Factors associated with asthma among under-fives in Mulago hospital, Kampala Uganda: A cross sectional study

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Study Justification:
– Asthma is the most common chronic childhood illness, with increasing prevalence in low-income countries.
– Asthma is often under-diagnosed in young children.
– The study aimed to investigate the factors associated with asthma among under-fives presenting with acute respiratory symptoms at Mulago hospital, Uganda.
Study Highlights:
– A cross-sectional study of 614 children with cough and/or difficult breathing was conducted.
– Factors associated with asthma included maternal asthma, a history of allergy in the patient, use of gas for cooking, prematurity, and high level of education of caretaker.
– Other diagnoses among the children included bronchiolitis, bacterial pneumonia, viral pneumonia, and pulmonary tuberculosis.
Study Recommendations:
– Further studies are needed to explore the role of the identified factors in the development and exacerbation of childhood asthma.
– The information from these studies can be used to design strategies for asthma prevention and control.
Key Role Players:
– Paediatricians
– Researchers
– Caretakers of children with asthma
– Policy makers
Cost Items for Planning Recommendations:
– Research funding
– Laboratory and radiological investigations
– Questionnaire development and testing
– Translation and adaptation of the questionnaire
– Enrolment and data collection
– Data analysis
– Expert panel meetings
– Dissemination of study findings

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study design is a cross-sectional study, which is appropriate for investigating factors associated with asthma. The sample size is adequate, and the study includes a diverse range of factors. However, the study relies on self-reported data and does not include objective measures such as spirometry. To improve the evidence, future studies could consider using a longitudinal design and incorporating objective measures of asthma.

Background: Asthma is the most common chronic childhood illness, with rapidly increasing prevalence in low-income countries. Among young children, asthma is often under-diagnosed.We investigated the factors associated with asthma among under-fives presenting with acute respiratory symptoms at Mulago hospital, Uganda.Methods: A hospital-based cross sectional study of 614 children with cough and/or difficult breathing, and fast breathing, was conducted between August 2011 and June 2012. A questionnaire focusing on clinical history of the child was administered to the caretakers. A physical examination and, laboratory and radiological investigations were done. Asthma was defined according to GINA (Global Initiative for Asthma) guidelines which were modified by excluding the symptom of ” chest tightness”, spirometry/peak expiratory flow measurements and by adding chest x-ray findings to distinguish asthma from pneumonia. A panel of three paediatricians reviewed the participants’ case reports and, guided by the study definitions, made a diagnosis of asthma or other. Multivariable logistic regression analysis was done to determine factors independently associated with asthma.Results: Of the 614 children, 128 (20.8%) had asthma, 125 (20.4%) bronchiolitis, 167 (27.2%) bacterial pneumonia only, 163 (26.5%) viral pneumonia while 31 (5.1%) had other diagnoses including pulmonary tuberculosis. The majority (71.1%) of children with asthma were aged ≥ 12 months. Factors associated with asthma included maternal asthma (AOR 2.4, 95% CI 1.2, 4.6), a history of allergy in the patient (AOR 2.6, 95% CI 1.2, 5.4,), use of gas for cooking (AOR 3.8, 95% CI 1.2, 13.3), prematurity (AOR 9.3, 95% CI 1.2, 83.3) and high level of education of caretaker (AOR 9.1, 95% CI 1.1, 72.8).Conclusion: Maternal asthma, a history of allergy in the patient, use of gas for cooking, prematurity and high level of education of caretaker were significantly associated with asthma. There is need for studies to explore the role of the above factors in development and exacerbation of childhood asthma to provide information that can be used to design strategies for asthma prevention and control. © 2013 Nantanda et al.; licensee BioMed Central Ltd.

We conducted a cross-sectional study among children aged 2 to 59 months presenting at the emergency paediatric unit of Mulago hospital Kampala between August 2011 and July 2012. Mulago hospital is a national referral hospital. It also acts as a district hospital serving an urban and peri-urban catchment population of about two million people. The paediatric emergency unit attends to children aged 1 day to 12 years. The average daily attendance is 80 children, 75% of whom are aged 2 to 59 months. An estimated 25% of the children present with cough and/or difficulty in breathing. The hospital was selected as the study site because of its ability to handle laboratory and radiological investigations for diagnosis of asthma and pneumonia, facilities that are not readily available in rural Ugandan hospitals. The study was approved by the Higher Degrees, Ethics and Research Committee (HDREC) at Makerere University College of Health Sciences and the Uganda National Council of Science and Technology. Informed written consent was obtained from the caretakers of the participants. The process of questionnaire development was led by one of us (MSO) in Denmark. Through a literature search, research team debates and expert opinion, study definitions and concepts for asthma were discussed. A qualitative study, focusing on caretakers of children with asthma, was undertaken to identify relevant items to be included in the questionnaire. The interviews were aimed at understanding the presentation and progression of the disease from the caretaker’s perspective. A preliminary questionnaire was hence developed consisting of items focusing on acute symptoms, past medical history of the child and medicine use during previous illnesses and, family history of asthma. The items were then tested for language, understanding and relevance through focus group discussions with caretakers. A new questionnaire was developed and this was further tested twice in the same way and a final version was generated, which was then tested for internal and external validity. It was then translated into English. The questionnaire was then adapted for use in Uganda by one of us (RN). It was translated to Luganda, the language commonly used in central Uganda, where Mulago hospital is located. It was then back-translated into English. Both the Luganda and English versions were pre-tested on a sample of 35 mothers to check for understanding of the questionnaire items and time taken to administer the questionnaire. Any necessary changes were made and a final questionnaire was developed. We enrolled children aged 2 to 59 months who presented at the paediatric emergency unit of Mulago hospital with cough and/or difficulty in breathing plus fast breathing, and whose caretakers gave informed written consent. The definition of fast breathing was based on WHO criteria [16] Children with heart conditions, or cardiac failure secondary to severe anaemia, based on the caretaker’s history, physical examination findings and medical records, were excluded. All potential participants were triaged and those with ‘severe classification’ according to the WHO guidelines [17] were given urgent care before proceeding with the consent process. Children with wheezing were nebulised with salbutamol solution using an ultrasonic nebulizer according to the hospital protocol [18] and the response noted. Participants were enrolled from 8.00.am to 10.00.pm on weekdays. After enrolment, a questionnaire (Additional file 1) was administered by the nurse. A physical examination was performed by the doctor. For all participants, we measured the peripheral oxygen saturation (SaO2) in room air. Children with SaO2 less than 92% were given oxygen by mask or nasal prongs. Six mill-litres of venous blood were drawn from the cubital vein or dorsum of the hand using a BD™ blood collection set in three aliquots; for blood culture, white cell count, and serum C-reactive protein (CRP) titres. A peripheral blood smear for malaria parasites was also done. A specimen of nasopharyngeal epithelium was collected for identification of Respiratory Syncytial Virus (RSV) according to the manufacturer’s instructions (BD Diagnostics, Becton, Dickinson and Company, Maryland USA). All specimens were delivered to the laboratory within six hours of collection. A posterior-anterior chest x-ray was taken for each of the study participants within 48 hours of enrolment. Total and differential white blood cell counts were determined using Coulter counter method (Beckman Coulter Inc. Z™ series). CRP titres were analyzed using CRP (Human) ELISA kit-ABNOVA™, Taiwan, according to the manufacturer’s instructions. Blood culture was done using the Bactec method (Becton, Dickson and Company Maryland USA) and positive samples were further analyzed for the bacterial species using a Gram stain. Drug susceptibility tests were done using the Disc diffusion method [19]. For malaria diagnosis, a peripheral blood smear was prepared using Leishman’s stain. Identification of Respiratory Synctial Virus (RSV) from nasal epithelium was done using Direct Fluorescence Antibody (DFA) technique (Light Diagnostics™ USA). The x-rays were interpreted by two independent radiologists who were blinded to the clinical and laboratory findings of the participants. Radiographic end-points included consolidation, collapse, alveolar and interstitial infiltrates, pleural effusion, hyper-inflation and normal. X-rays with discordant results from the two radiologists were interpreted by a third reader and the result taken as final if there was concordance between the third reader and any of the primary readers. There are no diagnostic gold standards for asthma among under-fives. In this study, we modified the GINA (Global Initiative for Asthma) guidelines for diagnosis of asthma [20] as follows: In the history; we excluded “recurrent chest tightness” as a symptom because it is not easily expressed by children less than five years [21,22]. We also we excluded peak expiratory flow measurements because children less than five years are not able to perform this test effectively [23]. Furthermore, we included chest x-rays to help distinguish asthma from pneumonia. Pneumonia is common in Uganda and, in under-fives, has a presentation similar to that of acute asthma [13,24]. The case definition of bronchiolitis was based on South African guidelines [14] for diagnosis, management and prevention of acute viral bronchiolitis. The details of the study definitions are provided in Table 1. Case definitions for asthma, bronchiolitis and pneumonia A panel of experts comprising paediatricians with experience in pulmonology and infectious diseases reviewed the participants’ case records. The experts had no access to the participants; hence the diagnoses were made post hoc. Each expert studied the case record of the participant, and guided by the study definitions, made a diagnosis, which was then discussed by all the panellists. A diagnosis of asthma or of some other condition such as pneumonia was made following agreement of all or two of the panellists. Where there was discordance between all the three panellists, the case records were subjected to a further discussion until a diagnosis was agreed upon. One of us (RN) took the minutes during the proceedings but did not participate in the discussions. To describe factors associated with asthma among young children with cough and/or difficult breathing, a minimum sample size of 308 was calculated. We assumed two-sided significance level of 95%, power of 80%, proportion of children with asthma and who had a family history of asthma to be 52%, and Odds’ ratio of 2.5, based on a study of asthma in preschoolers by Haby and colleagues [7]. However, this was part of a larger study involving 614 children and all were included in the analysis. Data was double-entered into Epidata version 3.0 and exported to Stata version 12.0 (Stata Corp, College station Texas, USA) for analysis. To determine factors independently associated with asthma, multivariable analysis was done. A logistic regression model was built by including all factors with a p value less than 0.2 at bivariate analysis. Adjusted Odd’s ratios were computed to adjust for confounding. Multi-colinearlity and interaction of the predictor variables was checked until we obtained the best fitting model. Cohen’s kappa was used to measure the degree of agreement between the primary radiologists. A p value of ≤0.05 was considered statistically significant. We also performed logistic regression analysis for factors associated with bronchiolitis and compared them to those associated with asthma. Results are summarized as frequencies, proportions, figures and tables as appropriate. In this study, children from the capital city, municipalities and town councils in Uganda were collectively referred to as coming from “urban setting” and the rest from “rural setting”. This was adapted from the Uganda Demographic and Health Survey [24].

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

1. Telemedicine: Implementing telemedicine services can allow pregnant women in remote areas to access healthcare professionals and receive prenatal care through virtual consultations. This can help overcome geographical barriers and improve access to maternal health services.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information and resources related to maternal health can empower pregnant women to take control of their own health. These apps can provide educational content, appointment reminders, and access to emergency services.

3. Community health workers: Training and deploying community health workers who can provide basic prenatal care, education, and support to pregnant women in underserved areas can help improve access to maternal health services. These workers can also help identify high-risk pregnancies and refer women to appropriate healthcare facilities.

4. Maternal health clinics on wheels: Setting up mobile clinics that travel to remote areas can bring essential maternal health services closer to pregnant women who would otherwise have limited access. These clinics can provide prenatal check-ups, vaccinations, and health education.

5. Public-private partnerships: Collaborating with private healthcare providers to expand access to maternal health services can help bridge the gap in underserved areas. This can involve subsidizing services, providing training to private providers, or establishing referral networks.

6. Maternal health vouchers: Introducing voucher programs that provide pregnant women with financial assistance to access maternal health services can help reduce financial barriers. These vouchers can cover the cost of prenatal care, delivery, and postnatal care.

7. Mobile clinics for antenatal care: Using specially equipped vehicles as mobile clinics that travel to different communities can provide antenatal care services to pregnant women who may not have access to a nearby healthcare facility. These mobile clinics can offer prenatal check-ups, ultrasounds, and screenings.

8. Maternal health hotlines: Establishing dedicated hotlines that pregnant women can call to receive information, advice, and support related to maternal health can help improve access to care. Trained healthcare professionals can provide guidance and refer women to appropriate services.

9. Maternal health education programs: Implementing comprehensive maternal health education programs in schools, community centers, and workplaces can help raise awareness and empower women to make informed decisions about their health. These programs can cover topics such as nutrition, prenatal care, and childbirth preparation.

10. Maternal health incentives: Introducing incentives, such as cash transfers or vouchers, for pregnant women who attend prenatal care visits and deliver at healthcare facilities can encourage women to seek and utilize maternal health services. These incentives can help overcome financial barriers and improve access to care.
AI Innovations Description
The study conducted at Mulago hospital in Uganda aimed to investigate the factors associated with asthma among children under the age of five. The study found that maternal asthma, a history of allergy in the patient, use of gas for cooking, prematurity, and a high level of education of the caretaker were significantly associated with asthma.

Based on these findings, a recommendation to improve access to maternal health and potentially prevent childhood asthma could be to provide education and support for pregnant women and new mothers with asthma or a history of allergy. This could include:

1. Antenatal education: Pregnant women with asthma or a history of allergy should receive education on how to manage their condition during pregnancy. This could include information on avoiding triggers, taking medication as prescribed, and seeking medical advice if symptoms worsen.

2. Postnatal support: New mothers with asthma or a history of allergy should be provided with support and resources to manage their condition while caring for their newborn. This could include access to asthma management plans, information on breastfeeding and medication safety, and guidance on creating a healthy home environment.

3. Healthcare provider training: Healthcare providers should receive training on the management of asthma and allergies in pregnant women and young children. This could include updates on current guidelines, strategies for identifying and managing asthma in children, and information on the importance of early intervention and prevention.

4. Access to healthcare services: Efforts should be made to improve access to healthcare services for pregnant women and young children, particularly in rural areas. This could include increasing the availability of healthcare facilities, ensuring the availability of essential medications, and providing transportation or mobile clinics for those who have difficulty accessing healthcare.

By implementing these recommendations, it is hoped that access to maternal health will be improved, leading to better management of asthma and potentially reducing the prevalence and severity of childhood asthma.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Increase awareness and education: Implement programs to educate pregnant women and their families about the importance of prenatal care, safe delivery practices, and postnatal care. This can be done through community health workers, mobile clinics, and health education campaigns.

2. Improve transportation: Enhance transportation infrastructure and services to ensure that pregnant women have access to healthcare facilities. This can include providing ambulances or transportation vouchers for pregnant women in remote areas.

3. Strengthen healthcare facilities: Invest in upgrading and equipping healthcare facilities to provide quality maternal health services. This can involve training healthcare providers, improving infrastructure, and ensuring the availability of essential medical supplies and equipment.

4. Increase availability of skilled birth attendants: Train and deploy more skilled birth attendants, such as midwives and nurses, especially in rural and underserved areas. This can be done through targeted recruitment and training programs.

5. Enhance community-based care: Establish and strengthen community-based maternal health programs that provide antenatal and postnatal care, as well as support for pregnant women and new mothers. This can involve training community health workers and providing them with the necessary resources and support.

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 key indicators that measure access to maternal health, such as the number of pregnant women receiving prenatal care, the percentage of deliveries attended by skilled birth attendants, and the availability of emergency obstetric care.

2. Collect baseline data: Gather data on the current status of these indicators in the target population or area. This can be done through surveys, interviews, and analysis of existing health records.

3. Develop a simulation model: Create a mathematical or statistical model that simulates the impact of the recommendations on the selected indicators. This model should take into account factors such as population size, geographical distribution, healthcare infrastructure, and resource allocation.

4. Input the intervention scenarios: Define different scenarios that represent the implementation of the recommendations. This can include variations in the scale and intensity of the interventions, as well as different timelines for implementation.

5. Run the simulations: Use the simulation model to calculate the projected changes in the selected indicators under each intervention scenario. This can involve running multiple iterations of the model to account for uncertainties and variations in the input parameters.

6. Analyze the results: Evaluate the simulated outcomes and compare them to the baseline data. Assess the potential impact of each recommendation on improving access to maternal health, and identify the most effective interventions.

7. Refine and validate the model: Validate the simulation model by comparing the simulated results with real-world data, if available. Refine the model based on feedback and further analysis, and repeat the simulations if necessary.

8. Communicate the findings: Present the findings of the simulation study in a clear and concise manner, highlighting the potential benefits of the recommended interventions. Use the results to advocate for policy changes and resource allocation to improve access to maternal health.

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.

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