In 2009–2010, the prevalence of obesity among U.S. adults was 40%, and the prevalence was 69% among long haul truck drivers. Researchers have not established a clear relationship between working environment and weight among truck drivers. This quantitative cross-sectional study, using an ecological framework, evaluated the relationship between the working environment (sleep performance, food choices, driving environment, and activity level) and weight severity (e.g., body mass index [BMI]) among long haul truck drivers. One hundred and twenty six adults (46 + 10, years of age), including both genders (male = 97 and females = 29) completed an online questionnaire evaluating their weight and work environment. BMI ranged between 19.7– 77.0 (35.4 + 11.0) kg/m2 among respondents. None of the respondents were underweight, 20 were healthy weight, 28 were overweight, and 78 were obese. Using multiple regression analysis, no statistically significant associations were found between the working environment and weight severity. Statistically significant (p < 0.05) mean differences between weight groups were found using a 1-way ANOVA. Regarding physical activity level, there was a statistically significant difference between the overweight and obese Class II groups (M = 1.034, p = .026). There was also a statistically significant difference between the overweight and obese Class III groups (M = -.506, p < 0.001) regarding physical activity within the prior month. The findings of this study support the need for further research to advance the knowledge of associations between weight groups and physical activity among this population, which could promote positive social change by guiding public health officials and trucking industry stakeholders toward effective interventions to reduce BMI among long haul truck drivers.
Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-4138 |
Date | 01 January 2016 |
Creators | Huntley, Charlotte Hughes |
Publisher | ScholarWorks |
Source Sets | Walden University |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Walden Dissertations and Doctoral Studies |
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