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14/191) and University of Auckland Faculty Research Development Fund. The Cambridge Weight Plan© donated all products for the 8-week LED period. The Danish Agriculture & Food Council. The Danish Meat and Research Institute. National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK). Engineering and Physical Sciences Research Council (EPSRC) (UK). Nutritics (Dublin) donated all dietary analyses software used by UNOTT. Juho Vainio Foundation (FIN), Academy of Finland (grant numbers: 272376, 314383, 266286, 314135), Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation, Finnish Diabetes Research Foundation, University of Helsinki, Government Research Funds for Helsinki University Hospital (FIN), Jenny and Antti Wihuri Foundation (FIN), Emil Aaltonen Foundation (FIN). China Scholarship Council. ; Plant-based diets are recommended by dietary guidelines. This secondary analysis aimed to assess longitudinal associations of an overall plant-based diet and specific plant foods with weight-loss maintenance and cardiometabolic risk factors. Longitudinal data on 710 participants (aged 26–70 years) with overweight or obesity and pre-diabetes from the 3-year weight-loss maintenance phase of the PREVIEW intervention were analyzed. Adherence to an overall plant-based diet was evaluated using a novel plant-based diet index, where all plant-based foods received positive scores and all animal-based foods received negative scores. After adjustment for potential confounders, linear mixed models with repeated measures showed that the plant-based diet index was inversely associated with weight regain, but not with cardiometabolic risk factors. Nut intake was inversely associated with regain of weight and fat mass and increments in total cholesterol and LDL cholesterol. Fruit intake was inversely associated with increments in diastolic blood pressure, total cholesterol, and LDL cholesterol. Vegetable intake was inversely associated with an increment in diastolic blood pressure and triglycerides and was positively associated with an increase in HDL cholesterol. All reported associations with cardiometabolic risk factors were independent of weight change. Long-term consumption of nuts, fruits, and vegetables may be beneficial for weight management and cardiometabolic health, whereas an overall plant-based diet may improve weight management only. ; publishersversion ; published

14/191 ) and University of Auckland Faculty Research Development Fund. The Cambridge Weight Plan© donated all products for the 8-weeks LED period. The Danish Agriculture & Food Council. The Danish Meat and Research Institute. National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK). Engineering and Physical Sciences Research Council (EPSRC) (UK). Nutritics (Dublin) donated all dietary analyses software used by UNOTT. Juho Vainio Foundation (FIN), Academy of Finland (grant numbers: 272376 , 314383 , 266286 , 314135 ), Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation, Finnish Diabetes Research Foundation, University of Helsinki, Government Research Funds for Helsinki University Hospital (FIN), Jenny and Antti Wihuri Foundation (FIN), Emil Aaltonen Foundation (FIN). China Scholarship Council. The funding sources had no role in the study design and conduct, data analysis, or manuscript preparation. Publisher Copyright: © 2021 The Author(s) ; Background & aims: The association of quantity and quality of carbohydrate sources with appetite during long-term weight-loss maintenance (WLM) after intentional weight loss (WL) is unclear. We aimed to investigate longitudinal associations of quantity and quality of carbohydrate sources with changes in subjective appetite sensations during WLM. Methods: This secondary analysis evaluated longitudinal data from the 3-year WLM phase of the PREVIEW study, a 2 × 2 factorial (diet–physical activity arms), multi-center, randomized trial. 1279 individuals with overweight or obesity and prediabetes (25–70 years; BMI≥25 kg m−2) were included. Individuals were merged into 1 group to assess longitudinal associations of yearly changes in appetite sensations. Quantity and quality of carbohydrate sources including total carbohydrate, glycemic index (GI), glycemic load (GL), and total dietary fiber were assessed via 4-day food diaries at 4 timepoints (26, 52, 104, and 156 weeks) during WLM. Visual analog scales were used to assess appetite sensations in the previous week. Results: During WLM, participants consumed on average 160.6 (25th, 75th percentiles 131.1, 195.8) g·day−1 of total carbohydrate, with GI 53.8 (48.7, 58.8) and GL 85.3 (67.2, 108.9) g day−1, and 22.3 (17.6, 27.3) g·day−1 of dietary fiber. In the available-case analysis, multivariable-adjusted linear mixed models with repeated measures showed that each 30-g increment in total carbohydrate was associated with increases in hunger (1.36 mm year−1, 95% CI 0.77, 1.95, P < 0.001), desire to eat (1.10 mm year−1, 0.59, 1.60, P < 0.001), desire to eat something sweet (0.99 mm year−1, 0.30, 1.68, P = 0.005), and weight regain (0.20%·year−1, 0.03, 0.36, P = 0.022). Increasing GI was associated with weight regain, but not associated with increases in appetite sensations. Each 20-unit increment in GL was associated with increases in hunger (0.92 mm year−1, 0.33, 1.51, P = 0.002), desire to eat (1.12 mm year−1, 0.62, 1.62, P < 0.001), desire to eat something sweet (1.13 mm year−1, 0.44, 1.81, P < 0.001), and weight regain (0.35%·year−1, 0.18, 0.52, P < 0.001). Surprisingly, dietary fiber was also associated with increases in desire to eat, after adjustment for carbohydrate or GL. Conclusions: In participants with moderate carbohydrate and dietary fiber intake, and low to moderate GI, we found that higher total carbohydrate, GL, and total fiber, but not GI, were associated with increases in subjective desire to eat or hunger over 3 years. This study was registered as ClinicalTrials.gov, NCT01777893. ; publishersversion ; published

Funding: Open Access funding provided by University of Helsinki including Helsinki University Central Hospital. This research was supported by the EU Seventh Framework Programme (FP7; 2007– 2013) (grant no. 312057); National Health and Medical Research Council (EU Collaborative Grant AUS 8, ID 1067711); Glycemic Diabetologia Index Foundation Australia through royalties to the University of Sydney; Health Research Council of New Zealand (grant no. 14/191) and University of Auckland Faculty Research Development Fund; Cambridge Weight Plan, which donated all products for the 8 week weight loss period; Danish Agriculture & Food Council; Danish Meat Research Institute; National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK); Biotechnology and Biological Sciences Research Council (BBSRC) (UK); Engineering and Physical Sciences Research Council (EPSRC) (UK); Nutritics (Dublin), which donated all dietary analysis software used by the University of Nottingham; Juho Vainio Foundation (Finland); Academy of Finland (grant nos 272376, 314383, 266286 and 314135); Finnish Medical Foundation; Gyllenberg Foundation (Finland); Novo Nordisk Foundation; Finnish Diabetes Research Foundation; University of Helsinki; Government Research Funds for Helsinki University Hospital; Jenny and Antti Wihuri Foundation (Finland); Emil Aaltonen Foundation (Finland); and China Scholarship Council. The funders were not involved in the design of the study, the collection, analysis and interpretation of the data or writing of the report and did not impose any restrictions regarding the publication of the report. ; AIMS/HYPOTHESIS: Lifestyle interventions are the first-line treatment option for body weight and cardiometabolic health management. However, whether age groups or women and men respond differently to lifestyle interventions is under debate. We aimed to examine age- and sex-specific effects of a low-energy diet (LED) followed by a long-term lifestyle intervention on body weight, body composition and ...

14/191) and University of Auckland Faculty Research Development Fund. The Cambridge Weight Plan© donated all products for the 8-weeks LED period. The Danish Agriculture & Food Council. The Danish Meat and Research Institute. National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK). Engineering and Physical Sciences Research Council (EPSRC) (UK). Nutritics (Dublin) donated all dietary analyses software used by UNOTT. Juho Vainio Foundation (FIN), Academy of Finland (grant numbers: 272376, 314383, 266286, 314135), Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation, Finnish Diabetes Research Foundation, University of Helsinki, Government Research Funds for Helsinki University Hospital (FIN), Jenny and Antti Wihuri Foundation (FIN), Emil Aaltonen Foundation (FIN). China Scholarship .The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. ; Background: Previous studies have shown an increase in hunger during weight-loss maintenance (WLM) after diet-induced weight loss. Whether a combination of a higher protein, lower glycemic index (GI) diet and physical activity (PA) can counteract this change remains unclear. Aim: To compare the long-term effects of two diets [high protein (HP)-low GI vs. moderate protein (MP)-moderate GI] and two PA programs [high intensity (HI) vs. moderate intensity (MI)] on subjective appetite sensations during WLM after ≥8% weight loss (WL). Methods: Data derived from the 3-years PREVIEW randomized intervention study. An 8-weeks WL phase using a low-energy diet was followed by a 148-weeks randomized WLM phase. For the WLM phase, participants were assigned to one of the four groups: HP-MI, HP-HI, MP-MI, and MP-HI. Available data from 2,223 participants with overweight or obesity (68% women; BMI ≥ 25 kg/m2). Appetite sensations including satiety, hunger, desire to eat, and desire to eat something sweet during the two phases (at 0, 8 weeks and 26, 52, 104, and 156 weeks) were assessed based on the recall of feelings during the previous week using visual analogue scales. Differences in changes in appetite sensations from baseline between the groups were determined using linear mixed models with repeated measures. Results: There was no significant diet × PA interaction. From 52 weeks onwards, decreases in hunger were significantly greater in HP-low GI than MP-moderate GI (Ptime × diet = 0.018, Pdietgroup = 0.021). Although there was no difference in weight regain between the diet groups (Ptime × diet = 0.630), hunger and satiety ratings correlated with changes in body weight at most timepoints. There were no significant differences in appetite sensations between the two PA groups. Decreases in hunger ratings were greater at 52 and 104 weeks in HP-HI vs. MP-HI, and greater at 104 and 156 weeks in HP-HI vs. MP-MI. Conclusions: This is the first long-term, large-scale randomized intervention to report that a HP-low GI diet was superior in preventing an increase in hunger, but not weight regain, during 3-years WLM compared with a MP-moderate GI diet. Similarly, HP-HI outperformed MP-HI in suppressing hunger. The role of exercise intensity requires further investigation. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT01777893. ; publishersversion ; published

Diet-quality scores (DQS), which are developed across the globe, are used to define adherence to specific eating patterns and have been associated with risk of coronary heart disease and type-II diabetes. We explored the association between five diet-quality scores (Healthy Eating Index, HEI; Alternate Healthy Eating Index, AHEI; MedDietScore, MDS; PREDIMED Mediterranean Diet Score, P-MDS; Dutch Healthy Diet-Index, DHDI) and markers of metabolic health (anthropometry, objective physical activity levels (PAL), and dried blood spot total cholesterol (TC), total carotenoids, and omega-3 index) in the Food4Me cohort, using regression analysis. Dietary intake was assessed using a validated Food Frequency Questionnaire. Participants (n = 1480) were adults recruited from seven European Union (EU) countries. Overall, women had higher HEI and AHEI than men (p < 0.05), and scores varied significantly between countries. For all DQS, higher scores were associated with lower body mass index, lower waist-to-height ratio and waist circumference, and higher total carotenoids and omega-3-index (p trends < 0.05). Higher HEI, AHEI, DHDI, and P-MDS scores were associated with increased daily PAL, moderate and vigorous activity, and reduced sedentary behaviour (p trend < 0.05). We observed no association between DQS and TC. To conclude, higher DQS, which reflect better dietary patterns, were associated with markers of better nutritional status and metabolic health.

Diet-quality scores (DQS), which are developed across the globe, are used to define adherence to specific eating patterns and have been associated with risk of coronary heart disease and type-II diabetes. We explored the association between five diet-quality scores (Healthy Eating Index, HEI; Alternate Healthy Eating Index, AHEI; MedDietScore, MDS; PREDIMED Mediterranean Diet Score, P-MDS; Dutch Healthy Diet-Index, DHDI) and markers of metabolic health (anthropometry, objective physical activity levels (PAL), and dried blood spot total cholesterol (TC), total carotenoids, and omega-3 index) in the Food4Me cohort, using regression analysis. Dietary intake was assessed using a validated Food Frequency Questionnaire. Participants (n = 1480) were adults recruited from seven European Union (EU) countries. Overall, women had higher HEI and AHEI than men (p < 0.05), and scores varied significantly between countries. For all DQS, higher scores were associated with lower body mass index, lower waist-to-height ratio and waist circumference, and higher total carotenoids and omega-3-index (p trends < 0.05). Higher HEI, AHEI, DHDI, and P-MDS scores were associated with increased daily PAL, moderate and vigorous activity, and reduced sedentary behaviour (p trend < 0.05). We observed no association between DQS and TC. To conclude, higher DQS, which reflect better dietary patterns, were associated with markers of better nutritional status and metabolic health.

Limited data exists on the interrelationships between physical activity (PA), sedentary behaviors and sleep concerning cardiometabolic risk factors in aged adults at high cardiovascular disease risk. Our aim was to examine independent and joint associations between time spent in leisure-time PA, sedentary behaviors and sleep on the prevalence of obesity, type 2 diabetes (T2D) and components of the metabolic syndrome (MetS) in Mediterranean individuals at high cardiovascular risk. Cross-sectional analyses were performed on baseline data from 5776 Spanish adults (aged 55-75y in men; 60-75y in women) with overweight/obesity and MetS, from October 2013 to October 2016, in the PREDIMED-PLUS trial. Employing multivariable-adjusted Cox regression with robust variance and constant time (given the cross-sectional design), higher prevalence of obesity, T2D and abdominal obesity as component of the MetS were associated with greater time in TV-viewing (Relative Risk, RR: 1.02, 95%CI: 1.01, 1.03; RR:1.04, 95%CI: 1.02, 1.06 and RR: 1.01 95%CI: 1.00, 1.02; respectively, all P < .01). Conversely, greater time in moderate-vigorous PA (MVPA) was associated with lower prevalence of obesity, T2D, abdominal obesity and low HDL-cholesterol (RR: 0.95, 95%CI: 0.93, 0.97; RR: 0.94, 95%CI: 0.89, 0.99; RR: 0.97, 95%CI: 0.96, 0.98; and RR: 0.95, 95%CI: 0.91, 0.99, respectively, all P < .05). For these outcomes, theoretically substituting 1-h/day of MVPA for 1-h/day TV-viewing was also significantly associated with lower prevalence (RR 0.91 to 0.97, all P < .05). Similar lower RR in these outcomes was observed when substituting 1-h/day of MVPA for 1-h/day of sleeping. Longer time watching TV and not meeting MVPA recommendations were jointly associated with higher RR of the prevalence of obesity and T2D. We concluded that, in senior individuals at high cardiovascular risk, greater time spent on MVPA and fewer on sedentary behaviors was inversely associated with prevalence of obesity, T2D, and some of the components of MetS. ; This study was funded by the Spanish Ministry of Health (Carlos III Health Institute) through the Fondo de Investigacion para la Salud (FIS), which is co-funded by the European Regional Development Fund (two coordinated FIS projects leaded by Jordi Salas-Salvado and Josep Vidal, including the following projects: PI13/00673, PI13/00492, PI13/00272, PI13/01123, PI13/00462, PI13/00233, PI13/02184, PI13/00728 PI13/01090 PI13/01056, PI14/01722, PI14/00636, PI14/00618, PI14- 00696, PI14/01206, PI14/01919, PI14/00853), the European Research Council (Advanced Research Grant 2013-2018; 340918) granted to MAMG, the Recercaixa grant 2013 (2013ACUP00194), the grant from the Consejeria de Salud de la Junta de Andalucia (PI0458/2013), and the SEMERGEN grant. NRE has been beneficiary of a predoctoral FIAGAUR 2016 Grant from the Catalan Government; Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement de la Generalitat de Catalunya. None of the funding sources took part in the design, collection, analysis or interpretation of the data, or in the decision to submit the manuscript for publication. CIBERobn (Centros de Investigacion Biomedica en Red: Obesidad y Nutricion), CIBEResp (Centros de Investigacion Biomedica en Red: Epidemiologia y Salud Publica) and CIBERdem (Centros de Investigacion Biomedica en Red: Diabetes y Enfermedades Metabolicas asociadas) are initiatives of ISCIII, Madrid, Spain. ; Sí

Diet-quality scores (DQS), which are developed across the globe, are used to define adherence to specific eating patterns and have been associated with risk of coronary heart disease and type-II diabetes. We explored the association between five diet-quality scores (Healthy Eating Index,HEI; Alternate Healthy Eating Index, AHEI; MedDietScore, MDS; PREDIMED Mediterranean DietScore, P-MDS; Dutch Healthy Diet-Index, DHDI) and markers of metabolic health (anthropometry,objective physical activity levels (PAL), and dried blood spot total cholesterol (TC), total carotenoids,and omega-3 index) in the Food4Me cohort, using regression analysis. Dietary intake was assessed using a validated Food Frequency Questionnaire. Participants (n= 1480) were adults recruited from seven European Union (EU) countries. Overall, women had higher HEI and AHEI than men (p< 0.05), and scores varied significantly between countries. For all DQS, higher scores were associated with lower body mass index, lower waist-to-height ratio and waist circumference, and higher total carotenoids and omega-3-index (p trends < 0.05). Higher HEI, AHEI, DHDI, and P-MDS scores were associated with increased daily PAL, moderate and vigorous activity, and reduced sedentary behaviour (p trend < 0.05). We observed no association between DQS and TC. To conclude,higher DQS, which reflect better dietary patterns, were associated with markers of better nutritional status and metabolic health.

Diet-quality scores (DQS), which are developed across the globe, are used to define adherence to specific eating patterns and have been associated with risk of coronary heart disease and type-II diabetes. We explored the association between five diet-quality scores (Healthy Eating Index, HEI; Alternate Healthy Eating Index, AHEI; MedDietScore, MDS; PREDIMED Mediterranean Diet Score, P-MDS; Dutch Healthy Diet-Index, DHDI) and markers of metabolic health (anthropometry, objective physical activity levels (PAL), and dried blood spot total cholesterol (TC), total carotenoids, and omega-3 index) in the Food4Me cohort, using regression analysis. Dietary intake was assessed using a validated Food Frequency Questionnaire. Participants (n = 1480) were adults recruited from seven European Union (EU) countries. Overall, women had higher HEI and AHEI than men (p < 0.05), and scores varied significantly between countries. For all DQS, higher scores were associated with lower body mass index, lower waist-to-height ratio and waist circumference, and higher total carotenoids and omega-3-index (p trends < 0.05). Higher HEI, AHEI, DHDI, and P-MDS scores were associated with increased daily PAL, moderate and vigorous activity, and reduced sedentary behaviour (p trend < 0.05). We observed no association between DQS and TC. To conclude, higher DQS, which reflect better dietary patterns, were associated with markers of better nutritional status and metabolic health.

Diet-quality scores (DQS), which are developed across the globe, are used to define adherence to specific eating patterns and have been associated with risk of coronary heart disease and type-II diabetes. We explored the association between five diet-quality scores (Healthy Eating Index, HEI; Alternate Healthy Eating Index, AHEI; MedDietScore, MDS; PREDIMED Mediterranean Diet Score, P-MDS; Dutch Healthy Diet-Index, DHDI) and markers of metabolic health (anthropometry, objective physical activity levels (PAL), and dried blood spot total cholesterol (TC), total carotenoids, and omega-3 index) in the Food4Me cohort, using regression analysis. Dietary intake was assessed using a validated Food Frequency Questionnaire. Participants (n = 1480) were adults recruited from seven European Union (EU) countries. Overall, women had higher HEI and AHEI than men (p < 0.05), and scores varied significantly between countries. For all DQS, higher scores were associated with lower body mass index, lower waist-to-height ratio and waist circumference, and higher total carotenoids and omega-3-index (p trends < 0.05). Higher HEI, AHEI, DHDI, and P-MDS scores were associated with increased daily PAL, moderate and vigorous activity, and reduced sedentary behaviour (p trend < 0.05). We observed no association between DQS and TC. To conclude, higher DQS, which reflect better dietary patterns, were associated with markers of better nutritional status and metabolic health.