CMAM Dr Briend MUAC E

During

this talk,

we

will examine why it is advised to use mid-operable circumference to identify children with severe acute malnutrition.

The

first reason why it is recommended to use mid-operable circumference, or MUAC, to identify higher with children is that MUAC is the anthropometric measure giving the best estimate of the risk of dying better than weight for height index.

And

this has been shown already more than 20 years ago by a series of community-based studies

looking

at the association between different anthropometric indices and the risk of death.

And

these studies were reviewed in 1994 in an article in the Journal of Nutrition by David Peltier in which you can read the following statement.

The

most consistent observation is that weight for height is the least effective index to predict mortality At high specificity level, MUAC is superior to height forage and weight forage.

Another

reason to recommend the use of MUAC is that MUAC is a simple measure which can be taken frequently by trained health workers, including community health workers and volunteers, to identify high-risk children.

An

interesting study was piloted by the NGO Alima, which even suggests that mothers themselves can measure MUAC after minimal training and are able to identify children with a low MUAC needing urgent treatment.

As

MUAC is a simple measure, it can be repeated frequently. And slide 4 shows the advantage of repeated measure.

This

slide shows a graph which is what we call a rock curve, which on the x-axis, you have the specificity of MUAC to assess the risk of death and on its y-axis, its sensitivity.

By

changing the cutoff, you get a family of curves and to interpret the data, you should know that

when

you get a curve which is higher on the graph, the prediction of the assessment of the risk of death is better. This graph is based on data collected in Bangladesh in the late 70s. And you can see very clearly

that

for shorter duration of follow-up, that is for shorter time between MUAC assessment and the time of death, you have a much better assessment of the risk of death.

And

this is a major advantage of MUAC, is that you can improve its ability to assess the risk of dying by repeated measurement. You can measure MUAC every month, which is something which in practice is impossible to do with weight for height.

When

it became clear about 20 years ago that MUAC is the best anthropometric index to assess the risk of death, it came up as a kind of unexpected result.

And

very quickly, the question came up, why do we get such results?

And

then two hypotheses were put forward.

First,

that MUAC used with the fixed cut-off, nowadays 150 millimeters, select younger children who are not at risk of dying. And to understand that, you should know that MUAC is increasing continuously with age, which means that when you use it with the fixed cut-off, you will have an over-representation of younger children.

Another

explanation is that MUAC is linked with muscle mass, and that MUAC identifies children who have a low muscle mass, which is important for survival. And this is in contrast with weight for height, which is influenced by the weight of other tissues and organs that cannot be used as nutrient stores. And also, weight for height is influenced by hydration status of the child, which is not related to his nutritional status.

These

two explanations are compatible, and of course, both can be true, as younger children have a low muscle mass in relation to their body weight. Slide 6 shows that younger children have a lower muscle mass in relation to their body weight.

This

slide is taken from a technical literature report published in 1985,

which

shows the proportion of muscle in relation to body weight in adults and in newborn. And you can see that muscle mass represents approximately 43% of body weight in adults,

compared

to 23% in newborn children,

which

means that

on

average, children are much more vulnerable to malnutrition, and they have lower nutritional stores to start with, even in absence of malnutrition.

As

MUAC increases continuously with age,

it

seems an attractive idea to correct MUAC for age, or for height, when age is not known, to improve the assessment of the risk of death. This has been proposed years ago, but early analysis already showed that this does not improve the assessment of the risk of dying. And on this slide, you can see a graph taken from an early article from Bangladesh, from Beharagi, showing a rock curve in which you cannot distinguish the rock curve of MUAC without correction and MUAC with correction for age, suggesting that correcting for age makes this identification of high-resilion more complicated, but not more effective. Also, this lack of effect of age

has

also been shown by multivariate model, which attempted to correct MUAC for age or for height, which also showed you don't get a better assessment of the risk of death compared to unadjusted MUAC. Maybe this lack of effect of the correction for age or height is due to age and height acting through a common factor on the risk of death, which maybe is related to this effect of muscle mass.

To

understand the better capacity of MUAC to assess the risk of dying compared to weight for height, it is important to realize that MUAC and weight for height do not identify the same children.

On

average, children who have a low MUAC are younger and also they are smaller, that is, they have a lower height for age, they are more stunted than children with just low weight for height.

And

this is important and may explain the association between low MUAC and high risk of death because younger children have a higher risk of dying to start with and also we know that the association between wasting and stunting is especially dangerous in young children.

As

low MUAC and low weight for height do not identify the same children, the question is often asked should not we use MUAC and weight for height at the same time to better identify high risk children. Unfortunately, attempts to use both MUAC and weight for height at the same time to improve risk assessment made the screening more complicated and less effective. and this has been shown by your study

done

in Senegal

based

on data collected in the 80s

and

which is represented on slide 10.

Here

again you have a ROG curve which is slightly different from the previous one because on the x-axis you don't have specificity but false positive which gives a mirror image of the previous ROG curve. But again, to interpret these curves you should know that when the curve is high on the graph it means the assessment of risk of death is better. And you can see on this graph that the MUAC curve is above the weight for height curve again suggesting that MUAC is more effective to assess the risk of dying. On this graph you have two dots. The dot on the left show what happens when you select which selection

is high-rich

children who have both a low MUAC and a low weight for height and in that case you have a higher specificity but you decrease sensitivity dramatically. The dot on the right side of the graph show what happens when you use MUAC or

low

weight for height as a criteria to identify high-rich children. In that case you do increase sensitivity but you decrease specificity dramatically.

The

main point to take from this graph is that when you combine these two indices low weight for height and low MUAC you get two dots which are below the MUAC curve

which

suggests that the screening is less effective.

If

you are interested in having a higher sensitivity you are better increasing slightly the cutoff of MUAC rather than combining these two indices which again make the screening more complicated and less effective.

A

very practical question which came up very quickly as soon as people started to use MUAC as admission criteria for therapeutic feeding program is which criteria to use to end treatment in children admitted based on the MUAC. What became very clear very rapidly is that MUAC cannot be used as discharge criteria in these children because there is a mismatch between weight for height and MUAC and in some children admitted for low MUAC they can reach normal target weight for height

in

a few days while remaining with the low MUAC which is while remaining with the high risk of death.

To

go around this problem

at

some stage the WHO recommended to use percentage of weight gain

but

this approach results in shorter treatment duration of the most severely malnour children and is no more advised. The best approach seems to be to use MUAC. MUAC does respond to treatment and grows very rapidly in children who are receiving intensive therapeutic feeding. There is still some discussion about which cutoff to take as discharge criteria but on average 125 mm seems to be a good criteria. So in conclusion MUAC is the best measure to identify high-rich children requiring urgent treatment. Using both MUAC and weight for height makes screening more complicated and does not improve the assessment of risk.

Using MUAC as the only criteria to identify high-rich children with severe acute malnutrition considerably simplifies management, reduces workload of skilled health workers and allows them to spend more time to do the clinical work which requires most attention and expertise.

On

slide 13 you can have some reference

on

which this talk is based.