Malnutrition

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Indicators for the Global Monitoring Framework on Maternal, Infant and Young Child Nutrition
With the timer eating away vital seconds, you'll need to guess where different world foods come from, rank countries by rates of undernourishment, and negotiate a tricky picture round. We also provide live chat support. Country-level progress in reducing undernutrition prevalence is evaluated by calculating the average annual rate of reduction AARR and comparing this to the AARR needed in order to achieve targets. Children from the poorest 20 per cent of the population have stunting rates that are double the rate in comparison with the richest quintile. Blencowe H et al.

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Global Nutrition Monitoring Framework Country Profile: Afghanistan

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Application Blocking Remotely Block Any App Stop usage of all or some apps, including built in apps and downloaded apps. Start Monitoring in Three Easy Steps! Why should I choose Mobile Spy over the rest? The percentage change since is only shown where the change is significantly different. Worldwide in , 38 million, or 5. Eastern Europe and Central Asia had the highest overweight prevalence in with The lowest overweight prevalence in was seen in South Asia, at 3.

East Asia and the Pacific had the highest number of overweight children in with 8. Overall the two Asian regions East Asia and the Pacific and South Asia account for more than one out of every three overweight children in the world. Eastern Europe and Central Asia as well as North America are the only regions that have seen a statistically significant increase in number of overweight children between and In globally, 51 million children under five were wasted of which 16 million were severely wasted.

This translates into a prevalence of 7. In , more than half of all wasted children lived in South Asia and about one quarter in sub-Saharan Africa, with similar proportions for severely wasted children.

Under-five wasting and severe wasting are highly sensitive to change. Thus, estimates for these indicators are only reported for current levels In almost all countries with available data, stunting rates are higher among boys than girls.

While analyses to determine underlying causes for this phenomenon are underway, an initial review of the literature suggests that the higher risk for preterm birth among boys which is inextricably linked with lower birth weight is a potential reason for this sex-based disparity in stunting.

Analysis is based on a subset of 92 countries with recent data by wealth quintile groupings covering 69 per cent of the global population. Children from the poorest 20 per cent of the population have stunting rates that are double the rate in comparison with the richest quintile.

In South Asia, the absolute disparities between the richest and poorest children in regard to stunting are greater than in any other region.

While the overall rates are lower, the relative disparities are greatest in Latin America and the Caribbean where the rate among the poorest is more than 4 times higher than among the richest. An analysis of 54 countries with comparable trend data between around and around shows that gaps between the poorest 20 per cent and richest 20 per cent of children under five have closed by at least 20 per cent in the majority of upper-middle-income countries.

However, in almost all low income countries, this gap has either remained the same or increased. Blencowe H et al. Preterm birth—associated neurodevelopmental impairment estimates at regional and global levels for Pediatric Research Volume No s1, December Please note that some children can suffer from more than one form of malnutrition — such as stunting and overweight or stunting and wasting.

There are currently no joint global or regional estimates for these combined conditions, but UNICEF has a country-level dataset with country level estimates, where re-analysis was possible. Prevalence of stunting, wasting and overweight among children under 5 is estimated by comparing actual measurements to an international standard reference population. The new standards are the result of an intensive study project involving more than 8, children from Brazil, Ghana, India, Norway, Oman and the United States.

Overcoming the technical and biological drawbacks of the old reference population, the new standards confirm that children born anywhere in the world and given the optimum start in life have the potential to reach the same range of height and weight. The new standards should be used in future assessments of child nutritional status.

It should be noted that because of the differences between the old reference population and the new standards, prevalence estimates of child anthropometry indicators based on these two references are not readily comparable. It is essential that all estimates are based on the same reference population preferably the new standards when conducting trend analyses. Before conducting trend analyses of child nutritional status, it is important to ensure that estimates from various data sources are comparable over time.

For example, household surveys in some countries in the early s only collected child anthropometry information among children up to 47 months of age — or even up to only 35 months of age. Prevalence estimates based on such data only referred to children under 4 or under 3 years of age and are not comparable to prevalence estimates based on data collected from children up to 59 months of age.

Some age adjustment needs to be applied to make these estimates based on non-standard age groups comparable to those based on the standard age range. For more information about age adjustment, please click here to read a technical note. In addition, prevalence estimates need to be calculated according to the same reference population.

For more information about the difference between the two references and its implications, please click here to read a series of questions and answers.

When data collection begins in one calendar year and continues into the next, the survey year assigned is the one in which most of the fieldwork took place. For example, if a survey was conducted between 1 September and 28 February , the year would be assigned, since the majority of data collection took place in that year i.

This method has been used since the edition prior to that, the latter year was used by default — e. As of the edition, the country-level dataset used to generate the global and regional joint malnutrition estimates is based only on final survey results. Preliminary survey results are no longer included in the dataset since the data are sometimes retracted or change significantly when the final version is released.

Country-level progress in reducing undernutrition prevalence is evaluated by calculating the average annual rate of reduction AARR and comparing this to the AARR needed in order to achieve targets. Estimation of regional and global trends is based on a multilevel modelling method see de Onis et al.

For the most recent trend analysis, a total of data points from countries over the period to were included in the model. This set of trend data points was jointly reviewed by UNICEF, WHO and the World Bank Group in January to ensure that it is nationally representative of under-five children, processed using standard algorithms and comparable vertically and horizontally. Global and regional trend modelling and graphing were carried out using SAS the country-level data set and analysis code are available on request.

Each circle represents a prevalence estimate from a country for one survey. The size of the circle is proportional to the under-five population in that country for the average of all survey years. The solid line indicates the regional trend as modelled on all the available data points in the region.

Explanation as to why trends are shown for stunting and overweight but only most current estimate for wasting and severe wasting: Prevalence estimates for stunting and overweight are relatively stable over the course of a calendar year. It is therefore possible to track global and regional changes in these two conditions over time. Wasting and severe wasting are acute conditions that can change frequently and rapidly over the course of a calendar year. This makes it difficult to generate reliable trends over time with the input data available, and as such, this report provides only the most recent global and regional estimates for the JME edition.

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