The composite index of anthropometric failure: …...Bristol text 2019.doc / 2019-03-06/ The...
Transcript of The composite index of anthropometric failure: …...Bristol text 2019.doc / 2019-03-06/ The...
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!