International Journal of Obesity最新文献

Introduction: Dietary techniques such as time-restricted feeding (TRF) have received support in recent years due to their ability to improve metabolic health and prevent serious diseases. In scientific research, animal models are widely utilized to understand the physiological impacts of fasting and other dietary interventions, as they have similar physiology to humans. Several feeding windows ranging from 4 to 12 h have been reported in the literature. This review evaluates TRF protocols to determine the most effective feeding window for improving metabolic profiles.

Methods: Several search keywords were utilized and only research articles published within the last fifteen years (2009-2024) were selected. Twelve studies were included in the final analysis to improve transparency.

Results: Obesity was successfully induced within 6 weeks for 100% weight gain in C57BL/6 mice. The shortest duration of TRF intervention in mice is 6 weeks with 10 h of feeding. Meanwhile, induced obesity with 300% weight gain in Sprague-Dawley rats within 12 weeks. The shortest duration of TRF is 6 weeks with 8 h of feeding.

Conclusion: TRF was consistently associated with reductions in body weight and total cholesterol, concomitant with an increase in glucose tolerance and insulin sensitivity in studies where these parameters were assessed. The most effective identified TRF regimen is a 10-h feeding window over 8 weeks in C57BL/6 mice. Future research on obesity may take into account the inclusion of different metabolic challenges to assess if the advantages of TRF are exclusive to any of the challenges or multiple challenges that contribute obesity.

Limitations: A key limitation of this review is the heterogeneity in study protocols. The included studies varied in the duration of feeding hours (ranging from 4 to 12 h) using different rodent models. This research was funded by the Ministry of Higher Education Malaysia, under the Fundamental Research Grant Scheme (FRGS/1/2023/SKK06/UPM/02/2).

Background and objective: Generative artificial intelligence (AI), particularly large language models (LLMs), is rapidly evolving and holds significant potential for addressing the multifaceted challenges of obesity management. This systematic review synthesizes current research on LLM applications within the obesity field, critically evaluating their performance, limitations, and key future research directions.

Design: Electronic databases, including MEDLINE, OVID, and SCOPUS, were systematically searched from inception to August 2025 to identify eligible studies. Eligible studies investigated the potential role of LLMs in obesity medical and surgical care. Key findings were extracted and synthesized narratively. The ROBINS-I tool was used to assess the risk of bias across each study.

Results: Thirty-three studies met the inclusion criteria. The analysis reveals that LLMs are being applied across a diverse range of obesity-related topics, including personalized nutrition, educational interventions, guideline-directed medical therapy, weight loss strategies, anti-obesity medication information, and motivational interviewing. While some LLMs demonstrated promising accuracy and utility, substantial variability was observed. Numerous studies highlighted limitations, including inconsistent recommendations, inaccuracies, difficulties in handling complex scenarios, and a potential for biased outputs.

Conclusions: Generative AI and LLMs show considerable promise for enhancing various aspects of obesity management, from personalized interventions to clinical decision support. However, the current state of the technology exhibits crucial limitations regarding accuracy, consistency, and the ability to handle nuanced clinical situations, mandating a continued critical role for clinician oversight and validation. Further research is imperative to address these shortcomings, focusing on improving model training, validating performance in real-world settings, and addressing ethical considerations before widespread clinical implementation.

Background: Emerging evidence suggests that digital therapies are effective for treating obesity; however, an evidence gap exists regarding the potency of stand-alone digital therapeutics with limited additional support from a health care professional. This randomized controlled trial examined the efficacy of a digital health application for weight management in people with obesity.

Methods: The decentralized digital randomized controlled trial included 164 adults with obesity (BMI 30-45 kg/m²) from Germany who were randomly assigned to either an intervention group (receiving a digital health application for weight management for 6 months) or a control group (receiving care as usual for 6 months). Data on weight (primary endpoint at 6 months), quality of life (WHOQOL-BREF), and food literacy (SFLQ) were collected at baseline, 3, and 6 months.

Results: Participants (n = 164; 42% female, 58% male) had a mean BMI of 37.82 ± 4.25 kg/m² and a mean age of 45.92 ± 10.66 years. At 6 months, the intervention group achieved a mean weight loss of 5.29% ([95% CI: -6.73% to -3.86%], p < 0.001) compared to 1.76% ([95% CI: -3.10% to -0.42%], p = 0.010) in the control group (estimated marginal mean difference (EMMD): -3.53% [95% CI: -5.16% to -1.91%]; p < 0.001) with a large effect size (d = 0.80, [95% CI: 0.43-1.19]). Compared to controls at 6 months, food literacy (EMMD: 2.77, d = 0.49, p < 0.001) and perceived overall quality of life (EMMD: 0.33, d = 0.40, p = 0.010) improved in the intervention group, though no differences in the four quality of life domains were found.

Conclusions: The digital health application for weight management demonstrated efficacy in achieving weight loss (>5%) in people with obesity at 6 months.

Trial registration: This study was registered in the German Clinical Trials Register (Registration number: DRKS00033045).

Background: People with obesity (PWO) often experience weight bias, resulting in weight bias internalization (WBI) which may impact their preferences for healthcare engagement. We explored sex differences in self-reported WBI and its influence on telehealth utilization preferences among racially/ethnically diverse PWO who have completed metabolic and bariatric surgery (MBS).

Methods: A qualitative approach was used. The impact of WBI on telehealth utilization preferences was assessed through in-depth interviews. Interviews were thematically analyzed to explore sex differences in preferences between telehealth and in-person visits.

Results: Qualitative analysis (n = 24, 54% female) identified themes such as quality of care, convenience, discrimination in healthcare settings, and shame. WBI was not a primary determinant of how to receive care for both men and women. Their perception of the quality of care they would receive from either telehealth, or in-person visits was the main consideration.

Conclusion: This qualitative research suggests WBI may be common among men and women who have completed MBS, but WBI was not the main factor considered when PWO made decisions about using telehealth or in-person care. Future studies should further explore how WBI impacts healthcare engagement and preferences among PWO who have completed MBS across diverse settings.

Background: The incidence of obesity has significantly increased worldwide. However, it is still unclear about the genetic susceptibility of obesity.

Methods: Here we performed the largest European meta-analysis of genome-wide association study, including 98,421 obesity cases and 2,108,019 healthy controls.

Results: We identified 322 novel genome-wide significant obesity-associated loci and 23 of 32 known loci. SNP-based heritability analyses revealed that common variants explain 17.19 ± 0.59% of genetic risk for obesity, whereas MiXeR predicted an estimated 1.6 million effective sample sizes explaining 90% of obesity-associated phenotypic variance. Across 345 obesity-associated loci, 2000 likely causal genes are indicated, and 410 causal genes are prioritized. Tissue specificity enrichment analyses demonstrated that obesity-related causal genes mainly expressed in brain putamen basal ganglia, hippocampus, amygdala, substantia nigra, and caudate basal ganglia. The genetic correlation and gene-set analyses showed that apart from obesity-related diseases, some brain diseases and mood (e.g., broad depression, neuroticism, mood swings), inflammatory and allergic diseases diseases (e.g., asthma, spondyloarthritis, Hashimoto thyroiditis), cardiovascular diseases (e.g., hypertension, myocardial infarction, coronary artery disease), and lung disease (e.g., interstitial lung disease, chronic obstructive pulmonary disease, lung cancer) have the positive correlations with obesity. Gene-drug interaction analysis suggested that obesity-associated genes overlapped with targets of current medications for obesity. Finally, we used this meta-analysis to explore some potential targets (e.g., GLP1R, SIGMAR1, MC4R) and drug repurposing (e.g., iloprost, flunarizine, edrophonium chloride) for obesity.

Conclusions: We identified 345 genome-wide significant loci, including 322 novel loci for obesity. Based on 345 loci, we provided new biological insights to the etiology of obesity. Of clinical interest, we provided some potential targets and drug repurposing for obesity.

Background: Mice developing obesity through their diet have fewer taste buds than littermates maintained on healthy chow. In this experiment we investigated if diet-induced taste bud loss, inflammation, and an attenuated regenerative capacity of taste buds would persist after return to a healthy weight.

Methods: 8-week-old C57Bl/6 mice were split into three groups, one (chow) maintained on a standard lab chow diet for 16 weeks, a second (HFD) maintained on a high fat diet for 16 weeks, while the third (diet) was placed on a HFD for the first 8 weeks, then switched to the healthy diet.

Results: In this second 8 week period, diet mice lost all excess weight. Despite returning to a healthy weight, dieted mice showed only minor recovery of taste buds, with better recovery for proliferating cells and cells undergoing apoptosis. HFD mice exhibited increased tumor necrosis factor alpha (TNFα) expression, with altered Sonic Hedgehog (Shh) and Bone morphogenetic protein 4 (BMP4) expression, both linked to taste homeostasis.

Conclusions: Overall, data demonstrate that obesity has a persistent effect on taste buds long after excess weight is lost.

Background and aims: Renal sinus fat (RSF) is an ectopic fat depot whose expansion has been linked to hypertension and chronic kidney disease. We assessed a range of adiposity indices to determine whether they offer more accurate predictions of RSF than BMI.

Methods and results: Renal sinus fat (RSF) and RSF relative to total kidney area (RSF%) were assessed via MRI in 74 individuals with severe obesity and 47 lean volunteers. 50 persons with obesity were re-evaluated 6 to 12 months after undergoing bariatric surgery. In multivariable regression analyses adjusted for age, sex, and BMI, the Body Roundness Index (BRI), waist-to-height ratio (WHtR), and waist circumference showed the strongest associations with RSF. Of these, only WHtR was significantly associated with RSF%. In univariate analyses, both RSF and RSF% were inversely correlated with estimated glomerular filtration rate (eGFR); however, in multivariate analysis, only RSF% remained independently associated with eGFR. Post-bariatric surgery, RSF change correlated with changes in WHtR and BRI.

Conclusion: Adiposity measures incorporating waist circumference are associated with RSF independent of BMI. While RSF exhibits a stronger relationship with adiposity measures, RSF% predicts eGFR. Both metrics offer complementary insights and should be considered in future studies.

Background: Obesity is a major contributor to cardiovascular disease. Although altered central hemodynamics have been reported in obesity, studies are few, small, and limited to specific populations, leaving these changes underrecognized. This study investigates the association between body mass index (BMI) and central hemodynamics in a large cohort of adult patients admitted for medical reasons. We hypothesized that higher BMI is associated with increased cardiac index (CI) and reduced systemic vascular resistance (SVR), reflecting a hyperdynamic circulatory state.

Methods: This is a cross-sectional study of adults admitted to the Emergency Department at a large tertiary care hospital in Copenhagen, Denmark during 2019-2023. Patients were evaluated by physical examination and laboratory testing. Hemodynamic measurements, including CI and SVR, were estimated within 24 hours of admission using the non-invasive and continuous pulse wave analysis by Finapres® NOVA. The relationship between BMI, CI, and SVR were investigated using linear regression models.

Results: Of 942 participants (mean age 64 years; 44% female), 187 had obesity (BMI ≥ 30 kg/m²). Compared to participants without obesity, participants with obesity had 16% higher CI and 23% lower SVR (p < 0.0001). In linear regression models, BMI was positively associated with CI (p = 0.0001) and inversely with SVR (p = 0.0102). Each 5 kg/m² increase in BMI corresponded to a 7.7% rise in CI and a 12.7% decrease in SVR (p < 0.0001).

Conclusion: Higher BMI is significantly associated with increased CI and decreased SVR, indicating a hyperdynamic circulatory state in obesity. These findings suggest a potential hemodynamic mechanism linking obesity to cardiovascular risk.

Clinical trial registration: ClinicalTrials.gov (NCT03934775).