Early feeding practices and stunting in Rwandan children: A cross-sectional study from the 2010 Rwanda demographic and health survey

Pan African Medical Journal, Volume 29, Year 2018

Interprétation

Introduction: in Rwanda, despite different interventions to improve child nutrition status, malnutrition in children under five years of age continue to be a public health concern. This study aimed to evaluate the factors that contribute to childhood stunting by assessing feeding practices of Rwandans in children ≤ 2 years of age. Methods: A cross-sectional study with data obtained from the 2010 Rwanda Demographic and Health Survey was conducted on 1,634 children ≤ 2 years of age with complete anthropometrical measurements. Multivariable logistic regression analysis was used to assess the association between feeding practices and childhood stunting. Results: The results revealed that 35.1% of 1,634 children were stunted. Breastfeeding for 1 year (OR = 2.77, 95% CI = 1.91-4.01, P < 0.001) increased the risk of childhood stunting. After controlling for confounders, solid food initiation (OR = 1.21, 95% CI = 0.47-3.16, P≥ 0.690) and early initiation to breastfeeding (OR = 1.16, CI = 0.90-1.51, P = 0.243) were not associated with childhood stunting. Conclusion: There was a significant association between continued breastfeeding for 1 year and childhood stunting. We suggest supplementary feeding for children who are breastfed for ≥1 year. Study design: We obtained data from the 2010 Rwanda Demographic and Health Survey (RDHS) to assess the effects of feeding practices on stunting in children ≤ 2 years of age. The RDHS, which has a cross-sectional design, is performed every five years by the National Institute of Statistics of Rwanda and the Ministry of Health. The 2010 RDHS utilized a two-stage sampling process. In the first stage, 492 villages were randomly selected with a sampling probability proportional to the village size and were stratified by district. In the second stage, 26 households from each village were randomly selected. The response rate was 99.1% from females and 98.7% from males. A total of 8,605 children were included in the survey [ 6]. Anthropometrical measurements were obtained from 4,117 children <5 y of age. A total of 1,634 children were ≤ 2 years of age. Study variables: Based on WHO [7] and Rwandan [4] reports, this study hypothesized that feeding practices (i.e., early initiation to breastfeeding; exclusive breastfeeding; continued breastfeeding; and introduction of solid, semi-solid, or soft foods) are independent contributors of stunting in Rwandan children ≤ 2 years of age. Children, parental, and household characteristics were considered to be potential confounders; therefore, they were controlled for in our statistical model (Figure 1). Conceptual framework Primary outcome: Our main study outcome was the prevalence of stunting in children ≤ 2 years of age. Anthropometric measurements were converted into nutritional indices [8]. Height-for-age was used to measure childhood stunting; a -2 z-score was indicative of childhood stunting. Main predictors: feeding pattern indicators: The main predictors of interest, which were based on the WHO Infant and Young Child Feeding indicators, included early initiation of breastfeeding; exclusive breastfeeding under 6 months; continued breastfeeding at 1 year; and introduction of solid, semi-solid, or soft foods [9]. Early initiation of breastfeeding represents the number of children born in the previous 24 months who were breastfed within one hour post-childbirth. Early initiation to breastfeeding is considered to be protective due to the health benefits of colostrum in early breast milk. Exclusive breastfeeding under 6 months represents the number of 0 to 5-month-old infants who were exclusively breastfed. Introduction of solid, semi-solid, or soft foods represents the number of 6 to 8-month-old infants who were fed solid, semi-solid, or soft foods [9]. Potential socio-demographic confounders: The covariates in this study included children age and sex; maternal age, occupation, and education; family residence (urban vs. rural); number of household members; household family income/wealth index; and accessibility to potable drinking water and adequate sanitation facilities. Wealth index was assessed on the basis of de jure population asset data using principal components analysis. Wealth data were obtained from responses to questions on ownership of certain goods and housing characteristics (e.g., access to electricity and source of drinking water, amongst others) [6]. Statistical analyses: Data were analysed using Stata v13 software (StataCorp LP, College Station, TX, USA). Survey commands were used to account for the complex sample design and unequal sampling probability. The associations between feeding practices, socio-demographic variables, and childhood stunting were assessed by simple logistic regression. We tested for confounders using multiple logistic regression. Only variables that modified the coefficient of the outcome by ≥10% were included and controlled for in the final models. Socio-demographic variables that modified the childhood stunting coefficient by ≥10% were included in the multivariable model as potential confounders of the association between childhood stunting and feeding practices. The unadjusted model included childhood stunting and all feeding practice variables. The adjusted model controlled for socio-demographic potential confounders. Odds ratio (OR), 95% confidence interval (CI), and P-values were reported. Ethical consideration: Authorization to use the RDHS dataset was obtained through an online application. The researchers did not make any efforts to identify the survey participants.

Résumé de l’IA

Study Justification:

– Malnutrition in children under five years of age is a public health concern in Rwanda.
– Despite interventions to improve child nutrition, the prevalence of stunting remains high.
– This study aimed to evaluate the factors contributing to childhood stunting by assessing feeding practices in Rwandan children ≤ 2 years of age.

Study Highlights:

– The study utilized data from the 2010 Rwanda Demographic and Health Survey.
– A total of 1,634 children ≤ 2 years of age were included in the study.
– The prevalence of stunting was found to be 35.1% among the children.
– Continued breastfeeding for 1 year was significantly associated with childhood stunting.
– Early initiation to breastfeeding and introduction of solid foods were not associated with stunting.

Study Recommendations:

– Supplementary feeding should be provided for children who are breastfed for ≥1 year.
– Further research is needed to explore other potential factors contributing to childhood stunting in Rwanda.

Key Role Players:

– National Institute of Statistics of Rwanda
– Ministry of Health
– Researchers and scientists specializing in child nutrition and public health

Cost Items for Planning Recommendations:

– Funding for supplementary feeding programs
– Research grants for further studies on childhood stunting
– Training and capacity building for healthcare professionals and community workers
– Monitoring and evaluation of the effectiveness of interventions
– Communication and awareness campaigns to promote optimal feeding practices

Force de la preuve

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is cross-sectional, which limits the ability to establish causality. Additionally, the sample size is relatively small (1,634 children) and may not be representative of the entire population. To improve the strength of the evidence, a longitudinal study design could be considered to establish temporal relationships between feeding practices and childhood stunting. Additionally, increasing the sample size and ensuring it is more representative of the population would enhance the generalizability of the findings. Finally, conducting further statistical analyses to control for potential confounders and exploring other factors that may contribute to childhood stunting would strengthen the evidence.

Abstrait

Study design: We obtained data from the 2010 Rwanda Demographic and Health Survey (RDHS) to assess the effects of feeding practices on stunting in children ≤ 2 years of age. The RDHS, which has a cross-sectional design, is performed every five years by the National Institute of Statistics of Rwanda and the Ministry of Health. The 2010 RDHS utilized a two-stage sampling process. In the first stage, 492 villages were randomly selected with a sampling probability proportional to the village size and were stratified by district. In the second stage, 26 households from each village were randomly selected. The response rate was 99.1% from females and 98.7% from males. A total of 8,605 children were included in the survey [ 6]. Anthropometrical measurements were obtained from 4,117 children <5 y of age. A total of 1,634 children were ≤ 2 years of age. Study variables: Based on WHO [7] and Rwandan [4] reports, this study hypothesized that feeding practices (i.e., early initiation to breastfeeding; exclusive breastfeeding; continued breastfeeding; and introduction of solid, semi-solid, or soft foods) are independent contributors of stunting in Rwandan children ≤ 2 years of age. Children, parental, and household characteristics were considered to be potential confounders; therefore, they were controlled for in our statistical model (Figure 1). Conceptual framework Primary outcome: Our main study outcome was the prevalence of stunting in children ≤ 2 years of age. Anthropometric measurements were converted into nutritional indices [8]. Height-for-age was used to measure childhood stunting; a -2 z-score was indicative of childhood stunting. Main predictors: feeding pattern indicators: The main predictors of interest, which were based on the WHO Infant and Young Child Feeding indicators, included early initiation of breastfeeding; exclusive breastfeeding under 6 months; continued breastfeeding at 1 year; and introduction of solid, semi-solid, or soft foods [9]. Early initiation of breastfeeding represents the number of children born in the previous 24 months who were breastfed within one hour post-childbirth. Early initiation to breastfeeding is considered to be protective due to the health benefits of colostrum in early breast milk. Exclusive breastfeeding under 6 months represents the number of 0 to 5-month-old infants who were exclusively breastfed. Introduction of solid, semi-solid, or soft foods represents the number of 6 to 8-month-old infants who were fed solid, semi-solid, or soft foods [9]. Potential socio-demographic confounders: The covariates in this study included children age and sex; maternal age, occupation, and education; family residence (urban vs. rural); number of household members; household family income/wealth index; and accessibility to potable drinking water and adequate sanitation facilities. Wealth index was assessed on the basis of de jure population asset data using principal components analysis. Wealth data were obtained from responses to questions on ownership of certain goods and housing characteristics (e.g., access to electricity and source of drinking water, amongst others) [6]. Statistical analyses: Data were analysed using Stata v13 software (StataCorp LP, College Station, TX, USA). Survey commands were used to account for the complex sample design and unequal sampling probability. The associations between feeding practices, socio-demographic variables, and childhood stunting were assessed by simple logistic regression. We tested for confounders using multiple logistic regression. Only variables that modified the coefficient of the outcome by ≥10% were included and controlled for in the final models. Socio-demographic variables that modified the childhood stunting coefficient by ≥10% were included in the multivariable model as potential confounders of the association between childhood stunting and feeding practices. The unadjusted model included childhood stunting and all feeding practice variables. The adjusted model controlled for socio-demographic potential confounders. Odds ratio (OR), 95% confidence interval (CI), and P-values were reported. Ethical consideration: Authorization to use the RDHS dataset was obtained through an online application. The researchers did not make any efforts to identify the survey participants.

Matériaux

N/A

Innovations

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information and support to pregnant women and new mothers. These apps can offer guidance on nutrition, breastfeeding, and child development, as well as reminders for prenatal and postnatal care appointments.

2. Telemedicine Services: Implement telemedicine services that allow pregnant women in remote areas to consult with healthcare professionals through video calls. This can help address the issue of limited access to healthcare facilities and provide timely advice and support.

3. Community Health Workers: Train and deploy community health workers who can provide education and support to pregnant women and new mothers in their local communities. These workers can offer guidance on nutrition, breastfeeding, and hygiene practices, as well as facilitate referrals to healthcare facilities when necessary.

4. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with access to essential maternal health services, such as prenatal care, delivery, and postnatal care. These vouchers can be distributed to women in need, particularly those from low-income backgrounds, to ensure they receive the necessary care.

5. Public Awareness Campaigns: Launch public awareness campaigns to educate communities about the importance of maternal health and the available services. These campaigns can focus on promoting early initiation of breastfeeding, exclusive breastfeeding, and proper nutrition during pregnancy and early childhood.

6. Maternal Health Clinics: Establish dedicated maternal health clinics that provide comprehensive care for pregnant women and new mothers. These clinics can offer prenatal check-ups, vaccinations, nutritional counseling, and postnatal care services in a single location, making it easier for women to access the care they need.

7. Maternity Waiting Homes: Set up maternity waiting homes near healthcare facilities to accommodate pregnant women who live far away. These homes can provide a safe and comfortable environment for women to stay in the weeks leading up to their due dates, ensuring they are close to the facility when it’s time to give birth.

8. Mobile Clinics: Deploy mobile clinics equipped with basic maternal health services to reach underserved areas. These clinics can travel to remote communities and provide prenatal check-ups, vaccinations, and health education to pregnant women who may not have easy access to healthcare facilities.

9. Partnerships with Non-Governmental Organizations (NGOs): Collaborate with NGOs that specialize in maternal health to leverage their expertise and resources. These partnerships can help expand access to maternal health services, improve community outreach, and provide additional support to pregnant women and new mothers.

10. Health Education Programs: Implement comprehensive health education programs in schools and communities to raise awareness about maternal health and promote healthy practices. These programs can include workshops, seminars, and educational materials that focus on the importance of proper nutrition, breastfeeding, and prenatal and postnatal care.

AI Innovations Description

Based on the study titled “Early feeding practices and stunting in Rwandan children: A cross-sectional study from the 2010 Rwanda demographic and health survey,” the recommendation to improve access to maternal health is to provide supplementary feeding for children who are breastfed for one year or more.

The study found that breastfeeding for one year increased the risk of childhood stunting. However, early initiation to breastfeeding and introduction of solid foods were not significantly associated with childhood stunting.

To implement this recommendation, healthcare providers and policymakers can focus on promoting and supporting supplementary feeding for children who are breastfed for one year or more. This can be done through education and awareness campaigns targeting mothers and caregivers, providing resources and guidance on appropriate complementary feeding practices, and ensuring access to nutritious foods for young children.

It is important to note that this recommendation is based on the specific findings of the study mentioned and may need to be adapted to the local context and resources available in order to effectively improve access to maternal health.

AI Innovations Methodology

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

1. Strengthening healthcare infrastructure: Investing in healthcare facilities, equipment, and trained healthcare professionals can improve access to maternal health services. This includes establishing well-equipped maternity clinics and hospitals, ensuring the availability of essential medical supplies, and training healthcare providers in maternal health care.

2. Mobile health (mHealth) interventions: Utilizing mobile technology to provide maternal health information, reminders, and access to healthcare services can help overcome geographical barriers and improve access to maternal health. This can include mobile apps, SMS reminders for prenatal care appointments, and telemedicine consultations.

3. Community-based interventions: Implementing community-based programs that focus on maternal health education, awareness, and support can improve access to maternal health services. This can involve training community health workers to provide basic maternal health services, conducting awareness campaigns, and establishing support groups for pregnant women.

4. Financial incentives: Providing financial incentives, such as cash transfers or subsidies, to pregnant women and their families can help reduce financial barriers to accessing maternal health services. This can include covering the costs of prenatal care, delivery, and postnatal care.

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

1. Define the target population: Identify the specific population group that the recommendations aim to benefit, such as pregnant women in a specific region or country.

2. Collect baseline data: Gather data on the current access to maternal health services, including factors such as healthcare infrastructure, availability of healthcare providers, utilization rates, and financial barriers.

3. Define indicators: Determine the key indicators that will be used to measure the impact of the recommendations, such as the number of pregnant women accessing prenatal care, the percentage of deliveries attended by skilled healthcare providers, or the reduction in maternal mortality rates.

4. Develop a simulation model: Create a simulation model that incorporates the recommendations and their potential impact on the defined indicators. This model can take into account factors such as population size, geographical distribution, healthcare infrastructure, and financial resources.

5. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to assess the potential impact of the recommendations on the defined indicators. This can involve adjusting variables such as the scale of implementation, coverage rates, and resource allocation.

6. Analyze results: Analyze the simulation results to determine the projected impact of the recommendations on improving access to maternal health. This can include assessing changes in the defined indicators, identifying potential challenges or limitations, and evaluating the cost-effectiveness of the recommendations.

7. Refine and validate the model: Continuously refine and validate the simulation model based on new data, feedback, and real-world implementation experiences. This can help improve the accuracy and reliability of the simulations and inform decision-making processes.

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

Auteurs et co-auteurs

Statistics:

Citations: 3

Authors: 6

Identifiers:

DOI: 10.11604/pamj.2018.29.157.10151

Research Areas:

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

Study Countries:

Rwanda

Study Design:

Case-Control Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female

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