Bioelectrical Impedance Analysis Detects Body Fat Changes After Surgical Subcutaneous Fat Removal.

IF 1.3 4区 医学 Q4 MEDICINE, RESEARCH & EXPERIMENTAL
Metabolic syndrome and related disorders Pub Date : 2024-05-01 Epub Date: 2024-03-18 DOI:10.1089/met.2023.0223
Mohamed Badie Ahmed, Suhail A Doi, Abdella M Habib, Graeme E Glass, Atalla Hammouda, Zaki T N Alyazji, Fatima Saoud Al-Mohannadi, Hoda Khoogaly, Asma Syed, Abeer Alsherawi, Saif Badran
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引用次数: 0

Abstract

Background: The risk and metabolic effects of obesity are determined by the distribution of fat throughout the body. It has been proposed that the distribution of abdominal fat is more closely related to the metabolic risks of obesity. High prevalence of overweight and obesity has thereby contributed to an increased uptake of surgical subcutaneous fat removal (SSFR) procedures. The goal of this study was to determine whether bioelectrical impedance analysis (Tanita system) can be used to detect the removal of excess abdominal subcutaneous fat tissue during SSFR when studying the metabolic effects of such procedures. Methods: Study population comprised patients who received body contouring procedures at the Hamad General Hospital's plastic surgery department between November 2020 and December 2022. To evaluate the factors of interest, subjects were prospectively followed up at two time points: within 1 week before the surgery and within 1-2 weeks thereafter. The following factors were measured: body weight, body fat percentage, body fat mass, body mass index (BMI), fat-free mass, estimated muscle mass, total body water, visceral fat score, and basal metabolic rate. Results: In total, 22 patients were included in the study. The two visits' medians for height, weight, BMI, fat percent (fat%), fat mass, visceral fat rating, and Doi's weighted average glucose (dwAG) were compared. Only in the case of Tanita fat% and fat mass, were the preoperative and postoperative medians significantly different. Furthermore, there was no association between these Tanita measures and dwAG or homeostatic model assessment (HOMA; insulin resistance [IR]) changes (before and after surgery). Tanita measures overestimated fat loss, as seen by the mountain plot and Bland-Altman plot agreement methods. Conclusions: Our findings indicated that the only two Tanita measures exhibited meaningful early associations with the amount of tissue excised which were fat mass and fat% differences. Although dwAG and HOMA-IR are not impacted immediately postsurgery, a trend was seen that suggested improvements in those parameters, even though the changes are not clinically significant.

生物电阻抗分析检测手术切除皮下脂肪后身体脂肪的变化
背景:肥胖的风险和代谢影响取决于脂肪在全身的分布。有人认为,腹部脂肪的分布与肥胖的代谢风险关系更为密切。因此,超重和肥胖的高发率促使皮下脂肪切除手术(SSFR)的使用率上升。本研究的目的是确定生物电阻抗分析(Tanita 系统)是否可用于检测手术切除多余腹部皮下脂肪组织对代谢的影响。研究方法研究对象包括 2020 年 11 月至 2022 年 12 月期间在哈马德总医院整形外科接受塑身手术的患者。为了评估相关因素,研究人员在两个时间点对受试者进行了前瞻性随访:手术前 1 周内和手术后 1-2 周内。对以下因素进行了测量:体重、体脂百分比、体脂质量、体重指数(BMI)、去脂质量、估计肌肉质量、体内总水分、内脏脂肪评分和基础代谢率。结果共有 22 名患者参与了研究。比较了两次就诊的身高、体重、体重指数、脂肪百分比(fat%)、脂肪量、内脏脂肪评分和土井加权平均血糖(dwAG)的中位数。只有塔尼塔脂肪率和脂肪量的术前和术后中位数有显著差异。此外,这些 Tanita 测量值与 dwAG 或同态模型评估(HOMA;胰岛素抵抗 [IR])变化(术前和术后)之间没有关联。从山形图和布兰-阿尔特曼图一致性方法中可以看出,塔尼塔测量值高估了脂肪损失。结论:我们的研究结果表明,仅有两种塔尼塔测量指标与切除的组织量存在有意义的早期关联,即脂肪量和脂肪率差异。虽然手术后 dwAG 和 HOMA-IR 不会立即受到影响,但可以看到一种趋势,表明这些参数有所改善,尽管这些变化在临床上并不显著。
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来源期刊
Metabolic syndrome and related disorders
Metabolic syndrome and related disorders MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
3.40
自引率
0.00%
发文量
74
审稿时长
6-12 weeks
期刊介绍: Metabolic Syndrome and Related Disorders is the only peer-reviewed journal focusing solely on the pathophysiology, recognition, and treatment of this major health condition. The Journal meets the imperative for comprehensive research, data, and commentary on metabolic disorder as a suspected precursor to a wide range of diseases, including type 2 diabetes, cardiovascular disease, stroke, cancer, polycystic ovary syndrome, gout, and asthma. Metabolic Syndrome and Related Disorders coverage includes: -Insulin resistance- Central obesity- Glucose intolerance- Dyslipidemia with elevated triglycerides- Low HDL-cholesterol- Microalbuminuria- Predominance of small dense LDL-cholesterol particles- Hypertension- Endothelial dysfunction- Oxidative stress- Inflammation- Related disorders of polycystic ovarian syndrome, fatty liver disease (NASH), and gout
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