Fathers’ Financial Support of Children in a Low Income Community in South Africa

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Study Justification:
– The study aims to understand children’s receipt of financial support from their fathers in a low-income, Black community in urban South Africa.
– The study provides valuable insights into father involvement and financial support in the South African context.
– The study uses data from the Birth to Twenty Cohort study, which is the longest running birth cohort study in Africa and offers rich data on father involvement.
Study Highlights:
– Most children in the study received full or partial financial support from their fathers throughout their life course.
– A high proportion of children continued to receive support after a parental union dissolution.
– Factors such as pre-dissolution support, father’s education, and the presence of extended kin influenced the variation in the receipt of support after a union dissolution.
Study Recommendations:
– Policy makers should recognize the importance of fathers’ financial support for children in low-income communities and develop strategies to promote and enhance father involvement.
– Interventions should focus on providing support and resources to fathers, particularly those with lower education levels, to ensure their ability to contribute financially to their children’s well-being.
– Programs should also consider the role of extended kin in providing support to children after a union dissolution and explore ways to strengthen these networks.
Key Role Players:
– Researchers and data analysts to analyze the data and provide insights.
– Policy makers and government officials to develop and implement policies and interventions.
– Community organizations and social workers to provide support and resources to fathers and families.
– Non-governmental organizations (NGOs) to advocate for father involvement and provide additional support services.
Cost Items for Planning Recommendations:
– Research and data analysis costs.
– Costs for developing and implementing policies and interventions.
– Costs for training and capacity building for community organizations and social workers.
– Costs for awareness campaigns and public education initiatives.
– Costs for monitoring and evaluation of interventions and programs.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are a few areas for improvement. Firstly, the study is based on data from the Birth to Twenty Cohort study, which is a well-established and long-running study. This adds credibility to the findings. Additionally, the study used both prospective and retrospective data collection methods, which helps to enhance the validity of the measures. However, there are a couple of limitations that need to be acknowledged. Firstly, most of the information about fathers came from mothers or other caregivers, which may introduce potential biases in reporting. Secondly, the use of retrospective data can be subject to memory recall issues. To improve the strength of the evidence, it would be beneficial to include data from fathers themselves to validate the reports provided by mothers. Additionally, conducting follow-up interviews with participants who dropped out of the study could provide insights into any potential biases introduced by survivor bias.

We used data from the Birth to Twenty Cohort study to understand children’s receipt of financial support from their fathers in a low income, Black community in urban South Africa. Specifically, we (1) described fathers’ financial support over the life course of children; (2) estimated survival probabilities of receiving support for all children and notreceiving support for children who experienced a parental union dissolution; and (3) identified factors that explained variation in the receipt of support after a union dissolution. Results suggest that most children received full or partial support throughout the life course. Furthermore, a high proportion of children received support after a union dissolution with much of the variation driven by pre-dissolution support, father’s education and the presence of extended kin.

Bt20 has been the longest running birth cohort study in Africa situated in the greater Johannesburg-Soweto municipality in South Africa (Sabet et al. 2009; Yach et al. 1991). The majority of families, most of whom were Black, came from socioeconomically disadvantaged circumstances. Bt20 was initiated as an observational, systematic study of human development, health and well-being, from birth extended through to young adulthood. Data collection covered a broad range of topics including anthropometric measures, nutrition, family composition, socioeconomic circumstances, childcare, parenting, cognitive development, and social experiences at home, school, and in the community. Prospective data collection began in the antenatal period and continued with approximately 21 follow up visits until age 23. Children born between April and June 1990 and resident for at least 6 months in the Soweto-Johannesburg municipality were enrolled into the study (n = 3273). The cohort included Black, White, Indian, and Colored children but we limited this analysis to only the Black children (n = 2568) who comprised the largest proportion of the cohort in line with the population distribution of the area. Even though data have been collected through age 23, this analysis used age 18 as the end point. While these data are not nationally representative, they offer some of the richest data on father involvement in the South African context, and therefore, are highly suitable for this analysis. Data in Bt20 on father involvement have been collected in two ways. Prospective data collected as part of household rosters to determine father co-residence, father contact and provision of financial support by fathers for most years of data collection. In addition, a retrospective questionnaire specifically focusing on father involvement across the child’s life course was administered at year 18. The questionnaires, most of which were answered by mothers, included detailed information on fathers’ co-residence with the child, extent of contact if not co-resident, provision of financial support, and other forms of interaction with the child for every year from birth until age 18. To both maximize our sample size and improve the validity of our measures, we used the retrospective data to supplement the prospective data but always privileged the prospective when it was available. There are two drawbacks that need to be acknowledged. One, most of the information about fathers came from mothers or other caregivers. Research from the US context has highlighted the potential biases in mothers’ reports, which consistently show underreporting of father involvement (Coley and Morris 2002). It is difficult to establish the extent of such bias in the Bt20 data but comparison of mothers’ reports of father contact over the life course and fathers’ reports of their own involvement (from the year 18 biological father questionnaires) suggested potential underreporting. Two, the use of retrospective data introduced problems associated with memory recall the farther back in time that data were sought. However, when we compared retrospective reports of father presence in the 0–2 year period with prospective data for the same time period, we found that 85 % of reports matched. Attrition over the course of the BT20 study has been about 30 %, mostly occurring during infancy and early childhood when women moved back to their rural homes after giving birth (Norris et al. 2007). A small number of children were lost to follow-up as a result of death. There have been very few withdrawals from the study. After removing non-Black children, the sample was 1,942 girls and boys followed up from birth to age 18, out of which, 1,557 were administered the retrospective father questionnaire. Table 1 shows descriptive characteristics of the analytical sample at the time of birth. Selected characteristics of analytical sample at time of birth (N = 1,557) A little more than a third of the cohort was composed of first births and the mean age of mothers at birth of the index child was 25.8 years. More than a third of all mothers were married or living together (a term used synonymously with cohabiting) with their partners. The majority of mothers had at least some secondary school education. We found a similar distribution for fathers on educational attainment though there was a sizeable missing proportion. The household wealth index used in this analysis was computed as quintile rankings of asset scores based on home ownership, access to regular electricity and ownership of car, TV, refrigerator, and phone. It ranged from 1 (very poor) to 5 (wealthy) and showed the highest proportions in the 2nd and 3rd quintile. Finally, the majority of households were classified as extended family structure although there were a sizeable number of records with missing data. Children’s receipt of financial support was treated as a dichotomous outcome (1/0) based on responses to the question, “In the past year, who was mainly responsible for the material support of the child?” To examine the timing of children receiving financial support from fathers, we used Kaplan–Meier estimation techniques to determine the survival probabilities of (1) receiving financial support from fathers for all children, and (2) not receiving financial support from fathers for those children who experienced a union dissolution. Although we recognized that the events of interest could recur, in these analyses we considered only the first observed event because of insufficient sample size. To examine correlates of father support provision post-union dissolution, we used a discrete time event history model. The child cohort was comprised of all children who had ever experienced a parental union dissolution before the age of 18. A child entered the cohort at the year of parental union dissolution. The dependent variable or event of interest occurred when a child received financial support from the father for the first time post-dissolution. Children who received support in the year of dissolution were included in the analysis and their odds of experiencing the event started at the year of dissolution. An observation was censored if the event did not occur by the age of 18 when the observation period ended or when the father died. Each child’s exposure time was divided into child-years starting at the time of parental union dissolution and consisting of 1 year intervals resulting in 3,777 child years of exposure. We used logistic models in SPSS to estimate the odds of children receiving financial support in the post-dissolution period. Paternal attributes included father’s age and educational level at time of birth of the child, which was also treated as a measure for employment potential. The maternal characteristics included mother’s age and education at time of birth, and whether she entered a new union following dissolution in the first 5 years after dissolution. Child characteristics included sex of child, and age at time of parental union dissolution categorized into four developmental stages (0–2, 3–5, 6–11 and 12–18) and entered as a continuous variable. Kin involvement was treated as a continuous variable measured by number of co-resident non-parental adults (data available in the household rosters). Control variables included household wealth at time of birth measured by quintile ranking of asset score based on ownership of household items (1–5) and whether father provided any support before or at the time of union dissolution. All covariates were time constant except number of co-resident non-parental adults which was treated as time varying and measured at the beginning of each period. In our quest for maximizing sample size by integrating retrospective data with the prospective data, the analytic sample was composed of only those children who “survived” in the study until year 18. It is, therefore, possible that those children who were lost to follow up might have had weaker links to their fathers which would, in turn, contribute to an overestimation of father involvement in our analysis. We examined this issue by comparing the means of duration of father contact for children who dropped out and those who did not by age of attrition. With the exception of two attrition periods: 6 months–2 years and 12–13, none of the differences were significant suggesting that our estimates of father contact in this analysis were not seriously affected by survivor bias.

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Based on the provided information, it is not clear what specific innovations or recommendations are being sought to improve access to maternal health. The information provided focuses on a study about fathers’ financial support of children in a low-income community in South Africa. If you have any specific questions or if there is additional information you can provide, I would be happy to assist you further.
AI Innovations Description
The description provided is a research study that examines fathers’ financial support of children in a low-income community in South Africa. The study used data from the Birth to Twenty Cohort study, which is a long-term observational study of human development, health, and well-being. The study aimed to understand the patterns of financial support provided by fathers to their children throughout their lives, estimate the probabilities of receiving support after a parental union dissolution, and identify factors that explain the variation in support after a union dissolution.

The study found that most children in the community received either full or partial financial support from their fathers throughout their lives. Additionally, a high proportion of children continued to receive support after a parental union dissolution, with factors such as pre-dissolution support, father’s education, and the presence of extended kin influencing the variation in support.

The study used a combination of prospective and retrospective data collection methods to gather information on father involvement. However, there were limitations to the study, including potential biases in mothers’ reports of father involvement and problems associated with memory recall when using retrospective data.

Based on the findings of this study, a recommendation to improve access to maternal health could be to involve fathers in maternal health programs and services. Engaging fathers in prenatal care, childbirth education, and postnatal support can promote their understanding of the importance of maternal health and their role in supporting it. This can lead to increased financial and emotional support for mothers and children, ultimately improving access to maternal health services and outcomes.
AI Innovations Methodology
The provided text does not contain information about innovations or recommendations to improve access to maternal health. However, I can provide a general methodology to simulate the impact of recommendations on improving access to maternal health.

Methodology to simulate the impact of recommendations on improving access to maternal health:

1. Define the recommendations: Identify specific recommendations that aim to improve access to maternal health. These recommendations can include interventions, policies, or strategies targeting various aspects of maternal health, such as prenatal care, skilled birth attendance, postnatal care, and family planning.

2. Collect baseline data: Gather relevant data on the current state of maternal health in the target population. This can include information on maternal mortality rates, access to healthcare facilities, utilization of maternal health services, and socio-economic factors that may influence access to care.

3. Develop a simulation model: Create a simulation model that represents the target population and the healthcare system. The model should incorporate factors such as population demographics, healthcare infrastructure, availability of resources, and the impact of the recommended interventions.

4. Define intervention scenarios: Based on the recommendations identified in step 1, develop different intervention scenarios that can be simulated. These scenarios can include variations in the coverage and quality of maternal health services, changes in healthcare policies, or the introduction of new technologies or programs.

5. Simulate the impact: Run the simulation model using the baseline data and the defined intervention scenarios. The model should simulate the impact of each scenario on key indicators of maternal health, such as maternal mortality rates, access to prenatal care, and utilization of skilled birth attendance.

6. Analyze the results: Evaluate the outcomes of the simulation by comparing the indicators of maternal health between the different intervention scenarios and the baseline. Assess the potential improvements in access to maternal health services, identify any trade-offs or unintended consequences, and determine the effectiveness of the recommendations.

7. Refine and iterate: Based on the results and analysis, refine the recommendations and simulation model as necessary. Repeat the simulation process with updated scenarios and data to further assess the impact of the recommendations on improving access to maternal health.

By following this methodology, policymakers and researchers can gain insights into the potential impact of different recommendations on improving access to maternal health. This can inform decision-making and help prioritize interventions that are most likely to have a positive impact on maternal health outcomes.

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