不同BMI患者内脏脂肪差异性分析

目的探讨不同体质量指数（BMI）患者其内脏脂肪（VAT）含量的差异。 方法应用计算机断层扫描（CT）测量符合纳排标准的1094例于2017年1月1日至12月31日在广州医科大学附属第一医院门诊或住院患者的VAT含量、皮下脂肪（SAT）含量和腰围（WC）。根据上述患者的BMI水平将所有患者分为四组：体重过低组（BMI<18.5 kg/m²，n=56），体重正常组（18.5 kg/m²≤BMI<24 kg/m²，n=444），超重组（24 kg/m²≤BMI<28 kg/m²，n=253）和肥胖组（BMI≥28.0 kg/m²，n=81）。采用秩和检验方法探讨四组患者VAT、SAT和WC的差异。采用Spearman相关分析方法了解BMI分别和VAT、SAT、WC等指标间的相关关系。 结果1094例患者中数据齐全的共834例，其中患有心血管系统疾病有71例，呼吸系统疾病114例，消化系统疾病349例，泌尿系统疾病210例，生殖系统疾病19例，内分泌系统疾病29例。不同疾病种类患者在各BMI水平的VAT含量差异无统计学意义（P>0.05）。四组间的VAT、SAT和WC均存在显著的差异（P<0.01）。组间比较结果显示：SAT含量在肥胖组>超重组>体重正常组>体重过轻组（P<0.01）。VAT含量及WC两个指标的组间比较则显示，超重及肥胖组>体重正常组>体重过轻组（P<0.01），在肥胖与超重两个组别间的比较则未发现差异的显著性（P>0.05）。Spearman相关分析结果显示，在正常体重组和超重组，BMI与VAT呈正相关关系（r分别为0.402、0.195，P<0.05）；在体重过轻组和肥胖组未发现两者的相关性（P>0.05）。BMI与SAT在正常体重组呈正相关关系（r=0.296，P<0.05），而在其余三组则未发现（P>0.05）。BMI与WC的正相关关系体现在正常体重组和超重组（r分别为0.199、0.144，P<0.05），而在体重过轻组和肥胖组未发现两者的相关关系（P>0.05）。 结论BMI作为肥胖程度判断的临床常用指标，与影像学肥胖的判断指标存在有限的相关关系。一定范围内的BMI水平有助于推测内脏脂肪含量，当体重过轻或肥胖达到某种程度时，BMI水平可能难以用于推测内脏脂肪的严重程度及其分布特征。

Difference analysis of visceral fat in patients with different body mass index.

ObjectiveTo investigate the difference of visceral adipose tissue(VAT) area in different body mass index (BMI) patients. MethodsComputed tomography (CT) was applied to measure VAT area, subcutaneous adipose tissue (SAT) area, and waist circumference (WC) in 1094 patients who met the inclusion and exclusion criteria. All patients were divided into four groups according to their BMI levels.Underweight group (BMI<18.5 kg/m², n=56), Normal weight group (18.5 kg/m²≤BMI<24 kg/m², n=444), overweight group (24 kg/m²≤BMI<28 kg/m², n=253) and obesity group (BMI≥28.0 kg/m², n=81). The difference of VAT, SAT and WC between the four groups was studied by rank sum test. Spearman correlation analysis method is used to understand the correlation between BMI and VAT, SAT, WC. ResultsThere were 834 patients with complete data in 1094 patients. There were 71 cases of cardiovascular disease, 114 cases of respiratory diseases, 349 of digestive diseases, 210 cases of urinary diseases, 19 cases of reproductive diseases, and endocrine system diseases in 29 cases. There was no significant difference in the VAT content of patients with different BMI above six systemic diseases (P>0.05). Four groups of patients included underweight group (n=56), normal weight group (n=444), overweight group (n=253) and obese group (n=81). The rank sum test shows, there were significant differences in VAT、SAT and WC between the four groups (P<0.01). The results of inter-group comparison showed that the SAT content of the four groups was in the obese and overweight group > normal weight group > underweight group (P<0.01). VAT area and WC in inter-group comparison shows, overweight and obesity group > normal weight group > underweight group (P<0.01). However, there was no significant difference between obesity and overweight (P>0.05). The inter-group correlation analysis showed, in normal and overweight groups, positive correlation between BMI and VAT (r=0.402 and 0.195, P<0.05). A correlation was not found in the underweight and obese groups (P>0.05). There was a positive correlation (r=0.296) between BMI and SAT area in normal weight group (P<0.05), but not in the other three groups (P>0.05). The positive correlation between BMI and WC was found in normal and overweight groups (r=0.199 and 0.144, P<0.05), but not in the underweight and obese groups (P>0.05). ConclusionsAs a common clinical index of obesity, there is a limited correlation between BMI and imaging obesity indicators. The BMI level in a certain range is helpful to speculate the visceral fat content. When the weight is too light or obesity reaches a certain degree, the BMI level may not be used to speculate the severity and distribution characteristics of visceral fat.