Survival Analysis in Social Neuroscience and Public Health: A Research Exemplar from the Field of Cognitive Epidemiology

Chapter

Abstract

Survival analysis is a group of methods designed to track the association between an exposure variable and the probability of some discrete outcome over time. Some examples of applications of survival analysis include the time to relapse among current smokers who are abstaining, tracking medication nonadherence over time among those living with diabetes, and the prediction of mortality as a function of cognitive ability. We use this latter example to illustrate one approach to survival analysis from the field of cognitive epidemiology. In this chapter we seek to answer the question: is some aspect of executive functioning associated with time until mortality? To achieve this goal, we utilize one of the most important models in biostatistics and public health, the so-called Cox proportional hazards model (Cox 1972). This model will allow us to investigate the survival association of interest while adjusting for important confounding variables. Through this example, we hope that readers will be convinced of the importance of considering the time until an event occurs, as opposed to a binary version of the event, due to the gain in information that the former approach provides.

References

  1. Batty, G. D., Mortensen, E. L., Nybo Andersen, A. M., & Osler, M. (2005). Childhood intelligence in relation to adult coronary heart disease and stroke risk: Evidence from a Danish birth cohort study. Paediatrics & Perinatal Epidemiology, 19, 452–459.CrossRefGoogle Scholar
  2. Batty, G. D., Deary, I. J., & Macintyre, S. (2007a). Childhood IQ in relation to risk factors for premature mortality in middle-aged persons: The Aberdeen children of the 1950s study. Journal of Epidemiology and Community Health, 61, 241–247.PubMedCrossRefGoogle Scholar
  3. Batty, G. D., Deary, I. J., Schoon, I., & Gale, C. R. (2007b). Mental ability across childhood in relation to risk factors for premature mortality in adult life: The 1970 British cohort study. Journal of Epidemiology and Community Health, 61, 997–1003.PubMedCrossRefGoogle Scholar
  4. Batty, G. D., Deary, I. J., Schoon, I., Emslie, C., Hunt, K., & Gale, C. R. (2008). Childhood mental ability and adult alcohol intake and alcohol problems: The 1970 British cohort study. American Journal of Public Health, 12, 2237–2243.CrossRefGoogle Scholar
  5. Chandola, T., Deary, I. J., Blane, D., & Batty, G. D. (2006). Childhood IQ in relation to obesity and weight gain in adult life: The national child development (1958) study. International Journal of Obesity, 30, 1422–1432.PubMedCrossRefGoogle Scholar
  6. Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B, 34, 187–220.Google Scholar
  7. Deary, I. J. (2010). Cognitive epidemiology: Its rise, its current issues, and its challenges. Personality and Individual Differences, 49, 337–343.CrossRefGoogle Scholar
  8. Gale, C. R., Deary, I. J., Schoon, I., & Batty, G. D. (2007). IQ in childhood and vegetarianism in adulthood: 1970 British cohort study. British Medical Journal, 334, 245.PubMedCrossRefGoogle Scholar
  9. Hall, P. A. (2012). Executive control resources and frequency of fatty food consumption: Findings from an age-stratified community sample. Health Psychology, 31, 235–241.PubMedCrossRefGoogle Scholar
  10. Hall, P. A., Elias, L. J., & Crossley, M. (2006). Neurocognitive influences on health behaviour in a community sample. Health Psychology, 25, 778–782.PubMedCrossRefGoogle Scholar
  11. Hall, P. A., Dubin, J., Crossley, M., Holmqvist, M., & D’Arcy, C. (2009). Does executive function explain the IQ-mortality association? Evidence from the Canadian study on health and aging. Psychosomatic Medicine, 71, 196–204.PubMedCrossRefGoogle Scholar
  12. Hart, C. L., Taylor, M. D., Davey-Smith, G., Whalley, L. J., Starr, J. M., Hole, D. J., et al. (2004). Childhood IQ and cardiovascular disease in adulthood: Prospective observational study linking the Scottish mental survey 1932 and the Midspan studies. Social Science and Medicine, 59, 2131–2138.PubMedCrossRefGoogle Scholar
  13. Hemmingsson, T., Melin, B., Allebeck, P., & Lundberg, I. (2006). The association between cognitive ability measured at ages 18–20 and mortality during 30 years of follow-up—a prospective observational study among Swedish males born 1949–51. International Journal of Epidemiology, 35, 665–670.PubMedCrossRefGoogle Scholar
  14. Hinkin, C. H., Castellon, S. A., Durvasula, R. S., Hardy, D. J., Lam, M. N., Mason, K. I., et al. (2002). Medication adherence among HIV adults: Effects of cognitive dysfunction and regimen complexity. Neurology, 59, 1944–1950.PubMedCrossRefGoogle Scholar
  15. Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). New York: Springer.CrossRefGoogle Scholar
  16. Insel, K., Morrow, D., Brewer, B., & Figueiredo, A. (2006). Executive function, working memory, and medication adherence among older adults. Journal of Gerontology, 61B, P102–P107.Google Scholar
  17. Lindgarde, F., Furu, M., & Ljung, B. O. (1987). A longitudinal study on the significance of environmental and individual factors associated with the development of essential hypertension. Journal of Epidemiology and Community Health, 1987(41), 220–226.CrossRefGoogle Scholar
  18. McAuley, E.,Mullen, S. P., Szabo, A. N., White, S. M., Wójcicki, T. R.,Mailey, E. L., Gothe, N., Olson, E. A., Voss, M., Erickson, K., Prakash, R., & Kramer, A. F. (2011). Self-regulatory processes and exercise adherence in older adults: Executive function and self-efficacy effects. American Journal of Preventive Medicine, 41, 284–290.PubMedCrossRefGoogle Scholar
  19. Robins, J. M., & Finkelstein, D. M. (2000). Correcting for noncompliance and dependent censoring in an AIDS clinical trial with inverse probability of censoring weighted (IPCW) log-rank tests. Biometrics, 56, 779–788.PubMedCrossRefGoogle Scholar
  20. Shipley, B. A., Der, G., Taylor, M. D., & Deary, I. J. (2006). Cognition and all-cause mortality across the entire adult age range: Health and lifestyle survey. Psychosomatic Medicine, 68, 17–24.PubMedCrossRefGoogle Scholar
  21. Sorensen, T. I., Sonne-Holm, S., & Christensen, U. (1983). Cognitive deficiency in obesity independent of social origin. Lancet, 1, 1105–1106.PubMedCrossRefGoogle Scholar
  22. Starr, J. M., Taylor, M. D., Hart, C. L., Davey-Smith, G., Whalley, L. J., Hole, D. J., et al. (2004). Childhood mental ability and blood pressure at midlife: Linking the Scottish mental survey 1932 and the Midspan studies. Journal of Hypertension, 22, 893–897.PubMedCrossRefGoogle Scholar
  23. Taylor, M. D., Hart, C. L., Davey-Smith, G., Starr, J. M., Hole, D. J., Whalley, L. J., et al. (2003). Childhood mental ability and smoking cessation in adulthood: Prospective observational study linking the Scottish mental survey 1932 and the Midspan studies. Journal of Epidemiology and Community Health, 57, 464–465.PubMedCrossRefGoogle Scholar
  24. Therneau, T. M., & Grambsch, P. M. (2000). Modeling survival data: Extending the Cox model. New York: Wiley.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.University of WaterlooWaterlooCanada

Personalised recommendations