基于身体指数的接收器工作特征曲线模型是评估亚洲女性代谢性疾病风险的重要工具

IF 1.9 Q3 ENDOCRINOLOGY & METABOLISM Human Nutrition and Metabolism Pub Date : 2024-01-16 DOI:10.1016/j.hnm.2024.200243
Zoomi Singh, Vandana Verma, Neelam Yadav
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引用次数: 0

摘要

目的 衡量肥胖的正确方法仍是一个争论不休的问题。本研究将对印度北方邦普拉亚格拉杰(阿拉哈巴德)城市成年女性的肥胖患病率、人体测量学和身体成分进行调查,以此作为肥胖和脂肪过多的筛查工具。结果除身体总水分 (TBW) 外,所有肥胖指标和健康指标均随年龄增长而增加(p < 0.000,95% CI-置信区间)。根据模型计算出的成年女性体脂(%)、肌肉质量(千克)、总水分(%)和内脏脂肪(千克)的适当临界值分别为 33.5、34.5、46.5 和 4.5。通过逐步逻辑回归,分别建立了消除腰围(WC)和腰臀比(WHR)的两个模型。在模型 1 中,年龄、WHR 和内脏脂肪(VF)与收缩压;年龄和 TBW 与舒张压;年龄和 VF 与随机血糖;WHR、体脂率(BF %)、肌肉质量(MM)和年龄(血红蛋白)均与代谢风险变量的存在显著相关。在模型 2 中,只有年龄对预测收缩压有显著影响;年龄、TBW 和 WC 对预测舒张压有显著影响;年龄和 VF 对预测随机血糖有显著影响;BF%、WC 和年龄对预测血红蛋白有显著影响。这两个模型都可用于评估他们的代谢风险。
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Body indices based receiver operating characteristics curve models are important risk assessing tools for metabolic diseases among Asian women

Purpose

The right way to measure obesity is still a matter of debate. This study will look at the prevalence of obesity, anthropometrics, and body composition as screening tools for obesity and adiposity among adult women in urban Prayagraj (Allahabad), Uttar Pradesh, India. It will also try to figure out exactly what level of obesity is linked to a metabolic risk.

Methods

A Cross-sectional study comprising 570 urban women of Prayagraj (Allahabad), Uttar Pradesh, India aged 20–49 years were examined for anthropometry, body composition analysis, blood pressure, random blood sugar, and haemoglobin.

Results

Except for total body water (TBW), all measures of obesity and health markers increased with age (p < 0.000, 95% CI-confidence interval). Appropriate cutoffs calculated with model for adult women for body fat (%), muscle mass (kg), total body water (%), and visceral fat (kg) were 33.5, 34.5, 46.5, and 4.5 respectively. Using stepwise logistic regression, two models eliminating waist circumference (WC) and wait to hip ratio (WHR), respectively, were created. Age, WHR, and visceral fat (VF) for systolic blood pressure; age and TBW for diastolic blood pressure; age and VF for random blood sugar; WHR, body fat% (BF %), Muscle mass (MM), and age for haemoglobin, were all significantly associated with the presence of metabolic risk variables in Model 1. In model 2, only age was significant for predicting systolic blood pressure; age, TBW, and WC for diastolic blood pressure; age and VF for random blood sugar; BF%, WC, and age for haemoglobin were shown to be significantly associated with metabolic risk variables.

Conclusions

Two basic models for predicting metabolic risk in Asian Indians were studied. Both models can be used to assess metabolic risk in them.

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来源期刊
Human Nutrition and Metabolism
Human Nutrition and Metabolism Agricultural and Biological Sciences-Food Science
CiteScore
1.50
自引率
0.00%
发文量
30
审稿时长
188 days
期刊最新文献
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