Determinants of Anemia in Pregnancy: Findings from the Ethiopian Health and Demographic Survey

  • Anemia, Volume 2020, Year 2020

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Study Justification:
– Anemia during pregnancy is a significant public health problem in Ethiopia.
– There is a lack of community-based evidence on the determinants of anemia among pregnant women in the country.
– Understanding the determinants of anemia in pregnancy is crucial for developing effective interventions and policies to address this issue.
Study Highlights:
– The overall prevalence of anemia among pregnant women in Ethiopia was 41%.
– The highest prevalence of anemia was found in the Somali region (62.7%), while the lowest was in Addis Ababa (11.9%).
– Factors significantly associated with anemia during pregnancy included age, education level, wealth quintile, religion, household size, number of under-five children, head of household gender, pregnancy intention, terminated pregnancy history, and age at first sexual intercourse.
Study Recommendations:
– Efforts should be made by concerned bodies to intervene and address the identified risk factors for anemia during pregnancy.
– Interventions should focus on improving education, socioeconomic status, and access to healthcare services for pregnant women.
– Targeted interventions should be developed for specific regions with high prevalence of anemia.
Key Role Players:
– Ministry of Health: Responsible for developing and implementing policies and interventions to address anemia in pregnancy.
– Health professionals: Including doctors, nurses, and midwives who provide antenatal care and education to pregnant women.
– Community health workers: Involved in community-based interventions and education programs.
– Non-governmental organizations (NGOs): Engaged in implementing programs and providing support for pregnant women.
Cost Items for Planning Recommendations:
– Education and awareness campaigns: Including materials development, training, and dissemination.
– Healthcare infrastructure: Improving access to healthcare facilities and equipment.
– Antenatal care services: Expanding and improving the quality of antenatal care services.
– Nutritional support: Providing supplements and nutritional counseling for pregnant women.
– Monitoring and evaluation: Establishing systems to monitor the effectiveness of interventions and track progress.
Please note that the cost items provided are general categories and not actual cost estimates. The actual cost will depend on the specific interventions and programs implemented.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design is cross-sectional, which limits the ability to establish causality. Additionally, the abstract does not provide information on the response rate or potential biases in the sample. To improve the evidence, future studies could consider using a longitudinal design to establish causality and provide more information on the sample selection process and potential biases.

In Ethiopia, anemia during pregnancy is a major public health problem and affects both the mother’s and their child’s health. There is a scarcity of community-based evidence on determinants of anemia among pregnant women in the country. Therefore, this study aimed to assess the determinants of anemia among pregnant women in Ethiopia. Method. This study was based on the 2016 Ethiopian Demographic Health Survey (EDHS) that used a two-stage stratified cluster sampling technique. A cross-sectional study was conducted among 3080 pregnant women. Data analysis was done using STATA v.14. Variables with P value <0.05 in the bivariate analysis were candidates for the multivariable analysis to identify independent determinants of anemia among pregnant mothers. Odds ratios (OR) were calculated at 95% confidence interval (CI). Results. The overall prevalence of anemia among pregnant women was 41% of which 20% were moderately anemic, 18%, mildly anemic, and 3%, severely anemic. The following were significantly associated with anemia during pregnancy: an age of 30-39 years, receiving no education (AOR = 2.19; 95% CI 1.45, 2.49), belonging to the poorest wealth quintile (AOR = 1.29; 95% CI 1.22, 1.60), being a Muslim (AOR = 1.59; 95% CI 1.69, 2.65), number of house members being 4-6 (AOR = 1.44; 95% CI 1.05, 1.97), number of under-five children being two (AOR = 1.47; 95% CI 1.10, 1.97), head of the household being a female (AOR = 2.02; 95% CI 1.61, 2.54), current pregnancy wanted later (AOR = 1.75; 95% CI 1.23, 1.63), no terminated pregnancy (AOR = 1.49; 95% CI 1.15, 1.93), and an age of 13-17 years at the first sexual intercourse (AOR = 1.97; 95% CI 1.291, 3.00). Conclusions. The study revealed that more than one-third of the pregnant women in Ethiopia were found anemic. Its prevalence varied among regions in which the highest (62.7%) and the lowest (11.9%) were from Somali and Addis Ababa, respectively. Hence, efforts should be made by concerned bodies to intervene in terms of the identified risk factors.

The data used in this analysis were downloaded from the Demographic and Health Survey (DHS) Program website. Administratively, regions in Ethiopia are divided into zones, and zones, into administrative units, called woreda. The 2016 EDHS was conducted on a nationally representative sample of nine regions and two city administrations of the country. They were subdivided into 68 zones, 817 districts, and 16,253 kebeles (lowest local administrative units of the nation). The EDHS is a periodical survey with a five-year interval; sometimes, in special cases, the interval is different. The 2016 EDHS is the fourth and the most recent DHS in Ethiopia, following 2000, 2005, and 2011 EDHS surveys. A community-based cross-sectional study design was conducted at the national level as one part of the periodic EDHS. The survey was conducted with nationally representative samples from all of the regions of the country. The details of the sample design and sampling procedure, including the sampling framework and implementation and response rates, are provided in the respective EDHS reports (http://www.measuredhs.com/). The 2016 EDHS data are by now chosen using a stratified, two-stage cluster design, and the enumeration areas were the sampling units for the first stage. In the first stage, 645 enumeration areas were randomly selected: 202 in urban areas and 443 in rural areas. In the second stage, a fixed number of 28 households per cluster were selected randomly for each enumeration area. 18,008 households were randomly selected, and 16,650 households were eligible and interviewed. Additional information about the methodology of EDHS 2016 can be accessed in the report of the main findings of the survey published [13]. EDHS 2016 data were downloaded, with permission, from the measure DHS website in SPSS. After a review of the detailed data coding, further data recoding was completed. In the 2016 EDHS dataset, there were 3327 pregnant mothers, of whom 155 pregnant mothers were excluded from the analysis data due to missed hemoglobin data. Information on a wide range of sociodemographic, economic, household, and obstetric characteristics, anemia level, and other indicators were extracted. Anemia status was determined based on hemoglobin concentration in blood adjusted to the altitude. Anemia was defined as the occurrence of a hemoglobin level of less than 11 g/dL. It was further categorized into mild, moderate, and severe anemia with a hemoglobin range of 10–<11 g/dl, 7–<10 g/dl, and <7 g/dl, respectively. The study population was randomly selected pregnant mothers who have hemoglobin data in their data record in the archive of EDHS 2016 data. The outcome variable is the anemia status of pregnant mothers. To investigate the determinants of anemia among pregnant mothers, a number of sociodemographic, health, and socioeconomic factors, such as maternal and paternal characteristics, household characteristics, and environmental conditions, were assessed. After the data were extracted, they were checked for its completeness and consistency, and we did the preliminary analysis. Data analysis was carried out using STATA version v.14. Sample weights were applied to compensate for the unequal probability of selection between the strata, which has also been geographically defined for nonresponses. A detailed explanation of the weighting procedure can be found in the EDHS methodology report [13]. We used “svy” in STATA v.14 to weight the survey data and perform the analyses. Descriptive statistics was done to describe the data such as frequencies and percentages. Anemia status was determined based on hemoglobin concentration in blood adjusted to altitude. Adjusted concentration less than 11 g/dl was considered as anemic. Logistic regression method was used to identify the determinants of anemia. Bivariate analysis was performed to determine the crude association of each covariate variables with the outcome variable (anemia status). Those covariate variables with P value less than 0.20 in the bivariate analysis were included in the final multivariable logistic regression analysis to adjust for the confounding variable and to identify the final determinant of anemia among pregnant mothers. We use the backward logistic regression method during the multivariable logistic regression analysis. Before inclusion of predictors to the final logistic regression model, the multicollinearity was checked using VIF0.1 for continuous independent variables. The goodness of fit of the final logistic model was tested using Hosmer–Lemeshow test at P value of >0.05. Outcome measures have been indicated by odds ratio with 95% confidence interval. Finally, covariate variables with P value of< 0.05 in the multivariable logistic regression model were considered as statistically significant variables in the final logistic model. The study proposal has received an ethical approval from Tigray Health Research Institute, and a formal letter of permission was obtained from measure DHS project website to access the dataset (http://www.measuredhs.com).

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

1. Mobile Health (mHealth) Interventions: Develop and implement mobile phone-based interventions to provide pregnant women with information and reminders about prenatal care, nutrition, and anemia prevention. This could include text messages, voice calls, or mobile applications.

2. Community Health Workers: Train and deploy community health workers to provide education and support to pregnant women in rural areas. These workers can conduct home visits, provide counseling on anemia prevention, and facilitate access to healthcare services.

3. Iron and Folic Acid Supplementation Programs: Implement targeted programs to ensure that pregnant women have access to and are taking iron and folic acid supplements. This could involve distributing supplements through antenatal care clinics, community health centers, or mobile health clinics.

4. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with financial assistance to access prenatal care, including anemia screening and treatment. These vouchers could be used at designated healthcare facilities or with trained healthcare providers.

5. Health Education Campaigns: Launch public awareness campaigns to educate pregnant women and their families about the importance of anemia prevention and the benefits of seeking early and regular prenatal care. This could include radio broadcasts, community meetings, and informational materials.

6. Strengthening Health Systems: Invest in improving the overall healthcare infrastructure, including increasing the number of healthcare facilities, training healthcare providers on anemia prevention and management, and ensuring the availability of necessary equipment and supplies.

7. Collaboration and Partnerships: Foster collaboration between government agencies, non-governmental organizations, and private sector entities to pool resources and expertise in addressing maternal health issues, including anemia prevention. This could involve joint initiatives, funding partnerships, and knowledge sharing.

It is important to note that the specific recommendations and interventions should be tailored to the local context and take into account the existing healthcare system, cultural practices, and socioeconomic factors.
AI Innovations Description
Based on the findings from the study “Determinants of Anemia in Pregnancy: Findings from the Ethiopian Health and Demographic Survey,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Strengthening Education and Awareness Programs: Implement education and awareness programs targeting pregnant women and their families to increase knowledge about the importance of proper nutrition, including iron-rich foods, and the prevention and management of anemia during pregnancy. This can be done through community health workers, antenatal care clinics, and mobile health applications.

2. Improving Socioeconomic Conditions: Address the socioeconomic determinants of anemia during pregnancy by implementing interventions that focus on poverty reduction, women’s empowerment, and access to education. This can include providing economic support, vocational training, and microfinance initiatives for pregnant women and their families.

3. Enhancing Antenatal Care Services: Strengthen antenatal care services by ensuring regular and timely screenings for anemia during pregnancy. This can be achieved by training healthcare providers on the importance of early detection and management of anemia, as well as providing necessary resources and equipment for screening and treatment.

4. Integrating Anemia Prevention and Treatment into Existing Maternal Health Programs: Integrate anemia prevention and treatment interventions into existing maternal health programs, such as antenatal care, immunization, and family planning services. This can be done by incorporating iron and folic acid supplementation, counseling on nutrition, and regular monitoring of hemoglobin levels into routine maternal health services.

5. Targeted Interventions for High-Risk Groups: Develop targeted interventions for high-risk groups, such as adolescent mothers, women with multiple pregnancies, and those from marginalized communities. These interventions can include tailored education and counseling, increased access to healthcare services, and community-based support programs.

6. Strengthening Health Systems: Improve the overall health system by addressing infrastructure and resource gaps, ensuring availability of essential medicines and supplies, and strengthening the capacity of healthcare providers to effectively diagnose and manage anemia during pregnancy.

By implementing these recommendations, it is possible to improve access to maternal health and reduce the prevalence of anemia among pregnant women in Ethiopia.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health in Ethiopia:

1. Strengthening education and awareness programs: Implementing comprehensive education and awareness programs targeting pregnant women and their families can help increase knowledge about maternal health, including the importance of proper nutrition, antenatal care, and early detection and management of anemia.

2. Enhancing antenatal care services: Improving the availability and quality of antenatal care services can contribute to early detection and management of anemia. This can include increasing the number of skilled healthcare providers, ensuring regular monitoring of hemoglobin levels, and providing iron and folic acid supplementation.

3. Addressing socioeconomic factors: Addressing socioeconomic factors such as poverty, education, and household size can help reduce the risk of anemia during pregnancy. Implementing poverty alleviation programs, promoting girls’ education, and providing family planning services can contribute to improving maternal health outcomes.

4. Strengthening healthcare infrastructure: Investing in healthcare infrastructure, particularly in rural areas, can improve access to maternal health services. This can include building and equipping healthcare facilities, improving transportation systems, and training healthcare providers in remote areas.

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

1. Define indicators: Identify key indicators related to access to maternal health, such as the percentage of pregnant women receiving antenatal care, the percentage of women with adequate iron and folic acid supplementation, and the prevalence of anemia among pregnant women.

2. Baseline data collection: Collect baseline data on the identified indicators from relevant sources, such as national surveys or health facility records. This will provide a starting point for comparison.

3. Introduce interventions: Implement the recommended interventions, such as education and awareness programs, enhanced antenatal care services, socioeconomic interventions, and healthcare infrastructure improvements.

4. Data collection after intervention: Collect data on the same indicators after the interventions have been implemented. This can be done through surveys, health facility records, or other data collection methods.

5. Data analysis: Analyze the post-intervention data and compare it with the baseline data to assess the impact of the interventions on the indicators. This can be done using statistical methods such as regression analysis or by calculating the percentage change in the indicators.

6. Interpretation and reporting: Interpret the results of the analysis and report on the impact of the interventions on improving access to maternal health. This can include identifying which interventions had the most significant impact and providing recommendations for further improvement.

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 sources in Ethiopia.


Statistics:
Citations: 10
Identifiers:
DOI: 10.1155/2020/2902498
ISSN: 20901267
Research Areas:
Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants
Study Countries:
Ethiopia
Study Design:
Case-Control Study, Cross Sectional Study
Study Approach:
Quantitative
Participants Gender:
Female
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