r In a classic study, Armstrong and Doll (1975) reported the correlation between 27 cancers and a wide range of dietary and other variables in 23 countries. Diet was strongly correlated with several types of cancer, particularly consumption of meat with cancer of the colon. Countries with low per-capita daily consumption of meat had the lowest rates of colon cancer. The findings from this study suggested that dietary factors play a role in the development of cancer and led to a burgeoning of research in this area.
r In 1979, the authors of another study reported a strong inverse association between average per-capita consumption of wine and mortality from ischaemic heart disease (high wine consumption was associated with low IHD mortality) (St Leger et al., 1979). Since then more than 60 ecological, case–control and cohort studies have been conducted and most have shown that moderate consumption of wine and other alcohol has a protective effect against heart disease.
This example illustrates the key characteristic of ecological studies – they com- pare the prevalence of exposure and occurrence of disease in populations or groups of people, not individuals. The points on the graph represent the pop- ulation prevalence of infection (in this case, taken from special surveys of indi- viduals in each county) and the rate of disease in the population. The focus is on whether counties or populations with a high prevalence of infection also had a high cancer rate. In general, ecological studies are attractive because they are easy to do, especially if the routine data are readily available, but they can be difficult to interpret. The populations being compared may well differ in ways other than their exposure to the factor of interest and it is possible that some- thing else that is related to the exposure is actually responsible for the observed differences in morbidity or mortality (i.e. an apparent relation could be due to
confounding – see Chapter 8). Another problem with this type of study is that an
observed association between variables at the group level might not represent the association at the individual level. In the example above, we have no way of knowing whether the people who developed cancer were actually infected with H. pylori. Ascribing characteristics to members of a group that they might not possess as individuals is called an ecological fallacy. For these reasons, ecological studies rarely give a strong test of a causal hypothesis but, more often, they help to generate or develop hypotheses. Box 3.5 shows some other ecological studies that have been instrumental in suggesting associations between exposures and disease.
Confidentiality
We cannot end any section on health data without touching on the issue of confi- dentiality. Clearly, information about an individual’s health is private and should not be accessible to anyone else other than their healthcare providers. Much of the available health data is in the form of summary statistics such as rates so that it is impossible to identify specific individuals, and these data can be made freely (or at least readily) available. To gain access to data on individuals it will almost certainly be necessary to sign a confidentiality agreement, have permission from a Human Research Ethics Committee or Institutional Review Board and/or obtain consent from the individual patients and sometimes their physicians as well. Rapidly changing and expanding privacy legislation in many countries is adding to the challenges. While properly highlighting ethical use of data, the increasing emphasis on the principle of autonomy has created ten- sions between the need to protect personal information on the one hand and the desire for public good, which may require some access to individual data, on the other.
Summary
You have now seen the most common types of descriptive data and where they come from and also some examples of the many ways in which they can be used. These data are core to health planning and, as you will see in later chapters, are also essential for identifying new health problems and monitoring the effects of health interventions. You have also seen that although it cannot provide strong evidence about the causes of disease, creative use of descriptive epidemiology can generate new ideas about causality. These hypotheses then need to be tested in more formal ‘analytic’ studies and we will move on to discuss these in the next chapter.
R E F E R E N C E S
Armstrong, B. and Doll, R. (1975). Environmental factors and cancer incidence and mor- tality in different countries, with special reference to dietary practices. International Journal of Cancer, 15: 617–631.
ABS (Australian Bureau of Statistics) (2006). Mental health in Australia: a snapshot, 2004– 05. Cat no. 4824.0.55.001. Downloaded from: http://www.abs.gov.au/AUSSTATS/abs@. nsf/ProductsbyTopic/3AB354FFA0B0A31FCA256F2A007E5075?OpenDocument, 16 September 2009.
CDC (Centres for Disease Control). (1981). Pneumocystis pneumonia – Los Angeles. Mor- bidity and Mortality Weekly Review, 30: 250.
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