Parity and institutional delivery in rural Tanzania: A multilevel analysis and policy implications

Health Policy and Planning, Volume 28, No. 6, Year 2013

Interprétation

Objectives We assess the extent to which the use of healthcare facilities for childbirth varies by parity, conditional on socio-economic, psychological and health characteristics. We also assess differences in the determinants of institutionalized delivery for first-time mothers and multiparous, and explore village-level variations in observed relationships.Methods Survey data from a three-stage cross-sectional cluster sample of 1205 women from a rural district of Tanzania were analysed using random-intercept multilevel models.Results Use of health facilities for delivery was low (39%), with odds of institutionalized delivery three times higher among nulliparous women (0 children prior to current delivery) compared with women with one to four children; and 30% lower among women with five or more children compared with those with one to four children. In parity group analyses, women with at least some education and women with more than three antenatal care visits had higher odds of institutionalized delivery among nulliparous. Belief in the importance of institutionalized delivery increased the odds of delivering in a facility among multiparous women; so did health insurance for women with five or more children. We found a significant variation in institutionalized delivery among multiparous women based on their village of residence (one to four and five or more children), but these variations were not observed among nulliparous women.Conclusion Parity is a pivotal determinant of the use of health facilities for delivery, and its significance varies by village of residence; hence, interventions targeting women according to parity may increase the use of facilities for delivery in rural Tanzania. Future research should focus on the village-level characteristics that influence institutionalized delivery in multiparous. © 2012 Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2012; all rights reserved. We used data from a cross-sectional survey of a representative sample of Tanzanian women living in the District of Kasulu in Tanzania (population of 630 000). The District of Kasulu is an isolated rural area, in the administrative Region of Kigoma, which nears the western border of the Democratic Republic of Congo. Most residents of the district are farmers, from the Muha tribe, and speak Kiha, the local language, and Swahili, the national language. The main town in the district of Kasulu, with ∼33 000 residents, was omitted from the study to reduce population heterogeneity. More information about the setting can be found in Kruk et al. (2008). The sampling methods relied on a three-stage representative cluster sampling of women living in rural Kasulu District. In the first stage, 50 villages were randomly selected from a total of 89 villages, with probability proportional to village size, determined using the 2002 Tanzania census. The villages in rural Kasulu are divided into subvillages approximately similar in size. In the second stage, one subvillage was randomly selected among subvillages in each village. In the final stage, subvillage leaders provided an exhaustive list of households, and 35 households were randomly selected from each subvillage, out of a total of 100. From each household, women aged 18 or older who had a child within the 5 years prior to study recruitment were invited to participate. The study received approval from both the National Institute for Medical Research in Tanzania and the Institutional Review Board at the University of Michigan. Face-to-face surveys translated into Swahili and back-translated into English for accuracy were administered to a total of 1205 (91% response rate) eligible women between June and mid-July of 2007. The questionnaires were administered by two teams of interviewers fluent in Swahili, with at least one interviewer fluent in Kiha. Each interview took ∼30 min, and an observer checked the reliability of the survey administration through daily field observations. The surveys asked questions about maternal health services utilization, childbirth history, household composition and assets, perceptions and knowledge about the local health system and barriers to health services utilization. The use of healthcare facility for delivery was coded as a dichotomous variable (1 = used a government, mission or private healthcare facility for delivery; 0 = delivered at a friend’s home or own home). The main predictor, ‘prior parity’ was assessed via a question about the number of children respondents had prior to the current delivery being investigated. Prior parity was categorized as no child (nulliparous), one to four children (multiparous) and five or more children (grand multiparous). This categorization is medically and socially relevant to the study of health services utilization. Since Solomons’ study of pregnancy outcome, it is widely accepted that women with more than four children are at increased risk of adverse maternal outcome (Solomons 1934); and thus high parity is likely to affect women’s self-appraisal of the risks and benefits of childbirth. Socially, however, women with a high number of children and uncomplicated deliveries may be attempted to bypass institutionalized delivery, especially if they did not encounter any complications (Stephenson and Tsui 2002). Women pregnant with their first-born child, on the other hand, may feel anxious to have a healthy child, and consequently more frequently use healthcare facility for delivery (Gabrysch and Campbell 2009). Women’s beliefs were measured with a self-assessed question on respondents’ beliefs of the importance of delivering in a healthcare facility for the health of the child and mother (1 = very important; 0 = important to not important). This categorization was necessary as most women’s response choices fell between the first two categories. In addition to parity, other socio-demographic characteristics relevant to the study of maternal health service utilization were included (World Bank 1999; Bloom et al. 2001; Van Den Broek 2003; Smith et al. 2004; Stekelenburg et al. 2004; Montgomery and Hewitt 2005; Magadi et al. 2007). These were age at childbirth (1 = 35 or older, 0 = younger than 35), marital status (1 = married; 0 = other), education (1 = some formal education; 0 = no formal education) and household poverty (1 = in the poorest household wealth index quintile). Education was used as a dichotomous variable for ease of interpretation, and because preliminary analyses showed similar associations for having less than high school education and high school education with the outcome, without substantive changes to the coefficients of the other covariates. The household wealth index was obtained by performing a principal components analysis based on 10 household assets (radio, bicycle, number of bed-nets, etc.). Households were then allocated into wealth quintiles. More information on the household wealth index can be found in Kruk et al. (2008). The use of a healthcare facility for delivery may also be influenced by women’s appraisal of threat, which is shaped by their knowledge, previous experiences such as complicated pregnancies, behaviour/treatment of attendants and personal biases and beliefs (Corbin 1987; Patterson 1993; Lazarus and Folkman 1984). One item asking whether respondents had at least one stillborn child or infant death was included in the analysis (1 = yes; 0 = no). We also included perceived quality of the nearest health facility, such as dispensary, health centre, hospital (1 = excellent, very good, good; 0 = fair or poor); and satisfaction with antenatal care (1 = very satisfied, fairly satisfied; 0 = fairly dissatisfied, very dissatisfied). In preliminary analyses, however, the latter two variables were not significantly related to the outcome, and did not significantly contribute to the estimation models. They were, therefore, not included in the final analyses. Access to resources was measured as insurance coverage (1 = insured; 0 = not insured) and use of antenatal care services (1 = at least four visits; 0 = less than four visits), whereas health status was measured as self-rated health on a five-point Likert scale (1 = very good to 5 = very bad). Four antenatal visits were used based on findings from a World Health Organization (WHO) randomized controlled trial. In this study, a minimum of four visits prior to childbirth had the optimal effect on positive birth outcomes (WHO 2002). We included four measures of community characteristics (community defined here as village), often cited in the literature: village physical characteristics (accessibility: distance from facility, road network), economic characteristics (village poverty) and social characteristics (female empowerment and freedom of choice: female literacy). Individual responses were aggregated at the village level and corresponding village estimates were computed for each variable, and assigned to the corresponding respondents. These were as follows: distance to the nearest facility in kilometres; percent female literacy in the village; type of road network (mostly primary, mostly secondary or mostly tertiary roads) and village poverty measured as the percent residents in the lowest quintiles within each village. Descriptive statistics were computed taking the complex design and nested-structure of the data into account. Rao–Scott chi-square tests for categorical variables and univariate linear combinations comparing variable means were performed to describe the total sample and parity groups. Because respondents living in the same village are more alike to each other (in observed and non-observable ways) than they are alike to respondents in other villages, and as some determinants of utilization may function at an area level, we used a random-intercept multilevel model (Raudenbush and Bryk 2002). First, the data were fitted to an empty random-intercept model to describe the total variance in the outcome attributable to context. Subsequently, parity was entered into the model, followed by other individual characteristics and the four village characteristics of interest. To test our second set of hypotheses of parity as a moderator, we ran similar models as described earlier within parity groups. Multilevel analyses were performed using the command xtlogit STATA 11® (Rabe-Hesketh and Skrondal 2008).

Résumé de l’IA

Study Justification:

– The study aims to assess the factors influencing the use of healthcare facilities for childbirth in rural Tanzania, specifically focusing on the role of parity (number of children a woman has had prior to the current delivery).
– Understanding the determinants of institutionalized delivery can help inform interventions and policies to increase the use of facilities for delivery in rural areas.
– The study also explores village-level variations in the relationship between parity and institutionalized delivery, providing insights into the contextual factors that may influence utilization of healthcare facilities.

Study Highlights:

– The use of healthcare facilities for delivery in rural Tanzania is low, with only 39% of women utilizing these facilities.
– Nulliparous women (women with no children prior to the current delivery) have higher odds of institutionalized delivery compared to women with one to four children.
– Among nulliparous women, those with some education and more antenatal care visits have higher odds of institutionalized delivery.
– Belief in the importance of institutionalized delivery increases the odds of delivering in a facility among multiparous women (women with five or more children).
– Health insurance also increases the odds of institutionalized delivery among multiparous women with five or more children.
– There is significant variation in institutionalized delivery among multiparous women based on their village of residence, but no such variations are observed among nulliparous women.

Recommendations for Lay Reader and Policy Maker:

– Interventions targeting women according to parity may increase the use of healthcare facilities for delivery in rural Tanzania.
– Future research should focus on understanding the village-level characteristics that influence institutionalized delivery among multiparous women.

Key Role Players:

– Ministry of Health: Responsible for implementing policies and interventions to improve maternal healthcare services in rural areas.
– Local Health Authorities: Involved in coordinating and delivering healthcare services at the village level.
– Community Health Workers: Play a crucial role in educating and mobilizing women to utilize healthcare facilities for delivery.
– Non-Governmental Organizations: Provide support and resources for improving maternal healthcare services in rural areas.

Cost Items for Planning Recommendations:

– Training and capacity building for healthcare providers and community health workers.
– Infrastructure development and improvement of healthcare facilities.
– Outreach and awareness campaigns to educate women about the importance of institutionalized delivery.
– Health insurance coverage for women with multiple children.
– Monitoring and evaluation of interventions to assess their effectiveness and make necessary adjustments.

Force de la preuve

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study used a representative sample and employed multilevel analysis to examine the determinants of institutionalized delivery in rural Tanzania. However, the evidence could be strengthened by providing more details about the sampling methods, data collection procedures, and statistical analyses. Additionally, the abstract does not mention any limitations of the study, which could be addressed to improve the overall quality of the evidence.

Abstrait

We used data from a cross-sectional survey of a representative sample of Tanzanian women living in the District of Kasulu in Tanzania (population of 630 000). The District of Kasulu is an isolated rural area, in the administrative Region of Kigoma, which nears the western border of the Democratic Republic of Congo. Most residents of the district are farmers, from the Muha tribe, and speak Kiha, the local language, and Swahili, the national language. The main town in the district of Kasulu, with ∼33 000 residents, was omitted from the study to reduce population heterogeneity. More information about the setting can be found in Kruk et al. (2008). The sampling methods relied on a three-stage representative cluster sampling of women living in rural Kasulu District. In the first stage, 50 villages were randomly selected from a total of 89 villages, with probability proportional to village size, determined using the 2002 Tanzania census. The villages in rural Kasulu are divided into subvillages approximately similar in size. In the second stage, one subvillage was randomly selected among subvillages in each village. In the final stage, subvillage leaders provided an exhaustive list of households, and 35 households were randomly selected from each subvillage, out of a total of 100. From each household, women aged 18 or older who had a child within the 5 years prior to study recruitment were invited to participate. The study received approval from both the National Institute for Medical Research in Tanzania and the Institutional Review Board at the University of Michigan. Face-to-face surveys translated into Swahili and back-translated into English for accuracy were administered to a total of 1205 (91% response rate) eligible women between June and mid-July of 2007. The questionnaires were administered by two teams of interviewers fluent in Swahili, with at least one interviewer fluent in Kiha. Each interview took ∼30 min, and an observer checked the reliability of the survey administration through daily field observations. The surveys asked questions about maternal health services utilization, childbirth history, household composition and assets, perceptions and knowledge about the local health system and barriers to health services utilization. The use of healthcare facility for delivery was coded as a dichotomous variable (1 = used a government, mission or private healthcare facility for delivery; 0 = delivered at a friend’s home or own home). The main predictor, ‘prior parity’ was assessed via a question about the number of children respondents had prior to the current delivery being investigated. Prior parity was categorized as no child (nulliparous), one to four children (multiparous) and five or more children (grand multiparous). This categorization is medically and socially relevant to the study of health services utilization. Since Solomons’ study of pregnancy outcome, it is widely accepted that women with more than four children are at increased risk of adverse maternal outcome (Solomons 1934); and thus high parity is likely to affect women’s self-appraisal of the risks and benefits of childbirth. Socially, however, women with a high number of children and uncomplicated deliveries may be attempted to bypass institutionalized delivery, especially if they did not encounter any complications (Stephenson and Tsui 2002). Women pregnant with their first-born child, on the other hand, may feel anxious to have a healthy child, and consequently more frequently use healthcare facility for delivery (Gabrysch and Campbell 2009). Women’s beliefs were measured with a self-assessed question on respondents’ beliefs of the importance of delivering in a healthcare facility for the health of the child and mother (1 = very important; 0 = important to not important). This categorization was necessary as most women’s response choices fell between the first two categories. In addition to parity, other socio-demographic characteristics relevant to the study of maternal health service utilization were included (World Bank 1999; Bloom et al. 2001; Van Den Broek 2003; Smith et al. 2004; Stekelenburg et al. 2004; Montgomery and Hewitt 2005; Magadi et al. 2007). These were age at childbirth (1 = 35 or older, 0 = younger than 35), marital status (1 = married; 0 = other), education (1 = some formal education; 0 = no formal education) and household poverty (1 = in the poorest household wealth index quintile). Education was used as a dichotomous variable for ease of interpretation, and because preliminary analyses showed similar associations for having less than high school education and high school education with the outcome, without substantive changes to the coefficients of the other covariates. The household wealth index was obtained by performing a principal components analysis based on 10 household assets (radio, bicycle, number of bed-nets, etc.). Households were then allocated into wealth quintiles. More information on the household wealth index can be found in Kruk et al. (2008). The use of a healthcare facility for delivery may also be influenced by women’s appraisal of threat, which is shaped by their knowledge, previous experiences such as complicated pregnancies, behaviour/treatment of attendants and personal biases and beliefs (Corbin 1987; Patterson 1993; Lazarus and Folkman 1984). One item asking whether respondents had at least one stillborn child or infant death was included in the analysis (1 = yes; 0 = no). We also included perceived quality of the nearest health facility, such as dispensary, health centre, hospital (1 = excellent, very good, good; 0 = fair or poor); and satisfaction with antenatal care (1 = very satisfied, fairly satisfied; 0 = fairly dissatisfied, very dissatisfied). In preliminary analyses, however, the latter two variables were not significantly related to the outcome, and did not significantly contribute to the estimation models. They were, therefore, not included in the final analyses. Access to resources was measured as insurance coverage (1 = insured; 0 = not insured) and use of antenatal care services (1 = at least four visits; 0 = less than four visits), whereas health status was measured as self-rated health on a five-point Likert scale (1 = very good to 5 = very bad). Four antenatal visits were used based on findings from a World Health Organization (WHO) randomized controlled trial. In this study, a minimum of four visits prior to childbirth had the optimal effect on positive birth outcomes (WHO 2002). We included four measures of community characteristics (community defined here as village), often cited in the literature: village physical characteristics (accessibility: distance from facility, road network), economic characteristics (village poverty) and social characteristics (female empowerment and freedom of choice: female literacy). Individual responses were aggregated at the village level and corresponding village estimates were computed for each variable, and assigned to the corresponding respondents. These were as follows: distance to the nearest facility in kilometres; percent female literacy in the village; type of road network (mostly primary, mostly secondary or mostly tertiary roads) and village poverty measured as the percent residents in the lowest quintiles within each village. Descriptive statistics were computed taking the complex design and nested-structure of the data into account. Rao–Scott chi-square tests for categorical variables and univariate linear combinations comparing variable means were performed to describe the total sample and parity groups. Because respondents living in the same village are more alike to each other (in observed and non-observable ways) than they are alike to respondents in other villages, and as some determinants of utilization may function at an area level, we used a random-intercept multilevel model (Raudenbush and Bryk 2002). First, the data were fitted to an empty random-intercept model to describe the total variance in the outcome attributable to context. Subsequently, parity was entered into the model, followed by other individual characteristics and the four village characteristics of interest. To test our second set of hypotheses of parity as a moderator, we ran similar models as described earlier within parity groups. Multilevel analyses were performed using the command xtlogit STATA 11® (Rabe-Hesketh and Skrondal 2008).

Matériaux

N/A

Innovations

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

1. Mobile health clinics: Implementing mobile health clinics that travel to rural areas can provide access to maternal health services for women who may not have easy access to healthcare facilities.

2. Telemedicine: Using telemedicine technology, healthcare providers can remotely provide prenatal care and consultations to women in rural areas, reducing the need for them to travel long distances for healthcare.

3. Community health workers: Training and deploying community health workers in rural areas can help educate and support pregnant women, provide basic prenatal care, and facilitate referrals to healthcare facilities when necessary.

4. Financial incentives: Providing financial incentives, such as cash transfers or vouchers, to pregnant women in rural areas can help offset the costs associated with accessing maternal health services, making it more affordable for them.

5. Improving transportation infrastructure: Investing in improving transportation infrastructure, such as roads and transportation services, can make it easier for pregnant women in rural areas to travel to healthcare facilities for prenatal care and delivery.

6. Education and awareness campaigns: Conducting education and awareness campaigns targeted at rural communities can help increase knowledge about the importance of maternal health services and encourage women to seek care during pregnancy.

7. Strengthening healthcare facilities: Investing in the infrastructure, equipment, and staffing of healthcare facilities in rural areas can improve the quality and availability of maternal health services, making them more accessible to pregnant women.

These innovations can help address the barriers to accessing maternal health services in rural areas and improve the health outcomes for pregnant women and their babies.

AI Innovations Description

The study mentioned in the description focuses on improving access to maternal health in rural Tanzania. The researchers found that the use of healthcare facilities for childbirth was low, with only 39% of women delivering in a facility. They also found that the likelihood of institutionalized delivery varied based on parity (number of children prior to current delivery) and other factors.

Based on their findings, the researchers made several recommendations to improve access to maternal health:

1. Target interventions based on parity: The study found that parity is a pivotal determinant of facility-based delivery. Interventions should be designed to specifically target women based on their parity. For example, interventions could focus on educating nulliparous women (women with no children prior to current delivery) about the benefits of delivering in a healthcare facility, while interventions for multiparous women (women with one to four children) could focus on addressing barriers to institutionalized delivery.

2. Address village-level variations: The study found significant variations in institutionalized delivery among multiparous women based on their village of residence. Future research should focus on understanding the village-level characteristics that influence institutionalized delivery in multiparous women. This information can help tailor interventions to specific villages and address the unique challenges they face.

3. Improve education and antenatal care: The study found that women with at least some education and women with more than three antenatal care visits had higher odds of institutionalized delivery among nulliparous women. This suggests that improving access to education and antenatal care services can increase the likelihood of facility-based delivery.

4. Address beliefs and insurance coverage: The study found that belief in the importance of institutionalized delivery increased the odds of delivering in a facility among multiparous women. Additionally, health insurance coverage was associated with higher odds of institutionalized delivery among women with five or more children. Interventions should focus on addressing beliefs and promoting health insurance coverage to encourage facility-based delivery.

Overall, the study highlights the importance of targeting interventions based on parity, addressing village-level variations, improving education and antenatal care, and addressing beliefs and insurance coverage to improve access to maternal health in rural Tanzania.

AI Innovations Methodology

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

1. Increase awareness and education: Implement programs to educate women and communities about the importance of institutionalized delivery and the benefits of accessing healthcare facilities for childbirth. This can be done through community health workers, local leaders, and mass media campaigns.

2. Improve transportation infrastructure: Enhance road networks and transportation systems to ensure that pregnant women can easily access healthcare facilities. This may involve building new roads, improving existing ones, or providing transportation subsidies for pregnant women.

3. Strengthen healthcare facilities: Invest in improving the quality and availability of healthcare facilities in rural areas. This can include training healthcare providers, ensuring the availability of essential equipment and supplies, and upgrading facilities to meet the needs of pregnant women.

4. Expand health insurance coverage: Increase access to health insurance for women, particularly those with multiple children. This can help reduce financial barriers to accessing healthcare facilities for childbirth.

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

1. Collect baseline data: Gather information on the current utilization of healthcare facilities for delivery, including the percentage of women using facilities, their socio-demographic characteristics, and any barriers they face.

2. Define indicators: Identify key indicators to measure the impact of the recommendations, such as the percentage increase in facility-based deliveries, changes in maternal and infant health outcomes, and improvements in women’s knowledge and attitudes towards institutionalized delivery.

3. Develop a simulation model: Use statistical modeling techniques, such as multilevel analysis or regression analysis, to simulate the potential impact of the recommendations on the identified indicators. This model should take into account the baseline data, as well as the specific characteristics of the population and healthcare system in rural Tanzania.

4. Run simulations: Apply the simulation model to estimate the potential impact of each recommendation individually and in combination. This can help determine which interventions are most effective and how they interact with each other.

5. Evaluate results: Analyze the simulation results to assess the potential benefits and challenges of implementing the recommendations. Consider factors such as cost-effectiveness, feasibility, and sustainability.

6. Refine and implement interventions: Based on the simulation results, refine the recommendations and develop an implementation plan. This may involve collaborating with local stakeholders, policymakers, and healthcare providers to ensure the successful implementation of the interventions.

7. Monitor and evaluate: Continuously monitor the implementation of the interventions and evaluate their impact on access to maternal health. This can involve collecting data on key indicators over time and comparing them to the baseline data.

By following this methodology, policymakers and healthcare providers can make informed decisions about which interventions to prioritize and how to allocate resources effectively to improve access to maternal health in rural Tanzania.

Auteurs et co-auteurs

Statistics:

Citations: 23

Authors: 3

Identifiers:

DOI: 10.1093/heapol/czs104

ISSN: 02681080

Research Areas:

Community Interventions, Disparities, Genetics and Genomics, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health

Study Countries:

Congo, Multi-Countries, Tanzania

Study Design:

Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female

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