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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.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).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.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.

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 (PM 2.5 ), coarse particulate matter (PM 2.5–10 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), carbon monoxide (CO), and ozone (O 3 ) 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 PM 2.5 , NO 2 , SO 2 , 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 PM 2.5 (36.0 μg/m 3 ), NO 2 (29.0 µg/m 3 ), SO 2 (9.0 µg/m 3 ), and CO (0.6 mg/m 3 ) 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. NO 2 showed the strongest associations with all 3 subtypes, followed by PM 2.5 , CO, and SO 2 . Greater magnitude of associations was observed among patients older than 65 years and in the cold season. Null associations of exposure to either PM 2.5–10 or O 3 with ACS onset were observed. Conclusions: The results suggest that transient exposure to the air pollutants PM 2.5 , NO 2 , SO 2 , or CO, but not PM 2.5–10 or O 3 , may trigger the onset of ACS, even at concentrations below the World Health Organization air quality guidelines.

BackgroundMenstrual characteristics are important signs of women’s health. We examined the variation of menstrual cycle length by age, race and ethnicity, and body weight using data collected from mobile menstrual tracking apps. Understanding how menstrual characteristics vary by these factors can provide important information for further study of environmental and social determinants of menstrual health.MethodsWe collected self-tracked menstrual cycle data from participants of the Apple Women’s Health Study. Demographic and lifestyle characteristics were self-reported from surveys. Linear mixed effect (LME) models were used to estimate the differences in cycle length associated with age, race/ethnicity, and body mass index (BMI), adjusted for possible confounders or predictors of cycle length. Cycle variability was estimated by the change of within-individual standard deviations of cycle length.FindingsA total of 165,668 cycles from 12,608 participants from US were included. After adjusting for all covariates, mean menstrual cycle length was shorter with older age across all age groups until age 50 and then became longer for those age 50 and older. Menstrual cycles were on average 1·6 (95%CI: 1·2, 2·0) days longer for Asian and 0·7 (0·4, 1·0) days longer for Hispanic participants compared to White non-Hispanic participants. Participants with Class 3 obesity (BMI≥40 kg/m2) had 1·5 (1·2, 1·8) days longer cycles compared to those with healthy BMI (18·5≤BMI2). Cycle variability was smaller among participants in older age groups but became considerably larger for those in the oldest age categories (45-49 and 50+). Asian and Hispanic participants and those who were obese had larger cycle variability.InterpretationThis study demonstrated differences in menstrual characteristics by age, race and ethnicity, and obesity using data collected from mobile health apps. Future studies should explore the underlying determinants of the racial and ethnic differences in menstrual characteristics.FundingApple Inc.Research in contextEvidence before this studyWe searched PubMed for studies on menstrual cycles with age, body weight, and race/ethnicity using the term “((“Menstrual Cycle”[Mesh:NoExp] OR menstrual cycle*[tiab]) AND (“Time Factors”[Mesh] OR cycle length*[tiab] OR variability[tiab] OR variation*[tiab])) OR (“Menstruation”[Mesh] AND (“Time Factors”[Mesh] OR length[tiab] OR variability[tiab] OR variation*[tiab]) AND 1950[pdat]:1986[pdat]) AND (“Age Factors”[Mesh:NoExp] OR “Race Factors”[Mesh] OR “Racial Groups”[Mesh] OR “Ethnicity”[Mesh] OR “ethnology” [Subheading] OR “Body Mass Index”[Mesh] OR “Body Weight”[Mesh:NoExp] OR “Overweight”[Mesh] OR age[tiab] OR ages[tiab] OR race[tiab] OR races[tiab] OR racial[tiab] OR ethnic*[tiab] OR body mass[tiab] OR bmi[tiab] OR weight[tiab] OR overweight[tiab] OR obes*[tiab]) NOT (“Animals”[Mesh] NOT “Humans”[Mesh])” from 1950 to August 3, 2022. This search yielded 2,064 sources and we identified 30 research articles comparing menstrual cycle length and/or variability by age, race/ethnicity, and/or body weight in population. Another 14 research articles were added to the search results by knowledge of existing literature. Of the 44 articles identified, studies on changes of menstrual cycle length and variability with age reported consistent results, although the age range of the participants differed across these studies. In general, menstrual cycles were longer and less regular in the first few years following menarche, but over the subsequent decades cycles tend to become shorter and more regular with older age until age 40-45, after which they can become increasingly longer and irregular until menopause. Obesity was associated with menstrual irregularity. However, the association with menstrual cycle length was less consistently reported. Some studies found obesity was associated with longer menstrual cycles while other studies reported null associations. Compared to age and body weight, fewer studies have considered racial and ethnic differences of menstrual characteristics, although results from separate studies in Japan, China, and India suggested that females in these countries had longer cycle lengths compared to those observed in White females in US. Many of the prior studies of menstrual cycle characteristics relied on self-reported typical menstrual cycle length and regularity in survey questions, without acquiring actual menstrual cycle data. Most of those that used menstrual diaries to obtain cycle characteristics with higher accuracy were limited by relatively small numbers of participants. A few recent studies using menstrual tracking app data from a large number of users in different countries (mainly in Europe and North America) reported similar associations of age with cycle length and variability. However, results for body weight were still inconsistent. In addition, menstrual cycle characteristics by race and ethnicity have seldom been characterized using such data.Added value of this studyIn this large digital cohort study, we collected menstrual cycle data from menstrual tracking apps and factors related to menstruation from surveys to comprehensively compare the distribution of menstrual cycle length by age, race and ethnicity, and body mass index in a diverse US population. Using this dataset, our study results confirmed the non-linear changes of menstrual pattern with age throughout the reproductive lifespan as characterized in previous studies. More importantly, after controlling for potential confounders, we observed racial and ethnic differences of menstrual cycle length, in which participants who were Asian and who were Hispanic had longer menstrual cycles and higher variability. Obesity was associated with longer menstrual cycle length and higher cycle variability, especially among Hispanic individuals.Implications of all the available evidenceMenstrual cycle characteristics such as cycle length and variability/regularity have been recognized as important vital signs associated with gynecological conditions, fertility, cardiometabolic diseases, and mortality risk. Previous studies provided different estimates on menstrual parameters and current recommendations on normal menstrual cycle length and variability were based on limited quantitative evidence that was mainly generated in the White population. With the popularity of menstrual cycle tracking apps, our study demonstrated that this app-based data is a promising and powerful resource for research of menstrual health today. This study also provided valuable evidence on possible racial and ethnic disparities in menstrual cycle characteristics in a large free-living population. Future studies should consider the underlying environmental, social, and behavioral factors that drive the observed racial and ethnic differences of menstrual characteristics.

Air pollution has been linked with sleep disturbance in adults, but the association in children remains unclear.To examine the associations of prenatal and postnatal exposure to fine particulate matter (PM2.5) with sleep quality and sleep disturbances among children in 551 Chinese cities.A total of 115,023 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.Early life PM2.5 exposure was associated with higher total CSHQ score, and the association was stronger for exposure in age 0-3 years (change of CSHQ score per interquartile range increase of PM2.5=0.46, 95% CI: 0.29, 0.63) than during pregnancy (0.22, 95% CI: 0.12, 0.32). The associations were more evident on sleep-disordered breathing and daytime sleepiness. Postnatal PM2.5 exposure was associated with increased risk of sleep disturbance (adjusted odds ratios for per interquartile range increase of PM2.5 exposure in age 0-3=1.10, 95% CI: 1.04, 1.15), but no associations were found for prenatal exposure. Children who were breastfed for less than 6 months and had NICU admission may be more vulnerable to sleep disturbance related to PM2.5 exposure.PM2.5 exposure can impair sleep quality in preschool children.

BACKGROUND By allowing users to track their menstrual periods and the associated signs and symptoms, Menstrual Cycle Tracking Apps (MCTAs) may have potential in epidemiological studies of women’s health. However, there is limited information on the characteristics of MCTA users compared to both those who track their cycles in other ways and those who do not track their cycles. OBJECTIVE We sought to examine differences between individuals tracking their cycles through MCTAs (app-users), individuals tracking through means other than MCTAs (other-trackers), and non-trackers in the Ovulation and Menstruation Health Pilot Study survey METHODS Our study collected survey responses from 263 participants recruited from a gynecology clinic (n=36), a community fair (n=61), and the internet (n=166). We then compared differences in demographic/socioeconomic/lifestyle factors, health conditions, and menstrual cycle characteristics between MCTA users and non-app users and between women who tracked their cycles (with any forms of tracking) and those who did not. RESULTS Overall, participants were mostly white, had attained 4-years of college education or higher, and had a median annual household income between $50,000-$74,999. Among all participants, 103 were MCTA users (app-users), 62 used other forms of cycle tracking (i.e., paper, digital calendar, software, birth control, and memory) (other-trackers), and 95 did not engage in any form of tracking (non-trackers). No meaningful differences in race/ethnicity, household income, and education level between app-users and other-trackers and between other-trackers and non-trackers were found. Menstrual cycle characteristics, such as cycle length, frequencies of normal and abnormal cycles, time to cycle regularity, and age at menarche were also comparable between app-users and other-trackers and between other-trackers and non-trackers. For self-reported factors, other trackers compared to app-users were more likely to smoke (18% vs 6%), use hormonal birth control (89% vs 72%), and had a higher prevalence of endometriosis (5% vs 1%) but a lower prevalence of heartburn (17% vs 26 %). Other trackers had a higher proportion of cholesterol (14%v 7 %), diabetes (5% v 0 %), and anxiety disorder (41% v 27%) compared to non-trackers in this study. CONCLUSIONS Our results suggest that app-users and other-trackers and other-trackers and non-trackers are largely comparable in demographic factors, socioeconomic factors, and menstrual cycle characteristics. Non-trackers, however, may potentially have a slightly differing disease burden compared to MCTA users. Our findings strengthen the generalizability of epidemiological results drawn from studies utilizing MCTAs. Within studies using MCTA sourced data, the addition of survey questions or health data may further facilitate whether differences exist between MCTA sourced data and comparison populations

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.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.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.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).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.

Pulmonary embolism (PE) is an important cause of death and its seasonality has long been observed. Very few epidemiological studies have explored the potential role of ambient temperature in PE symptom onset, especially at the hourly level.We conducted a time-stratified case-crossover study among 17,903 PE patients with hourly onset of symptom from 1590 hospitals across China between January 2015 and September 2020. Conditional logistic regression model combined with distributed lag non-linear models were used to explore the associations between hourly ambient temperature and PE symptom onset. The attributable fractions due to non-optimum temperature were calculated.The exposure-response relationship curve was inverse and almost linear. Lower temperature was significantly associated with higher risk of PE symptom onset when temperature was below 18 °C. This risk occurred immediately at the same hour, attenuated thereafter, and became nonsignificant at approximately 72 h after exposure. Compared with the referent temperature (PWe provided the first-hand robust evidence that transient exposure (at the hourly level) to low temperature might trigger the symptom onset of PE and constitute a considerable burden for PE patients. Targeted protections and health education are needed for susceptible populations.

Rationale It remains unknown whether long-term ozone exposure can impair lung function. Objectives To investigate the associations between long-term ozone exposure and adult lung function in China. Methods Lung function results and diagnosis of small airways dysfunction (SAD) were collected from a cross-sectional study, China Pulmonary Health Study (N=50,991). We used multivariate linear and logistic regression models to examine the associations of long-term ozone exposure with lung function parameters and SAD, respectively, adjusting for demographic characteristics, individual risk factors, and longitudinal trend. We then performed a stratification analysis by chronic obstructive pulmonary disease (COPD). Measurements and main results We observed each 1-standard deviation (SD, 4.9 ppb) increase in warm-season ozone concentrations was associated with a 14.2 mL/s [95% confidence interval (CI): 8.8, 19.6] decrease in forced expiratory flow at 75th percentile of vital capacity and a 29.5 mL/s (95% CI: 19.6, 39.5) decrease in mean forced expiratory flow between the 25th and 75th percentile of vital capacity. The odds ratio of SAD was 1.09 (95% CI: 1.06, 1.11) for a 1-SD increase in warm-season ozone concentrations. Meanwhile, we observed a significant association with a decreased ratio of expiratory volume in 1 second to forced vital capacity (FEV1/FVC) but not with FEV1 or FVC. The association estimates were greater in the COPD group than in the non-COPD group. Conclusion We found independent associations of long-term ozone exposure with impaired small airways function and higher SAD risks, while the associations with airflow obstruction were weak. COPD patients appear to be more vulnerable.

Exposure to fine particulate matter (PM

Association of prenatal air pollution exposure with maternal thyroid hormone (TH) levels remains unclear, especially during early pregnancy when even small changes in maternal TH could affect fetal neurodevelopment. We examined the effect of air pollution exposure on maternal TH levels in the second trimester of pregnancy. Serum concentrations of free thyroxine (FT4) and thyroid-stimulating hormone (TSH) in 8077 pregnant women were measured by fluorescence and chemiluminescence immunoassays. Prenatal exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) was estimated using land use regression models. FT4 levels were significantly inversely associated with both PM2.5 and NO2 exposure. A 10 μg/m3 increase in NO2 exposure in first trimester and PM2.5 exposure in second trimester was associated with 0.61% (95% CI, -0.88% to -0.35%) and 0.73% (95% CI, -1.25% to -0.20%) decrease in FT4 levels, respectively. PM2.5 exposure was also associated with elevated odds of maternal hypothyroxinemia. A 10 μg/m3 increase in PM2.5 exposure in both first and second trimester was associated with 28% (OR = 1.28, 95% CI, 1.05–1.57) and 23% (OR = 1.23, 95% CI, 1.00–1.51) increase in the odds of maternal hypothyroxinemia, respectively. Our findings suggest that air pollution may interfere with maternal thyroid function during early pregnancy.

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.

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 (PM(2.5)), black carbon (BC) and nitrogen dioxide (NO(2)) 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 PM(2.5) (BC) sites and 45 NO(2) 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 PM(2.5), 78% in BC and 73% in NO(2). Mean (±Standard Deviation) of predicted PM(2.5), BC and NO(2) exposure levels were 48.3 (±6.3) μg/m(3), 7.5 (±1.4) μg/m(3) and 27.3 (±8.2) μg/m(3), 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 PM(2.5), BC and NO(2) levels were positively associated with traffic variables. The former two also increased with farm land use; and higher NO(2) 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 NO(2). CONCLUSION: We concluded that based on a purpose-designed monitoring network, LUR model can be applied to predict PM(2.5), NO(2) 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 PM(2.5), NO(2) and BC concentrations.

The short-term associations of fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) with pulmonary function were inconsistent and rarely evaluated by dynamic measurements. Our study aimed to investigate the associations of PM2.5 and PM2.5–10 with real-time pulmonary function. We conducted a longitudinal study based on dynamic pulmonary function measurements among adult asthmatic patients in 25 cities of 19 provincial regions of China from 2017 to 2020. Linear mixed-effects models combined with polynomial distributed lag models were used for statistical analysis. A total of 298,396 records among 4,992 asthmatic patients were evaluated. We found generally inverse associations of PM2.5 and PM2.5–10 with 16 pulmonary function indicators that were independent of gaseous pollutants. The associations occurred at lag 1 d, became the strongest at lag 4 d, and vanished a week later. PM2.5-10 had stronger associations than PM2.5, especially in southern China. Nationally, an interquartile increase in PM2.5-10 (28.0 μg/m3) was significantly associated with decreases in forced expiratory volume in 1 s (FEV1, 41.6 mL), the ratio of FEV1 in forced vital capacity (1.1%), peak expiratory flow (136.9 mL/s), and forced expiratory flow at 25–75% of forced vital capacity (54.3 mL/s). We observed stronger associations in patients of male, BMI ≥ 25 kg/m2, age ≥ 45 years old, and during warm seasons. In conclusion, this study provided robust evidence for impaired pulmonary function by short-term exposure to PM2.5 and PM2.5-10 in asthmatic patients using the largest dataset of dynamic monitoring. The associations can last for one week and PM2.5-10 may be more hazardous.

The biological mechanism of adverse health outcomes related to exposure to traffic-related air pollution (TRAP) needs elucidation. We conducted a randomized, crossover trial among healthy young students in Shanghai, China. Participants wore earplugs and were randomly assigned to a 4-hour walking treatment either along a traffic-polluted road or through a traffic-free park. We conducted untargeted analyses of plasma exosome transcriptomics, serum mass spectrometry-based proteomics, and serum metabolomics to evaluate changes in genome-wide transcription, protein, and metabolite profiles in 35 randomly selected participants. Mean personal exposure levels of ultrafine particles, black carbon, nitrogen dioxide, and carbon monoxide in the road were 2–3 times higher than that in the park. We observed 3449 exosome mRNAs, 58 serum proteins, and 128 serum metabolites that were significantly associated with TRAP. The multi-omics analysis showed dozens of regulatory pathways altered in response to TRAP, such as inflammation, oxidative stress, coagulation, endothelin-1 signaling, and renin-angiotensin signaling. We found that several novel pathways activated in response to TRAP exposure: growth hormone signaling, adrenomedullin signaling, and arachidonic acid metabolism. Our study served as a demonstration and proof of concept on the evidence that associated TRAP exposure with global molecular changes based on the multi-omics level.

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.

Supplemental Digital Content is available in the text., Background: Previous studies have suggested noise, especially at night time, and light at night (LAN) could cause neuroendocrine disturbance and circadian disruption, which may lead to ovarian follicle atresia and earlier onset of menopause. However, no study to date has directly investigated the associations of exposure to these factors and menopausal age. Methods: Premenopausal women from the Nurses’ Health Study II (NHS II) were followed from age 40 through 2015. Median daytime and nighttime anthropogenic noise and outdoor LAN exposure were measured from a geospatial prediction model and satellite images, respectively, at residential addresses throughout the follow-up. Time-varying Cox proportional hazard models were used to calculate the hazard ratios and 95% confidence intervals, adjusting for individual lifestyle, reproductive history, and neighborhood socioeconomic factors. Possible effect modification by region, smoking status, body mass index, race/ethnicity, history of rotating shift work, and census tract population density and median income was examined. Results: A total of 63,380 of 105,326 women self-reported natural menopause during 1,043,298 person-years of follow-up. No associations were found for noise (both daytime and nighttime) and outdoor LAN exposure with age at natural menopause (hazard ratios = 0.99–1.00) in the fully adjusted models. Sensitivity analyses showed similar null associations. No meaningful effect modification was found for region, smoking status, body mass index, race/ethnicity, history of rotating shift work, and census tract socioeconomic measures in stratified analyses. Conclusion: No associations were found between environmental noise and outdoor LAN exposure in mid-adulthood and menopausal age in this cohort of US women.

Background Potential hazards of fine particulate matter (PM2.5) constituents on preterm birth (PTB) have rarely been explored in China. Objective To quantify the associations of PM2.5 constituents with PTB. Methods This study was based on a nationwide cohort of 3,723,169 live singleton births delivered between January 2010 and December 2015 in China. We applied satellite-based estimates of five PM2.5 constituents (organic carbon; black carbon; sulfate; ammonium; and nitrate). We used Cox proportional hazards regression models adjusted for individual covariates, temperature, humidity, and seasonality to evaluate the associations. Results During the entire pregnancy, each interquartile range (29 μg/m3) increase in PM2.5 concentrations was associated with a 7% increase in PTB risk [hazard ratio (HR): 1.07; 95% confidence interval (CI): 1.07-1.08). We observed the largest effect estimates on carbonaceous components (HR: 1.09; 95% CI: 1.08-1.10 for organic carbon and black carbon). Early pregnancy appeared to be the critical exposure window for most constituents. Women who were older, exposed to second-hand smoke, overweight or obese before pregnancy, conceived during winter, and living in northern China or rural areas were more susceptible. Conclusions Carbonaceous components of PM2.5 were associated with higher PTB risk. Findings on characteristics of vulnerability underlined targeted protections on susceptible subgroups.

Few cohort studies explored the associations of long-term exposure to ambient fine particulate matter with an aerodynamic diameter of 2.5 μm or less (PM

Evidence has shown associations between air pollution and traffic-related exposure with accelerated aging, but no study to date has linked the exposure with age at natural menopause, an important indicator of reproductive aging. In this study, we sought to examine the associations of residential exposure to ambient particulate matter (PM) and distance to major roadways with age at natural menopause in the Nurses’ Health Study II (NHS II), a large, prospective female cohort in US. A total of 105,996 premenopausal participants in NHS II were included at age 40 and followed through 2015. Time-varying residential exposures to PM(10), PM(2.5-10), and PM(2.5) and distance to roads was estimated. We calculated hazard ratios (HR) and 95% confidence intervals (CIs) for natural menopause using Cox proportional hazard models adjusting for potential confounders and predictors of age at menopause. We also examined effect modification by region, smoking, body mass, physical activity, menstrual cycle length, and population density. There were 64,340 reports of natural menopause throughout 1,059,229 person-years of follow-up. In fully adjusted models, a 10 μg/m(3) increase in the cumulative average exposure to PM(10) (HR: 1.02, 95% CI: 1.00, 1.04), PM(2.5-10) (HR: 1.03, 95% CI: 1.00, 1.05), and PM(2.5) (HR: 1.03, 95% CI:1.00, 1.06) and living within 50 m to a major road at age 40 (HR: 1.03, 95%CI: 1.00, 1.06) were associated with slightly earlier menopause. No statistically significant effect modification was found, although the associations of PM were slightly stronger for women who lived in the West and for never smokers. To conclude, we found exposure to ambient PM and traffic in midlife was associated with slightly earlier onset of natural menopause. Our results support previous evidence that exposure to air pollution and traffic may accelerate reproductive aging.

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

Background Exposure to fine particulate matter (PM2.5) has been linked with adverse cardiorespiratory health conditions. However, evidence for PM2.5 constituents is still scarce, especially among patients with chronic obstructive pulmonary disease (COPD). Objective To investigate the associations of short-term exposure to different chemical constituents of PM2.5 with measures of cardiac and lung function in COPD patients. Methods We conducted a retrospective panel study among 100 COPD patients who received repeated measures of left ventricular ejection fraction (LVEF), forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and peak expiratory flow (PEF) in Shanghai, China from August 2014 to September 2019. Daily PM2.5 and PM2.5 constituents were obtained from fixed-site monitoring station. Linear mixed-effects models were used to estimate the associations of PM2.5. Results We found water-soluble ions of PM2.5, mainly NO3−, SO42−, and NH4+ were robustly associated with reduced LVEF, and the reductions in LVEF associated with an IQR increase of them ranged from 1.8% to 2.0% (lag 1 d). Metal constituents such as Cu and As were associated with FEV1, FVC and PEF. The corresponding reductions in lung function parameters for an IQR increase of them ranged from 1.4% to 2.3% (lag 0 or 1 d). These associations remained relatively robust after adjusting for total PM2.5 mass and gaseous pollutants. Conclusions Our results suggest that water-soluble ions and several metal/metalloid elements might be important constituents in PM2.5 that were associated with reduced cardiorespiratory function among COPD patients.

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.

Background Short-term exposure to fine particulate matter (PM2.5) has been associated with reduced heart rate variability (HRV), an established indicator of cardiac autonomic function, but it remains uncertain which specific constituents of PM2.5 had key impacts. Objective To examine the short-term associations between various PM2.5 constituents and HRV measures. Methods We conducted a retrospective panel study among 78 participants who received repeated 24-h electrocardiogram testing in Shanghai, China from 2015 to 2019. We obtained daily concentrations of 14 main chemical constituents of PM2.5 from a fixed-site monitor. During 3 or 4 rounds of follow-ups, we measured 6 HRV parameters, including 3 frequency-domain parameters (power in very low frequency, low frequency and high frequency) and 3 time-domain parameters (standard deviation of normal-to-normal intervals, root mean square successive difference and percent of adjacent normal R-R intervals with a difference ≥50 msec). We used linear mixed-effects models to analyze the data after controlling for time trends, environmental and individual risk factors. Results The average daily PM2.5 exposure was 45.8 μg/m3 during the study period. The present-day exposure to PM2.5 had the strongest negative influences on various HRV indicators. These associations attenuated greatly on lag 1 d or lag 2 d. Elemental carbon, organic carbon, nitrate, sulfate, arsenic, cadmium, chromium and nickel were consistently associated with reduced HRV parameters in both single-constituent models and constituent-PM2.5 models. Conclusion Our study highlighted the key roles of traffic-related components of PM2.5 in inhibiting cardiac autonomic function.

Epidemiological studies have associated ozone exposure with cardiovascular diseases, but the molecular mechanisms were not elucidated. We performed an untargeted serum proteomic analysis in a randomized, crossover, controlled exposure trial. We recruited 32 healthy young adults and asked them to receive filtered air and 200-ppb ozone exposures for 2 h in a random order before serum collection. Linear mixed-effect models were used to identify differentially expressed proteins (DEPs) between the two exposures and Gene Ontology enrichment and ingenuity pathway analysis were performed to determine their biological function. A total of 56 DEPs were identified. For example, acute ozone exposure increased coagulation factor X and factor VII-activating protease by 20.96% and 28.35%, respectively. Whereas, protein Z, protein Z-dependent protease inhibitor, and plasminogen decreased by 13.62%, 33.54%, and 10.47%, respectively. We also observed a 42.32% decrease in paraoxonase 3 and evident changes in four apolipoproteins. Additionally, we found 18.21% and 95.82% increases in L-selectin and β2-microglobulin, respectively, and significant changes in three complements. DEPs and enriched pathways suggest that short-term ozone exposure may promote coagulation, suppress fibrinolysis, disrupt lipoprotein metabolism, activate immune responses, and affect the complement system. These findings provide additional insights into the mechanisms linking acute ozone exposure to thrombosis.

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.

Background Few studies have explored the role of ambient temperature in asthma exacerbation. Objective We aimed to explore the association of temperature with diurnal peak expiratory flow (PEF) variation and asthma exacerbation. Method We developed a longitudinal study among asthmatic adults in 18 Chinese cities. Subjects recorded PEF in dynamic pulmonary function monitoring from 2017 to 2020. Linear mixed-effect model and generalized additive model with distributed non-linear models were used to assess the effect of temperature and temperature change between neighboring days (TCN) on diurnal PEF variation and the risk of asthma exacerbation. Result We evaluated a total of 79,217 daily PEF monitoring records from 4467 adult asthmatic patients. There were significant increase of diurnal PEF variation and higher risk of asthma exacerbation with cold and sudden temperature drop. Compared with the referent temperature (99th percentile, 32 °C), exposure to moderate cold (25th percentile, 3 °C) and extreme cold (2.5th percentile, −7 °C) was associated with elevations of 1.28% and 1.16% in diurnal PEF variation over lag 0–2 days, respectively. The odds ratios of asthma exacerbation (determined by diurnal PEF variation >20%) at the two temperature cutoffs were 1.68 and 1.73. A sudden temperature drop (2.5th percentile of TCN, −5 °C) was associated with 1.13% elevation in diurnal PEF variation, and with increased risk of asthma exacerbation (odd ratio = 1.50) over lag 0–4 days. Conclusion This large multicenter study provided the first-hand empirical evidence that cold temperature and a temperature drop may increase the risk of asthma exacerbation.

Background: Previous studies have associated fine particulate (PM2.5) exposure with changes in gene-specific DNA methylation. However, the evidence was still limited and inconsistent in genome-wide DNA methylation. Objective: To examine the impact of short-term PM2.5 exposure on genome-wide DNA methylation. Methods: We designed a randomized, double-blind, crossover trial among 36 healthy young adults in Shanghai, China. A two-stage intervention with alternative use of real and sham air purifiers in dormitory rooms for consecutive 9 days were conducted to create natural low and high exposure scenarios of PM2.5. Blood genome-wide DNA methylation was analyzed using the Illumina Infinium Human Methylation EPIC BeadChip (850k). Mixed-effect models were used to evaluate the impacts of changes in PM2.5 levels on genome-wide DNA methylation. Results: There was a drastic contrast for PM2.5 exposure levels in the two scenarios (24-h averages: 53.1 and 24.3 μg/m3). Between the high and low exposure groups, methylation levels were changed significantly with a false discovery rate

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.