Obesity Reviews最新文献

Introduction: Although GLP-1-based pharmacotherapies achieve clinically significant weight loss, their influence on eating behavior is unknown.

Methods: This systematic review examined the effects of GLP-1-based pharmacotherapies on eating behavior, appetite, and energy intake in adults (≥ 18 years) with overweight or obesity (BMI ≥ 25 kg/m²) without major comorbidities. MEDLINE, PsycINFO, EMBASE and Web of Science were searched on 4^th November 2025. Risk of bias was assessed, and meta-analyses were conducted for energy intake and overall appetite suppression, with other outcomes synthesized qualitatively.

Results: Twenty-five articles involving 4060 participants were included (64% female, mean age = 44 years, mean BMI = 36.7 kg/m²). Four studies were deemed low risk of bias. A reduction in energy intake was observed (SMD = -0.775, 95% CI = -1.21 to -0.34, p = 0.002), although heterogeneity was high (I² = 82.7%) and the prediction interval included no effect. A small increase in appetite suppression was also observed (MD = 7.800, 95% CI = 3.74 to 11.86, p = 0.001). Qualitative findings suggested reductions in food craving and some measures of food reward. Nausea was more frequent with active treatment and may have influenced the observed effects or increased awareness of treatment allocation.

Conclusion: GLP-1-based pharmacotherapies may reduce short-term energy intake and appetite. However, the magnitude and consistency of these effects remain uncertain because of substantial heterogeneity, imputation of variance data, and variability in outcome assessment. Evidence relating to food craving, food preferences and other eating behaviors requires further investigation.

Objectives: Obesity and overweight pose a global health and economic burden. Lifestyle interventions are recommended as first-line treatment. Given their individual complexity, personalized lifestyle interventions may be more effective than one-size-fits-all approaches. This review assessed the methodology, findings and reporting quality of cost-effectiveness analyses evaluating personalized lifestyle interventions in adults with overweight or obesity.

Methods: MEDLINE, Embase, Web of Science, and Scopus were searched in March 2025, with backward reference tracking. Full economic evaluations were included without date restrictions. Studies were categorized by highest applicable personalization level: behavioral (Level 1), phenotype-based (Level 2), or omics-based (Level 3). Reporting quality was assessed using the CHEERS 2022 Checklist.

Results: From 15,385 records screened, 18 studies were included. Fourteen evaluated Level 1 interventions and two each evaluated Levels 2 and 3. Thirteen were cost-utility analyses: seven reported cost-effective or dominant findings, four reported not cost-effective findings, and two reported unclear or mixed results. Ten studies reported cost-effectiveness using clinical outcomes: eight showed favorable findings for at least one outcome, and two reported unclear findings. Heterogeneity in intervention design and methods between studies precluded robust conclusions. Findings for level 1 were mixed, evidence for levels 2 and 3 was limited, with favorable and inconsistent findings, respectively.  CONCLUSIONS: Evidence on the cost-effectiveness of personalized lifestyle interventions was mixed and predominantly behavioral personalization. The scarcity of economic evaluations evaluating more advanced personalized lifestyle interventions remains a key evidence gap. Future research should evaluate their added value to inform resource allocation in obesity management.

Mediation analysis identifies variables that explain the causal pathways linking an exposure (here genetic susceptibility to obesity) to an outcome (here obesity-related traits), offering potential targets for weight management interventions. This review followed the PRISMA guidelines and systematically searched the literature up to August 2024 in four databases (Web of Science, Embase, Medline, CINAHL) to identify studies using mediation analysis with genetic or polygenic risk scores of obesity as exposure and body mass index (BMI) as outcome. Twenty-nine studies focusing on eating behaviors, diet quality, physical activity, and other lifestyle factors were included. Eating behaviors traits emerged as the most influential mediators of genetic susceptibility to obesity. Mediation explained 23%-56% of the genetic effect on BMI for disinhibition, 6%-23% for uncontrolled eating, 4%-19% for susceptibility to hunger, 4%-15% for emotional eating and 8%-10% for satiety responsiveness. For diet quality, fat intake mediated 4%-5% of the effect, while whole grain intake explained 1%-2%. Physical activity accounted for 0.3%-23% of mediation, whereas sedentary time explained 5%-43%. These findings highlight that behavioral and lifestyle factors substantially mediate genetic risk for obesity. Interventions targeting disinhibition, uncontrolled eating, susceptibility to hunger, fat intake, whole grain consumption, physical activity and sedentary behavior could improve obesity prevention and management, particularly for individuals with higher genetic susceptibility.

Understanding obesity involves evaluating numerous contributing factors. Collecting the necessary data for this can impose a significant burden on both research participants during clinical studies and real-life deployments of digital tools aiding obesity management. The BETTER4U project (European Union's Horizon Europe, Grant Agreement ID 101080117) introduces 36 behavioral and 9 living environment indicators designed to unobtrusively and efficiently capture daily life through passive monitoring using market-available smartphones and smartwatches while accounting for environmental confounders. This concise set, intended for dietitians, physical activity experts, and healthcare professionals as a standard for assessing obesity-related behavior, summarizes the behavioral and environmental profile of a person with obesity/overweight. We present the selected indicators, their selection and implementation methodology and the high-level plan for their verification, describing their conceptual foundations and technical realization. These indicators can be deployed in a modular framework: by transforming raw sensor data into structured, interpretable measures they provide a scalable foundation for long-term monitoring of obesogenic behaviors, individual assessment, and evaluation of interventions targeting physical activity, diet, stress, and sleep. The indicators are intended for an expert-facing dashboard within the BETTER4U Intervention Platform, a participant-side interface within the BETTER4U application, and as input to the BETTER4U AI-based causal model, supporting relationship modeling between behavior, environment, and obesity outcomes to inform personalized interventions. This work lays the basis for data-driven validation of these indicators following the "BETTER4ALL Pilot Study" (ClinicalTrials.gov ID: NCT07120802), ahead of their use in the BETTER4U RCT among individuals with obesity/overweight.

Background: Physical inactivity increases the risk of developing chronic illnesses. However, the effectiveness of Zumba among women who are physically inactive remains understudied. This review aims to evaluate the effectiveness of Zumba in improving cardiorespiratory fitness and anthropometric measures (body mass index, body fat, and waist circumference) among women with low physical activity levels.

Methods: PubMed, EMBASE, Cochrane, Scopus, Web of Science, CINAHL, and ProQuest Education Collection were systematically searched until June 8, 2025. Eligibility criteria were as follows: (1) randomized controlled trials involving insufficiently active adult women (< 150 min moderate or < 75 min vigorous activity/week); (2) Zumba or its variations as the intervention; (3) no intervention or usual care as the comparator; and (4) reporting of cardiorespiratory fitness, body mass index, body fat percentage, or waist circumference. Quality appraisal for included studies was performed using the revised Cochrane Risk of Bias tool. Meta-analyses were performed using the random-effects model where possible.

Results: Seven randomized controlled trials (eight reports) were included. Zumba significantly improved cardiorespiratory fitness (MD = 3.63; 95% CI 2.00, 5.26; p < 0.01) and body fat percentage (MD = -5.11; 95% CI -8.77, -1.46; p < 0.01) compared to no intervention/usual care. No statistically significant differences were observed in body mass index between groups (MD = -0.97; 95% CI -2.49, 0.54; p = 0.21). Narrative synthesis of three reports found positive improvements in waist circumference after completion of Zumba interventions.

Conclusion: Zumba effectively improves cardiorespiratory fitness and reduces body fat percentage among women with low physical activity levels. Further high-quality research is warranted to determine optimal intervention dosage, assess other Zumba modalities, and explore Zumba's implementation and sustainability.