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Background and objective: Ecological studies have suggested an association between exposure to particulate matter ≤2.5 μm (PM 2.5 ) and coronavirus disease 2019 (COVID-19) severity. However, these findings are yet to be validated in individuallevel studies. We aimed to determine the association of long-term PM 2.5 exposure with hospitalization among individual patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: We estimated the 10-year (2009-2018) PM 2.5 exposure at the residential zip code of COVID-19 patients diagnosed at the University of Cincinnati healthcare system between 13 March 2020 and 30 September 2020. Logistic regression was used to determine the odds ratio (OR) and 95% CI for COVID-19 hospitalizations associated with PM 2.5 , adjusting for socioeconomic characteristics and comorbidities. Results: Among the 14,783 COVID-19 patients included in our study, 13.6% were hospitalized; the geometric mean (SD) PM 2.5 was 10.48 (1.12) μg/m 3 . In adjusted analysis, 1 μg/m 3 increase in 10-year annual average PM 2.5 was associated with 18% higher hospitalization (OR: 1.18, 95% CI: 1.11-1.26). Likewise, 1 μg/m 3 increase in PM 2.5 estimated for the year 2018 was associated with 14% higher hospitalization (OR: 1.14, 95% CI: 1.08-1.21). Conclusion: Long-term PM 2.5 exposure is associated with increased hospitalization in COVID-19. Therefore, more stringent COVID-19 prevention measures may be needed in areas with higher PM 2.5 exposure to reduce the disease morbidity and healthcare burden.

Context The age of pubertal onset is influenced by many variables in young girls. Previous studies have not examined sex hormones longitudinally around the time of breast development and their relationship to pubertal onset. Objective We sought to use an unbiased statistical approach to identify phenotypes of sex hormones in young girls and examine their relationship with pubertal milestones. Design and Setting Longitudinal observational study. Participants and Main Outcome Measures In 269 girls, serum concentrations of steroid sex hormones [estradiol (E2), estrone, testosterone, and dehydroepiandrosterone sulfate] were measured by HPLC-mass spectrometry at time points before, at, and after thelarche. Girls were classified into four hormone phenotypes using objective principal components and cluster analyses of longitudinal hormone data. The association between the identified phenotypes and age of pubertal milestones was estimated using Cox proportional hazards modeling. Results Mean ages at thelarche, pubarche, and menarche were 9.02, 9.85, and 12.30 years, respectively. Girls with low levels of all four hormones, phenotype 3b, were youngest at thelarche (8.67 years); those in phenotype 2, with the highest E2 levels and E2 surge 6 months after thelarche, were youngest at menarche (11.87 years) with shortest pubertal tempo. When controlling for race, maternal age of menarche, caregiver education, and body mass, different phenotypes were associated with the age of pubertal events. Conclusions Hormone phenotypic clustering can identify clinically relevant subgroups with differing ages of thelarche, pubarche, and menarche. These findings may enhance the understanding of timing of pubertal milestones and risk of adult disease.

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