Sleep and meal timing influence food intake and its hormonal regulation in healthy adults with overweight/obesity.
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ABSTRACT:
SUBMITTER: St-Onge MP
PROVIDER: S-EPMC6538463 | biostudies-literature | 2019 Jul
REPOSITORIES: biostudies-literature
Publications
Sleep and meal timing influence food intake and its hormonal regulation in healthy adults with overweight/obesity.
St-Onge Marie-Pierre MP Pizinger Theresa T Kovtun Kyle K RoyChoudhury Arindam A
European journal of clinical nutrition 20190701 Suppl 1
<h4>Background</h4>Studies associate sleeping and eating late in the day with poor dietary quality and higher obesity risk but differences in sleep duration confound this association. We aimed to determine whether sleep and meal timing, independent of sleep duration, influenced food intake in healthy adults.<h4>Methods</h4>This was a controlled, 2 × 2 inpatient crossover study with normal (0000-0800 h) or late (0330-1130 h) sleep and normal (1, 5, 11, and 12.5 h after awakening) or late (4.5, 8. ...[more]
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| S-EPMC5771427 | biostudies-literature
Project description:BackgroundTiming of dietary intake may play a role in obesity. However, previous studies produced mixed findings possibly due to inconsistent approaches to characterize meal timing and not taking into account chronotype and macronutrients. To address the aforementioned limitations, we have defined meal timing relative to sleep/wake timing, investigated the relationship between meal timing and body mass index (BMI) dependent on chronotype, and examined the associations.MethodsBMI, chronotype, and dietary intakes were measured in 872 middle-to-older-aged adults by six 24-h dietary recalls in 1 year. We defined four time windows of intake relative to sleep timing: morning (within 2 h after getting out of bed), night (within 2 h before bedtime), and two midday periods in between (split by the midpoint of the waking period).ResultsA higher percent of total daily energy intake consumed during the morning window was associated with lower odds of being overweight or obese (odds ratio (95% confidence intervals), 0.53 (0.31, 0.89)). This association was stronger in people with an earlier chronotype (0.32 (0.16, 0.66)). A higher percent of total daily energy intake consumed during the night window was associated with higher odds of being overweight or obese (1.82 (1.07, 3.08)), particularly in people with a later chronotype (4.94 (1.61, 15.14)). These associations were stronger for the intakes of carbohydrates and protein than for fat intake.ConclusionOur study suggests that higher dietary consumption after waking up and lower consumption close to bedtime associate with lower BMI, but the relationship differs by chronotype. Furthermore, the data demonstrate a clear relationship between the timing of carbohydrate and protein intake and obesity. Our findings highlight the importance of considering timing of intake relative to sleep timing when studying the associations of meal timing with obesity and metabolic health.
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Project description:Sleep restriction (SR) reliably increases caloric intake. It remains unknown whether such intake cumulatively increases with repeated SR exposures and is impacted by the number of intervening recovery sleep opportunities. Healthy adults (33.9 ± 8.9y; 17 women, Body Mass Index: 24.8 ± 3.6) participated in a laboratory protocol. N = 35 participants experienced two baseline nights (10 h time-in-bed (TIB)/night; 22:00-08:00) followed by 10 SR nights (4 h TIB/night; 04:00-08:00), which were divided into two exposures of five nights each and separated by one (n = 13), three (n = 12), or five (n = 10) recovery nights (12 h TIB/night; 22:00-10:00). Control participants (n = 10) were permitted 10 h TIB (22:00-08:00) on all nights. Food and drink consumption were ad libitum and recorded daily. Compared to baseline, sleep-restricted participants increased daily caloric (+527 kcal) and saturated fat (+7 g) intake and decreased protein (-1.2% kcal) intake during both SR exposures; however, intake did not differ between exposures or recovery conditions. Similarly, although sleep-restricted participants exhibited substantial late-night caloric intake (671 kcal), such intake did not differ between exposures or recovery conditions. By contrast, control participants showed no changes in caloric intake across days. We found consistent caloric and macronutrient intake increases during two SR exposures despite varying intervening recovery nights. Thus, energy intake outcomes do not cumulatively increase with repeated restriction and are unaffected by recovery opportunities.
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Project description:To avoid the pitfalls of self-reported dietary intake, wearable sensors can be used. Many food ingestion sensors offer the ability to automatically detect food intake using time resolutions that range from 23 ms to 8 min. There is no defined standard time resolution to accurately measure ingestive behavior or a meal microstructure. This paper aims to estimate the time resolution needed to accurately represent the microstructure of meals such as duration of eating episode, the duration of actual ingestion, and number of eating events. Twelve participants wore the automatic ingestion monitor (AIM) and kept a standard diet diary to report their food intake in free-living conditions for 24 h. As a reference, participants were also asked to mark food intake with a push button sampled every 0.1 s. The duration of eating episodes, duration of ingestion, and number of eating events were computed from the food diary, AIM, and the push button resampled at different time resolutions (0.1-30s). ANOVA and multiple comparison tests showed that the duration of eating episodes estimated from the diary differed significantly from that estimated by the AIM and the push button (p-value <0.001). There were no significant differences in the number of eating events for push button resolutions of 0.1, 1, and 5 s, but there were significant differences in resolutions of 10-30s (p-value <0.05). The results suggest that the desired time resolution of sensor-based food intake detection should be ≤5 s to accurately detect meal microstructure. Furthermore, the AIM provides more accurate measurement of the eating episode duration than the diet diary.
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Project description:BACKGROUND/OBJECTIVES:Experiments in animal models have shown a positive association between in utero exposure to pharmacologic sex hormones and offspring obesity. The developmental effects of such hormones on human obesity are unknown. SUBJECTS/METHODS:Using data from a large, prospective pregnancy cohort study (n=19?652), with linkage to a national prescription registry, we evaluated the association between use of hormonal contraceptives before and after conception (defined from dispensed prescription data and characterized by last date of use relative to conception, 12 to >4 months before (n=3392), 4 to >1 months before (n=2541), 1 to >0 months before (n=2997) and 0-12 weeks after (n=567)) in relation to offspring overweight or obesity at age 3 years. RESULTS:We observed a weak, inverse association between early pregnancy use of a combination oral contraceptive and offspring overweight or obesity at age 3 (adjusted odds ratio (OR): 0.75, 95% confidence interval (CI): 0.53, 1.08) and a positive, but imprecise, association with use of a progestin-only oral contraceptive in early pregnancy (adjusted OR: 1.26, 95% CI: 0.79, 2.02). In general, no association was observed between the use of a hormonal contraceptive before conception and offspring overweight or obesity. A sensitivity analysis comparing combination oral contraceptive users in early pregnancy to other unplanned pregnancies without hormonal contraceptive use further strengthened the inverse association (adjusted OR: 0.70, 95% CI: 0.48, 1.02). Other sensitivity analyses were conducted to evaluate the robustness of the associations observed given varying assumptions. CONCLUSIONS:Pharmacologic sex hormones in early pregnancy may be inversely or positively associated with offspring overweight or obesity at age 3, depending on the specific formulation used. The present study provides support for the potential for environmental sources of hormonally active agents to exert developmental effects.
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Project description:ObjectiveTo determine associations among objectively-measured nocturnal sleep time, bedtime and obesogenic behaviors, including dietary intake, timing of intake, and physical activity, in a diverse sample of school-aged children who presented for behavioral treatment to enhance sleep duration.MethodsEighty-seven children (8-11 y, 66.7% female, zBMI: 0.86 ± 1.0) who self-reported sleeping <9.5 h/night were studied for one week using wrist actigraphy to estimate sleep; hip-worn accelerometers to measure physical activity; and 24 h dietary recalls to capture dietary intake and meal timing. Pearson and Spearman's rho correlations and linear regressions controlling for age, gender and race were used for statistical analyses.Results and conclusionMean bedtime was 10:31 PM (±58.2 min) and mean nocturnal sleep time was 7.7 h (±37.5 min). Although later bedtime was associated with shorter sleep time (r = -0.61, p < 0.001), the two variables were differentially related to obesity risk factors. Later bedtime, but not sleep time, correlated with greater daily fat intake, later first meal of the day, and greater after-dinner intake (all p < 0.05). Nocturnal sleep time, but not bedtime, correlated with zBMI (p = 0.04). Both sleep time and later bedtime were associated with a later last meal of the day (all p < 0.05). Findings remained consistent after controlling for demographic factors. In short-sleeping school-aged children, bedtime may be more predictive of dietary obesity risk factors whereas sleep duration may be more predictive of zBMI. Results suggest that health providers should consider both bedtime and sleep duration for reducing obesity risk in children.Clinical trialEnhancing Sleep Duration: Effects on Children's Eating and Activity Behaviors, NCT03186508, https://clinicaltrials.gov/ct2/show/NCT03186508.
| S-EPMC8171434 | biostudies-literature
Project description:Accumulating evidence suggests that later timing of energy intake (EI) is associated with increased risk of obesity. In this study, 83 individuals with overweight and obesity underwent assessment of a 7-day period of data collection, including measures of body weight and body composition (DXA) and 24-h measures of EI (photographic food records), sleep (actigraphy), and physical activity (PA, activity monitors) for 7 days. Relationships between body mass index (BMI) and percent body fat (DXA) with meal timing, sleep, and PA were examined. For every 1 h later start of eating, there was a 1.25 (95% CI: 0.60, 1.91) unit increase in percent body fat (False Discovery Rate (FDR) adjusted p value = 0.010). For every 1 h later midpoint of the eating window, there was a 1.35 (95% CI: 0.51, 2.19) unit increase in percent body fat (FDR p value = 0.029). For every 1 h increase in the end of the sleep period, there was a 1.64 (95% CI: 0.56, 2.72) unit increase in percent body fat (FDR p value = 0.044). Later meal and sleep timing were also associated with lower PA levels. In summary, later timing of EI and sleep are associated with higher body fat and lower levels of PA in people with overweight and obesity.
| S-EPMC7823810 | biostudies-literature
Project description:Background & aimsWhile environmental factors are presumed to be primary drivers of food timing, preliminary evidence suggests that genetics may be an additional determinant. The aim was to explore the relative contribution of genetics and environmental factors to variation in the timing of food intake in a Spanish twin population. Because chronotype, bedtime and wake time are related to food timing, covariance with food timing was further assessed.MethodsIn this observational study, 53 pairs of adult (mean (SD) = 52 (6.03) years) female twins (28 monozygotic; 25 dizygotic) were recruited from the Murcia Twin Register. Zygosity was determined by DNA-testing. Timing of the three main meals of the day was assessed via 7-day dietary records, and the midpoint of food intake was computed by calculating the midpoint between breakfast and dinner times. Chronotype, bedtime and wake time were self-reported. Heritability of food timing and related traits were estimated by comparing monozygotic and dizygotic twin correlations and fitting genetic structural equation models to measured variables.ResultsWe observed genetic influences for food timing, with highest heritability for the midpoint of food intake (64%) in an overweight/obese population (BMI = 26.01 ± 3.77). Genetic factors contributed to a higher degree to the timing of breakfast (56%) than the timing of lunch (38%) or dinner (n.s.). Similarly, heritability estimates were larger in related behavioral traits earlier on in the day (i.e. wake time, (55%)), than those later on in the day (i.e. bedtime, (38%)). Bivariate analyses revealed a significant genetic overlap between food timing and bedtime and chronotype (rG between 0.78 and 0.91).ConclusionsGenetic influences appear to account for a significant proportion of the variability in food timing, particularly breakfast. Thus, interventions related to food timing may be more effective when targeting afternoon/evening traits, such as lunch or dinner times. Furthermore, our data suggest shared genetic architecture underlying food timing and phenotypically related traits.Clinical trialNCT03059576. https://clinicaltrials.gov/ct2/show/NCT03059576.
| S-EPMC6135708 | biostudies-literature