Search for: All records

Our lab previously established that repeated exposure to a bitter diet can increase salivary protein (SP) expression, which corresponds to an increase in acceptance of the bitter stimulus. However, this work was exclusively in male rodents, here we examine sex differences. We found that there are no differences in SP expression (experiment 1) or quinine diet acceptance (experiment 2) across stage of estrous cycle. Yet, males and females differ in feeding behaviors, SP expression, and responses to a quinine diet (experiment 3). On a quinine diet, males accepted the diet much faster than females. Males displayed a compensatory increase in meal number as meal size and rate of feeding decreased with initial exposure to a quinine diet, whereas females decreased meal size and rate of feeding with no compensation in meal number. There were sex differences in SP expression at day 14 of quinine exposure but these were gone by day 24. Both sexes increased acceptance of quinine in a brief access taste test after the feeding trial concluded. These data suggest that males and females have different patterns of bitter diet acceptance, but extended exposure to quinine diet still results in altered bitter taste responding and changes in SP profiles in females. 

Abstract Background In clinical research, there has been a call to move beyond individual psychosocial factors towards identifying cultural and social factors that inform mental health. Similar calls have been made in the eating disorders (ED) field underscoring the need to understand larger sociocultural influences on EDs. Discrimination is a social stressor that may influence mental health in similar ways to traumatic or adverse childhood experiences (ACEs). Given the high rates of EDs and discrimination among marginalized groups, it is vital to understand the role of discrimination and ACEs as predictors of ED symptoms in these populations. The aim of this study is to examine how perceived discrimination predicts ED pathology when statistically adjusting for gender, race, and ACEs. Methods The diverse study sample consisted of 331 undergraduate students from a longitudinal cohort study (ages 18–24; 66% female; 35% White/non-Hispanic). Participants completed measures of everyday discrimination, ACEs, and ED pathology. Results Following adjustment for multiple statistical comparisons, the frequency of daily discrimination predicted all ED symptoms above and beyond history of ACEs. In follow-up analyses, number of reasons for discrimination predicted cognitive restraint and purging. Differences in ED symptomatology were found based on the reason for discrimination, gender, and race. Specifically, those who experienced weight discrimination endorsed higher scores on all ED symptoms, and those experiencing gender discrimination endorsed higher body dissatisfaction, cognitive restraint, and restriction. People of color endorsed higher restriction, while female participants endorsed higher scores on all ED symptom with the exception of cognitive restraint. Conclusion Discrimination is a salient risk factor for ED symptoms even when accounting for individuals’ history of ACEs. Future research should utilize an intersectional approach to examine how perceived discrimination affects ED pathology over time. (Word count: 234). 

The COVID-19 pandemic has offered opportunities to immerse high needs 10–14-year-olds in real-life data that matter. We developed and tested an out-of-school program to increase youth understanding of data science through epidemiology. The 15–20-hour Data Detectives Clubs are structured around an adventure novel, The Case of the COVID Crisis, which introduces readers to epidemics across space and time. Chapters are accompanied by activities, discussion, and exploration of infection and vaccine data using CODAP, the Common Online Data Analysis Platform. To date, around 600 youth have experienced the program, focusing primarily on time-series data. Youth learned about noisy data, comparing graphs, and matching rates to cumulative numbers. These clubs demonstrate the feasibility of integrating data science with epidemiology outside of school.