Encyclopedia of Geropsychology

Living Edition
| Editors: Nancy A. Pachana

Neuropsychological Consequences of Chronic Disease in Older Persons

  • Romola S. BucksEmail author
  • Michelle Olaithe
Living reference work entry
DOI: https://doi.org/10.1007/978-981-287-080-3_324-1


What Is Chronic Disease?

The World Health Organization defines chronic disease as noncommunicable diseases (diseases not passed from person to person) that generally progress slowly and are of long duration (WHO 2014a). They are commonly divided into four types: cardiovascular diseases (such as hypertension, heart attack, or stroke), cancers, chronic respiratory diseases (such as asthma, obstructive sleep apnea, or chronic obstructive pulmonary disease), and diabetes (see Fig. 1), all of which are more common as we age.


Chronic Disease Obstructive Sleep Apnea Executive Function White Matter Lesion Obstructive Sleep Apnoea 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.


  1. AIHW. (2015). Australian Burden of Disease Study: fatal burden of disease 2010. Australian Burden of Disease Study series no. 1. Cat. no. BOD 1. Canberra: Australian Institute of Health and Welfare.Google Scholar
  2. Bloom, D. E., Cafiero, E. T., Jané-Llopis, E., Abrahams-Gessel, S., Bloom, L. R., Fathima, S., Feigl, A. B., Gaziano, T., Mowafi, M., Pandya, A., Prettner, K., Rosenberg, L., Seligman, B., Stein, A. Z., & Weinstein, C. (2011). The global economic burden of noncommunicable diseases. Geneva: World Economic Forum.Google Scholar
  3. Brands, A. M. A., Biessels, G. J., de Haan, E. H. F., Kappelle, L. J., & Kessels, R. P. C. (2005). The effects of type 1 diabetes on cognitive performance. Diabetes Care, 28(3), 726–735.CrossRefGoogle Scholar
  4. Bucks, R. S., Olaithe, M., & Eastwood, P. (2013). Neurocognitive function in obstructive sleep apnoea: A meta-review. Respirology, 18(1), 61–70.CrossRefGoogle Scholar
  5. Debette, S., & Markus, H. S. (2010). The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: Systematic review and meta-analysis. BMJ, 341, c3666.CrossRefGoogle Scholar
  6. DeRight, J., Jorgensen, R. S., & Cabral, M. J. (2015). Composite cardiovascular risk scores and neuropsychological functioning: A meta-analytic review. Annals of Behavioral Medicine, 49, 344–357.CrossRefGoogle Scholar
  7. Gifford, K. A., Badaracco, M., Liu, D., Tripodis, Y., Gentile, A., Lu, Z., Palmisano, J., & Jefferson, A. L. (2013). Blood pressure and cognition among older adults: A meta-analysis. Archives of Clinical Neuropsychology, 28(7), 649–664.CrossRefGoogle Scholar
  8. Gobel, E. W., Parrish, T. B., & Reber, P. J. (2011). Neural correlates of skill acquisition: Decreased cortical activity during a serial interception sequence learning task. NeuroImage, 58(4), 1150–1157.CrossRefGoogle Scholar
  9. Lezak, M. D., Howieson, D. B., & Loring, D. W. (2004). Neuropsychological assessment (4th ed.). New York: Oxford University Press.Google Scholar
  10. Lim, S. S., Gaziano, T. A., Gakidou, E., Reddy, K. S., Farzadfar, F., Lozano, R., & Rodgers, A. (2007). Prevention of cardiovascular disease in high-risk individuals in low-income and middle-income countries: Health effects and costs. The Lancet, 370(9604), 2054–2062.CrossRefGoogle Scholar
  11. McCrimmon, R. J., Ryan, C. M., & Frier, B. M. (2012). Diabetes and cognitive dysfunction. Lancet, 379(9833), 2291–2299.CrossRefGoogle Scholar
  12. Olaithe, M., & Bucks, R. S. (2013). Executive dysfunction in OSA before and after treatment: A meta-analysis. Sleep, 36(9), 1297–1305.Google Scholar
  13. Palta, P., Schneider, A. L. C., Biessels, G. J., Touradji, P., & Hill-Briggs, F. (2014). Magnitude of cognitive dysfunction in adults with type 2 diabetes: A meta-analysis of six cognitive domains and the most frequently reported neuropsychological tests within domains. Journal of International Neuropsychological Society, 20(30), 278–291.CrossRefGoogle Scholar
  14. Schoenberg, M. R., & Scott, J. G. (2011). Little black book of neuropsychology: A syndrome-based approach. New York: Springer.CrossRefGoogle Scholar
  15. Starkstein, S. E., & Kremer, J. L. (2001). Cerebral aging: Neuropsychological, neuroradiological, and neurometabolic correlates. Dialogues in Clinical Neuroscience, 3(3), 217–228.Google Scholar
  16. Stern, Y. (2012). Cognitive reserve in ageing and Alzheimer’s disease. Lancet Neurology, 11(11), 1006–1012.CrossRefGoogle Scholar
  17. Strauss, E., Sherman, E. M. S., & Spreen, O. (2006). A compendium of neuropsychological tests: Administration, norms, and commentary (3rd ed.). Oxford: Oxford University Press.Google Scholar
  18. Wallace, A., & Bucks, R. S. (2013). Memory and obstructive sleep apnoea: A meta-analysis. Sleep, 36(2), 203–220.Google Scholar
  19. WHO. (1999). Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus. Geneva: World Health Organization.Google Scholar
  20. WHO. (2014a). Global status report on non-communicable diseases, 2012. Geneva: World Health Organization.Google Scholar
  21. WHO. (2014b). Global health estimates: Deaths by cause, age, sex and country, 2000–2012. Geneva: World Health Organization.Google Scholar
  22. Xie, L., Kang, H., Xu, Q., Chen, M. J., Liao, Y., Thiyagarajan, M., O’Donnell, J., Christensen, D. J., Nicholson, C., Iliff, J. J., Takano, T., Deane, R., & Nedergaard, M. (2013). Sleep drives metabolite clearance from the young adult brain. Science, 342(6156), 373–377.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  1. 1.School of PsychologyUniversity of Western AustraliaCrawleyAustralia