Maternal healthcare services use in Mwanza Region, Tanzania: A cross-sectional baseline survey

BMC Pregnancy and Childbirth, Volume 19, No. 1, Year 2019

Ukuhunyushwa

Background: Improving maternal health by reducing maternal mortality/morbidity relates to Goal 3 of the Sustainable Development Goals. Achieving this goal is supported by antenatal care (ANC), health facility delivery, and postpartum care. This study aimed to understand levels of use and correlates of uptake of maternal healthcare services among women of reproductive age (15-49 years) in Mwanza Region, Tanzania. Methods: A cross-sectional multi-stage sampling household survey was conducted to obtain data from 1476 households in six districts of Mwanza Region. Data for the 409 women who delivered in the 2 years before the survey were analyzed for three outcomes: four or more ANC visits (ANC4+), health facility delivery, and postpartum visits. Factors associated with the three outcomes were determined using generalized estimating equations to account for clustering at the district level while adjusting for all variables. Results: Of the 409 eligible women, 58.2% attended ANC4+, 76.8% delivered in a health facility, and 43.5% attended a postpartum clinic. Women from peri-urban, island, and rural regions were less likely to have completed ANC4+ or health facility delivery compared with urban women. Education and early first antenatal visit were associated with ANC4+ and health facility delivery. Mothers from peri-urban areas and those who with health facility delivery were more likely to attend postpartum check-ups. Conclusion: Use of ANC services in early pregnancy influences the number of ANC visits, leading to higher uptake of ANC4+ and health facility delivery. Postpartum check-ups for mothers and newborns are associated with health facility delivery. Encouraging early initiation of ANC visits may increase the uptake of maternal healthcare services. Data were collected as part of the 2017 baseline survey for the “Improving Access to Reproductive, Maternal and Newborn Health in Tanzania” (IMPACT) project. The IMPACT project aims to accelerate the reduction of maternal and newborn mortality by addressing major reproductive, maternal and newborn challenges in eight districts of Mwanza Region. This study was conducted in six of the eight districts: Ukerewe, Nyamagana, Illemela, Magu, Sengerema, and Buchosa districts excluding Kwimba and Misungwi districts that had an ongoing similar project (Fig. 1). Map showing the districts of Mwanza Region, Tanzania [20]. Source: Mazigo HD, Okumu FO, Kweka EJ, Mnyone LL: Retrospective analysis of suspected rabies cases reported at bugando referral hospital, mwanza, Tanzania. J Glob Infect Dis 2010, 2(3):216–220 The present study used a descriptive, cross-sectional, multi-stage design to select eligible households for participation in the survey. With the help of village executive officers, a listing of all households was obtained for each district. This list was used as the master frame from which the number of households were randomly selected for the survey. In the first stage, 30 of 408 villages were selected across the six districts using probability proportional to the size of villages (number of households in the respective villages). The second stage involved random selection of households in each selected village. The required sample size for households was calculated to detect a change of 10% in skilled birth attendants between baseline and study endline, with a 95% level of significance, 0.05 margin of error, and 5.6 crude birth rate, using 2 as a design effect and a 10% non-response rate. This resulted in a required sample size of 1476 households, of which 1312 households’ members were present and consented. No further sampling was undertaken in the sample households; all women in those households aged 15–49 years were eligible to participate. Women present in the household at the time of the visit that consented to participate were interviewed. Data were collected from August to September 2017. A total of 1612 women met the eligibility criteria but 1167 consented, resulting in a 72% response rate. Of the 1167 women who consented, 409 reported a live birth in the preceding 2 years. The baseline survey was approved by the National Institute for Medical Research in Tanzania (registration certificate: NIMR/HQR/R.8a/Vol.IX/2517) and the Institutional Review Board at Aga-Khan University in Dar-es-salaam, Tanzania. The Regional Medical Officer and district reproductive and child health coordinators authorized the survey. Village administrators granted permission to conduct the survey in households in their village of jurisdiction. All survey participants provided oral and written informed consent after receiving an explanation of the purpose of this study, duration of the interview, and their right to refuse or withdraw from the interviews at any time during the study process. All data were collected through face-to-face interviews in either English or Swahili by the enumerators in a private place in the selected household (or in some cases in the homestead) using a translated electronic tool. Data collection was undertaken by teams of trained enumerators who were fluent in both English and Swahili. All enumerators participated in a 6-day training program covering data collection tools, interviewing skills, research ethics, and use of electronic devices (tablets) for data collection. The last day of the training was used for practical exercises in a nearby village, which was not part of the sample used for the baseline survey. Each district had a team of six enumerators. A team lead oversaw data collection and ensured that all data were uploaded onto the server. Data quality during and after the survey was ensured by setting validation checks in the electronic data collection forms, random spot checks on some households, and daily supervision of the data collection process. Any issues identified were discussed the following morning before the start of that day’s data collection. The selection of variables was based on a review of relevant literature. Three outcome measures of MHS use were evaluated: number of ANC visits, delivery in a health facility, and postpartum care. Based on the recommended standard of ANC4+ visits during pregnancy, a woman who attended at least four visits received a score of 1. Women that attended none or fewer than four visits received a score of 0. An ANC visit was defined as a woman that reported having visited a nurse, midwife, clinical officer, or medical doctor during their last pregnancy. Health facility delivery was assessed by a question about the place of delivery of the last pregnancy, and was coded dichotomously as 1 if a woman delivered in a formal private/public medical facility with the help of a health professional, or 0 if she delivered at home or on the way to a medical facility. Postpartum care was assessed by asking each woman if a healthcare worker had checked on her health after delivery regardless of the place of delivery. Postpartum care was coded a 1 if a woman received any form of postpartum care (irrespective of number of days after delivery and place of delivery) and 0 if she did not receive a postpartum check-up. Explanatory variables included: district of residence, maternal age at time of the survey, marital status, and gestational age at first ANC visit, wealth quintile, maternal education, and whether the last pregnancy was wanted. Age was recorded on a continuous scale and later categorized into four groups (15–19, 20–29, 30–39, and 40–49 years). Marital status was collected as a categorical variable (currently married, in-union, and not in-union). The in-union group was merged with the currently married group and coded as 1; the not in-union group was coded as 0. Gestational age at first ANC visit was collected as a continuous variable in weeks and then categorized as first, second, and third trimester/no ANC visit. This was then dichotomized as a first trimester group and a second/third trimester and no ANC group. This allowed comparison of women who had ANC during their first trimester and those who did not attend/had late ANC visits. Wealth index (generated through principal component analysis based on household assets) was grouped into quintiles: poorest, poor, middle, rich, and richest. Maternal education level was dichotomized as primary education or below and secondary education or above. Assistance during delivery was categorized as skilled delivery if the woman was assisted by a nurse, clinical officer, or medical doctor. Otherwise, the delivery was categorized as unskilled. Finally, women that reported that their last pregnancy was wanted were coded as 1, and pregnancies that were not wanted (e.g., mistimed) were coded as 0. The community level variable identifying district and village of residence was only used in the descriptive table and was not included in the analysis because there was no variation in outcomes at this level as determined by the intra-class correlation coefficient; therefore, it was included in the model as a fixed effect. District of residence was coded to compare urban, rural, peri-urban, and island locations. Magu and Sengerema were classified as peri-urban districts, Ukerewe as an island district, Nyamagana and Illemela as urban districts, and Buchosa as a rural district. Data were analyzed in three steps. First, data were explored descriptively using frequency (percentages) and median (interquartile range [IQR]). Second, bivariate analyses were completed using chi-square tests to examine associations between individual factors and different outcome measures. This was also used to select variables to be retained in the multivariate analysis. Third, multivariate generalized estimation equation (GEE) regression analysis which is a form of logistic regression for clustered data was conducted to determine the adjusted effects of all explanatory variables on the three outcome variables. Three models were examined to assess the adjusted effects of predictors on ANC4+, facility delivery, and postpartum care. Variables that had a p-value < 0.25 in the bivariate analysis were included in the multivariate models. Stata version 12 (College station, Texas, USA) was used for all analyses. Data were de-identified by deleting all personal identifiers before analysis to ensure participants’ anonymity and confidentiality throughout the study.

I-AI Digest

Study Justification:

This study aimed to assess the levels of use and factors associated with the uptake of maternal healthcare services among women of reproductive age in Mwanza Region, Tanzania. The study is justified by the need to improve maternal health and reduce maternal mortality/morbidity, which aligns with Goal 3 of the Sustainable Development Goals. The findings of this study can inform interventions and policies to increase the utilization of maternal healthcare services and ultimately improve maternal and newborn health outcomes.

Highlights:

– 58.2% of eligible women attended four or more antenatal care (ANC) visits.
– 76.8% of eligible women delivered in a health facility.
– 43.5% of eligible women attended a postpartum clinic.
– Women from peri-urban, island, and rural regions were less likely to have completed ANC visits or delivered in a health facility compared to urban women.
– Education and early first ANC visit were associated with higher ANC attendance and health facility delivery.
– Mothers from peri-urban areas and those who delivered in a health facility were more likely to attend postpartum check-ups.
– Encouraging early initiation of ANC visits may increase the uptake of maternal healthcare services.

Recommendations:

Based on the study findings, the following recommendations can be made:

1. Improve access to and availability of ANC services, particularly in peri-urban, island, and rural regions.
2. Promote early initiation of ANC visits to ensure women receive the recommended number of ANC visits.
3. Enhance education and awareness programs to emphasize the importance of ANC and health facility delivery.
4. Strengthen postpartum care services and encourage mothers to attend postpartum check-ups.

Key Role Players:

To address the recommendations, the involvement of the following key role players is crucial:

1. Ministry of Health: Responsible for policy development, planning, and implementation of maternal healthcare services.
2. District Health Authorities: Responsible for coordinating and overseeing healthcare services at the district level.
3. Healthcare Providers: Including doctors, nurses, midwives, and clinical officers who deliver maternal healthcare services.
4. Community Health Workers: Involved in community outreach, education, and promotion of maternal healthcare services.
5. Non-Governmental Organizations (NGOs): Engaged in implementing interventions and programs to improve maternal health.

Cost Items for Planning Recommendations:

While actual costs may vary, the following cost items should be considered in planning the recommendations:

1. Infrastructure Development: Construction or renovation of healthcare facilities to improve access and availability of maternal healthcare services.
2. Training and Capacity Building: Providing training programs for healthcare providers and community health workers to enhance their skills and knowledge.
3. Education and Awareness Campaigns: Development and implementation of campaigns to raise awareness about the importance of ANC, health facility delivery, and postpartum care.
4. Equipment and Supplies: Procurement of necessary medical equipment, supplies, and medications for maternal healthcare services.
5. Monitoring and Evaluation: Establishing systems to monitor and evaluate the implementation and impact of interventions aimed at improving maternal healthcare services.
Please note that the provided information is based on the description of the study and may not include all details.

Amandla Obufakazi

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but could be improved by providing more information on the statistical methods used and the significance of the findings.

Abstract

Data were collected as part of the 2017 baseline survey for the “Improving Access to Reproductive, Maternal and Newborn Health in Tanzania” (IMPACT) project. The IMPACT project aims to accelerate the reduction of maternal and newborn mortality by addressing major reproductive, maternal and newborn challenges in eight districts of Mwanza Region. This study was conducted in six of the eight districts: Ukerewe, Nyamagana, Illemela, Magu, Sengerema, and Buchosa districts excluding Kwimba and Misungwi districts that had an ongoing similar project (Fig. 1). Map showing the districts of Mwanza Region, Tanzania [20]. Source: Mazigo HD, Okumu FO, Kweka EJ, Mnyone LL: Retrospective analysis of suspected rabies cases reported at bugando referral hospital, mwanza, Tanzania. J Glob Infect Dis 2010, 2(3):216–220 The present study used a descriptive, cross-sectional, multi-stage design to select eligible households for participation in the survey. With the help of village executive officers, a listing of all households was obtained for each district. This list was used as the master frame from which the number of households were randomly selected for the survey. In the first stage, 30 of 408 villages were selected across the six districts using probability proportional to the size of villages (number of households in the respective villages). The second stage involved random selection of households in each selected village. The required sample size for households was calculated to detect a change of 10% in skilled birth attendants between baseline and study endline, with a 95% level of significance, 0.05 margin of error, and 5.6 crude birth rate, using 2 as a design effect and a 10% non-response rate. This resulted in a required sample size of 1476 households, of which 1312 households’ members were present and consented. No further sampling was undertaken in the sample households; all women in those households aged 15–49 years were eligible to participate. Women present in the household at the time of the visit that consented to participate were interviewed. Data were collected from August to September 2017. A total of 1612 women met the eligibility criteria but 1167 consented, resulting in a 72% response rate. Of the 1167 women who consented, 409 reported a live birth in the preceding 2 years. The baseline survey was approved by the National Institute for Medical Research in Tanzania (registration certificate: NIMR/HQR/R.8a/Vol.IX/2517) and the Institutional Review Board at Aga-Khan University in Dar-es-salaam, Tanzania. The Regional Medical Officer and district reproductive and child health coordinators authorized the survey. Village administrators granted permission to conduct the survey in households in their village of jurisdiction. All survey participants provided oral and written informed consent after receiving an explanation of the purpose of this study, duration of the interview, and their right to refuse or withdraw from the interviews at any time during the study process. All data were collected through face-to-face interviews in either English or Swahili by the enumerators in a private place in the selected household (or in some cases in the homestead) using a translated electronic tool. Data collection was undertaken by teams of trained enumerators who were fluent in both English and Swahili. All enumerators participated in a 6-day training program covering data collection tools, interviewing skills, research ethics, and use of electronic devices (tablets) for data collection. The last day of the training was used for practical exercises in a nearby village, which was not part of the sample used for the baseline survey. Each district had a team of six enumerators. A team lead oversaw data collection and ensured that all data were uploaded onto the server. Data quality during and after the survey was ensured by setting validation checks in the electronic data collection forms, random spot checks on some households, and daily supervision of the data collection process. Any issues identified were discussed the following morning before the start of that day’s data collection. The selection of variables was based on a review of relevant literature. Three outcome measures of MHS use were evaluated: number of ANC visits, delivery in a health facility, and postpartum care. Based on the recommended standard of ANC4+ visits during pregnancy, a woman who attended at least four visits received a score of 1. Women that attended none or fewer than four visits received a score of 0. An ANC visit was defined as a woman that reported having visited a nurse, midwife, clinical officer, or medical doctor during their last pregnancy. Health facility delivery was assessed by a question about the place of delivery of the last pregnancy, and was coded dichotomously as 1 if a woman delivered in a formal private/public medical facility with the help of a health professional, or 0 if she delivered at home or on the way to a medical facility. Postpartum care was assessed by asking each woman if a healthcare worker had checked on her health after delivery regardless of the place of delivery. Postpartum care was coded a 1 if a woman received any form of postpartum care (irrespective of number of days after delivery and place of delivery) and 0 if she did not receive a postpartum check-up. Explanatory variables included: district of residence, maternal age at time of the survey, marital status, and gestational age at first ANC visit, wealth quintile, maternal education, and whether the last pregnancy was wanted. Age was recorded on a continuous scale and later categorized into four groups (15–19, 20–29, 30–39, and 40–49 years). Marital status was collected as a categorical variable (currently married, in-union, and not in-union). The in-union group was merged with the currently married group and coded as 1; the not in-union group was coded as 0. Gestational age at first ANC visit was collected as a continuous variable in weeks and then categorized as first, second, and third trimester/no ANC visit. This was then dichotomized as a first trimester group and a second/third trimester and no ANC group. This allowed comparison of women who had ANC during their first trimester and those who did not attend/had late ANC visits. Wealth index (generated through principal component analysis based on household assets) was grouped into quintiles: poorest, poor, middle, rich, and richest. Maternal education level was dichotomized as primary education or below and secondary education or above. Assistance during delivery was categorized as skilled delivery if the woman was assisted by a nurse, clinical officer, or medical doctor. Otherwise, the delivery was categorized as unskilled. Finally, women that reported that their last pregnancy was wanted were coded as 1, and pregnancies that were not wanted (e.g., mistimed) were coded as 0. The community level variable identifying district and village of residence was only used in the descriptive table and was not included in the analysis because there was no variation in outcomes at this level as determined by the intra-class correlation coefficient; therefore, it was included in the model as a fixed effect. District of residence was coded to compare urban, rural, peri-urban, and island locations. Magu and Sengerema were classified as peri-urban districts, Ukerewe as an island district, Nyamagana and Illemela as urban districts, and Buchosa as a rural district. Data were analyzed in three steps. First, data were explored descriptively using frequency (percentages) and median (interquartile range [IQR]). Second, bivariate analyses were completed using chi-square tests to examine associations between individual factors and different outcome measures. This was also used to select variables to be retained in the multivariate analysis. Third, multivariate generalized estimation equation (GEE) regression analysis which is a form of logistic regression for clustered data was conducted to determine the adjusted effects of all explanatory variables on the three outcome variables. Three models were examined to assess the adjusted effects of predictors on ANC4+, facility delivery, and postpartum care. Variables that had a p-value < 0.25 in the bivariate analysis were included in the multivariate models. Stata version 12 (College station, Texas, USA) was used for all analyses. Data were de-identified by deleting all personal identifiers before analysis to ensure participants’ anonymity and confidentiality throughout the study.

Izinto zokwakha

N/A

Emisha

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

1. Mobile health (mHealth) interventions: Develop and implement mobile applications or text messaging services to provide pregnant women with information about antenatal care, postpartum care, and facility delivery. These interventions can also send reminders for appointments and provide educational resources.

2. Telemedicine: Establish telemedicine services to connect pregnant women in remote or underserved areas with healthcare providers. This can enable remote consultations, monitoring, and guidance throughout pregnancy, reducing the need for travel and improving access to healthcare.

3. Community health workers: Train and deploy community health workers to provide maternal health education, counseling, and support in rural and peri-urban areas. These workers can conduct home visits, facilitate referrals, and address barriers to accessing healthcare.

4. Transport solutions: Develop transportation systems or initiatives specifically designed to address the transportation challenges faced by pregnant women in reaching healthcare facilities. This could include providing affordable or subsidized transportation options or partnering with existing transportation services.

5. Maternal waiting homes: Establish maternal waiting homes near healthcare facilities to accommodate pregnant women who live far away and need to stay closer to the facility towards the end of their pregnancy. These homes can provide a safe and supportive environment for women to wait for labor and delivery.

6. Financial incentives: Implement financial incentive programs to encourage pregnant women to seek antenatal care, deliver in healthcare facilities, and attend postpartum check-ups. This could involve providing cash transfers, vouchers, or other forms of financial support.

7. Quality improvement initiatives: Implement quality improvement initiatives in healthcare facilities to ensure that maternal health services are accessible, equitable, and of high quality. This could involve training healthcare providers, improving infrastructure, and strengthening supply chains for essential maternal health commodities.

8. Public-private partnerships: Foster collaborations between the public and private sectors to improve access to maternal health services. This could involve leveraging private sector resources and expertise to expand healthcare infrastructure, improve service delivery, and increase affordability.

9. Health information systems: Strengthen health information systems to collect, analyze, and utilize data on maternal health service utilization. This can help identify gaps in access, monitor progress, and inform evidence-based decision-making.

10. Policy and advocacy: Advocate for policies and interventions that prioritize and address the barriers to accessing maternal health services. This could involve engaging with policymakers, raising awareness, and mobilizing resources to support maternal health initiatives.

It is important to note that the specific context and needs of the Mwanza Region in Tanzania should be taken into consideration when implementing these innovations.

AI Innovations Description

Based on the information provided, the following recommendation can be developed into an innovation to improve access to maternal health:

Encouraging early initiation of antenatal care (ANC) visits: The study found that early initiation of ANC visits during pregnancy influences the number of ANC visits, leading to higher uptake of ANC4+ (four or more ANC visits) and health facility delivery. Therefore, an innovation could be developed to promote and incentivize early initiation of ANC visits among pregnant women. This could include community-based awareness campaigns, mobile health applications, or telemedicine services that provide information and reminders about the importance of early ANC visits and facilitate easy access to healthcare providers.

By implementing this recommendation, it is expected that more pregnant women will receive adequate ANC, leading to improved maternal and newborn health outcomes.

AI Innovations Methodology

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

1. Strengthening Antenatal Care (ANC) Services: Focus on increasing the number of ANC visits by promoting early initiation of ANC visits and educating women about the importance of regular check-ups during pregnancy.

2. Enhancing Health Facility Delivery: Implement strategies to encourage more women to deliver in health facilities with the assistance of skilled birth attendants. This can be achieved through community awareness campaigns, improving the quality of maternity services, and addressing barriers such as transportation and cost.

3. Promoting Postpartum Care: Increase the uptake of postpartum care by ensuring that all women receive a postpartum check-up after delivery. This can be done by improving access to postpartum services, providing education on the importance of postpartum care, and involving community health workers in follow-up visits.

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

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the percentage of women receiving four or more ANC visits, the percentage of women delivering in health facilities, and the percentage of women attending postpartum check-ups.

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

3. Introduce the recommendations: Implement the recommended interventions, such as awareness campaigns, training programs for healthcare providers, and infrastructure improvements.

4. Monitor and collect data: Continuously collect data on the selected indicators to track changes over time. This can be done through regular surveys, monitoring systems, or health facility records.

5. Analyze the data: Use statistical analysis techniques to compare the baseline data with the data collected after implementing the recommendations. This will help determine the impact of the interventions on improving access to maternal health.

6. Evaluate the results: Assess the effectiveness of the recommendations by analyzing the changes in the selected indicators. Determine if the interventions have led to improvements in access to maternal health and identify any areas that may require further attention.

By following this methodology, it will be possible to simulate the impact of the recommendations on improving access to maternal health and evaluate the effectiveness of the interventions.

Umbhali

Dima Health

Statistics:

Citations: 6

Identifiers:

DOI: 10.1186/s12884-019-2653-4

Research Areas:

Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Workforce

Study Countries:

Tanzania

Study Design:

Cohort Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female

Yabelana ngalokhu: