The impact of unconditional cash transfers on morbidity and health-seeking behaviour in Africa: evidence from Ghana, Malawi, Zambia and Zimbabwe

Health Policy and Planning, Volume 37, No. 5, Year 2022

Interpretation

Unconditional cash transfers have demonstrated widespread, positive impacts on consumption, food security, productive activities and schooling. However, the evidence to date on cash transfers and health-seeking behaviours and morbidity is not only mixed, but the evidence base is biased towards conditional programmes from Latin America and is more limited in the context of Africa. Given contextual and programmatic design differences between the regions, more evidence from Africa is warranted. We investigate the impact of unconditional cash transfers on morbidity and health-seeking behaviour using data from experimental and quasi-experimental study designs of five government cash transfer programs in Ghana, Malawi, Zambia and Zimbabwe. Programme impacts were estimated using difference-in-differences models with longitudinal data. The results indicate positive programme impacts on health seeking when ill and on health expenditures. Our findings suggest that while unconditional cash transfers can improve health seeking when ill, morbidity impacts were mixed. More research is needed on longer-term impacts, mechanisms of impact and moderating factors. Additionally, taken together with existing evidence, our findings suggest that when summarizing the impacts of cash transfers on health, findings from conditional and unconditional programmes should be disaggregated. Data used in this study came from five UCT programmes from four countries in Africa. These programmes are the Ghana Livelihood Empowerment Against Poverty (LEAP) 1000 programme, the Malawi Social Cash Transfer Programme (Malawi SCTP), the Zambia Child Grant Programme (Zambia CGP), the Zambia Multiple Categorical Targeting Programme (Zambia MCT) and the Zimbabwe National Harmonized Social Cash Transfer Programme (Zimbabwe HSCT) (American Institutes for Research, 2014a; 2014b; Ghana Leap 1000 Evaluation Team, 2018; Ward et al., 2010). Table 1 summarizes the geographical regions where data were collected, survey years and household sample sizes. In all countries examined, study designs were either cluster randomized controlled trial (RCT) (Malawi and Zambia) or quasi-experimental (Ghana and Zimbabwe). The Ghana evaluation sampled households around an eligibility score cut-off for the programme to construct a treatment and comparison group. In Zimbabwe, comparison districts were selected based on agro-ecological characteristics (they neighbour each other), culture and level of development. Data summary and sample size We provide brief descriptions of these programmes below. The Ghana LEAP 1000 programme is an extension of the country’s flagship anti-poverty programme, LEAP. While LEAP is targeted to extremely poor households with orphans and vulnerable children, elderly with no productive capacity or persons with acute disability, LEAP 1000 was a pilot designed to add a new target group: pregnant women and mothers with infants under 1 year of age. The programme is implemented by the LEAP Management Secretariat (LMS) and the Department of Social Welfare, under the Ministry of Gender, Children and Social Protection. LEAP provides a bimonthly transfer, which ranges from GHc 64 to GHc 106 (approximately USD17–USD28 in 2015) based on the number of eligible beneficiaries in the household. Beneficiary households are targeted through a proxy-means test (PMT) with a sharp cut-off established by the LMS. Those households meeting the poverty criterion (a PMT score below the cut-off) were enrolled in LEAP 1000 from August 2015 onwards. In addition to the CT, eligible households received a fee waiver for enrolment into the National Health Insurance Scheme, providing access to free out-patient and in-patient services, dental services and maternal health services. The impact evaluation exploited the discontinuity at the PMT cut-off to establish a treatment and comparison group. Those falling just below the cut-off comprise the treatment group, and those just above the cut-off were sampled as the comparison group. Households close to the cut-off on both sides are highly similar in terms of their characteristics because they have very similar PMT scores. The baseline sample included 2497 households in 2015 and one follow-up was conducted after 23 months (Ghana Leap 1000 Evaluation Team, 2016; 2018). In Malawi, the beneficiaries include ultra-poor and labour-constrained households for whom the programme aims to reduce poverty and hunger and increase school enrolment rates. The SCTP is operated by the Ministry of Gender, Children, Disability and Social Welfare with support from the Ministry of Finance, Economic Planning and Development as well as UNICEF Malawi. Average transfer amounts are ∼2000 Kwacha per month (∼3 USD). As of the last wave of data collection used in this study (December 2015), the programme was operating in 18 out of 28 districts and reached over 160 000 households. Households were first selected by village-level committees to identify poor households containing individuals with a chronic illness or disability and then a PMT was used to verify poverty status before households were enrolled. Transfers in the Malawi programme are adjusted for household size. There is also a schooling bonus that is based on the number of youths of school age in the household (Abdoulayi et al., 2016; 2014). The evaluation utilized an RCT design with 29 village clusters randomized into treatment and delayed-entry control arms in two traditional authorities (Salima and Mangochi) and four districts (Maganga, Ndindi, Jalasi and M’bwana Nyambi). The evaluation sample consisted of 3531 eligible households at baseline in 2013, and follow-up waves were conducted at 12 months (2014) and 24 months (2015) (Abdoulayi et al., 2016). The Zambia CGP programme commenced in 2010 with the primary objective of reducing extreme poverty and the intergenerational transfer of poverty. Specifically, the programme sought to improve some specific health and education outcomes including (1) improvement in food security, (2) reduction in child mortality and morbidity, (3) reduction in stunting and wasting, (4) increase in school enrolment and attendance and (5) increased asset ownership (American Institutes for Research, 2011). Beneficiaries of the programme included all households with a child under age 5 years. Households with newborn babies were immediately enrolled in the programme through a continuous system. The CGP was operated by the Ministry of Community Development, Mother and Child Health in three districts (Kalabo, Kaputa and Shangombo). These districts were targeted because they face the highest rates of malnutrition, morbidity and mortality. Moreover, ∼95% of beneficiaries in the region were estimated to be living below the extreme poverty line in 2010. Beneficiaries received a flat monthly transfer, which started at 60 Zambian Kwacha (revised to 70 Zambian Kwacha in 2014; ∼11 USD) (American Institutes for Research, 2016a). The total amount translates to ∼12 Kwacha per capita per month and is estimated to be sufficient to provide one additional meal per person per day. The evaluation utilized an RCT design, with 92 communities randomized into treatment and control (delayed entry) arms in three districts (Kalabo, Kaputa and Shangombo). The evaluation sample consisted of 2515 households at baseline in 2010, and follow-up waves were conducted at 24, 30, 36 and 48 months (American Institutes for Research, 2016a). In Zambia, the MCT programme started in two of the most deprived districts: Luwingu and Serenje and targets: (1) households headed by widows and caring for orphans; (2) households headed by an elderly person and caring for orphans and (3) households that have a member living with some form of disability. The programme began with the broad objective of reducing poverty and the intergenerational transmission of poverty. Specifically, the programme seeks to (1) improve food security among beneficiary households, (2) increase school enrolment and attendance and (3) increase asset ownership. The programme is also operated by the Ministry of Community Development, Mother and Child Health. Flat monthly transfers are provided in the same amount as in the CGP (started at 60 Kwacha per month, revised to 70 Kwacha in 2014—∼11 USD). The evaluation utilized an RCT design, whereby 90 communities (CWACS, or community welfare assistance committees) were randomly assigned to either treatment or control (delayed entry) status, and the total evaluation sample consisted of 3078 households at baseline. Data collection for the baseline survey occurred in 2011, with 24- and 36-month follow-ups (American Institutes for Research, 2016b). The Zimbabwe HSCT targets labour-constrained and food-poor households and seeks to increase households’ consumption and food security. The programme is administered and managed by the Department of Social Services in the Ministry of Public Service, and funding for the programme comes from the Zimbabwe government and external donors. Transfers are distributed bi-monthly and amounts range from 10 to 25 USD per month, varying based on household size. A total of about 55 000 households were benefiting from the programme as of the last data collection utilized in this analysis (2014). The evaluation uses a case–control design, with the treatment arm drawn from three districts (Binga, Mwenzi and Mudzi) and the comparison group drawn from three neighbouring districts (UMP, Chiredzei and Hwange) matched to the treatment districts based on agro-ecological characteristics, culture and level of development. The evaluation sample consists of 3063 households in 90 wards across six districts (60 treatment wards and 30 comparison wards). Baseline data were collected in 2013, and a 12-month follow-up survey was carried out in 2014 (American Institutes for Research, 2014a). In this analysis, we examine the incidence of acute illness (disaggregated into specific illnesses such as fever/malaria, respiratory and diarrhoea), seeking medical care, health spending and self-assessed health (see Supplementary Appendix I for detailed indicator construction by country). Measures of child and adult health outcomes were examined separately, as information collected varied by age, except for the Zambia MCT and Zambia CGP, where the health status of children was reported with the same indicators as for all household members. In all programmes, questions were asked to the main household respondent (generally the main CT recipient or household head) on the health of all individuals in the household, with a recall period of 2–4 weeks preceding the survey (2 weeks in Ghana, Malawi and Zambia and 4 weeks Zimbabwe; Supplementary Appendix 1). Health outcomes for children under age 5 years include seeking preventive care, seeking medical treatment for various illnesses, the incidence of illness (diarrhoea, fever/malaria and cough/respiratory illness) and health spending. Controls included age in years; sex; main respondent characteristics (age, marital status and education); household size, household access to clean water, improved toilet, the experience of shocks, per capita monthly expenditures; and district (more details and availability by country outlined in Supplementary Appendix 2). In Ghana LEAP 1000, education is measured for the household head, not the main questionnaire respondent. We first summarize outcomes by treatment status and assess baseline balance between groups by regressing background characteristics and outcomes (at baseline) on the treatment indicator. Next, we assessed differential attrition between treatment and control groups across survey waves and age groups (sub-samples) by running a regression with an indicator for a respondent being observed at follow-up (i.e. not attritted) as the dependent variable and treatment dummy as the independent variable. A significant difference in our outcome(s) with respect to the treatment dummy in this regression would suggest that there was differential attrition, potentially threatening internal validity. To estimate the impact of UCT programmes on morbidity and health-seeking behaviour, a difference-in-differences (DID) estimation method was used. The estimating equation is as follows: where individual i’s treatment status is represented by T. R denotes the survey round taking the value of 1 for follow-up and 0 for baseline while j represents the health outcome of interest. X is a vector of baseline control variables, and is the error term. The coefficient of the interaction term () indicates the intent-to-treat programme impact. All analyses were conducted separately for each country and by age groups (under 5 years; 5–19 years; 20–59 years; 60 and above). For binary outcomes, linear probability models (LPMs) were estimated with robust standard errors adjusted for clustering at the community level. These models were chosen over logistic regressions for ease of interpretation of the interaction term (Norton et al., 2004), which represents the programme effect. Moreover, LPM indicates marginal effects (percentage point changes), which are meaningful for interpretation. For continuous outcomes (health expenditures), we run ordinary least squares regressions and report coefficient estimates that can be interpreted as the average change in health expenditures in local currency. Data sets for the Ghana LEAP 1000 evaluation are publicly available through the Carolina Population Center (https://data.cpc.unc.edu/projects/13/view). Other data sets are not publicly available.

AI Digest

Study Justification:

– Unconditional cash transfers have been shown to have positive impacts on consumption, food security, productive activities, and schooling.
– However, there is limited evidence on the impact of cash transfers on health-seeking behaviors and morbidity, especially in the context of Africa.
– Given the differences in context and program design between Africa and Latin America, more evidence from Africa is needed.
– This study aims to investigate the impact of unconditional cash transfers on morbidity and health-seeking behavior in Ghana, Malawi, Zambia, and Zimbabwe.

Highlights:

– The study used data from experimental and quasi-experimental study designs of five government cash transfer programs in the four countries.
– The results indicate positive impacts of the cash transfer programs on health-seeking behavior when ill and on health expenditures.
– However, the impacts on morbidity were mixed, suggesting the need for more research on longer-term impacts, mechanisms of impact, and moderating factors.
– The findings also highlight the importance of disaggregating the impacts of cash transfers on health between conditional and unconditional programs.

Recommendations:

– Further research is needed to understand the longer-term impacts of unconditional cash transfers on health outcomes.
– More studies should be conducted to explore the mechanisms through which cash transfers affect health-seeking behavior and morbidity.
– The impacts of cash transfers on health should be examined in different contexts and populations to identify moderating factors.
– When summarizing the impacts of cash transfers on health, findings from conditional and unconditional programs should be analyzed separately.

Key Role Players:

– Researchers and research institutions to conduct further studies on the impact of cash transfers on health in Africa.
– Government agencies responsible for implementing cash transfer programs to collaborate with researchers and incorporate health outcomes in program evaluations.
– Non-governmental organizations and international donors to provide funding and support for research and program implementation.

Cost Items for Planning Recommendations:

– Research funding for conducting additional studies on the impact of cash transfers on health outcomes.
– Budget for data collection, including surveys and interviews with program beneficiaries.
– Costs associated with data analysis and interpretation.
– Resources for program evaluation and monitoring, including the collection of health-related data.
– Funding for capacity building and training of program staff and researchers involved in the implementation and evaluation of cash transfer programs.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on experimental and quasi-experimental study designs from five government cash transfer programs in Ghana, Malawi, Zambia, and Zimbabwe. The impacts were estimated using difference-in-differences models with longitudinal data. The findings indicate positive impacts on health seeking when ill and on health expenditures, but the impacts on morbidity were mixed. The evidence is based on rigorous study designs and provides valuable insights into the effects of unconditional cash transfers on health-seeking behavior and morbidity in Africa. However, to improve the strength of the evidence, it would be beneficial to conduct longer-term studies to assess the sustainability of the impacts, investigate the mechanisms of impact, and explore moderating factors. Additionally, disaggregating the findings from conditional and unconditional programs when summarizing the impacts of cash transfers on health would provide more nuanced insights.

Abstract

Data used in this study came from five UCT programmes from four countries in Africa. These programmes are the Ghana Livelihood Empowerment Against Poverty (LEAP) 1000 programme, the Malawi Social Cash Transfer Programme (Malawi SCTP), the Zambia Child Grant Programme (Zambia CGP), the Zambia Multiple Categorical Targeting Programme (Zambia MCT) and the Zimbabwe National Harmonized Social Cash Transfer Programme (Zimbabwe HSCT) (American Institutes for Research, 2014a; 2014b; Ghana Leap 1000 Evaluation Team, 2018; Ward et al., 2010). Table 1 summarizes the geographical regions where data were collected, survey years and household sample sizes. In all countries examined, study designs were either cluster randomized controlled trial (RCT) (Malawi and Zambia) or quasi-experimental (Ghana and Zimbabwe). The Ghana evaluation sampled households around an eligibility score cut-off for the programme to construct a treatment and comparison group. In Zimbabwe, comparison districts were selected based on agro-ecological characteristics (they neighbour each other), culture and level of development. Data summary and sample size We provide brief descriptions of these programmes below. The Ghana LEAP 1000 programme is an extension of the country’s flagship anti-poverty programme, LEAP. While LEAP is targeted to extremely poor households with orphans and vulnerable children, elderly with no productive capacity or persons with acute disability, LEAP 1000 was a pilot designed to add a new target group: pregnant women and mothers with infants under 1 year of age. The programme is implemented by the LEAP Management Secretariat (LMS) and the Department of Social Welfare, under the Ministry of Gender, Children and Social Protection. LEAP provides a bimonthly transfer, which ranges from GHc 64 to GHc 106 (approximately USD17–USD28 in 2015) based on the number of eligible beneficiaries in the household. Beneficiary households are targeted through a proxy-means test (PMT) with a sharp cut-off established by the LMS. Those households meeting the poverty criterion (a PMT score below the cut-off) were enrolled in LEAP 1000 from August 2015 onwards. In addition to the CT, eligible households received a fee waiver for enrolment into the National Health Insurance Scheme, providing access to free out-patient and in-patient services, dental services and maternal health services. The impact evaluation exploited the discontinuity at the PMT cut-off to establish a treatment and comparison group. Those falling just below the cut-off comprise the treatment group, and those just above the cut-off were sampled as the comparison group. Households close to the cut-off on both sides are highly similar in terms of their characteristics because they have very similar PMT scores. The baseline sample included 2497 households in 2015 and one follow-up was conducted after 23 months (Ghana Leap 1000 Evaluation Team, 2016; 2018). In Malawi, the beneficiaries include ultra-poor and labour-constrained households for whom the programme aims to reduce poverty and hunger and increase school enrolment rates. The SCTP is operated by the Ministry of Gender, Children, Disability and Social Welfare with support from the Ministry of Finance, Economic Planning and Development as well as UNICEF Malawi. Average transfer amounts are ∼2000 Kwacha per month (∼3 USD). As of the last wave of data collection used in this study (December 2015), the programme was operating in 18 out of 28 districts and reached over 160 000 households. Households were first selected by village-level committees to identify poor households containing individuals with a chronic illness or disability and then a PMT was used to verify poverty status before households were enrolled. Transfers in the Malawi programme are adjusted for household size. There is also a schooling bonus that is based on the number of youths of school age in the household (Abdoulayi et al., 2016; 2014). The evaluation utilized an RCT design with 29 village clusters randomized into treatment and delayed-entry control arms in two traditional authorities (Salima and Mangochi) and four districts (Maganga, Ndindi, Jalasi and M’bwana Nyambi). The evaluation sample consisted of 3531 eligible households at baseline in 2013, and follow-up waves were conducted at 12 months (2014) and 24 months (2015) (Abdoulayi et al., 2016). The Zambia CGP programme commenced in 2010 with the primary objective of reducing extreme poverty and the intergenerational transfer of poverty. Specifically, the programme sought to improve some specific health and education outcomes including (1) improvement in food security, (2) reduction in child mortality and morbidity, (3) reduction in stunting and wasting, (4) increase in school enrolment and attendance and (5) increased asset ownership (American Institutes for Research, 2011). Beneficiaries of the programme included all households with a child under age 5 years. Households with newborn babies were immediately enrolled in the programme through a continuous system. The CGP was operated by the Ministry of Community Development, Mother and Child Health in three districts (Kalabo, Kaputa and Shangombo). These districts were targeted because they face the highest rates of malnutrition, morbidity and mortality. Moreover, ∼95% of beneficiaries in the region were estimated to be living below the extreme poverty line in 2010. Beneficiaries received a flat monthly transfer, which started at 60 Zambian Kwacha (revised to 70 Zambian Kwacha in 2014; ∼11 USD) (American Institutes for Research, 2016a). The total amount translates to ∼12 Kwacha per capita per month and is estimated to be sufficient to provide one additional meal per person per day. The evaluation utilized an RCT design, with 92 communities randomized into treatment and control (delayed entry) arms in three districts (Kalabo, Kaputa and Shangombo). The evaluation sample consisted of 2515 households at baseline in 2010, and follow-up waves were conducted at 24, 30, 36 and 48 months (American Institutes for Research, 2016a). In Zambia, the MCT programme started in two of the most deprived districts: Luwingu and Serenje and targets: (1) households headed by widows and caring for orphans; (2) households headed by an elderly person and caring for orphans and (3) households that have a member living with some form of disability. The programme began with the broad objective of reducing poverty and the intergenerational transmission of poverty. Specifically, the programme seeks to (1) improve food security among beneficiary households, (2) increase school enrolment and attendance and (3) increase asset ownership. The programme is also operated by the Ministry of Community Development, Mother and Child Health. Flat monthly transfers are provided in the same amount as in the CGP (started at 60 Kwacha per month, revised to 70 Kwacha in 2014—∼11 USD). The evaluation utilized an RCT design, whereby 90 communities (CWACS, or community welfare assistance committees) were randomly assigned to either treatment or control (delayed entry) status, and the total evaluation sample consisted of 3078 households at baseline. Data collection for the baseline survey occurred in 2011, with 24- and 36-month follow-ups (American Institutes for Research, 2016b). The Zimbabwe HSCT targets labour-constrained and food-poor households and seeks to increase households’ consumption and food security. The programme is administered and managed by the Department of Social Services in the Ministry of Public Service, and funding for the programme comes from the Zimbabwe government and external donors. Transfers are distributed bi-monthly and amounts range from 10 to 25 USD per month, varying based on household size. A total of about 55 000 households were benefiting from the programme as of the last data collection utilized in this analysis (2014). The evaluation uses a case–control design, with the treatment arm drawn from three districts (Binga, Mwenzi and Mudzi) and the comparison group drawn from three neighbouring districts (UMP, Chiredzei and Hwange) matched to the treatment districts based on agro-ecological characteristics, culture and level of development. The evaluation sample consists of 3063 households in 90 wards across six districts (60 treatment wards and 30 comparison wards). Baseline data were collected in 2013, and a 12-month follow-up survey was carried out in 2014 (American Institutes for Research, 2014a). In this analysis, we examine the incidence of acute illness (disaggregated into specific illnesses such as fever/malaria, respiratory and diarrhoea), seeking medical care, health spending and self-assessed health (see Supplementary Appendix I for detailed indicator construction by country). Measures of child and adult health outcomes were examined separately, as information collected varied by age, except for the Zambia MCT and Zambia CGP, where the health status of children was reported with the same indicators as for all household members. In all programmes, questions were asked to the main household respondent (generally the main CT recipient or household head) on the health of all individuals in the household, with a recall period of 2–4 weeks preceding the survey (2 weeks in Ghana, Malawi and Zambia and 4 weeks Zimbabwe; Supplementary Appendix 1). Health outcomes for children under age 5 years include seeking preventive care, seeking medical treatment for various illnesses, the incidence of illness (diarrhoea, fever/malaria and cough/respiratory illness) and health spending. Controls included age in years; sex; main respondent characteristics (age, marital status and education); household size, household access to clean water, improved toilet, the experience of shocks, per capita monthly expenditures; and district (more details and availability by country outlined in Supplementary Appendix 2). In Ghana LEAP 1000, education is measured for the household head, not the main questionnaire respondent. We first summarize outcomes by treatment status and assess baseline balance between groups by regressing background characteristics and outcomes (at baseline) on the treatment indicator. Next, we assessed differential attrition between treatment and control groups across survey waves and age groups (sub-samples) by running a regression with an indicator for a respondent being observed at follow-up (i.e. not attritted) as the dependent variable and treatment dummy as the independent variable. A significant difference in our outcome(s) with respect to the treatment dummy in this regression would suggest that there was differential attrition, potentially threatening internal validity. To estimate the impact of UCT programmes on morbidity and health-seeking behaviour, a difference-in-differences (DID) estimation method was used. The estimating equation is as follows: where individual i’s treatment status is represented by T. R denotes the survey round taking the value of 1 for follow-up and 0 for baseline while j represents the health outcome of interest. X is a vector of baseline control variables, and is the error term. The coefficient of the interaction term () indicates the intent-to-treat programme impact. All analyses were conducted separately for each country and by age groups (under 5 years; 5–19 years; 20–59 years; 60 and above). For binary outcomes, linear probability models (LPMs) were estimated with robust standard errors adjusted for clustering at the community level. These models were chosen over logistic regressions for ease of interpretation of the interaction term (Norton et al., 2004), which represents the programme effect. Moreover, LPM indicates marginal effects (percentage point changes), which are meaningful for interpretation. For continuous outcomes (health expenditures), we run ordinary least squares regressions and report coefficient estimates that can be interpreted as the average change in health expenditures in local currency. Data sets for the Ghana LEAP 1000 evaluation are publicly available through the Carolina Population Center (https://data.cpc.unc.edu/projects/13/view). Other data sets are not publicly available.

Materials

https://efashare.b-cdn.net/materials/35e67b591f90b7f0d103628415e21088390a1b9f4fdc7c190b465dfff3f858b5/czac014_supp.zip

Innovations

Based on the provided information, the innovation that can be recommended to improve access to maternal health is the implementation of unconditional cash transfer (UCT) programs. These programs have shown positive impacts on consumption, food security, productive activities, and schooling. In the context of maternal health, UCT programs have been found to improve health-seeking behavior when ill and increase health expenditures. However, the impact on morbidity is mixed and requires further research.

The specific UCT programs mentioned in the study include the Ghana Livelihood Empowerment Against Poverty (LEAP) 1000 program, the Malawi Social Cash Transfer Program (SCTP), the Zambia Child Grant Program (CGP), the Zambia Multiple Categorical Targeting Program (MCT), and the Zimbabwe National Harmonized Social Cash Transfer Program (HSCT).

These programs provide cash transfers to eligible households, targeting specific vulnerable groups such as pregnant women and mothers with infants under 1 year of age. In addition to the cash transfers, some programs also provide fee waivers for enrollment into the National Health Insurance Scheme, which grants access to free outpatient and inpatient services, dental services, and maternal health services.

The impact of these UCT programs on maternal health was assessed using experimental and quasi-experimental study designs, such as cluster randomized controlled trials (RCTs) and difference-in-differences models. The results indicated positive impacts on health-seeking behavior and health expenditures, but the effects on morbidity were mixed.

Further research is needed to understand the longer-term impacts of UCT programs on maternal health, as well as the mechanisms of impact and moderating factors. It is also important to disaggregate the findings from conditional and unconditional programs when summarizing the impacts of cash transfers on health.

Overall, implementing unconditional cash transfer programs can be an innovative approach to improve access to maternal health by providing financial support to vulnerable households and incentivizing health-seeking behavior.

AI Innovations Description

The recommendation based on the study is to implement unconditional cash transfer (UCT) programs to improve access to maternal health. The study found that UCT programs have positive impacts on health-seeking behavior and health expenditures. Specifically, the study examined five UCT programs in Ghana, Malawi, Zambia, and Zimbabwe. These programs provided cash transfers to households, targeting pregnant women and mothers with infants under 1 year of age. The cash transfers were accompanied by fee waivers for enrollment into the National Health Insurance Scheme, providing access to free outpatient and inpatient services, dental services, and maternal health services.

The study used experimental and quasi-experimental study designs, such as cluster randomized controlled trials and difference-in-differences models, to estimate the impacts of the UCT programs. The results indicated that the programs had positive impacts on health seeking when ill and on health expenditures. However, the impacts on morbidity were mixed.

Based on these findings, it is recommended to further research the longer-term impacts, mechanisms of impact, and moderating factors of UCT programs on maternal health. Additionally, it is suggested to disaggregate the impacts of cash transfers on health when summarizing the findings from both conditional and unconditional programs.

It is important to note that the data used in this study came from specific UCT programs in Ghana, Malawi, Zambia, and Zimbabwe. The programs included the Ghana Livelihood Empowerment Against Poverty (LEAP) 1000 program, the Malawi Social Cash Transfer Program (SCTP), the Zambia Child Grant Program (CGP), the Zambia Multiple Categorical Targeting Program (MCT), and the Zimbabwe National Harmonized Social Cash Transfer Program (HSCT). The study utilized data from cluster randomized controlled trials and quasi-experimental designs conducted in these countries.

For more detailed information on the study and the specific UCT programs examined, please refer to the original source.

AI Innovations Methodology

The study mentioned in the description investigates the impact of unconditional cash transfers (UCTs) on maternal health-seeking behavior and morbidity in Ghana, Malawi, Zambia, and Zimbabwe. The methodology used in this study involves the analysis of data from experimental and quasi-experimental study designs of five government cash transfer programs in the mentioned countries.

The impact of UCTs on health-seeking behavior and morbidity was estimated using a difference-in-differences (DID) model with longitudinal data. The DID estimation method compares changes in outcomes between the treatment group (those receiving the cash transfers) and the comparison group (those not receiving the cash transfers) before and after the implementation of the program. This allows for the identification of the program’s impact on health-seeking behavior and morbidity.

The study collected data from various sources, including cluster randomized controlled trials (RCTs) and quasi-experimental designs. The data included information on health outcomes, health-seeking behavior, health expenditures, and other relevant variables. The analysis was conducted separately for each country and by different age groups.

To estimate the impact of UCTs on health outcomes, linear probability models (LPMs) were used for binary outcomes, and ordinary least squares (OLS) regressions were used for continuous outcomes. Robust standard errors were adjusted for clustering at the community level to account for potential correlations within communities.

The findings of the study indicated positive impacts of UCTs on health-seeking behavior when ill and on health expenditures. However, the impacts on morbidity were mixed. The study also highlighted the need for more research on longer-term impacts, mechanisms of impact, and moderating factors.

It’s important to note that the data used in this study came from specific cash transfer programs in Africa, and the findings may not be generalizable to other contexts. Additionally, the availability of data sets may vary, with some being publicly available and others not.

Overall, the methodology used in this study provides valuable insights into the impact of unconditional cash transfers on maternal health-seeking behavior and morbidity in Africa.

Authors & Co-Authors

Statistics:

Citations: 1

Authors: 7

Identifiers:

DOI: 10.1093/heapol/czac014

ISSN: 02681080

Research Areas:

Community Interventions, Disability, Environmental, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Social Determinants, Workforce

Study Countries:

Ghana, Malawi, Multi-Countries, Zambia, Zimbabwe

Study Design:

Case-Control Study, Cohort Study, Cross Sectional Study, Grounded Theory, Quasi Experimental Study, randomised-control-trial

Study Approach:

Quantitative

Participants Gender:

Female