%0 Journal Article
%T An algorithm to assess methodological quality of nutrition and mortality cross-sectional surveys: development and application to surveys conducted in Darfur, Sudan
%A Claudine Prudhon
%A Xavier de Radigu¨¨s
%A Nancy Dale
%A Francesco Checchi
%J Population Health Metrics
%D 2011
%I BioMed Central
%R 10.1186/1478-7954-9-57
%X We developed an algorithm based on internationally agreed upon methods and best practices. Penalties are attributed for a list of errors, and an overall score is built from the summation of penalties accrued by the survey as a whole. To test the algorithm reproducibility, it was independently applied by three raters on 30 randomly selected survey reports. The algorithm was further applied to more than 100 surveys conducted in Darfur, Sudan.The Intra Class Correlation coefficient was 0.79 for mortality surveys and 0.78 for nutrition surveys. The overall median quality score and range of about 100 surveys conducted in Darfur were 0.60 (0.12-0.93) and 0.675 (0.23-0.86) for mortality and nutrition surveys, respectively. They varied between the organizations conducting the surveys, with no major trend over time.Our study suggests that it is possible to systematically assess quality of surveys and reveals considerable problems with the quality of nutritional and particularly mortality surveys conducted in the Darfur crisis.The prevalence of acute malnutrition and mortality rates are crucial indicators to benchmark the severity of a crisis, to track trends, and to inform funding and operational decisions [1,2]. Cross-sectional sample surveys are the main method currently used to estimate these indicators [3,4]. An adequate sampling design is indispensable to ensure the representativeness and accuracy of a survey. Moreover, standardized field data collection through suitable interview and measurement instruments and techniques is paramount to guarantee quality.Despite recent improvements in standardization of nutrition and mortality survey methodology and analysis [5-7], errors in the field application of survey methods persist, potentially resulting in biased data and harmful operational decisions. Reviews of surveys carried out in various crisis settings have consistently revealed a lack of rigor in many nutritional [8-12] and most mortality surveys [10,11].Cross-sectiona
%U http://www.pophealthmetrics.com/content/9/1/57