Maternal factors associated with low birth weight in public hospitals of Mekelle city, Ethiopia: A case-control study

Italian Journal of Pediatrics, Volume 46, No. 1, Year 2020

Interpretation

Background: Mothers in low socio-economic conditions frequently have low birth weight infants. Inaddition Physically demanding work during pregnancy also contributes to poor fetal growth. During gestation a woman needs balanced nutrition for a healthy outcome. Women with inadequate nutritional status at conception are at greater risk of aquiring disease; their health usually depends on the availability and consumption of balanced diet, and therefore they are unlikely to be able to resist with their high nutrient needs during pregnancy. Therefore, the main purpose of this study was to assess the maternal risk factors associated low birth weight in public hospitals of Mekelle city, Tigray North Ethiopia, 2017/2018. Methods: Un-matched case-control study design was conducted among women who delivered in public hospitals of Mekelle city. Data was collected using a structured questionnaire through interview, direct physical assessment and medical record review of mothers. Sample size was calculated by Epi-info version 7.0 to get a final sample size of 381(cases = 127 and controls = 254). SPSS version 20 was used for analysis. Bivariate and multivariate logistic regression analysis was used to determine the effect of the independent variables on birth weight. Presence of significant association was determined using OR with its 95%CI. A P value of less than 0.05 was considered to declare statistical significance. Table, graphs and texts were used to present the data. Result: Most of the mothers (70.1% cases and 43.7% controls) were housewives. This study showed that maternal age ≤ 20 years (AOR = 6.42(95% CI = (1.93-21.42)), ANC follow up (AOR = 3.73(95%CI (1.5-9.24)), History of medical illness (AOR = 14.56(95% CI (3.69-57.45), Iron folate intake (AOR = 21.56(95%CI (6.54-71.14)), Maternal height less than 150 cm (AOR = 9.27(95%CI 3.45-24.89)) and Pregnancy weight gain (AOR = 4.93(95%CI = 1.8-13.48) were significant predictors of low birth weight. Conclusion: The study suggests that inadequate ANC follow-up, preterm birth and history of chronic medical illness, maternal height, pregnancy weight gain, and Iron intake were. Were significant predictors of low birth weight. Health professionals should screen and consulate pregnant mothers who are at risk of having infants with LBW and ensure that women have access to essential health information on the causes of low birth weight. The study was conducted in Mekelle city, Tigray, Ethiopia. Mekelle is a capital city of Tigray regional state and one of the administrative towns. The city is located in the northern part of Ethiopia with a distance of 783 km from Addis Ababa, the capital city of Ethiopia. Its astronomical location is 13°32″North latitude and 39°28′ East longitude. The city has total population of 586,897 according 2015 EFY. In the city are about 12 public health centers and 4 public hospitals providing promotive, preventive, curative, and rehabilitative services. The health institutions in the city give maternal and child health services. The study was carried out from February to March 2018. Institutional based unmatched case-control study design was conducted among women who delivered in public hospitals of Mekelle city from November 2017 to June2018. All mothers who delivered at public hospitals of Mekelle, Tigray, Ethiopia during the study period. Mothers who delivered low birth weight neonate (< 2500 g) at public hospitals of Mekelle City, Tigray, Ethiopia from February to March 2018. Mothers who delivered normal birth weight neonates (2500–4000 g.) in public hospitals of Mekelle City, Tigray, Ethiopia from February to March 2018. For all cases and controls; Newborns with congenital anomalies and critically ill mothers were excluded from the study. Double population proportion formula using Epi-info version 7.0 statistical package was used considering maternal height (≤ 150 cm) as main exposure variable, percent of exposure for controls 6.2% (taken from a study conducted in Bale) [14]. And an assumptions of 95% CI, 80% power, case to control ratio of 1:2 and 2.8 odds ratio was used to get a total sample size of 345. Adding 10% non-respondent rate the final sample size was n = 381(cases = 127, controls = 254). All public hospitals in Mekelle city (Ayder Comprehensive Specialized Hospital, Quiha and Mekelle general hospitals) were included on the study. Both cases and controls were proportionally allocated to each hospitals by taking their average flow of deliveries for the last 3 month as a baseline. Averagely in 3 months there were about 1606 neonates delivered in those three public hospitals of Mekelle city. Among these 778 were in ACSH, 624 in Mekelle and 204 in Quiha hospital. All cases in each hospital were included consecutively until the required sample siz were obtained and controls were recruited using systematic random sampling by selecting the participants every 3rd interval [Fig. 1]. Schematic presentation of the sampling procedure for a study conducted on maternal risk factors associated with LBW Low Birth weight. Maternal Socio-demographic factor (Maternal age, Residence, Educational level and Maternal occupation). Maternal nutritional factors (Gestational weight gain, Height, Weight, and Iron and folic acid supplementation). Maternal obstetric and health –related factors (Birth interval, Gestational age, Gestational and chronic medical illness, History of abortion and Number ofANC follow up). Maternal behavioral factors (Drinking alcohol and Cigarette smoking). Newborns who have birth weight (2500 g. -4000 g.) Mothers who delivered low birth weight neonate (< 2500 g.) Mothers who delivered normal birth weight neonates (2500–4000 g.) Birth interval is defined as the length of time between two successive live births. Data were collected using a structured English version questionnaire which was adapted from different literatures. The socio- demographic and behavioral maternal factors were collected through interview. Maternal anthropometric measurements like Height was computed through physical assessment and ANC, gestational age and any relevant medical illness were extracted through reviewing of mothers’ medical record for both cases and controls within the first 6 h of delivery. Data collectors were interviewed to all mothers for whom who have singleton live births all over the data collection period at the selected hospitals for both controls and cases. Birth weight of every child was measured using balanced seca scale and the scale was rounded to the nearest 50 mg.. Pretest was conducted in Wukro Hospital on 5% (in 7 cases and 14 controls) of study participants which were not included in the study prior to the actual data collection period to test the clarity, consistency and completeness of the questioner. Six data collectors (BSc. midwives) two for each hospital and one supervisor (BSc. midwifery) were trained for 1 day on how to collect, interview and the overall objectives of the study by principal investigator. English version Questioner were changed in to local language (Tigrigna) then translated back in to English for analysis. Weighing scales were checked and adjusted at zero level for the validity of the measurement. Data were managed by using appropriate data entry in to SPSS version 20 software package and it was cleaned before analysis. Affter the data were codded and cleaned it was entered to SPSS version 20 for analysis. Descriptive statistics such as mean (+SD) were calculated to compare group variables.. In the Binary logistic regression model bivariate analysis was run to include variables as a candidate in the multivariate logistic regression at p value of ≤0.2. A multivariate logistic regression was used to determine the effect of the independent variables on birth weight and to control possible confounders. In order to test the significance level and association of variables at 95% confidence interval (CI), adjusted odds ratio and p-value ≤0.05 were used. Tables, graphs and texts were used to present the data. Ethical clearance was obtained from the Institutional Ethical Review Board of Mekelle University College of Health Sciences and support letter was given fromTigray regional heath bureau to the selected hospitals letting permission. As long as reviewing mothers card and assessing mothers immediately after delivery needs verbal informed consent and confidentiality was preserved by apprising data collectors to use codes instead of writing names of the respondents and assuring the consent of respondents before data collection inorder to maintain permission of the participants. The informed consent was also applied for the newbons and and young mothers. The verbal consent was obtained from a parent on behalf of the participants under the age of 16.

AI Digest

Study Justification:

– Low birth weight is a significant public health issue, particularly in low socio-economic conditions.
– Physically demanding work during pregnancy can contribute to poor fetal growth.
– Balanced nutrition during gestation is crucial for a healthy outcome.
– Inadequate nutritional status at conception increases the risk of disease and affects the health of the mother and baby.
– This study aimed to assess the maternal risk factors associated with low birth weight in public hospitals of Mekelle city, Ethiopia.

Highlights:

– The study found that maternal age ≤ 20 years, inadequate antenatal care (ANC) follow-up, history of medical illness, inadequate iron folate intake, maternal height less than 150 cm, and insufficient pregnancy weight gain were significant predictors of low birth weight.
– Health professionals should screen and consult pregnant mothers at risk of having infants with low birth weight.
– Access to essential health information on the causes of low birth weight should be ensured for women.

Recommendations:

– Increase awareness and access to antenatal care services for pregnant women, especially those at risk of low birth weight.
– Provide nutritional counseling and support to pregnant women to ensure adequate iron folate intake and healthy weight gain during pregnancy.
– Implement strategies to address the specific needs of pregnant women with chronic medical illnesses.
– Strengthen health education programs to promote healthy behaviors during pregnancy, such as avoiding alcohol and cigarette smoking.

Key Role Players:

– Health professionals (doctors, nurses, midwives) for screening and counseling pregnant women.
– Public health officials for implementing strategies and programs.
– Community health workers for raising awareness and providing support to pregnant women.

Cost Items for Planning Recommendations:

– Training programs for health professionals on screening and counseling pregnant women: cost of trainers, materials, and logistics.
– Development and dissemination of educational materials on nutrition and healthy behaviors during pregnancy: printing and distribution costs.
– Implementation of community health worker programs: recruitment, training, and supervision costs.
– Monitoring and evaluation of the interventions: data collection and analysis costs.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is mentioned (unmatched case-control study), and the sample size calculation is provided. The statistical analysis methods are described, including bivariate and multivariate logistic regression. The results are presented with odds ratios and confidence intervals. However, the abstract could be improved by providing more details about the study population, data collection methods, and potential limitations. Additionally, it would be helpful to include the main findings and their implications for practice. To improve the evidence, the abstract could be revised to include these missing details and provide a clearer summary of the study’s key findings.

Abstract

The study was conducted in Mekelle city, Tigray, Ethiopia. Mekelle is a capital city of Tigray regional state and one of the administrative towns. The city is located in the northern part of Ethiopia with a distance of 783 km from Addis Ababa, the capital city of Ethiopia. Its astronomical location is 13°32″North latitude and 39°28′ East longitude. The city has total population of 586,897 according 2015 EFY. In the city are about 12 public health centers and 4 public hospitals providing promotive, preventive, curative, and rehabilitative services. The health institutions in the city give maternal and child health services. The study was carried out from February to March 2018. Institutional based unmatched case-control study design was conducted among women who delivered in public hospitals of Mekelle city from November 2017 to June2018. All mothers who delivered at public hospitals of Mekelle, Tigray, Ethiopia during the study period. Mothers who delivered low birth weight neonate (< 2500 g) at public hospitals of Mekelle City, Tigray, Ethiopia from February to March 2018. Mothers who delivered normal birth weight neonates (2500–4000 g.) in public hospitals of Mekelle City, Tigray, Ethiopia from February to March 2018. For all cases and controls; Newborns with congenital anomalies and critically ill mothers were excluded from the study. Double population proportion formula using Epi-info version 7.0 statistical package was used considering maternal height (≤ 150 cm) as main exposure variable, percent of exposure for controls 6.2% (taken from a study conducted in Bale) [14]. And an assumptions of 95% CI, 80% power, case to control ratio of 1:2 and 2.8 odds ratio was used to get a total sample size of 345. Adding 10% non-respondent rate the final sample size was n = 381(cases = 127, controls = 254). All public hospitals in Mekelle city (Ayder Comprehensive Specialized Hospital, Quiha and Mekelle general hospitals) were included on the study. Both cases and controls were proportionally allocated to each hospitals by taking their average flow of deliveries for the last 3 month as a baseline. Averagely in 3 months there were about 1606 neonates delivered in those three public hospitals of Mekelle city. Among these 778 were in ACSH, 624 in Mekelle and 204 in Quiha hospital. All cases in each hospital were included consecutively until the required sample siz were obtained and controls were recruited using systematic random sampling by selecting the participants every 3rd interval [Fig. 1]. Schematic presentation of the sampling procedure for a study conducted on maternal risk factors associated with LBW Low Birth weight. Maternal Socio-demographic factor (Maternal age, Residence, Educational level and Maternal occupation). Maternal nutritional factors (Gestational weight gain, Height, Weight, and Iron and folic acid supplementation). Maternal obstetric and health –related factors (Birth interval, Gestational age, Gestational and chronic medical illness, History of abortion and Number ofANC follow up). Maternal behavioral factors (Drinking alcohol and Cigarette smoking). Newborns who have birth weight (2500 g. -4000 g.) Mothers who delivered low birth weight neonate (< 2500 g.) Mothers who delivered normal birth weight neonates (2500–4000 g.) Birth interval is defined as the length of time between two successive live births. Data were collected using a structured English version questionnaire which was adapted from different literatures. The socio- demographic and behavioral maternal factors were collected through interview. Maternal anthropometric measurements like Height was computed through physical assessment and ANC, gestational age and any relevant medical illness were extracted through reviewing of mothers’ medical record for both cases and controls within the first 6 h of delivery. Data collectors were interviewed to all mothers for whom who have singleton live births all over the data collection period at the selected hospitals for both controls and cases. Birth weight of every child was measured using balanced seca scale and the scale was rounded to the nearest 50 mg.. Pretest was conducted in Wukro Hospital on 5% (in 7 cases and 14 controls) of study participants which were not included in the study prior to the actual data collection period to test the clarity, consistency and completeness of the questioner. Six data collectors (BSc. midwives) two for each hospital and one supervisor (BSc. midwifery) were trained for 1 day on how to collect, interview and the overall objectives of the study by principal investigator. English version Questioner were changed in to local language (Tigrigna) then translated back in to English for analysis. Weighing scales were checked and adjusted at zero level for the validity of the measurement. Data were managed by using appropriate data entry in to SPSS version 20 software package and it was cleaned before analysis. Affter the data were codded and cleaned it was entered to SPSS version 20 for analysis. Descriptive statistics such as mean (+SD) were calculated to compare group variables.. In the Binary logistic regression model bivariate analysis was run to include variables as a candidate in the multivariate logistic regression at p value of ≤0.2. A multivariate logistic regression was used to determine the effect of the independent variables on birth weight and to control possible confounders. In order to test the significance level and association of variables at 95% confidence interval (CI), adjusted odds ratio and p-value ≤0.05 were used. Tables, graphs and texts were used to present the data. Ethical clearance was obtained from the Institutional Ethical Review Board of Mekelle University College of Health Sciences and support letter was given fromTigray regional heath bureau to the selected hospitals letting permission. As long as reviewing mothers card and assessing mothers immediately after delivery needs verbal informed consent and confidentiality was preserved by apprising data collectors to use codes instead of writing names of the respondents and assuring the consent of respondents before data collection inorder to maintain permission of the participants. The informed consent was also applied for the newbons and and young mothers. The verbal consent was obtained from a parent on behalf of the participants under the age of 16.

Materials

https://efashare.b-cdn.net/materials/a1a1f174f11f7053bc9184347ac8a0f27312957a20b5a1ba0b721b5d1383c202/13052_2020_890_MOESM1_ESM.docx

Innovations

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

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women with access to essential health information, including nutrition guidelines, antenatal care schedules, and reminders for medication intake. These applications can also include features for tracking maternal weight gain and fetal development.

2. Telemedicine Services: Establish telemedicine services that allow pregnant women in remote areas to consult with healthcare professionals through video calls or phone calls. This can help address the lack of healthcare facilities and specialists in certain regions, ensuring that women receive timely and appropriate care during pregnancy.

3. Community Health Workers: Train and deploy community health workers who can provide education and support to pregnant women in their local communities. These workers can conduct home visits, offer guidance on nutrition and healthy behaviors, and facilitate access to antenatal care services.

4. Maternal Health Vouchers: Implement a voucher system that provides pregnant women with subsidized or free access to essential maternal health services, including antenatal care visits, delivery services, and postnatal care. This can help reduce financial barriers and increase utilization of healthcare services.

5. Maternal Health Clinics: Establish dedicated maternal health clinics in underserved areas, equipped with skilled healthcare providers, essential medical equipment, and medications. These clinics can offer comprehensive antenatal care, delivery services, and postnatal care, ensuring that women have access to quality care throughout their pregnancy journey.

6. Health Education Programs: Develop and implement targeted health education programs that focus on improving maternal nutrition, promoting healthy behaviors during pregnancy, and raising awareness about the importance of antenatal care. These programs can be delivered through community workshops, radio broadcasts, and educational materials.

7. Transportation Support: Address transportation barriers by providing pregnant women with transportation support to access healthcare facilities for antenatal care visits, delivery, and postnatal care. This can involve partnerships with local transportation providers or the establishment of dedicated transportation services for pregnant women.

8. Maternal Health Hotline: Establish a toll-free hotline that pregnant women can call to receive information, guidance, and support related to maternal health. Trained healthcare professionals can provide advice, answer questions, and refer women to appropriate healthcare services when needed.

9. Maternal Health Monitoring Systems: Develop and implement digital systems for monitoring maternal health indicators, such as weight gain, blood pressure, and fetal movements. These systems can enable healthcare providers to remotely monitor pregnant women’s health status and intervene when necessary.

10. Public-Private Partnerships: Foster collaborations between public healthcare facilities and private sector organizations to improve access to maternal health services. This can involve leveraging private sector resources, expertise, and technology to enhance the quality and availability of maternal healthcare services.

It is important to note that the implementation of these innovations should be context-specific and tailored to the local healthcare system and cultural norms. Additionally, continuous monitoring and evaluation should be conducted to assess the effectiveness and impact of these innovations on improving access to maternal health.

AI Innovations Description

Based on the description provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Strengthen Antenatal Care (ANC) Services: The study found that inadequate ANC follow-up was a significant predictor of low birth weight. To address this, an innovation could be developed to improve access to ANC services for pregnant women. This could include mobile ANC clinics that visit remote areas, telemedicine consultations for pregnant women who cannot easily access healthcare facilities, or community-based ANC programs that provide education and support to pregnant women.

2. Improve Nutritional Support: The study highlighted the importance of balanced nutrition during pregnancy for a healthy outcome. An innovation could focus on improving access to nutritious food for pregnant women, especially those in low socio-economic conditions. This could involve initiatives such as community gardens, food assistance programs, or nutrition education programs to empower women to make healthier food choices.

3. Enhance Maternal Health Education: The study emphasized the need for pregnant women to have access to essential health information on the causes of low birth weight. An innovation could involve developing educational materials and programs specifically tailored to the needs of pregnant women. This could include mobile apps, interactive websites, or community workshops that provide information on prenatal care, nutrition, and healthy lifestyle choices during pregnancy.

4. Implement Early Screening and Intervention: The study identified several maternal risk factors associated with low birth weight, such as maternal age, history of medical illness, and maternal height. An innovation could focus on implementing early screening and intervention programs to identify pregnant women at risk and provide appropriate support and interventions. This could involve regular health check-ups, screening tools, and referral systems to ensure timely and targeted interventions for high-risk pregnancies.

Overall, the development of these innovations could help improve access to maternal health services, enhance nutrition support, provide essential health information, and implement early screening and intervention programs to reduce the incidence of low birth weight and improve maternal and child health outcomes.

AI Innovations Methodology

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

1. Strengthen Antenatal Care (ANC) services: Increase the availability and accessibility of ANC services, ensuring that pregnant women have regular check-ups, receive appropriate counseling, and are provided with necessary supplements such as iron and folic acid.

2. Improve maternal nutrition: Implement programs that promote balanced nutrition for pregnant women, especially those in low socio-economic conditions. This can include providing education on healthy eating habits, distributing nutritious food, and addressing underlying factors that contribute to inadequate nutrition.

3. Enhance healthcare infrastructure: Invest in improving the quality and capacity of public hospitals and health centers, particularly in areas with high maternal health needs. This can involve upgrading facilities, increasing the number of skilled healthcare providers, and ensuring the availability of essential medical equipment and supplies.

4. Increase awareness and education: Conduct awareness campaigns to educate pregnant women and their families about the importance of maternal health, including the risks associated with low birth weight. This can be done through community outreach programs, media campaigns, and partnerships with local organizations.

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 specific indicators that measure access to maternal health, such as the number of ANC visits, percentage of pregnant women receiving iron and folic acid supplementation, or the availability of skilled healthcare providers in public hospitals.

2. Collect baseline data: Gather data on the current status of these indicators in the target area (Mekelle city, Ethiopia). This can be done through surveys, interviews, and data collection from healthcare facilities.

3. Implement the recommendations: Introduce the recommended interventions, such as strengthening ANC services, improving maternal nutrition programs, enhancing healthcare infrastructure, and conducting awareness campaigns.

4. Monitor and evaluate: Continuously monitor the implementation of the interventions and collect data on the selected indicators. This can involve regular data collection from healthcare facilities, surveys of pregnant women, and feedback from healthcare providers.

5. Analyze the data: Use statistical analysis techniques to assess the impact of the interventions on the selected indicators. Compare the baseline data with the post-intervention data to determine any changes or improvements in access to maternal health.

6. Interpret the results: Interpret the findings to understand the effectiveness of the recommendations in improving access to maternal health. Identify any gaps or areas that require further attention and adjustment.

7. Adjust and refine: Based on the results and analysis, make necessary adjustments to the interventions to further enhance their impact. This can involve modifying strategies, reallocating resources, or targeting specific populations.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of the recommendations and make informed decisions to improve access to maternal health in Mekelle city, Ethiopia.

Author

Dima Health

Statistics:

Citations: 9

Identifiers:

DOI: 10.1186/s13052-020-00890-9

ISSN: 17208424

Research Areas:

Food Security, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Substance Abuse, Workforce

Study Countries:

Ethiopia

Study Design:

Case-Control Study, Cohort Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female