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BACKGROUND: Cluster surveys provide rapid but representative estimates of key nutrition indicators in humanitarian crises. For these surveys, an accurate estimate of the design effect is critical to calculate a sample size that achieves adequate precision with the minimum number of sampling units. This paper describes the variability in design effect for three key nutrition indicators measured in small-scale surveys and models the association of design effect with parameters hypothesized to explain this variability. METHODS: 380 small-scale surveys from 28 countries conducted between 2006 and 2013 were analyzed. We calculated prevalence and design effect of wasting, underweight, and stunting for each survey as well as standard deviations of the underlying continuous Z-score distribution. Mean cluster size, survey location and year were recorded. To describe design effects, median and interquartile ranges were examined. Generalized linear regression models were run to identify potential predictors of design effect. RESULTS: Median design effect was under 2.00 for all three indicators; for wasting, the median was 1.35, the lowest among the indicators. Multivariable linear regression models suggest significant, positive associations of design effect and mean cluster size for all three indicators, and with prevalence of wasting and underweight, but not stunting. Standard deviation was positively associated with design effect for wasting but negatively associated for stunting. Survey region was significant in all three models. CONCLUSIONS: This study supports the current field survey guidance recommending the use of 1.5 as a benchmark for design effect of wasting, but suggests this value may not be large enough for surveys with a primary objective of measuring stunting or underweight. The strong relationship between design effect and region in the models underscores the continued need to consider country- and locality-specific estimates when designing surveys. These models also provide empirical evidence of a positive relationship between design effect and both mean cluster size and prevalence, and introduces standard deviation of the underlying continuous variable (Z-scores) as a previously unexplored factor significantly associated with design effect. The magnitude and directionality of this association differed by indicator, underscoring the need for further investigation into the relationship between standard deviation and design effect.
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INTRODUCTION: The aim of this study was to describe the most recent trends and epidemiologic patterns of fatal injuries resulting from explosions in Iraq, one of the countries most affected by violence from explosive devices. METHODS: Iraqi Ministry of Health (MoH) routine prospective injury surveillance collects information on all fatal injuries recorded by coroners from physical examinations, police reports, and family members in eight governorates of Iraq: Baghdad, Al-Anbar, Basrah, Erbil, Kerbala, Maysan, Ninevah, and Al-Sulaimaniya. This study analyzed explosive-related fatal injuries that occurred from January 1, 2010 through December 31, 2013. RESULTS: Analysis included 2,803 fatal injuries. The number of fatal injuries declined from 2010 through 2012, followed by an increase in 2013. One-thousand one-hundred and one explosion-related fatalities were documented in 2013, more than twice as many as in 2012 or in 2011. Most fatalities were among men aged 20-39 years. Of all causalities, 194 (6.9%) were among females and 302 (10.8%) were among children aged less than 18 years. The majority of fatalities were caused by improvised explosive devices (IEDs): car bombs (15.3%), suicide bombs (4.0%), and other IEDs (29.6%). The highest number of fatalities occurred in streets and roads. Of all deaths, 95.6% occurred in three governorates: Baghdad, Ninevah, and Al-Anbar. CONCLUSIONS: Explosives continue to result in a high number of fatal injuries in Iraq. Following a period of declining violence from explosives, in 2013, fatalities increased. Most explosion-related injuries resulted from IEDs; males aged 20-39 years were at greatest risk.