Long-term PM2.5 exposure and sepsis mortality in a US medicare cohort.

BACKGROUND: Risk factors contributing to sepsis-related mortality include clinical conditions such as cardiovascular disease, chronic lung disease, and diabetes, all of which have also been shown to be associated with air pollution exposure. However, the impact of chronic exposure to air pollution on sepsis-related mortality has been little studied.  METHODS: In a cohort of 53 million Medicare beneficiaries (228,439 sepsis-related deaths) living across the conterminous United States between 2000 and 2008, we examined the association of long-term PM2.5 exposure and sepsis-related mortality. For each Medicare beneficiary (ages 65-120), we estimated the 12-month moving average PM2.5 concentration for the 12 month before death, for their ZIP code of residence using well validated GIS-based spatio-temporal models. Deaths were categorized as sepsis-related if they have ICD-10 codes for bacterial or other sepsis. We used Cox proportional hazard models to assess the association of long-term PM2.5 exposure on sepsis-related mortality. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socio-economic status (SES). We also evaluated confounding through adjustment of neighborhood behavioral covariates. RESULTS: A 10 µg/m3 increase in 12-month moving average PM2.5 was associated with a 9.1% increased risk of sepsis mortality (95% CI: 3.6-14.9) in models adjusted for age, sex, race, ZIP code, and SES. HRs for PM2.5 were higher and statistically significant for older (> 75), Black, and urban beneficiaries. In stratified analyses, null associations were found for younger beneficiaries (65-75), beneficiaries who lived in non-urban ZIP codes, and those residing in low-SES urban ZIP codes. CONCLUSIONS: Long-term PM2.5 exposure is associated with elevated risks of sepsis-related mortality.

Differential impacts of particulate air pollution exposure on early and late stages of spermatogenesis.

BACKGROUND: Despite increasing evidence that particulate air pollution has adverse effects on human semen quality, few studies examine the impact of air pollution on clinically relevant thresholds used to diagnose male fertility problems. Furthermore, exposure is often assessed using average air pollution levels in a geographic area rather than individualized estimates. Finally, physiologically-informed exposure windows are inconsistent. OBJECTIVES: We sought to test the hypothesis that airborne particulate exposures during early-phase spermatogenesis will have a differential impact on spermatogenic formation compared to late-phase exposures, using an individualized model of exposure to particulate matter ≤ 2.5 µm and ≤ 10 µm (PM2.5 and PM10, respectively). METHODS: From an original cohort of 183 couples, we conducted a retrospective analysis of 130 healthy males seeking to become parents, using spermatogenesis-relevant exposure windows of 77-34 days and 37-0 days prior to semen collection to encompass sperm development stages of mitosis/meiosis and spermiogenesis, respectively. Individualized residential exposure to PM2.5 and PM10 was estimated by selecting multiple air pollution sensors within the same geographic air basin as participants and employing inverse distance weighting to calculate mean daily exposure levels. We used multiple logistic regression to assess the association between pollution, temperature, and dichotomized World Health Organization semen parameters. RESULTS: During the early phase of spermatogenesis, air pollution exposure is associated with 1.52 (95% CI: 1.04-2.32) times greater odds of < 30% normal heads per 1-unit increase in IQR for PM2.5. In the late phase of spermatogenesis, air pollution exposure is associated with 0.35 (95% CI: 0.10-0.74) times greater odds of semen concentration < 15 million/mL per 1-unit increase in IQR for PM2.5, and 0.28 (95% CI: 0.07-0.72) for PM10. CONCLUSION: Particulate exposure has a differential and more deleterious impact on sperm during early-phase spermatogenesis than late-phase.

Maximizing Black applicant matriculation in U.S. PA programs: associations between the number of submitted applications and likelihood of matriculation.

BACKGROUND: Physician Assistants (PA) are important members of the medical team, and increasing diversity in healthcare professionals has been consistently associated with improved health outcomes for underrepresented minority patients. In this study of a national cohort of PA program applicants, we investigated whether the number of programs a student applied to (Application Number, AN) was significantly associated with increased likelihood of matriculation into a PA program. METHODS: We examined all applications (n = 27,282) to the 2017-2018 admissions cycle of the Central Application Service for Physician Assistants, which is utilized by over 90% of accredited PA programs in the US. As we a priori hypothesized that associations would be non-linear, we used natural cubic splines to estimate the associations between matriculation and AN, controlling for multiple metrics of academic achievement, experience, and applicant demographics. We subsequently used segmented regression analyses (modified poisson regression with robust error variance) to investigate log-linear associations above and below inflection points identified in the spline analyses. Additionally, we explored for effect modification by race/ethnicity. RESULTS: The strongest associations were observed between application number 2-7, and a threshold effect was observed at > 16 applications, beyond which there was no significant, incremental benefit in matriculation likelihood. Associations differed by race, particularly for application number 2-7, wherein the incremental benefit from each additional application was highest for Black applicants (Likelihood Ratio [LR]: 1.243, 95% CI: 1.136 to 1.360) vs non-Latinx White (LR: 1.098, 95% CI: 1.072 to 1.125), with no additional, incremental benefit beyond 7 program applications. For all other races, significant increased likelihoods of matriculation were observed until 16 program applications. CONCLUSIONS: These findings can help guide pre-PA advisors and PA programs, providing recommended thresholds to applicants on the most cost effective ways to increase their likelihood of admissions, and the PA profession as a whole by providing actionable information that can potentially increase Race/Ethnic diversity in the PA profession and, by extension, medical teams.