A Multisite Examination of Everyday Discrimination and the Prevalence of Spontaneous Preterm Birth in African American and Latina Women in the United States.

OBJECTIVE: African American women have a higher risk of spontaneous preterm birth than White and Latina women. Although Latina women are exposed to similar social determinants of health, they have lower rates of spontaneous preterm birth. One theory for this difference is the maternal stress biological pathway, whereby lifetime stressors, such as racial discrimination, lead to a premature activation of parturition. We investigated the prevalence of self-reported discrimination and its association with the prevalence of spontaneous preterm birth. STUDY DESIGN: Using data from the Community Child Health Research Network Study, a multisite cohort study from 2008 to 2012, we conducted a cross-sectional analysis of 1,154 African American women and 578 Latina women. RESULTS: Adjusting for multiple risk factors, African American and Latina women who experienced the highest tertile of discrimination had a higher prevalence of preterm birth compared with those who experienced discrimination less than once per year, adjusted hazard ratio (aHR) = 1.5 (0.7-3.1) and 3.6 (0.9-14.4), respectively. CONCLUSION: In our cohort, we found a statistically significant association only in the medium discrimination group in Latina women, but we did not find a statistically significant association in African American women. Reduction in experienced discrimination may be an important intervention for reducing adverse pregnancy outcomes.

The Association between Travel Time and Prenatal Care Attendance.

OBJECTIVE: This study aimed to evaluate the association between a patient's travel time to clinic and her prenatal care attendance. STUDY DESIGN: We conducted a retrospective cohort study of women (≥18 years) who received prenatal care and delivered at North Carolina Women's Hospital between July 1, 2014, and June 30, 2016 (n = 2,808 women, 24,021 appointments). We queried demographic data from the electronic medical record and calculated travel time with ArcGIS. Multinomial logistic regression models estimated the association between travel time and attendance, adjusted for sociodemographic covariates. RESULTS: For every 10 minutes of additional travel time, women were 1.05 (95% confidence interval [CI]: 1.02-1.08, p < 0.001) times as likely to arrive late and 1.03 (95% CI: 1.01-1.04, p < 0.001) times as likely to cancel appointments than arrive on time. Travel time did not significantly affect a patient's likelihood of not showing for appointments. Non-Hispanic black patients were 71% more likely to arrive late and 51% more likely to not show for appointments than non-Hispanic white patients (p < 0.05). Publicly insured women were 28% more likely to arrive late to appointments and 82% more likely to not show for appointments than privately insured women (p < 0.05). CONCLUSION: Changes to transportation availability alone may only modestly affect outcomes compared with strategically improving access for sociodemographically marginalized women.

Right-Sizing Prenatal Care to Meet Patients' Needs and Improve Maternity Care Value.

Prenatal care is one of the most widely used preventive care services in the United States, yet prenatal care delivery recommendations have remained largely unchanged since just before World War II. The current prenatal care model can be improved to better serve modern patients and the health care providers who care for them in three key ways: 1) focusing more on promotion of health and wellness as opposed to primarily focusing on medical complications, 2) flexibly incorporating patient preferences, and 3) individualizing care. As key policymakers and stakeholders grapple with higher maternity care costs and poorer outcomes, including lagging access, equity, and maternal and infant morbidity and mortality in the United States compared with other high-income countries, the opportunity to improve prenatal care has been given insufficient attention. In this manuscript, we present a new conceptual model for prenatal care that incorporates both patients' medical and social needs into four phenotypes, and use human-centered design methods to describe how better matching patient needs with prenatal services can increase the use of high-value services and decrease the use of low-value services. Finally, we address some of the key challenges to implementing right-sized prenatal care, including capturing outcomes through research and payment.

Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.

Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen.