levels and trends in child malnutrition...infrequently and measure malnutrition at one point in...
TRANSCRIPT
Levels and trends in child malnutritionUNICEF – WHO – World Bank Group joint child malnutrition estimatesKey findings of the 2015 edition
The ultimate goal: for all children to be free of malnutrition in all its forms.
Stunting rates are dropping but 159 million children around the world are still affected.
There are 41 million overweight children in the world; about 10 million more than there were 2 decades ago.
Wasting still threatens the lives of 50 million children across the globe.
The data in this 2015 edition supersede all historical data previously published by UNICEF, WHO and World Bank Group.
© UNICEF/GHAA2015-01436/Quarmyne
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Global overview
Stunting
Overweight
Wasting
In 2014, there were 667 million children under 5 in the world. An estimated:
The global trend in overweight prevalence and numbers of children affected is rising.
In 2014, the global wasting rate was 7.5 per cent.
...but not fast enough.
Between 1990 and 2014, stunting prevalence declined from 39.6 per cent to 23.8 per cent...
Overweight prevalence has gone up slightly between 1990 and 2014, from 4.8 per cent to 6.1 per cent…
Nearly a third of all wasted children were severely wasted, with a global prevalence in 2014 of 2.4 per cent.
159 millionwere stunted
41 million were overweight
50 million were wasted
(each pair of children represents 20 million children)
Approximately 1 out of every 13 children in the world was wasted in 2014.
1990
1990
2014
2014
2014
…and numbers affected declined from 255 million to 159 million.
…and numbers affected have risen from 31 million to 41 million.
Globally, 50 million children under 5 were wasted, of which 16 million were severely wasted in 2014.
Notes on the updated joint malnutrition estimates
The global trend in stunting prevalence and numbers of children affected is decreasing...
- 96M
+ 10M
50M
20M
In September 2015, UNICEF, WHO and World Bank Group released updated joint child malnutrition estimates for the 1990 to 2014 period, which represent the most recent global and regional figures after adding 62 new surveys from 57 countries to the joint dataset. This key findings report summarizes the new numbers, main messages and identifies some minor changes in methodology.
Additional materials include: (i) the latest country-level joint malnutrition dataset; and, (ii) interactive dashboards, which allow users to visualize and export the global and regional estimates.
UNICEF<uni.cf/jmedashboard2015>
WHO <www.who.int/nutgrowthdb/estimates>
World Bank Group <data.worldbank.org/child-malnutrition>
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Regional overview – prevalence
Unequal progress in stunting reduction since 1990
In 2014, one subregion was above the public health emergency line for wastingPercentage of children under 5 wasted, by United Nations subregion, 2014
...progress among subregions has been uneven.While Asia as a
whole has cut stunting by almost half...
-24%Africa
Eastern Asia
Southern Asia
-47%Asia
Not even one subregion in Africa has an
acceptable level of wasting.
Three subregions are approaching
the public health emergency line.
*Asia (excluding Japan); **Oceania (excluding Australia and New Zealand) 1990 and 1995 estimates had consecutive low population coverage.Source: UNICEF, WHO, World Bank Group joint malnutrition estimates, 2015 edition.
*Eastern Asia, excluding Japan**Oceania, excluding Australia and New ZealandSource: UNICEF, WHO, World Bank Group joint malnutrition estimates, 2015 edition.
This map is stylized and not to scale. It does not reflect a position by UNICEF, WHO or World Bank Group on the legal status of any country or territory or the delimitation of any frontiers.
Acceptable< 5%
Poor5 - < 10%
Serious10 - < 15%
Public healthemergencyrange
Critical≥ 15%
No data
Forms of malnutrition* highlighted in this key findings report
*Note it is possible for a child to show combinations of malnutrition, such as be stunted and overweight or stunted and wasted.
6.77.9
7.5
9.0
3.1
1.4
3.9
4.01.1
5.4
9.39.0
2.1
14.2
- 82%
42.3
32.0
1990
1995
2000
2005
2010
2014
4.9 5.7
0
10
20
30
40
50
60
70
Africa
1990
1995
2000
2005
2010
2014
1990
1995
2000
2005
2010
2014
1990
1995
2000
2005
2010
2014
47.6
25.1
4.0 5.4
Asia
35.9 38.1
3.48.9
Oceania*
24.5
11.7
6.6
7.2
Latin America and CaribbeanAsia*
Caribbean
WesternAfrica
MiddleAfrica
SouthernAfrica
EasternAfrica
WesternAsia
SouthernAsia
EasternAsia*
SoutheasternAsia
CentralAsia
Oceania
Northern Africa
CentralAmerica
SouthAmerica
Africa Oceania** Latin Americaand Caribbean
Africa has seen slow progress in reducing stuntingPercentage of children under 5 stunted and percentage of children under 5 overweight, by United Nations region, 1990 – 2014
stuntingoverweight95% confidence interval
2xreduction
- 41%
Overweight refers to a child who is too heavy for his/her height. This form of malnutrition results from expending too few calories for the amount consumed, and increases the risk of noncommunicable disease later in life.
per
cent
Wasting refers to a child who is too thin for his/her height. Wasting is the result of sudden or acute malnutrition, where the child is not getting enough calories from food and faces an immediate risk of death.
Stunting refers to a child who is too short for his/her age. Stunting is the failure to grow both physically and cognitively and is the result of chronic or recurrent malnutrition. Its effects often last a lifetime.
4
Oceania0.1 M
Regional overview – numbers affected
Strengths and weaknesses of malnutrition data
In Africa, the number of stunted children is risingNumber of children under 5 stunted, by United Nations region, 1990 and 2014
The number of overweight children is on the rise in all regionsNumber of children under 5 overweight, by United Nations region, 1990 and 2014
The majority of children under 5 suffering from wasting live in Asia(each child silhouette represents 1 million children)
In 2014, almost half of all overweight children under 5 lived in Asia and one quarter lived in Africa.
In 2014, almost all wasted children under 5 lived in Asia and Africa.
The number of overweight children under 5 in Africa has nearly doubled since 1990.
Southern Asia is home to more than half of all wasted children under 5
globally.
Asia 48%
Asia 68%
Africal.25%
Africal.28%
*Asia (excluding Japan); **Oceania (excluding Australia and New Zealand) 1990 estimate had consecutive low population coverage. Source: UNICEF, WHO, World Bank Group joint malnutrition estimates 2015 edition.
In 2014, more than half of all stunted children under 5 lived in Asia and more than one third lived in Africa.
Three out of five sub-regions in Africa, Eastern Africa, Middle Africa and Western Africa, have rising numbers of stunted children under 5.
Asia 57% Africal.37%
Asia34.3 M
Africa13.9 M
Latin America and Caribbean 0.7 M
190 4791 5814
6 0.3 0.5
1990 2014
0
50
100
150
200
-52%
+23%
-57% +67%
16.0
+22%
0.0319.6 10.3 3.9 0.120
5
10
15
20
25 1990 2014
nearly 3x
+5%
increase+91%
Trends are not informative for wasting and severe wasting given that these are acute conditions, which can change rapidly. Thus only 2014 global and regional estimates are presented.
The underlying data for global and regional estimates are from country-level household surveys. Such country data are collected infrequently and measure malnutrition at one point in time. This makes it difficult to capture the rapid fluctuations of wasting and severe wasting over time. For programme purposes, incidence data (i.e., the number of new cases that occur during an entire calendar year) would be ideal, however, these currently do not exist.
Prevalence estimates for stunting and overweight are relatively robust. Hence it is possible to generate reliable time trends.
5
Share of stunted children under 5 in 2014
Note: the numbers do not add up to 100 per cent; the residual is for high-income countries.
Share of under-5 population in 2014
Country income groupings overview
Low-income countries have made the least progress towards stunting reductions since 1990Percentage of children under 5 stunted and percentage of children under 5 overweight, by country income classification, 1990 – 2014
Overweight numbers have doubled in lower-middle-income countries since 1990
Low-income and lower-middle-income countries now account for almost all stunted children worldwide
Lower-income countries bear a disproportionate share of stunted children relative to the total population distribution
Low-income Lower-middle- income
Upper-middle-income55.3
37.6
3.1 3.4
1990
1995
2000
2005
2010
2014
0
10
20
30
40
50
60
70
1990
1995
2000
2005
2010
2014
1990
1995
2000
2005
2010
2014
54.6
33.5
2.7 4.9
32.6
7.5
6.8 6.8
stuntingoverweight95% confidence interval
Unequal progress in stunting reduction since 1990
-32% -77%
Only a 32% decrease in low-income countries...
... and a 77% decrease in upper-middle-income countries.Source: UNICEF, WHO, World Bank Group joint malnutrition estimates, 2015 edition.
The number of overweight children in lower-middle-income countries has more than doubled since 1990, from 7.5 million to 15.5 million.
The share of all stunted children that live in low- income and lower-middle-income countries has shifted from 7 in 10 to 9 in 10 between 1990 and 2014.
1990
1990
2014
2014
2xas high
Low-income countries only accounted for 15 per cent of the global under-5 population in 2014, but nearly one quarter of all stunted children live in these countries.
In 2014, one quarter of all children under 5 lived in upper-middle-income countries, yet these countries only accounted for 8 per cent of all stunted children globally.
Less than half of all children under 5 lived in lower-middle-income countries in 2014, yet these countries accounted for two thirds of all stunted children globally.
15%
47% 66%
26%24%
8%
per
cent
6
The analysis methods have remained unchanged from the 2012 report, except for some minor refinements detailed below:
1. Year assigned to each surveyWhen 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 2009 and 28 February 2010, the year 2009 would be assigned, since the majority of data collection took place in that year (i.e., four months in 2009 versus two months in 2010). This method has been used since the 2013 edition (prior to that, the latter year was used by default – e.g., 2010 in the example above).
2. Final reports onlyAs of the 2014 edition, the dataset used to generate the global and regional estimates is based only on final survey results. Preliminary survey results are no longer included in the dataset due to situations where they had been cancelled or significantly changed before release.
3. Updated data sourcesi. The updated joint dataset which includes:
62 new)
than 90 per cent of all children under 5 globally (population coverage varies by regions and periods)).
ii. The under 5 population estimates The United Nations World Population Prospects, 2015 Revision, were used as weighting factors for each country survey to derive the regional and global prevalence estimates and calculate the numbers affected.
iii. Regional and country income classifications as per July 2015
4. Footnotes on population coverageAs in the 2014 edition, a separate exercise was conducted to assess population coverage. This was important in order to alert the reader, via footnotes, to instances where the data should be interpreted with caution due to low population coverage (defined as less than 50 per cent). A conservative method was applied looking at available data within mutually exclusive five-year periods around the projected years. Population coverage was calculated as:
the sum of country five-year average populations (for which surveys are available in the dataset)the total of country five-year average population for all countries in the region
Notes on methodology
SEPT
2009
2010
JAN
FINAL V 0.1
OCT
FEB
NOV DEC
Russian Federation
Afghanistan
Colombia
Albania
Algeria
Angola
Argentina
ArmeniaAustralia
Azerbaijan
Bahrain
Bangladesh
Barbados
Belarus
Belize
Benin
Bhutan
Bolivia (Plurinational State of)
Bosnia and Herzegovina
Botswana
Brazil
Brunei Darussalam
Bulgaria
Burkina Faso
Burundi
Cabo Verde
Cambodia
Cameroon
Canada
Central African Republic
Chad Chile
China
Comoros Congo
Costa Rica
Côte d'Ivoire
Cuba
Czech Republic
Democratic People's Republic of Korea
Democratic Republic of the Congo
Djibouti
Dominican RepublicEcuador
EgyptEl Salvador
Equatorial GuineaEritreaEthiopia
Fiji
Gabon
GambiaGeorgia
Germany
Ghana
NigeriaIndia
United States
Uruguay
Turkmenistan
Zimbabwe
Zambia
Yemen
Viet Nam
Venezuela (Bolivarian Republic of)
Vanuatu
Uzbekistan
United Republic of Tanzania
Ukraine
Uganda
TuvaluTurkey
Tunisia
Trinidad and Tobago
Tonga
Togo
Timor-Leste
The former Yugoslav Republic of Macedonia
ThailandTajikistan
Syrian Arab Republic
Swaziland
Suriname
Sudan
State of Palestine
Sri Lanka
South Sudan
South Africa
SomaliaSolomon Islands
Singapore
Sierra Leone
Seychelles
Serbia
SenegalSaudi Arabia
Sao Tome and Principe
Samoa
Saint Lucia
Rwanda
Romania
Republic of Moldova
Republic of Korea
Qatar
Philippines
Peru
Paraguay
Papua New Guinea
Panama
Pakistan
Guatemala
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Indonesia
Iran (Islamic Republic of)
Iraq
Jamaica
Japan
Jordan
Kazakhstan
Kenya
Kiribati
Kuwait
Kyrgyzstan
Lao People's Democratic Republic
Lebanon
LesothoLiberia
Libya
Madagascar
Malawi
Malaysia
Maldives
MaliMauritania
Mauritius
Mexico
Mongolia
Montenegro
Morocco Mozambique
Myanmar
Namibia
NauruNepal
Nicaragua
Niger
Oman
Andorra
Antigua and Barbuda
Austria
Bahamas
Belgium
Cook Islands
Croatia
Cyprus
Denmark
Dominica
Estonia
Finland
France
GreeceGrenada
Holy See
Hungary
Iceland
Ireland
Israel
Italy
Latvia
Liechtenstein
Lithuania
Luxembourg
Marshall Islands
Micronesia (Federated States of)
MonacoNetherlands
New Zealand
Niue
Norway
Palau
Poland
PortugalSaint Kitts and Nevis
Saint Vincent and the Grenadines
San Marino
Slovakia
Slovenia
Spain
Sweden
Switzerland
United Arab Emirates
United Kingdom
countries with data countries without data
Email: [email protected]/nutrition
Email: [email protected] data.unicef.org
This brochure was prepared by the Data and Analytics Section of the Division of Data, Research and Policy, UNICEF New York, the Department of Nutrition for Health and Development, WHO Geneva and the Development Data Group, World Bank Group Washington DC. September 2015.
Email: [email protected]