Causation is an essential concept in epidemiology, yet there is no single, clearly articulated definition for the discipline. From a systematic review of the literature, five categories can be delineated: production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic. Strengths and weaknesses of these categories are examined in terms of proposed characteristics of a useful scientific definition of causation: it must be specific enough to distinguish causation from mere correlation, but not so narrow as to eliminate apparent causal phenomena from consideration. Two categories—production and counterfactual—are present in any definition of causation but are not themselves sufficient as definitions. The necessary and sufficient cause definition assumes that all causes are deterministic. The sufficient-component cause definition attempts to explain probabilistic phenomena via unknown component causes. Thus, on both of these views, heavy smoking can be cited as a cause of lung cancer only when the existence of unknown deterministic variables is assumed. The probabilistic definition, however, avoids these assumptions and appears to best fit the characteristics of a useful definition of causation. It is also concluded that the probabilistic definition is consistent with scientific and public health goals of epidemiology. In debates in the literature over these goals, proponents of epidemiology as pure science tend to favour a narrower deterministic notion of causation models while proponents of epidemiology as public health tend to favour a probabilistic view. The authors argue that a single definition of causation for the discipline should be and is consistent with both of these aims. It is concluded that a counterfactually-based probabilistic definition is more amenable to the quantitative tools of epidemiology, is consistent with both deterministic and probabilistic phenomena, and serves equally well for the acquisition and the application of scientific knowledge.

China is in the midst of a lung cancer epidemic on an unprecedented scale. In 2015, there were an estimated 733,000 new lung cancer cases (17% of total cancer incidence) and 610,000 deaths (21.7% of total cancer mortality) in China. Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer mortality in China. Tobacco smoke exposure is the primary factor driving current lung cancer trends. In 2015, smoking prevalence was 27.7% (52.1% among men and 2.7% among women). China has taken substantial steps to control tobacco use in recent years, including 19 cities implementing comprehensive smoke free laws and expansion of cessation services. However, significant challenges remain in order to meet the 2030 Healthy China goal of reducing smoking prevalence to 20%. In particular, ongoing attention is needed to continuing to control secondhand smoke exposure, to further enhance smoking cessation services, and to address novel alternative nicotine delivery devices (ANDS).

Tobacco kills more than 8 million people worldwide every year. Over 80% of the world’s 1.3 billion tobacco users live in low- and middle-income countries (LMICs), where the future burden is projected to grow. At the same time, progress in tobacco control has not advanced as far as in many LMICs. In particular, the implementation of tobacco-cessation programs and interventions remains limited. The bulk of the evidence for tobacco-cessation interventions comes from high-income countries and may not reflect the context in LMICs, particularly as resources and training for tobacco cessation are limited. This paper summarizes the current evidence for tobacco-cessation interventions in LMICs and highlights some key challenges and research gaps. Overall, there is a need to build capacity for locally relevant research and implementation science to support tailored cessation interventions and strategies for LMICs.

The discipline of modern "risk factor" epidemiology was in its formative stages in the early 1950s, when epidemiologic studies revealed a strong association between cigarette smoking and lung cancer mortality. Many medical scientists and physicians were reluctant to accept these studies as a demonstration of causation because the methods were "statistical" and involved data collected in uncontrolled conditions outside the laboratory. But a substantial number of senior biostatisticians and epidemiologists also voiced concerns, albeit more methodologically sophisticated, about the quality of the evidence at the time. Statistical methods were just beginning to work their way into medicine and public health, and many epidemiologists and statisticians were concerned about the potential misuse of these methods by untrained investigators. When studies of smoking and lung cancer gained increasing publicity and were being used to recommend public health policies, some prominent epidemiologists and statisticians highlighted this debate in their efforts to pursue methodological reform. Participants in the debate over smoking and lung cancer saw the need for explicit and rigorous standards for evaluating etiologic hypotheses, but they held conflicting views about what those standards should be. These diverging views reflect an underlying tension within the discipline of epidemiology between the search for "objective" methods of scientific inference and the practical needs of public health research that persists today.

Background: The epidemiologic literature is replete with conceptual discussions about causal inference, but little is known about how the causal criteria are applied in public health practice. The criteria for causal inference in use today by epidemiologists have been shaped substantially by their use over time in reports of the U.S. Surgeon General on Smoking and Health. Methods: We reviewed two classic reports on smoking and health from expert committees convened by the US Surgeon General, in 1964 and 1982, in order to evaluate and contrast how the committees applied causal criteria to the available evidence for the different cancer sites at different time periods. We focus on the evidence for four cancer sites in particular that received detailed reviews in the reports: lung, larynx, esophagus and bladder. Results: We found that strength of association and coherence (especially dose-response, biological plausibility and epidemiologic sense) appeared to carry the most weight; consistency carried less weight, and temporality and specificity were apparently not applied at all in some cases. No causal claim was made for associations with a summary odds ratio of less than 3.0. Conclusion: Our findings suggest that the causal criteria as described in textbooks and the Surgeon General reports can have variable interpretations and applications in practice. While the authors of these reports may have considered evidential factors that they did not explicitly cite, such lack of transparency of methods undermines the purpose of the causal criteria to promote objective, evidence-based decision making. Further empirical study and critical examination of the process by which causal conclusions are reached can play an important role in advancing the practice of epidemiology by helping public health scientists to better understand the practice of causal inference.