Calorie counting is better for weight loss than intermittent fasting


In a recent study published in Journal of the American Heart AssociationResearchers in the US evaluated the relationship between sleep and food intake and weight change over the long term.

Obesity and overweight are two well-defined, modifiable risk factors for chronic diseases that affect more than 70% of Americans. Experimental and mechanistic research has shown that the timing of food consumption (in the form of time-restricted eating or intermittent fasting) may modulate metabolic function and reduce body weight. In particular, time-restricted eating, which involves restricting food consumption to four to 12 hours per day without reducing caloric intake, has been linked to improved body weight balance and is a recommended technique for weight loss. However, there is still a lack of research regarding the potential benefits of time-restricted eating patterns, particularly the difficulties associated with maintaining such eating patterns.

Study: The Association of Eating and Sleeping Periods with Weight Change Over Time: The Daily24 Cohort.  Image credit: favita1987/Shutterstock

Stady: Association of eating and sleeping with weight change over time: The Daily24 Cohort. Image credit: favita1987/Shutterstock

about studying

In this study, the researchers evaluated the longitudinal relationship between the time interval between the first and last meal of the day and associated weight trajectories.

Potential eligible participants included individuals 18 years of age or older who had electronic health records (EHRs) in one of the three health systems, with at least one weight and one length measurement recorded in their EHR within the two years prior to the recruitment framework. With input from end-users as well as patient stakeholders, the team developed the Daily24 smartphone app, which allowed eligible individuals to record their eating, waking, and sleeping patterns for each 24-hour period in real time. The eating habits evaluated in the study were meal time and approximate meal size.

Participants recorded the time with a 24-hour wheel for each meal and chose the type of meal and expected portion size from the menu. Emails, in-app reminders, and SMS text messages asked users to use the app as much as possible for the first four weeks after installing it. In terms of sleep duration, participants noted the time they slept the night before and the time they woke up in the current day on the 24-hour wheel. A participant’s entries for a given day were considered complete when they chose the ‘Done for the day’ option.

At enrolment, participants were asked to complete an online survey and record their weight at baseline and follow-up four months later. At the time of enrollment, race, sex, education, smoking status, income, weight intentions, and behavioral characteristics were reported on the survey. The International Physical Activity Questionnaire was used to collect data on physical activity, which were then categorized into high, medium, and low activity levels according to time and intensity. In addition, an examiner’s dietary questionnaire was used to record food consumption.

results

Electronic consent and completion of basic questionnaires determine enrollment eligibility. The participants were then given directions to download the Daily24 mobile app. The final eligible sample consisted of 547 individuals. In electronic health records of 547 individuals, the average number of weight measures was 23.7 overall, 21.3 before enrolment, and 3.4 in the six months following enrolment. The median duration of follow-up for reported weights in electronic health records was 6.3 years.

The average period from the first meal to the last meal was 11.5 hours, waking up to the first 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 a higher body mass index (BMI) during enrollment had a higher chance of being older and black, had high blood pressure or diabetes, had a longer period between final meal and sleep, lower educational level, and vegetable/fruit consumption. , physical activity, and a shorter duration between the first and last meal.

The team noted that the time interval between first and last meal, waking up and first meal, final meal and falling asleep, and total sleep duration were not associated with weight change across follow-up time when recorded. In models that accounted for potential confounding variables, each 1-hour increase in the duration between the first and last meal at baseline was associated with an average of 0.005 kg of weight gain per year. The annual weight changes related to the time interval between wakefulness and sleep, the last meal and sleep, and the total sleep duration were 0.02 kg, 0.07 kg, and 0.11 kg, respectively, during the study follow-up period. These associations were maintained before and after enrollment, except for the duration between the last meal and sleep, which reveals an inverse relationship with weight change after enrollment.

conclusion

The results of the study showed that the number of medium and large meals was positively associated with weight gain, while the percentage of small meals was negatively associated with weight change. Distributing energy intake earlier in the day appears to be associated with a lower rate of weight gain after recording. The data did not support time-restricted eating as a long-term approach to weight loss. The researchers believe that more large-scale research with longer follow-up periods is needed to accurately describe the relationship between meal time and weight change.

Journal reference:

  • Association of eating and sleeping periods 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.122.026484And https://www.ahajournals.org/doi/10.1161/JAHA.122.026484



Source link

Related Posts

Precaliga