The effect of protein and glycemic index on children's body composition: the DiOGenes randomized study

OBJECTIVE: To investigate the effect of protein and glycemic index (GI) on body composition among European children in the randomized, 6-month dietary intervention DiOGenes (diet, obesity, and genes) family-based study. PATIENTS AND METHODS: In the study, 827 children (381 boys and 446 girls), aged 5 to 18 years, completed baseline examinations. Families with parents who lost >= 8% of their weight during an 8-week run-in low-calorie diet period were randomly assigned to 1 of 5 ad libitum diets: low protein (LP)/low glycemic index (LGI); LP/high GI (HGI); high protein (HP)/LGI; HP/HGI; and control diet. The target difference was 15 GI U between the LGI/HGI groups and 13 protein percentage points between the LP/HP groups. There were 658 children examined after 4 weeks. Advice on food-choice modification was provided at 6 visits during this period. No advice on weight loss was provided because the focus of the study was the ability of the diets to affect outcomes through appetite regulation. Anthropometric measurements and body composition were assessed at baseline, week 4, and week 26. RESULTS: In the study, 465 children (58.1%) completed all assessments. The achieved differences between the GI and protein groups were 2.3 GI U and 4.9 protein percentage points, respectively. The LP/HGI group increased body fat percentage significantly more than the other groups (P = .040; partial eta(2) = 0.039), and the percentage of overweight/obese children in the HP/LGI group decreased significantly during the intervention (P = .031). CONCLUSIONS: Neither GI nor protein had an isolated effect on body composition. However, the LP/HGI combination increased body fat, whereas the HP/LGI combination was protective against obesity in this sample of children

Diets with high or low protein content and glycemic index for weight-loss maintenance

BACKGROUND: Studies of weight-control diets that are high in protein or low in glycemic index have reached varied conclusions, probably owing to the fact that the studies had insufficient power. METHODS: We enrolled overweight adults from eight European countries who had lost at least 8% of their initial body weight with a 3.3-MJ (800-kcal) low-calorie diet. Participants were randomly assigned, in a two-by-two factorial design, to one of five ad libitum diets to prevent weight regain over a 26-week period: a low-protein and low-glycemic-index diet, a low-protein and high-glycemic-index diet, a high-protein and low-glycemic-index diet, a high-protein and high-glycemic-index diet, or a control diet. RESULTS: A total of 1209 adults were screened (mean age, 41 years; body-mass index [the weight in kilograms divided by the square of the height in meters], 34), of whom 938 entered the low-calorie-diet phase of the study. A total of 773 participants who completed that phase were randomly assigned to one of the five maintenance diets; 548 completed the intervention (71%). Fewer participants in the high-protein and the low-glycemic-index groups than in the low-protein-high-glycemic-index group dropped out of the study (26.4% and 25.6%, respectively, vs. 37.4%; P=0.02 and P=0.01 for the respective comparisons). The mean initial weight loss with the low-calorie diet was 11.0 kg. In the analysis of participants who completed the study, only the low-protein-high-glycemic-index diet was associated with subsequent significant weight regain (1.67 kg; 95% confidence interval [CI], 0.48 to 2.87). In an intention-to-treat analysis, the weight regain was 0.93 kg less (95% CI, 0.31 to 1.55) in the groups assigned to a high-protein diet than in those assigned to a low-protein diet (P=0.003) and 0.95 kg less (95% CI, 0.33 to 1.57) in the groups assigned to a low-glycemic-index diet than in those assigned to a high-glycemic-index diet (P=0.003). The analysis involving participants who completed the intervention produced similar results. The groups did not differ significantly with respect to diet-related adverse events. CONCLUSIONS: In this large European study, a modest increase in protein content and a modest reduction in the glycemic index led to an improvement in study completion and maintenance of weight loss

Caloric restriction induces changes in insulin and body weight measurements that are inversely associated with subsequent weight regain

BACKGROUND: Successful weight maintenance following weight loss is challenging for many people. Identifying predictors of longer-term success will help target clinical resources more effectively. To date, focus has been predominantly on the identification of predictors of weight loss. The goal of the current study was to determine if changes in anthropometric and clinical parameters during acute weight loss are associated with subsequent weight regain. METHODOLOGY: The study consisted of an 8-week low calorie diet (LCD) followed by a 6-month weight maintenance phase. Anthropometric and clinical parameters were analyzed before and after the LCD in the 285 participants (112 men, 173 women) who regained weight during the weight maintenance phase. Mixed model ANOVA, Spearman correlation, and linear regression were used to study the relationships between clinical measurements and weight regain. PRINCIPAL FINDINGS: Gender differences were observed for body weight and several clinical parameters at both baseline and during the LCD-induced weight loss phase. LCD-induced changes in BMI (Spearman's ρ = 0.22, p = 0.0002) were inversely associated with weight regain in both men and women. LCD-induced changes in fasting insulin (ρ = 0.18, p = 0.0043) and HOMA-IR (ρ = 0.19, p = 0.0023) were also associated independently with weight regain in both genders. The aforementioned associations remained statistically significant in regression models taking account of variables known to independently influence body weight. CONCLUSIONS/SIGNIFICANCE: LCD-induced changes in BMI, fasting insulin, and HOMA-IR are inversely associated with weight regain in the 6-month period following weight loss

Blood profile of proteins and steroid hormones predicts weight change after weight loss with interactions of dietary protein level and glycemic index

Weight regain after weight loss is common. In the Diogenes dietary intervention study, high protein and low glycemic index (GI) diet improved weight maintenance. OBJECTIVE: To identify blood predictors for weight change after weight loss following the dietary intervention within the Diogenes study. DESIGN: Blood samples were collected at baseline and after 8-week low caloric diet-induced weight loss from 48 women who continued to lose weight and 48 women who regained weight during subsequent 6-month dietary intervention period with 4 diets varying in protein and GI levels. Thirty-one proteins and 3 steroid hormones were measured. RESULTS: Angiotensin I converting enzyme (ACE) was the most important predictor. Its greater reduction during the 8-week weight loss was related to continued weight loss during the subsequent 6 months, identified by both Logistic Regression and Random Forests analyses. The prediction power of ACE was influenced by immunoproteins, particularly fibrinogen. Leptin, luteinizing hormone and some immunoproteins showed interactions with dietary protein level, while interleukin 8 showed interaction with GI level on the prediction of weight maintenance. A predictor panel of 15 variables enabled an optimal classification by Random Forests with an error rate of 24±1%. A logistic regression model with independent variables from 9 blood analytes had a prediction accuracy of 92%. CONCLUSIONS: A selected panel of blood proteins/steroids can predict the weight change after weight loss. ACE may play an important role in weight maintenance. The interactions of blood factors with dietary components are important for personalized dietary advice after weight loss

TFAP2B influences the effect of dietary fat on weight loss under energy restriction

BACKGROUND: Numerous gene loci are related to single measures of body weight and shape. We investigated if 55 SNPs previously associated with BMI or waist measures, modify the effects of fat intake on weight loss and waist reduction under energy restriction. METHODS AND FINDINGS: Randomized controlled trial of 771 obese adults. (Registration: ISRCTN25867281.) One SNP was selected for replication in another weight loss intervention study of 934 obese adults. The original trial was a 10-week 600 kcal/d energy-deficient diet with energy percentage from fat (fat%) in range of 20-25 or 40-45. The replication study used an 8-weeks diet of 880 kcal/d and 20 fat%; change in fat% intake was used for estimation of interaction effects. The main outcomes were intervention weight loss and waist reduction. In the trial, mean change in fat% intake was -12/+4 in the low/high-fat groups. In the replication study, it was -23/-12 among those reducing fat% more/less than the median. TFAP2B-rs987237 genotype AA was associated with 1.0 kg (95% CI, 0.4; 1.6) greater weight loss on the low-fat, and GG genotype with 2.6 kg (1.1; 4.1) greater weight loss on the high-fat (interaction p-value; p = 0.00007). The replication study showed a similar (non-significant) interaction pattern. Waist reduction results generally were similar. Study-strengths include (i) the discovery study randomised trial design combined with the replication opportunity (ii) the strict dietary intake control in both studies (iii) the large sample sizes of both studies. Limitations are (i) the low minor allele frequency of the TFAP2B polymorphism, making it hard to investigate non-additive genetic effects (ii) the different interventions preventing identical replication-discovery study designs (iii) some missing data for non-completers and dietary intake. No adverse effects/outcomes or side-effects were observed. CONCLUSIONS: Under energy restriction, TFAP2B may modify the effect of dietary fat intake on weight loss and waist reduction

Parental Perceptions of Children’s Weight Status in 22 Countries: The WHO European Childhood Obesity Surveillance Initiative: COSI 2015/2017

Introduction: Parents can act as important agents of change and support for healthy childhood growth and development. Studies have found that parents may not be able to accurately perceive their child’s weight status. The purpose of this study was to measure parental perceptions of their child’s weight status and to identify predictors of potential parental misperceptions. Methods: We used data from the World Health Organization (WHO) European Childhood Obesity Surveillance Initiative and 22 countries. Parents were asked to identify their perceptions of their children’s weight status as “underweight,” “normal weight,” “a little overweight,” or “extremely overweight.” We categorized children’s (6–9 years; n = 124,296) body mass index (BMI) as BMI-for-age Z-scores based on the 2007 WHO-recommended growth references. For each country included in the analysis and pooled estimates (country level), we calculated the distribution of children according to the WHO weight status classification, distribution by parental perception of child’s weight status, percentages of accurate, overestimating, or underestimating perceptions, misclassification levels, and predictors of parental misperceptions using a multilevel logistic regression analysis that included only children with overweight (including obesity). Statistical analyses were performed using Stata version 15 1. Results: Overall, 64.1% of parents categorized their child’s weight status accurately relative to the WHO growth charts. However, parents were more likely to underestimate their child’s weight if the child had overweight (82.3%) or obesity (93.8%). Parents were more likely to underestimate their child’s weight if the child was male (adjusted OR [adjOR]: 1.41; 95% confidence intervals [CI]: 1.28–1.55); the parent had a lower educational level (adjOR: 1.41; 95% CI: 1.26–1.57); the father was asked rather than the mother (adjOR: 1.14; 95% CI: 0.98–1.33); and the family lived in a rural area (adjOR: 1.10; 95% CI: 0.99–1.24). Overall, parents’ BMI was not strongly associated with the underestimation of children’s weight status, but there was a stronger association in some countries. Discussion/Conclusion: Our study supplements the current literature on factors that influence parental perceptions of their child’s weight status. Public health interventions aimed at promoting healthy childhood growth and development should consider parents’ knowledge and perceptions, as well as the sociocultural contexts in which children and families live.The authors gratefully acknowledge support from a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. Data collection in the countries was made possible through funding by: Albania: World Health Organization through the Joint Programme on Children, Food Security and Nutrition “Reducing Malnutrition in Children,” funded by the Millennium Development Goals Achievement Fund, and the Institute of Public Health; Bulgaria: Ministry of Health, National Center of Public Health and Analyses, World Health Organization Regional Office for Europe; Croatia: Ministry of Health, Croatian Institute of Public Health and World Health Organization Regional Office for Europe; Czechia: Grants AZV MZČR 17-31670 A and MZČR – RVO EÚ 00023761; Denmark: Danish Ministry of Health; France: French Public Health Agency; Georgia: World Health Organization; Ireland: Health Service Executive; Italy: Ministry of Health; Istituto Superiore di sanità (National Institute of Health); Kazakhstan: Ministry of Health of the Republic of Kazakhstan and World Health Organization Country Office; Latvia: n/a; Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and World Health Organization; Malta: Ministry of Health; Montenegro: World Health Organization and Institute of Public Health of Montenegro; Poland: National Health Programme, Ministry of Health; Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates and the kind technical support of Center for Studies and Research on Social Dynamics and Health (CEIDSS); Romania: Ministry of Health; Russia (Moscow): n/a; San Marino: Health Ministry; Educational Ministry; Social Security Institute; the Health Authority; Spain: Spanish Agency for Food Safety and Nutrition (AESAN); Tajikistan: World Health Organization Country Office in Tajikistan and Ministry of Health and Social Protection; and Turkmenistan: World Health Organization Country Office in Turkmenistan and Ministry of Health. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated.info:eu-repo/semantics/publishedVersio

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

Dietary Intake of Protein from Different Sources and Weight Regain, Changes in Body Composition and Cardiometabolic Risk Factors after Weight Loss:The DIOGenes Study

An increase in dietary protein intake has been shown to improve weight loss maintenance in the DIOGenes trial. Here, we analysed whether the source of the dietary proteins influenced changes in body weight, body composition, and cardiometabolic risk factors during the weight maintenance period while following an energy-restricted diet. 489 overweight or obese participants of the DIOGenes trial from eight European countries were included. They successfully lost >8% of body weight and subsequently completed a six month weight maintenance period, in which they consumed an ad libitum diet varying in protein content and glycemic index. Dietary intake was estimated from three-day food diaries. A higher plant protein intake with a proportional decrease in animal protein intake did not affect body weight maintenance or cardiometabolic risk factors. A higher plant protein intake from non-cereal products instead of cereal products was associated with benefits for body weight maintenance and blood pressure. Substituting meat protein for protein from other animal sources increased insulin and HOMA-IR (homeostasis model assessment of insulin resistance). This analysis suggests that not only the amount of dietary proteins, but also the source may be important for weight and cardiometabolic risk management. However, randomized trials are needed to test the causality of these associations

Anthropometric and clinical characteristics of women according to weight control groups during dietary intervention.

<p>Anthropometric, clinical and plasma parameters were determined at baseline (BAS), after 8 weeks of low calorie diet (LCD), and after 6 months of weight maintenance diet (WMD) according to weight control groups during dietary intervention (WR, weight regain group; WS, weight stable group; WL, weight loss group). BMI, body mass index; CRP, C reactive protein; DBP, diastolic blood pressure; HDL, high density lipoprotein; HOMA-IR, homeostatic model assessment of insulin resistance; LDL, low density lipoprotein; SBP, systolic blood pressure. Variables are shown as means ± SEM. The effect of time was analyzed by repeated measures ANOVA with Bonferroni post hoc test: ^<i>1</i> p < 0.05, data significantly different from BAS. ^<i>2</i> p < 0.05, data significantly different from LCD. Between group difference was analyzed by one-way ANOVA with Bonferroni post hoc test: ^<i>3</i> p < 0.05, data significantly different from WL group. ^<i>4</i> p < 0.05, data significantly different from WR group.</p><p>Anthropometric and clinical characteristics of women according to weight control groups during dietary intervention.</p