Household and maternal risk factors for malaria in pregnancy in a highly endemic area of Uganda: A prospective cohort study

Malaria Journal, Volume 18, No. 1, Year 2019

Interpretation

Background: Malaria in pregnancy is a major public health challenge, but its risk factors remain poorly understood in some settings. This study assessed the association between household and maternal characteristics and malaria among pregnant women in a high transmission area of Uganda. Methods: A nested prospective study was conducted between 6th September 2016 and 5th December 2017 in Busia district. 782 HIV uninfected women were enrolled in the parent study with convenience sampling. Socioeconomic and house construction data were collected via a household survey after enrolment. Homes were classified as modern (plaster or cement walls, metal or wooden roof and closed eaves) or traditional (all other homes). Maternal and household risk factors were evaluated for three outcomes: (1) malaria parasitaemia at enrolment, measured by thick blood smear and qPCR, (2) malaria parasitaemia during pregnancy following initiation of IPTp, measured by thick blood smear and qPCR and (3) placental malaria measured by histopathology. Results: A total of 753 of 782 women were included in the analysis. Most women had no or primary education (75%) and lived in traditional houses (77%). At enrolment, microscopic or sub-microscopic parasitaemia was associated with house type (traditional versus modern: adjusted risk ratio (aRR) 1.29, 95% confidence intervals 1.15-1.45, p < 0.001), level of education (primary or no education versus O-level or beyond: aRR 1.13, 95% confidence interval 1.02-1.24, p = 0.02), and gravidity (primigravida versus multigravida: aRR 1.10, 95% confidence interval 1.02-1.18, p = 0.009). After initiation of IPTp, microscopic or sub-microscopic parasitaemia was associated with wealth index (poorest versus least poor: aRR 1.24, 95% CI 1.10-1.39, p < 0.001), house type (aRR 1.14, 95% CI 1.01-1.28, p = 0.03), education level (aRR 1.19, 95% CI 1.06-1.34, p = 0.002) and gravidity (aRR 1.32, 95% CI 1.20-1.45, p < 0.001). Placental malaria was associated with gravidity (aRR 2.87, 95% CI 2.39-3.45, p < 0.001), but not with household characteristics. Conclusions: In an area of high malaria transmission, primigravid women and those belonging to the poorest households, living in traditional homes and with the least education had the greatest risk of malaria during pregnancy. This study was conducted in Busia district, an area in south-eastern Uganda where malaria transmission is perennial and holoendemic. This prospective cohort study was part of a randomized controlled trial of intermittent preventive treatment of malaria in pregnancy (IPTp), which has been previously described [23]. Briefly, eligible participants for the parent study were HIV-uninfected women at least 16 years of age with a viable pregnancy between 12 and 20 weeks gestation who provided written informed consent. At enrolment, women received a long-lasting insecticidal net (LLIN), underwent a standardized history and examination and had blood collected for the detection of malaria parasites by microscopy and quantitative PCR (qPCR). Women were randomized (1:1 ratio) to receive IPTp with monthly sulfadoxine–pyrimethamine (SP) or monthly dihydroartemisinin–piperaquine (DP) starting at 16 or 20 weeks gestational age as previously described [23]. Following enrolment, women were visited at home where a household survey was conducted to collect socioeconomic and house construction data using a structured questionnaire. Women received all their medical care at a study clinic open every day. Routine visits at the study clinic were conducted every 4 weeks, including collection of blood for the detection of malaria parasites by microscopy and quantitative qPCR. Women were encouraged to come to the clinic any time they were ill. Those who presented with a documented fever (tympanic temperature ≥ 38.0 °C) or history of fever in the previous 24 h had blood collected for a thick blood smear. If the smear was positive, the patient was diagnosed with malaria and treated with artemether–lumefantrine. Women were encouraged to deliver at the hospital adjacent to the study clinic. Women delivering at home were visited by study staff at the time of delivery or as soon as possible afterwards. At delivery, a standardized assessment was completed including collection of placental tissue for assessment of placental malaria. Blood smears were stained with 2% Giemsa and read by experienced microscopists. A blood smear was considered negative when the examination of 100 high power fields did not reveal asexual parasites. For quality control, all slides were read by a second microscopist and a third reviewer settled any discrepant readings. Blood samples collected at enrolment and at the time of each routine visit that were negative by microscopy were tested for the presence of submicroscopic parasitaemia using a highly sensitive qPCR assay targeting the multicopy conserved var gene acidic terminal sequence with a lower limit of detection of 1 parasite/ml [24]. Placental tissues were processed for histological evidence of placental malaria as previously described [23]. Data were collected in the study clinic using standardized case record forms entered into Microsoft Access. Data from the household survey were collected using hand-held computers and customized software designed and programmed to include range checks and internal consistency checks. All statistical analyses were performed using Stata version 14.1 (StataCorp, College Station, TX, USA). Exposure variables of interest included characteristics of the study participants (education, bed net ownership, gravidity and IPTp regimen) and their households (wealth index and house construction). Principal component analysis was used to generate a wealth index based on ownership of common household items. Households were ranked by wealth scores and grouped into tertiles to give a categorical measure of socioeconomic position. House types were classified based on definitions previously developed for the study area [25]. Modern houses were defined as having plaster or cement walls, metal or wooden roofs, and closed eaves; all other houses were defined as traditional. Three outcome measures were assessed: (1) microscopic and microscopic or sub-microscopic parasitaemia at enrolment, (2) microscopic and microscopic or sub-microscopic parasitaemia at the time of routine visits during pregnancy following initiation of IPTp, and (3) placental malaria based on the detection of malaria parasites or pigment by histopathology. Associations between exposure variables and parasitaemia at enrolment or placental malaria were estimated using generalized linear models with a Poisson family and robust error variance. Associations between exposure variables and parasitaemia during pregnancy were estimated using generalized estimating equations to adjust for repeated measures in the same study participant with a Poisson family and robust error variance. Measures of association were expressed as unadjusted and adjusted relative risks (RR and aRR, respectively) and p-values (two-sided) < 0.05 were considered statistically significant.

AI Digest

Study Justification:

– Malaria in pregnancy is a significant public health challenge.
– Risk factors for malaria in pregnancy are not well understood in certain areas, including Busia district in Uganda.
– This study aimed to assess the association between household and maternal characteristics and malaria among pregnant women in a highly endemic area of Uganda.

Study Highlights:

– The study was conducted in Busia district, an area with perennial and holoendemic malaria transmission.
– A total of 753 HIV-uninfected pregnant women were included in the analysis.
– Most women had no or primary education (75%) and lived in traditional houses (77%).
– The study found that primigravid women and those belonging to the poorest households, living in traditional homes and with the least education had the greatest risk of malaria during pregnancy.
– The risk of malaria parasitaemia at enrolment was associated with house type, level of education, and gravidity.
– After initiation of intermittent preventive treatment of malaria in pregnancy (IPTp), the risk of malaria parasitaemia was associated with wealth index, house type, education level, and gravidity.
– Placental malaria was associated with gravidity, but not with household characteristics.

Recommendations for Lay Reader and Policy Maker:

– Increase access to education for pregnant women to reduce the risk of malaria during pregnancy.
– Improve housing conditions, particularly for pregnant women in traditional homes, to decrease the risk of malaria.
– Target interventions towards primigravid women and those belonging to the poorest households to reduce the burden of malaria in pregnancy.
– Strengthen implementation of IPTp to effectively prevent and control malaria during pregnancy.
– Enhance antenatal care services to ensure early detection and treatment of malaria in pregnant women.
– Promote the use of long-lasting insecticidal nets (LLINs) to further reduce the risk of malaria transmission.

Key Role Players:

– Ministry of Health: Responsible for policy development and implementation of malaria prevention and control strategies.
– District Health Office: Coordinates and oversees health programs at the district level, including malaria control activities.
– Health Facilities: Provide antenatal care services and implement interventions to prevent and treat malaria in pregnant women.
– Community Health Workers: Educate and raise awareness among pregnant women about malaria prevention and control measures.
– Non-Governmental Organizations (NGOs): Support implementation of malaria control programs and provide resources for interventions.

Cost Items for Planning Recommendations:

– Education Programs: Budget for initiatives to increase access to education for pregnant women.
– Housing Improvement: Allocate funds for improving housing conditions, such as providing materials for house construction or renovation.
– IPTp Implementation: Include costs for procurement and distribution of IPTp drugs, training of healthcare providers, and monitoring and evaluation activities.
– Antenatal Care Services: Budget for strengthening antenatal care services, including training of healthcare providers, provision of diagnostic tools, and supply of essential medicines.
– LLIN Distribution: Allocate funds for the procurement and distribution of LLINs to pregnant women.
– Community Health Worker Training: Include costs for training and capacity building of community health workers to deliver malaria prevention messages and interventions.
Note: The provided cost items are general categories and not actual cost estimates. Actual budget planning should be based on detailed assessments and specific program requirements.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is a prospective cohort study, which is generally considered to provide strong evidence. The sample size is relatively large (753 out of 782 women included in the analysis), which increases the reliability of the findings. The study also uses multiple methods to measure malaria parasitaemia (thick blood smear and qPCR) and includes multiple outcomes (malaria parasitaemia at enrolment, during pregnancy, and placental malaria), which adds to the robustness of the evidence. However, there are some limitations that could be addressed to improve the strength of the evidence. First, the study uses convenience sampling, which may introduce selection bias and limit the generalizability of the findings. Using a more representative sampling method, such as random sampling, would strengthen the evidence. Second, the study relies on self-reported data for some variables, such as education level and house type, which may be subject to recall bias. Collecting objective data or using independent verification methods would enhance the validity of the findings. Finally, the study does not provide information on the statistical methods used for the analyses, such as the specific models and adjustments made. Including this information would improve the transparency and replicability of the study.

Abstract

This study was conducted in Busia district, an area in south-eastern Uganda where malaria transmission is perennial and holoendemic. This prospective cohort study was part of a randomized controlled trial of intermittent preventive treatment of malaria in pregnancy (IPTp), which has been previously described [23]. Briefly, eligible participants for the parent study were HIV-uninfected women at least 16 years of age with a viable pregnancy between 12 and 20 weeks gestation who provided written informed consent. At enrolment, women received a long-lasting insecticidal net (LLIN), underwent a standardized history and examination and had blood collected for the detection of malaria parasites by microscopy and quantitative PCR (qPCR). Women were randomized (1:1 ratio) to receive IPTp with monthly sulfadoxine–pyrimethamine (SP) or monthly dihydroartemisinin–piperaquine (DP) starting at 16 or 20 weeks gestational age as previously described [23]. Following enrolment, women were visited at home where a household survey was conducted to collect socioeconomic and house construction data using a structured questionnaire. Women received all their medical care at a study clinic open every day. Routine visits at the study clinic were conducted every 4 weeks, including collection of blood for the detection of malaria parasites by microscopy and quantitative qPCR. Women were encouraged to come to the clinic any time they were ill. Those who presented with a documented fever (tympanic temperature ≥ 38.0 °C) or history of fever in the previous 24 h had blood collected for a thick blood smear. If the smear was positive, the patient was diagnosed with malaria and treated with artemether–lumefantrine. Women were encouraged to deliver at the hospital adjacent to the study clinic. Women delivering at home were visited by study staff at the time of delivery or as soon as possible afterwards. At delivery, a standardized assessment was completed including collection of placental tissue for assessment of placental malaria. Blood smears were stained with 2% Giemsa and read by experienced microscopists. A blood smear was considered negative when the examination of 100 high power fields did not reveal asexual parasites. For quality control, all slides were read by a second microscopist and a third reviewer settled any discrepant readings. Blood samples collected at enrolment and at the time of each routine visit that were negative by microscopy were tested for the presence of submicroscopic parasitaemia using a highly sensitive qPCR assay targeting the multicopy conserved var gene acidic terminal sequence with a lower limit of detection of 1 parasite/ml [24]. Placental tissues were processed for histological evidence of placental malaria as previously described [23]. Data were collected in the study clinic using standardized case record forms entered into Microsoft Access. Data from the household survey were collected using hand-held computers and customized software designed and programmed to include range checks and internal consistency checks. All statistical analyses were performed using Stata version 14.1 (StataCorp, College Station, TX, USA). Exposure variables of interest included characteristics of the study participants (education, bed net ownership, gravidity and IPTp regimen) and their households (wealth index and house construction). Principal component analysis was used to generate a wealth index based on ownership of common household items. Households were ranked by wealth scores and grouped into tertiles to give a categorical measure of socioeconomic position. House types were classified based on definitions previously developed for the study area [25]. Modern houses were defined as having plaster or cement walls, metal or wooden roofs, and closed eaves; all other houses were defined as traditional. Three outcome measures were assessed: (1) microscopic and microscopic or sub-microscopic parasitaemia at enrolment, (2) microscopic and microscopic or sub-microscopic parasitaemia at the time of routine visits during pregnancy following initiation of IPTp, and (3) placental malaria based on the detection of malaria parasites or pigment by histopathology. Associations between exposure variables and parasitaemia at enrolment or placental malaria were estimated using generalized linear models with a Poisson family and robust error variance. Associations between exposure variables and parasitaemia during pregnancy were estimated using generalized estimating equations to adjust for repeated measures in the same study participant with a Poisson family and robust error variance. Measures of association were expressed as unadjusted and adjusted relative risks (RR and aRR, respectively) and p-values (two-sided) < 0.05 were considered statistically significant.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Solutions: Develop mobile applications or text messaging services to provide pregnant women with information on malaria prevention, antenatal care, and IPTp medication reminders. This can help improve knowledge and adherence to recommended practices.

2. Community Health Workers: Train and deploy community health workers to conduct home visits and provide education on malaria prevention, antenatal care, and the importance of IPTp. They can also distribute long-lasting insecticidal nets (LLINs) and conduct regular follow-ups to ensure pregnant women are receiving appropriate care.

3. Telemedicine: Implement telemedicine services to enable pregnant women in remote areas to consult with healthcare providers and receive guidance on malaria prevention and management. This can help overcome geographical barriers and improve access to timely and quality care.

4. Improved Housing Infrastructure: Advocate for improved housing infrastructure in high malaria transmission areas, such as Busia district. This can include promoting the construction of modern houses with plaster or cement walls, metal or wooden roofs, and closed eaves to reduce mosquito entry and malaria transmission.

5. Socioeconomic Support: Implement programs that provide socioeconomic support to pregnant women from the poorest households. This can include initiatives to improve access to education, income-generating activities, and financial assistance for antenatal care and IPTp medication.

6. Integrated Services: Strengthen integration between malaria prevention and maternal health services. This can involve co-locating antenatal care and malaria prevention services, ensuring that pregnant women receive both interventions during their visits.

7. Health Information Systems: Improve health information systems to enable better monitoring and evaluation of maternal health interventions, including malaria prevention. This can help identify gaps in service delivery and inform targeted interventions.

It is important to note that these recommendations are based on the specific context of the study conducted in Busia district, Uganda. The implementation of these innovations should be tailored to the local context and consider the resources and infrastructure available.

AI Innovations Description

Based on the information provided, the recommendation to improve access to maternal health in the context of malaria in pregnancy in Busia district, Uganda is to implement targeted interventions for high-risk groups.

1. Targeted Education Programs: Develop and implement educational programs that specifically target pregnant women with no or primary education. These programs should focus on raising awareness about malaria prevention strategies, such as the use of insecticide-treated bed nets, regular antenatal care visits, and adherence to intermittent preventive treatment of malaria in pregnancy (IPTp) guidelines.

2. Improved Housing Conditions: Implement initiatives to improve housing conditions, particularly for pregnant women living in traditional homes. This could involve providing resources and support for upgrading traditional homes to meet modern housing standards, such as plaster or cement walls, metal or wooden roofs, and closed eaves. Improved housing can help reduce the risk of malaria transmission by minimizing mosquito entry points.

3. Enhanced Access to Antenatal Care: Strengthen the availability and accessibility of antenatal care services in the study area. This can be achieved by increasing the number of healthcare facilities, ensuring regular supply of essential malaria prevention and treatment commodities, and promoting community awareness about the importance of antenatal care visits.

4. Socioeconomic Support: Provide targeted socioeconomic support to pregnant women belonging to the poorest households. This can include financial assistance for accessing healthcare services, provision of insecticide-treated bed nets, and support for income-generating activities to improve household wealth.

5. Collaboration and Partnerships: Foster collaboration between local health authorities, non-governmental organizations, and community leaders to implement and sustain these interventions. Partnerships can help mobilize resources, coordinate efforts, and ensure the effective implementation of maternal health programs.

By implementing these recommendations, it is expected that access to maternal health services and the prevention of malaria in pregnancy can be improved in Busia district, Uganda.

AI Innovations Methodology

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

1. Increase education and awareness: Implement programs that focus on educating pregnant women and their families about the importance of maternal health, including the risks of malaria during pregnancy and the available preventive measures.

2. Improve access to antenatal care: Strengthen the healthcare system by ensuring that pregnant women have access to regular antenatal care visits, where they can receive appropriate screening, prevention, and treatment for malaria.

3. Enhance availability and distribution of insecticide-treated bed nets: Increase the availability and distribution of insecticide-treated bed nets to pregnant women in the study area, particularly those belonging to the poorest households.

4. Provide targeted interventions for primigravid women: Develop targeted interventions specifically for primigravid women, who were found to have the greatest risk of malaria during pregnancy in the study. This could include additional education, preventive measures, and access to antenatal care.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the target population: Identify the specific population that will be the focus of the simulation, such as pregnant women in the study area.

2. Collect baseline data: Gather data on the current state of access to maternal health services, including the prevalence of malaria during pregnancy, the utilization of antenatal care, and the availability of insecticide-treated bed nets.

3. Develop a simulation model: Create a mathematical model that simulates the impact of the recommendations on the target population. This model should take into account factors such as population size, demographic characteristics, and the effectiveness of the interventions.

4. Input data and parameters: Input the baseline data and parameters into the simulation model, including information on the education level, household characteristics, and other risk factors identified in the study.

5. Run simulations: Run multiple simulations using different scenarios, such as varying levels of education and access to antenatal care, to assess the potential impact of the recommendations on improving access to maternal health.

6. Analyze results: Analyze the results of the simulations to determine the potential impact of the recommendations on key outcomes, such as the reduction in malaria prevalence during pregnancy and the increase in utilization of antenatal care.

7. Refine and validate the model: Refine the simulation model based on the analysis of the results and validate it using additional data or by comparing the simulated outcomes with real-world data, if available.

8. Communicate findings: Present the findings of the simulation study to relevant stakeholders, such as policymakers, healthcare providers, and community leaders, to inform decision-making and prioritize interventions for improving access to maternal health.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and available data in the study area.

Authors & Co-Authors

Statistics:

Citations: 16

Authors: 10

Identifiers:

DOI: 10.1186/s12936-019-2779-x

Research Areas:

Genetics and Genomics, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Uganda

Study Design:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female