Philippe P, Mansi O
Department of Social and Preventive Medicine, Faculty of Medicine, University of Montreal, Canada.
Theor Med Bioeth. 1998 Dec;19(6):591-607. doi: 10.1023/a:1009979306346.
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.
慢性病带来的挑战向流行病学家指出了疾病因果关系的多因素复杂本质。这一概念被称为因果关系网。从理论上讲，这个网络超出了风险标志物的范畴。它包括疾病发生/未发生的决定因素。这个决定因素网络是一种复杂系统的形式。由于其复杂性，该系统内的决定因素并非仅以线性、可预测的方式相互关联。可预测性仅在短期内存在，从长远来看则会出现不可预测性。理解这样一个决定因素系统需要构建和检验复杂模型，这些模型整合了我们在生物及其他多个尺度上对多种决定因素的认识。鉴于这个网络的复杂性以及关于此类系统非线性的现有知识，提出了以下问题：如果继续强调使用旨在从线性范式看待此类系统的工具和方法，能否充分应对研究因果关系的挑战？还是说现在是时候将非线性概念及其在其他学科中正在测试的相关分析方法纳入流行病学研究议程了？此外，这里提出的问题同样适用于健康决定因素的研究。研究健康决定因素给我们的任务增添了更多复杂性。
