Pamela L Maynard1, James E Rohrer2, Lawrence Fulton3. 1. William Woods University, Fulton, MO, USA pamela.maynard@williamwoods.edu. 2. Mayo Clinic, Rochester, MN, USA. 3. Walden University, Minneapolis, MN, USA.
Abstract
BACKGROUND AND OBJECTIVES: Online university students are a growing population whose health has received minimal attention. The purpose of this cross-sectional Internet survey was to identify risk factors for the health status among online university students. METHODS: This online survey collected data from 301 online university students through a large, US-based participant pool and LinkedIn. Health status was measured using 3 elements of health-related quality of life (HRQOL): self-rated overall health (SRH), unhealthy days, and recent activity limitation days. All 3 measures were dichotomized. RESULTS: The odds of poor SRH were higher for people who reported a body mass index in the overweight and obese categories (odds ratio [OR] = 2.99, P < .05) and for those who reported being smokers (OR = 2.52, P = .03). The odds of frequent unhealthy days were lower for those who made more than $35 000 compared with those who reported making less (OR = 0.50, P = .03) and those who exercised 4 or more times a week compared with those who exercised less (OR = 0.28, P < .05). The odds of frequent activity limitation were lower for those who reported an income of more than $35 000 (OR = 0.29, P = .04) and higher for persons who reported belonging to "other" race (OR = 14.75, P = .00). CONCLUSIONS: Universities might fruitfully target health promotion programs for online students who are low income, in disadvantaged racial groups, who are overweight, smoke, and who do not exercise.
BACKGROUND AND OBJECTIVES: Online university students are a growing population whose health has received minimal attention. The purpose of this cross-sectional Internet survey was to identify risk factors for the health status among online university students. METHODS: This online survey collected data from 301 online university students through a large, US-based participant pool and LinkedIn. Health status was measured using 3 elements of health-related quality of life (HRQOL): self-rated overall health (SRH), unhealthy days, and recent activity limitation days. All 3 measures were dichotomized. RESULTS: The odds of poor SRH were higher for people who reported a body mass index in the overweight and obese categories (odds ratio [OR] = 2.99, P < .05) and for those who reported being smokers (OR = 2.52, P = .03). The odds of frequent unhealthy days were lower for those who made more than $35 000 compared with those who reported making less (OR = 0.50, P = .03) and those who exercised 4 or more times a week compared with those who exercised less (OR = 0.28, P < .05). The odds of frequent activity limitation were lower for those who reported an income of more than $35 000 (OR = 0.29, P = .04) and higher for persons who reported belonging to "other" race (OR = 14.75, P = .00). CONCLUSIONS: Universities might fruitfully target health promotion programs for online students who are low income, in disadvantaged racial groups, who are overweight, smoke, and who do not exercise.