OBJECTIVE: Poor sleep quality could be a risk factor for obesity. This article utilized a person-centered approach to investigate whether distinct sleep quality subtypes were associated with obesity directly, and indirectly via physical activity. METHOD: The sample included 8,932 Australian employees who participated in the Household, Income and Labor Dynamics in Australia Survey. Structured interviews and self-report questionnaires collected information on sleep quality, obesity, and relevant demographic, health, and work-related variables. Latent class analysis identified distinct subtypes of sleep quality. General linear modeling examined the associations of sleep quality subtypes with body mass index (BMI) and waist circumference. Multicategorical mediation models examined indirect paths linking sleep quality classes with obesity via physical activity. RESULTS: Five distinct sleep quality subtypes were identified: Poor Sleepers (20.0%), Frequent Sleep Disturbances (19.2%), Minor Sleep Disturbances (24.5%), Long Sleepers (9.6%), and Good Sleepers (26.7%). BMI, waist circumference, and physical activity differed among the sleep quality subtypes, with similar results observed for males and females. For example, Poor Sleepers had the highest BMIs, followed by Frequent Sleep Disturbances and Minor Sleep Disturbances; Long Sleepers and Good Sleepers had the lowest BMIs. Mediation analyses indicated that low levels of physical activity linked the Poor Sleep, Frequent Sleep Disturbance, and Long Sleep classes with higher BMI. CONCLUSIONS: These results provide new insights into the nature of sleep quality in employees. In particular, distinct sleep quality patterns had differing associations with measures of obesity, suggesting the need for tailored workplace interventions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
OBJECTIVE: Poor sleep quality could be a risk factor for obesity. This article utilized a person-centered approach to investigate whether distinct sleep quality subtypes were associated with obesity directly, and indirectly via physical activity. METHOD: The sample included 8,932 Australian employees who participated in the Household, Income and Labor Dynamics in Australia Survey. Structured interviews and self-report questionnaires collected information on sleep quality, obesity, and relevant demographic, health, and work-related variables. Latent class analysis identified distinct subtypes of sleep quality. General linear modeling examined the associations of sleep quality subtypes with body mass index (BMI) and waist circumference. Multicategorical mediation models examined indirect paths linking sleep quality classes with obesity via physical activity. RESULTS: Five distinct sleep quality subtypes were identified: Poor Sleepers (20.0%), Frequent Sleep Disturbances (19.2%), Minor Sleep Disturbances (24.5%), Long Sleepers (9.6%), and Good Sleepers (26.7%). BMI, waist circumference, and physical activity differed among the sleep quality subtypes, with similar results observed for males and females. For example, Poor Sleepers had the highest BMIs, followed by Frequent Sleep Disturbances and Minor Sleep Disturbances; Long Sleepers and Good Sleepers had the lowest BMIs. Mediation analyses indicated that low levels of physical activity linked the Poor Sleep, Frequent Sleep Disturbance, and Long Sleep classes with higher BMI. CONCLUSIONS: These results provide new insights into the nature of sleep quality in employees. In particular, distinct sleep quality patterns had differing associations with measures of obesity, suggesting the need for tailored workplace interventions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Authors: Sheng Wang; Xianghong Zhou; Shi Qiu; Boyu Cai; Yifan Li; Chichen Zhang; Kunjie Wang; Lu Yang; Lei Chen Journal: BMC Public Health Date: 2022-09-20 Impact factor: 4.135