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Supplementary Material for: Influence of Hormonal Profile on Resting Metabolic Rate in Normal, Overweight and Obese Individuals

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DataCite Commons2020-09-02 更新2024-07-27 收录
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https://karger.figshare.com/articles/dataset/Supplementary_Material_for_Influence_of_Hormonal_Profile_on_Resting_Metabolic_Rate_in_Normal_Overweight_and_Obese_Individuals/5128006
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<b><i>Aims:</i></b> To investigate whether blood thyroid stimulating hormone (TSH), cortisol, insulin and glucose concentrations (plus glucose:insulin ratio; GIR) could improve the accuracy of resting metabolic rate (RMR) prediction in normal, overweight and obese persons. <b><i>Methods:</i></b> Predictive equations were developed and compared against indirect calorimetry measures for RMR in 217 weight-control clinic participants (n = 128 males and n = 89 females: ∼24% normal weight, ∼39% overweight and ∼37% obese). <b><i>Results:</i></b> Using the common accuracy criteria of the proportion of predicted RMR within ±10% of measured RMR, our equations (using age, height, weight and gender, plus the blood factors, both independently and in combination) were accurate ∼36-44% of the time, for the whole sample, and when separated by gender and weight class. Specifically, the addition of the blood hormone and glucose concentrations improved the accuracy of predicted RMR by only 1-8% (NS). <b><i>Conclusions:</i></b> Including blood TSH, cortisol, insulin, glucose and GIR into RMR prediction equations did not significantly improve estimation accuracy, which in any case only met a criterion of ±10% of the measured RMR ∼40% of the time. Further work to refine the prediction of RMR is still needed, and at present, direct measurements should be made wherever possible.

<b><i>研究目的:</i></b> 探讨血液中促甲状腺激素(thyroid stimulating hormone, TSH)、皮质醇、胰岛素及葡萄糖浓度(辅以葡萄糖胰岛素比值(glucose:insulin ratio, GIR))能否提升正常体重、超重及肥胖人群静息代谢率(resting metabolic rate, RMR)预测的准确性。<b><i>研究方法:</i></b> 本研究纳入217名体重管理门诊参与者(男性128名,女性89名;约24%为正常体重,约39%为超重,约37%为肥胖),构建预测方程,并将其与间接测热法(indirect calorimetry)测得的RMR数值进行对比。<b><i>研究结果:</i></b> 以"预测RMR与实测RMR的差值在±10%范围内的样本占比"作为通用准确性评判标准,针对全样本以及按性别、体重类别分层的亚组分析显示,本研究构建的方程(可单独纳入或联合纳入年龄、身高、体重、性别以及血液指标)的预测准确率约为36%~44%。具体而言,添加血液激素及葡萄糖浓度仅使RMR预测准确率提升1%~8%,差异无统计学意义(NS)。<b><i>研究结论:</i></b> 在静息代谢率预测方程中纳入血液促甲状腺激素、皮质醇、胰岛素、葡萄糖及GIR,并未显著提升预测准确性;且无论何种情况,该模型仅在约40%的样本中达到"预测值与实测RMR值偏差在±10%范围内"的评判标准。目前仍需开展进一步研究以优化RMR的预测方法,且在条件允许的前提下应优先采用直接测量手段。
提供机构:
Karger Publishers
创建时间:
2017-06-20
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