Association between maternal age and adverse perinatal outcomes in Arba Minch zuria, and Gacho Baba district, southern Ethiopia: A prospective cohort study

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Study Justification:
– The study aimed to assess the status of advanced maternal age and its effect on perinatal outcomes in Arba Minch zuria and Gacho Baba district, southern Ethiopia.
– This is important because delayed childbearing to an advanced age is becoming more common globally, and it is an emerging public health issue in developing countries.
– Adverse perinatal outcomes have significantly increased, but there are limited studies on the effect of advanced maternal age in Ethiopia.
– Most previous studies used secondary data or chart reviews, which increases the risk of biases.
Study Highlights:
– The study involved 709 study participants from October 15, 2018, to September 30, 2019, in Arba Minch zuria and Gacho Baba district, southern Ethiopia.
– Perinatal outcomes such as stillbirth and neonatal mortality were found to be significantly associated with advanced maternal age.
– The study used a community-based prospective cohort study design and collected data using a pretested interviewer-administered structured Open Data Kit survey tool.
– The data were analyzed using SPSS version 25 and the log-linear regression model.
Study Recommendations:
– Different strategies should be designed for women who plan to bear a child, especially those of advanced age or considering delayed childbearing.
– Information should be provided to women who are of advanced age or considering delayed childbearing to alert them about the potential risks and challenges.
Key Role Players:
– Arba Minch University
– Ethiopian Public Health Association
– Centers for Disease Control and Prevention (CDC) Ethiopia
Cost Items for Planning Recommendations:
– Development and implementation of educational programs for women
– Training programs for healthcare providers
– Awareness campaigns and information dissemination materials
– Monitoring and evaluation activities
– Research and data collection
– Collaboration and coordination efforts between stakeholders
Please note that the provided information is based on the description provided and may not include all details from the original study.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study design is a community-based prospective cohort study, which is generally considered a robust design for establishing causal relationships. The study involved a relatively large sample size of 709 participants and used statistical analysis to compare perinatal outcomes among women aged 20-34 years and ≥ 35 years. The study also controlled for possible confounders. However, there are a few areas where the evidence could be strengthened. First, the abstract does not provide information on the representativeness of the study population, which could affect the generalizability of the findings. Second, the abstract does not mention the specific measures taken to minimize biases in data collection and analysis. To improve the evidence, future studies could provide more details on the representativeness of the study population and the steps taken to minimize biases.

Background: Globally, delayed childbearing to the advanced age is a growing option. It is an emerging public health issue in developing countries. Currently, adverse perinatal outcomes significantly increased. A few studies showed the effect of advanced maternal age on adverse perinatal outcomes. However, most used secondary data or chart reviews, and this increases the risk of biases. Besides, there are limited studies in-country Ethiopia as advanced maternal age steadily increased. Therefore, this study aimed to assess the status of advanced maternal age and its effect on perinatal outcomes in the study setting. Methods: A community-based prospective cohort study was conducted among 709 study participants from October 15, 2018, to September 30, 2019, in Arba Minch zuria, and Gacho Baba district, southern Ethiopia. The data were collected by a pretested interviewer-Administered structured Open Data Kit survey tool and analyzed by SPSS version 25. The log-linear regression model was used to compare perinatal outcomes among women aged 20-34 years and ≥ 35 years. The log-likelihood ratio tested for the goodness of fit. In this study, P-value < 0.05 was considered to declare a result as a statistically significant association. Results: In this study, 209(29.5%) of the women were age group ≥35 years old, and 500(70.5%) were age group from20-34 years old. Stillbirth (β = 0.29, 95%CI: 0.05, 0.52), and neonatal mortality (β = 0.11, 95%CI: 0.01, 0.21) were significantly associated with the advanced maternal age. Conclusions: Perinatal outcomes such as stillbirth and neonatal mortality were independently associated with advanced maternal age after controlling for possible cofounders. Therefore, different strategies should design for the women who planned to bear child, and information should provide for women who are advanced age or delayed childbearing to alert them.

In this study, women’s in Arba Minch zuria, and Gacho Baba district, Arba Minch-Health, and Demographic Surveillance System sites (AM-HDSS), southern Ethiopia involved, from October 15, 2018, to September 30, 2019. Arba Minch-Health and Demographic Surveillance System sites were established in collaboration between Arba Minch University and Ethiopian Public Health Association with the support of the Centers for Disease Control and Prevention (CDC) Ethiopia in 2009 to track demographic changes. The surveillance site included nine kebeles from the 29 kebeles located in Arba Minch zuria, and Gacho Baba district, Gamo zone, southern Ethiopia [28]. Arba Minch is an administrative town in the Gamo zone, located 505 km south of Addis Ababa and 275 km southwest of Hawassa. Based on the 2007 Census conducted by the Central Statistical Agency (CSA), these districts have a total population of 164,529, of whom 82,199 are men and 82,330 women. According to the HDSS report, there is a total population of 74,157 in the surveillance site. A community-based prospective cohort study design was employed to meet study objectives. The source population for this study was all women who were pregnant in Arba Minch zuria, and Gacho Baba district, AM-HDSS site, southern Ethiopia. Those women who were pregnant during the study period (2018–2019) were study population for this study. At enrollment for this study, all women who were pregnant and inhabitants to a minimum of six months in the study area were eligible for this study. The eligibility defined by the pregnancy screening checklist, which was developed by Whiteman et al. [29]. During recruitment, all women whose ages less than twenty years old and known to be preexisting illnesses excluded from the study. Epi info7 software Stat Calc used to estimate the sample sizes. For the first objective, a single population proportion was used by considering the following assumptions: P = 0.334 from the study conducted in Norway [9], 95% level of confidence, and 5% margin of error used. Based on this, the estimated sample size was 342. A two-sample comparison proportion used to estimate the sample size for the second objective. The assumption was P1 (age group 20–34) = 0.207 and P2 (age group ≥35) = 0.124 in the study conducted in Malaysia [10], 95%CI, ratio 1:1, and Power = 80% and the sample size estimated by this assumption was 676. The sample size for this study estimated by adding a non-response rate of 10% to the larger sample size. Therefore, the calculated sample size for this study was 744. The data were collected using a pretested interviewer-administered structured Open Data Kit (ODK) survey tool. The tools were developed by reviewing different works of literature. The wealth index assessment questionnaire adapted from the questionnaire used in the Ethiopian Demographic Health Survey (EDHS) 2016 [30]. The household food insecurity level measured with Household Food Insecurity Access Scale (HFIAS), a structured, standardized, and validated tool that developed mainly by Food and Nutrition Technical Assistance (FANTA) [31]. They have three main parts for the questionnaire: Part I (pregnancy screening checklist), Part II (baseline information), and Part III (follow-up survey tool) (Additional file 1). The tools pretested in the Chencha district, which was out of the study area to verify the appropriateness, and modifications and amendments were taken accordingly before actual data collection. The well-trained nine data collectors and three field supervisors were prospectively identified perinatal outcomes among pregnant women during the study period. Intensive three days training gave for data collectors and supervisors separately regarding objectives of the study and data collection ways. Data collectors discussed the information about the ODK survey tool and pregnancy screening checklists to identify pregnant women. The data collected in different phases, as this was a community-based prospective follow-up study. In the first phase: all the baseline information about the women obtained and pregnancy status was checked by using a pregnancy-screening checklist. After identified whether women were advanced age or not, and the data collectors have recruited the women into the cohort. In the second phase: the women were followed started from the time pregnancy confirmed up to the immediate postpartum period to identify some of the perinatal outcomes. The follow-up terminated at the end of the neonatal period that the neonates reassessed with a similar fashion in the above mechanism. In the community setting, the data collectors frequently contacted women or any household members, surround health care institutions, and health extension workers during the follow-up period. The description and measurements for some of the outcome and explanatory variables were stated in detail below (Table 1). Measurements to assess the status of advanced maternal age and their effect on perinatal outcomes in Arba Minch zuria, and Gacho Baba district, southern Ethiopia, 2018/9 Classified into underweight ( 2 considered as suggestive of the existence of multi co-linearity. In this study, P < 0.05, considered to declare a result as a statistically significant association. Then the information, presented in simple frequencies, summary measures, tables, and figures.

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

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women with access to information, resources, and support for their maternal health needs. These apps can include features such as appointment reminders, educational content, nutrition tracking, and communication with healthcare providers.

2. Telemedicine Services: Establish telemedicine services that allow pregnant women in remote or underserved areas to consult with healthcare professionals through video calls or phone consultations. This can help overcome geographical barriers and provide timely access to prenatal care and advice.

3. Community Health Workers: Train and deploy community health workers who can provide maternal health education, conduct regular check-ups, and facilitate referrals to healthcare facilities for pregnant women in rural or marginalized communities. These workers can also help address cultural or language barriers that may hinder access to care.

4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access essential maternal health services, such as antenatal care visits, skilled birth attendance, and postnatal care. These vouchers can be distributed through community-based organizations or healthcare facilities.

5. Transportation Support: Develop transportation initiatives that address the challenge of reaching healthcare facilities for pregnant women in remote areas. This can include providing subsidized transportation services or partnering with existing transportation networks to ensure reliable and affordable access to healthcare facilities.

6. Maternal Health Education Campaigns: Launch targeted education campaigns to raise awareness about the importance of maternal health and encourage early and regular prenatal care. These campaigns can utilize various channels, such as radio, television, social media, and community outreach programs.

7. Maternity Waiting Homes: Establish maternity waiting homes near healthcare facilities to accommodate pregnant women who live far away and need to travel for delivery. These homes can provide a safe and comfortable environment for women to stay during the final weeks of pregnancy, ensuring timely access to skilled birth attendance.

8. Strengthening Healthcare Infrastructure: Invest in improving healthcare infrastructure, including the construction or renovation of healthcare facilities, equipping them with necessary medical supplies and equipment, and ensuring the availability of skilled healthcare professionals.

9. Public-Private Partnerships: Foster collaborations between the public and private sectors to leverage resources and expertise in improving maternal health services. This can involve partnerships with private healthcare providers, pharmaceutical companies, technology companies, and non-profit organizations.

10. Data-driven Decision Making: Utilize data collection and analysis tools to monitor and evaluate maternal health outcomes, identify gaps in access and quality of care, and inform evidence-based decision making. This can help prioritize interventions and allocate resources effectively.

These innovations can contribute to improving access to maternal health services, reducing maternal and neonatal mortality rates, and promoting positive perinatal outcomes.
AI Innovations Description
Based on the provided description, the study titled “Association between maternal age and adverse perinatal outcomes in Arba Minch zuria, and Gacho Baba district, southern Ethiopia: A prospective cohort study” aimed to assess the status of advanced maternal age and its effect on perinatal outcomes in the study setting. The study was conducted from October 15, 2018, to September 30, 2019, in Arba Minch zuria, and Gacho Baba district, southern Ethiopia.

The study involved 709 study participants and used a community-based prospective cohort study design. The data were collected using a pretested interviewer-administered structured Open Data Kit (ODK) survey tool. The study found that stillbirth and neonatal mortality were significantly associated with advanced maternal age.

Based on these findings, a recommendation to improve access to maternal health and address the adverse perinatal outcomes associated with advanced maternal age could be to implement targeted interventions for women who are planning to have children. These interventions could include providing information and education about the potential risks and complications associated with advanced maternal age, as well as promoting early and regular prenatal care for women in this age group. Additionally, healthcare providers should be trained to identify and manage any potential complications that may arise during pregnancy and childbirth for women of advanced maternal age. By implementing these recommendations, it is hoped that the access to maternal health services will be improved and the adverse perinatal outcomes associated with advanced maternal age will be reduced.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Increase awareness and education: Develop and implement targeted educational campaigns to raise awareness about the risks associated with advanced maternal age and the importance of early and regular prenatal care. This can be done through community outreach programs, media campaigns, and partnerships with local healthcare providers.

2. Strengthen healthcare infrastructure: Invest in improving healthcare facilities, especially in rural areas, by providing necessary equipment, supplies, and trained healthcare professionals. This will ensure that pregnant women, regardless of their age, have access to quality prenatal care and delivery services.

3. Expand access to antenatal and postnatal care: Establish more antenatal and postnatal care clinics in underserved areas to ensure that pregnant women receive comprehensive care throughout their pregnancy and after childbirth. This can include providing transportation services for women who live far from healthcare facilities.

4. Implement telemedicine services: Utilize technology to provide remote healthcare services, such as telemedicine consultations, to pregnant women in remote areas. This can help overcome geographical barriers and improve access to specialized care for high-risk pregnancies.

5. Strengthen community health worker programs: Train and deploy community health workers who can provide basic prenatal care, health education, and referrals for pregnant women in their communities. This can help bridge the gap between healthcare facilities and remote areas.

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

1. Define the baseline: Collect data on the current state of maternal health access in the study area, including factors such as the number of healthcare facilities, availability of prenatal and postnatal care services, and the percentage of women receiving adequate care.

2. Identify key indicators: Select indicators that reflect the desired outcomes of the recommendations, such as the percentage of pregnant women receiving early prenatal care, the number of healthcare facilities per population, or the reduction in adverse perinatal outcomes.

3. Collect data: Gather data on the selected indicators before and after implementing the recommendations. This can be done through surveys, interviews, or analysis of existing data sources.

4. Analyze the data: Use statistical methods to compare the baseline data with the post-implementation data. This can involve calculating percentages, conducting regression analyses, or using other appropriate statistical techniques to assess the impact of the recommendations.

5. Interpret the results: Analyze the findings to determine the extent to which the recommendations have improved access to maternal health. Identify any significant changes in the selected indicators and assess the overall effectiveness of the interventions.

6. Adjust and refine: Based on the results, make any necessary adjustments or refinements to the recommendations to further improve access to maternal health. This can involve scaling up successful interventions, addressing any identified barriers or challenges, and continuously monitoring and evaluating the impact of the interventions.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of the recommendations on improving access to maternal health and make informed decisions on implementing and scaling up effective interventions.

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