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. 2020 Dec 29;13(1):73.
doi: 10.3390/nu13010073.

Later Meal and Sleep Timing Predicts Higher Percent Body Fat

Elizabeth A Thomas  1   2   3 , Adnin Zaman  1   2 , Marc-Andre Cornier  1   2   3 , Victoria A Catenacci  1   2 , Emma J Tussey  4 , Laura Grau  5 , Jaron Arbet  5 , Josiane L Broussard  1   6 , Corey A Rynders  4
Affiliations

Later Meal and Sleep Timing Predicts Higher Percent Body Fat

Elizabeth A Thomas et al. Nutrients. .

Abstract

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.

Keywords: meal timing; sleep timing; time-restricted eating.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Timing of energy intake by day of the week. Ridgeline plot showing the distribution of energy intake over 24 h for each day of the recording period. Each curve shows the probability density function for energy intake with the area under each curve equal to one. The vertical lines indicate the mid-point of the eating window. The hash marks in each plot correspond to the individual photographs.
Figure 2
Figure 2
Scatter plots showing correlations between percent body fat and the start of the eating window (A), the mid-point of the eating window (B), sleep offset (C), and daily step counts per 1000 steps (D).
Figure 3
Figure 3
Heatmap showing correlations between body composition, energy intake, meal timing, physical activity and sleep variables. Darker shading indicates a greater degree of correlation, and correlations with p-values > 0.05 are displayed in white.
Figure 4
Figure 4
Elastic Net variable selection results showing the highest ranking meal timing, sleep, and physical activity variables as they relate to body fat percentage (A) and BMI (B).
See this image and copyright information in PMC

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