Breakfast Consumption May Improve Fasting Insulin, HOMA-IR, and HbA1c Levels in Predominately Low-Income, Hispanic Children 7-12 Years of Age

Chrononutrition and metabolic health in children and adolescents: a systematic review and meta-analysis

CONTEXT

Obesity has emerged as a global health issue for the pediatric population, increasing the need to investigate physiopathological aspects to prevent the appearance of its cardiometabolic complications. Chrononutrition is a field of research in nutritional sciences that investigates the health impact of 3 different dimensions of feeding behavior: regularity of meals, frequency, and timing of food intake.

OBJECTIVE

We carried out a systematic review and meta-analysis to investigate the association between chrononutrition in children and adolescents and the risk of overweight/obesity or a cluster of metabolic abnormalities related to glucose and lipid metabolism, blood pressure, and cardiovascular disease risk.

DATA EXTRACTION

A literature search was performed using PubMed, EMBASE, and The Cochrane Library for relevant articles published before August 2022.

DATA ANALYSIS

A total of 64 articles were included in the narrative synthesis (47 cross-sectional and 17 cohort studies), while 16 studies were included in the meta-analysis. Meta-analysis showed that non-daily breakfast consumers (≤6 d/wk) had a higher risk of overweight/obesity (odds ratio [OR], 1.45; 95% confidence interval [CI], 1.08-1.82] compared with daily breakfast eaters (7 d/wk). Similarly, irregular breakfast consumption (only 0-to-3 times/wk) increased the risk of abdominal obesity (waist-to-height ratio ≥ 0.5) compared with regular consumption (5-to-7 times/wk) (OR, 1.38; 95% CI, 1.26-1.49). There was evidence to suggest that a regular frequency of meal consumption (≥4 times/d) is preventive against overweight/obesity development compared with fewer meals (≤3 times/d) (OR, 0.83; 95% CI, 0.70-0.97). In the narrative synthesis, snacking habits showed controversial results, while food timing was the most understudied dimension.

CONCLUSION

Overall, our data indicate a potential implication of chrononutrition in affecting pediatric metabolic health; however, the evidence of this association is limited and heterogeneous. Further prospective and intervention studies with a consistent approach to categorize the exposure are needed to elucidate the importance of chrononutrition for pediatric metabolic health.

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.

Effect of skipping breakfast on cardiovascular risk factors: a grade-assessed systematic review and meta-analysis of randomized controlled trials and prospective cohort studies

Skipping breakfast is one of the most prevalent irregular eating habits. Several pieces of evidence have reported the association between breakfast omission and a higher risk of cardiovascular diseases. Numerous publications have focused on the impact of skipping breakfast on various cardiovascular risk factors. Therefore, the current systematic review and meta-analysis aimed to assess this impact, especially with regard to anthropometric measurements, serum lipid profiles, blood pressure, and glycemic control indicators. A comprehensive search was performed in PubMed, Web of Science, Embase, Scopus, and the Cochrane Central Register of Controlled Trials up to 1 April 2023. A total of 11 eligible trials were identified to evaluate the combined effects of skipping breakfast. Final integrated results demonstrated that breakfast omission significantly decreased the body weight (mean difference = -0.66, 95% CI: -1.09 to -0.24, p = 0.002, I2 = 0.0) and increased the level of serum low-density lipoprotein cholesterol (LDL-C) (mean difference = 9.89, 95% CI: 5.14 to 14.63, p = 0.000, I2 = 17.3). Subgroup analysis also revealed potential factors that may affect the outcomes, for example, the physiological condition of participants, duration, gender, and type of breakfast. In conclusion, skipping breakfast may reduce body weight while increasing the level of serum LDL-C at the same time. In view of the limited trials, further studies are needed to expound the role of breakfast omission in cardiovascular diseases.