nutrition community urgently needs to develop diagnostic tools to assess the malnutrition landscape in order to help sequence, prioritize, and strategize about nutrition-relevant action at the national level. Understanding associations and implications for action is also important because one form of malnutrition can drive the manifestation of other forms of malnutrition. For example, wasting is often associated with stunting and can have similar causes (Bergeron and Castleman 2012), and undernutri- tion in childhood is associated with overweight and obesity in adulthood (Adair et al. 2013).
Finally, it is important to note that high-income countries tend not to appear in these tables. That is because they do not report some of the data in ways that are compatible with inclusion in international databases. This is a major account- ability gap. As Panel 4.1 shows, the United States and United Kingdom face serious malnutrition issues related to overweight and obesity, and their citizens, like the citizens of any of the 193 UN member states, need to be able to hold their governments accountable for efforts to improve the situation.
DISTRIBUTION OF MALNUTRITION WITHIN COUNTRIES
In every country, some regions are forging ahead in terms of im- proving nutrition status while others are lagging behind. One re- sponse to this variation is to decentralize nutrition improvement efforts and develop subnational strategies. Decentralization will lead to a greater need for subnational nutrition analyses and data collection. This information can be disaggregated in many ways, including by administrative or geographic unit or accord- ing to equity-based categories.
Administrative disaggregation
Many countries, such as Indonesia and Kenya, are decentralizing nutrition plans and intervention delivery. This poses a challenge for accountability. Often responsibility and accountability are decentralized because local factors are typically important drivers of nutritional outcomes. But for local governments to be accountable, they must have adequate authority, resources, and human and institutional capacity. Panel 4.2 highlights the importance of regional drivers of nutrition status in Indonesia.
In India, a partnership is using nutrition profiles for districts in three Indian states to begin conversations about nutrition,
TABLE 4.2 COUNTRIES WITH OVERLAPPING THINNESS IN WOMEN OF REPRODUCTIVE AGE, SHORT STATURE IN WOMEN OF REPRODUCTIVE AGE, AND ADULT FEMALE OVERWEIGHT
Overlap/indicator group WRA short stature only WRA thinness only
Adult female overweight only
Number of countries 5 3
25
Total population (millions) 232 110 610
Countries
Cambodia, Congo, Nepal, Pakistan, Sierra Leone Chad, Eritrea, Ethiopia
Albania, Armenia, Azerbaijan, Brazil, Cameroon, Colombia, Dominican Republic, Egypt, Gabon, Ghana, Jordan, Kazakhstan, Kyrgyzstan, Lesotho, Mauritania, Morocco, Namibia, Republic of Moldova, Sao Tome and Principe, Senegal, Swaziland, Turkey, Turkmenistan, Uzbekistan, Yemen, Zimbabwe
WRA short stature and WRA thinness only
WRA short stature and adult female overweight only
Adult female overweight and WRA thinness only
WRA short stature, WRA thinness, and adult female overweight
Below cutoff for all three indicators
Total with data
Missing data for at least one indicator
Total 4 7 0 1 22 67 126 193
Source: Indicator data are from Demographic and Health Survey Statcompiler (2014; data from 1994–2013) and WHO (2014g; data from 2008). Population data are from United Nations (2013b).
Note: WRA = women of reproductive age. Thinness is defined as a body mass index (BMI) < 18.5; short stature is defined as a height < 145 centimeters; and over- weight is defined as a BMI ≥ 25. The cutoffs for placing countries in each indicator category are as follows: WRA thinness ≥ 20 percent, WRA short stature ≥ 4.8 percent, and adult female overweight ≥ 35 percent. A cutoff of 20 percent for WRA thinness is used because WHO has classified this level as a high/very high prevalence indic- ative of a serious/very serious situation (WHO 2010a). A cutoff of 4.8 percent for WRA short stature is used because no universal cutoff exists; instead the 75th percen- tile is used as cutoff. A cutoff of 35 percent for adult female overweight is used because overweight ≥ 35 percent is higher than the global average (WHO 2014b; FAO 2013b).
1,415 71 0 24 562 3,025 Yemen
Benin, Burkina Faso, Burundi, Central African Republic, Comoros, Côte d’Ivoire, Demo- cratic Republic of the Congo, Guinea, Haiti, Kenya, Liberia, Malawi, Mali, Mozambique, Niger, Nigeria, Rwanda, Tajikistan, Togo, Uganda, United Republic of Tanzania, Zambia
India, Bangladesh, Madagascar, Timor-Leste Bolivia, Guatemala, Guyana, Honduras, Maldives, Nicaragua, Peru
24
GLOBAL NUTRITION REPORT 2014
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