Women's Policy Action Tank: Asbestos, mesothelioma, and the predictive model 'gender gap'

A/Prof Alison Reid of Curtin University knows more than most about predictive models for the asbestos-related cancer mesothelioma. In today's policy analysis she draws on her ANZSOG-funded research in the latest issue of Evidence Base journal to explain why these models are important to get right - and why we need to pay attention to women as well as men!

Predictions about the future burden of asbestos-related mesothelioma cases are commonly undertaken, for a variety of policy and planning reasons. They usually try to predict the year at which the peak number of cases may occur, after which the disease may then decline. 

Knowledge about future cases of a particular disease can help health planners to allocate resources for primary prevention, screening and diagnosis, treatment, and palliative care. It can help companies to plan for future numbers of compensation claims. Estimates of the future burden of disease can also be used to evaluate prevention programs. For example, the number of cases diagnosed after the introduction of a prevention program could be evaluated against the number of expected cases (assuming that pre-program trends continued into the future).

Historical patterns of exposure among men

Mesothelioma is an interesting disease to predict because the sole cause of this cancer is exposure to asbestos. Traditionally, most cases have occurred among people who were exposed to asbestos through their work, for example milling or mining it, working in an asbestos cement factory, or coming into contact with it in their work environment (like carpenters, plumbers and insulators). More recently, workers who maintain buildings or remove asbestos from buildings have the highest exposure potential. These are all male-dominated professions, meaning the vast majority of predictions about future cases of mesothelioma have been done on male workers.

Historical patterns of exposure among women

However, women's patterns of exposure were very different. They were much less likely to be exposed to asbestos in their job. Instead, they were exposed either from their environment - for example living near an asbestos mine, mill or cement factory, or by washing an asbestos worker's dirty clothes. This type of exposure is different from men's occupational exposure, as it tends to be lower. The pattern of disease was different between women and men too, with the latency period (the length of time between first exposure to asbestos and diagnosis with disease) tending to be longer for women.

Today: non-occupational asbestos exposure

Australia was an avid user, producer and consumer of asbestos, and every capital city had an asbestos cement factory. Today, as a legacy of that past use, we have large amounts of asbestos containing materials (ACM), mostly in the form of asbestos cement sheeting, throughout our built environment. Little is known about the condition of the ACM, where it is located, and who and how many are currently exposed.

Similarly, little is known about the risks of disease that may be associated with such exposure. Increasingly, cases of mesothelioma have been occurring among people with non-occupational asbestos exposure, but to date little attention has been paid to the future burden of mesothelioma from this kind of exposure. But what we do know is that it is probably very low-dose exposure, and thus is probably similar to the type of asbestos exposure that women historically incurred. This also means the pattern of disease resulting from that type of exposure may more closely resemble the pattern of disease seen in women, with a longer latency period.

A problematic focus on cases in men

As mentioned, most methods developed to predict future cases of mesothelioma were created to best reflect the situation of occupational (high) exposure among men. Fewer studies have predicted cases of mesothelioma among populations with low-level asbestos exposure, and the robustness of these methods is less clear. In addition, many predictions specifically excluded women from their predictions, in general because of the smaller number of female cases.

However, Reid argues that estimating the future burden of disease based on past rates in women may inform the future burden and pattern of disease for the whole population, who are currently exposed to those low levels of asbestos from the ACM in their built environment. Similarly, prediction models could be tested for their accuracy by comparing their predicted cases against observed cases in women. Here, as in medical research more generally, the 'gender gap' has become an area of concern!

Read the full article here.

This analysis is a contribution to the Scorecard on Women and Policy project, initiated by the Women's Policy Action Tank.  We invite policy specialists in all areas to provide analysis of public policy using a gender lens:  womenspolicy@goodshep.org.au  Follow us on Twitter: @PolicyforWomen

Posted by @MsSophieRae