Encyclopedia of Behavioral Medicine

Living Edition
| Editors: Marc Gellman

Multiple Risk Factors

  • Yori GidronEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6439-6_1441-2

Keywords

Physical Activity Coronary Heart Disease Physical Inactivity Coronary Heart Disease Risk Multiple Risk Factor 
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.

Synonyms

Definition

The etiology and prognosis of many diseases are complex, and assuming single causal agents alone could result in scientific and clinical “ignorance.” Most major causes of morbidity and mortality, such as cancer, coronary heart disease (CHD), dementia, or traffic accidents (TA), are caused by and are predicted by multiple risk factors. In the case of CHD, for example, researchers often distinguish in behavioral medicine between background demographic risk factors such as age, gender, and education level; known biomedical risk factors such as family history of CHD, smoking, hypertension, physical inactivity, cholesterol level, and inflammatory markers; and behavioral risk factors such as hostility, effort-reward imbalance at work, and little social support. Some of the biomedical risk factors can indeed also be conceptualized as behavioral such as physical inactivity or smoking. Simultaneously testing multiple risk factors is then statistically done by multivariate analyses, where statistically significant risk factors from univariate tests are then simultaneously considered, to identify the unique risk factors of a disease, independent of other ones considered. This then helps to create a parsimonious model, which only considers the independent predictors, of use in clinical prognostication.

For example, after finding that hostility is the main “toxic” element from the type A behavior pattern, studies examined extensively the etiological and prognostic role of hostility in CHD, in multivariate analyses, where multiple risk factors named above were considered. Many studies supported the etiological independent role of hostility in CHD in multivariate analyses (e.g., Dembroski et al. 1989). However, some studies did find that certain “known” CHD risk factors, such as physical activity, smoking, and alcohol consumption, accounted for the hostility-CHD relationship, since after statistically controlling for their effects, hostility no longer predicted CHD (Everson et al. 1997). Yet, in a recent meta-analysis of all studies on anger, hostility, and CHD, Chida and Steptoe (2009) concluded that anger and hostility have an independent role in the risk of CHD and in its prognosis. The multivariate analysis serves to examine whether a factor has an etiological or prognostic role, independent of established risk factors, and if not, then to identify which factor mediates (“explains”) its role in the disease. Another recent and unique example of testing effects of multiple risk factors comes from a prospective study which examined the ability of physical activity and self-efficacy to perform physical activity, to predict cardiovascular events in middle-aged men. In a multivariate analysis which controlled for multiple confounders including triglycerides, blood pressure, and actual reported physical activity, self-efficacy to perform physical activity still significantly predicted cardiovascular events (Bergström et al. 2015).

At times, consideration of multiple risk factors also enables to identify interactive effects, which can help to point at a particularly high-risk group, who can benefit from scarce intervention efforts. For example, Gidron et al. (2002) found that hostility synergistically interacted with CHD family history in relation to severity of coronary artery disease. Thus, for prevention at the population level, it may be better to focus on high-hostile people who have a first-degree relative with CHD. Thus, the identification of multiple risk factors and their statistical interactions enables to better estimate one’s risk of a disease and to treat people by targeting all significant independent risk factors (e.g., diet, physical activity, hostility reduction). By identifying and modifying multiple risk factors, we can aim to prevent or treat illnesses more effectively, as was done in the lifestyle modification intervention trial (Ornish et al. 1990).

Cross-References

References and Further Readings

  1. Bergström, G., Börjesson, M., & Schmidt, C. (2015). Self-efficacy regarding physical activity is superior to self-assessed activity level, in long-term prediction of cardiovascular events in middle-aged men. BMC Public Health, 15, 820.CrossRefPubMedPubMedCentralGoogle Scholar
  2. Chida, Y., & Steptoe, A. (2009). The association of anger and hostility with future coronary heart disease: A meta-analytic review of prospective evidence. Journal of the American College of Cardiology, 53, 936–946.CrossRefPubMedGoogle Scholar
  3. Dembroski, T. M., MacDougall, J. M., Costa, P. T., Jr., & Grandits, G. A. (1989). Components of hostility as predictors of sudden death and myocardial infarction in the multiple risk factor intervention trial. Psychosomatic Medicine, 51, 514–522.CrossRefPubMedGoogle Scholar
  4. Everson, S. A., Kauhanen, J., Kaplan, G. A., Goldberg, D. E., Julkunen, J., Tuomilehto, J., et al. (1997). Hostility and increased risk of mortality and acute myocardial infarction: The mediating role of behavioral risk factors. American Journal of Epidemiology, 146, 142–152.CrossRefPubMedGoogle Scholar
  5. Gidron, Y., Berger, R., Lugasi, B., & Ilia, R. (2002). Interactions of psychological factors and family history in relation to coronary artery disease. Coronary Artery Disease, 13, 205–208.CrossRefPubMedGoogle Scholar
  6. Ornish, D., Brown, S. E., Scherwitz, L. W., Billings, J. H., Armstrong, W. T., Ports, T. A., et al. (1990). Can lifestyle changes reverse coronary heart disease? The lifestyle heart trial. Lancet, 336, 129–133.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Faculty of Medicine and PharmacyFree University of Brussels (VUB)JetteBelgium