Predictors of inappropriate complementary feeding practice among children aged 6 to 23 months in Wonago District, South Ethiopia, 2017; Case control study

BMC Pediatrics, Volume 19, No. 1, Year 2019

Ukuhunyushwa

Background: Inappropriate complementary feeding practice could result in child illness, sub-optimal growth and development. Evidence shows a huge burden of inappropriate complementary feeding practice from global to national level. But studies regarding predictors of inappropriate complementary feeding practices were scarce especially in the study area. Therefore, the aim of this study was to determine predictors and community level factors associated with inappropriate complementary feeding practice among children age 6 to 23 months in Wonago district, South Ethiopia. Methods: A community based unmatched case-control study design complemented by a qualitative and dietary data was employed among children in Wonago district from April- 07 to June- 06, 2017. A total of 372 study subjects were enrolled to the study by stratified sampling technique. Data were checked, coded and entered to Epi data and exported to SPSS for analysis. Univariate, bivariable and multivariable logistic regressions analyses were applied. A p- value < 0.05 was considered as statistical significant level. Results: Paternal household decision making on feeding(AOR = 4.65, 95% CI = (1.69, 12.81)), family priority to elders during feeding(AOR = 2.35, 95% CI = (1.08, 5.14)), absence of nearby health facility(AOR = 4.15, 95% CI = (1.63, 10.55)), unplanned pregnancy (AOR = 3.45, 95% CI = (1.21, 9.85)), missing ANC(AOR = 2.71, 95% CI = (1.48, 4.96)) and missing EPI service utilization (AOR = 2.43, 95% CI = (1.34, 4.38)) were independent predictors of inappropriate complementary feeding practices. Whereas; lack of awareness, short birth spacing practice, poverty and feeding culture were community related factors. The nutrient density of complementary foods were below WHO desired density level except for energy, protein and vitamin C. Conclusions: Inappropriate complementary feeding practice was related to household feeding cultures, health service access and utilization and community related factors like awareness, poverty and low birth spacing. Complementary foods were found to have lower nutrient density than desired by WHO. Promoting community's health service utilization and increasing awareness regarding complementary feeding were recommended. The study was conducted in Wonago district of Gedeo zone, SNNPR, Ethiopia. The district was located 13, 102 and 377 kms from the zonal, regional and national capitals, Dilla, Hawassa and Addis Ababa, respectively. The district have 17 rural and 4 urban kebeles. The latest 2016 population projection of the national statistical authority shows that the district has 156,481 total population. There are 33,294 households having 4.7 persons per household. From the total population, 91.3% dwells in the rural, while the rest 8.7% lives in urban. There are 29,780 and 3077 households in rural and urban respectively. Person per household is 4.8 and 4.4 for rural and urban respectively. According to Gedeo zone agriculture office coffee, inset, maize, teff, cabbage, sweet potato, avocado, banana, mango were among the main agricultural production of the district. The major economic activity of the area is commerce especially on coffee and product of inset. There are 6 health centers, 20 health posts and 2 private clinics in Wonago district. The study was conducted between April 07 and June 06, 2017 G.C. The study employed a community based unmatched case-control analytic study design. This was complemented by a qualitative data from community and dietary data from selected households. The sample size was calculated using EPI-Info version 7 statistical software (Center for Disease Control and Prevention, Atlanta, 2005) and the largest feasible sample size was taken. The assumptions for the sample size calculation were: proportion of young children who had exposure(maternal education with secondary and above) were 17.9% among the cases and 31% among controls [24], 80% power, 95% confidence interval, 10% non-response rate and a case: control ratio of 1:1. This yielded, a total sample size of 372 (186 cases and 186 controls). Similarly, saturation and redundancy level of information was used to limit the number of key informants and focus group discussant of the qualitative part of the study. A stratified sampling technique was employed. Initially, all kebeles in the district was stratified into urban and rural. Five rural and one urban kebeles were randomly selected. Three weeks prior to actual data collection, using 6 data collectors census was conducted on complementary feeding practices of young children aged 6–23 months using a 24 h recall dietary assessment tool in the selected kebeles. The tool was developed based on WHO core indicators used to assess complementary feeding practices of infant and young children [2]. These are introduction of solid, semi-solid or soft foods at 6–8 months of age, meal frequency and dietary diversity. The 24 h dietary intake of the children were assessed using these structured questionnaire as of the mothers report. Based on this assessment the children’s dietary intake were labeled as appropriate (control) and inappropriate (case). Appropriate when they meet all the three indicators timely introduction, minimum meal frequency and minimum dietary diversity while it was considered inappropriate when it fails to fulfill even a single indicators. From these list of identified households, a total of 186 cases and 186 controls were selected using a simple random sampling technique. Timely introduction of complementary feeding: introduction of solid, semi-solid or soft foods is recommended to start at age of 6–8 months [2]. Minimum dietary diversity: it is receiving foods from 4 or more food groups for children 6–23 months of age [2]. Minimum meal frequency: it is receiving solid, semi-solid, or soft foods the minimum number of times or more among children 6–23 months. The recommended number of meals per day for 6–8 months, 9–11 months & 12–23 months is 2–3 times, 3–4 times and 3–4 plus 1–2 snacks respectively [2]. Minimum acceptable diet: Is the combination of both minimum dietary diversity and meal frequency [2]. Inappropriate complementary feeding practice: complementary feeding practices that fails to fulfill either timely introduction or minimum acceptable diet. Cases: Are young children (6–23 months) with inappropriate complementary feeding practices. Controls: Are young children (6–23 months) with appropriate complementary feeding practices. Data was collected using a study format, structured, semi-structured and unstructured quantitative and qualitative data collection questionnaires. The quantitave data collection utilized a structured interviewer administer questionnaires. It do have section that address sociodemographic, household, community and health services characteristics. Under household characteristic wealth index was assessed using household asset and housing characteristics while household food insecurity was assessed using household food insecurity access scale measurement tool. While the qualitative data was collected using semi and unstructured in-depth and focus group discussion guide more focusing on community and cultural aspects. The data collection tools were prepared in English and translated to local languages, Amharic and Gede’uffa. The energy density and nutrient adequacy of complementary foods were estimated among 15% of the sample size, using dietary assessment method. The children food intake were weighted for two days. During each meal, weight of each ingredients during preparation, final weight of the food before taken by the child and leftover weight were taken. The quantitative data was collected using 6 data collectors who complete at least grade 10; one for each selected kebeles. While the qualitative data collection utilized a total of 7 data collectors who are health professional. Two public health professionals supervised the whole data collection process day today. All data collectors and supervises were trained for one day before preceding to data collection. Pre-testing and standardization of the study tools was carried out on April 2017, in Chichu which is closer but outside the proposed study area. Chichu was known to share similar economic, geographic, cultural and socio-demographic characteristics with study villages. During pre-testing the questionnaire was assessed for its clarity, understandability, length, completeness, validity and reliability. A total of 37 (10% of sample size) households was selected for pre-testing. Data was checked, coded and entered to Epi data version 3.1 and exported to SPSS (Statistical Package for Social science) version 20 for analysis. Univariate analysis like mean, median and frequencies were conducted and presented using text, tables and graphs. Wealth index was computed using the principal component analysis. Then bivariable analysis was carried out to identify candidate factors associated with outcome variable for multivariable analysis. The decision was made using Odds ratio (OR) and confidence interval (CI) at 95% confidence level. Finally those predictor variables with P < 0.25 were entered into multivariable analysis and the final model was fitted using variables with P < 0.05. Dietary data collected from sub sample two days follow up was converted to nutritional data using the Ethiopian Food Composition Table for major macro and micronutrient contents. Each nutrient amount was calculated from each ingredient of complementary foods using the conversion factor from the above table. Then total amount of each nutrients over the two days were calculated by summing individual amount of nutrient from each ingredient of each meal. The same procedure were followed to calculate the total energy of complementary foods. Nutrient densities per 100Kcal complementary food was calculated by dividing the amount of nutrients to total energy level of complementary foods(in Kcal) and multiplying by 100Kcal while energy density was calculated by dividing total energy of complementary foods in Kcal to total amount of complementary foods in grams. Qualitative data analysis was done manually. Each audiotape interview was professionally transcribed word by word in Geddu’uffa (local language) to Amharic and then translated to English languages. Transcribed data was analyzed manually using the thematic framework analysis method.

I-AI Digest

Study Justification:

– Inappropriate complementary feeding practices can lead to child illness and sub-optimal growth and development.
– There is a significant burden of inappropriate complementary feeding practices globally and nationally.
– Limited studies have been conducted on predictors of inappropriate complementary feeding practices in the study area.

Study Highlights:

– The study aimed to determine predictors and community-level factors associated with inappropriate complementary feeding practices among children aged 6 to 23 months in Wonago district, South Ethiopia.
– A total of 372 study subjects were enrolled in the study.
– Paternal household decision making on feeding, family priority to elders during feeding, absence of nearby health facility, unplanned pregnancy, missing ANC, and missing EPI service utilization were identified as independent predictors of inappropriate complementary feeding practices.
– Lack of awareness, short birth spacing practice, poverty, and feeding culture were identified as community-related factors.
– The nutrient density of complementary foods was found to be below the desired level recommended by WHO, except for energy, protein, and vitamin C.

Recommendations for Lay Reader and Policy Maker:

– Promote community’s health service utilization to improve appropriate complementary feeding practices.
– Increase awareness among caregivers regarding appropriate complementary feeding.
– Address household feeding cultures and prioritize child feeding practices.
– Improve access to nearby health facilities for better child feeding practices.
– Address factors related to unplanned pregnancy and missing ANC and EPI service utilization.
– Address community-related factors such as lack of awareness, poverty, and short birth spacing practice.
– Improve the nutrient density of complementary foods to meet WHO recommendations.

Key Role Players:

– Health professionals and community health workers for health education and awareness campaigns.
– Local government authorities for policy implementation and resource allocation.
– Non-governmental organizations for support and intervention programs.
– Community leaders and elders for promoting positive feeding cultures and practices.

Cost Items for Planning Recommendations:

– Health education and awareness campaigns.
– Training programs for health professionals and community health workers.
– Resource allocation for improving access to nearby health facilities.
– Support and intervention programs by non-governmental organizations.
– Research and development for improving nutrient density of complementary foods.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a case-control study design, which is a strong study design for determining predictors. The study used a large sample size and conducted both quantitative and qualitative data collection. The statistical analysis was appropriate, including univariate, bivariable, and multivariable logistic regression analyses. The study also provided specific results, including odds ratios and confidence intervals. However, the study was conducted in a specific district in South Ethiopia, which may limit the generalizability of the findings. To improve the evidence, future studies could consider conducting a multi-center study to increase the generalizability of the results.

Abstract

The study was conducted in Wonago district of Gedeo zone, SNNPR, Ethiopia. The district was located 13, 102 and 377 kms from the zonal, regional and national capitals, Dilla, Hawassa and Addis Ababa, respectively. The district have 17 rural and 4 urban kebeles. The latest 2016 population projection of the national statistical authority shows that the district has 156,481 total population. There are 33,294 households having 4.7 persons per household. From the total population, 91.3% dwells in the rural, while the rest 8.7% lives in urban. There are 29,780 and 3077 households in rural and urban respectively. Person per household is 4.8 and 4.4 for rural and urban respectively. According to Gedeo zone agriculture office coffee, inset, maize, teff, cabbage, sweet potato, avocado, banana, mango were among the main agricultural production of the district. The major economic activity of the area is commerce especially on coffee and product of inset. There are 6 health centers, 20 health posts and 2 private clinics in Wonago district. The study was conducted between April 07 and June 06, 2017 G.C. The study employed a community based unmatched case-control analytic study design. This was complemented by a qualitative data from community and dietary data from selected households. The sample size was calculated using EPI-Info version 7 statistical software (Center for Disease Control and Prevention, Atlanta, 2005) and the largest feasible sample size was taken. The assumptions for the sample size calculation were: proportion of young children who had exposure(maternal education with secondary and above) were 17.9% among the cases and 31% among controls [24], 80% power, 95% confidence interval, 10% non-response rate and a case: control ratio of 1:1. This yielded, a total sample size of 372 (186 cases and 186 controls). Similarly, saturation and redundancy level of information was used to limit the number of key informants and focus group discussant of the qualitative part of the study. A stratified sampling technique was employed. Initially, all kebeles in the district was stratified into urban and rural. Five rural and one urban kebeles were randomly selected. Three weeks prior to actual data collection, using 6 data collectors census was conducted on complementary feeding practices of young children aged 6–23 months using a 24 h recall dietary assessment tool in the selected kebeles. The tool was developed based on WHO core indicators used to assess complementary feeding practices of infant and young children [2]. These are introduction of solid, semi-solid or soft foods at 6–8 months of age, meal frequency and dietary diversity. The 24 h dietary intake of the children were assessed using these structured questionnaire as of the mothers report. Based on this assessment the children’s dietary intake were labeled as appropriate (control) and inappropriate (case). Appropriate when they meet all the three indicators timely introduction, minimum meal frequency and minimum dietary diversity while it was considered inappropriate when it fails to fulfill even a single indicators. From these list of identified households, a total of 186 cases and 186 controls were selected using a simple random sampling technique. Timely introduction of complementary feeding: introduction of solid, semi-solid or soft foods is recommended to start at age of 6–8 months [2]. Minimum dietary diversity: it is receiving foods from 4 or more food groups for children 6–23 months of age [2]. Minimum meal frequency: it is receiving solid, semi-solid, or soft foods the minimum number of times or more among children 6–23 months. The recommended number of meals per day for 6–8 months, 9–11 months & 12–23 months is 2–3 times, 3–4 times and 3–4 plus 1–2 snacks respectively [2]. Minimum acceptable diet: Is the combination of both minimum dietary diversity and meal frequency [2]. Inappropriate complementary feeding practice: complementary feeding practices that fails to fulfill either timely introduction or minimum acceptable diet. Cases: Are young children (6–23 months) with inappropriate complementary feeding practices. Controls: Are young children (6–23 months) with appropriate complementary feeding practices. Data was collected using a study format, structured, semi-structured and unstructured quantitative and qualitative data collection questionnaires. The quantitave data collection utilized a structured interviewer administer questionnaires. It do have section that address sociodemographic, household, community and health services characteristics. Under household characteristic wealth index was assessed using household asset and housing characteristics while household food insecurity was assessed using household food insecurity access scale measurement tool. While the qualitative data was collected using semi and unstructured in-depth and focus group discussion guide more focusing on community and cultural aspects. The data collection tools were prepared in English and translated to local languages, Amharic and Gede’uffa. The energy density and nutrient adequacy of complementary foods were estimated among 15% of the sample size, using dietary assessment method. The children food intake were weighted for two days. During each meal, weight of each ingredients during preparation, final weight of the food before taken by the child and leftover weight were taken. The quantitative data was collected using 6 data collectors who complete at least grade 10; one for each selected kebeles. While the qualitative data collection utilized a total of 7 data collectors who are health professional. Two public health professionals supervised the whole data collection process day today. All data collectors and supervises were trained for one day before preceding to data collection. Pre-testing and standardization of the study tools was carried out on April 2017, in Chichu which is closer but outside the proposed study area. Chichu was known to share similar economic, geographic, cultural and socio-demographic characteristics with study villages. During pre-testing the questionnaire was assessed for its clarity, understandability, length, completeness, validity and reliability. A total of 37 (10% of sample size) households was selected for pre-testing. Data was checked, coded and entered to Epi data version 3.1 and exported to SPSS (Statistical Package for Social science) version 20 for analysis. Univariate analysis like mean, median and frequencies were conducted and presented using text, tables and graphs. Wealth index was computed using the principal component analysis. Then bivariable analysis was carried out to identify candidate factors associated with outcome variable for multivariable analysis. The decision was made using Odds ratio (OR) and confidence interval (CI) at 95% confidence level. Finally those predictor variables with P < 0.25 were entered into multivariable analysis and the final model was fitted using variables with P < 0.05. Dietary data collected from sub sample two days follow up was converted to nutritional data using the Ethiopian Food Composition Table for major macro and micronutrient contents. Each nutrient amount was calculated from each ingredient of complementary foods using the conversion factor from the above table. Then total amount of each nutrients over the two days were calculated by summing individual amount of nutrient from each ingredient of each meal. The same procedure were followed to calculate the total energy of complementary foods. Nutrient densities per 100Kcal complementary food was calculated by dividing the amount of nutrients to total energy level of complementary foods(in Kcal) and multiplying by 100Kcal while energy density was calculated by dividing total energy of complementary foods in Kcal to total amount of complementary foods in grams. Qualitative data analysis was done manually. Each audiotape interview was professionally transcribed word by word in Geddu’uffa (local language) to Amharic and then translated to English languages. Transcribed data was analyzed manually using the thematic framework analysis method.

Izinto zokwakha

N/A

Emisha

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information and guidance on appropriate complementary feeding practices for mothers. These apps can also include reminders for important health appointments and provide access to telemedicine services.

2. Community Health Workers: Train and deploy community health workers to educate and support mothers in implementing appropriate complementary feeding practices. These workers can provide personalized guidance, conduct home visits, and connect mothers to healthcare services.

3. Telemedicine Services: Establish telemedicine services that allow mothers in remote areas to consult with healthcare professionals for guidance on complementary feeding practices. This can help overcome barriers related to distance and lack of nearby health facilities.

4. Health Education Campaigns: Launch targeted health education campaigns to raise awareness about the importance of appropriate complementary feeding practices. These campaigns can utilize various communication channels, such as radio, television, and community gatherings, to reach a wide audience.

5. Nutritional Support Programs: Implement programs that provide nutritional support to mothers and children, ensuring access to diverse and nutrient-rich foods. This can be done through initiatives like food vouchers, subsidized nutritious food packages, or community gardens.

6. Maternal Health Clinics: Establish dedicated maternal health clinics that offer comprehensive services, including antenatal care, postnatal care, and counseling on complementary feeding practices. These clinics can serve as a one-stop solution for mothers’ healthcare needs.

7. Public-Private Partnerships: Foster collaborations between the public and private sectors to improve access to maternal health services. This can involve leveraging private sector resources and expertise to expand healthcare infrastructure and service delivery.

8. Health Information Systems: Develop robust health information systems that capture data on maternal health indicators, including complementary feeding practices. This data can be used to monitor progress, identify areas for improvement, and inform evidence-based interventions.

9. Maternal Health Hotlines: Establish toll-free hotlines staffed by trained healthcare professionals who can provide guidance and support to mothers regarding complementary feeding practices. This can be particularly helpful for mothers who have limited access to healthcare facilities.

10. Maternal Health Mobile Units: Deploy mobile health units equipped with necessary medical equipment and staffed by healthcare professionals. These units can travel to remote areas, providing maternal health services, including counseling on complementary feeding practices.

It is important to note that the implementation of these innovations should be context-specific and tailored to the local needs and resources of the Wonago district in South Ethiopia.

AI Innovations Description

The study titled “Predictors of inappropriate complementary feeding practice among children aged 6 to 23 months in Wonago District, South Ethiopia, 2017; Case control study” aimed to determine predictors and community-level factors associated with inappropriate complementary feeding practices among children aged 6 to 23 months in Wonago district, South Ethiopia.

The study found several predictors of inappropriate complementary feeding practices, including paternal household decision making on feeding, family priority to elders during feeding, absence of nearby health facility, unplanned pregnancy, missing antenatal care (ANC), and missing Expanded Program on Immunization (EPI) service utilization. Additionally, lack of awareness, short birth spacing practice, poverty, and feeding culture were identified as community-related factors.

The study also assessed the nutrient density of complementary foods and found that they were below the desired density level recommended by the World Health Organization (WHO), except for energy, protein, and vitamin C.

Based on the findings, the study recommended promoting community’s health service utilization and increasing awareness regarding complementary feeding to improve access to maternal health. It also highlighted the importance of addressing household feeding cultures, health service access and utilization, and community-related factors such as awareness, poverty, and low birth spacing.

The study was conducted in Wonago district of Gedeo zone, SNNPR, Ethiopia. The district has a total population of 156,481, with 91.3% residing in rural areas. The major economic activities in the area are agriculture, particularly coffee, inset, maize, teff, cabbage, sweet potato, avocado, banana, and mango. The district has 6 health centers, 20 health posts, and 2 private clinics.

The study employed a community-based unmatched case-control study design, complemented by qualitative and dietary data. A total of 372 study subjects were enrolled using stratified sampling technique. Data were collected using structured questionnaires, and statistical analysis was conducted using Epi data and SPSS software.

Overall, the study provides valuable insights into the predictors of inappropriate complementary feeding practices and highlights the need for interventions to improve access to maternal health in the study area.

AI Innovations Methodology

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

1. Strengthening Health Facilities: Address the issue of absence of nearby health facilities by improving the availability and accessibility of health facilities in the Wonago district. This could involve building new health centers or expanding existing ones to ensure that pregnant women have access to quality maternal health services.

2. Increasing Awareness: Develop and implement community-based awareness campaigns to educate families and communities about the importance of appropriate complementary feeding practices. This could include providing information on the recommended age to introduce solid foods, the importance of dietary diversity, and the minimum meal frequency for children aged 6 to 23 months.

3. Empowering Women: Promote gender equality and women’s empowerment to address the issue of paternal household decision making on feeding. Encourage shared decision making between spouses and provide support to women in asserting their preferences and choices regarding maternal and child health.

4. Strengthening Antenatal Care (ANC) and Immunization Services: Address the issues of missing ANC and missing EPI service utilization by improving the availability and quality of ANC and immunization services in the district. This could involve training healthcare providers, ensuring the availability of necessary supplies and equipment, and promoting community awareness about the importance of ANC and immunization.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Baseline Data Collection: Collect baseline data on the current status of maternal health access in the Wonago district. This could include information on the number and location of health facilities, utilization rates of ANC and immunization services, and the prevalence of inappropriate complementary feeding practices.

2. Intervention Implementation: Implement the recommended interventions, such as building new health facilities, conducting awareness campaigns, promoting gender equality, and strengthening ANC and immunization services. Monitor the implementation process to ensure that the interventions are carried out effectively.

3. Data Collection after Intervention: Collect data after the interventions have been implemented to assess their impact on improving access to maternal health. This could involve conducting surveys, interviews, or focus group discussions with community members, healthcare providers, and other stakeholders.

4. Data Analysis: Analyze the collected data to evaluate the changes in maternal health access indicators, such as the utilization rates of health facilities, ANC, and immunization services, as well as the prevalence of appropriate complementary feeding practices. Compare the post-intervention data with the baseline data to determine the impact of the interventions.

5. Evaluation and Recommendations: Evaluate the findings of the data analysis and make recommendations for further improvements. Identify any gaps or challenges that need to be addressed and propose additional interventions or modifications to existing interventions.

By following this methodology, it would be possible to simulate the impact of the recommended interventions on improving access to maternal health in the Wonago district.

Ababhali & Co-Ababhali

Statistics:

Citations: 4

Authors: 3

Identifiers:

DOI: 10.1186/s12887-019-1523-6

Research Areas:

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

Study Countries:

Ethiopia

Study Design:

Case-Control Study, Cross Sectional Study, Grounded Theory

Study Approach:

Mixed-methods, Qualitative, Quantitative

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