Maternal minimum dietary diversity and associated factors among pregnant women, Southwest Ethiopia, 2021

BMC Nutrition, Volume 7, No. 1, Year 2021

Interprétation

Background: Inadequate dietary diversity intake during pregnancy increases risks of intrauterine growth restriction, abortion, low birth weight, preterm birth, prenatal and infant mortality,and morbidity and has long-lasting health impacts. Dietary diversity during pregnancy promotes the health status of the mother and her fetus. This study aimed to assess the magnitude of minimum dietary diversity and associated factors among pregnant women attending antenatal care. Methods: A facility-based cross-sectional study was conducted among 274 pregnant women who attended antenatal care at Wacha primary hospital from January to February 2021. A systematic sampling method was used to select the study participants. The data were collected through face-to-face interviews using a structured and semi-structured questionnaire. Bivariate logistic regression was done to identify factors associated with maternal dietary diversity. Finally, multivariate logistic regression was done, and variables that showed P values of < 0.05 were considered statistically significant. Result: The magnitude of minimum dietary diversity was 51% (95% CI: 44.5, 56.7). The mean (±SD) minimum dietary diversity score was 4.5 (± 1.268) with a minimum of 1 anda maximum of 8 food groups consumed out of ten food groups. Age fewer than 25 years (AOR 4.649; 95% CI; 1.404, 15.396), and the age group between 25 to 34 years (AOR 3.624; 95% CI: 1.315, 10.269), husband age group of 26 to 34 years (AOR 2.238; 95% CI; 1.028,4.873), and 35 to 44 years (AOR 3.555; 95% CI; 1.228,10.292) and nutrition awareness of women (AOR 2.182; 95% CI; 1.243, 3.829) were significantly associated with minimum dietary diversity. Conclusion: The consumption of minimum dietary diversity of the pregnant mothers was found to be low. Women aged less than 25 and age between 25 to 34 years, husband’s age between 26 to 34 and 35 to 44 years, and nutrition awareness were the factors significantly associated with minimum dietary diversity. Therefore, providing nutrition education and counseling service warranted to promote maternal dietary diversity. The study was conducted at Wacha primary hospital which was established in 2005. It is found in Chena town, Kaffa Zone, Southwest Ethiopia which is located 541 km far from Addis Ababa, the capital city of Ethiopia and it is the only hospital in Chena district. The hospital has been giving health services for the total population of 30,891 people in its catchment area with different four major departments including medical, pediatrics, surgical, and obstetrics, and gynecology. It also provides outpatient service, ophthalmology, emergency, antiretroviral Therapy (ART) clinic, and ANC clinic. There were a total of 723 pregnant women who had attended ANC in 2020/21 and on average around 30–40 followers have been attended ANC clinic every day at Wacha primary hospital. A facility-based cross-sectional study was conducted from January to February 2021. All pregnant women attended the ANC clinic at Wacha primary hospital, Kaffa zone. All randomly selected pregnant women attending ANC clinic at Wacha primary hospital from 16 weeks gestational age were included in the sample. The required sample size was determined using single population proportion formula based on the assumption of high minimum dietary diversity of 55.2% in Bale zone, Ethiopia [33], 5% margin of error, 95% of Confidence Interval (CI), 10% of non-response rate, and by using the correction formula since the target population of the study area was below 10,000. Then the final sample sizes 274 of pregnant women were included. The study participants were selected by using a systematic random sampling technique. The sampling interval was determined by calculating monthly average attendance for ANC follow-up divided by the required sample size, and then, the first study participant was selected randomly and then every third pregnant woman was included. Pregnant women with greater than 16 week’s gestational age and who lived in the study area for at least one year were included in the study. Pregnant women who were unable to speak&/hear and who have seriously ill during data collection. The dependent variable of this study was dietary diversity status, and independent variables like age, marital status, occupation, residence, educational status, family size, household head, nutrition awareness of women, maternal health status, husband support, income, having mobile phone, radio and bank account, garden, water source, availability of latrine, marketing, and household food security and nutritional status of pregnant women. The data were collected through face-to-face interviews using pretested structured and semi-structured questionnaires adapted from different kinds of literature [2, 33, 36]. The data were collected by well-trained Nurse professionals. The questionnaire had three parts. The first part includes socio-demographic factors (age, marital status, residence, family size, education, occupation, and others). The second part was dietary-related information questionnaires which were adapted and modified from the Food and Agriculture Organization of the United Nations (FAO) 2016 [36]. The dietary diversity questioner has ten different food groups based on their nutrients:1) grains, white root, tubers, and plantains, 2) pulses (beans, peas, and lentils), 3) nuts and seeds, 4) dairy, 5) meat and fish (poultry and fish), 6) eggs, 7) dark green leafy vegetables, 8) vitamin A-rich fruits and vegetables, 9) others vegetables, and 10) others fruits. It was assessed by using 24-h open dietary recall methods; one point was given to each food group consumed over the past 24 h before the survey period. The participants were asked about all food and beverage consumed during the day and night including any snack in the past 24 h and the interviewer were probing for any food types forgotten by participants. Each food or beverage that the respondent mentions was circled underlined on a predefined list. The foods not included on the predefined list were classify by the principal investigator on an existing predefined food group or recorded in a separate place on the questionnaire and coded and organized later into one of the predefined food groups [36]. The third part was household food security status which was assessed by using Household Food Insecurity Access Scale (HFIAS) [37]. The household food security was categorized as food insecure for those who score 2 and above out of 27 household food insecurity indicators and while food secures categorized for pregnant women who scored less than 2 out of 27 household food insecurity indicators. Nutritional status of pregnant women was assessed by using mid-upper arm circumference (MUAC) which was measured halfway between the olecranon process and acromion process by using -non-stretchable tape to the nearest 0.1 cm. Nutritional status was defined as MUAC less than 22 cm were undernutrition and while 22 cm or more was considered to be normal nutritional status [38, 39]. Initially, a survey questionnaire was prepared in English translated to the local language and translated back to English to check for consistency. A three days training was given for data collectors and supervisors and a pretest was done on 5% of the study sample size. The Cronbach’s alpha was calculated (P = 0.78). The data were checked by the principal investigator on the daily basis for completeness and consistency. After the data were cleaned and coded, the data were entered in Epidata 3.1 version software and exported to statistical package for social science (SPSS) version 21 for analysis. A minimum dietary diversity score (MDDS) was dichotomized as meet minimum dietary diversity for pregnant women who consumed 5 and above out of ten food groups coded as 1 and while unmeet minimum dietary diversity for those who consume less than 5 out of ten food groups in the past 24 h coded as 0. Descriptive analysis was done to calculate the mean, frequencies, and percentage distributions for the variables. A stepwise backward elimination logistic regression was done to identify variables associated with minimum dietary diversity. The model fitness was checked by using Hosmer and Lemeshow statistic (P = 0.47), which showed the model was fitted. Bivariate logistic regression was done to identify the covariate associated with minimum dietary diversity and independents variables and the variables with a p-value less than 0.05 were considered for multivariable logistic regression to control all possible confounders and to determine the strength of association between minimum dietary diversity and each explanatory variable. The strength of association was measured with an adjusted odds ratio (AOR) with a 95% CI. Finally, the variables with a P-value less than 0.05 were considered statistically significant.

Résumé de l’IA

Study Justification:

– Inadequate dietary diversity during pregnancy can lead to various negative outcomes for both the mother and the fetus, including intrauterine growth restriction, low birth weight, preterm birth, and increased mortality and morbidity.
– Promoting maternal dietary diversity is crucial for improving the health status of pregnant women and their babies.
– This study aimed to assess the magnitude of minimum dietary diversity and identify associated factors among pregnant women attending antenatal care in Southwest Ethiopia.

Study Highlights:

– The study found that the magnitude of minimum dietary diversity among pregnant women was 51%.
– The mean minimum dietary diversity score was 4.5 out of 10 food groups.
– Factors significantly associated with minimum dietary diversity included age (less than 25 years and 25 to 34 years), husband’s age (26 to 34 years and 35 to 44 years), and nutrition awareness of women.

Study Recommendations:

– Provide nutrition education and counseling services to pregnant women to promote dietary diversity.
– Target interventions towards younger pregnant women and their husbands to improve their understanding of the importance of dietary diversity.
– Develop strategies to increase nutrition awareness among pregnant women and their families.

Key Role Players:

– Healthcare professionals: Nurses, doctors, and nutritionists who can provide nutrition education and counseling services.
– Community health workers: They can play a role in disseminating information about the importance of dietary diversity to pregnant women and their families.
– Policy makers: They can develop and implement policies that support nutrition education and counseling services for pregnant women.

Cost Items for Planning Recommendations:

– Training and capacity building for healthcare professionals and community health workers.
– Development and dissemination of educational materials on nutrition during pregnancy.
– Awareness campaigns targeting pregnant women and their families.
– Monitoring and evaluation of the implemented interventions.
– Coordination and collaboration between different stakeholders involved in promoting maternal dietary diversity.

Force de la preuve

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study design is a facility-based cross-sectional study, which limits the ability to establish causality. However, the study had a relatively large sample size and used a systematic sampling method. The data collection methods were described, and statistical analyses were conducted to identify factors associated with minimum dietary diversity. To improve the strength of the evidence, future studies could consider using a longitudinal design to establish causality and include a control group for comparison.

Abstrait

The study was conducted at Wacha primary hospital which was established in 2005. It is found in Chena town, Kaffa Zone, Southwest Ethiopia which is located 541 km far from Addis Ababa, the capital city of Ethiopia and it is the only hospital in Chena district. The hospital has been giving health services for the total population of 30,891 people in its catchment area with different four major departments including medical, pediatrics, surgical, and obstetrics, and gynecology. It also provides outpatient service, ophthalmology, emergency, antiretroviral Therapy (ART) clinic, and ANC clinic. There were a total of 723 pregnant women who had attended ANC in 2020/21 and on average around 30–40 followers have been attended ANC clinic every day at Wacha primary hospital. A facility-based cross-sectional study was conducted from January to February 2021. All pregnant women attended the ANC clinic at Wacha primary hospital, Kaffa zone. All randomly selected pregnant women attending ANC clinic at Wacha primary hospital from 16 weeks gestational age were included in the sample. The required sample size was determined using single population proportion formula based on the assumption of high minimum dietary diversity of 55.2% in Bale zone, Ethiopia [33], 5% margin of error, 95% of Confidence Interval (CI), 10% of non-response rate, and by using the correction formula since the target population of the study area was below 10,000. Then the final sample sizes 274 of pregnant women were included. The study participants were selected by using a systematic random sampling technique. The sampling interval was determined by calculating monthly average attendance for ANC follow-up divided by the required sample size, and then, the first study participant was selected randomly and then every third pregnant woman was included. Pregnant women with greater than 16 week’s gestational age and who lived in the study area for at least one year were included in the study. Pregnant women who were unable to speak&/hear and who have seriously ill during data collection. The dependent variable of this study was dietary diversity status, and independent variables like age, marital status, occupation, residence, educational status, family size, household head, nutrition awareness of women, maternal health status, husband support, income, having mobile phone, radio and bank account, garden, water source, availability of latrine, marketing, and household food security and nutritional status of pregnant women. The data were collected through face-to-face interviews using pretested structured and semi-structured questionnaires adapted from different kinds of literature [2, 33, 36]. The data were collected by well-trained Nurse professionals. The questionnaire had three parts. The first part includes socio-demographic factors (age, marital status, residence, family size, education, occupation, and others). The second part was dietary-related information questionnaires which were adapted and modified from the Food and Agriculture Organization of the United Nations (FAO) 2016 [36]. The dietary diversity questioner has ten different food groups based on their nutrients:1) grains, white root, tubers, and plantains, 2) pulses (beans, peas, and lentils), 3) nuts and seeds, 4) dairy, 5) meat and fish (poultry and fish), 6) eggs, 7) dark green leafy vegetables, 8) vitamin A-rich fruits and vegetables, 9) others vegetables, and 10) others fruits. It was assessed by using 24-h open dietary recall methods; one point was given to each food group consumed over the past 24 h before the survey period. The participants were asked about all food and beverage consumed during the day and night including any snack in the past 24 h and the interviewer were probing for any food types forgotten by participants. Each food or beverage that the respondent mentions was circled underlined on a predefined list. The foods not included on the predefined list were classify by the principal investigator on an existing predefined food group or recorded in a separate place on the questionnaire and coded and organized later into one of the predefined food groups [36]. The third part was household food security status which was assessed by using Household Food Insecurity Access Scale (HFIAS) [37]. The household food security was categorized as food insecure for those who score 2 and above out of 27 household food insecurity indicators and while food secures categorized for pregnant women who scored less than 2 out of 27 household food insecurity indicators. Nutritional status of pregnant women was assessed by using mid-upper arm circumference (MUAC) which was measured halfway between the olecranon process and acromion process by using -non-stretchable tape to the nearest 0.1 cm. Nutritional status was defined as MUAC less than 22 cm were undernutrition and while 22 cm or more was considered to be normal nutritional status [38, 39]. Initially, a survey questionnaire was prepared in English translated to the local language and translated back to English to check for consistency. A three days training was given for data collectors and supervisors and a pretest was done on 5% of the study sample size. The Cronbach’s alpha was calculated (P = 0.78). The data were checked by the principal investigator on the daily basis for completeness and consistency. After the data were cleaned and coded, the data were entered in Epidata 3.1 version software and exported to statistical package for social science (SPSS) version 21 for analysis. A minimum dietary diversity score (MDDS) was dichotomized as meet minimum dietary diversity for pregnant women who consumed 5 and above out of ten food groups coded as 1 and while unmeet minimum dietary diversity for those who consume less than 5 out of ten food groups in the past 24 h coded as 0. Descriptive analysis was done to calculate the mean, frequencies, and percentage distributions for the variables. A stepwise backward elimination logistic regression was done to identify variables associated with minimum dietary diversity. The model fitness was checked by using Hosmer and Lemeshow statistic (P = 0.47), which showed the model was fitted. Bivariate logistic regression was done to identify the covariate associated with minimum dietary diversity and independents variables and the variables with a p-value less than 0.05 were considered for multivariable logistic regression to control all possible confounders and to determine the strength of association between minimum dietary diversity and each explanatory variable. The strength of association was measured with an adjusted odds ratio (AOR) with a 95% CI. Finally, the variables with a P-value less than 0.05 were considered statistically significant.

Matériaux

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 mobile applications that provide pregnant women with information and reminders about proper nutrition during pregnancy. These apps can also track dietary diversity and provide personalized recommendations.

2. Telemedicine Services: Implement telemedicine services to allow pregnant women in remote areas to access antenatal care and receive guidance on proper nutrition. This can be done through video consultations with healthcare providers.

3. Community Health Workers: Train and deploy community health workers to educate pregnant women about the importance of dietary diversity and provide counseling on nutrition. These workers can also conduct home visits to monitor the dietary habits of pregnant women and provide support.

4. Nutrition Education Programs: Establish nutrition education programs specifically targeted at pregnant women. These programs can include workshops, group sessions, and educational materials that emphasize the importance of a diverse and balanced diet during pregnancy.

5. Partnerships with Local Food Suppliers: Collaborate with local food suppliers to ensure the availability and affordability of diverse and nutritious food options for pregnant women. This can involve promoting the production and distribution of locally sourced fruits, vegetables, and other food groups.

6. Maternal Health Mobile Clinics: Set up mobile clinics that travel to remote areas to provide antenatal care services, including nutrition counseling and support. These clinics can also offer screenings for nutritional deficiencies and provide appropriate supplements.

7. Financial Incentives: Introduce financial incentives, such as vouchers or subsidies, to encourage pregnant women to prioritize dietary diversity. This can help offset the cost of purchasing a variety of foods and make them more accessible.

8. Public Awareness Campaigns: Launch public awareness campaigns to educate the general population about the importance of maternal nutrition and the potential risks associated with inadequate dietary diversity. These campaigns can use various media channels to reach a wide audience.

9. Integration of Maternal Health Services: Ensure that maternal health services, including nutrition counseling, are integrated into existing healthcare systems. This can help streamline access to care and ensure that pregnant women receive comprehensive support.

10. Research and Data Collection: Conduct further research to better understand the barriers to dietary diversity among pregnant women and identify effective strategies for improvement. Collecting data on dietary habits and outcomes can help inform future interventions and policies.

AI Innovations Description

Based on the study titled “Maternal minimum dietary diversity and associated factors among pregnant women, Southwest Ethiopia, 2021,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Provide nutrition education and counseling services: Implementing nutrition education programs that specifically target pregnant women can help increase their awareness and knowledge about the importance of dietary diversity during pregnancy. This can be done through antenatal care clinics, community health centers, and mobile health units.

2. Develop culturally appropriate dietary guidelines: Create guidelines that are tailored to the local context and cultural preferences of pregnant women in Southwest Ethiopia. These guidelines should emphasize the importance of consuming a variety of food groups to ensure adequate nutrient intake during pregnancy.

3. Strengthen antenatal care services: Enhance the quality and accessibility of antenatal care services in Southwest Ethiopia. This can include improving the availability of trained healthcare professionals, ensuring the availability of essential medicines and supplements, and promoting regular antenatal care visits.

4. Engage husbands and family members: Involve husbands and other family members in promoting maternal dietary diversity. Educate them about the importance of supporting pregnant women in making healthy food choices and encourage their active involvement in meal planning and preparation.

5. Improve food security: Address underlying factors that contribute to food insecurity among pregnant women, such as poverty and limited access to nutritious foods. This can be achieved through initiatives that promote income generation, agricultural development, and improved access to markets.

6. Utilize technology for behavior change: Explore the use of mobile applications, SMS reminders, and other digital platforms to deliver personalized nutrition messages and reminders to pregnant women. This can help reinforce positive dietary behaviors and provide ongoing support throughout pregnancy.

By implementing these recommendations, it is expected that access to maternal health will be improved, leading to better maternal and fetal outcomes in Southwest Ethiopia.

AI Innovations Methodology

Based on the study “Maternal minimum dietary diversity and associated factors among pregnant women, Southwest Ethiopia, 2021,” here are some potential recommendations to improve access to maternal health:

1. Nutrition Education and Counseling: Provide comprehensive nutrition education and counseling services to pregnant women attending antenatal care. This can include information on the importance of dietary diversity during pregnancy, specific food groups to consume, meal planning, and healthy cooking techniques.

2. Community Outreach Programs: Implement community-based programs that focus on raising awareness about maternal health and nutrition. These programs can involve community health workers who visit households to provide education, support, and resources to pregnant women and their families.

3. Mobile Health (mHealth) Interventions: Utilize mobile technology to deliver health information and reminders to pregnant women. This can include text messages or mobile applications that provide tips on nutrition, reminders for antenatal care visits, and access to virtual support groups.

4. Collaboration with Local Farmers and Markets: Foster partnerships with local farmers and markets to increase the availability and affordability of diverse and nutritious food options. This can involve initiatives such as farmers’ markets, community gardens, and subsidized programs for pregnant women to access fresh produce.

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

1. Baseline Data Collection: Collect data on the current status of maternal dietary diversity and associated factors among pregnant women in the target population. This can be done through surveys, interviews, and medical records review.

2. Intervention Implementation: Implement the recommended interventions, such as nutrition education and counseling, community outreach programs, mHealth interventions, and collaborations with local farmers and markets. Ensure that these interventions are tailored to the specific needs and context of the target population.

3. Monitoring and Evaluation: Continuously monitor the implementation of the interventions and collect data on their reach and effectiveness. This can involve tracking the number of pregnant women reached by the interventions, changes in knowledge and behavior related to dietary diversity, and feedback from participants.

4. Data Analysis: Analyze the collected data to assess the impact of the interventions on improving access to maternal health. This can include comparing pre- and post-intervention data, conducting statistical analyses to determine the significance of any observed changes, and identifying any factors that may have influenced the outcomes.

5. Recommendations and Scaling Up: Based on the findings of the data analysis, make recommendations for further improvements and scaling up of the interventions. This can involve refining the interventions based on lessons learned, expanding their reach to a larger population, and advocating for policy changes to support sustainable improvements in maternal health access.

It is important to note that the specific methodology for simulating the impact of these recommendations may vary depending on the resources available, the target population, and the local context.

Auteur

Dima Health

Statistics:

Citations: 2

Identifiers:

DOI: 10.1186/s40795-021-00474-8

Research Areas:

Disparities, Environmental, Food Security, 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, Cohort Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female

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