C J Bennett1, H Truby1, Z Zia2, S W Cain3, M L Blumfield1. 1. Be Active Sleep Eat (BASE) Facility, Department of Nutrition and Dietetics, School of Clinical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC, Australia. 2. Department of Medicine, School of Clinical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC, Australia. 3. Faculty of Medicine, Nursing and Health Sciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia.
Abstract
BACKGROUND/ OBJECTIVE: Reduced sleep is a strong and independent risk factor for weight gain and obesity. Maternal obesity preconception and throughout gestation can increase the risk of adverse pregnancy outcomes and impact on offspring health in later life. This study investigated the relationship between sleeping behaviour and macronutrient intake in childbearing aged women. SUBJECTS/ METHODS: We used cross-sectional data from the Australian Longitudinal Study on Women's Health 1973-78 cohort, aged 31-36 years in 2009 (n=8200). Subjective sleeping behaviour was reported and macronutrient intake was measured using a validated food frequency questionnaire. Latent class analysis (LCA) was used to derive sleeping patterns. Multivariate regression analysis was used to investigate the relationships between sleep and macronutrient intake. RESULTS: LCA identified three sleep patterns: (LC1) average sleep (~8 h) with no adverse sleep-related symptoms (n=3570); (LC2) average sleep (~8 h) with sleeping difficulties and severe tiredness (n=2109); and (LC3) short sleep (~6 h) with sleeping difficulties and severe tiredness (n=915). In fully adjusted models, LC2 was inversely associated with percentage energy as protein (b=-0.24; P=0.01) and the protein-to-carbohydrate ratio (b=-0.01; P<0.05). LC3 was positively associated with percentage of energy as fat (b=0.29; P=0.01), saturated fat (b=0.24; P=<0.001) and monounsaturated fat (b=0.09; P=0.04). CONCLUSIONS: Sleeping behaviour patterns were associated with macronutrient intake in childbearing aged women. Improved sleep patterns, together with diet and physical activity strategies, may make it easier for women to achieve a balanced diet and optimise their weight status in preparation for pregnancy.
BACKGROUND/ OBJECTIVE: Reduced sleep is a strong and independent risk factor for weight gain and obesity. Maternal obesity preconception and throughout gestation can increase the risk of adverse pregnancy outcomes and impact on offspring health in later life. This study investigated the relationship between sleeping behaviour and macronutrient intake in childbearing aged women. SUBJECTS/ METHODS: We used cross-sectional data from the Australian Longitudinal Study on Women's Health 1973-78 cohort, aged 31-36 years in 2009 (n=8200). Subjective sleeping behaviour was reported and macronutrient intake was measured using a validated food frequency questionnaire. Latent class analysis (LCA) was used to derive sleeping patterns. Multivariate regression analysis was used to investigate the relationships between sleep and macronutrient intake. RESULTS: LCA identified three sleep patterns: (LC1) average sleep (~8 h) with no adverse sleep-related symptoms (n=3570); (LC2) average sleep (~8 h) with sleeping difficulties and severe tiredness (n=2109); and (LC3) short sleep (~6 h) with sleeping difficulties and severe tiredness (n=915). In fully adjusted models, LC2 was inversely associated with percentage energy as protein (b=-0.24; P=0.01) and the protein-to-carbohydrate ratio (b=-0.01; P<0.05). LC3 was positively associated with percentage of energy as fat (b=0.29; P=0.01), saturated fat (b=0.24; P=<0.001) and monounsaturated fat (b=0.09; P=0.04). CONCLUSIONS: Sleeping behaviour patterns were associated with macronutrient intake in childbearing aged women. Improved sleep patterns, together with diet and physical activity strategies, may make it easier for women to achieve a balanced diet and optimise their weight status in preparation for pregnancy.
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