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      Concordance between the estimates of wasting measured by weight-for-height and by mid-upper arm circumference for classification of severity of nutrition crisis: analysis of population-representative surveys from humanitarian settings

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      BMC nutrition
      Wasting, Survey, Nutrition, Humanitarian

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          Abstract

          Background:

          Despite frequent use of mid-upper arm circumference (MUAC) to assess populations at risk of nutrition emergencies, as well as evidence that measurement of children based on MUAC identifies different children than weight-for-height (WHZ) as wasted, no crisis classification thresholds based on prevalence of wasting by MUAC currently exist.

          Methods:

          We analyzed 733 population-representative anthropometric surveys from 41 countries conducted by Action Contre la Faim (ACF) and the United Nations High Commissioner for Refugees (UNHCR) between 2001 and 2016. Children aged 6–59 months were classified as wasted if they had a WHZ < − 2 and/or a MUAC < 125 mm. Prevalence of wasting as assessed by WHZ and by MUAC were compared using correlations and linear regression models adjusting for stunting prevalence, sex and age distribution of the sample. Median prevalence of wasting by MUAC corresponding to each of the WHZ-based crisis thresholds was examined.

          Results:

          Median prevalence of wasting by WHZ was 10.47% (IQR: 6.34–17.55%) and by MUAC was 6.66% (IQR:4.12–10.88%). Prevalence of wasting by WHZ exceeded prevalence by MUAC in 543 (74.1%) surveys and median prevalence by WHZ was greater in 30 (73.17%) countries. Prevalence of wasting by WHZ is poorly correlated with prevalence of wasting by MUAC (ρ = 0.55). R 2 was 0.36 for unadjusted and 0.45 for adjusted linear regression model. The difference between the prevalence by WHZ and by MUAC increased as the overall prevalence by WHZ increased (ρ = 0.69). Surveys with prevalence of wasting by WHZ approximately equal to thresholds for “poor” (5% ± 2.5%), “serious” (10% ± 2.5%), “emergency” (15% ± 2.5%), and “famine” (30% ± 2.5%) were observed to have median prevalence of wasting by MUAC of 4.51% (IQR: 2.73–6.81%), 6.67% (IQR: 4.27–10.03%), 8.15% (IQR: 5.11–11.86%), and 15.71% (IQR: 10.28–17.50%), respectively. There was a very substantial overlap of MUAC values across the threshold categories.

          Conclusions:

          Given a poor correlation between population prevalence of wasting by WHZ and by MUAC, classification of surveys based on prevalence of wasting by MUAC will result in poor concordance with current WHZ-based crisis thresholds, even if regional differences are considered, regardless of the cutoffs used.

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          Algorithms for converting estimates of child malnutrition based on the NCHS reference into estimates based on the WHO Child Growth Standards

          Background The child growth standards released by the World Health Organization (WHO) in 2006 have several technical advantages over the previous 1977 National Center for Health Statistics (NCHS)/WHO reference and are recommended for international comparisons and secular trend analysis of child malnutrition. To obtain comparable data over time, earlier surveys should be reanalyzed using the WHO standards; however, reanalysis is impossible for older surveys since the raw data are not available. This paper provides algorithms for converting estimates of child malnutrition based on the NCHS reference into estimates based on the WHO standards. Methods Sixty-eight surveys from the WHO Global Database on Child Growth and Malnutrition were analyzed using the WHO standards to derive estimates of underweight, stunting, wasting and overweight. The prevalences based on the NCHS reference were taken directly from the database. National/regional estimates with a minimum sample size of 400 children were used to develop the algorithms. For each indicator, a simple linear regression model was fitted, using the logit of WHO and NCHS estimates as, respectively, dependent and independent variables. The resulting algorithms were validated using a different set of surveys, on the basis of which the point estimate and 95% confidence interval (CI) of the predicted WHO prevalence were compared to the observed prevalence. Results In total, 271 data points were used to develop the algorithms. The correlation coefficients (R2) were all greater than 0.90, indicating that most of the variability of the dependent variable is explained by the fitted model. The average difference between the predicted WHO estimate and the observed value was <0.5% for stunting, wasting and overweight. For underweight, the mean difference was 0.8%. The proportion of the 95% CI of the predicted estimate containing the observed prevalence was above 90% for all four indicators. The algorithms performed equally well for surveys without the entire age coverage 0 to 60 months. Conclusion To obtain comparable data concerning child malnutrition, individual survey data should be analyzed using the WHO standards. When the raw data are not available, the algorithms presented here provide a highly accurate tool for converting existing NCHS estimates into WHO estimates.
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            Famine intensity and magnitude scales: a proposal for an instrumental definition of famine.

            Ambiguities in current usage of the term "famine" have had tragic implications for response and accountability in a number of recent food crises. This paper proposes a new approach to defining famine based on the use of intensity and magnitude scales, where "intensity" refers to the severity of the crisis at a given location and point in time, while "magnitude" describes the aggregate impact of a crisis. The scales perform three operations on "famine": first, moving from a binary conception of "famine/no famine" to a graduated, multi-level definition; second, disaggregating the dimensions of intensity and magnitude; and third, assigning harmonised "objective" criteria in place of subjective, case-by-case judgements. If adopted, the famine scales should contribute to more effective and proportionate responses, as well as greater accountability in future food crises.
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              Inconsistent diagnosis of acute malnutrition by weight-for-height and mid-upper arm circumference: contributors in 16 cross-sectional surveys from South Sudan, the Philippines, Chad, and Bangladesh

              Background The two anthropometric indicators of acute malnutrition in children under 5 years, i.e. a Mid-Upper Arm Circumference < 125 mm (MUAC125) or a Weight-for-Height Z-score<−2 (WHZ−2), correlate poorly. We aimed at assessing the contribution of age, sex, stunting (Height-for-Age HAZ<−2), and low sitting-standing height ratio Z-score (SSRZ in the 1st tertile of the study population, called hereafter ‘longer legs’) to this diagnosis discrepancy. Methods Data from 16 cross-sectional nutritional surveys carried out by Action Against Hunger International in South Sudan, the Philippines, Chad, and Bangladesh fed multilevel, multivariate regression models, with either WHZ−2 or MUAC125 as the dependent variable and age, sex, stunting, and ‘longer legs’ as the independent ones. We also compared how the performance of MUAC125 and WHZ−2 to detect slim children, i.e. children with a low Weight-for-Age (WAZ<−2) but no linear growth retardation (HAZ≥−2), was modified by the contributors. Results Overall 23.1 % of the 14,409 children were identified as acutely malnourished by either WHZ−2 or MUAC125, but only 28.5 % of those (949/3,328) were identified by both indicators. Being stunted (+17.8 %; 95 % CI: 14.8 %; 22.8 %), being a female (+16.5 %; 95 % CI: 13.5 %; 19.5 %) and being younger than 24 months (+33.6 %; 95 % CI: 30.4 %; 36.7 %) were factors strongly associated with being detected as malnourished by MUAC125 and not by WHZ−2, whereas having ‘longer legs’ moderately increased the diagnosis by WHZ−2 (+4.2 %; 95 % CI: 0.7 %; 7.6 %). The sensitivity to detect slim children by MUAC125 was 31.0 % (95 % CI: 26.8 %; 35.2 %) whereas it was 70.6 % (95 % CI: 65.4 %; 75.9 %) for WHZ−2. The sensitivity of MUAC125 was particularly affected by age (57.4 % vs. 18.1 % in children aged < 24 months vs. ≥ 24 months). Specificity was high for both indicators. Conclusions MUAC125 should not be used as a stand-alone criterion of acute malnutrition given its strong association with age, sex and stunting, and its low sensitivity to detect slim children. Having ‘longer legs’ moderately increases the diagnosis of acute malnutrition by WHZ−2. Prospective studies are urgently needed to elucidate the clinical and physiological outcomes of the various anthropometric indicators of malnutrition.
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                Author and article information

                Journal
                101672434
                44651
                BMC Nutr
                BMC Nutr
                BMC nutrition
                2055-0928
                20 December 2019
                18 May 2018
                2018
                07 January 2020
                : 4
                : 24
                Affiliations
                Emergency Response and Recovery Branch, Division of Global Health Protection, Center for Global Health, Centers for Disease Control, 1600 Clifton Road, Atlanta, GA 30329, USA
                Author notes

                Both authors contributed equally to this study.

                Authors’ contributions

                EL, OB designed the study, EL, OB collected the data, EL, OB analyzed and interpreted the data, EL and OB drafted the manuscript, EL, OB critically revised the manuscript for important intellectual content. EL, OB read and approved the final manuscript. EL is a guarantor. Both authors have read and approved the manuscript, have full access to all of the data, and take responsibility for the integrity of the data and the accuracy of the data analysis.

                [* ]Correspondence: eleidman@ 123456cdc.gov
                Author information
                http://orcid.org/0000-0002-4191-5931
                Article
                HHSPA1064485
                10.1186/s40795-018-0232-0
                6945813
                31911840
                8f4684f6-fb37-4ee9-bbd8-3c173cfcb98b

                This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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                wasting,survey,nutrition,humanitarian
                wasting, survey, nutrition, humanitarian

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