Determinants of nutritional status among pregnant women in East Shoa zone, Central Ethiopia

Frontiers in Nutrition, Volume 9, Year 2022

Interpretation

Background: Undernutrition is an insufficient intake of energy and nutrients to meet an individual’s needs to maintain good health. Undernutrition during pregnancy severely affects the health of mothers and her baby. Globally it contributes directly or indirectly to 3.5 million maternal deaths annually. This study aimed to determine the level of undernutrition and identify factors associated with undernutrition among pregnant women attending public health facilities in the East Shoa Zone, Central Ethiopia. Methods: Institution-based cross-sectional study was conducted among 472 randomly selected pregnant women from June to August 2021. Sociodemographic, obstetrics, and knowledge related data were collected using a structured interviewer-administered questionnaire, and maternal nutritional status was measured using the Mid Upper Arm Circumference (MUAC). The collected data were entered to EPI-info version 3.5.4 and then exported to SPSS for windows version 26.0 software for analysis. Multivariable regression analysis was fitted to identify determinants of undernutrition. An adjusted odds ratio with 95% confidence intervals and a p-value < 0.05 was considered a statistically significant. Results: The prevalence of undernutrition among pregnant women was 13.9% [95% CI: 11.0–17.4]. On multivariable logistic regression model after adjusting background variables, wealth (AOR: 4.9, 95% CI 1.34–18.20), women's decision making power (AOR: 3.31, 95% CI 1.18–7.79), and nutritional counseling (AOR: 3.53, 95% CI 1.29–9.60) were independently associated with nutritional status of pregnant women. Conclusion: Findings indicated that significant number of pregnant women in the study were undernourished. Higher wealth index, nutritional counseling, and women's decision-making power were inversely associated with undernutrition. The findings imply the need for economic empowerment of women, enhancing decision-making ability of women and routine and consistent nutritional counseling to decrease undernutrition among pregnant women. According to the East Shoa zone health office, the health service delivery is organized under 3 hospitals, 59 health centers, and 290 health posts. All the facilities are expected to provide maternal and neonatal health care services based on the National Essential Health Services Packages (EHSP) for different levels of health care. According to the zonal report of 2020, the facilities in the zone provided antenatal care service (ANC) for more than 54,408 pregnant women. The food production system in the district is characterized by mixed crop-livestock farming, with predominant crop production. The community is also known for cultivating different fruits and vegetables, which are considered cash crops. Teff is the principal crop produced in the area. This study was conducted from June to August 2021. Institution-based cross-sectional study design was used. All pregnant women who came for ANC service at selected health institutions in Eastern Shoa Zone during the study period were considered the study population. Pregnant women living in Eastern Shoa Zone and attending ANC service at the selected health center during the study period were given a chance to be included in the study. Severely sick women were not eligible. The sample size was calculated by using OpenEpi version 3.01 software (OpenSource.org/licenses). The minimum sample size was calculated using a single population proportion formula. Assuming standard error corresponding to a 95% confidence level (Z) = 1.96, the proportion of undernourished pregnant women from the previous study (p = 19.1), (17), margin of error (d) = 5% and design effect 2, the estimated sample size was 475. Multistage stratified sampling techniques was used to select study participants. Of a total of health centers in the east Shoa zone, six health centers from urban and eight health centers were included from rural kebele by using the lottery method. The total sample size was allocated to each health center based on the number of women who visited the health center in the preceding year in the same month. Finally, a systematic random sampling technique was used to select participants by following the Kth value. The Kth value was calculated by taking the total number of pregnant women on ANC during the study period and dividing it by the sample size, and it was found to be three. Then, lottery methods was used to choose the first case within the interval, which turned out to be 1.The first comer was considered as the first participants, and participants who came at the third interval were interviewed until the determined sample size was achieved. A structured and pretested questionnaire was used to collect information on sociodemographic and obstetrics characteristics, women autonomy, Household Food Insecurity Access Scale (HHFIAS), and knowledge of women. The data collectors were trained nurses and midwives recruited for this study. Participants were invited to the survey when they came to receive ANC service at the selected health institution. All the participants completed the survey questions. Mid upper arm circumference of pregnant women was measured by using inelastic MUAC tape. The midpoint of the left upper arm was located by flexing the women's elbows to 900 with the palm facing upwards and the midpoint between acromion to olecranon processes was marked. After this, measuring tape was placed around the arm at the midpoint. Two measurements was taken and reported to the nearest 0.1 cm. Women with MUAC < 22 cm were considered undernourished, and ≥ 22 cm were considered well-nourished (7). The household food security status in the past 4 weeks before data collection was assessed by using the Food Insecurity Access Scale (HFIAS) measurement tool. The score was calculated for each household by summing up the nine food insecurity-related conditions' frequency of occurrence. A household that obtained < 2 scores were considered food secured and those that obtained ≥ 2 scores were considered food insecure (18). Women's decision-making power was assessed using six questions adapted from previous literature (19). For each question, three options were presented, and one score was given when a decision was made by the woman alone or jointly with her husband, or zero was given if the decision did not involve women. Gravidity is number of times that a women get pregnant. Parity is the number of times that a woman had given birth to a fetus with a gestational age of 24 weeks or more, regardless of the child was born alive or was stillbirth. A total of 16 questions focusing on nutrition knowledge were presented to participants of this study. For knowledge questions, respondents with an average score greater than or equal to mean score were categorized as having adequate knowledge about nutrition during pregnancy and respondents with average score less than mean value were classified as having inadequate knowledge (20). To ensure the quality of the data, local languages were used for understanding of the questions. In addition, pre-test of research instruments and thorough training of data collectors and supervisors were done before the actual data collection. The supervisors provided on-site support to data collectors daily. All completed questionnaires were collected by respective supervisors and checked overnight to ensure completeness and consistencies. Regular meetings were held to provide feedback on issues of concern identified from data collected the next day. The data were entered to EPI-info version 3.5.4 and then exported to SPSS version 26.0 software for analysis. Binary logistic regression was used to check the association between explanotory variables and undernutrition. All variables with a p-value < 0.25 in bivariate analyses remained in the model as potential confounders for multivariable analysis. Hosmer and Lemeshow's goodness-of-fit test was performed to assess whether the required assumption was fulfilled, and variance inflation factors were checked to assess for multi-collinearity. The strength of association was expressed as adjusted odds ratio with 95% confidence intervals. A p-value < 0.05 was considered a statistically significant association with undernutrition. Multicolliniarity was checked using standard error of >2.

AI Digest

Study Justification:

– Undernutrition during pregnancy has severe health consequences for both mothers and babies, contributing to a significant number of maternal deaths globally.
– This study aimed to determine the level of undernutrition and identify factors associated with undernutrition among pregnant women in the East Shoa Zone, Central Ethiopia.
– The findings of this study will provide valuable insights into the prevalence and determinants of undernutrition among pregnant women in the study area, which can inform targeted interventions and policies to improve maternal and child health outcomes.

Highlights:

– The prevalence of undernutrition among pregnant women in the study area was found to be 13.9%.
– Factors independently associated with undernutrition included wealth, women’s decision-making power, and nutritional counseling.
– These findings highlight the importance of economic empowerment of women, enhancing women’s decision-making ability, and providing routine and consistent nutritional counseling to reduce undernutrition among pregnant women.

Recommendations:

– Economic empowerment programs should be implemented to improve the wealth status of pregnant women, which can positively impact their nutritional status.
– Efforts should be made to enhance women’s decision-making power, ensuring their involvement in matters related to their own health and nutrition.
– Routine and consistent nutritional counseling should be provided to pregnant women, focusing on the importance of a balanced diet and adequate nutrient intake during pregnancy.

Key Role Players:

– Ministry of Health: Responsible for developing and implementing policies and programs related to maternal and child health, including nutrition.
– Health Facilities: Provide antenatal care services and play a crucial role in delivering nutritional counseling to pregnant women.
– Community Health Workers: Act as intermediaries between health facilities and the community, providing education and support to pregnant women.
– Non-Governmental Organizations: Can contribute by implementing economic empowerment programs and supporting nutritional interventions for pregnant women.

Cost Items for Planning Recommendations:

– Training and Capacity Building: Budget for training healthcare providers on nutritional counseling and empowering women.
– Awareness and Education Campaigns: Allocate funds for community-level awareness campaigns on the importance of nutrition during pregnancy.
– Economic Empowerment Programs: Budget for implementing income-generating activities and providing financial support to pregnant women.
– Monitoring and Evaluation: Allocate resources for monitoring and evaluating the effectiveness of interventions and programs aimed at reducing undernutrition among pregnant women.
Please note that the cost items provided are general categories and not actual cost estimates. The specific budget items would depend on the context and resources available in the study area.

Strength of Evidence

N/A

Abstract

According to the East Shoa zone health office, the health service delivery is organized under 3 hospitals, 59 health centers, and 290 health posts. All the facilities are expected to provide maternal and neonatal health care services based on the National Essential Health Services Packages (EHSP) for different levels of health care. According to the zonal report of 2020, the facilities in the zone provided antenatal care service (ANC) for more than 54,408 pregnant women. The food production system in the district is characterized by mixed crop-livestock farming, with predominant crop production. The community is also known for cultivating different fruits and vegetables, which are considered cash crops. Teff is the principal crop produced in the area. This study was conducted from June to August 2021. Institution-based cross-sectional study design was used. All pregnant women who came for ANC service at selected health institutions in Eastern Shoa Zone during the study period were considered the study population. Pregnant women living in Eastern Shoa Zone and attending ANC service at the selected health center during the study period were given a chance to be included in the study. Severely sick women were not eligible. The sample size was calculated by using OpenEpi version 3.01 software (OpenSource.org/licenses). The minimum sample size was calculated using a single population proportion formula. Assuming standard error corresponding to a 95% confidence level (Z) = 1.96, the proportion of undernourished pregnant women from the previous study (p = 19.1), (17), margin of error (d) = 5% and design effect 2, the estimated sample size was 475. Multistage stratified sampling techniques was used to select study participants. Of a total of health centers in the east Shoa zone, six health centers from urban and eight health centers were included from rural kebele by using the lottery method. The total sample size was allocated to each health center based on the number of women who visited the health center in the preceding year in the same month. Finally, a systematic random sampling technique was used to select participants by following the Kth value. The Kth value was calculated by taking the total number of pregnant women on ANC during the study period and dividing it by the sample size, and it was found to be three. Then, lottery methods was used to choose the first case within the interval, which turned out to be 1.The first comer was considered as the first participants, and participants who came at the third interval were interviewed until the determined sample size was achieved. A structured and pretested questionnaire was used to collect information on sociodemographic and obstetrics characteristics, women autonomy, Household Food Insecurity Access Scale (HHFIAS), and knowledge of women. The data collectors were trained nurses and midwives recruited for this study. Participants were invited to the survey when they came to receive ANC service at the selected health institution. All the participants completed the survey questions. Mid upper arm circumference of pregnant women was measured by using inelastic MUAC tape. The midpoint of the left upper arm was located by flexing the women's elbows to 900 with the palm facing upwards and the midpoint between acromion to olecranon processes was marked. After this, measuring tape was placed around the arm at the midpoint. Two measurements was taken and reported to the nearest 0.1 cm. Women with MUAC < 22 cm were considered undernourished, and ≥ 22 cm were considered well-nourished (7). The household food security status in the past 4 weeks before data collection was assessed by using the Food Insecurity Access Scale (HFIAS) measurement tool. The score was calculated for each household by summing up the nine food insecurity-related conditions' frequency of occurrence. A household that obtained < 2 scores were considered food secured and those that obtained ≥ 2 scores were considered food insecure (18). Women's decision-making power was assessed using six questions adapted from previous literature (19). For each question, three options were presented, and one score was given when a decision was made by the woman alone or jointly with her husband, or zero was given if the decision did not involve women. Gravidity is number of times that a women get pregnant. Parity is the number of times that a woman had given birth to a fetus with a gestational age of 24 weeks or more, regardless of the child was born alive or was stillbirth. A total of 16 questions focusing on nutrition knowledge were presented to participants of this study. For knowledge questions, respondents with an average score greater than or equal to mean score were categorized as having adequate knowledge about nutrition during pregnancy and respondents with average score less than mean value were classified as having inadequate knowledge (20). To ensure the quality of the data, local languages were used for understanding of the questions. In addition, pre-test of research instruments and thorough training of data collectors and supervisors were done before the actual data collection. The supervisors provided on-site support to data collectors daily. All completed questionnaires were collected by respective supervisors and checked overnight to ensure completeness and consistencies. Regular meetings were held to provide feedback on issues of concern identified from data collected the next day. The data were entered to EPI-info version 3.5.4 and then exported to SPSS version 26.0 software for analysis. Binary logistic regression was used to check the association between explanotory variables and undernutrition. All variables with a p-value < 0.25 in bivariate analyses remained in the model as potential confounders for multivariable analysis. Hosmer and Lemeshow's goodness-of-fit test was performed to assess whether the required assumption was fulfilled, and variance inflation factors were checked to assess for multi-collinearity. The strength of association was expressed as adjusted odds ratio with 95% confidence intervals. A p-value 2.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women with access to important health information, including nutrition guidelines, appointment reminders, and educational resources. These apps can be easily accessed on smartphones, making it convenient for women in remote areas to receive timely and accurate information.

2. Telemedicine Services: Establish telemedicine services that allow pregnant women to consult with healthcare providers remotely. This can help overcome geographical barriers and ensure that women receive necessary prenatal care, including nutritional counseling, without having to travel long distances.

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, organize group sessions, and provide personalized guidance on nutrition and other aspects of maternal health.

4. Nutritional Support Programs: Implement programs that provide pregnant women with access to nutritious food and supplements. This can be done through partnerships with local farmers and markets to ensure a steady supply of fresh produce, as well as the distribution of prenatal vitamins and other essential nutrients.

5. Empowerment Initiatives: Develop initiatives that empower women and promote their decision-making power regarding their own health. This can include educational programs that focus on women’s rights, gender equality, and the importance of maternal health, as well as initiatives that provide economic opportunities for women to improve their financial status and access to healthcare.

These innovations have the potential to improve access to maternal health by addressing factors such as information availability, geographical barriers, community support, and women’s empowerment. However, it is important to consider the specific context and needs of the East Shoa Zone in Central Ethiopia when implementing these recommendations.

AI Innovations Description

Based on the study titled “Determinants of nutritional status among pregnant women in East Shoa zone, Central Ethiopia,” several recommendations can be developed into innovations to improve access to maternal health. These recommendations include:

1. Economic empowerment of women: The study found that higher wealth index was inversely associated with undernutrition among pregnant women. Therefore, implementing innovative programs that focus on economic empowerment of women, such as providing microfinance opportunities or vocational training, can help improve access to maternal health by addressing the financial barriers that pregnant women may face.

2. Enhancing women’s decision-making power: The study also found that women’s decision-making power was associated with nutritional status of pregnant women. To improve access to maternal health, innovative interventions can be developed to empower women and ensure their active participation in decision-making processes related to their health and nutrition during pregnancy. This can be achieved through community-based education programs or support groups that promote women’s rights and autonomy.

3. Routine and consistent nutritional counseling: The study identified that nutritional counseling was independently associated with nutritional status of pregnant women. To improve access to maternal health, innovative approaches can be implemented to ensure that pregnant women receive regular and consistent nutritional counseling throughout their pregnancy. This can be done through the use of mobile health technologies, such as text messages or mobile applications, that provide personalized and timely nutrition advice to pregnant women.

Overall, these recommendations can be developed into innovative interventions that address the determinants of undernutrition among pregnant women and improve access to maternal health in the East Shoa zone, Central Ethiopia.

AI Innovations Methodology

To improve access to maternal health in the East Shoa Zone, Central Ethiopia, the following innovations and recommendations can be considered:

1. Mobile Health (mHealth) Solutions: Implementing mobile health technologies, such as mobile apps or SMS-based systems, can help improve access to maternal health information and services. These technologies can provide pregnant women with important health tips, appointment reminders, and access to teleconsultations with healthcare providers.

2. Community Health Workers (CHWs): Training and deploying community health workers can help bridge the gap between healthcare facilities and remote communities. CHWs can provide essential maternal health services, including antenatal care, health education, and referrals for complicated cases.

3. Telemedicine: Establishing telemedicine services can enable pregnant women in remote areas to consult with healthcare professionals without the need for physical travel. Telemedicine can provide timely advice, diagnosis, and treatment options, reducing the barriers to accessing maternal healthcare.

4. Transportation Support: Improving transportation infrastructure and providing transportation support, such as ambulances or community transport systems, can ensure that pregnant women can reach healthcare facilities in a timely manner, especially during emergencies.

Methodology to simulate the impact of these recommendations on improving access to maternal health:

1. Define the Simulation Objective: Clearly define the objective of the simulation, such as assessing the potential impact of the recommended innovations on improving access to maternal health services in the East Shoa Zone.

2. Identify Key Variables: Identify the key variables that will be used to measure access to maternal health, such as the number of pregnant women receiving antenatal care, the distance to the nearest healthcare facility, and the time taken to reach healthcare facilities.

3. Collect Baseline Data: Gather baseline data on the current state of maternal health access in the East Shoa Zone. This can include data on the number of healthcare facilities, the availability of transportation, and the utilization of maternal health services.

4. Define Scenarios: Develop different scenarios based on the recommended innovations. For example, one scenario could involve the implementation of mHealth solutions, while another scenario could focus on the deployment of community health workers. Define the specific changes that will be simulated for each scenario.

5. Simulate the Impact: Use appropriate simulation techniques, such as agent-based modeling or system dynamics modeling, to simulate the impact of the recommended innovations on access to maternal health. Incorporate the key variables and scenarios defined earlier to model the potential changes in access.

6. Analyze Results: Analyze the simulation results to assess the potential impact of the recommended innovations. Compare the outcomes of different scenarios to identify the most effective strategies for improving access to maternal health.

7. Validate and Refine: Validate the simulation results by comparing them with real-world data and expert opinions. Refine the simulation model as needed to improve its accuracy and reliability.

8. Communicate Findings: Present the findings of the simulation study to relevant stakeholders, such as policymakers, healthcare providers, and community leaders. Use the results to advocate for the implementation of the recommended innovations and inform decision-making processes.

By following this methodology, stakeholders can gain insights into the potential impact of the recommended innovations and make informed decisions to improve access to maternal health in the East Shoa Zone.

Author

Dima Health

Identifiers:

DOI: 10.3389/fnut.2022.958591

Research Areas:

Community Interventions, Disparities, Food Security, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Workforce

Study Countries:

Ethiopia

Study Design:

Case-Control Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female