营养不良:无声的危机:整理2岁以下儿童营养状况的人体测量测量:一项基于医院的病例对照研究。

IF 1 Q4 PRIMARY HEALTH CARE
Vibha V Gosalia, Rujal D Bhitora, Harsha M Solanki
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引用次数: 0

摘要

背景:即使营养不良是一种危及生命的疾病,也没有一个单一的“黄金标准”人体测量来诊断儿童营养不良。因此,本病例对照研究比较了不同的人体测量值来评估儿童营养不良。方法:使用世卫组织2006年MGRS标准,选择病例和对照,并对年龄和性别进行匹配。计算的样本量为154例(77例和77例对照),假设双侧置信水平为95%,研究功率为80%,病例对照比为1:1,将10%的无反应率和缺乏纯母乳喂养作为暴露因素。z评分(WFH、HFA、WFA)采用WHO Anthro软件计算。计算每个人体测量值的敏感性、特异性和准确性。对MUAC与WFA和HFA z -评分进行多元线性回归比较。并计算了人体测量失败综合指数(CIAF)。结果:即使在对照组中,也有26%的人严重发育迟缓,14.2%的人严重体重不足。MUAC诊断严重体重不足和严重发育不良的敏感性分别为84.2%和58.5%。多元线性回归发现WAZ与MUAC呈正相关。在154名儿童中,114名(74%)有人体测量失败。结论:强烈推荐联合人体测量方法筛查社区慢性营养不良。需要用当地语言开发简单可行的软件,供草路工人使用,以早期诊断SAM儿童。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Malnutrition: The silent crisis: Collation of anthropometric measures of nutritional status in children under 2 years of age: A hospital-based case-control study.

Background: Even if malnourishment is a life-threatening condition, there is not a single 'gold standard' anthropometric measurement to diagnose child undernutrition. Hence, this case-control study compared different anthropometric measurements to assess child malnutrition.

Methodology: Using WHO's MGRS Criteria 2006, cases and controls were selected and matching was done for age and sex. The calculated sample size was 154 (77 cases and 77 controls), assuming a two-sided confidence level of 95%, power of the study 80% and a case-control ratio of 1:1, 10% nonresponse rate and lack of exclusive breastfeeding taken as an exposure factor. The Z-scores (WFH, HFA, WFA) were calculated using WHO Anthro software. The sensitivity, specificity, and accuracy were calculated for each anthropometric measure. Multiple linear regressions for comparison of MUAC against WFA and HFA Z-scores were performed. The Composite Index of Anthropometric Failure (CIAF) was also calculated.

Results: Even among controls, 26% were severely stunted and 14.2% were severely underweight. The sensitivity MUAC to diagnose severely underweight and severely stunted children was 84.2% and 58.5%, respectively. Multiple Linear regression found positive association of WAZ and MUAC. Out of 154 children, 114 (74%) had anthropometric failure.

Conclusions: The combined anthropometric measurements approach to screen chronic malnutrition in the community is strongly recommended. There is a need to develop software in the local language that is simple and feasible to use by grass route workers for early diagnosis of SAM children.

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