Bristol text 2019.doc / 2019-03-06/

The composite index of anthropometric failure:

Empirical applications*

Peter Svedberg

Institute for International Economic Studies

Stockholm University, Sweden

Presentation based on Annual Review Nutrition 31, 2011, and Handbook of

Anthropometry, Preedy V (ed.), Springer Verlag (with Shailen Nandy)

Scope of presentation

* The presentation will be confined to macro-level measurements of

malnutrition; how it is defined and measured in large populations, not

malnutrition at the level of individuals, related to disease, metabolic

disorders and mal-absorption of micro-nutrients etc.

* The main objective of the talk is to try to convince you that my

measure, the composite index of anthropometric failure is a more

relevant measure of child malnutrition than conventional indicators

Why important to assess the overall prevalence of malnutrition in a

population?

▲ Quite obviously, malnutrition is in itself an impairment, but also

closely linked to disease, learning ability, and labour productivity

▲ In order to design and implement interventions the scope of the

problem has to be known (general or targeted policies?)

▲ Also have to know who the most affected groups are and where they

are living

Why important to assess the prevalence of malnutrition? (cont’d)

▲ When it comes to infants and young children in rich countries,

almost all are routinely individually examined by medically trained

professionals on a regular basis

▲ In poor countries, the medical and other facilities for early detection

and remedy at the level of individuals are often lacking, or are not

affordable for large parts of the population

▲ Policies are therefore often targeted to broad groups of people

(children) according to income (poverty) levels or geographical areas

How many, who and where? These important questions cannot be

answered with the precision warranted for three main reasons:

▲ First, malnutrition is not a single-dimension state of a person that is

easily defined and delineated from other adverse conditions, such as ill

health in various forms

▲ Second, there are measurement problems associated with all

concepts and definitions of malnutrition that are not fully resolved

▲ Third, there is little evidence on the nutritional status of others than

infants and young children and their mothers; school children,

adolescents and the elderly are not sufficiently covered in any data

Roadmap:

Present a method for assessing the total burden of child malnutrition in

a population — the Composite Index of Anthropometric Failure

(CIAF).

Based on anthropometric assessments (WHO, UNICEF, DHS)

Not dealing with alternative measures of “malnutrition”:

1) Self-reported hunger (mainly India)

2) Estimates based on food availability (FAO)

Malnutrition as measured by anthropometrics — advantages

▲ No need for assessing how many calories a person consumes or

expends for metabolism and physical activity. Anthropometrics simply

reflect the (im)balance between intakes and expenditures (body size)

▲ Anthropometric indicators can provide detailed maps of the

concentration of malnutrition along age- and gender lines and spatially,

important for targeting interventions efficiently

▲ A further advantage is that the anthropometric norms are universal,

at least for children below the age of five (WHO 2006)

Inherent limitations with anthropometrics

▲ The anthropometric norms are statistical constructs rather than

derived from epidemiological or other evidence on (health) impairments

▲ Albeit statistical constructs, anthropometric failures are correlated

to adverse outcomes, such as elevated morbidity and mortality risk

▲ Anthropometric measures do not reveal the underlying cause of

weight and height failure. Malnutrition, and frequent and prolonged

illness, are intertwined in a complicated and multi-facetted pattern

The total burden of child malnutrition and the CIAF

Some 20 years ago, I proposed a measure of child malnutrition that

encompasses the conventional indicators of anthropometric failure,

which I dubbed the Composite Index of Anthropometric Failure

▲ The CIAF index provides a comprehensive measure of overall

prevalence of child anthropometric failure ─ or the total burden of child

malnutrition

▲ The CIAF has been used in more than 300 studies (Google Scholar)

▲ The CIAF model or index can be described with the help of Figure 1

Figure 1. The total prevalence of child anthropometric failure and the CIAF

_________________________________________________________________

_________________________________________________________________

W/A

H/A

W/H

● A ● B

● C

● D

● E

● F

● G

The model explained

▲ On the horizontal axis children’s height-for-specific-age is

measured and on the vertical axis, weight-for-specific-age

▲ The intersection of these two axes marks the anthropometric cut-

off points for stunting and underweight

▲ The south-west to north-east diagonal marks the weight-for-height

norm; a child with a weight-for-height failure is found below this line

▲ There are seven different categories of child anthropometric failure

(we disregard overweight for the time being)

Different combinations of child anthropometric failure

Suppose we have seven children, A, B, … and G, with different

anthropometric status

▲ Only child A does not suffer from any anthropometric failure

▲ Child B, F and G are malnourished in one dimension

(single-burden)

▲ Child C and E are malnourished in two (double-burden)

▲ Child D in all three dimensions (triple-burden)

Estimates of the total burden of child malnutrition in India

▲ Detailed CIAF estimates were first provided by Nandy et al (2005),

based on data from the Indian NFHS survey (1998-99)

▲ Nandy and Svedberg (2011) updated the index for India, based on

data from NFHS (2005-06), and also for seven additional countries

▲ The estimated CIAF and the sub-categories (A to G), based on the

two most recent Indian NFHS surveys (2005-06 and 2015-16), have

been replicated in Table 1

Table 1. Estimated CIAF failure categories, children 0-5 y. India (%)

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CIAF category 2005-06 2015-16 Change

______________________________________________________________

No failure 38 45 8

Wasted only 2 3 1

Stunted only 15 13 -2

Underweight only 4 6 2

Wasted and underweight 7 8 1

Stunted and underweight 25 18 -7

Stunted, underw, wasted 9 7 -2

All failure categories 62 55 -7

All children 100 100

______________________________________________________________

Source: Rajpal, S. et al (2018), FAQ on Child Anthropometric Failure in India.

Harvard CPDS Working Paper, volume 18, number 3

¤ Large differences in levels and changes over time depending on what sub-

categories of anthropometric failure we consult

¤ The stunted-only measure suggest a decline in child malnutrition; the

underweight only indicator suggest an increase over time

¤ More than half the children with failures have 2 or 3 failures (multiple

failures)

¤ Only 45% of the Indian children aged 0-5 years are totally free from

any form of anthropometric failure (in 2015-16)

Recent extensions of the CIAF model (Nandy and Svedberg 2011)

▲ Estimates of severe anthropometric failure in India (<3 sd of norms)

▲ Inclusion of overweight and obesity among children in the CIAF

(increasing in most developing countries)

▲ Coverage of more countries In all countries studied, the CIAF is

notably higher than shown by the conventional anthropometric measures

▲ Investigations of correlates between CIAF categories and diseases

(stronger than for conventional measures)

# Checking on Google Scholar reveals that more than 300 studies in

which the CIAF index is cited, or applied, have been published

# At least 100 studies have been carried out in which the overall burden of

child malnutrition as estimated by CIAF are compared with the

conventional indicators (stunted, underweight and wasted)

# All these studies, from all geographical regions in the world, show the

same main results: the burden of child malnutrition is underestimated

by conventional indicators

Are the sub-categories of the CIAF index more accurate predictors of

child adversities in terms of health and other functions?

¤ In my opinion, this is the most important empirical question that the

CIAF index may provide answers to

¤ Several studies have provided tests of how different sub-indices of CIAF

may relate to impairments of child health and other dysfunctions

¤ I will just present the main features and results from one of these studies

The study is:

McDonald, C. M. et al. ”The effect of multiple anthropometric deficits on

child mortality: meta-analysis on individual data in 10 prospective studies

from developing countries”, The American Journal of Clinical Nutrition,

vol. 97, issue 4, pp 896-901

The reason for choosing this study is that the scope is larger and wider

than in other related studies, and it is published in one of the top

nutritional journals.

The study attempts to estimate the relationship between anthropometric

failure in different subcategories and child deaths in subsequent periods.

The measure estimated is the Hazard Ratio (HR) = λ1/ λ2.

Where λ1 is the risk of premature death of a child in anthropometric sub-

category 1, say those with tripel-burden of anthropometric failure -- those

who are simultaneously stunted, underweight, as well as wasted.

λ2 is the risk of premature death in the control group, i.e. the children in

the same population but with no anthropometric failure

An estimated HR of 2 hence means that the risk of premature death is

twice as high in the target group as in the control group.

An estimated HR of 10 means that the risk is 10 times higher in the target

group as in the control group.

The main results, in terms of estimated Hazard Ratios for the 10 countries

studied in the McDonald study (2013), are summarized in Table 2 below

Table 2. Estimated HR in McDonald’s et al study (2013), table 2 and 3.

(based on 53,767 children and 1306 deaths)

Region (no of

countries)

Single

failures

Stunt, uw

failure

Wasted, uw

failure

Wast, uw,

stunt failure

HR HR HR HR

Africa (4) - 2.55 3.62 6.54

Asia (5) - 4.08 5.74 18.64

Pooled 1.47 – 2.49 3.36 4.69 12.25

(all 10 count)

Comments on results

The numbers in the right-most column are notable. They tell the estimated

risk of death in the group of children with triple failure.

In fact, these children are on average 12 times more likely to die than

children in the same group with no failures

The classification of children according to the CIAF index is hence a much

more accurate instrument for identifying the children at the most elevated

risk of premature death than the traditional instruments (stunting or

underweight or wasting).

There are other studies that have used the CIAF classification to estimate

risks of other impairments than premature deaths.

¤ The risk of anaemia in pre-school children in West Africa (Magalhäes et

al., PLOS Medicine 2011)

¤ Delayed psychomotor development of children in Pakistan (Avan et al,

Transactions of the Royal ….2014)

¤ Increased prevalence of various child diseases with multiple

anthropometric failure (e.g. Nandy et al 2005 and 2012)

My hope for the future is that the CIAF components will be used in

additional studies of the links between child malnutrition, as measured by

these components, and child impairments of various kinds.

I am quite convinced in the light of hitherto results for elevated death risk,

increased psychomotor delays and increased burden of illness that such

studies will reveal interesting associations with additional impairments.

A more frequent use of the CIAF classification can hopefully increase the

efficiency in reaching children in need of interventions

Thank you for the attention!