Does sleep grow on trees? A longitudinal study to investigate potential prevention of insufficient sleep with different types of urban green space

Abstract

Introduction: To investigate association between urban green space and prevalent and incident cases of insufficient sleep (<6 h sleep per day).

Methods: This longitudinal study examined the odds of prevalent and incident insufficient sleep in relation to indicators of total green space, tree canopy, open grass and other low-lying vegetation in the Sax Institute's 45 and Up Study (baseline 2006-2009; follow-up 2012-2015). Association between green space within 1.6 km road distances and insufficient sleep among 38,982 participants living in Sydney, Wollongong or Newcastle were analysed using multilevel logistic regressions adjusted for confounding.

Results: Participants with more total green space had lower odds of prevalent insufficient sleep (e.g. ≥30% compared with 0-4% total green space odds ratio (OR) = 0.68, 95% credible interval (95%CI) = 0.53, 0.85). The odds of prevalent insufficient sleep were lower among participants with more tree canopy (e.g. ≥30% compared with 0-9% tree canopy OR = 0.78, 95%CI 0.69, 0.88). The odds of incident insufficient sleep were also lower with more tree canopy (e.g. ≥30% compared with 0-9% tree canopy OR = 0.87, 95%CI = 0.75, 0.99). There were no statistically significant associations between prevalent or incident insufficient sleep with open grass or other low-lying vegetation, nor incident sufficient sleep with total green space.

Conclusions: Prioritising restoration and protection of urban tree canopy may help to promote population-wide prevention of insufficient sleep in middle-to-older aged adults.

Keywords: 45 and Up Study; Australia; Longitudinal study; Open grass; Sleep duration; Tree canopy; Urban green space.

Fig. 1

Odds of prevalent and incident short sleep durations in association with total (A) urban green space, (B) tree canopy, and (C) open grass: multilevel logistic regressions adjusted for confounding and estimated using Markov Chain Monte Carlo method. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)