scholarly journals Understanding socio-economic inequalities in the prevalence of asthma in India: an evidence from national sample survey 2017–18

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rashmi Rashmi ◽  
Pradeep Kumar ◽  
Shobhit Srivastava ◽  
T. Muhammad
Keyword(s):  
Concentration Index ◽  
Economic Inequality ◽  
Decomposition Analysis ◽  
National Sample ◽  
Household Size ◽  
Sample Survey ◽  
Asthma Prevalence ◽  
Place Of Residence ◽  
National Sample Survey ◽  
Factors Associated

Abstract Background Today, over 300 million people reside with asthma worldwide and India alone is home for 6% of children and 2% of adults suffering from this chronic disease. A common notion of disparity persists in terms of health outcomes across the poor and better-off section of the society. Thus, there is a need to explore socio-economic inequality in the contribution of various factors associated with asthma prevalence in India. Methods Data for the study were carved out from the 75th round of National Sample Survey (NSS), collected by the National Sample Survey Organization (NSSO) during 2017–18. The sample size for this study was 555,289 individuals, for which data was used for the analysis. Descriptive statistics were used to show the distribution of the study population. Further, bivariate and multivariate analysis was performed to identify the factors associated with Asthma prevalence. The concentration index was used to measure the inequality. Further, we used decomposition analysis to find the contribution of factors responsible for socio-economic status-related inequality in asthma prevalence. Results The prevalence of asthma was 2 per 1000 in the whole population; however, the prevalence differs by age groups in a significant manner. Age, sex, educational status, place of residence, cooking fuel, source of drinking water, household size and garbage disposal facility were significantly associated with asthma prevalence in India. It was found that asthma was more concentrated among individuals from higher socioeconomic status (concentration index: 0.15; p < 0.05). While exploring socio-economic inequality for asthma, richest wealth status (53.9%) was the most significant contributor in explaining the majority of the inequality followed by the urban place of residence (37.9%) and individual from age group 45–65 years (33.3%). Additionally, individual aged 65 years and above (27.9%) and household size less than four members (14.7%) contributed in explaining socio-economic inequality for asthma. Conclusion Due to the heterogeneous nature of asthma, associations between different socio-economic indicators and asthma can be complex and may point in different directions. Hence, considering the concentration of asthma prevalence in vulnerable populations and its long-term effect on general health, a comprehensive programme to tackle chronic respiratory diseases and asthma, in particular, is urgently needed.

scholarly journals Measuring Socio-Economic Inequality in Self-Reported Morbidity in India: Decomposition Analysis

2020 ◽  
Vol 25 (1) ◽  
pp. 89-111 ◽  
Author(s):  
M.D. Azharuddin Akhtar ◽  
Nadeem Ahmad ◽  
Indrani Roy Chowdhury
Keyword(s):  
Economic Inequality ◽  
Decomposition Analysis ◽  
Transportation Cost ◽  
National Sample ◽  
Sample Survey ◽  
Healthcare Sector ◽  
Health Coverage ◽  
Probit Regression ◽  
Related Inequality ◽  
The Government

This paper assesses socio-economic inequalities in self-reported morbidities (SRMs) among households in India. Particularly, we addressed two questions. Is socio-economic-related inequality in SRMs significantly pro-rich or pro-poor? What are the major socio-economic and regional determinants contributing to inequality? This study is based on National Sample Survey 71st round (2014). We calculated equity ratio and concentration index (CI) to assess socio-economic-related inequality. Further, we applied probit regression and decomposition of CI to identify the major factors contributing to inequality. The finding suggests that SRMs and hospital admission have significantly pro-rich distribution, and accessibility to healthcare is a constraint against poor households. After adjusting the inequality, the unjust inequality due to socio-economic gradient is still found to be significant. Overall, income and regional differences are observed to be inflating factors, while education and insurance are observed to be deflating factors in socio-economic inequality in SRMs. High out-of-pocket expenditure with high proportion of transportation cost indicates high burden of accessing healthcare, which acts as a deterrent for poor in seeking healthcare. The government targets of investing 2.5 per cent of the Gross Domestic Product in the healthcare sector and running an ambitious programme like Universal Health Coverage are necessary efforts in the presence of income and health inequalities.

scholarly journals National sample survey organization survey report: An estimation of prevalence of mental illness and its association with age in India

2015 ◽  
Vol 6 (01) ◽  
pp. 051-054 ◽  
Author(s):  
Ram Lakhan ◽  
Olúgbémiga T. Ekúndayò
Keyword(s):  
Mental Illness ◽  
Prevalence Rate ◽  
Large Population ◽  
National Sample ◽  
Epidemiological Studies ◽  
Sample Survey ◽  
Rural Setting ◽  
National Sample Survey ◽  
Rural And Urban ◽  
National Sample Survey Organization

ABSTRACT Background: The Indian population suffers with significant burden of mental illness. The prevalence rate and its association with age and other demographic indicators are needed for planning purpose. Objective: This study attempted to calculate age-wise prevalence of mental illness for rural and urban settings, and its association with age. Materials and Methods: Data published in National Sample Survey Organization (2002) report on disability is used for the analysis. Spearman correlation for strength of association, z-test for difference in prevalence, and regression statistics for predicting the prevalence rate of mental illness are used. Result: Overall population have 14.9/1000 prevalence of mental illness. It is higher in rural setting 17.1/1000 than urban 12.7/1000 (P < 0.001). There is a strong correlation found with age in rural (ϱ = 0.910, P = 0.001) and urban (ϱ = 0.940, P = 0.001). Conclusion: Results of this study confirm other epidemiological research in India. Large-population epidemiological studies are recommended.

Women Entrepreneurship

2019 ◽  
pp. 99-118
Author(s):  
Prachita A. Patil ◽  
Yogesh M. Deshpande
Keyword(s):  
Rural Areas ◽  
National Sample ◽  
The State ◽  
Sample Survey ◽  
Female Entrepreneurs ◽  
National Sample Survey ◽  
Leading Role ◽  
National Sample Survey Organization ◽  
State Of Mind

According to the National Sample Survey Organization (NSSO), not more than 14% of business establishments are run by female entrepreneurs in India, especially in rural areas. Entrepreneurship is not an easy step for women. It was traditionally considered as a man's bastion, but now with the due course of time, women are coming in the limelight to fulfil their aspiration as it is a fruitful opportunity where educated or illiterates can do wonders to achieve their dreams. Entrepreneurship is the state of mind which every woman has in her but has not been capitalized in India in a way it should have been. With the drastic change in modernization, people are more comfortable to accept the leading role of women in society, with some exceptions.

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