Equity in newborn care, evidence from national surveys in low- and middle-income countries

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Study Justification:
– High coverage of newborn care is crucial for improving newborn survival.
– Gaps exist in access to timely and appropriate newborn care between and within countries.
– Health inequities due to social and economic factors may impact newborn outcomes.
– This study aims to examine equity in co-coverage of newborn care interventions in low- and low middle-income countries in sub-Saharan Africa and South Asia.
Highlights:
– Large gaps in coverage and co-coverage of newborn care interventions between and within countries.
– Inequities based on individual, family, contextual, and structural factors.
– Wealth-based inequities are smaller among facility births compared to non-facility births.
– Facility birth is important for improved and more equitable newborn care.
– Shifting births to facilities, improving facility-based care, and community-based or pro-poor interventions are crucial to mitigate wealth-based inequities in newborn care.
Recommendations:
– Encourage facility births to improve newborn care.
– Improve facility-based care to ensure better outcomes.
– Implement community-based or pro-poor interventions to address inequities.
– Focus on countries with large differences between the poorest and richest families and low coverage of care.
Key Role Players:
– Researchers and data analysts to conduct further analysis and interpretation of the data.
– Policy makers and government officials to implement recommended interventions.
– Healthcare providers and facilities to improve the quality of newborn care.
– Community leaders and organizations to support community-based interventions.
– NGOs and international organizations to provide funding and technical support.
Cost Items for Planning Recommendations:
– Training and capacity building for healthcare providers.
– Infrastructure improvement in healthcare facilities.
– Outreach programs and community engagement initiatives.
– Monitoring and evaluation systems to track progress.
– Advocacy and awareness campaigns.
– Research and data collection activities.
– Collaboration and coordination efforts among stakeholders.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, as it is based on secondary data from recent Demographic and Health Surveys in 16 countries. The study examines equity in co-coverage of newborn care interventions and identifies important inequities based on individual, family, contextual, and structural factors. The analysis highlights the importance of facility birth for improved and more equitable newborn care. To improve the evidence, the study could include a larger sample size and conduct a more comprehensive analysis of the social determinants of health.

Background: High coverage of care is essential to improving newborn survival; however, gaps exist in access to timely and appropriate newborn care between and within countries. In high mortality burden settings, health inequities due to social and economic factors may also impact on newborn outcomes. This study aimed to examine equity in co-coverage of newborn care interventions in low- and low middle-income countries in sub-Saharan Africa and South Asia. Methods: We analysed secondary data from recent Demographic and Health Surveys in 16 countries. We created a co-coverage index of five newborn care interventions. We examined differences in coverage and co-coverage of newborn care interventions by country, place of birth, and wealth quintile. Using multilevel logistic regression, we examined the association between high co-coverage of newborn care (4 or 5 interventions) and social determinants of health. Results: Coverage and co-coverage of newborn care showed large between- and within-country gaps for home and facility births, with important inequities based on individual, family, contextual, and structural factors. Wealth-based inequities were smaller amongst facility births compared to non-facility births. Conclusion: This analysis underlines the importance of facility birth for improved and more equitable newborn care. Shifting births to facilities, improving facility-based care, and community-based or pro-poor interventions are important to mitigate wealth-based inequities in newborn care, particularly in countries with large differences between the poorest and richest families and in countries with very low coverage of care.

The Demographic and Health Survey Program (DHS) collects health data in high burden mortality settings including newborn care. Surveys are completed at household- and individual-levels, focusing on report from women of reproductive age (15–49 years). Complex, multi-stage sampling and stratification produce nationally-representative results for each country [18]. We analysed secondary DHS survey data since 2015 from low- and low middle-income countries in sub-Saharan Africa and south Asia which included questions on newborn care interventions in the first 2 days of life. We included last (most recent) live births in the 2 years before the survey. Exclusion criteria were births in the 2 days before the survey and neonates who died before the second day. Table 1 shows the included countries, survey years, and number of women interviewed. List of included countries from DHS, survey year, and sample sizes aWeighted, from ICF International [19] b includes only most recent live-born children surviving the first 2 days of life We created a co-coverage index of provider-initiated early newborn care interventions, using a method similar to Victora et al. [20] and Carvajal-Aguirre et al. [9]. We included five provider-initiated interventions included in the WHO standards for maternal and newborn care [21]: 1) examining the umbilical cord, 2) taking the newborn’s temperature, 3) counselling on danger signs in the newborn, 4) counselling on breastfeeding, and 5) observing breastfeeding (Table 2). The primary outcome measure was receipt of 4–5 of these interventions provided in the first two days of life and hereafter called “appropriate newborn care”. Newborn care intervention survey questions. Newborn care interventions and question wordings from the phase seven DHS model questionnaire [22] Key predictor variables focused on social determinants of health using an adapted person-centred conceptual framework (Fig. ​(Fig.1)1) where individual women and their newborns sit at the centre, encircled by their families and the wider community and structural contexts [17]. Conceptual framework for social determinants of health, adapted from the United Nations Development Programme [17] Simple weighted descriptive statistics on individual intervention coverage and co-coverage by birth location, wealth quintile, and country were calculated. We visually examined patterns of wealth-based inequities (Victora et al. [20]) assigning “top inequity,” “bottom inequity,” and “linear inequity”. Top inequity, also described as ‘mass deprivation’ [26], is when the majority of the population are deprived and only a minority have access to care. Bottom inequity, also described as ‘marginalisation’ [26], is when the majority of the population have access to care but a minority are excluded. Linear inequity, also described as queuing, lies somewhere between top and bottom inequity, with a linear relationship between wealth and access [26]. In descriptive analyses, individual-level weights were applied to account for sampling probability and non-response to ensure each sample was nationally representative. Descriptive results are presented for facility birth and home birth separately. Multilevel, multivariable logistic regression models were fitted, by country for facility birth only to assess the association between the factors in the conceptual framework and appropriate newborn care. For the multilevel models, individual-level weights were denormalised and cluster-level weights were approximated with equal allocation between individual and cluster levels (α = 0.5) using a method described by Elkasabi et al. [27]. The models were adjusted for the independent variables listed above. All statistical analyses for this study were conducted in R [28] and Stata, using the survey package [29] in R and applying the svy commands in Stata where appropriate to adjust for the complex sampling design.

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

1. Mobile health (mHealth) interventions: Develop mobile applications or text messaging services that provide pregnant women and new mothers with information and reminders about newborn care interventions. This can help bridge the gap in access to timely and appropriate care, especially in low-resource settings.

2. Community-based interventions: Implement community-based programs that train and empower local health workers or community volunteers to provide essential newborn care interventions. This can improve access to care, particularly in remote areas where facility-based care may be limited.

3. Pro-poor interventions: Design and implement interventions that specifically target and prioritize the needs of economically disadvantaged women and families. This can help mitigate wealth-based inequities in newborn care and ensure that the most vulnerable populations have access to essential services.

4. Facility strengthening: Invest in improving the quality and availability of facility-based care for maternal and newborn health. This includes ensuring that health facilities have the necessary equipment, supplies, and skilled healthcare providers to provide comprehensive care during childbirth and the postnatal period.

5. Health system strengthening: Implement broader health system strengthening initiatives that address the underlying social, economic, and structural factors that contribute to inequities in access to maternal health services. This can involve improving infrastructure, strengthening health workforce capacity, and addressing barriers to healthcare utilization.

It is important to note that these are general recommendations based on the information provided. The specific context and needs of each country or region should be taken into consideration when designing and implementing innovations to improve access to maternal health.
AI Innovations Description
The recommendation to improve access to maternal health based on the study “Equity in newborn care, evidence from national surveys in low- and middle-income countries” includes the following:

1. Shifting births to facilities: Encouraging women to give birth in healthcare facilities can improve access to timely and appropriate newborn care. This can be achieved through awareness campaigns, providing incentives for facility births, and ensuring the availability of quality healthcare services in facilities.

2. Improving facility-based care: Enhancing the quality of care provided in healthcare facilities is crucial for improving newborn outcomes. This can be done by training healthcare providers on evidence-based practices for newborn care, ensuring the availability of essential equipment and supplies, and implementing quality improvement initiatives.

3. Community-based or pro-poor interventions: Implementing interventions that target vulnerable populations, such as the poorest families, can help mitigate wealth-based inequities in newborn care. This can include community-based outreach programs, providing financial support for healthcare expenses, and improving access to transportation for pregnant women.

By implementing these recommendations, countries can work towards improving access to maternal health and reducing inequities in newborn care, particularly in low- and middle-income settings with limited coverage of care.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations to improve access to maternal health:

1. Strengthening facility-based care: Improving the quality and availability of maternal health services in healthcare facilities can encourage more women to give birth in a safe and controlled environment. This can include training healthcare providers, ensuring the availability of essential equipment and supplies, and improving the overall infrastructure of healthcare facilities.

2. Promoting community-based interventions: Implementing community-based programs that focus on maternal health education, awareness, and support can help reach women in remote or underserved areas. These interventions can include training community health workers, conducting outreach programs, and providing mobile healthcare services.

3. Addressing social determinants of health: Recognizing and addressing the social and economic factors that contribute to health inequities is crucial. This can involve implementing policies and programs that aim to reduce poverty, improve education, empower women, and address cultural barriers to accessing maternal health services.

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

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the percentage of women giving birth in healthcare facilities, the availability of skilled birth attendants, or the coverage of essential maternal health interventions.

2. Collect baseline data: Gather data on the current status of the selected indicators in the target population. This can be done through surveys, interviews, or existing data sources such as the Demographic and Health Surveys (DHS) mentioned in the description.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on the selected indicators. This model should consider factors such as population demographics, healthcare infrastructure, resource allocation, and the implementation timeline of the recommendations.

4. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to assess the potential impact of the recommendations. This can involve adjusting parameters related to the recommendations, such as the percentage of women accessing facility-based care or the coverage of community-based interventions.

5. Analyze results: Analyze the simulation results to determine the projected changes in the selected indicators. This can include comparing the baseline data with the simulated outcomes to quantify the potential improvements in access to maternal health.

6. Validate and refine the model: Validate the simulation model by comparing the simulated outcomes with real-world data or expert opinions. Refine the model based on feedback and make adjustments as necessary.

7. Communicate findings: Present the findings of the simulation study to relevant stakeholders, policymakers, and healthcare providers. Use the results to advocate for the implementation of the recommended interventions and to guide decision-making processes.

It is important to note that the methodology for simulating the impact of recommendations on improving access to maternal health may vary depending on the specific context and available data.

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