Assessing the use of acute malnutrition indicators for nutrition surveillance: Results from 682 283 child observations in 27 low- and middle-income countries

Surveillance with anthropometric indicators is crucial to detect any deterioration in the nutritional status of a population as it provides information on trends to monitor progress and effectiveness of interventions and facilitates geographical and contextual situation analysis which informs prioritization of actions and allocation of resources. For this purposes it is essential that the indicators used to monitor the situation yield comparable results. However, the two indicators most widely used to identify children´s acute malnutrition (AM), the weight-for-height/length Z-score (WHZ) and the absolute value of mid-upper arm circumference (MUAC) provide discrepant results when applied to the same populations. The aim of this report is to shed light on the relationships between WHZ and MUAC in identifying possible population level patterns of acute malnutrition, and explore how they relate to individual characteristics such as sex, age or stunting status, in order to guide their interpretation and use to inform nutrition interventions. The MUAC for age (MUACZ) is also assessed to explore further possibilities of using this indicator as part of population based surveillance taking into account the age bias that exists when assessing children for acute malnutrition using absolute MUAC measurement only. The JRC-UNICEF collaboration was set up to collate, harmonise and analyse a large dataset composed of surveys from 19 West and 7 East African countries and Yemen. In total, 135 national and subnational representative surveys containing 682,283 child observations from 27countries (2011-2018) were collated. We use descriptive statistics and regression analyses to analyse these data. The findings show that WHZ and MUAC measurements identify different manifestations of acute malnutrition and are thus complementary and additive, rather than alternative or exchangeable. Overall and in most of the countries the global acute malnutrition prevalence was lower when using MUAC as compared to WHZ or MUACZ. However, results at country and regional level differed from findings described in other multi-country studies, suggesting that the relationship between the indicators doesn´t follow a geographical pattern (no regional or country pattern can be identified), but rather depend on the sample characteristics of the population surveyed. Importantly, sex, age, and stunting status were confirmed to impact how children are diagnosed as acutely malnourished by the different indicators. Whereas absolute MUAC consistently identifies more acutely malnourished children in younger age groups (below 2 years), MUAC for age (MUACZ) identifies more acute malnutrition in older children. And in relation to the sex of the child, depending on the indicator, the prevalence of acute malnutrition is higher among girls (MUAC) or among boys (WHZ and MUACZ). Conversely, acute malnutrition was consistently higher among stunted children (compared to non-stunted children) across the three indicators, although MUACZ invariably identified the highest number of AM children within the stunted children, as compared to MUAC and WHZ. Finally, these discrepancies can result in discordant situation analysis if the same severity thresholds are applied to all AM population estimates, independently of the indicator used. At the time being, the only global thresholds prescribed to categorize the severity of AM within populations are the ones defined by WHO for wasting based on WHZ. In conclusion, the recommendation is to always specify the indicator used to diagnose acute malnutrition when reporting nutrition outcomes, as well as to disaggregate results by sex, age (below and at/above 24 months) and stunting status for better interpretation. The use of MUAC for age showed potential to improve estimation of acute malnutrition for surveillance but requires additional research. Also, further investigations are needed to define global thresholds to describe severity of acute malnutrition at population level when using the different indicators. Alternatively, to reconsider the age targeting of surveys to 0-23 months, in line with 1000 days programming, and to develop population threholds specific of this age group. Meanwhile, the WHO population based thresholds to interpret the severity of global acute malnutrition for children under five years should be used exclusively for WHZ, and for the acute malnutrition derived from absolute MUAC we recommend to use alternative methods such as the one developed by the Integrated Food Security Phase Classification initiative.S

Can we predict the burden of acute malnutrition in crisis-affected countries? Findings from Somalia and South Sudan.

BACKGROUND: Sample surveys are the mainstay of surveillance for acute malnutrition in settings affected by crises but are burdensome and have limited geographical coverage due to insecurity and other access issues. As a possible complement to surveys, we explored a statistical approach to predict the prevalent burden of acute malnutrition for small population strata in two crisis-affected countries, Somalia (2014-2018) and South Sudan (2015-2018). METHODS: For each country, we sourced datasets generated by humanitarian actors or other entities on insecurity, displacement, food insecurity, access to services, epidemic occurrence and other factors on the causal pathway to malnutrition. We merged these with datasets of sample household anthropometric surveys done at administrative level 3 (district, county) as part of nutritional surveillance, and, for each of several outcomes including binary and continuous indices based on either weight-for-height or middle-upper-arm circumference, fitted and evaluated the predictive performance of generalised linear models and, as an alternative, machine learning random forests. RESULTS: We developed models based on 85 ground surveys in Somalia and 175 in South Sudan. Livelihood type, armed conflict intensity, measles incidence, vegetation index and water price were important predictors in Somalia, and livelihood, measles incidence, rainfall and terms of trade (purchasing power) in South Sudan. However, both generalised linear models and random forests had low performance for both binary and continuous anthropometric outcomes. CONCLUSIONS: Predictive models had disappointing performance and are not usable for action. The range of data used and their quality probably limited our analysis. The predictive approach remains theoretically attractive and deserves further evaluation with larger datasets across multiple settings

Factors associated with diet diversity among infants and young children in the Eastern and Southern Africa region

Abstract This study explores common factors associated with not meeting minimum dietary diversity (MDD) among 27,072 children aged 6–23 months in Eastern and Southern Africa using data from nine Demographic and Health Surveys from 2013 to 2016. MDD was defined as consumption of more than or equals to five of eight food groups including breast milk in the past 24 h. Equity gaps were calculated as the difference in MDD prevalence between the top and bottom wealth quintiles. Logistic regression was conducted to identify common factors for not meeting MDD at the household, maternal and child levels across two or more countries to inform regional policies to improve children's diets. Kenya had the highest MDD wealth equity gap (40.4 pts), and South Africa had the smallest (14.4 pts). Equity gaps for flesh foods or eggs (up to 39.8 pp) were larger than for grain or legumes (up to 20 pp). Common risk factors for not reaching MDD included younger child age (6–11 months) (n = 9 countries), no formal maternal occupation (n = 6), not receiving vitamin‐A supplementation (n = 3), younger maternal age (n = 3), lower maternal education (n = 3), no media (n = 3) or newspaper (n = 3) exposure, lower household wealth quintile (n = 3), use of nonefficient cooking fuel (n = 2), longer time to get to the water source (n = 2), not listening to the radio (n = 2) and higher birth order (n = 2). Priorities for improving MDD in the region include introducing diverse foods at a young age from 6 months with early nutrition counselling, promoting higher maternal education, increasing food purchasing power and ensuring the support of younger mothers

Development, Validity, and Cross-Context Equivalence of the Child Food Insecurity Experiences Scale for Assessing Food Insecurity of School-Age Children and Adolescents

BACKGROUND: Children ages 6 to 17 years can accurately assess their own food insecurity, whereas parents are inaccurate reporters of their children's experiences of food insecurity. No globally applicable scale to assess the food insecurity of children has been developed and validated. OBJECTIVES: We aimed to develop a globally applicable, experience-based measure of child and adolescent food insecurity and establish the validity and cross-contextual equivalence of the measure. METHODS: The 10-item Child Food Insecurity Experiences Scale (CFIES) was based on items previously validated from questionnaires from the United States, Venezuela, and Lebanon. Cognitive interviews were conducted to check understanding of the items. The questionnaire then was administered in 15 surveys in 13 countries. Other items in each survey that assessed the household socioeconomic status, household food security, or child psychological functioning were selected as criterion variables to compare to the scores from the CFIES. To investigate accuracy (i.e., criterion validity), linear regression estimated the associations of the CFIES scores with the criterion variables. To investigate the cross-contextual equivalence (i.e., measurement invariance), the alignment method was used based on classical measurement theory. RESULTS: Across the 15 surveys, the mean scale scores for the CFIES ranged from 1.65 to 5.86 (possible range of 0 to 20) and the Cronbach alpha ranged from 0.88 to 0.94. The variance explained by a 1-factor model ranged from 0.92 to 0.99. Accuracy was demonstrated by expected associations with criterion variables. The percentages of equivalent thresholds and loadings across the 15 surveys were 28.0 and 5.33, respectively, for a total percentage of nonequivalent thresholds and loadings of 16.7, well below the guideline of <25%. That is, 83.3% of thresholds and loadings were equivalent across these surveys. CONCLUSIONS: The CFIES provides a globally applicable, valid, and cross-contextually equivalent measure of the experiences of food insecurity of school-aged children and adolescents, as reported by them