Undernutrition and associated factors among urban children aged 24-59 months in Northwest Ethiopia: A community based cross sectional study

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Study Justification:
– Globally, one in every three preschool children is affected by malnutrition.
– Child undernutrition is a serious public health problem in Ethiopia.
– Data on undernutrition in children aged 24-59 months in Ethiopia are scarce.
– This study aimed to estimate undernutrition and identify associated factors in Aykel Town, Northwest Ethiopia.
Highlights:
– The study found that the prevalence of stunting, wasting, and underweight among children aged 24-59 months in Aykel Town was 28.4%, 10%, and 13.5% respectively.
– Factors associated with stunting included low birth order, large family size, and low meal frequency.
– Factors associated with wasting included not feeding on cow milk and poor maternal hand washing practice.
– Factors associated with underweight included not feeding on cow milk, breastfeeding for less than 24 months, consuming foods from less than four food groups, and poor maternal hand washing practice.
Recommendations:
– Educating mothers/caregivers on the importance of proper child feeding practices and maintaining hygienic practices at critical times.
– Implementing interventions to improve meal frequency and dietary diversity among children.
– Promoting the consumption of cow milk and breastfeeding for at least 24 months.
– Providing support and resources to improve maternal hand washing practices.
Key Role Players:
– Health Extension Workers
– Community Health Workers
– Local Government Officials
– Non-Governmental Organizations (NGOs)
– Health Care Providers
– Nutritionists/Dieticians
Cost Items for Planning Recommendations:
– Training materials and workshops for health workers and caregivers
– Educational materials for mothers/caregivers
– Cow milk supply and distribution
– Support for breastfeeding initiatives
– Promotion of local food production and dietary diversity
– Hygiene promotion materials and campaigns
– Monitoring and evaluation activities to assess the impact of interventions

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides specific details about the study design, sample size, data collection methods, and statistical analysis. However, it does not mention the specific measures taken to ensure the quality of data, such as inter-rater reliability or data validation procedures. To improve the evidence, the abstract could include information on the reliability and validity of the measurement tools used, as well as any steps taken to minimize bias in data collection. Additionally, it would be helpful to include information on the response rate and any potential limitations of the study.

Background: Globally, in every three preschool children one is affected by malnutrition. In Ethiopia, child undernutrition continues to be a serious public health problem. Data are scarce, especially in 24-59 months age children. We aimed at estimating under nutrition and its associated factors among children 24-59 months age in Aykel Town, Northwest Ethiopia. Methods: A community based cross-sectional study was conducted among children aged 24-59 months in Aykel Town from January to February 2017. A total of 416 children were included in to the study using a systematic random sampling technique. Data were collected by interview and anthropometric measurements. Multivariable analysis was performed to identify the predictors of stunting, wasting and underweight. Results: The prevalence of stunting, wasting and underweight were 28.4, 10 and 13.5%, respectively. Children from low birth order; 1st (AOR = 8.60, 95%CI: 2.40, 3.70) and 2nd -4th (AOR = 5.80, 95%CI: 1.80, 18.90), from large family size (AOR = 3.67, 95%CI: 1.92, 7.00), and had meal frequency < 3/day (AOR = 5.09, 95%CI: 2.96, 8.74) were at a higher risk of stunting. Children who had not fed on cow milk (AOR = 5.50, 95%CI: 2.30, 13.00), and from mothers who had poor hand washing practice (AOR = 11.00, 95%CI: 4.30, 27.9) were more likely to be wasted. Children who had not fed on cow milk (AOR = 2.90, 95%CI: 1.40, 6.00), breast fed for less than 24 months (AOR = 2.60, 95%CI: 1.35, 5.00), consumed foods from less than four food groups (AOR = 6.30, 95%CI: 1.70, 23.00), and were from mothers' who had poor hand washing practice (AOR = 2.50, 95%CI: 1.30, 4.70) had higher odds of being underweight. Conclusion: Stunting, wasting and underweight are high among children aged 24-59 months in Aykel Town. Poor child feeding and maternal hygienic practices were identified as risk factors of undernutrition. Educating mothers/care givers on the advantages of proper child feeding and maintaining hygienic practices at critical times is valuable in improving the nutritional status of children.

A community based cross-sectional study was conducted among children aged between 24 and 59 months in Aykel Town from January to February 2017. Aykel Town is located in Chilga district, Northwest Ethiopia about 780 km away from the capital city of Ethiopia, Addis Ababa. There are two kebeles (the smallest administrative unit in Ethiopia) in the Town and each kebele has four villages. The Town has one hospital, one health center and two urban health posts. It has a total of 4246 households and total population of 30,201 among which 16,498 (54.6%) are females. Of the total population, 1768 (6%) are preschool children. The people in this area are engaged in different activities such as farming, trade, civil servant, carpentering, and construction. They also produce cereals, legumes and spices and root crops, and keep animals, including goats, sheep and cattle [14]. All children aged 24–59 months with their mothers/caregivers in Aykel Town were the study population. All randomly selected children aged 24–59 months with their mothers/caregivers who lived in the Town for at least 6 months were included in to the study. Children who were seriously ill, with diarrhoea and /or malaria, and whose mothers’/care givers were unable to communicate were excluded from the study. The minimum sample size was determined by using single population proportion formula. The prevalence of undernutrition in the specific age group (24–59 months) was used to calculate the sample size. The prevalence of stunting, wasting and underweight were 57, 16 and 25%, respectively [15]. Considering 95% confidence interval and 5% margin of error, the largest sample size was taken after sample size was calculated for the three indicators of under nutrition. The prevalence of stunting provided the largest sample size. Finally, a sample size of 416 was obtained after considering a 10% non-response rate. Regarding the sampling procedure, both kebeles of the Aykel Town were included in the study. There were 4246 households in the two kebeles. The total number of households (1768) with children aged 24–59 months was obtained from the Health Extension Workers housing registration. Then households were sampled from each kebele based on proportional allocation. Finally, a systematic random sampling technique was used to select households with eligible children. The first household was selected by lottery method from the first four households by spinning a pen at the center of the Town. Where impossible to get preschool aged children, the next house was considered for the study. When there were more two or more children in the household, one of them was selected by lottery method. Interviewer-administered questionnaire was used to collect data on socio-demographic and other relevant child and mothers/caregivers related information. To maintain its consistency, the questionnaire was first prepared in English and translated into Amharic, the local language of the study area, and then back translated to English. Six data collectors and two supervisors were involved in the data collection process. Two days training has been given for both data collectors and supervisors on areas related to anthropometric measurements and interview techniques. The questionnaire was pre-tested on 5% of the total sample size outside of Aykel Town. Based on the results of the pre-test, the acceptability and applicability of the procedures and tools were assessed. Necessary revisions were made on the questionnaire. Early initiation of breastfeeding: Children who received breast milk within 1 h of birth [16] Exclusive breastfeeding: Children who received breast milk exclusively up to 6th months of life [16]. Continued breastfeeding at 1 year: Children 12–15 months of age who continued breast feeding after the age 1 year [16] Introduction of solid, semi-solid or soft foods: Children who received solid, semi-solid or soft foods during the age of 6–8 months [16] Minimum dietary diversity: Children 6–23 months of age who received foods from 4 or more food groups in the past 24 h [16] Minimum meal frequency: Children from 6 to 23 months of age who received solid, semi-solid, or soft foods (including milk feeds for non-breastfed children) for at least three times per day in the past 24 h [16] Continued breastfeeding at 2 years: Children 20–23 months of age who continued breast feeding after his/her 23 months of age [16] Duration of breastfeeding: Median duration of breastfeeding among children less than 36 months of age [16] Under-nutrition: Refers to a state/condition/ resulting from deficiency of one or more essential nutrients and manifested by stunting, wasting and underweight [17] Stunting: Wasting: Underweight: Refer to a low height for age, weight for height and weight for age, respectively. The child was classified as stunted, wasted and underweight if his/her z score was less than −2SD; otherwise, he/she was considered as well-nourished (≥ − 2 Z score), based on international median of WHO reference value, taking sex into consideration [17]. Weight was measured with light cloths and no shoes by using beam balance in kilogram to the nearest of 0.1 kg. A vertical measuring board was used to measure the height of children. The child stands up on the board barefooted; have hands putting loosely with feet parallel to the body, and heels, buttocks, shoulders calve and back of the head touching the board. Child’s head was held straight comfortably with the lower border of the orbit of the eye being in the same horizontal plane as the external canal of the ear. The head piece of the measuring board was then moved gently, touching the hair and making contact with the top of the head. Height was read to the nearest 0.1 cm [17]. To determine the minimum dietary diversity score (DDS) of the child, the mother was asked to list all food items consumed by the child in the previous 24 h ahead of data collection. Then, the listed food items were grouped in to seven food groups. Namely grains, roots and tubers, legumes and nuts; Dairy products (milk, yogurt, cheese); flesh foods (meat, fish, poultry and liver/organ meats); Eggs, Vitamin-A rich fruits and vegetables and Other fruits and vegetables. Considering the four food groups as the minimum acceptable dietary diversity, a child with a DDS of less than four was classified as poor dietary diversity [18]. Initiation of complementary feeding was measured as early initiation, timely initiation and lately initiation if the mother initiated complementary feeding to the index child before sixth month, at sixth month and after sixth months of age, respectively [16]. Appropriate hand washing practice is defined through 2 questions. The first question was as to when do mothers/caregivers wash their hands. The possible answers for this question were after defecation, after cleaning baby’s bottom, before food preparation, before eating, before feeding children (including breastfeeding). The second question was about how the mothers/caregivers wash their hands. The possible answers for this question were uses water, uses soap or ashes, washes both hands, rubs hands together at least three times, and dries hands hygienically by air-drying or using a clean cloth. A score of 9 points or more (out of a possible 10 points) qualifies a hand washing behavior as appropriate [19]. Wealth index of the household was constructed using household assets data via a principal component analysis to categorize the household wealth index in to lowest, middle, and highest. Household food insecurity was measured using Household Food Insecurity Access Scale (HFIAS) measurement tools of FAO-FANTA. The HFIAS consists of 9 items specific to an experience of food insecurity occurring within the previous 4 weeks. Respondents were asked whether they had encountered the items because of lack of food or money to buy food in the last month. Each item was received either 1 for occurrence or 0 for non-occurrence. The frequency scores were ranged from 0 to 3, while 0 was the score for non-occurrence, 1 for rarely (once or twice in the past 4 week), 2 for sometimes (three to ten times in the past 4 weeks), and 3 for often (more than ten times in the past month), renamed as food secure, mildly food insecure, moderately food insecure, and severely food insecure, respectively [20]. Maximum efforts were made to maintain the quality of data. The measuring equipment was calibrated using a known weight material each day. At the end of every data collection day, each questionnaire was examined for its completeness and consistency by field supervisors and investigators and pertinent feedback was given to data collectors and supervisors. Data was coded, cleaned, and entered in to Epi-Info version 3.5.3 and then exported to Statistical Package for Social Sciences (SPSS) version 20 for further analysis. Anthropometric measurements were converted into Z-sore values using WHO Anthro version 3.2.2 software for the indices; Height for- Age (HAZ), Weight-for-Height (WHZ) and Weight-for- Age (WAZ) taking sex into consideration using WHO 2006 standards. The child was classified as stunted, wasted and underweight if his/her z score was less than −2SD; otherwise, he/she was well-nourished (≥ − 2 Z score) [17]. Mean with standard deviation for continuous and proportion for categorical variables were calculated. Binary logistic regression model was used to identify factors associated with stunting, wasting and underweight. Variables which had a p-value of < 0.2 in the bivariable analysis were taken in to the multivariable analysis to control the possible effects of confounders. Adjusted odds ratio (AOR) with a 95% confidence interval (CI) was computed to assess the strength of the association. A p-value of < 0.05 was used to determine statistical significance in the multivariable analysis. The Hosmer and lemeshows goodness of fit-test was run to check the fitness of the final model for the three separate models. Ethical clearance was obtained from Ethical Review Board of University of Gondar. An official permission letter was secured from Aykel Town administration health office. Participants were involved in the study on a voluntary basis after written consent, signed or verified by fingerprint was obtained. Parents/care givers of the children were informed about the study and written consent on behalf of the children were obtained from the parents. Privacy of the participants was protected and the information was kept confidential.

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 and new mothers with information on nutrition, breastfeeding, and hygiene practices. These apps can also send reminders for prenatal and postnatal care appointments.

2. Community Health Workers: Train and deploy community health workers to provide education and support to pregnant women and new mothers in Aykel Town. These workers can conduct home visits, provide counseling on nutrition and hygiene practices, and refer women to healthcare facilities when necessary.

3. Telemedicine: Establish telemedicine services in Aykel Town to enable pregnant women and new mothers to consult with healthcare professionals remotely. This can help address barriers to accessing healthcare, such as long travel distances and limited healthcare facilities.

4. Maternal Health Vouchers: Implement a voucher system that provides pregnant women with subsidized or free access to prenatal and postnatal care services. This can help reduce financial barriers and increase utilization of maternal health services.

5. Maternal Health Education Campaigns: Conduct community-wide education campaigns to raise awareness about the importance of proper nutrition, breastfeeding, and hygiene practices during pregnancy and after childbirth. These campaigns can include workshops, seminars, and informational materials distributed in the community.

6. Maternal Health Support Groups: Establish support groups for pregnant women and new mothers in Aykel Town. These groups can provide a platform for women to share experiences, receive emotional support, and learn from each other’s experiences.

7. Improved Water and Sanitation Facilities: Invest in improving water and sanitation infrastructure in Aykel Town to ensure access to clean water and proper sanitation facilities. This can help reduce the risk of waterborne diseases and improve overall maternal and child health.

8. Maternal Health Hotline: Set up a toll-free hotline that pregnant women and new mothers can call to receive information and support related to maternal health. Trained healthcare professionals can provide guidance and answer questions over the phone.

9. Maternal Health Monitoring System: Develop a system to track the health and well-being of pregnant women and new mothers in Aykel Town. This can help identify high-risk cases and ensure timely interventions and follow-up care.

10. Collaboration with Non-Governmental Organizations (NGOs): Partner with NGOs working in the field of maternal health to leverage their expertise, resources, and networks. This collaboration can help implement and scale up innovative interventions to improve access to maternal health services in Aykel Town.
AI Innovations Description
Based on the description provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Implement community-based education programs: Develop and implement community-based education programs that focus on educating mothers and caregivers about the importance of proper child feeding practices and maintaining hygienic practices at critical times. These programs can be conducted by trained health workers or community volunteers and should provide clear and practical information on topics such as early initiation of breastfeeding, exclusive breastfeeding, introduction of complementary foods, minimum dietary diversity, and minimum meal frequency.

2. Strengthen healthcare infrastructure: Improve access to maternal health services by strengthening healthcare infrastructure in Aykel Town. This can include increasing the number of health facilities, such as hospitals, health centers, and urban health posts, and ensuring that these facilities are adequately staffed and equipped to provide quality maternal and child health services. Additionally, efforts should be made to improve transportation and communication systems to facilitate access to healthcare services for mothers and children in remote areas.

3. Enhance maternal and child nutrition programs: Implement targeted maternal and child nutrition programs that address the identified risk factors of undernutrition, such as low birth order, large family size, inadequate meal frequency, lack of cow milk consumption, and poor hand washing practices. These programs can include interventions such as providing nutritional supplements, promoting breastfeeding and appropriate complementary feeding practices, and improving access to clean water and sanitation facilities.

4. Strengthen data collection and monitoring systems: Improve data collection and monitoring systems to better understand the prevalence and determinants of undernutrition among children aged 24-59 months in Aykel Town. This can involve conducting regular surveys or assessments to collect accurate and up-to-date data on the nutritional status of children and the factors contributing to undernutrition. The data collected can then be used to inform the design and implementation of targeted interventions and to monitor the progress and impact of these interventions over time.

5. Foster collaboration and partnerships: Foster collaboration and partnerships between government agencies, non-governmental organizations, community-based organizations, and other stakeholders to collectively address the issue of undernutrition and improve access to maternal health in Aykel Town. This can involve sharing resources, expertise, and best practices, as well as coordinating efforts to ensure a comprehensive and integrated approach to addressing the underlying causes of undernutrition and improving maternal and child health outcomes.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Increase awareness and education: Implement community-based education programs to raise awareness about the importance of maternal health and nutrition. This can include educating mothers and caregivers about proper child feeding practices, the benefits of breastfeeding, and the importance of maintaining hygienic practices.

2. Improve access to healthcare facilities: Increase the number of healthcare facilities, such as hospitals, health centers, and urban health posts, in the area to improve access to maternal health services. This can include providing necessary resources and equipment for maternal and child healthcare.

3. Strengthen healthcare workforce: Train and deploy more healthcare professionals, including doctors, nurses, and midwives, to provide quality maternal healthcare services. This can help ensure that there are enough skilled healthcare providers to meet the needs of the community.

4. Enhance nutrition programs: Implement nutrition programs that focus on improving the nutritional status of children aged 24-59 months. This can include providing nutritional supplements, promoting diverse and balanced diets, and addressing specific nutritional deficiencies.

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 health and access to healthcare services in the target area. This can include information on the number of healthcare facilities, healthcare workforce, and maternal health indicators.

2. Define indicators: Identify specific indicators that will be used to measure the impact of the recommendations. This can include indicators such as the number of healthcare facilities per population, the percentage of women receiving prenatal care, and the prevalence of undernutrition among children.

3. Develop a simulation model: Create a simulation model that incorporates the baseline data and the potential impact of the recommendations. This model can be based on mathematical equations or statistical models that estimate the relationship between the recommendations and the desired outcomes.

4. Input data and run simulations: Input the baseline data into the simulation model and run simulations to estimate the potential impact of the recommendations. This can involve adjusting variables such as the number of healthcare facilities, the coverage of education programs, and the availability of resources.

5. Analyze results: Analyze the results of the simulations to assess the potential impact of the recommendations on improving access to maternal health. This can include comparing the baseline data with the simulated outcomes to determine the effectiveness of the recommendations.

6. Refine and validate the model: Refine the simulation model based on the analysis of the results and validate the model using additional data or real-world observations. This can help ensure the accuracy and reliability of the simulation results.

7. Communicate findings: Present the findings of the simulation study to relevant stakeholders, such as policymakers, healthcare providers, and community members. This can help inform decision-making and guide the implementation of interventions to improve access to maternal health.

It is important to note that the methodology for simulating the impact of recommendations may vary depending on the specific context and available data.

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