Socioeconomic Determinants of Health Inequalities Among the Older Population in India: A Decomposition Analysis

Goli, Srinivas; Singh, Lucky; Jain, Kshipra; Pou, Ladumai Maikho Apollo

doi:10.1007/s10823-014-9251-8

Cited by 31 publications

(34 citation statements)

References 43 publications

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“…The findings of the present study are generally in line with other studies decomposing income inequalities in mental health, in Europe [5,23], North America [31] and in low- and middle-income countries [32–34], pointing out the existence of inequalities disfavoring the less affluent population. Although it is hazardous to make a straight comparison between the Cs, it should be noted that the magnitude of inequalities in mental health in the present study is larger than that reported in a former study conducted in Europe [23].…”

Section: Discussionsupporting

confidence: 92%

Explaining mental health inequalities in Northern Sweden: a decomposition analysis

Amroussia

Gustafsson

Mosquera

2017

Global Health Action

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Background: There has been a substantial increase of income inequalities in Sweden over the last 20 years, which also could be reflected in health inequalities, including mental health inequalities. Despite the growing body of literature focusing on health inequalities in Sweden, income-related inequalities in mental health have received little attention. Particularly scarce are research from Northern Sweden and examinations of the social determinants of health inequalities.Objectives: The present study seeks to provide evidence regarding inequalities in mental health in Northern Sweden. The specific aims were to (1) quantify the income-related inequality in mental health in Northern Sweden, and (2) determine the contribution of social determinants to the inequality.Methods: The study population comprised 25,646 participants of the 2014 Health on Equal Terms survey in the four northernmost counties of Sweden, aged 16 to 84 years old. Income-related inequalities in mental health were quantified by the concentration index and further decomposed by applying Wagstaff-type decomposition analysis.Results: The overall concentration index of mental health in Northern Sweden was−0.15 (95% CI: −0.17 to −0.13), indicating income inequalities in mental health disfavoring the less affluent population. The decomposition analysis results revealed that socio-economic conditions, including employment status (31%), income (22.6%), and cash margin (14%), made the largest contribution to the pro-rich inequalities in mental health. The second-largest contribution came from demographic factors, mainly age (11.3%) and gender (6%). Psychosocial factors were of smaller importance, with perceived discrimination (8%) and emotional support (3.4%) making moderate contributions to the health inequalities. Conclusions: The present study demonstrates substantial income-related mental health inequalities in Northern Sweden, and provides insights into their underpinnings. These findings suggest that addressing the root causes is essential for promoting mental health equity in this region.

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Section: Discussionsupporting

confidence: 92%

Explaining mental health inequalities in Northern Sweden: a decomposition analysis

Amroussia

Gustafsson

Mosquera

2017

Global Health Action

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“…The concentration index has been widely used for measuring income-related inequalities in the health sector internationally, whilst its decomposition analysis has been increasingly adopted to study inequality determinants [11–13]. The majority of previous studies investigated health utilization inequality in China, with very limited study focused on health status [12, 14].…”

Section: Introductionmentioning

confidence: 99%

Decomposing socioeconomic inequalities in depressive symptoms among the elderly in China

Yang

Gao

et al. 2016

BMC Public Health

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BackgroundAccelerated population ageing brings about unprecedented challenges to the health system in China. This study aimed to measure the prevalence and the income-related inequality of depressive symptoms, and also identify the determinants of depressive symptom inequality among the elderly in China.MethodsData were drawn from the second wave of the China Health and Retirement Longitudinal Study (CHARLS). Depressive symptoms were assessed with a 10-item Center for Epidemiologic Studies–Depression Scale (CES-D), which was preselected in CHARLS. The concentration index was used to measure the magnitude of income-related inequality in depressive symptoms. A decomposition analysis, based on the logit model, was employed to quantify the contribution of each determinant to total inequality.ResultsMore than 32.55% of the elderly in China had depressive symptoms. Women had a higher prevalence of depressive symptoms than men. The overall concentration index of depressive symptoms was -0.0645 among the elderly, indicating that depressive symptoms are more concentrated among the elderly who lived in economically disadvantaged situations, favoring the rich. Income was found to have the largest percentage of contribution to overall inequality, followed by residents’ location and educational attainment.ConclusionThe prevalence of depressive symptoms in the elderly was considerably high in China. There was also a pro-rich inequality in depressive symptoms amongst elderly Chinese. It is suggested that some form of policy and intervention strategies, such as establishing the urban-rural integrated medical insurance scheme, enhancing the medical assistance system, and promoting health education programs, is required to alleviate inequitable distribution of depressive symptoms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-3876-1) contains supplementary material, which is available to authorized users.

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“…In addition, the older people tend to have fewer resources available to pay for health care (Freedman et al, 2004;Yadav et al, 2011;Goli et al, 2012). As the population ageing continues in India, the likeliest tendency is that the demand to access paid care and assistive technology will increase.…”

Section: Socioeconomic Differentials In the Burden Of Multiple Disabimentioning

confidence: 99%

“…As the population ageing continues in India, the likeliest tendency is that the demand to access paid care and assistive technology will increase. Thus, the disparity among the socioeconomic group will be the factor to reckon with, when a serious attempt is being made to reduce the potential of negative impact of population aging on labor Assessment of socioeconomic differentials productivity (Goli et al, 2012). Therefore, the assessment of disability by socioeconomic characteristics is critical in identifying the vulnerable groups and to make needs based assessment.…”

Section: Socioeconomic Differentials In the Burden Of Multiple Disabimentioning

confidence: 99%

Burden of multiple disabilities among the older population in India

Pou

Goli²

2013

International Journal of Sociology and Social Policy

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The aim of this study is twofold, first, to estimate the prevalence of multiple disabilities among the older population in India; second, to examine the socio economic determinants of multiple disabilities among the older population. Design/methodology/approach -This study used the India Human Development Survey Data (IHDS) for the analysis. Bivariate, multinomial logit regression and multiple classification analysis are used as methods for the study. Disability score is constructed for measuring the multiple disabilities among the older population. Findings -The results of disability prevalence show, a high prevalence of multiple disabilities among the older population in India. Further, disability prevalence varies considerably by age and socio-economic characteristics of the older population. Among all the socioeconomic factors, economic factor emerged as a dominant predictor of prevalence of disabilities among the older population in India. The findings of the dimension specific assessment reveal that the disability in walking is the highest among all the disabilities. The distribution of disabled older population by living arrangement and the social network indicates that a large proportion of disabled older population lives with their children. In addition, only a few of the disabled older people have social networks. The distribution of disabled older people by employment and financial source reveal that there is a meager government support to the disabled older population in India. This study evidently suggests that a significant number of older populations in India are suffering from multiple disabilities. The number of multiple disabilities increases with the decrease in the socioeconomic status. The living arrangement and financial security assessment suggest that there is an increasing need of children and government support to the disabled older population. Originality/value -The distinctiveness of this study can be primarily found in the type of the data used, the assessment of additional disability dimensions, and the inclusion of differentials such as living arrangement, social network and work status as part of the analysis. Overall, the study with its...

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Socioeconomic Determinants of Health Inequalities Among the Older Population in India: A Decomposition Analysis

Cited by 31 publications

References 43 publications

Explaining mental health inequalities in Northern Sweden: a decomposition analysis

Explaining mental health inequalities in Northern Sweden: a decomposition analysis

Decomposing socioeconomic inequalities in depressive symptoms among the elderly in China

Burden of multiple disabilities among the older population in India

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