Determinants of Health among Senior Citizens

Tyagi, Renu; Paltasingh, Tattwamasi

doi:10.1177/0972063416682613

Cited by 9 publications

(8 citation statements)

References 16 publications

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“…Sociodemographic health inequities have been well documented among elderly individuals in India in various studies. [4567] But, sociodemographic health inequalities have been highlighted in most of these studies among elderly in terms of inequalities in diseases,[4567] whereas there is paucity of research on inequalities with respect to HRQOL across various sociodemographic groups. Existence of such differences in HRQOL between different subpopulations have been documented in other countries, pointing out the need for a differential public health approach for improving equity in HRQOL.…”

Section: Introductionmentioning

confidence: 99%

Sociodemographic variations in health-related quality of life (HRQOL) among elderly individuals in an urban locality in India

Medhi

Sarma

Bhattacharyya

et al. 2019

J Family Med Prim Care

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Background: Elderly population is growing rapidly in India. To direct public health actions to improve quality of life among elderly, it is important to understand the sociodemographic factors associated with quality of life. The aim of study was to assess health-related quality of life (HRQOL) among urban elderly in a setting of Assam, India, and to examine how HRQOL varied across different sociodemographic groups among the elderly populations. Materials and Methods: A cross-sectional study was carried among elderly aged ≥60 involving 300 participants. Eight domains of HRQOL of participants were measured using RAND SF-36. Analysis of variance test was used to examine sociodemographic differences in HRQOL. Results: The BP domain had highest (71.78 ± 22.25) and GH had lowest mean HRQOL score (48 ± 16.93). Males had significantly higher HRQOL score than females only in BP domain. Age gradients were observed with respect to HRQOl scores in five domains, with youngest age group having the best and oldest age group having the poorest HRQOL. Financially dependent subjects had lower HRQOL in five domains than those who were financially independent. Significant associations between education and HRQOL were found only in physical components of HRQOL, with lowest educated group being the most disadvantaged in terms of HRQOL. Marital status was found to be significantly associated with lower HRQOL scores. Conclusion: The study highlights sociodemographic inequalities in HRQOL among urban elderly in an Indian setting. The results may help reducing sociodemographic health inequalities among elderly in this region initiating public health actions paying more attention toward more vulnerable sections of populations.

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Section: Introductionmentioning

confidence: 99%

Sociodemographic variations in health-related quality of life (HRQOL) among elderly individuals in an urban locality in India

Medhi

Sarma

Bhattacharyya

et al. 2019

J Family Med Prim Care

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“…Tsimbos (2010) found a similar result that disparity in education dominates the income and wealth in contributing to inequality in health status among the elderly. Indian elderly who are illiterate are more likely to have multiple health issues (Tyagi & Paltasingh, 2017). Regarding educational inequality in healthy ageing in India, it is highest in BIMARU (0.0477) and least in South India (0.0353).…”

Section: Resultsmentioning

confidence: 99%

“…Years of schooling and the HAS show a significantly progressive trend from those without formal education to more than 12 years of schooling. Tyagi and Paltasingh (2017) observed that a lack of health awareness results in low healthcare utilisation and health status among senior citizens in India. The education level is inversely related to the reduction in cognitive function in older age (Cabello et al, 2014), which might contribute to the low HAS.…”

Section: Determinants Of Healthy Ageing In Different Regions Of Indiamentioning

confidence: 99%

Socioeconomic Inequalities in Healthy Ageing in Different Regions of India: Evidence from the Longitudinal Ageing Study in India, Wave 1

Rahman

Chittedi

2022

Review of Development and Change

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The present study investigates the socioeconomic inequality and determinants of healthy ageing in different regions of India using the Longitudinal Ageing Study in India (LASI), Wave 1 (2017–2018). This study developed an individual-level healthy ageing score (HAS) by incorporating 53 variables suggested by the expert committee of the WHO on healthy ageing. Income, wealth and education inequality are measured using the indirectly adjusted concentration index (CI). The multiple linear regression estimates the socioeconomic, demographic and behavioural determinants. It has been found that the mean HAS in India is 72.57; it is highest in the North-east and lowest in South India. The CI indicated socioeconomic inequality in healthy ageing in India, favouring high-income, wealthy and educated elders across the region. The regression shows that older adults who are relatively young, male, rich and living in urban areas are more likely to be healthy than their counterparts. It is also found that the habit of smoking, physical inactivity and prevalence of chronic diseases are significantly associated with a low HAS in India.

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“…Earlier research also exhibited such phenomenon as almost universal. [ 3 4 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 ]…”

Section: Discussionmentioning

confidence: 99%

Self reported health status and its determinants among elderly widows in Puducherry, India

Narayanasamy

Das

Narayanasamy

et al. 2021

Indian J Community Med

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Background: Aging of population is a worldwide phenomenon of the 21 st century, which leads to many socioeconomic consequences including their health status. Hence, this study tries to assess the self-reported health status (SRHS) of elderly widows (60+ years) and its principal determinants. Materials and Methods: A cross-sectional study was conducted among 360 elderly widows from Puducherry district, 260 urban and 130 from rural areas. The sociodemographic information and the self-rated health status of elderly widows were collected with semi-structured interview schedule. Data were analyzed adopting descriptive statistics and multivariate analysis making use IBM-SPSS software 22 version. Results: Thirty-seven percent each of the elderly widows felt to be in “fair” and “good” health status, respectively, whereas 26% of them stated to be living with “poor” health status. Results of multinomial regression analysis showed that multinomial regression analysis showed that the odds of “poor” and “fair” SRHS (as against “good” SRHS) of elderly widows are conspicuously higher among those who are suffering from 2 or more chronic morbidities, whereas such odds are significantly lower among those who have 2 or more sons, educated up to middle school level and above, and who have higher functional ability. Urban residence, middle-old ages (66–76), and moderate monthly family income (Rs. 3001–9000) have also exhibited some net effects on the “poor” and/or “fair” SRHS of elderly widows. Conclusion: Chronic morbidity, having son(s), education, economic status, functional ability, and urban residence are found to be the major determinants of the SRHS among elderly widows.

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Determinants of Health among Senior Citizens

Cited by 9 publications

References 16 publications

Sociodemographic variations in health-related quality of life (HRQOL) among elderly individuals in an urban locality in India

Sociodemographic variations in health-related quality of life (HRQOL) among elderly individuals in an urban locality in India

Socioeconomic Inequalities in Healthy Ageing in Different Regions of India: Evidence from the Longitudinal Ageing Study in India, Wave 1

Self reported health status and its determinants among elderly widows in Puducherry, India

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