The stabilizing prevalence of asthma and the origins of the disease
Statistics Canada recently reported that the prevalence of asthma among 2-7 year old children had declined to its lowest level in more than 10 years, from 13.2 percent in 2000-01 to 9.8 percent in 2008-09, the most recent year for which data are available.
The findings, drawn from the National Longitudinal Survey of Children and Youth, echo many others that have previously pointed to a plateau and decline in asthma prevalence in the last decade in many high-income countries. Reports in respiratory journals began to appear as early as 2000 suggesting that the number of cases of asthma appeared to be stabilizing in some countries and even subsiding in others. These data imply that in Canada, exposure to the cause(s) of the epidemic is no longer increasing, and could even be declining.
The changing trends in asthma prevalence highlight fundamental shortcomings in our current epidemiological theories. Just when it appeared that we finally had the evidence and theoretical framework to explain the increasing prevalence of asthma worldwide, we now rather suddenly have to account for an inexplicable and unanticipated decline.
The hygiene hypothesis, for example, emerged as a predominant explanation for the epidemic of asthma. It suggested that lifestyle changes accompanying westernization and modernization had reduced exposure to microbes that had previously played a valuable role in training the immune system during childhood. It proved to be a useful explanation that made sense of important findings of lower rates of asthma among children raised on farms, for example. But the hygiene hypotheses could never really adequately account for rising rates of asthma in inner cities, and now, of course, it lacks the power to explain the decline in asthma.
Official reports announcing the declining prevalence of asthma in Canada pin it on reductions in the rates of tobacco smoking and improvements in other environmental exposures. In the report, Eleanor Thomas from Statistics Canada writes:
“A number of environmental factors may be related to the recent declines in childhood…asthma: changes in the population structure; changes in diagnostic practices; decreases in the prevalence of respiratory allergies; improvements in air quality; changes in hygiene practices (particularly, in child care settings); and reductions in children’s exposure to cigarette smoke at home….[R]educed exposure to tobacco smoke may be contributing to the decreased prevalence of…asthma among young children.”
But the situation in asthma epidemiology is actually quite a bit more complex. Statistics Canada has it mostly wrong about the environmental exposures it scrutinizes. And they have it wrong in a way that productively highlights an important difference between public health and population health.
Primary and secondary risk factors in asthma epidemiology
The key difference hinges on the distinction between primary and secondary risk factors. Statistics Canada, and much of asthma related public health at the moment, is focused on tracking secondary risk factors for asthma. Secondary risk factors are those inputs that influence which individuals in a population will develop asthma. By contrast, primary risk factors are those that determine the overall level of asthma in the population.
Tobacco smoke exposure offers a useful example. Over the years, research has repeatedly established that tobacco smoke exposure increases the odds that a given child will develop asthma. However, we also know that tobacco smoke exposure cannot, in and of itself, be responsible for the increase in asthma cases in the latter half of the twentieth century. The asthma epidemic occurred in populations at a time when rates of tobacco smoking were declining. Tobacco smoke exposure and asthma prevalence, in other words, demonstrate counter trends at the population level.
Statistics Canada’s own evidence on tobacco use bears this out. Here is a figure showing the prevalence of cigarette smoking between 1985 and 2001.
Cigarette smoking (above) declined from 35.1% in 1985 to 21.7% in 2001 while asthma prevalence (below) rose from approximately 3% in 1984 to more than 13% in 2000-01.
In addition to tobacco smoking, Statistics Canada highlighted improving environmental factors — improvements in air quality specifically — as potential contributors to the recent decline in asthma rates. But again we have evidence that atmospheric pollutants cannot be responsible for the epidemic of asthma because exposure to these risk factors has been reduced at the population level over the same time period. The following figure illustrates changes in the mean concentration of particulate matter (2.5 microns) as measured by Canadian National Air Pollution Surveillance network between 1990 and 2001.
The story is the same whether you look at mean annual concentrations of particulate matter (PM2.5 concentration in 2001 was 27% lower than in 1990, while the PM10 level was 34% lower), carbon monoxide (34% lower in 2001) sulfur dioxide (32% lower in 2001), or nitrogen oxides (NO in 2001 21% lower, while NO2 concentration15% lower). [For the full report see Environmental Protection Series National Air Pollution Surveillance (NAPS) Network. Air Quality in Canada: 2001 Summary and 1990-2001 Trend Analysis. Report EPS 7/AP/36 May 2004.]
In short, air quality in Canada improved in many places during the time period when there was a rather uniformly increasing trend in the prevalence of asthma, and continued to do so when the rates of asthma stabilized and began to decline. One cannot attribute only the recent decline in asthma prevalence to improving air quality.
What we see in these explanations is that many clinicians, researchers and epidemiologists and public health agencies tend to focus on associations and explanations involving secondary risk factors, such as tobacco smoke or air pollution, and to develop and field interventions that address them. There are certainly valuable reasons for doing so. These kinds of exposures are more ascertainable in clinical encounters, they are often modifiable by patients, and their control and mitigation may have an important positive effect on the individual and the day-to-day manifestation of their asthma. Indeed, the evidence from Statistics Canada suggests exactly that:
“A key finding is that the percentage of children with asthma who reported an asthma attack in the past 12 months fell steadily from 53 per cent in the mid-1990s to 36 per cent last year.”
In short, children with asthma in Canada are being less frequently exposed to asthma triggers and, as a result, reporting fewer asthma attacks. Good news. Reduced tobacco smoke exposure certainly deserves credit for contributing to this decline.
It should be evident, then, that there are clear, important risk factors for asthma that play a significant role in the natural history of the disease in a given patient, but which, all the same, cannot be responsible for the epidemic.
These secondary risk factors are not (necessarily) the same things that we would choose to focus on if we were trying to change the overall rate of asthma in the population. As Jeroen Douwes and Neil Pearce, two international asthma experts, wrote in a 2006 editorial:
“Thus, the ‘established’ risk factors for asthma do not appear to explain the global prevalence patterns and time trends. These risk factors were ‘discovered’ primarily on the basis of clinical studies and case reports of exacerbations in asthma patients. It is natural for physicians and patients to assume that the factors involved in secondary causation may also be important for primary causation. However, for most of the ‘established’ risk factors, the evidence of primary causation is relatively weak, and risk factors such as allergen exposure do not appear to explain the prevalence patterns and time trends.”
The population health possibilities
In his 1985 article “Sick Individuals and Sick Populations,” Geoffrey Rose made the observation that small changes in the risk of a disease, when summed across a population, could result in dramatic shifts in the prevalence of a disease. Although he didn’t consider the concept of primary and secondary risk factors, his work demonstrated how risk factors insignificant to an individual could be meaningful to the population, and prompted a reevaluation of public health preventive strategies.
The growing evidence of a plateau and decline in asthma should have had similarly major implications for our view of the (partially understood) potential etiologic mechanisms underlying the asthma epidemic and the origins of asthma. So far, however, the signs of shift to a population health perspective have been minimal. In part, our ability to think about and understand the complex causes of the long increase in asthma and the plateau and decline has been hampered by the continuing orientation of epidemiology and public health to surveillance and analysis of secondary risk factors.
In the case of asthma, it remains a struggle to identify primary risk factors from available public health data. We are limited to retrospective and outdated data on only the most severe exacerbations (those that result in hospitalizations and, in some states, emergency room visits). Altogether, that amounts to just a tiny fraction of the daily burden of asthma morbidity.
Moreover, our surveillance system is designed to ignore potentially valuable information about where and when the attack began, whether that is at home, at school, at work, or out in the community. Typically the only geographic information available is the billing address. As a result, we cannot understand the small area variation in rates of asthma that we know exists.
New approaches to chronic disease surveillance and epidemiology are emerging that, if guided by a population health perspective, have enormous potential to advance our understanding of chronic diseases. It is already clear that these systems will be increasingly driven by participatory ethics (see the 2010 article by Freifeld et al. in PLoS Medicine) and will collect and rapidly make sense of valuable new streams of data, drawn from distributed networks of sensors and connected devices. They will bring growing numbers of people (see notes below) and their daily experiences of health, disease, medicine and the environment under increasing statistical scrutiny (cf. RWJF Project HealthDesign), with many potential benefits. It is likely that such approaches will generate new, useful clinical knowledge. A recent analysis of data volunteered by individuals using CureTogether, for example, has identified a new symptom marker that predicts negative response to a specific migraine treatment.
But the materialization of an epidemiological advance from these tools will be more complex and less certain. It will, in fact, turn on our ability to use them to marshal a new hunt for primary causes – that will complement the traditional clinical and public health focus on secondary risk factors that has dominated them so far.
Even then, there may still be very difficult challenges. For example, it is worth considering the possibility that it may be too late to search for the primary cause(s) of a number of chronic diseases in the urban areas of high-income countries. In these settings, exposure to the primary causes of a given disease may already be ubiquitous across the population. Without variability in exposure to the disease’s primary causes, all that would be revealed are the effects of secondary risk factors. Similarly, repeated investigations over short periods will only be informative if they capture a dramatic, and thus unusual, change in lifestyle or environmental exposures.
In other words, our odds of making fundamental discoveries are tied to our ability to develop tools and systems that help us collectively uncover a new list of primary risk factors and hypotheses. To do this might mean we engage communities that display a broad range of prevalence (urban vs. rural areas of low income countries), or populations that abruptly change their environment and lifestyle (immigrants, refugees, adoptees, etc.) Such efforts would have a much greater probability of identifying primary causes of the chronic diseases we’re targeting, especially if the confounding role of secondary causes is also accounted for.
Our new systems should help us explain the overall rates of asthma in populations, its global gradients and time trends, and do so with some evolutionary probability. We need to pause to reflect on the u-turn that the prevalence of asthma has done and re-double our efforts to piece together the rules that underlie the surge, pause and decline in the prevalence of asthma. It will also almost certainly mean evolving our approaches to better sample experience, understand context, lifestyle and environment, and to look for connections where there may not be evidence of an effect on individuals.
In a recent article in Science on open mHealth architecture, Deborah Estrin and Ida Sim noted that if only 1 out of every 250 patients in the US taking antidepressants participated in a collaborative study of their long term efficacy, more than 100,000 patients enrolled would exceed the total number of patients enrolled in all antidepressant studies conducted worldwide since 2005.