Title |
Smoking: additional burden on aging and death
|
---|---|
Published in |
Genes and Environment, January 2016
|
DOI | 10.1186/s41021-016-0029-9 |
Pubmed ID | |
Authors |
Masahiko Watanabe |
Abstract |
Tobacco smoking is a major cause of lung cancer. It has been suggested that there is an approximately linear dose-response relationship between the number of cigarettes smoked per day and clinical outcome such as lung cancer mortality. It has also been proposed that there is a greater increase in mortality at high doses when the dose is represented by the duration of the smoking habit rather than the number of cigarettes. The multistep carcinogenesis theory indicates that a greater increase in mortality rate at high doses is possible, as is the case between aging and cancer, even though each dose-response relationship between a carcinogenic factor and a carcinogenic step forward is linear. The high incidence of lung cancer after long-term smoking and the decreased relative risk after smoking cessation suggests a similarity between the effects of smoking and aging. Prediction of lung cancer risk in former smokers by simple integration of smoking effects with aging demonstrated a good correlation with that estimated from the relative risk of the period of smoking cessation. In contrast to the smoking period, there appears to be a linear relationship between smoking strength and cancer risk. This might arise if the dose-response relationship between smoking strength and each carcinogenic step is less than linear, or the effects become saturated with a large dose of daily smoking. Such a dose-response relationship could lead to relatively large clinical effects, such as cardiovascular mortality, by low-dose tobacco smoke exposure, e.g., second-hand smoking. Consideration of the dose-response of each effect is important to evaluate the risk arising from each carcinogenic factor. |
Twitter Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 50% |
India | 1 | 17% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 33% |
Scientists | 2 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 17% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 6% |
Unknown | 17 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Doctoral Student | 3 | 17% |
Student > Ph. D. Student | 2 | 11% |
Researcher | 2 | 11% |
Student > Postgraduate | 2 | 11% |
Student > Master | 1 | 6% |
Other | 3 | 17% |
Unknown | 5 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 5 | 28% |
Medicine and Dentistry | 3 | 17% |
Agricultural and Biological Sciences | 2 | 11% |
Psychology | 1 | 6% |
Nursing and Health Professions | 1 | 6% |
Other | 0 | 0% |
Unknown | 6 | 33% |