Objective. To characterize trends in chorioamnionitis (CAM) by maternal race/ethnicity and gestational age. Study Design. We examined trends in CAM from 1995-2010 among singleton births in all Kaiser Permanente Southern California hospitals (n = 471,821). Data were extracted from Perinatal Service System and clinical utilization records. Gestational age- and race/ethnicity-specific biannual diagnosis rates were estimated using the Poisson regression after adjusting for potential confounding factors. Results. Overall diagnosis rates of CAM increased from 2.7% in 1995-1996 to 6.0% in 2009-2010 with a relative increase of 126% (95% confidence intervals [CI] 113%-149%). From 1995-1996 to 2009-2010, CAM increased among the Whites (1.8% to 4.3%, P-value for trend <.001), Blacks (2.2% to 3.7%, P-value for trend <.001), Hispanics (2.4% to 5.8%, P-value for trend <.001), and Asian/Pacific Islanders (3.6% to 9.0%, P-value for trend <.001). The adjusted relative percentage change in CAM from 1995-1996 to 2009-2010 was for Whites [preterm 21% (9%-78%), term 138% (108%-173%)], for Blacks [preterm 24% (-9%-81%), term 62% (30%-101%)], for Hispanics [preterm 31% (3%-66%), term 135% (114%-159%)], and for Asian/Pacific Islanders [preterm 44% (9%-127%), term 145% (109%-188%)]. Conclusion. The findings suggest that CAM diagnosis rate has increased for all race/ethnic groups. This increase is primarily due to increased diagnosis at term gestation.

Purpose: To assess the prevalence and motivations for obtaining tattoos among transgender persons. Methods: A survey of 696 transgender persons recruited from the Study of Transition, Outcomes, and Gender (STRONG) cohort evaluated the prevalence of tattoos and motivations for acquiring tattoos. Results: Transmasculine persons were more likely than transfeminine persons to have tattoos (66.5% versus 24.0%, P<0.05). Most commonly reported motivators were personal preference, aesthetics, and/or symbolism (61.8%). Scar coverage and replacement of anatomic features accounted for 10.2% of responses. Conclusion: Future studies should look into the relationship between tattoos and health status in the transgender population.

Few studies have assessed extreme temperatures' impact on gestational diabetes mellitus (GDM). We examined the relation between GDM risk with weekly exposure to extreme high and low temperatures during the first 24 weeks of gestation and assessed potential effect modification by microclimate indicators.

Methods

We utilized 2008-2018 data for pregnant women from Kaiser Permanente Southern California electronic health records. GDM screening occurred between 24 and 28 gestational weeks for most women using the Carpenter-Coustan criteria or the International Association of Diabetes and Pregnancy Study Groups criteria. Daily maximum, minimum, and mean temperature data were linked to participants' residential address. We utilized distributed lag models, which assessed the lag from the first to the corresponding week, with logistic regression models to examine the exposure-lag-response associations between the 12 weekly extreme temperature exposures and GDM risk. We used the relative risk due to interaction (RERI) to estimate the additive modification of microclimate indicators on the relation between extreme temperature and GDM risk.

Results

GDM risks increased with extreme low temperature during gestational weeks 20--24 and with extreme high temperature at weeks 11-16. Microclimate indicators modified the influence of extreme temperatures on GDM risk. For example, there were positive RERIs for high-temperature extremes and less greenness, and a negative RERI for low-temperature extremes and increased impervious surface percentage.

Discussion

Susceptibility windows to extreme temperatures during pregnancy were observed. Modifiable microclimate indicators were identified that may attenuate temperature exposures during these windows, which could in turn reduce the health burden from GDM.

BACKGROUND: Epidemiological findings regarding the association of particulate matter ≤2.5 μm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP) are inconsistent; evidence for HDP risk related to PM2.5 components, mixture effects, and windows of susceptibility is limited. We aimed to investigate the relationships between HDP and exposure to PM2.5 during pregnancy. METHODS AND FINDINGS: A large retrospective cohort study was conducted among mothers with singleton pregnancies in Kaiser Permanente Southern California from 2008 to 2017. HDP were defined by International Classification of Diseases-9/10 (ICD-9/10) diagnostic codes and were classified into 2 subcategories based on the severity of HDP: gestational hypertension (GH) and preeclampsia and eclampsia (PE-E). Monthly averages of PM2.5 total mass and its constituents (i.e., sulfate, nitrate, ammonium, organic matter, and black carbon) were estimated using outputs from a fine-resolution geoscience-derived model. Multilevel Cox proportional hazard models were used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of PM2.5 constituents. The distributed lag model was applied to estimate the association between monthly PM2.5 exposure and HDP risk. This study included 386,361 participants (30.3 ± 6.1 years) with 4.8% (17,977/373,905) GH and 5.0% (19,381/386,361) PE-E cases, respectively. In single-pollutant models, we observed increased relative risks for PE-E associated with exposures to PM2.5 total mass [adjusted hazard ratio (HR) per interquartile range: 1.07, 95% confidence interval (CI) [1.04, 1.10] p < 0.001], black carbon [HR = 1.12 (95% CI [1.08, 1.16] p < 0.001)] and organic matter [HR = 1.06 (95% CI [1.03, 1.09] p < 0.001)], but not for GH. The population attributable fraction for PE-E corresponding to the standards of the US Environmental Protection Agency (9 μg/m3) was 6.37%. In multi-pollutant models, the PM2.5 mixture was associated with an increased relative risk of PE-E ([HR = 1.05 (95% CI [1.03, 1.07] p < 0.001)], simultaneous increase in PM2.5 constituents of interest by a quartile) and PM2.5 black carbon gave the greatest contribution of the overall mixture effects (71%) among all individual constituents. The susceptible window is the late first trimester and second trimester. Furthermore, the risks of PE-E associated with PM2.5 exposure were significantly higher among Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods (p < 0.05 for Cochrans Q test). Study limitations include potential exposure misclassification solely based on residential outdoor air pollution, misclassification of disease status defined by ICD codes, the date of diagnosis not reflecting the actual time of onset, and lack of information on potential covariates and unmeasured factors for HDP. CONCLUSIONS: Our findings add to the literature on associations between air pollution exposure and HDP. To our knowledge, this is the first study reporting that specific air pollution components, mixture effects, and susceptible windows of PM2.5 may affect GH and PE-E differently.

BACKGROUND: Significant mortality and morbidity in pregnant women and their offspring are linked to premature rupture of membranes (PROM). Epidemiological evidence for heat-related PROM risk is extremely limited. We investigated associations between acute heatwave exposure and spontaneous PROM. METHODS: We conducted this retrospective cohort study among mothers in Kaiser Permanente Southern California who experienced membrane ruptures during the warm season (May-September) from 2008 to 2018. Twelve definitions of heatwaves with different cut-off percentiles (75th, 90th, 95th, and 98th) and durations (≥ 2, 3, and 4 consecutive days) were developed using the daily maximum heat index, which incorporates both daily maximum temperature and minimum relative humidity in the last gestational week. Cox proportional hazards models were fitted separately for spontaneous PROM, term PROM (TPROM), and preterm PROM (PPROM) with zip codes as the random effect and gestational week as the temporal unit. Effect modification by air pollution (i.e., PM2.5 and NO2), climate adaptation measures (i.e., green space and air conditioning [AC] penetration), sociodemographic factors, and smoking behavior was examined. RESULTS: In total, we included 190,767 subjects with 16,490 (8.6%) spontaneous PROMs. We identified a 9-14% increase in PROM risks associated with less intense heatwaves. Similar patterns as PROM were found for TPROM and PPROM. The heat-related PROM risks were greater among mothers exposed to a higher level of PM2.5 during pregnancy, under 25 years old, with lower education and household income level, and who smoked. Even though climate adaptation factors were not statistically significant effect modifiers, mothers living with lower green space or lower AC penetration were at consistently higher heat-related PROM risks compared to their counterparts. CONCLUSION: Using a rich and high-quality clinical database, we detected harmful heat exposure for spontaneous PROM in preterm and term deliveries. Some subgroups with specific characteristics were more susceptible to heat-related PROM risk.

Background

Little research exists regarding the relationships between green space and postpartum depression (PPD). We aimed to investigate the relationships between PPD and green space exposure, and the mediating role of physical activity (PA).

Methods

Clinical data were obtained from Kaiser Permanente Southern California electronic health records in 2008-2018. PPD ascertainment was based on both diagnostic codes and prescription medications. Maternal residential green space exposures were assessed using street view-based measures and vegetation types (i.e., street tree, low-lying vegetation, and grass), satellite-based measures [i.e., Normalized Difference Vegetation Index (NDVI), land-cover green space, and tree canopy cover], and proximity to the nearest park. Multilevel logistic regression was applied to estimate the association between green space and PPD. A causal mediation analysis was performed to estimate the proportion mediated by PA during pregnancy in the total effects of green space on PPD.

Findings

In total, we included 415,020 participants (30.2 ± 5.8 years) with 43,399 (10.5%) PPD cases. Hispanic mothers accounted for about half of the total population. A reduced risk for PPD was associated with total green space exposure based on street-view measure [500 m buffer, adjusted odds ratio (OR) per interquartile range: 0.98, 95% CI: 0.97-0.99], but not NDVI, land-cover greenness, or proximity to a park. Compared to other types of green space, tree coverage showed stronger protective effects (500 m buffer, OR = 0.98, 95% CI: 0.97-0.99). The proportions of mediation effects attributable to PA during pregnancy ranged from 2.7% to 7.2% across green space indicators.

Interpretation

Street view-based green space and tree coverage were associated with a decreased risk of PPD. The observed association was primarily due to increased tree coverage, rather than low-lying vegetation or grass. Increased PA was a plausible pathway linking green space to lower risk for PPD.

Funding

National Institute of Environmental Health Sciences (NIEHS; R01ES030353).

BACKGROUND: The effect of gender affirming hormone therapy (GAHT) on clinical laboratory parameters, including levels of liver enzymes alanine aminotransferase (ALT) and aspartate transaminase (AST), is an area of uncertainty in transgender health. AIM: We sought to estimate the distribution parameters of liver enzyme levels among transmasculine (TM) and transfeminine (TF) persons receiving GAHT relative to the corresponding measures in cisgender reference groups, and to evaluate longitudinal changes in these laboratory measures following GAHT initiation. METHODS: The data for this longitudinal study included 624 TF and 438 transmasculine (TM) people as well as 4,090 cisgender males and 4,797 cisgender females enrolled in 3 integrated health systems. Time under observation was divided into 2 intervals: from the first blood test to the date of the first filled GAHT prescription and from GAHT initiation to the most recent ALT or AST measurement. Linear mixed models were used to compare changes in log-transformed ALT and AST values among transgender cohort members before and after GAHT initiation, and relative to the reference groups. The results were expressed as relative differences (in %) and the ratios of these differences (ratios-of-ratios) along with the 95% confidence intervals (CIs). OUTCOMES: Changes in ALT and AST levels among transgender people over time and relative to the corresponding changes in cisgender referents. RESULTS: Among TM study participants, the post GAHT ratios-of-ratios for AST were 1.61 (95% CI: 1.13, 2.31) and 1.57 (95% CI: 1.06, 2.31) relative to cisgender males and females respectively. For ALT, the corresponding comparisons yielded the ratios-of-ratios (95% CIs) of 2.06 (1.67, 2.54) and 1.90 (1.50, 2.40). No statistically significant changes were observed among TF participants. Other factors associated with higher liver enzyme levels included alcohol use/abuse and obesity. CLINICAL IMPLICATIONS: TM persons may experience modest increases in ALT and AST concentrations following testosterone initiation; however, clinical significance of the observed association remains unclear and requires further investigation. By contrast, feminizing GAHT is unlikely to induce appreciable changes in liver enzyme levels. STRENGTH AND LIMITATIONS: The strengths of this study are the longitudinal design and the ability to assemble an unselected cohort nested within large health systems. The main limitations include the lack of information on hormone levels and the inability to take into account GAHT doses and routes of administration. CONCLUSION: The influence of long-term GAHT on ALT and AST levels appears modest and not likely to reflect clinically meaningful changes in liver function. Hashemi L, Zhang Q, Getahun D, et al. Longitudinal Changes in Liver Enzyme Levels Among Transgender People Receiving Gender Affirming Hormone Therapy. J Sex Med 2021;18:1662-1675.

Background

Epidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents.

Objectives

To assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents.

Methods

Detailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter < 2.5 μm (PM_2.5), <10 μm (PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) were estimated using kriging interpolation of Environmental Protection Agency's routine monitoring station data, while PM_2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon) were estimated using a fine-resolution geoscience-derived model. A multilevel logistic regression was used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of air pollution and PM component mixtures. Main analyses adjusted for maternal age, race/ethnicity, education, median family household income, pre-pregnancy BMI, smoking during pregnancy, insurance type, season of conception and year of delivery.

Results

The incidence of GDM was 10.9% in the study population. In single-pollutant models, we observed an increased odds for GDM associated with exposures to PM_2.5, PM₁₀, NO₂ and PM_2.5 constituents. The association was strongest for NO₂ [adjusted odds ratio (OR) per interquartile range: 1.176, 95% confidence interval (CI): 1.147-1.205)]. In multi-pollutant models, increased ORs for GDM in association with one quartile increase in air pollution mixtures were found for both kriging-based regional air pollutants (NO₂, PM_2.5, and PM₁₀, OR = 1.095, 95% CI: 1.082-1.108) and PM_2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon, OR = 1.258, 95% CI: 1.206-1.314); NO₂ (78%) and black carbon (48%) contributed the most to the overall mixture effects among all krigged air pollutants and all PM_2.5 constituents, respectively. The risk of GDM associated with air pollution exposure were significantly higher among Hispanic mothers, and overweight/obese mothers.

Conclusion

This study found that exposure to a mixture of ambient PM_2.5, PM₁₀, NO₂, and PM_2.5 chemical constituents was associated with an increased risk of GDM. NO₂ and black carbon PM_2.5 contributed most to GDM risk.

Gestational diabetes mellitus (GDM) is a major pregnancy complication affecting approximately 14.0% of pregnancies around the world. Air pollution exposure, particularly exposure to PM2.5, has become a major environmental issue affecting health, especially for vulnerable pregnant women. Associations between PM2.5 exposure and adverse birth outcomes are generally assumed to be the same throughout a large geographical area. However, the effects of air pollution on health can very spatially in subpopulations. Such spatially varying effects are likely due to a wide range of contextual neighborhood and individual factors that are spatially correlated, including SES, demographics, exposure to housing characteristics and due to different composition of particulate matter from different emission sources. This combination of elevated environmental hazards in conjunction with socioeconomic-based disparities forms what has been described as a double jeopardy for marginalized sub-populations. In this manuscript our analysis combines both an examination of spatially varying effects of a) unit-changes in exposure and examines effects of b) changes from current exposure levels down to a fixed compliance level, where compliance levels correspond to the Air Quality Standards (AQS) set by the U.S. Environmental Protection Agency (EPA) and World Health Organization (WHO) air quality guideline values. Results suggest that exposure reduction policies should target certain hotspot areas where size and effects of potential reductions will reap the greatest rewards in terms of health benefits, such as areas of southeast Los Angeles County which experiences high levels of PM2.5 exposures and consist of individuals who may be particularly vulnerable to the effects of air pollution on the risk of GDM.