Grellety et al. BMC Medicine (2017) 15:87
DOI 10.1186/s12916-017-0848-y

RESEARCH ARTICLE

Open Access

Effects of unconditional cash transfers on
the outcome of treatment for severe acutemalnutrition (SAM): a cluster-randomised
trial in the Democratic Republic of the
Congo
Emmanuel Grellety1*, Pélagie Babakazo2, Amina Bangana3, Gustave Mwamba4, Ines Lezama3,Noël Marie Zagre5 and Eric-Alain Ategbo3

Abstract
Background: Cash transfer programs (CTPs) aim to strengthen financial security for vulnerable households. Thispotentially enables improvements in diet, hygiene, health service access and investment in food production or
income generation. The effect of CTPs on the outcome of children already severely malnourished is not welldelineated. The objective of this study was to test whether CTPs will improve the outcome of children treated forsevere acute malnutrition (SAM) in the Democratic Republic of the Congo over 6 months.
Methods: We conducted a cluster-randomised controlled trial in children with uncomplicated SAM who received
treatment according to the national protocol and counselling with or without a cash supplement of US$40 monthly
for 6 months. Analyses were by intention to treat.
Results: The hazard ratio of reaching full recovery from SAM was 35% higher in the intervention group than thecontrol group (adjusted hazard ratio, 1.35, 95% confidence interval (CI) = 1.10 to 1.69, P = 0.007). The adjusted hazard
ratios in the intervention group for relapse to moderate acute malnutrition (MAM) and SAM were 0.21 (95% CI = 0.11
to 0.41, P = 0.001) and 0.30 (95% CI = 0.16 to 0.58, P = 0.001) respectively. Non-response and defaulting were lower
when the households received cash. All the nutritional outcomes in the intervention group were significantly better
than those in the control group. After 6 months, 80% of cash-intervened children had re-gained their mid-upper arm
circumference measurements and weight-for-height/length Z-scores and showed evidence of catch-up. Less than 40%of the control group had a fully successful outcome, with many deteriorating after discharge. There was a significant
increase in diet diversity and food consumption scores for both groups from baseline; the increase was significantly
greater in the intervention group than the control group.
Conclusions: CTPs can increase recovery from SAM and decrease default, non-response and relapse rates during andfollowing treatment. Household developmental support is critical in food insecure areas to maximise the efficiency of
SAM treatment programs.
Trial registration: ClinicalTrials.gov, NCT02460848. Registered on 27 May 2015.
Keywords: Malnutrition, Severe acute malnutrition, Cash transfer, Community-based management of acute malnutrition,
CMAM, Democratic Republic of the Congo, Cluster-randomised trial* Correspondence: emmanuel.grellety@gmail.com
1
Independent Consultant, Paris, France
Full list of author information is available at the end of the article© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Grellety et al. BMC Medicine (2017) 15:87

BackgroundChildhood malnutrition is a significant cause of ill healthand poor development worldwide. High-quality nutritionis essential in early childhood to ensure healthy growth,proper organ formation and function, a strong immune
system and neurological and cognitive development. Children with severe acute malnutrition (SAM) are at highrisk of morbidity and death [1]. There are estimated to be
19 million children younger than 5 years of age with SAM
worldwide, of whom more than 800,000 die annually [1].
Although considerable progress has been made in treating SAM [2–4], one way to reduce the burden of acutemalnutrition is to prevent its emergence among children byincreasing the resilience of poor and vulnerable households.
Poverty is generally acknowledged to be the major antecedent of malnutrition [5–7], and social protection andsafety-net interventions are important to protect maternaland child nutrition [8]. Recently, cash transfer programs(CTPs), which deliver direct unconditional or conditional
cash to households, are being tested in developing countries[9]. Such programs have been used in developed countries
for many years as the main method for poverty reduction
and social security. Although literature reviews of CTPs
used in humanitarian relief interventions have appeared
over the last few years, none has provided conclusive evidence of a sustained positive impact on child nutritional
status, and several comment that the ways in which theseinterventions have an impact are not clearly understood[10–17]. Even if an increasing number of studies havehighlighted a positive effect of CTPs in increasing diet diversity [18–20], food consumption [20, 21], health status[18, 22] and access to health care [19, 21], the evidence of a
resulting effect on child nutrition is mixed and inconclusive, particularly in sub-Saharan Africa [18, 19, 23]. Nevertheless, evidence is emerging to show that complementary
cash interventions could improve the results of nutritioninterventions. In Niger and Somalia, cash transfers provided to households with acutely malnourished children
improved recovery beyond the provision of ready-to-use
therapeutic foods (RUTF) [24, 25]. CTPs appear to reduce
the sharing of therapeutic foods and may improve the effectiveness of such interventions. It is also possible that theadditional cash could increase the cost-effectiveness of thenutrition intervention, if gains in effectiveness more thanbalance the added cost of the subvention.
There is a particular need to determine the effect of CTP
strategies and their impact on vulnerable households withmalnourished members among different target groups andcontexts. Most underlying causes of malnutrition are afunction of people’s resources and social context. Whathouseholds produce as well as the time they have to carefor dependent members are determined by a range of social, economic and political factors; these are thought to include the division of labour, gender inequality, educational

Page 2 of 19

opportunities and property and power relations. Whenhouseholds have more money, they can diversify their dietsby buying or growing food of a higher quality, being able toafford to attend the health centre and investing capital tocreate ongoing income-generating opportunities. Here, wehypothesised that additional cash will have a direct effect toimprove the final outcome of children enrolled in acommunity-based management of acute malnutrition(CMAM) program. Specifically, within the household the
cash would decrease intra-household sharing of the RUTF
and improve the food diversity and consumption. The cash
would improve the outcome of the malnourished child by
reducing death, morbidity, transfer to hospital, defaulting,relapse or other causes of failure. The child would havehigher rates of mid-upper arm circumference (MUAC) andweight gain and derived anthropometric indices.
This paper presents the findings from a clusterrandomised trial comparing the outcome of a standard
Outpatient Therapeutic Program (OTP) for SAM andinfant and young child feeding (IYCF) counselling withand without a monthly cash transfer over a 6-month
period in the Democratic Republic of the Congo (DRC).

Methods
Study design

The present study took place in the DRC, where around
two million children younger than 5 years old are affectedby SAM every year [26, 27]. This case load is higher than
the number of children suffering from SAM in all of the
Sahelian countries combined. Our cluster-randomised
controlled trial was carried out in Bipemba (a communeof 57.5 km2 in the city of Mbuji-Mayi; GPS 6°11'S 23°54'E)
in the Kasaï-Oriental province. There are 52 functional
health centres where management of SAM was established using the OTP module of the National Integrated
Management of Acute Malnutrition protocol. This setting
was selected for the following reasons. First, the socioeconomic homogeneity of the whole livelihood zone was confirmed by three baseline surveys: (1) a market chain
analysis [28], (2) a Household Economy Approach (HEA)
assessment [29] and (3) a Knowledge, Attitude and Practices (KAP) survey [30]. Second, the prevalence of severe
wasting, using World Health Organisation (WHO) criteria, in children between 6 to 59 months of age reported
in the province between 2013 and 2014 was above 2%[26]. Third, there are no major seasonal changes in thisarea which could affect the outcome of children discharged at different times during the study [31].
A cluster was defined by a health centre and its catchment area. There were 52 eligible health centres, of which
20 were selected. The health centres were selected at random by sequentially drawing, in public, sealed, numberedpapers from a basket in the presence of all 52 healthcentre representatives. A priori, in order to minimise

Grellety et al. BMC Medicine (2017) 15:87

contamination bias between clusters if a subsequent
health centre was drawn but was found to have a catchment area adjoining a health centre that had already been
selected, that centre was eliminated from the draw and afurther sealed paper drawn; the health centre representatives were aware of this procedure before the draw took
place. When the 20 health centres that were to be included in the trial were chosen, a second selection round
was conducted with each selected centre drawing a sealed
paper with either a 1 or 2 written on it to indicate towhich arm of the trial that centre would be entered. A
third selection was made in private when one of the arms
was assigned at random to receive standard SAM management plus counselling and the other arm standard SAM
management plus counselling plus cash transfer. In orderto detect an expected recovery rate of 70% after 8 weeks
and an expected difference between groups of 10%, with
an α-error = 5%, a β-error = 20% and an intra-class correlation of 0.001, a sample size of 1392 children was required. Assuming a study dropout of up to 15%, a total
sample size of 1600 children was projected with an average of 80 participants per cluster: 800 per arm. Because
we wished to avoid any confounding from temporal variation in the centres’ recruitment rate, we determined thepotential case load from the admissions during the previous year when there had not been any active screening of
the population. We then conducted an exhaustive, active
screening of the whole catchment area of each healthcentre in order to recruit the required number of children(about 4 per centre per day) over as short a time as possible. The staff in each health centre comprised the nurse
in charge and two Save the Children staff dedicated tocheck and collect the data. The study’s staff were supervised by Pronanut (the DRC Government nutrition
agency) and UNICEF. The study teams were trained intensively for 3 weeks prior to the start of the study by the
Principal Investigator, and the details of the national
protocol were revised with the nurses in charge of thecentres.
Inclusion criteria for the trial required participants tobe eligible for outpatient SAM treatment according to
the integrated management of acute malnutrition(IMAM) national protocol [32], have no congenital abnormality that may affect growth, no peanut allergy, be
resident in the catchment area of the health centre andbe available for the 6-month study period. A child was
eligible for selection if aged between 6 and 59 months
with a MUAC <115 mm and/or a weight-for-height/
length Z-score (WHZ) < –3Z [33] and/or with bilateraloedema. As treatment was as an outpatient at recruitment, the child also had to have a moderate or good appetite using a formal test meal of RUTF, an absence ofdefined clinical complications and no generalised (grade+++) oedema according to the national protocol [32].

Page 3 of 19

Patients with complications, a poor appetite or generalised oedema were referred for in-patient management
and were not subsequently enrolled after discharge. Patients who deteriorated after recruitment were maintained within the study; if they required admission tohospital, they were again followed after discharge. The
participant children were either detected through passive
screening during routine growth monitoring and outpatient clinic visits or through active screening in thecommunity using MUAC and oedema only; they werethen sequentially included in the trial until the preset
sample size was reached.
Ethical considerations

The objectives and procedures of the study were explained to heads of households or principal child caregivers before inclusion. An informed consent statement
was read aloud in the local dialect before consenting
adults signed or gave their fingerprint. It was emphasised that participation in the study was not a precondition for obtaining nutritional treatment and free
medical services. It was clearly stated that participants
were free to withdraw from the study at any time. The
protocol was approved by both the National EthicalCommittee of the School of Public Health from the Faculty of Medicine of University of Kinshasa and the Ministry of Public Health. The study was registered on
ClinicalTrials.gov as NCT02460848 and was performedin accordance with Good Clinical Practice (GCP) guidelines for clinical trials and according to the tenets of the
Declaration of Helsinki.
Interventions

In both study arms, children with SAM received treatment according to the IMAM national protocol for OTP
and counselling on IYCF [32]. At admission, children received a weekly take-home ration of RUTF supplying approximately 170 kcal per kilogram per day (Plumpy’nut®,
Nutriset) and routine medicines: routine anti-helminthic
treatment for those older than 1 year of age, 7 days ofamoxicillin and a vitamin A preventive dose; where indicated measles vaccination and anti-malarial treatment
were given. Weekly follow-up was conducted at the healthcentres. At baseline and at each visit the following were
performed: clinical history; physical examination; an appetite test; and anthropometric measurements using standard techniques (weight was measured with UNISCALE
electronic scales with a precision of 100 g; length with arigid wooden length board for children <87 cm and standing height for children ≥87 cm to the nearest 0.1 cm;
MUAC was measured with a non-stretchable tape with a
precision of 1 mm) [34]. They were then given the next
therapeutic ration until they reached discharge criteria.
Children were transferred to inpatient therapeuticGrellety et al. BMC Medicine (2017) 15:87

program (ITP) for any clinical complication, including
poor appetite, or meeting the
failure to respond totreatment’ criteria of the national protocol. Children weredischarged as recovered’ if they achieved WHZ ≥ −1.5
(WHO Growth Standards 2006) or MUAC ≥125 mm at
two consecutive visits and absence of bilateral oedema forat least 14 days. Non-response was defined as not meetingthe criteria for nutritional recovery by 12 weeks and default as failing to appear for two consecutive follow-up
visits confirmed by a home visit. Diet replacement andintra-household sharing of the RUTF were assessed using
a questionnaire with the household each week during thetreatment period. The IYCF counselling sessions took
place in the household during a home visit; they lasted approximately 1.5 h at admission and 45 min during subsequent visits. During the first 3 months, caretakers werealso invited to attend cooking sessions where recipes for
optimising the children’s meals with local ingredients were
demonstrated.
After discharge, children were followed up monthly:
medical history, physical examination, and anthropometry
were repeated at each visit until the end of the study. Observations were concluded 6 months after recruitment.
Thus, those who were under treatment for longer had ashorter post-discharge follow-up; as failure to respond was
defined as still being malnourished after 12 weeks of treatment, the minimum follow-up period was 14 weeks, sothat individual children had either three, four or fivemonthly follow-up assessments. Children were defined ashaving relapsed to SAM if they again reached any of thethree criteria defining SAM at least once during themonthly follow-up visits after being discharged as recovered. Children’s relapse to moderate acute malnutrition(MAM) was defined as the development of WHZ < –2.0
and ≥ –3.0 (WHO Growth Standards 2006) or MUAC
<125 mm and ≥115 mm (without bilateral oedema) atleast once during the monthly follow-up visits, without
the child developing SAM criteria during any otherfollow-up visit. ‘Unknown’ was defined as a defaulter notconfirmed by a home visit or with no information for thechild at the end of the trial. Withdrawal from the study
was defined as participants who elected to stop the study
for personal reasons.
At enrolment, trained health workers recorded the socioeconomic characteristics of the household and categorised it into wealth groups according to local
definitions of wealth and assets from the HEA assessment. The Household Dietary Diversity Scores (HDDSs)[35] and the Food Consumption Scores (FCSs) [36] werecollected at the first and last household visit; each ofthem included respectively 12 and 8 food groups. Individual Dietary Diversity Scores (IDDSs) [35, 37] included
8 food groups and were collected at each clinic visit, i.e.
weekly during treatment and monthly during follow-up.

Page 4 of 19

All participating caretakers from the intervention
group with one or more children with SAM received an
unconditional cash transfer of US$40 value each month
during treatment and follow-up for a total of 6 months(US$240 in total). We emphasised to the participantsthat they could use the funds in any way they saw fit in
a completely unrestricted way without any conditions
being imposed on how the cash was used. The cash was
distributed directly to the child’s caretaker for eachhousehold in the intervention group without informing
or involving the health centre staff. Each month the cash
was given from 10 separate administrative offices (separately located from the health centre) by two Save theChildren financial staff and two food security supervisors
attached to the study and completely independent of thehealth centre staff. The dispensing of the money was
spread throughout the month according to the patient's
admission date, so that daily attendance was minimised.
This mechanism was considered the most secure to preserve confidentiality and to avoid contamination bias;
electronic and other forms of cash transfer were notavailable in the area at the time of this study.
The amount given to each household was fixed and not
adjusted by the size of the household or the number ofmalnourished children. This amount was calculated toprovide 70% of the monthly household income for ahousehold of seven persons characterised as very poor
using HEA criteria [29]. Seventy percent of the averagemonthly expenditure would be sufficient to purchase all
the household’s food energy needs (2100 kcal per day perperson), the costs of food preparation and consumption(e.g. salt, soap, kerosene and/or firewood and basic lighting) and drinking water. The main household expenditures and sources of income were collected at enrolment;
how the household spent the additional cash provided by
the CTP was determined monthly during the study.
The cash transfer for a family of seven persons amounts
to 18 cents US per person per day. As the area is isolated
without reliable ground transportation of goods, it tends tobe more expensive than less isolated areas. The cash given
in other CTPs in the DRC varies from US$110 to US$135
monthly (except for one pilot project which dispensed
US$20.5 per month). The amount given in this study was
judged by the Emergency Department of UNICEF to be asustainable amount that could be supported by donors andother stakeholders if the program were to be scaled up; thehigher amounts given in other programs were judged to beunsustainable operationally [38].
Data analysis

All data were collected on standardised paper forms anddouble-entered into EpiData version 3.1 (EpiData Association) by staff unaware of the arm to which each healthcentre belonged. Any anthropometric data which fellGrellety et al. BMC Medicine (2017) 15:87

outside the limits of biological plausibility, using WHO criteria, were eliminated from the database [39]. Changes inheight of more than 5 cm, weight by more than 10% ofbody weight or MUAC of more than 20 mm between visitswere considered implausible data recording or measurement errors; in this case, the data from the previous or thelater visit were substituted. All data cleaning was performed
by a qualified individual who was not aware of the assignment, grouping or centres to which individual children
belonged. Potential anthropometric errors which wereslightly less gross were considered suspect’ and viewed
individually in relation to the other longitudinal values ofthat variable obtained with the rest of the child’s data
blinded in accordance with recent recommendations [40].
Obvious errors inconsistent with the other recordings ofthat variable were corrected (such as a single value showing
a loss of height with a subsequent measurement in agreement with the antecedent measurements), but other formsof suspect data were not altered. All analyses were byintention to treat at recruitment except the examination of
relapse, which was confined to children who reached thedischarge criteria as recovered’ (children who had not recovered could not relapse). Statistical significance was set atthe 5% level. All analyses were conducted in accordancewith Consolidated Standards of Reporting Trials (CONSORT) guidelines, extended to cluster-randomised trials,
using R software version 3.2.2.
Significance testing for differences between intervention
and control groups at baseline was performed using theindependent sample Student's t test for continuous variables and the chi-square test for categorical variables.
Differences in child recovery between trial arms of the
primary outcomes and relapse rate after discharge fromtherapeutic home treatment were tested by using a mixedeffects Poisson regression model, with health centre as random effect to estimate the incidence rate ratio (IRR). Next,
we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) using marginal Cox proportional hazards models
adjusted for baseline values, where the outcome variable istime from recruitment to the event (recovery) and the timescale is calendar week. All 95% CIs used robust estimates ofthe variance to account for clustering at the health centre
level as well as a shared-frailty model as developed by Andersen [41]. Potential interactions were assessed using apartial likelihood ratio test and a robust score test to calculate P values. We checked for possible deviation from the
proportional hazards assumption of the Cox regression
model by using the non-proportionality test on the basis of
the Schoenfeld residuals.
Comparisons between arms for the secondary outcomes(recovery, defaulter, transfer, death and relapse rates), time
to recovery, length/height change, IDDS, HDDS, FCS anddaily, weekly and monthly anthropometrics changes weremade by using linear mixed-effects models for continuous

Page 5 of 19

outcome variables, whereas mixed-effects logistic regression models were used for proportions, with health centre
as random effect and models adjusted for baseline values.
Analyses of anthropometric data which depended uponbody weight excluded children with oedema; oedematouschildren were included in all other analyses.
We produced and used Kaplan-Meier plots to estimate
the probability of failure to achieve and maintain nutritional recovery up to 6 months from enrolment. Survival
curves of two groups were compared using the Cox regression analyses with robust estimates of the varianceto account for clustering at the health centre level, and P
values were computed with the robust score test.

Results
Between 16 July 2015 and 31 July 2015, 1600 children
were admitted to the centres with a diagnosis of SAM;
119 (7.4%) children did not meet the inclusion criteria
and were excluded. Among those, some were admittedusing the IMAM unisex weight-for-height table butwere ineligible using sex-specific assessment, a few
lived outside the catchment area and others were referred directly to the hospital. Figure 1 shows the flow
and outcomes of the 1481 subjects in the two arms of
the study.
The control and intervention (cash) group’s baselinecharacteristics are shown and compared in Table 1. The
malnourished children in each group were not significantly different; in particular, the anthropometry was
similar between the groups. The IDDS becomes nonsignificant if a correction for multiple significance tests
is made P > 0.05 (but the IDDS was used for the adjusted
Cox analyses). The mothers had a higher school achievement in the intervention group, but were otherwise notdifferent. The HEA assessment showed that 75% of thehouseholds were classified as poor or very poor in botharms. The household size and number of children younger than 5 years were both greater in the intervention
group. However, there were fewer household members
younger than 5 years in the intervention group compared to the control group (5.3 vs 5.5), so that the increased number of young children, and hence thedependency ratio, in the intervention group would tend
to make this group more vulnerable to nutritional deficits. In both groups, less than 20% of the households
had an acceptable diet diversity score with 43% being in
the lowest category; 53% were considered to have pooror borderline food consumption. These results are
consistent with previous assessments conducted inKasaï-Oriental [42] and show that the households withSAM children are generally poor with a restricted diet,and most had an unacceptable food consumption score.
The baseline characteristics of all enrolled children
appeared balanced between the trial arms.

Grellety et al. BMC Medicine (2017) 15:87

Fig. 1 Trial flow chart of the study. Recovery was defined as a
WHZ ≥ −1.5 (WHO Growth Standards 2006) or MUAC ≥125 mm at
two consecutive visits and absence of bilateral oedema for at least
14 days. Non-response was defined as not meeting the criteria fornutritional recovery at 12 weeks and default as failing to appear for
two consecutive follow-up visits confirmed by a home visit. Defaulter
was defined as a patient absent for two consecutive visits andconfirmed as absent by a home visit at week 3. Relapse to MAM wasdefined as the development of a WHZ < –2.0 and ≥ –3.0 (WHO GrowthStandards 2006) or MUAC <125 mm and ≥115 mm (without bilateraloedema) at least once during the monthly follow-up visits without thechild developing SAM criteria during any other follow-up visit. Relapse
to SAM was defined as development of a WHZ < −3.0 (WHO GrowthStandards 2006) or MUAC <115 mm or presence of bilateral oedema
at least once during the monthly follow-up visits. Unknown was
defined as defaulter not confirmed by a home visit or as no
information for children at the end of the trial. Withdrawal fromthe study was defined as participants who had to stop the study
for personal reasons

The results of the treatment are given in Table 2. The
difference in the proportion of children reaching the recovery criteria was highly significant between the control
and intervention groups. This was partly due to children
who failed to respond to treatment and to defaulting being significantly lower for children whose households received the cash supplement than those who did not.
There was no difference in the mortality rate; however,the number of deaths recorded was very low and insufficient to show a statistical difference.
During treatment, changes in weight, WHZ, weight-forage Z-score (WAZ), body mass index Z-score (BMIZ) and
IDDS were all significantly greater in the intervention
group compared to the control group; however, there was
not a difference in the rate of increase in MUAC or height.

Page 6 of 19

Both groups gained less height than expected when compared with the standards for age of height-for-age Z-score(HAZ); the changes were not significant. The mean lengthof stay among children in the therapeutic program was
6.9 weeks (±2.5). It did not differ significantly between thegroups, although the median was 1 week shorter in theintervention group.
The Cox regression analyses (Table 3) showed that byweek 8 of treatment the cumulative probability of recovery was 29% higher in the intervention group than thecontrol group; it was 28% at week 10 and increased to
35% by the 12th week. Adjustment of the analysis for thesignificant baseline household and maternal characteristics increased the difference between the groups by atrivial amount. The mixed-effects Poisson regression
analysis gave similar results.
Table 4 shows the follow-up data of the children after
recovery. At this stage the control children were not receiving any further input, but the intervention group continued to receive US$ 40/month. Compared to the control
group, the cash-intervention group shows that the children from households with additional funds continued tohave a higher weight and MUAC gains, which resulted insignificant continued catch-up. The WAZ, WHZ, BMIZ,
mid-upper arm circumference for age Z-score (MUACZage) and mid-upper arm circumference for height Z-score(MUACZ-ht) changes are all significantly greater thanzero, showing true catch-up compared to the WHO standards. In contrast, the control group’s changes in Z-score
for these parameters were all negative; this was significantly less than no change for WHZ, and not different
from zero for the other indices. This shows that, on average, the control children were deteriorating after discharge
to become progressively less well-nourished with timeafter recovery and discharge from the treatment program.
There was no catch-up in height-for-age for either group,
so that the children remained stunted and the intervention did not improve linear growth over the time courseof this study. When MUAC is related to height, there wasalso considerable catch-up in the intervened children
compared with the control children.
This deterioration in the control children’s status postdischarge is confirmed by the proportion of children
who again developed MAM or SAM. Altogether 44% of
the control children deteriorated after treatment, 11% toa level where they would be readmitted for SAM. Mostof the children who relapsed to MAM did so with both
WHZ and MUAC. Furthermore, as there was no significant gain in height, the deterioration in WHZ for those
who relapsed to MAM or to SAM could not be ascribedto a disproportionate gain in height relative to weight.
For those who relapsed to SAM, only 8 of the 707 (1.1%)
intervened children relapsed anthropometrically by the
WHZ criterion and none by the MUAC criterion. The

Grellety et al. BMC Medicine (2017) 15:87

Page 7 of 19

Table 1 Child, maternal and household characteristics at inclusion by study group
Characteristics

Intervention arm

Number (%)

734

P valuea

Control arm(49.6)

747(50.4)

Child characteristics
Sex, female, n (%)

422(57.5)

429(57.4)

1.000

Age (months), mean (SD)

27.7

±14.7

27.0

±13.8

0.348

6–11 months

94(12.8)

94(12.6)

12–23 months

213(29.0)

214(28.6)

24–59 months

427(58.2)

439(58.8)

Elder

86(11.7)

69(9.2)

Second103(14.0)

109(14.6)

Third

126(17.2)

119(15.9)

Age category, n (%)

0.973

Sibling rank, n (%)

0.144

Fourth130(17.7)

114(15.3)

Fifth and more288

(39.2)

336(45.0)Do not know

1

(0.1)

0

(0.0)

Weight (kg), mean (SD)b

7.6

±1.7

7.5

±1.7

Height/length (cm), mean (SD)

76.8

±9.3

76.3

±9.1

0.311

WHZ, mean (SD)b

–3.1

±0.6

–3.0

±0.7

0.052

0.442

HAZ, mean (SD)

–3.4

±1.4

–3.5

±1.5

0.342

MUAC (mm), mean (SD)b

112.3

±4.6

111.9

±5.6

0.086

Bilateral oedema, n (%)

63

(8.6)

88

(11.8)

0.052

IDDS, mean (SD)

2.8

±1.0

2.7

±0.9

0.009

29.5

±7.7

29.6

±7.4

0.675

None

53

(7.2)

47

(6.3)

Primary school369(50.3)

466(62.4)

Secondary or high286

(39.0)

211(28.2)Do not know

26

(3.5)

23

(3.1)

Maternal characteristics
Age (years), mean (SD)
School achievement, n (%)<0.001

Marital status, n (%)

0.649

Monogamous marriage

505(68.8)

513(68.7)

Polygamous marriage

166(22.6)

173(23.2)

Other (single, widow, divorcee, separated)

40

(5.4)

45

(6.0)

Do not know

23

(3.1)

16

(2.1)

BMI, mean (SD)

21.1

±2.8

21.0

±2.7

0.423

Breastfeeding at time of enrolment, n (%)

243(33.1)

240(32.1)

0.729

Household size, mean (SD)

8.0

±2.5

7.6

±2.5

0.001

No. of children <5 years at home, mean (SD)

2.7

±1.3

2.1

±0.9

Household characteristics

Socioeconomic level (HEA criteria), n (%)<0.001
0.058

Very poor

378(51.5)

371(49.7)

Poor

184(25.1)

179(24.0)

Middle

68

(9.3)

103

(13.8)

Grellety et al. BMC Medicine (2017) 15:87

Page 8 of 19

Table 1 Child, maternal and household characteristics at inclusion by study group (Continued)
Better-off

104(14.2)

94(12.6)

HDDS, mean (SD)

4.1

±1.5

4.0

±1.5

HDDS category, n (%)

0.185
0.098

Lowest dietary diversity (≤3 food groups)

296(40.3)

339(45.4)

Medium dietary diversity (4–5 food groups)

309(42.1)

299(40.0)High dietary diversity (≥6 food groups)

129(17.6)

109(14.6)

43.7±12.19

43.5

±12.8

Poor (score 0–28)

59

(8.0)

68

(9.1)

Borderline (score 28.5–42)311(42.4)

322(43.1)

Acceptable (score >42)364

(49.6)

357(47.8)

FCS, mean (SD)FCS category, n (%)

0.768
0.676

a

From Student’s t tests for continuous variables and chi-square tests for categorical variables. Note: no corrections for multiple significance tests have been madein this table. With Bonferroni-Holm correction the child’s IDDS score becomes non-significant. It was however, retained as an adjustment in the Cox analyses; theother significances were not changedbChildren with oedema were excluded from the analysis for the assessment of weight and WHZ
HAZ height-for-age Z-score, BMI body mass index

main type of relapse in the intervened children was redevelopment of oedema. There were slightly more children
who relapsed with oedema in the control group (26 vs 16),
but the difference was not significant (χ2 = 2.7, P = 0.10). In
contrast, 47 (7.1%) of the control children re-developed anthropometric SAM having been discharged as cured.
The multivariate analysis results of the relative risk of
relapse are shown in Table 5. Here the data are adjusted
for baseline variables to take into account the initial foodconsumption score, the household size and the education of the mother to determine whether differences in
the households could account for the difference. The
cluster effect was also allowed for in case the performance of the different health centres could account forthe differences. The results remained highly significant
for relapse to MAM, with an IRR of 0.25 for the intervention group and a HR of 0.21. The more serious relapse to SAM was also highly significant, being less than

Table 2 Outcomes and progress of children with SAM during treatment by study group
P valuea

Parameters

Intervention arm

Control arm

Number (%)

734(49.6)

747(50.4)

Recovery, n (%)

707(96.3)

660(88.4)<0.001

Non-response, n (%)

5

(0.7)

23

(3.1)

0.016

Defaulter, n (%)

10

(1.4)

45

(6.0)

<0.001

Death, n (%)

4

(0.5)

6

(0.8)

0.759

Length of stay (week), mean (SD)

6.77

±2.31

7.04

±2.77

0.541

Length/height change (mm/week), mean (SD)

0.55

±1.15

0.39

±1.18

0.554

HAZ change (Z-score/month), mean (SD)

–0.15

±0.24

–0.18

±0.23

0.278

Weight change (gram/kg/day), mean (SD)b

4.37

±1.88

3.84

±1.98

0.021

b

WAZ change (Z-score/month), mean (SD)

0.79

±0.39

0.67

±0.41

0.011

WHZ change (Z-score/month), mean (SD)b

1.41

±0.57

1.25

±0.64

0.026

b

BMIZ change (Z-score/month), mean (SD)

1.49

±0.60

1.33

±0.68

0.038

MUAC change (mm/day), mean (SD)

0.30

±0.13

0.29

±0.16

0.552

MUACZ-age change (Z-score/month), mean (SD)

0.91

±0.39

0.86

±0.49

0.493

MUACZ-ht change (Z-score/month), mean (SD)

0.95

±0.41

0.92

±0.51

0.604

IDDS change, mean (SD)

1.30

±1.54

0.42

±1.29

0.008

a

Comparisons between arms were made by using linear mixed-effects models for continuous outcomes, whereas mixed-effects logistic regression models wereused for proportions, with health centre as random effectsbChildren with oedema were excluded from the analysis of parameters including weight
HAZ height-for-age Z-score, WAZ weight-for-age Z-score, BMIZ body mass index for age Z-score, MUACZ-age mid-upper arm circumference for age Z-score,
MUACZ-ht mid-upper arm circumference for height Z-score

Grellety et al. BMC Medicine (2017) 15:87

Page 9 of 19

Table 3 Cumulative recovery rate during therapeutic home treatment for SAM by study group
Nutritional recoverya

Intervention arm

Control arm

P value

Numberb

734

747

Number of events/child-weeks at risk

364/4000

307/3979

Incidence rate per 100 child-weeks (95% CI)

9.10 (8.17–10.00)

7.71 (6.85–8.58)

Incidence rate ratio (95% CI)c

1.18 (0.78–1.80)

1.00 (Reference)

0.414

Unadjusted HR (95% CI)

1.21 (0.80–1.81)

1.00 (Reference)

0.372

1.20 (0.78–1.81)

1.00 (Reference)

0.184

Numberb

734

747

Number of events/child-weeks at risk539/4592

455/4681

Week 6dAdjusted HR (95% CI)
Week 8

Incidence rate per 100 child-weeks (95% CI)

11.74 (10.75–12.73)

9.72 (8.83–10.61)

Incidence rate ratio (95% CI)c

1.18 (0.88–1.58)

1.00 (Reference)

0.128

Unadjusted HR (95% CI)

1.29 (0.96–1.74)

1.00 (Reference)

0.084

Adjusted HR (95% CI)d1.29 (1.01–1.68)

1.00 (Reference)

0.027

Numberb

734

747

Number of events/child-weeks at risk

645/4874

587/5081

Incidence rate per 100 child-weeks (95% CI)

13.23 (12.21–14.25)

11.55 (10.62–12.49)

Incidence rate ratio (95% CI)c

1.14 (1.01–1.27)

1.00 (Reference)

0.039

Unadjusted HR (95% CI)

1.27 (1.01–1.60)

1.00 (Reference)

0.046

1.28 (1.01–1.62)

1.00 (Reference)

0.011

Numberb

734

747

Number of events/child-weeks at risk

707/4970

660/5260

Week 10d

Adjusted HR (95% CI)
Week 12

Incidence rate per 100 child-weeks (95% CI)

14.23 (13.18–15.27)

12.54 (11.59–13.50)

Incidence rate ratio (95% CI)c

1.15 (1.03–1.27)

1.00 (Reference)

0.020

Unadjusted HR (95% CI)

1.34 (1.09–1.66)

1.00 (Reference)

0.026

Adjusted HR (95% CI)d1.35 (1.10–1.69)

1.00 (Reference)

0.007

a
Recovery was defined as a WHZ ≥ −1.5 (WHO Growth Standards 2006) or MUAC ≥125 mm at two consecutive visits and absence of bilateral oedema for atleast 14 daysb
Number of children contributing to unadjusted analysiscComputed by using a mixed-effects Poisson regression model, with health centre as random effects
d
From marginal Cox proportional hazards models where the outcome variable is time until first event and time is calendar week. 95% CIs used robust estimates ofthe variance to account for clustering at the health centre level, and P value was performed with the robust score test. Co-variates in the adjusted model included
the household size, the IDDS score and the school achievement of the motherone third for both IRR and HR, despite our including
the relapse to oedema in the model. For this analysis it
should be noted that the reference group for those who
relapsed to SAM included all children who remained normal and those who relapsed to MAM on the basis thatthose who developed MAM were also at risk of further
deterioration to SAM. If the children who developed
oedema are omitted from the analysis and we include only
those who relapsed anthropometrically, the incidence rateand hazard ratios are even lower. Adjustment for the baseline characteristics had almost no effect upon the results,
confirming that the two groups were balanced in terms ofchild, maternal and household characteristics.

In Table 6 we present the changes over the whole study
period from admission of the severely malnourished childto the end of the study 6 months later, by intention totreat. With the exception of height gain (and HAZ), all
the anthropometric indices showed a highly significant
benefit for the cash-intervention group compared to thecontrol group. The IRR and the Cox analysis are given in
Table 7 and confirm that the HR for the intervened children was less than three quarters of that for the children
whose families did not receive the cash supplement.
Thus, the cash intervention had a positive effect on all
aspects of the management of these children. There wasless defaulting, non-response to treatment, withdrawal,

Grellety et al. BMC Medicine (2017) 15:87

Page 10 of 19

Table 4 Results during follow-up after discharge among those who recovered by study group
P valuea

Parameters

Intervention arm

Number (%)

707(51.7)

660(48.3)

Relapse to MAM, n (%)b91

(12.9)

292(44.2)

Relapse to WHZ < –2 and ≥ –3

58

(8.2)

201

(30.5)

Relapse to MUAC <125 mm and ≥115 mm

57

(8.1)

279

(42.3)

Relapse to SAM, n (%)

24

(3.4)

73

(11.1)

Relapse to WHZ < -3

8

(1.1)

30

(4.5)

c

Control arm

Relapse to MUAC <115 mm

0

(0.0)

22

(3.3)

Relapse to oedema

16

(2.3)

26

(3.9)

<0.001<0.001

Length/height change (mm/week), mean (SD)

1.35

±1.33

1.45

±0.18

0.602

Weight change (gram/kg/day), mean (SD)d

0.86

±0.66

0.46

±0.72

<0.001

MUAC change (mm/day), mean (SD)

0.060

±0.05

0.012

±0.04

<0.001

HAZ change (Z-score/month), mean (SD)–0.018**

±0.18

0.003

±0.15

0.502

WAZ change (Z-score/month), mean (SD)d0.08**

±0.15

–0.01

±0.15

<0.001

WHZ change (Z-score/month), mean (SD)d0.13**±0.24–0.03**

±0.22

0.006

d

BMIZ change (Z-score/month), mean (SD)

0.14**±0.28– 0.02*

±0.23

0.017

MUACZ-age change (Z-score/month), mean (SD)0.132**±0.14– 0.001±0.14<0.001

MUACZ-ht change (Z-score/month), mean (SD)

0.141**

±0.14

0.005

±0.15

<0.001*P < 0.05 for change in standardised anthropometric parameter different from zero**P < 0.001 for change in standardised anthropometric parameter significantly different from zeroaComparisons between arms were made by using linear mixed-effects models for continuous outcomes, whereas mixed-effects logistic regression models wereused for proportions, with health centre as random effectsb
Relapse to MAM was defined as the development of a WHZ < –2.0 and ≥ –3.0 (WHO Growth Standards 2006) or MUAC <125 mm and ≥115 mm (without bilateraloedema) at least once during the monthly follow-up visits without the child developing SAM criteria during any other follow-up visitcRelapse to SAM was defined as development of a WHZ < −3.0 (WHO Growth Standards 2006) or MUAC <115 mm or presence of bilateral oedema at least once
during the monthly follow-up visitsdChildren with oedema were excluded from the analysis of parameters including weight

Table 5 Relapse rate after discharge from therapeutic home treatment for SAM by study group
Nutritional relapsea, bIntervention arm

Control arm

Number (%)

707 (51.7)

660 (48.3)

Number of events/child-weeks at risk

91/11,505

292/7813

Incidence rate per 100 child-weeks (95% CI)

0.79 (0.63–0.95)

3.74 (3.31–4.17)

Incidence rate ratio (95% CI)c0.25 (0.14–0.45)

1.00 (Reference)

P value

Relapsed to MAMa

<0.001

Unadjusted HR (95% CI)

0.21 (0.11–0.41)

1.00 (Reference)

0.005

Adjusted HR (95% CI)d0.21 (0.11–0.41)

1.00 (Reference)

0.001

Number of events/child-weeks at risk

24/12,761

73/11,558

Incidence rate per 100 child-weeks (95% CI)

0.19 (0.11–0.26)

0.63 (0.49–0.78)

Incidence rate ratio (95% CI)c

0.31 (0.19–0.49)

1.00 (Reference)

Relapsed to SAMb

<0.001

Unadjusted HR (95% CI)

0.31 (0.17–0.59)

1.00 (Reference)

0.003

Adjusted HR (95% CI)d0.30 (0.16–0.58)

1.00 (Reference)

0.001

a
Relapse to MAM was defined as the development of a WHZ < –2.0 and ≥ –3.0 (WHO Growth Standards 2006) or MUAC <125 mm and ≥115 mm (without bilateraloedema) at least once during the monthly follow-up visits without the child developing SAM criteria during any other follow-up visitb
Relapse to SAM was defined as development of a WHZ < −3.0 (WHO Growth Standards 2006) or MUAC <115 mm or presence of bilateral oedema at least once
during the monthly follow-up visitscComputed by using a mixed-effects Poisson regression model, with health centre as random effects
d
From marginal Cox proportional hazards models where the outcome variable is time until first event and time is calendar week. 95% CIs used robust estimates ofthe variance to account for clustering at the health centre level, and P value was performed with the robust score test. Co-variates in the adjusted model included
the household size, the IDDS score and the school achievement of the motherGrellety et al. BMC Medicine (2017) 15:87

Page 11 of 19

Table 6 Overall changes over the 6-month period by study group (intention to treat)
P valuea

Parameters

Intervention arm

Control arm

Number (%)

734(49.6)

747(50.4)

Length/height change (mm/week), mean (SD)

1.14

±1.00

1.17

±0.88

0.644

HAZ change (Z-score/month), mean (SD)

–0.05

±0.15

–0.04

±0.12

0.578

Weight change (gram/kg/day), mean (SD)b

1.86

±0.68

1.41

±0.74

<0.001b

WAZ change (Z-score/month), mean (SD)

0.25

±0.11

0.16

±0.12

<0.001

WHZ change (Z-score/month), mean (SD)b

0.45

±0.18

0.30

±0.18

0.001

b

BMIZ change (Z-score/month), mean (SD)

0.48

±0.21

0.33

±0.20

0.005

MUAC change (mm/day), mean (SD)

0.12

±0.04

0.08

±0.04

<0.001

MUACZ-age change (Z-score/month), mean (SD)

0.33

±0.11

0.22

±0.12

<0.001

MUACZ-ht change (Z-score/month), mean (SD)

0.35

±0.11

0.24

±0.12

<0.001IDDS change, mean (SD)

1.53

±1.44

0.59

±1.24

0.013

HDDS change, mean (SD)

2.34

±1.91

0.44

±1.41

<0.001Lowest dietary diversity (≤3 food groups)

66

(9.0)

194

(26.0)

Medium dietary diversity (4–5 food groups)

205(27.9)

358(47.9)High dietary diversity (≥6 food groups)

439(59.8)

126(16.9)

Lost to follow-up

24

(3.3)

69

(9.2)

FCS change, mean (SD)

19.9

±13.1

5.7

±13.1

Poor (score 0 - 28)

2

(0.3)

11

(1.5)

Borderline (score 28.5–42)

26

(3.5)

175

(23.4)

Acceptable (score >42)682

(92.9)

492(65.9)

24

(3.3)

69

(9.2)

HDDS category, n (%)

c<0.001

FCS category, n (%)<0.001<0.001c

Lost to follow-upaComparisons between arms were made by using linear mixed-effects models for continuous outcomes, whereas mixed-effects logistic regression models wereused for proportions, with health centre as random effectsbChildren with oedema were excluded from the analysis of parameters including weightcNinety-three participants were dead, defaulters, unknown or withdrew from the study

and relapse; faster gain in weight and MUAC, particularly after discharge; and actual catch-up in anthropometry relative to WHO standards. The cumulative effectof these factors on the final success or failure of the twodifferent arms of the program to affect the children’s
overall recovery up to 6 months is shown in the Kaplan-

Meier plot (Fig. 2). It is clear that the proportion of
failures’ starts to increase shortly after admission andsteadily increases so that by 12 weeks (the maximum
time of treatment before declaring the child a nonresponder) there was a substantial difference between
the groups. There followed a steep decline in the control

Table 7 Failure to achieve and maintain nutritional recovery over a 6-month period (intention to treat)
Failure of nutritional recoverya

Intervention arm

Control arm

Number (%)b734 (49.6)

747 (50.4)

Number of events/child-weeks at risk

144/16,408

457/13,257

Incidence rate per 100 child-weeks (95% CI)

0.88 (0.73–1.02)

3.45 (3.13 – 3.76)

Incidence rate ratio (95% CI)c

0.31 (0.21–0.46)

1.00 (Reference)

P value<0.001

Unadjusted HR (95% CI)

0.24 (0.15–0.39)

1.00 (Reference)<0.001

Adjusted HR (95% CI)d0.24 (0.15–0.39)

1.00 (Reference)<0.001a
Failure to achieve and maintain nutritional recovery during treatment and follow-up to 6 months from enrolment was defined as dead, non-response to treatment after
12 weeks, a defaulter, a relapse to either SAM or MAM or unknown at 6 monthsb
Number of children contributing to unadjusted analysiscComputed by using a mixed-effects Poisson regression model, with health centre as random effects
d
From marginal Cox proportional hazards models where the outcome variable is time until first event and time is calendar week. 95% CIs used robust estimates ofthe variance to account for clustering at the health centre level, and P value was performed with the robust score test. Co-variates in the adjusted model included
the household size, the IDDS score and the school achievement of the motherGrellety et al. BMC Medicine (2017) 15:87

Page 12 of 19

Fig. 2 Probability of failure to achieve and maintain nutritional recovery during treatment and follow-up to 6 months from enrolment in the twostudy groups. Failure of nutritional recovery was defined as dead, non-response to treatment after 12 weeks, a defaulter, a relapse to either SAM
or MAM or unknown at 6 months from enrolment. Children were right censored where their nutritional recovery was defined as a WHZ ≥ −1.5
(WHO Growth Standards 2006) or MUAC ≥125 mm and absence of bilateral oedema and they did not relapse. Survival curves of the two groups
were compared using the Cox regression analyses with robust estimates of the variance to account for clustering at the health centre level, and P
value was performed with the robust score test (HR = 0.24, 95% CI 015 to 0.39; P < 0.001)

group as children relapsed without the post-treatment
support given to the intervention group. In contrast, thedecline in the cash-intervention group was relatively
small and steady without any inflection at the time ofdischarge. Although by the time of discharge the successof the program was above Sphere standards for bothgroups, albeit much better in the cash group, the overalloutcome was dramatically different [43]. After 6 months,
80.4% of the children in the intervention group not
only recovered but remained so and on average hadsignificant catch-up in weight and MUAC comparedto WHO standards. In contrast, without the cash
intervention only 38.8% of the children had an entirely successful outcome.
As the baseline characteristics or health centre performance did not account for the differences, the question arises of whether the difference is due to the way inwhich the cash was used by the family, and whether it
was used specifically to support the child’s recovery orwhether it was used by the adults for other purposes.
The heads of household reported that they spent 67.2%of the money received to purchase food; 14.8% was dedicated to income-generating activities, followed by clothing (4.3%), water (2.8%), bill payment (2.3%), tuition fees
(1.8%), health costs (1.5%) and the remaining 5.3% onother activities and basic needs. The extra expenditure
on food should translate to an improvement of the quality of the diet for the index child and the whole family.
Table 6 shows the IDDS, HDDS and FCS at the end of
the study and the increments from the baseline values.
There was a significant increase in each of these indices offood quality during the course of the study in both groups(P < 0.001). However, the increment in the cashintervention group was very much greater than that in thecontrol group; the increment amounted to between 2.6
times for the index child’s dietary diversity to 5.3 times thecontrol group value for the household diet diversity score.
By the end of the study, 60% of the intervention group’s
households had achieved a high dietary diversity, whereas
only 17% of the non-intervened group had an acceptabledietary diversity at this time. Their food consumption
scores mirrored these data with only 3.8% of the group receiving cash having a poor or borderline score compared toabout 25% of the control group.
The comparison of the children who relapsed after recovery with those who maintained their recovery is given in
Additional files 1 and 2: Tables S1 and S2. The children
who relapsed all had highly significant losses of WAZ,
WHZ, BMIZ, MUAC-age and MUAC-ht. The increments
in diet diversity at both an individual and household level

Grellety et al. BMC Medicine (2017) 15:87

were significantly greater than zero, but very much lessthan those for the control group (P < 0.001).

Discussion
To our knowledge, this is the only study to assess the
direct effect of supporting households with cash during
the course of treatment and follow-up of children with
SAM. The analysis by intention to treat showed that the
cash supplement significantly improved all aspects oftreatment. Six months after admission, 80% of the children whose families were given additional support
remained within the normal range of WHZ and MUAC.
In contrast, less than 40% of those whose families did
not receive this additional support had a good outcome;this is not only statistically significant but also biologically highly significant.
For a child to develop severe acute malnutrition shows
the child, and presumably the siblings and whole household, to be at particular risk of death and the other serious consequences of being severely malnourished.
Follow-up of young children in a DRC community withgood medical facilities, but without specific managementof SAM, shows that about 5% with a WHZ < –3Z aredead within 3 months; this increases to 15 to 20% at < –4Z and 30% for those approaching –5Z [44–46].
The parents of malnourished children need to choose
between attending the health centre and all their othercompeting activities essential to the integrity of thehousehold. The poorer the household, the more important each individual economic activity is, because the survival of the household is fragile and continuously at risk
from even minor additional stress. If the parents consider that the treatment at the health centre is not helping, competing activities critical or the costs of attending
excessive, attending will not be a priority and they will
default. Thus, the defaulting rate is one measure of thequality of the service provided. Children are much lesslikely to recover if they default from treatment [47]. The
cash incentive could have altered the parents’ perception
and priorities so that there were far fewer defaulters in
the intervention group from the early stages of treatment. The financial incentive to remain in the programis an important aspect of a CTP.
During treatment the intervention group gained
weight faster than the control group, more children recovered and fewer failed to respond to treatment. Thisoccurred despite the same amount of RUTF being dispensed to the families and all other aspects of treatment
being the same apart from the cash delivery. The question arises of how the cash delivered to the family
effected this improvement in recovery from wasting. We
hypothesise that it was due either to the children receiving a higher proportion of the dispensed therapeutic
food or to the child getting a higher quality diet fromPage 13 of 19

the family pot or a combination of these factors. As
most of the funds were spent on food, it is unlikely thatthe immediate environment (water and sanitation for example) improved over a short time or that there was significantly more health-seeking behaviour.
We collected data on the sharing of the RUTF. The
data is not presented because we judged it to be very inaccurate. The respondents from both groups reported
very low levels of sharing within the family. In fact, compliance is usually poor in resource-poor settings with extensive sharing and there is an incentive for the families
to exaggerate the amount taken by the child in order toensure continued enrolment in the program [48, 49].
The mean energy cost of tissue deposition when acomplete diet is given is about 5 kcal/g of new tissue[50], and the requirement for maintaining body weight isabout 100 kcal/kg/day. Thus, as the rates of weight gain
were 3.8 to 4.4 g/kg/day, the intakes of these children
would average around 120 kcal/kg/day. Thus, the maximum average intake of the RUTF is around 70% of theamount dispensed; the actual intake is likely to be much
lower because some of the 120 kcal/kg taken by thechild will come from the family food and not from the
RUTF. Furthermore, if the RUTF were being taken exclusively, there would have been no other foods taken
and the IDDS would have shown no diversity at all. As
this was not the case, it confirms that the children wereindeed consuming less than the computed 70% of thedispensed RUTF. Unrealised low compliance can be amajor reason why randomised controlled trials reportfalse negative results [51]. It is possible that in our trial,
the extra cash, mostly spent on food, may have resulted
in less sharing of the RUTF, because other family members now had adequate wholesome food, but this is unlikely. It is possible that the responses given to theinvestigators who reported less sharing in other studies
were biased. However, the extra cash allowed the intervention households to purchase more expensive
nutrient-rich food items, as shown by the increments inthe food consumption and diet diversity scores. This,
combined with the IYCF counseling, may have resulted
in the whole family, including the index child, having amuch higher quality family pot to augment the RUTF.
Dietary diversity is associated with a child’s nutritional
status [52–54]. Globally less than one third of 6 to
23 month old children meet the minimum criteria for
dietary diversity, and only half receive the minimum
number of meals required to maintain health [54]. Dietary monotony has been described as the hallmark ofpoverty and poor nutrition, and indeed, typical child diets in communities and households with high rates ofmalnutrition are restricted, nutrient-deficient, monotonous and bulky [55]. It is not possible to link poor growthto specific nutrient deficiencies in epidemiologicalGrellety et al. BMC Medicine (2017) 15:87

studies because multiple nutrients are required for
growth, and deficient diets usually lack several nutrients
essential for growth.
In agreement with our results, CTPs in African countries and programs have reported an increase in household consumption with the majority of the additional
income from the cash intervention being spent on a variety of foods with a resulting improvement of diet diversity [18–21]. Cash transfers used in social protection
programs are different from cash transfers in an emergency. In our case, the transfer took place during a relatively short period, when vulnerability was particularlyhigh and the targeting criteria were clear; this may haveaffected how the money was used, because it was known
by the beneficiaries that the cash income would not besustained. The decision to use unconditional instead ofconditional cash transfer in our study was based on themarket analysis and KAP survey. Any consequentchange in diet quality will depend upon the type andcost of the foods that are available for purchase locally,
which will vary from place to place and from season toseason. The children’s intake will also depend on how
the households appreciate the foods that are usuallymore expensive than the family staple and how they apportion these foods between family members — in particular to the index child. The IDDS scores indicate thatthe individual children’s diet was greatly improved in theintervention group.
The most dramatic finding of our study was thedifference in the relapse rate between the children ofhouseholds who received ongoing support to the end of
the 6-month period and those who were simply returned
cured’ to their households. Relapse after discharge was
the main reason for failure of the program without the
cash transfer; of those admitted initially less than 40%
were deemed a success after 6 months. These are themost vulnerable children in the community; after treatment they are returned to exactly the same environmentand circumstances that they endured whilst becoming
malnourished. Although after treatment they are older
and healthier and thus more likely to demand and receive their share of the household food, they are still athigh risk of relapse without continued support.
The relapse rate without family support after dischargevaries greatly from study to study [47], but is often veryhigh. Examples of follow-up studies include two from
Malawi, one where moderately malnourished children
were followed for 12 months, only 63% remained wellnourished, 17% relapsed to MAM and 10% developed
SAM, 4% died and 7% were lost to follow-up [56]; in another 25% of the children died after discharge [57], although many of these children had HIV. In one study in
Bangladesh, 21% had either died or relapsed to SAM[58] after discharge, but in another study less than 1%

Page 14 of 19

relapsed although 2.3% died and 7.5% were lost tofollow-up [59]. Little has changed since the early studies,as 8.9% of children were dead within 3 months of discharge having been treated for SAM in a recent study
from Dhaka [60]. In Kenya, 1.5 years after discharge,
36% were dead and 28% were again underweight [61]. In
Burkina Faso, after 1.1 years the relapse rate was 15.5%
with 2.2% of children dying; in this study the loss tofollow-up was very high at 34% [62]. In all such studies
the relapse and death rates after discharge are minimum
values, because a higher proportion of thelost tofollow-up’ children are likely to be lost because of death.
The state of food security at discharge has a decisive
effect in countries with seasonality. This is elegantly
shown in a study from India. Discharge when food security is low was followed by a relapse rate of 35% to
MAM and 6.5% SAM; with moderate food security thisfell to 29% and 3.8% and with high food security to 8.7%
and 0.7% respectively [31]. These marked differences in
relapse rate following discharge show the critical effectfood security has on the subsequent fate of the children
treated for SAM.
Thus, the very large differences between the relapse
rates during food-insecure and food-secure times is artificially mirrored in the DRC with our study. The cash
converted the food-insecure households with restricted
diets and high levels of malnutrition to relatively foodsecure households in the same area at the same time as
the control group households remained food-insecure.
The difference in outcome for the two groups is clear.
The intervention children continued to catch up from –1.5Z weight-for-height and MUAC for age towards themedian; in contrast, the control group without thishousehold support significantly deteriorated with a highproportion of the children relapsing.
Other forms of post-discharge support may also have abeneficial impact on the further fate of the children; forexample, a quasi-controlled analysis showed a better outcome of MAM with prolonged supplementary feeding[63]. Cash may not be sufficient to give the best postdischarge outcome for the children; a preventive study in
Niger showed that cash plus highly nutritious supplements was superior to cash alone [64], although in ourstudy there did not appear to be significant anthropometric relapse (1.1%) in the intervened group given cash alone
post-discharge. There are inter alia differences in thetypes of food available, cultural practices, taboos, woman’sroles, seasonality and climate between the DRC and Niger.
This raises the question of the external validity of suchstudies. However, it is noteworthy that IYCF was not included in the Niger study, and it is possible that suchcounselling affected the choices, behaviour and disbursements of the recipient households in our study to thebenefit of the children.

Grellety et al. BMC Medicine (2017) 15:87

There was no difference by group in the proportion ofchildren developing oedema after discharge. We do nothave an explanation for this observation, but it may depend upon individual nutrients, such as sulphur or particular antioxidants, being generally deficient from thefoods available in this area [65].
Our study emphasises that the protocols specifically developed for short-term relief in emergency situations may
not be sufficient for use in impoverished communities in adevelopmental context. Having identified households witha malnourished child in the poorer sections of the society,giving short-term treatment to increase the weight of thechild is appropriate to prevent imminent death, but is insufficient when the cured’ children are simply returned totheir original poverty-stricken households without other interventions. In this context the emergency’ home treatment should be combined with developmental’ support
to the family that can be sustained in the longer term andlead to an improvement in their circumstances. It is unknown what happened to the children in this study when
the cash transfer program ceased, because the children
were not followed for logistical reasons. They may have deteriorated subsequently in the same way that the control
group deteriorated without family support. Given the dramatic findings of this study, in terms of relapse, longer term
follow-up should be investigated in further studies.
Although the increases in food diversity and food consumption scores were much greater in the intervention
group, there was also an improvement in the control
group which was significantly greater than their baseline
assessments. This could be due to temporal changes in
the whole community; alternatively, it could be ascribedto the IYCF counselling. Whatever the cause, it is clearthat IYCF counselling did not have a dramatic effect on
preventing deterioration or relapse in the control group.
Knowledge about IYCF by the household could notcompensate for the effect of poverty on their ability topurchase higher quality foods and presumably to follow
the advice given about young child feeding. However,IYCF was probably critical for the changes in the intervention group, who now had the resources to implement
the advice given during counselling.
It is important that distribution of cash respects theautonomy of households to decide how to best meettheir own requirements. However, we expect that any
significant effect on child nutritional status depends onthe duration of exposure to the intervention and theamount of cash transfer received per household, permonth, relative to the local costs and the local availability of high-quality food. Information on program costs,
although a key indicator for public health decisionmakers and program managers, was not an objective of
this study. Nevertheless, it usually costs less to get cashtransfers to people than in-kind assistance because aid

Page 15 of 19

agencies do not need to purchase, transport, store andthen pay to distribute relief goods. A four-country study
comparing cash transfers and food aid found that 18%
more people could be assisted at no extra cost if everyone received cash instead of basic food (i.e. not including fresh foods) [66]. In Ethiopia, the World Food
Programme found cash to be more cost efficient thanfood aid by 25–30% [9]. Furthermore, when delivering
assistance in conflict zones, especially food aid, there are
additional difficulties. For example, in Somalia, only 35%
of food aid budgets went to beneficiaries, compared to
85% of cash transfer budgets [67].
In the DRC, and other large countries with a relatively
scattered population and poor transport, preventive programs like general food distribution or blanket feeding are
logistically too difficult and expensive and so have neverbeen implemented country-wide. Supplementary feeding
programs for treating MAM are sporadic and not functional in most of the DRC. In this context, CTPs should
be considered as an alternative to in-kind assistance andservices or as a complement to more traditional interventions. Normally national protocols for treating SAM statethat children who have recovered from SAM should beenrolled in a supplementary feeding program to befollowed and receive a fortified food ration for at least
3 months after discharge. This provision is frequently unrealistic. The results of the present study, which showsthat a cash supplement effectively prevents relapse and allows for continued catch-up, demonstrate CTP to be a viable and more easily implemented alternative to a
supplementary feeding program [68, 69]. Furthermore, if
the cash is used to generate an ongoing income throughminor entrepreneurial activities or other capital expenditures, then these poorest of families and their at-risk children may be helped in the longer term. The emergency
non-governmental organisations (NGOs) which spearheaded the community management of SAM should consider adopting a developmental approach after treatmentof the children with SAM, to alleviate poverty for suchfamilies rather than simply dispensing food andantibiotics.
Most programs for managing severely malnourishedchildren do not automatically include a follow-up program and only report the (usually) excellent recovery’rates. Such would have been the results of both arms of
our study. By including the follow-up in the assessmentof our program, we have shown that many reports canbe misleading in terms of the overall success of a program. We strongly recommend that such continued support and its evaluation should be routine for all CMAM/
IMAM programs in relatively stable countries.
This study showed that there was no catch-up inheight-for-age in either group. Thus, the program had
no effect on stunting. It may be that increased rates ofGrellety et al. BMC Medicine (2017) 15:87

normal growth, indicated by a height increase, are delayed beyond the study period, as observed by Heikens
et al. [70]. Nevertheless, in none of the follow-up studies
quoted above has a significant height increment been
described. Studies of children involved in programs toprevent malnutrition have shown that the intervention
prevents deterioration in height-for-age among the beneficiaries [71] but without evidence of catch-up. Nevertheless, catch-up has been shown, only after fullrecovery in weight-for-height, when high-quality dietsare given under supervision [72]. A change in home environment has frequently led to catch-up in height [73],but rarely if the home environment does not change[74]. Thus, although our program was very successful incorrecting wasting and preventing relapse, there was neither a significant effect on stunting nor on the recurrence of oedematous malnutrition. The nutritional andother requirements to correct these deficits appear not
to depend upon or be prevented by the interventions
tested in this study.
Limitations of the study

It was not possible, of course, to blind the participants
to the transfer of cash into their hands. Indeed, thisintervention might have been the incentive to continue
participation in the study and may have affected the results by preventing defaulting which was then analysedby intention to treat so that all defaulting children were
included in the analyses and, where possible, followed
up with home visits. Although the health centre staff
were not involved in any way with the cash transfer, it isdifficult on a practical level to prevent the service
personnel from becoming aware of who received theintervention and who did not.
As the participants were not blinded, it is possible thatthe intervention group’s respondents were more disposed towards the study than those of the control group,
which could have affected the answers they gave to thequestionnaires. We do not think that this is likely tohave biased the results, as they both reported clearly erroneous reports of RUTF sharing to the same extent,
and there were similarities of the two groups’ responses
at baseline. Nevertheless, it was not possible to verify theaccuracy of the other questionnaire data with direct
home observations. Clearly, this potential bias will notaffect the anthropometric data.
There is likely to have been an ascertainment bias so thatthe patients were not properly representative of severe malnutrition in the community, because those who were recruited by MUAC criteria were selected from community
screening and those who were selected by WHZ criteria
were taken from attendees at the health centre. Survey datafrom the DRC indicate that 32% of the severely malnourished children by WHZ have a MUAC above the cut-off

Page 16 of 19

point for SAM [75]. They will be under-represented in thepatient population. If the WHZ children are more severely
ill than those identified by MUAC, it could account for thefact that none of the intervention children relapsed using
MUAC criteria, but 1.1% relapsed using WHZ criteria.
However, this difference is quite trivial compared to the difference in the two arms of the study, so we do not consider
this to have resulted in a major bias.
As there is no real seasonality in this location and as
the two arms were conducted concurrently, we do notconsider the time of discharge as a cause of bias. The
data for the non-intervened group are consistent withthe reports of other programs of outpatient treatment inmany other locations, and their rates of relapse are similar to those of many other reports. We therefore consider the study to have reasonable external validity forthe control group. The effect of the intervention, however, is dependent upon variables such as the availabilityof varied nutrient-dense products on the market, reasonable market access for the participants and reasonable
price stability; therefore, the external validity of theintervention arm needs to be confirmed in other contexts with differing potential effectors.
This research demonstrates the benefits of cash assistance; any potential negative impacts were not consideredor examined (such as the extra cash in the society increasing market prices to the detriment of the control
group). However, one possible negative effect of a therapeutic treatment program is that the child will be purposefully kept malnourished in order to receive thebenefit. This is not thought to be a problem in thepresent study, as it was made clear to the beneficiariesof the intervention arm that they would receive the cashtransfer monthly for 6 months independently of the recovery rate of the child, provided that they did not default from the program. Thus, the cash is likely to havedeterred defaulting (a good outcome), but there was no
incentive to maintain the child in a malnourished state
to continue to benefit from the program. It is possiblethat such an effect was present for some children in thecontrol arm of the study; however, the mean length ofstay under treatment was not different between thegroups. If this did occur, it is a further benefit of the
cash transfer for the intervention group.
The study does not provide evidence of a greater positive effect of providing cash assistance rather than in-kindor other forms of assistance. The study estimates the impacts of cash when US$240 was delivered per household
over the course of 6 months to children with SAM. The
findings should not be extrapolated to different amounts
or time frames. Moreover, this trial was conducted in asemi-urban area of the DRC without marked seasonalvariation that had during the study a relatively poor foodinsecurity and a high prevalence of wasting. Therefore,

Grellety et al. BMC Medicine (2017) 15:87

our results need to be extrapolated with care and interpreted within the given context.

Conclusions
This study shows that giving cash in impoverished communities can be effective in improving the outcome of children
treated for SAM and provides a safety net that prevents relapse and allows for continued catch-up in weight and
MUAC up to 6 months from admission. This very positive
impact over a relatively short time on the children’s nutritional status is most easily explained by the improved access to high-quality food, enabling households not only tomeet minimal needs for survival but also to diversify theirdiet within a society characterised by a high level of endemic malnutrition. In the DRC, where supplementary
feeding interventions are logistically difficult and expensive
to implement, to reduce acute malnutrition and improve its
coverage, carefully designed cash transfer is shown to be a
viable and highly effective intervention. Such innovative
programs merit further investigation in different contexts
to assess their cost-effectiveness compared to other interventions. Nutritional rehabilitation programs, often using
the procedures derived directly from emergency relief operations, should always consider the feasibility of incorporating developmental programs such as micro-credit, homegardening, etc. into their procedures to enable the gains
from acute nutritional intervention to be sustained.
Additional files
Additional file 1: Table S1. Changes in diet diversity and foodconsumption score between children who relapsed and recovered.
(DOC 35 kb)
Additional file 2: Table S2. Changes in anthropometric indicators
between children who relapsed and those who did not relapse
after discharge from therapeutic home treatment for severe acutemalnutrition. (DOC 51 kb)
Abbreviations
BMIZ: Body mass index for age Z-score; CI: Confidence interval;
CMAM: Community-based management of acute malnutrition; CTP: Cash transfer
program; DRC: Democratic Republic of the Congo; FCS: Food Consumption Score;
HAZ: Height-for-age Z-score; HDDS: Household Dietary Diversity Score;
HEA: Household Economy Approach; HR: Hazard ratio; IDDS: Individual Dietary
Diversity Score; IMAM: Integrated management of acute malnutrition;
ITP: Inpatient therapeutic program; IYCF: Infant and young child feeding;
KAP: Knowledge, Attitude and Practices survey; MAM: Moderate acutemalnutrition; MUAC: Mid-upper arm circumference; MUACZ-age: Mid-upper arm
circumference for age Z-score; MUACZ-ht: Mid-upper arm circumference forheight Z-score; NGO: Non-governmental organisation; OTP: Outpatient therapeutic
program; RUTF: Ready-to-use therapeutic foods; SAM: Severe acute malnutrition;
WAZ: Weight-for-age Z-score; WHZ: Weight-for-height /length Z-score
Acknowledgements
We thank all the families and children who participated in this study. We thankthe Save the Children and UNICEF teams in Mbuji-Mayi and Kinshasa for their
dedication and work on ensuring the data collection in this study. In particular,
we wish to thank Consolata Buhendwa (UNICEF), Guy Clarysse (UNICEF), Eric
Mabanza (Save the Children) and Arsène Niangoran (Save the Chidlren). We also
wish to acknowledge the support of Prof. Michael H. Golden for his advice

Page 17 of 19

throughout the study and for reviewing the manuscript. We thank theGovernment of the UK (Department for International Development (DFID)) for
supporting this work. We are grateful to the Ministry of Health of DRC, the KasaïOriental province authorities, the Pronanut, the health care providers, thecommunity health workers and all others who facilitated our work.
Funding
This study was co-ordinated by UNICEF DRC with DFID funding support. The
funding agency had no role in the design of the study, data collection andanalysis or interpretation of the results.
Availability of data and materials
The datasets used and/or analysed during the current study are available
from the corresponding author on reasonable request.
Authors’ contributions
The authors’ responsibilities were as follows. EG designed the study,
conducted the research, analysed the data and wrote the manuscript. EAA,
IL, AB and NMZ conceived and designed the research with EG and revised
the manuscript. GM supervised the field staff and collection of data andrevised the manuscript. PB conducted the research, analysed the data andrevised the manuscript. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable.
Ethics approval and consent to participate
The objectives and procedures of the study were explained to heads ofhouseholds or principal child caregivers before inclusion. An informed consent
statement was read aloud in the local dialect before consenting adults signed orgave their fingerprint. It was emphasised that participation in the study was not a
pre-condition for obtaining nutritional treatment and free medical services. It was
clearly stated that participants were free to withdraw from the study at any time.
The protocol was approved by both the National Ethical Committee of the Schoolof Public Health from the Faculty of Medicine of University of Kinshasa and theMinistry of Public Health. The study was registered on ClinicalTrials.gov as
NCT02460848 and was performed in accordance with Good Clinical Practice (GCP)
guidelines for clinical trials and according to the tenets of the Declaration of
Helsinki.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.
Author details
1
Independent Consultant, Paris, France. 2Kinshasa School of Public Health,
University of Kinshasa, Kinshasa, Democratic Republic of the Congo. 3United
Nations International Children Emergency Fund, Kinshasa, Democratic
Republic of the Congo. 4Save the Children United Kingdom, Kinshasa,
Democratic Republic of the Congo. 5United Nations International Children
Emergency Fund West and Central Africa Regional Office, Dakar, Senegal.
Received: 22 November 2016 Accepted: 30 March 2017

References
1. Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M,
Ezzati M, Grantham-McGregor S, Katz J, et al. Maternal and childundernutrition and overweight in low-income and middle-income
countries. Lancet. 2013;382:427–51.
2. World Health Organization, World Food Programme, United Nations System
Standing Committee on Nutrition, United Nations Children's Fund.
Community-based management of severe acute malnutrition. A jointstatement by the World Health Organization, the World Food Programme,
the United Nations System Standing Committee on Nutrition and theUnited Nations Children's Fund. Geneva: World Health Organization; 2007.
http://www.who.int/nutrition/topics/Statement_community_based_man_
sev_acute_mal_eng.pdf. Accessed 16 Jan 2017.

Grellety et al. BMC Medicine (2017) 15:87

3.

4.

5.
6.
7.
8.

9.

10.

11.

12.
13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

World Health Organization, United Nations Children's Fund. WHO child
growth standards and the identification of severe acute malnutrition in
infants and children. A joint statement by the World HealthOrganization and the United Nations Children's Fund. Geneva: World
Health Organization; 2009. http://apps.who.int/iris/bitstream/10665/
44129/1/9789241598163_eng.pdf. Accessed 16 Jan 2017.
World Health Organization. Guideline update: technical aspects of the
management of severe acute malnutrition in infants and children. Geneva:
World Health Organization; 2013. http://apps.who.int/iris/bitstream/10665/
95584/1/9789241506328_eng.pdf. Accessed 16 Jan 2017.
Sen A. Poverty and famines: an essay on entitlement and deprivation. Oxford:
Oxford University Press; 1981.
Young H, Jaspars S. Nutrition, disease and death in times of famine. Disasters.
1995;19(2):94–109.
Devereux S. Sen's entitlement approach: critiques and counter-critiques. Oxf
Dev Stud. 2001;29(3):245–63.
Ruel M, Alderman H, the Maternal and Child Nutrition Study Group. Nutritionsensitive interventions and programmes: how can they help to accelerate
progress in improving maternal and child nutrition? Lancet.
2013;382:536–51.
The High Level Panel on Humanitarian Cash Transfers. Doing cash
differently: how cash transfers can transform humanitarian aid. Overseas
Development Institute 2015. http://www.odi.org/sites/odi.org.uk/files/odiassets/publications-opinion-files/9828.pdf. Accessed 16 Jan 2017.
Lagarde M, Haines A, Palmer N. The impact of conditional cash transfers on
health outcomes and use of health services in low and middle income
countries. A systematic review. Cochrane Database Syst Rev. 2009;4, CD008137.
Leroy JL, Ruel M, Verhofstadt E. The impact of conditional cash transfer
programmes on child nutrition: a review of evidence using a programme
theory framework. J Dev Eff. 2009;1(2):103–29.
Adato M, Hoddinott J. Conditional cash transfers in Latin America. International
Food Policy Research Institue. Baltimore: Johns Hopkins University Press; 2010.
Fernald LCH, Gertler P, Hidrobo M. Conditional cash transfer programs: effects
on growth, health, and development in young children. In: Maholmes V, Kings
RB, editors. The Oxford handbook of poverty and child development. New
York: Oxford University Press; 2012.
Glassman A, Duran D, Fleisher L, Singer D, Sturke R, Angeles G, Koblinsky M.
Impact of conditional cash transfers on maternal and newborn health. J
Health Popul Nutr. 2013;31(4 Suppl 2):S48.
Van de Bold M, Quisumbing AR, Gillespie S. Women’s empowerment andnutrition: an evidence review. IFPRI discussion paper 01294. Washington,
DC: International Food Policy Research Institute (IFPRI); 2013.
Owusu-Addo E, Cross R. The impact of conditional cash transfers on childhealth in low- and middle-income countries: a systematic review. Int J
Public Health. 2014;59(4):609–18.
de Groot R, Palermo T, Handa S, Ragno LP, Peterman A. Cash transfers andchild nutrition: what we know and what we need to know. Innocenti
Working Paper No.2015-07, UNICEF Office of Research, Florence, 2015.
http://www.unicef-irc.org/publications/pdf/
Social%20protection%20and%20nutrition_layout.pdf. Accessed 16 Jan 2017.
Miller CM, Tsoka M, Reichert K. Impact evaluation report: external evaluationof the Mchinji Social Cash Transfer Pilot. Center for International Health andDevelopment, Boston University School of Public Health, Boston, MA, andCentre for Social Research University of Malawi, 2008. http://www.unicef.
org/malawi/MLW_resources_impactsocialcashtrf.pdf. Accessed 16 Jan 2017.
Oxford Policy Management. Kenya Hunger Safety Net Programme monitoringand evaluation component: impact evaluation final report: 2009 to 2012.
Oxford, UK, 2013. http://www.oecd.org/derec/unitedkingdom/Evaluation-ofthe-Hunger-Safety-Net-Programme-Kenya.pdf. Accessed 16 Jan 2017
Seidenfeld D, Handa S, Tembo G, Michelo S, Harland Scott C, Prencipe L.
The impact of an unconditional cash transfer on food security and nutrition:
the Zambia Child Grant Programme. 2014. http://citeseerx.ist.psu.edu/
viewdoc/download?doi=10.1.1.974.8715&rep=rep1&type=pdf#page=48.
Accessed 16 Jan 2017.
Adato M, Bassett L. Social protection to support vulnerable children andfamilies: the potential of cash transfers to protect education, health andnutrition, AIDS Care: Psychological and Socio-medical Aspects of AIDS/HIV
2009;21:S1:60–75.
Handa S, Peterman A, Seidenfeld D, Tembo G. Income transfers and maternal
health: evidence from a national randomized social cash transfer program in
Zambia. Health Econ. 2016;25(2):225–36.

Page 18 of 19

23. Agüero JM, Carter MR, Woolard I. The impact of unconditional cash transfers
on nutrition: the South African Child Support Grant. Southern Africa Labourand Development Research Unit working paper number 06/08. Cape Town:
SALDRU, University of Cape Town; 2006.
24. Poulsen L, Fabre D. Cash transfer for protection of blanket feeding: Maradi
and Tahoua Regions: independent final evaluation. 2011. UNICEF, http://
www.unicef.org/evaluation/files/HQ_2010-007_UNICEF_Cash_Transfer_-_
Final_Evaluation.pdf. Accessed 16 Jan 2017.
25. Dunn S, Brewin M, Scek A. Cash and Voucher Monitoring Group final
monitoring report of the Somalia Cash and Vvoucher Transfer Programme.
Phase 2: April 2012–March 2013. Humanitarian Policy Group/Overseas
Development Institute, 2012. http://www.odi.org/sites/odi.org.uk/files/odiassets/publications-opinion-files/8521.pdf. Accessed 16 Jan 2017
26. Ministère du Plan et Suivi de la Mise en œuvre de la Révolution de laModernité, en collaboration avec le Ministère de la Santé Publique. Enquête
Démographique et de Santé, République Démocratique du Congo (EDSRDC) 2013–2014. Rockville: Measure DHS; 2014. http://pdf.usaid.gov/pdf_
docs/PBAAB112.pdf. Accessed 16 Jan 2017.
27. United Nations International Children Emergency Fund. Integrated
management of acute malnutrition programme and stocks report. West
and Central Africa Regional Office IMAM report, 2015. https://www.
humanitarianresponse.info/system/files/documents/files/4eme_trim_-_unicef_imam_final_report_year_2015.pdf. Accessed 16 Jan 2017
28. Lundy M, Gottret MV, Ostertag C, Best R, Ferris S. Participatory market chain
analysis for smallholder producers. Good practice guide 4 (No. 357). The
International Centre for Tropical Agriculture, 2007. http://www.crs.org/sites/
default/files/tools-research/participatory-market-chain-analysis-forsmallholder-producers.pdf. Accessed 16 Jan 2017.
29. Holzmann P, Boudreau T, Holt J, Lawrence M, O’Donnell M. The household
economy approach: a guide for programme planners and policy-makers.
2008. Save the Children UK, https://www.savethechildren.org.uk/sites/
default/files/images/HEA_Guide.pdf. Accessed 16 Jan 2017.
30. Kaliyaperumal K. Guideline for conducting a knowledge, attitude andpractice (KAP) study. AECS Illumination. 2004;4(1):7–9.
31. Burza S, Mahajan R, Marino E, Sunyoto T, Shandilya C, Tabrez M,
Kumar K, Jha A, Mathew P, Salse N, et al. Seasonal effect and longterm nutritional status following exit from a community-based
management of severe acute malnutrition program in Bihar, India. Eur
J Clin Nutr. 2016;70:437–44. http://www.nature.com/ejcn/journal/v70/
n4/full/ejcn2015140a.html. Accessed 17 Jan 2017.
32. Ministère de la Santé Publique, Secrétariat General. Protocole national deprise en charge intégrée de la malnutrition aigüe (PCIMA) République
Démocratique du Congo, 2012. http://reliefweb.int/sites/reliefweb.int/files/
resources/Situation_Report_258.pdf. Accessed 16 Jan 2017.
33. WHO child growth standards. Length/height-for-age, weight-for-age,weight-for-length, weight-for-height and body mass index-forage: methods
and development. Geneva: World Health Organization, 2006. http://www.
who.int/childgrowth/standards/Technical_report.pdf. Accessed 16 Jan 2017.
34. World Health Organization. Nutrition for Health. WHO child growthstandards: growth velocity based on weight, length and headcircumference: methods and development. World Health Organization,2009. http://www.who.int/childgrowth/standards/velocity/technical_report/
en/index.html. Accessed 16 Jan 2017.
35. Swindale A, Bilinsky P. Household Dietary Diversity Score (HDDS) for
measurement of household food access: Indicator Guide version 2.
Washington, DC: Food and Nutrition Technical Assistance Project(FANTA), Academy for Educational Development, 2006. http://www.
fantaproject.org/sites/default/files/resources/HDDS_v2_Sep06_0.pdf.
Accessed 16 Jan 2017
36. World Food Programme, Vulnerability Analysis and Mapping Branch. Foodconsumption analysis calculation and use of the food consumption score in foodsecurity analysis: Version 1, 2008. http://documents.wfp.org/stellent/groups/
public/documents/manual_guide_proced/wfp197216.pdf. Accessed 16 Jan 2017.
37. Kennedy G, Ballard T, Dop MC. Guidelines for measuring household andindividual dietary diversity. 2011. Food and Agriculture Organization of theUnited Nations, http://www.fao.org/docrep/014/i1983e/i1983e00.pdf. Accessed
16 Jan 2017.
38. Erba G. UNICEF’s Alternative Responses for Communities in Crisis (ARCC)
programme – the largest humanitarian multi-purpose unconditional cashtransfer program in the DRC. The Cash Learning Partnership 2016. http://
www.cashlearning.org/news-and-events/news-and-events/post/223-

Grellety et al. BMC Medicine (2017) 15:87

39.

40.
41.

42.

43.
44.

45.

46.

47.

48.

49.

50.
51.

52.

53.

54.

55.
56.

57.

58.

59.

unicefas-alternative-responses-for-communities-in-crisis-arcc-programme-athe-largest-humanitarian-multi-purpose-unconditional-cash-transferprogram-in-the-drc. Accessed 16 Jan 2017
World Health Organization. WHO Child Growth Standards: methods anddevelopment: Length/height-for-age, weight-for-age, weight-for-length,
weight-for-height and body mass index-for-age. World Health Organisation,
2006. http://www.who.int/childgrowth/publications/technical_report_pub/
en/index.html. Accessed 16 Jan 2017.
Van den Broeck J, Cunningham SA, Eeckels R, Herbst K. Data cleaning:detecting, diagnosing, and editing data abnormalities. PLoS Med. 2005;2, e267.
Andersen R. Modern methods for robust regression. Sage University Paper
Series on quantitative applications in the social sciences. Thousand Oaks:
Sage Publishing; 2008.
Akakpo K, Randriamamonjy J. Comprehensive food security and vulnerability
analysis (CFSVA): Democratic Republic of Congo. World Food Programme,
Department of Food Security Analysis (VAM), 2014. http://ebrary.ifpri.org/cdm/
ref/collection/p15738coll2/id/128957. Accessed 16 Jan 2017
Trehan I, Manary MJ. Management of severe acute malnutrition in lowincome and middle-income countries. Arch Dis Child. 2015;100:283–7.
O'Neill SM, Fitzgerald A, Briend A, Van Den Broeck J. Child mortality as
predicted by nutritional status and recent weight velocity in children under
two in rural Africa. J Nutr. 2012;142:520–5. doi:10.3945/jn.111.151878.
Van Den Broeck J, Eeckels R, Vuylsteke J. Influence of nutritional status on childmortality in rural Zaire. Lancet. 1993;341:1491–5. http://www.sciencedirect.
com/science/article/pii/014067369390632Q. Accessed 16 Jan 2017.
Van Den Broeck J, Eeckels R. Effect of malnutrition on child mortality.
Lancet. 1994;344:273. http://www.sciencedirect.com/science/article/pii/
S0140673694930414. Accessed 16 Jan 2017.
Bahwere P, Mtimuni A, Sadler K, Theresa B, Collins S. Long term mortality
after community and facility based treatment of severe acute malnutrition:
Analysis of data from Bangladesh, Kenya, Malawi and Niger. J Public Health
Epidemiol. 2012;4:215–25.
Grellety E, Shepherd S, Roederer T, Manzo ML, Doyon S, Ategbo EA, Grais
RF. Effect of mass supplementation with ready-to-use supplementary foodduring an anticipated nutritional emergency. PloS One. 2012;7(9), e44549.
Abbeddou S, Hess SY, Yakes Jimenez E, Somé JW, Vosti SA, Guissou RM,
Ouédraogo JB, Brown KH. Comparison of methods to assess adherence tosmall‐quantity lipid‐based nutrient supplements (SQ‐LNS) and dispersible
tablets among young Burkinabé children participating in a community‐
based intervention trial. Matern Child Nutr. 2015;11(S4):90–104.
Golden MH. Proposed recommended nutrient densities for moderately
malnourished children. Food Nutr Bull. 2009;30(3 suppl3):S267–342.
Kehoe SH, Chheda PS, Sahariah SA, Baird J, Fall CH. Reporting of participant
compliance in randomized controlled trials of nutrition supplements during
pregnancy. Matern Child Nutr. 2009;5(2):97–103.
Arimond M, Ruel MT. Dietary diversity is associated with child nutritional
status: evidence from 11 demographic and health surveys. J Nutr. 2004;
134(10):2579–85.
Moursi MM, Arimond M, Dewey KG, Treche S, Ruel MT, Delpeuch F. Dietary
diversity is a good predictor of the micronutrient density of the diet of 6- to
23-month-old children in Madagascar. J Nutr. 2008;138:2448–53. PM:19022971.
Lutter CK, Daelmans BM, de Onis M, Kothari M, Ruel MT, Arimond M,
Deitchler M, Dewey KG, Blössner M, Borghi E. Undernutrition, poor feedingpractices, and low coverage of key nutrition interventions. Pediatrics. 2011;
128:e1418–27.
Golden MH. The nature of nutritional deficiency in relation to growth failure
and poverty. Acta Paediatrica. 1991;80(s374):95–110.
Chang CY, Trehan I, Wang RJ, Thakwalakwa C, Maleta K, Deitchler M,
Manaryet MJ. Children successfully treated for moderate acute malnutrition
remain at risk for malnutrition and death in the subsequent year after
recovery. J Nutr. 2013;143:215–20.
Kerac M, Bunn J, Chagaluka G, Bahwere P, Tomkins A, Collins S, Seal A.
Follow-up of post-discharge growth and mortality after treatment for severe
acute malnutrition (FuSAM study): a prospective cohort study. Plos One.
2014;9, e96030.
Ashraf H, Alam NH, Chisti MJ, Mahmud SR, Hossain MI, Ahmed T, Salam MA,
Gyr N. A follow-up experience of 6 months after treatment of children withsevere acute malnutrition in Dhaka, Bangladesh. J Trop Pediatr. 2012;58:253–7.
Khanum S, Ashworth A, Huttly SR. Growth, morbidity, and mortality ofchildren in Dhaka after treatment for severe malnutrition: a prospective
study. Am J Clin Nutr. 1998;67:940–5. PM:9583853.

Page 19 of 19

60. Chisti MJ, Graham SM, Duke T, Ahmed T, Faruque ASG, Ashraf H, Bardhan
PK, Shahid AS, Shahunja KM, Salamet MA. Post-discharge mortality inchildren with severe malnutrition and pneumonia in Bangladesh. Plos One.
2014;9, e107663.
61. Reneman L, Derwig J. Long-term prospects of malnourished children after
rehabilitation at the Nutrition Rehabilitation Centre of St Mary's Hospital,
Mumias, Kenya. J Trop Pediatr. 1997;43:293–6. http://tropej.oxfordjournals.
org/content/43/5/293.long. Accessed 16 Jan 2017.
62. Somasse Y, Dramaix M, Bahwere P, Donnen P. Relapses from acutemalnutrition and related factors in a community-based management
programme in Burkina Faso. Matern Child Nutr. 2015. doi:10.1111/mcn.12197.
63. Trehan I, Banerjee S, Murray E, Ryan KN, Thakwalakwa C, Maleta KM, Manary
MJ. Extending supplementary feeding for children younger than 5 years
with moderate acute malnutrition leads to lower relapse rates. J Pediatr
Gastroenterol Nutr. 2015;60:544–9.
64. Langendorf C, Roederer T, De Pee S, Brown D, Doyon S, Mamaty AA, Touré
LWM, Manzo ML, Grais RF. Preventing acute malnutrition among young
children in crises: a prospective intervention study in Niger. PLoS Med. 2014;
11, e1001714.
65. Golden MH. Nutritional and other types of oedema, albumin, complex
carbohydrates and the interstitium. Paediatr Int Child Health. 2015;35:90–109.
66. Margolies A, Hoddinott J. Costing alternative transfer modalities. J Dev Eff.
2014. doi:10.1080/19439342.2014.984745.
67. Humanitarian Outcomes team. Final evaluation of the unconditional cash
and voucher response to the 2011–12 crisis in Southern and Central
Somalia. New York: UNICEF; 2012.
68. Cash Learning Partnership. Ban Ki-moon — give people cash not goods as
best form of assistance in emergency. Cash Learning Partnership (CaLP)
press release, 2016. http://www.cashlearning.org/news-and-events/newsand-events/post/333-press-release–bank-ki-moon—give-people-cash-notgoods-as-best-form-of-assistance-in-emergency. Accessed 16 Jan 2017.
69. UN General Assembly. One humanity: shared responsibility — Report of theSecretary-General for the World Humanitarian Summit. United Nations
Seventieth session 2016. http://sgreport.whsummit.org/. Accessed 16 Jan 2017.
70. Heikens GT, Schofield WN, Dawson S, Grantham-McGregor SM. The Kingston
project. I. Growth of malnourished children during rehabilitation in thecommunity, given a high energy supplement. Eur J Clin Nutr. 1989;43:145–60.
71. Isanaka S, Nombela N, Djibo A, Poupard M, Van Beckhoven D, Gaboulaud V,
Guerin PJ, Grais RF. Effect of preventive supplementation with ready-to-usetherapeutic food on the nutritional status, mortality and morbidity of children
6 to 60 months in Niger: a cluster randomized trial. JAMA. 2009;301(3):277–85.
72. Walker SP, et al. Growth in length of children recovering from severe
malnutrition. Eur J Clin Nutr. 1988;42:395–404.
73. Golden MH. Is complete catch-up possible for stunted malnourishedchildren? Eur J Clin Nutr. 1994;48 Suppl 1:S58–70.
74. Martorell R, Khan LK, Schroeder DG. Reversibility of stunting:epidemiological findings in children from developing countries. Eur J Clin
Nutr. 1994;48 Suppl 1:S45–57.
75. Grellety E, Golden MH. Weight-for-height and mid-upper-arm circumference
should be used independently to diagnose acute malnutrition: policy
implications. BMC Nutr. 2016;2:1–17. http://bmcnutr.biomedcentral.com/
articles/10.1186/s40795-016-0049-7. Accessed 16 Jan 2017.

Submit your next manuscript to BioMed Central
and we will help you at every step:• We accept pre-submission inquiries• Our selector tool helps you to find the most relevant journal• We provide round the clock customer support• Convenient online submission• Thorough peer review• Inclusion in PubMed and all major indexing services• Maximum visibility for your research
Submit your manuscript at
www.biomedcentral.com/submit