Sleep quality subtypes and obesity

Magee, CA; Reddy, P; Robinson, L; McGregor, A

Sleep quality subtypes and obesity

Magee, CA Reddy, P

Robinson, L McGregor, A

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Publication Type:: Journal Article
Citation:: Health Psychology, 2016, 35 (12), pp. 1289 - 1297
Issue Date:: 2016-12-01

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Field	Value	Language
dc.contributor.author	Magee, CA	en_US
dc.contributor.author	Reddy, P https://orcid.org/0000-0002-0709-9352	en_US
dc.contributor.author	Robinson, L	en_US
dc.contributor.author	McGregor, A	en_US
dc.date.issued	2016-12-01	en_US
dc.identifier.citation	Health Psychology, 2016, 35 (12), pp. 1289 - 1297	en_US
dc.identifier.issn	0278-6133	en_US
dc.identifier.uri	http://hdl.handle.net/10453/99274
dc.description.abstract	© 2016 American Psychological Association. 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.	en_US
dc.relation.ispartof	Health Psychology	en_US
dc.relation.isbasedon	10.1037/hea0000370	en_US
dc.subject.classification	Public Health	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Sleep Deprivation	en_US
dc.subject.mesh	Obesity	en_US
dc.subject.mesh	Body Mass Index	en_US
dc.subject.mesh	Exercise	en_US
dc.subject.mesh	Risk Factors	en_US
dc.subject.mesh	Qualitative Research	en_US
dc.subject.mesh	Adult	en_US
dc.subject.mesh	Middle Aged	en_US
dc.subject.mesh	Australia	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Interviews as Topic	en_US
dc.subject.mesh	Waist Circumference	en_US
dc.subject.mesh	Self Report	en_US
dc.subject.mesh	Surveys and Questionnaires	en_US
dc.subject.mesh	Sleep Wake Disorders	en_US
dc.title	Sleep quality subtypes and obesity	en_US
dc.type	Journal Article
utslib.citation.volume	12	en_US
utslib.citation.volume	35	en_US
utslib.for	1117 Public Health and Health Services	en_US
utslib.for	11 Medical and Health Sciences	en_US
utslib.for	13 Education	en_US
utslib.for	17 Psychology and Cognitive Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Management Discipline
utslib.copyright.status	closed_access
pubs.issue	12	en_US
pubs.publication-status	Published	en_US
pubs.volume	35	en_US

Abstract:

© 2016 American Psychological Association. 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.

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http://hdl.handle.net/10453/99274