Effects of 4- and 6-h Time-Restricted Feeding on Weight and Cardiometabolic Health: A Randomized Controlled Trial in Adults with Obesity

Cienfuegos, Sofia; Gabel, Kelsey; Kalam, Faiza; Ezpeleta, Mark; Wiseman, Eric; Pavlou, Vasiliki; Lin, Shuhao; Oliveira, Manoela Lima; Varady, Krista A

doi:10.1016/j.cmet.2020.06.018

Cited by 371 publications

(533 citation statements)

References 59 publications

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“…The survey exposed that food intake was the key course of weight change, increasing food intake may resulting weight gain, and decreasing food intake may leading to weight loss, which coincided with the current clinical research on reducing food intake through alternate fasting to achieve weight loss (19,20). Ideal and satisfaction of weight, daily steps and BMI changes of participants.…”

Section: Discussionmentioning

confidence: 92%

Risk Factors Related to Weight Gain for Chines During Home Confinement in COVID-19 Pandemic: An Observational Retrospective Study

Qing

Gong

et al. 2020

Preprint

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Objective: The observational study was intended to explore the weight changes and risk factors of weight gain during the self-quarantine and find available methods to lose weight.Method: This was an online retrospective observational study investigating the weight changes before and after home confinement. A total of 530 participants completed the online questionnaire. diet, sleep, self-reported depression, disease history and exercise information possibly relating to weight changes were incorporated into the questionnaire. The differences among four groups (underweight, normal weight, overweight and obesity) in BMI change and weight change were compared, and the risk factors of weight gain was also analyzed by multiple linear regression analysis. Result: Participants were mostly between 21-50 years old, getting an average weight change of 0.82±3.31kg, and an average BMI change of 0.35 [-0.37, 1.00]. 43.77% of them gained weight by 2.99±2.29kg averagely. People with normal weight were easier to gain weight than obese group (p=0.001). There were differences in food intake (p<0.001), eating habits(p<0.001), taste preference (p=0.047), daily exercise step change(p=0.007), exercise (p=0.02) between non-weight gain group and weight gain group. The multiple linear regression revealed that weight gains were associated with sex (p=0.002), food intake (p=0.004), current daily exercise step (p=0.009) and self-reported depression (p=0.002) and weight loss was related to food intake (p=0.004) and pre-BMI (p=0.001).Conclusion: Eating irregularly, increasing food intake, self-reported depression and decreased daily steps were risk factors of weight gain, yet weight loss was related to decreased food intake and pre-BMI.

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Section: Discussionmentioning

confidence: 92%

Risk Factors Related to Weight Gain for Chines During Home Confinement in COVID-19 Pandemic: An Observational Retrospective Study

Qing

Gong

et al. 2020

Preprint

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“…While various measures of glycaemic control have been improved in previous ad libitum and energy-matched TRE interventions of varying durations (4 days to 12 weeks), all previous investigations have been in those with normal or impaired glucose tolerance [4,5,[7][8][9]27,44,48]. Individuals with T2D have altered circadian patterns of glucose regulation [17,49], with greatest impairments to glucose tolerance in the morning compared to the evening in those with normal or impaired glucose tolerance.…”

Section: Discussionmentioning

confidence: 99%

Time-Restricted Eating as a Nutrition Strategy for Individuals with Type 2 Diabetes: A Feasibility Study

et al. 2020

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Individuals with type 2 diabetes (T2D) require a long-term dietary strategy for blood glucose management and may benefit from time-restricted eating (TRE, where the duration between the first and last energy intake is restricted to 8–10 h/day). We aimed to determine the feasibility of TRE for individuals with T2D. Participants with T2D (HbA1c >6.5 to <9%, eating window >12 h/day) were recruited to a pre-post, non-randomised intervention consisting of a 2-week Habitual period to establish baseline dietary intake, followed by a 4-weeks TRE intervention during which they were instructed to limit all eating occasions to between 10:00 and 19:00 h on as many days of each week as possible. Recruitment, retention, acceptability, and safety were recorded throughout the study as indicators of feasibility. Dietary intake, glycaemic control, psychological well-being, acceptability, cognitive outcomes, and physiological measures were explored as secondary outcomes. From 594 interested persons, and 27 eligible individuals, 24 participants enrolled and 19 participants (mean ± SD; age: 50 ± 9 years, BMI: 34 ± 5 kg/m2, HbA1c: 7.6 ± 1.1%) completed the 6-week study. Overall daily dietary intake did not change between Habitual (~8400 kJ/d; 35% carbohydrate, 20% protein, 41% fat, 1% alcohol) and TRE periods (~8500 kJ/d; 35% carbohydrate, 19% protein, 42% fat, 1% alcohol). Compliance to the 9 h TRE period was 72 ± 24% of 28 days (i.e., ~5 days/week), with varied adherence (range: 4–100%). Comparisons of adherent vs. non-adherent TRE days showed that adherence to the 9-h TRE window reduced daily energy intake through lower absolute carbohydrate and alcohol intakes. Overall, TRE did not significantly improve measures of glycaemic control (HbA1c −0.2 ± 0.4%; p = 0.053) or reduce body mass. TRE did not impair or improve psychological well-being, with variable effects on cognitive function. Participants described hunger, daily stressors, and emotions as the main barriers to adherence. We demonstrate that 4-weeks of TRE is feasible and achievable for these individuals with T2D to adhere to for at least 5 days/week. The degree of adherence to TRE strongly influenced daily energy intake. Future trials may benefit from supporting participants to incorporate TRE in regular daily life and to overcome barriers to adherence.

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“…Several human studies have evaluated the metabolic effects of short-term, eucaloric TRE (6–8 h eating windows) aligned early in the biologic day, finding improvements in glucose homeostasis, insulin sensitivity and β cell responsiveness [ 53 , 54 , 55 ], increased fat oxidation [ 56 ], and reductions in blood pressure [ 54 ] and appetite [ 56 ]. However, most studies evaluating the effects of longer-duration TRE (8–16 weeks) on weight loss have used self-selected or mid-day eating windows [ 9 , 57 , 58 , 59 , 60 , 61 ] and have shown modest (2–4%) weight loss. In addition, many patients may prefer a later eating window (eating from 12–8 p.m., for example) to better align with social eating occasions [ 62 , 63 ], but data to support this practice are lacking.…”

Section: Discussionmentioning

confidence: 99%

Later Meal and Sleep Timing Predicts Higher Percent Body Fat

et al. 2020

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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.

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Effects of 4- and 6-h Time-Restricted Feeding on Weight and Cardiometabolic Health: A Randomized Controlled Trial in Adults with Obesity

Cited by 371 publications

References 59 publications

Risk Factors Related to Weight Gain for Chines During Home Confinement in COVID-19 Pandemic: An Observational Retrospective Study

Risk Factors Related to Weight Gain for Chines During Home Confinement in COVID-19 Pandemic: An Observational Retrospective Study

Time-Restricted Eating as a Nutrition Strategy for Individuals with Type 2 Diabetes: A Feasibility Study

Later Meal and Sleep Timing Predicts Higher Percent Body Fat

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