We have found a robust and novel association between objectively measured sleep duration and five-year incidence of coronary artery calcification. One hour more sleep decreased the estimated odds of calcification by 33%. shows that the (unadjusted) dose-response relationship held up across the range of measured sleep; the lack of significant heterogeneity by race or sex strengthened this finding. Controlling for potential confounders and mediators did not greatly attenuate the relationship, as seen by multiply-adjusted odds-ratios ranging only between 0.64 and 0.68 and significant adjusted p-values. While this is surprising, there exists a large amount of unexplained variance in cardiac outcomes and hence potential for previously unidentified risk factors. The magnitude of the observed effect was similar to sizable differences in established coronary risk factors, e.g. one additional hour sleep reduced risk similarly to a reduction of 16.5 mmHg systolic blood pressure.
Our study has several limitations. First, too few participants had calcification at baseline for us to examine the rate of further calcification among them. Second, our first wave of sleep measures was taken more than halfway through the period between baseline and follow-up. While calcification may have occurred before sleep measurements, there is no obvious reverse causation mechanism. Finally, actigraphy is unable to measure potentially important dimensions of sleep such as sleep stages, which may underlie the apparent association between duration and calcification. Sleep quality is multidimensional, and there is no perfect metric for measuring it; the apnea-hypopnea index from polysomnography is probably the closest to a “gold standard.” Actigraph-measured fragmentation has not been widely used in research, although one recent study did find a significant correlation between it and obesity in the elderly [33
]. How actigraphic fragmentation relates to other measures of sleep quality remains unclear.
However, actigraphy provides several advantages compared to self-reported sleep. Previous data indicate that self reported sleep is only weakly correlated to total sleep time from polysomnography (r = 0.16) [12
] but that actigraphy is highly correlated to polysomnography total sleep time (r > 0.90) [19
]. Actigraphy measured sleep has been shown to be relatively stable year-to-year in this cohort [34
], indicating that our measure likely represents sleep duration throughout the study. Actigraphy avoids potential biases in self-reported sleep duration caused by the perception of fatigue in states of poor health [14
While some participants at risk do not have follow-up data (), we do not see evidence that omitting them is likely to affect our conclusions. There were a few significant differences between those with follow-up scans and those without, but we adjust for these factors in regression analysis. Importantly, the mean measured and self-reported sleep levels were very similar between those with and without follow-up data.
Because of the well-established association between apnea and cardiac outcomes [35
], our lack of a clinical apnea diagnosis is the study’s main limitation. We used the Berlin Questionnaire to identify high-risk individuals. For apnea to bias our results away from the null hypothesis, apnea must be more prevalent among individuals with short sleep duration, and the Berlin Questionnaire must be so inaccurate as to leave significant residual confounding. Different studies have reported both longer and shorter sleep durations for apnea patients [38
]. The Berlin Questionnaire has been found to have high sensitivity (0.86) and moderate specificity (0.77) [23
], meaning our high-risk group should include almost all of the persons with apnea and a moderate number without. If we stratify by apnea risk, however, the sleep effect among those with low apnea risk is quite similar to the effect in the whole sample (0.72, 95% CI 0.2, 1.01), suggesting that residual apnea confounding is not likely to be responsible for our positive results. The small effect of apnea risk on incidence in is likely a result both of the inclusion of persons without apnea in the high-risk group and also the large effect on baseline prevalence; that is, persons with apnea were not in our “at-risk” cohort because they had already developed calcification before baseline.
Calcification as an endpoint also has strengths and weaknesses. Calcification tends to increase over time [32
] and is a potent risk factor for coronary events [2
]. By observing persons in early middle-age we have reduced the possibility that unmeasured health problems confound the association [14
]. However, early calcification is not a clinical outcome and coronary events may not necessarily follow.
We have not been able to find previous literature directly relating sleep and calcification. However, we note that previous studies have established a relationship between self-reported sleep duration and related outcomes, such as hypertension [8
] and coronary events [44
]. Sleep apnea has been linked to calcification in a clinical population [35
] as well as to heart disease in population-based cohorts [36
]. Contrary to others [43
], we find no evidence of a U-shaped relationship. However, such a relationship might be impossible to find in this study population because so few had more than eight hours measured sleep. Also, our sleep measurement avoided the potential problem that self-reports of long sleep are confounded by health factors [14
]. Finally, the long sleep-cardiac outcome association could be a feature that emerges at older ages.
We highlight three possible mechanisms to explain this association. First, the determinants of sleep duration are poorly understood, although socioeconomic correlations [10
] exist. There may be unknown common factors predicting both sleep and calcification. Second, we may have been unable to adequately assess mediating mechanisms. Our inflammatory marker data are incomplete; fibrinogen and interleukin-6 were available only at follow-up. Cortisol profiles, which have been correlated to both calcification [45
] and sleep [46
], were not investigated. More frequent measurements may be needed to capture the activity of hypothesized mediators. For example, transient decreases in glucose tolerance following evenings of short sleep [47
] might not be detected at either examination. Third, unmeasured diurnal variation of calcification pathways may be at work. For example, blood pressure declines during sleep [48
] and significantly predicts [4
] calcification incidence.
Future studies will be needed for crucial extensions to these result. First, these results need confirmation in other cohorts. Second, does sleep moderate the rate at which calcification accumulates? Third, will objective sleep tie to coronary disease event outcomes over the long term? While calcification predicts such outcomes, it is difficult to know how and if the predictors of calcification themselves will determine outcomes, or if their impact will be purely mediated by their effect on calcification. Finally, if this association is born out, interventional studies will be needed to guide clinical advice.