2. SDG Metadata
3. 2-2-2a
4. French

<p><strong>URL:</strong></p>
<p>data.unicef.org/nutrition/malnutrition.html;</p>
<p>https://www.who.int/data/gho/data/themes/topics/joint-child-malnutrition-estimates-unicef-who-wb; http://datatopics.worldbank.org/child-malnutrition;</p>
<p><strong>References:</strong></p>
<p>de Onis M, Bl&#xF6;ssner M, Borghi E, et al. (2004), Methodology for estimating regional and global trends of childhood malnutrition. Int J Epidemiol, 33(6):1260-70. &lt;<a href="https://pubmed.ncbi.nlm.nih.gov/15542535/">https://pubmed.ncbi.nlm.nih.gov/15542535/</a>&gt;</p>
<p>de Onis, M., Onyango, A., Borghi, E., Garza, C., and Yang, H. (2006). Comparison of the World Health Organization (WHO) Child Growth Standards and the National Center for Health Statistics/WHO international growth reference: Implications for child health pro&#xAD;grammes. Public Health Nutrition, 9(7), 942-947. doi:10.1017/PHN20062005 &lt;<a href="https://www.who.int/childgrowth/publications/Comparison_implications.pdf">https://www.who.int/childgrowth/publications/Comparison_implications.pdf</a>&gt;</p>
<p>McLain A, Frongillo E, Feng J, Borghi E (2018). Prediction intervals for penalized longitudinal models with multi-source summary measures: an application to childhood malnutrition. Stat Med; 38(6):1002-1012; doi: 10.1002/sim.8024. Epub 2018 Nov 14. &lt;<a href="https://pubmed.ncbi.nlm.nih.gov/30430613/">https://pubmed.ncbi.nlm.nih.gov/30430613/</a>&gt;</p>
<p>United Nations Children&#x2019;s Fund (UNICEF), World Health Organization, International Bank for Reconstruction and Development/The World Bank (2019). Meeting report on Technical Consultation on a Country-level model for SDG2.2. December 2019</p>
<p>UNICEF-WHO-World Bank (2020). Technical notes from the country consultation on SDG Indicators 2.2.1 on stunting, 2.2.2a on wasting and 2.2.2b on overweight &lt;<a href="https://data.unicef.org/resources/jme-2021-country-consultations/">https://data.unicef.org/resources/jme-2021-country-consultations/</a>&gt;</p>
<p>WHO (2006). WHO Multicentre Growth Reference Study (MGRS) &lt;https://www.who.int/tools/child-growth-standards/who-multicentre-growth-reference-study&gt;</p>
<p>World Health Organization and United Nations Children&#x2019;s Fund (2019). 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&#x2019;s Fund (UNICEF), 2019. Licence: CC BY-NC-SA 3.0 IGO. &lt;<a href="https://www.who.int/nutrition/publications/anthropometry-data-quality-report">https://www.who.int/nutrition/publications/anthropometry-data-quality-report</a>&gt;</p>
<p>WHO. WHO Anthro Survey Analyser (2019). Available at <a href="https://www.who.int/tools/child-growth-standards/software">https://www.who.int/tools/child-growth-standards/software</a>. </p>
<p>Yang H and de Onis M (2008). <a href="http://www.who.int/entity/nutgrowthdb/publications/algorithms/en/index.html">Algorithms for converting estimates of child malnutrition based on the NCHS reference into estimates based on the WHO Child Growth Standards</a>. BMC Pediatrics 2008, 8:19 (05 May 2008) &lt;http://www.biomedcentral.com/1471-2431/8/19&gt;.</p>

<p>(Toutes les références sont en anglais)</p>
<p><strong>URL : </strong></p>
<p>data.unicef.org/nutrition/malnutrition.html;</p>
<p>http://www.who.int/nutgrowthdb/estimates2014/en/;</p>
<p>http://datatopics.worldbank.org/child-malnutrition;</p>
<p><strong>Références :</strong></p>
<p>Fonds des Nations Unies pour l'enfance, Organisation mondiale de la Santé, Banque mondiale (2012). UNICEF-OMS-Banque mondiale « Joint Child Malnutrition Estimates ». (UNICEF, New York; OMS, Genève; Banque mondiale, Washington, DC ; 2012). </p>
<p>de Onis M, Blössner M, Borghi E, et autres (2004), Methodology for estimating regional and global trends of childhood malnutrition.nternational Journal of Epidemiology, 33(6):1260-70. </p>
<p>Yang H et de Onis M. <a href="http://www.who.int/entity/nutgrowthdb/publications/algorithms/en/index.html">Algorithms for converting estimates of child malnutrition based on the NCHS reference into estimates based on the WHO Child Growth Standards </a><br> BMC Pediatrics 2008, 8:19 (05 mai 2008)<br> (http://www.biomedcentral.com/1471-2431/8/19). </p>
<p>Organisation mondiale de la Santé (2008). « Training Course on Child Growth Assessment ». Genève, OMS, 2008.</p>
<p>International Journal of Epidemiology 2003;32:518-26</p>

<p><strong>URL:</strong></p>
<p>data.unicef.org/nutrition/malnutrition.html; </p>
<p>https://www.who.int/nutgrowthdb/estimates2014/en/data/gho/data/themes/topics/joint-child-malnutrition-estimates-unicef-who-wb; http://datatopics.worldbank.org/child-malnutrition;</p>
<p><strong>References:</strong></p>
<p>United Nations Children&#x2019;s Fund, World Health Organization, The World Bank (2012). UNICEFWHO-World Bank Joint Child Malnutrition Estimates.de Onis M, Bl&#xF6;ssner M, Borghi E, et al. (2004), Methodology for estimating regional and global trends of childhood malnutrition. Int J Epidemiol, 33(6):1260-70. &lt;<a href="https://pubmed.ncbi.nlm.nih.gov/15542535/">https://pubmed.ncbi.nlm.nih.gov/15542535/</a>&gt;</p>
<p>de Onis, M., Onyango, A., Borghi, E., Garza, C., and Yang, H. (2006). Comparison of the World Health Organization (WHO) Child Growth Standards and the National Center for Health Statistics/WHO international growth reference: Implications for child health pro&#xAD;grammes. Public Health Nutrition, 9(7), 942-947. doi:10.1017/PHN20062005 &lt;<a href="https://www.who.int/childgrowth/publications/Comparison_implications.pdf">https://www.who.int/childgrowth/publications/Comparison_implications.pdf</a>&gt;</p>
<p>McLain A, Frongillo E, Feng J, Borghi E (2018). Prediction intervals for penalized longitudinal models with multi-source summary measures: an application to childhood malnutrition. Stat Med; 38(6):1002-1012; doi: 10.1002/sim.8024. Epub 2018 Nov 14. &lt;<a href="https://pubmed.ncbi.nlm.nih.gov/30430613/">https://pubmed.ncbi.nlm.nih.gov/30430613/</a>&gt;</p>
<p>United Nations Children&#x2019;s Fund (UNICEF), New York; WHO, Geneva; The World Bank, Washington, DC; 2012). </p>
<p>de Onis M, Bl&#xF6;ssner M, Borghi E, et al. (2004), Methodology for estimating regional and global trends of childhood malnutrition. Int J Epidemiol, 33(6):1260-70.World Health Organization, International Bank for Reconstruction and Development/The World Bank (2019). Meeting report on Technical Consultation on a Country-level model for SDG2.2. December 2019</p>
<p>UNICEF-WHO-World Bank (2020). Technical notes from the country consultation on SDG Indicators 2.2.1 on stunting, 2.2.2a on wasting and 2.2.2b on overweight &lt;<a href="https://data.unicef.org/resources/jme-2021-country-consultations/">https://data.unicef.org/resources/jme-2021-country-consultations/</a>&gt;</p>
<p>WHO (2006). WHO Multicentre Growth Reference Study (MGRS) &lt;https://www.who.int/tools/child-growth-standards/who-multicentre-growth-reference-study&gt;</p>
<p>World Health Organization and United Nations Children&#x2019;s Fund (2019). 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&#x2019;s Fund (UNICEF), 2019. Licence: CC BY-NC-SA 3.0 IGO. &lt;<a href="https://www.who.int/nutrition/publications/anthropometry-data-quality-report">https://www.who.int/nutrition/publications/anthropometry-data-quality-report</a>&gt;</p>
<p>WHO. WHO Anthro Survey Analyser (2019). Available at <a href="https://www.who.int/tools/child-growth-standards/software">https://www.who.int/tools/child-growth-standards/software</a>. </p>
<p>Yang H and de Onis M (2008). <a href="http://www.who.int/entity/nutgrowthdb/publications/algorithms/en/index.html">Algorithms for converting estimates of child malnutrition based on the NCHS reference into estimates based on the WHO Child Growth Standards</a>. <br>BMC Pediatrics 2008, 8:19 (05 May 2008) <br>(&lt;http://www.biomedcentral.com/1471-2431/8/19).</p>
<p>World Health Organization (2008). Training Course on Child Growth Assessment. Geneva, WHO, 2008.</p>
<p>International Journal of Epidemiology 2004;33:1260-70</p>
<p>International Journal of Epidemiology 2003;32:518-26</p>
<p>http://www.biomedcentral.com/1471-2431/8/19&gt;.</p>

<p><strong>Sources of discrepancies:</strong></p>
<p>For the survey estimates included in the JME joint database of primary sources, re-analysis based on standardized methodology using the WHO Child Growth Standards as described in Recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old (<a href="https://data.unicef.org/resources/data-collection-analysis-reporting-on-anthropometric-indicators-in-children-under-5/">WHO/UNICEF 2019</a>) and WHO Anthro Survey Analyser (<a href="https://www.who.int/tools/child-growth-standards/software">WHO, 2019</a>) is applied whenever microdata are available to enhance comparability across the time series. Country teams are encouraged to use the WHO Anthro Survey Analyser (<a href="https://www.who.int/tools/child-growth-standards/software">WHO, 2019</a>) to undertake survey analysis and harmonize with the global standard analysis methods. </p>
<p>For the inclusion of survey estimates into the JME database, the inter-agency group applies a set of survey quality assessment criteria. When there is insufficient documentation, the survey is not included until information becomes available. Discrepancies between results from standard methodology and those reported may occur for various reasons, for example, the use of different standards for z-score calculations, imputation of the day of birth when missing, the use of rounded age in months, the use of different flagging systems for data exclusion. For surveys based on the previous NCHS/WHO references, and for which raw data are not available, a method for converting the z-scores to be based on the WHO Child Growth Standards is applied (<a href="http://www.biomedcentral.com/1471-2431/8/19">Yang and de Onis, 2008</a>). In addition, when surveys do not cover the age interval 0-59 months, or are only representative of the rural areas, an adjustment based on other surveys for the same country, is performed. Any adjustment or conversion is transparently stated in the annotated joint data set.</p>
<p>The JME country modelled estimates, which are based on smoothing techniques and covariates, as described elsewhere (<a href="https://pubmed.ncbi.nlm.nih.gov/30430613/">McLain et al. 2018</a>), vary from estimates from primary data sources such as household surveys, but in most cases the 95 per cent confidence bounds of the country modelled estimates for a given country in a given year fall within the 95 per cent confidence bounds of the estimate from the primary source for the corresponding country and year(s).</p>

<p><strong>Sources des divergences :</strong></p>
<p>L'approche d'analyse standard pour construire l'ensemble de données communes vise à une comparabilité maximale des estimations des pays. Pour l'inclusion des estimations de l'enquête dans l'ensemble de données des estimations conjointes de la malnutrition (JME), le groupe inter agences applique des critères d'évaluation de la qualité de l'enquête. Lorsque la documentation est insuffisante, l'enquête n'est pas incluse tant que les informations ne sont pas disponibles. Lorsque des données brutes sont disponibles et qu'une question se pose sur l'approche d'analyse, une nouvelle analyse des données est effectuée selon la méthodologie standard. Des divergences entre les résultats de l'approche standardisée et ceux qui sont déclarés peuvent se produire pour diverses raisons (par exemple, utilisation de normes différentes pour le calcul du score z, imputation du jour de naissance lorsque celui-ci est manquant, utilisation de l'âge arrondi en mois, utilisation de systèmes de marquage différents pour l'exclusion des données). Pour les enquêtes basées sur les précédentes références du « National Center for Health Statistics (NCHS) » et de l'OMS, et pour lesquelles les données brutes ne sont pas disponibles, une méthode de conversion des scores z basée sur les normes de croissance des enfants de l'OMS est appliquée (Yang et de Onis, 2008). En outre, lorsque les enquêtes ne couvrent pas l'intervalle d'âge 0-5 ans, ou sont uniquement représentatives des zones rurales, un ajustement basé sur d'autres enquêtes pour le même pays est effectué. Tout ajustement ou conversion est indiqué de manière transparente dans l'ensemble de données commun annoté.</p>

<p><strong>Sources of discrepancies:</strong></p>
<p>The standard analysis approach to construct the joint data set aims for a maximum comparability of country estimates. For the survey estimates included in the JME joint database of primary sources, re-analysis based on standardized methodology using the WHO Child Growth Standards as described in Recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old (<a href="https://data.unicef.org/resources/data-collection-analysis-reporting-on-anthropometric-indicators-in-children-under-5/">WHO/UNICEF 2019</a>) and WHO Anthro Survey Analyser (<a href="https://www.who.int/tools/child-growth-standards/software">WHO, 2019</a>) is applied whenever microdata are available to enhance comparability across the time series. Country teams are encouraged to use the WHO Anthro Survey Analyser (<a href="https://www.who.int/tools/child-growth-standards/software">WHO, 2019</a>) to undertake survey analysis and harmonize with the global standard analysis methods. </p>
<p>For the inclusion of survey estimates into the JME databaset, the inter-agency group applies a set of survey quality assessment criteria. When there is insufficient documentation, the survey is not included until information becomes available. When raw data are available, and there is a question about the analysis approach, data re-analysis is performed following the standard methodology. Discrepancies between results from standardised approach methodology and those reported may occur for various reasons, for example, the use of different standards for z-score calculations, imputation of the day of birth when missing, the use of rounded age in months, the use of different flagging systems for data exclusion. For surveys based on the previous NCHS/WHO references, and for which raw data are not available, a method for converting the z-scores to be based on the WHO Child Growth Standards is applied (<a href="http://www.biomedcentral.com/1471-2431/8/19">Yang and de Onis, 2008</a>). In addition, when surveys do not cover the age interval 0-&lt;5 year59 months, or are only representative of the rural areas, an adjustment based on other surveys for the same country, is performed. Any adjustment or conversion is transparently stated in the annotated joint data set.</p>
<p>The JME country modelled estimates, which are based on smoothing techniques and covariates, as described elsewhere (<a href="https://pubmed.ncbi.nlm.nih.gov/30430613/">McLain et al. 2018</a>), vary from estimates from primary data sources such as household surveys, but in most cases the 95 per cent confidence bounds of the country modelled estimates for a given country in a given year fall within the 95 per cent confidence bounds of the estimate from the primary source for the corresponding country and year(s).</p>

<p><strong>Data availability:</strong></p>
<p>The JME modelled country estimates from 2000 to 2022 for overweight were released for 161 countries that had at least one primary data source (e.g., from household survey) included in the 2023 JME country database.</p>
<p><strong>Time series:</strong></p>
<p>At country level, JME country modelled estimates from 2000 to the year before the JME release ) are presented for countries with at least one data point (e.g., from survey/surveillance included in the joint database of primary data sources. Survey years range from 1983 to the year before the JME release. Worldwide and regional annual estimates are available from 2000 to the year before the JME release. </p>
<p><strong>Disaggregation:</strong></p>
<p>Country, regional and worldwide JME estimates refer to the age group of children under 5 years, sexes combined. Disaggregations are currently not available for the JME modelled estimates. However, a disaggregated dataset of national primary sources with sub national and stratified estimates (e.g., sex, age groups, wealth, mothers&apos; education, residence) is available.</p>

<p><strong>Disponibilité des données :</strong></p>
<p>Plus de 150 pays. </p>
<p><strong>Séries chronologiques :</strong></p>
<p>Au niveau national, des données sont fournies pour les années où les enquêtes sont incluses dans l’ensemble de données conjoint. Les années d’enquête vont de 1983 à 2016. Pour les niveaux mondial et régional, les estimations de 1990 à la dernière année disponible lors de la diffusion chaque année (c’est-à-dire que dans l’édition de septembre 2016 des estimations conjointes de la malnutrition (JME), la dernière estimation disponible était pour 2015). </p>
<p><strong>Désagrégation :</strong></p>
<p>Les estimations mondiales et régionales se réfèrent au groupe d’âge des enfants de moins de 5 ans, tous sexes confondus. Des données ventilées par pays sont disponibles dans la majorité des enquêtes auprès des ménages et le groupe UNICEF - OMS - Banque mondiale élargit l’ensemble de données conjoint pour inclure des estimations infranationales et stratifiées (p. ex., sexe, groupes d’âge, richesse, éducation des mères, résidence) en 2017.</p>

<p><strong>Data availability:</strong></p>
<p>More than 150 countries.</p>
<p><strong>Time series:</strong></p>
<p>At country level, dataThe JME modelled country estimates from 2000 to 2022 for overweight were released for 161 countries that had at least one primary data source (e.g., from household survey) included in the 2023 JME country database.</p>
<p><strong>Time series:</strong></p>
<p>At country level, JME country modelled estimates from 2000 to the year before the JME release ) are providesented for the years where surveys are included in the joint datasetcountries with at least one data point (e.g., from survey/surveillance included in the joint database of primary data sources. Survey years range from 1983 to 2016. Fthe year before the globalJME release. Worldwide and regional levels,annual estimates for the years 1990 to the latest available estimate upon release each year (i.e. in Sept 2016 edition of the Joint Malnutrition Estimates the latest available estimate was for 2015)are available from 2000 to the year before the JME release. </p>
<p><strong>Disaggregation:</strong></p>
<p>Global and regionalCountry, regional and worldwide JME estimates refer to the age group of children under 5 years, sexes combined. Disaggregated country data areions are currently not available in a majority of household surveys and UNICEF - WHO- The World Bank Group are expanding the jointfor the JME modelled estimates. However, a disaggregated data set to includeof national primary sources with sub national and stratified estimates (e.g., sex, age groups, wealth, mothers&apos; education, residence) in 2017s available.</p>

<p>Data consistency and quality checks described above are conducted for each potential primary data source (e.g., household survey) before inclusion in the JME country database of primary sources that are used to generate the JME modelled estimates. Cross-validation exercises are performed for the modelled estimates to ensure the method generates estimates that are aligned to national data points. Country consultations with SDG 2.2 focal points an held every other year also provide opportunity to ensure the estimates include all recent and relevant country data. </p>

<p>The quality criteria established in the 2019 UNICEF/WHO guidance (<a href="https://data.unicef.org/resources/data-collection-analysis-reporting-on-anthropometric-indicators-in-children-under-5/">WHO/UNICEF, 2019</a>) were used to update the JME primary data source review form . The JME review form is used to abstract key information including methodological details (e.g., sampling procedures, description of anthropometrical equipment), data quality outputs (e.g., response rates, weight and height distributions, percentage of cases that were flagged as having implausible anthropometry outcomes according to the WHO Child Growth Standards) and the malnutrition prevalence estimates from each primary data source (e.g., household survey) under review. One JME working group member fills in the review form for each data source and when information is missing or further details are required, the country teams are contacted. Once all information is available and the JME primary data source review form is completed, each data source is reviewed by the three agencies (UNICEF, WHO, WB) which form the JME working group. This allows for a thorough and efficient standard joint review of each data source by the three agencies prior to inclusion in the JME country database of primary sources (e.g., household surveys) that are used to generate the JME country modelled estimates. </p>

<p>The JME working group, which was formed in 2011 with representatives from UNICEF, WHO and the World Bank, is responsible for management of the processes used to develop regular updates of the JME estimates. This includes the regular update of the country database of surveys used to generate the JME country modelled estimates, for which regular communication with regional and country teams allows the JME working group to secure microdata for re-analysis according to the standard method. The JME working group also continuously review methods and considers and tests different methodologies to improve the estimates as necessary. Additionally, a Technical Expert Advisory Group on Nutrition Monitoring (TEAM), jointly established by UNICEF and WHO, provides advice on nutrition monitoring methods and processes, including on the JME.</p>