ArticleBMC nutrition2020
Comparison of anthropometric data quality in children aged 6-23 and 24-59 months: lessons from population-representative surveys from humanitarian settings.
Article in BMC nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 15 citations in OpenAlex.
- Three-arm clinical trial of improved flour targeting intestinal microbiota (MALINEA).Maternal & child nutrition · 2024Trial
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- Accuracy of a smartphone-based 3D imaging tool for height measurement and stunting detection among children 24-59 months of age in Nepal: a validation study.The Lancet regional health. Southeast Asia · 2026Article
- Assessment of Stunting and Its Effect on Wasting in Children Under Two in Rural Madagascar.Children (Basel, Switzerland) · 2025Article
- Assessment of Kidney Function Discrepancies in Pediatric CAKUT Patients Using Bedside Schwartz Equation and Renal Scintigraphy.Diseases (Basel, Switzerland) · 2024Article
- Identifying biologically implausible values in big longitudinal data: an example applied to child growth data from the Brazilian food and nutrition surveillance system.BMC medical research methodology · 2024Article
- Influence of non-directional errors in anthropometric measurements and age estimation on anthropometric prevalence indicators.PloS one · 2024Article
- [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
- Prevalence, severity, and predictors of malnutrition in Indian children with cerebral palsy and their impact on health-related quality of life.European journal of pediatrics · 2023Article
- Article
- Child wasting before and after age two years: A cross-sectional study of 94 countries.EClinicalMedicine · 2022Article
- Nutritional status of children under 5 years old in Namibia: adjusting for poor quality child anthropometry.Journal of nutritional science · 2022Article
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Authors and funding
4 authors at 3 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundEnsuring the quality of anthropometry data is paramount for getting accurate estimates of malnutrition prevalence among children aged 6-59 months in humanitarian and refugee settings. Previous reports based on data from Demographic and Health Surveys suggested systematic differences in anthropometric data quality between the younger and older groups of preschool children.
methodsWe analyzed 712 anthropometric population-representative field surveys from humanitarian and refugee settings conducted during 2011-2018. We examined and compared the quality of five anthropometric indicators in children aged 6-23 months and children aged 24-59 months: weight for height, weight for age, height for age, body mass index for age and mid-upper arm circumference (MUAC) for age. Using the z-score distribution of each indicator, we calculated the following parameters: standard deviation (SD), percentage of outliers, and measures of distribution normality. We also examined and compared the quality of height, weight, MUAC and age measurements using missing data and rounding criteria.
resultsBoth SD and percentage of flags were significantly smaller on average in older than in younger age group for all five anthropometric indicators. Differences in SD between age groups did not change meaningfully depending on overall survey quality or on the quality of age ascertainment. Over 50% of surveys overall did not deviate significantly from normality. The percentage of non-normal surveys was higher in older than in the younger age groups. Digit preference score for weight, height and MUAC was slightly higher in younger age group, and for age slightly higher in the older age group. Children with reported exact date of birth (DOB) had much lower digit preference for age than those without exact DOB. SD, percentage flags and digit preference scores were positively correlated between the two age groups at the survey level, such as those surveys showing higher anthropometry data quality in younger age group also tended to show higher quality in older age group.
conclusionsThere should be an emphasis on increased rigor of training survey measurers in taking anthropometric measurements in the youngest children. Standardization test, a mandatory component of the pre-survey measurer training and evaluation, of 10 children should include at least 4-5 children below 2 years of age.
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