Factors Associated with Underutilization of Maternity Health Care Cascade in Mozambique: Analysis of the 2015 National Health Survey

International Journal of Environmental Research and Public Health, Volume 19, No. 13, Year 2022

Ukuhunyushwa

Maternity health care services utilization determines maternal and neonate outcomes. Evidence about factors associated with composite non-utilization of four or more antenatal con-sultations and intrapartum health care services is needed in Mozambique. This study uses data from the 2015 nationwide Mozambique’s Malaria, Immunization and HIV Indicators Survey. At selected representative households, women (n = 2629) with child aged up to 3 years answered a standardized structured questionnaire. Adjusted binary logistic regression assessed associations between women-child pairs characteristics and non-utilization of maternity health care. Seventy five percent (95% confidence interval (CI) = 71.8–77.7%) of women missed a health care cascade step during their last pregnancy. Higher education (adjusted odds ratio (AOR) = 0.65; 95% CI = 0.46–0.91), lowest wealth (AOR = 2.1; 95% CI = 1.2–3.7), rural residency (AOR = 1.5; 95% CI = 1.1–2.2), living distant from health facility (AOR = 1.5; 95% CI = 1.1–1.9) and unknown HIV status (AOR = 1.9; 95% CI = 1.4–2.7) were factors associated with non-utilization of the maternity health care cascade. The study highlights that, by 2015, recommended maternity health care cascade utilization did not cover 7 out of 10 pregnant women in Mozambique. Unfavorable sociodemographic and economic factors increase the relative odds for women not being covered by the maternity health care cascade. This study is based on a secondary analysis of the 2015 Mozambique national survey on HIV, malaria and immunization indicators (MZAIS 2015, locally designed as IMASIDA 2015). The survey applied women and child health questionnaires to which respondents were women of childbearing age (15–49 years old). The survey collected general household composition, assets and family members characteristics, demographics of the women and of their child/ren born since January 2010, child health, women reproductive characteristics and utilization of health services during pregnancy (antenatal, delivery and post-natal care); this latest survey primarily aimed to estimate HIV prevalence in the adult population and malaria prevalence amongst children. Specific HIV and malaria questions and biomarkers were also available, but were deemed not required for the current assessment. The data is publicly available on request through the Demographic and Health Survey Program (DHS) website—www.dhsprogram.com/data (accessed on 5 January 2019) [7]. The survey used a multistage random sampling that was representative at provinces, national and rural-urban levels. Sampling strategies and detailed survey procedures are published in the survey report [30] and in Demographics and Health Surveys program’s reference documents [6]. A 7169-household sample was included in the MZAIS 2015 survey. The survey had above 97% response rate and included 7749 women aged 15–49 years for interview on reproductive, maternal and child health. While the survey included women with children up to 5 years old by the time the survey was implemented, comprehensive questionnaires on reproductive health and experiences with health services, namely ANC, ID and PNC, were applied to women who gave birth to children between 1 January 2013 and the survey date [31]. Thus, this study uses a MZAIS 2015 sub-sample of 2629 Mozambican women, who had a living child born between 1 January 2013 and the interview date in 2015. Control variables are contingent to the MZAIS 2015 questionnaires. These include sociodemographic characteristic such as age, marital status, employment, schooling, wealth index, accessibility to health facility, place of residence, health-seeking behavior and other health matters (e.g., immunization, HIV status, knowledge). We transformed some covariates into commonly used factors. For example, age was recorded in years, but was thereby recoded to the commonly used 5-year span categories; the family members number, and time to reach a health setting, primarily recorded as discrete numbers, were both categorized into binary variables; having access to, and use of television or radio or newspaper were composed into “access to media”; several questions on how decisions are taken within households allowed to compose “participating in household decision”; the child immunization status was adjusted to the child’s age and national immunization calendar [32], which allowed to compute a binary variable “immunization up-to-date”. Wealth index was computed by the data provider using household assets principal components analysis. Survey weights were also provided by the DHS program. Computation methods are published in the DHS program reference manual [6]. All other categorical variables were composed and used as routinely applied in similar studies using DHS program databases [29,33]. Several stepwise computations were conducted to prepare intermediate standalone binary variables as components of the maternity health care cascade, according to the following: (i) any number of ANC for the index birth; (ii) any number of ANC with skilled health professional, being skilled professional midwife or mother and child health nurse or doctor; (iii) 4 or more ANC; (iv) 4 or more ANC provided by skilled health worker; (v) adequate ANC content, adopting similar approach from published literature [13]; the “adequate ANC content” is defined if women had at least 0.75 (3 or more) of the 5 ANC components, namely counselling on HIV vertical transmissions, measures to prevent HIV infection, how to access HIV testing, how to perform an HIV test and malaria chemoprophylaxis; (vi) institutional delivery in a health center or hospital; vii) post-childbirth consultation by the 28th day; (viii) consultation by the 28th day post birth with a skilled health worker; (ix) post-birth consultation by the 60th day and (x) post-birth consultation by 60 days post birth with a skilled worker. Appendix A, Table A2 describes outputs of the abovementioned maternity health care standalone indicators, relative frequencies and 95% confidence intervals. The computation of “qualified” health facility excluded the health posts. This exclusion considers the fact that health centers and hospitals are exclusively the Mozambican health facility types qualified for basic (BEmNOC) and comprehensive (CEmNOC) emergency neonatal and obstetric health care, respectively. This construct is thereby aligned to national policies [25,34]. We excluded community health workers from skilled health professionals since, by the year 2015, they were neither trained nor qualified to assist and were not allowed to classify perinatal and obstetric cases according to the, then, national policy [35]. The non-utilization the PNC cascade step was only considered in the descriptive analysis outputs shown in Figure 1 and Appendix A, Table A2. The specific PNC stand-alone indicator computation considered: (i) an intermediate PNC step, that is, whether the neonate-mother dyad had PNC within 28 days post birth and (ii) whether the neonate-mother dyad had a consultation completed within 60 days post birth. These cut-offs of the post-birth consultation periods are both of much interest for early HIV diagnosis and treatment initiation amongst HIV-exposed infants as established by national health care guidelines [3,23,34]. The computation of both PNC standalone indicators as guided by HIV program policy was deemed important given the high HIV prevalence (15%) amongst Mozambican women of childbearing age, one of the highest HIV prevalence worldwide [30,36]. Levels of non-utilization of select maternity health care cascade components among women respondents (n = 2629) of the 2015 national health survey, Mozambique. Notes: ANC—ante natal consultation, HF—health facility; PNC—postpartum (post-natal) consultation. We constructed the dependent variable, after the above explained stepwise stand-alone intermediate health care cascade indicators, based on published concepts about maternal and child health care [16]. In turn, the dependent variable used for the regression analysis is thereby, sequential, and conditional to non-utilization of 1, 2, 3, 4 or more ANC with skilled professional, or delivery out of a qualified health center or hospital. Thus, the dependent variable was computed as a binary composite variable comprising non-utilization of, any ANC or four or more ANC or ID in a qualified health facility. Because non-utilization of the maternity health care cascade is the outcome of interest, for analysis purposes, non-utilization is coded as success taking the value 1, while utilization is coded as 0. We first conducted univariate analysis to describe the women’s sociodemographic and economic characteristics and presented weighted proportions and 95% confidence intervals. Second, we described non-utilization proportions for each step of the maternity health care cascade and its respective 95% confidence intervals. Third, we cross-tabulated the “maternity health care cascade” non-utilization from ANC up to ID against sociodemographic, reproductive and health-seeking behavioral factors, and presented crude odds ratios (COR) and COR 95% confidence intervals (CI). In step four, we used binary logistic regression to compute adjusted odds ratios (AOR) and respective 95% confidence interval to identify factors with definitive significant associations with the dependent variable. Confidence intervals not crossing the null value (null = 1) indicated statistically significant associations. Computation, transformations, recodification and analysis were performed using the Statistical Package for Social Sciences (SPSS version 24.0 (New York, NY, USA)). All analyses were weighted and adjusted for the survey complex sampling.

I-AI Digest

Study Justification:

This study aims to investigate the factors associated with the underutilization of maternity health care services in Mozambique. The utilization of these services is crucial for ensuring positive maternal and neonatal outcomes. By analyzing data from the 2015 National Health Survey, the study provides valuable insights into the barriers that prevent pregnant women from accessing adequate antenatal and intrapartum care.

Highlights:

– The study found that 75% of women in Mozambique did not fully utilize the recommended maternity health care cascade during their last pregnancy.
– Factors associated with non-utilization of maternity health care included higher education, lowest wealth, rural residency, living distant from health facilities, and unknown HIV status.
– The study highlights the need to address unfavorable sociodemographic and economic factors that contribute to the underutilization of maternity health care services.

Recommendations:

– Improve access to maternity health care services in rural areas by increasing the number of health facilities and improving transportation infrastructure.
– Implement targeted interventions to address the barriers faced by women with lower education and wealth status.
– Strengthen HIV testing and counseling services to ensure that pregnant women have access to appropriate care and treatment.
– Enhance community awareness and education programs to promote the importance of maternity health care utilization.

Key Role Players:

– Ministry of Health: Responsible for developing and implementing policies and programs to improve maternity health care services.
– Health Care Providers: Including doctors, midwives, and nurses who play a crucial role in delivering quality antenatal and intrapartum care.
– Community Health Workers: Involved in raising awareness, providing education, and facilitating access to maternity health care services.
– Non-Governmental Organizations (NGOs): Collaborating with the government to implement interventions and support the improvement of maternity health care services.

Cost Items for Planning Recommendations:

– Infrastructure Development: Construction and renovation of health facilities, including maternity wards and clinics.
– Transportation: Investment in ambulances and transportation systems to ensure pregnant women can access health facilities.
– Training and Capacity Building: Providing education and training programs for health care providers and community health workers.
– Awareness Campaigns: Funding for community outreach programs, health education materials, and media campaigns.
– HIV Testing and Treatment: Resources for HIV testing kits, antiretroviral drugs, and counseling services.
Please note that the cost items provided are general categories and not actual cost estimates. The specific costs will depend on the context and scale of the interventions implemented.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a secondary analysis of a national survey, which provides a relatively strong foundation. The study uses a large sample size and applies statistical analysis to identify factors associated with non-utilization of maternity health care. However, the abstract does not provide information on the specific methodology used for the analysis, such as the regression model employed. To improve the evidence, the abstract could include more details on the statistical methods used, such as the type of logistic regression model and any adjustments made for confounding variables. Additionally, it would be helpful to provide information on the limitations of the study, such as potential biases or sources of error in the data collection process.

Abstract

This study is based on a secondary analysis of the 2015 Mozambique national survey on HIV, malaria and immunization indicators (MZAIS 2015, locally designed as IMASIDA 2015). The survey applied women and child health questionnaires to which respondents were women of childbearing age (15–49 years old). The survey collected general household composition, assets and family members characteristics, demographics of the women and of their child/ren born since January 2010, child health, women reproductive characteristics and utilization of health services during pregnancy (antenatal, delivery and post-natal care); this latest survey primarily aimed to estimate HIV prevalence in the adult population and malaria prevalence amongst children. Specific HIV and malaria questions and biomarkers were also available, but were deemed not required for the current assessment. The data is publicly available on request through the Demographic and Health Survey Program (DHS) website—www.dhsprogram.com/data (accessed on 5 January 2019) [7]. The survey used a multistage random sampling that was representative at provinces, national and rural-urban levels. Sampling strategies and detailed survey procedures are published in the survey report [30] and in Demographics and Health Surveys program’s reference documents [6]. A 7169-household sample was included in the MZAIS 2015 survey. The survey had above 97% response rate and included 7749 women aged 15–49 years for interview on reproductive, maternal and child health. While the survey included women with children up to 5 years old by the time the survey was implemented, comprehensive questionnaires on reproductive health and experiences with health services, namely ANC, ID and PNC, were applied to women who gave birth to children between 1 January 2013 and the survey date [31]. Thus, this study uses a MZAIS 2015 sub-sample of 2629 Mozambican women, who had a living child born between 1 January 2013 and the interview date in 2015. Control variables are contingent to the MZAIS 2015 questionnaires. These include sociodemographic characteristic such as age, marital status, employment, schooling, wealth index, accessibility to health facility, place of residence, health-seeking behavior and other health matters (e.g., immunization, HIV status, knowledge). We transformed some covariates into commonly used factors. For example, age was recorded in years, but was thereby recoded to the commonly used 5-year span categories; the family members number, and time to reach a health setting, primarily recorded as discrete numbers, were both categorized into binary variables; having access to, and use of television or radio or newspaper were composed into “access to media”; several questions on how decisions are taken within households allowed to compose “participating in household decision”; the child immunization status was adjusted to the child’s age and national immunization calendar [32], which allowed to compute a binary variable “immunization up-to-date”. Wealth index was computed by the data provider using household assets principal components analysis. Survey weights were also provided by the DHS program. Computation methods are published in the DHS program reference manual [6]. All other categorical variables were composed and used as routinely applied in similar studies using DHS program databases [29,33]. Several stepwise computations were conducted to prepare intermediate standalone binary variables as components of the maternity health care cascade, according to the following: (i) any number of ANC for the index birth; (ii) any number of ANC with skilled health professional, being skilled professional midwife or mother and child health nurse or doctor; (iii) 4 or more ANC; (iv) 4 or more ANC provided by skilled health worker; (v) adequate ANC content, adopting similar approach from published literature [13]; the “adequate ANC content” is defined if women had at least 0.75 (3 or more) of the 5 ANC components, namely counselling on HIV vertical transmissions, measures to prevent HIV infection, how to access HIV testing, how to perform an HIV test and malaria chemoprophylaxis; (vi) institutional delivery in a health center or hospital; vii) post-childbirth consultation by the 28th day; (viii) consultation by the 28th day post birth with a skilled health worker; (ix) post-birth consultation by the 60th day and (x) post-birth consultation by 60 days post birth with a skilled worker. Appendix A, Table A2 describes outputs of the abovementioned maternity health care standalone indicators, relative frequencies and 95% confidence intervals. The computation of “qualified” health facility excluded the health posts. This exclusion considers the fact that health centers and hospitals are exclusively the Mozambican health facility types qualified for basic (BEmNOC) and comprehensive (CEmNOC) emergency neonatal and obstetric health care, respectively. This construct is thereby aligned to national policies [25,34]. We excluded community health workers from skilled health professionals since, by the year 2015, they were neither trained nor qualified to assist and were not allowed to classify perinatal and obstetric cases according to the, then, national policy [35]. The non-utilization the PNC cascade step was only considered in the descriptive analysis outputs shown in Figure 1 and Appendix A, Table A2. The specific PNC stand-alone indicator computation considered: (i) an intermediate PNC step, that is, whether the neonate-mother dyad had PNC within 28 days post birth and (ii) whether the neonate-mother dyad had a consultation completed within 60 days post birth. These cut-offs of the post-birth consultation periods are both of much interest for early HIV diagnosis and treatment initiation amongst HIV-exposed infants as established by national health care guidelines [3,23,34]. The computation of both PNC standalone indicators as guided by HIV program policy was deemed important given the high HIV prevalence (15%) amongst Mozambican women of childbearing age, one of the highest HIV prevalence worldwide [30,36]. Levels of non-utilization of select maternity health care cascade components among women respondents (n = 2629) of the 2015 national health survey, Mozambique. Notes: ANC—ante natal consultation, HF—health facility; PNC—postpartum (post-natal) consultation. We constructed the dependent variable, after the above explained stepwise stand-alone intermediate health care cascade indicators, based on published concepts about maternal and child health care [16]. In turn, the dependent variable used for the regression analysis is thereby, sequential, and conditional to non-utilization of 1, 2, 3, 4 or more ANC with skilled professional, or delivery out of a qualified health center or hospital. Thus, the dependent variable was computed as a binary composite variable comprising non-utilization of, any ANC or four or more ANC or ID in a qualified health facility. Because non-utilization of the maternity health care cascade is the outcome of interest, for analysis purposes, non-utilization is coded as success taking the value 1, while utilization is coded as 0. We first conducted univariate analysis to describe the women’s sociodemographic and economic characteristics and presented weighted proportions and 95% confidence intervals. Second, we described non-utilization proportions for each step of the maternity health care cascade and its respective 95% confidence intervals. Third, we cross-tabulated the “maternity health care cascade” non-utilization from ANC up to ID against sociodemographic, reproductive and health-seeking behavioral factors, and presented crude odds ratios (COR) and COR 95% confidence intervals (CI). In step four, we used binary logistic regression to compute adjusted odds ratios (AOR) and respective 95% confidence interval to identify factors with definitive significant associations with the dependent variable. Confidence intervals not crossing the null value (null = 1) indicated statistically significant associations. Computation, transformations, recodification and analysis were performed using the Statistical Package for Social Sciences (SPSS version 24.0 (New York, NY, USA)). All analyses were weighted and adjusted for the survey complex sampling.

Izinto zokwakha

N/A

Emisha

Based on the information provided, it seems that the study is focused on identifying factors associated with the underutilization of maternity health care services in Mozambique. The study uses data from the 2015 Mozambique national survey on HIV, malaria, and immunization indicators.

To improve access to maternal health in Mozambique, the following innovations could be considered:

1. Mobile health (mHealth) interventions: Implementing mobile phone-based interventions to provide information and reminders about antenatal care visits, immunizations, and postnatal care. This could help overcome barriers such as distance to health facilities and lack of awareness.

2. Community health worker programs: Expanding and strengthening community health worker programs to provide education, counseling, and support to pregnant women and new mothers in remote areas. Community health workers can help bridge the gap between communities and health facilities.

3. Transport solutions: Developing transportation solutions, such as community ambulances or transportation vouchers, to ensure that pregnant women can reach health facilities in a timely manner, especially in rural areas with limited access to transportation.

4. Financial incentives: Introducing financial incentives, such as conditional cash transfers or maternity vouchers, to encourage pregnant women to seek and utilize maternal health care services. This could help address financial barriers and increase utilization rates.

5. Telemedicine services: Implementing telemedicine services to enable remote consultations between pregnant women and healthcare providers. This could be particularly beneficial for women living in remote areas with limited access to healthcare facilities.

6. Quality improvement initiatives: Implementing quality improvement initiatives at health facilities to ensure that pregnant women receive high-quality and respectful care. This could include training healthcare providers, improving infrastructure, and strengthening infection prevention and control measures.

These innovations have the potential to improve access to maternal health care services in Mozambique by addressing various barriers and challenges identified in the study. However, it is important to note that the feasibility and effectiveness of these innovations would need to be further assessed and tailored to the specific context and needs of Mozambique.

AI Innovations Description

The study titled “Factors Associated with Underutilization of Maternity Health Care Cascade in Mozambique: Analysis of the 2015 National Health Survey” provides important insights into the factors contributing to the underutilization of maternal health care services in Mozambique. The study used data from the 2015 Mozambique’s Malaria, Immunization and HIV Indicators Survey, which included women aged 15-49 years with a child aged up to 3 years.

The study found that 75% of women in Mozambique missed a step in the maternity health care cascade during their last pregnancy. Several factors were identified as being associated with non-utilization of maternity health care. These factors include higher education, lowest wealth, rural residency, living distant from a health facility, and unknown HIV status.

To improve access to maternal health in Mozambique, the following recommendations can be considered:

1. Improve education: Promote education and awareness about the importance of maternal health care among women and their families. This can be done through community-based education programs, campaigns, and partnerships with local organizations.

2. Address economic barriers: Implement strategies to address the economic barriers that prevent women from accessing maternal health care. This can include providing financial support for transportation to health facilities, reducing or eliminating user fees, and improving the availability of affordable maternal health services.

3. Enhance rural health infrastructure: Invest in improving the availability and quality of health facilities in rural areas. This can include building new health centers, upgrading existing facilities, and ensuring the availability of skilled health professionals in rural areas.

4. Strengthen community-based care: Promote community-based care models that bring maternal health services closer to women in remote areas. This can involve training and empowering community health workers to provide basic maternal health services, conducting outreach programs, and facilitating referrals to higher-level health facilities when needed.

5. Improve HIV testing and counseling: Strengthen efforts to increase HIV testing and counseling during pregnancy. This can include integrating HIV services into antenatal care, providing training to health workers on HIV prevention and treatment, and ensuring the availability of HIV testing and treatment services.

By implementing these recommendations, Mozambique can work towards improving access to maternal health care and reducing the underutilization of maternity health care services, ultimately leading to better maternal and neonatal outcomes.

AI Innovations Methodology

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

1. Strengthening education: Implement programs that focus on increasing the education level of women, as higher education was found to be associated with a lower likelihood of non-utilization of maternity health care.

2. Addressing economic disparities: Develop interventions that target the poorest populations, as the study found that women from the lowest wealth index were more likely to not utilize maternity health care. This could involve providing financial support or subsidies for maternal health services.

3. Improving rural access: Enhance transportation infrastructure and increase the number of health facilities in rural areas to reduce the barriers faced by women living in remote locations.

4. HIV testing and counseling: Promote HIV testing and counseling services during antenatal care visits to ensure that women are aware of their HIV status and can access appropriate care and treatment.

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

1. Define indicators: Identify specific indicators that measure access to maternal health, such as the percentage of women receiving the recommended number of antenatal care visits or the percentage of women delivering in a health facility.

2. Data collection: Collect data on the selected indicators before implementing the recommendations. This could involve conducting surveys or utilizing existing data sources, such as national health surveys or routine health information systems.

3. Implement recommendations: Introduce the recommended interventions, such as education programs, economic support initiatives, infrastructure improvements, and HIV testing and counseling services.

4. Data collection after implementation: Collect data on the same indicators after implementing the recommendations. This could be done through follow-up surveys or by analyzing routine health information systems data.

5. Analyze and compare data: Compare the data collected before and after implementing the recommendations to assess the impact. This could involve calculating the changes in the selected indicators and conducting statistical analyses to determine the significance of the changes.

6. Interpret and report findings: Interpret the findings of the analysis and report on the impact of the recommendations on improving access to maternal health. This could include discussing the magnitude of the changes observed and any associations between the recommendations and the indicators.

By following this methodology, policymakers and stakeholders can gain insights into the potential impact of the recommendations and make informed decisions on how to improve access to maternal health in Mozambique.

Umbhali

Dima Health

Identifiers:

DOI: 10.3390/ijerph19137861

ISSN: 16617827

Research Areas:

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

Study Countries:

Mozambique

Study Design:

Case-Control Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female

Yabelana ngalokhu: