Using actigraphy, an objective sleep measurement, we confirmed the cross-sectional association between shorter sleep duration and higher BMI that has been reported in previous studies relying on self-reported sleep duration. However, we find no evidence that sleep duration influences weight change over 5 years. Our findings advance the evidence about sleep and weight in several additional ways: 1) Markers of socioeconomic status (race and education) strongly confound the cross-sectional association. 2) Sleep fragmentation, an index of restlessness, is also associated with BMI in the cross-sectional analysis. Few prior studies have considered measures of sleep quality. Because fragmentation and duration, both estimated from actigraphy, are strongly inversely correlated, their effects cannot be untangled. 3) Snoring is an effect modifier of the cross-sectional association. The sleep duration-BMI association observed across the entire sample is mostly due to the strong association among the subset who report snoring.
Despite substantial evidence of a cross-sectional correlation between BMI and sleep duration, such data do not prove causality. Far fewer studies have investigated the prospective association, which would provide more compelling evidence. The paucity of studies is primarily because so few cohorts have sleep information. In the First National Health and Nutrition Examination Survey (NHANES I), there was a cross-sectional association, but only among those aged 32–49 years (10
). Sleep duration did not significantly predict change in BMI over 8–10 years (n
3,208). The effect was in the hypothesized direction but was not adjusted for baseline BMI. In the Nurses’ Health Study, women aged 39–65 years (n
68,183) were followed up to 16 years or to the age of 65 years (8
). After adjustment for baseline BMI and confounders, self-reported sleep durations of less than 7 hours were significantly associated with slightly greater weight gain: Those reporting ≤5 hours and 6 hours gained, on average, 0.73 kg and 0.26 kg more than those reporting 7 hours. Although all participants were registered nurses, there may have been residual socioeconomic confounding, because education and household income do vary among nurses (22
). In the Whitehall II cohort of British civil servants aged 35–55 years at baseline (n
4,378), there was a significant cross-sectional association but no longitudinal association for changes in BMI, waist circumference, or incident obesity (12
), similar to results from our study. These studies did not examine effect modification by snoring or apnea.
Two smaller studies with self-reported sleep hours were longitudinal. In a study of 496 adults oversampling persons with psychological problems, information on sleep hours, height, and weight was collected at ages 27, 29, 34, and 40 years (11
). The primary analysis focused on testing a durable cross-sectional association rather than a longitudinal trajectory: Sleep duration was associated with concurrent, previous, and later obesity. The data do not clarify the causal direction: The odds ratios between sleep duration and previous obesity are slightly higher than those with later obesity. In a study of 276 adults aged 21–64 years, from families oversampled for obesity, short sleepers (5–6 hours, 15% of the sample) and long sleepers (9–10 hours, 13% of the sample) gained more weight over 6 years than did average sleepers (6
). In an adjusted model, the greater weight gain was 1.8 kg for short sleepers and 1.5 kg for long sleepers relative to average sleepers.
One prior study among adults examined the cross-sectional association with actigraphy among 983 persons aged 57–97 years in the Netherlands (8
). In contrast to our younger US sample, 28% of the Dutch population had 8 hours or more of actigraph-estimated sleep. Duration and fragmentation were estimated with an average of 6 nights of actigraphy. There was a quadratic association between sleep duration and BMI, but the higher BMI at the low end of sleep duration was not significant when adjusted for fragmentation.
Interest in sleep duration and BMI has been heightened by the discovery of a potential biologic mechanism—sensitivity of the appetite-regulating hormones leptin and ghrelin to sleep duration. Laboratory studies find that restricting sleep to 4 hours suppresses leptin and increases ghrelin; it also increases perceptions of hunger (23
). The Wisconsin Sleep Cohort Study also found that ghrelin levels were responsive to a single night in a sleep laboratory, while leptin levels correlated with self-reported habitual sleep (7
). However, in the Rancho Bernardo cohort, leptin and ghrelin levels did not predict weight change (25
). In an exercise intervention for overweight women, there was no baseline association between self-reported sleep and ghrelin or leptin. Those who reported improved sleep quality actually had relatively higher ghrelin and lower leptin levels (26
). If leptin and ghrelin explain the effect of sleep on BMI, increased caloric consumption should be on the causal pathway. Sleep studies that have included questions about diet (or physical activity) have not found this (2
); however, diet and physical activity are difficult to measure.
The opposite causal direction is also plausible, that obesity reduces sleep duration or quality. Obesity is the major risk factor for apnea, which interrupts sleep with arousals prompted by oxygen desaturation (27
). However, obese persons without apnea also have disturbed sleep and report greater daytime sleepiness (28
). Poor sleep quality tends to cause persons to report shorter sleep than persons with better sleep quality who have the same amount of measured sleep (14
), presumably because their sleepiness influences their estimate of sleep duration. The 2 causal directions are not necessarily mutually exclusive.
While our objective sleep measurement is an improvement on most prior studies, there is no measurement method that is both perfectly accurate and nondisruptive. The “gold standard” is polysomnography, but it requires a technician and multiple sensors, both of which may affect routine behavior. Actigraphy's advantage is low respondent burden that does not alter sleep behavior, as there is no “first night effect” (30
). Many prior studies have compared actigraphy with concurrent polysomnography in a sleep laboratory. In a comprehensive review, correlations for sleep duration were over 0.9 in healthy adults (30
). Some of the discrepancy is because the 2 methods key into different points in the sleep onset process. Nor is polysomnography perfectly reliable, particularly for identifying shallow stage 1 sleep (34
). Almost all previous epidemiologic studies have relied on self-reported habitual sleep, which does not correlate highly with either polysomnography or actigraphy. In the Sleep Heart Health Study, the correlation between a single night of home polysomnography and previously reported habitual sleep was only 0.18 (13
). In the CARDIA Sleep Study, we used a measurement-error model to evaluate the correlation between self-reported habitual sleep and 3 nights of actigraphy and found a correlation of 0.47 (14
). We also found that obese persons systematically reported less sleep than the nonobese at the same level of measured sleep.
There were challenges in actigraphy data collection. Most participants forgot to press the event marker at least once, but almost all provided backup data in their sleep log. When both were missing (fewer than 5% of bedtimes or waketimes), we used a discernible decline or increase in activity to mark the beginning or end of the period scanned for sleep. A few “actiwatches” were not mailed back (even after reminders); this occurred more often in the second wave, perhaps because the personal sleep report was less of an inducement the second time. Some participants did not wear the actiwatch the exact days requested. We included 2 weeknights and 1 weekend night in each wave, but we did not know participants’ actual work schedules. We designed our study with 2 waves of data collection, allowing us to determine that day-to-day variability was high but year-to-year variability was low. Based on this data collection experience, we would collect a single 7-day period in future studies.
Another limitation is our reliance on self-reported snoring in lieu of a clinical apnea diagnosis. Snoring is a highly sensitive, but not very specific, marker of obstructive sleep apnea, resulting in moderate positive predictive value (35
). Some persons are unaware that they snore. It is unclear whether the snoring effect modification would be stronger or weaker if we knew apnea status. We are unaware of previous studies that have found that snoring predicts weight gain, although snoring ascertained at the end of the study period was associated with greater weight gain over 10 years in the Nurses’ Health Study (36
). This association needs confirmation in longitudinal studies with snoring ascertained at baseline.
Our measurement of sleep after
baseline is another limitation. However, the cross-sectional associations were very similar whether we used follow-up or baseline BMI, suggesting that baseline sleep measurement would have yielded similar cross-sectional and longitudinal estimates. In separate analyses, our sleep duration measurement has predicted other longitudinal clinical outcomes (e.g., incident coronary artery calcification) (37
). The lack of a longitudinal sleep effect on BMI does not seem to be due to a lack of power to detect any significant predictors of weight change, since other variables are associated with weight change.
Prior evidence that shorter sleep leads to weight gain among adults has not been consistent. Differences in the ages of study populations may contribute to apparent heterogeneity, as may variations across populations in the accuracy of self-reported sleep. Future studies are needed to confirm our finding that the cross-sectional association between sleep duration and BMI is due to the powerful association among the subset who snore. The mechanism underlying the cross-sectional association is not clear; this study does not provide evidence that persons who sleep less are more likely to gain weight.