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Childhood Undernutrition

The population level of childhood undernutrition impacts IFs forecasts of under-5 mortality related to communicable causes.  The “full” IFs forecast is based on estimated calories per capita [1] and access to safe water/sanitation:

undernutrition eq 1

undernutrition eq 2


CLPC is calories per capita

WATSAFE(R, 2) is improved access to water
WATSAFE(R, 3) is piped access to water
SANITATION(R, 2) is shared access to sanitation
SANITATION(R, 3) is improved access to sanitation 
MALNCHP is percent of children malnourished.

For each country/region r

Parameters for the distal regression were estimated in a mixed model regression analysis (using Proc Mixed in SAS Version 9.1) from historical data (1960-2005):

undernutrition eq 3

undernutrition eq 4

In the above equation GDPPCP is GDP per capita at purchasing power parity and EDYRSAG25 is average years of formal education for adults over 25.  PMN is the percentage of children categorized as “moderately” or “severely” undernourished (<=-2 standard deviations below the international standard of weight for age).  Both the distal and full models incorporate an additive shift factor to match initial year (2010) model estimates to historical data.  This additive shift factor converges to 0 in 100 years.

Assuming a normal distribution, we further categorize the under-5 population into four categories: severe (<-3 standard deviations below normal weight for age); moderate (-3 <= -2 standard deviations below normal weight for age); mild (-2 <= -1 standard deviations below normal weight for age); and baseline (>-1 standard deviations below normal weight for age).  The relative risks of mortality related to communicable disease category (compared to a baseline risk of 1) are listed in the table below [2] .

Cause Mild Moderate Severe
Other Group I 2.06 4.24 8.72
Diarrheal Disease 2.32 5.39 12.5
Malaria 2.12 4.48 9.49
Respiratory Infection 2.01 4.03 8.09



[1] Calories per capita are calculated through the agricultural module in IFs.  The number of available calories depends strongly on the interaction of two factors: income (including its distribution) and food price.  Long-term trends in caloric availability reflect fairly rapidly-rising incomes in most parts of the world.  

[2] Relative risk estimates from Gakidou et al. 2007, Table 3: 1880.