Longer sleep improves cardiovascular outcomes: time to make sleep a priority

In this issue of the European Heart Journal, Ai et al.1 address the important question of whether inadequate sleep duration increases risk of cardiovascular outcomes, or whether it is a biomarker of such an increased risk. They further studied the functional form of the association between sleep duration and risk of cardiovascular disease (CVD). They concluded that sleep duration is indeed causally associated with CVD risk, with an ‘L’-, rather than a ‘U’-, shaped association, i.e. that short sleep increases CVD risk while long sleep does not. Indeed, while many studies showed that long sleep duration is associated with increased CVD risk,2,3 there is very little experimental evidence supporting this association. In contrast, the experimental data and mechanisms relating short sleep to CVD more clearly implicate inflammatory and neurohumoral causal mechanisms. The findings of Ai et al. support a causal association of short but not long sleep with several CVDs (hypertension, atrial fibrillation, and ischaemic heart disease, as well as pulmonary embolism). However, an important limitation of the analysis is that fewer genetic variants are associated with long sleep, thus reducing the power of the instrumental variables (IVs) for assessing causal associations. Other important limitations are the use of self-reported sleep data, which may differentially under- and overestimate sleep duration,4 and the generalizability of the sample, which represents a generally healthier population than in the UK. In addition, in interpreting the short sleep duration findings, further information on the causes and subtypes of short sleep duration (e.g. secondary to job demands, associated with insomnia) would help target clinical sleep phenotypes for intervention. Here, we discuss several opportunities that may be pursued in expanding upon findings of causal association between sleep duration and CVD: increasing diversity and generalizability of estimates, employing additional analytical approaches to estimate causal effects, and progressing towards translation of findings to advance public health.

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