Socio-economic and demographic determinants of female genital mutilation in sub-Saharan Africa: analysis of data from demographic and health surveys

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Study Justification:
This study aimed to examine the socioeconomic and demographic factors associated with female genital mutilation (FGM) among women and their daughters in sub-Saharan Africa (SSA). FGM has severe repercussions and is considered illegal in many countries. The World Health Organization (WHO), human rights organizations, and governments in SSA have made efforts to end the practice. Understanding the determinants of FGM can help inform interventions and policies to address this harmful practice.
Highlights:
1. The study used data from Demographic and Health Surveys conducted between 2010 and 2018 in 12 countries in SSA.
2. The study found that household wealth and education level were associated with the likelihood of women and their daughters undergoing FGM. Women and daughters in the richest wealth quintile and with higher levels of education were less likely to undergo FGM.
3. Age and rural residence were also factors associated with FGM. Older women and daughters were more likely to undergo FGM, while women in rural areas were less likely to undergo FGM compared to urban areas.
4. Married women and their daughters had the highest odds of undergoing FGM.
5. The study recommends implementing multifaceted interventions such as advocacy, educational strategies, legislative instruments, women’s capacity-building, media advocacy, and community dialogue to address the challenges associated with FGM.
Recommendations for Lay Reader and Policy Maker:
1. Implement advocacy and educational strategies at both national and community levels to raise awareness about the harmful effects of FGM and promote behavior change.
2. Develop mentor-mentee programs, focus group discussions, and peer teaching initiatives to empower women and girls and provide them with information and support to resist FGM.
3. Strengthen legislative instruments to enforce laws against FGM and ensure accountability for those who perpetrate the practice.
4. Provide women with entrepreneurial training and other capacity-building initiatives to enhance their economic empowerment and reduce the social and economic factors that contribute to FGM.
5. Engage the media to advocate against FGM and promote positive social norms and attitudes towards women’s rights and health.
6. Facilitate community dialogues to address cultural beliefs and practices that perpetuate FGM and promote community-led efforts to abandon the practice.
Key Role Players:
1. Government agencies responsible for health, women’s rights, and education.
2. Non-governmental organizations (NGOs) working on women’s rights, gender equality, and health.
3. Community leaders, including religious leaders and traditional authorities.
4. Health professionals, including doctors, nurses, and midwives.
5. Educators and school administrators.
6. Media organizations and journalists.
Cost Items for Planning Recommendations:
1. Development and dissemination of educational materials and resources.
2. Training programs for health professionals, educators, and community leaders.
3. Awareness campaigns and media advocacy initiatives.
4. Community dialogues and workshops.
5. Entrepreneurial training programs for women.
6. Monitoring and evaluation of interventions.
7. Research and data collection on FGM prevalence and determinants.
8. Administrative and logistical support for implementing interventions.
Please note that the cost items provided are general categories and not actual cost estimates. The actual cost will depend on the specific context and scale of the interventions.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a large sample size and uses data from current Demographic and Health Surveys (DHS) conducted in 12 countries in sub-Saharan Africa. The study includes both bivariate and multivariable analyses using STATA version 13.0. The findings show significant associations between FGM and socioeconomic and demographic factors such as household wealth index, education level, age, rural residence, and marital status. The study also suggests actionable steps to improve the situation, including implementing multifaceted interventions, advocacy and educational strategies, legislative instruments, women capacity-building, media advocacy, and community dialogue. However, to further strengthen the evidence, future studies could consider using more accurate measures and examining the determinants of intention to discontinue or continue the practice in countries with different levels of FGM prevalence.

Background: Owing to the severe repercussions associated with female genital mutilation (FGM) and its illicit status in many countries, the WHO, human rights organisations and governments of most sub-Saharan African countries have garnered concerted efforts to end the practice. This study examined the socioeconomic and demographic factors associated with FGM among women and their daughters in sub-Saharan Africa (SSA). Methods: We used pooled data from current Demographic and Health Surveys (DHS) conducted between January 1, 2010 and December 31, 2018 in 12 countries in SSA. In this study, two different samples were considered. The first sample was made up of women aged 15–49 who responded to questions on whether they had undergone FGM. The second sample was made up of women aged 15–49 who had at least one daughter and responded to questions on whether their daughter(s) had undergone FGM. Both bivariate and multivariable analyses were performed using STATA version 13.0. Results: The results showed that FGM among women and their daughters are significantly associated with household wealth index, with women in the richest wealth quintile (AOR, 0.51 CI 0.48–0.55) and their daughters (AOR, 0.64 CI 0.59–0.70) less likely to undergo FGM compared to those in the poorest wealth quintile. Across education, the odds of women and their daughters undergoing FGM decreased with increasing level of education as women with higher level of education had the lowest propensity of undergoing FGM (AOR, 0.62 CI 0.57–0.68) as well as their daughters (AOR, 0.32 CI 0.24–0.38). FGM among women and their daughters increased with age, with women aged 45–49 (AOR = 1.85, CI 1.73–1.99) and their daughters (AOR = 12.61, CI 10.86–14.64) more likely to undergo FGM. Whiles women in rural areas were less likely to undergo FGM (AOR = 0.81, CI 0.78–0.84), their daughters were more likely to undergo FGM (AOR = 1.09, CI 1.03–1.15). Married women (AOR = 1.67, CI 1.59–1.75) and their daughters (AOR = 8.24, CI 6.88–9.87) had the highest odds of undergoing FGM. Conclusion: Based on the findings, there is the need to implement multifaceted interventions such as advocacy and educational strategies like focus group discussions, peer teaching, mentor–mentee programmes at both national and community levels in countries in SSA where FGM is practiced. Other legislative instruments, women capacity-building (e.g., entrepreneurial training), media advocacy and community dialogue could help address the challenges associated with FGM. Future studies could consider the determinants of intention to discontinue or continue the practice using more accurate measures in countries identified with low to high FGM prevalence.

The study used pooled data from current Demographic and Health Surveys (DHS) conducted between January 1, 2010 and December 31, 2018 in 12 countries in SSA. The countries are Burkina Faso, Chad, Ethiopia, Guinea, Kenya, Mali, Niger, Nigeria, Senegal, Sierra Leone, Tanzania and Togo. These 12 countries were included in the study because their surveys had information on FGM and had questions on whether the woman herself had undergone FGM; and whether she had daughter(s) who have also undergone FGM. We excluded two countries (Côte d’Ivoire and Gambia) because although they had data on FGM, data for daughters of women aged 15–49 were non-existent. The 12 countries were considered to provide a holistic and in-depth evidence of FGM in SSA. DHS is a nationwide survey executed every five years across low-and-middle-income countries (LMICs). It is representative of each of these countries. Women’s files that have responses by women aged 15–49 were used in the study. The surveys targeted core maternal and child health indicators such as FGM, unintended pregnancy, contraceptive use, skilled birth attendance, immunisation among under-fives and intimate partner violence. Stratified dual-stage sampling approach was employed and the same questions were posed to women of all these countries and thus make it feasible for multi-country study. The study involved cluster sampling process (i.e. enumeration areas [EAs]), followed by systematic household sampling within the selected EAs. The sample frame usually excludes nomadic and institutional groups such as prisoners and hotel occupants. In this study, two different samples were considered. The first sample was made up of 130,605 women aged 15–49 who responded to questions on whether they had undergone FGM. The second sample was made up of 122,941 women aged 15–49 who had at least one daughter and responded to questions on whether their daughter(s) had undergone FGM. We followed the ‘Strengthening the Reporting of Observational Studies in Epidemiology’ (STROBE) statement in conducting this study. The dependent variable in this study was “has had FGM or undergone FGM’. To derive this variable, respondents were asked if their genital area was “nicked with nothing removed;” “something removed,” or “sewn shut”. The responses were ‘Yes’ and ‘No’. These were coded as follows; No = 0, Yes = 1. Respondents who had daughters were further asked how many of their daughter(s) had their genital area “nicked with nothing removed;” “something removed,” or “sewn shut”. The response ranged from ‘no daughter’ to ‘1, 2, 3, 4, 5, 6, 7 daughters’. To provide a binary outcome, women who said none of their daughters went through FGM were coded as ‘No = 0’ and those who had at least one daughter going through FGM were coded ‘Yes = 1’. The main explanatory variable was ‘socio-economic status’. Following some previous studies [18–20], we used wealth quintile and maternal education as proxy measures of socio-economic status. In the standard DHS, wealth quintile is computed from data on household ownership of selected assets such as bicycle, materials used for house construction, television, type of water access and sanitation facilities. A composite variable, wealth status, is created from these assets through Principal Component Analysis (PCA) by placing households on a continuous measure of relative wealth after which households are categorized into five wealth quintiles namely poorest, poorer, middle, richer and richest [21]. Maternal education, on the other hand is a standardized variable of highest education attained and offers level of education in these four categories: No education, Primary, Secondary, and Higher [21]. We maintained the original categorization and coding of these two variables, (i. e. wealth quintile and maternal education). Apart from these independent variables, we controlled for country of survey and demographic variables like age, residence, marital status, occupation, frequency of reading newspaper, frequency of listening to radio and frequency of watching television. The coding of these variables are found in Table ​Table1.1. Apart from country of survey, which was included a priori, selection of all the explanatory variables was influenced by previous studies [14, 22, 23] and their availability in the datasets. Socio-demographic characteristics of respondents (Weighted) The analyses begun with computation of FGM among women aged 15–49 and their daughters. Secondly, we appended the datasets and this generated a total sample of 130,605 women aged 15–49 with data on FGM and 122,941 of women aged 15–49 who had at least one daughter and answered questions on FGM among their daughters. After appending, we presented the weighted socio-demographic characteristics of women aged 15–49 and those who had at least one daughter (see Table ​Table1).1). After this, we calculated the prevalence of FGM among women aged 15–49 and their daughters and presented them using charts (see Figs. 1, ​,2).2). We also calculated the prevalence of FGM among women and their daughters across their socio-economic status and other socio-demographic characteristics. We presented these using proportions, chi-square and p values. Finally, two binary logistic regression models were built. The first model (Model I) reports on womens’ FGM whilst the second model (Model II) reports on daughters’ FGM. Proportion of women aged 15–49 who have undergone FGM in SSA Proportion of daughters of women aged 15–49 who have undergone FGM in SSA The model fitness specification was done with the Hosmer–Lemeshow test while multicollinearity was checked using the variance inflation factor (VIF). The multicollinearity test for the explanatory variables for FGM among women (Mean VIF = 1.46, Max VIF = 1.90, Minimum = 1.06) and that of FGM among daughters (Mean VIF = 1.45, Max VIF = 1.80, Minimum = 1.06) showed no evidence of collinearity among the independent variables. Binary logistic regression was employed because our dependent variables were measured using a binary factor. Results for the regression analysis were presented as crude odds ratios (COR) and adjusted odds ratios (AOR), with their corresponding 95% confidence intervals (CI) signifying precision. The analyses were carried out with STATA version 13.0 with inherent sample weight applied. Sample weight was applied and the survey command (svy) was used to account for the complex sampling design of the survey. The DHS surveys obtain ethical clearance from the Ethics Committee of ORC Macro Inc. as well as Ethics Boards of partner organisations of the various countries such the Ministries of Health. During each of the surveys, either written or verbal consent was provided by the women. Since the data was not collected by the authors of this manuscript, we sought permission from MEASURE DHS’s website and access to the data was provided after our intent for the request was assessed and approved on 3rd April, 2019. The dataset is freely available at https://dhsprogram.com/data/available-datasets.cfm.

Based on the provided information, it appears that the study focused on analyzing the socio-economic and demographic factors associated with female genital mutilation (FGM) in sub-Saharan Africa (SSA). The study used data from Demographic and Health Surveys (DHS) conducted between 2010 and 2018 in 12 countries in SSA.

To improve access to maternal health and address the challenges associated with FGM, the study suggests implementing multifaceted interventions such as:

1. Advocacy and educational strategies: Conducting focus group discussions, peer teaching, and mentor-mentee programs at both national and community levels to raise awareness about the harmful effects of FGM and promote alternative practices.

2. Legislative instruments: Implementing laws and policies that explicitly prohibit FGM and provide legal protection for women and girls.

3. Women capacity-building: Providing entrepreneurial training and other skills development programs to empower women economically, enabling them to make independent decisions regarding their health and well-being.

4. Media advocacy: Using media platforms to disseminate information about the negative consequences of FGM and promote positive cultural practices that respect women’s rights and health.

5. Community dialogue: Facilitating open and inclusive discussions within communities to challenge traditional norms and beliefs surrounding FGM, promoting dialogue and understanding.

It is important to note that these recommendations are based on the findings of the study and should be implemented in conjunction with other evidence-based interventions to effectively improve access to maternal health and eliminate the practice of FGM.
AI Innovations Description
The study you described analyzed data from Demographic and Health Surveys conducted between 2010 and 2018 in 12 sub-Saharan African countries. The study aimed to identify the socioeconomic and demographic factors associated with female genital mutilation (FGM) among women and their daughters in these countries.

The study found several significant associations between FGM and various factors. Women and their daughters from wealthier households were less likely to undergo FGM compared to those from poorer households. Similarly, women with higher levels of education and their daughters had lower odds of undergoing FGM. FGM prevalence increased with age, with older women and their daughters being more likely to undergo the practice. Women in rural areas were less likely to undergo FGM, but their daughters were more likely to undergo it. Married women and their daughters had the highest odds of undergoing FGM.

Based on these findings, the study recommended implementing multifaceted interventions to address the challenges associated with FGM. These interventions could include advocacy and educational strategies such as focus group discussions, peer teaching, and mentor-mentee programs at both national and community levels. Other recommendations include the use of legislative instruments, women’s capacity-building (e.g., entrepreneurial training), media advocacy, and community dialogue.

The study also suggested that future research should consider studying the determinants of intention to discontinue or continue the practice of FGM using more accurate measures in countries with varying levels of FGM prevalence.

Overall, the study provides valuable insights into the socioeconomic and demographic factors associated with FGM in sub-Saharan Africa and offers recommendations for interventions to improve access to maternal health.
AI Innovations Methodology
The provided description is about a study that analyzed the socioeconomic and demographic factors associated with female genital mutilation (FGM) in sub-Saharan Africa. The study used pooled data from current Demographic and Health Surveys (DHS) conducted between January 1, 2010, and December 31, 2018, in 12 countries in SSA.

To improve access to maternal health, it is important to consider innovations that address the challenges associated with FGM. Here are some potential recommendations:

1. Advocacy and educational strategies: Implement multifaceted interventions such as focus group discussions, peer teaching, and mentor-mentee programs at both national and community levels. These strategies can help raise awareness about the harmful effects of FGM and promote alternative practices.

2. Legislative instruments: Strengthen existing legislation and develop new laws to prohibit and penalize FGM. This can create a legal framework that supports the elimination of FGM and protects the rights of women and girls.

3. Women capacity-building: Provide women with entrepreneurial training and skills development programs. This can empower women economically and provide them with alternative livelihood options, reducing the reliance on traditional practices like FGM.

4. Media advocacy: Utilize media platforms to raise awareness about the consequences of FGM and promote positive social norms. This can include TV and radio programs, documentaries, and social media campaigns.

5. Community dialogue: Facilitate open and inclusive discussions within communities to challenge the social norms and beliefs that perpetuate FGM. Engage community leaders, religious leaders, and influential individuals to promote dialogue and change.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as maternal mortality rates, antenatal care coverage, skilled birth attendance, and postnatal care utilization.

2. Collect baseline data: Gather data on the current status of these indicators in the target population or region. This can be done through surveys, health facility records, or existing data sources.

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the potential impact of the recommendations on the selected indicators. This model should consider the contextual factors, such as the prevalence of FGM, socioeconomic conditions, and healthcare infrastructure.

4. Input the intervention parameters: Define the parameters of each recommendation, such as the coverage and intensity of advocacy and educational strategies, the extent of legislative changes, the scale of women capacity-building programs, and the reach of media advocacy efforts.

5. Run the simulation: Use the model to simulate the impact of the recommendations over a specified time period. This can involve adjusting the intervention parameters and observing the resulting changes in the selected indicators.

6. Analyze the results: Evaluate the simulated outcomes and assess the potential improvements in access to maternal health. Compare the results with the baseline data to determine the effectiveness of the recommendations.

7. Refine and iterate: Based on the simulation results, refine the intervention parameters and repeat the simulation to explore different scenarios and optimize the impact on maternal health.

By using this methodology, policymakers and stakeholders can gain insights into the potential impact of the recommendations and make informed decisions on implementing interventions to improve access to maternal health in the context of FGM.

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