The incidence of childhood obesity has become increasingly prevalent in the United States in recent years. The development of obesity at any age, but especially in adolescence, can have lasting negative effects in the form of cardiometabolic disease, increased incurred healthcare costs, and potential negative effects on quality of life. In recent years, a rising trend of obesity, in both adults and adolescents, has been observed in lower income and ethnic groups. Increased adiposity can be influenced by modifiable factors -(physical activity, caloric intake, or sleep) or by non-modifiable factors (ethnicity, genetic predispositions, and socioeconomic status). The influence of these factors can be observed in individuals of all ages, including infants. A common indicator of the development of childhood obesity is rapid weight gain (RWG) within an infant’s first year of life. The composition of the gut microbiome can act as a predictor for RWG and the development of childhood obesity. Infants are exposed to an immense microbial load when they are born and their gut microbiome is continually diversified through their method of feeding and the subsequent introduction to solid foods. While currently understudied, it is understood that cultural and socioeconomic factors influence the development of the gut microbiome, which is further explored in this analysis. The DNA from 51 fecal samples from infants ranging from 3 weeks to 12 months in age was extracted and sequenced using next-generation sequencing, and the resulting sequences were analyzed using QIIME 2. Results from alpha-diversity and beta-diversity metrics showed significant differences in the gut microbiome of infants when comparing groups based on baby race/ethnicity, household income, and mom’s education. These findings suggest the importance of sociodemographic characteristics in shaping the gut microbiome and suggest the importance of future studies including diverse populations in gut microbiome work.

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.