Time to initiation of antenatal care and its predictors among pregnant women in Ethiopia: Cox-gamma shared frailty model

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Study Justification:
– Timely initiation of antenatal care (ANC) is crucial for reducing maternal morbidity and mortality.
– However, the timing of ANC initiation among pregnant women in Ethiopia has not been well-studied.
– This study aimed to assess the time to first ANC visit and its predictors among pregnant women in Ethiopia.
Study Highlights:
– A community-based cross-sectional study was conducted among 7,543 pregnant women in Ethiopia using the Ethiopian Demographic Health Survey (EDHS) 2016 data.
– The median time to first ANC visit was 5 months.
– The study identified several predictors of time to first ANC visit, including education level, media exposure, household wealth index, distance from health facility, and community factors such as literacy and media access.
– The study found that women’s time to first ANC visit in Ethiopia was significantly later compared to the World Health Organization (WHO) recommendation.
Recommendations for Lay Readers:
– Maternal and child health policies and strategies should focus on women’s education and development.
– Interventions should be designed and implemented to increase timely initiation of ANC among pregnant women.
– Efforts should be made to improve access to healthcare facilities, especially in rural and nomadic regions.
– Media campaigns can play a role in increasing awareness and promoting early ANC visits.
Recommendations for Policy Makers:
– Allocate resources to improve women’s education and literacy rates, particularly in rural areas.
– Invest in infrastructure and transportation to reduce the distance between communities and healthcare facilities.
– Develop targeted interventions to address the barriers to early ANC initiation, such as lack of awareness and cultural beliefs.
– Strengthen health systems and ensure the availability of quality ANC services.
– Collaborate with media outlets to disseminate information and raise awareness about the importance of early ANC visits.
Key Role Players:
– Ministry of Health: Responsible for developing and implementing policies and strategies related to maternal and child health.
– Education Ministry: Involved in improving women’s education and literacy rates.
– Local Government Authorities: Responsible for infrastructure development and improving access to healthcare facilities.
– Non-Governmental Organizations (NGOs): Can provide support in implementing interventions and raising awareness.
– Media Outlets: Play a crucial role in disseminating information and promoting behavior change.
Cost Items for Planning Recommendations:
– Education programs and campaigns to improve women’s education and literacy: Includes costs for curriculum development, teacher training, and educational materials.
– Infrastructure development: Includes costs for building and renovating healthcare facilities, improving road networks, and transportation systems.
– Awareness campaigns: Includes costs for media production, advertising, and community mobilization.
– Training programs for healthcare providers: Includes costs for capacity building and continuing education.
– Monitoring and evaluation: Includes costs for data collection, analysis, and reporting to assess the impact of interventions.
Please note that the cost items provided are general categories and the actual cost estimation would require a detailed budget analysis based on specific interventions and local context.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a community-based cross-sectional study conducted among a large sample size of pregnant women in Ethiopia. The study utilized the Ethiopian Demographic Health Survey (EDHS) 2016 data and employed a two-stage stratified cluster sampling design. The study used appropriate statistical methods, such as the Kaplan-Meier method and Cox-gamma shared frailty model, to estimate time to first antenatal care visit and determine predictors. Adjusted Hazard Ratios (AHR) with 95% confidence intervals were reported. The study identified several predictors of time to first ANC visit, including education status, media exposure, household wealth index, distance from health facility, and community factors. The study concludes that women’s time to first ANC visit in Ethiopia is late compared to WHO recommendations and suggests the need for interventions to increase timely initiation of ANC. However, the study is limited by its cross-sectional design, which prevents establishing causality and temporality. To improve the evidence, future studies could consider using a stronger design, such as a cohort study, to establish temporality and reduce biases.

Background Timely initiating antenatal care (ANC) is crucial in the countries that have high maternal morbidity and mortality. However, in developing countries including Ethiopia, pregnant mother’s time to initiate antenatal care was not well-studied. Therefore, this study aimed to assess time to first ANC and its predictors among pregnant women in Ethiopia. Methods A community-based cross-sectional study was conducted among 7,543 pregnant women in Ethiopia using the Ethiopian Demographic Health Survey (EDHS), 2016 data. A two-stage stratified cluster sampling was employed. The Kaplan-Meier (KM) method was used to estimate time to first antenatal care visit. Cox-gamma shared frailty model was applied to determine predictors. Adjusted Hazard Ratio (AHR) with 95% confidence interval was reported as the effect size. Model adequacy was assessed by using the Cox-Snell residual plot. Statistical significance was considered at p value 40 years”), and religion (nominal categorical variable with categories ‘orthodox’, ‘Muslim’, ‘protestant ‘and ‘others’), marital status (nominal categorical variable with “not married”, “married”, and”Widowed and others”) and spousal age difference (ordinal variable “less than 5 years”, “5-10years” and “greater than 10 years”); socio-economic factors such as education level (ordinal categorical variable with categories ‘no education’, ‘primary education’, ‘secondary education’, and ‘higher education’), respondents occupational status (nominal categorical variable with “house wives”, “agricultural” or “none agricultural”), wealth index (ordinal categorical variables with”poorest”,”poorer”,”middle”,”richer” and “richest”), husband’s education as women, husband occupation (nominal categorical variable with “not working”, “agriculture” and “nonagricultural”), distance from health facility (nominal categorical variable with “distance is problem” and “distance is not problem”) and Mass media exposure (nominal categorical variable with “yes” and “no”); obstetric factors such as parity (ordinal variable with “1”, “2–3”, and “4+”) age at pregnancy (ordinal variable with “below 20 years”, “20–24”, “25–34” and “older than 35 years”) and Community level factors like region (nominal categorical variables with “Agrarian”, “Pastoralist” and “Urban”) and residence (nominal categorical variables with “urban” and “rural”) community level women literacy and husband literacy (nominal categorical variables with “illiterate” and “at least primary”), community media access (nominal categorical variables with “not accessed” and “accessed”) and community poverty level (nominal categorical variables with “in poverty level” and “above poverty”). Time was measured in month(s) from date of pregnancy to first ANC booking for women’s having at least one ANC visit and their current gestational age otherwise. Event was considered happened if the pregnant women had at least one ANC ad considered censored otherwise. Those who responded at least once a week for read a newspaper, listened to the radio, or watched television are considered to be regularly exposed to media and other considered as had no media exposure [2]. Regions (Amhara, harari, Oromia, SNNP and Tigray) whose livelihood mainly based on agriculture considered and with better distribution of health facilities classified as agrarian, regions whose livelihood based on mainly nomadism (Somali, Benshangul-Gumuz, Gambela and Afar) were with less access of Healthcare services considered as pastoralist or emerging regions and urban regions (city administration) those livelihood based on employment and trade (Addis Ababa and Dire Dawa) [31, 32]. Community considered as exposed to media if more than 50% of the community exposed to media and otherwise unexposed. Community considered as literate if at least 50% of women in the community attained at least primary education and illiterate if women in the community had no education or only less than half proportion of women in the community educated. Community husband considered as literate if at least 50% of husband in the community attained at least primary education and illiterate if husband in the community had no education or only less than half proportion of the husband in the community only educated. For this study secondary data from the 2016 EDHS was used. The data set downloaded from the website https://dhsprogram.com after approval letter for use had been obtained from the measure DHS. Variables were extracted from the EDHS 2016 kids and individual women’s data set using a data extraction tool. After data management, cleaning and weighting descriptive measures such as median, percentage, graphs, and frequency tables were used to characterize the study population. Time to first ANC visit was estimated using the Kaplan-Meier (K-M) method. The log-rank test was applied to compare survival time difference between groups of categorical variables with outcome of interest. A likelihood ratio test for a variance of frailty θ = 0 was checked and a statistical significant with p-value of <0.05 for cox-gamma shared frailty model were considered the frailty component contributes to the model and suggested presence of a within-cluster correlation. Cox gamma shared frailty model was modeled by taking enumeration areas/clusters as a random effect to identify predictors of time to first antenatal care booking among pregnant women in Ethiopia. Model adequacy was checked using Cox-Snell residuals subjective evaluation Stata 14.0/SE was used for the data management and analysis. In statistical terms, a frailty model is a random effect model for time-to-event data, where the random effect (the frailty) has a multiplicative effect on the baseline hazard function [33]. In shared frailty study, the survival experience of individuals from the same cluster may be more similar than that for individuals from different clusters. Thus it is responsible for creating dependence between event times in a cluster. This dependence is always positive in shared frailty models. Conditional on the random effect, called the frailty denoted by ui, the survival times in cluster i (1 ≤ i ≤ n) are assumed to be independent and the proportional hazard frailty model assumes: where i indicates the ith cluster and j indicates the jth individual for the ith cluster, ho(t) is the baseline hazard function, ui the random term of all the subjects in cluster i, xij the vector of covariates for subject j in cluster i and β the vector of regression coefficients. If we tried to estimate each subject’s frailty (ui), then there would be more parameters to estimate than observations in the dataset and the model would be over-parameterized. Rather, the variance of the frailty is estimated. The gamma distribution is a two-parameter distribution. Because the mean is set at 1, we need only estimate its variance (θ) to fully specify the frailty distribution. The associations within group members are measured by Kendall's Tau, which is given by As the study was secondary data analysis, the dataset were downloaded from the website https://dhsprogram.com after legal registration and approval letter was obtained from the measure DHS. The data were used only for this study and it was not passed to other researchers. All data were treated as confidential and no personal or household identifiers were used in the survey. The detailed information on ethical issues was published within the EDHS report.

Based on the provided description, here are some potential innovations that could improve access to maternal health:

1. Mobile Health (mHealth) Solutions: Develop mobile applications or SMS-based systems to provide pregnant women with information about antenatal care, including the importance of early initiation, appointment reminders, and access to healthcare providers.

2. Community Health Workers: Train and deploy community health workers to educate pregnant women about the benefits of early antenatal care and provide support in accessing healthcare services. These workers can also conduct home visits to reach women in remote areas.

3. Telemedicine: Implement telemedicine services to enable pregnant women to consult with healthcare providers remotely, reducing the need for travel and improving access to antenatal care.

4. Transportation Support: Establish transportation systems or subsidies to help pregnant women overcome geographical barriers and reach healthcare facilities for antenatal care.

5. Health Education Programs: Develop targeted health education programs that focus on raising awareness about the importance of early initiation of antenatal care and address cultural or social barriers that may prevent women from seeking care.

6. Financial Incentives: Introduce financial incentives, such as conditional cash transfers or vouchers, to encourage pregnant women to seek antenatal care early and regularly.

7. Strengthening Health Facilities: Improve the infrastructure and capacity of healthcare facilities, particularly in rural areas, to ensure that pregnant women have access to quality antenatal care services.

8. Public-Private Partnerships: Foster collaborations between the public and private sectors to expand access to antenatal care services, leveraging the resources and expertise of both sectors.

9. Maternal Health Information Systems: Implement robust information systems to track and monitor pregnant women’s antenatal care visits, enabling healthcare providers to identify and reach out to women who have not initiated care.

10. Policy and Advocacy: Advocate for policy changes and increased investment in maternal health to prioritize early initiation of antenatal care and improve access for all pregnant women.

These innovations can help address the barriers identified in the study and improve access to timely and quality antenatal care for pregnant women in Ethiopia.
AI Innovations Description
The study titled “Time to initiation of antenatal care and its predictors among pregnant women in Ethiopia: Cox-gamma shared frailty model” aimed to assess the time to first antenatal care (ANC) visit and its predictors among pregnant women in Ethiopia. The study used data from the Ethiopian Demographic Health Survey (EDHS) conducted in 2016.

The study found that the median time to first ANC visit among pregnant women in Ethiopia was 5 months. This is considered late compared to the World Health Organization (WHO) recommendation. The study identified several predictors of the time to first ANC visit, including education status of women, media exposure, household wealth index, distance from health facility, community women literacy, and residence.

The study recommended that maternal and child health policies and strategies should focus on women’s development and design interventions to increase timely initiation of ANC among pregnant women. The researchers also suggested conducting studies using stronger designs, such as cohort studies, to establish temporality and reduce biases.

It is important to note that the study was based on secondary data analysis, and the dataset used was obtained from the EDHS website after obtaining legal registration and approval. The data were treated as confidential, and no personal or household identifiers were used in the survey.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations to improve access to maternal health:

1. Increase awareness and education: Implement comprehensive education programs to raise awareness about the importance of timely initiation of antenatal care (ANC) among pregnant women and their families. This can include information on the benefits of ANC, potential risks during pregnancy, and the availability of healthcare services.

2. Strengthen healthcare infrastructure: Improve the availability and accessibility of healthcare facilities, particularly in rural and nomadic regions. This can involve building new healthcare centers, upgrading existing facilities, and ensuring the availability of skilled healthcare professionals.

3. Enhance media campaigns: Utilize mass media platforms such as radio, television, and newspapers to disseminate information about the importance of ANC and the availability of healthcare services. This can help reach a wider audience and increase awareness among pregnant women and their communities.

4. Address socioeconomic barriers: Implement interventions to address socioeconomic factors that hinder timely initiation of ANC, such as poverty and low education levels. This can involve providing financial support for transportation to healthcare facilities, offering incentives for early ANC visits, and promoting women’s education and empowerment.

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

1. Define the target population: Identify the specific population group that the recommendations aim to benefit, such as pregnant women in Ethiopia.

2. Collect baseline data: Gather data on the current access to maternal health services, including the time to initiation of ANC and the factors influencing it. This can be done through surveys, interviews, or analysis of existing data sources like the Ethiopian Demographic Health Survey (EDHS).

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the identified recommendations and their potential impact on access to maternal health. This model should consider factors such as population size, geographical distribution, socioeconomic characteristics, and healthcare infrastructure.

4. Input data and run simulations: Input the collected baseline data into the simulation model and run multiple simulations to estimate the potential impact of the recommendations. This can involve varying parameters such as the coverage of education programs, the number of healthcare facilities, and the reach of media campaigns.

5. Analyze results: Analyze the simulation results to assess the projected changes in access to maternal health services. This can include evaluating the expected reduction in the time to initiation of ANC, the increase in healthcare facility utilization, and the potential improvements in maternal and child health outcomes.

6. Refine and validate the model: Continuously refine and validate the simulation model based on real-world data and feedback from stakeholders. This can help improve the accuracy and reliability of the simulations and ensure that the recommendations are evidence-based.

7. Communicate findings and implement recommendations: Present the simulation findings to relevant stakeholders, policymakers, and healthcare providers. Advocate for the implementation of the recommended interventions based on the projected impact on improving access to maternal health.

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.

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