Association between self-reported Sleep Quality and Body Mass Index among Jimma University Academic Staff: A Structural Equation Modeling

Abstract

Background: According to the World Health Organization report, in 2016, more than 1.9 billion adults were overweight, with more than 650 million being obese. If present trends continue unabated, by 2030, 1.12 and 2.16 billion adults will suffer from obesity and overweight, respectively. Sleep duration and sleep quality has declined simultaneously with the increased prevalence of overweight and obesity, thereby suggesting a potential link. However, there are limited published article showing that poor sleep quality is an independent risk factor to cause obesity for young and older adults in Ethiopia. Methods: An institution based cross sectional study was conducted in Jimma University academic staff. A total of 427 academic staff participated in the study. A two-stage cluster sampling procedure was employed to select study participants by their departments. Height and weight measurements were collected by trained data collectors. Sleep quality was assessed by a reliable self-administered questionnaire. Analysis was done using Stata version13.1.Structural equation modeling using maximum likelihood estimation method was used to analyze the data. Result: The prevalence of poor sleep quality was 32.3% (95% CI: 28.0, 36.9). The mean (±SD) BMI of the respondents was 22.7 (±3.1) kg/m 2 . The study indicated that 23.1% of academician in Jimma University had a BMI of greater than 25 kg/m 2 . The overall prevalence of depression, anxiety, and stress was found to be 25.5%, 44.7%, and 16.62%, respectively. Poor sleep quality has appeared to have an inverse and significant indirect association with BMI (β = -0.08 / P = 0.042), mediated through depression and obsogenic dietary behavior. Conclusion: Poor sleep quality is found to be inversely associated with BMI among Jimma University academic staff. The present findings highlight the interplay between depression, obsogenic eating behavior and poor sleep quality in influencing healthy weight. Future research should test the clinical significance of this observation by tailoring weight management programs according to these characteristics.