R
ecent anthropometric studies have
emphasized the need for larger datasets from the community
level to validate the use of Mid-Upper Arm Circumference
(MUAC), with a cut-off of 115mm, as an anthropometric marker
to diagnose Severe Acute Malnutrition (SAM) [1].
10 gram panchayats were randomly selected
from each of the five blocks, across three poorest districts
of Madhya Pradesh. In every panchayat, the list of children
in the age group of 0-6 years was collected from the
anganwadi centres. From this list, 50 children were randomly
selected. Of the children included in the sample, 1879 were
in the age group of 6 months to 3 years. Weight,
height/length and MUAC of all children were recorded using
standard procedures with adequate quality assurance
measures. Z-scores were calculated using the WHO
Anthro for PC software.
57.2% of our sample children belonged to
tribal communities and 48% had BPL cards. 48% were girls.
The mean (SD) weight, height and MUAC were 8.6 (1.67) kg,
75.4 (8.42) cm, and 13.3 (1.0) cm, respectively. The overlap
between MUAC and WHZ is low. While 8.9% of our sample have a
WHZ <-3; 4.9% were with MUAC
£115mm.
Table I presents the performance of different
cut-offs of MUAC for diagnosing severe wasting. The
prevalence of stunting in children with MUAC
£11.5 cm
was greater than in those with WHZ
£3. In
our sample, 26% (47/181) of the children who had a WHZ
£3
were severely stunted compared to 60.9% (56/92) of children
with a MUAC £11.5.
Further 80.4% (74/92) children with MUAC
£11.5
were either severely stunted or severely underweight or
both.
TABLE I Cut-offs of Mid-upper arm Circumference in 1879 Study Children
Performance Parameter
|
MUAC Cut-Off (in mm) |
|
110 |
115 |
120 |
125 |
130 |
Sensitivity |
6.3% (10/160) |
17.5% (28/160) |
33.1% (53/160) |
46.9% (75/160) |
71.3% (114/160) |
Specificity |
98.5% (1693/1719) |
96.3% (1655/1719) |
85.0% (1462/1719) |
75.2% (1292/1719) |
49.6% (852/1719) |
Positive predictive value |
27.8(10/36) |
30.4(28/92) |
17.1(53/310) |
14.9(75/502) |
11.6(114/867) |
Negative predictive value |
91.9(1693/1843) |
92.6(1655/1787) |
93.2(1462/1569) |
93.8(1292/1377) |
94.9(852/898) |
Youden index |
0.05 |
0.14 |
0.18 |
0.22 |
0.21 |
LR for positive test |
4.1 |
4.7 |
2.2 |
1.9 |
1.4 |
LR for negative test |
1.0 |
0.9 |
0.8 |
0.7 |
0.6 |
LR: likehood ratio. |
Current guidelines in India for (active
and passive) screening of SAM by ASHAs and ANMs at the
community level advocate using "simple colored plastic
strips" with a MUAC cut-off of <115 mm [2,3]. Some issues
related to the dangers of using inappropriate screening
tools for referring SAM children have also been raised
earlier [4]. MUAC as a screening tool should not be
identifying less children than WHZ (the ‘gold standard’).
Stunting levels in India are higher than
African children and exceedingly so in our sample (57% had
heights <-3 SD) as the most marginalized (including tribals)
were purposively sampled. This brings us to question the
reliability and validity of MUAC as a screening tool in
chronically undernourished populations. The correlation of
weight-for-height and MUAC is hard to come by; one source
reported it as 60-70% [5]. MUAC has been considered to
correlate better with lean mass ratio (LMR is the ratio of
estimated mass of limbs to estimated mass of trunk) [6].
Further, pediatric body composition data is not yet
available for Indian populations.
Higher cutoffs of 140 mm and even 155 cm
have been proposed by Indian and Nigerian scholars,
respectively [7,8]. While MUAC is generally understood to be
age-independent, MUAC-for-height reference curves have been
considered to be a better alternative (height being measured
by WHO-modified QUAC sticks in field settings) [9]. In the
light of our findings, there is a need to introspect on the
suitability of current MUAC cut-offs. It is imperative that
the screening tool not be a reason for exclusion of those
who need institutional and rehabilitative support the most.
Acknowledgments: This survey was
conducted jointly by Vikas Samvad, Bhopal; Spandan, Khandwa
and Community Development Centre, Balaghat.
Contributors: SKJ and DS
conceptualized and led the data collection; all authors
contributed to the data analysis; DS and RD drafted the
initial manuscript; SKJ and VP provided critical inputs and
revised the draft; all authors have approved the final
draft.
Funding: Sir Dorabji Tata Trust;
Competing interests: None.
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