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Abstract Context Pre-exercise nutrient availability alters acute metabolic responses to exercise, which could modulate training responsiveness. Objective To assess acute and chronic effects of exercise performed before versus after nutrient ingestion on whole-body and intramuscular lipid utilization and postprandial glucose metabolism. Design (1) Acute, randomized, crossover design (Acute Study); (2) 6-week, randomized, controlled design (Training Study). Setting General community. Participants Men with overweight/obesity (mean ± standard deviation, body mass index: 30.2 ± 3.5 kg⋅m-2 for Acute Study, 30.9 ± 4.5 kg⋅m-2 for Training Study). Interventions Moderate-intensity cycling performed before versus after mixed-macronutrient breakfast (Acute Study) or carbohydrate (Training Study) ingestion. Results Acute Study—exercise before versus after breakfast consumption increased net intramuscular lipid utilization in type I (net change: –3.44 ± 2.63% versus 1.44 ± 4.18% area lipid staining, P < 0.01) and type II fibers (–1.89 ± 2.48% versus 1.83 ± 1.92% area lipid staining, P < 0.05). Training Study—postprandial glycemia was not differentially affected by 6 weeks of exercise training performed before versus after carbohydrate intake (P > 0.05). However, postprandial insulinemia was reduced with exercise training performed before but not after carbohydrate ingestion (P = 0.03). This resulted in increased oral glucose insulin sensitivity (25 ± 38 vs –21 ± 32 mL⋅min-1⋅m-2; P = 0.01), associated with increased lipid utilization during exercise (r = 0.50, P = 0.02). Regular exercise before nutrient provision also augmented remodeling of skeletal muscle phospholipids and protein content of the glucose transport protein GLUT4 (P < 0.05). Conclusions Experiments investigating exercise training and metabolic health should consider nutrient-exercise timing, and exercise performed before versus after nutrient intake (ie, in the fasted state) may exert beneficial effects on lipid utilization and reduce postprandial insulinemia.

Background and objectivesPrevious studies have documented that high rates of delay discounting are associated with obesity. However, studies utilizing monetary reward experiments typically report no associations, as opposed to positive associations apparent in studies utilising food-reward experiments. Our objective was to investigate the reasons behind the mixed evidence from a methodological perspective using systematic review and meta-analytic methodologies.MethodsSeven databases (EMBASE, MEDLINE, PsycINFO, Scopus, Web of Science, Econlit and IBSS) were systematically searched. Logistic meta-regression was applied to identify the determinants of a significant association and risk of bias was assessed using a modified form of the Newcastle Ottawa cohort scale.ResultsA total of 59 studies were identified, among which 29 studies (49.2%) found a significant positive association and 29 (49.2%) reported no association. A higher proportion of significant and positive associations was reported in those studies utilizing ‘best-practice’ methods (i.e. appropriate measurement models) to estimate monetary delay discounting (15/27; 55.6%) and incentive-compatible experiments (10/16; 62.5%) than those using non-‘best-practice’ methods (14/34; 41.2%) and hypothetical experiments (19/43; 44.2%). All five studies utilizing both ‘best-practice’ methods and incentive-compatible experiments generated a positive and significant relationship. Results from a logistic meta-regression also suggested that studies employing incentive-compatible experiments (OR: 4.38, 95% CI = 1.05–18.33, p value: 0.04), ‘best-practice’ methods (OR: 4.40, 95% CI = 0.88–22.99, p value: 0.07), parametric methods (OR: 3.36, 95% CI = 0.83–13.57, p value: 0.04), those conducted in children/adolescent populations (OR: 3.90, 95% CI = 0.85–17.88, p value: 0.08), and those with larger sample size (OR: 1.91, 95% CI = 1.15–3.18, p value: 0.01) tended to show positive and significant associations between delay discounting and obesity.ConclusionsThis review suggests that the mixed evidence to date is a result of methodological heterogeneity, and that future studies should utilise ‘best practice’ methods.

PurposePrior studies exploring the reliability of peak fat oxidation (PFO) and the intensity that elicits PFO (FATMAX) are often limited by small samples. This study characterised the reliability of PFO and FATMAX in a large cohort of healthy men and women.MethodsNinety-nine adults [49 women; age: 35 (11) years; V˙O2peak: 42.2 (10.3) mL·kg BM−1·min−1; mean (SD)] completed two identical exercise tests (7–28 days apart) to determine PFO (g·min−1) and FATMAX (%V˙O2peak) by indirect calorimetry. Systematic bias and the absolute and relative reliability of PFO and FATMAX were explored in the whole sample and sub-categories of: cardiorespiratory fitness, biological sex, objectively measured physical activity levels, fat mass index (derived by dual-energy X-ray absorptiometry) and menstrual cycle status.ResultsNo systematic bias in PFO or FATMAX was found between exercise tests in the entire sample (− 0.01 g·min−1 and 0%V˙O2peak, respectively; p > 0.05). Absolute reliability was poor [within-subject coefficient of variation: 21% and 26%; typical errors: ± 0.06 g·min−1 and × / ÷ 1.26%V˙O2peak; 95% limits of agreement: ± 0.17 g·min−1 and × / ÷ 1.90%V˙O2peak, respectively), despite high (r = 0.75) and moderate (r = 0.45) relative reliability for PFO and FATMAX, respectively. These findings were consistent across all sub-groups.ConclusionRepeated assessments are required to more accurately determine PFO and FATMAX.

Purpose To examine whether calcium type and co-ingestion with protein alter gut hormone availability. Methods Healthy adults aged 26 ± 7 years (mean ± SD) completed three randomized, double-blind, crossover studies. In all studies, arterialized blood was sampled postprandially over 120 min to determine GLP-1, GIP and PYY responses, alongside appetite ratings, energy expenditure and blood pressure. In study 1 ( n  = 20), three treatments matched for total calcium content (1058 mg) were compared: calcium citrate (CALCITR); milk minerals rich in calcium (MILK MINERALS); and milk minerals rich in calcium plus co-ingestion of 50 g whey protein hydrolysate (MILK MINERALS + PROTEIN). In study 2 ( n  = 6), 50 g whey protein hydrolysate (PROTEIN) was compared to MILK MINERALS + PROTEIN. In study 3 ( n  = 6), MILK MINERALS was compared to the vehicle of ingestion (water plus sucralose; CONTROL). Results MILK MINERALS + PROTEIN increased GLP-1 incremental area under the curve (iAUC) by ~ ninefold (43.7 ± 11.1 pmol L −1  120 min; p  < 0.001) versus both CALCITR and MILK MINERALS, with no difference detected between CALCITR (6.6 ± 3.7 pmol L −1  120 min) and MILK MINERALS (5.3 ± 3.5 pmol L −1  120 min; p  > 0.999). MILK MINERALS + PROTEIN produced a GLP-1 iAUC ~ 25% greater than PROTEIN ( p  = 0.024; mean difference: 9.1 ± 6.9 pmol L −1  120 min), whereas the difference between MILK MINERALS versus CONTROL was small and non-significant ( p  = 0.098; mean difference: 4.2 ± 5.1 pmol L −1  120 min). Conclusions When ingested alone, milk minerals rich in calcium do not increase GLP-1 secretion compared to calcium citrate. Co-ingesting high-dose whey protein hydrolysate with milk minerals rich in calcium increases postprandial GLP-1 concentrations to some of the highest physiological levels ever reported. Registered at ClinicalTrials.gov: NCT03232034, NCT03370484, NCT03370497.

Context: Pre-exercise nutrient availability alters acute metabolic responses to exercise, which could modulate training responsiveness. We hypothesised that in men with overweight/obesity, acute exercise before versus after nutrient ingestion would increase whole-body and intramuscular lipid utilization, translating into greater increases in oral glucose insulin sensitivity over 6-weeks of training. Design and Participants: We showed in men with overweight/obesity (mean+/-SD for BMI: 30.2+/-3.5 kg.m-2 for acute, crossover study, 30.9+/-4.5 kg.m-2 for randomized, controlled, training study) a single exercise bout before versus after nutrient provision increased lipid utilisation at the whole-body level, but also in both type I (p<0.01) and type II muscle fibres (p=0.02). We then used a 6-week training intervention to show sustained, 2-fold increases in lipid utilisation with exercise before versus after nutrient provision (p<0.01). Main Outcome Measures: Postprandial glycemia was not differentially affected by exercise training before vs after nutrient provision (p>0.05), yet plasma was reduced with exercise training before, but not after nutrient provision (p=0.03), resulting in increased oral glucose insulin sensitivity when training was performed before versus after nutrient provision (25+/-38 vs -21+/-32 mL.min-1.m-2; p=0.01) and this was associated with increased lipid utilisation during exercise (r=0.50, p=0.02). Regular exercise prior to nutrient provision augmented remodelling of skeletal muscle phospholipids and protein content of the glucose transport protein GLUT4 (p<0.05). Conclusions: Experiments investigating exercise training and metabolic health should consider nutrient-exercise timing, and exercise performed before versus after nutrient intake (i.e., in the fasted state) may exert beneficial effects on lipid utilisation and reduce postprandial insulinemia. Footnotes * https://researchportal.bath.ac.uk/en/datasets/