ArticleEmerging themes in epidemiology2018
Change in quality of malnutrition surveys between 1986 and 2015.
Article in Emerging themes in epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Predicting the burden of acute malnutrition in drought-prone regions of Kenya: A statistical analysis.PLOS global public health · 2026Article
- Subnational variations in the quality of household survey data in sub-Saharan Africa.Nature communications · 2025Article
- Estimating double burden of malnutrition among rural and urban children in Amazonia using Bayesian latent models.Frontiers in public health · 2025Article
- [Quality of anthropometric data of children under 5 years in the Brazilian National Food and Nutrition Surveillance System, 2008-2020].Cadernos de saude publica · 2024Article
- Measuring results of humanitarian action: adapting public health indicators to different contexts.Conflict and health · 2022Article
- Quality of anthropometric data in India's National Family Health Survey: Disentangling interviewer and area effect using a cross-classified multilevel model.SSM - population health · 2022Article
- A method for small-area estimation of population mortality in settings affected by crises.Population health metrics · 2022Article
- The impact of improved data quality on the prevalence estimates of anthropometric measures using DHS datasets in India.Scientific reports · 2021Article
- Comparison of anthropometric data quality in children aged 6-23 and 24-59 months: lessons from population-representative surveys from humanitarian settings.BMC nutrition · 2020Article
- Anthropometric data quality assessment in multisurvey studies of child growth.The American journal of clinical nutrition · 2020Article
- Data on acute malnutrition and mortality among under-5 children of pastoralists in a humanitarian setting: a cross-sectional Standardized Monitoring and Assessment of Relief and Transitions Study.BMC research notes · 2019Article
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2 authors.
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Abstract
backgroundRepresentative surveys collecting weight, height and MUAC are used to estimate the prevalence of acute malnutrition. The results are then used to assess the scale of malnutrition in a population and type of nutritional intervention required. There have been changes in methodology over recent decades; the objective of this study was to determine if these have resulted in higher quality surveys.
methodsIn order to examine the change in reliability of such surveys we have analysed the statistical distributions of the derived anthropometric parameters from 1843 surveys conducted by 19 agencies between 1986 and 2015.
resultsWith the introduction of standardised guidelines and software by 2003 and their more general application from 2007 the mean standard deviation, kurtosis and skewness of the parameters used to assess nutritional status have each moved to now approximate the distribution of the WHO standards when the exclusion of outliers from analysis is based upon SMART flagging procedure. Where WHO flags, that only exclude data incompatible with life, are used the quality of anthropometric surveys has improved and the results now approach those seen with SMART flags and the WHO standards distribution. Agencies vary in their uptake and adherence to standard guidelines. Those agencies that fully implement the guidelines achieve the most consistently reliable results.
conclusionsStandard methods should be universally used to produce reliable data and tests of data quality and SMART type flagging procedures should be applied and reported to ensure that the data are credible and therefore inform appropriate intervention. Use of SMART guidelines has coincided with reliable anthropometric data since 2007.
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