The data used for this study wereobtained from food security and nutrition analysis unit (FSNAU). Food Security and Nutrition Unit(FSNAU) is a unit in World Food Programme of United Nations (UNFAO), which wasset up in 1994 to provide evidence-based analysis of Somali food, nutrition andlivelihood security to enable both short-term emergency responses and long-term strategic planning. Therefore, in partnership with UNICEF, FSNAU has beenconducting bi-annual seasonal nutrition assessment surveys since 2001.
Ourstudy focuses on survey data ranging from 2007 – 2010Figure 1. Within thisperiod, FSNAUconducted cross-sectional nutrition assessment surveys twice ayear where information on falciparummalaria parasitaemia was included upon request of United Nations Children’sEmergency Fund (UNICEF).26,28. In each survey, a stratified multi-stagecluster sampling design was adopted where the sampling frame of a selecteddistrict was based on the four livelihood definitions (pastoral, agro-pastoral,riverine and fishing) within which 30 communities and 30 households within eachvillage were selected using systematic random sampling method and the urban population were clearlydefined and considered separately.
Vulnerable groups that could not beclassified in any of the livelihood such as IDPs were surveyed separately. Respectivesamples sizes (number of households and number of children) were calculatedusing the Epiinfo/Ena 2008 software after considering the population size,estimated prevalence and desired precision. A list of all villages andpopulation within each of the assessed livelihoods served as a sampling frameand was used to construct cumulative population for the assessment area. Villageswere then randomly selected from these villages with the chance of any villagebeing selected being proportional to the size of its population. This is calledsampling with “probability proportional to population size (PPS)”.
Selectionof households within the village was done using systematic random sampling,preferably from a list of eligible names or a map of households. Where thesewere not available, the number of households in the village was estimated fromthe population figures (the total population divided by the mean householdsize). Starting from a random household, every nth household was selected andall eligible children (aged 6-59) in that household measured (Figure SI 1).
Retrospective mortality data was collected from all the households in each villagefrom each livelihood, including even those that did not have children aged 6-59months. At the individual child level, age, gender, weight, height, mid-upperarm circumference (MUAC), vitamin A supplementation in the last six months,diarrhoea, acute respiratory infections (ARI) and febrile illness in the twoweeks before the survey, and Polio and Measles vaccination history werecollected. At the household level, information recorded included the householdsize and age structure, gender of the household head, and access to differenttypes of foods in the last 24 hours. Data on falciparum malaria infection in children aged 5-59 months werecollected in sub-sets of villages at the request of UNICEF29–31.
The data used in this study weretherefore a subset of the whole survey dataset with information on both thechildhood malnutrition and malaria. We considered two outcome measurementsto describe the anthropometric indicators of malnutrition, lowweight-for-height (wasting) and low-MUAC, which detect different sets of childrenas malnourished. Wasting is traditionally the main indicator in communitysurveys. Although MUAC is a better predictor of mortality32, few studies have examinedassociations between MUAC and specific pathogens. A child was defined as wasted whens/he was below -2 Z scores for weight-for-height, according to World HealthOrganization (WHO) 2006 standards33. A child with MUAC below 125mm wasclassified as having low-MUAC.
Malaria parasitaemia was determined usingParacheck Pf™ (Orchid Biomedical Systems, Goa, India) in a subset of the samplein every FSNAU surveys during this period33. A child was regarded as malaria infectedwhen s/he had a positive Paracheck Pf™ test result, regardless of any clinicalsymptoms. A detailed search were undertaken toestablish a set of spatial coordinates for each village in Somalia using the villagenames in the data. The location of village was verified by using Google Earth(Google, Seattle, USA) and other online databases to visually inspect whetherthe coordinates matched evidence of human settlement. Those settlements forwhich no reliable source of the coordinates was obtained were excluded from theanalysis.A set of four plausible environmentalcovariates, together with wasting, low-MUAC and malaria in children were includedin the analysis18,34. These were rainfall, enhancedvegetation index (EVI), mean temperature, and urbanization. Rainfall and meantemperature were derived from the monthly average grid surfaces obtained fromWorldClim database35.
The EVI values were derived from theMODerate-resolution Imaging Spectroradiometer (MODIS) sensor imagery for period2007-2010 while the urbanization information was obtained from Global RuralUrban Mapping Project (GRUMP)36,37. All the environmental covariateswere extracted from 1 x 1 km spatial resolution grids. Rainfall, temperatureand EVI were summarized to compute seasonal averages corresponding to the timeof survey.
