This presentation was made by Dr. Alan Pereira (Medicins Sans Frontiers) in the session on ‘Implementation research on delivery of preventive and curative interventions during early childhood’ at the POSHAN Conference "Delivering for Nutrition in India Learnings from Implementation Research", November 9–10, 2016, New Delhi. For more information about the conference visit our website: www.poshan.ifpri.info

1. Implementing Community Based
Management of Severe Acute Malnutrition
MSF experience in Bihar
Delivering for Nutrition in India: Learnings from Implementation Research
9-10th November, New Delhi
Dr. Alan Pereira
MBBS, MMed, MPH, DTMH
Medical Coordinator
MSF / Doctors Without Borders

2. MSF activity summary, Dharbhanga district, Bihar
• MSF has been active in CMAM in India since 2008
• Built upon decades of worldwide experience in acute nutritional crises
• Initial project started in Biraul province, Bihar
• Conventional standardised methodology for CMAM
• F75/100 for complicated cases in stablilisation center until fit for community management
• Uncomplicated cases treated with WHO pre-qualified F100 equivalent oil based paste
(Eezypaste, Compact, India)
• Ambulatory treatment provided at the APHCs and PHCs
• A more ´medicalised´ approach
• Initially combined MUAC & WHZ admission and discharge criteria
• Switched to MUAC only programming mid-way
• >17,000 children treated through the programme

3. Summary statistics (n=8274):
Females: 62.2%
6 -24 months age: 89.6%
Mean age: 16.4m
Scheduled Castes /OBC: 87.3%
Outside Biraul block: 51.8 %
Overall admissions at SC: 9.3%
Direct admission to SC: 1.5%
Severe Stunting (Mean Z): -3.9 ± 1.5 SD
Overall default rate: 37.2%
Overall mortality rate: 0.9%
AWG: 4.9 ± 3.4g/kg/d
LoS: 7.9 ± 5.9 wks
Subset analysis of both admission criteria
Old criteria (n=3873): Admission MUAC <110mm and/or WHZ <-3SD
Discharge MUAC >110mm and/or WHZ >-3SD
New criteria (n=4401): Admission MUAC <115mm
Discharge MUAC > 120mm

4. Admission trends follows seasonality and food security

5. MUAC & WHZ MUAC only Mean difference or RR
(95%CI)
p-value Total
Outcome
Cured 2069 (53.4%) 2526 (57.4%) - - 4595 (55.5%)
Dead 41 (1.1%) 36 (0.8%) RR 0.7 (0.5-1.1) 0.150 77 (0.9%)
Defaulter 1485 (38.3%) 1591 (36.2%) RR 0.92 (0.88-0.98) <0.01 3076 (37.2%)
Non-responder 278 (7.2%) 248 (5.6%) RR 0.8 (0.6-0.9) <0.01 526 (6.4%)
Treatment response if cured (SD) or (range)
Average Weight Gain (g/kg/day)
Median WG in g/kg/day (IQR)
4.7 ± 3.2
3.9 (2.5-6.2)
5.1 ± 3.7
4.2 (2.7-6.4)
0.34 (0.15-0.54)
-
<0.01 4.9 ± 3.4
4.1 (2.6-6.3)
Average Length of Stay (weeks)
Median LOS in weeks (IQR)
8.7 ± 6.1
7 (4-11)
7.3 ± 5.6
6 (3.3- 9.3)
-1.5 (-1.8, -1.2)
-
<0.01 7.9 ± 5.9
6 (4-10)
Average MUAC gain mm/day 0.34 ± 0.25 0.40 ± 0.30 0.06 (0.05-0.08) <0.01 0.38 ± 0.28
Proportion of children gain ≥15% BW 71% 56.2% RR 1.5(1.4-1.6) <0.01 62.9
Average % increase in BW 22.0 ± 12.9 19.4 ± 12.9 -2.6 (-3.4-1.9) <0.01 20.6 ± 13.0
Nutrition Status at discharge
Mean MUAC ± SD (mm) 121.9 ± 6.6 123.1 ± 2.4 1.2 (1.0-1.5) <0.01 122.6 ± 4.8
WHO W/H z-score mean ± SD -1.6 ± 0.7 -1.5 ± 0.8 0.05 (0.003-0.09) 0.035 -1.5 ± 0.8
WHO H/A z-score mean ± SD -4.0 ± 1.6 -3.7 ± 1.5 0.30 (0.21-0.39) <0.01 -3.9 ± 1.5
Subset analysis of both admission criteria

6. Risk factors for default
• High programme default rate: 3076 (37.2%)
• Higher default rates followed seasonality:
– Rains, floods, harvesting season, wedding season
Risk factors statistically associated with default:
• Younger age, W/H z score <-3 at time of admission, lower admission MUAC, Children living
outside Biraul block, not being referred by ASHA (aOR =10.2)
Factors not statistically associated with default:
• Sex, Caste, W/H z score ≥-2

7. What happens with MUAC only programming?
• ↑ females and younger children (age 6-24 months) admitted
• Slight ↓ in default rate (2%)
• ↓ in Length of Stay (1.5 weeks)
• Of the children who did not default from the programme:
• 88.4% were discharged as cured
• mean weight gain of 4.9 g/kg/day
• length of stay of 7.9 weeks
• Weight and MUAC recovery was
most rapid in the early stages of
admission
• MUAC and weight follow a near
identical route
• Suggests MUAC can be used
safely as a proxy indicator for
weight gain progress

8. What happens after exit with MUAC only programming - mortality?
• Mortality is low in Bihar context
• Suggests little difference in mortality between exit at 115mm or 125mm

9. What happens after exit with MUAC only programming – relapse
or self-recovery?
0.8%
deaths

10. What happens after exit with MUAC only programming – relapse
or self-recovery?
5.2%
deaths

11. What have we learned?
• SAM is associated with lower mortality in the Indian context (vs Africa)
– Absolute numbers mean it is still an emergency
• Large burden of SAM in India: CMAM appears workable
– Evidence emerging from India supports that already established across the world
– CMAM needs to be tailored to each state/region
– There is no ´one size fits all´ model, and we should stop trying to define this
– The burden of SAM still makes even CMAM challenging within the health system
– Need to focus on those who are failed by ICDS and those at highest risk of mortality
• MUAC is simple, valid and cheap tool to detect and monitor SAM in the community
– African mothers have been trained to screen their children!
– Need to move away from WHZ screening and programming?
• Defining the optimum length of stay: opportunity cost v/s benefit
• Reducing defaulter rate: role of ASHAs and frontline workers is crucial
• Active case detection strategy : ASHA training, age <2 year as target group using MUAC

12. What can MSF contribute?
• Work alongside state authorities to expand CMAM programmes
– Move to the ICDS level; ↑coverage and ↓ distance
– Simplification of existing CMAM standards will be critical
• Can CMAM be made more efficient in India?
– Optimum and simplified entry and discharge criteria
– Focus resources on those highest at risk of death, relapse and non-recovery
– Integrate seasonality into field level programming (eg ACD, follow up, LoS)
• Pending India specific research questions:
i. Is MUAC only programming adequate and the best way forward?
ii. How to focus resources on SAM children at highest risk of death?
iii. Are WHO worldwide admission and discharge criteria appropriate for Indian CMAM programming?
iv. What are the seasonal effects on default, relapse and death?
v. How can CMAM be scaled up effectively using state-specific models?
vi. How do we deal with stunting?

13. Thank You
www.msfindia.in
www.msf.org
Email: msfe-delhi-medco@barcelona.msf.org
Special thanks to the team
in Bihar and support from
health authorities without
whom none of this would
be possible.