Life 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. A 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. Cognitive 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. It 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.

Multi-morbidity among elderly is increasingly recognized as a major public health challenge in most of the developing countries. However, information on the size of population suffering from multi-morbidity and socio-economic differentials of multi-morbidity is scarce. The objectives of this paper are twofold; first, to assess the prevalence of various chronic conditions and morbidity among rural elderly and second, to examine the socio-economic and demographic factors that have a significant effect on the morbidity. A cross-sectional survey has been done using multi-stage random sampling procedure that was conducted among elderly (60+ years) in Bargarh District of Odisha during October 2011-February 2012. The survey was conducted among 310 respondents including 153 males and 157 females. Descriptive analyses were performed to assess the pattern of multi-morbidity. Logistic regression analyses were used to see the adjusted effect of various socio-economic and demographic covariates of multi-morbidity. The overall prevalence of multi-morbidity is 57% among rural elderly in Bargarh District of Odisha. The most common diseases in rural areas are: Arthritis, Chronic Obstructive Pulmonary Disease (COPD), High Blood Pressure and Cataract. Results from the logistic regression analyses show that age, state of economic independence and life style indicators are the most important measured predictors of multi-morbidity. Unlike earlier studies, wealth index and education have a marginal impact on multi-morbidity rate. Moreover, the occurrence of multi-morbidity is higher for elderly males compared to their female counterparts, though the difference is not significant. The high prevalence of morbidity observed in the present study suggests that there is an urgent need to develop geriatric health care services in a developing country like India. Any effort to reorganize primary care for elderly people should also consider the high prevalence of multi-morbidity among rural elderly in India.

To our knowledge, the present study provides a first time assessment of the contributions of socioeconomic determinants of immunization coverage in India using the recent National Family Health Survey data. Measurement of socioeconomic inequalities in health and health care, and understanding the determinants of such inequalities in terms of their contributions, are critical for health intervention strategies and for achieving equity in health care. A decomposition approach is applied to quantify the contributions from socio-demographic factors to inequality in immunization coverage. The results reveal that poor household economic status, mother's illiteracy, per capita state domestic product and proportion of illiterate at the state level is systematically related to 97% of predictable socioeconomic inequalities in full immunization coverage at the national level. These patterns of evidence suggest the need for immunization strategies targeted at different states and towards certain socioeconomic determinants as pointed out above in order to reduce socioeconomic inequalities in immunization coverage.

Summary: As India rapidly urbanizes, within urban areas socioeconomic disparities are rising and health inequality among urban children is an emerging challenge. This paper assesses the relative contribution of socioeconomic factors to child health inequalities between the less developed Empowered Action Group (EAG) states and more developed South Indian states in urban India using data from the 2005–06 National Family Health Survey. Focusing on urban health from varying regional and developmental contexts, socioeconomic inequalities in child health are examined first using Concentration Indices (CIs) and then the contributions of socioeconomic factors to the CIs of health variables are derived. The results reveal, in order of importance, pronounced contributions of household economic status, parent's illiteracy and caste to urban child health inequalities in the South Indian states. In contrast, parent's illiteracy, poor economic status, being Muslim and child birth order 3 or more are major contributors to health inequalities among urban children in the EAG states. The results suggest the need to adopt different health policy interventions in accordance with the pattern of varying contributions of socioeconomic factors to child health inequalities between the more developed South Indian states and less developed EAG states.

High maternity-related health care spending is often cited as an important barrier in utilizing quality health care during pregnancy and childbirth. This study has two objectives: (i) to measure the levels of expenditure on total maternity care in disaggregated components such as ANCs, PNCs, and Natal care expenditure; (ii) to quantify the extent of catastrophic maternity expenditure (CME) incurred by households and identify the factors responsible for it. Data from the 71^st round of the National Sample Survey (2014) was used to estimate maternity expenditure and its predictors. CME was measured as a share of consumption expenditure by different cut-offs. The two-part model was used to identify the factors associated with maternity spending and CME. The findings show that household spending on maternity care (US$ 149 in constant price) is much higher than previous estimates (US$ 50 in constant price). A significant proportion of households in India (51%) are incurring CME. Along with economic and educational status, type of health care and place of residence emerged as significant factors in explaining CME. Findings from this study assume importance in the context of an emerging demand for higher maternity entitlements and government spending on public health care in India. To reduce CME, India needs to improve the availability and accessibility of better-quality public health services and increase maternity entitlements in line with maternity expenditure identified in this study.