Faculty Bibliography

INTRODUCTION/UNASSIGNED: METHODS/UNASSIGNED: RESULTS/UNASSIGNED: CONCLUSIONS/UNASSIGNED:

Importance:Decades of inequitable policies in the US have yielded disparities in neighborhood quality, and some studies show that living in a socioeconomically disadvantaged neighborhood is associated with worse health outcomes, including reproductive health outcomes. However, no US studies to date have directly examined the association between residence in disadvantaged neighborhoods and fertility. Objective:To examine the association between residence in disadvantaged neighborhoods and fecundability, a sensitive marker of fertility with many health implications. Design, Setting, and Participants:This prospective preconception cohort study used the Pregnancy Study Online, for which baseline data were collected from June 19, 2013, through April 12, 2019. The study included 6356 participants who identified as female, were 21 to 45 years of age, were attempting conception without fertility treatment, and provided a valid residential address in the contiguous US at enrollment. Exposures:A standardized area deprivation index (ADI) derived at the census block group level applied to each residential address. Main Outcomes and Measures:Fecundability, the per-cycle probability of conception, via questionnaires that were completed every 8 weeks for 12 months, until conception or a censoring event. Proportional probabilities models were used to estimate fecundability ratios and 95% CIs for associations between ADI and fecundability. Restricted cubic splines were also implemented to examine nonlinearity. Models were adjusted for demographic characteristics and factors associated with fertility. The study's a priori hypothesis was that higher levels of neighborhood disadvantage would be associated with decreased fecundability. Results:Among 6356 participants, 3725 pregnancies were observed for 27 427 menstrual cycles of follow-up. The mean (SD) baseline age was 30.0 (4.1) years, and most participants were non-Hispanic White (5297 [83.3%]) and nulliparous (4179 [65.7%]). Comparing the top and bottom deciles of disadvantaged neighborhood status, adjusted fecundability ratios were 0.79 (95% CI, 0.66-0.96) for national-level ADI rankings and 0.77 (95% CI, 0.65-0.92) for within-state ADI rankings. Restricted cubic splines showed some evidence of nonlinearity in the association. Associations were slightly stronger among participants with lower annual incomes (<$50 000). Conclusions and Relevance:In this cohort study, residence in a socioeconomically disadvantaged neighborhood was associated with moderately decreased fecundability. If confirmed in other studies, these results suggest that investments to reduce disadvantaged neighborhood status may yield positive cobenefits for fertility.

The coronavirus disease 2019 (COVID-19) pandemic thrust the field of public health into the spotlight. For many epidemiologists, biostatisticians, and other public health professionals, this caused the professional aspects of our lives to collide with the personal, as friends and family reached out with concerns and questions. Learning how to navigate this space was new for many of us and required refining our communication style depending on context, setting, and audience. Some of us took to social media, utilizing our existing personal accounts to share information after sorting through and summarizing the rapidly emerging literature to keep loved ones safe. However, those in our lives sometimes asked unanswerable questions, or began distancing themselves when we suggested more stringent guidance than they had hoped for, causing additional stress during an already traumatic time. We often had to remind ourselves that we were also individuals experiencing this pandemic and that our time-intensive efforts were meaningful, relevant, and impactful. As this pandemic and other public health crises continue, we encourage members of our discipline to consider how we can best use shared lessons from this period and to recognize that our professional knowledge, when used in our personal lives, can promote, protect, and bolster confidence in public health.

The Asian American health narrative reflects a long history of structural racism in the US and the complex interplay of racialized history, immigrant patterns, and policies regarding Asians in the US. Yet owing to systematic issues in data collection including missing or misclassified data for Asian Americans and practices that lead to indiscriminate grouping of unlike individuals (for example, Chinese, Vietnamese, and Bangladeshi) together in data systems and pervasive stereotypes of Asian Americans, the drivers and experiences of health disparities experienced by these diverse groups remain unclear. The perpetual exclusion and misrepresentation of Asian American experiences in health research is exacerbated by three racialized stereotypes-the model minority, healthy immigrant effect, and perpetual foreigner-that fuel scientific and societal perceptions that Asian Americans do not experience health disparities. This codifies racist biases against the Asian American population in a mutually reinforcing cycle. In this article we describe the poor-quality data infrastructure and biases on the part of researchers and public health professionals, and we highlight examples from the health disparities literature. We provide recommendations on how to implement systems-level change and educational reform to infuse racial equity in future policy and practice for Asian American communities.

Older adults are often underrepresented in clinical research, even though older adults are major consumers of novel therapies. We present major themes and recommendations from the 2021 "Inclusion of Older Adults in Clinical Research" Workshop, convened by the Clinical and Translational Science Award (CTSA) Inclusion of Older Adults as a Model for Special Populations Workgroup and the Research Centers Collaborative Network (RCCN). The goal of this workshop was to develop strategies to assist the research community in increasing the inclusion of older adults in clinical research. Major identified barriers include historical lack of federal guidelines, ageist biases and stereotypes, and lack of recruitment and retention techniques or infrastructure focused on older adults. Three key recommendations emerged: 1) engaging with the policymaking process to further promote inclusion; 2) using the CTSA Workgroup Presentation Materials Library and other resources to overcome ageism, and 3) building institutional capacity to support age inclusion.