Evidence map›Paper›PMID 34016039›Full record

ArticleBMC geriatrics2021

Socio-economic inequality in the prevalence of violence against older adults - findings from India.

Debashree Sinha, Prem Shankar Mishra, Shobhit Srivastava, Pradeep Kumar

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Article in BMC geriatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
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5citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Debashree SinhaDepartment of Development Studies, International Institute for Population Sciences, Mumbai, Maharashtra, 400088, India.
Prem Shankar MishraPopulation Research Centre, Institute for Social and Economic Change, Bengaluru, Karnataka, 560072, India.ORCID 0000-0003-0601-7025
Shobhit SrivastavaDepartment of Mathematical Demography & Statistics, International Institute for Population Sciences, Mumbai, Maharashtra, 400088, India.ORCID 0000-0002-7138-4916
Pradeep KumarDepartment of Mathematical Demography & Statistics, International Institute for Population Sciences, Mumbai, Maharashtra, 400088, India. pradeepiips@yahoo.com.ORCID 0000-0003-4259-820X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundViolence against older adults is a well-recognised socio-psychological and public health problem. It is uncared-for, undiagnosed, and an untreated problem that is widespread across both developed and developing countries. The present paper aims to understand the extent of the socio-economic status related inequality in violence against older adults in India.

methodsThe study uses data from Building a Knowledge Base on Population Aging in India (BKPAI). Violence against older adults is the outcome variable for the study and is defined as older adults who faced any abuse or violence or neglect or disrespect by any person. Bivariate analysis and regression-based decomposition technique is used to understand the relative contribution of various socio-economic factors to violence against older adults (N = 9541).

resultsThe prevalence of violence faced by older adults was 11.2%. Older adults aged 80+ years [OR: 1.49; CI: 1.14-1.93] and working [OR: 1.26; CI: 1.02-1.56] had higher likelihood to face violence than their counterparts. On the other hand, older adults who were currently in union [OR: 0.79; CI: 0.65-0.95], lived with children [OR: 0.53; CI: 0.40-0.72] and who belonged to richer wealth quintile [OR: 0.35; CI:0.24-0.51] had lower likelihood to suffer from violence than their counterparts. The decomposition results revealed that poor older adults were more prone to violence (Concentration index: - 0.20). Household's wealth status was responsible for explaining 93.7% of the socio-economic status related inequality whereas living arrangement of older adults explained 13.7% of the socio-economic related inequality. Education and working status of older adults made a substantial contribution to the inequalities in reported violence, explaining 3.7% and 3.3% of the total inequality, respectively.

conclusionThough interpretation of the results requires a cautious understanding of the data used, the present study highlights some of the relevant issues faced by the country's older adults. With no or meagre income of their own, older adults belonging to the poorest wealth quintile have little or no bargaining power to secure a violent free environment for themselves. Therefore, special attention in terms of social and economic support should be given to the economically vulnerable older population.

Indexed as

Social ClassViolenceAgedHumansIndiaPrevalenceSocioeconomic FactorsIndiaOlder adultsSocio-economic inequalityViolence

Identifiers

PMID34016039
PMCPMC8135164

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.