Effect of nutrition survey 'cleaning criteria' on estimates of malnutrition prevalence and disease burden: secondary data analysis.
Effect of nutrition survey 'cleaning criteria' on estimates of malnutrition prevalence and disease burden: secondary data analysis.
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作者：
Crowe S;Seal A;Grijalva-Eternod C;Kerac M
解决儿童营养不良问题是全球卫生的优先事项。一个关键指标是通过营养调查估计的营养不良发生率。调查设计的大多数方面都是标准化的，但数据“清洗标准”却不是。其目的是排除可能代表测量或数据输入错误的极端值。不同清洁标准对营养不良患病率估计的影响尚不清楚。我们采用了五种常用的数据清理标准（WHO 2006; EPI-Info; WHO 1995 fixed; WHO 1995 flexible; SMART）对21个国家的人口与健康调查数据集进行了数据清理。其中包括163 228名6至59个月的儿童。我们重点关注消瘦（身高体重比低），这是治疗方案的一个关键指标。清洁标准的选择有明显的效果：SMART的包容性最小，导致报告的营养不良患病率最低，而WHO 2006的包容性最大，导致最高。在21个国家中，使用SMART时排除的记录比例是WHO 2006标准的3 - 5倍，导致总消瘦的估计患病率差异为0.5%-3.8%，严重消瘦的差异为0.4%-3.9%。差异的大小与调查样本的标准差有关，标准差是一个既能反映人口异质性又能反映数据质量的统计量。利用这些结果来估计治疗方案的病例量，结果发现所有国家的差异很大。浪费流行率和案件量估计的强烈影响的选择清洗标准。由于关键的政策和方案规划决定取决于这些统计数据，分析做法的差异可能导致营养不良治疗方案的执行不一致和可能不适当。因此，我们呼吁强制报告清洁标准的使用情况，以便对结果进行适当的比较和解释。迫切需要在选择标准方面达成国际共识，以提高营养调查数据的可比性。
Tackling childhood malnutrition is a global health priority. A key indicator is the estimated prevalence of malnutrition, measured by nutrition surveys. Most aspects of survey design are standardised, but data ‘cleaning criteria’ are not. These aim to exclude extreme values which may represent measurement or data-entry errors. The effect of different cleaning criteria on malnutrition prevalence estimates was unknown. We applied five commonly used data cleaning criteria (WHO 2006; EPI-Info; WHO 1995 fixed; WHO 1995 flexible; SMART) to 21 national Demographic and Health Survey datasets. These included a total of 163,228 children, aged 6–59 months. We focused on wasting (low weight-for-height), a key indicator for treatment programmes. Choice of cleaning criteria had a marked effect: SMART were least inclusive, resulting in the lowest reported malnutrition prevalence, while WHO 2006 were most inclusive, resulting in the highest. Across the 21 countries, the proportion of records excluded was 3 to 5 times greater when using SMART compared to WHO 2006 criteria, resulting in differences in the estimated prevalence of total wasting of between 0.5 and 3.8%, and differences in severe wasting of 0.4–3.9%. The magnitude of difference was associated with the standard deviation of the survey sample, a statistic that can reflect both population heterogeneity and data quality. Using these results to estimate case-loads for treatment programmes resulted in large differences for all countries. Wasting prevalence and caseload estimations are strongly influenced by choice of cleaning criterion. Because key policy and programming decisions depend on these statistics, variations in analytical practice could lead to inconsistent and potentially inappropriate implementation of malnutrition treatment programmes. We therefore call for mandatory reporting of cleaning criteria use so that results can be compared and interpreted appropriately. International consensus is urgently needed regarding choice of criteria to improve the comparability of nutrition survey data.
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影响因子：
168.9
作者：
Liu, Li;Johnson, Hope L.;Black, Robert E.
通讯作者：
Black, Robert E.
影响因子：
168.9
作者：
Stevens, Gretchen A.;Finucane, Mariel M.;Paciorek, Christopher J.;Flaxman, Seth R.;White, Richard A.;Donner, Abigail J.;Ezzati, Majid
通讯作者：
Ezzati, Majid
影响因子：
5.2
作者：
Collins, Steve
通讯作者：
Collins, Steve
影响因子：
15.8
作者：
Grijalva-Eternod, Carlos S.;Wells, Jonathan C. K.;Seal, Andrew J.
通讯作者：
Seal, Andrew J.
影响因子：
5.5
作者：
DEAN, AG;DEAN, JA;DICKER, RC
通讯作者：
DICKER, RC