Area-level and family-level socioeconomic position and body composition trajectories: longitudinal analysis of the UK Millennium Cohort Study

Oxidative balance score is inversely associated with low muscle mass in young and middle-aged adults: a cross-sectional NHANES study

BACKGROUND

Low muscle mass is a critical indicator of frailty and adverse health outcomes. However, the potential link between systemic oxidative stress and low muscle mass remains underexplored. This study aims to investigate the association between the Oxidative Balance Score (OBS) and low muscle mass in U.S. adults.

METHODS

In this cross-sectional study, data from 4096 adults aged 20 to 59 years from National Health and Nutritional Examination Survey (NHANES) 2011 to 2018 were analyzed. Low muscle mass, the primary outcome, was evaluated utilizing the Foundation for the National Institutes of Health (FNIH) definition. Analysis involved the application of restricted cubic splines and weighted multivariate regression techniques.

RESULTS

A nonlinear association was observed between OBS and low muscle mass (p for nonlinearity < 0.0049). Compared to the lowest OBS quartile, individuals in the highest quartile had an adjusted OR of 0.26 (95% CI: 0.14-0.48) for low muscle mass (P for trend < 0.001). Additionally, the adjusted β value for ALM/BMI was 0.067 (95% CI: 0.053-0.082), P for trend < 0.001. Both dietary and lifestyle OBS also showed negative associations with low muscle mass, with fully adjusted ORs of 0.38 (95% CI: 0.19-0.76) and 0.17 (95% CI: 0.05-0.62), respectively (both P for trends < 0.01). Furthermore, in stratified analyses, this relationship was particularly prominent in the 40-59 years age group (P for interaction = 0.048).

CONCLUSION

Higher OBS, indicative of greater antioxidant exposure, was robustly associated with a lower risk of low muscle mass, particularly in 40-59 old adults. These findings underscore the potential role of oxidative balance in preserving muscle health and highlight the need for targeted interventions in this demographic. Further longitudinal studies are warranted to confirm these associations and evaluate potential clinical applications.

Sex-specific socioeconomic inequalities in trajectories of anthropometry, blood pressure, and blood-based biomarkers from birth to 18 years: a prospective cohort study

Evidence on when socioeconomic inequalities in conventional cardiometabolic risk factors emerge and how these change over time is sparse but important in identifying pathways to socioeconomic inequalities in cardiovascular disease (CVD). We examine socioeconomic inequalities in cardiometabolic risk factors trajectories across childhood and adolescence. Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC), born in 1991/1992. Socioeconomic position (SEP) was measured using maternal education from questionnaires at 32-weeks' gestation. Cardiometabolic risk factors measured from birth/mid-childhood to 18 years (y) included fat and lean mass (9-18 y), systolic and diastolic blood pressure (SBP, DBP), pulse rate and glucose (7-18 y), high-density lipoprotein cholesterol (HDL-c), non-HDL-c and triglycerides (birth-18y). Associations were examined using linear spline multilevel models. Among 6517-8952 participants with 11 948-42 607 repeated measures, socioeconomic inequalities in fat mass were evident at age 9 y and persisted throughout adolescence. By 18 y, fat mass was 12.32% [95% confidence interval (CI): 6.96, 17.68] lower among females and 7.94% (95% CI: 1.91, 13.97) lower among males with the highest SEP compared to the lowest. Socioeconomic inequalities in SBP and DBP were evident at 7 y, narrowed in early adolescence and re-emerged between 16 and 18 y, particularly among females. Socioeconomic inequalities in lipids emerged, among females only, between birth and 9 y in non-HDL-c, 7 and 18 y in HDL-c, and 9 and 18 y in triglycerides while inequalities in glucose emerged among males only between 15 and 18 y. Prevention targeting the early life course may be beneficial for reducing socioeconomic inequalities in CVD especially among females who have greater inequalities in cardiometabolic risk factors than males at the end of adolescence.

Do the effects of interventions aimed at the prevention of childhood obesity reduce inequities? A re-analysis of randomized trial data from two Cochrane reviews

Background

Public health attempts to prevent obesity in children and young people should aim to minimize health inequalities. Two Cochrane reviews examining interventions aiming to prevent childhood obesity found that interventions promoting (only) physical activity have a small beneficial effect on BMI for people aged 5-18 years, as do interventions promoting physical activity alongside healthy eating for 5-11 year olds. We examined whether the effectiveness of the interventions included in these reviews differed according to eight factors associated with inequity: place, race/ethnicity, occupation, gender/sex, religion, education, socio-economic status, and social capital (the PROGRESS framework).

Methods

We collected data on change in BMI (standardized or unstandardized), subgrouped by baseline measures of PROGRESS factors, for intervention and control groups, from trial authors. We calculated the intervention effect per subgroup (mean difference), then contrasted these to estimate interactions between intervention and the baseline factors. We combined interaction estimates for each factor across trials using meta-analyses.

Findings

We collected subgrouped data from 81 trials that took place between 2001 and 2020, involving 84,713 participants. We found no substantial differences in effectiveness of interventions for PROGRESS subgroups in most scenarios. However, in the younger age group (5-11 years), the effect of interventions on standardized BMI appeared to be higher in boys (average difference in mean differences 0.03; 95% CI 0.01 to 0.06; 45 studies, n = 44,740), which was consistent in direction with the BMI effect (average difference in mean differences 0.06 kg/m2; 95% CI -0.02 to 0.13; 31 studies, n = 27,083).

Interpretation

Our findings suggest that those responsible for public health can promote these beneficial interventions without major concerns about increasing inequalities but should be mindful that these interventions may work better in boys aged 5-11 years than girls. More data are needed, so we encourage future trialists to perform subgroup analyses on PROGRESS factors.

Funding

National Institute for Health and Care Research (NIHR).

Varying optimal power for height-standardisation of childhood weight, fat mass and fat-free mass across the obesity epidemic

INTRODUCTION

Childhood adiposity markers can be standardised for height in the form of indices (marker/heightp) to make meaningful comparisons of adiposity patterns within and between individuals of differing heights. The optimal value of p has been shown to differ by birth year, sex, age, and ethnicity. We investigated whether height powers for childhood weight and fat mass (FM) differed by birth year, sex, or age over the period before and during the child obesity epidemic in Copenhagen.

SETTING/METHODS

Population-based cross-sectional study of 391,801 schoolchildren aged 7 years, 10 years and 13 years, born between 1930 and 1996, from the Copenhagen School Health Records Register. Sex- and age-specific estimates of the height powers for weight and FM were obtained using log-log regression, stratified by a decade of birth.

RESULTS

For weight, amongst children born 1930-39, optimal height powers at 7 years were 2.20 (95% CI: 2.19-2.22) for boys and 2.28 (95% CI: 2.26-2.30) for girls. These increased with birth year to 2.82 (95% CI: 2.76-2.87) and 2.92 (95% CI: 2.87-2.97) for boys and girls born in 1990-96, respectively. For FM, amongst those born 1930-39, powers at 7 years were 2.46 (95% CI: 2.42-2.51) and 2.58 (95% CI: 2.53-2.63) for boys and girls, respectively, and increased with birth year reaching 3.89 (95% CI: 3.75-4.02) and 3.93 (95% CI: 3.80-4.06) for boys and girls born 1990-96, respectively. Powers within birth cohort groups for weight and FM were higher at 10 years than at 7 years, though similar increases across groups were observed at both ages. At 13 years, height powers for weight and FM initially increased with the birth year before declining from the 1970s/80s.

CONCLUSION

Due to increases in the standard deviation of weight and FM during the obesity epidemic, optimal height powers needed to standardise childhood weight and FM varied by birth year, sex, and age. Adiposity indices using a uniform height power mean different things for different birth cohort groups, sexes, and ages thus should be interpreted with caution. Alternative methods to account for height in epidemiological analyses are needed.

Socio-Ecologic Influences on Weight Trajectories Among Children with Obesity Living in Rural and Urban Settings

Background: Childhood obesity is a risk factor for poor cardiovascular, metabolic, and respiratory health. The studies examining influences of socio-ecologic factors on weight trajectories using longitudinal data are limited, often examine single measures (e.g., proximity to parks), and have not examined the specific trajectories of children with obesity. Methods: We examined influences on weight among 1518 children, 6-12 years of age, who had obesity using body mass index (BMI) criteria. BMI slope trajectories were categorized as decreasing, flat, or increasing, with a median of 2.1 years of follow-up. We examined socio-ecologic exposures, stratified by rural and urban settings, using census tracts to map indices, including food access, proximity to parks, normalized difference vegetation index, and area deprivation index (ADI). We used ordinal logistic regression to examine the associations between the socio-ecologic factors and BMI trajectories. Results: Among the 1518 children, 360 (24%) had a decreasing BMI trajectory with the remainder having flat (23%) or increasing (53%) trajectories. Children in rural areas were more likely to live in high disadvantage areas, 85%, compared with urban children, 46%. In the multivariable ordinal model, living in a lower ADI census tract had a 0.78 (95% CI 0.61-0.99) lower odds of being in an increasing BMI slope group, and no other socio-ecologic factor was associated. Conclusions: The area deprivation index captures a range of resources and social context compared with the built environment indicators, which had no association with BMI trajectory. Further work examining how to develop effective interventions in high deprivation areas is warranted.

Childhood Body Fat Patterns and Obesity Prevalence in Kazakhstan

Background

In Kazakhstan the pediatric population levels of obesity based on fat mass (FM) assessment are currently unknown. The present work aimed to assess average childhood FM levels and the prevalence of high levels of adiposity (based upon FM levels).

Methods

Cross-sectional data from 2015 to 2020 nationally representative Childhood obesity surveillance initiative and 2022 regional surveys were used for this study of children aged 8 years (n = 4770) and 9 years (n = 3863). Childhood FM assessment was made using a validated prediction model using height, weight, age, sex and ethnicity. Average levels of FM, fat mass percent (FM%) and the prevalence of overfat and obesity were estimated.

Results

Amongst 8-year-olds, the population average FM% was 32.3% (95% CI: 31.7%-32.8%) for boys and 35.2% (95% CI: 34.8-35.6) for girls (2015) and 32.7% (95% CI: 32.3-33.1) for boys and 35.1% (95% CI: 34.7-35.5) for girls in 2020. The Almaty region had the average FM% 32.7% (95% CI: 32.1-33.2) and 34.8% (95% CI: 34.3-35.4) for boys and girls respectively in 2022. The similar pattern was observed for 9 year old children.

Conclusions

The present study reveals high FM% levels in primary school age children from Kazakhstan across study years. Understanding patterns of FM levels is important for preventing and addressing childhood obesity.

Measurement invariance of the parent-reported Strengths and Difficulties Questionnaire in autistic adolescents

LAY ABSTRACT

Autistic people are more likely than non-autistic people to experience mental health difficulties. The Strengths and Difficulties Questionnaire is often used to screen for these difficulties and to otherwise make important decisions about mental health treatment and research in populations of autistic people. However, this study suggests that parent-reported Strengths and Difficulties Questionnaire scores may not be useful for comparing autistic and non-autistic adolescents at 11, 14 and 17 years old, as well as screening for mental health conditions in autistic adolescents. In addition, several items may be more likely to be endorsed by parents of autistic 17-year-olds than by parents of non-autistic 17-year-olds (and vice versa), which might suggest caution is needed when comparing groups on specific items.

Socioeconomic Status and Obesity

Obesity is a pervasive public health problem that causes debilitating complications across the life course. One opportunity for preventing the onset of obesity is to focus on its social determinants. Socioeconomic status (SES), which includes factors such as income, educational attainment, occupational prestige, and access to resources, is a key determinant of obesity. In this scoping mini-review, we summarized review articles and meta-analyses of the SES-obesity association. From the 1980s to the present, cross-sectional studies have demonstrated a persistent socioeconomic gradient in obesity in which the association is negative in developed countries and positive in developing countries. Longitudinal studies have revealed the bidirectionality of the SES-obesity association; some studies demonstrate that socioeconomic adversity precedes the onset of obesity, while others provide evidence of reverse causality. While earlier studies relied on anthropometric assessments of weight and height to define obesity, the use of modern technologies like dual-energy x-ray absorptiometry and bioelectrical impedance have demonstrated that the socioeconomic gradient in obesity is robust across multiple indicators of body composition, including direct measures of lean and fat mass. More recently, examination of mediators and moderators of the SES-obesity association have highlighted causal pathways and potential intervention targets, with a focus on health behaviors, environmental conditions, psychological factors, and biological processes. We describe current gaps in knowledge and propose opportunities for future innovation to reduce the burden of obesity and related socioeconomic disparities.

High serum klotho levels are inversely associated with the risk of low muscle mass in middle-aged adults: results from a cross-sectional study

Objective

Muscle mass gradually declines with advancing age, and as an anti-aging protein, klotho may be associated with muscle mass. This study aims to explore the relationship between klotho levels and muscle mass in the middle-aged population.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2018, we conducted a cross-sectional analysis on a cohort of individuals aged 40-59. Weighted multivariable analysis was employed to assess the correlation between klotho and low muscle mass, with stratified and Restricted Cubic Spline (RCS) analyses.

Results

The cross-sectional investigation revealed a significant negative correlation between klotho levels and the risk of low muscle mass (Model 3: OR = 0.807, 95% CI: 0.712-0.915). A notable interaction between klotho and sex was observed, with a significant interaction effect (P for interaction = 0.01). The risk association was notably higher in females. The risk association was notably higher in females. Additionally, RCS analysis unveiled a significant linear relationship between klotho and low muscle mass (P for nonlinear = 0.9495, P for overall<0.0001).

Conclusion

Our observational analysis revealed a noteworthy inverse relationship between klotho and low muscle mass, particularly prominent among female participants. This discovery provides crucial insights for the development of more effective intervention strategies and offers a new direction for enhancing muscle quality in the middle-aged population.

Interventions to prevent obesity in children aged 5 to 11 years old

BACKGROUND

Prevention of obesity in children is an international public health priority given the prevalence of the condition (and its significant impact on health, development and well-being). Interventions that aim to prevent obesity involve behavioural change strategies that promote healthy eating or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective and numerous new studies have been published over the last five years, since the previous version of this Cochrane review.

OBJECTIVES

To assess the effects of interventions that aim to prevent obesity in children by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was February 2023.

SELECTION CRITERIA

Randomised controlled trials in children (mean age 5 years and above but less than 12 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our outcomes were body mass index (BMI), zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

This review includes 172 studies (189,707 participants); 149 studies (160,267 participants) were included in meta-analyses. One hundred forty-six studies were based in high-income countries. The main setting for intervention delivery was schools (111 studies), followed by the community (15 studies), the home (eight studies) and a clinical setting (seven studies); one intervention was conducted by telehealth and 31 studies were conducted in more than one setting. Eighty-six interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over four years. Non-industry funding was declared by 132 studies; 24 studies were funded in part or wholly by industry. Dietary interventions versus control Dietary interventions, compared with control, may have little to no effect on BMI at short-term follow-up (mean difference (MD) 0, 95% confidence interval (CI) -0.10 to 0.10; 5 studies, 2107 participants; low-certainty evidence) and at medium-term follow-up (MD -0.01, 95% CI -0.15 to 0.12; 9 studies, 6815 participants; low-certainty evidence) or zBMI at long-term follow-up (MD -0.05, 95% CI -0.10 to 0.01; 7 studies, 5285 participants; low-certainty evidence). Dietary interventions, compared with control, probably have little to no effect on BMI at long-term follow-up (MD -0.17, 95% CI -0.48 to 0.13; 2 studies, 945 participants; moderate-certainty evidence) and zBMI at short- or medium-term follow-up (MD -0.06, 95% CI -0.13 to 0.01; 8 studies, 3695 participants; MD -0.04, 95% CI -0.10 to 0.02; 9 studies, 7048 participants; moderate-certainty evidence). Five studies (1913 participants; very low-certainty evidence) reported data on serious adverse events: one reported serious adverse events (e.g. allergy, behavioural problems and abdominal discomfort) that may have occurred as a result of the intervention; four reported no effect. Activity interventions versus control Activity interventions, compared with control, may have little to no effect on BMI and zBMI at short-term or long-term follow-up (BMI short-term: MD -0.02, 95% CI -0.17 to 0.13; 14 studies, 4069 participants; zBMI short-term: MD -0.02, 95% CI -0.07 to 0.02; 6 studies, 3580 participants; low-certainty evidence; BMI long-term: MD -0.07, 95% CI -0.24 to 0.10; 8 studies, 8302 participants; zBMI long-term: MD -0.02, 95% CI -0.09 to 0.04; 6 studies, 6940 participants; low-certainty evidence). Activity interventions likely result in a slight reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.18 to -0.05; 16 studies, 21,286 participants; zBMI: MD -0.05, 95% CI -0.09 to -0.02; 13 studies, 20,600 participants; moderate-certainty evidence). Eleven studies (21,278 participants; low-certainty evidence) reported data on serious adverse events; one study reported two minor ankle sprains and one study reported the incident rate of adverse events (e.g. musculoskeletal injuries) that may have occurred as a result of the intervention; nine studies reported no effect. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, may result in a slight reduction in BMI and zBMI at short-term follow-up (BMI: MD -0.11, 95% CI -0.21 to -0.01; 27 studies, 16,066 participants; zBMI: MD -0.03, 95% CI -0.06 to 0.00; 26 studies, 12,784 participants; low-certainty evidence) and likely result in a reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.21 to 0.00; 21 studies, 17,547 participants; zBMI: MD -0.05, 95% CI -0.07 to -0.02; 24 studies, 20,998 participants; moderate-certainty evidence). Dietary and activity interventions compared with control may result in little to no difference in BMI and zBMI at long-term follow-up (BMI: MD 0.03, 95% CI -0.11 to 0.16; 16 studies, 22,098 participants; zBMI: MD -0.02, 95% CI -0.06 to 0.01; 22 studies, 23,594 participants; low-certainty evidence). Nineteen studies (27,882 participants; low-certainty evidence) reported data on serious adverse events: four studies reported occurrence of serious adverse events (e.g. injuries, low levels of extreme dieting behaviour); 15 studies reported no effect. Heterogeneity was apparent in the results for all outcomes at the three follow-up times, which could not be explained by the main setting of the interventions (school, home, school and home, other), country income status (high-income versus non-high-income), participants' socioeconomic status (low versus mixed) and duration of the intervention. Most studies excluded children with a mental or physical disability.

AUTHORS' CONCLUSIONS

The body of evidence in this review demonstrates that a range of school-based 'activity' interventions, alone or in combination with dietary interventions, may have a modest beneficial effect on obesity in childhood at short- and medium-term, but not at long-term follow-up. Dietary interventions alone may result in little to no difference. Limited evidence of low quality was identified on the effect of dietary and/or activity interventions on severe adverse events and health inequalities; exploratory analyses of these data suggest no meaningful impact. We identified a dearth of evidence for home and community-based settings (e.g. delivered through local youth groups), for children living with disabilities and indicators of health inequities.

Interventions to prevent obesity in children aged 12 to 18 years old

BACKGROUND

Prevention of obesity in adolescents is an international public health priority. The prevalence of overweight and obesity is over 25% in North and South America, Australia, most of Europe, and the Gulf region. Interventions that aim to prevent obesity involve strategies that promote healthy diets or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective, and numerous new studies have been published over the last five years since the previous version of this Cochrane Review.

OBJECTIVES

To assess the effects of interventions that aim to prevent obesity in adolescents by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was February 2023.

SELECTION CRITERIA

Randomised controlled trials in adolescents (mean age 12 years and above but less than 19 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our outcomes were BMI, zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

This review includes 74 studies (83,407 participants); 54 studies (46,358 participants) were included in meta-analyses. Sixty studies were based in high-income countries. The main setting for intervention delivery was schools (57 studies), followed by home (nine studies), the community (five studies) and a primary care setting (three studies). Fifty-one interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over 28 months. Sixty-two studies declared non-industry funding; five were funded in part by industry. Dietary interventions versus control The evidence is very uncertain about the effects of dietary interventions on body mass index (BMI) at short-term follow-up (mean difference (MD) -0.18, 95% confidence interval (CI) -0.41 to 0.06; 3 studies, 605 participants), medium-term follow-up (MD -0.65, 95% CI -1.18 to -0.11; 3 studies, 900 participants), and standardised BMI (zBMI) at long-term follow-up (MD -0.14, 95% CI -0.38 to 0.10; 2 studies, 1089 participants); all very low-certainty evidence. Compared with control, dietary interventions may have little to no effect on BMI at long-term follow-up (MD -0.30, 95% CI -1.67 to 1.07; 1 study, 44 participants); zBMI at short-term (MD -0.06, 95% CI -0.12 to 0.01; 5 studies, 3154 participants); and zBMI at medium-term (MD 0.02, 95% CI -0.17 to 0.21; 1 study, 112 participants) follow-up; all low-certainty evidence. Dietary interventions may have little to no effect on serious adverse events (two studies, 377 participants; low-certainty evidence). Activity interventions versus control Compared with control, activity interventions do not reduce BMI at short-term follow-up (MD -0.64, 95% CI -1.86 to 0.58; 6 studies, 1780 participants; low-certainty evidence) and probably do not reduce zBMI at medium- (MD 0, 95% CI -0.04 to 0.05; 6 studies, 5335 participants) or long-term (MD -0.05, 95% CI -0.12 to 0.02; 1 study, 985 participants) follow-up; both moderate-certainty evidence. Activity interventions do not reduce zBMI at short-term follow-up (MD 0.02, 95% CI -0.01 to 0.05; 7 studies, 4718 participants; high-certainty evidence), but may reduce BMI slightly at medium-term (MD -0.32, 95% CI -0.53 to -0.11; 3 studies, 2143 participants) and long-term (MD -0.28, 95% CI -0.51 to -0.05; 1 study, 985 participants) follow-up; both low-certainty evidence. Seven studies (5428 participants; low-certainty evidence) reported data on serious adverse events: two reported injuries relating to the exercise component of the intervention and five reported no effect of intervention on reported serious adverse events. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, do not reduce BMI at short-term follow-up (MD 0.03, 95% CI -0.07 to 0.13; 11 studies, 3429 participants; high-certainty evidence), and probably do not reduce BMI at medium-term (MD 0.01, 95% CI -0.09 to 0.11; 8 studies, 5612 participants; moderate-certainty evidence) or long-term (MD 0.06, 95% CI -0.04 to 0.16; 6 studies, 8736 participants; moderate-certainty evidence) follow-up. They may have little to no effect on zBMI in the short term, but the evidence is very uncertain (MD -0.09, 95% CI -0.2 to 0.02; 3 studies, 515 participants; very low-certainty evidence), and they may not reduce zBMI at medium-term (MD -0.05, 95% CI -0.1 to 0.01; 6 studies, 3511 participants; low-certainty evidence) or long-term (MD -0.02, 95% CI -0.05 to 0.01; 7 studies, 8430 participants; low-certainty evidence) follow-up. Four studies (2394 participants) reported data on serious adverse events (very low-certainty evidence): one reported an increase in weight concern in a few adolescents and three reported no effect.

AUTHORS' CONCLUSIONS

The evidence demonstrates that dietary interventions may have little to no effect on obesity in adolescents. There is low-certainty evidence that activity interventions may have a small beneficial effect on BMI at medium- and long-term follow-up. Diet plus activity interventions may result in little to no difference. Importantly, this updated review also suggests that interventions to prevent obesity in this age group may result in little to no difference in serious adverse effects. Limitations of the evidence include inconsistent results across studies, lack of methodological rigour in some studies and small sample sizes. Further research is justified to investigate the effects of diet and activity interventions to prevent childhood obesity in community settings, and in young people with disabilities, since very few ongoing studies are likely to address these. Further randomised trials to address the remaining uncertainty about the effects of diet, activity interventions, or both, to prevent childhood obesity in schools (ideally with zBMI as the measured outcome) would need to have larger samples.

Change in neighborhood socioeconomic status and childhood weight status and body composition from birth to adolescence

BACKGROUND

We aim to assess the associations between the change in neighborhood socioeconomic score (SES) between birth and 6 years and childhood weight status and body composition from 6 to 13 years.

METHODS

Data for 3909 children from the Generation R Study, a prospective population-based cohort in the Netherlands were analyzed. The change in neighborhood SES between birth and 6 years was defined as static-high, static-middle, static-low, upward, and downward mobility. Child body mass index (BMI), overweight and obesity (OWOB), fat mass index (FMI) and lean mass index (LMI) were measured at age 6, 10, and 13 years. The associations were explored using generalized estimating equations. The effect modification by child sex was examined.

RESULTS

In total, 19.5% and 18.1% of children were allocated to the upward mobility and downward mobility neighborhood SES group. The associations between the change in neighborhood SES and child weight status and body composition were moderated by child sex (p < 0.05). Compared to girls in the static-high group, girls in the static-low group had relatively higher BMI-SDS (β, 95% confidence interval (CI): 0.24, 0.09-0.40) and higher risk of OWOB (RR, 95% CI: 1.98, 1.35-2.91), together with higher FMI-SDS (β, 95% CI: 0.27, 0.14-0.41) and LMI-SDS (β, 95% CI: 0.18, 0.03-0.33). The associations in boys were not significant.

CONCLUSIONS

An increased BMI and fat mass, and higher risk of OWOB from 6 to 13 years were evident in girls living in a low-SES neighborhood or moving downward from a high- to a low-SES neighborhood. Support for children and families from low-SES neighborhoods is warranted.

AI-generated CT body composition biomarkers associated with increased mortality risk in socioeconomically disadvantaged individuals

PURPOSE

To evaluate the relationship between socioeconomic disadvantage using national area deprivation index (ADI) and CT-based body composition measures derived from fully automated artificial intelligence (AI) tools to identify body composition measures associated with increased risk for all-cause mortality and adverse cardiovascular events.

METHODS

Fully automated AI body composition tools quantifying abdominal aortic calcium, abdominal fat (visceral [VAT], visceral-to-subcutaneous ratio [VSR]), and muscle attenuation (muscle HU) were applied to non-contrast CT examinations in adults undergoing screening CT colonography (CTC). Patients were partitioned into 5 socioeconomic groups based on the national ADI rank at the census block group level. Pearson correlation analysis was performed to determine the association between national ADI and body composition measures. One-way analysis of variance was used to compare means across groups. Odds ratios (ORs) were generated using high-risk, high specificity (90% specificity) body composition thresholds with the most disadvantaged groups being compared to the least disadvantaged group (ADI < 20).

RESULTS

7785 asymptomatic adults (mean age, 57 years; 4361:3424 F:M) underwent screening CTC from April 2004-December 2016. ADI rank data were available in 7644 patients. Median ADI was 31 (IQR 22-43). Aortic calcium, VAT, and VSR had positive correlation with ADI and muscle attenuation had a negative correlation with ADI (all p < .001). Compared with the least disadvantaged group, mean differences for the most disadvantaged group (ADI > 80) were: Aortic calcium (Agatston) = 567, VAT = 27 cm2, VSR = 0.1, and muscle HU = -6 HU (all p < .05). Compared with the least disadvantaged group, the most disadvantaged group had significantly higher odds of having high-risk body composition measures: Aortic calcium OR = 3.8, VAT OR = 2.5, VSR OR = 2.0, and muscle HU OR = 3.1(all p < .001).

CONCLUSION

Fully automated CT body composition tools show that socioeconomic disadvantage is associated with high-risk body composition measures and can be used to identify individuals at increased risk for all-cause mortality and adverse cardiovascular events.

Higher ultra processed foods intake is associated with low muscle mass in young to middle-aged adults: a cross-sectional NHANES study

Design

Ultra-processed foods (UPFs) have become a pressing global health concern, prompting investigations into their potential association with low muscle mass in adults.

Methods

This cross-sectional study analyzed data from 10,255 adults aged 20-59 years who participated in the National Health and Nutritional Examination Survey (NHANES) during cycles spanning from 2011 to 2018. The primary outcome, low muscle mass, was assessed using the Foundation for the National Institutes of Health (FNIH) definition, employing restricted cubic splines and weighted multivariate regression for analysis. Sensitivity analysis incorporated three other prevalent definitions to explore optimal cut points for muscle quality in the context of sarcopenia.

Results

The weighted prevalence of low muscle mass was 7.65%. Comparing the percentage of UPFs calories intake between individuals with normal and low muscle mass, the values were found to be similar (55.70 vs. 54.62%). Significantly linear associations were observed between UPFs consumption and low muscle mass (P for non-linear = 0.7915, P for total = 0.0117). Upon full adjustment for potential confounding factors, participants with the highest UPFs intake exhibited a 60% increased risk of low muscle mass (OR = 1.60, 95% CI: 1.13 to 2.26, P for trend = 0.003) and a decrease in ALM/BMI (β = -0.0176, 95% CI: -0.0274 to -0.0077, P for trend = 0.003). Sensitivity analysis confirmed the consistency of these associations, except for the International Working Group on Sarcopenia (IWGS) definition, where the observed association between the highest quartiles of UPFs (%Kcal) and low muscle mass did not attain statistical significance (OR = 1.35, 95% CI: 0.97 to 1.87, P for trend = 0.082).

Conclusion

Our study underscores a significant linear association between higher UPFs consumption and an elevated risk of low muscle mass in adults. These findings emphasize the potential adverse impact of UPFs on muscle health and emphasize the need to address UPFs consumption as a modifiable risk factor in the context of sarcopenia.

Interlinkages between Climate Change and Food Systems: The Impact on Child Malnutrition-Narrative Review

The pandemics of obesity, undernutrition, and climate change represent severe threats to child health. They co-occur; interact with each other to produce sequelae at biological, psychological, or social levels; and share common underlying drivers. In this paper, we review the key issues concerning child diet and nutritional status, focusing on the interactions with climate and food systems. Inadequate infant and young child feeding practices, food insecurity, poverty, and limited access to health services are the leading causes of malnutrition across generations. Food system industrialization and globalization lead to a double burden of malnutrition, whereby undernutrition (i.e., stunting, wasting, and deficiencies in micronutrients) coexists with overweight and obesity, as well as to harmful effects on climate. Climate change and the COVID-19 pandemic are worsening child malnutrition, impacting the main underlying causes (i.e., household food security, dietary diversity, nutrient quality, and access to maternal and child health), as well as the social, economic, and political factors determining food security and nutrition (livelihoods, income, infrastructure resources, and political context). Existing interventions have the potential to be further scaled-up to concurrently address undernutrition, overnutrition, and climate change by cross-cutting education, agriculture, food systems, and social safety nets. Several stakeholders must work co-operatively to improve global sustainable nutrition.

Interventions to prevent obesity in school-aged children 6-18 years: An update of a Cochrane systematic review and meta-analysis including studies from 2015-2021

Background

Childhood obesity remains a global public health priority due to the enormous burden it generates. Recent surveillance data suggests there has been a sharp increase in the prevalence of childhood obesity during the COVID-19 pandemic. The Cochrane review of childhood obesity prevention interventions (0-18 years) updated to 2015 is the most rigorous and comprehensive review of randomised controlled trials (RCTs) on this topic. A burgeoning number of high quality studies have been published since that are yet to be synthesised.

Methods

An update of the Cochrane systematic review was conducted to include RCT studies in school-aged children (6-18 years) published to 30 June 2021 that assessed effectiveness on child weight (PROSPERO registration: CRD42020218928). Available cost-effectiveness and adverse effect data were extracted. Intervention effects on body mass index (BMI) were synthesised in random effects meta-analyses by setting (school, after-school program, community, home), and meta-regression examined the association of study characteristics with intervention effect.

Findings

Meta-analysis of 140 of 195 included studies (183,063 participants) found a very small positive effect on body mass index for school-based studies (SMD -0·03, 95%CI -0·06,-0·01; trials = 93; participants = 131,443; moderate certainty evidence) but not after-school programs, community or home-based studies. Subgroup analysis by age (6-12 years; 13-18 years) found no differential effects in any setting. Meta-regression found no associations between study characteristics (including setting, income level) and intervention effect. Ten of 53 studies assessing adverse effects reported presence of an adverse event. Insufficient data was available to draw conclusions on cost-effectiveness.

Interpretation

This updated synthesis of obesity prevention interventions for children aged 6-18 years, found a small beneficial impact on child BMI for school-based obesity prevention interventions. A more comprehensive assessment of interventions is required to identify mechanisms of effective interventions to inform future obesity prevention public health policy, which may be particularly salient in for COVID-19 recovery planning.

Funding

This research was funded by the National Health and Medical Research Council (NHMRC), Australia (Application No APP1153479).

Polygenic scores for schizophrenia and major depression are associated with psychosocial risk factors in children: evidence of gene-environment correlation

BACKGROUND

Whilst genetic and environmental risk factors for schizophrenia (SCZ) and major depressive disorder (MDD) have been established, it is unclear whether exposure to environmental risk factors is genetically confounded by passive, evocative or active gene-environment correlation (rGE).

STUDY OBJECTIVE

This study aims to investigate: (a) whether the genetic risk for SCZ/MDD in children is correlated with established environmental and psychosocial risk factors in two British community samples, the 1958 National Child Development Study (NCDS) and the Millennium Cohort Study (MCS), (b) whether these associations vary between both psychopathologies, and (c) whether findings differ across the two cohorts which were born 42 years apart.

METHODS

Polygenic risk scores (PRS) from existing large genome-wide associations studies (GWAS) were applied to test the correlation between the child genetic risk for SCZ/MDD and known environmental risk factors. In addition, parental and child genetic data from MCS were used to distinguish between passive and evocative rGE.

RESULTS

The child polygenic risk for SCZ and MDD was correlated with single parenthood in MCS. Moreover, the lack of father's involvement in child care was associated with the genetic risk for SCZ in NCDS. However, we also found associations between several indicators of low socioeconomic status and heightened genetic risk for MDD in children in both cohorts. Further, the genetic risk for MDD was associated with parental lack of interest in the child's education in NCDS as well as more maternal smoking and less maternal alcohol consumption during childhood in MCS. According to sensitivity analyses in MCS (controlling for parental genotype), more than half of our significant correlations reflected passive rGE.

CONCLUSIONS

Findings suggest that several established environmental and psychosocial risk factors for SCZ and MDD are at least partially associated with children's genetic risk for these psychiatric disorders.

Obesity, Pregnancy and the Social Contract with Today's Adolescents

Adolescent health and well-being are of great concern worldwide, and adolescents encounter particular challenges, vulnerabilities and constraints. The dual challenges of adolescent parenthood and obesity are of public health relevance because of the life-altering health and socioeconomic effects on both the parents and the offspring. Prevention and treatment strategies at the individual and population levels have not been successful in the long term, suggesting that adolescent pregnancy and obesity cannot be managed by more of the same. Here, we view adolescent obese pregnancy through the lens of the social contract with youth. The disruption of this contract is faced by today's adolescents, with work, social and economic dilemmas which perpetuate socioeconomic and health inequities across generations. The lack of employment, education and social opportunities, together with obesogenic settings, increase vulnerability and exposure to lifelong health risks, affecting their offspring's life chances too. To break such vicious circles of disadvantage and achieve sustainable solutions in real-world settings, strong efforts on the part of policymakers, healthcare providers and the community must be oriented towards guaranteeing equity and healthy nutrition and environments for today's adolescents. The involvement of adolescents themselves in developing such programs is paramount, not only so that they feel a sense of agency but also to better meet their real life needs.