Calorie restriction (CR) is a common approach to inducing negative energy balance. Recently, time-restricted feeding (TRF), which involves consuming food within specific time windows during a 24h day, has become popular owing to its relative ease of practice and potential to aid in achieving and maintaining a negative energy balance. TRF can be implemented intentionally with CR, or TRF might induce CR simply due to the time restriction. This review focuses on summarizing our current knowledge on how time-restricted feeding (TRF) and continuous caloric restriction (CR) affect gut peptides that influence satiety. Based on peer-reviewed studies, in response to CR there is an increase in the orexigenic hormone ghrelin and reduction in fasting leptin and insulin. There is likely a reduction in glucagon-like-peptide-1 (GLP-1), peptide-YY (PYY), and cholecystokinin (CCK), albeit the evidence for this is weak. Following TRF, unlike CR, fasting ghrelin decreased in some TRF studies, while showing no change in several others. Further, a reduction in fasting leptin, insulin, and GLP-1 has been observed. In conclusion, when other determinants of food intake are held equal, the peripheral satiety systems appeared to be somewhat similarly affected by CR and TRF with regard to leptin, insulin and GLP-1. But unlike CR, TRF did not appear to robustly increase ghrelin suggesting different influences on appetite with a potential decrease of hunger following TRF when compared to CR. However, there are several established and novel gut peptides that have not been measured within the context of CR and TRF, and studies that have evaluated effects of TRF are often short-term, with non-uniform study designs, and highly varying temporal eating patterns. More evidence and studies addressing these aspects are needed to draw definitive conclusions.
Objectives To examine and compare reported food and nutrient intake in men and women who differ in cognitive restraint (CR) and disinhibition (D) scores. We hypothesize that average intake of sodium, total sugar, saturated fat, and Healthy Eating Index (HEI) scores of diet quality will differ between low and high D groups. Methods 330 adults from a cross-sectional study who completed 3 dietary recalls and the three-factor eating questionnaire (TFEQ) were included in this analysis. Participants were classified into 4 groups based on TFEQ scores for CR and D: high CR + high D (CRD, n = 46); high CR + low D (CR, n = 104); low CR + high D (D, n = 42); and low CR + low D (LL, n = 138). The Automated Self-Administered 24-hour (ASA24) tool was used to obtain dietary recalls on 2 weekdays and 1 weekend day. Nutrient intakes were averaged for the 3 recalls, and HEI scores were calculated using the HEI-2015 scoring standards. Differences in average calories, sodium, total sugar, saturated fat, and HEI scores between groups were analyzed using analysis of covariance with age, sex, and BMI as covariates. Results There were differences in average sodium and saturated fat intake, with CR group reporting lower sodium intake (p = 0.041) and lower saturated fat (p = 0.007) intake compared to the LL group only. There were no differences in calorie or total sugar intake between groups. Interestingly, added sugar intake based on HEI-2015 scoring showed group differences, with CR reporting lower added sugar intake than LL group (p = 0.042). HEI subscore for refined grain intake was also higher in LL group compared to CR (p = 0.002) and CRD (p = 0.023). Total HEI score was lower in LL (59.5 ± 1.0) compared to CR (65.1 ± 1.15, p = 0.002) and CRD (65.6 ± 1.75, p = 0.017). Conclusions High cognitive restraint was associated with a more “healthful” diet with lower sodium and saturated fat intakes compared to groups with low restraint. While there were no associations between total sugar intake and cognitive restraint, reduced consumption of added sugar and refined grains were reported by the cognitively restrained participants, regardless of disinhibition status. Contrary to our hypothesis, high cognitive restraint was the predominant behavior associated with diet quality, not disinhibition. Funding Sources Funding was provided through the USDA.
This review focuses on summarizing current knowledge on how time-restricted feeding (TRF) and continuous caloric restriction (CR) affect central neuro-endocrine systems involved in regulating satiety. Several interconnected regions of the hypothalamus, brainstem, and cortical areas of the brain are involved in the regulation of satiety. Following CR and TRF, the increase in hunger and reduction of satiety signals of the melanocortin system (NPY, POMC, and AgRP) appear similar between CR and TRF protocols, as do the dopaminergic responses in the mesocorticolimbic circuit. However, ghrelin and leptin signaling via the melanocortin system appears to improve energy balance signals and reduce hyperphagia following TRF, which has not been reported in CR. In addition to satiety systems, CR and TRF also influence circadian rhythms. CR influences the SCN (suprachiasmatic nucleus) or the primary circadian clock as seen by increased clock gene expression. In contrast, TRF appears to affect both the SCN and the peripheral clocks, as seen by phasic changes in the non-SCN (potentially the elusive food entrainable oscillator) and metabolic clocks. The peripheral clocks are influenced by the primary circadian clock but are also entrained by food timing, sleep timing, and other lifestyle parameters, which can supersede the metabolic processes that are regulated by the primary circadian clock. Taken together, TRF influences hunger/satiety, energy balances systems, and circadian rhythms, suggesting a role for adherence to CR in the long run if implemented using the TRF approach. However, these suggestions are based on only a few studies, and future investigations that use standardized protocols for the evaluation of the effect of these diet patterns (time, duration, meal composition, sufficiently powered) are necessary to verify these preliminary observations.
International Journal of Exercise Science 8(4): 425-430, 2015. Use of wearabletechnology to obtain various body metrics appears to be a trending phenomenon. However there is very little literature supporting the notion that these apparatuses can be used for research purposes in the field. The purpose of this study was to utilize Hexoskin wearable technology shirts (HxS) to obtain data in a pilot study using a trail hiking situation. Ten individuals (male, n = 4, female n = 6) volunteered to participate. On the first day, volunteers completed two approximately flat trail hikes at a self-preferred pace with a 15-minute rest between trials. On the second day, participants completed a strenuous uphill hike (17.6% grade) with a 15-minute rest at the summit and then completed the downhill portion. Body metrics provided by the HxS were average heart rate (HR), maximal HR (MHR), total energy expenditure (EE), average respiratory rate (RR), maximal respiratory rate (MRR), total steps (SC), and cadence (CA). Other measurements obtained were systolic and diastolic blood pressure (SBP, DBP), and ratings of perceived exertion (RPE). Data were analyzed using both one-way repeated measures analysis of variance (ANOVA) with significance accepted at p≤0.05 and intraclass correlation coefficients (ICC) for each variable. Both were determined using Statistical Package for the Social Sciences software (SPSS). No significant differences for trail type were noted for MHR (p=0.38), RR (p=0.45) or MRR (p=0.31). The uphill trail elicited significantly elevated HR (up=154±24 bpm, easy=118±11 bpm, down=129±19 bpm; p=0.04) and EE (up=251±78 kcal, easy=124±38 kcal, down=171±52 kcal; p=0.02). Significant ICC were observed for DBP (r = 0.80, p = 0.02), RR (r = 0.98, p = 0.01), SC (r = 0.97, p = 0.01) and RPE (r = 0.94, p = 0.01). Non-significant correlation were noted for uphill RR vs CA (r=0.51, p=0.16) or RPE vs SBP (r=0.03, p=0.94), HR (r=0.60, p=0.12), and MHR (r=0.70, p=0.051). We utilized HxS to provide physiological data in an applied setting. It should be noted that HR did not register in 5 out of 10 subjects on the easy trail, and 8 of 10 participants during the uphill hike. Additionally, estimated EE appears to be linked to HR intensity. Future investigations taken in an outdoor environment should take these findings into consideration.
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