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.
Existing research has shown that both ethnic discrimination and household wealth can shape child well-being and development. However, little work examines ethnic discrimination and its relation to income in predicting childhood health globally. This study explores two possible explanations for disparities in infant mortality between ethnic groups across countries worldwide. The first is an explanation based on wealth differentials across ethnic groups. The second is the impact of forms of ethnic discrimination such as past lethal violence or forced labor experienced by the group. This study examines the correlation between ethnic discrimination and infant mortality using household wealth as a covariate. Analyses focused on 266 ethnicities in 40 low- and middle-income countries globally, drawing on infant mortality data from Demographic and Health Surveys and data on ethnic discrimination compiled by the Inclusive Human Learning Lab at Arizona State University. Findings without the inclusion of household wealth show that ethnic groups that predominantly spoke the state language had significantly lower rates of infant mortality. However, this trend disappears when income is added as a covariate. No other measures of discrimination or privilege were associated with infant mortality. Across all analyses, the wealth of the ethnic group was a significant predictor of infant mortality. Future studies should examine whether these trends persist in high-income countries, and whether the general lack of association of discrimination and privilege variables with infant mortality is influenced by how the variables were coded.