Arnab Mukherji

Government health insurance for people below poverty line in India: quasi-experimental evaluation of insurance and health outcomes

Objectives To evaluate the effects of a government insurance program covering tertiary care for people below the poverty line in Karnataka, India, on out-of-pocket expenditures, hospital use, and mortality. Design Geographic regression discontinuity study. Setting 572 villages in Karnataka, India. Participants 31 476 households (22 796 below poverty line and 8680 above poverty line) in 300 villages where the scheme was implemented and 28 633 households (21 767 below poverty line and 6866 above poverty line) in 272 neighboring matched villages ineligible for the scheme. Intervention A government insurance program (Vajpayee Arogyashree scheme) that provided free tertiary care to households below the poverty line in about half of villages in Karnataka from February 2010 to August 2012. Main outcome measure Out-of-pocket expenditures, hospital use, and mortality. Results Among households below the poverty line, the mortality rate from conditions potentially responsive to services covered by the scheme (mostly cardiac conditions and cancer) was 0.32% in households eligible for the scheme compared with 0.90% among ineligible households just south of the eligibility border (difference of 0.58 percentage points, 95% confidence interval 0.40 to 0.75; P<0.001). We found no difference in mortality rates for households above the poverty line (households above the poverty line were not eligible for the scheme), with a mortality rate from conditions covered by the scheme of 0.56% in eligible villages compared with 0.55% in ineligible villages (difference of 0.01 percentage points, −0.03 to 0.03; P=0.95). Eligible households had significantly reduced out-of-pocket health expenditures for admissions to hospitals with tertiary care facilities likely to be covered by the scheme (64% reduction, 35% to 97%; P<0.001). There was no significant increase in use of covered services, although the point estimate of a 44.2% increase approached significance (−5.1% to 90.5%; P=0.059). Both reductions in out-of-pocket expenditures and potential increases in use might have contributed to the observed reductions in mortality. Conclusions Insuring poor households for efficacious but costly and underused health services significantly improves population health in India.

Ramanagaram financial diaries: Cash patterns and repayments of microfinance borrowers

Using three months of data from financial diaries tracking daily cash flows of a group of microfinance borrowers in two urban slums in Karnataka, India, we show that the burgeoning microfinance sector faces a number of constraints. These households are borrowing from multiple sources, specifically multiple MFIs. Secondly, a large fraction of each households budget is spent servicing loans with the two largest components of budget being loan repayment and food expenditure. Finally, households are observed to recycle their debts with over 27 per cent of fresh borrowings being spent on existing debts. These households in the urban slums of Ramanagaram are organizing their lives around multiple MFI memberships, multiple group meetings in a week and numerous repayment schedules. Apart from the stress to MFI clients of managing debts of small amounts from various MFIs, the Indian MFI sector will have to learn to grapple with the fallout of multiple memberships.

Slums and Malnourishment: Evidence From Women in India

OBJECTIVES We examined the association between slum residence and nutritional status in women in India by using competing classifications of slum type. METHODS We used nationally representative data from the 2005-2006 National Family Health Survey (NFHS-3) to create our citywide analysis sample. The data provided us with individual, household, and community information. We used the body mass index data to identify nutritional status, whereas the residential status variable provided slum details. We used a multinomial regression framework to model the 3 nutrition states-undernutrition, normal, and overnutrition. RESULTS After we controlled for a range of attributes, we found that living in a census slum did not affect nutritional status. By contrast, living in NFHS slums decreased the odds of being overweight by 14% (95% confidence interval [CI] =0.79, 0.95) and increased the odds of being underweight by 10% (95% CI=1.00, 1.22). CONCLUSIONS The association between slum residence and nutritional outcomes is nuanced and depends on how one defines a slum. This suggests that interventions targeted at slums should look beyond official definitions and include current living conditions to effectively reach the most vulnerable.

Report from a symposium on catalyzing primary and secondary prevention of cancer in India.

AbstractPurposeOral, breast, and cervical cancers are amenable to early detection and account for a third of India’s cancer burden. We convened a symposium of diverse stakeholders to identify gaps in evidence, policy, and advocacy for the primary and secondary prevention of these cancers and recommendations to accelerate these efforts. MethodsIndian and global experts from government, academia, private sector (health care, media), donor organizations, and civil society (including cancer survivors and patient advocates) presented and discussed challenges and solutions related to strategic communication and implementation of prevention, early detection, and treatment linkages.ResultsInnovative approaches to implementing and scaling up primary and secondary prevention were discussed using examples from India and elsewhere in the world. Participants also reflected on existing global guidelines and national cancer prevention policies and experiences.ConclusionsSymposium participants proposed implementation-focused research, advocacy, and policy/program priorities to strengthen primary and secondary prevention efforts in India to address the burden of oral, breast, and cervical cancers and improve survival.

Evidence on Community Driven Development from an Indian Village

This article examines the functioning of a community-driven development (CDD) project that, unlike most CDDs, was set in a homogeneous community, consisted of simple tasks, had a year-long pre-intervention planning period, and maintained records of its decisions. To identify the impacts of the intervention on agricultural outcomes, and on strategies to manage risk, we use a semi-parametric difference-in-difference model that collected retrospective panel data on programme participants and non-participants over multiple seasons. Our findings suggest that the CDD project led to greater exposure to risk and no gains in productivity for the community.

Economic Development, Inequality and Malnutrition in India

Economic development and inequality is known to have an impact on health outcomes. We show this to be true in India where we study the effect of economic status on under and over nutrition. Inequality is measured using income or assets and we show that both matter for malnutrition. We find women are at much higher risk of being malnourished and this risk increases with age. Our results suggest that while under nutrition should remain a policy priority, rising over nutrition in the population cannot be ignored by nutritional planners.

Financial risk protection from social health insurance

This paper estimates the impact of social health insurance on financial risk by utilizing data from a natural experiment created by the phased roll-out of a social health insurance program for the poor in India. We estimate the distributional impact of insurance on of out-of-pocket costs and incorporate these results with a stylized expected utility model to compute associated welfare effects. We adjust the standard model, accounting for conditions of developing countries by incorporating consumption floors, informal borrowing, and asset selling which allow us to separate the value of financial risk reduction from consumption smoothing and asset protection. Results show that insurance reduces out-of-pocket costs, particularly in higher quantiles of the distribution. We find reductions in the frequency and amount of money borrowed for health reasons. Finally, we find that the value of financial risk reduction outweighs total per household costs of the insurance program by two to five times.

The effect of paid maternity leave on early childhood growth in low-income and middle-income countries

Background Despite recent improvements, low height-for-age, a key indicator of inadequate child nutrition, is an ongoing public health issue in low-income and middle-income countries. Paid maternity leave has the potential to improve child nutrition, but few studies have estimated its impact. Methods We used data from 583 227 children younger than 5 years in 37 countries surveyed as part of the Demographic and Health Surveys (2000–2014) to compare the change in children’s height-for-age z score in five countries that increased their legislated duration of paid maternity leave (Uganda, Zambia, Zimbabwe, Bangladesh and Lesotho) relative to 32 other countries that did not. A quasiexperimental difference-in-difference design involving a linear regression of height-for-age z score on the number of weeks of legislated paid maternity leave was used. We included fixed effects for country and birth year to control for, respectively, fixed country characteristics and shared trends in height-for-age, and adjusted for time-varying covariates such as gross domestic product per capita and the female labour force participation rate. Results The mean height-for-age z scores in the pretreatment period were -1.91 (SD=1.44) and –1.47 (SD=1.57) in countries that did and did not change their policies, respectively. The scores increased in treated and control countries over time. A 1-month increase in legislated paid maternity leave was associated with a decrease of 0.08(95% CI −0.20 to 0.04) in child height-for-age z score. Sensitivity analyses did not support a robust association between paid maternity leave policies and height-for-age z score. Conclusion We found little evidence that recent changes in legislated paid maternity leave have been sufficient to affect child height-for-age z scores. The relatively short durations of leave, the potential for low coverage and the strong increasing trend in children’s growth may explain our findings. Future studies considering longer durations or combined interventions may reveal further insight to support policy.

Estimating Healthcare Demand for an Aging Population: A Flexible and Robust Bayesian Joint Model

In this paper, we analyse two frequently used measures of the demand for health care, namely hospital visits and out-of-pocket health care expenditure, which have been analysed separately in the existing literature. Given that these two measures of healthcare demand are highly likely to be closely correlated, we propose a framework to jointly model hospital visits and out-of-pocket medical expenditure. Furthermore, the joint framework allows for the presence of non-linear effects of covariates using splines to capture the effects of aging on healthcare demand. Sample heterogeneity is modelled robustly with the random effects following Dirichlet process priors with explicit cross-part correlation. The findings of our empirical analysis of the U.S. Health and Retirement Survey indicate that the demand for healthcare varies with age and gender and exhibits significant cross-part correlation that provides a rich understanding of how aging affects health care demand, which is of particular policy relevance in the context of an aging population.

Firm Size Distribution of Indian Medium, Small and Micro Enterprises

This paper analyzes the firm size distribution of Micro, Small and Medium Enterprises (MSME) using a nationally representative survey of unregistered firms in India that were collected as a part of the 3rd MSME Census in 2002. We find that the firm size distribution for younger firms is skewed to the right and the estimated density becomes log normal with age when we measure size using value of gross output. However, when we measure size using employment, the firm size is not log normal. We close with potential hypothesis as to why this may be so.