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Objective: This study aimed to examine whether children in rural outdoor kindergartens had attained a lower body mass index z-score (BMIz) and were at lower risk of overweight after school entrance compared to children in urban conventional kindergartens. Methods: This is a longitudinal observational study of 1,544 children from outdoor kindergartens and 1,640 from conventional kindergartens. The mean age at kindergarten enrolment was 3.5 years (SD: 0.9) in the outdoor kindergartens and 3.6 years (SD: 1.0) in the conventional kindergartens. Anthropometry was measured after school entry by school health nurses when the children were 6 to 8 years old. Attained BMIz was included as the primary outcome. The risk of attaining overweight (including obesity) was included as a secondary outcome. Register-based information was available on potential confounding factors. Linear and logistic regression models were used to assess group differences in outcome measures. Results: Our basic models, with information on outcome, kindergarten type, and birth weight showed a borderline statistically significantly lower attained BMIz (−0.07 [95% CI: −0.14, 0.00], P = 0.060) and a lower risk of overweight (adjusted risk ratio: 0.83 [95% CI: 0.72, 0.97], P = 0.016) among children attending outdoor kindergartens. However, when adjusting for sociodemographic factors and parental BMI, there was no evidence of differences in attained BMIz (P = 0.153) or overweight (P = 0.967). Conclusion: When considering confounding factors, our findings indicate no differences in attained BMIz or risk of overweight after school entry among children attending rural outdoor kindergartens compared to those attending urban conventional kindergartens., Objective: This study aimed to examine whether children in rural outdoor kindergartens had attained a lower body mass index z-score (BMIz) and were at lower risk of overweight after school entrance compared to children in urban conventional kindergartens. Methods: This is a longitudinal observational study of 1,544 children from outdoor kindergartens and 1,640 from conventional kindergartens. The mean age at kindergarten enrolment was 3.5 years (SD: 0.9) in the outdoor kindergartens and 3.6 years (SD: 1.0) in the conventional kindergartens. Anthropometry was measured after school entry by school health nurses when the children were 6 to 8 years old. Attained BMIz was included as the primary outcome. The risk of attaining overweight (including obesity) was included as a secondary outcome. Register-based information was available on potential confounding factors. Linear and logistic regression models were used to assess group differences in outcome measures. Results: Our basic models, with information on outcome, kindergarten type, and birth weight showed a borderline statistically significantly lower attained BMIz (−0.07 [95% CI: −0.14, 0.00], P = 0.060) and a lower risk of overweight (adjusted risk ratio: 0.83 [95% CI: 0.72, 0.97], P = 0.016) among children attending outdoor kindergartens. However, when adjusting for sociodemographic factors and parental BMI, there was no evidence of differences in attained BMIz (P = 0.153) or overweight (P = 0.967). Conclusion: When considering confounding factors, our findings indicate no differences in attained BMIz or risk of overweight after school entry among children attending rural outdoor kindergartens compared to those attending urban conventional kindergartens.

Background: Optimal nutrition during early childhood, including dietary fibre intake, is important for children’s health and development. Knowledge of fibre intake and its determinants in early childhood is limited. We aimed to describe fibre intake and sources and to identify trajectories of fibre intake at age 9, 18, 42, and 60 months and its child and maternal determinants. Associations between fibre trajectory groups and BMI z-scores and child overweight status were also assessed. Methods: This is a secondary analysis of longitudinal data from the Melbourne InFANT Program, trial registration: Current Controlled Trials (ISRCTN81847050). Group-based trajectory modelling was used to identify trajectories of fibre intake from ages 9 to 60 months (n = 503). Multivariable logistic or linear regression was used to assess the determinants of fibre intake trajectories and the association between fibre intake trajectories and obesity outcomes. Results: Four fibre intake trajectory groups were identified, with three groups following stable, rising trajectories of “Low” (52.3%), “Moderate” (32.2%), and “High” (13.3%), respectively. The remaining followed an “unstable” trajectory (2.2%). Girls versus boys were more likely to follow the “Low” fibre intake trajectory, whereas children who were breastfed for ≥6 months and whose mother had a university education were less likely to follow the “Low” fibre trajectory. No association was found between fibre trajectory groups and obesity outcomes. Conclusion: Most children followed a stable, rising trajectory of low fibre intake in early childhood. Child sex, breastfeeding duration and maternal education were significant determinants of low fibre intake trajectory. Keywords: fibre intake; trajectory; determinants; obesity, Background: Optimal nutrition during early childhood, including dietary fibre intake, is important for children’s health and development. Knowledge of fibre intake and its determinants in early childhood is limited. We aimed to describe fibre intake and sources and to identify trajectories of fibre intake at age 9, 18, 42, and 60 months and its child and maternal determinants. Associations between fibre trajectory groups and BMI z-scores and child overweight status were also assessed. Methods: This is a secondary analysis of longitudinal data from the Melbourne InFANT Program, trial registration: Current Controlled Trials (ISRCTN81847050). Group-based trajectory modelling was used to identify trajectories of fibre intake from ages 9 to 60 months (n = 503). Multivariable logistic or linear regression was used to assess the determinants of fibre intake trajectories and the association between fibre intake trajectories and obesity outcomes. Results: Four fibre intake trajectory groups were identified, with three groups following stable, rising trajectories of “Low” (52.3%), “Moderate” (32.2%), and “High” (13.3%), respectively. The remaining followed an “unstable” trajectory (2.2%). Girls versus boys were more likely to follow the “Low” fibre intake trajectory, whereas children who were breastfed for ≥6 months and whose mother had a university education were less likely to follow the “Low” fibre trajectory. No association was found between fibre trajectory groups and obesity outcomes. Conclusion: Most children followed a stable, rising trajectory of low fibre intake in early childhood. Child sex, breastfeeding duration and maternal education were significant determinants of low fibre intake trajectory.

Background/Objectives The strong regulation of protein intake can lead to overconsumption of total energy on diets with a low proportion of energy from protein, a process referred to as protein leverage. The protein leverage hypothesis posits that protein leverage explains variation in energy intake and potentially obesity in ecological settings. Here, we tested for protein leverage and the protein leverage hypothesis in children and adolescents. Subjects/Methods A population sample of children, mean (SD) age 7.6 (0.4) years (n = 422), followed up at age 9.8 (0.4) years (n = 387) and at age 15.8 (0.4) years (n = 229), participating for the Physical Activity and Nutrition in Children (PANIC) study. Exposures: 4-day food records-related proportional energy intake of proteins, fats, and carbohydrates. Outcomes: energy intake, body mass index (BMI) z-score and dual-energy X-ray absorptiometry-related energy expenditure. Results Proportional energy intake of proteins was inversely associated with energy intake following power functions at all 3 ages (mean [95%CI] strength of leverage of L = −0.36 [−0.47 to −0.25]; L = −0.26 [−0.37 to −0.15]; L = −0.25 [−0.38 to −0.13]; all P < 0.001). Mixture analysis indicated that variance in energy intake was associated primarily with the proportional intake of energy from proteins, not with either fats or carbohydrates. At all 3 ages, energy intake was not associated with BMI z-score but positively associated with energy expenditure (all P < 0.001). Conclusions This study provides evidence consistent with protein leverage in a population sample of children and adolescents. Increased energy intake on diets with lower protein content was counterbalanced by increased energy expenditure and therefore did not translate into increased adiposity. Introduction, Background/Objectives: The strong regulation of protein intake can lead to overconsumption of total energy on diets with a low proportion of energy from protein, a process referred to as protein leverage. The protein leverage hypothesis posits that protein leverage explains variation in energy intake and potentially obesity in ecological settings. Here, we tested for protein leverage and the protein leverage hypothesis in children and adolescents. Subjects/Methods: A population sample of children, mean (SD) age 7.6 (0.4) years (n = 422), followed up at age 9.8 (0.4) years (n = 387) and at age 15.8 (0.4) years (n = 229), participating for the Physical Activity and Nutrition in Children (PANIC) study. Exposures: 4-day food records-related proportional energy intake of proteins, fats, and carbohydrates. Outcomes: energy intake, body mass index (BMI) z-score and dual-energy X-ray absorptiometry-related energy expenditure. Results: Proportional energy intake of proteins was inversely associated with energy intake following power functions at all 3 ages (mean [95%CI] strength of leverage of L = −0.36 [−0.47 to −0.25]; L = −0.26 [−0.37 to −0.15]; L = −0.25 [−0.38 to −0.13]; all P < 0.001). Mixture analysis indicated that variance in energy intake was associated primarily with the proportional intake of energy from proteins, not with either fats or carbohydrates. At all 3 ages, energy intake was not associated with BMI z-score but positively associated with energy expenditure (all P < 0.001). Conclusions: This study provides evidence consistent with protein leverage in a population sample of children and adolescents. Increased energy intake on diets with lower protein content was counterbalanced by increased energy expenditure and therefore did not translate into increased adiposity.

Objective In this study, the associations between the substitution of sedentary time with sleep or physical activity at different intensities and subsequent weight-loss maintenance were examined. Methods This prospective study included 1152 adults from the NoHoW trial who had achieved a successful weight loss of ≥5% during the 12 months prior to baseline and had BMI ≥25 kg/m2 before losing weight. Physical activity and sleep were objectively measured during a 14-day period at baseline. Change in body weight was included as the primary outcome. Secondary outcomes were changes in body fat percentage and waist circumference. Cardiometabolic variables were included as exploratory outcomes. Results Using isotemporal substitution models, no associations were found between activity substitutions and changes in body weight or waist circumference. However, the substitution of sedentary behavior with moderate-to-vigorous physical activity was associated with a decrease in body fat percentage during the first 6 months of the trial (−0.33% per 30 minutes higher moderate-to-vigorous physical activity [95% CI: −0.60% to −0.07%], p = 0.013). Conclusions Sedentary behavior had little or no influence on subsequent weight-loss maintenance, but during the early stages of a weight-loss maintenance program, substituting sedentary behavior with moderate-to-vigorous physical activity may prevent a gain in body fat percentage, Objective: In this study, the associations between the substitution of sedentary time with sleep or physical activity at different intensities and subsequent weight-loss maintenance were examined. Methods: This prospective study included 1152 adults from the NoHoW trial who had achieved a successful weight loss of ≥5% during the 12 months prior to baseline and had BMI ≥25 kg/m2 before losing weight. Physical activity and sleep were objectively measured during a 14-day period at baseline. Change in body weight was included as the primary outcome. Secondary outcomes were changes in body fat percentage and waist circumference. Cardiometabolic variables were included as exploratory outcomes. Results: Using isotemporal substitution models, no associations were found between activity substitutions and changes in body weight or waist circumference. However, the substitution of sedentary behavior with moderate-to-vigorous physical activity was associated with a decrease in body fat percentage during the first 6 months of the trial (−0.33% per 30 minutes higher moderate-to-vigorous physical activity [95% CI: −0.60% to −0.07%], p = 0.013). Conclusions: Sedentary behavior had little or no influence on subsequent weight-loss maintenance, but during the early stages of a weight-loss maintenance program, substituting sedentary behavior with moderate-to-vigorous physical activity may prevent a gain in body fat percentage.

ObjectiveWeight regain prevention is a critical public health challenge. Digital behaviour change interventions provide a scalable platform for applying and testing behaviour change theories in this challenging context. This study's goal was to analyse reciprocal effects between psychosocial variables (i.e., needs satisfaction, eating regulation, self-efficacy) and weight over 12 months using data from a large sample of participants engaged in a weight regain prevention trial. MethodsThe NoHoW study is a three-centre, large-scale weight regain prevention trial. Adults who lost >5% of their weight in the past year (N = 1627, 68.7% female, 44.10 +/- 11.86 years, 84.47 +/- 17.03 kg) participated in a 12-month' digital behaviour change-based intervention. Weight and validated measures of basic psychological needs satisfaction, eating regulation and self-efficacy were collected at baseline, six- and 12 months. Correlational, latent growth models and cross-lagged analysis were used to identify potential reciprocal effects. ResultsBaseline higher scores of needs satisfaction and self-efficacy were associated with six- and 12-month' weight loss. Baseline weight was linked to all psychosocial variables at six months, and six-months weight was associated with needs satisfaction and self-efficacy at 12 months. During the 12 months, increases in eating regulation, needs satisfaction and self-efficacy were associated with weight loss over the same period, and reciprocal effects were observed between the variables, suggesting the existence of Weight Management Cycles. ConclusionsWhile further studies are needed, during long-term weight regain prevention, weight decrease, needs satisfaction and self-efficacy may lead to Weight Management Cycles, which, if recurrent, may provide sustained prevention of weight regain.

Objective: To investigate the prognostic value of illness perception (IP) on knee pain, quality of life (QoL) and functional level in elderly individuals reporting knee pain. Design: A prospective cohort study of 1552 elderly with knee pain comparing two previously established clusters based on the Brief Illness Perception questionnaire. Cluster 1 (“Concerned optimists” [hypothesized unfavorable profile]; n ​= ​642) perceived their knee pain as a greater threat to them than Cluster 2 (“Unconcerned confident” [hypothesized favorable profile]; n ​= ​910). Primary outcome was the change from baseline to year 2 in the KOOS Pain subscale. Secondary outcomes were changes from baseline in quality of life (EuroQol-5 Domain and EQ VAS) and in the KOOS subscales Symptom, Activities of Daily Living, Knee-related QoL and Sports and recreation. Analyses were done on the original Intention-To-Survey (ITS) population, using repeated measures mixed linear models. Results: Among the ITS population, 841 (54%) responded to the 2-year survey. There was a statistically significant but clinically irrelevant cluster difference in the 2-year change from baseline in KOOS pain (mean difference: 6.0 KOOS points [95% CI: 7.3 to −4.7]) explained by a minor improvement in Cluster 1: (6.2 points) and no changes in Cluster 2: (0.2 points). Comparable results were found across the secondary outcomes. Clinically irrelevant cluster changes in IP were seen. Conclusion: In a cohort of people with knee pain, IP phenotype (i.e., Clusters) were of no prognostic value for the 2-year changes in pain, function, and QoL. Targeting IP may not be relevant in this patient population. Trial registration number and date of registration: The Frederiksberg Cohort study was pre-registered at clinicaltrials.gov (NCT03472300) on March 21, 2018.

Primary prevention targets development of overweight in individuals with healthy weight and is a great challenge. This paper summarizes the main findings of a working group of the Danish Council on Health and Disease Prevention that reviewed the literature on primary prevention of overweight and obesity among children and adolescents. The results were presented in a Danish report, in which a 2019 Cochrane review on childhood obesity prevention was complemented by searches in PubMed to include all relevant subsequent studies published from January 2018 until March 2020. In this paper, the review was updated until June 2023. Numerous childhood overweight prevention interventions have been developed during the past decades, primarily targeting diet and/or physical activity. Several of these interventions showed positive effects on diet and physical activity level but did not show effects on risk of developing overweight. The evidence foundation is inconsistent as four out of five interventions did not show positive effects. Previously observed intervention effects may not reflect excessive weight gain prevention among children with healthy weight but rather bodyweight reduction among those with overweight or obesity. We do not have sufficient knowledge about how to prevent children with healthy weight from developing overweight, and creative solutions are urgently needed.

Background Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians’ offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the ‘BIA International Database’ project and encourage researchers to join the consortium. Methods The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants. Conclusion The BIA International Database represents a key resource for research on body composition., Background: Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians’ offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the ‘BIA International Database’ project and encourage researchers to join the consortium. Methods: The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants. Conclusion: The BIA International Database represents a key resource for research on body composition.