Objective To examine the prevalence of food insecurity and associations with health outcomes among college freshmen. Methods A diverse sample of freshmen (n=209) attending a large southwestern university and living in campus residence halls completed online surveys; anthropometrics were measured by trained staff. Using mixed logistic regression, associations were examined between food insecurity and health outcomes, adjusting for sociodemographics and clustering of students within residence halls. Results Food insecurity was prevalent, with 32% reporting inconsistent access to food in the past month and 37% in the past three months. Food insecure freshmen had higher odds of depression (OR=2.97; 95% CI=1.58, 5.60) compared to food secure students. Food insecure freshmen had significantly lower odds of eating breakfast, consuming home-cooked meals, perceiving their off-campus eating habits to be healthy, and receiving food from parents, (p<0.05). Conclusions Interventions are needed to support students struggling with food insecurity, as it is related to health outcomes.

BackgroundThe majority of nutrition and physical activity assessments methods commonly used in scientific research are subject to recall and social desirability biases, which result in over- or under-reporting of behaviors. Real-time mobile-based ecological momentary assessments (mEMAs) may result in decreased measurement biases and minimize participant burden.ObjectiveThe aim was to examine the validity of a mEMA methodology to assess dietary and physical activity levels compared to 24-hour dietary recalls and accelerometers.MethodsThis study was a pilot test of the SPARC (Social impact of Physical Activity and nutRition in College) study, which aimed to determine the mechanism by which friendship networks impact weight-related behaviors among young people. An mEMA app, devilSPARC, was developed to assess weight-related behaviors in real time. A diverse sample of 109 freshmen and community mentors attending a large southwestern university downloaded the devilSPARC mEMA app onto their personal mobile phones. Participants were prompted randomly eight times per day over the course of 4 days to complete mEMAs. During the same 4-day period, participants completed up to three 24-hour dietary recalls and/or 4 days of accelerometry. Self-reported mEMA responses were compared to 24-hour dietary recalls and accelerometry measures using comparison statistics, such as match rate, sensitivity and specificity, and mixed model odds ratios, adjusted for within-person correlation among repeated measurements.ResultsAt the day level, total dietary intake data reported through the mEMA app reflected eating choices also captured by the 24-hour recall. Entrées had the lowest match rate, and fruits and vegetables had the highest match rate. Widening the window of aggregation of 24-hour dietary recall data on either side of the mEMA response resulted in increased specificity and decreased sensitivity. For physical activity behaviors, levels of activity reported through mEMA differed for sedentary versus non-sedentary activity at the day level as measured by accelerometers.ConclusionsThe devilSPARC mEMA app is valid for assessing eating behaviors and the presence of sedentary activity at the day level. This mEMA may be useful in studies examining real-time weight-related behaviors.

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Objective To perform a factor analysis of the Practice Integration Profile (PIP), a 30‐item practice‐level measure of primary care and behavioral health integration derived from the Agency for Healthcare Research and Quality's Lexicon for Behavioral Health and Primary Care Integration. Data Sources The PIP was completed by 735 individuals, representing 357 practices across the United States. Study Design The study design was a cross‐sectional survey. An exploratory factor analysis and assessment of internal consistency reliability via Cronbach's alpha were performed. Data Collection Methods Participant responses were collected using REDCap, a secure, web‐based data capture tool. Principal Findings Five of the PIP's six domains had factor loadings for most items related to each factor representing the PIP of 0.50 or greater. However, one factor had items from two PIP domains that had loadings >0.50. A five‐factor model with redistributed items resulted in improved factor loadings for all domains along with greater internal consistency reliability (>0.80). Conclusions Five of the PIP's six domains demonstrated excellent internal consistency for measures of health care resources. Although minor improvements to strengthen the PIP are possible, it is a valid and reliable measure of the integration of primary care and behavioral health.

College populations are groups of emerging adults undergoing significant transitions in eating and diet, being exposed to new social influences; many experience weight gain. Theoretically, college campuses should be places where weight stigma is evident and matters for dietary decision-making. We present the findings from two studies conducted within the same college population at a large public university, including anthropometric measures of body mass. Study 1 included two different measures of weight stigma (implicit and explicit) and measures of weight-control eating behaviors and fruit and vegetable consumption in a randomized representative sample of 204 students. Study 2 included a measure of weight responsibility and multiple measures of eating (food frequency, alcohol intake, and 24-hour dietary recalls), among freshman students (n = 202, n = 157 with 24-hour dietary recalls). Study 1 showed that the three types of stigmas were prevalent. Study 2 had a high prevalence of weight stigma attitudes and demonstrated the occurrence of unhealthful eating and binge drinking behaviors. Both studies found no relationship between weight stigma/responsibility and eating behaviors regardless of weight status. Beyond considering limitations of the study design, we propose two possible reasons for college students' relative immunity to the effects of weight stigma. Those with very high levels of stigma could be suppressing stigmatizing attitudes based on what they think others think is acceptable in a liberal college setting, or the chaotic form of “normal” eating in this population hides the effects of weight stigma.