RESUMO
OBJECTIVE: The present study provides ranges for the magnitude of bias caused by measurement error in stunting rates, a widely used a proxy for long-term nutritional status. DESIGN: Stunting, which is determined by the number of cases that fall below -2 sd from the mean height-for-age in the population, mechanically increases with higher variance. This variance stems from both natural heterogeneity in the population and measurement error. To isolate the effect of measurement error, we model the true distributions which could give rise to the observed distributions after subtracting a simulated measurement error. SETTING: We analyse information from three rounds of the Demographic and Health Survey (DHS) in Egypt (2005, 2008 and 2014). Egypt ranks high among developing countries with low-quality anthropometric data collected in the DHS, currently the main source of anthropometry in the country. PARTICIPANTS: The study relies on re-analysis of existing DHS data, which record height, weight and age data for children under 5 years old. RESULTS: Under the most conservative assumptions about measurement error, the stunting rate falls by 4 percentage points for the most recent DHS round, while assuming higher levels of measurement error reduces the stunting rate more dramatically. CONCLUSIONS: Researchers should be aware of and adjust for data quality concerns in calculating stunting rates for cross-survey comparisons or in communicating to policy makers.