Scholarlink

Background <p>This study aimed to determine the factors related to insufficient weight loss (IWL) following bariatric surgery.</p> Methods <p>The data for 3456 individuals who had bariatric surgery were obtained prospectively. A bioelectrical impedance analyzer was used to measure body composition changes and compare them between the sufficient (SWL) and IWL groups. The generalized estimated equation approach was used to assess changes in fat mass (FM), fat-free mass (FFM), FFM loss/weight loss percentage (FFML/WL%), and excess weight loss percentage (EWL%). Multivariate logistic regression models were used for IWL to establish independent baseline factors.</p> Results <p>IWL was recorded in 8% of the cases. The data analysis revealed substantial differences in the changes in FM%, FFM%, FFML/WL%, and EWL% between the SWL and IWL groups after six months of follow-up. The IWL group demonstrated a greater FFML/WL% (Ptime before &amp; after 6 months &lt; 0.05). An older age, a higher baseline BMI, diabetes mellitus (DM), non-smoking, and sleeve gastrectomy (SG) were the predictors of IWL.</p> Conclusion <p>the significant predictors of IWL included older age, a higher baseline BMI, DM, SG, and non-smoking.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Insufficient weight loss after bariatric surgery and its predictors: Tehran Obesity Treatment Study (TOTS)

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月2日

查看全文
  • Minoo Heidari Almasi,
  • Maryam Barzin,
  • Maryam Mahdavi,
  • Alireza Khalaj,
  • Danial Ebrahimi,
  • Majid Valizadeh,
  • Farhad Hosseinpanah

摘要

Background

This study aimed to determine the factors related to insufficient weight loss (IWL) following bariatric surgery.

Methods

The data for 3456 individuals who had bariatric surgery were obtained prospectively. A bioelectrical impedance analyzer was used to measure body composition changes and compare them between the sufficient (SWL) and IWL groups. The generalized estimated equation approach was used to assess changes in fat mass (FM), fat-free mass (FFM), FFM loss/weight loss percentage (FFML/WL%), and excess weight loss percentage (EWL%). Multivariate logistic regression models were used for IWL to establish independent baseline factors.

Results

IWL was recorded in 8% of the cases. The data analysis revealed substantial differences in the changes in FM%, FFM%, FFML/WL%, and EWL% between the SWL and IWL groups after six months of follow-up. The IWL group demonstrated a greater FFML/WL% (Ptime before & after 6 months < 0.05). An older age, a higher baseline BMI, diabetes mellitus (DM), non-smoking, and sleeve gastrectomy (SG) were the predictors of IWL.

Conclusion

the significant predictors of IWL included older age, a higher baseline BMI, DM, SG, and non-smoking.