Institutional delivery and associated factors among women in Ghana: Findings from a 2017-2018 multiple indicator cluster survey

International Health, Volume 13, No. 6, Year 2021

Interpretation

Background: Institutional delivery is essential in reducing maternal morbidity and mortality. We investigated the prevalence of institutional delivery and associated factors among women in Ghana. Methods: National representative data from the 2017-2018 Ghana Multiple Indicator Cluster Survey was used for the analysis. The study included 3466 women, ages 15-49 y, who had a live birth in the last 2 y. Descriptive statistics were used to assess the prevalence of institutional delivery while multivariate logistic regression was used to assess the relationship between our variables of interest and institutional delivery. Results: The prevalence of institutional delivery among women in Ghana was 77.89% (95% confidence interval [CI] 75.29 to 80.50). High-income households (adjusted odds ratio [aOR] 2.13 [95% CI 1.36 to 3.35]), attending antenatal care at least four times (aOR 2.37 [95% CI 1.54 to 3.65]) and knowing one’s human immunodeficiency virus status (aOR 1.41 [95% CI 1.08 to 1.84]) were associated with higher odds of institutional delivery. Living in rural areas (aOR 0.43 [95% CI 0.27 to 0.67]), multiparity (aOR 0.59 [95% CI 0.41 to 0.85]) and no health insurance (aOR 0.57 [95% CI 0.44 to 0.74]) were associated with lower odds of institutional delivery. Conclusions: The government of Ghana may need to focus on increasing health insurance utilization and antenatal care attendance in order to increase the coverage of institutional delivery. We analysed data from the 2017–2018 MICS for Ghana. The MICS is a national representative household population-based survey.27 A total of 3466 women, ages 15–49 y, with a live birth within the last 2 y were included in the study. The MICS uses a two-stage sampling procedure. The first stage involves selection of census enumeration areas from each sampling strata using a probability proportional to the number of households in each enumeration area. In the second stage, households are selected from enumeration areas using systematic random sampling. A description of the MICS sampling design and data collection procedures has been published.27 Institutional delivery was the outcome variable of interest. The outcome variable was binary and coded as 1 for women who delivered at a health facility and 0 for those who were reported not to have delivered at a health facility. The predictor variables were age, marital status, education, household wealth, place of residence, attended antenatal care, parity, access to media, insurance status, know human immunodeficiency virus (HIV) status and number of sulfadoxine–pyrimethamine (SP) doses. SP was used to assess the intermittent preventive treatment regime in relation to institutional delivery. Age was categorized as 15–24, 25–34 and 35–49 y while marital status was categorized as never married and married/cohabitation. The other variables were categorized as follows: education (no formal education, primary education, secondary or higher education), health insurance status (no insurance, insurance), parity (primiparous, multiparous), attended antenatal care (0–3, ≥4), place of residence (rural, urban), know HIV status (yes, no) and number of SP doses (0–1, ≥2). Wealth quintiles were used to construct the household wealth variable. The upper two, middle and lower two wealth quintiles were used to represent high income, middle income and poor households, respectively. Access to media was also dichotomized as ‘yes’ for women who reported having access to any of the following: read the newspaper/magazine, listen to radio, watch television or use the internet at least once a week or almost every day, and ‘no’ for otherwise. Our variable selection was informed by previous studies11,28–30 and data available in the MICS.27 Descriptive statistics were used to assess the prevalence and characteristics of the study population. Bivariate and multivariable logistic regression models were used to assess the relationship between all our predictor variables of interest and the outcome variable. We accounted for clustering and stratification and applied sampling weights to account for the complex sampling design. A p-value <0.05 was considered statistically significant. Descriptive statistics and logistic regression analysis were done using SAS version 9.3 (SAS Institute, Cary, NC, USA).

AI Digest

Study Justification:

The study aimed to investigate the prevalence of institutional delivery and associated factors among women in Ghana. This is important because institutional delivery plays a crucial role in reducing maternal morbidity and mortality. By understanding the factors that influence institutional delivery, policymakers and healthcare providers can develop targeted interventions to improve maternal health outcomes in Ghana.

Study Highlights:

– The prevalence of institutional delivery among women in Ghana was found to be 77.89%.
– Factors associated with higher odds of institutional delivery included belonging to a high-income household, attending antenatal care at least four times, and knowing one’s HIV status.
– Factors associated with lower odds of institutional delivery included living in rural areas, having multiple children, and not having health insurance.

Study Recommendations for Lay Readers:

– The government of Ghana should focus on increasing health insurance utilization to improve access to institutional delivery services.
– Pregnant women should be encouraged to attend antenatal care visits regularly, as this is associated with higher odds of institutional delivery.
– Efforts should be made to improve healthcare services in rural areas to increase the coverage of institutional delivery.
– Women should be educated about the importance of knowing their HIV status and its impact on maternal health.

Study Recommendations for Policy Makers:

– Allocate resources to improve health insurance coverage and affordability, particularly for vulnerable populations, to increase the utilization of institutional delivery services.
– Strengthen antenatal care services by ensuring availability, accessibility, and quality, with a focus on reaching women in rural areas.
– Implement targeted interventions to address the specific needs of multiparous women and promote their access to institutional delivery.
– Enhance awareness campaigns and education programs to promote HIV testing and counseling among pregnant women, with a focus on the benefits for maternal health.

Key Role Players:

– Ministry of Health, Ghana
– National Health Insurance Authority
– Regional and District Health Directorates
– Health facilities and healthcare providers
– Non-governmental organizations (NGOs) working in maternal health

Cost Items for Planning Recommendations:

– Health insurance subsidies and premium waivers
– Infrastructure development and improvement of health facilities
– Training and capacity building for healthcare providers
– Outreach programs and mobile clinics to reach rural areas
– Public awareness campaigns and educational materials
– Monitoring and evaluation systems for tracking progress and impact

Strength of Evidence

N/A

Abstract

We analysed data from the 2017–2018 MICS for Ghana. The MICS is a national representative household population-based survey.27 A total of 3466 women, ages 15–49 y, with a live birth within the last 2 y were included in the study. The MICS uses a two-stage sampling procedure. The first stage involves selection of census enumeration areas from each sampling strata using a probability proportional to the number of households in each enumeration area. In the second stage, households are selected from enumeration areas using systematic random sampling. A description of the MICS sampling design and data collection procedures has been published.27 Institutional delivery was the outcome variable of interest. The outcome variable was binary and coded as 1 for women who delivered at a health facility and 0 for those who were reported not to have delivered at a health facility. The predictor variables were age, marital status, education, household wealth, place of residence, attended antenatal care, parity, access to media, insurance status, know human immunodeficiency virus (HIV) status and number of sulfadoxine–pyrimethamine (SP) doses. SP was used to assess the intermittent preventive treatment regime in relation to institutional delivery. Age was categorized as 15–24, 25–34 and 35–49 y while marital status was categorized as never married and married/cohabitation. The other variables were categorized as follows: education (no formal education, primary education, secondary or higher education), health insurance status (no insurance, insurance), parity (primiparous, multiparous), attended antenatal care (0–3, ≥4), place of residence (rural, urban), know HIV status (yes, no) and number of SP doses (0–1, ≥2). Wealth quintiles were used to construct the household wealth variable. The upper two, middle and lower two wealth quintiles were used to represent high income, middle income and poor households, respectively. Access to media was also dichotomized as ‘yes’ for women who reported having access to any of the following: read the newspaper/magazine, listen to radio, watch television or use the internet at least once a week or almost every day, and ‘no’ for otherwise. Our variable selection was informed by previous studies11,28–30 and data available in the MICS.27 Descriptive statistics were used to assess the prevalence and characteristics of the study population. Bivariate and multivariable logistic regression models were used to assess the relationship between all our predictor variables of interest and the outcome variable. We accounted for clustering and stratification and applied sampling weights to account for the complex sampling design. A p-value <0.05 was considered statistically significant. Descriptive statistics and logistic regression analysis were done using SAS version 9.3 (SAS Institute, Cary, NC, USA).

Materials

N/A

Innovations

Based on the analysis of the data from the 2017-2018 Ghana Multiple Indicator Cluster Survey, the following innovations could be considered to improve access to maternal health:

1. Increase health insurance utilization: The study found that women without health insurance had lower odds of institutional delivery. Implementing innovative strategies to increase health insurance coverage among pregnant women could help improve access to maternal health services.

2. Improve antenatal care attendance: The study found that women who attended antenatal care at least four times had higher odds of institutional delivery. Innovative approaches could be implemented to encourage and facilitate regular antenatal care visits, such as mobile clinics, telemedicine, or community-based outreach programs.

3. Address barriers in rural areas: The study found that living in rural areas was associated with lower odds of institutional delivery. Innovative solutions could be developed to address the unique challenges faced by women in rural areas, such as mobile health units, transportation services, or telemedicine.

4. Increase awareness of HIV status: The study found that knowing one’s HIV status was associated with higher odds of institutional delivery. Innovative strategies could be implemented to increase awareness and testing for HIV among pregnant women, such as community-based testing campaigns or integrating HIV testing into antenatal care services.

5. Target high-risk populations: The study found that multiparity was associated with lower odds of institutional delivery. Innovative approaches could be developed to specifically target high-risk populations, such as providing additional support and resources for women with multiple pregnancies.

These innovations, if implemented effectively, could help improve access to maternal health services and contribute to reducing maternal morbidity and mortality in Ghana.

AI Innovations Description

Based on the analysis of the data from the 2017-2018 Ghana Multiple Indicator Cluster Survey, the following recommendation can be made to improve access to maternal health:

1. Increase health insurance utilization: The study found that women without health insurance had lower odds of institutional delivery. Therefore, the government of Ghana should focus on increasing health insurance coverage, particularly among pregnant women, to ensure that they have access to affordable maternal health services.

2. Improve antenatal care attendance: The study found that women who attended antenatal care at least four times had higher odds of institutional delivery. Therefore, efforts should be made to encourage pregnant women to attend regular antenatal care visits, as this can help identify and manage any potential complications early on and increase the likelihood of delivering in a health facility.

By implementing these recommendations, the coverage of institutional delivery can be increased, leading to improved maternal health outcomes in Ghana.

AI Innovations Methodology

Based on the information provided, here are some potential recommendations to improve access to maternal health:

1. Increase health insurance utilization: The study found that women without health insurance had lower odds of institutional delivery. Therefore, efforts should be made to increase health insurance coverage among women in Ghana. This can be achieved through public awareness campaigns, subsidies for insurance premiums, and expanding the availability of affordable insurance options.

2. Improve antenatal care attendance: The study found that women who attended antenatal care at least four times had higher odds of institutional delivery. To improve access to maternal health, it is important to promote and facilitate regular antenatal care visits. This can be done through community outreach programs, mobile clinics, and ensuring that antenatal care services are easily accessible and affordable.

3. Enhance rural healthcare infrastructure: The study found that women living in rural areas had lower odds of institutional delivery. To address this disparity, it is crucial to invest in improving healthcare infrastructure in rural areas. This includes building and staffing more health facilities, ensuring the availability of skilled healthcare providers, and providing transportation options for pregnant women in remote areas.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could involve the following steps:

1. Define the target population: Identify the specific group of women in Ghana who would benefit from the recommendations, such as pregnant women or women of reproductive age.

2. Collect baseline data: Gather data on the current prevalence of institutional delivery, health insurance coverage, antenatal care attendance, and other relevant variables among the target population. This can be done through surveys, interviews, or analysis of existing data sources.

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the relationships between the variables of interest (e.g., institutional delivery, health insurance, antenatal care) and their impact on access to maternal health. This model should consider the potential effects of the recommendations on the outcome variable (e.g., increase in institutional delivery rates).

4. Input intervention scenarios: Input different scenarios into the simulation model to represent the potential impact of the recommendations. For example, simulate the effect of increasing health insurance coverage by a certain percentage or improving antenatal care attendance rates.

5. Analyze the results: Analyze the outputs of the simulation model to assess the potential impact of the recommendations on improving access to maternal health. This can include quantifying changes in institutional delivery rates, comparing different intervention scenarios, and identifying any potential barriers or limitations.

6. Validate the model: Validate the simulation model by comparing the predicted outcomes with real-world data or expert opinions. This helps ensure the accuracy and reliability of the model’s predictions.

7. Communicate findings and make recommendations: Present the findings of the simulation analysis to relevant stakeholders, such as policymakers, healthcare providers, and community organizations. Use the results to inform decision-making and advocate for the implementation of the recommended interventions.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and available data in Ghana.

Author

Dima Health

Statistics:

Citations: 4

Identifiers:

DOI: 10.1093/inthealth/ihab002

ISSN: 18763413

Research Areas:

Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Social Determinants

Study Countries:

Ghana

Study Design:

Case-Control Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female