Comparison of weight and height-based indices for assessing the risk of death in severely malnourished chidren

To compare the effectiveness of treating malnourished children in different centers, the authors believe there is a need to have a simple method of adjusting mortality rates so that differences in the nutritional status of the children are taken into account. The authors compared different anthropometric indices based on weight and height to predict the risk of death among severely malnourished children. Anthropometric data from 1047 children who survived were compared with those of 147 children who died during treatment in therapeutic feeding centers set up in African countries in 1993. The optimal ratio of weight to height determined by logistic regression was weight (kg)/height (m) (95% confidence interval of bêta estimate 1.65-1.84). The receiver operating curves (sensitivity vs. specificity) showed that the body mass index (weight (kg)/height (m) -puissance 2-), optimal ratio of weight to height, and weight/height index expressed as the percentage of the median of the National Center for Health Statistics' standard were equivalent and superior to the weight/height index expressed as the z score of the National Center for Health Statistics' standard to predict death. As the optimal ratio of weight to height is easier to calculate than the weight/height index expressed as the percentage of the median or z score and does not depend upon either standards or tables, the optimal ratio of weight to height could be conveniently used to adjust mortality rates for nutritional status in therapeutic feeding centers. (Résumé d'auteur

An algorithm to assess methodological quality of nutrition and mortality cross-sectional surveys: development and application to surveys conducted in Darfur, Sudan

Background Nutrition and mortality surveys are the main tools whereby evidence on the health status of populations affected by disasters and armed conflict is quantified and monitored over time. Several reviews have consistently revealed a lack of rigor in many surveys. We describe an algorithm for analyzing nutritional and mortality survey reports to identify a comprehensive range of errors that may result in sampling, response, or measurement biases and score quality. We apply the algorithm to surveys conducted in Darfur, Sudan. Methods 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. Results 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. Conclusion 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.BioMed Central Open acces

A review of methodology and analysis of nutrition and mortality surveys conducted in humanitarian emergencies from October 1993 to April 2004

<p>Abstract</p> <p>Background</p> <p>Malnutrition prevalence and mortality rates are increasingly used as essential indicators to assess the severity of a crisis, to follow trends, and to guide decision-making, including allocation of funds. Although consensus has slowly developed on the methodology to accurately measure these indicators, errors in the application of the survey methodology and analysis have persisted. The aim of this study was to identify common methodological weaknesses in nutrition and mortality surveys and to provide practical recommendations for improvement.</p> <p>Methods</p> <p>Nutrition (N = 368) and crude mortality rate (CMR; N = 158) surveys conducted by 33 non-governmental organisations and United Nations agencies in 17 countries from October 1993 to April 2004 were analysed for sampling validity, precision, quality of measurement and calculation according to several criteria.</p> <p>Results</p> <p>One hundred and thirty (35.3%) nutrition surveys and 5 (3.2%) CMR surveys met the criteria for quality. Quality of surveys varied significantly depending on the agency. The proportion of nutrition surveys that met criteria for quality rose significantly from 1993 to 2004; there was no improvement for mortality surveys during this period.</p> <p>Conclusion</p> <p>Significant errors and imprecision in the methodology and reporting of nutrition and mortality surveys were identified. While there was an improvement in the quality of nutrition surveys over the years, the quality of mortality surveys remained poor. Recent initiatives aimed at standardising nutrition and mortality survey quality should be strengthened. There are still a number of methodological issues in nutrition and mortality surveys in humanitarian emergencies that need further study.</p

Economic Feasibility of a New Method to Estimate Mortality in Crisis-Affected and Resource-Poor Settings

INTRODUCTION: Mortality data provide essential evidence on the health status of populations in crisis-affected and resource-poor settings and to guide and assess relief operations. Retrospective surveys are commonly used to collect mortality data in such populations, but require substantial resources and have important methodological limitations. We evaluated the feasibility of an alternative method for rapidly quantifying mortality (the informant method). The study objective was to assess the economic feasibility of the informant method. METHODS: The informant method captures deaths through an exhaustive search for all deaths occurring in a population over a defined and recent recall period, using key community informants and next-of-kin of decedents. Between July and October 2008, we implemented and evaluated the informant method in: Kabul, Afghanistan; Mae La camp for Karen refugees, Thai-Burma border; Chiradzulu District, Malawi; and Lugufu and Mtabila refugee camps, Tanzania. We documented the time and cost inputs for the informant method in each site, and compared these with projections for hypothetical retrospective mortality surveys implemented in the same site with a 6 month recall period and with a 30 day recall period. FINDINGS: The informant method was estimated to require an average of 29% less time inputs and 33% less monetary inputs across all four study sites when compared with retrospective surveys with a 6 month recall period, and 88% less time inputs and 86% less monetary inputs when compared with retrospective surveys with a 1 month recall period. Verbal autopsy questionnaires were feasible and efficient, constituting only 4% of total person-time for the informant method's implementation in Chiradzulu District. CONCLUSIONS: The informant method requires fewer resources and incurs less respondent burden. The method's generally impressive feasibility and the near real-time mortality data it provides warrant further work to develop the method given the importance of mortality measurement in such settings

Old and new cluster designs in emergency field surveys: in search of a one-fits-all solution

<p>Abstract</p> <p>Introduction</p> <p>Cluster surveys are frequently used to measure key nutrition and health indicators in humanitarian emergencies. The survey design of 30 clusters of 7 children (30 × 7) was initially proposed by the World Health Organization for measuring vaccination coverage, and later a design of 30 clusters of 30 children (30 × 30) was introduced to measure acute malnutrition in emergency settings. Recently, designs of 33 clusters of 6 children (33 × 6) and 67 clusters of 3 children (67 × 3) have been proposed as alternatives that enable measurement of several key indicators with sufficient precision, while offering substantial savings in time. This paper explores expected effects of using 67 × 3, 33 × 6, or 30 × 7 designs instead of a "standard" 30 × 30 design on precision and accuracy of estimates, and on time required to complete the survey.</p> <p>Analysis</p> <p>The 67 × 3, 33 × 6, and 30 × 7 designs are expected to be more statistically efficient for measuring outcomes having high design effects (e.g., vaccination coverage, vitamin A distribution coverage, or access to safe water sources), and less efficient for measuring outcomes with more within-cluster variability, such as global acute malnutrition or anemia. Because of small sample sizes, these designs may not provide sufficient levels of precision to measure crude mortality rates. Given the small number (3 to 7) of survey subjects per cluster, it may be hard to select representative samples of subjects within clusters.</p> <p>The smaller sample size in these designs will likely result in substantial time savings. The magnitude of the savings will depend on several factors, including the average travel time between clusters. The 67 × 3 design will provide the least time savings. The 33 × 6 and 30 × 7 designs perform similarly to each other, both in terms of statistical efficiency and in terms of time required to complete the survey.</p> <p>Conclusion</p> <p>Cluster designs discussed in this paper may offer substantial time and cost savings compared to the traditional 30 × 30 design, and may provide acceptable levels of precision when measuring outcomes that have high intracluster homogeneity. Further investigation is required to determine whether these designs can consistently provide accurate point estimates for key outcomes of interest. Organizations conducting cluster surveys in emergency settings need to build their technical capacity in survey design to be able to calculate context-specific sample sizes individually for each planned survey.</p