In a recent study published within the Journal of the American Heart Association, researchers in the US assessed the correlation between sleeping and eating intervals and long-term weight change.
Obesity and chubby are two well-defined modifiable risk aspects for chronic illness impacting over 70% of Americans. Experimental and mechanistic research showed that the timing of food consumption (in the shape of time-restricted eating or intermittent fasting) might modulate metabolic function and lower body weight. Specifically, time-restricted eating, which involves restricting food consumption to 4 to 12 hours per day without reducing calorie intake, has been linked to enhanced body weight homeostasis and is a beneficial weight reduction technique. Nonetheless, research continues to be lacking regarding the possible benefits of time-restricted eating patterns, particularly the difficulties related to maintaining such eating patterns.
Study: Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort. Image Credit: favorita1987 / Shutterstock
In regards to the study
In the current study, researchers assessed the longitudinal connection between the time interval between the primary and last meal of the day and associated weight trajectories.
Potentially eligible participants included individuals aged 18 years or above who had electronic health records (EHR) in considered one of the three health systems, with a minimum of 1 weight and one height measurement recorded of their EHR throughout the two years preceding the recruitment window. With input from end users in addition to patient stakeholders, the team developed the Daily24 smartphone application, which allowed eligible individuals to record their eating, waking, and sleeping patterns per 24-hour interval in real-time. The eating habits evaluated within the study were supper time and the approximate size of a meal.
Participants recorded the time through a 24-hour wheel for every meal and selected the meal type and anticipated portion size from a menu. Emails, in-app reminders, and short message service (SMS) text messages asked the users to utilize the app as often as possible throughout the initial 4 weeks after installing it. With respect to sleep duration, the participants noted the time they fell asleep the night before and the time they woke up on the present day on the 24-hour wheel. The participant’s entries for a selected day were deemed complete after they selected the “done for the day” option.
At enrolment, participants were asked to finish a web based survey and record their weight at baseline and follow up 4 months later. On the time of enrolment, race, gender, education, smoking status, income, weight intentions, and behavioral characteristics were self-reported within the survey. The International Physical Activity Questionnaire was employed to collect data on physical activity, which was then classified into high, moderate, and low activity levels based on time and intensity. As well as, the dietary screener questionnaire was used to record food consumption.
Electronic consent and the completion of baseline questionnaires determined enrollment eligibility. Participants were then supplied with directions for downloading the Daily24 mobile application. The ultimate eligible sample consisted of 547 individuals. Within the EHRs of the 547 individuals, the typical variety of weight measures was 23.7 overall, 21.3 prior to enrolment, and three.4 within the six months following enrollment. The typical duration of follow-up for weights reported within the EHR was 6.3 years.
The mean period from the primary to the ultimate meal was 11.5 hours, waking as much as the primary meal was 1.6 hours, the last meal to sleep was 4.0 hours, and the sleep duration was 7.5 hours. Participants who reported higher body-mass index (BMI) during enrollment had a better likelihood of being older and Black, having hypertension or diabetes, having an extended interval between final meal and sleep, having a lower level of education, vegetable/fruit consumption, and physical activity, and having a shorter duration between first and last meal.
The team noted that the time interval between the primary and last meal, waking up and first meal, final meal and sleep, and total sleep duration weren’t linked with weight change across follow-up time at enrolment. In models that accounted for potential confounding variables, each one-hour increase within the duration between the primary and final meal at baseline was related to a median of 0.005 kg yearly weight gain. The yearly weight changes related to the interval between waking and sleeping, last meal and sleeping, and total sleep duration were 0.02 kg, 0.07 kg, and 0.11 kg, respectively, throughout the study’s follow-up period. These correlations were maintained before and after enrolment, aside from the duration between the last meal and sleeping, revealing an inverse relationship with weight change post-enrollment.
The study findings showed that the variety of medium and enormous meals was positively related to weight gain, while the proportion of small meals was negatively related to the burden change. The distribution of energy intake earlier within the day seemed to be related to a lower incidence of weight gain after enrolment. The information didn’t support time-restricted eating as a long-term weight reduction approach. The researchers imagine that further large-scale research with long follow-up periods is required to explain the connection between supper time and weight change accurately.
- Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort, Di Zhao, Eliseo Guallar, Thomas B. Woolf, Lindsay Martin, Harold Lehmann, Janelle Coughlin, Katherine Holzhauer, Attia A. Goheer, Kathleen M. McTigue, Michelle R. Lent, Marquis Hawkins, Jeanne M. Clark, Wendy L. Bennett, Journal of the American Heart Association, American Heart Association, e026484, doi: https://doi.org/10.1161/JAHA.122.026484, https://www.ahajournals.org/doi/10.1161/JAHA.122.026484