Health care seeking behaviour for children with acute childhood illnesses and its relating factors in sub-Saharan Africa: evidence from 24 countries

Tropical Medicine and Health, Volume 49, No. 1, Year 2021

Ukuhunyushwa

Background: Childhood illnesses and mortality rates have declined over the past years in sub-Saharan African countries; however, under-five mortality is still high in the region. This study investigated the magnitude and factors associated with health care seeking behaviour for children with childhood illnesses in 24 sub-Saharan African countries. Methods: We used secondary data from Demographic and Health Surveys (DHSs) conducted between 2013 and 2018 across the 24 sub-Saharan African countries. Binary logistic regression models were applied to identify the factors associated with health care seeking behaviour for children with acute childhood illnesses. The results were presented using adjusted odds ratios (aOR) with 95% confidence intervals (CIs). Results: Overall, 45% of children under-5 years with acute childhood illnesses utilized health care facilities. The factors associated with health care seeking behaviour for children with acute illnesses were sex of child, number of living children, education, work status, wealth index, exposure to media and distance to a health facility. Conclusions: Over half of mothers did not seek appropriate health care for under-five childhood illnesses. Effective health policy interventions are needed to enhance health care seeking behaviour of mothers for childhood illnesses in sub-Saharan African countries. The study used secondary data from the Demographic and Health Surveys (DHSs) of 24 countries in sub-Saharan Africa. The countries were selected if the surveys were conducted between 2010 and 2018 [33, 38], and outcome and explanatory variables were available. The DHSs use multi-stage stratified sampling method [33, 38, 39]. These DHSs are nationally representative and comparable surveys conducted worldwide in more than 85 countries [40]. The surveys usually collect a wide range of self-reported and objective data with a strong focus on indicators of reproductive health, fertility, child and maternal health, nutrition, mortality, and self-reported health behaviours among adults [41]. The sample for the final analyses was 98,590. It included children who had diarrhea and/or fever or cough in the 2 weeks preceding the surveys, whether they sought private or public health care or not. The country specific details are presented in Additional file 1. The outcome of interest was under-five children with incidence of diarrhea and/or cough or fever in the past 2 weeks before the surveys. Those who went for consultation in a public or private health care service provider and those who did not go were classified as users and non-users, respectively [14]. The explanatory variables considered were maternal education (no formal education, primary and secondary plus), age of mother (15–24, 25–34 and 35–49), occupation of mother (working and not working), wealth index (poorest, poorer, middle, richer and richest), marital status (never married and ever married), residence (urban and rural), distance to health facility (experience no difficulty in getting to a health facility/not a problem in getting to a health facility or experienced difficulty in getting to a health facility/a problem to in getting to a health facility), media access (no access and have access) and sex of the child (male and female) [14]. First, descriptive analyses were performed using frequency and percentage distributions to examine the characteristics of participants and prevalence of health care seeking behaviour among mothers for children with childhood illnesses. Differences in prevalence were examined using chi-square test. Furthermore, to assess multicollinearity, correlation test was performed among independent variables. The findings showed that the assumptions of multicollinearity were not violated. The tolerance value was greater than 0.10 [42]. Non-response and missing data were excluded to arrive at the weighted sample size. Second, a binary logistic regression model was fitted to examine the relationship between explanatory variables and health care seeking behaviour of mothers. To adjust for sampling variability, DHSs incorporate two-stage cluster sampling [33, 38, 39, 43] and sampling weight was applied to account for the complex survey design including weight, cluster, and strata. Stata version 14 (Stata Corp, College Station, Texas, USA) was used to estimate the prevalence of health seeking behaviour of mothers and odds ratios with 95% confidence intervals (95% CI).

I-AI Digest

Study Justification:

– Childhood illnesses and mortality rates have declined in sub-Saharan African countries, but under-five mortality is still high.
– This study aims to investigate the factors associated with health care seeking behavior for children with childhood illnesses in 24 sub-Saharan African countries.
– Understanding these factors can help inform effective health policy interventions to improve health care seeking behavior for childhood illnesses.

Study Highlights:

– The study used secondary data from Demographic and Health Surveys (DHSs) conducted between 2013 and 2018 in 24 sub-Saharan African countries.
– Overall, 45% of children under-5 years with acute childhood illnesses utilized health care facilities.
– Factors associated with health care seeking behavior for children with acute illnesses included sex of child, number of living children, education, work status, wealth index, exposure to media, and distance to a health facility.
– Over half of mothers did not seek appropriate health care for under-five childhood illnesses.

Study Recommendations for Lay Reader and Policy Maker:

– Implement effective health policy interventions to enhance health care seeking behavior of mothers for childhood illnesses in sub-Saharan African countries.
– Focus on improving access to health care facilities, especially for mothers living in rural areas or facing difficulties in reaching a health facility.
– Promote education and awareness about childhood illnesses and the importance of seeking timely and appropriate health care.
– Address socio-economic factors such as wealth index and work status that may influence health care seeking behavior.
– Increase media access and use it as a platform to disseminate information about childhood illnesses and available health care services.

Key Role Players Needed to Address Recommendations:

– Government health departments and ministries
– Non-governmental organizations (NGOs) working in the health sector
– Community health workers and volunteers
– Health care providers and facilities
– Educators and schools
– Media organizations and journalists

Cost Items to Include in Planning the Recommendations:

– Infrastructure development and improvement of health care facilities
– Training and capacity building for health care providers and community health workers
– Education and awareness campaigns targeting mothers and communities
– Media campaigns and advertisements
– Research and data collection on health care seeking behavior and childhood illnesses
– Monitoring and evaluation of interventions
– Collaboration and coordination between different stakeholders

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on secondary data from nationally representative surveys conducted in 24 sub-Saharan African countries. The study used binary logistic regression models to identify factors associated with health care seeking behavior for children with acute childhood illnesses. The results were presented using adjusted odds ratios (aOR) with 95% confidence intervals (CIs). The sample size for the final analyses was 98,590. However, the abstract does not provide information on the specific methodology used in the surveys or the representativeness of the sample. Additionally, the abstract does not mention any limitations of the study. To improve the evidence, the abstract should include more details on the survey methodology, sample representativeness, and potential limitations of the study.

Abstract

The study used secondary data from the Demographic and Health Surveys (DHSs) of 24 countries in sub-Saharan Africa. The countries were selected if the surveys were conducted between 2010 and 2018 [33, 38], and outcome and explanatory variables were available. The DHSs use multi-stage stratified sampling method [33, 38, 39]. These DHSs are nationally representative and comparable surveys conducted worldwide in more than 85 countries [40]. The surveys usually collect a wide range of self-reported and objective data with a strong focus on indicators of reproductive health, fertility, child and maternal health, nutrition, mortality, and self-reported health behaviours among adults [41]. The sample for the final analyses was 98,590. It included children who had diarrhea and/or fever or cough in the 2 weeks preceding the surveys, whether they sought private or public health care or not. The country specific details are presented in Additional file 1. The outcome of interest was under-five children with incidence of diarrhea and/or cough or fever in the past 2 weeks before the surveys. Those who went for consultation in a public or private health care service provider and those who did not go were classified as users and non-users, respectively [14]. The explanatory variables considered were maternal education (no formal education, primary and secondary plus), age of mother (15–24, 25–34 and 35–49), occupation of mother (working and not working), wealth index (poorest, poorer, middle, richer and richest), marital status (never married and ever married), residence (urban and rural), distance to health facility (experience no difficulty in getting to a health facility/not a problem in getting to a health facility or experienced difficulty in getting to a health facility/a problem to in getting to a health facility), media access (no access and have access) and sex of the child (male and female) [14]. First, descriptive analyses were performed using frequency and percentage distributions to examine the characteristics of participants and prevalence of health care seeking behaviour among mothers for children with childhood illnesses. Differences in prevalence were examined using chi-square test. Furthermore, to assess multicollinearity, correlation test was performed among independent variables. The findings showed that the assumptions of multicollinearity were not violated. The tolerance value was greater than 0.10 [42]. Non-response and missing data were excluded to arrive at the weighted sample size. Second, a binary logistic regression model was fitted to examine the relationship between explanatory variables and health care seeking behaviour of mothers. To adjust for sampling variability, DHSs incorporate two-stage cluster sampling [33, 38, 39, 43] and sampling weight was applied to account for the complex survey design including weight, cluster, and strata. Stata version 14 (Stata Corp, College Station, Texas, USA) was used to estimate the prevalence of health seeking behaviour of mothers and odds ratios with 95% confidence intervals (95% CI).

Izinto zokwakha

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Emisha

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

1. Mobile Health (mHealth) Solutions: Develop and implement mobile applications or SMS-based systems that provide information and reminders to pregnant women and new mothers about prenatal care, vaccinations, and postnatal care. These solutions can also facilitate communication between healthcare providers and patients, allowing for remote consultations and monitoring.

2. Community Health Workers (CHWs): Train and deploy community health workers who can provide basic maternal health services and education in remote or underserved areas. CHWs can conduct home visits, provide antenatal and postnatal care, and refer women to healthcare facilities when necessary.

3. Telemedicine: Establish telemedicine networks that connect healthcare providers in urban areas with pregnant women and new mothers in rural or remote locations. This allows for remote consultations, diagnosis, and treatment, reducing the need for women to travel long distances for healthcare.

4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access maternal health services. These vouchers can cover the cost of antenatal care, delivery, and postnatal care, ensuring that women can afford and access the necessary healthcare services.

5. Maternal Waiting Homes: Set up maternal waiting homes near healthcare facilities in rural areas. These homes provide accommodation for pregnant women who live far from healthcare facilities, allowing them to stay closer to the facility as they approach their due date, reducing the risk of complications during childbirth.

6. Transportation Support: Develop transportation support programs that provide pregnant women with affordable and reliable transportation to healthcare facilities. This can include subsidized transportation services or partnerships with local transportation providers.

7. Task-Shifting: Train and empower non-specialist healthcare providers, such as nurses and midwives, to provide a wider range of maternal health services. This can help alleviate the shortage of specialized healthcare providers in underserved areas.

8. Quality Improvement Initiatives: Implement quality improvement initiatives in healthcare facilities to ensure that maternal health services are provided in a safe and effective manner. This can include training healthcare providers, improving infrastructure and equipment, and implementing standardized protocols and guidelines.

These innovations have the potential to improve access to maternal health services, reduce maternal mortality rates, and improve the overall health outcomes for pregnant women and new mothers in sub-Saharan Africa.

AI Innovations Description

Based on the study’s findings, here is a recommendation that can be developed into an innovation to improve access to maternal health:

Develop a mobile health (mHealth) application that provides information and reminders to mothers in sub-Saharan African countries about the importance of seeking appropriate healthcare for childhood illnesses. The application should include educational content on recognizing symptoms, understanding when to seek medical help, and the benefits of timely healthcare seeking. It should also provide information on the nearest healthcare facilities, including their services and opening hours.

The mHealth application can be designed to send push notifications or SMS reminders to mothers, reminding them to seek medical help for their children when necessary. The application can also include a feature for tracking and monitoring the child’s health, allowing mothers to input symptoms and receive personalized recommendations based on the severity of the illness.

To address barriers such as distance to healthcare facilities, the application can incorporate a feature that helps mothers locate the nearest healthcare facility and provides directions on how to get there. Additionally, the application can partner with local transportation services to offer discounted or subsidized transportation options for mothers who face difficulties in accessing healthcare facilities.

To ensure the effectiveness of the innovation, it is important to collaborate with local healthcare providers, community leaders, and organizations working in maternal and child health. This collaboration can help tailor the content and features of the application to the specific needs and cultural context of each sub-Saharan African country.

By providing accessible and timely information, reminders, and support, this mHealth application can empower mothers to make informed decisions about seeking appropriate healthcare for their children, ultimately improving access to maternal health in sub-Saharan Africa.

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 rural areas, can help increase access to maternal health services. This includes building and equipping health clinics, hospitals, and maternity centers, as well as ensuring the availability of essential medical supplies and equipment.

2. Enhancing transportation services: Improving transportation infrastructure and services can address the issue of distance to health facilities, which was identified as a factor affecting health care seeking behavior. This can involve initiatives such as providing ambulances or mobile health clinics to reach remote areas, improving road networks, and implementing transportation subsidies or vouchers for pregnant women to access healthcare services.

3. Increasing awareness and education: Promoting maternal health education and awareness campaigns can help address factors like maternal education and media access. These campaigns can provide information on the importance of seeking timely and appropriate healthcare during pregnancy, childbirth, and postpartum, as well as address any misconceptions or cultural barriers that may exist.

4. Strengthening health workforce: Ensuring an adequate number of skilled healthcare professionals, such as doctors, nurses, midwives, and community health workers, is crucial for providing quality maternal health services. This can involve training and capacity-building programs, incentives to attract and retain healthcare professionals in underserved areas, and promoting task-shifting strategies to optimize the use of available resources.

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

1. Define indicators: Identify key indicators that reflect access to maternal health, such as the percentage of pregnant women receiving antenatal care, the percentage of births attended by skilled birth attendants, or the percentage of women receiving postnatal care within a specified timeframe.

2. Baseline data collection: Gather existing data on the selected indicators from reliable sources, such as national health surveys, health facility records, or population-based surveys. This will provide a baseline against which the impact of the recommendations can be measured.

3. Model development: Develop a simulation model that incorporates the identified recommendations and their potential effects on the selected indicators. This can be done using statistical software or specialized simulation tools.

4. Parameter estimation: Estimate the parameters of the simulation model based on available evidence, expert opinions, or data from pilot interventions or similar contexts. This may involve conducting literature reviews, consulting with relevant stakeholders, or conducting small-scale studies.

5. Scenario analysis: Run the simulation model using different scenarios that reflect the implementation of the recommendations. This can involve varying the intensity or coverage of each recommendation to assess their individual and combined effects on the selected indicators.

6. Impact assessment: Analyze the simulation results to assess the impact of the recommendations on improving access to maternal health. This can include comparing the indicators between the baseline and simulated scenarios, calculating the percentage change or absolute differences, and conducting statistical tests to determine the significance of the findings.

7. Sensitivity analysis: Perform sensitivity analysis to explore the robustness of the simulation results by varying the input parameters or assumptions. This can help identify the key drivers of the impact and assess the uncertainty associated with the findings.

8. Communication and policy recommendations: Summarize the simulation findings in a clear and concise manner, highlighting the potential benefits of the recommendations in improving access to maternal health. Use the results to inform policy discussions, advocacy efforts, and resource allocation decisions to prioritize and implement the most effective interventions.

It is important to note that the methodology for simulating the impact of recommendations may vary depending on the specific context, available data, and resources. Therefore, it is recommended to consult with experts in the field and adapt the methodology accordingly.

Ababhali & Co-Ababhali

Statistics:

Citations: 4

Authors: 3

Identifiers:

DOI: 10.1186/s41182-021-00385-1

ISSN: 13488945

Research Areas:

Community Interventions, Food Security, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health

Study Design:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Male & Female

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