NOTES CHAPTER 1


1 The World Health Organization estimates that at least a third of the world’s population is affected by micronutrient malnutrition (Allen et al. 2006) and that in 2008 more than 1.4 billion adults over the age of 20 were overweight (WHO 2014b).


2 Nutritional needs change over the life course, and adequate nu- trition early in life—particularly during the 1,000 days between a woman’s pregnancy and a child’s second birthday—has enormous benefits throughout the life cycle and across generations.


3 The scope for progress in nutrition outcomes will depend on ex- ternal factors such as climate, conflict, trade, and financial shocks; political opportunities generated by changes in leadership or crisis; and the capacity of different actors to deliver nutrition-relevant ac- tions. Data can play a vital role in building commitment and guiding action, but it is only one of the factors at play.


4 For more information, see http://globalnutritionreport.org /governance/concept-note/.


5 The main criterion for selecting indicators was evidence of relevance in improving nutrition outcomes. Many other indicators were con- sidered but not included because there was little evidence that they mattered for nutrition outcomes or they were not available for more than a handful of countries. The nutrition country profile document on the Global Nutrition Report website (www.globalnutrition report.org) provides a rationale for each indicator included and for indicators considered but not included. Appendix 1 describes how to use the nutrition country profiles as a diagnostic tool, and Appendix 6 summarizes the indicators by category. Technical Note 1 (available at www.globalnutritionreport.org) provides definitions and full data sources for all 84 indicators.


6 In addition to the report, key data can be found on the Global Nutrition Report website (www.globalnutritionreport.org), includ- ing nutrition country profiles, more in-depth panels and additional panels beyond those presented in the report, detailed Nutrition for Growth tracking tables, and relevant blogs and news pieces.


Panel 1.1 1 These concepts are based on Ruel and Alderman (2013), Gillespie et al. (2013), and Haddad and Isenman (2014).


CHAPTER 2 1 In fact they may be more competitive because they exclude several benefit categories that these health sector studies included: (1) the social value of human life, (2) morbidity averted, and (3) changes in the dependency ratio due to subsequent fertility declines resulting from improved child survival.


2 The rate of progress required for countries to meet targets is expressed by WHO as the annual average rate of reduction (AARR) or annual average rate of increase (AARI). They can be applied to prevalence rates or numbers of individuals. For example, the AARR for a change from a 40 percent stunting rate in 2005 (P1) to a 30 percent rate in 2012 (P2), a seven-year time frame, is ([7√(P2/P1)] - 1) * 100 = an AARI of −4.026 percent or an AARR of 4.026 percent. AARI is analogous to a compound rate of interest that generates P2 after being applied to P1 over a period of, in this case, seven years.


For more details, see http://www.childinfo.org/files/Technical_Note_ AARR.pdf.


3 For example, the WHA goal of reducing the number of stunted children under the age of five from 162 million in 2012 to 102.5 million in 2025 translates into an average annual rate of reduction (AARR) of 3.9 percent (de Onis et al. 2013). But the new data on stunting in India may generate an opportunity for more ambitious steps. If the number of stunted children globally, say, is now actually about 150 million (not 162 million as in Table 2.3) because of the new India results, then an AARR of 3.9 percent from 2013 to 2025 would reduce the number of stunted children to about 93 million and to 76 million by 2030. Moreover, as prevalence rates decline, it becomes mathematically easier to attain a given AARR, suggesting that we should increase our AARR ambitions as progress is made in stunting rates. A modest increase in the target AARR to 4.2 percent, applied from 2013 to 2030 from a base of 150 million stunted children would make the 2030 target 61 million. We do not suggest this as a 2030 SDG target for stunting. What we do suggest is that it is time to reassess our aspirations for nutritional status improve- ments toward 2030 in the light of new data and evidence.


Panel 2.2 1 Anthropometric measurements were made for 90,667 children younger than five years old. Inquiries on the methodological details can be directed to UNICEF’s India office.


Panel 2.3 1 Haddad et al. (2014) used a review of existing studies and reports, a comparison of 2005–2006 and 2012 survey data, and a set of 28 stakeholder interviews in four districts.


Panel 2.4 1 Using a multiyear sample covering 1970 to 2012 and 116 low- and middle-income developing countries (accounting for 96 percent of the developing world’s population), we generated panel regression estimates for the associations between stunting prevalence and the six underlying determinants of stunting. The regression model (six proxy underlying determinants, country dummy variables, and time-period dummy variables) predicted much of the variation in stunting and was stable over time (pre- and post-2000).


2 For access to improved water source, Brazil had a level of 95 percent in 2006; Vietnam had access to improved sanitation facilities of 76 percent in 2011 and Sri Lanka had 89 percent in 2006. For female secondary school enrollment, South Africa posted a rate of 95 percent in 2008. For the ratio of female to male life expectan- cy, Indonesia had 1.06 in 2004, Honduras had 1.07 in 2005, and the Central African Republic had 1.08 in 2010. For dietary energy supply, Ghana had 2,934 in 2011. Finally, for the share of dietary energy supply from nonstaples, Guatemala had 49 percent in 2008, Brazil had 64 percent in 2006, Thailand had 50 percent in 2005, and Swaziland had 45 percent in 2005.


CHAPTER 3 1 The rationale for and formulation of the WHA nutrition targets is provided in WHO (2012b).


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