Smokers Lose an Average of 10 Years of Life Compared to Non-Smokers - Essay Example

Smokers lose an average of 10 years of life compared to non-smokers Grade (April 28th, Smokers lose anaverage of 10 years of life compared to non-smokers According to an article in The Guardian Newspaper, titled Smoking increases risk of breast cancer in older women by almost a fifth, the authors have established a very interesting relationship between lifespan and smoking. According to this article, “smokers lose an average of 10 years of life compared to non-smokers” (Press Association, 2014). This statement, which is the concluding statement of the article, has clearly established a direct relationship between smoking and the reduction of the smoker’s lifespan. Therefore, simply put, the article has established a causal relationship between smoking and the life span of the smoker, as opposed to establishing a correlation relationship between the two. The causal relationship requires that one variable leads to the other. In this case, the authors of the article have suggested that smoking leads to a reduction of a smoker’s life span by 10 years. This is a practical example of the authors incorrectly inferring causation from correlation, because the author ought to have stated that smoking may be related to a reduction in the lifespan of the smokers, as opposed to stating conclusively that in fact smoking causes the reduction of the lifespan of the smoker. The effect of this causal relationship established by the author is that; those people who do not smoke are guaranteed to live 10 more years, compared to the individuals who are involved in smoking. However, this assertion might not be true, because there are many smokers who live for many years compared to non-smokers based on different life factors. Therefore, this assertion cannot explain this practical variation between the assertion and the reality in life. The assertion above by the authors has come about as a result of a study that has suggested that smoking causes breast cancer. This is a case of the authors incorrectly inferring causation from correlation, because the right reporting ought to have been that there is a relationship between smoking and reduced lifespan. The authors arrived at the conclusion after the consideration of a study undertaken by researchers from the American Cancer Society, which produced findings “showing a 24% higher rate of breast cancer among women who smoked” (Press Association, 2014). This study served to add to the already existing evidence pointing to the existence of a link between the exposure to tobacco smoke and the breast cancer. This now marks the turning point of this study, from presenting a correlation relationship between breast cancer and tobacco smoke, to inferring a causal relationship between smoking and reduced lifespan. This is because, according to the heading of the Newspaper article, which states Smoking increases risk of breast cancer in older women by almost a fifth, the authors have concluded that it is smoking, rather than exposure to tobacco smoke that is related to breast cancer (Press Association, 2014). However, the authors have not established the secondary relationship between the primary relationship of smoking and breast cancer, and the one of smoking and reduced lifespan. The reality is that it is the exposure to the tobacco smoke, regardless of whether the exposure is through smoking or if it is through inhaling the tobacco smoke through alternative ways that may be related to breast cancer. Therefore, through using such a heading as the title for the article, the authors of the article have already given the wrong conclusion, since existence of a correlation relationship between smoking and breast cancer does not in any way lead to the causal relationship that the authors have established between smoking and reduced lifespan as the conclusion of the article. The major difference between a correlation relationship and a causal relationship is that; while the correlation relationship establishes a linkage or association between two variables, the causal relationship establishes a ‘cause-effect’ relationship. Therefore, in correlation relationship, there is no adducing what causes the effect that is felt, but only stating that two variables are associated in a certain way. However, a causal relationship establishes the relationship such that; it sets one variable as the being caused by the other. In this case, the study used 186,000 women aged 50 to 71 to study how smoking was related to breast cancer, and the findings were that the women who smoked were 19% more likely to develop breast cancer, than those women who did not (Press Association, 2014). With this finding, then the question that arises becomes; if smoking is the factor that is contributing to reduced lifespan, why then is it that the study did not seek to establish how smoking is related to the smoker’s lifespan? The finding of the study in relations to the previous smokers who already quit suggests that such women are still at risk of getting breast cancer. This is because, the findings of the study that is relied by this article concluded that “Women who once smoked but then kicked the habit were still 7% more at risk” (Press Association, 2014). This serves to show that there is a need to assess how the lifespan of those who smoked and stopped at some point is affected. By how many years is it reduced, based on the duration that the individual smoked? If it is smoking that causes reduced lifespan, then those who have quit smoking should already have a reduced lifespan by a certain number of years, based on the duration that they smoked. The results of the study relied by this article has also concluded that women who started smoking while still young, such as before menstruating or before getting their first child, were at a higher risk of getting breast cancer (Press Association, 2014). At this point, the study has then introduced another variable that did not exist before, that of age. The major variables of the study are the breast cancer (dependent variable) and smoking (independent variable). Thus, the addition of age as a factor related to breast cancer does not serve to develop or even reinforce the relationship already established by the study, but to add more complexity. This is because, the addition of age as a variable leads to the question; does the age at which an individual start smoking define the rate at which the individual’s lifespan will be reduced? Thus to answer all these questions, a quasi-experimental study is necessary. The quasi-experiment that requires establishing the causal relationship in this case, is undertaking an experiment that isolates smokers from the non-smokers within a given population, and then assessing the lifespan of the two groups. The experiment must entail a complete isolation, such that the non-smokers will at no one time be affected by the smoke, even when they are not smoking since this may interfere with the results of the quasi-experiment study. Further, the quasi-experiment study must be undertaken to people who are of the same age, meaning that such two groups of persons should be isolated as study groups from the day they are born until their death, so that they may not have been exposed to smoking at any point of their lives, until the smoking group starts, while the non-smoking group is completely shielded from any access to smoke. In addition, the two set of participants in the quasi-experiment study must be exposed to the same conditions of life throughout their life time, to ensure that results of the study are not interfered by other differing factors. The effect of such a study is that it will give very accurate results, which will determine whether smoking causes a reduction of the smokers’ lifespan by 10 years. Reference Press Association. (March 19, 2014). Smoking increases risk of breast cancer in older women by almost a fifth. The Guardian. Accessed Read More