Aerobic physical activity and muscle-strengthening activities are beneficial to both physical and mental health, though disparities in these behaviors exist based on social determinants. The purpose of this study was to examine differences in college students' aerobic physical activity and muscle-strengthening activities based on gender, race, and sexual orientation. Undergraduates enrolled in general education health and wellness courses at a large northeastern University in the United States responded to an online survey in August 2018 that assessed their demographics and physical activity behaviors. Differences in physical activity behaviors based on social determinants were examined using independent-samples t-tests and chi-square tests for independence. Less than half (40.3%) of participants (n = 606) met both aerobic physical activity and muscle-strengthening recommendations. No differences were found in physical activity based on sexual orientation. However, significantly more non-Hispanic white participants met aerobic physical activity (74.4% vs. 63.8%) and muscle-strengthening recommendations (47.2% vs. 37.6%); and, men reported significantly greater vigorous physical activity (p = .034, η2 = 0.01) and participation in muscle-strengthening activities (p < .001, η2 = 0.06), and were more likely to meet muscle-strengthening recommendations compared to women (50.8% vs. 41.4%). Findings demonstrate disparities in physical activity based on race and sex, particularly with respect to muscle-strengthening activities. Findings are of concern given the importance of muscle-strengthening activities to both physical and mental health. Colleges should consider ways in which they can facilitate increased participation of racial/ethnic minorities and women in muscle-strengthening activities.
Understanding the relationship between college students’ physical activity (PA) self-monitoring and PA levels has the potential to inform initiatives to promote PA. This study’s purpose was to examine the prevalence of technology-based self-monitoring among college students the potential relationship between device usage, goal setting behaviors, PA enjoyment, and PA levels. An online survey assessed students’ demographics, current PA level, technology-based PA self-monitoring, and psychosocial outcomes. Independent t-tests examined differences in PA level and psychosocial outcomes by device use. 55.5% of the final sample (N=1,154) reported technology-based self-monitoring. Mobile phone app-based PA tracking was the most commonly reported (29.9%), followed by heart rate monitors (23.1%). Device use was significantly related to vigorous PA and psychosocial outcomes. Findings have the potential to inform development of technology-based interventions that promote student PA.
Widespread implementation of Exercise Is Medicine® on Campus (EIM-OC) has the potential to address college student physical inactivity; however, limited research has comprehensively assessed how EIM-OC is operationalized at campuses. Purpose This study aimed to assess EIM-OC implementation and outcomes at various academic institutions. Methods A survey was developed in consultation with key EIM-OC stakeholders and administered online among EIM-OC representatives. Data collected included institutional information; promotion, education, and healthcare system integration; partnerships; challenges; and goals. Descriptive statistics were used to explore institution characteristics and other variables. Thematic analysis was conducted to identify the dominant themes and subthemes in qualitative data collected from open-ended questions. Results Forty-one responses were received from a diverse group of academic institutions ranging in size (<10,000 to >50,000 students) and type (public and private). Campus recreation departments, campus health providers, and student organizations/clubs emerged as the most important partners. Student involvement was critical to the success of many EIM-OC programs, with students involved in a range of roles from promotion (n = 20), leadership/organization/planning (n = 18), education (n = 16), implementation (n = 14), and data collection (n = 10). Implementing the physical activity vital sign emerged as a common challenge, with many institutions having no protocol in place for arranging a follow-up between students and physical fitness professionals after referral acceptances, and no protocol existing for referral declinations. Finally, social media was underused, with no social media platforms used by over a third of programs. Conclusion EIM-OC programs at various institutions experienced similar challenges. This research will serve to inform and improve on the implementation and outcomes of EIM-OC programs and ultimately contribute to helping academic institutions increase the physical activity of students and their local communities.
Summary Researchers, policymakers and clinicians commonly use height and weight to determine body mass index (BMI) and classify weight status. Self‐report measures are widely used but often result in misreported height and weight and, consequentially, underestimation of BMI and—potentially—weight status misclassification. The purpose of this study was to examine differences in objective and self‐reported height, weight and BMI values and to find whether discordance is associated with other anthropometric measures, fitness and physical activity. Data were collected from college students through: (a) a pre‐consultation online questionnaire where participants self‐reported gender, height and weight; (b) an objective fitness assessment that assessed height, weight, body fat percentage, abdominal girth and predicted aerobic fitness; and (c) a post‐assessment electronic survey that assessed physical activity. Parametric and non‐parametric analyses examined differences between groups. Objective and self‐reported height and weight data were collected from 1061 participants, 224 of whom also provided physical activity data. Women significantly under‐reported weight (P = .003, η2 = 0.02), and both genders over‐reported height (P < .001, η2 ≥ 0.07), resulting in a significant difference between BMIs calculated using the different measures (P < .001, η2 ≥ 0.07) and the weight status misclassification of ~15% of participants. Significant differences were found in anthropometrics, fitness and physical activity based on reporting differences for weight (P ≤ .015) and BMI (P ≤ .015). Students demonstrated a tendency to under‐report weight and over‐report height, resulting in weight status misclassification. Those who under‐reported weight tended to be in poorer health as indicated by lower aerobic fitness and higher abdominal girth and body fat percentage in particular. Further research is required to establish the link between under‐reporting weight and over‐reporting physical activity.
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