Developmental performance of hospitalized severely acutely malnourished under-six children in low- income setting

BMC Pediatrics, Volume 17, No. 1, Year 2017

Interpretation

Background: Retrospective studies show that severe acute malnutrition (SAM) affects child development. However, to what extent SAM affects children of different ages at its acute stage is not well documented. This study was aimed at comparing the developmental performance of severely acutely malnourished children under six with that of age and gender-matched non-malnourished healthy children. Methods: The developmental performances of 310 children with SAM (male = 155, female = 155); mean age = 30.7 mo; SD = 15.2 mo) admitted to the nutritional rehabilitation unit (NRU) at Jimma University’s Hospital was compared with that of 310 age and gender-matched, non-malnourished healthy children (male = 155, female = 155; mean age = 29.6 mo; SD = 15.4 mo) living in Jimma Town in Ethiopia. Two culturally adapted tools were used: (1) the Denver II-Jimma, to assess the children’s performance on personal social (PS), fine motor (FM) language (LA), gross motor (GM) skills, and (2) the Ages and Stages Questionnaires: Social-Emotional (ASQ:SE), to assess social-emotional (SE) skills. Multivariable Poisson regression analysis was conducted to compare the developmental performance scores of SAM and non-malnourished children. Results: For one-year-old children, SAM delays their developmental performance on GM, FM, PS and LA by 300%, 200%, 140% and 71.4% respectively. For three-years-old children, SAM delays their developmental performance on GM by 80%, on FM and LA by 50% each, and on PS by 28.6%. Of the skills assessed on Denver II-Jimma, GM is the most, and PS is the least affected. Younger SAM children are more affected than older ones on all the domains of development. The delay in FM, GM, LA and PS generally decreases with an increase in age. Social-emotional behavior problems seem to be most pronounced in the very young and older age ranges. Conclusions: SAM has a differential age effect on the different dimensions of development in children under 6 years of age. The study was conducted in Jimma Zone, south west Ethiopia. According to the 2007 census [33], Jimma Zone has 17 districts having a population of 2,486,155 (50.3% male). Majority (94.5%) live in rural areas on subsistence agriculture; 2,129,321 (85.6%) are followers of Islam. The zonal capital, Jimma Town, has a population of 120,960 (50.3% male). The majority (56,661 or 46.8%) of residents of Jimma Town are Orthodox Christians; 47,205, or 39% are Muslims, and 15,799 or 13.1% are protestant Christians. Cross-sectional data were collected from both severely acutely malnourished (SAM) and non-malnourished healthy children. SAM children admitted to hospital for treatment were recruited with a non-probability convenient sampling. Age and gender matched non-malnourished healthy children were selected purposefully from families with middle or high socio-economic status assumed to be suitable for optimal child development. The SAM and the non-malnourished groups were assessed using culturally adapted tools and compared on five different areas of child development. A total of 826 SAM children were coming from nearby districts in Jimma Zone and admitted to the nutritional rehabilitation unit (NRU) at the pediatric ward of Jimma University’s Specialized Referral Teaching Hospital from 8/02/2011 to 28/04/2013. Only 310 (155 male, 155 female) children (mean age = 30.7 mo; SD = 15.2 mo; range = 3.1—65.7 mo) were involved in the study (see Fig. 1). Inclusion criteria were based primarily on a protocol prepared by the Ethiopian Federal Ministry of Health [34]: children (a) whose wasting was severe (weight-for-height [W/H] less than 70%, National Centre for Health Statistics (NCHS) [35]), or (b) with a low mid upper arm circumference (MUAC), i.e., MUAC less than 110 mm with a length greater than 65 cm; or, (c) having bilateral pitting edema. Only 3 months to 6 years of age children living within accessible driving and/or walking distance in the different districts of Jimma Zone were included. In case of twins, only one child was randomly chosen. Children with obvious disabilities, mobility problems and sensory impairments (hearing and visual problems) were excluded. Selection of study participants Of the three phases (stabilization, transition and rehabilitation) in the treatment of SAM children [34], developmental and anthropometric assessment were made during the transition phase. SAM patients cannot be tested during the first phase since they are without adequate appetite and /or have severe medical complications. Assessment was made when the patients had good appetite and no major medical complications. From a total of 1682 apparently healthy children under six who belong to families with middle or higher socio-economic status in Jimma Town, 310 children were selected and matched for age and gender with the severely malnourished children. Parental socio-economic status was determined using child’s access to preschool education as a proxy. The children of parents not affording payment for preschool education were excluded assuming that they belong to lower socio-economic status. A-10-point checklist was used to exclude the following potentially developmentally at-risk children: prematurely born, birth weight less than 2500 g, very tiny body at birth, instrumentally delivered, or delivered after 24 h of labor, born with chronic health problem, sick during the first year after birth, having observable impairments affecting sight or/and hearing, or/and mobility, having a mother who was seriously sick during pregnancy. In case of twins, one child was randomly excluded. Children suspected to be malnourished were excluded using weight-for-age and MUAC z-scores in line with WHO 2006 child growth standards [36]. Five areas of child development were looked into: fine motor (FM), gross motor (GM), language (LA), personal social (PS) and social-emotional (SE) skills. The first four were assessed using the Denver II-Jimma [37]: a tool adapted to the Jimma context from the Denver II [38]. No test item was dropped during the adaptation. Test item administration and raw scoring is similar as in Denver II [39]. For each domain, the number of test items successfully performed by a child was counted. The SE competences (self-regulation, adaptive functioning, affect, compliance, autonomy, interaction with people and communication behaviors) were assessed using parent completed Ages and Stages Questionnaire: Social-Emotional (ASQ:SE) [40] adapted to the study context (unpublished). For each item, a score equals zero if no problem is reported. A total score below an age specific cutoff indicates a typical behavior of a child, and above this cutoff indicates a presence of social-emotional problems. Socio-demographic variables such as maternal education, socio-economic status, child sex and age were documented through a structured questionnaire because they were identified in earlier studies [41–44] as potential predictors of child developmental outcomes. Electronic digital weight scale and MUAC tape were used respectively to measure weight and MUAC of children. Data were collected by five pairs of clinical nurses trained in anthropometric measurements and administrations of the ASQ:SE and Denver II-Jimma test items. The testing procedure was as follows: 1) interviewing parents or caregivers using a questionnaire on socio-demographic information, and the ASQ:SE; 2) testing the child with the Denver II-Jimma test; and, 3) finally, measuring weight and then MUAC. The primary goal was to investigate whether developmental performances of severely malnourished and non-malnourished children differ. The five developmental outcomes were summarized as count scores. Hence, Poisson regression was fitted to the data, and a negative binomial regression, in case of over dispersion. A step-wise selection procedure was employed to find the most parsimonious model. In the first step, the regression model included maternal religion, a child’s gender, age and nutritional status as explanatory variables. In the second step, only the significant terms in the first step were kept and the evolutions of developmental performance with age was allowed to be curvi-linear (possibly a quadratic association). Furthermore, interactions of the child’s nutritional status with maternal religion, with a child’s gender and age were allowed to examine mediating effects. A significant level of 5% was used. This model building was done for all of the five developmental domains separately. The parsimonious model comprised age as both linear term and quadratic term, nutritional status and their interactions. Ideally, the difference in developmental performance between malnourished and non-malnourished children was also corrected for maternal education and socio-economic status.Earlier studies have shown association of maternal education with a number of factors such as economic condition [45] and severe malnutrition [46]. But the strong collinearity between these covariates makes the results of a multiple regression model including these factors together untrustworthy. Therefore, for each developmental performance, we opted to investigate three regression models, each focusing on one of these predictors at a time. Model I (as discussed above) studied the relationship between the developmental performance and the nutritional status, Model II between the developmental performance and family socio-economic status, and Model III between the developmental performance and maternal education. In line with the primary objective of this study, more attention was given to model I. To estimate the delay in developmental performance of SAM children on the different domains of the Denver II-Jimma scale, the number of test items performed by SAM and non-malnourished children at ages three to 70 months were predicted from the regression model. The difference in age of attaining equal number of test items was calculated as an index of developmental delay. A weighted score was calculated by dividing the delay index by the age at which the non-malnourished children perform the same number of items performed by the SAM children. The weighted scores were also converted into percentages, and used for comparisons of different domains at different ages. An index to quantify social-emotional problems was computed by subtracting the total ASQ:SE scores of the healthy children from that of SAM children at median ages on eight age groups (6, 12, 18, 23.5, 29.5, 37.5, 47.5, 59.5 months). Dividing this problem behavior index by the respective median age resulted in a weighted index. The index was also converted into percentages. The age-specific cutoff was also subtracted from the mean score of SAM child at median age and then divided by the cutoff. This also produced an alternative standard score to determine the deviation of SAM children’s score from the cutoff score. The statistical analysis was performed using STATA Software: Release 12 [47].

AI Digest

Study Justification:

This study aimed to investigate the developmental performance of severely acutely malnourished children under the age of six in a low-income setting. The study aimed to compare the developmental performance of these children with that of age and gender-matched non-malnourished healthy children. The study is important because it provides valuable information on the extent to which severe acute malnutrition affects child development at different ages. This information can help inform interventions and policies aimed at improving the developmental outcomes of malnourished children.

Study Highlights:

– The study included 310 severely acutely malnourished children and 310 age and gender-matched non-malnourished healthy children.
– Developmental performances were assessed using culturally adapted tools, including the Denver II-Jimma and Ages and Stages Questionnaires: Social-Emotional.
– The study found that severe acute malnutrition delays developmental performance in children under the age of six.
– The delay in developmental performance varied across different domains, with gross motor skills being the most affected and personal social skills being the least affected.
– Younger children were more affected by malnutrition than older children, and the delay in developmental performance generally decreased with age.
– Social-emotional behavior problems were more pronounced in very young and older children.

Recommendations for Lay Reader:

– The study shows that severe acute malnutrition can have a negative impact on the development of children under the age of six.
– It is important to identify and treat malnutrition in children as early as possible to minimize the developmental delays.
– Interventions should focus on improving gross motor skills, fine motor skills, language skills, and personal social skills in malnourished children.
– Parents and caregivers should be aware of the potential social-emotional behavior problems in malnourished children and provide appropriate support and intervention.

Recommendations for Policy Maker:

– Policies and programs should prioritize the prevention and treatment of severe acute malnutrition in children under the age of six.
– Health facilities should be equipped to identify and treat malnutrition in children, with a focus on early intervention.
– Training programs should be implemented to educate healthcare providers on the assessment and management of malnutrition-related developmental delays.
– Resources should be allocated to support interventions aimed at improving the developmental outcomes of malnourished children, including access to nutritional rehabilitation units and culturally adapted assessment tools.

Key Role Players:

– Healthcare providers: Trained professionals who can assess and manage malnutrition-related developmental delays.
– Parents and caregivers: Play a crucial role in providing support and intervention for malnourished children.
– Policy makers: Responsible for implementing policies and allocating resources to address the developmental needs of malnourished children.
– Researchers: Conduct further studies to explore effective interventions and strategies for improving the developmental outcomes of malnourished children.

Cost Items for Planning Recommendations:

– Training programs for healthcare providers: Budget for training sessions and materials.
– Nutritional rehabilitation units: Budget for equipment, staffing, and maintenance.
– Culturally adapted assessment tools: Budget for the development and distribution of assessment tools.
– Awareness campaigns: Budget for materials and outreach activities to educate parents and caregivers about the importance of early intervention and support for malnourished children.
– Research funding: Budget for conducting further studies to inform evidence-based interventions and policies.

Strength of Evidence

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because the study was conducted with a large sample size of 310 severely acutely malnourished children and 310 age and gender-matched non-malnourished healthy children. The study used culturally adapted tools to assess the developmental performance of the children in five different areas. The results showed significant delays in developmental performance for severely malnourished children compared to non-malnourished children. However, to improve the evidence, the study could have included a control group of malnourished children who did not receive treatment to compare the effects of treatment on developmental performance. Additionally, the study could have included a follow-up assessment to determine if the developmental delays persisted over time.

Abstract

The study was conducted in Jimma Zone, south west Ethiopia. According to the 2007 census [33], Jimma Zone has 17 districts having a population of 2,486,155 (50.3% male). Majority (94.5%) live in rural areas on subsistence agriculture; 2,129,321 (85.6%) are followers of Islam. The zonal capital, Jimma Town, has a population of 120,960 (50.3% male). The majority (56,661 or 46.8%) of residents of Jimma Town are Orthodox Christians; 47,205, or 39% are Muslims, and 15,799 or 13.1% are protestant Christians. Cross-sectional data were collected from both severely acutely malnourished (SAM) and non-malnourished healthy children. SAM children admitted to hospital for treatment were recruited with a non-probability convenient sampling. Age and gender matched non-malnourished healthy children were selected purposefully from families with middle or high socio-economic status assumed to be suitable for optimal child development. The SAM and the non-malnourished groups were assessed using culturally adapted tools and compared on five different areas of child development. A total of 826 SAM children were coming from nearby districts in Jimma Zone and admitted to the nutritional rehabilitation unit (NRU) at the pediatric ward of Jimma University’s Specialized Referral Teaching Hospital from 8/02/2011 to 28/04/2013. Only 310 (155 male, 155 female) children (mean age = 30.7 mo; SD = 15.2 mo; range = 3.1—65.7 mo) were involved in the study (see Fig. 1). Inclusion criteria were based primarily on a protocol prepared by the Ethiopian Federal Ministry of Health [34]: children (a) whose wasting was severe (weight-for-height [W/H] less than 70%, National Centre for Health Statistics (NCHS) [35]), or (b) with a low mid upper arm circumference (MUAC), i.e., MUAC less than 110 mm with a length greater than 65 cm; or, (c) having bilateral pitting edema. Only 3 months to 6 years of age children living within accessible driving and/or walking distance in the different districts of Jimma Zone were included. In case of twins, only one child was randomly chosen. Children with obvious disabilities, mobility problems and sensory impairments (hearing and visual problems) were excluded. Selection of study participants Of the three phases (stabilization, transition and rehabilitation) in the treatment of SAM children [34], developmental and anthropometric assessment were made during the transition phase. SAM patients cannot be tested during the first phase since they are without adequate appetite and /or have severe medical complications. Assessment was made when the patients had good appetite and no major medical complications. From a total of 1682 apparently healthy children under six who belong to families with middle or higher socio-economic status in Jimma Town, 310 children were selected and matched for age and gender with the severely malnourished children. Parental socio-economic status was determined using child’s access to preschool education as a proxy. The children of parents not affording payment for preschool education were excluded assuming that they belong to lower socio-economic status. A-10-point checklist was used to exclude the following potentially developmentally at-risk children: prematurely born, birth weight less than 2500 g, very tiny body at birth, instrumentally delivered, or delivered after 24 h of labor, born with chronic health problem, sick during the first year after birth, having observable impairments affecting sight or/and hearing, or/and mobility, having a mother who was seriously sick during pregnancy. In case of twins, one child was randomly excluded. Children suspected to be malnourished were excluded using weight-for-age and MUAC z-scores in line with WHO 2006 child growth standards [36]. Five areas of child development were looked into: fine motor (FM), gross motor (GM), language (LA), personal social (PS) and social-emotional (SE) skills. The first four were assessed using the Denver II-Jimma [37]: a tool adapted to the Jimma context from the Denver II [38]. No test item was dropped during the adaptation. Test item administration and raw scoring is similar as in Denver II [39]. For each domain, the number of test items successfully performed by a child was counted. The SE competences (self-regulation, adaptive functioning, affect, compliance, autonomy, interaction with people and communication behaviors) were assessed using parent completed Ages and Stages Questionnaire: Social-Emotional (ASQ:SE) [40] adapted to the study context (unpublished). For each item, a score equals zero if no problem is reported. A total score below an age specific cutoff indicates a typical behavior of a child, and above this cutoff indicates a presence of social-emotional problems. Socio-demographic variables such as maternal education, socio-economic status, child sex and age were documented through a structured questionnaire because they were identified in earlier studies [41–44] as potential predictors of child developmental outcomes. Electronic digital weight scale and MUAC tape were used respectively to measure weight and MUAC of children. Data were collected by five pairs of clinical nurses trained in anthropometric measurements and administrations of the ASQ:SE and Denver II-Jimma test items. The testing procedure was as follows: 1) interviewing parents or caregivers using a questionnaire on socio-demographic information, and the ASQ:SE; 2) testing the child with the Denver II-Jimma test; and, 3) finally, measuring weight and then MUAC. The primary goal was to investigate whether developmental performances of severely malnourished and non-malnourished children differ. The five developmental outcomes were summarized as count scores. Hence, Poisson regression was fitted to the data, and a negative binomial regression, in case of over dispersion. A step-wise selection procedure was employed to find the most parsimonious model. In the first step, the regression model included maternal religion, a child’s gender, age and nutritional status as explanatory variables. In the second step, only the significant terms in the first step were kept and the evolutions of developmental performance with age was allowed to be curvi-linear (possibly a quadratic association). Furthermore, interactions of the child’s nutritional status with maternal religion, with a child’s gender and age were allowed to examine mediating effects. A significant level of 5% was used. This model building was done for all of the five developmental domains separately. The parsimonious model comprised age as both linear term and quadratic term, nutritional status and their interactions. Ideally, the difference in developmental performance between malnourished and non-malnourished children was also corrected for maternal education and socio-economic status.Earlier studies have shown association of maternal education with a number of factors such as economic condition [45] and severe malnutrition [46]. But the strong collinearity between these covariates makes the results of a multiple regression model including these factors together untrustworthy. Therefore, for each developmental performance, we opted to investigate three regression models, each focusing on one of these predictors at a time. Model I (as discussed above) studied the relationship between the developmental performance and the nutritional status, Model II between the developmental performance and family socio-economic status, and Model III between the developmental performance and maternal education. In line with the primary objective of this study, more attention was given to model I. To estimate the delay in developmental performance of SAM children on the different domains of the Denver II-Jimma scale, the number of test items performed by SAM and non-malnourished children at ages three to 70 months were predicted from the regression model. The difference in age of attaining equal number of test items was calculated as an index of developmental delay. A weighted score was calculated by dividing the delay index by the age at which the non-malnourished children perform the same number of items performed by the SAM children. The weighted scores were also converted into percentages, and used for comparisons of different domains at different ages. An index to quantify social-emotional problems was computed by subtracting the total ASQ:SE scores of the healthy children from that of SAM children at median ages on eight age groups (6, 12, 18, 23.5, 29.5, 37.5, 47.5, 59.5 months). Dividing this problem behavior index by the respective median age resulted in a weighted index. The index was also converted into percentages. The age-specific cutoff was also subtracted from the mean score of SAM child at median age and then divided by the cutoff. This also produced an alternative standard score to determine the deviation of SAM children’s score from the cutoff score. The statistical analysis was performed using STATA Software: Release 12 [47].

Materials

https://efashare.b-cdn.net/materials/3cb719c3c866f2924452b36d9c83e085b54170d6865431504ed07e25176ba6eb/12887_2017_950_MOESM1_ESM.docx

Innovations

Based on the provided description, it seems that the study focused on comparing the developmental performance of severely acutely malnourished children under six years old with that of non-malnourished healthy children. The study used culturally adapted tools to assess the children’s performance in different areas of development, such as fine motor skills, gross motor skills, language skills, personal social skills, and social-emotional skills.

To improve access to maternal health, some potential innovations or recommendations based on the study findings could include:

1. Early identification and intervention: Implementing screening programs to identify malnourished children at an early stage and providing appropriate interventions to prevent developmental delays.

2. Nutritional rehabilitation units: Establishing specialized units or centers within hospitals or healthcare facilities that focus on the nutritional rehabilitation of severely malnourished children. These units can provide comprehensive care, including medical treatment, nutritional support, and developmental interventions.

3. Training healthcare providers: Providing training and education to healthcare providers on the assessment and management of malnutrition and its impact on child development. This can help improve the quality of care provided to malnourished children and ensure early detection of developmental delays.

4. Community-based interventions: Implementing community-based programs that focus on improving nutrition and child development. These programs can involve community health workers or volunteers who provide education and support to families, promote healthy nutrition practices, and monitor child development.

5. Integration of services: Integrating maternal health services with nutrition and child development services to ensure a holistic approach to care. This can include providing antenatal and postnatal care, nutrition counseling, and developmental assessments as part of routine maternal health visits.

6. Awareness and education: Conducting awareness campaigns and educational programs to increase knowledge and understanding of the importance of maternal nutrition and its impact on child development. This can help empower mothers and caregivers to make informed decisions regarding nutrition and child care.

It is important to note that these recommendations are based on the provided description and may need to be further evaluated and adapted to the specific context and resources available in the target setting.

AI Innovations Description

The study described in the provided text focuses on the developmental performance of severely acutely malnourished children under the age of six in a low-income setting. The study compares the developmental performance of these malnourished children with that of age and gender-matched non-malnourished healthy children. The study was conducted in Jimma Zone, southwest Ethiopia.

The study used culturally adapted tools to assess the developmental performance of the children in five areas: fine motor skills, gross motor skills, language skills, personal social skills, and social-emotional skills. The results of the study showed that severe acute malnutrition (SAM) has a differential age effect on the different dimensions of development in children under six years of age. Younger SAM children are more affected than older ones, and the delay in developmental performance generally decreases with an increase in age.

The study provides valuable insights into the impact of severe acute malnutrition on child development in low-income settings. The findings highlight the need for interventions and innovations to improve access to maternal health and nutrition services to prevent and address severe acute malnutrition in young children. By addressing the underlying causes of malnutrition and providing appropriate care and support, it is possible to improve the developmental outcomes of children in these settings.

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 the development and improvement of healthcare facilities, particularly in low-income settings, can help ensure that pregnant women have access to quality maternal health services. This includes building and equipping hospitals, clinics, and maternity centers, as well as training healthcare professionals to provide comprehensive maternal care.

2. Increasing awareness and education: Implementing community-based education programs can help raise awareness about the importance of maternal health and encourage women to seek prenatal and postnatal care. This can be done through health campaigns, workshops, and the distribution of educational materials in local languages.

3. Improving transportation and logistics: In many low-income settings, lack of transportation can be a major barrier to accessing maternal health services. Implementing transportation solutions such as ambulances, mobile clinics, or community transport systems can help overcome this challenge and ensure that pregnant women can reach healthcare facilities in a timely manner.

4. Enhancing telemedicine and digital health solutions: Utilizing telemedicine and digital health technologies can help improve access to maternal health services, especially in remote or underserved areas. This can include teleconsultations, mobile health applications, and remote monitoring devices to provide prenatal care, postnatal care, and health education.

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

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the number of pregnant women receiving prenatal care, the number of deliveries attended by skilled birth attendants, or the distance traveled to reach a healthcare facility.

2. Collect baseline data: Gather data on the current status of maternal health access in the target area. This can be done through surveys, interviews, or existing health records.

3. Develop a simulation model: Create a simulation model that incorporates the recommended interventions and their potential impact on the identified indicators. This model should take into account factors such as population demographics, healthcare infrastructure, transportation availability, and community engagement.

4. Input intervention parameters: Define the parameters of each intervention, such as the number of healthcare facilities to be built, the coverage of education programs, the frequency of transportation services, or the reach of telemedicine technologies.

5. Run simulations: Use the simulation model to run different scenarios, varying the parameters of the interventions. This will allow for the estimation of the potential impact of each intervention on the selected indicators.

6. Analyze results: Analyze the simulation results to determine the effectiveness of each intervention in improving access to maternal health. Compare the scenarios to identify the most impactful interventions and their potential synergies.

7. Refine and validate the model: Continuously refine and validate the simulation model based on real-world data and feedback from stakeholders. This will ensure that the model accurately represents the context and provides reliable predictions.

By following this methodology, policymakers and healthcare providers can make informed decisions about which interventions to prioritize and invest in to improve access to maternal health in low-income settings.

Author

Dima Health

Statistics:

Citations: 7

Identifiers:

DOI: 10.1186/s12887-017-0950-5

Research Areas:

Disability, 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:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Male & Female