resource implications of who growth standards - final

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Adopting the WHO Growth Standards forDiagnosis and Classification of Acute

Malnutrition in Emergencies:An Assessment of Resource Implications

Andrew Seal

UCL Centre for International Health and DevelopmentInstitute of Child Health, London


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Abbreviations

CTC Community Therapeutic CareGAM Global Acute MalnutritionIQR Inter-quartile rangeMAM Moderate Acute Malnutrition

NCHS National Center for Health StatisticsSAM Severe Acute MalnutritionSFP Supplementary Feeding ProgrammeTFP Therapeutic Feeding ProgrammeWH weight-for-heightWHO World Health OrganisationWHZ weight-for-height z-scoresWHM weight-for-height percentage of the median

Acknowledgments

I gratefully acknowledge the contribution of Mark Myatt and SC(UK) who kindly provided thedatabase of nutritional surveys that was analysed for part of this report.

I would also like to thank all the reviewers who provided valuablefeedback and comments on earlier drafts.

This work was funded by a grant from the IASC Nutrition Cluster, via RNIS, Geneva.


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Implications of the WHO 2006 Growth Standards Page 3 of 26

Contents

Part 1 - Modelling the Resource Implications of Using Different Diagnostic and ClassificationCriteria for Acute Malnutrition...................................................................................................4

Overview..............................................................................................................................4

Section 1..............................................................................................................................4Assumptions....................................................................................................................5Classification of Scenarios ..............................................................................................5Classification of Responses.............................................................................................7Implications for Number of Potential Programme Beneficiaries .......................................8

Section 2............................................................................................................................12Modelling weight gains required for nutritional cure.......................................................12Modelling days of treatment required for nutritional cure ...............................................13

Section 3............................................................................................................................14Modelling costs of treatment..........................................................................................14

Conclusions and recommendations...................................................................................17

Part 2 - A Review of Software Available for the Calculation of Acute Malnutrition Using theNCHS Reference and WHO Standards .................................................................................19

Overview............................................................................................................................19Objective technical and user service comparisons ........................................................19Subjective assessments of usability ..............................................................................21

Conclusions and recommendations...................................................................................21

Tables

Table 1 - Classification of Survey Results for Global Acute Malnutrition (n=560).....................7Table 2 - Survey Sites with Indicated Selective Feeding Interventions for Children1 ................7Table 3 - Number of Potential Child Beneficiaries for Selective Feeding1 ..............................11Table 4 - Estimation of the change in costs for treatment of SAM (US$)* ..............................15Table 5 - Estimation of the change in costs for treatment of MAM (US$)*..............................16

Table 6 - Comparison of Selected Software Characteristics ..................................................23

Figures

Figure 1: Comparison of Prevalence Estimates for Global Acute malnutrition..........................6Figure 2: Comparison of Survey Estimates of Moderate Acute Malnutrition (n=560) ...............9Figure 3: Comparison of Prevalence Estimates for Severe Acute Malnutrition (n=560) .........10Figure 4: Weight Gain Required for Nutritional Cure of SAM (Boys)1 .....................................12Figure 5: Days of Recovery Required for Nutritional Cure of SAM.........................................13 Figure 6: Days of Treatment Required for SAM at Different Rates of Weight Gain (Boys)1,2 ..14Figure 7: Sensitivity of the SAM treatment programme cost model to different levels of ........17


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Part 1 - Modelling the Resource Implications of UsingDifferent Diagnostic and Classification Criteria for AcuteMalnutrition

Overview

The diagnosis of childhood malnutrition is usually performed using anthropometric criteria. Inemergencies, the weight-for-height index (WH), in conjunction with oedema, is commonlyused for characterising moderate and severe acute malnutrition. The WH index may beexpressed using a standard deviation score (z-score), as a percentile, or as a percentage ofthe median value. The use of the WH z-score (WHZ) has several statistical advantages andhas been recommended for reporting survey results for some years. However, due to itsease of calculation and conceptual simplicity, the WH percentage of the median (WHM) iscurrently widely used for admission and discharge criteria in selective feeding programmes.WHM based diagnostic criteria have also been shown to be better predictors of response totreatment than WHZ based criteria when calculated using the NCHS Reference.

1

Calculation of WH requires comparison against a growth norm, and since 1978 theNCHS/WHO/CDC Growth Reference (NCHS Reference) has been widely used in

international nutrition. However, new Child Growth Standards were released by WHO in April2006 for use with children between 0 and 59 months.2 These have significant differencescompared to the NCHS Reference but little was known about the implications of using thisnew norm on the numbers of patients that would eligible for treatment and the resourcesrequired for their care.

To assess the resource implications of adopting different diagnostic criteria for acutemalnutrition two things need to be considered. Firstly, the numbers diagnosed as requiringtreatment and secondly, the cost of providing that treatment.

In the first section of this report, data from Myatt and Duffield3

is re-analysed to assess thenumber of scenarios that would be classified as requiring selective feeding interventions andthe number of individuals requiring treatment. A comparison is made between WHMcalculated with the NCHS Reference (WHM-NCHS), and the diagnostic criteria proposed byWHO, which uses WHZ based on the WHO 2006 Child Growth Standards (WHZ-WHO).

In the second section I examine the duration of treatment involved and if this is affected bythe use of the different diagnostic criteria.

In the third section the costs of treatment are considered based on the available data forcentre based and community based programmes, and drawing on our estimates for changesin the number of potential programme beneficiaries and the average duration of treatment.

Section 1

This report follows on from work conducted by Myatt and Duffield for the Nutrition Cluster,which involved the analysis of a dataset comprising the results from 560 nutrition surveys.The surveys were carried out in 31 different countries between September 1992 and October2006 and include data on 459,036 children.

To construct this data base individual datasets were collated by SC(UK), whose nutritionadviser contacted her counterparts at the main agencies working in the field of internationalnutrition. The aims of the work were outlined and permission to use the agencies data wasrequested. Datasets of nutritional anthropometry surveys including age, sex, weight, height,

1 Prudhon, C., Briend, A., Laurier, D., Golden, M. H. N., & Mary, J. Y. (1996) Comparison of weight- and height-basedindices for assessing the risk of death in severely malnourished children. American Journal of Epidemiology 144:116-123.2http://www.who.int/childgrowth/en/3 Weight-for-height and MUAC for estimating the prevalence of acute undernutrition? A review of survey datacollected between September 1992 and October 2006 (2008) Myatt M and Duffield A


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MUAC and oedema were requested. Agencies were also asked to describe where and whenthe survey took place.

Data was received from ACF-F, ACF-US, Concern, FSAU, Goal, MSF-B, MSF-CH, MSF-H,MSF-S SC UK and SC US. The data was obtained in a variety of file formats and thenimported into R4, which was used for subsequent analysis. Additional analysis for this reportwas done using SPSS v14.5

Myatts report considers the differences in estimates of malnutrition prevalence derived usingWHZ and WHM and defined using either the NCHS Reference or WHO Standard. They alsocompare these with the use of MUAC.

Of relevance to this report, they consider the implications for programme size by comparingthe estimated numbers of potential beneficiaries calculated using WHM-NCHS with theestimated numbers of potential beneficiaries calculated using WHM-WHO and WHZ-WHO.This comparison was done separately for moderate acute malnutrition (MAM) and SAM.

In this report we extend the analysis of the difference in need estimated using WHM-NCHSand WHZ-WHO based diagnosis, and go on to look at how these differences may be reflectedin changes in resource requirements.

Assumptions

Calculation of the number of individuals requiring treatment for acute malnutrition is based onprevalence data from anthropometric surveys of the beneficiary population and estimates oftotal population size. It should be noted that this estimated need will usually be different thanthe numbers actually treated, as this will also depend on beneficiary access to the programmeand on the programme coverage actually achieved (4). For the analysis conducted here weassume that the degree of programme access and coverage is not affected by the use of thedifferent anthropometric criteria.

The use of different criteria to define an acutely malnourished child will inevitably lead to theselection of a group that has differing clinical as well as anthropometric characteristics. Forexample, as well as differences in weight, the prevalence of clinical features such asdiarrhoea, ARI and anaemia has been shown to vary according to whether patients were

admitted using MUAC or weight-for-height (5). Unfortunately, data are not currently availableon how the average characteristics of patients will vary if they are admitted and dischargedusing weight-for-height Z-scores based on the WHO Standards (WHZ-WHO) or percentage ofthe median cut-offs based on the NCHS Reference (WHM-NCHS). Therefore, due to lack ofdata on these issues, the analysis reported below assumes that the differences in thecharacteristics of patients are negligible.

With that in mind, it is also assumed that the cost per day of treatment will remain constantwhichever diagnostic criteria are used. Therefore, any differences in cost will be attributableto the duration of treatment, which are enumerated in this analysis as treatment days, andthe number of patients that are treated.

Classification of Scenarios

The classification of emergency situations and their nutritional seriousness depends, largely,upon the reported prevalence of GAM in a survey area. While this is by no means the solecriterion by which a decision to launch a humanitarian response is made, it nonetheless formsan important piece of the information jigsaw. Taken together with other contextualinformation, the prevalence of GAM helps drive the decision making process of donors andoperational agencies. Therefore, the estimation of GAM, and the resulting classification ofscenarios, has important operational significance.

4http://www.r-project.org/index.html 5http://www.spss.com/


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The histograms shown in figure 1 compare the distributions of GAM prevalence estimateswhen using WHZ-WHO and WHZ-NCHS.

Figure 1: Comparison of Prevalence Estimates for Global Acute malnutrition (n=560 surveys)


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In Table 1 the 560 survey results from the study by Myatt et al. are classified according to theWHO prevalence categories that are currently used, where < 5% wasting is consideredacceptable, 5-9% as poor, 10-14% as serious, and 15% or more as critical (6). The surveysare classified according to 2 different case definitions of GAM: (1) WHZ-NCHS


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is required. There may also be a 9% increase in results indicating the need for blanket SFPsand a 5% increase in results indicating the need for a TFP.

Implications for Number of Potential Programme Beneficiaries

The potential beneficiary numbers for selective feeding programmes are usually calculatedseparately by program type. Targeted SFP interventions generally admit cases of moderatelyacute malnutrition (MAM), and TFPs admit cases of SAM.

To arrive at an estimate of beneficiary numbers we first look at differences in estimates ofMAM and SAM prevalence by the WHM NCHS references and WHZ WHO standards, andthen extrapolate this to reach an estimate for the number of children.

Moderate Acute Malnutrition

Figure 2 shows the distribution of the survey estimates of MAM prevalence according to twodifferent case definitions. Note that in this analysis the case definitions that are compared arethose used and proposed for admission and discharge of patients to programmes, not for theclassification of situations as presented in the section above.

If the current practice case definition for MAM (


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Figure 2: Comparison of Survey Estimates of Moderate Acute Malnutrition

(n=560 surveys)


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ImplicationsoftheWHO2006GrowthS

tandards

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Figure3:ComparisonofPrevalen

ceEstimatesforSevereAcuteMalnut

rition(n=560surveys)

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15

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10

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5.

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PrevalenceofSAM(%)

120

100

80

60

40

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Numberofsurveys(B)

resource implications of who growth standards - final

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