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Sikandra Kurdi (IFPRI Egypt)• 2018 IFPRI Egypt Seminar: “High quality evidence is critical for high quality nutrition policy”

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as part of the IFPRI-Egypt Seminar Series- funded by the United States Agency for International Development (USAID) project called “Evaluating Impact and Building Capacity” (EIBC) that is implemented by IFPRI.

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Sikandra Kurdi (IFPRI Egypt)• 2018 IFPRI Egypt Seminar: “High quality evidence is critical for high quality nutrition policy”

  1. 1. The Influence of Measurement Error on Stunting Rates in Egypt IFPRI Egypt Seminar Series Jose Luis Figueroa and Sikandra Kurdi September 25, 2018
  2. 2. What is Stunting? • Share of children with height-for-age z-score<-2 • Height in cm divided by age in months compared to a reference population of healthy children • Usually calculated for children under age 5 • Measure of long-term nutritional deficiency • Correlated with low dietary diversity (lack of important micronutrients) and severe economic shocks during childhood • Also correlated with cognitive development and long-term job market outcomes
  3. 3. Growth Curves for Reference Population • Separate reference standards for boys and girls • Some variation is natural: the green line is the average in the reference population and the red and black lines show 95% of the reference population (2 standard deviations) and 99% (3 standard deviation of the reference population) • Note: the break in the curve at age of 2 years is caused by the switch from measuring lying down vs. standing up
  4. 4. Influence of Variance on Stunting • A higher variance increases the “spread” of the distribution. • The number of cases falling below the cut-off point (-2SD) increases, and thus, the number of children considered stunted. • Policy makers and stakeholders often ignore the effort of measurement error! Source: Grellety and Golden, 2016
  5. 5. Egypt Stunting Rate • Stunting decreased for 6-23 mo from 2005 to 2014. • For older children (24-59 mo) there is a sharp “peak” in 2008 • Very high standard deviations: reference population is 1 and most surveys around 1.2 since there can be real heterogeneity • Error is likely to lead to overestimations of real stunting, especially in the 2014 round which presents the highest variance Mean Mean Mean 6-23 mo -1.04 -0.91 -0.28 24-59 mo -1.09 -1.25 -0.46 Panel A. DHS observed data SD 2.32 2.02 20.4 25.6 30.2 Stunted 31.0 2008 StuntedStunted 2005 SD 2.22 1.71 2014 SD 2.24 1.86 32.0 19.8
  6. 6. Egypt Stunting Rate • In Egypt measurement error is high and differs from one survey round to another • In an analysis of Demographic and Health Surveys (DHS) anthropometric data quality from DHS in 52 countries, Egypt is one of the seven countries listed as having the most concerns raised across a variety of different quality indicators (see Assaf et al.2015) • Adjustment for measurement error is necessary to make statements about the evolution of stunting rates in Egypt over time, and how the situation in Egypt compares to other countries
  7. 7. Ex-post adjustment of measurement error • To provide potential ranges of stunting after removing measurement error under different assumptions about the magnitude of error. • We present three cases which show the range of true values which could give rise to the observed data, depending on how much measurement error we assume: • Scenario 1: Conservative approach inferring error from share of tall children in a reference population • Scenario 2: Aggressive approach reduce error until SD=1 as in reference population • Scenario 3: Moderate approach reduce error until SD=1.64 for younger children and 1.3 for older children (SD found in FAS survey) • Each scenario assumes measurement error normally distributed with mean 0 and uncorrelated with true values
  8. 8. Results0 .1.2.3.4 -10 -5 0 5 10 x DHS (observed) HAZ HAZ based on FAS HAZ based on share tall children HAZ based on SD=1 HAZ for chidren 6-23 months old 0 .1.2.3.4 -5 0 5 x DHS (observed) HAZ HAZ based on FAS HAZ based on share tall children HAZ based on SD=1 HAZ for children 24-59 months old
  9. 9. Conclusion • Adjustments of error are needed before using surveys with questionable data quality in time-series or cross-sectional analysis of stunting rates. • Policy makers and stakeholders need to be aware of the degree of uncertainty surrounding the stunting rate when the only available data is from survey rounds with data quality concerns. • If other views about the true variance z-scores in Egypt, can run simulations using our methodology to see what the implied stunting rate would be

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