Anthropometric parameters of nutritional assessment as predictive factors of the MINI nutritional assessment (MNA) of hospitalized elderly patients
Anthropometric parameters of nutritional assessment as predictive factors of the MINI nutritional assessment (MNA) of hospitalized elderly patients
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DOI：
10.1007/s12603-010-0116-8
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发表时间：
2011-03-01
影响因子：
5.8
通讯作者：
De Aquino, J. L. Braga
中科院分区：
文献类型：
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作者：
Leandro-Merhi, V. A.;De Aquino, J. L. Braga
本研究的目的是确定预测住院老年患者MNA（迷你营养评估）分类的营养指标。这项横断面研究评估了109名老年患者在住院初期的营养状况，包括人体测量和实验室指标以及MNA。同时测定习惯性能量摄入（HEI）。评估的营养指标通过单因素和多因素logistic回归分析来验证它们是否可以预测MNA分类。计算比值比（OR）及其各自的置信区间（CI）为95%，显著性水平设为5% （p < 0.05）。大多数患者（61.47%）营养状况良好，但存在营养不良风险的占30.28%，营养不良的占8.26%。年龄在70岁以上的人群，以及臂围、体重指数、小腿围、三头肌皮褶厚度和臂中肌围等指标均存在统计学差异。最初，单因素logistic回归确定的预测因素为体重指数（BMI） （p=0.0001； OR=0.825）、小腿围（CC） （p=0.0026； OR=0.832）、臂围（AC） （p < 0.0001； OR=0.787）、肱三头肌皮褶厚度（TST） （p=0.0014； OR=0.920）和臂中肌围（MAMC） （p=0.0003； OR=0.975）；多元logistic回归分析显示，AC （p=0.0025； OR=0.731(0.597-0.895)）、BMI （p=< 0.0001； OR=10.909(3.298-36.085)）、TST （p=0.0040； OR=0.924(0.876-0.975)）和MAMC （p=0.0010； OR=0.976(0.962-0.990)）是预测MNA分类的主要因素。在本研究条件下，首先是AC，然后是BMI，最后是TST和MAMC共同预测MNA分类。
The objective of this study was to identify nutritional indicators that predict MNA (mini nutritional assessment) classification in hospitalized elderly patients.This cross-sectional study assessed the nutritional status of 109 elderly patients at the beginning of their hospital stay with anthropometric and laboratory indicators and the MNA. Habitual energy intake (HEI) was also determined. The assessed nutritional indicators were investigated by univariate and multivariate logistic regression analysis to verify if they can predict MNA classification. The odds ratio (OR) and its respective confidence interval (CI) of 95% were also calculated, and the significance level was set at 5% (p < 0.05).The nutritional status of most patients (61.47%) was appropriate but 30.28% were at risk of malnourishment and 8.26% were malnourished. Statistical differences were found for those aged more than 70 years and for arm circumference, body mass index, calf circumference, triceps skinfold thickness and mid-arm muscle circumference. Initially, the predictive factors identified by univariate logistic regression were body mass index (BMI) (p=0.0001; OR=0.825), calf circumference (CC) (p=0.0026; OR=0.832), arm circumference (AC) (p < 0.0001; OR=0.787), triceps skinfold thickness (TST) (p=0.0014; OR=0.920) and mid-arm muscle circumference (MAMC) (p=0.0003; OR=0.975); later, multiple logistic regression analyses revealed that first AC (p=0.0025; OR=0.731 (0.597-0.895)), then BMI (p=< 0.0001; OR=10.909 (3.298-36.085)) and finally TST (p=0.0040; OR=0.924 (0.876-0.975)) and MAMC (p=0.0010; OR=0.976 (0.962-0.990)) were factors that predict MNA classification.In the conditions of this study, first AC, then BMI and finally TST and MAMC together were capable of predicting MNA classification.