Prevalence of Undernutrition and Associated Factors among Pregnant Women in a Public General Hospital, Tigray, Northern Ethiopia: A Cross-Sectional Study Design

Journal of Nutrition and Metabolism, Volume 2020, Year 2020

Interpretation

Background. Undernutrition is a global health problem, particularly in pregnant women. Despite the limited studies performed in different parts of Ethiopia, the information about the prevalence of undernutrition of pregnant women in the current study area is not documented. Therefore, this study aimed to assess the prevalence of undernutrition and associated factors in pregnant women. Methods. An institution-based cross-sectional study design was conducted in the Tigray region from August 01 to December 30, 2018. Study subjects were selected by systematic sampling technique from the respective hospitals. An interviewer-administered questionnaire was used to collect the data. Data were cleaned and entered using Epi-Data version 3.1 and then exported to statistical package for social science (SPSS) version 23.0 for analysis. Multivariate analyses were carried out, and adjusted odds ratios (AORs) with 95% CI and significance level (p value) <0.05 were considered. Results. Out of the total 844 selected pregnant women, 840 participated in the study, yielding a response rate of 99.5%; of this, respondent's undernutrition prevalence was found to be 40.6% with 95% confidence interval (38.93% and 42.27%). Agriculture as occupation (AOR = 2.6, 95% CI: 1.5, 4.5), women who wanted the pregnancy (AOR = 0.25, 95% CI: 0.14, 0.448), no history malaria during pregnancy (AOR = 0.291, 95%: (0.152, 0.555)), coffee intake during pregnancy (AOR = 1.6, 95% CI: 1.04, 2.69), and hemoglobin < 11 g/dl (AOR = 4.9, 95% CI: 3.09, 7.8) were the factors that were significantly associated with undernutrition, p value (<0.05). Conclusion. In this study, occupation, history of having malaria during pregnancy, wanted type pregnancy, coffee intake during pregnancy, and hemoglobin < 11 g/dl were factors significantly associated with undernutrition in pregnant mothers. So, healthcare providers, policymakers, and other stakeholders should give special focus on these factors. An institution-based cross-sectional study design was carried out. This study was conducted in public general hospitals of the Tigray region; in the region, there were 14 total public general hospitals from those five hospitals: Mekelle public general Hospital found in the regional administration, St. Marry public general hospital found in the central zone of the region, Lemlem Karl public general Hospital found in the southern zone of the region, Kahsay Abera public general Hospital west zone of the region, and Adigrat public general hospital found in the southeast were the selected study area. Data collection for this study was undertaken from August 01 to December 30, 2018. The source populations were all third-trimester pregnant women who were coming for delivery and antenatal care visits in the selected public general hospitals of the Tigray region. Third-trimester pregnancy women who were coming for delivery and antenatal care visits in general public hospitals of the Tigray region were selected as the study population. All selected third-trimester pregnant women who were coming for delivery and ANC in public general hospitals during the study period were included, whereas pregnancy women with bilateral edema were excluded. Sample size was calculated using single population proportion formula by assuming precision (d) = 5%, confidence level = 95% (Ζα/2 = 1.96), and proportion of undernutrition (P) = 50%. By considering a 10% nonresponse rate, it becomes 422. Finally, 844 pregnant women were taken as a final sample size after using the design effect two. Two-stage sampling was employed to select the study participants. In Tigray, there were 14 public general hospitals; from those, five hospitals were selected randomly and the sample size was proportionally allocated to each hospital. A systematic random sampling technique was used to select every (determined interval K = 2) study subjects from all the five hospitals. A semistructured questionnaire was initially prepared in English and then translated into the local language; Tigrigna was used. Tigrigna version was again translated back to English to check for any inconsistencies or distortion in the meaning of words. Data were collected using an interviewer-administered, and MUAC measurement questionnaire was adapted from the literature. Data collection was performed by five B.Sc. nurses. To assure the quality of the data properly designed data collection instrument and training of data collectors and supervisors was done, the enumerators and the supervisor were given training for three days on procedures, techniques, ways of collecting the data, and monitoring the procedure. Ten percent pretest was done at the Shul public general hospital to check the consistency of the questioner. The collected data were reviewed and checked for completeness by supervisors and principal investigators each week. MUAC was measured by considering the mothers in Frankfurt plane and sideways to measure the left side, arms hanging loosely at the side with the palm facing inward, taken at marked midpoint of upper left arm, a flexible nonstretchable tape should be used, and difference between trainee and trainer should be 0–5 mm. Nutritional status of pregnant mothers is the outcome variable, and the independent variables were all the sociodemographic characteristics and maternal obstetrical and gynecology history. A brief description of how some of these variables were measured is as follows. The mid-upper arm circumstance values below a cutoff point <23 cm were considered as undernutrition in this study, whereas for the individual in the third-trimester (23 cm and above), it was considered normal [12]. Potential confounding variables measured in the study were sociodemographic characteristics and obstetrics and gynecology including the age of mother, marital status, religion, educational background of mothers and household, income, occupation, ethnicity, number of antenatal care visits, type of pregnancy, maternal previous surgery, malaria, parity, iron and folic acid supplementation, marriage at age, hemoglobin level, coffee intake, husband's support, depression, difficulty to access food during the last three months, and history of low birthweight. The anthropometric measurement midupper arm circumstance was taken from individual third-trimester pregnant women. After data were entered into Epi-Data 3.1, they were exported to (SPSS) Version 23 for analysis. Binary logistic regression analysis was executed to see the association between independent and outcome variables. All explanatory variables associated with the outcome variable with p < 0.25 were entered into multivariable logistic regression analysis, and a significant association was identified based on p < 0.05 and AOR with 95% CI.

AI Digest

Study Justification:

– Undernutrition is a global health problem, particularly in pregnant women.
– Limited studies have been conducted on the prevalence of undernutrition among pregnant women in the study area.
– Assessing the prevalence of undernutrition and associated factors is important for identifying at-risk populations and developing targeted interventions.

Study Highlights:

– The study was conducted in public general hospitals in the Tigray region of Northern Ethiopia.
– A total of 840 pregnant women participated in the study, with a response rate of 99.5%.
– The prevalence of undernutrition among pregnant women was found to be 40.6%.
– Factors significantly associated with undernutrition included occupation, history of malaria during pregnancy, type of pregnancy, coffee intake during pregnancy, and low hemoglobin levels.

Recommendations for Lay Reader:

– Pregnant women should be aware of the risk factors associated with undernutrition, such as occupation, history of malaria, and coffee intake.
– Healthcare providers should provide targeted interventions and support for pregnant women at risk of undernutrition.
– Pregnant women should prioritize their nutritional needs and seek appropriate antenatal care.

Recommendations for Policy Maker:

– Develop and implement policies to address the risk factors associated with undernutrition among pregnant women, such as improving occupational conditions and providing malaria prevention measures.
– Allocate resources for targeted interventions and programs to improve the nutritional status of pregnant women.
– Strengthen antenatal care services to include nutritional counseling and support for pregnant women.

Key Role Players:

– Healthcare providers: Responsible for providing antenatal care, nutritional counseling, and support to pregnant women.
– Policy makers: Responsible for developing and implementing policies to address undernutrition among pregnant women.
– Researchers: Responsible for conducting further studies to explore additional factors and interventions related to undernutrition in pregnant women.

Cost Items for Planning Recommendations:

– Training and capacity building for healthcare providers: Budget for training programs and workshops to enhance the knowledge and skills of healthcare providers in addressing undernutrition among pregnant women.
– Implementation of targeted interventions: Budget for the development and implementation of programs and interventions to improve the nutritional status of pregnant women.
– Monitoring and evaluation: Budget for monitoring and evaluating the effectiveness of interventions and programs aimed at reducing undernutrition among pregnant women.
– Research funding: Budget for conducting further research to explore additional factors and interventions related to undernutrition in pregnant women.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides a clear study design, sample size calculation, data collection methods, and statistical analysis. However, it lacks information on the representativeness of the sample and potential limitations of the study. To improve the evidence, the abstract could include details on the representativeness of the sample, such as the demographic characteristics of the participants and how they were selected. Additionally, it would be helpful to mention any limitations of the study, such as potential biases or confounding factors that were not accounted for.

Abstract

An institution-based cross-sectional study design was carried out. This study was conducted in public general hospitals of the Tigray region; in the region, there were 14 total public general hospitals from those five hospitals: Mekelle public general Hospital found in the regional administration, St. Marry public general hospital found in the central zone of the region, Lemlem Karl public general Hospital found in the southern zone of the region, Kahsay Abera public general Hospital west zone of the region, and Adigrat public general hospital found in the southeast were the selected study area. Data collection for this study was undertaken from August 01 to December 30, 2018. The source populations were all third-trimester pregnant women who were coming for delivery and antenatal care visits in the selected public general hospitals of the Tigray region. Third-trimester pregnancy women who were coming for delivery and antenatal care visits in general public hospitals of the Tigray region were selected as the study population. All selected third-trimester pregnant women who were coming for delivery and ANC in public general hospitals during the study period were included, whereas pregnancy women with bilateral edema were excluded. Sample size was calculated using single population proportion formula by assuming precision (d) = 5%, confidence level = 95% (Ζα/2 = 1.96), and proportion of undernutrition (P) = 50%. By considering a 10% nonresponse rate, it becomes 422. Finally, 844 pregnant women were taken as a final sample size after using the design effect two. Two-stage sampling was employed to select the study participants. In Tigray, there were 14 public general hospitals; from those, five hospitals were selected randomly and the sample size was proportionally allocated to each hospital. A systematic random sampling technique was used to select every (determined interval K = 2) study subjects from all the five hospitals. A semistructured questionnaire was initially prepared in English and then translated into the local language; Tigrigna was used. Tigrigna version was again translated back to English to check for any inconsistencies or distortion in the meaning of words. Data were collected using an interviewer-administered, and MUAC measurement questionnaire was adapted from the literature. Data collection was performed by five B.Sc. nurses. To assure the quality of the data properly designed data collection instrument and training of data collectors and supervisors was done, the enumerators and the supervisor were given training for three days on procedures, techniques, ways of collecting the data, and monitoring the procedure. Ten percent pretest was done at the Shul public general hospital to check the consistency of the questioner. The collected data were reviewed and checked for completeness by supervisors and principal investigators each week. MUAC was measured by considering the mothers in Frankfurt plane and sideways to measure the left side, arms hanging loosely at the side with the palm facing inward, taken at marked midpoint of upper left arm, a flexible nonstretchable tape should be used, and difference between trainee and trainer should be 0–5 mm. Nutritional status of pregnant mothers is the outcome variable, and the independent variables were all the sociodemographic characteristics and maternal obstetrical and gynecology history. A brief description of how some of these variables were measured is as follows. The mid-upper arm circumstance values below a cutoff point <23 cm were considered as undernutrition in this study, whereas for the individual in the third-trimester (23 cm and above), it was considered normal [12]. Potential confounding variables measured in the study were sociodemographic characteristics and obstetrics and gynecology including the age of mother, marital status, religion, educational background of mothers and household, income, occupation, ethnicity, number of antenatal care visits, type of pregnancy, maternal previous surgery, malaria, parity, iron and folic acid supplementation, marriage at age, hemoglobin level, coffee intake, husband's support, depression, difficulty to access food during the last three months, and history of low birthweight. The anthropometric measurement midupper arm circumstance was taken from individual third-trimester pregnant women. After data were entered into Epi-Data 3.1, they were exported to (SPSS) Version 23 for analysis. Binary logistic regression analysis was executed to see the association between independent and outcome variables. All explanatory variables associated with the outcome variable with p < 0.25 were entered into multivariable logistic regression analysis, and a significant association was identified based on p < 0.05 and AOR with 95% CI.

Materials

N/A

Innovations

Based on the provided information, here are some potential innovations that could be recommended to 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, appointment reminders, and personalized care plans. These apps can also include features for tracking maternal nutrition and providing dietary recommendations.

2. Telemedicine Services: Establish telemedicine services that allow pregnant women in remote or underserved areas to consult with healthcare providers through video calls or phone consultations. This can help overcome geographical barriers and improve access to prenatal care.

3. Community Health Workers: Train and deploy community health workers who can provide education, support, and basic healthcare services to pregnant women in their local communities. These workers can help identify and refer high-risk pregnancies, provide antenatal care, and promote healthy behaviors.

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. Public-Private Partnerships: Foster collaborations between public healthcare facilities and private healthcare providers to expand access to maternal health services. This can involve contracting private providers to deliver services in underserved areas or leveraging their resources and expertise to improve the quality of care in public facilities.

6. Maternal Health Education Campaigns: Launch targeted education campaigns to raise awareness about the importance of maternal health and promote healthy behaviors during pregnancy. These campaigns can be conducted through various channels, such as mass media, community outreach programs, and social media platforms.

7. Transportation Support: Develop transportation support programs that provide pregnant women with affordable and reliable transportation to healthcare facilities for prenatal visits, delivery, and postnatal care. This can help address transportation barriers, especially in rural or remote areas.

8. Maternal Health Hotlines: Establish toll-free hotlines staffed by trained healthcare professionals who can provide information, counseling, and referrals to pregnant women seeking advice or assistance. This can be particularly beneficial for women with questions or concerns outside of regular clinic hours.

9. Maternal Health Monitoring Systems: Implement electronic health record systems that enable healthcare providers to track and monitor the health status of pregnant women throughout their pregnancy. This can improve continuity of care, facilitate timely interventions, and ensure comprehensive follow-up.

10. Maternal Health Task Forces: Create multidisciplinary task forces or committees dedicated to improving maternal health outcomes. These task forces can bring together healthcare professionals, policymakers, researchers, and community representatives to identify and address barriers to access, develop evidence-based interventions, and monitor progress towards improving maternal health.

AI Innovations Description

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

1. Strengthen Antenatal Care (ANC) Services: Implementing regular and comprehensive ANC visits can help identify and address undernutrition in pregnant women. ANC visits should include nutritional counseling, supplementation of iron and folic acid, and monitoring of weight gain.

2. Improve Education and Awareness: Develop educational programs targeting pregnant women and their families to raise awareness about the importance of proper nutrition during pregnancy. This can include information on balanced diets, food choices, and the impact of undernutrition on maternal and fetal health.

3. Enhance Access to Nutritious Food: Collaborate with local agricultural and food production sectors to improve access to nutritious food for pregnant women. This can involve promoting the cultivation and consumption of locally available nutrient-rich foods, as well as exploring options for food supplementation programs.

4. Strengthen Healthcare Provider Training: Provide training to healthcare providers on the identification, prevention, and management of undernutrition in pregnant women. This can help ensure that healthcare providers have the necessary knowledge and skills to effectively address undernutrition during antenatal and delivery care.

5. Implement Community-Based Interventions: Engage community health workers and volunteers to conduct regular home visits and provide support and guidance to pregnant women. These interventions can include nutrition education, cooking demonstrations, and monitoring of weight gain to promote healthy maternal nutrition.

6. Improve Access to Malaria Prevention and Treatment: Strengthen efforts to prevent and treat malaria during pregnancy, as it was found to be significantly associated with undernutrition. This can involve distributing insecticide-treated bed nets, providing antimalarial medications, and promoting awareness about the importance of malaria prevention.

7. Enhance Collaboration and Coordination: Foster collaboration between healthcare providers, policymakers, and other stakeholders involved in maternal health to develop comprehensive strategies and policies addressing undernutrition. This can include regular meetings, information sharing, and joint planning to ensure a holistic approach to improving access to maternal health services.

By implementing these recommendations, it is possible to develop innovative approaches that address undernutrition and improve access to maternal health services, ultimately leading to better health outcomes for pregnant women and their babies.

AI Innovations Methodology

To improve access to maternal health, here are some potential recommendations:

1. Strengthening Antenatal Care (ANC) Services: Enhance the quality and availability of ANC services by ensuring regular check-ups, providing comprehensive health education, and promoting early detection and management of maternal health issues.

2. Mobile Health (mHealth) Interventions: Utilize mobile technology to deliver maternal health information, reminders for appointments and medication, and provide access to teleconsultations with healthcare providers.

3. Community-Based Interventions: Implement community-based programs that focus on raising awareness about maternal health, promoting healthy behaviors, and providing support networks for pregnant women.

4. Transportation Support: Improve transportation infrastructure and provide transportation support for pregnant women in remote areas to ensure they can access healthcare facilities in a timely manner.

5. Task-Shifting and Training: Train and empower community health workers and midwives to provide basic maternal healthcare services, including prenatal care and postnatal support, in areas with limited access to healthcare facilities.

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

1. Define the target population: Identify the specific population group (e.g., pregnant women in a particular region) for which access to maternal health needs improvement.

2. Collect baseline data: Gather relevant data on the current state of access to maternal health services, including factors such as distance to healthcare facilities, availability of transportation, utilization of ANC services, and prevalence of undernutrition.

3. Develop a simulation model: Create a mathematical or statistical model that incorporates the identified recommendations and their potential impact on improving access to maternal health. This model should consider factors such as the number of ANC visits, distance traveled, utilization rates, and health outcomes.

4. Input data and parameters: Input the collected baseline data and parameters into the simulation model. This includes information on the target population, the implementation of the recommendations, and any assumptions or constraints.

5. Run simulations: Use the simulation model to run multiple scenarios that simulate the impact of the recommendations on access to maternal health. Vary the parameters and assumptions to explore different potential outcomes.

6. Analyze results: Analyze the simulation results to assess the potential impact of the recommendations on improving access to maternal health. This may include evaluating changes in utilization rates, reduction in travel distance, improvements in health outcomes, and cost-effectiveness.

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

8. Communicate findings: Present the findings of the simulation study, including the potential impact of the recommendations on improving access to maternal health, to relevant stakeholders such as policymakers, healthcare providers, and community organizations. This can inform decision-making and resource allocation for implementing the recommendations.

By following this methodology, stakeholders can gain insights into the potential benefits and challenges of implementing specific recommendations to improve access to maternal health and make informed decisions on how to prioritize and allocate resources effectively.

Author

Dima Health

Statistics:

Citations: 10

Identifiers:

DOI: 10.1155/2020/2736536

ISSN: 20900724

Research Areas:

Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Mental Health, Sexual and Reproductive Health, Social Determinants

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study, Grounded Theory, Phenomenological Study

Study Approach:

Quantitative

Participants Gender:

Female