Inequities in maternal and child health outcomes and interventions in Ghana

BMC Public Health, Volume 12, No. 1, Year 2012

Interprétation

Background: With the date for achieving the targets of the Millennium Development Goals (MDGs) approaching fast, there is a heightened concern about equity, as inequities hamper progress towards the MDGs. Equity-focused approaches have the potential to accelerate the progress towards achieving the health-related MDGs faster than the current pace in a more cost-effective and sustainable manner. Ghana’s rate of progress towards MDGs 4 and 5 related to reducing child and maternal mortality respectively is less than what is required to achieve the targets. The objective of this paper is to examine the equity dimension of child and maternal health outcomes and interventions using Ghana as a case study. Methods. Data from Ghana Demographic and Health Survey 2008 report is analyzed for inequities in selected maternal and child health outcomes and interventions using population-weighted, regression-based measures: slope index of inequality and relative index of inequality. Results: No statistically significant inequities are observed in infant and under-five mortality, perinatal mortality, wasting and acute respiratory infection in children. However, stunting, underweight in under-five children, anaemia in children and women, childhood diarrhoea and underweight in women (BMI < 18.5) show inequities that are to the disadvantage of the poorest. The rates significantly decrease among the wealthiest quintile as compared to the poorest. In contrast, overweight (BMI 25-29.9) and obesity (BMI 30) among women reveals a different trend - there are inequities in favour of the poorest. In other words, in Ghana overweight and obesity increase significantly among women in the wealthiest quintile compared to the poorest. With respect to interventions: treatment of diarrhoea in children, receiving all basic vaccines among children and sleeping under ITN (children and pregnant women) have no wealth-related gradient. Skilled care at birth, deliveries in a health facility (both public and private), caesarean section, use of modern contraceptives and intermittent preventive treatment for malaria during pregnancy all indicate gradients that are in favour of the wealthiest. The poorest use less of these interventions. Not unexpectedly, there is more use of home delivery among women of the poorest quintile. Conclusion: Significant Inequities are observed in many of the selected child and maternal health outcomes and interventions. Failure to address these inequities vigorously is likely to lead to non-achievement of the MDG targets related to improving child and maternal health (MDGs 4 and 5). The government should therefore give due attention to tackling inequities in health outcomes and use of interventions by implementing equity-enhancing measure both within and outside the health sector in line with the principles of Primary Health Care and the recommendations of the WHO Commission on Social Determinants of Health. © 2012 Zere et al; licensee BioMed Central Ltd. Data is extracted from Ghana demographic and health survey (GDHS) of 2008 report. The 2008 DHS was a nationally representative survey of 11,778 households comprising 4,916 women in the age group 15 to 49 years and 4,568 men aged 15-59 years. The survey employed a two-stage sampling based on the 2000 Population and Housing Census [18]. The health outcomes included in this study are defined in GDHS 2008 as indicated in Table Table22[18]. Maternal and child health outcomes included in the study and their definitions The interventions included in this study are defined in GDHS 2008 as indicated in Table Table33[18]. Maternal and child health interventions included in the study and their definitions The measurement of inequities in maternal and child health outcomes and access to health care interventions entails three steps [19]: (i) identification of the health outcome or intervention whose distribution is to be measured; (ii) classification of the population into different strata by a selected equity stratifier; and (iii) measuring the degree of inequality. The variables of interest, that is the maternal and child health outcomes and interventions are listed in Tables Tables22 and and3.3. In the Demographic and Health Surveys, the socio-economic stratifier used is household wealth, which is derived from the household ownership of assets such as television, car etc. and dwelling characteristics such as flooring material and source of drinking water. In this study, we have used wealth quintiles that are provided in the DHS report. In this study, we have used wealth quintiles that are provided in the DHS report. Each asset was assigned a weight (factor score) generated through principal components analysis, and the resulting asset scores were standardised in relation to a normal distribution with a mean of zero and standard deviation of one. Each household was then assigned a score for each asset, and the scores were summed for each household; individuals were ranked according to the total score of the household in which they resided. The sample was then divided into quintiles from one (lowest) to five (highest). A single asset index was developed for the whole sample; separate indices were not prepared for the urban and rural populations [18]. To date, various measures have been used in the measurement of inequities in health and health care. Of the available measures only the slope index of inequality (SII), the relative index of inequality (RII) and the concentration index have the following desirable characteristics: (i) they reflect the socio-economic dimension of health inequalities; (ii) they reflect the experience of the entire population rather than only two groups such as wealth quintiles one and five and (iii) they are sensitive to changes in the distribution of the population across socio-economic groups [20]. In this study, the presence or absence of inequities is measured using population-weighted, regression-based measures: SII and RII. These measures are selected for this analysis because of their ease of interpretation. The SII and RII are based on the socio-economic dimension to inequalities in health and are weighted by the social group proportions [20,21]. The SII is a measure of absolute effect, while the RII measures relative effect. The SII and RII are interpreted as the effect on health or utilization of health care intervention of moving from the lowest to the highest socio-economic group, which is from wealth quintile 1 to wealth quintile 5. To compute the SII, social groups (wealth quintiles) are ranked from lowest to highest. The population in each wealth quintile covers a range in the distribution of the population and is given a score based on the midpoint of its range in the cumulative distribution in the population. The SII is the linear regression coefficient (slope of the regression line) showing the relationship between a group's (wealth quintile in this case) health and its relative socio-economic rank. In other words: Where: yi is the value of the health variable of wealth quintile i; xi is the relative rank of wealth quintile i; β0 is the constant or intercept term, which captures the value of y when x equals zero; βi is the slope coefficient (or parameter), and it indicates the amount the y will change when x changes by one unit; and ε is the stochastic error (or disturbance) term that captures the variation in y that cannot be explained by the included xi. The coefficient β1represents the SII. The relative index of inequality is derived from the SII as follows: where, μ is the population average of the specific health variable. However, because we are making use of grouped data, the error term of the regression equation is heteroskedastic making the Ordinary Least Squares (OLS) estimates inefficient. To avoid this problem, the SII is therefore estimated using Weighted Least Squares (WLS) [20]. This can be done by running OLS regression on the following transformed equation: Where, niis the size of wealth quintile "i", that is the number of individuals in each wealth quintile. It has to be noted that there is no constant term in Equation (3). SII and RII avoid the defects of the range measures such as rate difference between the wealthiest and poorest quintiles or rate ratio of these two extreme quintiles. They reflect the experience of the entire population as opposed to extreme groups such as wealth quintiles 1 and 5 and are sensitive to the distribution of the population across socio-economic groups (wealth quintiles). The disadvantage of the SII/RII is that it can only be applied to socio-economic variables that can be ordered hierarchically. Besides, linearity is assumed in the regression model; non-linearity would lead to bias in the magnitude of the index. Data was analyzed using STATA 10 statistical software.

Résumé de l’IA

Study Justification:

This study examines the inequities in maternal and child health outcomes and interventions in Ghana. The study is justified by the need to address the equity dimension of health outcomes, as inequities hinder progress towards achieving the Millennium Development Goals (MDGs). By understanding and addressing these inequities, Ghana can work towards improving child and maternal health outcomes and achieving the MDG targets.

Highlights:

– No statistically significant inequities are observed in infant and under-five mortality, perinatal mortality, wasting, and acute respiratory infection in children.
– However, stunting, underweight in under-five children, anemia in children and women, childhood diarrhea, and underweight in women show inequities that disadvantage the poorest.
– Overweight and obesity among women show inequities in favor of the poorest.
– Interventions such as treatment of diarrhea in children, receiving all basic vaccines among children, and sleeping under insecticide-treated nets (ITNs) have no wealth-related gradient.
– Skilled care at birth, deliveries in a health facility, caesarean section, use of modern contraceptives, and intermittent preventive treatment for malaria during pregnancy all indicate gradients that favor the wealthiest.
– The poorest use less of these interventions, and there is more use of home delivery among women of the poorest quintile.

Recommendations:

– The government should give due attention to tackling inequities in health outcomes and use of interventions.
– Implement equity-enhancing measures both within and outside the health sector.
– Align efforts with the principles of Primary Health Care and the recommendations of the WHO Commission on Social Determinants of Health.

Key Role Players:

– Government health agencies and ministries
– Non-governmental organizations (NGOs) working in the health sector
– Community leaders and organizations
– Health professionals and providers
– Researchers and academics

Cost Items for Planning Recommendations:

– Funding for implementing equity-enhancing measures
– Resources for training and capacity building of health professionals
– Investments in infrastructure and equipment for health facilities
– Outreach and awareness campaigns
– Monitoring and evaluation systems
– Research and data collection on health outcomes and interventions
Please note that the cost items provided are general categories and not actual cost estimates.

Force de la preuve

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are a few areas for improvement. The study provides detailed information on the methods used, including the data source and analysis techniques. The findings are presented clearly, with specific outcomes and interventions analyzed. However, the abstract could be improved by including more information on the sample size and demographics of the study population. Additionally, it would be helpful to provide more context on the significance of the observed inequities and their implications for achieving the Millennium Development Goals. Overall, the evidence is strong, but these suggestions would enhance the clarity and impact of the abstract.

Abstrait

Data is extracted from Ghana demographic and health survey (GDHS) of 2008 report. The 2008 DHS was a nationally representative survey of 11,778 households comprising 4,916 women in the age group 15 to 49 years and 4,568 men aged 15-59 years. The survey employed a two-stage sampling based on the 2000 Population and Housing Census [18]. The health outcomes included in this study are defined in GDHS 2008 as indicated in Table Table22[18]. Maternal and child health outcomes included in the study and their definitions The interventions included in this study are defined in GDHS 2008 as indicated in Table Table33[18]. Maternal and child health interventions included in the study and their definitions The measurement of inequities in maternal and child health outcomes and access to health care interventions entails three steps [19]: (i) identification of the health outcome or intervention whose distribution is to be measured; (ii) classification of the population into different strata by a selected equity stratifier; and (iii) measuring the degree of inequality. The variables of interest, that is the maternal and child health outcomes and interventions are listed in Tables Tables22 and and3.3. In the Demographic and Health Surveys, the socio-economic stratifier used is household wealth, which is derived from the household ownership of assets such as television, car etc. and dwelling characteristics such as flooring material and source of drinking water. In this study, we have used wealth quintiles that are provided in the DHS report. In this study, we have used wealth quintiles that are provided in the DHS report. Each asset was assigned a weight (factor score) generated through principal components analysis, and the resulting asset scores were standardised in relation to a normal distribution with a mean of zero and standard deviation of one. Each household was then assigned a score for each asset, and the scores were summed for each household; individuals were ranked according to the total score of the household in which they resided. The sample was then divided into quintiles from one (lowest) to five (highest). A single asset index was developed for the whole sample; separate indices were not prepared for the urban and rural populations [18]. To date, various measures have been used in the measurement of inequities in health and health care. Of the available measures only the slope index of inequality (SII), the relative index of inequality (RII) and the concentration index have the following desirable characteristics: (i) they reflect the socio-economic dimension of health inequalities; (ii) they reflect the experience of the entire population rather than only two groups such as wealth quintiles one and five and (iii) they are sensitive to changes in the distribution of the population across socio-economic groups [20]. In this study, the presence or absence of inequities is measured using population-weighted, regression-based measures: SII and RII. These measures are selected for this analysis because of their ease of interpretation. The SII and RII are based on the socio-economic dimension to inequalities in health and are weighted by the social group proportions [20,21]. The SII is a measure of absolute effect, while the RII measures relative effect. The SII and RII are interpreted as the effect on health or utilization of health care intervention of moving from the lowest to the highest socio-economic group, which is from wealth quintile 1 to wealth quintile 5. To compute the SII, social groups (wealth quintiles) are ranked from lowest to highest. The population in each wealth quintile covers a range in the distribution of the population and is given a score based on the midpoint of its range in the cumulative distribution in the population. The SII is the linear regression coefficient (slope of the regression line) showing the relationship between a group's (wealth quintile in this case) health and its relative socio-economic rank. In other words: Where: yi is the value of the health variable of wealth quintile i; xi is the relative rank of wealth quintile i; β0 is the constant or intercept term, which captures the value of y when x equals zero; βi is the slope coefficient (or parameter), and it indicates the amount the y will change when x changes by one unit; and ε is the stochastic error (or disturbance) term that captures the variation in y that cannot be explained by the included xi. The coefficient β1represents the SII. The relative index of inequality is derived from the SII as follows: where, μ is the population average of the specific health variable. However, because we are making use of grouped data, the error term of the regression equation is heteroskedastic making the Ordinary Least Squares (OLS) estimates inefficient. To avoid this problem, the SII is therefore estimated using Weighted Least Squares (WLS) [20]. This can be done by running OLS regression on the following transformed equation: Where, niis the size of wealth quintile "i", that is the number of individuals in each wealth quintile. It has to be noted that there is no constant term in Equation (3). SII and RII avoid the defects of the range measures such as rate difference between the wealthiest and poorest quintiles or rate ratio of these two extreme quintiles. They reflect the experience of the entire population as opposed to extreme groups such as wealth quintiles 1 and 5 and are sensitive to the distribution of the population across socio-economic groups (wealth quintiles). The disadvantage of the SII/RII is that it can only be applied to socio-economic variables that can be ordered hierarchically. Besides, linearity is assumed in the regression model; non-linearity would lead to bias in the magnitude of the index. Data was analyzed using STATA 10 statistical software.

Matériaux

https://efashare.b-cdn.net/materials/1be23a0ce9761bb93aeb236d7aacc0276cc15d5b36e48df75362214639a3aa3a/1471-2458-12-252-S1.DOCX

Innovations

The information provided is a background and methodology of a study conducted in Ghana to examine the equity dimension of child and maternal health outcomes and interventions. The study analyzed data from the Ghana Demographic and Health Survey 2008 report to identify inequities in selected maternal and child health outcomes and interventions.

The study found that significant inequities exist in many maternal and child health outcomes and interventions in Ghana. While there were no statistically significant inequities in infant and under-five mortality, perinatal mortality, wasting, and acute respiratory infection in children, there were inequities in stunting, underweight in under-five children, anemia in children and women, childhood diarrhea, and underweight in women. These inequities were to the disadvantage of the poorest, with rates significantly decreasing among the wealthiest quintile compared to the poorest.

In terms of interventions, the study found that treatment of diarrhea in children, receiving all basic vaccines among children, and sleeping under an insecticide-treated net (ITN) for both children and pregnant women had no wealth-related gradient. However, skilled care at birth, deliveries in a health facility (both public and private), cesarean section, use of modern contraceptives, and intermittent preventive treatment for malaria during pregnancy all showed gradients that favored the wealthiest. The poorest used these interventions less, and there was a higher use of home delivery among women in the poorest quintile.

The study recommends implementing equity-enhancing measures both within and outside the health sector to address these inequities. These measures should prioritize tackling disparities in health outcomes and access to interventions by targeting the poorest populations and ensuring they have equal access to quality maternal health services. The study also emphasizes the importance of addressing social determinants of health, such as poverty, education, and gender inequality, and monitoring and evaluating progress to track the reduction of health inequities.

Overall, the study highlights the need for the government of Ghana to give due attention to addressing inequities in health outcomes and interventions to achieve the Millennium Development Goals related to improving child and maternal health.

AI Innovations Description

Based on the information provided, the recommendation to improve access to maternal health in Ghana is to implement equity-enhancing measures both within and outside the health sector. This recommendation is based on the findings that significant inequities exist in many maternal and child health outcomes and interventions in Ghana.

To address these inequities, the government should prioritize tackling the disparities in health outcomes and access to interventions. This can be done by implementing policies and programs that target the poorest populations and ensure they have equal access to quality maternal health services.

Some specific actions that can be taken include:

1. Improve access to skilled care at birth: Ensure that all women, regardless of their socioeconomic status, have access to skilled birth attendants during delivery. This can be achieved by increasing the number of skilled health workers, particularly in rural areas, and providing training and incentives to encourage them to work in underserved areas.

2. Increase access to health facilities: Improve the availability and quality of health facilities, especially in rural and remote areas. This can be done by investing in infrastructure, equipment, and supplies, as well as providing transportation services for pregnant women who need to travel long distances to reach a health facility.

3. Expand coverage of essential interventions: Increase the coverage of interventions such as vaccinations, prenatal care, postnatal care, and family planning services. This can be achieved by strengthening the health system, training healthcare providers, and raising awareness among communities about the importance of these interventions.

4. Address social determinants of health: Recognize that health inequities are influenced by social factors such as poverty, education, and gender inequality. Implement policies and programs that address these social determinants of health, such as poverty reduction initiatives, girls’ education programs, and women’s empowerment initiatives.

5. Monitor and evaluate progress: Establish a robust monitoring and evaluation system to track progress in reducing health inequities and ensure that interventions are reaching the most vulnerable populations. Regularly collect and analyze data on maternal health outcomes and access to interventions, and use this information to inform decision-making and policy development.

By implementing these recommendations, Ghana can make significant progress in improving access to maternal health and reducing health inequities. It is important for the government to prioritize these efforts and allocate sufficient resources to ensure their successful implementation.

AI Innovations Methodology

The methodology used to simulate the impact of the main recommendations on improving access to maternal health in Ghana would involve the following steps:

1. Data collection: Extract data from the Ghana Demographic and Health Survey (GDHS) 2008 report, which includes information on maternal and child health outcomes and interventions. This data will serve as the baseline for the simulation.

2. Identification of health outcomes and interventions: Select the specific maternal and child health outcomes and interventions that will be the focus of the simulation. These should align with the main recommendations mentioned in the abstract.

3. Classification of the population: Use the wealth quintiles provided in the GDHS report to classify the population into different strata based on household wealth. This will allow for the measurement of inequities in health outcomes and access to interventions.

4. Measurement of inequality: Calculate the slope index of inequality (SII) and relative index of inequality (RII) using population-weighted, regression-based measures. These measures will provide information on the absolute and relative effects of moving from the lowest to the highest wealth quintile on health outcomes and access to interventions.

5. Simulation of the impact: Apply the main recommendations mentioned in the abstract to the data and assess the potential impact on improving access to maternal health. This can be done by adjusting the distribution of health outcomes and interventions across wealth quintiles based on the expected changes resulting from the recommendations.

6. Analysis and interpretation: Analyze the simulated data to determine the extent to which the main recommendations would improve access to maternal health in Ghana. Interpret the results in terms of the changes in health outcomes and access to interventions, as well as the reduction in inequities.

7. Reporting and dissemination: Prepare a report summarizing the findings of the simulation and the potential impact of the main recommendations on improving access to maternal health in Ghana. Disseminate the findings to relevant stakeholders, such as policymakers, healthcare providers, and researchers, to inform decision-making and policy development.

It is important to note that this methodology is based on the information provided in the abstract and may need to be adapted or expanded upon depending on the specific objectives and resources available for the simulation.

Auteur

Dima Health

Statistics:

Citations: 62

Identifiers:

DOI: 10.1186/1471-2458-12-252

Research Areas:

Community Interventions, Disparities, Environmental, Food Security, Health System and Policy, Infectious Diseases, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Ghana

Study Design:

Case Study, Cross Sectional Study, randomised-control-trial

Study Approach:

Mixed-methods, Qualitative, Quantitative

Participants Gender:

Male & Female

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