Geographical disparities and determinants of adherence to iron folate supplementation among pregnant women in Ethiopia: spatial and multilevel analysis of the Ethiopian Mini Demographic and Health Survey of 2019

BMJ Open, Volume 12, No. 9, Year 2022

Interpretation

Objective This study aimed to investigate geographic disparities and determinants of adherence to iron and folate supplementation among pregnant women in Ethiopia. Method A secondary data analysis was performed using data from the Ethiopian Mini Demographic and Health Survey 2019. A total of 2235 pregnant women aged 15-49 years were included in the analysis. ArcGIS V.10.8 and SaTScan V.9.6 were used for spatial analysis. Multilevel logistic regression analysis was used to determinants. Result Of the total number of participants, 80.3% of pregnant mothers took iron and folate supplements for less than the recommended days. Adherence to iron folate supplementation among pregnant women in Ethiopia was spatially clustered with Moran’s global I=0.15868. The SaTScan analysis identified the most likely significant clusters found in the eastern Tigray, northeast Amhara and northwest Afar regions. Multivariable multilevel analysis showed that mothers who were living apart from their partner (adjusted OR (AOR)=10.05, 95% CI 1.84 to 55.04), had antenatal care (ANC) visits at least four times (AOR=0.53, 95% CI 0.41 to 0.69), a higher education level (AOR=0.39, 95% CI 0.25 to 0.63), big distance from health facilities (AOR=1.7, 95% CI 1.51 to 1.97) were significant factors of adherence to iron-folate supplementation. Mothers living in the Amhara and Addis Ababa regions were 0.35 (AOR=0.35, 95% CI 0.19 to 0.621), and 0.29 (AOR=0.29, 95% CI 0.15 to 0.7) times lower iron-folate supplementation intake than mother’s in Tigray region. Conclusion In this study, 8 out of 10 pregnant women did not take iron and folate supplements during the recommended period. As a result, health education activities were necessary to raise awareness among women and the community about the importance of iron folate supplementation during pregnancy, and public health programmes should increase iron folate supplementation through women’s education, ANC visits and mothers living in low-iron areas. Data for this study were obtained from secondary data analysis based on the EMDHS 2019 and access data from the official database of the DHS programme (https://dhsprogram.com/). It is the second mini demographic and health survey conducted in Ethiopia from March to June 2019. All women age 15–49 who were usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. The survey was carried out in nine Ethiopian regional states, namely Tigray, Afar, Amhara, Oromia, Somali, Benishangul-Gumuz, Southern Nations Nationalities and Peoples (SNNP), Gambela and Harari, as well as two city administrations (Addis Ababa and Dire Dawa). Then reviewing the account permission was given via email. A cross-sectional study design using secondary data from 2019 intermediate Ethiopian demography and health survey was conducted. The 2019 EMDHS is the second EMDHS in the country and the fifth DHS. The survey used a nationally representative sample to provide estimates at the national, regional and urban/rural levels. On a nationally representative sample of 8663 families, the survey interviewed 8855 women of reproductive age (age 15–49). The basic characteristics of the respondents, determinants of fertility, marriage, knowledge and use of family planning methods, infant feeding practices, infant nutritional status, infant mortality and height and the weight of babies from 0 to 59 months have been extensively studied. The DHS samples are separated by region, as well as by urban or rural areas within each region. Initially, the enumeration areas (EAs) was selected from each stratum using a proprietary scale. As a result, the sample was stratified and chosen in two stages.19 A total of 305 EAs were chosen for the survey (93 in urban areas and 212 in rural areas) with probability proportional to the size of the AE and with independent selection in each sampling stratum. Second, from the newly created list of families, a fixed number of 30 families per group was chosen with a systematic selection of equal probability.19 In EMDHS 2019, a total of 9150 households were selected for the sample. Of the 8794 employed families, 8663 were successfully interviewed, obtaining a response rate. A total of 8885 interviews were completed with women out of a total of 9012 eligible women, resulting in a 99% response rate. Overall, there was little variation in response rates by residence; however, the rates were slightly higher in rural than in urban areas.19 This study included 2235 pregnant women who had received iron-folate supplements and asked how many days they consumed iron tablets/syrups during their most recent pregnancy. Our outcome variable was the adherence to iron/folate supplementation during pregnancy, split into pregnant women adhering to iron folic acid supplementation (IFAS) (women who took iron tablets/syrups during their most recent pregnancy for 90 days or more) coded as ‘0’ and pregnant women who did not adhere to IFAS (women took iron tablets/syrups during their most recent pregnancy for less than 90 days) coded as ‘1’. To assess the adherence to iron/folate supplementation among pregnant women in the country, explanatory variables were used at the individual and community levels. Individual-level independent variables include maternal sociodemographic factors, maternal health service and related factors, and child factors. Community-level factors in this study were residence and contextual regions. This study was done based on the 2019 EMDHS, which was accessed from the official database of the DHS programme (https://dhsprogram.com/). Online registration and applications were done to grant permission for the use of these data sets. Geographic coordinate (longitude and latitude) data were taken at EAs/cluster level. The STATA V.14 software was used to generate descriptive and summary statistics. STATA V.14, ArcGIS V.10.8 and SaTScan V.9.6 were used in the analysis. Spatial autocorrelation (Global Moran’s I) is a statistic used to assess spatial heterogeneity in iron/folate supplementation adherence among pregnant women. Moran’s I values close to −1 indicate dispersed adherence to iron/folate supplementation, close to +1 indicates clustered adherence and Moran’s I values 0 indicate randomly distributed adherence.20 A statistically significant Moran I value (p<0.05) had the potential to reject the null hypothesis, indicating the presence of spatial autocorrelation. In addition, incremental spatial autocorrelation was used to determine the distance band where the spatial processes that promote clustering were the most pronounced. Hot spot analysis (Getis-Ord Gi* statistic), z-scores and significant p values provided features with hot or cold spot values for the clusters spatially.21 For unsampled areas of the country, the spatial interpolation technique was used to predict adherence to iron/folate supplementation among pregnant women. We used geostatistical empirical Bayesian Kriging spatial interpolation techniques with ArcGIS V.10.8 software to predict unsampled EAs. Empirical Bayesian kriging relaxes the assumption that the observed semivariogram in the input data has a Gaussian distribution, which rarely holds in practice. Bayes’ rule was used to determine the weight of the new simulated semi-variogram.22 Using Kuldorff’s SaTScan V.9.6 software, we used Bernoulli-based model spatial scan statistics to determine the geographical locations of statistically significant clusters for poor iron/folate supplementation adherence among pregnant women.23 The scanning window that moves throughout the study area, with pregnant women with low iron/folate supplementation intake as cases and those with adequate intake as controls to fit the Bernoulli model. The default maximum spatial cluster size of less than 50% of the population was used as an upper limit, allowing both small and large clusters to be detected, and ignored clusters that contained more than the maximum limit with the circular shape of the window. The most likely clusters were identified using p values and log-likelihood ratio (LLR) tests based on 999 Monte Carlo replications. As a result of the hararichial nature of the EMDHS dataset, the observations within the cluster are correlated (dependent), which violates the independence assumption.24 The intraclass correlation (ICC) value identifies the correlation within the cluster. The following formula was used to calculate the ICC, which is a measure of the variability within the cluster and between individuals within the same cluster: ICC=VAVA+π23=VAVA+3.29, where VA is the estimated variance in each model described elsewhere.25 At each model, the total variation attributed to factors at the individual or community level was measured using a proportional change in variance (PCV) calculated as: PCV=VA−VBVA, where VA=variance of the initial model and VB=variance of the model with more terms.26 The MOR is the median OR that compares two people from two different randomly chosen clusters and measures unexplained cluster heterogeneity, as well as variation between clusters by comparing two people from two different randomly chosen clusters. It was determined using the following formula: MOR=exp(2×VA×0.6745)≈exp(0.95VA), where VA is the cluster level variance. The MOR measure is always greater than or equal to 1. If the MOR is 1, there is no variation between clusters.27 To identify community and individual level factors associated with pregnant women taking iron-folate supplementation, multilevel models were fitted. The first model (model I or the empty model) lacked explanatory variables. Instead, it was fitted to decompose total variance into individual and community-level components. The second model included individual-level factors. Household level factors were included in the third model. Community-level factors were included in the fourth model. Finally, the fourth model included individual and community-level factors. The deviance information criteria, Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare models (BIC).28 No patients or public were involved in this study.

AI Digest

Study Justification:

– The study aimed to investigate geographic disparities and determinants of adherence to iron and folate supplementation among pregnant women in Ethiopia.
– This is important because iron and folate supplementation during pregnancy is crucial for the health of both the mother and the baby.
– Understanding the factors that influence adherence to supplementation can help inform targeted interventions to improve maternal and child health outcomes.

Study Highlights:

– The study found that 80.3% of pregnant women in Ethiopia did not adhere to the recommended duration of iron and folate supplementation.
– Spatial analysis identified significant clusters of low adherence in the eastern Tigray, northeast Amhara, and northwest Afar regions.
– Factors associated with adherence included living apart from partner, having at least four antenatal care visits, higher education level, and distance from health facilities.
– Pregnant women in the Amhara and Addis Ababa regions had lower iron-folate supplementation intake compared to those in the Tigray region.

Recommendations for Lay Reader and Policy Maker:

– Health education activities should be implemented to raise awareness among women and the community about the importance of iron and folate supplementation during pregnancy.
– Public health programs should focus on increasing iron and folate supplementation through women’s education, promoting regular antenatal care visits, and targeting mothers living in low-iron areas.
– Efforts should be made to improve access to health facilities, especially in remote areas, to ensure pregnant women have easy access to iron and folate supplements.

Key Role Players:

– Ministry of Health: Responsible for developing and implementing health education programs and policies related to maternal and child health.
– Healthcare Providers: Involved in delivering antenatal care services and providing information and counseling on iron and folate supplementation.
– Community Health Workers: Engaged in community-level health education and outreach activities to promote awareness and adherence to iron and folate supplementation.
– Non-Governmental Organizations (NGOs): Collaborate with the government to implement health programs and provide support in improving access to healthcare services and supplements.

Cost Items for Planning Recommendations:

– Health Education Materials: Development and distribution of educational materials, including brochures, posters, and audiovisual resources.
– Training Programs: Conducting training sessions for healthcare providers and community health workers on iron and folate supplementation counseling.
– Outreach Activities: Organizing community-level events and campaigns to raise awareness and provide information on the importance of supplementation.
– Infrastructure Development: Investing in the establishment or improvement of health facilities, especially in remote areas, to ensure accessibility to iron and folate supplements.
– Monitoring and Evaluation: Allocating resources for monitoring and evaluating the implementation and impact of interventions aimed at improving adherence to supplementation.
Please note that the cost items provided are general categories and may vary depending on the specific context and implementation strategies.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study used a secondary data analysis from a nationally representative survey, which provides a good sample size. The study also employed spatial and multilevel analysis techniques to identify geographic disparities and determinants of adherence to iron and folate supplementation among pregnant women in Ethiopia. However, the abstract does not provide information on the specific methodology used for the logistic regression analysis and the statistical significance of the findings. To improve the evidence, the abstract should include more details on the statistical methods used and provide p-values or confidence intervals for the significant factors identified in the analysis.

Abstract

Data for this study were obtained from secondary data analysis based on the EMDHS 2019 and access data from the official database of the DHS programme (https://dhsprogram.com/). It is the second mini demographic and health survey conducted in Ethiopia from March to June 2019. All women age 15–49 who were usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. The survey was carried out in nine Ethiopian regional states, namely Tigray, Afar, Amhara, Oromia, Somali, Benishangul-Gumuz, Southern Nations Nationalities and Peoples (SNNP), Gambela and Harari, as well as two city administrations (Addis Ababa and Dire Dawa). Then reviewing the account permission was given via email. A cross-sectional study design using secondary data from 2019 intermediate Ethiopian demography and health survey was conducted. The 2019 EMDHS is the second EMDHS in the country and the fifth DHS. The survey used a nationally representative sample to provide estimates at the national, regional and urban/rural levels. On a nationally representative sample of 8663 families, the survey interviewed 8855 women of reproductive age (age 15–49). The basic characteristics of the respondents, determinants of fertility, marriage, knowledge and use of family planning methods, infant feeding practices, infant nutritional status, infant mortality and height and the weight of babies from 0 to 59 months have been extensively studied. The DHS samples are separated by region, as well as by urban or rural areas within each region. Initially, the enumeration areas (EAs) was selected from each stratum using a proprietary scale. As a result, the sample was stratified and chosen in two stages.19 A total of 305 EAs were chosen for the survey (93 in urban areas and 212 in rural areas) with probability proportional to the size of the AE and with independent selection in each sampling stratum. Second, from the newly created list of families, a fixed number of 30 families per group was chosen with a systematic selection of equal probability.19 In EMDHS 2019, a total of 9150 households were selected for the sample. Of the 8794 employed families, 8663 were successfully interviewed, obtaining a response rate. A total of 8885 interviews were completed with women out of a total of 9012 eligible women, resulting in a 99% response rate. Overall, there was little variation in response rates by residence; however, the rates were slightly higher in rural than in urban areas.19 This study included 2235 pregnant women who had received iron-folate supplements and asked how many days they consumed iron tablets/syrups during their most recent pregnancy. Our outcome variable was the adherence to iron/folate supplementation during pregnancy, split into pregnant women adhering to iron folic acid supplementation (IFAS) (women who took iron tablets/syrups during their most recent pregnancy for 90 days or more) coded as ‘0’ and pregnant women who did not adhere to IFAS (women took iron tablets/syrups during their most recent pregnancy for less than 90 days) coded as ‘1’. To assess the adherence to iron/folate supplementation among pregnant women in the country, explanatory variables were used at the individual and community levels. Individual-level independent variables include maternal sociodemographic factors, maternal health service and related factors, and child factors. Community-level factors in this study were residence and contextual regions. This study was done based on the 2019 EMDHS, which was accessed from the official database of the DHS programme (https://dhsprogram.com/). Online registration and applications were done to grant permission for the use of these data sets. Geographic coordinate (longitude and latitude) data were taken at EAs/cluster level. The STATA V.14 software was used to generate descriptive and summary statistics. STATA V.14, ArcGIS V.10.8 and SaTScan V.9.6 were used in the analysis. Spatial autocorrelation (Global Moran’s I) is a statistic used to assess spatial heterogeneity in iron/folate supplementation adherence among pregnant women. Moran’s I values close to −1 indicate dispersed adherence to iron/folate supplementation, close to +1 indicates clustered adherence and Moran’s I values 0 indicate randomly distributed adherence.20 A statistically significant Moran I value (p<0.05) had the potential to reject the null hypothesis, indicating the presence of spatial autocorrelation. In addition, incremental spatial autocorrelation was used to determine the distance band where the spatial processes that promote clustering were the most pronounced. Hot spot analysis (Getis-Ord Gi* statistic), z-scores and significant p values provided features with hot or cold spot values for the clusters spatially.21 For unsampled areas of the country, the spatial interpolation technique was used to predict adherence to iron/folate supplementation among pregnant women. We used geostatistical empirical Bayesian Kriging spatial interpolation techniques with ArcGIS V.10.8 software to predict unsampled EAs. Empirical Bayesian kriging relaxes the assumption that the observed semivariogram in the input data has a Gaussian distribution, which rarely holds in practice. Bayes’ rule was used to determine the weight of the new simulated semi-variogram.22 Using Kuldorff’s SaTScan V.9.6 software, we used Bernoulli-based model spatial scan statistics to determine the geographical locations of statistically significant clusters for poor iron/folate supplementation adherence among pregnant women.23 The scanning window that moves throughout the study area, with pregnant women with low iron/folate supplementation intake as cases and those with adequate intake as controls to fit the Bernoulli model. The default maximum spatial cluster size of less than 50% of the population was used as an upper limit, allowing both small and large clusters to be detected, and ignored clusters that contained more than the maximum limit with the circular shape of the window. The most likely clusters were identified using p values and log-likelihood ratio (LLR) tests based on 999 Monte Carlo replications. As a result of the hararichial nature of the EMDHS dataset, the observations within the cluster are correlated (dependent), which violates the independence assumption.24 The intraclass correlation (ICC) value identifies the correlation within the cluster. The following formula was used to calculate the ICC, which is a measure of the variability within the cluster and between individuals within the same cluster: ICC=VAVA+π23=VAVA+3.29, where VA is the estimated variance in each model described elsewhere.25 At each model, the total variation attributed to factors at the individual or community level was measured using a proportional change in variance (PCV) calculated as: PCV=VA−VBVA, where VA=variance of the initial model and VB=variance of the model with more terms.26 The MOR is the median OR that compares two people from two different randomly chosen clusters and measures unexplained cluster heterogeneity, as well as variation between clusters by comparing two people from two different randomly chosen clusters. It was determined using the following formula: MOR=exp(2×VA×0.6745)≈exp(0.95VA), where VA is the cluster level variance. The MOR measure is always greater than or equal to 1. If the MOR is 1, there is no variation between clusters.27 To identify community and individual level factors associated with pregnant women taking iron-folate supplementation, multilevel models were fitted. The first model (model I or the empty model) lacked explanatory variables. Instead, it was fitted to decompose total variance into individual and community-level components. The second model included individual-level factors. Household level factors were included in the third model. Community-level factors were included in the fourth model. Finally, the fourth model included individual and community-level factors. The deviance information criteria, Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare models (BIC).28 No patients or public were involved in this study.

Materials

Innovations

The research study titled “Geographical disparities and determinants of adherence to iron folate supplementation among pregnant women in Ethiopia: spatial and multilevel analysis of the Ethiopian Mini Demographic and Health Survey of 2019” provides valuable insights into the factors influencing adherence to iron and folate supplementation among pregnant women in Ethiopia. Based on the study’s findings, the following recommendations can be developed into innovations to improve access to maternal health:

1. Health Education and Awareness Campaigns: Implement targeted health education and awareness campaigns to raise awareness among pregnant women and the community about the importance of iron and folate supplementation during pregnancy. These campaigns should emphasize the benefits of adherence to iron and folate supplementation and address any misconceptions or concerns.

2. Strengthen Antenatal Care (ANC) Services: Enhance ANC services by ensuring that pregnant women receive adequate and regular ANC visits. ANC visits should include counseling on the importance of iron and folate supplementation, as well as the provision of iron and folate supplements. This can be achieved by training healthcare providers on the latest guidelines and recommendations for maternal health.

3. Improve Access to Iron and Folate Supplements: Address the barriers to access by ensuring the availability and affordability of iron and folate supplements in health facilities. This can be done by strengthening the supply chain management system, improving procurement processes, and reducing the cost of these supplements.

4. Mobile Health (mHealth) Interventions: Utilize mobile health technologies, such as SMS reminders and mobile applications, to provide pregnant women with timely reminders and information about iron and folate supplementation. These interventions can help improve adherence and provide additional support to pregnant women, especially those living in remote or underserved areas.

5. Community Engagement and Empowerment: Engage community leaders, local organizations, and community health workers to promote iron and folate supplementation and encourage pregnant women to adhere to the recommended guidelines. Community-based interventions, such as support groups and peer education programs, can also be implemented to provide social support and empower pregnant women to prioritize their maternal health.

By implementing these recommendations, it is expected that access to maternal health, specifically adherence to iron and folate supplementation, will be improved, leading to better health outcomes for pregnant women in Ethiopia.

AI Innovations Description

Based on the research study titled “Geographical disparities and determinants of adherence to iron folate supplementation among pregnant women in Ethiopia: spatial and multilevel analysis of the Ethiopian Mini Demographic and Health Survey of 2019,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Health Education and Awareness Campaigns: Implement targeted health education and awareness campaigns to raise awareness among pregnant women and the community about the importance of iron and folate supplementation during pregnancy. These campaigns should emphasize the benefits of adherence to iron and folate supplementation and address any misconceptions or concerns.

2. Strengthen Antenatal Care (ANC) Services: Enhance ANC services by ensuring that pregnant women receive adequate and regular ANC visits. ANC visits should include counseling on the importance of iron and folate supplementation, as well as the provision of iron and folate supplements. This can be achieved by training healthcare providers on the latest guidelines and recommendations for maternal health.

3. Improve Access to Iron and Folate Supplements: Address the barriers to access by ensuring the availability and affordability of iron and folate supplements in health facilities. This can be done by strengthening the supply chain management system, improving procurement processes, and reducing the cost of these supplements.

4. Mobile Health (mHealth) Interventions: Utilize mobile health technologies, such as SMS reminders and mobile applications, to provide pregnant women with timely reminders and information about iron and folate supplementation. These interventions can help improve adherence and provide additional support to pregnant women, especially those living in remote or underserved areas.

5. Community Engagement and Empowerment: Engage community leaders, local organizations, and community health workers to promote iron and folate supplementation and encourage pregnant women to adhere to the recommended guidelines. Community-based interventions, such as support groups and peer education programs, can also be implemented to provide social support and empower pregnant women to prioritize their maternal health.

AI Innovations Methodology

To simulate the impact of the main recommendations on improving access to maternal health, the following methodology can be used:

1. Baseline Data: Collect baseline data on the current levels of adherence to iron and folate supplementation among pregnant women in different regions of Ethiopia. This can be done through surveys or by using existing data sources such as the Ethiopian Mini Demographic and Health Survey of 2019.

2. Intervention Design: Develop a detailed plan for implementing the recommended interventions, including health education and awareness campaigns, strengthening ANC services, improving access to iron and folate supplements, implementing mobile health interventions, and community engagement and empowerment activities.

3. Sample Selection: Select a representative sample of pregnant women from different regions of Ethiopia to participate in the simulation study. Ensure that the sample size is sufficient to provide statistically significant results.

4. Intervention Implementation: Implement the recommended interventions in the selected regions. This may involve training healthcare providers, conducting health education campaigns, improving the supply chain for iron and folate supplements, and implementing mobile health interventions.

5. Data Collection: Collect data on the adherence to iron and folate supplementation among pregnant women before and after the implementation of the interventions. This can be done through surveys, interviews, or by using existing data sources.

6. Data Analysis: Analyze the collected data to assess the impact of the interventions on improving access to maternal health. Compare the adherence rates before and after the interventions and determine if there are any significant changes.

7. Evaluation: Evaluate the effectiveness of each intervention in improving access to maternal health. Assess the reach, acceptability, and feasibility of the interventions, as well as any unintended consequences.

8. Recommendations: Based on the findings of the simulation study, develop recommendations for scaling up the interventions that have shown the most promising results. Consider factors such as cost-effectiveness, sustainability, and scalability.

9. Implementation and Monitoring: Implement the recommended interventions on a larger scale and monitor their impact on improving access to maternal health. Continuously evaluate and refine the interventions based on feedback and lessons learned.

By following this methodology, it will be possible to simulate the impact of the main recommendations on improving access to maternal health in Ethiopia. The findings of the simulation study can inform policy and programmatic decisions to address geographical disparities and improve adherence to iron and folate supplementation among pregnant women.

Author

Dima Health

Identifiers:

DOI: 10.1136/bmjopen-2022-061900

Research Areas:

Community Interventions, Disparities, Genetics and Genomics, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female