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Cognitive Impairment and Quality of Life among Elderly in India

Author

Listed:
  • Pushpendra Singh

    (Indian Institute of Technology Roorkee, Roorkee)

  • Dipti Govil

    (International Institute of Population Studies (IIPS))

  • Virendra Kumar

    (Indian Institute of Technology Roorkee, Roorkee)

  • Jitendra Kumar

    (International Institute of Population Studies (IIPS))

Abstract

Introduction As per the census of India, the Indian population has nearly tripled in last 50 years and the number of older persons has increased more than fourfold. A significant population of the older persons is experiencing cognitive changes which lead to several cognitive health issues and affect their quality of life. Thus, the elderly population in India creates a holistic research base by looking at the dynamics of cognitive impairment and quality of life. This paper aims to examine level of cognitive impairment among the elderly in India and its effect on quality of life. Data and Methods The present paper examines change in the cognitive functioning of the elderly on the basis of score obtained for four cognitive variables (verbal fluency, verbal recall, and digit span (backward & forward). Better score signifies better cognitive health. Data from Study of Global Aging and Adult Health (SAGE) WAVE-I, 2007–10 has been utilised in this study. A sample of 7150 aged 50 and above has been analysed by using principal component analysis (PCA) and structural equation modeling (SEM). Results The result reveals that cognitive scores for all four variables are very low. Hence with presences of low cognitive scores, the quality of life will reduce by 7% among elderly. Conclusion Cognitive impairment significantly and directly affected the quality of life of Indian elderly.

Suggested Citation

  • Pushpendra Singh & Dipti Govil & Virendra Kumar & Jitendra Kumar, 2017. "Cognitive Impairment and Quality of Life among Elderly in India," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 12(4), pages 963-979, December.
    • Handle: RePEc:spr:ariqol:v:12:y:2017:i:4:d:10.1007_s11482-016-9499-y
    DOI: 10.1007/s11482-016-9499-y
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    1. Ying-Chieh Chen & Ren-Hau Li & Sheng-Hwang Chen, 2013. "Relationships Among Adolescents’ Leisure Motivation, Leisure Involvement, and Leisure Satisfaction: A Structural Equation Model," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(3), pages 1187-1199, February.
    2. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    3. Muthen, Bengt, 1983. "Latent variable structural equation modeling with categorical data," Journal of Econometrics, Elsevier, vol. 22(1-2), pages 43-65.
    4. P. Arokiasamy & David E. Bloom & Jinkook Lee & Kevin Feeney & Marija Ozolins, 2011. "Longitudinal Aging Study in India: Vision, Design, Implementation, and Some Early Results," PGDA Working Papers 8211, Program on the Global Demography of Aging.
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    1. David Cantarero-Prieto & Marta Pascual-Sáez & Carla Blázquez-Fernández, 2018. "What is Happening with Quality of Life Among the Oldest People in Southern European Countries? An Empirical Approach Based on the SHARE Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(3), pages 1195-1209, December.
    2. Richa Nigam & Bhoomika R. Kar, 2020. "Cognitive Ageing in Developing Societies: An Overview and a Cross-sectional Study on Young, Middle-aged and Older Adults in the Indian Context," Psychology and Developing Societies, , vol. 32(2), pages 278-307, September.
    3. Adrián Segura-Camacho & Juan-José García-Orozco & Gabriela Topa, 2018. "Sustainable and Healthy Organizations Promote Employee Well-Being: The Moderating Role of Selection, Optimization, and Compensation Strategies," Sustainability, MDPI, vol. 10(10), pages 1-18, September.

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