Numerous attempts have been made to explain the time-trend patterns in coronary heart disease (CHD) mortality in America and Europe over the last century. The question as to why CHD mortality rose steadily until approximately mid-century and then began to decline has been intriguing investigators for a long time, and a series of possible explanations for such a pattern have been described. In their article, Azambuja & Duncan introduce another interesting hypothesis seeking to explain the rise and fall in CHD.

Focusing on events in the United States, the authors argue that the time-trend pattern in CHD mortality can be explained by the influenza epidemic striking that country during the first half of the 20th century. The infection, they explain, could have changed individual susceptibility to other known risk factors for CHD, leading to increased mortality among the exposed. Since the flu epidemic was restricted to certain time periods, new generations of unexposed individuals were then responsible for the later decline in CHD mortality.

It is interesting to note the growing interest in infectious disease theories for many of the most common degenerative diseases of our times. For some specific cancers, for example, established mechanisms have already linked the diseases to various infectious agents. Some even claim that every disease has an infectious "cause", an argument that has been disputed by others that affirm that most "causes" are "environmental".

Without going into each theory's pros and cons, which is beyond the scope of this article, it is interesting to note that some infectious agents such as Chlamydia pneumoniae and cytomegalovirus have already been associated with coronary and peripheral arterial diseases. In addition, it is known that influenza epidemics are associated with excess morbidity and mortality, not only from respiratory diseases but also from other causes.

Nevertheless, the contribution of influenza to clinical events, including clinical cardiovascular diseases, is frequently not recognized (Siscovick et al., 2000). We identified some articles in this respect showing associations between influenza vaccination and both reduced risk of primary cardiac arrest (Siscovick et al., 2000) and reduced mortality from influenza among older persons (Reichert et al., 2001).

However, the main argument of Azambuja's & Duncan's theory is built upon data from influenza and pneumonia mortality (a marker for influenza activity). It is conceived that about 99% of mortality classified as due to pneumonia and influenza are in fact due to pneumonia, clearly not all associated with primary influenza virus infection. The sources of the data they used are from death certificates and hospital discharge diagnoses. Both probably underestimate the impact of influenza, but using pneumonia and influenza can overestimate the impact of influenza as well.

Moreover, they state that the epidemic affected whites and males most heavily, which were also the main groups hit by the rise in CHD mortality in the US. However, one can argue that if the pandemic had hit these groups the hardest, survivors of the pandemic, that is, the ones "primed" by the infection to predispose them to future development of CHD, would more likely be blacks and women.

In addition, influenza A (H1N1) circulated in human populations from 1918 (the great pandemic) to 1956, and reemerged about 1976-1977. The authors do not discuss, at least not very clearly, what happened to CHD in the period from 1956 to 1976, when H1N1 was not circulating in humans. Also, they do not propose any association between coronary cardiac diseases since H3N2 emerged in 1968 until the present.

Borrowing Hill's criteria for assessing "causality" to illustrate this commentary, we observed that the Authors provided a series of clinical-pathological and biomolecular clues to reinforce their argument, thus presenting biological credibility or plausibility for their findings. However, this is one of the most criticized criteria in the epidemiological literature, given that biological mechanisms can easily be elaborated linking an exposure to an outcome. If the epidemiological evidence pointed exactly in the opposite direction it would not be difficult to find another biological explanation.

As far as the strength of the association is concerned, the authors consider a Spearman correlation = -0.68 with a descriptive level of significance = 0.042 as being a NOTABLE (our capitals) negative correlation. It should be noted that with nine observations, they had only seven observations to contribute to the calculation of the residual in the estimated linear equation, and particularly that taking into account an R² = 0.46 (-0.68²), which means low precision, they do lacked sufficient evidence to consider correlation notable.

The essential temporal relation criterion is clear in their analysis of birth cohorts, but another important criterion that could be investigated is the consistency of findings. During 1918-1919, influenza was pandemic, since it affected most countries in the world. In Brazil, there are reports of more than 300,000 excess deaths attributed to the flu epidemic. The same occurred in European countries, where historical data are usually available. Thus, it would be interesting to replicate similar analysis to data from other countries to learn whether a similar pattern of CHD mortality across birth cohorts, in accordance with mortality from influenza in the same cohorts, corroborate their study's findings.

Finally, as the authors made clear, the study presented here is a correlational one with the clear purpose of raising new hypotheses to be further evaluated using different epidemiological designs. According to Hennekens & Buring (1987), the chief limitation of such studies is their inability to link exposure to diseases in particular individuals, in other words, correlation data represent average exposure levels rather than individual values. Thus, it could be that individuals unexposed to the influenza virus were the ones who later died of CHD, that is, the so-called ecological fallacy. A second major limitation of correlational studies, as recognized by the Authors, is the inability to control for the effects of potential confounding factors.

Notwithstanding such considerable limitations, Azambuja & Duncan were brave in facing the challenge of introducing a new pioneering theory.

As such, it is worth quoting Andrew J. Hall (2001:1197-1198), commenting on another pioneering article: "the study illustrates another saying of Geoffrey Rose: an epidemiologist needs dirty hands and a clean mind". Dirty hands from collecting all of the confounding variables, influenza, and CHD data, and clean minds with which to judge the evidence.

Acknowledgments

We thank Tim Uyeki (Centers for Disease Control and Prevention/National Center for Infectious Diseases/ Epidemiology Section/Influenza Branch) for comments and provision of influenza data in the United States, and for advice in literature searches on influenza vaccination effects.

HALL, A. J., 2001. Ecological studies and debate on rotavirus vaccine and intussusception. Lancet, 358:1197-1198.

HENNEKENS, C. H. & BURING, J. E., 1987. Epidemiology in Medicine. Boston: Little, Brown & Company.

REICHERT, T. A.; SUGAYA, N.; FEDSON, D. S.; GLEZEN, W. P.; SIMONSEN, L. & TASHIRO, M., 2001. The Japanese experience with vaccinating schoolchildren against influenza. New England Journal of Medicine, 344:889-896.

SISCOVICK, D. S.; RAGHUNATHAN, T. E.; LIN, D.; WEINMANN, S.; ARBOGAST, P.; LEMAITRE, R. N.; PSATY, B. M.; ALEXANDER, R. & COBB, L. A., 2000. Influenza vaccination and the risk of primary cardiac arrest. American Journal of Epidemiology, 152:674-677.