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Examining the Complex Dynamics Influencing Persistent Acute Malnutrition in Turkana and Samburu Counties – A Longitudinal Mixed Methods Study to Support Community Driven Activity Design, NAWIRI

KENYA, 2021
Health and Well-Being (HaW)
Dr. Estelle M. Sidze, Dr. Faith Thuita
Last modified June 14, 2022 Page views 386701 Documentation in PDF Metadata DDI/XML JSON

Identification

IDNO
DDI-KEN-APHRC-NAWIRI-2022-v01
Title
Examining the Complex Dynamics Influencing Persistent Acute Malnutrition in Turkana and Samburu Counties – A Longitudinal Mixed Methods Study to Support Community Driven Activity Design, NAWIRI
Subtitle
NAWIRI
Country
Name Country code
KENYA KEN
Abstract
Background: Acute malnutrition in infants and children less than 5 years is persistent in the arid and semi-arid lands (ASALs) of East Africa and the Sahel region despite years of investment. In the ASALs of Kenya, the situation is exacerbated by deep-rooted poverty and unequal access to basic services, sustained community conflicts, migration, poor seasonal rainfall/drought and other shocks. Nutrition specific and nutrition sensitive national and county level programs have either not been developed or not implemented effectively.

Objectives: To understand and map immediate, underlying, basic and systemic drivers of acute malnutrition for the development of overarching as well as micro-solutions for the sustainable reduction of persistent acute malnutrition (PAM) and inform pilot studies and Phase 2 (second phase of NAWIRI project implementation) activities in Turkana and Samburu Counties.

Methods: This study will be a longitudinal mixed-methods observational cohort study of children less than 3 years and their mothers and/or caregivers in Samburu and Turkana Counties. Both quantitative and qualitative methods will be utilized in the data collection processes. Data collection is scheduled to begin in January 2021. Data analysis and learning and adapting will be ongoing so that results can inform pilots, theory of change (ToC) review and Phase 2 activities throughout the study.

Study outcomes: To develop new interventions, and to adapt and contextualize existing interventions to prevent global acute malnutrition (GAM); strengthen social and behavior change (SBC) strategies around maternal, infant and young child nutrition (MIYCN), water and sanitation (WASH), community health systems, gender dynamics, livelihoods and resilience, and to inform improvements of the current nutrition surveillance system.

Version

Version Date
2022-01-26
Version Notes
na

Coverage

Geographic Coverage
Turkana and Samburu Counties.
Unit of Analysis
Children less than 3 years and their mothers and/or caregivers
Universe
The survey covered household with children less than 3 years and their mothers and/or caregivers in Samburu and Turkana Counties

Producers and sponsors

Authoring entity/Primary investigators
Agency Name Affiliation
Dr. Estelle M. Sidze African Population and Health Research Center
Dr. Faith Thuita RTI International (registered trademark and trade name of Research Triangle Institute)
Producers
Name Affiliation Role
Dr. Dickson Amugsi African Population and Health Research Center Quantitative Component Lead
Dr. Amanuel Abajobir African Population and Health Research Center Coordination Lead
Dr. Martin K. Mutua African Population and Health Research Center Lead Statistician
Mr. Bonventure Mwangi African Population and Health Research Center Data Management and Analysis
Dr. Chessa Lutter RTI International (registered trademark and trade name of Research Triangle Institute) Co-Investigator
Dr. Valerie Flax RTI International (registered trademark and trade name of Research Triangle Institute) Co-Investigator
Mr. Albert Webale RTI International (registered trademark and trade name of Research Triangle Institute) Co-Investigator
Mr. Brad Sagara Mercy Corps Co-Investigator
Mr. Godfrey Wafula RTI International (registered trademark and trade name of Research Triangle Institute) Field Research Coordinator
Mr. John Ebei African Population and Health Research Center Study Field Coordinator
Mr. Gabriel Ekuwam Nawiri Field Director
Mr. Peter Ingolan Government Engagement Manager
Mr. Benson Mutiso CARITAS Monitoring and Evaluation Officer
Mr. Edwin Chemiron Mercy Corps Monitoring and Evaluation Coordinator
Mr. Emmanuel Essau Eruppe Livestock and Agriculture Officer
Mr. Jacob Esinyen Emanikor Ministry of Health Sub-County Nutrition Coordinator
Mrs. Fridah Asimit Ekaudu Ministry of Health Nutrition Coordinator Turkana West
Mrs. Cynthia Ekato Ministry of Health County Nutrition Coordinator
Mr. Julius Gogong Ministry of Health County Monitoring and Evaluation Officer
Mr. Evans Onyiego Nawiri Field Director
Mr. Simon Eris RTI International (registered trademark and trade name of Research Triangle Institute) Field Research Coordinator
Mr. Dancan Lesiamito African Population and Health Research Center Study Field Coordinator
Mr. Joel Olewe Mercy Corps Monitoring and Evaluation Coordinator
Mr. Timothy Lesingiran Mercy Corps Government Engagement Manager
Mr. Koolic Loosengei NDMA Turkana County County Information Officer
Mr. Augustine Lemowanapi Ministry of Health County Community Strategy Focal Person
Mr. Jeff Mukuria County Monitoring and Evaluation Coordinator
Mr. Christopher Lengusuranga Ministry of Health County Nursing Officer
Ms. Delphina Kaaman Ministry of Health County Nutrition Coordinator
Mr. Francis Lesiantam Ministry of Health Sub-County Nutrition Coordinator
Mr. John Bosco Losusui Ministry of Health Sub-County Nutrition Coordinator
Funding Agency/Sponsor
Name
USAID through Food for Peace

Sampling

Sampling Procedure
SAMBURU

The study sample was population-based, with stratification by sub-counties grouped into three survey zones (Central, North, and East) reflecting administrative sub-counties used in the Samburu Standardized Monitoring and Assessment of Relief and Transitions (SMART) Surveys. Stratification by livelihood zones was done through post-stratification analysis. We analyzed the data by livelihood zone because it was hypothesized that undernutrition might be more related to a household's livelihood than to its physical location.

As noted, the study used mixed-method techniques with quantitative and qualitative data collection. The quantitative component included a household survey and a caregiver survey and covered 699 households. The qualitative data collection activities yielded rich and in-depth insights that will be triangulated with the quantitative survey findings in a companion report. Therefore, this report focuses only on findings from the quantitative survey component. Results are reported for global acute malnutrition (GAM), stunting, and underweight. However, the discussion focuses only on GAM because the purpose of the Nawiri program is to reduce persistent acute malnutrition.

The baseline data collection was carried out in June and July 2021 following a full household listing operation in the county to establish the sampling frame of households with children under 3 years. Subsequent data collection waves are planned for November-December 2021 (Wave 2), March-April 2022 (Wave 3), September-October 2022 (Wave 4), March-April 2023 (Wave 5), and August-September 2023 (Wave 6).


TURKANA

The study sample was population-based, with stratification by sub-counties grouped into four survey zones (Central, North, West, and South) reflecting administrative sub-counties used in the Turkana Standardized Monitoring and Assessment of Relief and Transitions (SMART) Surveys. Stratification by livelihood zones was done through post-stratification analysis. We analyzed the data by livelihood zone because it was hypothesized that undernutrition might be more related to a household's livelihood than to its physical location.
As noted, the study used mixed-method techniques with quantitative and qualitative data collection. The quantitative component included a household survey and a caregiver survey and covered 1,211 households. The qualitative data collection activities yielded rich and in-depth insights that will be triangulated with the quantitative survey findings in a companion report. Therefore, this report focuses only on findings from the quantitative survey component. Results are reported for global acute malnutrition (GAM), stunting, and underweight. However, the discussion focuses only on GAM because the purpose of the Nawiri program is to reduce persistent acute malnutrition.

The baseline data collection was carried out in May and June 2021 following a full household listing operation in the county to establish the sampling frame of households with children under 3 years. Anthropometric data were collected from all under-5 children in the sampled households. Subsequent data collection waves are planned for October-November 2021 (Wave 2), March-April 2022 (Wave 3), September-October 2022 (Wave 4), March-April 2023 (Wave 5), and August-September 2023 (Wave 6).
Deviations from the Sample Design
na
Response Rate
na
Weighting
na

Data Collection

Dates of Data Collection (YYYY/MM/DD)
Start date End date Cycle
2021-05-08 2021-07-19 1
Mode of data collection
Face-to-face [f2f]
Supervision
Field operations supervision was done in two layers: daily supervision by team leaders, and a weekly review of activities and data quality by the data coordination team, which included a research officer, a data analyst, a software programmer, and a postdoctoral research scientist. At a higher level, a weekly report on issues arising from the field and discrepancies observed in data were shared with the senior research team, which included the co-principal investigators and co-investigators, who advised on the necessary actions to be taken. The county Nawiri team and county government officials-consisting of sub-county nutrition coordinators from Turkana East and North/Kibish, the county nutrition coordinator, representatives from Mercy Corps and RTI, the Ministry of Health Monitoring and Evaluation Officer, and NDMA staff-were also involved in the whole process, from training fieldworkers to supervising data collection activities in all four survey zones.
Type of Research Instrument
HOUSEHOLD QUESTIONNAIRE:background, informed consent, household schedule/roster, household demographics, household characteristics, socio-economic characteristics (socio-economic characteristics, POVERTY PROBABILITY INDEX (PP1), HOUSEHOLD WEALTH RANKING (PERCEPTION)), food consumption, water, hygiene and sanitation (wash) (water access, availability and seasonality, household water insecurity experiences (hwise) scale, hygiene and sanitation), household shocks experienced, social safety nets and economic safety guards.


WOMEN/CAREGIVER QUESTIONNAIRE:background, informed consent, mother's/caregivers information, births / pregnancy history, pregnancy and antenatal care, family planning, infant and young child feeding practices, supplementation and consumption of iron rich or iron fortified foods, maternal knowledge and attitude, on infant and young child feeding practices, caregiving practices, child feeding utensils hygiene, food safety, hygiene, and sanitation practices, child immunization, health and health seeking practices, acute malnutrition screening (community health volunteers), womens minimum dietary diversity, food insecurity experience scale (hfies), gender, women empowerment, violence and community conflict, psychological wellbeing, anthropometric measurements

Data Processing

Cleaning Operations
Data quality monitoring processes and checks were implemented throughout the data collection process, during the time of developing the data collection tools (through built-in quality control in the tablet-based platform), during training of fieldworkers, in real time during data collection (routine monitoring by the research team and periodic cross-checks against the protocols), and during the data cleaning process. During fieldwork, data quality was enhanced through regular spot checks and sit-ins by supervisors to verify the authenticity of data collected. Data were then reviewed and certified by the field coordinator before they were transferred to the server.


The quantitative data were collected using SurveyCTO, a survey platform for electronic data collection that has in-built skips and quality checks. Using this software increased efficiency and reduced the time needed for cleaning the data. In addition, the platform supported offline data capturing for regions with slow or no internet connectivity and data transmission when the internet became available. Fieldwork was conducted by trained fieldworkers using digital tablets with the questionnaire loaded in SurveyCTO. The questionnaire included the following modules: (1) identification and tracking, (2) demographics and household composition, (3) anthropometry of children <5 years and mothers, (4) socioeconomics, (5) household food security, (6) WASH, (7) health-seeking behavior, (8) MIYCN, (9) shock experience/exposure, and (10) shock preparedness and response. Data were uploaded from the tablets onto a secure African Population and Health Research Center (APHRC) server after each day of data collection. Data were synchronized automatically to a server when the tablet was in a location with network coverage. The uploaded data were then checked for quality daily by a data manager and a team dedicated to coordinate field procedures and at the APHRC head office in Nairobi.
Other Processing
na

Data access

Citation requirement
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download

Metadata production

Document ID
DDI-KEN-APHRC-NAWIRI-2022-v01
Producers
Name Abbreviation Role
African Population and Health Research Center APHRC Documentation of the DDI
Date of Production
2021-12-26
Document version
Version 1.0 (January 2022)