Objectives: To determine the distribution of EOSS stages and differences in weight loss achieved according to EOSS stage, in patients attending a referral-based publically funded multisite weight management clinic.
Subjects/methods: 5,787 obese patients were categorized using EOSS staging using metabolic risk factors, medication use, and severity of doctor diagnosis of obesity-related physiological, functional, and psychological comorbidities from electronic patient files.
Results: The prevalence of EOSS stages 0 (no risk factors or comorbidities), 1 (mild conditions), 2 (moderate conditions), and 3 (severe conditions) was 1.7%, 10.4%, 84.0%, and 3.9%, respectively. Prehypertension (63%), hypertension (76%), and knee replacement (33%) were the most common obesity-related comorbidities for stages 1, 2, and 3, respectively. In the models including age, sex, initial BMI, EOSS stage, and treatment time, lower EOSS stage and longer treatment times were independently associated with greater absolute (kg) and percentage of weight loss relative to initial body weight (P < 0.05).
Conclusions: Patients attending this publicly funded, referral-based weight management clinic were more likely to be classified in the higher stages of EOSS. Patients in higher EOSS stages required longer treatment times to achieve similar weight outcomes as those in lower EOSS stages.
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http://dx.doi.org/10.1155/2015/619734 | DOI Listing |
J Clin Endocrinol Metab
March 2025
Metabolic Diseases Research Unit, National Institute of Medical Science and Nutrition Salvador Zubiran, Mexico City, Mexico.
Background: There is large variation in the individual risk of developing obesity-associated comorbidities. While obesity is highly prevalent in Mexico, data on the extent and heterogeneity of its associated co-morbidities is lacking. Hereby, we estimated the prevalence of different obesity-associated comorbidities, and how they have changed over 15 years.
View Article and Find Full Text PDFNutrients
October 2024
Department of Medical Sciences, University of Torino, 10126 Torino, Italy.
Objective: To assess the complementary role of the Body Mass Index (BMI) and Edmonton Obesity Staging System (EOSS) in predicting all-cause and cause-specific mortality in people living with overweight and obesity (PLwOW/O).
Methods: A longitudinal analysis of prospectively collected data from the 1999-2018 cycles of the National Health and Nutrition Examination Survey (NHANES) was conducted. The association between BMI, EOSS, and mortality was evaluated through Cox regression models, adjusted for confounders.
Acta Parasitol
September 2024
Laboratory of Experimental Chemotherapy in Veterinary Parasitology (LQEPV), Department of Animal Parasitology, Institute of Veterinary Medicine, Federal Rural University of Rio de Janeiro, BR 465, Km 7, Seropedica, Rio de Janeiro, 23890-000, Brazil.
J Assoc Physicians India
October 2023
Associate Professor, Department of Endocrinology, MS Ramaiah Medical College, Bengaluru, Karnataka, India.
: The objective of this consensus article was to form a list of expert recommendations and an easily adaptable algorithm for obesity management in India by primary care physicians (PCPs). : A Delphi-based model was followed to form a list of the consensus recommendations. Consensus statements were created from the results of a literature review that were graded as per the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria.
View Article and Find Full Text PDFAnn Saudi Med
April 2024
From the College of Medicine, Imam Muhammad Ibn Saud Islamic University.
Background: Multiple studies have demonstrated a correlation between a high body mass index and discriminatory COVID-19 outcomes. Studies appear to indicate that there is a correlation between obesity-related comorbidities and less favorable outcomes.
Objectives: The primary aim of the current investigation is to conduct a thorough assessment of the correlation between BMI and comorbidities associated with obesity, and their potential impact on the severity and consequences of COVID-19 infection among patients receiving care in a tertiary healthcare setting.
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