Kenya: Linking
informationto action.
Synthesisof coverageassessment
findings
Lucy Maina Gathigi
Nutrition Specialist, Information
System, Monitoring & Evaluation,
Nutrition Section, UNICEF Kenya
Country OfficeCharles Mumbi
Nutrition Support Officer, Data
and Monitoring at the Nutrition
Section, UNICEF Kenya Country
OfficeLucy Kinyua
Monitoring & Evaluation Manager
at the Division of Nutrition andWellbeing, Ministry of Health,Kenya
Ellyn Yakowenko
Project Director, Scaling
Nutrition at International Rescue
Committee (IRC)
Everlyne Adhiambo
Nutrition Policy and Research
Uptake Advisor at IRC

Shadrack Oiye
Public Health Nutrition Specialistat the Intergovernmental
Authority on Development(IGAD)
This integrated management of acutemalnutrition (IMAM) coverage assessments
synthesis was funded by United States Agency forInternational Development (USAID). The authors
recognise the leadership of the Government of
Kenya in this work. Special thanks to Veronica
Kirogo, Head of Nutrition at the Ministry of Health,and Dr Ismael Teta, Chief of Nutrition at UNICEF
Kenya, for their leadership and guidance. Technicalinputs from members of the Nutrition Information
working group (NITWG) led by Lucy Kinyua
and Samuel Murage, as well as the Emergency
Nutrition Advisory Committee (ENAC) led by Grace
Gichohi, are appreciated. We acknowledge inputs
from the UNICEF Kenya Country Office team,including Francis Wambua (Emergency Nutrition
Specialist) and Victoria Mwenda (former Nutrition
Sector Coordinator), and UNICEF nutrition fieldteams led by Francis Kidake and Tom Amolo.
Special thanks to Edwine Ochieng from theInternational Centre of Policy and Research
Solutions (ICPRS) for his inputs.
The analysis, interpretation, and conclusionreflected in this article are those of the authors.
They do not necessarily represent the views of
USAID, UNICEF, IGAD, ICPRS, or IRC.

18

Original Article

Screening for acutemalnutrition in a Kenya© Kelsey Jones, Kenya, 2013

Original Article

What we know:

Since August 2010, Kenya has adopted IMAM programming as part of routine healthservices. Semi-Quantitative Evaluation of Access and Coverage (SQUEAC) surveys
are conducted regularly to provide localised, contextual information on IMAM
services.

What this adds:

The need to systematically combine SQUEAC survey results to generate allinclusive recommendations for improving IMAM coverage across the Arid andSemi-Arid Land counties (ASALs) was recognised. This article explores thesynthesis of findings from 18 independent surveys. Most IMAM programmes
in ASALs have attained coverage above 50% targets, but there is room for
improvement. Key barriers and facilitators are explored and recommendations toimprove policy, programmes, and coordination are provided.

I

n Kenya, around 5% of children aged under five years are wasted and about 18%
stunted (KNBS, 2022). However, the national prevalence of wasting obscuresimportant sub-national patterns – particularly in the ASALs where wasting is generally more prevalent than the national average(Figure 1). The scale-up of IMAM servic-

Figure 1

es in the ASALs is a key component of Kenya’s country roadmap toward achieving andsustaining the Global Action Plan targets on
wasting. IMAM is implemented by the Ministry of Health in collaboration with UNICEF,
the World Food Programme, and implementing partners as part of the emergency nutrition response in the ASALs.

Wasting prevalence in different Kenyan counties

Classification of Wasting(WHO 2017)
Very low <2.5%
Low 2.5 - <5%Medium 5 - <10%High 10 <15%
Very high =>15%

FIELD EXCHANGE ISSUE 73, July 2024 www.ennonline.net/fex

AREA
COUNTRYWASTING
Arid
WAJIR
22.8%
Arid
TURKANA
22.6%
Arid
MARSABIT
20.4%
Arid
MANDERA
17.3%
Arid
SAMBURU
15.4%
Arid
GARISSA
15.3%
Arid
BARINGO
13.6%
Arid
TANARIVER
11.3%
Semi-arid WEST POKOT
11.0%
Semi-arid KAJIADO
7.6%
Arid
ISIOLO
7.2%
Semi-arid KILIFI
7.2%
Semi-arid KWALE
6.2%
Semi-arid MERU
6.0%
Semi-arid EMBU
5.3%
Semi-arid KITUI
4.9%
KENYA
4.9%
Semi-arid TAITATAVETA
4.1%
Semi-arid MAKUENI
4.0%
Semi-arid LAMU
3.5%
Semi-arid MACHAKOS
3.5%
Semi-arid THARAKA
3.1%
Semi-arid NYERI
2.7%
Semi-arid LAIKIPIA
2.6%
Semi-arid NAROK
2.1%
Wasting prevalence data source: KDHS 2022

Original Article
Figure 2

The Kenya Nutrition Information Technical
Working Group (NITWG) recognised the need tosystematically review localised data, from SQUEAC surveys, to generate all-inclusive recommendations to address key challenges to IMAM coverage across the ASALs. This single, high-levelcomprehensive outlook could then be used for advocacy, planning, and resource mobilisation, informing the scale-up of IMAM in the ASALs.

Key steps used to conduct SQUEAC surveys in Kenya

STAGE 1
Quantitative: Analysisof routine programme data
Quantitative: contextual data
analysis(Identification ofBarriers/Boosters to
Access services)

Methods

STAGE 2+

Small Area
Survey +Small Studies+

STAGE 3
Wide-Area
Survey=Understandingof barriers/boosters
to coverage+coverage estimation (%)+
Recommendations
and Action Plan

Conducting independent SQUEAC
surveys

A total of 18 coverage assessments were conducted between May and July 2023 across 10
ASALs: Turkana, Marsabit, Samburu, West
Pokot, Baringo, Isiolo, Tana River, Mandera,
Garissa, and Wajir. These assessed Outpatient
Therapeutic Programmes (OTPs) and Supplementary Feeding Programmes (SFPs) according to the key steps summarised in Figure 2.
In Turkana and Marsabit, six and four separate

surveys were conducted at the sub-county level, respectively. This was due to the geographicalexpansiveness of these counties.

Synthesis of SQUEAC surveys

We conducted a ‘quasi’ meta-analysis that collated the results of the 18 SQUEAC surveys.
First, the single coverage estimates for either

Figure 3 Analysis framework for SQUEAC survey synthesis
Conducting 18 SQUEAC
surveys in 10 counties

Level 2b: Futhercategorisation
under each generalcategory.
• Futher granular
categorisation
was done to groupalmost similarbarriers/boosters
into sub-category
themes.
• For Example,
under thegeneral categoryof community
level issues, subcategory themes
for barriers were
stigmatisation;
RUTF/RUSF
perceived as food;negative culturalbeliefs; poverty
and food security;
nomadic lifestyleand insecurity.

Level 1: From each survey
report, the barriers/boosters
were drawn and collated ina spreadsheet, where eachsurvey area was allocated aworksheet (tab)Level 2a: Reviewing ofbarriers/boosters andcategorisation them into
general groups.
• These general categories
included: Communitylevel issues, geographicalfactors, maternal/caregiver
determinants and healthsystem issues• All possible categories
included and each category
given a worksheet• Each barrier/booster was
moved manually to therespective category andcoded by country or subcounty (survey area)

Level 3:
Identification ofcommon barriers
and boosters (subcategory themes)• To determine
whether a barrieror booster wascommon, it was
hypothetically
set that it musthave been
identified bynine or moresurvey areas(counties or
sub-counties).

Collection of
information fromthe key informants

Themecategorisationand drawing ofrecommendations
Triangulation,
amalgamation ofarising issues
National outlookof barriers
to coverage,
facilitatorsand common
lessons; andrecommendations

coverage estimates for outpatient and supplementary
Figure 4 Single
feeding programmes compared to observed wasting prevalence

a,b

72.2%
68.7%

80%
70%

Percentage

60%
50%

38.4%

36.6%

40%
30%
20%
10%

OTP

SFP

Wasting

WEST POKOT

WAJIR

TURKANA LOIMA

TURKANA CENTRALTURKANA WEST

TURKANA SOUTH

TURKANA NORTH

TURKANA EAST

TANA RIVERSAMBURUMARSABIT SAKUMARSABIT NORTH HORRMARSABIT MOYALEMARSABIT LAISAMISMANDERAISIOLOGARISSABARINGO

0%

Minimum Sphere Coverage Standing

Wasting prevalence was taken from recent Standardised Monitoring and Assessment of Relief and Transitions (SMART) surveys (July 2022
or January 2023).
b
In Turkana and Marsabit counties, sub-counties were assessed separately due to the expansiveness of these areas. Highest and lowest
coverages are labelled.
aprogramme (OTP or SFP) were compiled forcomparison. From each survey area, coveragebarriers and facilitators were collated into an
Excel worksheet. Each survey area was allocated a separate worksheet. This was the ‘level one’analysis of OTP/SFP barriers/facilitators.
In ‘level two’, barriers and facilitators were reviewed and categorised into four general groups:
community-level issues, geographical factors,
caregiver determinants, and health system issues. The barriers and facilitators that were similar in each of the general groups were further organised into more granular sub-category themes.
Sub-categories were then coded in a drop-downmenu for ease in enumerating which survey areas
reported which barriers and/or facilitators. This
allowed us to determine the number of survey areas that reported each sub-category. Our threshold for determining whether a barrier or facilitator (sub-category) was common was that it musthave been reported by nine (50%) or more survey
areas (counties or sub-counties).
Key informant interviews were also conducted to draw on a broader perspective andto complement county-specific issues. Purposively selected national-level interviewees included: the Ministry of Health National Manager for Emergency Nutrition (n=1), the Ministryof Health Monitoring and Evaluation Manager (1), national staff of implementing partners
supporting IMAM (4), the UNICEF Monitoring & Evaluation Specialist (1), the Nutrition
Sector Coordinator (1), the UNICEF Emergency Nutrition Specialist (1), nutrition supply chain officers (2), national-level World
Food Programme staff (1), the UNICEF Data
and Monitoring Nutrition Support Officer (1),and UNICEF Nutrition Specialists at zonal level (2). Guide questions for the key informant interviews were drafted and distributed appropriately across these key informants. This gatheredadditional information about IMAM coveragethat may not have been addressed through the
SQUEAC survey methodology alone.
The information collected from key informants was categorised into common themes.
These were then triangulated with the synthesised barriers and facilitators to inform the national outlook of issues affecting IMAM programming in Kenya’s ASAL areas (Figure 3).

Results

Programme coverage

There were seven OTP and five SFP survey areasthat reported single coverage estimates of less than
the 50% minimum standard for rural areas (Figure 4) (Sphere, 2018). When SFP and OTP cov-

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19Original Article
erage and wasting data were merged, and regression analysis performed, a positive relationshipwas observed – coverage increased in line with increasing wasting rates. Almost two in every threesurvey areas (64%) with high wasting rates (over15%) had higher coverage rates (greater than 50%)for both OTP and SFP. From the synthesis, we noted that areas with higher wasting prevalence also
had many nutrition partners supporting IMAM
programming, thus explaining the higher cov-

Table 1erage estimates. However, this did not come intoplay for areas with high levels of insecurity (suchas Samburu and Laisamis).

Common barriers to coverage andtreatment

In both OTPs and SFPs, 94% of survey areas reported the sharing of ready-to-use therapeutic
food (RUTF) or ready-to-use supplementary
food (RUSF) – or exchanging them for moneyor food – as a major barrier (Table 1). Similarfindings were reported by key informants, who
noted nutrition commodity sharing was commonplace. Some caregivers who consumed alcohol would also exchange RUTF for money or
alcohol. Maternal workload was also highlighted as a key barrier, as well as poor active casefinding and referral. Long distances to health facilities and migration (due to drought or floods)
were also important barriers to access.

Barriers and facilitators to outpatient and supplementary feeding programme coveragea
Supplementary Feeding Programme

Outpatient Therapeutic Feeding Programme
Surveyareas%

Commonly reported barriers

RUTF sharing or exchange for money or food

17

94%

Poor active case findings and referral system

15

83%

Commonly reported barriers

Surveyareas%

RUSF sharing or exchange for money or food

17

94%

Challenges with HCWs

16

89%

83%

Long distance from health facility

16

89%

Challenges with CHVs

15

Maternal workload

14

78%

Maternal workload

15

83%

Long distance from health facility

13

72%

Poor active case finding and referral

15

83%

Poor knowledge on causes and treatment ofsevere wasting

12

67%

Migration due to drought and floods

15

83%

Negative cultural beliefs, practices, and myths

12

67%

Migration due to drought and floods

12

67%

Challenges with the CHVs
RUSF and other commodity stockouts

14
14

78%
78%

Poverty and food insecurity

11

61%

Stigmatisation of households with moderatechild wasting

13

72%

Stigmatisation of households with severe childwasting

1056%

Poor documentation/records

950%

Poverty and food insecurity
Maternal knowledge and perceptions

12
12

67%
67%

Nomadic lifestyle and insecurity

8

44%

11

61%

Poor health seeking behaviours

8

44%

Poor knowledge on causes and treatment ofmoderate wasting
Negative cultural beliefs, practices, and myths

10

56%

10

56%

Alcoholism
Challenges with HCWs

8
8

44%
44%

Poor health seeking behaviours
Nomadic lifestyle and insecurity

950%

RUTF and other commodity stockouts

844%

Poor or impassable roads

950%

RUTF is perceived as food

7

39%

RUSF perceived as food

8

44%

7

39%

Limited defaulter tracing and follow-up

739%

Limited defaulter tracing and follow-up

Maternal knowledge and perceptions

6

33%

Poor documentation/records

7

39%

Surveyareas%

Alcoholism

633%

Health facility amenities

6

33%

Awareness on causes and treatment of severe
wasting
Health Care Worker capacity to implement IMAM

18

100%

Commonly reported facilitators

Survey
areas

%

18

100%

100%

17

94%

Positive health seeking behaviours

16

89%

Awareness of and limited stigma regarding
moderate wasting
Active case finding and referrals

18

RUTF and other supplies available (no stockouts)

18

100%

Community Health Volunteer capacity to
implement IMAM

16

89%

HCW capacity to implement IMAM

17

94%

16

89%

Active case finding

14

78%

Support supervision and programme review

14

78%

Collaboration between HCWs, CHVs,
communities, and leaders
Active outreach services and mass screening

16

89%

Family led MUAC and self-referral

13

72%

CHV capacity to implement IMAM

15

83%

Active outreach services

13

72%

Family led MUAC and self-referral

15

83%

Positive health seeking behaviours

13

72%

RUSF supplies available (no stockouts)

13

72%

Stakeholder support and coordination

12

67%
61%
61%

Commonly reported facilitators

Stakeholder support and coordination

12

67%

Collaboration between HCWs and CHVs

10

56%

OTP services available at health facilities

950%

Availability of screening, referral and reporting
tools

9

50%

Defaulter tracing mechanisms
Support supervision and programme review

11
11Active community and leader’s involvement

8

44%

SFP services available (at various service points)

10

56%

Defaulter tracing mechanisms

8

44%

Availability of equipment

7

39%

Recognition of role of CHVs

6

33%

Proximity to health facilities

6

33%

Only commonly reported barriers / facilitators have been shown here (i.e. those reported in six or more survey areas)
RUTF/RUSF = Ready-to-use therapeutic/supplementary food; CHV = Community Health Volunteer; HCW = Health Care Worker;
MUAC = Mid-upper arm circumferencea20

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Original Article
Kenya’s community health strategy waslaunched in 2006 to improve community accessto healthcare. Since then, most counties haveadopted it – including all the survey areas featured in this article. However, continued challenges were observed in regard to the community health strategy. In some areas, there were nocommunity health volunteers (CHVs). Where
they existed, numbers were often not adequate
to support in active case finding, defaulter tracing, and referral. Some CHVs had capacity gaps,
as was reported by a partner staff key informant.

“Knowledge of IMAM by CHVs
has enhanced screening and active
case finding in the community.
However, a good number of CHVs
have not been trained on IMAM
due to limited resources.”– Key informant, nutrition partner

Demotivation, due to a lack of or a delayed
stipend, was commonly reported for CHVs
across the survey areas. We also observed thata barrier may have a geographical aspect due
to geopolitical and sociocultural similarities.
An example is maternal alcoholism, which wasreported in Turkana Central, Turkana South,
Turkana West, Samburu, West Pokot, Baringo,
Laisamis, and North Horr. These areas bordereach other, and this finding calls for inter-county collaboration in addressing the challenge.

Common facilitators of coverage

Most health systems facilitators were common
across the survey areas for both OTPs and
SFPs. These included HCWs and CHVs’ availability and their capacity to provide IMAM
services, active case finding, active outreaches, and mass screening exercises. Also important were no stock-out of nutrition commodities, provision of supportive supervision andprogramme reviews. All the surveyed areas indicated awareness of the causes and treatment
of severe and moderate wasting as a key community-level facilitator.
Common maternal/caregiver facilitators
identified were positive health seeking behaviour, training caregivers to identify early signsof malnutrition in their children using MUAC(“Family-led MUAC”) and self-referral. Only
Turkana North reported availability of active
mother support groups as a facilitator.

What next?

The synthesis of findings from the independent surveys, together with the consolidationof insights from key informants, highlightactions to be considered to scale up IMAM
across Kenya’s ASALs.

Policy and strategy considerations

Developing and implementing a national strategy for peace, security, development, and humanitarian operations, as well as tackling poverty and infrastructural challenges, all remain
important. Poverty and childhood malnutrition
are interlinked – and they are mediated by inadequate diets, lower education, poorer living
standards, and limited access to healthcare fa-

cilities and appropriate water, sanitation, andhygiene. This clearly articulates the need forpolicies and guidelines that prioritise overall
poverty and malnutrition reduction.

grammes as a facilitator. National and county
governments, and partners, must scale up social
safety net and poverty alleviation programmesthat integrate nutrition.

Kenya has chosen the primary healthcare
system to deliver universal health coverage.
A ‘community health strategy’ has been given prominence in all the survey areas. However, challenges to full strategy implementation
still exist, as only two counties are reported to
be giving CHVs a monthly stipend. There is aneed for county governments to collaborate
with partners to develop and implement community health acts. These acts will provide a legal basis for counties to allocate funds for renumeration and provide adequate supervision of
CHVs. This will result in CHVs who are better motivated, better equipped, and who areaccountable when providing health services atcommunity level.

The adequacy and availability of nutrition
supplies was a key facilitator leading to the success of the IMAM programme. Although the
supply chain is government led, procurement isheavily supported by donors. Advocacy efforts
should continue at both the national and county
levels for resource allocation to cover nutrition
supplies and for ring-fencing finances to protect
any allocated funding for this task.

Programmatic issues

Across 18 independent SQUEAC surveys, witha few exceptions (Turkana East, Turkana Loima, and Wajir), the OTP was found to performbetter in both coverage and outcome indicators
than the SFP. This is despite both programmes
being implemented jointly in all the survey areas. This calls for further analysis to understandthe associations and unique factors that could
be causing this difference.
Maternal workload was highlighted as a key
caregiver barrier. Programming should be designed to encompass male involvement in childcare activities and not purely focus on mothers and children. Counties and partners could
also support establishing peer-to-peer support
groups for fathers at community level, whichhave been proven to positively influence childfeeding practices (Bogale et al, 2022; Atuman
et al, 2023). Fathers can be involved in financial and resource support, as well as social andphysical support, such as shared responsibility
for the nutritional wellbeing and health of thechild. A study in Ethiopia found that, for children aged 6–23 months, dietary diversity in thehousehold increased by 13.7% when fathers
were involved in infant and young child feeding(Gebremedhin et al, 2017).
Community engagement, sensitisation, andmobilisation clearly remain as barriers to increasing coverage for both OTPs and SFPs. Addressing these issues will be central to achieving greater
coverage in IMAM programmes. As well as developing guidelines and strategy documents, it is critical for counties and partners to allocate resources
for improved community engagement.
The sharing and commodification of RUTF/
RUSF was a major barrier. This directly affects
programme outcomes, increasing both lengthof stay and non-response in a programme. Ultimately, children who remain wasted remain atheightened risk of mortality and morbidity associated with malnutrition. Such practices also
increase the cost of programmes. To curb this, itis critical to link households with malnourishedchildren who have exited as ‘cured’ from IMAM
programmes to social safety net schemes. However, in this analysis, only two survey zones reported the availability of social safety net pro-

Coordination actions

Several coordination mechanisms for nutrition
exist in the country at national level, providing
opportunities for collaboration and to strengthen partnerships between the Ministry of Healthand nutrition stakeholders. These include the
Nutrition Technical Forum, ENAC, and NITWG. Counties could establish such coordination structures for inter-county information
sharing and collaboration, seeking to addresscommon barriers and documenting best working practices.

Conclusion

This systematic synthesis of findings from 18
SQUEAC surveys highlighted that most IMAM
programmes in ASALs have attained OTP and
SFP single coverage above 50% but there isroom for improvement and a need to sustain thegains already made. OTP was noted to performbetter compared to SFP.
The identified common barriers and facilitators, and additional key observations, provide relevant information for policy, advocacy,
and programmatic efforts to scale up the management of wasting across the ASALs. Moreover,the synthesis diagnoses the need for inter-county collaboration in tackling specific barriers, given their geographical spread. Ultimately, systems
need to be strengthened to prevent children frombecoming wasted in the first place. Poverty alleviation, stronger community systems, and gender equity (all advocated for above) will not only
reduce barriers to increasing treatment coverage
but also promote prevention.
For more information, please contact Lucy
Maina at lmaina@unicef.org

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