Purpose: Ectopic fat in non-adipose tissues is linked to higher chronic-disease risk. Using the UK Biobank, this study examined associations of device-measured physical activity (PA) and sedentary time with ectopic fat. Methods: Liver and pancreas proton density fat fraction (PDFF), and anterior-thigh skeletal muscle fat infiltration (MFI) were assessed by magnetic resonance imaging. Reallocations among accelerometer derived time spent sedentary and in light intensity PA (LPA), and moderate-to-vigorous intensity PA (MVPA) were examined using isotemporal substitution. Multi-variable linear regression was employed with stepwise adjustment for sex, age, height, socioeconomic factors, and counts of cancer and non-cancer illnesses. Sex*activity interaction terms were then added to the models, and sex-stratified analyses were conducted where interactions were significant. Results: The final sample comprised 9,213 participants with liver PDFF, 6,521 participants with pancreatic PDFF, and 9,197 participants with MFI (mean age ~64 years). Replacing 30 minutes of sedentary time with LPA was associated with lower ectopic fat, with relative percentage differences in fully adjusted models of -2.2% [-2.7%, -1.8%] for liver PDFF, 1.9% [-2.4%, -1.3%] for pancreas PDFF, and -0.5% [-0.7%, -0.4%] for MFI. Substituting sedentary time with MVPA showed greater differences (-9.9% [11.0%, 8.7%], 7.9% [-9.2%, -6.6%], and -3.6 % [-3.9%, -3.2%], respectively). Replacing LPA with MVPA was also associated with lower ectopic fat (-7.6% [-8.9%, -6.4%], -6.0% [7.5%, -4.6%], and -3.0% [-3.4%, -2.6%] for liver PDFF, pancreas PDFF, and MFI. Associations were stronger in females for liver and pancreas PDFF and MFI when sedentary time was replaced with LPA or MVPA. Conclusions: Reallocation of sedentary time or lower-intensity PA to higher intensity PA is linked to lower ectopic fat. These relationships are stronger in women than men.

Oxyntomodulin (OXM) is a gut-derived peptide hormone with anorexigenic properties that reduce food intake and increase energy expenditure. This study investigated the effect of a single bout of moderate-intensity running on OXM concentrations and whether OXM response were associated with appetite perceptions and energy intake. Twenty healthy adults (10 men, 10 women; age: 25 ± 4 years; BMI: 22.2 ± 2.0 kg m-2) completed two randomised crossover trials: (1) 60-min treadmill running at 70% of peak oxygen uptake, and (2) rest control. Plasma OXM concentrations were measured at baseline (0 min), immediately post-exercise/rest, and every 30 min until 210 min. Appetite ratings were assessed throughout. Energy intake was measured from an ad libitum meal provided at 120 min. Linear mixed-effect models were used to examine the main effect of trial, time, and their interaction. OXM concentrations increased after the meal in both trials (p < 0.001), with no main effect of trial (p = 0.413) or trial-by-time interaction (p = 0.748). Pre-lunch OXM time-averaged incremental area under the curve (iAUC) was higher following exercise compared with control (0-120 min, mean difference = 16 pg mL-1·min, p = 0.006), whereas no difference was observed across the full sampling period (0-210 min; p = 0.265). Exercise increased fullness at 60 min (mean difference = 13 mm, p = 0.019) and reduced relative energy intake compared with control (mean difference = 2056 kJ, p < 0.001). No associations were observed between OXM iAUC and appetite perceptions or energy intake (p ≥ 0.098). Moderate-intensity running did not alter OXM concentrations. Changes in OXM were not associated with appetite perceptions or energy intake, suggesting that OXM may not play a central role in exercise-induced appetite regulation. Research across different exercise modes, intensities, and durations is warranted.

BACKGROUND:While fat-free mass (FFM), fat mass (FM), and resting metabolic rate (RMR) influence energy intake, their specific roles as homoeostatic and hedonic drivers of eating-and factors moderating these relationships-are uncertain. This study examined associations of FFM, FM, and RMR with a comprehensive set of appetite-related outcomes in adults. METHODS:130 participants (58% male; age: 25.0 ± 8.5 years; BMI: 24.0 ± 3.7 kg/m²; mean ± SD) completed assessments of RMR (indirect-calorimetry), body composition (air-displacement plethysmography), energy intake (laboratory-based), appetite-related hormones (fasted and meal-stimulated), appetite (visual analogue scales), food reward (Leeds Food Preference Questionnaire [LFPQ]), food cravings (Control of Eating Questionnaire), taste and smell perception. GLM examined associations between exposure and outcome variables, controlling for demographic and lifestyle factors. Effect modification was assessed via interaction terms and stratified analyses with median splits for continuous variables. RESULTS:RMR was positively associated with energy intake (P < 0.001), while FFM and FM were not. The positive RMR-energy intake association was stronger in individuals who were younger, more active, smokers, and with lower BMI (P ≤ 0.020). FFM was positively associated with postprandial peptide-YY (PYY) and hunger, craving control and smell sensitivity (P ≤ 0.026). FM was positively associated with fasting PYY and leptin, and inversely associated with postprandial PYY and hunger, craving control, and taste sensitivity (P ≤ 0.047). RMR was inversely associated with fasting ghrelin (P < 0.001). No consistent associations were observed between body composition, RMR and food reward (LFPQ). Several associations were moderated by age, sex, BMI, physical activity and smoking. CONCLUSIONS:RMR is a key driver of energy intake, with sex, BMI, physical activity and smoking status moderating the relationship. Body composition (FFM and FM) is linked to distinct variations in homoeostatic and hedonic components of appetite, particularly gut hormone responses, craving control and taste perception.

Background Physical inactivity is a risk factor for severe COVID-19 and often worsens after hospitalisation. Clinicians need quick, accurate assessments to target interventions. We aimed to assess the validity of the General Practice Physical Activity Questionnaire (GPPAQ) in adults recovering one year after COVID-19 hospitalisation . Methods Post-hospitalisation for COVID-19, adults attended a one-year-visit and completed the GPPAQ Physical Activity Index (PAI-4 active), 14-day wrist-worn accelerometry (Moderate-Vigorous PA [MVPA]- active), and other health outcomes. Validity was examined via : (i) internal consistency (factor analysis); (ii) measurement invariance across sex, age, and ethnicity using differential item functioning (DIF); (iii) convergent validity (GPPAQ sensitivity/specificity versus accelerometry); and (iv) construct validity (correlations with health outcomes). Results 752 participants had GPPAQ and accelerometry (265 female, mean± sd age 60.9±11.6 years, MVPA 18.75 min·day −1 (IQR 7.55, 36.11), PAI-1 46.8%, PAI-2 15.6%, PAI-3 19.4%, PAI-4 18.2%. Factor analyses supported good internal consistency with two factors (daily activities, physical exercise). Confirmatory factor Index (CFI) showed excellent fit (CFI 0.965). DIF indicated moderate variability by sex and age. GPPAQ-PAI showed limited sensitivity (26.3%) for correctly classifying physically active individuals, but higher specificity (88.4%) for classifying physical inactivity, and weak-to-moderate correlations with health outcomes. Conclusions GPPAQ demonstrates internal consistency, with construct and convergent validity in adults 1-year post-COVID-19 hospitalisation. GPPAQ effectively identifies inactive individuals to support clinical care; however, its sensitivity suggests underestimation of activity relative to accelerometry. Future pathways should combine GPPAQ with device-based assessment to optimise evaluation of physical activity to guide pulmonary rehabilitation and targeted interventions.

BACKGROUND/OBJECTIVES:Sleeve gastrectomy (SG) improves glycaemic control; however, it also markedly accelerates gastric emptying, which can lead to exaggerated postprandial glucose and insulin excursions and, in some cases, postprandial hyperinsulinaemic hypoglycaemia. In non-surgical populations, fat preloads can reduce postprandial glycaemia by slowing gastric emptying, but their effects after SG are unclear. METHODS:Ten adults >1-year post-SG completed a randomised, open-label, crossover study involving two mixed-meal tolerance tests (MMTTs), preceded (-30 min) by either a moderate, fat-dominant preload (28 g Brazil nuts) or 100 mL water (control). Blood samples were collected over three hours to assess plasma glucose, insulin, c-peptide, and total glucagon-like peptide-1 (GLP-1). Hypoglycaemia and dumping symptoms were assessed using validated questionnaires. Nadir plasma glucose concentration was the primary outcome. RESULTS:Nadir plasma glucose was identical between conditions (both 3.8 mmol/L; 95% CI: -0.4, 0.3, p = 0.849), and neither peak glucose nor overall postprandial glucose exposure (incremental area under the curve iAUC0-180 min) differed between the preload and water conditions. Insulin and c-peptide concentrations immediately before the MMTT were higher after the fat-dominant preload (both p < 0.001). Overall insulin and c-peptide responses during the MMTT (iAUC0-180 min) remained comparable between conditions (95% CI -225, 2665; p = 0.442 and -67,787, 70,263; 0.968), but peak values for both hormones were higher after the preload (95% CI 2.9, 79.1, p = 0.038 and 17.3, 2402.7, p = 0.040, respectively). Total GLP-1 was also elevated prior to the MMTT (95% CI 1.6, 22.8, p = 0.028), while its early and overall postprandial responses did not differ (both p > 0.05). Ratings of hypoglycaemia and dumping symptoms were similar for both study arms. DISCUSSION:A moderate, fat-dominant preload consumed before a mixed meal did not alter nadir or overall postprandial glucose in adults without diabetes after SG. However, the preload was associated with higher peak insulin secretion, a finding that should be interpreted with caution, as the study was not powered for secondary outcomes. Given the unique gastrointestinal physiology after SG, further research is needed to determine how different nutrient compositions or timing approaches influence postprandial glucose homeostasis in this population.

BACKGROUND:Glucose has been implicated in the control of appetite and food intake. This study investigated whether glycaemic patterns relate to energy intake and whether appetite-related hormones mediate this relationship. METHODS:Thirty healthy young women (age: 25 ± 4 years; BMI: 21.4 ± 2.0 kg/m2) arrived at the laboratory at 8:00 AM after an overnight fast. Upon arrival, participants completed a 30 min resting period, during which the cannula was inserted, and all fasted glucose measurements were collected. Glucose was measured every 5 min using FreeStyle Libre 2™ continuous glucose monitors (CGM), and one venous plasma glucose (VPG) sample was obtained immediately after cannula insertion. Following the 30 min fasting measurement period, participants consumed a fixed breakfast and then remained in the laboratory for an additional 240 min. Glucose was monitored via CGM every 5 min and VPG was measured every 15 min after breakfast. Energy intake was assessed at 240 min using an ad-libitum homogeneous pasta meal. Subjective appetite ratings were collected fasted and every 15 min after breakfast. Appetite-related hormones, including insulin, acylated ghrelin (AG), total glucagon-like peptide-1 (GLP-1) and oxyntomodulin (OXM) were measured in the fasted state, immediately after breakfast (t = 0 min), and subsequently at 30 min intervals after breakfast until t = 240 mins. Menstrual cycle phase was recorded and included as a covariate in all analyses. Associations between glycaemic variables and satiety or energy intake were examined using generalised linear models with a gamma distribution and log link function, adjusting for BMI and menstrual cycle phase. Bootstrap-based causal mediation analyses were conducted to evaluate whether appetite-related hormones mediated any significant associations between glycaemic responses and satiety or energy intake. RESULTS:CGM-derived glucose nadir (lowest concentration) and dip (deviation of nadir from baseline as a percentage) were significantly associated with subsequent energy intake. A higher glucose nadir was associated with lower energy intake (β = -0.17, p = 0.003), whereas a greater glucose dip was associated with higher energy intake (β = 0.007; p < 0.001). When standardised, a one standard deviation (SD) increases in glucose nadir corresponded to an approximately 13% reduction in energy intake, while a one-SD increase in glucose dip corresponded to an approximately 16% increase in energy intake. Glucose nadir (CGM: β = 0.23, p = 0.041; VPG: β = 0.26, p = 0.008) and dip (CGM: β = -0.01, p = 0.006; VPG: β = -0.012, p < 0.001) derived from both CGM and VPG were also significantly associated with overall satiety measured immediately before the ad libitum lunch. A one-SD increase in glucose nadir was associated with higher satiety (CGM: 20% increase; VPG: 20% increase), whereas a one-SD increase in glucose dip was associated with lower satiety (CGM: 15% reduction; VPG: 17% reduction). Causal mediation analyses provided no evidence that insulin, acylated ghrelin, total GLP-1, or oxyntomodulin mediated these associations (p ≥ 0.09). CONCLUSIONS:Glucose dynamics including nadir and dip may influence satiety and subsequent energy intake. These data support for a role of glucose in models of appetite regulation.

Cardiorespiratory fitness (CRF) is a powerful predictor of numerous health outcomes; however, its relationship with liver health remains unclear. This study examined the associations of CRF with non-invasive markers of liver steatosis and fibrosis in a large, health-screening cohort, and explored potential effect modification by demographic, cardiometabolic, and clinical factors. In this independent healthcare-based cross-sectional study of 39,197 UK adults (32

To determine whether a pre-lunch single bout of moderate-intensity aerobic exercise (AEX) alters time spent in hypoglycaemia (<3.0 mmol/L) during the subsequent 24 hours (24-h) and parameters of glucose homeostasis in individuals without diabetes after metabolic/bariatric surgery (MBS). In a randomised crossover study, 15 participants completed two conditions: 30min treadmill walking at 60

To compare acute effects of continuous moderate-intensity exercise (CME) and low-volume high-intensity interval exercise (LV-HIIE) on appetite responses between South Asians and white Europeans with non-diabetic hyperglycaemia. Thirteen white Europeans and 10 South Asians (age 50–74 years) completed three, 5-h experimental conditions (CME, LV-HIIE, control) in randomised sequences. Standardised meals were provided at 0 and 3 h. Exercise involved a 25-min LV-HIIE or 35-min CME bout that ended at 2 h. Subjective appetite perceptions and appetite-related hormones (glucagon-like peptide-1 (GLP-1), peptide YY (PYY), acylated ghrelin (AG)) were measured at 0, 0.5, 1, 2, 3, 3.5, 4 and 5 h. Time-averaged total area under the curve (TAUC; 1–5 h) was analysed, adjusted for age, sex, and pre-intervention time-averaged TAUC (0–1 h). Total GLP-1 was higher in LV-HIIE (mean difference [95% CI] 4.3 [1.5, 7.1] pmol/L h) and CME (4.5 [1.4, 7.7] pmol/L h) versus control (condition effect P = 0.01), but exercise had no effect on the other outcomes in the whole study population (P ≥ 0.28). Appetite responses to exercise were similar between ethnicities for total GLP-1 and total PYY (interaction P ≥ 0.11), but subtle differences emerged for AG and overall appetite (interaction P ≤ 0.02). AG was higher and overall appetite lower in LV-HIIE versus CME in South Asians whilst overall appetite was higher in LV-HIIE versus CME in white Europeans, but neither exercise bout was different to control. Single LV-HIIE and CME bouts increased total GLP-1 in individuals with non-diabetic hyperglycaemia, but exercise-related appetite responses were not strongly modulated by exercise intensity or ethnicity.

Roux-en-Y gastric bypass (RYGB) induces substantial weight loss and changes in glucose homeostasis, partly through alterations in gastrointestinal anatomy and nutrient absorption. Sodium-glucose co-transporters-1 (SGLT-1) facilitate intestinal glucose absorption, a process that may be compromised post-RYGB. Animal studies suggest that sodium supplementation to a meal may enhance SGLT-1 activity post-RYGB. In this study, we investigated whether adding sodium chloride (NaCl) to a carbohydrate-rich meal affects glucose homeostasis in people after RYGB. In this open-label, randomized, crossover study, eleven adults without diabetes post-RYGB (mean age 57.3 ± 11.3 years, BMI 35.1 ± 7.5 kg/m2, 64

OBJECTIVES:Altered appetite-related gut hormone concentrations may reflect a physiological adaptation facilitating weight regain after weight loss. This review investigates hormonal changes after weight loss achieved through calorie restriction (CR), exercise (EX), or both combined (CREX). METHODS:A systematic search of PubMed (MEDLINE), EMBASE, SPORTDiscus, Cochrane Library, Web of Science, and ClinicalTrials.gov was conducted to identify randomised controlled trials (RCTs) and non-RCTs reporting in a fasting state either pre- and post-intervention appetite-related hormone concentrations or the changes therein after weight loss. The hormones examined were ghrelin, peptide tyrosine tyrosine (PYY), glucagon-like peptide -1 (GLP-1), and cholecystokinin (CCK), in their total and/or active form. Standardised mean differences (SMD) were extracted as the effect size. RESULTS:127 studies were identified: 19 RCTs, 108 non-RCTs, 1305 and 4725 participants, respectively. In response to weight loss induced by CR, EX or CREX, the meta-analysis revealed an increase in total ghrelin from both RCTs (SMD: 0.55, 95% CI: 0.07-1.04) and non-RCTs (SMD: 0.24, 95% CI: 0.14-0.35). A decrease in acylated ghrelin was identified for RCTs (SMD: -0.58, 95% CI: -1.09 to -0.06) but an increase was observed for non-RCTs (SMD: 0.15, 95% CI: 0.03 to 0.27). Findings also revealed a decrease in PYY (total PYY: SMD: -0.17, 95%CI: -0.28 to -0.06; PYY3-36: SMD: -0.17, 95%CI: -0.32 to -0.02) and active GLP-1 (SMD: -0.16, 95% CI: -0.28 to -0.05) from non-RCTs. Changes in hormones did not differ among the three interventions when controlling for weight loss. Meta-regression indicated that greater weight loss was associated with a greater increase in total ghrelin. CONCLUSIONS:Weight loss induced by CR, EX, or CREX elicits an increase in total ghrelin, but varied responses in other appetite-related hormones. The extent of weight loss influences changes in appetite-related gut hormone concentrations.

This study examined associations of cigarette smoking with appetite perceptions, appetite-related hormones, food preferences and eating traits. In a cross-sectional matched-pair cohort design, 25 participants who smoke cigarettes and 25 who do not were matched 1:1 by age, sex, ethnicity, and BMI. Across two visits, participants' food preferences (Leeds Food Preference Questionnaire), cravings (Control of Eating Questionnaire), and eating traits (Three-Factor Eating Questionnaire) were assessed. Fasting and postprandial appetite perceptions (visual analogue scales) were also assessed during a 4-h mixed-meal tolerance test (MM-TT), while fasting leptin and fasting and postprandial acylated ghrelin and total peptide-YY (PYY) were measured for 2 h postprandially. Group differences in study outcomes were analysed using generalised linear models. After adjustment (age and BMI), explicit liking and wanting for high-fat foods and cravings for savoury foods were higher in participants who smoke versus those who do not (P ≤ 0.065; d ≥ 0.52). Cognitive restraint was lower, while disinhibition was higher in participants who smoke compared to those who do not (P ≤ 0.014; d ≥ 0.69). Smoking was also associated with lower fasting acylated ghrelin and lower postprandial total PYY (P ≤ 0.041; d ≥ 0.58), whereas fasting leptin was similar between groups (P = 0.821; d = 0.06). Additionally, participants who smoke had higher fasting perceived fullness (P = 0.021; d = 0.65), while no other fasting or postprandial differences were identified for other appetite perceptions (hunger, prospective food consumption, satisfaction; P ≥ 0.373; d ≤ 0.25). In conclusion, cigarette smoking is associated with altered food preferences and less favourable eating traits, while more subtle differences may exist in appetite perceptions and appetite-related hormones.

Appetite control is a topic which attracts widespread interest given its importance to energy balance and obesity. In this research area, the mixed-meal tolerance test (MM-TT) has emerged as an ‘appetite regulation assay’, facilitating the dynamic assessment of appetite parameters (e.g. subjective appetite perceptions, appetite-related hormones, food reward) in response to an individual meal. The MM-TT is commonly employed in observational and experimental studies to examine population differences and intervention effects. Problematically, no practice standard exists for the MM-TT and protocols vary widely. This presents a challenge for researchers designing new MM-TTs and hampers the comparability of findings. Therefore, within this narrative review we sought to identify and discuss key methodological considerations inherent within a MM-TT. The scope of our review extends to evaluating participant familiarisation and methodological standardisation practices, test meal characteristics, appetite perception assessment, blood sampling techniques, measurement of appetite-related hormones and data handling/analysis. A checklist has been devised to summarise relevant methodological issues identified within this review. This checklist can be used as a tool by researchers to facilitate MM-TT design and promote greater standardisation/comparability between studies. This review highlights the need for broader standardisation of MM-TT procedures to support consistency across future research. Additional research is needed to strengthen the evidence base on which various recommendations are made, particularly relating to participant familiarisation and methodological standardisation practices. Additional scrutiny of less common outcomes employed in MM-TTs (not addressed here), such as diet-induced thermogenesis, gastric emptying and ad libitum energy intake, is also needed.

This study examined whether supplementation with collagen peptides (CP) affects appetite and post-exercise energy intake in healthy active females. In this randomised, double-blind cross-over study, fifteen healthy females (23 (sd 3) years) consumed 15 g/d of CP or a taste matched non-energy control (CON) for 7 d. On day 7, participants cycled for 45 min at ∼55 % Wmax, before consuming the final supplement. Sixty-min post supplementation an ad libitum meal was provided, and energy intake recorded. Subjective appetite sensations were measured daily for 6 d (pre- and 30 min post-supplement) and pre (0 min) to 280 min post-exercise on day 7. Blood glucose and hormone concentrations (total ghrelin, glucagon-like peptide-1 (GLP-1), and peptide YY (PYY), cholecystokinin (CCK), dipeptidyl peptidase-4 (sDPP-4), leptin, and insulin) were measured fasted at baseline (day 0), then pre-breakfast (0 min), post-exercise (100 min), post-supplement (115, 130, 145, 160 min) and post-meal (220, 280 min) on day 7. Ad libitum energy intake was ∼10 % (∼41 kcal) lower in the CP trial (P = 0·037). There was no difference in gastrointestinal symptoms or subjective appetite sensations throughout the trial (P ≥ 0·412). Total plasma GLP-1 (AUC, CON: 6369 (sd 2330); CP: 9064 (sd 3021) pmol/l; P < 0·001) and insulin (+80 % at peak) were higher after CP (P < 0·001). Plasma ghrelin and leptin were lower in CP (condition effect; P ≤ 0·032). PYY, CCK and glucose were not different between CP and placebo (P ≥ 0·100). CP supplementation following exercise increased GLP-1 and insulin concentrations and reduced ad libitum energy intake at a subsequent meal in physically active females.

Crossover randomized controlled trials (RCTs) are common in exercise and nutrition sciences. Since researchers randomize participants to different sequences of the treatment and comparator/control conditions, crossover RCTs are powerful for detecting mean treatment effects under certain circumstances. We aim to review the information that can be derived from crossover RCTs about treatment response heterogeneity-a fundamental issue in precision medicine for tailoring treatments to individuals. After covering the fundamental design issues, we describe the variance components that underlie observed data. The crucial person-by-treatment variance component can be quantified from a repeated or "replicate" crossover RCT by exposing participants to multiple cycles of trial conditions. As a type of n-of-1 trial, replicate crossover RCTs have important design and statistical power considerations, which we describe. By synthesizing findings from our six published replicate crossover RCTs, we also compare various data analysis approaches. We find general agreement between these approaches, and a link between within-person consistency of response and the detection of person-by-treatment interactions. We postulate that a paired "variance comparison," for example, the Pitman-Morgan test, provides some preliminary information regarding response heterogeneity from a typical single-cycle crossover RCT. Nevertheless, underlying assumptions are critical, rendering these comparisons as merely exploratory until an n-of-1 or replicate crossover RCT is undertaken. Multiple-cycle n-of-1 trials and replicate crossover RCTs are underused but are informative for treatment response heterogeneity. However, these trials are still only one component of the process for predicting individual magnitude of response from any personal traits, which is the "holy grail" of personalized treatment.

Sub-optimal sleep, whether insufficient, excessive, or poor-quality, is an independent risk factor for obesity, largely through influencing energy intake via altered appetite and reward processing. Less is known about its influence on real-world dietary behaviours. We examined associations of self-reported sleep quality and duration with dietary eating behaviours in a large UK adult cohort. 27,263 adults (median (interquartile range): age, 51.0 (16.0) years; BMI, 25.2 (5.3) kg/m2; 40.5 % female) completed a standardised health assessment, including self-reported sleep quality (1-10 scale) and duration. Thirteen eating behaviours broadly reflecting emotional/reward-driven eating, dietary disinhibition, food preferences, and meal patterns were assessed via questionnaire. Regression models examined associations between sleep characteristics and eating behaviours, adjusting for age, sex, socioeconomic status, assessment year, and region. Odds ratios (OR) are presented for ordinal/binary outcomes and rate ratios (RR) for count outcomes. Poor sleep quality and short sleep duration were associated with an eating profile suggestive of heightened emotional/reward-driven eating and reduced dietary restraint. This included higher odds/frequency of eating out of boredom, stress, or anger, overeating, skipping meals, and consuming energy-dense foods (OR/RR range: 1.08-3.50, P ≤ 0.018). Long sleep duration was linked to higher emotional eating (OR range: 1.16-1.19, P < 0.001) but showed fewer signs of impulsivity or disinhibited intake. Some behaviours, like adding sugar to food and snacking, were not consistently related to sleep characteristics. In conclusion, short and poor-quality sleep are associated with eating patterns that may increase obesity risk. Interventions targeting sleep extension and quality could support healthier dietary behaviours and appetite regulation.

Adults living with overweight or obesity do not represent a single homogenous group in terms of mortality and disease risks. The aim of our study was to evaluate how the associations of adulthood overweight and obesity with mortality and incident disease are modified by (i.e., differ according to) self-reported childhood body weight categories. The sample comprised 191,181 men and 242,806 women aged 40–69 years (in 2006–2010) in the UK Biobank. The outcomes were all-cause mortality, incident cardiovascular disease (CVD), and incident obesity-related cancer. Cox proportional hazards regression models were used to estimate how the associations with the outcomes of adulthood weight status (normal weight, overweight, obesity) differed according to perceived body weight at age 10 years (about average, thinner, plumper). To triangulate results using an approach that better accounts for confounding, analyses were repeated using previously developed and validated polygenic risk scores (PRSs) for childhood body weight and adulthood BMI, categorised into three-tier variables using the same proportions as in the observational variables. In both sexes, adulthood obesity was associated with higher hazards of all outcomes. However, the associations of obesity with all-cause mortality and incident CVD were stronger in adults who reported being thinner at 10 years. For example, obesity was associated with a 1.28 (1.21, 1.35) times higher hazard of all-cause mortality in men who reported being an average weight child, but among men who reported being a thinner child this estimate was 1.63 (1.53, 1.75). The ratio between these two estimates was 1.28 (1.17, 1.40). There was also some evidence that the associations of obesity with all-cause mortality and incident CVD were stronger in adults who reported being plumper at 10 years. In genetic analyses, however, there was no evidence that the association of obesity (according to the adult PRS) with mortality or incident CVD differed according to childhood body size (according to the child PRS). For incident obesity-related cancer, the evidence for effect modification was limited and inconsistent between the observational and genetic analyses. Greater risks for all-cause mortality and incident CVD in adults with obesity who perceive themselves to have been a thinner or plumper than average child may be due to confounding and/or recall bias.

Self-reported physical activity is associated with lower brain food cue responsiveness in reward-related regions, but relationships utilizing objective physical activity measurement tools have not been explored. This cross-sectional study examined whether device-measured moderate-to-vigorous intensity physical activity and sedentary time are related to neural responses to visual food cues using functional magnetic resonance imaging. Fifty-one healthy adults (30 men, 21 women; mean ± SD: age 26 ± 6 years; body mass index 24.1 ± 3.0 kg/m 2 ) underwent a functional magnetic resonance imaging scan after an overnight fast while viewing images of high/very high-energy density foods (HED), very low/low-energy density foods (LED) and non-food objects. Free-living moderate-to-vigorous intensity physical activity and sedentary time were measured for seven consecutive days using an ActiGraph wGT3X-BT and activPAL4 accelerometer, respectively. Associations of behavioural variables with brain food cue reactivity were examined in regression models controlling for physiological and behavioural covariates. After adjusting for age, sex, body mass index and device weartime, moderate-to-vigorous intensity physical activity was negatively associated with reactivity to LED versus non-food cues in the precentral gyrus, hippocampus, posterior insula, and amygdala, which may diminish inhibitory-related responses towards healthier lower energy value foods. Time spent in moderate-to-vigorous intensity physical activity was positively associated with reactivity to LED versus non-food cues in the dorsal striatum, a region implicated in food motivation. A positive association was identified between sedentary time and reactivity to HED versus non-food cues in the dorsal division of the posterior cingulate gyrus that has been implicated in attention allocation. These findings suggest that moderate-to-vigorous intensity physical activity may enhance the appeal of and motivation to consume LED foods, whereas sedentary time may promote attention towards HED foods, highlighting the potential for engaging in greater physical activity and less sedentary time to positively influence the central (brain) appetite control system.

Background: Physical activity, sedentary behaviour, and sleep are interdependent components of the 24 h movement profile that may influence appetite control. While acute exercise can alter appetite perceptions and food reward, less is known about how reallocating time between daily behaviours affects appetite outcomes under free-living conditions. Methods: We applied isotemporal-substitution modelling in a cross-sectional study of 130 young, healthy, active adults. Accelerometer-derived estimates of sedentary time, light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and sleep were analysed in relation to energy intake (food diaries, laboratory meals), subjective appetite perceptions, appetite-related hormones (acylated ghrelin, PYY, leptin), and psychological traits, including food reward (Leeds Food Preference Questionnaire, LFPQ), food cravings (Control of Eating Questionnaire, CoEQ), and eating behaviour traits (Three-Factor Eating Questionnaire, TFEQ). Results: Reallocating 30 min/day of sedentary time to MVPA was associated with higher energy intake in free-living (+113 kcal/day, 95% CI: 34-192) and laboratory settings (+120 kcal/day, 95% CI: 55-185), along with greater postprandial hunger and prospective food consumption, reduced fullness, elevated fasting acylated ghrelin, and lower postprandial PYY. No associations were observed for reallocations to LPA or sleep. Furthermore, sedentary time reallocations were unrelated to leptin or psychological eating traits assessed by the LFPQ, CoEQ, or TFEQ. Conclusions: In this population, reallocating sedentary time to MVPA was linked to physiological and behavioural compensation consistent with elevated energy demands, whereas reallocating to LPA or sleep showed no associations. Trait-level eating behaviours were unaffected, suggesting MVPA influences appetite primarily through acute physiological rather than enduring cognitive or hedonic pathways.