Obesity Science & Practice最新文献

{"title":"Aligning Biomedical Research With Neurodiversity to Support the Metabolic Health of Autistic Individuals.","authors":"Emily Hotez, A Janet Tomiyama","doi":"10.1002/osp4.70117","DOIUrl":"10.1002/osp4.70117","url":null,"abstract":"<p><p>Autistic individuals represent approximately 1 in 31 people in the United States and experience disproportionately high rates of obesity, type 2 diabetes, cardiovascular disease, and feeding and eating challenges, alongside reduced life expectancy. However, evidence-based metabolic health interventions for autistic populations remain sparse. This Perspective synthesizes evidence on two interconnected barriers that limit metabolic health research in the autism field: (1) lack of accessible biomedical research methodologies and (2) insufficient attention to mechanisms underlying poor metabolic health in this population, including chronic stress and weight stigma. Drawing on principles from neurodiversity, Universal Design for Research, and the Academic Autism Spectrum Partnership in Research and Education (AASPIRE) guidelines, we outline a neuro-affirming paradigm that can improve metabolic health research in the autism field. Finally, we provide phase-by-phase practical recommendations for researchers, spanning study design, measure development, recruitment, consent, screening, data collection, and interpretation. Aligning metabolic health research with neuro-affirming principles can generate more rigorous, representative, and ethically grounded evidence and ultimately support more meaningful improvements in metabolic health and overall well-being for autistic individuals across the life course.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"12 1","pages":"e70117"},"PeriodicalIF":1.9,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12852506/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146106397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationships Between Metabolic and Bariatric Surgery and Adverse Kidney Outcomes: An Analysis of a Retrospective Cohort.","authors":"Kevin C Maki, Stephanie L Dickinson, Carol F Kirkpatrick, Yongming Qu, Vipin Arora, Xiwei Chen, Bailey Ortyl, Douglas P Landsittel, Sumayyah Ali, Allon N Friedman","doi":"10.1002/osp4.70109","DOIUrl":"10.1002/osp4.70109","url":null,"abstract":"<p><strong>Objective: </strong>Obesity is associated with an increased risk of chronic kidney disease. Metabolic and bariatric surgery (MBS) is currently the most effective intervention for sustained weight loss and may reduce the risk of obesity-associated kidney disease. This study examined the relationships between MBS and adverse kidney outcomes.</p><p><strong>Methods: </strong>This retrospective cohort analysis included 4322 patients with obesity, with or without type 2 diabetes mellitus (T2D), who underwent MBS, and 30,919 nonsurgical control patients from a large health system within the state of Indiana. A primary kidney composite [≥ 1 estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m², ≥ 1 eGFR measurement with a ≥ 40% decrease from baseline, or kidney failure-related death], as well as secondary and tertiary composite and individual outcomes were assessed. Multivariable Cox regression models with and without inverse propensity of treatment weighting were employed to assess associations between MBS and incidence rate for each kidney outcome compared with nonsurgical controls.</p><p><strong>Results: </strong>The mean (standard deviation) follow-up duration was 6.1 (4.5) years. MBS was associated with a 53% (HR: 0.47; 95% CI: 0.42, 0.52; <i>p</i> < 0.001) and 48% (HR: 0.52; 95% CI: 0.46, 0.60; <i>p</i> < 0.001) lower incidence of the primary kidney composite outcome in patients with and without T2D, respectively, and 48%-56% lower risks for the secondary and tertiary outcomes, regardless of T2D status, compared to controls.</p><p><strong>Conclusions: </strong>MBS was associated with markedly lower risks for adverse kidney outcomes in patients with obesity. These results support the potential for MBS as a weight loss intervention to preserve kidney function in patients with obesity, both with and without T2D.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 6","pages":"e70109"},"PeriodicalIF":1.9,"publicationDate":"2025-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12744858/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145857598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Methods of Adjusting VO₂max for Body Size to Estimate Aerobic Capacity in People Presenting for Metabolic and Bariatric Surgery.","authors":"Rebecca Dostan, Sara Slayman, Belinda Durey, Brett Tarca, Justin Bessell, Kade Davison","doi":"10.1002/osp4.70105","DOIUrl":"10.1002/osp4.70105","url":null,"abstract":"<p><strong>Background: </strong>In perioperative settings exercise testing can be used to assess a patient's physical fitness, with VO₂max used as a marker to indicate fitness and subsequent risk of adverse surgical outcomes. However, the commonly used reporting methods of VO₂max may be problematic in populations with excessive FM such as those awaiting MBS for obesity. Hence, alternative ways of expressing VO₂max will be explored.</p><p><strong>Methods: </strong>Historical data from individuals presenting for MBS were analyzed. Predicted VO₂max values were adjusted relative to the participants measured and \"normative\" body mass, where each prediction was assigned a classification score. Predicted VO₂max adjusted to the participants measured FFM was also considered. Data were compared to individuals that are lean and sedentary as well as those with obesity from a previous study.</p><p><strong>Results: </strong>Data from 20 participants awaiting MBS (43.15 ± 11.82 years, 68.50 ± 8.39 cm, 115.29 ± 16.82 kg and 59.93 ± 8.69 kg FFM) were examined. Predicted VO₂max relative: to total mass was 20.15 ± 5.00 mL/kg/min; normative body mass was 30.04 ± 6.58 mL/kg/min; and FFM was 38.55 ± 9.08 mL/kg FFM/min. Median fitness classifications increased from very poor to poor when predicted VO₂max was expressed relative to normative body mass.</p><p><strong>Conclusions: </strong>Reporting predicted VO₂max results relative to body mass may be underestimating fitness and overestimating surgical risk in people who are very obese.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 6","pages":"e70105"},"PeriodicalIF":1.9,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12723064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145828073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interaction of Obese Body Mass Index and Comorbidities on Inflammatory Profiles and Clinical Outcomes After Traumatic Brain Injury: A TRACK-TBI Study.","authors":"Shawn R Eagle, Mary U Simons, Jason Barber, Nancy Temkin, John K Yue, Ava Puccio, Michael A McCrea, Joseph Giacino, Geoffrey Manley, David O Okonkwo, Lindsay D Nelson","doi":"10.1002/osp4.70101","DOIUrl":"10.1002/osp4.70101","url":null,"abstract":"<p><strong>Objective: </strong>Obesity has been associated with worse clinical outcomes after mild traumatic brain injury (mTBI; Glasgow Coma Scale score between 13 and 15). Augmented inflammatory response to mTBI appears to be an important modifier of outcomes for the patients with obesity, but the contribution of comorbidity profile has yet to be analyzed. The objective of this study was to examine the association of: 1. comorbidity profile; and 2. the interaction of obesity with comorbidity profile on clinical outcomes and inflammatory blood biomarkers after mTBI.</p><p><strong>Methods: </strong>Participants were enrolled across emergency departments within 24 h of injury, with clinical outcomes and neurocognitive tests assessed at 2 weeks and 6 months post-injury (<i>n</i> = 1337). Latent class analysis (LCA) was used to identify comorbidity profiles and mixed-effect models for the association of obesity and comorbidity profile on inflammatory/clinical outcomes.</p><p><strong>Results: </strong>Using LCA, 3 classes of comorbidities were identified: \"cardiovascular\" (high rates of cardiovascular disease, hypertension, hyperlipidemia, diabetes; <i>n</i> = 287; 21%), \"internalizing\" (high rates of depression/anxiety, <i>n</i> = 121; 9%), and \"healthy\" (0%-8% rate of comorbidities; <i>n</i> = 929; 69%). \"Healthy\" had higher rates of functional recovery at 6 month (31%; <i>p</i> = 0.001) than \"cardiovascular\" and \"internalizing\" (15%-26%). Within \"healthy,\" obesity was associated with higher c-reactive protein levels on day 1 (ratio = 1.86; <i>p</i> < 0.001), 2 week (ratio = 2.05; <i>p</i> < 0.001) and 6 month (ratio = 2.34; <i>p</i> < 0.001) relative to normal BMI. Obesity was associated with higher IL-6 levels at 2 week (ratio = 1.36; <i>p</i> = 0.005) and 6 month (ratio = 1.47; <i>p</i> < 0.001) relative to normal BMI within \"healthy.\"</p><p><strong>Conclusions: </strong>Obesity and comorbidity profiles are associated with an inflammatory response with the potential to impact recovery; consideration of systemic health at the time of injury could improve recovery.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 6","pages":"e70101"},"PeriodicalIF":1.9,"publicationDate":"2025-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12719804/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145820404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Body Mass Index and Its Influence on Electrocardiographic Parameters in Healthy and Cardiovascular Patients.","authors":"Roholla Hemmati, Mohanna Parvenous, Dorsa Bahrami Zanjanbar, Seyed Hossein Kia, Abbas Soleimani, Sina Bakhshaei","doi":"10.1002/osp4.70107","DOIUrl":"10.1002/osp4.70107","url":null,"abstract":"<p><strong>Objective: </strong>Cardiovascular diseases (CVDs) are a significant cause of mortality worldwide. Smoking, unhealthy diets, physical inactivity, and psychological stress are the main lifestyle factors associated with CVDs. This study was designed to investigate the relationship between electrocardiographic (ECG) changes and various body mass index (BMI) categories, considering demographic characteristics of the participants, such as age, gender, height, and weight.</p><p><strong>Methods: </strong>This cross-sectional study was conducted on 964 patients attending Mostafa Khomeini Hospital, Ilam, Iran. Pearson correlation coefficients and regression models were employed using SPSS v. 24 to assess the relationship between BMI and ECG parameters recorded using a 12-lead ECG.</p><p><strong>Results: </strong>A 10-cm increase in height (165 ± 14) was associated with a 0.089 ms decrease in the PR interval, while a 5-kg weight gain resulted in a 0.20 ms increase in the PR interval (<i>p</i> = 0.49). The QRS interval increased by 2 and 0.03 ms, with a 10 cm height and 5 kg weight gain, respectively. The QT interval remained stable with changes in height but decreased by 1.34 ms with a 5-kg increase in weight.</p><p><strong>Conclusion: </strong>The findings of this study suggest that ECG parameters are influenced by BMI and may be related to cardiovascular risks. An increase in PR and QRS intervals, a decrease in QRS voltage, and alterations in the ST segment and QT interval underscore the importance of maintaining a healthy BMI to reduce the risk of CVD. This message encourages proactive lifestyle changes to improve heart health.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 6","pages":"e70107"},"PeriodicalIF":1.9,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12706520/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145774858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Term Weight Loss in Adults With Overweight or Obesity Using a Breath Biofeedback mHealth App: A One-Year Follow-Up of a Randomized Trial.","authors":"Kaja Falkenhain, Dylan A Lowe, Sean R Locke, Joel Singer, Ethan J Weiss, Jonathan P Little","doi":"10.1002/osp4.70106","DOIUrl":"10.1002/osp4.70106","url":null,"abstract":"<p><strong>Background: </strong>Long-term weight loss success with dietary interventions is notoriously limited. Mobile health (mHealth) interventions offering personalized dietary guidance combined with real-time biofeedback may enhance long-term adherence and provide a sustainable solution for weight management.</p><p><strong>Objectives: </strong>This study reports the prespecified secondary outcome of weight loss at 48 weeks from a parallel-arm randomized clinical trial (ClinicalTrials.gov: NCT04165707) that aimed to evaluate the long-term effectiveness and sustainability of a Mediterranean-style low-carbohydrate diet delivered via an mHealth application paired with breath biofeedback compared with a calorie-restricted low-fat diet application.</p><p><strong>Methods: </strong>Adults with overweight or obesity (<i>N</i> = 155; mean ± SD age, 41 ± 11 years; 71% female; BMI, 33.5 ± 4.7 kg/m²) were randomized to either an intervention promoting a Mediterranean-style low-carbohydrate diet combined with biofeedback from a handheld breath acetone device or an evidence-based comparator promoting a calorie-restricted, low-fat diet. Participants recorded their daily weights using Bluetooth scales. Weight loss over 48 weeks was analyzed using a linear mixed-effects model, incorporating all available daily weight measurements from participants who provided at least one follow-up measurement.</p><p><strong>Results: </strong>At 48 weeks, participants using the breath biofeedback mHealth app achieved clinically meaningful weight loss (-9.54 kg, 95% CI: -12.27 to -6.81 kg). In contrast, participants using the low-fat diet app did not achieve statistically significant weight loss (-2.68 kg, 95% CI: -5.49 to 0.14 kg), resulting in a statistically significant between-group difference (-6.9 kg, 95% CI: -10.8 to -2.9, <i>p</i> < 0.001). No adverse effects were reported in either group.</p><p><strong>Conclusions: </strong>This study demonstrates that a Mediterranean-style diet promoting carbohydrate restriction coupled with biofeedback support delivered via an mHealth app results in clinically meaningful sustained weight loss at 48 weeks. Given its practicality and demonstrated effectiveness, this approach presents a promising non-pharmacological alternative or complement for longer-term weight management.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 6","pages":"e70106"},"PeriodicalIF":1.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12680900/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145701430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Shared Decision-Making in Metabolic and Bariatric Surgery: A Multi-System Implementation and Evaluation.","authors":"David E Arterburn, Robert Wellman, Anita Courcoulas, Jane Anau, Clarissa Hsu, Ali Tavakkoli, Gary S Fischer, Bestoun Ahmed, Joanna Eavey, Casey Luce, Neely Williams, Diana Stilwell, Kathleen Paul, Christopher R Daigle, Glyn Elwyn, Kathleen M McTigue","doi":"10.1002/osp4.70091","DOIUrl":"10.1002/osp4.70091","url":null,"abstract":"<p><strong>Objective: </strong>To enhance shared decision-making (SDM) about metabolic and bariatric surgery (MBS) through the systematic implementation and evaluation of SDM tools across two large healthcare systems.</p><p><strong>Methods: </strong>The project involved developing and integrating SDM tools into clinical workflows at two health systems and training clinicians to use two decision aids with eligible patients. Data were collected using patient surveys, electronic health record (EHR) data, and qualitative interviews with clinicians. The primary outcome was change in patient-reported measures of SDM using the collaboRATE items.</p><p><strong>Results: </strong>Decision aids were delivered to 1675 patients. Implementation was associated with an increase in referrals to MBS and the number of patients undergoing surgery at KPWA but not at UPMC. Baseline levels of SDM quality were high. Post-implementation collaboRATE scores decreased significantly, indicating a perceived decline in SDM quality, but not in two other SDM measures. Qualitative feedback highlighted the challenges and successes of integrating SDM tools into clinical practice.</p><p><strong>Conclusions: </strong>Implementation of SDM tools had mixed results across the sites. Implementation was associated with an increase in referrals and surgery at KPWA but not at UPMC. The perceived quality of SDM conversations also declined. Future efforts should focus on incorporating all weight management options, including medications and lifestyle interventions.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 6","pages":"e70091"},"PeriodicalIF":1.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12680512/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145701485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Expert Perspectives on Self-Monitoring Feedback Personalization, Content, Modality and Frequency: A Delphi Study.","authors":"Rebecca A Krukowski, Katherine Paulikonis, Theresa Markwalter, Simone Minor, Kathryn M Ross","doi":"10.1002/osp4.70104","DOIUrl":"10.1002/osp4.70104","url":null,"abstract":"<p><strong>Introduction: </strong>Participants in behavioral weight management programs are typically provided with weekly interventionist-crafted self-monitoring feedback; however, there is a lack of empirical evidence regarding optimal feedback construction.</p><p><strong>Methods: </strong>Using a Delphi method, experts (<i>N</i> = 67) provided perspectives regarding the optimal focus, frequency, interactivity, and modality of feedback messages. Directed content analyses were used to analyze qualitative data, and descriptive statistics were used to summarize quantitative data.</p><p><strong>Results: </strong>Experts' views on the modality (e.g., email, app notification) varied, and participant preference and practicality were noted as key considerations. Experts ranked 8 feedback components as most important: problem solving, goal setting prompts, calorie intake and physical activity goal attainment, diet tracking frequency, weight trajectory (since the last message and since the start of the program), and diet quality. More experts endorsed the \"sandwich\" approach (i.e., positive comments along with strategies for change) for those experiencing weight loss challenges (95%) than for those experiencing weight loss success (55%). Overall, 82% noted that personalized feedback was important, but they were not always able to provide it due to time restrictions/personnel cost (75% identified these as key barriers).</p><p><strong>Conclusions: </strong>Although most experts viewed personalized self-monitoring feedback as important, time/cost considerations in crafting this feedback are critical. Future experimental studies should be used to evaluate the expert recommendations gathered from this Delphi study.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 6","pages":"e70104"},"PeriodicalIF":1.9,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12676179/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145701477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of an MRI Body Fat Imaging Report on Obesity-Related Cardiometabolic Risk: Findings From the BODY-REAL Study, A Randomized Trial.","authors":"Shradha M Chhabria, Jaime A Pérez, Ian J Neeland","doi":"10.1002/osp4.70099","DOIUrl":"10.1002/osp4.70099","url":null,"abstract":"<p><strong>Objective: </strong>Advanced imaging can inform risk assessment and preventive/therapeutic decision-making to enhance care. It is not known how quantification of body fat distribution using advanced imaging and communication of the result through a graphic report may impact cardiometabolic risk factors and attitudes/behaviors among persons living with overweight or obesity. The BODY-REAL study assessed whether providing patients with (1) visual body fat MRI reports compared with the weight/body mass index (BMI) alone and (2) direct-to-patient reports versus through providers would improve cardiometabolic risk among individuals at elevated cardiometabolic risk.</p><p><strong>Methods: </strong>Participants were randomized in a 2 × 2 factorial design to receive a BMI or MRI body fat distribution report, provided direct-to-patient report or a report through their healthcare provider. Clinical and psychosocial outcomes were measured at 2 weeks, 3, and 6 months and compared using analysis of covariance and linear models with both fixed and random (time-updated) effects.</p><p><strong>Results: </strong>29 participants (31% female, mean BMI 33.6 kg/m²) were randomized. After 6 months of follow-up, MRI report recipients had lower fasting glucose and higher physical activity scores (<i>p</i> < 0.01). Provider-mediated reporting demonstrated greater medication adherence (<i>p</i> = 0.01) and greater perception of personal control of diabetes (<i>p</i> = 0.02) but lower perception of diabetes-related risk (<i>p</i> = 0.003). There were no significant differences in BMI, blood pressure, cholesterol, glycosylated hemoglobin, or other risk perception across study arms.</p><p><strong>Conclusions: </strong>This pilot feasibility study demonstrated potential for direct-to-patient visualization of body fat distribution to improve risk markers and preventive behaviors. Further investigation in a sufficiently powered study is warranted.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov NCT04763772.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 6","pages":"e70099"},"PeriodicalIF":1.9,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12612552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145541700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association Between Weight Stigma Experiences in Healthcare and Self-Reported Healthcare Avoidance in a National Sample.","authors":"Kathleen M Robinson, Aaron M Scherer, Alithea N Zorn, Michelle A Mengeling, Helena H Laroche","doi":"10.1002/osp4.70095","DOIUrl":"10.1002/osp4.70095","url":null,"abstract":"<p><strong>Objectives: </strong>Although weight stigma in healthcare is common, existing measures may not capture the full range of patients' weight stigma experiences in clinical practice. We aimed to examine how physical examination by healthcare providers, communication, and the built environment perpetuate weight stigma and impact healthcare avoidance. Items from the previously developed Weight Stigma in Healthcare Inventory (WSHCI) were tested to assess weight stigma experiences and assess association with healthcare avoidance.</p><p><strong>Methods: </strong>Two sample groups, identified through ResearchMatch and a Qualtrics survey panel, completed the WSHCI online. We analyzed the association between individual items and healthcare avoidance, and between a summation of weight stigma experiences and healthcare avoidance, adjusting for demographics.</p><p><strong>Results: </strong>Five-hundred twenty four surveys were received. All weight stigma items were associated with healthcare avoidance, with the strongest associations found for items related to experiencing stigma during physical examination. Greater numbers of stigmatizing experiences were associated with healthcare avoidance (OR 1.31, 95% CI [1.26, 1.37]).</p><p><strong>Conclusions: </strong>To reduce healthcare avoidance due to weight stigma, all aspects-the physical examination, communication, overall experiences and the built environment-need to be addressed. Reducing the overall number of negative experiences and reducing weight stigma experiences during physical examination may be especially important to reduce healthcare avoidance.</p>","PeriodicalId":19448,"journal":{"name":"Obesity Science & Practice","volume":"11 5","pages":"e70095"},"PeriodicalIF":1.9,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12550863/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145372902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}