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A systematic review and meta-analysis of school-based interventions with health education to reduce body mass index in adolescents aged 10 to 19 years.
Jacob, CM, Hardy-Johnson, PL, Inskip, HM, Morris, T, Parsons, CM, Barrett, M, Hanson, M, Woods-Townsend, K, Baird, J
The international journal of behavioral nutrition and physical activity. 2021;18(1):1
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Obesity in childhood and adolescence is associated with an increased risk of non-communicable diseases such as Type 2 diabetes, cardiovascular disease, chronic obstructive lung disease and some forms of cancer. The aim of this study was to investigate the effectiveness of health education interventions delivered in school settings to prevent overweight and obesity and/ or reduce BMI in adolescents, and to explore the key features of effectiveness. This study is a systematic review and meta-analysis of 39 publications based on 33 studies. Six studies recruited adolescent girls only, one adolescent boys only and one study included parent-student dyad. Results show that: - Most of the effective interventions were delivered by teachers who were trained prior to the intervention. - School-based interventions are often delivered through school-staff, however, appropriate training/ CPD prior to the intervention could be a crucial component to support the provision and uptake of the intervention. - Many of the effective interventions included parental involvement and modifications to the school environment. - Interventions should target the biological, psychosocial, environmental, and behavioural influences on diet and physical activity. Authors conclude that school-based health education interventions could potentially help in improving BMI outcomes in the adolescent age group.
Abstract
BACKGROUND Adolescents are increasingly susceptible to obesity, and thus at risk of later non-communicable diseases, due to changes in food choices, physical activity levels and exposure to an obesogenic environment. This review aimed to synthesize the literature investigating the effectiveness of health education interventions delivered in school settings to prevent overweight and obesity and/ or reduce BMI in adolescents, and to explore the key features of effectiveness. METHODS A systematic search of electronic databases including MEDLINE, CINAHL, PsychINFO and ERIC for papers published from Jan 2006 was carried out in 2020, following PRISMA guidelines. Studies that evaluated health education interventions in 10-19-year-olds delivered in schools in high-income countries, with a control group and reported BMI/BMI z-score were selected. Three researchers screened titles and abstracts, conducted data extraction and assessed quality of the full text publications. A third of the papers from each set were cross-checked by another reviewer. A meta-analysis of a sub-set of studies was conducted for BMI z-score. RESULTS Thirty-three interventions based on 39 publications were included in the review. Most studies evaluated multi-component interventions using health education to improve behaviours related to diet, physical activity and body composition measures. Fourteen interventions were associated with reduced BMI/BMI z-score. Most interventions (n = 22) were delivered by teachers in classroom settings, 19 of which trained teachers before the intervention. The multi-component interventions (n = 26) included strategies such as environment modifications (n = 10), digital interventions (n = 15) and parent involvement (n = 16). Fourteen studies had a low risk of bias, followed by 10 with medium and nine with a high risk of bias. Fourteen studies were included in a random-effects meta-analysis for BMI z-score. The pooled estimate of this meta-analysis showed a small difference between intervention and control in change in BMI z-score (- 0.06 [95% CI -0.10, - 0.03]). A funnel plot indicated that some degree of publication bias was operating, and hence the effect size might be inflated. CONCLUSIONS Findings from our review suggest that school-based health education interventions have the public health potential to lower BMI towards a healthier range in adolescents. Multi-component interventions involving key stakeholders such as teachers and parents and digital components are a promising strategy.
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A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring.
Alpert, A, Pickman, Y, Leipold, M, Rosenberg-Hasson, Y, Ji, X, Gaujoux, R, Rabani, H, Starosvetsky, E, Kveler, K, Schaffert, S, et al
Nature medicine. 2019;25(3):487-495
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The human immune system changes with age, ultimately leading to a clinically evident, profound deterioration resulting in high morbidity and mortality rates attributed to infectious and chronic diseases. The aim of this study was to assess at high resolution the dynamics of older adults’ immune systems. The study uses multiple ‘omics’ technologies in a cohort of 135 adults (63 young adults and 72 older adults) of different ages who were sampled longitudinally over the course of 9 years to comprehensively capture population- and individual-level changes in the immune system over time. Results indicate that immune-cell frequencies changed at substantially different rates; some cell subsets show no directionality of change yet differ between young and old individuals, whereas other cell subsets continued changing (either increasing or decreasing) throughout the course of the study. Authors postulate that an individual’s immune age is a function of life history, namely environmental exposure coupled with genetic background. Thus, immune modulators may one day be identified that affect the position of an individual’s immune system along the immunological landscape.
Abstract
Immune responses generally decline with age. However, the dynamics of this process at the individual level have not been characterized, hindering quantification of an individual's immune age. Here, we use multiple 'omics' technologies to capture population- and individual-level changes in the human immune system of 135 healthy adult individuals of different ages sampled longitudinally over a nine-year period. We observed high inter-individual variability in the rates of change of cellular frequencies that was dictated by their baseline values, allowing identification of steady-state levels toward which a cell subset converged and the ordered convergence of multiple cell subsets toward an older adult homeostasis. These data form a high-dimensional trajectory of immune aging (IMM-AGE) that describes a person's immune status better than chronological age. We show that the IMM-AGE score predicted all-cause mortality beyond well-established risk factors in the Framingham Heart Study, establishing its potential use in clinics for identification of patients at risk.
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Functional interactions between the gut microbiota and host metabolism.
Tremaroli, V, Bäckhed, F
Nature. 2012;489(7415):242-9
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This literature review aims to discuss evidence for the role of the gut microbiota in metabolism and possible links to obesity. Obesity and caloric intake can influence the microbiota, but whether the reverse is true in humans remains unclear. Much of the mechanisms have been determined in rodents, determining similar pathways in humans is difficult. The interplay of diet, host and gut microbiota may cause increased gut permeability (leaky gut) that could lead to an increase in inflammation that may cause obesity, fatty liver disease and insulin resistance. It is increasingly accepted that gut microbiota can contribute to diseases such as obesity, diabetes and cardiovascular disease, but exactly how and by how much remains unclear. Evidence for treating the microbiota to help with these metabolic diseases, either by pre- or probiotic supplementation, is building. However, double-blind, placebo-controlled studies are required to determine effects. The influence of the gut microbiota is a promising area, but one that needs further research.
Abstract
The link between the microbes in the human gut and the development of obesity, cardiovascular disease and metabolic syndromes, such as type 2 diabetes, is becoming clearer. However, because of the complexity of the microbial community, the functional connections are less well understood. Studies in both mice and humans are helping to show what effect the gut microbiota has on host metabolism by improving energy yield from food and modulating dietary or the host-derived compounds that alter host metabolic pathways. Through increased knowledge of the mechanisms involved in the interactions between the microbiota and its host, we will be in a better position to develop treatments for metabolic disease.