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.

Background

The transition from the home to college is a phase in which emerging adults shift toward more unhealthy eating and physical activity patterns, higher body mass indices, thus increasing risk of overweight/obesity. Currently, little is understood about how changing friendship networks shape weight gain behaviors. This paper describes the recruitment, data collection, and data analytic protocols for the SPARC (Social impact of Physical Activity and nutRition in College) study, a longitudinal examination of the mechanisms by which friends and friendship networks influence nutrition and physical activity behaviors and weight gain in the transition to college life.

Methods

The SPARC study aims to follow 1450 university freshmen from a large university over an academic year, collecting data on multiple aspects of friends and friendship networks. Integrating multiple types of data related to student lives, ecological momentary assessments (EMAs) are administered via a cell phone application, devilSPARC. EMAs collected in four 1-week periods (a total of 4 EMA waves) are integrated with linked data from web-based surveys and anthropometric measurements conducted at four times points (for a total of eight data collection periods including EMAs, separated by ~1 month). University databases will provide student card data, allowing integration of both time-dated data on food purchasing, use of physical activity venues, and geographical information system (GIS) locations of these activities relative to other students in their social networks.

Discussion

Findings are intended to guide the development of more effective interventions to enhance behaviors among college students that protect against weight gain during college.

Many women are subject to role conflict. Between participating in their jobs and social expectations about duties as a mother, they might experience considerable stress trying to fulfill both those demanding roles. Data was analyzed from 182,617 women in 38 low- and middle-income countries from MICS surveys, using linear regression to examine how a number of children and working status interact to predict life satisfaction and happiness. Having more children was almost always associated with lower life satisfaction and happiness. The only exception was that among women who worked, more children to a point was associated with greater life satisfaction. Notably, work had different associations with emotional well-being depending on how it was measured. Having a job was generally associated with lower happiness, but greater life satisfaction. There is little evidence of an interaction between work and children indicating role conflict. Indeed, for life satisfaction, working seems to counteract the negative effect of having more children. Determining how large the effect of having both children and jobs are in women's lives can help determine the burden placed on women today and how that burden can be alleviated.

With the accelerated emergence of telehealth systems being deployed with promises to access unreachable populations in today’s socially distant environment, it is increasingly important to understand the barriers that underprivileged populations face when trying to access healthcare through digital platforms. This research investigates the use of telehealth in social and cultural sub-populations, focusing on how the diverse student population at Arizona State University (ASU) use the recently-launched ASU Telehealth system. Statistical analysis of demographic factors spanning the five categories of social determinants of health were coupled with population studies of the ASU student body to evaluate the reach of services and patient diversity across telehealth and in person health platforms. Results show that insurance, racial and international student identity influence the percentage of students within these demographic categories Also, though the ASU Telehealth patient body reflects ASU’s general student population, the platform did not increase the reach of Health Services and the magnitude of students served. using ASU Telehealth. Due to the COVID-19 pandemic, it is difficult to determine the validity and reliability of these findings. However, the findings and background research point to targeted marketing campaigns, intentional policy decision-making, post-pandemic telehealth resilience, and the continuation of quantitative and qualitative data collection as means to expand the impact and equity of ASU Telehealth into future iterations of the platform. Outputs of this study include web communication materials and qualitative data collection mechanisms for future use and implementation by ASU Health Services.