评估颈围作为5-8岁巴西儿童心脏代谢风险升高结果的预测指标

M. Shirley, Joilane Alves Pereira-Freire, Karoline de Macêdo Gonçalves Frota, Jesuana Oliveira Lemos, J. Wells, Lays Arnaud Rosal Lopes Rodrigues, Larisse Monteles Nascimento, Valdenir Queiroz Ribeiro, Patrícia Helen de Carvalho Rondó
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引用次数: 2

摘要

背景:儿童超重和肥胖是一个全球性的健康问题,在许多低收入和中等收入国家持续恶化。监测超重和相对代谢风险的低成本测量方法,如颈围(NC),应在不同人群和年龄组中进行评估。目的:探讨5-8岁巴西儿童NC和BMI与心脏代谢参数的关系。方法:本横断面研究于2004-2006年进行,通过人体测量法测量身高、体重和NC,并通过生物电阻抗估计脂肪和无脂质量。评估的心脏代谢危险因素包括收缩压和舒张压、高密度和低密度脂蛋白胆固醇、甘油三酯和胰岛素抵抗的稳态模型评估(HOMA)。采用多元回归和精确召回率图分析检验NC和BMI与心脏代谢危险因素的相关性。结果:纳入371例儿童(52%为女性)。在性别分层的多元回归模型中,NC与BMI、脂肪量和无脂肪量呈正相关,并与收缩压和HOMA呈正相关。然而,后一种关系在BMI调整后基本消失。NC或BMI与收缩压或HOMA bb0第90百分位数相关的曲线下面积在合并样本中较低,表明分类器性能较差。结论:NC和BMI与心脏代谢危险因素具有相似的相关性,尽管NC大多不独立于BMI与危险因素相关。与先前的研究相反,NC对儿童心脏代谢危险因素的分类很差。NC与脂肪和无脂肪质量的关系可能有助于解释其不良性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of neck circumference as a predictor of elevated cardiometabolic risk outcomes in 5–8-year-old Brazilian children
ABSTRACT Background: Childhood overweight and obesity is a global health problem that continues to worsen in many low- and middle-income countries. Low-cost measurements for monitoring overweight and relative metabolic risk, such as neck circumference (NC), should be evaluated in different populations and age groups. Aim: To test associations of NC and BMI with cardiometabolic parameters in 5-8-year-old Brazilian children. Methods: This cross-sectional study carried out from 2004–2006 measured height, weight and NC by anthropometry, and estimated fat and fat-free mass by bioelectrical impedance. Cardiometabolic risk factors assessed were systolic and diastolic blood pressure, high- and low-density lipoprotein cholesterol, triglycerides, and homeostatic model assessment of insulin resistance (HOMA). Associations of NC and BMI with cardiometabolic risk factors were tested using multiple regression and precision-recall plot analysis. Results: Analyses included 371 children (52% female). NC associated positively with BMI, fat mass, and fat-free mass, and with systolic blood pressure and HOMA following adjustment for age in sex-stratified multiple regression models. However, the latter relationships largely disappeared following adjustment for BMI. Area under the curve for NC or BMI in association with systolic blood pressure or HOMA >90th percentile was low in the pooled sample, indicating poor classifier performance. Conclusions: NC and BMI demonstrated similar associations with cardiometabolic risk factors, although NC mostly did not correlate with risk factors independently of BMI. In contrast to previous studies, NC was a poor classifier of cardiometabolic risk factors in children. The association of NC with both fat and fat-free mass may aid in explaining its poor performance.
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