Why those who drink the most coffee appear to be at increased risk of disease. A modest proposal

Abstract

A sample of 2,706 adults, considered representative of the United States, was interviewed by telephone about coffee consumption and about experiences and personal characteristics that have been considered antecedents or risk factors of vascular diseases and malignancies. Consumption of more than 5.6 cups per day placed a person in the top quartile of total daily coffee. People in the top quartile of caffeine-containing coffee consumption averaged 429 mg of caffeine in coffee each day and were more likely than others to smoke cigarettes, and less likely to take vitamin supplements and to consume a "healthy" diet (i.e., containing large amounts of fiber, vitamins and cruciferous vegetables, and small amounts of fat). Thus, the heightened risk of disease sometimes associated with coffee consumption might reflect the characteristics and disease-promoting activities of some drinkers and not necessarily their consumption of caffeine and coffee. The findings of this study are consistent with the hypothesis that drinkers of relatively large amounts of coffee are less likely than others to feel the need for health-promoting behaviors.

Systematic Reviews of Observational Studies

“…19 Based on over 390 000 men and almost five million years of follow-up, a meta-analysis of these cohorts produces very precise and statistically significant estimates of the increase in suicide risk that is associated with smoking different daily amounts of cigarettes: relative rate for 1-14 cigarettes 1·43 (95% confidence interval 1·06 to 1·93), for 15-24 cigarettes 1·88 (1·53 to 2·32), 25 or more cigarettes 2·18 (1·82 to 2·61). 21 However, even if adjustments for confounding factors have been made in the analysis, residual confounding remains a potentially serious problem in observational research. It is improbable that smoking is causally related to suicide.…”

Meta-analysis Spurious precision? Meta-analysis of observational studies

“…If the factor is known and has been measured, the usual approach is to adjust for its influence in the analysis. For example, studies assessing the influence of coffee consumption on the risk of myocardial infarction should make statistical adjustments for smoking, as smoking is generally associated with drinking larger amounts of coffee, and smoking is a cause of coronary heart disease 21. However, even if adjustments for confounding factors have been made in the analysis, residual confounding remains a potentially serious problem in observational research.…”

Imaging in Paediatrics: a Casebook.

“…Because those who smoke the most cigarettes also drink the most coVee/caVeine, 4 caVeine will carry information about magnitude of cigarette smoking that was not carried by the "maternal tobacco: yes/no" variable, but should have been carried by a "parental tobacco: small, light, moderate, heavy" variable. [4][5][6][7][8][9][10] The result of having better information about caVeine than about tobacco is that adjustment for tobacco will not eliminate tobacco confounding of the association between caVeine consumption and the risk of SIDS. 4 11-13 Consider the possibility that the caVeine consumption variable tends to carry tobacco consumption information at the highest levels of caVeine consumption.…”