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Cognitive Impairment and Quality of Life among Elderly in India

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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.

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References

  • Addington, D. D., Azorin, J. M., Falloon, I. R. H., Gerlach, J., Hirsch, S. R., & Siris, S. G. (2002). Clinical issues related to depression in schizophrenia: an international survey of psychiatrists. Acta Psychiatrica Scandinavica, 105(3), 189–195.

    Article  Google Scholar 

  • Arokiasamy, P., Bloom D., Lee J., K. Feeney, and Ozolins M. (2011). Longitudinal Aging Study in India: Vision, Design, Implementation, and Some Early Results, PGDA Working Paper No. 82, pp 1–42.

  • Bekibele, C. O., & Gureje, O. (2008). Impact of self-reported visual impairment on quality of life in the Ibadan study of ageing. British Journal of Ophthalmology, 92, 612–615.

    Article  Google Scholar 

  • Boxtel, C. V., M. P., Buntinx, F., Houx, P. J., Metsemakers, J. F., Knottnerus, A., & Jolles, J. (1998). The relation between morbidity and cognitive performance in a normal aging population. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 53(2), M147–M154.

    Article  Google Scholar 

  • Boxtel, C. V., Van der Linden, J., & Kanselaar, G. (2000). Collaborative learning tasks and the elaboration of conceptual knowledge. Learning and Instruction, 10(4), 311–330.

    Article  Google Scholar 

  • Boyer, L., Simeoni, M. C., Loundou, A., D’Amato, T., Reine, G., Lancon, C., & Auquier, P. (2010). The development of the S-QoL 18: a shortened quality of life questionnaire for patients with schizophrenia. Schizophrenia Research, 121(1), 241–250.

    Article  Google Scholar 

  • Büssing, A., Fischer, J., Ostermann, T., & Matthiessen, P. F. (2009). Reliance on God’s help as a measure of intrinsic religiosity in healthy elderly and patients with chronic diseases. correlations with health- related quality of life? Applied Research in Quality of Life, 4(1), 77–90.

    Article  Google Scholar 

  • Catalano, D., Chan, F., Wilson, L., Chiu, C. Y., & Muller, V. R. (2011). The buffering effect of resilience on depression among individuals with spinal cord injury: a structural equation model. Rehabilitation Psychology, 56(3), 200.

    Article  Google Scholar 

  • Census of India (2011). Registrar General India. Provisional population totals-India data sheet. Office of the Registrar General Census Commissioner, India. Indian Census Bureau.

  • Chen, Y. C., Li, R. H., & Chen, S. H. (2013). Relationships among adolescents’ leisure motivation, leisure involvement, and leisure satisfaction: A structural equation model. Social Indicators Research, 110(3), 1187–1199.

    Article  Google Scholar 

  • Chou, C. Y., Ma, M. C., & Yang, T. T. (2014). Determinants of subjective health-related quality of life (HRQoL) for patients with schizophrenia. Schizophrenia Research, 154(1), 83–88.

    Article  Google Scholar 

  • Cong, L., Dou, P., Chen, D., & Cai, L. (2015). Depression and associated factors in the elderly cadres in Fuzhou, china: a community-based study. International Journal of Gerontology, 9(1), 29–33.

    Article  Google Scholar 

  • Das, S. K., Bose, P., Biswas, A., Dutt, A., Banerjee, T. K., Hazra, A., & Roy, T. (2007). An epidemiologic study of mild cognitive impairment in Kolkata, India. Neurology, 68(23), 2019–2026.

    Article  Google Scholar 

  • Dias, A., & Patel, V. (2009). Closing the treatment gap for dementia in India. Indian Journal of Psychiatry, 51(5), 93.

    Google Scholar 

  • Elis, O., Caponigro, J. M., & Kring, A. M. (2013). Psychosocial treatments for negative symptoms in schizophrenia: current practices and future directions. Clinical Psychology Review, 33(8), 914–928.

    Article  Google Scholar 

  • Fastame, M. C., Penna, M. P., Rossetti, E. S., & Agus, M. (2014). The effect of age and socio-cultural factors on self-rated well-being and metacognitive and mnestic efficiency among healthy elderly people. Applied Research in Quality of Life, 9(2), 325–334.

    Article  Google Scholar 

  • Felce, D., & Perry, J. (1995). Quality of life: Its definition and measurement. Research in Developmental Disabilities, 16(1), 51–74.

    Article  Google Scholar 

  • Fernández-Ballesteros, R. (2011). Quality of life in old age: problematic issues. Applied Research in Quality of Life, 6(1), 21–40.

    Article  Google Scholar 

  • Fleury, M. J., Grenier, G., Bamvita, J. M., Tremblay, J., Schmitz, N., & Caron, J. (2013). Predictors of quality of life in a longitudinal study of users with severe mental disorders. Health and Quality of Life Outcomes, 11(1), 1.

    Article  Google Scholar 

  • Gambhir, I. S., Khurana, V., Kishore, D., Sinha, A. K., & Mohapatra, S. C. (2014). A clinico- epidemiological study of cognitive function status of community-dwelling elderly. Indian Journal of Psychiatry, 56(4), 365.

    Google Scholar 

  • Graham, J. E., Rockwood, K., Beattie, B. L., Eastwood, R., Gauthier, S., Tuokko, H., & McDowell, I. (1997). Prevalence and severity of cognitive impairment with and without dementia in an elderly population. The Lancet, 349(9068), 1793–1796.

    Article  Google Scholar 

  • Greene, W. H. (2000). Econometric analysis. London: Prentice Hall.

    Google Scholar 

  • Grover, S., & Malhotra, N. (2015). Depression in elderly: a review of Indian research. Journal of Geriatric Mental Health, 2(1), 4.

    Article  Google Scholar 

  • Hair, J. F., Anderson, R. E., Tatham, R. L., & William, C. (1998). Black (1998), Multivariate data analysis.

  • Help Age India (2013). Elder Abuse & Crime in India, New Delhi.

  • Ibrahim, N., Din, N. C., Ahmad, M., Ghazali, S. E., Said, Z., Shahar, S., et al. (2013). Relationships between social support and depression, and quality of life of the elderly in a rural community in Malaysia. Asia-Pacific Psychiatry, 5(Suppl. 1), 59–66.

    Article  Google Scholar 

  • Jaccard, J., & Wan, C. K. (1996). LISREL approaches to interaction effects in multiple regression (No. 114). Sage.

  • Jitapunkul, S., Chansirikanjana, S., & Thamarpirat, J. (2009). Undiagnosed dementia and value of serial cognitive impairment screening in developing countries: a population‐based study. Geriatrics & Gerontology International, 9(1), 47–53.

    Article  Google Scholar 

  • Jolles, J. (1986). Cognitive, emotional and behavioral dysfunctions in aging and dementia. Progress in Brain Research, 70, 15–39.

    Article  Google Scholar 

  • Jung, H. Y., Hwang, S. S. H., Yi, J. S., Kim, Y., & Kim, Y. S. (2010). Clinician-rated functioning and patient-rated quality of life in schizophrenia: Implications of their correspondence for psychopathology and side effects. Progress in Neuro Psychopharmacology and Biological Psychiatry, 34(1), 225–230.

    Article  Google Scholar 

  • Karow, A., Wittmann, L., Schöttle, D., Schäfer, I., & Lambert, M. (2014). The assessment of quality of life in clinical practice in patients with schizophrenia. Dialogues in Clinical Neuroscience, 16(2), 185.

    Google Scholar 

  • Khan, H. T., & Raeside, R. (2014). Between country variations in self-rated-health and associations with the quality of life of older people: evidence from the global ageing survey. Applied Research in Quality of Life, 9(4), 923–949.

    Article  Google Scholar 

  • Laurendeau-Bendavid, M. (1977). Culture, schooling, and cognitive development: A comparative study of children in French Canada and Rwanda. Piagetian psychology: Cross-Cultural Contributions, 123–168.

  • Lezak, M. D. (2004). Neuropsychological assessment. USA: Oxford University Press.

    Google Scholar 

  • Lysaker, P. H., & Dimaggio, G. (2014). Metacognitive capacities for reflection in schizophrenia: implications for developing treatments. Schizophrenia Bulletin, 40(3), 487–491.

    Article  Google Scholar 

  • Mauriño, J., Sanjúan, J., Haro, J. M., Díez, T., & Ballesteros Rodríguez, F. J. (2011). Impact of depressive symptoms on subjective well-being: the importance of patient-reported outcomes in schizophrenia.

  • Mavrodaris, A., Powell, J., & Thorogood, M. (2013). Prevalences of dementia and cognitive impairment among older people in sub-Saharan Africa: a systematic review. Bulletin of the World Health Organization, 91(10), 773–783.

    Article  Google Scholar 

  • Moser, C., & Felton, A. (2007). The construction of an asset index measuring asset accumulation in Ecuador. Chronic Poverty Research Centre Working Paper, (87).

  • Muthen, B. (1983). Latent variable structural equation modeling with categorical data. Journal of Econometrics, 22(1), 43–65.

    Article  Google Scholar 

  • Nair, G., Van Dyk, K., Shah, U., Purohit, D. P., Pinto, C., Shah, A. B., & Sano, M. (2012). Characterizing cognitive deficits and dementia in an aging urban population in India. International Journal of Alzheimer’s Disease.

  • Renaud, J., & Be’ dard, E. (2013). Depression in the elderly with visual impairment and its association with quality of life. Clinical Interventions in Aging, 8, 931–943.

    Article  Google Scholar 

  • Rothenberg, T. J. (1971). Identification in parametric models. Econometrica: Journal of the Econometric Society, 577–591.

  • SAGE (2012). Working Paper No. 3. November 2012. Measuring cognitive status in older age in lower income countries: Results from a pilot of the Study on global AGEing and Adult Health (SAGE). Retrieved from http://www.who.int/healthinfo/sage/SAGEWorkingPaper3_Pilot_cognition_Nov12.pdf.

  • Salthouse, T. A. (1992). Influence of processing speed on adult age differences in working memory. Acta Psychologica, 79(2), 155–170.

    Article  Google Scholar 

  • Shaji, K. S., Jithu, V. P., & Jyothi, K. S. (2010). Indian research on aging and dementia. Indian Journal of Psychiatry, 52(7), 148.

    Article  Google Scholar 

  • Sibitz, I., Unger, A., Woppmann, A., Zidek, T., & Amering, M. (2011). Stigma resistance in patients with schizophrenia. Schizophrenia Bulletin, 37(2), 316–323.

    Article  Google Scholar 

  • Siris, S.G., (1995). Depression in schizophrenia. In: Irsch, S.R., Einhorder, D.W. (Eds.), Schizophrenia, pp. 128–145.

  • Sosa-Ortiz, A. L., Acosta-Castillo, I., & Prince, M. J. (2012). Epidemiology of dementias and Alzheimer’s disease. Archives of Medical Research, 43(8), 600–608.

    Article  Google Scholar 

  • Sun, W., Aodeng, S., Tanimoto, Y., Watanabe, M., Han, J., Wang, B., & Kono, K. (2015). Quality of life (QOL) of the community-dwelling elderly and associated factors: A population-based study in urban areas of China. Archives of Gerontology and Geriatrics, 60(2), 311–316.

    Article  Google Scholar 

  • Tamari, K. (2011). Self-reported home exercise and younger age predict improved health-related quality of life among community-dwelling elderly participants in a three-month group exercise class. Journal of Physiological Anthropology, 30, 77–85.

    Article  Google Scholar 

  • Theil, H. (1971). Principles of econometrics. New York: Wiley.

    Google Scholar 

  • Tripathi, R. K., & Tiwari, S. C. (2013). Cognitive functioning of community dwelling urban older adults with reference to socio-demographic variables. Indian Journal of Clinical Psychology, 40(2), 92–102.

    Google Scholar 

  • Vyas, S., & Kumaranayake, L. (2006). Constructing socio-economic status indices: how to use principal components analysis. Health Policy and Planning, 21(6), 459–468.

    Article  Google Scholar 

  • Wilson, R. S., Barnes, L. L., & Bennett, D. A. (2003). Assessment of lifetime participation in cognitively stimulating activities. Journal of Clinical and Experimental. Neuropsychology, 25(5), 634–642.

    Google Scholar 

  • Woo, E., Kim, H., & Uysal, M. (2016). A measure of quality of life in elderly tourists. Applied Research in Quality of Life, 11(1), 1–18.

    Article  Google Scholar 

  • Xiang, Y. T., Weng, Y. Z., Leung, C. M., Tang, W. K., & Ungvari, G. S. (2008). Subjective quality of life in outpatients with schizophrenia in Hong Kong and Beijing: relationship to socio-demographic and clinical factors. Quality of Life Research, 17(1), 27–36.

    Article  Google Scholar 

  • Yanos, P. T., & Moos, R. H. (2007). Determinants of functioning and well-being among individuals with schizophrenia: an integrated model. Clinical Psychology Review, 27(1), 58–77.

    Article  Google Scholar 

  • Yenilmez, M. I. (2015). Economic and social consequences of population aging the dilemmas and opportunities in the twenty-first century. Applied Research in Quality of Life, 10(4), 735–752.

    Article  Google Scholar 

  • Yoon, J., Campanelli, L., Goral, M., Marton, K., Eichorn, N., & Obler, L. K. (2015). The effect of plausibility on sentence comprehension among older adults and its relation to cognitive functions. Experimental Aging Research, 41(3), 272–302.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Humanities & Social Sciences, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India

    Pushpendra Singh & Virendra Kumar

  2. Department of Population Policy and Programmes, International Institute of Population Studies (IIPS), Deonar, Mumbai, Maharashtra, 400088, India

    Dipti Govil & Jitendra Kumar

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  1. Pushpendra Singh
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  2. Dipti Govil
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Correspondence to Virendra Kumar.

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Appendix

Appendix

Cognitive Tests Used in SAGE

QUESTION 1: VERBAL FLUENCY (MAXIMUM 70 POINTS):

Now we are going to ask you to think of animals and name as many as you can. I am going to give you one minute, and I want to see how many animals you can name.

INTERVIEWER: See Interviewers Manual instructions about what is acceptable and what is not. If respondent stops before the end of the minute, encourage them to try to name more animals. If there is a silence of about 15 s, prompt them to continue or repeat the basic instructions.

Ready? Start:

INTERVIEWER: Press START/STOP on stopwatch. Time for 1 min. Use space below to record.

INTERVIEWER: SAY “FINE” OR “GOOD” when completed the one minute.

Q2536

total score (number of animals named correctly)

Q2537

Number of errors INTERVIEWER: errors include anything that is not an animal

QUESTION 2: VERBAL RECALL (MAXIMUM 10 POINTS):

We are now going to test your memory. I know these questions may be difficult to answer, but please try to provide an answer. I am going to read you a list of words. Listen to them carefully and try to remember as many of them as you can, not necessarily in order. I will ask you to repeat them again after some time.

List of words used

Arm, Bed, Plane, Dog, Clock, Bike, Ear, Hammer, Chair, Cat

Immediate Recall Plus Learning Saturation

Number of words recalled correctly Trial 1, 2, 3

Number of words that respondent failed to recall Trial 1, 2, 3

Number of words substituted Trial 1, 2, 3

Delayed Recall

Number of words recalled correctly

Number of words that respondent failed to recall

Number of words substituted

QUESTION 3: DIGIT SPAN (maximum 9 points for forward and 8 points for backward)

DIGIT SPAN - DIGITS FORWARD

INTERVIEWER: For the following tests, digits forward and backward, say the digits at the rate of one per second, not grouped. Let the pitch of your voice drop with the last digit of each series. In any series if the subject fails Trial 1 - give Trial 2 of the same series, then proceed to the next series if the respondent responds correctly. Trial 2 is only given if Trial 1 is failed.

I am going to say some numbers to you. Listen carefully, and when I am through, say them right after me. I want you to repeat each set of numbers exactly as I say them to you. For example, if I said “1-2”, you would say…?

INTERVIEWER: Wait for correct provide the correct response and repeat after me, “5-3”. If correct, (Q2536)

Points

Sequence of numbers

3

5-8-2

4

6-4-3-9

5

4-2-7-3-1

6

6-1-9-4-7-3

7

5-9-1-7-4-2-8

8

5-8-1-9-2-6-4-7

9

2-7-5-8-6-2-5-8-4

DIGIT SPAN - DIGITS BACKWARD

Now, I am going to say more numbers, but this time when I stop, I want you to say them to me backwards. For example, if I said 1–7, what would you say?

INTERVIEWER: Wait for subject to say 7–1. If the response is correct, start with Series 2. If the respondent does not reply correctly or fails to understand, give the correct answer and another example, saying Remember, you are to say them backwards. Try this, “3-8”. If the response is correct, continue. If fails second example, mark “0” in Q2535 and skip to Verbal Fluency (Q2536).

Points

Sequence of numbers

2

2-4

3

6-2-9

4

3-2-7-9

5

1-5-2-8-6

6

5-3-9-4-1-8

7

8-1-2-9-3-6-5

8

9-4-3-7-6-2-5-8

Quality of Life:

Domains

Related questions

Physical health

(Pain + Energy + Sleep)

Psychological health

(Positive feel + Negative feel + Self-esteem)

Level of independent

(Mobility + Additional Daily life Activities + General health)

Social relation

(Personal Relation + Social Relation)

Environment

(Safe + Finance + Transport)

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Singh, P., Govil, D., Kumar, V. et al. Cognitive Impairment and Quality of Life among Elderly in India. Applied Research Quality Life 12, 963–979 (2017). https://doi.org/10.1007/s11482-016-9499-y

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