Undernutrition and Associated Factors Among Children Aged 6–23 Months in Dessie Town, Northeastern Ethiopia, 2021: A Community Based Cross-Sectional Study

Frontiers in Pediatrics, Volume 10, Year 2022

Interpretation

Background: Globally about 159, 101, and 52 million children are stunted, underweight, and wasted, respectively. According to the 2016 Ethiopian Demographic and Health Survey, about 38% of Ethiopian children are stunted and 46, 28.4, and 9.8% of children in Amhara Region are stunted, underweight and wasted, respectively. This study aimed to assess undernutrition and associated factors among children aged 6-23 months old at Dessie town, 2021. Method: A community-based cross-sectional study was conducted from October – November 2021 in Dessie Town. A total of 421 Mothers/caregivers with children aged 6-23 months old were selected by a systematic sampling method from the health extension registration book. Epi-data 3.01 was used for data entry, SPSS version 20 for statistical analysis, and WHO Anthro version 3.2.2 software for calculating the z scores. Binary logistic regression and multivariate logistic regression were used to analyze the data. AOR with 95% CI and P-values less than 0.05 were considered to see the statistical significance. Results: A total of 421 mothers or care givers paired with 6-23 months old children participated in the study. The prevalence of stunting, underweight, wasting were 36.8% (95% CI: 32%, 41.6%), 27.6% (95% CI: 23.6%, 32.2%), and 11.5% (95% CI: 8.4%, 14.7%) respectively. Sex of the child (AOR = 1.55; 95% CI: 1.02, 2.34), handwashing practice (AOR = 2.32; 95% CI: 1.05, 5.11) and maternal family planning use (AOR = 0.39; 95% CI: 0.19, 0.77) were significantly associated with stunting. Age of child 12-17 months (AOR = 4.62; 95% CI: 2.65, 8.06) and sex of the child (AOR = 1.93; 95% CI: 1.21, 3.07) were associated with underweight. Age of child 12-17 months (AOR = 2.25; 95% CI: 1.06, 4.78) and treatment of drinking water (AOR = 0.21; 95% CI: 0.07, 0.59) were associated with wasting. Conclusion and Recommendation: In this study, the prevalence of undernutrition among children aged 6-23 months was higher for stunting (36.8%), underweight (27.6%) and wasting (11.5%) compared to WHO classification. Improved access to water, hygiene and sanitation, family planning services, avoiding gender discrimination during child feeding, and age-appropriate feeding practices are recommended. Moreover, implementation of public policies on food and nutrition is required for children 6-23 months of age. This study was conducted in the Dessie Town administration. There are two governmental and three private hospitals in Dessie town. Based on the 2007 national census conducted by the Central Statistical Agency of Ethiopia (CSA), Dessie town has a total population of 151,174, of whom 72,932 are men and 78,242 are women. A total of 2,924 children 6-23 months of age live in Dessie Town, and 770 children 6-23 months of age live in the selected three sub cities. The study was conducted from October – November 2021. Community-based cross-sectional study design was conducted. The source population the source population was all mothers/caregivers with a child aged 6-23 months who resided in Dessie Town. The study population was all children aged 6-23 months who resided in the selected sub cities during the study period. In this study, all children aged 6-23 months living in the selected sub cities were included, and mothers/caregivers with communication barriers or mental problems and children with physical deformities were excluded. The sample size was calculated using Epi Info version 7.2 statistical software and by considering the following assumption. Based on findings from the EDHS 2016 report, the prevalence of stunting, wasting, and underweight in Amhara Regions was 46, 9.8, and 28.4%, respectively (7). Therefore, the total sample sizes were calculated with a margin of error of 0.05, 95% confidence level, and 10% non-response. Finally, 421 children 6-23 months of age were taken from the study area. A multistage sampling method was used for this study. The sampled sub city was selected by using the lottery method from the 10 sub cities, and lists of under-five children were obtained from the sub city responsible person (Health extension worker housing registration). The sampling technique was a systematic random sampling technique. The total samples were proportionally allocated for the three sub cities, and the allocated sample size was selected by a systematic random sampling technique and determination of the K value, K = 770/421 = 1.8 (approximately = 2). The first subject was selected by the lottery method, which was number 1. Data were collected through interviewer-administered structured questionnaires and anthropometric tools. The data were collected by three diploma health extension workers working in the respective kebele (a total of three supervisors and nine data collectors were recruited from the three kebeles), and target children were selected using systematic random sampling from the document. This document was used to find their home/residence address. Finally, after obtaining the target children by using a structured questionnaire, caregivers/mothers were interviewed, and the length and weight of the child were measured. The date of birth was obtained from EPI cards and cross-check with neighbors. Children wore similar clothes and without shoes while measuring weight. During length measurement, children were in a recumbent position and Frankfurt plane 90 degrees in length. To measure weight, a medically acceptable weight scale (Digital SECA, made in Germany, model 874 1021659, serial number 5874269114011, graduation of 0.1 kg and measuring up to 150 kg) was used. Stunting (Yes/No), Wasting (Yes/No) and Underweight (Yes/No). Socioeconomic and demographic factors (age, sex, income, educational status (mother and father), maternal and child health status (diarrhea, pneumonia, TB &HIV immunization status, F/P, ANC, PNC, others), child feeding practice (initiation of complementary feeding, breastfeeding, minimum dietary diversity, and household food security status) and WASH factors (water availability, sanitation, handwashing) were the independent variables. Dietary diversity: The number of food or food group children from 6-23 months of age consumed for 24 h in the study period/reference period (from October to November 2021). High dietary diversity: Children are 6-23 months of age who receive four or more food groups of the seven food groups (8). Low dietary diversity: Children are 6-23 months of age who receive fewer than four food groups of the seven food groups (8). Minimum dietary diversity: Children 6–23 months of age who receive foods from 4 or more food groups from the seven during the study period (from October to November 2021) (8). Caregiver: A person who provides direct care for children (parents or other caregivers). Stunting: Height -for- age <−2 standard deviations (SDs) from the median of the WHO reference population (9). Wasting: Weight-for-height <−2 SD from the median of the WHO reference population (9). Underweight: Weight-for-age <−2 SD from the median of the WHO reference population (9). Food security: Assessed by nine food insecurity questions that hold the occurrence of food insecurity in the previous month (0 – 3 = secure, >3 = insecure) (10). Kebele: A “Kebele” is a small administrative unit that comprises up to 5,000 households (11). Food and Nutrition Technical Assistant (FANTA) tool for dietary diversity questions based on 24 recall periods from mother or child caregivers who are responsible for food preparation. The questionnaires have a minimum score of 0-7 (0-3 = low Dietary Diversity Score (DDS), 4-5 = medium DDS, 6-7 = high DDS). Though, Food and Nutrition Technical Assistant (FANTA) tool for dietary diversity classified in to three categories, previous studies conducted here in Ethiopia used the high and low dietary diversity classifications. It is because the medium category was not applicable for intervention here in our country, Ethiopia. Based on this reason, we all the authors modified this tool in to two categories as high (>4 food groups) and low dietary diversity (<4 food groups) (Reference no. 8). The Household Food Insecurity Access Scale (HFIAS) was used to assess the household food security status of households. Food security status was categorized into food security if the score was 0-3 and insecure if the score was greater than three. A weight scale (digital SECA, made in Germany, model 8741021659, serial number 5874269114011 and Graduation of 0.1 kg and measuring up to 150 kg and capable of reading to the nearest 0.1 kg) was used to measure the weight of the child. A horizontal wooden length board was used to measure the length in a recumbent position, which was read to the nearest 0.1 cm. Weight and length measurements were made three times, and then the average was computed. All completed questionnaires and weight measuring instruments were checked and calibrated daily (calibration was performed before weighing every child by setting it to zero and checking by putting a 1 kg iron rod before taking children’s weight) and regularly supervised on a daily basis by trained supervisors, and each questionnaire was checked for its completeness, accuracy, and consistency by the primary investigator. To ensure data quality, the recruited data collectors and supervisors were trained for two successive days. The questionnaire was developed in English and translated and adopted into locally acceptable “Amharic” and translated back to English to ensure consistency in the asking of questions by the interviewers. A pre-test was carried out on 10% of the actual sample size in another kebele to determine the acceptability of the question to be asked, appropriateness of the methods, reaction, and willingness of the respondents. To analyze the data, the dietary diversity score was determined by asking the food groups they ate within 24-h periods during the data collection period. Each food group has one mark, and the total food groups were scored from seven. Data processing and analysis were employed by the appropriate software Epi-data version 3.01 software for data entry. After the completion of data entry, recorded data were exported to SPSS version 20 for data analysis, and nutrition-related data (sex, age, height, and weight) were transferred to WHO Anthro version 3.2.2 to determine stunting, wasting, and underweight. All the findings are described in detail and summarized in percentages, mean + = SD, tables, and graphs, and for each outcome variable, binary logistic regression was performed. Binary logistic regression was used to indicate the gross association between each independent variable and the outcome variable. Then, those candidate variables that were filtered from the binary logistic regression (P value < 0.2) were moved to multivariable logistic regression, and adjusted odds ratios with 95% confidence intervals were reported, so the level of statistical significance was considered at a p value of <0.05 from the final model. Ethical clearance was obtained from Wollo University College of Medicine and Health Sciences ethical review committee and a written letter was given to the selected sub-cities. All the study participants were informed about the purpose of the study and assured confidentiality of the responses. Written consent was obtained from each participant. There are no known risks to a participant who takes part in this study. Accountability, confidentiality, neutrality, and academic honesty were maintained throughout the study.

AI Digest

Study Justification:

This study aimed to assess the prevalence of undernutrition and associated factors among children aged 6-23 months in Dessie Town, Northeastern Ethiopia. The justification for this study is based on the high prevalence of undernutrition globally and in Ethiopia, particularly in the Amhara Region. Understanding the factors contributing to undernutrition in this specific population can help inform interventions and policies to improve child health and nutrition.

Highlights:

– The prevalence of stunting, underweight, and wasting among children aged 6-23 months in Dessie Town was found to be 36.8%, 27.6%, and 11.5% respectively.
– Factors significantly associated with stunting included the sex of the child, handwashing practice, and maternal family planning use.
– Factors significantly associated with underweight included the age and sex of the child.
– Factors significantly associated with wasting included the age of the child and treatment of drinking water.
– The study highlights the need for improved access to water, hygiene and sanitation, family planning services, gender equality in child feeding practices, and age-appropriate feeding practices.

Recommendations:

– Improve access to water, hygiene, and sanitation facilities in Dessie Town to reduce the risk of undernutrition.
– Strengthen family planning services to ensure that mothers can adequately space their pregnancies and provide optimal care for their children.
– Promote gender equality in child feeding practices to ensure that both boys and girls receive adequate nutrition.
– Implement age-appropriate feeding practices to meet the nutritional needs of children aged 6-23 months.
– Develop and implement public policies on food and nutrition specifically targeting children aged 6-23 months.

Key Role Players:

– Local government authorities in Dessie Town
– Health extension workers
– Health facilities (governmental and private hospitals)
– Non-governmental organizations working in nutrition and child health
– Community leaders and volunteers

Cost Items for Planning Recommendations:

– Infrastructure development for improved water, hygiene, and sanitation facilities
– Training and capacity building for health extension workers and other healthcare providers
– Outreach programs and awareness campaigns on family planning and gender equality in child feeding practices
– Development and dissemination of educational materials on age-appropriate feeding practices
– Monitoring and evaluation of the implementation of public policies on food and nutrition
Please note that the cost items provided are general suggestions and may vary based on the specific context and resources available in Dessie Town.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a community-based cross-sectional study conducted in Dessie Town, Northeastern Ethiopia. The study provides prevalence rates of stunting, underweight, and wasting among children aged 6-23 months, as well as associated factors. The study design and statistical analysis methods are mentioned, which adds to the strength of the evidence. However, the abstract lacks information on the sampling technique used, response rate, and potential limitations of the study. To improve the evidence, it would be helpful to include these details and discuss any potential biases or limitations in the study design and data collection process.

Abstract

This study was conducted in the Dessie Town administration. There are two governmental and three private hospitals in Dessie town. Based on the 2007 national census conducted by the Central Statistical Agency of Ethiopia (CSA), Dessie town has a total population of 151,174, of whom 72,932 are men and 78,242 are women. A total of 2,924 children 6-23 months of age live in Dessie Town, and 770 children 6-23 months of age live in the selected three sub cities. The study was conducted from October – November 2021. Community-based cross-sectional study design was conducted. The source population the source population was all mothers/caregivers with a child aged 6-23 months who resided in Dessie Town. The study population was all children aged 6-23 months who resided in the selected sub cities during the study period. In this study, all children aged 6-23 months living in the selected sub cities were included, and mothers/caregivers with communication barriers or mental problems and children with physical deformities were excluded. The sample size was calculated using Epi Info version 7.2 statistical software and by considering the following assumption. Based on findings from the EDHS 2016 report, the prevalence of stunting, wasting, and underweight in Amhara Regions was 46, 9.8, and 28.4%, respectively (7). Therefore, the total sample sizes were calculated with a margin of error of 0.05, 95% confidence level, and 10% non-response. Finally, 421 children 6-23 months of age were taken from the study area. A multistage sampling method was used for this study. The sampled sub city was selected by using the lottery method from the 10 sub cities, and lists of under-five children were obtained from the sub city responsible person (Health extension worker housing registration). The sampling technique was a systematic random sampling technique. The total samples were proportionally allocated for the three sub cities, and the allocated sample size was selected by a systematic random sampling technique and determination of the K value, K = 770/421 = 1.8 (approximately = 2). The first subject was selected by the lottery method, which was number 1. Data were collected through interviewer-administered structured questionnaires and anthropometric tools. The data were collected by three diploma health extension workers working in the respective kebele (a total of three supervisors and nine data collectors were recruited from the three kebeles), and target children were selected using systematic random sampling from the document. This document was used to find their home/residence address. Finally, after obtaining the target children by using a structured questionnaire, caregivers/mothers were interviewed, and the length and weight of the child were measured. The date of birth was obtained from EPI cards and cross-check with neighbors. Children wore similar clothes and without shoes while measuring weight. During length measurement, children were in a recumbent position and Frankfurt plane 90 degrees in length. To measure weight, a medically acceptable weight scale (Digital SECA, made in Germany, model 874 1021659, serial number 5874269114011, graduation of 0.1 kg and measuring up to 150 kg) was used. Stunting (Yes/No), Wasting (Yes/No) and Underweight (Yes/No). Socioeconomic and demographic factors (age, sex, income, educational status (mother and father), maternal and child health status (diarrhea, pneumonia, TB &HIV immunization status, F/P, ANC, PNC, others), child feeding practice (initiation of complementary feeding, breastfeeding, minimum dietary diversity, and household food security status) and WASH factors (water availability, sanitation, handwashing) were the independent variables. Dietary diversity: The number of food or food group children from 6-23 months of age consumed for 24 h in the study period/reference period (from October to November 2021). High dietary diversity: Children are 6-23 months of age who receive four or more food groups of the seven food groups (8). Low dietary diversity: Children are 6-23 months of age who receive fewer than four food groups of the seven food groups (8). Minimum dietary diversity: Children 6–23 months of age who receive foods from 4 or more food groups from the seven during the study period (from October to November 2021) (8). Caregiver: A person who provides direct care for children (parents or other caregivers). Stunting: Height -for- age <−2 standard deviations (SDs) from the median of the WHO reference population (9). Wasting: Weight-for-height <−2 SD from the median of the WHO reference population (9). Underweight: Weight-for-age 3 = insecure) (10). Kebele: A “Kebele” is a small administrative unit that comprises up to 5,000 households (11). Food and Nutrition Technical Assistant (FANTA) tool for dietary diversity questions based on 24 recall periods from mother or child caregivers who are responsible for food preparation. The questionnaires have a minimum score of 0-7 (0-3 = low Dietary Diversity Score (DDS), 4-5 = medium DDS, 6-7 = high DDS). Though, Food and Nutrition Technical Assistant (FANTA) tool for dietary diversity classified in to three categories, previous studies conducted here in Ethiopia used the high and low dietary diversity classifications. It is because the medium category was not applicable for intervention here in our country, Ethiopia. Based on this reason, we all the authors modified this tool in to two categories as high (>4 food groups) and low dietary diversity (<4 food groups) (Reference no. 8). The Household Food Insecurity Access Scale (HFIAS) was used to assess the household food security status of households. Food security status was categorized into food security if the score was 0-3 and insecure if the score was greater than three. A weight scale (digital SECA, made in Germany, model 8741021659, serial number 5874269114011 and Graduation of 0.1 kg and measuring up to 150 kg and capable of reading to the nearest 0.1 kg) was used to measure the weight of the child. A horizontal wooden length board was used to measure the length in a recumbent position, which was read to the nearest 0.1 cm. Weight and length measurements were made three times, and then the average was computed. All completed questionnaires and weight measuring instruments were checked and calibrated daily (calibration was performed before weighing every child by setting it to zero and checking by putting a 1 kg iron rod before taking children’s weight) and regularly supervised on a daily basis by trained supervisors, and each questionnaire was checked for its completeness, accuracy, and consistency by the primary investigator. To ensure data quality, the recruited data collectors and supervisors were trained for two successive days. The questionnaire was developed in English and translated and adopted into locally acceptable “Amharic” and translated back to English to ensure consistency in the asking of questions by the interviewers. A pre-test was carried out on 10% of the actual sample size in another kebele to determine the acceptability of the question to be asked, appropriateness of the methods, reaction, and willingness of the respondents. To analyze the data, the dietary diversity score was determined by asking the food groups they ate within 24-h periods during the data collection period. Each food group has one mark, and the total food groups were scored from seven. Data processing and analysis were employed by the appropriate software Epi-data version 3.01 software for data entry. After the completion of data entry, recorded data were exported to SPSS version 20 for data analysis, and nutrition-related data (sex, age, height, and weight) were transferred to WHO Anthro version 3.2.2 to determine stunting, wasting, and underweight. All the findings are described in detail and summarized in percentages, mean + = SD, tables, and graphs, and for each outcome variable, binary logistic regression was performed. Binary logistic regression was used to indicate the gross association between each independent variable and the outcome variable. Then, those candidate variables that were filtered from the binary logistic regression (P value < 0.2) were moved to multivariable logistic regression, and adjusted odds ratios with 95% confidence intervals were reported, so the level of statistical significance was considered at a p value of <0.05 from the final model. Ethical clearance was obtained from Wollo University College of Medicine and Health Sciences ethical review committee and a written letter was given to the selected sub-cities. All the study participants were informed about the purpose of the study and assured confidentiality of the responses. Written consent was obtained from each participant. There are no known risks to a participant who takes part in this study. Accountability, confidentiality, neutrality, and academic honesty were maintained throughout the study.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Solutions: Develop mobile applications or text messaging services that provide pregnant women and new mothers with important health information, reminders for prenatal and postnatal care visits, and access to teleconsultations with healthcare providers.

2. Telemedicine: Implement telemedicine programs that allow pregnant women in remote or underserved areas to consult with healthcare professionals through video calls or phone calls, reducing the need for travel and improving access to medical advice.

3. Community Health Workers: Train and deploy community health workers who can provide maternal health education, conduct regular check-ups, and refer pregnant women to healthcare facilities for specialized care when needed.

4. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with financial assistance to cover the costs of prenatal care, delivery, and postnatal care, ensuring that cost is not a barrier to accessing essential maternal health services.

5. Transport Solutions: Establish transportation systems or partnerships with transportation providers to ensure that pregnant women have access to safe and reliable transportation to healthcare facilities for prenatal visits, delivery, and emergency obstetric care.

6. Maternal Waiting Homes: Set up maternal waiting homes near healthcare facilities, where pregnant women from remote areas can stay during the final weeks of pregnancy to ensure timely access to skilled birth attendants and emergency obstetric care.

7. Health Education and Awareness Campaigns: Conduct targeted health education campaigns to raise awareness about the importance of prenatal care, nutrition, hygiene, and family planning, empowering women and their families to make informed decisions regarding maternal health.

8. Integration of Services: Improve coordination and integration of maternal health services with other healthcare services, such as family planning, immunization, and HIV/AIDS prevention and treatment, to provide comprehensive care for women and their children.

9. Quality Improvement Initiatives: Implement quality improvement initiatives in healthcare facilities to ensure that maternal health services are provided in a safe, respectful, and effective manner, addressing any gaps or deficiencies in the delivery of care.

10. Policy and Advocacy: Advocate for policies and investments that prioritize maternal health, including increased funding for maternal health programs, improved infrastructure, and training for healthcare providers.

These innovations can help address the challenges identified in the study and improve access to maternal health services in Dessie Town and similar settings.

AI Innovations Description

The study conducted in Dessie Town, Northeastern Ethiopia, aimed to assess undernutrition and associated factors among children aged 6-23 months. The prevalence of stunting, underweight, and wasting among the children was found to be 36.8%, 27.6%, and 11.5% respectively, which is higher than the WHO classification.

Based on the findings, the following recommendations were made to improve access to maternal health and address undernutrition:

1. Improved access to water, hygiene, and sanitation: Ensuring access to clean and safe water, promoting proper handwashing practices, and improving sanitation facilities can help prevent infections and reduce the risk of undernutrition.

2. Family planning services: Promoting the use of family planning methods can help in spacing pregnancies and ensuring adequate time for maternal recovery between pregnancies. This can contribute to better maternal health and nutrition, which in turn can positively impact child nutrition.

3. Avoiding gender discrimination during child feeding: Promoting gender equality and ensuring that both male and female children receive equal attention and care during feeding can help prevent undernutrition.

4. Age-appropriate feeding practices: Providing age-appropriate and diverse foods to children aged 6-23 months can help meet their nutritional needs and prevent undernutrition. Promoting minimum dietary diversity and ensuring access to a variety of nutritious foods can be beneficial.

5. Implementation of public policies on food and nutrition: Developing and implementing public policies that prioritize food and nutrition for children aged 6-23 months can help address undernutrition. This can include interventions such as promoting breastfeeding, improving access to nutritious foods, and addressing food insecurity.

By implementing these recommendations, it is expected that access to maternal health will be improved, leading to better nutrition outcomes for children aged 6-23 months in Dessie Town, Northeastern Ethiopia.

AI Innovations Methodology

Based on the information provided, here are some potential recommendations for improving access to maternal health:

1. Strengthen water, hygiene, and sanitation (WASH) infrastructure: Improve access to clean water, sanitation facilities, and promote proper hygiene practices in the community. This can help reduce the risk of waterborne diseases and improve overall maternal and child health.

2. Increase availability and accessibility of family planning services: Ensure that family planning services are readily available and accessible to women in the community. This can help prevent unintended pregnancies and enable women to space their pregnancies, leading to better maternal and child health outcomes.

3. Promote gender equality and empowerment: Address gender discrimination and promote women’s empowerment in decision-making processes, including child feeding practices. This can help ensure that women have the resources and support they need to provide adequate nutrition to their children.

4. Implement age-appropriate feeding practices: Promote and educate caregivers on age-appropriate feeding practices for children aged 6-23 months. This can include promoting exclusive breastfeeding for the first six months, introducing complementary foods at the appropriate time, and ensuring a diverse and nutritious diet for young children.

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

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the percentage of women receiving prenatal care, the percentage of women delivering in a healthcare facility, or the percentage of women using modern contraceptives.

2. Collect baseline data: Gather data on the current status of the selected indicators in the target population. This can be done through surveys, interviews, or existing data sources.

3. Define the intervention: Clearly define the interventions being considered, such as improving WASH infrastructure, increasing availability of family planning services, promoting gender equality, and implementing age-appropriate feeding practices.

4. Simulate the impact: Use statistical modeling or simulation techniques to estimate the potential impact of the interventions on the selected indicators. This can involve comparing the baseline data with projected data after implementing the interventions.

5. Analyze the results: Evaluate the simulated impact of the interventions on access to maternal health. Assess the changes in the selected indicators and determine the effectiveness of the recommendations in improving access to maternal health.

6. Refine and adjust: Based on the results, refine the interventions and adjust the simulation model if necessary. This iterative process can help optimize the recommendations and improve their potential impact on access to maternal health.

It is important to note that the methodology for simulating the impact may vary depending on the specific context and available data. Consulting with experts in the field and utilizing appropriate statistical methods can help ensure the accuracy and reliability of the simulation results.

Author

Dima Health

Statistics:

Citations: 1

Identifiers:

DOI: 10.3389/fped.2022.916726

Research Areas:

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

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study, Grounded Theory, randomised-control-trial

Study Approach:

Quantitative

Participants Gender:

Male & Female