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Sedentary Behavior and Associated Factors Among Working Adults in Eastern Ethiopia
Aboma Motuma1, Tesfaye Gobena2, Kedir Teji Roba1
1School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia.
Abstract:
Background: Sedentary behavior is a major risk factor for non-communicable diseases. Due to changes in lifestyle, sedentary behavior is increasing in sub-Saharan Africa. However, information on the extent of sedentarism among various segments of the population is scant in low-income countries. The objective of this study was to assess the extent of high sedentary behavior and associated factors among working adults in eastern Ethiopia. Methods: A crosssectional study was conducted among 1,164 working adults at Haramaya University from December 2018 to February 2019. Data were collected through face-to-face interviews using the WHO STEPS and sedentary behavior questionnaire. All reported sedentary activities were added to calculate the total number of hours spent on sedentary behavior, which was then dichotomized into two categories. Those who had ≥8 sedentary hours per day were categorized as having high sedentary behavior. The prevalence ratio (PR) with 95% confidence intervals (CIs) was calculated. Factors associated with outcome variables were identified using Poisson regression with a robust variance statistical model. Results: The prevalence of high sedentary behavior was 20.3% (95% CI, 18.0-22.7%) among the study participants. The prevalence of high sedentary behavior was associated with age 45-54 years adjusted PR (APR: 2.00; 95% CI = 1.01-3.97) and 55-64 years (APR: 2.16; 95% CI = 1.03-4.57), being a non-manual worker (APR: 2.11; 95% CI = 1.46-3.05), frequent khat chewers (APR: 1.57; 95% CI = 1.22-2.01), with body mass index of ≥25 kg/m2 (APR: 1.93; 95% CI = 1.53-2.44), and regular alcohol drinker (APR: 1.39; 95% CI = 1.11-1.76). Conclusion: One-fifth of working adults had high sedentary behavior. Factors associated with high sedentary behaviors were older age, being a non-manual worker, substance-use behaviors, and having a high body mass index.
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