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Associated Indicators
Short name:
Children aged <5 years underweight Data type:
Percent/Numbers
Topic:
Risk factors
Sustainable Development Goals
General Programme of Work
Nutrition, Child Malnutrition
Rationale:
Child growth is an internationally accepted outcome reflecting child nutritional status. Child underweight belongs to a set of indicators whose purpose is to measure nutritional imbalance and malnutrition resulting in undernutrition (assessed by underweight, stunting and wasting) and overweight. Definition:
Prevalence of underweight (weight-for-age <-2 standard deviation from the median of the World Health Organization (WHO) Child Growth Standards) among children under 5 years of age.
Numbers affected (thousands) of underweight (weight-for-age <-2 standard deviation from the median of the World Health Organization (WHO) Child Growth Standards) among children under 5 years of age. Disaggregation:
Country, regional and worldwide JME global estimates refer to the age group of children under 5 years, sexes combined. Disaggregation are currently not available for the JME global estimates. However, a disaggregated dataset of national primary sources with sub national and stratified estimates (e.g. sex, age groups, wealth, mothers' education, residence) is available. Method of measurement
Methods and Guidance:
WHO and UNICEF provide recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old. (Recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old. Geneva: World Health Organization and the United Nations Children’s Fund (UNICEF), 2019. Licence: CC BY-NC-SA 3.0 IGO. )
Analysis Tool
To facilitate re-running of nutritional survey data based on standardized approach, WHO has developed an online tool to analyse child anthropometric data. The WHO Anthro Survey Analyzer aims to promote best practices on data collection, analyses and reporting of anthropometric indicators. It offers analysis for four indicators: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age. (WHO Anthro Survey Analyser and other tools) M&E Framework:
Impact Method of estimation:
Data collection method
UNICEF and WHO employ their existing networks to obtain data. WHO relies on the organization’s structure and an expanding network developed following the creation of the WHO Global Database on Child Growth and Malnutrition. For UNICEF, the cadre of dedicated data and monitoring specialists working at national, regional and international levels in 190 countries routinely provides technical support to produce child malnutrition estimates through surveys and administrative systems and analyses for improved programme planning. The World Bank Group provides estimates available through the Living Standard Measurement Surveys (LSMS). Method of estimation of global and regional aggregates:
Method of estimation of global and regional aggregates:
A well-established methodology for deriving global and regional trends and forecasting future trends, have been published. (de Onis M, Blössner M, Borghi E, Morris R, Frongillo EA. Methodology for estimating regional and global trends of child malnutrition. Int J Epidemiol. 2004 Dec;33(6):1260-70. doi: 10.1093/ije/dyh202. Epub 2004 Nov 12. PMID: 15542535. ;
de Onis M, Blössner M, Borghi E, Frongillo EA, Morris R. Estimates of global prevalence of childhood underweight in 1990 and 2015. JAMA. 2004 Jun 2;291(21):2600-6. doi: 10.1001/jama.291.21.2600. PMID: 15173151.) The trend estimation uses a linear mixed-effect model allowing for random effects at country level and for heterogeneous covariance structures. The basic model contains the factors sub-region, year, and the interaction between year and the sub-region as fixed effects with country as a random effect.
(The UNICEF-WHO-World Bank Joint Child Malnutrition Estimates (JME) standard methodology New York: the United Nations Children’s Fund (UNICEF), the World Health Organization and the World Bank, 2024. Licence: CC BY-NC-SA 3.0 IGO. )
Preferred data sources:
Household surveys
Specific population surveys
Surveillance systems
Expected frequency of data dissemination:
Data sources are updated in the WHO Global Database for Child Growth and Malnutrition a continuous basis to feed into the annual production of global and regional estimates and updated country level dataset released every March.
For more information about contributing to the WHO Global Database for Child Growth and Malnutrition, please review the “Identification of data sources section” on the Methodology Page (WHO Department of Nutrition and Food Safety – Joint Child Malnutrition Estimates) Expected frequency of data collection:
The UNICEF-WHO-WB Joint Child Malnutrition (JME) group releases country, regional and worldwide estimates at the end of March so that data are available for reporting on the Sustainable Development Goals (SDGs). (The UNICEF-WHO-World Bank Joint Child Malnutrition Estimates (JME) standard methodology New York: the United Nations Children’s Fund (UNICEF), the World Health Organization and the World Bank, 2024. Licence: CC BY-NC-SA 3.0 IGO. ) Contact person email:
nfsdata@who.int Name:
Department of Nutrition and Food Safety Data Type Representation:
Data sourcesFor the majority of countries, nationally representative household surveys constitute the primary data source used to generate the JME global estimates. For a limited number of countries data from surveillance systems are also used as a primary data source for generation of the JME global estimates if sufficient population coverage is documented (about 80%). For both types of primary data sources, the child’s length/height and weight measurements have to be collected following recommended standard measuring techniques (WHO/UNICEF 2019).
IMRID:
27 Limitations:
Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels. Links: