Factors associated with anaemia among preschool- age children in underprivileged neighbourhoods in Antananarivo, Madagascar

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Study Justification:
– Anaemia is a prevalent public health problem in low-income countries, including Madagascar.
– Data on risk factors for anaemia in underprivileged neighborhoods in Antananarivo, Madagascar are lacking.
– This study aims to investigate the factors associated with anaemia in preschool-age children in underprivileged neighborhoods in Antananarivo.
Study Highlights:
– The study analyzed data collected as part of the AFRIBIOTA project, which focused on the pathophysiology of environmental enteric dysfunction (EED) in Antananarivo and Bangui.
– The study included 414 children aged 24 to 59 months from underprivileged areas of Antananarivo.
– The prevalence of anaemia among the children was found to be 24.4%.
– Older children were less likely to have anaemia, while those with iron deficiency and high levels of faecal calprotectin were more likely to have anaemia.
Recommendations for Lay Reader and Policy Maker:
– National strategies should prioritize improving children’s dietary quality and micronutrient intake to reduce anaemia in underprivileged areas.
– Existing measures should be expanded to include efforts to reduce infectious disease burden, which can contribute to anaemia.
Key Role Players:
– Ministry of Public Health in Madagascar
– Community health workers
– Health care facilities (Centre de Santé Maternelle et Infantile de Tsaralalana, Centre Hospitalier Universitaire Mère Enfant de Tsaralalana, Centre Hospitalier Universitaire Joseph Ravoahangy Andrianavalona)
– Clinical Biology Center of the Institut Pasteur de Madagascar
– Hôpital Universitaire Necker-Enfants Malades, Paris
– Service de Coprologie Fonctionnelle, Hôpital Salpêtrière Paris
Cost Items for Planning Recommendations:
– Dietary quality improvement programs
– Micronutrient supplementation programs
– Infectious disease prevention and control measures
– Training and capacity building for healthcare professionals
– Monitoring and evaluation of interventions
– Public awareness campaigns and education materials

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a secondary analysis of data collected as part of a well-designed project. The study includes a large sample size and uses logistic regression modeling to identify factors associated with anaemia. The findings are supported by statistical analysis and provide actionable steps to improve the situation, such as improving children’s dietary quality and micronutrient intake. To improve the evidence, the abstract could provide more details about the methodology used in the data collection and analysis, as well as the limitations of the study.

Background: Anaemia occurs in children when the haemoglobin level in the blood is less than the normal (11 g/dL), the consequence is the decrease of oxygen quantity in the tissues. It is a prevalent public health problem in many low-income countries, including Madagascar, and data on risk factors are lacking. We used existing data collected within the pathophysiology of environmental enteric dysfunction (EED) in Madagascar and the Central African Republic project (AFRIBIOTA project) conducted in underprivileged neighbourhoods of Antananarivo to investigate the factors associated with anaemia in children 24 to 59 months of age. Methods: Children included in the AFRIBIOTA project in Antananarivo for whom data on haemoglobin and ferritin concentrations were available were included in the study. Logistic regression modelling was performed to identify factors associated with anaemia. Results: Of the 414 children included in this data analysis, 24.4% were found to suffer from anaemia. We found that older children (adjusted OR: 0.95; 95% CI: 0.93–0.98) were less likely to have anaemia. Those with iron deficiency (adjusted OR: 6.1; 95% CI: 3.4–11.1) and those with a high level of faecal calprotectin (adjusted OR: 2.5; 95% CI: 1.4–4.4) were more likely to have anaemia than controls. Conclusions: To reduce anaemia in the children in this underprivileged area, more emphasis should be given to national strategies that improve children’s dietary quality and micronutrient intake. Furthermore, existing measures should be broadened to include measures to reduce infectious disease burden.

This study conducts a secondary analysis of data collected as part of the AFRIBIOTA project, a translational study of the pathophysiology of EED performed in the two African cities of Antananarivo (Madagascar) and Bangui (Central African Republic). Details of the project objectives and methodology of the AFRIBIOTA project are provided elsewhere [14]. AFRIBIOTA is a case–control study of stunting in which 260 stunted children and 200 age- and sex-matched nonstunted children were recruited in each country. Data collection for the AFRIBIOTA project was conducted from November 2016 to March 2018. Children from 24 to 59 months of age with no obvious signs of severe disease and with negative HIV serology were recruited. The recruitment was mainly community-based and was conducted in underprivileged areas of the Urban Commune of Antananarivo (Andranomanalina Isotry, Ankasina and their surrounding neighbourhoods) and in three health care facilities (The Centre de Santé Maternelle et Infantile de Tsaralalana (CSMI), the Centre Hospitalier Universitaire Mère Enfant de Tsaralalana and the paediatric surgery department of the Centre Hospitalier Universitaire Joseph Ravoahangy Andrianavalona). This secondary data analysis focuses on the children living in Antananarivo who were recruited from the community setting. Children included in the AFRIBIOTA project in Antananarivo and for whom data on haemoglobin and ferritin concentrations were available were included in this secondary analysis (Fig. 1). Flow chart of the study participants Data were collected by interviewing mothers/closest caregivers and using a standardized questionnaire. Anthropometric measurements were performed by trained health professionals; blood and stool samples were also collected. Screening and recruitment were conducted at the community level with the support of community health workers. The interviews and the collection of biological samples were conducted at the hospital centres: Centre Hospitalo-Universitaire Mère Enfant de Tsaralalana and Centre Hospitalo-Universitaire Joseph Ravoahangy Andrianavalona. Each child’s weight was measured twice to the nearest 0.1 kg using an electronic scale (KERN, ref. MGB 150 K100 and EKS, People’s Republic of China). When the difference in the two measurements exceeded 0.1 kg, another measurement was performed until the last three values did not differ by more than 0.1 kg. Each child’s height was measured to the nearest 0.1 cm with the child in a standing position using collapsible height boards (ShorrBoard® Infant/Child/Adult Measuring Board, MD, USA). The same procedure was followed for each child to ensure consistent measurement. For both indicators, the mean of the two or three values obtained was reported. Venous blood samples (2 mL) were collected and used in complete blood count, C-reactive protein (CRP), ferritin and citrulline analysis. They were collected in Microtainer® tubes containing ethylenediamine tetraacetic acid (EDTA) and sent at + 4 °C to the Clinical Biology Center of the Institut Pasteur de Madagascar (IPM) within 1 hour after blood collection. One hundred microlitres (100 μL) of plasma was extracted from each sample of whole blood, stored at − 80 °C and sent to the Hôpital Universitaire Necker-Enfants Malades, Paris for citrulline testing. A clean, dry plastic container was given to the mother/caregiver of each child for stool sample collection with detailed instructions on how to collect fresh stool samples. Part of each stool sample was sent to the Unité de Bactériologie expérimentale at IPM as soon as possible for the detection of intestinal parasites. The remainder of each stool sample was stored in liquid nitrogen in the field and shipped to IPM for storage at − 80 °C. An aliquot of each sample was shipped on dry ice to the Service de Coprologie Fonctionnelle, Hôpital Salpétrière Paris for measurement of calprotectin and alpha-antitrypsin levels. The questionnaire collected individual data about each child (diseases requiring hospital admission during the year prior to the survey, feeding practices (age at introduction of complementary feeding, age at cessation of breastfeeding, 24-hour recall)) and about the child’s mother (education level, nutritional status). Household data, including type of housing and amount of household assets, were also collected. A detailed description of the questionnaire is given in [15]. The complete blood count, including haemoglobin assessment, was performed on a SYSMEX autoanalyser (XN 1000 or XT-2000 i) (Landskrona, Sweden) using the fluorocytometric technique. Plasma CRP concentrations were assessed using an enzyme-linked immunosorbent assay (ELISA). Plasma ferritin concentrations were assessed on the ARCHITECT machine (Abbott, IL, USA) using a chemiluminescent microparticle immunoassay (CMIA). These analyses were performed according to standard procedures at the Clinical Biology Centre of IPM (ISO18189 certification). Citrulline was measured by liquid chromatography coupled to tandem mass spectrometry (UPLC–MS/MS) at the Laboratoire de Biochimie Métabolomique et Protéomique, Hôpital Universitaire Necker-Enfants Malades, Paris. For accurate quantification, a stable isotope internal standard of the same structure (purchased from Eurisotop, Saint Aubin, France) was added to the sample before protein precipitation. Before analysis, the samples were derivatized using the AccQ Tag™ Ultra (Waters Corporation, Milford, MA, USA) according to the manufacturer’s recommendations. Amino acid separation was performed on an Acquity™ UPLC system using a CORTECS™ UPLC C18 column (1.6 μm, 2.1 × 150 mm) coupled to a microTQS™ tandem mass spectrometer (Waters Corporation, Milford, MA, USA). Faecal calprotectin was assayed using a “sandwich”-type ELISA that uses a polyclonal Ab system (Calprest; Eurospital). The concentration of α1 antitrypsin (AAT) in faeces was measured using an immunonephelemetric method adapted on the BN ProSpec system (Siemens) [16]. The analysis of these faecal biomarkers was conducted at the Service de Coprologie Fonctionnelle, Hôpital Salpétrière Paris. All faecal samples were physically examined and screened for intestinal parasites as previously described [17]. The main variable of interest was the occurrence of anaemia. Anaemia was defined according to the WHO criteria [18] as Hb less than 110 g/l (adjusted for altitude). Age, sex and height and the 2006 WHO Child Growth Standards for children 24 to 59 months of age [19] were used to calculate children’s height-for-age z scores, which were used to define stunting and normal growth. Stunting and normal growth were defined as height-for-age z score  − 2 SD, respectively. Anaemia was defined as severe when the child’s Hb level was less than 70 g/l and moderate at Hb levels between 70 g/l and 99 g/l. Anaemia was defined as mild if the child’s Hb level was between 100 g/l and 109 g/l [1]. A dietary diversity score (DDS) was calculated by counting the number of food groups consumed by the child during the 24-hour period prior to the survey. The WHO recommends basing the DDS on seven food groups: (1) grains, roots and tubers; (2) legumes and nuts; (3) dairy products; (4) flesh foods (meats/fish/poultry); (5) eggs; (6) vitamin A-rich fruits and vegetables; and (7) other fruits and vegetables. A diverse diet is defined as one that has a DDS of at least four. Accordingly, children with a DDS < 4 were classified as having low dietary diversity; otherwise, they were considered to have an adequate diet [20]. The body mass index (BMI) of the mothers was assessed by dividing their weight (in kilograms) by the square of their body height (in metres). Mothers were classified as underweight if their BMI was < 18.5 kg/m2 and as not underweight if their BMI was ≥18.5 kg/m2. Pregnant mothers were classified according to the categories proposed by Ververs et al. [21]. A wealth index based on a minimal set of assets was created, allowing separation of the subjects into three distinct groups based on principal component analysis (PCA). The minimal set of assets included housing materials (floor and wall materials, ownership of an automobile, telephone, bicycle, motorcycle), access to specific utilities (electricity, plumbing, cooking location), and family size. We defined three household wealth categories according to the clusters observed: the poorest, middle and wealthiest categories. Details of the wealth index have been described previously [15]. Iron deficiency was defined as a plasma ferritin concentration  6 mg/l was considered an indicator of inflammation. For citrulline, a value below 7 μmol/l was considered too low, and a value above 43 μmol/l was considered too high according to the normal values provided by the Hôpital Necker Enfants Malades. According to the thresholds used in routine diagnostics at the Hôpital Pitié-Salpêtrière, the threshold for AAT was 1.25 mg/g dry weight, and values above this threshold were considered elevated. For calprotectin, the normal value was equal to or less than 150 μg/g for children 2–3 years of age and equal to or less than 100 μg/g for those between 3 and 5 years of age; children who had values above these thresholds were classified as having elevated values. Statistical analysis was performed using R statistical software (version 3.4.3; The R Foundation for Statistical Computing, Vienna, Austria). Descriptive analysis was performed using proportions for categorical variables and means or medians with interquartile ranges for continuous variables according to their distributions. We used binomial logistic regression model analysis to identify independent predictors of the occurrence of anaemia. A bivariate analysis was performed to identify the explanatory variables to be included in the multivariate analysis. All explanatory variables with p value < 0.20 in the bivariate analysis were included in the logistic regression model. A backwards stepwise logistic regression was applied to obtain the variables associated with the occurrence of anaemia. Explanatory variables included the following: 1) biological characteristics: iron status, presence of intestinal parasites, alpha-antitrypsin and calprotectin levels, status of intestinal damage and repair (citrulline levels in blood); 2) child characteristics: age, gender, nutritional status, occurrence of dental caries or symptoms such as dermatitis, cough, runny nose, or clogged nose, age at introduction of the first complementary food, weaning age, and dietary diversity status; 3) maternal characteristics: body mass index; and 4) household characteristics: wealth index. This study was conducted within the framework of the AFRIBIOTA project, which has been approved by the Ethics Committee for Biomedical Research at the Ministry of Public Health in Madagascar (N°104-MSANP/CE – 12/09/2016) and the Institutional Review Board of the Institut Pasteur (2016–06/IRB). Parents or caregivers were informed about the study and signed the informed consent form before the inclusion of their children. The biological analyses were performed free of charge. Treatments were given to infected and anaemic children according to the national recommendation; the cost of the treatment was covered by the project.

Based on the provided information, 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 resources on maternal health, including prenatal care, nutrition, and breastfeeding. These apps can also offer reminders for appointments and medication, as well as access to telemedicine consultations.

2. Telemedicine Services: Implement telemedicine services to provide remote consultations with healthcare professionals. This can help overcome geographical barriers and improve access to prenatal care and medical advice for pregnant women in underprivileged areas.

3. Community Health Workers: Train and deploy community health workers to provide education and support to pregnant women and new mothers. These workers can offer guidance on nutrition, hygiene practices, and breastfeeding, as well as identify and refer women with high-risk pregnancies to appropriate healthcare facilities.

4. Mobile Clinics: Establish mobile clinics that can travel to underprivileged areas to provide prenatal care, vaccinations, and other essential maternal health services. This can help reach women who may have limited access to healthcare facilities.

5. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private sector resources and expertise to enhance healthcare infrastructure and service delivery in underprivileged areas.

6. Maternal Health Vouchers: Implement voucher programs that provide financial assistance to pregnant women for accessing maternal health services. These vouchers can cover costs related to prenatal care, delivery, and postnatal care, ensuring that women have access to essential healthcare without financial barriers.

7. Health Education Campaigns: Conduct targeted health education campaigns to raise awareness about the importance of maternal health and encourage women to seek timely care. These campaigns can utilize various media channels, including radio, television, and community outreach programs.

8. Maternal Health Monitoring Systems: Develop and implement digital systems for monitoring maternal health indicators, such as anaemia prevalence and iron deficiency. These systems can help identify high-risk areas and populations, enabling targeted interventions and resource allocation.

9. Maternal Health Financing Mechanisms: Explore innovative financing mechanisms, such as microinsurance or community-based health financing, to ensure financial protection for pregnant women and improve access to maternal health services.

10. Integration of Maternal Health Services: Promote the integration of maternal health services with other healthcare programs, such as family planning and child health services. This can improve efficiency and ensure comprehensive care for women and their children.

It is important to note that the specific context and needs of the target population should be considered when implementing these innovations to ensure their effectiveness and sustainability.
AI Innovations Description
Based on the information provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Strengthen National Strategies: Emphasize the importance of improving children’s dietary quality and micronutrient intake in underprivileged areas. This can be achieved through targeted interventions such as providing nutritional supplements, promoting breastfeeding, and educating caregivers about the importance of a balanced diet.

2. Expand Existing Measures: Broaden existing measures to include interventions that aim to reduce the burden of infectious diseases. This can be done through vaccination campaigns, improved sanitation and hygiene practices, and access to clean water sources.

3. Community-based Approach: Implement community-based interventions to reach children in underprivileged areas. This can involve training and mobilizing community health workers to provide education, screenings, and referrals for anaemia and other maternal health issues.

4. Collaboration and Partnerships: Foster collaboration between government agencies, non-governmental organizations, and international partners to pool resources and expertise. This can help ensure a coordinated and comprehensive approach to improving access to maternal health services.

5. Data Collection and Analysis: Continuously collect and analyze data on risk factors associated with anaemia and other maternal health issues. This will help identify trends, evaluate the effectiveness of interventions, and inform future strategies.

By implementing these recommendations, it is possible to develop innovative approaches to improve access to maternal health and reduce the prevalence of anaemia among children in underprivileged areas.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthen National Strategies: Emphasize the importance of improving children’s dietary quality and micronutrient intake through national strategies. This can include promoting breastfeeding, encouraging the consumption of diverse and nutritious foods, and providing access to nutritional supplements.

2. Expand Existing Measures: Broaden existing measures to include interventions that reduce the burden of infectious diseases. This can involve implementing vaccination programs, improving sanitation and hygiene practices, and providing access to clean water sources.

3. Community-Based Interventions: Implement community-based interventions to reach underprivileged areas. This can involve training and empowering community health workers to provide education, counseling, and basic healthcare services to mothers and children.

4. Health Facility Support: Strengthen health facilities in underprivileged areas by improving infrastructure, ensuring the availability of essential medical supplies and equipment, and training healthcare providers to deliver quality maternal and child healthcare services.

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

1. Data Collection: Gather data on the current status of maternal health access, including indicators such as maternal mortality rates, antenatal care coverage, skilled birth attendance, and access to essential maternal health services.

2. Baseline Assessment: Analyze the collected data to establish a baseline for maternal health access. This will provide a reference point for measuring the impact of the recommendations.

3. Modeling: Use statistical modeling techniques, such as logistic regression or other appropriate methods, to simulate the potential impact of the recommendations on improving access to maternal health. This can involve estimating the expected changes in key indicators based on the proposed interventions.

4. Sensitivity Analysis: Conduct sensitivity analysis to assess the robustness of the results and explore different scenarios. This can involve varying the parameters and assumptions used in the model to understand the potential range of outcomes.

5. Evaluation and Monitoring: Continuously evaluate and monitor the implementation of the recommendations to assess their effectiveness and make necessary adjustments. This can involve tracking key indicators over time and comparing them to the baseline assessment to measure progress.

By following this methodology, policymakers and healthcare professionals can gain insights into the potential impact of the recommendations on improving access to maternal health and make informed decisions to prioritize interventions and allocate resources effectively.

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