Short-Term PM2.5 Exposure and DNA Methylation Changes of Circadian Rhythm Genes: Evidence from Two Experimental Studies.

The circadian rhythm regulates many crucial physiological processes, impacting human aging and aging-related outcomes. Observational evidence links circadian rhythm disturbance to PM2.5 exposure, yet the underlying DNA methylation mechanisms remain unclear due to limited PM2.5-dominated experimental settings. Therefore, we investigated the associations between short-term PM2.5 exposure and DNA methylation changes of 1188 CpG candidates across circadian genes among 32 young adults in the FDU study, with the validation in 26 individuals from the PKU study. Further mediation analyses tested whether DNA methylation of circadian genes could mediate the influence of PM2.5 on aging measured by three epigenetic ages: DNAmGrimAge, DunedinPoAm, and the mortality risk score. We identified three CpG sites associated with personal PM2.5 exposure: cg01248361 (CSNK2A2), cg17728065 (RORA), and cg22513396 (PRKAG2). Acute effects of PM2.5 on the three loci could be mediated by several circulating biomarkers, including MDA and EGF, with up to ∼30% of mediated proportions. Three loci further showed varying potentials in mediating the aging acceleration effect of PM2.5. Locus cg17728065 is the key site exhibiting a robust mediating effect (7.54-12.52%) on PM2.5-induced aging acceleration. Our findings demonstrated that PM2.5, even short-term peaks, could leave imprints on human aging via inducing aberrant temporal fluctuation in circadian homeostasis captured by DNA methylation profiles.

Projection of Mortality Burden Attributable to Nonoptimum Temperature with High Spatial Resolution in China.

The updated climate models provide projections at a fine scale, allowing us to estimate health risks due to future warming after accounting for spatial heterogeneity. Here, we utilized an ensemble of high-resolution (25 km) climate simulations and nationwide mortality data from 306 Chinese cities to estimate death anomalies attributable to future warming. Historical estimation (1986-2014) reveals that about 15.5% [95% empirical confidence interval (eCI):13.1%, 17.6%] of deaths are attributable to nonoptimal temperature, of which heat and cold corresponded to attributable fractions of 4.1% (eCI:2.4%, 5.5%) and 11.4% (eCI:10.7%, 12.1%), respectively. Under three climate scenarios (SSP126, SSP245, and SSP585), the national average temperature was projected to increase by 1.45, 2.57, and 4.98 °C by the 2090s, respectively. The corresponding mortality fractions attributable to heat would be 6.5% (eCI:5.2%, 7.7%), 7.9% (eCI:6.3%, 9.4%), and 11.4% (eCI:9.2%, 13.3%). More than half of the attributable deaths due to future warming would occur in north China and cardiovascular mortality would increase more drastically than respiratory mortality. Our study shows that the increased heat-attributable mortality burden would outweigh the decreased cold-attributable burden even under a moderate climate change scenario across China. The results are helpful for national or local policymakers to better address the challenges of future warming.

Early-Life Exposure to PM2.5 and Sleep Disturbances in Preschoolers from 551 Cities of China.

Rationale: Air pollution has been linked with sleep disturbance in adults, but the association in children remains unclear. Objectives: To examine the associations of prenatal and postnatal exposure to fine particulate matter (particulate matter ⩽2.5 µm in aerodynamic diameter; PM2.5) with sleep quality and sleep disturbances among children in 551 Chinese cities. Methods: A total of 1,15,023 children aged 3-7 years from the Chinese National Cohort of Motor Development were included. Sleep quality was measured using the Children's Sleep Habits Questionnaire (CSHQ). PM2.5 exposure was estimated using a satellite-based model. Generalized additive mixed models with Gaussian and binomial distributions were used to examine the associations of PM2.5 exposure with CSHQ scores and risk of sleep disturbance, respectively, adjusting for demographic characteristics and temporal trends. Measurements and Main Results: Early-life PM2.5 exposure was associated with higher total CSHQ score, and the association was stronger for exposure at age 0-3 years (change of CSHQ score per interquartile range increase of PM2.5 = 0.46; 95% confidence interval [CI], 0.29-0.63) than during pregnancy (0.22; 95% CI, 0.12-0.32). The associations were more evident in sleep-disordered breathing and daytime sleepiness. Postnatal PM2.5 exposure was associated with increased risk of sleep disturbance (adjusted odds ratio for per-interquartile range increase of PM2.5 exposure at age 0-3 years, 1.10; 95% CI, 1.04-1.15), but no associations were found for prenatal exposure. Children who were exclusively breastfed for <6 months and had neonatal ICU admission may be more vulnerable to sleep disturbance related to PM2.5 exposure. Conclusions: PM2.5 exposure can impair sleep quality in preschool children.

Hourly Air Pollutants and Acute Coronary Syndrome Onset in 1.29 Million Patients.

BACKGROUND: Short-term exposure to ambient air pollution has been linked with daily hospitalization and mortality from acute coronary syndrome (ACS); however, the associations of subdaily (hourly) levels of criteria air pollutants with the onset of ACS and its subtypes have rarely been evaluated. METHODS: We conducted a time-stratified case-crossover study among 1 292 880 patients with ACS from 2239 hospitals in 318 Chinese cities between January 1, 2015, and September 30, 2020. Hourly concentrations of fine particulate matter (PM2.5), coarse particulate matter (PM2.5-10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) were collected. Hourly onset data of ACS and its subtypes, including ST-segment-elevation myocardial infarction, non-ST-segment-elevation myocardial infarction, and unstable angina, were also obtained. Conditional logistic regressions combined with polynomial distributed lag models were applied. RESULTS: Acute exposures to PM2.5, NO2, SO2, and CO were each associated with the onset of ACS and its subtypes. These associations were strongest in the concurrent hour of exposure and were attenuated thereafter, with the weakest effects observed after 15 to 29 hours. There were no apparent thresholds in the concentration-response curves. An interquartile range increase in concentrations of PM2.5 (36.0 µg/m3), NO2 (29.0 µg/m3), SO2 (9.0 µg/m3), and CO (0.6 mg/m3) over the 0 to 24 hours before onset was significantly associated with 1.32%, 3.89%, 0.67%, and 1.55% higher risks of ACS onset, respectively. For a given pollutant, the associations were comparable in magnitude across different subtypes of ACS. NO2 showed the strongest associations with all 3 subtypes, followed by PM2.5, CO, and SO2. Greater magnitude of associations was observed among patients older than 65 years and in the cold season. Null associations of exposure to either PM2.5-10 or O3 with ACS onset were observed. CONCLUSIONS: The results suggest that transient exposure to the air pollutants PM2.5, NO2, SO2, or CO, but not PM2.5-10 or O3, may trigger the onset of ACS, even at concentrations below the World Health Organization air quality guidelines.

Environmental Exposures and Anti-Müllerian Hormone: A Mixture Analysis in the Nurses' Health Study II.

BACKGROUND: Previous studies have linked environmental exposures with anti-Müllerian hormone (AMH), a marker of ovarian reserve. However, associations with multiple environment factors has to our knowledge not been addressed. METHODS: We included a total of 2,447 premenopausal women in the Nurses' Health Study II (NHSII) who provided blood samples during 1996-1999. We selected environmental exposures linked previously with reproductive outcomes that had measurement data available in NHSII, including greenness, particulate matter, noise, outdoor light at night, ultraviolet radiation, and six hazardous air pollutants (1,3-butadiene, benzene, diesel particulate matter, formaldehyde, methylene chloride, and tetrachloroethylene). For these, we calculated cumulative averages from enrollment (1989) to blood draw and estimated associations with AMH in adjusted single-exposure models, principal component analysis (PCA), and hierarchical Bayesian kernel machine regression (BKMR). RESULTS: Single-exposure models showed negative associations of AMH with benzene (percentage reduction in AMH per interquartile range [IQR] increase = 5.5%, 95% confidence interval [CI] = 1.0, 9.8) and formaldehyde (6.1%, 95% CI = 1.6, 10). PCA identified four major exposure patterns but only one with high exposure to air pollutants and light at night was associated with lower AMH. Hierarchical BKMR pointed to benzene, formaldehyde, and greenness and suggested an inverse joint association with AMH (percentage reduction comparing all exposures at the 75th percentile to median = 8.2%, 95% CI = 0.7, 15.1). Observed associations were mainly among women above age 40. CONCLUSIONS: We found exposure to benzene and formaldehyde to be consistently associated with lower AMH levels. The associations among older women are consistent with the hypothesis that environmental exposures accelerate reproductive aging.

Abnormal uterine bleeding patterns determined through menstrual tracking among participants in the Apple Women's Health Study.

BACKGROUND: Use of menstrual tracking data to understand abnormal bleeding patterns has been limited because of lack of incorporation of key demographic and health characteristics and confirmation of menstrual tracking accuracy. OBJECTIVE: This study aimed to identify abnormal uterine bleeding patterns and their prevalence and confirm existing and expected associations between abnormal uterine bleeding patterns, demographics, and medical conditions. STUDY DESIGN: Apple Women's Health Study participants from November 2019 through July 2021 who contributed menstrual tracking data and did not report pregnancy, lactation, use of hormones, or menopause were included in the analysis. Four abnormal uterine bleeding patterns were evaluated: irregular menses, infrequent menses, prolonged menses, and irregular intermenstrual bleeding (spotting). Monthly tracking confirmation using survey responses was used to exclude inaccurate or incomplete digital records. We investigated the prevalence of abnormal uterine bleeding stratified by demographic characteristics and used logistic regression to evaluate the relationship of abnormal uterine bleeding to a number of self-reported medical conditions. RESULTS: There were 18,875 participants who met inclusion criteria, with a mean age of 33 (standard deviation, 8.2) years, mean body mass index of 29.3 (standard deviation, 8.0), and with 68.9% (95% confidence interval, 68.2-69.5) identifying as White, non-Hispanic. Abnormal uterine bleeding was found in 16.4% of participants (n=3103; 95% confidence interval, 15.9-17.0) after accurate tracking was confirmed; 2.9% had irregular menses (95% confidence interval, 2.7-3.1), 8.4% had infrequent menses (95% confidence interval, 8.0-8.8), 2.3% had prolonged menses (95% confidence interval, 2.1-2.5), and 6.1% had spotting (95% confidence interval, 5.7-6.4). Black participants had 33% higher prevalence (prevalence ratio, 1.33; 95% confidence interval, 1.09-1.61) of infrequent menses compared with White, non-Hispanic participants after controlling for age and body mass index. The prevalence of infrequent menses was increased in class 1, 2, and 3 obesity (class 1: body mass index, 30-34.9; prevalence ratio, 1.31; 95% confidence interval, 1.13-1.52; class 2: body mass index, 35-39.9; prevalence ratio, 1.25; 95% confidence interval, 1.05-1.49; class 3: body mass index, >40; prevalence ratio, 1.51; 95% confidence interval, 1.21-1.88) after controlling for age and race/ethnicity. Those with class 3 obesity had 18% higher prevalence of abnormal uterine bleeding compared with healthy-weight participants (prevalence ratio, 1.18; 95% confidence interval, 1.02-1.38). Participants with polycystic ovary syndrome had 19% higher prevalence of abnormal uterine bleeding compared with participants without this condition (prevalence ratio, 1.19; 95% confidence interval, 1.08-1.31). Participants with hyperthyroidism (prevalence ratio, 1.34; 95% confidence interval, 1.13-1.59) and hypothyroidism (prevalence ratio, 1.17; 95% confidence interval, 1.05-1.31) had a higher prevalence of abnormal uterine bleeding, as did those reporting endometriosis (prevalence ratio, 1.28; 95% confidence interval, 1.12-1.45), cervical dysplasia (prevalence ratio, 1.20; 95% confidence interval, 1.03-1.39), and fibroids (prevalence ratio, 1.14; 95% confidence interval, 1.00-1.30). CONCLUSION: In this cohort, abnormal uterine bleeding was present in 16.4% of those with confirmed menstrual tracking. Black or obese participants had increased prevalence of abnormal uterine bleeding. Participants reporting conditions such as polycystic ovary syndrome, thyroid disease, endometriosis, and cervical dysplasia had a higher prevalence of abnormal uterine bleeding.

Hourly air pollution exposure and the onset of symptomatic arrhythmia: an individual-level case-crossover study in 322 Chinese cities.

BACKGROUND: Few studies have explored the relationship between air pollution and arrhythmia onset at the hourly level. We aimed to examine the association of exposure to air pollution with the onset of acute symptomatic arrhythmia at an hourly level. METHODS: We conducted a nationwide, time-stratified, case-crossover study in China between 2015 and 2021. We obtained hourly information on the onset of symptomatic arrhythmia (including atrial fibrillation, atrial flutter, atrial and ventricular premature beats and supraventricular tachycardia) from the Chinese Cardiovascular Association Database - Chest Pain Center (including 2025 certified hospitals in 322 cities). We obtained data on hourly concentrations of 6 air pollutants from the nearest monitors, including fine particles (PM2.5), coarse particles (PM2.5-10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone. For each patient, we matched the case period to 3 or 4 control periods during the same hour, day of week, month and year. We used conditional logistic regression models to analyze the data. RESULTS: We included a total of 190 115 patients with acute onset of symptomatic arrhythmia. Air pollution was associated with increased risk of onset of symptomatic arrhythmia within the first few hours of exposure; this risk attenuated substantially after 24 hours. An interquartile range increase in PM2.5, NO2, SO2 and CO in the first 24 hours after exposure (i.e., lag period 0-24 h) was associated with significantly higher odds of atrial fibrillation (1.7%-3.4%), atrial flutter (8.1%-11.4%) and supraventricular tachycardia (3.4%-8.9%). Exposure to PM2.5-10 was associated with significantly higher odds of atrial flutter (8.7%) and supraventricular tachycardia (5.4%), and exposure to ozone was associated with higher odds of supraventricular tachycardia (3.4%). The exposure-response relationships were approximately linear, without discernible concentration thresholds. INTERPRETATION: Exposure to air pollution was associated with the onset of symptomatic arrhythmia shortly after exposure. This finding highlights the importance of further reducing air pollution and taking prompt protective measures for susceptible populations during periods of elevated levels of air pollutants.

Associations between air pollution, residential greenness, and glycated hemoglobin (HbA1c) in three prospective cohorts of U.S. adults.

BACKGROUND: While studies suggest impacts of individual environmental exposures on type 2 diabetes (T2D) risk, mechanisms remain poorly characterized. Glycated hemoglobin (HbA1c) is a biomarker of glycemia and diagnostic criterion for prediabetes and T2D. We explored associations between multiple environmental exposures and HbA1c in non-diabetic adults. METHODS: HbA1c was assessed once in 12,315 women and men in three U.S.-based prospective cohorts: the Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-up Study (HPFS). Residential greenness within 270 m and 1,230 m (normalized difference vegetation index, NDVI) was obtained from Landsat. Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated from nationwide spatiotemporal models. Three-month and one-year averages prior to blood draw were assigned to participants' addresses. We assessed associations between single exposure, multi-exposure, and component scores from Principal Components Analysis (PCA) and HbA1c. Fully-adjusted models built on basic models of age and year at blood draw, BMI, alcohol use, and neighborhood socioeconomic status (nSES) to include diet quality, race, family history, smoking status, postmenopausal hormone use, population density, and season. We assessed interactions between environmental exposures, and effect modification by population density, nSES, and sex. RESULTS: Based on HbA1c, 19% of participants had prediabetes. In single exposure fully-adjusted models, an IQR (0.14) higher 1-year 1,230 m NDVI was associated with a 0.27% (95% CI: 0.05%, 0.49%) lower HbA1c. In basic component score models, a SD increase in Component 1 (high loadings for 1-year NDVI) was associated with a 0.19% (95% CI: 0.04%, 0.34%) lower HbA1c. CI's crossed the null in multi-exposure and fully-adjusted component score models. There was little evidence of associations between air pollution and HbA1c, and no evidence of effect modification. CONCLUSIONS: Among non-diabetic adults, environmental exposures were not consistently associated with HbA1c. More work is needed to elucidate biological pathways between the environment and prediabetes.

Evaluation of Menstrual Cycle Tracking Behaviors in the Ovulation and Menstruation Health Pilot Study: Cross-Sectional Study.

BACKGROUND: Menstrual cycle tracking apps (MCTAs) have potential in epidemiological studies of women's health, facilitating real-time tracking of bleeding days and menstrual-associated signs and symptoms. However, information regarding the characteristics of MCTA users versus cycle nontrackers is limited, which may inform generalizability. OBJECTIVE: We compared characteristics among individuals using MCTAs (app users), individuals who do not track their cycles (nontrackers), and those who used other forms of menstrual tracking (other trackers). METHODS: The Ovulation and Menstruation Health Pilot Study tested the feasibility of a digitally enabled evaluation of menstrual health. Recruitment occurred between September 2017 and March 2018. Menstrual cycle tracking behavior, demographic, and general and reproductive health history data were collected from eligible individuals (females aged 18-45 years, comfortable communicating in English). Menstrual cycle tracking behavior was categorized in 3 ways: menstrual cycle tracking via app usage, that via other methods, and nontracking. Demographic factors, health conditions, and menstrual cycle characteristics were compared across the menstrual tracking method (app users vs nontrackers, app users vs other trackers, and other trackers vs nontrackers) were assessed using chi-square or Fisher exact tests. RESULTS: In total, 263 participants met the eligibility criteria and completed the digital survey. Most of the cohort (n=191, 72.6%) was 18-29 years old, predominantly White (n=170, 64.6%), had attained 4 years of college education or higher (n= 209, 79.5%), and had a household income below US $50,000 (n=123, 46.8%). Among all participants, 103 (39%) were MCTA users (app users), 97 (37%) did not engage in any tracking (nontrackers), and 63 (24%) used other forms of tracking (other trackers). Across all groups, no meaningful differences existed in race and ethnicity, household income, and education level. The proportion of ever-use of hormonal contraceptives was lower (n=74, 71.8% vs n=87, 90%, P=.001), lifetime smoking status was lower (n=6, 6% vs n=15, 17%, P=.04), and diagnosis rate of gastrointestinal reflux disease (GERD) was higher (n=25, 24.3% vs n=12, 12.4%, P=.04) in app users than in nontrackers. The proportions of hormonal contraceptives ever used and lifetime smoking status were both lower (n=74, 71.8% vs n=56, 88.9%, P=.01; n=6, 6% vs n=11, 17.5%, P=.02) in app users than in other trackers. Other trackers had lower proportions of ever-use of hormonal contraceptives (n=130, 78.3% vs n=87, 89.7%, P=.02) and higher diagnostic rates of heartburn or GERD (n=39, 23.5% vs n=12, 12.4%, P.03) and anxiety or panic disorder (n=64, 38.6% vs n=25, 25.8%, P=.04) than nontrackers. Menstrual cycle characteristics did not differ across all groups. CONCLUSIONS: Our results suggest that app users, other trackers, and nontrackers are largely comparable in demographic and menstrual cycle characteristics. Future studies should determine reasons for tracking and tracking-related behaviors to further understand whether individuals who use MCTAs are comparable to nontrackers.

Low ambient temperature and temperature drop between neighbouring days and acute aortic dissection: a case-crossover study.

AIMS: The incidence of acute aortic dissection (AAD) has been shown to have seasonal variation, but whether this variation can be explained by non-optimum ambient temperature and temperature change between neighbouring days (TCN) is not clear. METHODS AND RESULTS: We performed a time-stratified case-crossover study in the Registry of Aortic Dissection in China covering 14 tertiary hospitals in 11 cities from 2009 to 2019. A total of 8182 cases of AAD were included. Weather data at residential address were matched from nearby monitoring stations. Conditional logistic regression model and distributed lag nonlinear model were used to estimate the associations of daily temperature and TCN with AAD, adjusting for possible confounders. We observed an increase of AAD risk with lower temperature cumulated over lag 0-1 day and this association became statistically significant when daily mean temperature was below 24°C. Relative to the referent temperature (28°C), the odds ratios (ORs) of AAD onset at extremely low (-10°C) and low (1°C) temperature cumulated over lag 0-1 day were 2.84 [95% confidence interval (CI): 1.69, 4.75] and 2.36 (95% CI: 1.61, 3.47), respectively. A negative TCN was associated with increased risk of AAD. The OR of AAD cumulated over lag 0-6 days was 2.66 (95% CI: 1.76, 4.02) comparing the extremely negative TCN (-7°C) to no temperature change. In contrast, a positive TCN was associated with reduced AAD risk. CONCLUSION: This study provides novel and robust evidence that low ambient temperature and temperature drop between neighbouring days were associated with increased risk of AAD onset. KEY QUESTION: Incidence of acute aortic dissection (AAD) was reported to have seasonal trends, but it remains unclear whether non-optimum ambient temperature and temperature change between neighbouring days (TCN) is associated with AAD onset. KEY FINDING: Daily mean temperature lower than 24°C was significantly associated with increased risk of AAD at lag 0-1 day. A negative TCN (temperature drop) was associated with increased risk of AAD, whereas a positive TCN was associated with decreased risk. TAKE HOME MESSAGE: This multi-centre, case-crossover study provides novel and robust evidence that low ambient temperature and temperature drop between neighbouring days were associated with increased AAD risk.

Design and methods of the Apple Women's Health Study: a digital longitudinal cohort study.

BACKGROUND: Prospective longitudinal cohorts assessing women's health and gynecologic conditions have historically been limited. OBJECTIVE: The Apple Women's Health Study was designed to gain a deeper understanding of the relationship among menstrual cycles, health, and behavior. This paper describes the design and methods of the ongoing Apple Women's Health Study and provides the demographic characteristics of the first 10,000 participants. STUDY DESIGN: This was a mobile-application-based longitudinal cohort study involving survey and sensor-based data. We collected the data from 10,000 participants who responded to the demographics survey on enrollment between November 14, 2019 and May 20, 2020. The participants were asked to complete a monthly follow-up through November 2020. The eligibility included installed Apple Research app on their iPhone with iOS version 13.2 or later, were living in the United States, being of age greater than 18 years (19 in Alabama and Nebraska, 21 years old in Puerto Rico), were comfortable in communicating in written and spoken English, were the sole user of an iCloud account or iPhone, and were willing to provide consent to participate in the study. RESULTS: The mean age at enrollment was 33.6 years old (±standard deviation, 10.3). The race and ethnicity was representative of the US population (69% White and Non-Hispanic [6910/10,000]), whereas 51% (5089/10,000) had a college education or above. The participant geographic distribution included all the US states and Puerto Rico. Seventy-two percent (7223/10,000) reported the use of an Apple Watch, and 24.4% (2438/10,000) consented to sensor-based data collection. For this cohort, 38% (3490/9238) did not respond to the Monthly Survey: Menstrual Update after enrollment. At the 6-month follow-up, there was a 35% (3099/8972) response rate to the Monthly Survey: Menstrual Update. 82.7% (8266/10,000) of the initial cohort and 95.1% (2948/3099) of the participants who responded to month 6 of the Monthly Survey: Menstrual Update tracked at least 1 menstrual cycle via HealthKit. The participants tracked their menstrual bleeding days for an average of 4.44 (25%-75%; range, 3-6) calendar months during the study period. Non-White participants were slightly more likely to drop out than White participants; those remaining at 6 months were otherwise similar in demographic characteristics to the original enrollment group. CONCLUSION: The first 10,000 participants of the Apple Women's Health Study were recruited via the Research app and were diverse in race and ethnicity, educational attainment, and economic status, despite all using an Apple iPhone. Future studies within this cohort incorporating this high-dimensional data may facilitate discovery in women's health in exposure outcome relationships and population-level trends among iPhone users. Retention efforts centered around education, communication, and engagement will be utilized to improve the survey response rates, such as the study update feature.

Ultraviolet radiation and age at natural menopause in a nationwide, prospective US cohort.

BACKGROUND: Solar ultraviolet radiation (UV) is a critical environmental factor for dermal conversion of vitamin D, which is suggested to support reproductive health. However, current epidemiological studies have reported conflicting results on the associations between vitamin D levels and ovarian reserve. Further, few studies have considered UV exposure and reproductive aging, which is closely related to declined ovarian reserve. OBJECTIVES: We sought to examine the associations of long-term UV exposure and age at natural menopause in a large, nationwide, prospective cohort. METHODS: Participants in the Nurses' Health Study II (NHS II) who were premenopausal at age 40 were included and followed through 2015. Erythemal UV radiation from a high-resolution geospatial model was linked to the participants' residential histories. Early-life UV was estimated using the reported state of residence at birth, age 15, and age 30. We used time-varying Cox proportional hazards models to estimate the hazard ratio (HR) and 95% confidence intervals (CIs) for natural menopause, adjusting for potential confounders and predictors of menopause. RESULTS: A total of 63,801 women reported natural menopause across the 1,051,185 person-years of follow-up among 105,631 eligible participants. We found very modest associations with delayed menopause for long-term UV exposure (adjusted HR comparing highest to lowest quartile of cumulative average UV: 0.96, 95% CI: 0.94, 0.99). There was a suggestive inverse association between UV at age 30 with menopause (adjusted HR comparing highest to lowest quartile: 0.97, 95% CI: 0.95, 1.00) but not with UV at birth and age 15. CONCLUSIONS: Solar UV exposure in adulthood was modestly associated with later onset of menopause. Although consistent with previous findings on vitamin D intake and menopause in the same population, these weak associations found in this study may not be of clinical relevance.

Associations of PM2.5 exposure with blood glucose impairment in early pregnancy and gestational diabetes mellitus.

Exposure to fine particulate matter (PM2.5) during pregnancy has been linked to the risk of gestational diabetes mellitus (GDM), while conclusions are inconsistent. In this study we aimed to estimate the effects of prenatal PM2.5 exposure with blood glucose in early pregnancy and the GDM risk. Participants were recruited from the SH-IPMCH-BTH cohort (n = 41,929), a study of air pollution and birth outcome. All participants provided serum samples for analyses of fasting blood glucose (FBG) and HbA1c during early pregnancy. GDM was diagnosed using an oral glucose tolerance test (OGTT) with the time interval of 1 h. Prenatal exposure to PM2.5 was estimated using gap-filled satellite exposure assessments in Shanghai, China. Both FBG and HbA1c levels were significantly and positively associated with PM2.5 exposure during early pregnancy. A 10 µg/m3 increase of PM2.5 exposure from early to middle pregnancy was associated with the risk of GDM (first trimester OR=1.09, 95% CI: 1.02, 1.16; second trimester OR=1.09, 95% CI: 1.03, 1.16; first two trimester OR=1.15, 95%CI: 1.04, 1.28). The combined effects were greater among elevated FBG and HbA1c women with higher PM2.5 exposure in middle trimester (P for interaction=0.037 and 0.001, respectively). This study found that exposure to PM2.5 exposure in the 1st and 2nd trimesters was related to GDM. FBG and HbA1c played roles in the relationship between PM2.5 exposure in the 2nd trimester and GDM.

The acute effects of temperature variability on heart rate variability: A repeated-measure study.

BACKGROUND: The impacts of temperature variability on cardiac autonomic function remain unclear. OBJECTIVE: To explore the short-term associations between daily temperature variability and parameters of heart rate variability (HRV). METHODS: This is a repeated-measure study among 78 eligible participants in Shanghai, China. We defined temperature variability as diurnal temperature range (DTR), the standard-deviation of temperature (SDT) and temperature variability (TV). We evaluated 3 frequency-domain HRV parameters (VLF, LF and HF) and 4 time-domain parameters (SDNN, SDANN, rMSSD and pNN50). We used linear mixed-effect models to analyze the data after controlling for environmental and individual confounders. RESULTS: Temperature variability was significantly associated with decreased HRV, especially on the concurrent day. The exposure-response relationships were almost inversely linear for most parameters. Every one interquartile range (IQR) increase of DTR was associated with a decrease of 3.92% for VLF, 6.99% for LF, 5.88% for HF, 3.94% for rMSSD and 1.30% for pNN50. Each IQR increase of SDT was associated with a decline of 6.48% for LF, 5.91% for HF, 4.26% for rMSSD and 1.87% for pNN50. Every IQR increase of SDT was associated with a decrease of 4.39% for VLF, 7.67% for LF, 6.52% for HF, 3.22% for SDNN, 2.98% for SDANN, 4.05% for rMSSD, and 1.41% for pNN50. The decrements in HRV associated with temperature variability were more prominent in females. CONCLUSION: Temperature variability on the concurrent day could significantly decrease cardiac autonomic function, especially in females.

Particulate matter air pollution and reduced heart rate variability: How the associations vary by particle size in Shanghai, China.

BACKGROUND: It remains unclear which size of particles has the strongest effects on heart rate variability (HRV). OBJECTIVE: To explore the association between HRV parameters and daily variations of size-fractionated particle number concentrations (PNCs). METHODS: We conducted a longitudinal repeated-measure study among 78 participants with a 24-h continuous ambulatory Holter electrocardiographic recorder in Shanghai, China, from January 2015 to June 2019. Linear mixed-effects models were employed to evaluate the changes of HRV parameters associated with PNCs of 7 size ranges from 0.01 to 10 µm after controlling for environmental and individual confounders. RESULTS: On the concurrent day, decreased HRV parameters were associated with increased PNCs of 0.01-0.3 µm, and smaller particles showed greater effects. For an interquartile range increase in ultrafine particles (UFP, those < 0.1 µm, 2453 particles/cm3), the declines in very-low-frequency power, low-frequency power, high-frequency power, standard deviation of normal R-R intervals, root mean square of the successive differences between R-R intervals and percentage of adjacent normal R-R intervals with a difference ≥ 50 ms were 5.06% [95% confidence interval (CI): 2.09%, 7.94%], 7.65% (95%CI: 2.73%, 12.32%), 9.49% (95%CI: 4.64%, 14.09%), 5.10% (95%CI: 2.21%, 7.91%), 8.09% (95%CI: 4.39%, 11.65%) and 24.98% (95%CI: 14.70%, 34.02%), respectively. These results were robust to the adjustment of criteria air pollutants, temperature at different lags, and the status of heart medication. CONCLUSIONS: Particles less than 0.3 µm (especially UFP) may dominate the acute effects of particulate air pollution on cardiac autonomic dysfunction.

Application of land use regression to assess exposure and identify potential sources in PM2.5, BC, NO2 concentrations.

BACKGROUND: Understanding spatial variation of air pollution is critical for public health assessments. Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations. However, they have limited application in China due to the lack of spatially resolved data. OBJECTIVE: Based on purpose-designed monitoring networks, this study developed LUR models to predict fine particulate matter (PM2.5), black carbon (BC) and nitrogen dioxide (NO2) exposure and to identify their potential outdoor-origin sources within an urban/rural region, using Taizhou, China as a case study. METHOD: Two one-week integrated samples were collected at 30 PM2.5 (BC) sites and 45 NO2 sites in each two distinct seasons. Samples of 1/3 of the sites were collected simultaneously. Annual adjusted average was calculated and regressed against pre-selected GIS-derived predictor variables in a multivariate regression model. RESULTS: LUR explained 65% of the spatial variability in PM2.5, 78% in BC and 73% in NO2. Mean (±Standard Deviation) of predicted PM2.5, BC and NO2 exposure levels were 48.3 (±6.3) µg/m3, 7.5 (±1.4) µg/m3 and 27.3 (±8.2) µg/m3, respectively. Weak spatial corrections (Pearson r = 0.05-0.25) among three pollutants were observed, indicating the presence of different sources. Regression results showed that PM2.5, BC and NO2 levels were positively associated with traffic variables. The former two also increased with farm land use; and higher NO2 levels were associated with larger industrial land use. The three pollutants were correlated with sources at a scale of ≤5 km and even smaller scales (100-700m) were found for BC and NO2. CONCLUSION: We concluded that based on a purpose-designed monitoring network, LUR model can be applied to predict PM2.5, NO2 and BC concentrations in urban/rural settings of China. Our findings highlighted important contributors to within-city heterogeneity in outdoor-generated exposure, and indicated traffic, industry and agriculture may significantly contribute to PM2.5, NO2 and BC concentrations.

Particulate Matter Exposure and Stress Hormone Levels: A Randomized, Double-Blind, Crossover Trial of Air Purification.

BACKGROUND: Exposure to ambient particulate matter (PM) is associated with a number of adverse health outcomes, but potential mechanisms are largely unknown. Metabolomics represents a powerful approach to study global metabolic changes in response to environmental exposures. We therefore conducted this study to investigate changes in serum metabolites in response to the reduction of PM exposure among healthy college students. METHODS: We conducted a randomized, double-blind crossover trial in 55 healthy college students in Shanghai, China. Real and sham air purifiers were placed in participants' dormitories in random order for 9 days with a 12-day washout period. Serum metabolites were quantified by using gas chromatography-mass spectrometry and ultrahigh performance liquid chromatography-mass spectrometry. Between-treatment differences in metabolites were examined using orthogonal partial least square-discriminant analysis and mixed-effect models. Secondary outcomes include blood pressure, corticotropin-releasing hormone, adrenocorticotropic hormone, insulin resistance, and biomarkers of oxidative stress and inflammation. RESULTS: The average personal exposure to PMs with aerodynamic diameters ≤2.5 µm was 24.3 µg/m3 during the real purification and 53.1 µg/m3 during the sham purification. Metabolomics analysis showed that higher exposure to PMs with aerodynamic diameters ≤2.5 µm led to significant increases in cortisol, cortisone, epinephrine, and norepinephrine. Between-treatment differences were also observed for glucose, amino acids, fatty acids, and lipids. We found significantly higher blood pressure, hormones, insulin resistance, and biomarkers of oxidative stress and inflammation among individuals exposed to higher PMs with aerodynamic diameters ≤2.5 µm. CONCLUSIONS: This study suggests that higher PM may induce metabolic alterations that are consistent with activations of the hypothalamus-pituitary-adrenal and sympathetic-adrenal-medullary axes, adding potential mechanistic insights into the adverse health outcomes associated with PM. Furthermore, our study demonstrated short-term reductions in stress hormone following indoor air purification. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT02712333.

Possible Mediation by Methylation in Acute Inflammation Following Personal Exposure to Fine Particulate Air Pollution.

Air pollution may increase cardiovascular and respiratory risk through inflammatory pathways, but evidence for acute effects has been weak and indirect. Between December 2014 and July 2015, we enrolled 36 healthy, nonsmoking college students for a panel study in Shanghai, China, a city with highly variable levels of air pollution. We measured personal exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) continuously for 72 hours preceding each of 4 clinical visits that included phlebotomy. We measured 4 inflammation proteins and DNA methylation at nearby regulatory cytosine-phosphate-guanine (CpG) loci. We applied linear mixed-effect models to examine associations over various lag times. When results suggested mediation, we evaluated methylation as mediator. Increased PM2.5 concentration was positively associated with all 4 inflammation proteins and negatively associated with DNA methylation at regulatory loci for tumor necrosis factor alpha (TNF-α) and soluble intercellular adhesion molecule-1. A 10-µg/m3 increase in average PM2.5 during the 24 hours preceding blood draw corresponded to a 4.4% increase in TNF-α and a statistically significant decrease in methylation at one of the two studied candidate CpG loci for TNF-α. Epigenetics may play an important role in mediating effects of PM2.5 on inflammatory pathways.

Effects of Personal Short-Term Exposure to Ambient Ozone on Blood Pressure and Vascular Endothelial Function: A Mechanistic Study Based on DNA Methylation and Metabolomics.

Short-term exposure to ambient ozone is associated with adverse cardiovascular effects, with inconsistent evidence on the molecular mechanisms. We conducted a longitudinal panel study among 43 college students in Shanghai to explore the effects of personal ozone exposure on blood pressure (BP), vascular endothelial function, and the potential molecular mechanisms. We measured real-time personal ozone exposure levels, serum angiotensin-converting enzyme (ACE) and endothelin-1 (ET-1), and locus-specific DNA methylation of ACE and EDN1 (coding ET-1). We used an untargeted metabolomic approach to explore potentially important metabolites. We applied linear mixed-effect models to examine the effects of ozone on the above biomarkers. An increase in 2 h-average ozone exposure was significantly associated with elevated levels of BP, ACE, and ET-1. ACE and EDN1 methylation decreased with ozone exposure, but the magnitude differed by genomic loci. Metabolomics analysis showed significant changes in serum lipid metabolites following ozone exposure that are involved in maintaining vascular endothelial function. Our findings suggested that acute exposure to ambient ozone can elevate serum levels of ACE and ET-1, decrease their DNA methylation, and alter the lipid metabolism, which may be partly responsible for the effects of ozone on BP and vascular endothelial function.

Associations Between Air Quality Changes and Biomarkers of Systemic Inflammation During the 2014 Nanjing Youth Olympics: A Quasi-Experimental Study.

There is increasing interest in quasi-experimental research to evaluate whether actions taken to improve air quality will benefit public health. We conducted a quasi-experimental study to evaluate inflammatory response to changes in air quality during the 2014 Nanjing Youth Olympics in China. We repeatedly measured 8 biomarkers of systemic inflammation in 31 healthy adults and obtained hourly air pollutant concentrations from a nearby fixed-site monitoring station. We used linear mixed-effect models to examine the associations between air quality changes and blood biomarkers. Air pollutant concentrations decreased apparently during the Youth Olympics. Concomitantly, we observed significant decreases in levels of soluble cluster of differentiation 40 (CD40) ligand and interleukin 1ß (geometric means ratios were 0.45 and 0.24, respectively) from the pre-Olympic period to the intra-Olympic period. Afterwards, levels of C-reactive protein and vascular cell adhesion molecule 1 increased significantly (geometric means ratios were 2.22 and 1.29, respectively) in the post-Olympic period. Fine particulate matter and ozone were significantly associated with soluble CD40 ligand, P-selectin, interleukin 1ß, intercellular adhesion molecule 1, and vascular cell adhesion molecule 1. Other pollutants showed positive but nonsignificant associations. Our study indicated that reduced air pollution, especially fine particulate matter and ozone, during the 2014 Nanjing Youth Olympics was associated with alleviated systemic inflammation in healthy adults.