Anthropometric data quality assessment in multisurvey studies of child growth

Perumal, Nandita; Namasté, Sorrel; Qamar, Huma; Aimone, Ashley; Bassani, Diego G.; Roth, Daniel

doi:10.1093/ajcn/nqaa162

Cited by 27 publications

(26 citation statements)

References 15 publications

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“…For example, an error of only 1.5 centimeter in length or height measurement could result in approximately 0.1 in the WHZ mean and 3 percent points in wasting prevalence ( 36 ). Earlier evaluations of DHS and MICS surveys showed heterogeneity in anthropometric data quality between and within surveys and over time, although there is evidence of improvements in more recent surveys such as those included in the present analyses ( 37 , 38 ). We are unaware of any previous multicountry analyses examining how the standard deviations of WHZ vary with age in existing surveys.…”

Section: Discussionmentioning

confidence: 64%

Age patterns in overweight and wasting prevalence of under 5-year-old children from low- and middle-income countries

et al. 2021

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Objectives To describe how overweight and wasting prevalence varies with age among children under 5 years in low- and middle-income countries (LMICs). Methods We used data from nationally representative Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Overweight and wasting prevalence were defined as the proportions of children presenting mean weight for length/height (WHZ) more than 2 standard deviations above or below 2 standard deviations from the median value of the 2006 WHO standards, respectively. Descriptive analyses include national estimates of child overweight and wasting prevalence, mean, and standard deviations of WHZ stratified by age in years. National results were pooled using the population of children aged under 5 years in each country as weight. Fractional polynomials were used to compare mean WHZ with both overweight and wasting prevalence. Results Ninety national surveys from LMICs carried out between 2010 and 2019 were included. The overall prevalence of overweight declined with age from 6.3% for infants (aged 0–11 months) to 3.0% in 4 years olds (p = 0.03). In all age groups, lower prevalence was observed in low-income compared to upper-middle-income countries. Wasting was also more frequent among infants, with a slight decrease between the first and second year of life, and little variation thereafter. Lower-middle-income countries showed the highest wasting prevalence in all age groups. On the other hand, mean WHZ was stable over the first 5 years of life, but the median standard deviation for WHZ decreased from 1.39 in infants to 1.09 in 4-year-old children (p < 0.001). For any given value of WHZ, both overweight and wasting prevalence were higher in infants than in older children. Conclusion The higher values of WHZ standard deviations in infants suggest that declining prevalence in overweight and wasting by age may be possibly due to measurement error or rapid crossing of growth channels by infants.

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Section: Discussionmentioning

confidence: 64%

Age patterns in overweight and wasting prevalence of under 5-year-old children from low- and middle-income countries

et al. 2021

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“…High-quality and up-to-date anthropometric data serves as the basis for the evaluation of combined nutritional status indexes of weight, age, and height, and helps to make the difference between high-quality surveys and those with low-quality data. In the context of surveys like the ENSANUT which are applied periodically, the validity, and robustness of the data collected allows estimation of the changes over time of the prevalence of nutritional status indicators of the Mexican population (see Supplemental Material ) ( 17 ).…”

Section: Discussionmentioning

confidence: 99%

Nutrition Status of Children, Teenagers, and Adults From National Health and Nutrition Surveys in Mexico From 2006 to 2020

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Background: Population-level health and nutrition surveys provide critical anthropometric data used to monitor trends of the prevalence of under nutrition and overweight in children under 5 years old, and overweight and obesity in the population over 5 years of age.Objective: Analyze the children malnutrition and overweight and obesity in children, teenagers and adults through the National Health and Nutrition Surveys information available from public databases.Materials and Methods: Comparable anthropometric data was gathered by five Mexican National Health and Nutrition Surveys (in Spanish, ENSANUT). In pre-school-age children, under nutrition status was identified through underweight (Z-score below −2 in weight-for-age), stunting (chronic malnutrition) (Z-score below −2 for length/height-for-age), or wasting (Z-score below −2, for weight-for-length/height); overweight status was defined as a body mass index (BMI, kg/m2) for age over +2. For school-age children and adolescents, a Z-score BMI between +1 and +2 deviations was defined as overweight, and between +2 and +5.5 as obesity. In adults (≥20 years of age), overweight status was classified as a BMI between 25.0 and 29.9, and obesity as ≥30.Results: The anthropometric data presented derives from the databases of five survey years of the Mexican National Health and Nutrition Survey: 2006, 2012, 2016, 2018, and 2020. They include a total of 210,915 subjects with complete anthropometric data (weight, length/height) distributed on five survey moments; subjects were categorized by age group: pre-school-age children (n = 25,968), school-age children (n = 42,255), adolescents (n = 39,275), and adults (n = 103,417). Prevalence of malnutrition by indicator was calculated: in pre-school-age children: low height- and weight-for-age, low weight-for-height, and overweight; and in school-age children, adolescents, and adults, the indicators calculated were overweight and obesity.Conclusions: Results demonstrate the importance of maintaining systematic, reliable, and timely national anthropometric data in the population, in order to detect and track trends and to form the basis of nutrition-related public policy.

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“…The Anthropometry Group aimed to guarantee and control the quality of the anthropometric data by establishing standardized procedures and developing tools to prevent or minimize errors during the data collection. The procedures were based on international guidelines 13,14,15,16 , and those of the Brazilian Ministry of Health 17 for collecting, quality control, and presentation of the anthropometric data.…”

Section: Establishment Of the Expert Group In The Anthropometry Domainmentioning

confidence: 99%

“…Data quality was also assessed by estimating its "heaping", or tendency for a preference in the final digit, in the anthropometric measurements performed by the interviewers. The dissimilarity index was calculated for this purpose: calculating the sum of the differences (without the positive/negative sign) between the observed percentage and the predicted percentage (10%) for each of the last 10 possible digits divided by 2 16 . The value indicates the number of new measurements needed to achieve perfection, i.e., zero, the situation in which each of the last digits occurs in 10% of the measurements 14 , a rare outcome in studies involving many interviewers.…”

Section: Procedures For Assessment Of the Trainingmentioning

confidence: 99%

Methodological aspects of the anthropometric assessment in the Brazilian National Survey on Child Nutrition (ENANI-2019): a population-based household survey

et al. 2021

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The article presents methodological aspects of anthropometric assessment of nutritional status in children under five years of age and their biological mothers. It discusses the strategies used for training and data collection in the Brazilian National Survey on Child Nutrition (ENANI-2019). ENANI-2019 is a population-based household survey conducted in 123 municipalities in Brazil’s 26 states and the Federal District. The anthropometric measurements were body mass and length/stature. The equipment was purchased according to its measurement capacity and precision, portability, and cost-benefit ratio after an extensive market search. The study used internationally established procedures described in manuals, videos, and support material developed for the study by a group of experts. The interviewers were trained to perform the anthropometric measurements and were assessed according to technical measurement error, which was considered adequate (0.30cm) for the children’s length/stature measurements. Measurement errors were identified, and the interviewers were retrained when necessary. Of the 14,558 children in the sample, body mass and length/stature measurements were taken in duplicate in 13,835 and 13,693 children, respectively. The standardized methodological aspects will be helpful in future population studies and were essential for obtaining greater reliability in the data for generating current evidence on the anthropometric assessment of the nutritional status of Brazilian children under five years of age, allowing new perspectives for public policy development.

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Anthropometric data quality assessment in multisurvey studies of child growth

Cited by 27 publications

References 15 publications

Age patterns in overweight and wasting prevalence of under 5-year-old children from low- and middle-income countries

Age patterns in overweight and wasting prevalence of under 5-year-old children from low- and middle-income countries

Nutrition Status of Children, Teenagers, and Adults From National Health and Nutrition Surveys in Mexico From 2006 to 2020

Methodological aspects of the anthropometric assessment in the Brazilian National Survey on Child Nutrition (ENANI-2019): a population-based household survey

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