BackgroundEquity 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.MethodsThe 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.ResultsThe gap in the ratio of average healthcare spending between the poorest and richest households was maximum in Category A states (richest/poorest = 14.60), followed by Category B (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.ConclusionsIn 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.

BackgroundLife Satisfaction (LS) is an indicator of subjective well-being (SWB) among the elderly, and is directly associated with health and mortality. Present study deals with the factors associated with the LS among the rural elderly in Odisha, India.MethodsA cross-sectional survey using multi-stage random sampling procedure was conducted among elderly (60+ years) in Bargarh district of Odisha. The survey was conducted among 310 respondents. Hierarchical regression analysis was used to assess the adjusted effect of various socio-economic, demographic, health conditions (physical and mental), social support and effects of multi-morbidity on LS.ResultsCognitive health was the most influential factor in determining LS among both men (β = 0.327) and women (β = 0.329). Individual’s social support also plays an influential role in LS among rural elderly. Elderly who are living alone and have any sort of disability and had low score of activities of daily living (ADL) have also reported significantly lower perceived LS for both the genders.ConclusionIt is necessary to analyze and identify the major factors which can improve upon the level of LS among the elderly population. Better understanding of these factors can help in removing the superfluous anxiety of old age in the mindset of people which is pervading in the society.

Subjects with epilepsy had lower marriage prevalence rate, delayed marriage (especially females), withheld marriage and higher divorce rate compared to general population. Marriage rate was lower in people with age at onset of epilepsy less than 20 years and in whom seizures were not in remission. Majority of people with epilepsy did not disclose epilepsy before marriage. Though fertility was not affected in people with epilepsy as compared to general population, males had lower fertility than females.

Background: Multimorbidity, the presence of two or more chronic health conditions is linked to premature mortality among psychiatric patients since the presence of one can further complicate the management of either. Little research has focused on the magnitude and effect of multimorbidity among psychiatric patients in low-and middle-income settings. Our study, provides the first ever data on multimorbidity and its outcomes among patients attending psychiatric clinics in Odisha, India. It further explored whether multimorbidity was associated with higher medical expenditure and the interaction effect of psychiatric illness on this association.Methods: This cross-sectional study included 500 adult patients presenting to the psychiatric clinic of a medical college hospital in Odisha over a period of 6 months (February 2019–July 2019). A validated structured questionnaire, “multimorbidity assessment questionnaire for psychiatric care” (MAQ-PsyC) was used for data collection. We used multinomial logistic model for the effect estimation. Odds ratios (OR) and 95% confidence intervals (CI) for high healthcare utilization and expenditure were calculated by number and pattern of multimorbidity. Data was analyzed by STATA 14.Results: Half (50%) of the psychiatric outpatients had multimorbidity. The relative probabilities of having one additional condition were 5.3 times (RRR = 5.3; 95% CI: 2.3, 11.9) and multiple morbidities were 6.6 times (RRR = 6.6; 95%CI: 3.3, 13.1) higher for patients in 60+ age group. Healthcare utilization i.e., medication use and physician consultation was significantly higher for psychiatric conditions such as mood disorders, schizophrenia, schizotypal and delusional disorders, and for hypertension, cancer, diabetes, among somatic conditions. Out of pocket expenditure (OOPE) was found to be highest for laboratory investigations, followed by medicines and transport expenditure. Within psychiatric conditions, mood disorders incurred highest OOPE ($93.43) while hypertension was the most leading for OOPE in physical morbidities ($93.43). Psychiatric illnesses had a significant interaction effect on the association between multimorbidity and high medical expenditure (P = 0.001).Conclusion: Multimorbidity is highly prevalent in psychiatric patients associated with significantly high healthcare utilization and medical expenditure. Such disproportionate effect of psychiatric multimorbidity on healthcare cost and use insinuates the need for stronger financial protection and tailor-made clinical decision making for these vulnerable patient subgroups.