Associated Factors with Low Birth Weight in Dire Dawa City, Eastern Ethiopia: A Cross-Sectional Study

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Study Justification:
– Low birth weight is a significant public health concern in low- and middle-income countries.
– The prevalence of low birth weight in sub-Saharan Africa is high.
– More research studies on low birth weight are needed to meet the World Health Assembly’s target of reducing it by 30% by 2025.
Study Highlights:
– The study was conducted in Dire Dawa City, eastern Ethiopia.
– A cross-sectional study design was used, and 431 mothers who gave birth in public hospitals were selected.
– The prevalence of low birth weight in the study area was found to be 21%.
– Factors significantly associated with low birth weight included not receiving nutritional counseling during antenatal care, preterm birth, maternal smoking, and maternal height less than 150 cm.
– Effective dietary counseling, additional diet, strategies to prevent preterm birth, and avoiding smoking during pregnancy were recommended to decrease low birth weight and improve child survival.
Recommendations for Lay Reader and Policy Maker:
– Lay Reader: It is important to receive proper nutritional counseling during pregnancy, avoid smoking, and ensure a healthy diet to reduce the risk of low birth weight. Pregnant women should also be aware of the importance of full-term pregnancy and seek appropriate medical care.
– Policy Maker: Policies should be implemented to ensure that pregnant women have access to nutritional counseling and support. Efforts should be made to prevent preterm birth and discourage smoking during pregnancy. Health education programs should be developed to raise awareness about the risks of low birth weight and promote healthy behaviors during pregnancy.
Key Role Players:
– Health professionals: Midwives, nurses, and doctors who provide antenatal care and support to pregnant women.
– Health educators: Professionals who can develop and deliver health education programs to raise awareness about the risks of low birth weight and promote healthy behaviors during pregnancy.
– Policy makers: Government officials and policymakers who can develop and implement policies to improve maternal and child health.
Cost Items for Planning Recommendations:
– Training: Budget for training health professionals and health educators on providing nutritional counseling and delivering health education programs.
– Awareness campaigns: Budget for developing and implementing awareness campaigns targeting pregnant women and their families.
– Infrastructure: Budget for improving healthcare facilities and ensuring access to quality antenatal care services.
– Research: Budget for conducting further research studies to monitor the prevalence and associated factors of low birth weight and evaluate the effectiveness of interventions.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is rated 8 because it provides a clear description of the study design, sample size, data collection methods, statistical analysis, and results. The prevalence of low birth weight is reported, along with the associated factors. The study also includes a discussion on the implications of the findings and suggests actionable steps to improve child survival, such as effective dietary counseling and strategies to prevent preterm birth and smoking during pregnancy. However, the abstract could be improved by providing more details on the limitations of the study and the generalizability of the findings.

Background. Low Birth Weight (LBW) is a serious public health concern in low- and middle-income countries. Globally, 20 million, an estimated 15% to 20% of babies were born with LBW, and, of these, 13% were in sub-Saharan Africa. Although the World Health Assembly targeted to reduce LBW by 30% by the end of 2025, little has been done on and known about LBW. To meet the goal successfully and efficiently, more research studies on the problem are vital. Hence, the aim of this study was to determine the prevalence and the associated factors of LBW in Dire Dawa city, eastern Ethiopia. Objective. The purpose of this study was to assess the prevalence and the associated factors of low birth weight in Dire Dawa City, eastern Ethiopia, 2017. Method. A cross-sectional study designed was conducted, and using a systematic sampling technique, 431 mothers who gave birth in the public hospitals in Dire Dawa city from July 01 to August 30, 2018, were selected. Stillbirth and infants with birth defects were excluded from the study. Well-trained data collectors collected the data using a structured questionnaire which was pretested. The data were analyzed using SPSS Version 22.0. The Adjusted Odds Ratio (AOR) with 95% confidence interval (CI) was applied in multivariate logistic regression models, and p value less than 0.05 was considered as statistical significant. Result. The prevalence of low birth weight was 21%. Not received nutritional counseling during antenatal care (AOR = 2.03, 95% CI: 1.01, 4.06), preterm birth (AOR = 18.48, 95% CI: 6.51, 52.42), maternal smoking (AOR = 3.97, 95% CI: 1.59, 9.88), and height of the mother less than 150 cm (AOR = 3.54, 95% CI: 1.07, 11.76) were significantly associated with Low birth weight. Conclusion. There was a high prevalence of low birth weight in the study area. Effective dietary counseling and additional diet, implementing proven strategies to prevent preterm birth and avoid smoking during pregnancy might decrease the low birth weight and then enhance child survival.

An institutional-based cross-sectional study design was conducted in Dire Dawa City Administration. It is located 515 kilometers away from Addis Ababa, the capital of Ethiopia. According to the 2007 Ethiopian census, an estimated 3,96,423 people were living in the administration. It has achieved 100% primary health care access. In terms of the distribution of health facilities, there are 2 governmental and 4 private hospitals, 8 health centers, 5 higher clinics, and 12 medium clinics in the city. Mothers who gave birth in Dilchora Referral Hospital and Sabina Primary Hospital from July to August 2018 were included. According to the Dire Dawa City Administration’s health office report, approximately about 2000 live births happened every two months in the administration and 58.7% of delivery took place in the health facilities (26). The two hospitals were included because more than two-thirds (1260) of the delivery takes place in these facilities. Stillbirth and infants with birth defects were not included in this study. The sample size was determined using a single population proportion formula (n = (Zα/2)2pq/d2) by considering the proportion of LBW in eastern Ethiopia 21.9% [28] and using 95% CI, 4% marginal error, and 5% of nonresponse rate. The final sample size was 431. Moreover, the double population proportion formula was used to determine the sample size for the factors associated with LBW. Also, this was calculated for some of the associated factors obtained from different literatures using Epi Info statistical software version 7 with the following assumptions: confidence level = 95%, power = 80%, the ratio of unexposed to exposed almost equivalent to 1 not received dietary counseling 34% (19). This yields 144 participants. Finally, we selected the largest sample size from the first objective, which was 431 samples. According to the hospital’s delivery report, about 1,260 mothers give birth per two months. Hence, the study subjects were selected using a systematic sampling technique. The sampling interval (K) was three. The initial mother was employed using the lottery method. When the selected study subject did not fulfill the inclusion criteria, the subsequent mother was included. The data were collected through a face-to-face interview and using a questionnaire which was an adapted and modified form different works of the literature and prepared originally in English, translated into local languages (Amharic, Afan Oromo, and Somali) and then translated back into English for checking the consistency by different language expertise. Trained midwives and nurses working in the labour ward conducted the interview and anthropometric measurements. The weight of the newborns was measured within the first hour of birth using a balanced Seca scale. The measurement scale was always checked and calibrated before weighing each newborn. Maternal height was measured against a wall using a height scale to the nearest centimeter, and maternal weight was measured by using a beam balance to the nearest kilogram. To ensure the quality of the data, a two-day intensive training was given for all the supervisors and the data collectors. The data collection process was undertaken with frequent monitoring and supervision. Finally, double data entry was done to check the consistency of the data and minimize the entry errors. Birth weight: the first weight of the newborns measured within the first hour after birth. Low birth weight was for those newborns who weighed less than 2500 g, while those newborns with a birth weight of 2500 g and above were considered of normal birth weight. The data were coded, entered into EPI data Version 3.1, and exported to SPSS Version 22.0 software for analysis. Then, they were summarized and presented using descriptive statistics. The outcome variables were coded as “1” for LBW whereas “0” for others. The association between the outcome variables (i.e., LBW) and the independent variables was analyzed using a binary logistic regression model. The covariates which had a p value <0.2 were retained and entered into the multivariable logistic regression analysis. Hosmer and Lemeshow goodness-of-fit tests were used to assess whether the necessary assumptions were fulfilled. Adjusted odds ratio (AOR) with 95% confidence intervals (CI) was used. A p value <0.05 was considered statistically significant. Before the data collection, ethical permission was obtained from the ethical review committee of the College of Medicine and Health Science in Dire Dawa University, and informed written consent was obtained from the participants before conducting the interview and the measurement.

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Based on the provided information, 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 important information and resources related to maternal health. These apps can provide educational materials, appointment reminders, nutrition advice, and emergency contact information.

2. Telemedicine Services: Establish telemedicine services that allow pregnant women in remote areas to consult with healthcare professionals remotely. This can help overcome geographical barriers and provide access to prenatal care and consultations.

3. Community Health Workers: Train and deploy community health workers who can provide basic prenatal care, education, and support to pregnant women in underserved areas. These workers can help identify high-risk pregnancies, provide health education, and refer women to appropriate healthcare facilities.

4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access maternal health services. These vouchers can cover the cost of prenatal care, delivery, and postnatal care, ensuring that women can afford the necessary healthcare services.

5. Transport and Logistics Support: Improve transportation infrastructure and logistics systems to ensure that pregnant women can easily access healthcare facilities. This can involve providing transportation subsidies, establishing ambulance services, and improving road networks in rural areas.

6. Maternal Health Education Campaigns: Launch targeted education campaigns to raise awareness about the importance of maternal health and the available healthcare services. These campaigns can be conducted through various channels, including radio, television, community meetings, and social media.

7. Maternal Health Clinics: Establish dedicated maternal health clinics in underserved areas to provide comprehensive prenatal care, delivery services, and postnatal care. These clinics can be staffed with skilled healthcare professionals and equipped with necessary medical equipment.

8. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve partnering with private healthcare providers to expand service coverage, leveraging private sector resources for infrastructure development, and implementing innovative financing models.

9. Maternal Health Hotlines: Set up toll-free hotlines that pregnant women can call to receive information, advice, and support related to maternal health. Trained healthcare professionals can staff these hotlines and provide guidance on various maternal health issues.

10. Maternal Health Monitoring Systems: Develop and implement digital health systems that allow for real-time monitoring of maternal health indicators. These systems can help identify high-risk pregnancies, track progress, and ensure timely interventions.

It is important to note that the implementation of these innovations should be context-specific and tailored to the local healthcare system and resources available in Dire Dawa City, Eastern Ethiopia.
AI Innovations Description
Based on the study titled “Associated Factors with Low Birth Weight in Dire Dawa City, Eastern Ethiopia: A Cross-Sectional Study,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Implement comprehensive antenatal care programs: The study found that not receiving nutritional counseling during antenatal care was significantly associated with low birth weight. To address this, healthcare providers can develop and implement comprehensive antenatal care programs that include regular nutritional counseling sessions for pregnant women. These programs can educate women about the importance of a balanced diet during pregnancy and provide them with personalized dietary recommendations.

2. Focus on preventing preterm birth: The study identified preterm birth as a significant factor associated with low birth weight. To address this, healthcare providers can prioritize interventions and strategies aimed at preventing preterm birth. This can include promoting healthy lifestyle choices during pregnancy, such as avoiding smoking and alcohol consumption, as well as providing adequate prenatal care and monitoring for signs of preterm labor.

3. Enhance maternal healthcare services in public hospitals: The study was conducted in public hospitals in Dire Dawa City, and the findings highlight the need for improved maternal healthcare services in these facilities. To improve access to maternal health, it is important to invest in public hospitals by providing them with necessary resources, including trained healthcare professionals, medical equipment, and infrastructure. This can help ensure that pregnant women receive high-quality care throughout their pregnancy and delivery.

4. Increase awareness about the importance of maternal health: The study found that maternal smoking was significantly associated with low birth weight. To address this, it is crucial to increase awareness about the harmful effects of smoking during pregnancy and provide support for smoking cessation. This can be done through community-based education programs, public health campaigns, and targeted interventions aimed at helping pregnant women quit smoking.

By implementing these recommendations, healthcare systems can work towards improving access to maternal health and reducing the prevalence of low birth weight, ultimately enhancing child survival and maternal well-being.
AI Innovations Methodology
To improve access to maternal health, here are some potential recommendations:

1. Strengthening Antenatal Care Services: Enhance the quality and availability of antenatal care services, including regular check-ups, nutritional counseling, and education on healthy behaviors during pregnancy.

2. Community-Based Interventions: Implement community-based interventions to raise awareness about the importance of maternal health, promote early and regular antenatal care visits, and encourage women to seek skilled care during childbirth.

3. Mobile Health (mHealth) Solutions: Utilize mobile technology to provide maternal health information, reminders for antenatal care visits, and access to teleconsultations with healthcare providers, particularly in remote or underserved areas.

4. Transportation Support: Improve transportation infrastructure and provide transportation support for pregnant women to reach healthcare facilities, especially in rural areas where access to healthcare services is limited.

5. Skilled Birth Attendant Training: Increase the number of skilled birth attendants and provide them with comprehensive training to ensure safe deliveries and timely emergency obstetric care.

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

1. Define the indicators: Identify key indicators to measure access to maternal health, such as the number of antenatal care visits, percentage of deliveries attended by skilled birth attendants, and maternal mortality rate.

2. Collect baseline data: Gather data on the current status of maternal health access in the target area, including the indicators mentioned above.

3. Model the interventions: Develop a simulation model that incorporates the potential recommendations mentioned earlier. This model should consider factors such as population demographics, healthcare infrastructure, and resource availability.

4. Input data and assumptions: Input relevant data into the simulation model, including population size, healthcare facility locations, and the expected impact of each recommendation. Make assumptions about the adoption rate and effectiveness of the interventions.

5. Run the simulation: Execute the simulation model to project the potential impact of the recommendations on access to maternal health. This could involve running multiple scenarios to assess different combinations of interventions.

6. Analyze the results: Analyze the simulation results to determine the projected changes in the selected indicators. Assess the effectiveness of each recommendation and identify any potential challenges or limitations.

7. Refine and iterate: Use the simulation results to refine the recommendations and make adjustments to the model. Iterate the simulation process to further optimize the interventions and improve access to maternal health.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of different interventions and make informed decisions to improve access to maternal health.

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