Promising trends and influencing factors of complementary feeding practices in Côte d’Ivoire: An analysis of nationally representative survey data between 1994 and 2016

Maternal and Child Nutrition, Volume 19, No. 1, Year 2023

Interpretation

Poor complementary feeding (CF) challenges early childhood growth. We examined the trends and influencing factors of CF practices among children aged 6–23 months in Côte d’Ivoire. Using data from Demographic and Health Surveys (DHS, 1994–2011) and Multiple Indicator Cluster Surveys (MICS, 2000–2016), the trends and predictors of World Health Organization-United Nations International Children’s Emergency Fund CF indicators including the timely introduction of complementary foods (INTRO), minimum meal frequency (MMF), minimum dietary diversity (MDD) and minimum acceptable diet (MAD) were determined. Using 2016 MICS data, we applied multivariate logistic regression models to identify factors associated with CF indicators. Between 1994 and 2016, the mean proportion of children aged 6–8 months achieving INTRO was 56.9% and increased by about 25% points since 2006. Over 2011–2016, the proportion of children aged 6–23 months meeting MMF, MDD and MAD increased from 40.2% to 47.7%, 11.3% to 26.0% and 4.6% to 12.5%, respectively. Older children and those from urban households had higher odds of meeting MDD and MAD. Maternal TV watching was associated with higher odds of meeting MDD. The secondary or higher education levels of mothers significantly predicted higher odds of meeting INTRO and MDD. Currently, breastfeeding was also positively associated with odds of meeting MMF and MAD. Children from poorer households had lower odds of meeting MMF, MDD and MAD. Despite the improvements, CF practices remain suboptimal in Côte d’Ivoire. Influencing factors associated with CF were distributed across individual, household and community levels, calling for future programmes and policies to implement multi-level strategies to improve young children’s diet in Côte d’Ivoire. To understand the CF trends (aim 1), we extracted data on the key CF indicators from five nationally representative survey reports: the 1994 and 2011 Côte d’Ivoire Demographic and Health Surveys (DHS) reports and 2000, 2006 and 2016 Côte d’Ivoire Multi‐Indicator Cluster Survey (MICS) reports. Four independent researchers conducted data extraction in pairs. Any discrepancy (i.e., inaccurate data extracted from wrong tables in reports) between the researchers were resolved through group discussion until consensus was reached. To explore the current influencing factors of CF (aim 2), we analyzed the most recent 2016 MICS data. Information on the 2016 MICS survey methodology, sampling procedure and questionnaires has been published previously (Institut National de la Statistique et al., 2016). Briefly, eligible women and children were included based on a two‐stage stratified sampling procedure. At the first stage, a total of 512 census enumeration areas were selected with probability as the primary sampling units (PSUs). At the second stage, 25 households were selected by systematic sampling within each PSU. Based on prior studies looking at CF practices in low‐ and middle‐income countries (Na, Aguayo, Arimond, Dahal, et al., 2018; Na, Aguayo, Arimond, Mustaphi, et al., 2018; Na et al., 2017), the inclusion criteria of mother–child pairs to be included in our analysis were: (1) mothers were between 15 and 49 years of age; (2) the youngest singleton child was aged 6–23 months; (3) children were alive at the time of the survey; and (4) children lived with their mothers. We included mothers aged 15–49 years old to decrease the possibility of enroling children with potential health problems born from teenage (<15 years) or older (>49 years) mothers. The study further defined the youngest singleton children aged 6–23 months to avoid potential recall bias and to prevent enroling more than one child from each household. In addition, only alive children living with their mothers were included, so the surveys were able to collect their CF practices from mother–child pairs. Four CF indicators defined by WHO in 2010 were analyzed in this study, including the introduction of solid, semisolid, or soft foods (INTRO), minimum meal frequency (MMF), minimum dietary diversity (MDD) and MAD (World Health Organization, 2010). Data for INTRO were available in 1994 and 2011 DHS and 2000, 2006 and 2016 MICS reports. Data for MMF, MDD and MAD were only available in the 2011 DHS and 2016 MICS reports. The CF indicators were defined per WHO definitions as follows (WHO, 2010): INTRO: The proportion of infants 6–8 months of age who received solid, semisolid and soft foods in the previous day or night. MMF: The proportion of breastfed and nonbreastfed children 6–23 months of age, who received solid, semisolid or soft foods (including milk for nonbreastfed children) the minimum recommended number of times or more in the previous day or night. For breastfed children, MMF is met if at least two solid/semisolid feeds occurred for children aged 6–8 months and at least three feeds occurred for children aged 9–23 months. For nonbreastfed children, MMF is met if at least four feeds of complementary food or milk for children aged 6–23 months occurred. MDD: The proportion of children 6–23 months of age who received foods from four or more food groups in the previous day or night out of the following seven food groups: (1) grains, roots and tubers, (2) legumes and nuts, (3) dairy products, (4) flesh foods, (5) eggs, (6) vitamin‐A‐rich fruits and vegetables and (7) other fruits and vegetables. MAD: The proportion of children 6–23 months of age who received the minimum recommended dietary diversity and the minimum recommended meal frequency in the previous day or night. For breastfed children, they are classified as having a MAD when they meet the MMF and MDD standards. For nonbreastfed children, they are classified as having a MAD when they meet the MMF standards and receive at least two milk feedings along with at least four food groups other than milk products. The selection of the influencing factors at the individual, household and community levels was based on the conceptual framework developed by Stewart et al. (2013) and our previous work in South Asia (Na, Aguayo, Arimond, Dahal, et al., 2018; Na, Aguayo, Arimond, Mustaphi, et al., 2018; Na, Aguayo, Arimond, Narayan, et al., 2018; Na et al., 2017). Individual‐level factors included child, maternal and paternal characteristics. For children, the following variables were included: sex, age, birth order, birth interval, measured birthweight, perceived birthweight and child morbidity including diarrhoea, fever and cough. Maternal characteristics included age, smoking status, education, marital status, occupation, nutritional status (height and body mass index), breastfeeding practices, utilization of reproductive health care, exposure to media and women’s attitude towards domestic violence. Paternal characteristics included age and education. Household‐level factors included household structures and socioeconomic status. The household characteristics included the place of residence, sex of household head, number of household members, number of children under five years, types of cooking fuel, water characteristics (source and location of drinking water, time to get to water sources) and quintiles of overall household wealth index (higher quintiles indicate poorer households). The community‐level factor described access to health care within the community where the selected subjects lived. Based on the utilization of maternal and child nutrition and health care services among all respondents, the rank score for community access to health care was generated first and then categorized into quintiles. Higher rank scores or quintiles indicate poorer community access to health care. A detailed description of the factors is available elsewhere (Na et al., 2020). All data analysis was performed using STATA/SE 15.1 (StataCorp). The prevalence of four CF indicators was extracted from the national DHS and MICS reports. Multivariable models were applied to determine the associations between influencing factors and CF indicators among children aged 6–23 months: (1) the bivariate associations between influencing factors and CF indicators were examined first to select the significant risk factors at p= 0.1, and (2) the selected variables from the bivariate analysis were included in the multivariate risk factor analysis.

AI Digest

Study Justification:

– The study aims to examine the trends and influencing factors of complementary feeding (CF) practices among children aged 6-23 months in Côte d’Ivoire.
– Poor CF practices can negatively impact early childhood growth, so understanding the factors influencing these practices is crucial for improving child nutrition and health outcomes.
– The study utilizes nationally representative survey data from 1994 to 2016 to provide comprehensive insights into CF practices in Côte d’Ivoire.

Highlights:

– Between 1994 and 2016, there has been an increase in the proportion of children aged 6-8 months achieving timely introduction of complementary foods (INTRO), with a 25% point increase since 2006.
– From 2011 to 2016, there were improvements in the proportion of children aged 6-23 months meeting minimum meal frequency (MMF), minimum dietary diversity (MDD), and minimum acceptable diet (MAD).
– Factors associated with better CF practices include older age of children, urban households, maternal TV watching, higher education levels of mothers, and breastfeeding.
– However, despite these improvements, CF practices in Côte d’Ivoire remain suboptimal, indicating the need for further interventions and policies.

Recommendations:

– Implement multi-level strategies: CF practices are influenced by factors at the individual, household, and community levels. Future programs and policies should adopt multi-level approaches to improve young children’s diet in Côte d’Ivoire.
– Target specific populations: Interventions should focus on addressing the needs of children from poorer households, as they have lower odds of meeting MMF, MDD, and MAD.
– Promote education and awareness: Emphasize the importance of education, particularly for mothers, as higher education levels are associated with better CF practices. Additionally, raise awareness about the benefits of breastfeeding and the importance of diverse and nutritious diets for young children.

Key Role Players:

– Researchers: Conduct further studies to explore the effectiveness of multi-level strategies and interventions to improve CF practices in Côte d’Ivoire.
– Government Agencies: Develop and implement policies that prioritize child nutrition and support interventions aimed at improving CF practices.
– Healthcare Professionals: Provide guidance and support to mothers and caregivers on appropriate CF practices and the importance of diverse and nutritious diets for young children.
– Community Leaders and Organizations: Raise awareness about CF practices and promote education and resources within communities.

Cost Items for Planning Recommendations:

– Research Funding: Allocate resources for further studies and data collection to assess the effectiveness of multi-level strategies and interventions.
– Program Implementation: Budget for the development and implementation of interventions targeting specific populations, including training, education materials, and monitoring.
– Education and Awareness Campaigns: Allocate funds for campaigns to raise awareness about CF practices, breastfeeding, and the importance of diverse and nutritious diets for young children.
– Capacity Building: Invest in training and capacity building for healthcare professionals and community leaders to effectively support and promote improved CF practices.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides a detailed description of the methodology used, including the data sources and analysis methods. However, it does not mention the sample size or the representativeness of the surveys. To improve the evidence, the abstract could include information on the sample size and how the surveys were designed to be representative of the population. Additionally, providing information on the statistical significance of the associations between influencing factors and CF indicators would strengthen the evidence.

Abstract

To understand the CF trends (aim 1), we extracted data on the key CF indicators from five nationally representative survey reports: the 1994 and 2011 Côte d’Ivoire Demographic and Health Surveys (DHS) reports and 2000, 2006 and 2016 Côte d’Ivoire Multi‐Indicator Cluster Survey (MICS) reports. Four independent researchers conducted data extraction in pairs. Any discrepancy (i.e., inaccurate data extracted from wrong tables in reports) between the researchers were resolved through group discussion until consensus was reached. To explore the current influencing factors of CF (aim 2), we analyzed the most recent 2016 MICS data. Information on the 2016 MICS survey methodology, sampling procedure and questionnaires has been published previously (Institut National de la Statistique et al., 2016). Briefly, eligible women and children were included based on a two‐stage stratified sampling procedure. At the first stage, a total of 512 census enumeration areas were selected with probability as the primary sampling units (PSUs). At the second stage, 25 households were selected by systematic sampling within each PSU. Based on prior studies looking at CF practices in low‐ and middle‐income countries (Na, Aguayo, Arimond, Dahal, et al., 2018; Na, Aguayo, Arimond, Mustaphi, et al., 2018; Na et al., 2017), the inclusion criteria of mother–child pairs to be included in our analysis were: (1) mothers were between 15 and 49 years of age; (2) the youngest singleton child was aged 6–23 months; (3) children were alive at the time of the survey; and (4) children lived with their mothers. We included mothers aged 15–49 years old to decrease the possibility of enroling children with potential health problems born from teenage (49 years) mothers. The study further defined the youngest singleton children aged 6–23 months to avoid potential recall bias and to prevent enroling more than one child from each household. In addition, only alive children living with their mothers were included, so the surveys were able to collect their CF practices from mother–child pairs. Four CF indicators defined by WHO in 2010 were analyzed in this study, including the introduction of solid, semisolid, or soft foods (INTRO), minimum meal frequency (MMF), minimum dietary diversity (MDD) and MAD (World Health Organization, 2010). Data for INTRO were available in 1994 and 2011 DHS and 2000, 2006 and 2016 MICS reports. Data for MMF, MDD and MAD were only available in the 2011 DHS and 2016 MICS reports. The CF indicators were defined per WHO definitions as follows (WHO, 2010): INTRO: The proportion of infants 6–8 months of age who received solid, semisolid and soft foods in the previous day or night. MMF: The proportion of breastfed and nonbreastfed children 6–23 months of age, who received solid, semisolid or soft foods (including milk for nonbreastfed children) the minimum recommended number of times or more in the previous day or night. For breastfed children, MMF is met if at least two solid/semisolid feeds occurred for children aged 6–8 months and at least three feeds occurred for children aged 9–23 months. For nonbreastfed children, MMF is met if at least four feeds of complementary food or milk for children aged 6–23 months occurred. MDD: The proportion of children 6–23 months of age who received foods from four or more food groups in the previous day or night out of the following seven food groups: (1) grains, roots and tubers, (2) legumes and nuts, (3) dairy products, (4) flesh foods, (5) eggs, (6) vitamin‐A‐rich fruits and vegetables and (7) other fruits and vegetables. MAD: The proportion of children 6–23 months of age who received the minimum recommended dietary diversity and the minimum recommended meal frequency in the previous day or night. For breastfed children, they are classified as having a MAD when they meet the MMF and MDD standards. For nonbreastfed children, they are classified as having a MAD when they meet the MMF standards and receive at least two milk feedings along with at least four food groups other than milk products. The selection of the influencing factors at the individual, household and community levels was based on the conceptual framework developed by Stewart et al. (2013) and our previous work in South Asia (Na, Aguayo, Arimond, Dahal, et al., 2018; Na, Aguayo, Arimond, Mustaphi, et al., 2018; Na, Aguayo, Arimond, Narayan, et al., 2018; Na et al., 2017). Individual‐level factors included child, maternal and paternal characteristics. For children, the following variables were included: sex, age, birth order, birth interval, measured birthweight, perceived birthweight and child morbidity including diarrhoea, fever and cough. Maternal characteristics included age, smoking status, education, marital status, occupation, nutritional status (height and body mass index), breastfeeding practices, utilization of reproductive health care, exposure to media and women’s attitude towards domestic violence. Paternal characteristics included age and education. Household‐level factors included household structures and socioeconomic status. The household characteristics included the place of residence, sex of household head, number of household members, number of children under five years, types of cooking fuel, water characteristics (source and location of drinking water, time to get to water sources) and quintiles of overall household wealth index (higher quintiles indicate poorer households). The community‐level factor described access to health care within the community where the selected subjects lived. Based on the utilization of maternal and child nutrition and health care services among all respondents, the rank score for community access to health care was generated first and then categorized into quintiles. Higher rank scores or quintiles indicate poorer community access to health care. A detailed description of the factors is available elsewhere (Na et al., 2020). All data analysis was performed using STATA/SE 15.1 (StataCorp). The prevalence of four CF indicators was extracted from the national DHS and MICS reports. Multivariable models were applied to determine the associations between influencing factors and CF indicators among children aged 6–23 months: (1) the bivariate associations between influencing factors and CF indicators were examined first to select the significant risk factors at p= 0.1, and (2) the selected variables from the bivariate analysis were included in the multivariate risk factor analysis.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Solutions: Develop and implement mobile applications or text messaging services that provide pregnant women and new mothers with important information about maternal health, including nutrition, breastfeeding, and complementary feeding practices. These tools can also send reminders for prenatal and postnatal appointments and provide access to teleconsultations with healthcare professionals.

2. Community Health Workers (CHWs): Train and deploy CHWs to provide education and support to pregnant women and new mothers in their communities. CHWs can conduct home visits, provide counseling on maternal health practices, and refer women to healthcare facilities when necessary. This approach can help reach women in remote or underserved areas who may have limited access to healthcare services.

3. Telemedicine: Establish telemedicine services that allow pregnant women and new mothers to consult with healthcare professionals remotely. This can help address barriers to accessing healthcare, such as long travel distances or lack of transportation. Telemedicine consultations can provide guidance on maternal health practices, answer questions, and address concerns without the need for in-person visits.

4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access maternal health services, including prenatal care, delivery, and postnatal care. These vouchers can be distributed through community health centers or local organizations and can help reduce financial barriers to accessing essential maternal health services.

5. Maternal Health Education Programs: Develop and implement comprehensive maternal health education programs that target women, families, and communities. These programs can provide information on prenatal care, nutrition, breastfeeding, and postnatal care. They can also address cultural beliefs and practices that may impact maternal health and promote positive behavior change.

6. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve partnering with private healthcare providers to expand service delivery, leveraging private sector resources for health infrastructure development, or implementing public-private financing mechanisms to increase affordability and accessibility of maternal health services.

7. Maternal Health Monitoring Systems: Establish robust monitoring and evaluation systems to track maternal health indicators and identify areas for improvement. This can involve the use of digital health technologies to collect and analyze data, allowing for real-time monitoring of maternal health outcomes and the identification of trends or gaps in service delivery.

These innovations can help improve access to maternal health services, promote positive maternal health practices, and ultimately contribute to better maternal and child health outcomes.

AI Innovations Description

Based on the provided description, the recommendation to improve access to maternal health in Côte d’Ivoire is to implement multi-level strategies that address influencing factors at the individual, household, and community levels. These strategies should focus on the following areas:

1. Individual-level factors: Target interventions towards mothers and children, considering factors such as maternal age, education, nutritional status, breastfeeding practices, and utilization of reproductive health care. Promote awareness and education on the importance of complementary feeding practices and provide support for mothers to adopt appropriate feeding practices.

2. Household-level factors: Address household structures and socioeconomic status by targeting households in urban areas and those from poorer backgrounds. Provide resources and support to improve access to nutritious foods, cooking fuel, and clean drinking water. Promote the involvement of fathers in maternal and child health care decisions.

3. Community-level factors: Improve access to health care within communities by strengthening the availability and quality of maternal and child nutrition and health care services. Enhance community engagement and awareness through health education programs, community health workers, and outreach initiatives.

By implementing these multi-level strategies, it is expected that complementary feeding practices and overall maternal health in Côte d’Ivoire will improve. Continuous monitoring and evaluation of these interventions will be crucial to ensure their effectiveness and make necessary adjustments as needed.

AI Innovations Methodology

Based on the provided description, the study aims to analyze the trends and influencing factors of complementary feeding (CF) practices among children aged 6-23 months in Côte d’Ivoire. The study uses data from nationally representative survey reports, including the Côte d’Ivoire Demographic and Health Surveys (DHS) and the Côte d’Ivoire Multiple Indicator Cluster Surveys (MICS). The study examines CF indicators such as the timely introduction of complementary foods (INTRO), minimum meal frequency (MMF), minimum dietary diversity (MDD), and minimum acceptable diet (MAD).

To understand the CF trends, the researchers extracted data on the key CF indicators from the survey reports. Four independent researchers conducted data extraction in pairs, resolving any discrepancies through group discussion until consensus was reached.

To explore the influencing factors of CF, the study analyzed the most recent MICS data from 2016. The survey methodology involved a two-stage stratified sampling procedure, selecting census enumeration areas as primary sampling units (PSUs) and households within each PSU. The inclusion criteria for mother-child pairs in the analysis included mothers aged 15-49 years, the youngest singleton child aged 6-23 months, children alive at the time of the survey, and children living with their mothers.

The study analyzed four CF indicators defined by the World Health Organization (WHO): INTRO, MMF, MDD, and MAD. The indicators were defined based on specific criteria outlined by the WHO. The study selected influencing factors at the individual, household, and community levels, considering variables such as child, maternal, and paternal characteristics, household structures and socioeconomic status, and access to healthcare within the community.

Data analysis was performed using STATA/SE 15.1, and prevalence of CF indicators was extracted from the national survey reports. Multivariable models were applied to determine the associations between influencing factors and CF indicators among children aged 6-23 months.

In summary, the study utilized nationally representative survey data to analyze CF trends and influencing factors in Côte d’Ivoire. The methodology involved data extraction, analysis of survey data, and multivariable modeling to identify significant risk factors associated with CF indicators.

Author

Dima Health

Identifiers:

DOI: 10.1111/mcn.13418

ISSN: 17408695

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, Violence and Injury

Study Countries:

Ivory Coast

Study Design:

Cross Sectional Study

Study Approach:

Mixed-methods, Quantitative, Systematic Review

Participants Gender:

Female