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Background: Health policy interventions were expected to improve access to health care delivery, provide financial risk protection, besides reducing inequities that underlie geographic and socio-economic variation in population access to health care. This article examines whether health policy interventions and accelerated health investments in India during 2004–2018 could close the gap in inequity in health care utilization and access to public subsidy by different population groups. Did the poor and socio-economically vulnerable population gain from such government initiatives, compared to the rich and affluent sections of society? And whether the intended objective of improving equity between different regions of the country been achieved during the policy initiatives? This article attempts to assess and provide robust evidence in the Indian context. Methods: Employing Benefit-Incidence Analysis (BIA) framework, this paper advances earlier evidence by highlighting estimates of health care utilization, concentration and government subsidy by broader provider categories (public versus private) and across service levels (outpatient, inpatient, maternal, pre-and post-natal services). We used 2 waves of household surveys conducted by the National Sample Survey Organisation (NSSO) on health and morbidity. The period of analysis was chosen to represent policy interventions spanning 2004 (pre-policy) and 2018 (post-policy era). We present this evidence across three categories of Indian states, namely, high-focus states, high-focus north eastern states and non-focus states. Such categorization facilitates quantification of reform impact of policy level interventions across the three groups. Results: Utilisation of healthcare services, except outpatient care visits, accelerated significantly in 2018 from 2004. The difference in utilisation rates between poor and rich (between poorest 20% and richest 20%) had significantly declined during the same period. As far as concentration of healthcare is concerned, the Concentrate Index (CI) underlying inpatient care in public sector fell from 0.07 in 2004 to 0.05 in 2018, implying less pro-rich distribution. The CI in relation to pre-natal, institutional delivery and postnatal services in government facilities were pro-poor both in 2004 and 2018 in all 3 groups of states. The distribution of public subsidy underscoring curative services (inpatient and outpatient) remained pro-rich in 2004 but turned less pro-rich in 2018, measured by CIs which declined sharply across all groups of states for both outpatient (from 0.21 in 2004 to 0.16 in 2018) and inpatient (from 0.24 in 2004 to 0.14 in 2018) respectively. The CI for subsidy on prenatal services declined from approximately 0.01 in 2004 to 0.12 in 2018. In respect to post-natal care, similar results were observed, implying the subsidy on prenatal and post-natal services was overwhelmingly received by poor. The CI underscoring subsidy for institutional delivery although remained positive both in 2018 and 2004, but slightly increased from 0.17 in 2004 to 0.28 in 2018. Conclusions: Improvement in infrastructure and service provisioning through NHM route in the public facilities appears to have relatively benefited the poor. Yet they received a relatively smaller health subsidy than the rich when utilising inpatient and outpatient health services. Inequality continues to persist across all healthcare services in private health sector. Although the NHM remained committed to broader expansion of health care services, a singular focus on maternal and child health conditions especially in backward regions of the country has yielded desired results. [ABSTRACT FROM AUTHOR]

Background: Researching access to health services, and ways to improve equity, frequently requires researchers to recruit people facing social disadvantage. Recruitment can be challenging, and there is limited high quality evidence to guide researchers. This paper describes experiences of recruiting 1068 participants facing social disadvantage for a randomised controlled trial of prescription charges, and provides evidence on the advantages and disadvantages of recruitment methods. Methods: Those living in areas of higher social deprivation, taking medicines for diabetes, taking anti-psychotic medicines, or with COPD were eligible to participate in the study. Several strategies were trialled to meet recruitment targets. We initially attempted to recruit participants in person, and then switched to a phone-based system, eventually utilising a market research company to deal with incoming calls. We used a range of strategies to publicise the study, including pamphlets in pharmacies and medical centres, media (especially local newspapers) and social media. Results: Enrolling people on the phone was cheaper on average than recruiting in person, but as we refined our approach over time, the cost of the latter dropped significantly. In person recruitment had many advantages, such as enhancing our understanding of potential participants' concerns. Forty-nine percent of our participants are Māori, which we attribute to having Māori researchers on the team, recruiting in areas of high Māori population, team members' existing links with Māori health providers, and engaging and working with Māori providers. Conclusions: Recruiting people facing social disadvantage requires careful planning and flexible recruitment strategies. Support from organisations trusted by potential participants is essential. Registration: The Free Meds study is registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12618001486213). [ABSTRACT FROM AUTHOR]

Background: Health outcomes in India are characterized by pervasive inequities due to deeply entrenched socio-economic gradients amongst the population. Therefore, it is imperative to investigate these systematic disparities in health, however, evidence of inequities does not commensurate with its policy objectives in India. Thus, our paper aims to examine the magnitude of and trends in horizontal inequities in self-reported morbidity and untreated morbidity in India over the period of 2004 to 2017–18. Methods: The study used cross-sectional data from nationwide healthcare surveys conducted in 2004, 2014 and 2017–18 encompassing sample size of 3,85,055; 3,35,499 and 5,57,887 individuals respectively. Erreygers concentration indices were employed to discern the magnitude and trend in horizontal inequities in self-reported morbidity and untreated morbidity. Need standardized concentration indices were further used to unravel the inter-regional and intra-regional income related inequities in outcomes of interest. Additionally, regression based decomposition approach was applied to ascertain the contributions of both legitimate and illegitimate factors in the measured inequalities. Results: Estimates were indicative of profound inequities in self-reported morbidity as inequity indices were positive and significant for all study years, connoting better-off reporting more morbidity, given their needs. These inequities however, declined marginally from 2004(HI: 0.049, p< 0.01) to 2017–18(HI: 0.045, P< 0.01). Untreated morbidity exhibited pro-poor inequities with negative concentration indices. Albeit, significant reduction in horizontal inequity was found from 2004(HI= − 0.103, p< 0.01) to 2017–18(HI = − 0.048, p< 0.01) in treatment seeking over the years. The largest contribution of inequality for both outcomes stemmed from illegitimate variables in all the study years. Our findings also elucidated inter-state heterogeneities in inequities with high-income states like Andhra Pradesh, Kerala and West Bengal evincing inequities greater than all India estimates and Northeastern states divulged equity in reporting morbidity. Inequities in untreated morbidity converged for most states except in Punjab, Chhattisgarh and Himachal Pradesh where widening of inequities were observed from 2004 to 2017–18. Conclusions: Pro-rich and pro-poor inequities in reported and untreated morbidities respectively persisted from 2004 to 2017–18 despite reforms in Indian healthcare. Magnitude of these inequities declined marginally over the years. Health policy in India should strive for targeted interventions closing inequity gap. [ABSTRACT FROM AUTHOR]

Background: Health outcomes in India are characterized by pervasive inequities due to deeply entrenched socio-economic gradients amongst the population. Therefore, it is imperative to investigate these systematic disparities in health, however, evidence of inequities does not commensurate with its policy objectives in India. Thus, our paper aims to examine the magnitude of and trends in horizontal inequities in self-reported morbidity and untreated morbidity in India over the period of 2004 to 2017–18. Methods: The study used cross-sectional data from nationwide healthcare surveys conducted in 2004, 2014 and 2017–18 encompassing sample size of 3,85,055; 3,35,499 and 5,57,887 individuals respectively. Erreygers concentration indices were employed to discern the magnitude and trend in horizontal inequities in self-reported morbidity and untreated morbidity. Need standardized concentration indices were further used to unravel the inter-regional and intra-regional income related inequities in outcomes of interest. Additionally, regression based decomposition approach was applied to ascertain the contributions of both legitimate and illegitimate factors in the measured inequalities. Results: Estimates were indicative of profound inequities in self-reported morbidity as inequity indices were positive and significant for all study years, connoting better-off reporting more morbidity, given their needs. These inequities however, declined marginally from 2004(HI: 0.049, p< 0.01) to 2017–18(HI: 0.045, P< 0.01). Untreated morbidity exhibited pro-poor inequities with negative concentration indices. Albeit, significant reduction in horizontal inequity was found from 2004(HI= − 0.103, p< 0.01) to 2017–18(HI = − 0.048, p< 0.01) in treatment seeking over the years. The largest contribution of inequality for both outcomes stemmed from illegitimate variables in all the study years. Our findings also elucidated inter-state heterogeneities in inequities with high-income states like Andhra Pradesh, Kerala and West Bengal evincing inequities greater than all India estimates and Northeastern states divulged equity in reporting morbidity. Inequities in untreated morbidity converged for most states except in Punjab, Chhattisgarh and Himachal Pradesh where widening of inequities were observed from 2004 to 2017–18. Conclusions: Pro-rich and pro-poor inequities in reported and untreated morbidities respectively persisted from 2004 to 2017–18 despite reforms in Indian healthcare. Magnitude of these inequities declined marginally over the years. Health policy in India should strive for targeted interventions closing inequity gap. [ABSTRACT FROM AUTHOR]

Background: China issued strict nationwide guidelines to combat the COVID-19 outbreak in January 2020 and gradually loosened the restrictions on movement in early March. Little is known about how these disease control measures affected the 600 million people who live in rural China. The goal of this paper is to document the quarantine measures implemented in rural China outside the epicenter of Hubei Province and to assess the socioeconomic effect of the measures on rural communities over time. Methods: We conducted three rounds of interviews with informants from 726 villages in seven provinces, accounting for over 25% of China's overall rural population. The survey collected data on rural quarantine implementation; COVID-19 infections and deaths in the survey villages; and effects of the quarantine on employment, income, education, health care, and government policies to address any negative impacts. The empirical findings of the work established that strict quarantine measures were implemented in rural villages throughout China in February. Results: There was little spread of COVID-19 in rural communities: an infection rate of 0.001% and zero deaths reported in our sample. However, there were negative social and economic outcomes, including high rates of unemployment, falling household income, rising prices, and disrupted student learning. Health care was generally accessible, but many delayed their non-COVID-19 health care due to the quarantine measures. Only 20% of villagers received any form of local government aid, and only 11% of villages received financial subsidies. There were no reports of national government aid programs that targeted rural villagers in the sample areas. Conclusions: By examining the economic and social effects of the COVID-19 restrictions in rural communities, this study will help to guide other middle- and low-income countries in their containment and restorative processes. Without consideration for economically vulnerable populations, economic hardships and poverty will likely continue to have a negative impact on the most susceptible communities. [ABSTRACT FROM AUTHOR]

Introduction: Although India has made significant progress in institutional delivery after the implementation of the National Rural Health Mission under which the Janani Suraksha Yojana (JSY) is a sub-programme which played a vital role in the increase of institutional delivery in public facilities. Therefore, this paper aims to provide an understanding of the JSY coverage at the district level in India. Further, it tries to carve out the factors responsible for the regional disparity of JSY coverage at district levels. Methods: The study used the National Family Health Survey data, which is a cross-sectional survey conducted in 2015–16, India. The sample size of this study was 148,145 women aged 15–49 years who gave last birth in the institution during 5 years preceding the survey. Bivariate and multivariate regression analysis was used to fulfill the study objectives. Additionally, Moran's I statistics and bivariate Local Indicator for Spatial Association (LISA) maps were used to understand spatial dependence and clustering of JSY coverage. Ordinary least square, spatial lag and spatial error models were used to examine the correlates of JSY utilization. Results: The value of spatial-autocorrelation for JSY was 0.71 which depicts the high dependence of the JSY coverage over districts of India. The overall coverage of JSY in India is 36.4% and it highly varied across different regions, districts, and even socioeconomic groups. The spatial error model depicts that if in a district the women with no schooling status increase by 10% then the benefits of JSY get increased by 2.3%. Similarly, if in a district the women from poor wealth quintile, it increases by 10% the benefits of JSY also increased by 4.6%. However, the coverage of JSY made greater imperative to understand it due to its clustering among districts of specific states only. Conclusion: It is well reflected in the EAGs states in terms of spatial-inequality in service coverage. There is a need to universalize the JSY programme at a very individual level. And, it is required to revisit the policy strategy and the implementation plans at regional or district levels. [ABSTRACT FROM AUTHOR]

Background: The National Health Mission (NHM), the largest ever publicly funded health programme worldwide, used over half of the national health budget in India and primarily aimed to improve maternal and child health in the country. Though large scale public health investment has improved the health care utilization and health outcomes across states and socio-economic groups in India, little is known on the equity concern of NHM. In this context, this paper examines the utilization pattern and net benefit of public subsidy for institutional delivery by the level of care in India. Methods: Data from the most recent round of the National Family Health Survey (NFHS 4), conducted during 2015–16, was used in the study. A total of 148,645 last birth delivered in a health centre during the 5 years preceding the survey were used for the analyses. Out-of-pocket (OOP) payment on delivery care was taken as the dependent variable and was analysed by primary care and secondary level of care. Benefits Incidence Analysis (BIA), descriptive statistics, concentration index (CI), and concentration curve (CC) were used to do the analysis. Results: Institutional delivery from the public health centres in India is pro-poor and has a strong economic gradient. However, about 28% mothers from richest wealth quintile did not pay for delivery in public health centres compared to 16% among the poorest wealth quintile. Benefit incidence analyses suggests a pro-poor distribution of institutional delivery both at primary and secondary level of care. In 2015–16, at the primary level, about 32.29% of subsidies were used by the poorest, 27.22% by poorer, 20.39% by middle, 13.36% by richer and 6.73% by the richest wealth quintile. The pattern at the secondary level was similar, though the magnitude was lower. The concentration index of institutional delivery in public health centres was − 0.161 [95% CI, − 0.158, − 0.165] compared to 0.296 [95% CI, 0.289, 0.303] from private health centres. Conclusion: Provision and use of public subsidy for institutional delivery in public health centres is pro-poor in India. Improving the quality of service in primary health centres is recommended to increase utilisation and reduce OOP payment for health care in India. [ABSTRACT FROM AUTHOR]

Background: The objective of this paper is to analyse whether the recent recession has altered health care utilisation patterns of different income groups in Spain. Methods: Based on information concerning individuals 'income and health care use, along with health need indicators and demographic characteristics (provided by the Spanish National Health Surveys from 2006/07 and 2011/12), econometric models are estimated in two parts (mixed logistic regressions and truncated negative binominal regressions) for each of the public health services studied (family doctor appointments, appointments with specialists, hospitalisations, emergencies and prescription drug use). Results: The results show that the principle of universal access to public health provision does not in fact prevent a financial crisis from affecting certain income groups more than others in their utilisation of public health services. Conclusions: Specifically, in relative terms the recession has been more detrimental to low-income groups in the cases of specialist appointments and hospitalisations, whereas it has worked to their advantage in the cases of emergency services and family doctor appointments. [ABSTRACT FROM AUTHOR]

Background: There is limited evidence on how health care inputs are distributed from the sub-national level down to health facilities and their potential influence on promoting health equity. To address this gap, this paper assesses equity in the distribution of health care inputs across public primary health facilities at the district level in Tanzania. Methods: This is a quantitative assessment of equity in the distribution of health care inputs (staff, drugs, medical supplies and equipment) from district to facility level. The study was carried out in three districts (Kinondoni, Singida Rural and Manyoni district) in Tanzania. These districts were selected because they were implementing primary care reforms. We administered 729 exit surveys with patients seeking out-patient care; and health facility surveys at 69 facilities in early 2014. A total of seventeen indices of input availability were constructed with the collected data. The distribution of inputs was considered in relation to (i) the wealth of patients accessing the facilities, which was taken as a proxy for the wealth of the population in the catchment area; and (ii) facility distance from the district headquarters. We assessed equity in the distribution of inputs through the use of equity ratios, concentration indices and curves. Results: We found a significant pro-rich distribution of clinical staff and nurses per 1000 population. Facilities with the poorest patients (most remote facilities) have fewer staff per 1000 population than those with the least poor patients (least remote facilities): 0.6 staff per 1000 among the poorest, compared to 0.9 among the least poor; 0.7 staff per 1000 among the most remote facilities compared to 0.9 among the least remote. The negative concentration index for support staff suggests a pro-poor distribution of this cadre but the 45 degree dominated the concentration curve. The distribution of vaccines, antibiotics, anti-diarrhoeal, anti-malarials and medical supplies was approximately proportional (non dominance), whereas the distribution of oxytocics, anti-retroviral therapy (ART) and anti-hypertensive drugs was pro-rich, with the 45 degree line dominating the concentration curve for ART. Conclusion: This study has shown there are inequities in the distribution of health care inputs across public primary care facilities. This highlights the need to ensure a better coordinated and equitable distribution of inputs through regular monitoring of the availability of health care inputs and strengthening of reporting systems. [ABSTRACT FROM AUTHOR]

Background: Inequalities in demographic, socio-economic and health status for China labor force place them at greater health risks, and marginalized them in the utilization of healthcare services. This paper identifies the inequalities which limit the utilization of health services among China labor force, and provides a reference point for health policy. Methods: Data were collected from 23,505 participants aged 15 to 65, from the 2014 China Labor Force Dynamic Survey (a nationwide cross-sectional survey covering 29 provinces with a multi-stage cluster, and stratified, probability sampling strategy) conducted by Sun Yat-sen University. Logistic regression models were used to study the effects of demographic (age, gender, marital status, type of hukou and migration status), socio-economic (education, social class and insurance) and health status (self-perceived general health and several chronic illnesses) variables on the utilization of health services (two-week visiting and hospitalization during the past 12 months). Goodness of fit was assessed using Hosmer-Lemeshow test. Discrimination ability was assessed based on the area under the receiver operating curve (AUC). Results: Migrants with more than 1 (OR 2.80, 95% CI 1.01 ~ 7.82) or none chronic illnesses (OR 1.26, 95% CI 1.01 ~ 7.82) are more likely to be two week visiting to the clinic than non-migrants; migrants with none chronic illnesses (OR 0.61, 95% CI 0.45 ~ 0.82) are less likely to be in hospitalization during the past 12 months than non-migrants. Female, elder, hukou of non-agriculture, higher education level, higher social class, purchasing more insurance and poorer selfperceived health were predictors for more utilization of health service. More insurance benefited more two-week visiting (OR 1.12, 95% CI 1.06 ~ 1.17) and hospitalization during the past 12 months (OR 1.12, 95% CI 1.07 ~ 1.18) for individuals with none chronic illness but not ≥1 chronic illnesses. All models achieved good calibration (Hosmer-Lemeshow test's P range of 0.258-0.987) and discrimination (AUC range of 0.626-0.725). Conclusions: This study has shown that there are inequalities of demographic, socio-economic and health status in the utilization of health services for China labor force. Prudent health policy with equitable utilization of health services eliminating mentioned inequalities should be a priority in shaping China's healthcare system reform. [ABSTRACT FROM AUTHOR]

Background: Equity and justice in healthcare payment form an integral part of health policy and planning. In the majority of low and middle-income countries (LMICs), healthcare inequalities are further aggravated by Out of Pocket Expenditure (OOPE). This paper examines the pattern of health equity and regional disparities in healthcare spending among Indian states by applying Andersen's behavioural model of healthcare utilization. Methods: The present study uses data from the 66th quinquennial round of Consumer Expenditure Survey, of the National Sample Survey Organization (NSSO), conducted in 2009-10 by Ministry of Statistics and Programme Implementation (MoSPI), Government of India (GoI). To measure equity and regional disparities in healthcare expenditure, states have been categorized under three heads on the basis of monthly OOPE i.e., Category A (OOPE > =INR 100); Category B (OOPE between INR 50 to 99) and Category C (OOPE < INR 50). Multiple Generalised Linear Regression Model (GLRM) has been employed to explore the effect of various socio-economic covariates on the level of OOPE. Results: The gap in the ratio of average healthcare spending between the poorest and richest households was maximum in Category A states Category B (richest/poorest = 14.60), followed by (richest/poorest 11.70) and Category C (richest/poorest 11.40). Results also indicate geographical concentration of lower level healthcare spending among Indian states (e.g., Odisha, Chhattisgarh and all the north-eastern states). Results from the multivariate analysis suggest that people residing in urban areas, having higher economic status, belonging to non-Muslim communities, non-Scheduled Tribes (STs), and non-poor households spend more on healthcare than their counterparts. Conclusions: In spite of various efforts by the government to reduce the burden of healthcare spending, widespread inequalities in healthcare expenditure are prevalent. Households with high healthcare needs (SCs/STs, and the poor) are in a more disadvantaged position in terms of spending on health care. It has also been observed that spending on healthcare was comparatively lower among backward or isolated states. No doubt, the overall social security measures should be enhanced, but at the same time, looking at the regional differences, more priority should be assigned to the disadvantaged states to reduce the burden of OOPE. It is proposed that there is need to increase government spending, especially for the disadvantaged states and population, to minimise the burden of OOPE. [ABSTRACT FROM AUTHOR]

Background: Worldwide, Cervical Cancer (CC) is the fourth most common type of cancer and cause of death in women. It is a significant public health problem, especially in low and middle-income/Gross Domestic Product (GDP) countries. In the past decade, several studies of CC have been published, that identify the main modifiable and non-modifiable CC risk factors for Mexican women. However, there are no studies that attempt to explain the residual spatial variation in CC incidence In Mexico, i.e. spatial variation that cannot be ascribed to known, spatially varying risk factors. Methods: This paper uses a spatial statistical methodology that takes into account spatial variation in socioeconomic factors and accessibility to health services, whilst allowing for residual, unexplained spatial variation in risk. To describe residual spatial variations in CC risk, we used generalised linear mixed models (GLMM) with both spatially structured and unstructured random effects, using a Bayesian approach to inference. Results: The highest risk is concentrated in the southeast, where the Matlapa and Aquismón municipalities register excessive risk, with posterior probabilities greater than 0.8. The lack of coverage of Cervical Cancer-Screening Programme (CCSP) (RR 1.17, 95 % CI 1.12-1.22), Marginalisation Index (RR 1.05, 95 % CI 1.03-1.08), and lack of accessibility to health services (RR 1.01, 95 % CI 1.00-1.03) were significant covariates. Conclusions: There are substantial differences between municipalities, with high-risk areas mainly in low-resource areas lacking accessibility to health services for CC. Our results clearly indicate the presence of spatial patterns, and the relevance of the spatial analysis for public health intervention. Ignoring the spatial variability means to continue a public policy that does not tackle deficiencies in its national CCSP and to keep disadvantaging and disempowering Mexican women in regard to their health care. [ABSTRACT FROM AUTHOR]

Background: Physical inactivity is associated with an increased risk of all-cause mortality and entails a substantial economic burden for health systems. Also, the analysis of inequality in lifestyles for young populations may contribute to reduce health inequalities during adulthood. This paper examines the income-related inequality regarding leisure-time physical inactivity in Spanish children. Methods: In this cross-sectional study based on the Spanish National Health Survey for 2011-12, concentration indices are estimated to measure socioeconomic inequalities in leisure-time physical inactivity. A decomposition analysis is performed to determine the factors that explain income-related inequalities. Results: There is a significant socioeconomic gradient favouring the better-off associated with leisure-time physical inactivity amongst Spanish children, which is more pronounced in the case of girls. Income shows the highest contribution to total inequality, followed by education of the head of the household. The contribution of several factors (education, place of residence, age) significantly differs by gender. Conclusions: There is an important inequity in the distribution of leisure-time physical inactivity. Public policies aimed at promoting physical activity for children should prioritize the action into the most disadvantaged subgroups of the population. As the influence of determinants of health styles significantly differ by gender, this study points out the need of addressing the research on income-related inequalities in health habits from a gender perspective. [ABSTRACT FROM AUTHOR]

Background: Older persons report poor health status and greater need for healthcare. However, there is limited research on older persons' healthcare disparities in Uganda. Therefore, this paper aimed at investigating factors associated with older persons' healthcare access in Uganda, using a nationally representative sample. Methods: We conducted secondary analysis of data from a sample of 1602 older persons who reported being sick in the last 30 days preceding the Uganda National Household Survey. We used frequency distributions for descriptive data analysis and chi-square tests to identify initial associations. We fit generalized linear models (GLM) with the poisson family and the log link function, to obtain incidence risk ratios (RR) of accessing healthcare in the last 30 days, by older persons in Uganda. Results: More than three quarters (76%) of the older persons accessed healthcare in the last 30 days. Access to healthcare in the last 30 days was reduced for older persons from poor households (RR = 0.91, 95% CI: 0.83-0.99); with some walking difficulty (RR = 0.90, 95% CI: 0.83-0.97); or with a lot of walking difficulty (RR = 0.84, 95% CI: 0.75-0.95). Conversely, accessing healthcare in the last 30 days for older persons increased for those who earned wages (RR = 1.08, 95% CI: 1.00-1.15) and missed work due to illness for 1-7 days (RR =1.19, 95% CI: 1.10-1.30); and 8-14 days (RR = 1.19, 95% CI: 1.07-1.31). In addition, those who reported non-communicable diseases (NCDs) such as heart disease, hypertension or diabetes (RR= 1.09, 95% CI: 1.01-1.16); were more likely to access healthcare during the last 30 days. Conclusion: In the Ugandan context, health need factors (self-reported NCDs, severity of illness and mobility imitations) and enabling factors (household wealth status and earning wages in particular) were the most important determinants of accessing healthcare in the last 30 days among older persons. [ABSTRACT FROM AUTHOR]

Introduction Accurate measurement of health inequities is indispensable to track progress or to identify needs for health equity policy interventions. A key empirical task is to measure the extent to which observed inequality in health - a difference in health - is inequitable. Empirically operationalizing definitions of health inequity has generated an important question not considered in the conceptual literature on health inequity. Empirical analysis can explain only a portion of observed health inequality. This paper demonstrates that the treatment of unexplained inequality is not only a methodological but ethical question and that the answer to the ethical question - whether unexplained health inequality is unfair - determines the appropriate standardization method for health inequity analysis and can lead to potentially divergent estimates of health inequity. Methods We use the American sample of the 2002-03 Joint Canada/United States Survey of Health and measure health by the Health Utilities Index (HUI). We model variation in the observed HUI by demographic, socioeconomic, health behaviour, and health care variables using Ordinary Least Squares. We estimate unfair HUI by standardizing fairness, removing the fair component from the observed HUI. We consider health inequality due to factors amenable to policy intervention as unfair. We contrast estimates of inequity using two fairness- standardization methods: direct (considering unexplained inequality as ethically acceptable) and indirect (considering unexplained inequality as unfair). We use the Gini coefficient to quantify inequity. Results Our analysis shows that about 75% of the variation in the observed HUI is unexplained by the model. The direct standardization results in a smaller inequity estimate (about 60% of health inequality is inequitable) than the indirect standardization (almost all inequality is inequitable). Conclusions The choice of the fairness-standardization method is ethical and influences the empirical health inequity results considerably. More debate and analysis is necessary regarding which treatment of the unexplained inequality has the stronger foundation in equity considerations. [ABSTRACT FROM AUTHOR]

Background The provision of insecticide-treated nets (ITNs) is widely accepted in Burkina Faso thanks to large-scale national distribution campaigns. However, household also use other methods of prevention. Thus far, there is little knowledge about the expenditures of these malaria prevention methods, particularly in combination with the national interventions. This paper presents the utilization levels and expenditures of malaria prevention tools in Burkina Faso and explores the potential inequality in ownership. Methods The analysis is based on a cross-sectional survey, conducted during the 2010 high transmission season from July to September in the Nanoro Health and Demographic Surveillance Site. Following a systematic sampling technique, the survey covers 500 households with children under 5 years of age from 24 villages. In the survey, households were asked about expenditures on malaria prevention methods in the month preceding the survey. This includes expenditure on coils, indoor spraying, aerosols, repellents, herbs, cleaning of the environment and clearing of the vegetation. The data analysis was conducted with SPSS taking into account the socio-economic status (SES) of the household to examine any differences in the utilization of the prevention method and expenditure quintiles. An asset-based index, created through principal components analysis (PCA), was used to categorize the households into quintiles. Findings Of the households surveyed, 45% used one preventive measure in the past month; 29% used two measures; and 25% used three or more measures. A significant association was found between the number of prevention measures and the SES of the household (p < 0.05). The majority of households owned at least one insecticide treated net (ITN) (98%). Among households that used ITN, 53.8% used methods other than bed nets. The majority of households paid nothing for malaria prevention. Conclusion Most of the households received bed nets and other preventive method for free. There is equity in expenditures across SES groups. Free distribution of ITNs ensured that there was equity in ITN ownership among households. More research on the possibility of increasing access to other locally relevant methods of malaria control that proved to be effective is need. [ABSTRACT FROM AUTHOR]

Introduction: In countries such as Bangladesh many women may only seek skilled care at birth when complications become evident. This often results in higher neonatal mortality for women who give birth in institutions than for those that give birth at home. However, we hypothesise that this apparent excess mortality is concentrated among less advantaged women. The aim of this paper is to examine the association between place of birth and neonatal mortality in Bangladesh, and how this varies by socio-economic status. Methodology: The study is based on pooled data from four Bangladesh Demographic and Household Surveys, and uses descriptive analysis and binomial multivariate logistic regression. It uses regression models stratified for place of delivery to examine the impact of socio-economic status and place of residence on neonatal mortality. Results: Poor women from rural areas and those with no education who gave birth in institutions had much worse outcomes than those who gave birth at home. There is no difference for more wealthy women. There is a much stronger socio-economic gradient in neonatal mortality for women who gave birth in institutions than those who delivered at home. Conclusion: In Bangladesh babies from lower socio-economic groups and particularly those in rural areas have very poor outcomes if born in a facility. This suggests poorer, rural and less educated women are failing to obtain the timely access to quality maternal health care services needed to improve newborn outcomes. [ABSTRACT FROM AUTHOR]

Introduction: A recent health reform was implemented in Chile (the AUGE reform) with the objective of reducing the socioeconomic gaps to access healthcare. This reform did not seek to eliminate the private insurance system, which coexists with the public one, but to ensure minimum conditions of access to the entire population, at a reasonable cost and with a quality guarantee, to cover an important group of health conditions. This paper's main objective is to enquire what has happened with the use of several healthcare services after the reform was fully implemented. Methods: Concentration and Horizontal Inequity indices were estimated for the use of general practitioners, specialists, emergency room visits, laboratory and x-ray exams and hospitalization days. The change in such indices (pre and post-reform) was decomposed, following Zhong (2010). A "mean effect" (how these indices would change if the differential use in healthcare services were evenly distributed) and a "distribution effect" (how these indices would change with no change in average use) were obtained. Results: Changes in concentration indices were mainly due to mean effects for all cases, except for specialists (where "distribution effect" prevailed) and hospitalization days (where none of these effects prevailed over others). This implies that by providing more services across socioeconomic groups, less inequality in the use of services was achieved. On the other hand, changes in horizontal inequity indices were due to distribution effects in the case of GP, ER visits and hospitalization days; and due to mean effect in the case of x-rays. In the first three cases indices reduced their pro-poorness implying that after the reform relatively higher socioeconomic groups used these services more (in relation to their needs). In the case of x-rays, increased use was responsible for improving its horizontal inequity index. Conclusions: The increase in the average use of healthcare services after the AUGE reform has not always led to improved equity in the use of such services in most services. This indicates that there are still barriers to the equitable use of healthcare services (e.g. insufficient medical human resources, financial barriers, capacity constraints, etc.) that have remained after the reform. [ABSTRACT FROM AUTHOR]

Background: The paper presents evidence about the distribution of the benefits of public expenditures on a subset of priority public health services that are supposed to be provided free of charge in the public sector, using the framework of benefit incidence analysis. Methods: The study took place in 2 rural and 2 urban Local Government Areas from Enugu and Anambra states, southeast Nigeria. A questionnaire was used to collect data on use of the priority public health services by all individuals in the households (n=22,169). The level of use was disaggregated by socio-economic status (SES), rural-urban location and gender. Benefits were valued using the cost of providing the service. Net benefit incidence was calculated by subtracting payments made for services from the value of benefits. Results: The results showed that 3,281 (14.8%) individuals consumed wholly free services. There was a greater consumption of most free services by rural dwellers, females and those from poorer SES quintiles (but not for insecticide-treated nets and ante-natal care services). High levels of payment were observed for immunisation services, insecticide-treated nets, anti-malarial medicines, antenatal care and childbirth services, all of which are supposed to be provided for free. The net benefits were significantly higher for the rural residents, males and the poor compared to the urban residents, females and better-off quintiles. Conclusion: It is concluded that coverage of all of these priority public health services fell well below target levels, but the poorer quintiles and rural residents that are in greater need received more benefits, although not so for females. Payments for services that are supposed to be delivered free of charge suggests that there may have been illegal payments which probably hindered access to the public health services. [ABSTRACT FROM AUTHOR]

Introduction: Little rigorous evidence exists on how health service utilization varies across socioeconomic groups after a user fee exemption policy has been implemented, and the evidence that does exist is mixed. In this paper, we estimate the distribution of caesarean section deliveries across socioeconomic groups following Mali's implementation of a fee exemption policy for caesareans in 2005. Methods: We conducted a patient survey in 2010 to collect socioeconomic data from 2,477 women who had caesareans in a representative sample of 25 facilities across all regions of Mali. We used these data along with data from the most recent Demographic and Health Survey to construct a wealth index and classify women into population-based wealth groupings. We compared the wealth distribution of women delivering via caesarean section to that of a nationally representative sample of women giving birth. Results: We found that wealthier women make up a disproportionate share of those having free caesareans, five years after implementation of the fee exemption policy. Women in the richest two quintiles accounted for 58 percent of all caesareans, while women in the poorest two quintiles accounted for 27 percent of all caesareans. Fewer women in the poorest two-fifths of the population are receiving caesareans than what we would expect given their share in the population of women giving birth. Conclusions: While fee exemptions remove important financial barriers to accessing priority maternal health services, they are insufficient to ensure equal access among wealth groups. [ABSTRACT FROM AUTHOR]

Background: Health is recognized as a fundamental right in Brazil's constitution. In the absence of a clearly defined benefit packages of healthcare services that are financed under the Unified Health System (Sistema Único de Saúde, SUS), courts have become important in adjudicating coverage decisions. Empirical assessments of equity and the right to health tend to focus on simple measures of access. However, these empirical perspectives belie the significant inequalities and rights violations that arise in the case of more complex health needs such as cancer. To shed light on these issues, this paper focuses on the care pathways for breast and cervical cancer and explores access and quality issues that arise at different points along the care pathway with implications for the realization of the right to health in Brazil. Method: A mixed method approach is used. The analysis is primarily based on a quantitative analysis of national representative administrative data principally from the cervical and breast cancer information systems and the hospital cancer registry. To gain more insights into the organization of cancer care, qualitative data was collected from the state of Bahia, through document analysis, direct observation, roundtable discussions with health workers (HWs), and structured interviews with health care administrators. Results: The paper reveals that the volume of completed screening exams is well below the estimated need, and a tendency toward lower breast cancer screening rates in poorer states and for women in the lowest income brackets. Only 26% of breast cancer cases and 29% of cervical cancer cases are diagnosed at an early stage (stage 0 or I), thereby reducing the survival prospects of patients. Waiting times between confirmed diagnosis and treatment are long, despite new legislation that guarantees a maximum of 60 days. The waiting times are significantly longer for patients that follow the recommended patient pathways, and who are diagnosed outside the hospital. Conclusion: The study reveals that there are large variations between states and patients, where the poorest states and patients fare worse on key indicators. More broadly, the paper shows the importance of collecting data both on patient characteristics and health system performance and carry out detailed health system analysis for exposing, empirically, rights violations and for identifying how they can be addressed. [ABSTRACT FROM AUTHOR]