A prospective cohort study on the intersectionality of obesity, chronic disease, social factors, and incident risk of COVID-19 in US low-income minority middle-age mothers.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) has disproportionally affected communities of color. We aimed to determine what factors are associated with COVID-19 testing and test positivity in an underrepresented, understudied, and underreported (U3) population of mothers. METHODS: This study included 2996 middle-aged mothers of the Boston Birth Cohort (a sample of predominantly urban, low-income, Black and Hispanic mothers) who were enrolled shortly after they gave birth and followed onward at the Boston Medical Center. COVID-19 testing and test positivity were defined by the SARS-CoV-2 nucleic acid test. Two-probit Heckman selection models were performed to identify factors associated with test positivity while accounting for potential selection associated with COVID testing. RESULTS: The mean (SD) age of study mothers was 41.9 (±7.7) years. In the sample, 1741 (58.1%) and 667 (22.3%) mothers were self-identified as Black and Hispanic, respectively. A total of 396 mothers had COVID-19 testing and of those, 95 mothers tested positive from March 2020 to February 2021. Among a multitude of factors examined, factors associated with the probability of being tested were obesity (RR = 1.27; 95% confidence interval (CI): 1.08-1.49); and presence of preexisting chronic medical conditions including hypertension, asthma, stroke, and other comorbidities (coronary heart disease, chronic kidney disease, and sickle cell disease) with a corresponding RR = 1.40 (95% CI: 1.23-1.60); 1.29 (95% CI: 1.11-1.50); 1.44 (95% CI: 1.23-1.68); and 1.37 (95% CI: 1.12-1.67), respectively. Factors associated with higher incident risk of a positive COVID-19 test were body mass index, birthplace outside of the USA, and being without a college-level education. CONCLUSIONS: This study demonstrated the intersectionality of obesity and social factors in modulating incident risk of COVID-19 in this sample of US Black and Hispanic middle-aged mothers. Methodologically, our findings underscore the importance of accounting for potential selection bias in COVID-19 testing in order to obtain unbiased estimates of COVID-19 infection.

COVID-19 and Children's Well-Being: A Rapid Research Agenda.

PURPOSE: Understanding the full impact of COVID-19 on U.S. children, families, and communities is critical to (a) document the scope of the problem, (b) identify solutions to mitigate harm, and (c) build more resilient response systems. We sought to develop a research agenda to understand the short- and long-term mechanisms and impacts of the COVID-19 pandemic on children's healthy development, with the goal of devising and ultimately testing interventions to respond to urgent needs and prepare for future pandemics. DESCRIPTION: The Life Course Intervention Research Network facilitated a series of virtual meetings that included members of 10 Maternal and Child Health (MCH) research programs, their research and implementation partners, as well as family and community representatives, to develop an MCH COVID-19 Research Agenda. Stakeholders from academia, clinical practice, nonprofit organizations, and family advocates participated in four meetings, with 30-35 participants at each meeting. ASSESSMENT: Investigating the impacts of COVID-19 on children's mental health and ways to address them emerged as the highest research priority, followed by studying resilience at individual and community levels; identifying and mitigating the disparate negative effects of the pandemic on children and families of color, prioritizing community-based research partnerships, and strengthening local, state and national measurement systems to monitor children's well-being during a national crisis. CONCLUSION: Enacting this research agenda will require engaging the community, especially youth, as equal partners in research co-design processes; centering anti-racist perspectives; adopting a "strengths-based" approach; and integrating young researchers who identify as Black, Indigenous, and People of Color (BIPOC). New collaborative funding models and investments in data infrastructure are also needed.