Author(s)

Helen Fowler, George T. H. Ellison, Eleanor M. Scott, Graham R. Law

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Temporal Influences on Metabolic Events (TIME) Research Group, Division of Epidemiology and Biostatistics, Leeds Institute of Genetics, Health and Therapeutics (LIGHT), University of Leeds, Leeds, UK.

Aims: To establish the relationship between household composition and sleep, we: 1) used latent class analysis (LCA) to classify households; 2) examined the reliability and stability of household composition classes over time; 3) conducted multinomial logistic regression analyses to determine the relationship between household class and the self-reported sleep duration and quality of adults. Methods: Data were sourced from Waves 1 and 2 of the United Kingdom “Understanding Society” (USoc) longitudinal panel survey. LCA was used to classify household composition as a categorical latent construct using data on the number and ages of household occupants and the number of rooms used for sleeping. The Bayesian Information Criterion assessed model fit and identified the optimum number of latent classes. Multi-nomial logistic regression was used to investigate cross-sectional relationships between the household classes and self-reported sleep duration and quality amongst adults, after adjustment for confounders. Results: Household composition was best defined by 7 latent classes in data from Wave 1 of USoc. This finding was confirmed in Wave 2. Compared to the reference class (households with no children and no overcrowding), there was a higher risk of short sleep (≤5 hours) versus 7-8 hours sleep for latent household composition classes that included children (RR: 1.56; 95% CI: 1.29-1.89) and for those with both children and overcrowding (RR: 1.57; 95% CI: 1.31-1.88). Similarly the risk of “very bad” versus “fairly good” quality sleep was significantly higher in those household classes with overcrowding, particularly those with extended (RR: 1.75; 95% CI: 1.34-2.29) and large (RR: 1.51; 95% CI: 1.21-1.87) households. Conclusion: These analyses of a recent, nationally representative cohort from the UK, demonstrated that latent household composition classes are reliable over time; and that these latent household composition classes are important correlates of self-reported sleep amongst adult occupants. We showed that household composition is an important contextual variable to consider in most epidemiological studies of sleep.

Latent Class Analysis; Household Composition; Children; Overcrowding; Sleep

Fowler, H. , T. H. Ellison, G. , M. Scott, E. and R. Law, G. (2014) The importance of household composition in epidemiological analyses of sleep: Evidence from the Understanding Society longitudinal panel survey. Open Journal of Epidemiology, 4, 46-55. doi: 10.4236/ojepi.2014.41009.