Achieving universal health coverage and sustainable development goals by 2030: investment estimates to increase production of health professionals in India.

BACKGROUND: COVID-19 has reinforced the importance of having a sufficient, well-distributed and competent health workforce. In addition to improving health outcomes, increased investment in health has the potential to generate employment, increase labour productivity and foster economic growth. We estimate the required investment for increasing the production of the health workforce in India for achieving the UHC/SDGs. METHODS: We used data from National Health Workforce Account 2018, Periodic Labour Force Survey 2018-19, population projection of Census of India, and government documents and reports. We distinguish between total stock of health professionals and active health workforce. We estimated current shortages in the health workforce using WHO and ILO recommended health worker:population ratio thresholds and extrapolated the supply of health workforce till 2030, using a range of scenarios of production of doctors and nurses/midwives. Using unit costs of opening a new medical college/nursing institute, we estimated the required levels of investment to bridge the potential gap in the health workforce. RESULTS: To meet the threshold of 34.5 skilled health workers per 10 000 population, there will be a shortfall of 0.16 million doctors and 0.65 million nurses/midwives in the total stock and 0.57 million doctors and 1.98 million nurses/midwives in active health workforce by the year 2030. The shortages are higher when compared with a higher threshold of 44.5 health workers per 10 000 population. The estimated investment for the required increase in the production of health workforce ranges from INR 523 billion to 2 580 billion for doctors and INR 1 096 billion for nurses/midwives. Such investment during 2021-2025 has the potential of an additional employment generation within the health sector to the tune of 5.4 million and to contribute to national income to the extent of INR 3 429 billion annually. CONCLUSION: India needs to significantly increase the production of doctors and nurses/midwives through investing in opening up new medical colleges. Nursing sector should be prioritized to encourage talents to join nursing profession and provide quality education. India needs to set up a benchmark for skill-mix ratio and provide attractive employment opportunities in the health sector to increase the demand and absorb the new graduates.

Socio-Economic Status Differences in Changing Affordability of Tobacco Products from 2011-2012 to 2018-2019 in India.

INTRODUCTION: We studied the change in affordability of tobacco products, an important determinant of tobacco use, across the different socio-economic status (SES) in India. AIMS AND METHODS: We calculated affordability in the form of relative income price (RIP-cost of tobacco products relative to income) for the years 2011-2012 and 2018-2019 using three different denominators, that is per capita gross domestic product (GDP) and net state domestic product at national and state levels, respectively; monthly per capita consumer expenditure (MPCE); and individual wages. We investigated RIP for cigarettes, bidis, and smokeless tobacco (SLT) across different SES groups (caste groups, type of employment, and education). RESULTS: RIP increased marginally for cigarettes, bidis and remained almost constant for SLT across casual workers. However, when RIP was adjusted with SES variables, there was no significant change (p > .05) in the affordability of products for casual workers in the year 2018-2019 as compared to 2011-2012. For regular workers, cigarettes and bidis became marginally less affordable (ß < 1), whereas affordability remained constant for SLT. All products became more affordable for backward caste groups within regular workers. When RIP was calculated using MPCE all tobacco products became less affordable in the year 2018-2019. However, after adjusting for SES variables SLT reported no change in affordability. There was a marginal increase in affordability for all products when RIP was calculated with GDP. CONCLUSIONS: Although implementation of GST has increased the price of tobacco products, it is still not sufficient to reduce the affordability of tobacco products, particularly SLT and especially for the lower SES group. IMPLICATIONS: Tobacco use and economic disadvantage conditions of the population are intricately linked. Affordability of tobacco products is influenced by socio-economic indicators like age, sex, income, education, etc. The literature measuring the affordability of tobacco products across different SES groups is scant in India. Additionally, existing literature measures affordability of tobacco products based on per capita GDP as a proxy for income. This is the first study in Indian context to report the change in affordability of tobacco products across different SES groups after adjusting for SES indicators, using individual-level income data. We have calculated the change in affordability of tobacco products between the year 2011-2012 and 2018-2019 using GDP, household income, and individual wages as a proxy for income.

Out-of-pocket expenditure on childhood infections and its financial burden on Indian households: Evidence from nationally representative household survey (2017-18).

The key objective of this research was to estimate out of pocket expenditure (OOPE) incurred by the Indian households for the treatment of childhood infections. We estimated OOPE estimates on outpatient care and hospitalization by disease conditions and type of health facilities. In addition, we also estimated OOPE as a share of households' total consumption expenditure (TCE) by MPCE quintile groups to assess the quantum of the financial burden on the households. We analyzed the Social Consumption: Health (SCH) data from National Sample Survey Organization (NSSO) 75th round (2017-18). Outcome indicators were prevalence of selected infectious diseases in children aged less than 5 years, per episode of OOPE on outpatient care in the preceding 15 days, hospitalization in the preceding year and OOPE as a share of households' total consumption expenditure. Our analysis suggests that the most common childhood infection was 'fever with rash' followed by 'acute upper respiratory infection' and 'acute meningitis'. However, the highest OOPE for outpatient care and hospitalization was reported for 'viral hepatitis' and 'tuberculosis' episodes. Among the households reporting childhood infections, OOPE was 4.8% and 6.7% of households' total consumption expenditure (TCE) for outpatient care and hospitalization, respectively. Furthermore, OOPE as a share of TCE was disproportionately higher for the poorest MPCE quintiles (outpatient, 7.9%; hospitalization, 8.2%) in comparison to the richest MPCE quintiles (outpatient, 4.8%; hospitalization, 6.7%). This treatment and care-related OOPE has equity implications for Indian households as the poorest households bear a disproportionately higher burden of OOPE as a share of TCE. Ensuring financial risk protection and universal access to care for childhood illnesses is critical to addressing inequity in care.

Multimorbidity, healthcare use and catastrophic health expenditure by households in India: a cross-section analysis of self-reported morbidity from national sample survey data 2017-18.

BACKGROUND: The purpose of this research is to generate new evidence on the economic consequences of multimorbidity on households in terms of out-of-pocket (OOP) expenditures and their implications for catastrophic OOP expenditure. METHODS: We analyzed Social Consumption Health data from National Sample Survey Organization (NSSO) 75th round conducted in the year 2017-2018 in India. The sample included 1,13,823 households (64,552 rural and 49,271 urban) through a multistage stratified random sampling process. Prevalence of multimorbidity and related OOP expenditure were estimated. Using Coarsened Exact Matching (CEM) we estimated the mean OOP expenditure for individuals reporting multimorbidity and single morbidity for each episode of outpatient visits and hospital admission. We also estimated implications in terms of catastrophic OOP expenditure for households. RESULTS: Results suggest that outpatient OOP expenditure is invariably lower in the presence of multimorbidity as compared with single conditions of the selected Non-Communicable Diseases(NCDs) (overall, INR 720 [USD 11.3] for multimorbidity vs. INR 880 [USD 14.8] for single). In the case of hospitalization, the OOP expenditures were mostly higher for the same NCD conditions in the presence of multimorbidity as compared with single conditions, except for cancers and cardiovascular diseases. For cancers and cardiovascular, OOP expenditures in the presence of multimorbidity were lower by 39% and 14% respectively). Furthermore, around 46.7% (46.674-46.676) households reported incurring catastrophic spending (10% threshold) because of any NCD in the standalone disease scenario which rose to 63.3% (63.359-63.361) under the multimorbidity scenario. The catastrophic implications of cancer among individual diseases was the highest. CONCLUSIONS: Multimorbidity leads to high and catastrophic OOP payments by households and treatment of high expenditure diseases like cancers and cardiovascular are under-financed by households in the presence of competing multimorbidity conditions. Multimorbidity should be considered as an integrated treatment strategy under the existing financial risk protection measures (Ayushman Bharat) to reduce the burden of household OOP expenditure at the country level.

Did the poor gain from India's health policy interventions? Evidence from benefit-incidence analysis, 2004-2018.

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.

Size, composition and distribution of health workforce in India: why, and where to invest?

BACKGROUND: Investment in human resources for health not only strengthens the health system, but also generates employment and contributes to economic growth. India can gain from enhanced investment in health workforce in multiple ways. This study in addition to presenting updated estimates on size and composition of health workforce, identifies areas of investment in health workforce in India. METHODS: We analyzed two sources of data: (i) National Health Workforce Account (NHWA) 2018 and (ii) Periodic Labour Force Survey 2017-2018 of the National Sample Survey Office (NSSO). Using the two sources, we collated comparable estimates of different categories of health workers in India, density of health workforce and skill-mix at the all India and state levels. RESULTS: The study estimated (from NHWA 2018) a total stock of 5.76 million health workers which included allopathic doctors (1.16 million), nurses/midwives (2.34 million), pharmacist (1.20 million), dentists (0.27 million), and traditional medical practitioner (AYUSH 0.79 million). However, the active health workforce size estimated (NSSO 2017-2018) is much lower (3.12 million) with allopathic doctors and nurses/midwives estimated as 0.80 million and 1.40 million, respectively. Stock density of doctor and nurses/midwives are 8.8 and 17.7, respectively, per 10,000 persons as per NHWA. However, active health workers' density (estimated from NSSO) of doctor and nurses/midwives are estimated to be 6.1 and 10.6, respectively. The numbers further drop to 5.0 and 6.0, respectively, after accounting for the adequate qualifications. All these estimates are well below the WHO threshold of 44.5 doctor, nurses and midwives per 10,000 population. The results reflected highly skewed distribution of health workforce across states, rural-urban and public-private sectors. A substantial proportion of active health worker were found not adequately qualified on the one hand and on the other more than 20% of qualified health professionals are not active in labor markets. CONCLUSION: India needs to invest in HRH for increasing the number of active health workers and also improve the skill-mix which requires investment in professional colleges and technical education. India also needs encouraging qualified health professionals to join the labor markets and additional trainings and skill building for already working but inadequately qualified health workers.

Size, composition and distribution of human resource for health in India: new estimates using National Sample Survey and Registry data.

OBJECTIVES: We provide new estimates on size, composition and distribution of human resource for health in India and compare with the health workers population ratio as recommended by the WHO. We also estimate size of non-health workers engaged in health sector and the size of technically qualified health professionals who are not a part of the health workforce. DESIGN: Nationally representative cross-section household survey and review of published documents by the Central Bureau of Health Intelligence. SETTING: National. PARTICIPANTS: Head of household/key informant in a sample of 101 724 households. INTERVENTIONS: Not applicable. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the number and density of health workers,and the secondary outcome was the percentage of health workers who are technically qualified and the percentage of individuals technically qualified and not in workforce. RESULTS: The total size of health workforce estimated from the National Sample Survey (NSS) data is 3.8 million as of January 2016, which is about 1.2 million less than the total number of health professionals registered with different councils and associations. The density of doctors and nurses and midwives per 10 000 population is 20.6 according to the NSS and 26.7 based on the registry data. Health workforce density in rural India and states in eastern India is lower than the WHO minimum threshold of 22.8 per 10 000 population. More than 80% of doctors and 70% of nurses and midwives are employed in the private sector. Approximately 25% of the currently working health professionals do not have the required qualifications as laid down by professional councils, while 20% of adequately qualified doctors are not in the current workforce. CONCLUSIONS: Distribution and qualification of health professionals are serious problems in India when compared with the overall size of the health workers. Policy should focus on enhancing the quality of health workers and mainstreaming professionally qualified persons into the health workforce.

Quantifying the financial burden of households' out-of-pocket payments on medicines in India: a repeated cross-sectional analysis of National Sample Survey data, 1994-2014.

OBJECTIVE: The objective of this research is to generate new evidence on financial implications of medicines out-of-pocket (OOP) payments for households. Another objective is to investigate which disease conditions contributed to a significant proportion of households' financial burden. SETTING: All Indian states including union territories, 1993-2014. DESIGN: Repeated cross-sectional household surveys. DATA: Secondary data of nationwide Consumer Expenditure Surveys for the years 1993-1994, 2004-2005 and 2011-2012 and one wave of Social Consumption: Health for the year 2014 from National Sample Survey Organisation. OUTCOME MEASURES: OOP expenditure on healthcare in general and medicines in specific. RESULTS: Total OOP payments and medicines OOP payments were estimated to be 6.77% (95% CI 6.70% to 6.84%) and 4.49% (95% CI 4.45% to 4.54%) of total consumption expenditure, respectively, in the year 2011-2012 which marked significant increase since 1993-1994. These proportions were 11.46% (95% CI 11.36% to 11.56%) and 7.60% (95% CI 7.54% to 7.67%) of non-food expenditure, respectively, in the same year. Total OOP payments and medicines OOP payments were catastrophic for 17.9% (95% CI 17.7% to 18.2%) and 11.2% (95% CI 11.0% to 11.4%) households, respectively, in 2011-2012 at the 10% of total consumption expenditure threshold, implying 29 million households incurred catastrophic OOP payments in the year 2011-2012. Further, medicines OOP payments pushed 3.09% (95% CI 2.99% to 3.20%), implying 38 million persons into poverty in the year 2011-2012. Among the leading cause of diseases that caused significant OOP payments are cancers, injuries, cardiovascular diseases, genitourinary conditions and mental disorders. CONCLUSIONS: Purchase of medicines constitutes the single largest component of the total OOP payments by households. Hence, strengthening government intervention in providing medicines free in public healthcare facilities has the potential to considerably reduce medicine-related spending and total OOP payments of households and reduction in OOP-induced poverty.

Progress Toward Universal Health Coverage: A Comparative Analysis in 5 South Asian Countries.

Importance: Achieving universal health coverage is one of the key targets in the newly adopted Sustainable Development Goals of the United Nations. Objective: To investigate progress toward universal health coverage in 5 South Asian countries and assess inequalities in health services and financial risk protection indicators. Design and Settings: In a population-based study, nationally representative household (335 373 households) survey data from Afghanistan (2014 and 2015), Bangladesh (2010 and 2014), India (2012 and 2014), Nepal (2014 and 2015), and Pakistan (2014) were used to calculate relative indices of health coverage, financial risk protection, and inequality in coverage among wealth quintiles. The study was conducted from June 2012 to February 2016. Main Outcomes and Measures: Three dimensions of universal health coverage were assessed: access to basic services, financial risk protection, and equity. Composite and indicator-specific coverage rates, stratified by wealth quintiles, were then estimated. Slope and relative index of inequality were used to assess inequalities in service and financial indicators. Results: Access to basic care varied substantially across all South Asian countries, with mean rates of overall prevention coverage and treatment coverage of 53.0% (95% CI, 42.2%-63.6%) and 51.2% (95% CI, 45.2%-57.1%) in Afghanistan, 76.5% (95% CI, 61.0%-89.0%) and 44.8% (95% CI, 37.1%-52.5%) in Bangladesh, 74.2% (95% CI, 57.0%-88.1%) and 83.5% (95% CI, 54.4%-99.1%) in India, 76.8% (95% CI, 66.5%-85.7%) and 57.8% (95% CI, 50.1%-65.4%) in Nepal, and 69.8% (95% CI, 58.3%-80.2%) and 50.4% (95% CI, 37.1%-63.6%) in Pakistan. Financial risk protection was generally low, with 15.3% (95% CI, 14.7%-16.0%) of respondents in Afghanistan, 15.8% (95% CI, 14.9%-16.8%) in Bangladesh, 17.9% (95% CI, 17.7%-18.2%) in India, 11.8% (95% CI, 11.8%-11.9%) in Nepal, and 4.4% (95% CI, 4.0%-4.9%) in Pakistan reporting incurred catastrophic payments due to health care costs. Access to at least 4 antenatal care visits, institutional delivery, and presence of skilled attendant during delivery were at least 3 times higher among the wealthiest mothers in Afghanistan, Bangladesh, Nepal, and Pakistan compared with the rates among poor mothers. Access to institutional delivery was 60 to 65 percentage points higher among wealthy than poor mothers in Afghanistan, Bangladesh, Nepal, and Pakistan compared with 21 percentage points higher in India. Coverage was least equitable among the countries for adequate sanitation, institutional delivery, and the presence of skilled birth attendants. Conclusions and Relevance: Health coverage and financial risk protection was low, and inequality in access to health care remains a serious issue for these South Asian countries. Greater progress is needed to improve treatment and preventive services and financial security.

Extending health insurance to the poor in India: An impact evaluation of Rashtriya Swasthya Bima Yojana on out of pocket spending for healthcare.

India launched the 'Rashtriya Swasthya Bima Yojana' (RSBY) health insurance scheme for the poor in 2008. Utilising 3 waves (1999-2000, 2004-05 and 2011-12) of household level data from nationally representative surveys of the National Sample Survey Organisation (NSSO) (N = 346,615) and district level RSBY administrative data on enrolment, we estimated causal effects of RSBY on out-of-pocket expenditure. Using 'difference-in-differences' methods on households in matched districts we find that RSBY did not affect the likelihood of inpatient out-of-pocket spending, the level of inpatient out of pocket spending or catastrophic inpatient spending. We also do not find any statistically significant effect of RSBY on the level of outpatient out-of-pocket expenditure and the probability of incurring outpatient expenditure. In contrast, the likelihood of incurring any out of pocket spending (inpatient and outpatient) rose by 30% due to RSBY and was statistically significant. Although out of pocket spending levels did not change, RSBY raised household non-medical spending by 5%. Overall, the results suggest that RSBY has been ineffective in reducing the burden of out-of-pocket spending on poor households.

Impact of Publicly Financed Health Insurance Schemes on Healthcare Utilization and Financial Risk Protection in India: A Systematic Review.

Several publicly financed health insurance schemes have been launched in India with the aim of providing universalizing health coverage (UHC). In this paper, we report the impact of publicly financed health insurance schemes on health service utilization, out-of-pocket (OOP) expenditure, financial risk protection and health status. Empirical research studies focussing on the impact or evaluation of publicly financed health insurance schemes in India were searched on PubMed, Google scholar, Ovid, Scopus, Embase and relevant websites. The studies were selected based on two stage screening PRISMA guidelines in which two researchers independently assessed the suitability and quality of the studies. The studies included in the review were divided into two groups i.e., with and without a comparison group. To assess the impact on utilization, OOP expenditure and health indicators, only the studies with a comparison group were reviewed. Out of 1265 articles screened after initial search, 43 studies were found eligible and reviewed in full text, finally yielding 14 studies which had a comparator group in their evaluation design. All the studies (n-7) focussing on utilization showed a positive effect in terms of increase in the consumption of health services with introduction of health insurance. About 70% studies (n-5) studies with a strong design and assessing financial risk protection showed no impact in reduction of OOP expenditures, while remaining 30% of evaluations (n-2), which particularly evaluated state sponsored health insurance schemes, reported a decline in OOP expenditure among the enrolled households. One study which evaluated impact on health outcome showed reduction in mortality among enrolled as compared to non-enrolled households, from conditions covered by the insurance scheme. While utilization of healthcare did improve among those enrolled in the scheme, there is no clear evidence yet to suggest that these have resulted in reduced OOP expenditures or higher financial risk protection.

What is the private sector? Understanding private provision in the health systems of low-income and middle-income countries.

Private health care in low-income and middle-income countries is very extensive and very heterogeneous, ranging from itinerant medicine sellers, through millions of independent practitioners-both unlicensed and licensed-to corporate hospital chains and large private insurers. Policies for universal health coverage (UHC) must address this complex private sector. However, no agreed measures exist to assess the scale and scope of the private health sector in these countries, and policy makers tasked with managing and regulating mixed health systems struggle to identify the key features of their private sectors. In this report, we propose a set of metrics, drawn from existing data that can form a starting point for policy makers to identify the structure and dynamics of private provision in their particular mixed health systems; that is, to identify the consequences of specific structures, the drivers of change, and levers available to improve efficiency and outcomes. The central message is that private sectors cannot be understood except within their context of mixed health systems since private and public sectors interact. We develop an illustrative and partial country typology, using the metrics and other country information, to illustrate how the scale and operation of the public sector can shape the private sector's structure and behaviour, and vice versa.

Have Socioeconomic Inequalities in Tobacco Use in India Increased Over Time? Trends From the National Sample Surveys (2000-2012).

INTRODUCTION: India has experienced marked sociocultural change, economic growth and industry promotion of tobacco products over the past decade. Little is known about the influence of these factors on socioeconomic patterning of tobacco use. This study examines trends in tobacco use by socioeconomic status (SES) in India between 2000 and 2012. METHODS: We analyzed data in 2014 from nationally-representative repeated cross-sectional National Sample Surveys (NSS) in India for 1999-2000, 2004-2005 and 2011-2012 (n = 346 612 households). Prevalence and volume trends in cigarette, "bidi" and smokeless tobacco use were examined by household expenditure, educational attainment and caste/tribe status using Two-part model. RESULTS: Prevalence of any tobacco use remained consistent in the poorest households (61.5% to 62.7%) and declined among the richest (43.8% to 36.8%) between 2000-2012. Bidi use declined across all groups (poorest: 26.3% to 16.8%, richest: 19.8% to 10.7%) while cigarette use increased (poorest: 1.2% to 1.3%, richest: 6.5% to 7.0%). Relative to educated and general caste households, between 2000 and 2012 cigarette use in illiterate households increased by 38% and among Scheduled Tribe households increased by 32%. Smokeless tobacco use increased for all households (poorest: 26.2% to 33.9%, richest: 11.4% to 13.5%, Scheduled Tribe: 31.1% to 34.8%, general caste: 13.6% to 18.5%), with greater increases among richer, more educated and general caste households. CONCLUSION: Marked SES patterning of tobacco use has persisted in India. Improving enforcement of tobacco control policies and monitoring comprehensive smoke-free legislations are needed to address this growing burden. IMPLICATIONS: We found "resilient" tobacco patterns in the last decade despite prevention interventions. SES continues to be inversely associated with tobacco products, with the exception of cigarettes. The declines in bidi use may be getting replaced by increase in cigarette use trends, especially among lower SES groups. The use of smokeless tobacco products has increased across all SES groups and the volume of smokeless tobacco use is not been declining despite a number of policies on tobacco use. This may be attributed to inadequate attention to chewed forms of tobacco in current policies, particularly to implementing pictoral warnings and regulating surrogate advertising. Evaluating the implementation of anti-tobacco policies and ensuring equity dimensions in interventions is urgently needed to address tobacco use inequalities.

Price elasticity of tobacco products among economic classes in India, 2011-2012.

OBJECTIVES: The objectives of this study are to: (1) examine the pattern of price elasticity of three major tobacco products (bidi, cigarette and leaf tobacco) by economic groups of population based on household monthly per capita consumption expenditure in India and (2) assess the effect of tax increases on tobacco consumption and revenue across expenditure groups. SETTING: Data from the 2011-2012 nationally representative Consumer Expenditure Survey from 101,662 Indian households were used. PARTICIPANTS: Households which consumed any tobacco or alcohol product were retained in final models. PRIMARY OUTCOME MEASURES: The study draws theoretical frameworks from a model using the augmented utility function of consumer behaviour, with a two-stage two-equation system of unit values and budget shares. Primary outcome measures were price elasticity of demand for different tobacco products for three hierarchical economic groups of population and change in tax revenue due to changes in tax structure. We finally estimated price elasticity of demand for bidi, cigarette and leaf tobacco and effects of changes in their tax rates on demand for these tobacco products and tax revenue. RESULTS: Own price elasticities for bidi were highest in the poorest group (-0.4328) and lowest in the richest group (-0.0815). Cigarette own price elasticities were -0.832 in the poorest group and -0.2645 in the richest group. Leaf tobacco elasticities were highest in the poorest (-0.557) and middle (-0.4537) groups. CONCLUSIONS: Poorer group elasticities were the highest, indicating that poorer consumers are more price responsive. Elasticity estimates show positive distributional effects of uniform bidi and cigarette taxation on the poorest consumers, as their consumption is affected the most due to increases in taxation. Leaf tobacco also displayed moderate elasticities in poor and middle tertiles, suggesting that tax increases may result in a trade-off between consumption decline and revenue generation. A broad spectrum rise in tax rates across all products is critical for tobacco control.

Evidence for cost-effectiveness of lifestyle primary preventions for cardiovascular disease in the Asia-Pacific Region: a systematic review.

BACKGROUND: Countries of the Asia Pacific region account for a major share of the global burden of disease due to cardiovascular disease (CVD) and this burden is rising over time. Modifiable behavioural risk factors for CVD are considered a key target for reduction in incidence but their effectiveness and cost-effectiveness tend to depend on country context. However, no systematic assessment of cost-effectiveness of interventions addressing behavioural risk factors in the region exists. METHODS: A systematic review of the published literature on cost-effectiveness of interventions targeting modifiable behavioural risk factors for CVD was undertaken. Inclusion criteria were (a) countries in Asia and the Pacific, (b) studies that had conducted economic evaluations of interventions (c) published papers in major economic and public health databases and (d) a comprehensive list of search words to identify appropriate articles. All authors independently examined the final list of articles relating to methodology and findings. RESULTS: Under our inclusion criteria a total of 28 studies, with baseline years ranging from 1990 to 2012, were included in the review, 19 conducted in high-income countries of the region. Reviewed studies assessed cost-effectiveness of interventions for tobacco control, alcohol reduction, salt intake control, physical activity and dietary interventions. The majority of cost-effectiveness analyses were simulation analyses mostly relying on developed country data, and only 6 studies used effectiveness data from RCTs in the region. Other than for Australia, no direct conclusions could be drawn about cost-effectiveness of interventions targeting behavioural risk factors due to the small number of studies, interventions that varied widely in design, and varied methods for measurement of costs associated with interventions. CONCLUSIONS: Good quality cost-effectiveness information on interventions targeting behavioural interventions for the Asia-Pacific region remains a major gap in the literature.

Moving to universal coverage? Trends in the burden of out-of-pocket payments for health care across social groups in India, 1999-2000 to 2011-12.

In the background of ongoing health sector reforms in India, the paper investigates the magnitude and trends in out-of-pocket and catastrophic payments for key population sub-groups. Data from three rounds of nationally representative consumer expenditure surveys (1999-2000, 2004-05 and 2011-12) were pooled to assess changes over time in a range of out-of-pocket -related outcome indicators for the poorest 20% households, scheduled caste and tribe households and Muslims households relative to their better-off/majority religion counterparts. Our results suggest that the poorest 20% of households experienced a decline in the proportion reporting any OOP for inpatient care relative to the top 20% and Muslim households saw an increase in the proportion reporting any inpatient OOP relative to non-Muslim households during 2000-2012. The change in the proportion of Muslim households or SC/ST households reporting any OOP for outpatient care was similar to that for their respective more advantaged counterparts; but the poorest 20% of households experienced a faster increase in the proportion reporting any OOP for outpatient care than their top 20% counterparts. SC/ST, Muslim and the poorest 20% of households experienced as faster increase in the share of outpatient OOP in total household spending relative to their advantaged counterparts. We conclude that the financial burden of out of pocket spending increased faster among the disadvantaged groups relative to their more advantaged counterparts. Although the poorest 20% saw a relative decline in OOP spending on inpatient care as a share of household spending, this is likely the result of foregoing inpatient care, than of accessing benefits from the recent expansion of cashless publicly financed insurance schemes for inpatient care. Our results highlight the need to explore the reasons underlying the lack of effectiveness of existing public health financing programs and public sector health services in reaching less-advantaged castes and religious minorities.

The household-level economic burden of heart disease in India.

OBJECTIVES: To estimate healthcare use and financial burden associated with heart disease among Indian households. METHODS: Data from the 2004 round household survey of the National Sample Survey in India were used to assess the implications of heart disease for out-of-pocket health spending, spending on items other than health care, employment and healthcare financing patterns, by matching households with a member self-reporting heart disease (cardiovascular disease (CVD)-affected households) to (control) households with similar socio-economic and demographic characteristics. Propensity score matching methods were used. RESULTS: Compared with control households, CVD-affected households had more outpatient visits and inpatient stays, spent an extra INT$ (International Dollars) 232 (P < 0.01) per member on inpatient care annually, had lower non-medical spending (by INT$5 (P < 0.01) per member for a 15-day reference period), had a share of out-of-pocket health spending in total household expenditure that was 16.5% higher (P < 0.01) and relied more on borrowing and asset sales to finance inpatient care (32.7% vs. 12.8%, P < 0.01). Members of CVD-affected households had lower employment rates than members of control households (43.6% vs. 46.4%, P < 0.01), and elderly members experienced larger declines in employment than younger adults. CVD-affected households with lower socio-economic status were at heightened financial risk. CONCLUSION: Non-communicable conditions such as CVD can impose a serious economic burden on Indian households.

The economic burden of cancers on Indian households.

We assessed the burden of cancer on households' out-of-pocket health spending, non-medical consumption, workforce participation, and debt and asset sales using data from a nationally representative health and morbidity survey in India for 2004 of nearly 74 thousand households. Propensity scores were used to match households containing a member diagnosed with cancer (i.e. cancer-affected households) to households with similar socioeconomic and demographic characteristics (controls). Our estimates are based on data from 1,645 households chosen through matching. Cancer-affected households experienced higher levels of outpatient visits and hospital admissions and increased out-of-pocket health expenditures per member, relative to controls. Cancer-affected households spent between Indian Rupees (INR) 66 and INR 85 more per member on healthcare over a 15-day reference period, than controls and additional expenditures (per member) incurred on inpatient care by cancer-affected households annually is equivalent to 36% to 44% of annual household expenditures of matched controls. Members without cancer in cancer-affected households used less health-care and spent less on healthcare. Overall, adult workforce participation rates were lower by between 2.4 and 3.2 percentage points compared to controls; whereas workforce participation rates among adult members without cancer were higher than in control households. Cancer-affected households also had significantly higher rates of borrowing and asset sales for financing outpatient care that were 3.3% to 4.0% higher compared to control households; and even higher for inpatient care.

State health insurance and out-of-pocket health expenditures in Andhra Pradesh, India.

In 2007 the state of Andhra Pradesh in southern India began rolling out Aarogyasri health insurance to reduce catastrophic health expenditures in households 'below the poverty line'. We exploit variation in program roll-out over time and districts to evaluate the impacts of the scheme using difference-in-differences. Our results suggest that within the first nine months of implementation Phase I of Aarogyasri significantly reduced out-of-pocket inpatient expenditures and, to a lesser extent, outpatient expenditures. These results are robust to checks using quantile regression and matching methods. No clear effects on catastrophic health expenditures or medical impoverishment are seen. Aarogyasri is not benefiting scheduled caste and scheduled tribe households as much as the rest of the population.

The Economic impact of Non-communicable Diseases on households in India.

BACKGROUND: In India, Non Communicable Diseases (NCDs) and injuries account for an estimated 62% of the total age-standardized burden of forgone Disability Adjusted Life Years (DALYs). Public and private financing of clinical services to reduce the NCD burden is a major challenge. METHODS: We used National Sample Survey Organization (NSSO) survey data from 1995-96 and 2004 covering nearly 200 thousand households to assess healthcare utilization patterns and out of pocket health spending by disease category. For this purpose, self-reported diseases and conditions were categorized into NCDs and non-NCDs. Survey data were used to assess how households financed their overall health expenditures and related this pattern to specific health conditions. We measured catastrophic spending on NCD-related hospitalization, defined as occurring when health expenditures exceeded 40% of a household's ability to pay, that is, household consumption spending less combined survival consumption expenditure; and impoverishment when per capita expenditure within the household decreased to below the poverty line once health spending was netted out. RESULTS: The share of NCDs in out of pocket health expenses incurred by households increased over time, from 31.6 percent in 1995-96 to 47.3 percent in 2004. In both years, own savings and income were the most important source of financing for many health conditions, typically between 40-60 percent of all spending, whereas 30-35 percent was from borrowing. The odds of catastrophic hospitalization expenditures for cancer was nearly 170% greater and for CVD and injuries 22 percent greater than the odds due to communicable diseases. Impoverishment patterns were similar. CONCLUSIONS: Out of pocket expenses for treating NCDs rose sharply over the period from 1995-96 to 2004. When NCDs are present, the financial risks to which Indians households are exposed are significant.