Abstract
The challenges posed by chronic illness have pointed out to epidemiologists the multifactorial complex nature of disease causality. This notion has been referred to as a web of causality. This web extends theoretically beyond risk markers. It includes determinants of emergence/non-emergence of disease. This web of determinants is a form of complex system. Due to its complexity, the determinants within such system are not linked to each others in a linear, predictable manner only. Predictability is possible only on a short-term basis, and unpredictability sets in over the long run. Understanding such a system of determinants calls for articulation and testing of complex models which synthesize our knowledge of multiple determinants at many scales, both biological and otherwise. Given the complexity of this web and existing knowledge about the nonlinearity of such systems, the following question is posed: Can the challenge of studying causality be adequately addressed if emphasis continues to be placed on using tools and methods that are geared towards looking at such system from a linear paradigm? Or is it time to add to the epidemiologic research agenda the notion of nonlinearity and its relevant form of analytical approaches that are being tested in other disciplines? Furthermore, the question posed here applies as well to the study of determinants of health. Addressing determinants of heath adds further complexity to our task.
Similar content being viewed by others
REFERENCES
Rothman KJ Causal Inference. Chestnut Hill, MA: Epidemiology Resources Inc., 1988.
Waldrop MM. Complexity. The Emerging Science at the Edge of Order and Chaos. New York: Simon & Schuster, 1992.
Horgan J. From complexity to perplexity. Scient Amer 1995; June: 104–109.
West JB, Deering WD. The Lure of Modern Science: Fractal Thinking. World Scientific Publishing, 1995.
Koopman JS, Longini, Jr, IM. The ecological effects of individual exposures and nonlinear disease dynamics in populations. Am J Publ Hlth 1994; 84: 836–842.
May RM. Simple mathematical models with very complicated dynamics. Nature 1976; 261: 459–467.
Halloran ME, Struchiner CJ. Study designs for dependent happenings. Epidemiology 1991; 2: 331–338.
Halloran ME, Struchiner CJ. Causal inference in infectious diseases. Epidemiology 1995; 6: 142–151.
Prigogine, I. Les Lois Du Chaos. Paris: Flammarion: Nouvelle Bibliotheque, 1994.
Nowak A, Lewenstein M. Dynamical systems: A tool for social psychology? In Vallacher RR, Nowak A, eds., Dynamical Systems in Social Psychology. New York: Academic Press; 1994; 17–53.
Sing CF, Haviland MB, Templeton AR, Zerba KE, Reilly SL. Biological complexity and strategies for finding DNA variations responsible for inter-individual variation in risk of a common chronic disease, coronary artery disease, Ann Med 1992; 24: 539–547.
Vallacher RR, Nowak A. Dynamical Systems in Social Psychology. New York: Academic Press, 1994.
Thomas R, Thieffry D, Kaufman M. Dynamical behaviour of biological regulatory networks. I. Biological role of feedback loops and practical use of the concept of the loop-characteristic state. Bull Math Biol 1995; 57: 247–276.
O'Flaherty EJ. Physiologic changes during growth and development. Environ Hlth Persp 1994; 102(Suppl 11): 103–106.
Sommerfeld HJ, Meeker AK, Posadas EM, Coffey DS. Frontiers in prostate cancer. Telomeres and chaos. Cancer 1995; 75: 2027–2035.
Murase M. Alzheimer's disease as subcellular ‘cancer’. The scale-invariance principles underlying the mechanism of aging. Prog Theoret Physics 1996; 95: 1–36.
Matthysse S, Deutsch C. Convergence and chaos in morphogenesis. Prog Clin Biol Res 1991; 393: 19–41.
Wolf U. The genetic contribution to the phenotype. Hum Genet 1995; 95: 127–148.
Sing CF, Zerba KE, Reilly SL. Traversing the biological complexity in the hierarchy between genome and CAD (coronary artery disease) endpoints in the population at large. Clin Genet 1994; 46: 6–14.
Kraus M, Wolf B. Emergence of self-organization in tumor cells: Relevance for diagnosis and therapy. Tumour Biol 1993; 14: 338–353.
Lipsitz LA, Goldberger AL. Loss of ‘Complexity’ and aging. Potential applications of fractals and chaos theory to senescence. JAMA 1992; 267: 1806–1809.
Cryer PE. Regulation of glucose metabolism in man. J Intern Med, Supplement 1991; 735: 31–39.
Philippe P. The complex dynamics of diabetes modeled as a fractal process. Submitted for publication.
Weder AB, Schork NJ. Adaptation, allometry, and hypertension. Hypertension 1994; 24: 145–156.
Velanovich V. Reductionism in biology and medicine: The implications of fractal and chaos theory. Theoret Surg 1994; 9: 104–107.
Yates FE. Order and complexity in dynamical systems. Homeodynamics as a generalized mechanics for biology. Math Comp Model 1994; 9: 49–74.
Savitz DA, In defense of black-box epidemiology. Epidemiology 1994; 5: 550–552.
Skrabanek P. The emptiness of the black box. Epidemiology 1994; 5: 553–555.
Cross SS, Cotton DWK. Chaos and antichaos in pathology. Hum Pathol 1994; 25: 630–637.
Rosser MN. Catastrophe, chaos and Alzheimer's disease. The F. E. Williams lecture. J Roy Coll Phys Lond 1995; 29: 412–418.
Philippe P. Chaos, population biology, and epidemiology. some research implications. Hum Biol 1993; 65: 525–546.
Philippe P. Sartwell's incubation period model revisited in the light of dynamic modelling. J Clin Epidemiol 1994; 47: 419–433.
Anderson RM. Populations, infectious disease and immunity: A very nonlinear world. Phil Trans Soc Lond, B 1994; 346: 457–505.
West BJ. Goldberger AL. Physiology in fractal dimensions. Am Scient 1987; 75(July–August): 354–365.
Cairns J. The cancer problem. Scient Amer 1975; 233(5): 64–72.
Hessol NA, Byers RH, Lifson AR, O'malley PM, Cannon L, BarnhArt JL, Harrison JS, Rutherford GW. Relationship between AIDS latency period and AIDS survival time in homosexual and bisexual men. J Acq Imm Def Syn 1990; 3: 1078–1085.
Burch PRJ. The Biology of Cancer: A New Approach. Baltimore: University Park Press; 1976.
Firth WJ. Chaos—Predicting the unpredictable. Br Med J 1991; 303: 1565–1568.
Garcia Rosa ML, Philippe P. Permanencia no setor de urgencia: Um fenomeno fractal (abstract). Proceedings of the III Congresso Brasileiro, Salvador, Bahia, Brasil, 1995.
Mehl LE, Manchanda S. Use of chaos theory and complex systems modeling to study alcohol effects on fetal condition. Comp Biomed Res 1993; 26: 424–448.
Baxt WG. Complexity, chaos and human physiology: The justification for non-linear neural computational analysis. Cancer Letters 1994; 77: 85–93.
Veng-Pedersen P, Modi NB. Neural networks in pharmacodynamic modeling. Is current modeling practice of complex kinetic systems at a dead end? J Pharmacokin Biopharm 1992; 20: 397–412.
Rivard GE, Infante-Rivard C, Hoyoux C. Maintenance chemotherapy for childhood acute lymphoblastic leukaemia: better in the evening. Lancet 1985; 2: 1264–1266.
Krieger N. Epidemiology and the web of causation: Has anyone seen the spider? Soc Sci Med 1995; 39: 887–903.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Philippe, P., Mansi, O. Nonlinearity in the Epidemiology of Complex Health and Disease Processes. Theor Med Bioeth 19, 591–607 (1998). https://doi.org/10.1023/A:1009979306346
Issue Date:
DOI: https://doi.org/10.1023/A:1009979306346