Effects of cash transfers on Children’s health and social protection in Sub-Saharan Africa: differences in outcomes based on orphan status and household assets

Abstract

BackgroundUnconditional and conditional cash transfer programmes (UCT and CCT) show potential to improve the well-being of orphans and other children made vulnerable by HIV/AIDS (OVC). We address the gap in current understanding about the extent to which household-based cash transfers differentially impact individual children’s outcomes, according to risk or protective factors such as orphan status and household assets.MethodsData were obtained from a cluster-randomised controlled trial in eastern Zimbabwe, with random assignment to three study arms – UCT, CCT or control. The sample included 5,331 children ages 6-17 from 1,697 households. Generalized linear mixed models were specified to predict OVC health vulnerability (child chronic illness and disability) and social protection (birth registration and 90% school attendance). Models included child-level risk factors (age, orphan status); household risk factors (adults with chronic illnesses and disabilities, greater household size); and household protective factors (including asset-holding). Interactions were systematically tested.ResultsOrphan status was associated with decreased likelihood for birth registration, and paternal orphans and children for whom both parents’ survival status was unknown were less likely to attend school. In the UCT arm, paternal orphans fared better in likelihood of birth registration compared with non-paternal orphans. Effects of study arms on outcomes were not moderated by any other risk or protective factors. High household asset-holding was associated with decreased likelihood of child’s chronic illness and increased birth registration and school attendance, but household assets did not moderate the effects of cash transfers on risk or protective factors.ConclusionOrphaned children are at higher risk for poor social protection outcomes even when cared for in family-based settings. UCT and CCT each produced direct effects on children’s social protection which are not moderated by other child- and household-level risk factors, but orphans are less likely to attend school or obtain birth registration. The effects of UCT and CCT are not moderated by asset-holding, but greater household assets predict greater social protection outcomes. Intervention efforts need to focus on ameliorating the additional risk burden carried by orphaned children. These efforts might include caregiver education, and additional incentives based on efforts made specifically for orphaned children.

Unconditional cash transfers for reducing poverty and vulnerabilities: effect on use of health services and health outcomes in low- and middle-income countries

“…We received the requested information, including the missing data, for the Baird 2010, Bazzi 2012, Cunha 2014, Fernald 2011, Galiani 2014, Leroy 2010, Luseno 2012, Miller 2008, Oxford Policy Management 2012, Pellerano 2014, Schady 2012, Seidenfeld 2013, and Ward 2010 studies. If we could not obtain missing information and data, we analysed only the available data and addressed the potential impact of the missing information and data on the findings of the review in the Discussion section.…”

“…Of the 21 studies included in this review, 16 were cluster-RCTs (Akresh 2012;Baird 2010;Beck 2015;Cunha 2014;Fernald 2011;Haushofer 2013;Leroy 2010;Luseno 2012;Miller 2008;Oxford Policy Management 2012;Paxson 2007;Pellerano 2014;Schady 2012;Seidenfeld 2013;Ward 2010), 4 were CBAs (Amarante 2011; Bazzi 2012; Galiani 2014; Salinas-Rodríguez 2014), and 1 was a cohort study (Agüero 2007). Cluster-RCTs were so common because -as some authors noted -by selecting clusters of individuals rather than individuals, there is less risk of bias from contamination.…”

“…Half (8 out of 16) of the included cluster-RCTs derived treatment e ects using DD methods (Cunha 2014;Leroy 2010;Miller 2008;Oxford Policy Management 2012;Paxson 2007;Pellerano 2014;Seidenfeld 2013;Ward 2010). Di erence-in-di erences methods are common econometric methods for assessing the e ect of a treatment on an outcome (Wooldridge 2010).…”

“…In essence, as used in the included studies, they derive a treatment e ect estimate by subtracting the before-and-a er di erence of the intervention group from that of the control group, thereby adjusting for underlying time trends of the outcome and for potential confounding that may have occurred despite random assignment or due to errors in random assignment of the intervention or interventions (see also Measures of treatment e ect). The other half of the included cluster-RCTs derived treatment e ects using regression analytic methods to control for potential confounding (Akresh 2012;Baird 2010;Beck 2015;Fernald 2011;Haushofer 2013, Luseno 2012Schady 2012). All four CBAs used DD methods to estimate treatment e ects (Amarante 2011; Bazzi 2012; Galiani 2014; Salinas-Rodríguez 2014).…”

A School Support Intervention and Educational Outcomes Among Orphaned Adolescents: Results of a Cluster Randomized Controlled Trial in Kenya

“…School attendance or absenteeism is another commonly examined outcome of educational interventions in SSA. Three of the five evaluated interventions improved attendance (Akresh et al, 2013; Crea et al, 2015; Hallfors et al, 2011;2015; Iritani et al, 2016; Robertson et al, 2013). The two programs that failed to improve attendance were the South African CCT (Pettifor et al, 2016) in which school attendance was universally high, and an intervention that only subsidized school uniforms for sixth graders in western Kenya (Duflo et al, 2015).…”