly attributable to the infiltration of ambient sources of combustion indoors. Indoor BC of ambient origin is associated with increases in systemic inflammation in patients with COPD, even when staying indoors.

The paradox of high greenness and poor health in rural Central Appalachia.

While many studies have found positive correlations between greenness and human health, rural Central Appalachia is an exception. The region has high greenness levels but poor health. The purpose of this commentary is to provide a possible explanation for this paradox: three sets of factors overwhelming or attenuating the health benefits of greenness. These include environmental (e.g., steep typography and limited access to green space used for outdoor recreation), social (e.g., chronic poverty, declining coal industry, and limited access to healthcare), and psychological and behavioral factors (e.g., perceptions about health behaviors, healthcare, and greenness). The influence of these factors on the expected health benefits of greenness should be considered as working hypotheses for future research. Policymakers and public health officials need to ensure that greenness-based interventions account for contextual factors and other determinants of health to ensure these interventions have the expected health benefits.

Timing and duration of dog walking and dog owner's chronotype in relation to incident depression risk among middle to older-aged female nurses.

BACKGROUND: We examined associations between dog ownership, morning dog walking and its timing and duration, and depression risk in female nurses, exploring effect modification by chronotype. We hypothesized that dog ownership and morning walking with the dog are associated with lower odds of depression, and that the latter is particularly beneficial for evening chronotypes by helping them to synchronize their biological clock with the solar system. METHODS: 26,169 depression-free US women aged 53-72 from the Nurses' Health Study 2 (NHS2) were prospectively followed from 2017-2019. We used age- and multivariable-adjusted logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for depression according to dog ownership, and morning dog walking, duration, and timing. RESULTS: Overall, there was no association between owning a dog (ORvs_no_pets = 1.12, 95%CI = 0.91-1.37), morning dog walking (ORvs_not = 0.87, 95%CI = 0.64-1.18), or the duration (OR>30min vs. ≤15mins = 0.68, 95%CI = 0.35-1.29) or timing of morning dog walks (ORafter9am vs. before7am = 1.06, 95%CI = 0.54-2.05) and depression. Chronotype of dog owners appeared to modify these associations. Compared to women of the same chronotype but without pets, dog owners with evening chronotypes had a significantly increased odds of depression (OR = 1.60, 95%CI = 1.12-2.29), whereas morning chronotypes did not (OR = 0.94, 95%CI = 0.71-1.23). Further, our data suggested that evening chronotypes benefited more from walking their dog themselves in the morning (OR = 0.75, 95%CI = 0.46-1.23, Pintx = 0.064;) than morning chronotypes. CONCLUSIONS: Overall, dog ownership was not associated with depression risk though it was increased among evening chronotypes. Walking their dog in the morning might help evening chronotypes to lower their odds of depression, though more data are needed to confirm this finding.

Chronic respiratory symptoms following deployment-related occupational and environmental exposures among US veterans.

OBJECTIVES: Characterise inhalational exposures during deployment to Afghanistan and Southwest Asia and associations with postdeployment respiratory symptoms. METHODS: Participants (n=1960) in this cross-sectional study of US Veterans (Veterans Affairs Cooperative Study 'Service and Health Among Deployed Veterans') completed an interviewer-administered questionnaire regarding 32 deployment exposures, grouped a priori into six categories: burn pit smoke; other combustion sources; engine exhaust; mechanical and desert dusts; toxicants; and military job-related vapours gas, dusts or fumes (VGDF). Responses were scored ordinally (0, 1, 2) according to exposure frequency. Factor analysis supported item reduction and category consolidation yielding 28 exposure items in 5 categories. Generalised linear models with a logit link tested associations with symptoms (by respiratory health questionnaire) adjusting for other covariates. OR were scaled per 20-point score increment (normalised maximum=100). RESULTS: The cohort mean age was 40.7 years with a median deployment duration of 11.7 months. Heavy exposures to multiple inhalational exposures were commonly reported, including burn pit smoke (72.7%) and VGDF (72.0%). The prevalence of dyspnoea, chronic bronchitis and wheeze in the past 12 months was 7.3%, 8.2% and 15.6%, respectively. Burn pit smoke exposure was associated with dyspnoea (OR 1.22; 95% CI 1.06 to 1.47) and chronic bronchitis (OR 1.22; 95% CI 1.13 to 1.44). Exposure to VGDF was associated with dyspnoea (OR 1.29; 95% CI 1.14 to 1.58) and wheeze (OR 1.18; 95% CI 1.02 to 1.35). CONCLUSION: Exposures to burn pit smoke and military occupational VGDF during deployment were associated with an increased odds of chronic respiratory symptoms among US Veterans.

The association between preconception cannabis use and gestational diabetes mellitus: The Preconception Period Analysis of Risks and Exposures Influencing health and Development (PrePARED) consortium.

BACKGROUND: The metabolic changes that ultimately lead to gestational diabetes mellitus (GDM) likely begin before pregnancy. Cannabis use might increase the risk of GDM by increasing appetite or promoting fat deposition and adipogenesis. OBJECTIVES: We aimed to assess the association between preconception cannabis use and GDM incidence. METHODS: We analysed individual-level data from eight prospective cohort studies. We identified the first, or index, pregnancy (lasting ≥20 weeks of gestation with GDM status) after cannabis use. In analyses of pooled individual-level data, we used logistic regression to estimate study-type-specific odds ratios (OR) and 95% confidence intervals (CI), adjusting for potential confounders using random effect meta-analysis to combine study-type-specific ORs and 95% CIs. Stratified analyses assessed potential effect modification by preconception tobacco use and pre-pregnancy body mass index (BMI). RESULTS: Of 17,880 participants with an index pregnancy, 1198 (6.7%) were diagnosed with GDM. Before the index pregnancy, 12.5% of participants used cannabis in the past year. Overall, there was no association between preconception cannabis use in the past year and GDM (OR 0.97, 95% CI 0.79, 1.18). Among participants who never used tobacco, however, those who used cannabis more than weekly had a higher risk of developing GDM than those who did not use cannabis in the past year (OR 2.65, 95% CI 1.15, 6.09). This association was not present among former or current tobacco users. Results were similar across all preconception BMI groups. CONCLUSIONS: In this pooled analysis of preconception cohort studies, preconception cannabis use was associated with a higher risk of developing GDM among individuals who never used tobacco but not among individuals who formerly or currently used tobacco. Future studies with more detailed measurements are needed to investigate the influence of preconception cannabis use on pregnancy complications.

Association between Noise and Cardiovascular Disease in a Nationwide U.S. Prospective Cohort Study of Women Followed from 1988 to 2018.

BACKGROUND: Long-term noise exposure is associated with cardiovascular disease (CVD), including acute cardiovascular events such as myocardial infarction and stroke. However, longitudinal cohort studies in the U.S. of long-term noise and CVD are almost exclusively from Europe and few modeled nighttime noise, when an individual is likely at home or asleep, separately from daytime noise. We aimed to examine the prospective association of outdoor long-term nighttime and daytime noise from anthropogenic sources with incident CVD using a U.S.-based, nationwide cohort of women. METHODS: We linked L50 nighttime and L50 daytime anthropogenic modeled noise estimates from a U.S. National Parks Service model (L50: sound pressure levels exceeded 50 percent of the time) to geocoded residential addresses of 114,116 participants in the Nurses' Health Study. We used time-varying Cox proportional hazards models to estimate risk of incident CVD, coronary heart disease (CHD), and stroke associated with long-term average (14-y measurement period) noise exposure, adjusted for potential individual- and area-level confounders and CVD risk factors (1988-2018; biennial residential address updates; monthly CVD updates). We assessed effect modification by population density, region, air pollution, vegetation cover, and neighborhood socioeconomic status, and explored mediation by self-reported average nightly sleep duration. RESULTS: Over 2,548,927 person-years, there were 10,331 incident CVD events. In fully adjusted models, the hazard ratios for each interquartile range increase in L50 nighttime noise (3.67 dBA) and L50 daytime noise (4.35 dBA), respectively, were 1.04 (95% CI: 1.02, 1.06) and 1.04 (95% CI: 1.02, 1.07). Associations for total energy-equivalent noise level (Leq) measures were stronger than for the anthropogenic statistical L50 noise measures. Similar associations were observed for CHD and stroke. Interaction analyses suggested that associations of L50 nighttime and L50 daytime noise with CVD did not differ by prespecified effect modifiers. We found no evidence that inadequate sleep (<5 h/night) mediated associations of L50 nighttime noise and CVD. DISCUSSION: Outdoor L50 anthropogenic nighttime and daytime noise at the residential address was associated with a small increase in CVD risk in a cohort of adult female nurses. https://doi.org/10.1289/EHP12906.

Exposure to Particulate Matter Air Pollution and Age of Menarche in a Nationwide Cohort of U.S. Girls.

BACKGROUND: It remains unclear whether in utero and childhood exposure to air pollution affects pubertal development, particularly age of menarche in girls. OBJECTIVE: The aim of this study was to determine whether residential ambient particulate matter (PM) exposure in utero and during childhood is associated with age of menarche. METHODS: We studied 5,201 girls in the Growing Up Today Study 2 (2004-present) who were 10-17 y of age at enrollment (47.7% premenarchal; 52.3% postmenarchal). Exposure to three size fractions of PM [fine PM with aerodynamic diameter ≤2.5µm (PM2.5), PM with aerodynamic diameters between 2.5µm and 10µm (PM2.5-10), and PM with aerodynamic diameter 10µm (PM10)] was assigned based on maternal residential address, updated every 2 y, using nationwide spatiotemporal models. We estimated average PM exposure in utero, and time-varying windows: annual average exposure in the prior 1 and 2 y and cumulative average from birth. Age of menarche was self-reported on three surveys administered in 2004, 2006, and 2008. We calculated hazard ratios (HR) for menarche for an interquartile range (IQR) increase in PM exposure using Cox proportional hazard models adjusting for potential confounders. RESULTS: Girls attained menarche at 12.3 y of age on average. In the adjusted model, higher residential exposure to ambient PM2.5 during all time windows was associated with earlier age of menarche. The HRs of menarche for each IQR (4 µg/m3) increase in exposure to PM2.5 during the in utero period, 1 y prior to menarche, and throughout childhood were 1.03 [95% confidence interval (CI): 1.00, 1.06], 1.06 (95% CI: 1.02, 1.10) and 1.06 (95% CI: 1.02, 1.10), respectively. Effect estimates for PM10 exposure were similar, albeit attenuated, for all time windows. PM2.5-10 exposure was not associated with age of menarche. DISCUSSION: Among a large, nationwide, prospective cohort of U.S. girls, higher exposure to PM2.5 and PM10 in utero and throughout childhood was associated with an earlier age of menarche. Our results suggest that PM2.5 and PM10 may have endocrine-disrupting properties that could lead to altered timing of menarche. https://doi.org/10.1289/EHP12110.