Obesity Reviews最新文献

This review synthesized the evidence from randomized controlled trials comparing the effect of meal replacements (MRs) as part of a weight loss intervention with conventional food-based weight loss diets on cardiometabolic risk in individuals with pre-diabetes and features of metabolic syndrome. MEDLINE, EMBASE, and Cochrane Library were searched through January 16, 2024. Data were pooled using the generic inverse variance method and expressed as mean difference [95% confidence intervals]. The overall certainty of the evidence was assessed using GRADE. Ten trials (n = 1254) met the eligibility criteria. MRs led to greater reductions in body weight (−1.38 kg [−1.81, −0.95]), body mass index (BMI, −0.56 kg/m² [−0.78, −0.34]), waist circumference (−1.17 cm [−1.93, −0.41]), HbA_1c (−0.11% [−0.22, 0.00]), LDL-c (−0.18 mmol/L [−0.28, −0.08]), non-HDL-c (−0.17 mmol/L [−0.33, −0.01]), and systolic blood pressure (−2.22 mmHg [−4.20, −0.23]). The overall certainty of the evidence was low to moderate owing to imprecision and/or inconsistency. The available evidence suggests that incorporating MRs into a weight loss intervention leads to small important reductions in body weight, BMI, LDL-c, non-HDL-c, and systolic blood pressure, and trivial reductions in waist circumference and HbA_1c, beyond that seen with conventional food-based weight loss diets.

Food insecurity is a well-established obesity driver. Less is known about food insecurity during pregnancy. This review (PROSPERO:CRD42022311669) aimed to explore associations between food insecurity, maternal obesity, gestational weight gain (GWG), and nutrition. Searches included seven databases, gray literature, references, citations, and contacting authors. Observational studies reporting data from January 1st, 2008 to 21 November 2023 in high-income countries were included. Duplicate screening, data extraction, and quality assessments were performed. Random effects meta-analysis estimated odds ratios (OR), mean difference (MD), and 95% confidence intervals (CI). Narrative synthesis was conducted when data could not be pooled. Database searches identified 22,272 results; 20 studies were included (n = 19 North America, n = 1 Europe; n = 32,803 women). Food insecurity significantly increased obesity (OR 1.53 95%CI 1.39, 1.66), but not underweight (OR 1.12 95%CI 0.89, 1.34) or overweight (OR 1.18 95%CI 0.90, 1.46). Food insecurity significantly reduced GWG (MD -0.42 kg 95%CI -0.62, −0.22) and increased inadequate GWG (OR 1.16 95%CI 1.05, 1.28), but not excessive GWG (OR 1.04 95%CI 0.96, 1.13). Diet outcomes were inconsistent, with some evidence of reduced vitamin E and diet quality and increased red/processed meat consumption. Further studies outside of North America are needed to inform practice and policy to support maternal health.

Perceptions and biases influence how we interact with and experience the world, including in professional roles as researchers. Weight bias, defined as negative attitudes or perceptions towards people that have large bodies, can contribute to weight stigma and discrimination leading to negative health and social consequences. Weight bias is experienced by people living with obesity in media, health care, education, employment and social settings. In research settings, there is potential for weight bias to impact various aspects of qualitative research including the participant-researcher dynamic in interviews. However, evidence-based strategies to reduce weight bias in qualitative research interviews have yet to be identified. We discuss how weight bias may influence research interviews and identify several considerations and strategies for researchers to minimize the impact of weight bias. Strategies include practicing reflexivity, planning and conducting interviews in ways that support rapport building, using inclusive language, and considering participatory methods.

Maternal obesity and gestational diabetes mellitus (GDM) prevalence are increasing, with both conditions associated with adverse neonatal outcomes. This review aimed to determine the risk of adverse outcomes in women with obesity and GDM, compared with women with obesity alone. A systematic search identified 28 eligible articles. Meta-analysis was conducted using a random effects model, to generate pooled estimates (odds ratios, OR, or mean difference, MD). Compared with normal-weight controls, women with obesity had increased risks of large for gestational age (LGA, OR 1.98, 95% CI: 1.56, 2.52) and macrosomia (OR 2.93, 95% CI: 1.71, 5.03); the latter's risk almost double in women with obesity than GDM. Birth weight (MD 113 g, 95% CI: 69, 156) and shoulder dystocia (OR 1.23, 95% CI: 0.85, 1.78) risk was also higher. GDM significantly amplified neonatal risk in women with obesity, with a three- to four-fold risk of LGA (OR 3.22, 95% CI: 2.17, 4.79) and macrosomia (OR 3.71, 95% CI: 2.76, 4.98), as well as higher birth weights (MD 176 g, 95% CI: 89, 263), preterm delivery (OR 1.49, 95% CI: 1.25, 1.77), and shoulder dystocia (OR 1.99, 95% CI: 1.31, 3.03), when compared with normal-weight controls. Our findings demonstrate that maternal obesity increases serious neonatal adverse risk, magnified by the presence of GDM. Effective strategies are needed to safeguard against neonatal complications associated with maternal obesity, regardless of GDM status.

Micro-RNAs have emerged as important actors in the onset of metabolic disorders including obesity or type 2 diabetes. Particularly, several micro-RNAs are known to be key modulators of lipid metabolism, glucose homeostasis, or feeding behavior. Interestingly, the role of extracellular vesicles containing micro-RNAs, especially adipose-derived extracellular vesicles, are well-documented endocrine signals and disease biomarkers. However, the role of adipose-derived extracellular vesicles on the different tissues is different and highly related to the micro-RNA content. This review provides recent data about the potential involvement of adipose-derived extracellular vesicle-containing micro-RNAs in metabolic diseases.

Attentional bias modification (ABM) is a novel cognitive-based treatment that may help individuals reduce overeating by decreasing food processing bias and food cravings. However, most empirical studies have evaluated the short-term effects of ABM in populations that have body mass indexes that are within healthy ranges; therefore, the extent to which this training method can influence eating behavior in individuals who are overweight or obese remains unclear. This systematic review explored the efficacy of ABM as a tool to support weight management for individuals who are overweight or obese. Ten studies met the inclusion criteria for the review. The findings reveal that although training is effective at manipulating attentional bias to food cues, there is limited evidence that training significantly impacted appetite and eating behaviors or led to maintained weight loss.