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FFM Index, FM Index and PBF in Subjects with Normal, Overweight, and Obese BMI in Saudi Arabia Female Population

机译:沙特阿拉伯女性人群中BMI正常,超重和肥胖的受试者的FFM指数,FM指数和PBF

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Aims: To assess Fat Free Mass Index, Fat Mass Index and Percent Body Fat in subjects with normal, overweight, and obese BMI and to examine if FFMI and FMI as compared to BMI have higher predictability in identification of high risk groups as defined by metabolic measurements among female college students and employees in Hail, Northern part of Saudi Arabia.Methods: Sample of 514 female college students and employees were enrolled and body composition was measured by using bioelectrical impendence technique. FFMI and FMI are calculated using the standard formula. Blood pressure (BP) and pulse were measured using automatic BP reader in a resting sitting position. Random blood glucose was tested using strip method (One touch, Simple).Results: Around 11 percent of study subjects were underweight while 25 percent were overweight and another 22 percent were obese. Only 42 percent of study population had normal weight. Except for height there were significant differences for weight, BMI, FM, FFM and %BF across age groups. Weight, FM, FFM shows a linear trend till the age 40 yrs after which an inverse trend begins. BMI continues to show linear trend across all ages. Mean FFMI was around 14 kg/m2 (range 5th – 95th percentile: 12.5 – 17.8 kg/m2) and was modestly but significantly higher (P 0.001) in the higher age group. Similarly, Mean FMI was 8.4 kg/m2 (range 5th – 95th percentile: 3.8 – 18.3 kg/m2) and significantly higher (P 0.001) in the higher age group. In Regression models for SBP, BMI and %BF explain 18.7 % of variance; while for DBP, WC and %BF explain 11.2 % of variance. For blood glucose, it is FFMI, FMI and Visceral fat which explain maximum variance.Conclusion: BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.
机译:目的:评估BMI正常,超重和肥胖的受试者的无脂肪质量指数,脂肪质量指数和体脂百分比,并检查FFMI和FMI与BMI相比是否具有较高的可预测性,以鉴定由代谢确定的高危人群方法:采用生物电阻抗技术,对514名女大学生和员工进行抽样调查,并对身体成分进行测量。 FFMI和FMI使用标准公式计算。使用自动BP读取器在静止的坐姿下测量血压(BP)和脉搏。结果:大约11%的受试者体重不足,而25%的体重超标,另有22%的肥胖。只有42%的研究人群体重正常。除身高外,不同年龄组的体重,BMI,FM,FFM和%BF均存在显着差异。体重,FM,FFM呈线性趋势,直至40岁,此后开始出现反趋势。 BMI在所有年龄段都继续显示线性趋势。平均FFMI约为14 kg / m2(第5 – 95%百分位数:12.5 – 17.8 kg / m2),在较高年龄组中中等偏高,但显着较高(P <0.001)。同样,平均FMI为8.4 kg / m2(第5 – 95%百分数:3.8 – 18.3 kg / m2),并且在较高年龄组中显着较高(P <0.001)。在SBP的回归模型中,BMI和%BF解释了18.7%的方差;而对于DBP,WC和%BF解释了11.2%的方差。对于血糖,由FFMI,FMI和内脏脂肪来解释最大差异。结论:仅BMI不能提供有关FFM或脂肪量对体重的各自贡献的信息。这项研究提出了与低,正常,超重和肥胖BMI相对应的FFMI和BFMI值。 FFMI和BFMI提供有关车厢的信息,而不管高度如何。

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