Maternal steroids during pregnancy and their associations with ambient air pollution and temperature during preconception and early gestational periods.

Hormones play critical roles in facilitating pregnancy progression and the onset of parturition. Several classes of environmental contaminants, including fine particulate matter (PM2.5) and ambient temperature, have been shown to alter hormone biosynthesis or activity. However, epidemiologic research has not considered PM2.5 in relation to a broader range of steroid hormones, particularly in pregnant women. Using metabolomics data collected within 20-40 weeks of gestation in an ethnically diverse pregnancy cohort study, we identified 42 steroid hormones that we grouped into five classes (pregnenolone, androgens, estrogens, progestin, and corticosteroids) based on their biosynthesis type. We found that exposure to PM2.5 during the pre-conception and early prenatal periods was associated with higher maternal androgen concentrations in late pregnancy. We also detected a positive association between early pregnancy PM2.5 exposure and maternal pregnenolone levels and a marginal positive association between early pregnancy PM2.5 exposure and progestin levels. When considering each hormone metabolite individually, we found positive associations between early pregnancy PM2.5 exposure and five steroids, two of which survived multiple comparison testing: 11beta-hydroxyandrosterone glucuronide (a pregnenolone steroid) and adrosteroneglucuronide (a progestin steroid). None of the steroid classes were statistically significant associated with ambient temperature. In sex-stratified analyses, we did not detect any sex differences in our associations. This is the first study showing that exposure to fine particulate matter during the pre-conception and early prenatal periods can lead to altered steroid adaptation during the state of pregnancy, which has been shown to have potential consequences on maternal and child health.

The global viralization of policies to contain the spreading of the COVID-19 pandemic: analyses of school closures and first reported cases.

BackgroundWith the exposure to the COVID-19 pandemic, countries swiftly implemented a variety of health policies. In this work we examine how rapid countries responded to this pandemic using two events: the day in which the first case of COVID-19 was reported, and first day in which countries used school closure as one of the measures to avoid outbreaks. MethodsWe compiled information from multiple sources, from December 31st 2019 to June 1st 2020, to trace when 172 countries reported their first COVID-19 case and implemented school closure to contain outbreaks. We applied cross-national Weibull survival analysis to evaluate the global speed of detection of first COVID-19 reported cases and school closure. We also assessed how countries health systems, globalization, economic development, political systems, and economic integration to China, Republic of Korea and Italy increased the speed of adoption. ResultsTen days after the World Health Organization (WHO) declared COVID-19 to be an international emergency, countries were 28 (95% CI: 12,77) times more likely to report first COVID-19 cases and 42 (95% CI: 22,90) times more likely to close schools. One standard deviation increase in the epidemic security index rises the rate of report first cases by 37% (Hazard Ratio (HR) 1.37 (95% CI: 1.09,1.72) and delays the adoption for school closures by 36% (HR 0.64 (95% CI:0.50,0.82). One standard deviation increase in the globalization index augments the adoption for school closures by 74% (HR 1.74 (95% CI:1.34,2.24). ConclusionAfter the WHO declared a global emergency, countries were unprecedently acting very rapidly. While countries more globally integrated were swifter in closing schools, countries with better designed health systems to tackle epidemics were slower in adopting it. More studies are needed to assess how the speed of school closures and other policies will affect the development of the pandemic.