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

<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>

<h1>Referencias</h1>
<h2>URL:</h2>
<p><a href="http://data.unicef.org/nutrition/malnutrition.html">http://data.unicef.org/nutrition/malnutrition.html</a></p>
<p><a href="http://www.who.int/nutgrowthdb/estimates2014/en/">http://www.who.int/nutgrowthdb/estimates2014/en/</a></p>
<p><a href="http://datatopics.worldbank.org/child-malnutrition">http://datatopics.worldbank.org/child-malnutrition</a></p>
<h2>Referencias:</h2>
<p>Fondo de las Naciones Unidas para la Infancia, Organización Mundial de la Salud y Banco Mundial (2012). Estimaciones conjuntas de malnutrición infantil de UNICEF-OMS-Banco Mundial. (UNICEF, Nueva York; OMS, Ginebra; Banco Mundial, Washington, DC; 2012). </p>
<p>de Onis M, Bl&#xF6;ssner M, Borghi E, et al. (2004), Metodología para estimar las tendencias regionales y mundiales de la malnutrición infantil. <em>Int J Epidemiol</em>, 33(6):1260-70.</p>
<p>Yang H y de Onis M. <a href="http://www.who.int/entity/nutgrowthdb/publications/algorithms/en/index.html">Algoritmos para convertir las estimaciones de malnutrición infantil basadas en la referencia del NCHS en estimaciones basadas en el Patrón de Crecimiento Infantil de la OMS</a> BMC <em>Pediatrics</em> 2008, 8:19 (05 de mayo de 2008) (<a href="http://www.biomedcentral.com/1471-2431/8/19"> http://www.biomedcentral.com/1471-2431/8/19</a>).</p>
<p>Organización Mundial de la Salud (2008). <em>Curso de formación sobre la evaluación del crecimiento infantil</em>. Ginebra, OMS, 2008.</p>
<p><em>Revista Internacional de Epidemiología</em> 2004;33:1260-70</p>
<p><em>Revista Internacional de Epidemiología</em> 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>

<h2>Fuentes de discrepancia:</h2>
<p>El enfoque de análisis estándar para construir el conjunto de datos tiene como objetivo la máxima comparabilidad de las estimaciones de los países. Para la inclusión de las estimaciones de las encuestas en el conjunto de datos de las estimaciones conjuntas de la malnutrición infantil, el grupo interinstitucional aplica criterios de evaluación de la calidad de las encuestas. Cuando la documentación es insuficiente, la encuesta no se incluye hasta que la información esté disponible. Cuando se dispone de datos brutos y se cuestiona el enfoque del análisis, se realiza un nuevo análisis de los datos siguiendo la metodología estándar. Las discrepancias entre los resultados del enfoque normalizado y los comunicados pueden producirse por diversas razones, por ejemplo, el uso de diferentes normas para los cálculos de las puntuaciones z (z-scores), la imputación del día de nacimiento cuando falta, el uso de la edad redondeada en meses, el uso de diferentes sistemas de marcado para la exclusión de datos. En el caso de las encuestas basadas en las referencias anteriores del NCHS/OMS, y para las que no se dispone de datos brutos, se aplica un método de conversión de las puntuaciones z para que se basen en los patrones de crecimiento infantil de la OMS (Yang y de Onis, 2008). Además, cuando las encuestas no cubren el intervalo de edad 0-&lt;5 años, o sólo son representativas de las zonas rurales, se realiza un ajuste basado en otras encuestas para el mismo país. Cualquier ajuste o conversión se indica de forma transparente en el conjunto de datos.</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>

<h1>Disponibilidad de datos</h1>
<h2>Descripción:</h2>
<p>Más de 150 países </p>
<h2>Series temporales:</h2>
<p>A nivel de país, se proporcionan datos para los años en los que las encuestas están incluidas en el conjunto de datos. Los años de las encuestas van de 1983 a 2016. Para los niveles mundial y regional, las estimaciones correspondientes a los años 1990 a la última estimación disponible en el momento de la publicación de cada año (es decir, en la edición de septiembre de 2016 de las Estimaciones Conjuntas de la Malnutrición la última estimación disponible era la de 2015). </p>
<h2>Desagregación:</h2>
<p>Las estimaciones mundiales y regionales se refieren al grupo de edad de los niños menores de 5 años, combinando los sexos. Los datos desagregados de los países están disponibles en la mayoría de las encuestas de hogares y UNICEF - OMS - Grupo del Banco Mundial están ampliando el conjunto de datos conjuntos para incluir estimaciones subnacionales y estratificadas (por ejemplo, sexo, grupos de edad, riqueza, educación de las madres, residencia) 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>