山东省4326名7～1 2岁儿童体成分指数与血压水平的相关性研究

目的 探讨儿童体成分指数与血压水平的相关性.方法 对4326名7～12岁儿童进行身高、体重、血压和皮褶厚度测量,采用回归方程推算体脂比(BF%),用公式计算脂肪组织指数(FMI)=BF%×体重/身高2和非脂肪组织指数(FFMI)=(体重-BF%×体重)/身高2.结果 FMI、FFMI与收缩压(SBP)和舒张压(DBP)呈一定程度正相关,7～12岁儿童FMI与SBP的相关系数为0.432～0.531(男生)、0.413～0.485(女生),与DBP的相关系数为0.316～0450(男生)、0.345～0.421(女生).FFMI与SBP的相关系数为0.214～0.366(男生)、0.108～0.383(女生);与DBP的相关系数为0.090～0.250(男生)、0.063～0.214(女生).血压与FMI的相关性高于FFMI.血压偏高儿童的体成分指数显著高于正常儿童,以FMI差距最大.结论 预防儿童高血压应从控制体脂肪、预防肥胖做起.     

整体生物电阻抗法分析小儿身体组成的可行性

整体生物电阻抗(WBI)测量是成本低廉、操作简便的方法。我们连续5天在上、下午测量12名小儿WBI,以证实其稳定性;用水下浸入体密度法测量22名小儿的体脂(BF)和非脂肪组织(FFM),与WBI及体格指标行相关分析,以证实其分析小儿身体组成的准确性。上、下午Z均值间以及连续5天的Z均值间均无显著差异(P<0.05)。Zw/H~2与BF、H~z/Z与FFM的直线相关系数r分别为0.9617和0.9326(P<0.001),Z、H、W与BF及Z、H与FFM的偏相关系数r有显著性意义(P<0.05)。结果证明了该法分析小儿身体组成的可行性。     

Body composition in 98 patients awaiting kidney transplantation

ObjectiveRecent data suggest that the nutritional status of patients who are on the waiting list for kidney transplantation, influence outcomes after renal transplantation. Body composition (BC) analysis is rarely included in pretransplant evaluation. The aim of this study was to determine how alteration of the BC of these patients could influence pretransplant and post-transplant care.MethodsWe compared the BC of French patients on a waiting list for kidney transplantation to a sex- and age-matched healthy, European control population. Patients were included when listed for kidney grafting in a prospective longitudinal study (CORPOS). Biological nutritional parameters, fat free mass (FFM) and fat mass (FM) estimated by dual-energy x-ray absorptiometry (DXA) were assessed on the day of wait-list registration. FFM and FM index (FFMi - FMi) are the ratio of FFM and FM to height squared. Results are expressed as median (range). These indexes were compared with previous study values used as a normal range in nutritional assessment and clinical practice.ResultsThe study included 28 women and 70 men aged 25.3 to 65.9 y. Body mass index ranged from 16.8 kg/m² to 39.4 kg/m². Compared with controls, FMi was higher in women (10.6 kg/m² [3.7–18.6 kg/m²]) than in men (8.1 kg/m² [3.5–13.3 kg/m²] in M) and FFMi was lower in women (14.3 kg/m² [11.8–21.4 kg/m²]) than in men (17.9 kg/m² [13.9-24.2 kg/m²]) (P < 0.01), reflecting an abnormal distribution of body compartments. All biological parameters were within the normal range.ConclusionBC abnormalities, which can only be detected with the use of DXA, are present in patients on a kidney transplantation waiting list. Detection of these abnormalities could influence the post-transplantation survey in order to prevent the frequent risk for developing metabolic complications after the procedure.     

Weight change adjusted equations for assessing resting metabolic rate in overweight and obese adults

BackgroundAlthough over one hundred equations have been developed to predict the energy expenditure of individuals, none are sensitive to weight change in assessment of resting metabolic rate (RMR) before and after weight loss.ObjectiveTo formulate adjusted equations for overweight and obese individuals and to compare their accuracy with existing prediction RMR equations before and after weight loss.Subjects/materialsThis is historical prospective study. Participants included 39 overweight and obese men and women before and after losing 10–20% from baseline weight on a diet and physical activity regimen for at least three months. Pre and post weight loss measured RMR results were compared to estimated RMR using several existing prediction equations: Harris and Benedict, Ravussin and Bogardus, and Mifflin et al. To improve the accuracy of these prediction equations, we suggest new equations adjusted for weight loss, based on measured RMR and evaluated their accuracy.ResultsPre and post weight loss data indicated: significant fat reduction in both genders; reduction in free-fat mass only in men, and a significant decrease in measured RMR only in women. Our suggested equations were the most accurate and closest to measured RMR in both genders, in comparison to the Harris and Benedict, Ravussin and Bogardus, and Mifflin et al equation results. Estimated RMR using the latter equations was significantly lower than measured RMR in both genders at pre and post weight loss (P < 0.01).ConclusionsThis study highlights the need for adjusting RMR equations before and after weight loss in overweight and obese individuals. Further research is needed to validate our suggested equations.     

生物电阻抗法和双能X线吸收法测量7~ 17岁儿童青少年体成分的一致性评价

目的评价生物电阻抗法(BIA)与双能X线吸收法(DXA)测量7~17岁儿童青少年体成分的一致性。方法对1431名儿童进行BIA和DXA检测。采用组内相关系数(ICC)和Bland-Altman分析评价方法间所测去脂体重和脂肪量的一致性。Bland-Altman分析在对数变换的数据中进行。结果男、女生中BIA与DXA所测去脂体重的ICC分别为0.986和0.974,脂肪量的ICC则分别为0.854和0.926。男生中BIA与DXA的去脂体重比值均值及一致性界限(LoA)分别为1.04和0.95~1.14,女生中则为1.02和0.90~1.15。男、女生中去脂体重的LoA范围均随年龄增长而变窄。男、女生中两种方法的脂肪量比值LoA范围均较宽,分别为0.40~1.27和0.48~1.48。此外,男、女生中均可看到各成分的比值LoA范围随BMI等级增高而变窄。结论BIA所测去脂体重与DXA的一致性良好,但BIA测量脂肪量的误差较大。肥胖儿童的BIA与DXA一致性优于消瘦和正常体重儿童。     

Longitudinal study of body composition changes associated with weight change and physical activity

OBJECTIVE: Weight changes result in fat-free mass (FFM) and body fat (BF) changes. This study determined FFM and BF changes after weight gain or loss and whether these changes differ by gender, physical activity, and age. METHODS: Healthy volunteers, recruited between 1991 and 2003, were followed for 1 y (n = 400) or 3 y (n = 305). Active subjects performed >3 h of physical activity of > or =4.0 metabolic equivalents/wk, sedentary subjects performed <3 h/wk. Body weight and body composition by bioelectrical impedance analysis were determined at year 0, 1, or 3. RESULTS: At years 1 and 3, FFM and BF decreased with weight loss and increased with weight gain. BF was more sensitive (P < 0.03) to weight change than FFM. Compared to weight-stable individuals at year 1, weight gains of 1.0-1.9, 2.0-2.9, and > or =3.0 kg changed FFM by -0.04 (P = 0.90), +0.48 (P = 0.15), and +1.39 kg and BF by +1.35, +1.87, and +3.09 kg, respectively (all P < 0.001). Comparable FFM and BF decreases were observed for weight losses (FFM -0.28 kg, P = 0.38; -0.75 kg, P = 0.04; -1.51 kg, P < 0.001; BF -1.01 kg, P < 0.01; -1.55 kg, P = 0.01; -3.13 kg, P < 0.001). These relations were similar across gender and age strata. At year 1, active individuals were less likely to gain BF with weight gain and more likely to lose BF with weight loss than were sedentary individuals, except for weight losses >3 kg. At year 3, the association between body weight and FFM and BF change was similar between active and sedentary individuals. CONCLUSION: Greater weight changes (>3 kg) are necessary for weight change to have a significant effect on FFM than to have an effect on BF.     

生物电阻抗法测量7～10岁儿童总体水含量和去脂体重的预测模型

目的利用生物电阻抗方法测量儿童的体成分,建立适合我国儿童体成分的预测方程。方法在北京市采用目的抽样法选取409名7～10岁的儿童（男生220名,女生189名）,测量身高和体重,采用生物电阻抗仪测量全身电阻抗和电容抗,采用单标水法测量的总体水（totalbodywater,TBW）和去脂体重（fat—freemass,FFM）作为标准,用多元线性逐步回归法建立回归方程,并采用纯误差和Bland—Altman分析法来判断预测方程的准确度。结果TBW的预测方程=-6．893＋0．410x性别（男：1,女=0）＋0．273×年龄（岁）＋0．174x体重（k）＋0．081×身高（cm）＋0．206x阻抗指数（cm2/Ω）（R2=0．90,均方根误差=1．2kg）;FFM的预测方程=-9．742＋0．784x性别（男=1,女=0）＋0．429x年龄（岁）＋0．227×体重（kg）＋0．104x身高（cm）＋0．269×阻抗指数（cm2／Ω）（R2=0．90,均方根误差=1．6kg）。TBW和FFM的预测值与测量值间差异均无统计学意义,纯误差分别是1．4、1．8kg。TBW和FFM的测量值与预测值的差值与均值之间存在显著正相关性（相关系数分别为0．24、0．23,P〈0．01）。不同BMI分组的测量值与预测值间差异均无统计学意义。结论推导的预测方程有较高的精确度和准确度,能有效准确地预测我国7～10岁儿童的体成分。     

儿童青少年身体脂肪含量和非脂体重的变化分析

目的:分析儿童、青少年身体脂肪含量(FM)和去脂全重(FFM)及其随年龄变化特点及性别差异。方法选择7～15岁体重正常的儿童180名,男、女及每个年龄组各约10名,采用双能 X 线吸收测量法(DEXA)测量身体成分。根据公式 FFMI(kg·m~2,去脂体重指数)=FFM(kg)/身高~2(m~2)和 FMI(kg·m~2,脂肪含量指数)=FM(kg)/身高~2(m~2),计算 FFMI 和 FMI。结果 7～13岁儿童 FM 及全身脂肪含量占体重百分比随年龄增加而增加,13岁以后有所下降,女高于男。7～15岁男、女儿童 FFMI 随年龄增加而增加,男生青春期 FFMI 增长加速,增加总量为女生的2倍,7～15岁男生 FMI 先增后降,女生则一直呈上升趋势,女生 FMI 增加总量为男生的2倍。男生身高与 FMI 相关性差,11～15岁男生的身高与 FFMI 呈显著性正相关。7～10岁女生身高与 FMI 呈显著性正相关,9～10岁女生的身高与 FFMI 呈显著性正相关(P<0.05)。男、女儿童的 BMI 与 FMI 均呈显著性正相关,男生相关系数大于女生。13～15岁男生和7～15岁女生的BMI 与 FFMI 呈显著性正相关(P<0.05)。结论青春期前后儿童脂肪含量及分布随年龄而变化,男女差异有显著性。男性脂肪向分布加速期发生在12岁,女性在10岁。男生 BMI 随年龄增长而增加,主要为 FFMI 的增加,尤其是青春期男生。女生 BMI 的增长为 FFMI 和 FMI 的同时增加。