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Can Women Self-Help Groups Improve Financial Stability and Quality of Life of Households Receiving Government Cash Transfers? Evidence from Inua Jamii-OVC program in the Slums of Nairobi, Kenya, Inua Jamii

Kenya, 2025
Health and Well-Being (HaW)
Peter Otieno
Last modified October 08, 2025 Page views 10 Documentation in PDF Metadata DDI/XML JSON

Identification

IDNO
DDI-KEN-APHRC-InuaJamii-2024-v1.0
Title
Can Women Self-Help Groups Improve Financial Stability and Quality of Life of Households Receiving Government Cash Transfers? Evidence from Inua Jamii-OVC program in the Slums of Nairobi, Kenya, Inua Jamii
Subtitle
Inua Jamii
Country
Name Country code
Kenya KEN
Abstract
Abstract
Background: Unconditional cash transfer is a potent social policy program in advancing Sustainable Development Goals, particularly targeting poverty reduction, hunger eradication, and improved health and well-being. In Kenya, the Inua Jamii-Orphans and Vulnerable Children (OVC) program targets impoverished households with orphans and vulnerable children, but concerns remain regarding dependency and financial literacy. Integrating women's self-help groups (SHGs) with cash transfers presents a novel approach to fostering economic stability, particularly in urban slums where access to traditional microfinance is limited.
Objectives: The overarching aim of this study was to investigate the impact of women SHGs on the financial stability and quality of life of Inua Jamii-OVC beneficiaries in Nairobi slums. Specifically, it seeks to assess household expenditures, savings, assets, and debts for financial stability, as well as the World Health Organization quality of life index and self-rated health status.
Methods: This study is nested within the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) and implemented in two phases. Phase 1 involves co-designing the SHG intervention with stakeholders. Phase 2 is a cluster randomized controlled trial design to measure program impact. Eligible women caregivers will be recruited from Inua Jamii-OVC beneficiary households in Korogocho and Viwandani slums. Randomization will be conducted at the community unit level, with intervention groups participating in SHGs while control groups will receive regular cash transfers. Data will be collected at baseline and end-line after a follow-up period of six months..An average treatment effect of the program will be estimated using a mixed-effects model or generalized estimating equations (GEE) that incorporate random effects for clusters and handle within-subject correlation due to repeated measures We will use an ingredients approach to estimate the total program costs from both the participant's perspective and the societal perspective.
Significance: This study addresses critical gaps in understanding the synergy between SHGs and cash transfer programs in urban slum settings. The findings will inform the design and implementation of sustainable cash transfer programs to break the cycle of poverty and dependency on cash transfers.

Version

Version Date
2025-02-19
Version Notes
N/A

Scope

Keywords
Keyword Vocabulary URI
N/A N/A N/A

Coverage

Geographic Coverage
Urban areas only
Unit of Analysis
Individual - Women caregivers
Household
Universe
All women caregivers receiving Inua Jamii Cash transfers

Producers and sponsors

Authoring entity/Primary investigators
Agency Name Affiliation
Peter Otieno APHRC
Producers
Name Affiliation Role
Flavio Malugutti University of California, Santa Babara Co-Investigator
Grace Kyule APHRC Co-Investigator
James Kavai APHRC Co-Investigator
Winnie Opondo APHRC Co-Investigator
Wanjiru Murigi APHRC Co-Investigator
Funding Agency/Sponsor
Name Abbreviation Role
Center for Effective Global Action CEGA Funder
Other Identifications/Acknowledgments
Name Affiliation Role
N/A N/A N/A

Sampling

Sampling Procedure
Sample size and Sampling
Prior research indicates that interventions that address savings, access to finance, and income within savings groups yield an average effect size of 27%, with a minimum effect size of 10% (26-28). Thus, our power calculation assumes this effect size as the parameter for power analysis. We further assume a margin of error of 0.05, standard deviation of 1 and power of 80% to estimate the number of clusters and cluster size (26-28). We know the variation within the cluster is vital to consider in the cluster RCT, we set our ICC to 0.1 based in previous studies (26-28). We then fixed our number of clusters to be included in our study at 14 clusters per treatment arm. These results in a cluster size of 50 per cluster and the overall sample size we require at the endline of 700 with 350 in the treatment group and 350 in the control group (Figure 3). We further assume an attrition rate of 10%, therefore the sample size for the baseline will be 772 households.
Deviations from the Sample Design
None
Response Rate
100%
Weighting
None

Data Collection

Dates of Data Collection (YYYY/MM/DD)
Start date End date
2025-03-05 2025-03-10
Mode of data collection
Face-to-face [f2f]
Supervision
During the implementation of the Inua Jamii Project, close supervision and follow-up strategies were put in place to ensure the smooth running of both the baseline and endline data collection exercises.
The teams were organized in 2 groups for both sites with a team of six enumeartors and one teamleader for Ruaraka and seven enumearators and one teamleader for Makdara site. The team leaders were in charge of the welfare of the team in their care. They were to provide the overall leadership in the field including, allocating work for the enumerators, logisitical planning and sit-ins to ensure alignment to the standards and protocol for the study. The team leaders were also acting as the link between the field team and the research team.
Regular check-in phone calls were made to team leaders throughout the data collection period. These calls gave us a chance to monitor daily progress, clarify any new challenges and offer prompt support when required. The check in phone calls also provided a forum for the team leaders to discuss logistical issues and provide updates on field operations.
The research officer also conducted field visits to the two project sites. In order to make sure that data collection was conducted in accordance with the required standards and protocol, these visits included spot checks and sit-ins during interviews. Additionally the sit-ins provided a chance to observe the enumerators, give feedback on interviewing techniques and address any quality issues in real time.
Furthermore, weekly progress meetings were held with the data collection teams. These meetings created a space to openly discuss challenges encountered in the field, such as respondent availability, geographical access issues, or questionnaire-related concerns. They also provided a valuable platform for the team to share their field experiences, which helped in refining strategies and boosting team morale.
Through this combination of consistent check-ins, field supervision, and structured team engagements, the quality and reliability of the data collected during the Inua Jamii Project was safeguarded.
Type of Research Instrument
HOUSEHOLD Questionnaire- Household demographics, Household amenities, Household possessions, Household income and expenditure, Household shocks experienced, Households savings, Quality of life scales, PPsychosocial factors, Decision making, Sharing of housework, Access, Household relationships, Orphan and Vulnerable children schooling details, Health status and health seeking behavoir, Food intake, Drug and substance abuse, Health insurance, Domestic violence,

Data Processing

Cleaning Operations
All data sources underwent quality control procedures. The survey data was collected using electronic tablets with built-in range checks and skip logic (based on the Caregiver Questionnaire instrument), and daily monitoring reports were generated to check for missing entries or inconsistencies. Data cleaning steps (conducted prior to analysis) iincluded verification of unique identifiers, resolution of any duplicate entries, consistency checks between related variables (e.g., total household members in different sections), and handling of outliers or implausible values (such as extremely high savings amounts) through cross-verification with field teams. After cleaning, the baseline and follow-up datasets were merged by household ID to create a panel dataset for analysis. No survey weights were applied, as noted, because the sample was not intended to be representative of a larger population beyond the study as it is an experimental census of eligible households in the chosen sites. All analyses wasl therefore be unweighted, focusing on internal comparisons between the treatment and control groups.
Other Processing
N/A

Data Appraisal

Estimates of Sampling Error
N/A

Data access

Contact
Name Email
African Population and Health Research Center datarequest@aphrc.org
Conditions
APHRC data access condition

All non-APHRC staff seeking to use data generated at the Center must obtain written approval to use the data from the Director of Research.
This form is developed to assess applications for data use and facilitate responsible sharing of data with external partners/collaborators/researchers. By entering into this agreement, the undersigned agrees to use these data only for the purpose for which they were obtained and to abide by the conditions outlined below:

1.Data Ownership:
The data remain the property of APHRC; any unauthorized reproduction and sharing of the data is strictly prohibited. The user will, therefore, not release nor permit others to use or release the data to any other person without the written authorization from the Center.

2.Purpose:
The provided data must be used for the purpose specified in the Data Request Form; any other use not specified in the form must receive additional or separate authorization.

3.Respondent Identifiers:
The Center is committed to protecting the identity of the respondents who provide information in its research. All analytical data sets (both qualitative and quantitative) released by the Data Unit MUST are stripped of respondent identifiers to protect the identity of the respondents. By accepting to use APHRC data, the user is pledging that he/she will not, under any circumstance, regenerate the identifiers or permit others to use the data to learn the identity of any individual, household or community included in any data set.

4.Confidentiality pledge:
The user will not use nor permit others to use the data to report any information in the data sets that could identify, directly or by inference, individuals or households.

5.Reporting of errors or inconsistencies:
The user will promptly notify the Head of the Statistics and Survey Unit any errors discovered in the data as soon as the errors are discovered.

6.Publications resulting from APHRC data:
The Center requires external collaborators to work with APHRC staff on all publications resulting from its data. In order to facilitate this, lead authors should send a detailed concept note of the paper (including the background, rationale, data, analytical methods, and preliminary findings) to the Principle Investigator (or Theme Leader) for the project (with a copy to the Director of Research), who will circulate the abstract to concerned researchers for possible expression of interest in participating in the publication as co-authors. Any exception to the involvement of APHRC staff should be approved by the Director of Research, APHRC.

7.Security:
The user will take responsibility for the security of the data by ensuring that the data are used and stored in a secure environment where access is password protected. This will ensure that non-authorized people should not have access to the data.

8.Loss of privilege to use data:
In the event that APHRC determines that the data user is in violation of the conditions for using the data, or if the user wishes to cancel this agreement, the user will destroy the data files provided to him/her. APHRC retains the right to revoke this agreement or informs publishers to withhold publication of any work based wholly or in part on its data if the conditions for using the data are violated.

9.Acknowledgement:
Any work/reports from this data must acknowledge APHRC as the source of these data. For example, the suggested acknowledgement for NUHDSS data is:
"This research uses livelihoods data collected under the longitudinal Nairobi Urban Health and Demographic Surveillance System (NUHDSS) since 2006. The NUHDSS is carried out by the African Population and Health Research Center in two slums settlements (Korogocho and Viwandani) in Nairobi City."Additionally all funders, the study communities that provided the data, and staff who collected and analyzed or processed the data should be acknowledged.

10.Deposit of Reports/Papers:
The user should submit electronic and paper copies of all publications generated using APHRC data to the Policy Engagement and Communications Department, with copies to the Director of Research.

11.Change of contact details:
The user will promptly inform the Director of Research of any change in your personal details as contained on this data request form.
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-InuaJamii-2024-v1.0
Producers
Name Abbreviation Role
African Population and Health Research Center APHRC Documentation of the DDI
Date of Production
2025-02-19
Document version
Version 1.0 (February 2025)