The goal of this study was to test the feasibility of time restricted eating (TRE) in adults with overweight and obesity. Participants (n = 50) logged all eating occasions (>0 kcal) for a 2-week run-in period using a smartphone application. Participants with eating duration ≥14 h enrolled in an open label, non-randomized, prospective 90-day TRE intervention, with a self-selected reduced eating window of 10 h. No dietary counseling was provided. Changes in anthropometrics, eating patterns and adherence after TRE were analyzed using t-tests or Wilcoxon Rank-Sum Test. The mean duration of the baseline eating window was 14 h 32 m ± 2 h 36 m (n = 50) with 56% of participants with duration ≥14 h. TRE participants (n = 16) successfully decreased their eating window from 16 h 04 m ± 1 h 24 m to 11 h 54 m ± 2 h 06 m (p < 0.001), and reduced the number of daily eating occasions by half (p < 0.001). Adherence to logging and to the reduced eating window was 64% ± 22% and 47% ± 19%, respectively. TRE resulted in decreases in body weight (−2.1 ± 3.0 kg, p = 0.017), waist circumference (−2.2 ± 4.6 cm, p = 0.002) and systolic blood pressure (−12 ± 11 mmHg, p = 0.002). This study demonstrates the feasibility and efficacy of TRE administered via a smartphone, in adults with overweight and obesity.
We aim to describe temporal eating patterns in a population of adults with overweight or obesity. In this cross-sectional analysis, data were combined from two separate pilot studies during which participants entered the timing of all eating occasions (>0 kcals) for 10–14 days. Data were aggregated to determine total eating occasions, local time of the first and last eating occasions, eating window, eating midpoint, and within-person variability of eating patterns. Eating patterns were compared between sexes, as well as between weekday and weekends. Participants (n = 85) had a median age of 56 ± 19 years, were mostly female (>70%), white (56.5%), and had a BMI of 31.8 ± 8.0 kg/m2. The median eating window was 14 h 04 min [12 h 57 min–15 h 21 min], which was significantly shorter on the weekend compared to weekdays (p < 0.0001). Only 13.1% of participants had an eating window <12 h/d. Additionally, there was greater irregularity with the first eating occasion during the week when compared to the weekend (p = 0.0002). In conclusion, adults with overweight or obesity have prolonged eating windows (>14 h/d). Future trials should examine the contribution of a prolonged eating window on adiposity independent of energy intake.
Indirect calorimetry (IC) measurements to estimate resting energy expenditure (REE) necessitate a stable measurement period or steady state (SS). There is limited evidence when assessing the time to reach SS in young, healthy adults. The aims of this prospective study are to determine the approximate time to necessary reach SS using open-circuit IC and to establish the appropriate duration of SS needed to estimate REE. One hundred young, healthy participants (54 males and 46 females; age = 20.6 ± 2.1 years; body weight = 73.6 ± 16.3 kg; height 172.5 ± 9.3 cm; BMI = 24.5 ± 3.8 kg/m2) completed IC measurement for approximately 30 min while the volume of oxygen (VO2) and volume of carbon dioxide (VCO2) were collected. SS was defined by variations in the VO2 and VCO2 of ≤10% coefficient of variation (%CV) over a period of five consecutive minutes. The 30-min IC measurement was divided into six 5-min segments, such as S1, S2, S3, S4, S5, and S6. The results show that SS was achieved during S2 (%CV = 6.81 ± 3.2%), and the %CV continued to met the SS criteria for the duration of the IC measurement (S3 = 8.07 ± 4.4%, S4 = 7.93 ± 3.7%, S5 = 7.75 ± 4.1%, and S6 = 8.60 ± 4.6%). The current study found that in a population of young, healthy adults the duration of the IC measurement period could be a minimum of 10 min. The first 5-min segment was discarded, while SS occurred by the second 5-min segment.
ImportanceInterindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that estimates personalized PPGR to specific foods may be more efficacious for weight loss.ObjectiveTo compare a standardized low-fat vs a personalized diet regarding percentage of weight loss in adults with abnormal glucose metabolism and obesity.Design, Setting, and ParticipantsThe Personal Diet Study was a single-center, population-based, 6-month randomized clinical trial with measurements at baseline (0 months) and 3 and 6 months conducted from February 12, 2018, to October 28, 2021. A total of 269 adults aged 18 to 80 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) ranging from 27 to 50 and a hemoglobin A1c level ranging from 5.7% to 8.0% were recruited. Individuals were excluded if receiving medications other than metformin or with evidence of kidney disease, assessed as an estimated glomerular filtration rate of less than 60 mL/min/1.73 m2 using the Chronic Kidney Disease Epidemiology Collaboration equation, to avoid recruiting patients with advanced type 2 diabetes.InterventionsParticipants were randomized to either a low-fat diet (&lt;25% of energy intake; standardized group) or a personalized diet that estimates PPGR to foods using a machine learning algorithm (personalized group). Participants in both groups received a total of 14 behavioral counseling sessions and self-monitored dietary intake. In addition, the participants in the personalized group received color-coded meal scores on estimated PPGR delivered via a mobile app.Main Outcomes and MeasuresThe primary outcome was the percentage of weight loss from baseline to 6 months. Secondary outcomes included changes in body composition (fat mass, fat-free mass, and percentage of body weight), resting energy expenditure, and adaptive thermogenesis. Data were collected at baseline and 3 and 6 months. Analysis was based on intention to treat using linear mixed modeling.ResultsOf a total of 204 adults randomized, 199 (102 in the personalized group vs 97 in the standardized group) contributed data (mean [SD] age, 58 [11] years; 133 women [66.8%]; mean [SD] body mass index, 33.9 [4.8]). Weight change at 6 months was −4.31% (95% CI, −5.37% to −3.24%) for the standardized group and −3.26% (95% CI, −4.25% to −2.26%) for the personalized group, which was not significantly different (difference between groups, 1.05% [95% CI, −0.40% to 2.50%]; P = .16). There were no between-group differences in body composition and adaptive thermogenesis; however, the change in resting energy expenditure was significantly greater in the standardized group from 0 to 6 months (difference between groups, 92.3 [95% CI, 0.9-183.8] kcal/d; P = .05).Conclusions and RelevanceA personalized diet targeting a reduction in PPGR did not result in greater weight loss compared with a low-fat diet at 6 months. Future studies should assess methods of increasing dietary self-monitoring adherence and intervention exposure.Trial RegistrationClinicalTrials.gov Identifier: NCT03336411
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