Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort

Abstract

Background We aim to evaluate the association between meal intervals and weight trajectory among adults from a clinical cohort. Methods and Results This is a multisite prospective cohort study of adults recruited from 3 health systems. Over the 6-month study period, 547 participants downloaded and used a mobile application to record the timing of meals and sleep for at least 1 day. We obtained information on weight and comorbidities at each outpatient visit from electronic health records for up to 10 years before until 10 months after baseline. We used mixed linear regression to model weight trajectories. Mean age was 51.1 (SD 15.0) years, and body mass index was 30.8 (SD 7.8) kg/m²; 77.9% were women, and 77.5% reported White race. Mean interval from first to last meal was 11.5 (2.3) hours and was not associated with weight change. The number of meals per day was positively associated with weight change. The average difference in annual weight change (95% CI) associated with an increase of 1 daily meal was 0.28 kg (0.02-0.53). Conclusions Number of daily meals was positively associated with weight change over 6 years. Our findings did not support the use of time-restricted eating as a strategy for long-term weight loss in a general medical population.

Keywords: eating behavior; eating intervals; weight trajectory.

Figure .. Average differences in annual weight change (kg) per unit increase in interval duration and meal frequency.

The forest plot represents the average difference in annual weight change (kg) per 1 hour increase in interval duration and per 1 meal increase in meal frequency. For instance, an increase in 1 large meal per day was associated with an average annual weight increase of 0.69 kg (95% CI, 0.19–1.18 kg). Models were adjusted for age at consent (continuous, years), sex (men; women), center (Geisinger; Johns Hopkins University; Pittsburgh), race (White; Black; Asian; Pacific Islander, American Indian, other; ≥2 races), education (≤high school; some college; ≥college), income (<$35k; $35–<50k; 50–<75k; ≥75k; do not know), height (continuous, meters), current smoking (yes, no), time‐varying diabetes (yes, no), chronic kidney disease (yes, no), acute myocardial infarction (yes, no), chronic obstructive pulmonary disease (yes, no), heart failure (yes, no), hypertension status (yes, no), ischemia heart disease (yes, no), stroke (yes, no), and number of complete days for using the app (continuous, days). IQR indicates interquartile range.