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

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

Further Support to the Uncoupling-to-Survive Theory: The Genetic Variation of Human UCP Genes Is Associated with Longevity

In humans Uncoupling Proteins (UCPs) are a group of five mitochondrial inner membrane transporters with variable tissue expression, which seem to function as regulators of energy homeostasis and antioxidants. In particular, these proteins uncouple respiration from ATP production, allowing stored energy to be released as heat. Data from experimental models have previously suggested that UCPs may play an important role on aging rate and lifespan. We analyzed the genetic variability of human UCPs in cohorts of subjects ranging between 64 and 105 years of age (for a total of 598 subjects), to determine whether specific UCP variability affects human longevity. Indeed, we found that the genetic variability of UCP2, UCP3 and UCP4 do affect the individual's chances of surviving up to a very old age. This confirms the importance of energy storage, energy use and modulation of ROS production in the aging process. In addition, given the different localization of these UCPs (UCP2 is expressed in various tissues including brain, hearth and adipose tissue, while UCP3 is expressed in muscles and Brown Adipose Tissue and UCP4 is expressed in neuronal cells), our results may suggest that the uncoupling process plays an important role in modulating aging especially in muscular and nervous tissues, which are indeed very responsive to metabolic alterations and are very important in estimating health status and survival in the elderly