This is the most important study in many years, and we can expect the public health establishment to ignore it. They get their paychecks for blaming smoking, so they’d rather do things wrong, not right!
Assortative mixing as a source of bias in epidemiological studies of sexually transmitted infections: the case of smoking and human papillomavirus. P Lemieux-Mellouki, M Drolet, J Brisson, EL Franco, MC Boily, I Baussano, M Brisson. Epidemiol Infect 2015 Nov 20:1-10 [Epub ahead of print].
For studies examining risk factors of sexually transmitted infections (STIs), confounding can stem from characteristics of partners of study subjects, and persist after adjustment for the subjects’ individual-level characteristics. Two conditions that can result in confounding by the subjects’ partners are: (C1) partner choice is assortative by the risk factor examined and, (C2) sexual activity is associated with the risk factor. The objective of this paper is to illustrate the potential impact of the assortativity bias in studies examining STI risk factors, using smoking and human papillomavirus (HPV) as an example. We developed an HPV transmission-dynamic mathematical model in which we nested a cross-sectional study assessing the smoking-HPV association. In our base case, we assumed (1) no effect of smoking on HPV, and (2) conditions C1-C2 hold for smoking (based on empirical data). The assortativity bias caused an overestimation of the odds ratio (OR) in the simulated study after perfect adjustment for the subjects’ individual-level characteristics (adjusted OR 1·51 instead of 1·00). The bias was amplified by a lower basic reproductive number (R 0), greater mixing assortativity and stronger association of smoking with sexual activity. Adjustment for characteristics of partners is needed to mitigate assortativity bias.
[And, as explained in the Supplementary Materials]
Formula (1) can be understood by thinking of partnership formation as an individual having three different types of partner selection: each term of the sum represents a different type of partner selection and the parameters a, b, c, 1-a-b-c are the probabilities of each type of selection. The first term is the event of selecting assortatively a partner from the same smoking and sexual activity class. The second term is selecting from the same sexual activity class, but randomly as for smoking status. Thus, if the second choice is made, it is still possible to be choosing from the same sexual activity and smoking class. The third term is random selection for sexual activity, and assortatively for smoking. The last is selecting completely at random. Thus, the assortativity bias comes from the third term, where the probability of selecting a highly sexually active individual is greater for smokers.
It basically expresses common sense in fancy statistical terms – that because peoples’ partners aren’t randomized, confounding will result from group differences. For that matter, people aren’t randomly assigned to families, either, so they’re not equally likely to be exposed to infections such as EBV and CMV during childhood.