# Standardized Rates of Disease

As noted earlier, a key question for Woburn was whether or not the community was experiencing an unusually high frequency of leukemia (or other diseases). The strategy for doing this is generally to compare the incidence of a particular disease in a community to the incidence of that disease relative to that in other communities or relative to the overall rates seen in the state or in the country. However, comparisons like this can be distorted by confounding factors, such as age and gender. Imagine, for example, that you are comparing overall rates of cancer mortality in two populations, one of which has a large proportion of older citizens, while the other has a younger age distribution. If the overall cancer mortality is greater in the older population, it would not be valid to conclude that this community has an environmental factor that increases the risk of cancer, because age is another risk factor that independently associated with an increased the risk of cancer mortality. As a result, the comparison isn't fair, because of the unequal age distribution. Age differences always have the potential to confound these comparisons, because so many health outcomes are affected by age. Many health outcomes are dependent on gender, so differences in gender distribution between two populations can also introduce confounding.

When comparing rates of disease among communities, the problem of confounding by age or gender can be dealt with by computing age-standardized rates separately for males and females. There are two techniques for doing this.

1. Age-adjusted Standardized Rates - One can calculate age-adjusted standardized rates from the age-specific rates of disease for each of the populations to be compared. If age-specific rates of disease are available for the populations being compared, one can then use a standard age distribution to compute a hypothetical summary rate that indicates what the overall rate of disease would be for each population, if they had had the same age distribution as the standard. In other words, one uses each population's real age-specific rates and applies these to a single standard age distribution.
2. Standardized Incidence Ratios - In some situations the age distribution of the populations being compared is know, but it is difficult, if not impossible, to obtain reliable estimates of age-specific rates if the disease is rare or if one or more of the populations is small. In these situations the age-specific rates would be subject to random error because of relatively small numbers of observations. In this situation one can compute a standardized incidence ratio which addresses how the observed number of cases of disease in a community (like Woburn) compare to the number of cases that would have been expected if the community had had the same rate of disease as the comparison population.

Standardized rates are explained in detail in the online learning module on Standardized Rates. Review the module paying particular attention to the section on standardized incidence ratios on page 6. As the module indicates, standardized incidence ratios are particularly useful when dealing with relatively uncommon diseases, such as leukemia. The strategy for SIRs is to compare the number of observed cases of disease to the number of cases that would have been expected if the community's rate of disease were the same as the overall rate for the state. Consequently, an important application of SIRs is to monitor the frequency of cancer and other diseases in individual communities. The Massachusetts Cancer Registry was established in 1980, partly in response to the childhood leukemia cluster in Woburn.

Review the examples in the module on Standardized Rates to familiarize yourself with calculation of an SIR; then use this information to compute the SIRs for leukemia in male and female children in Woburn using the data in the tables below.

 The tables below summarize data that were used for computation of standardized incidence ratios in both the 1981 report (Woburn - Cancer Incidence and Environmental Hazards, 1969-1978) and in a a subsequent article published in 1986 (Cutler JJ, Parker GS, Rosen S , et al.:"Childhood Leukemia in Woburn, Massachusetts." Public Health Reports, March-April 1986; 101(2):201-205). The tables (for males and females) provide age-specific information on populations size, overall rate of leukemia in MA, and the observed number of leukemia cases in Woburn for the period 1969-1979. The numbers of expected cases were determined from the Third National Cancer Survey, 1969-71, as described in the article. Following the example on page 6 of the module on standardized rates, compute the missing information in the tables below, and use this to compute the SIR for male children and the SIR for female children. Complete your calculations and interpret your findings before looking at the answer.

Male Children (1969-1976)

Age Group

Population

State Rate

Observed Cases

Expected Cases

<5

1784

0.0008

4

?

5-9

2057

0.0004

3

?

10-14

2128

0.0003

2

?

SUM

5969

------

?

?

Female Children (1969-1976)

Age Group

Population

State Rate

Observed Cases

Expected Cases

<5

1714

0.0007

0

?

5-9

1982

0.0004

0

?

10-14

2083

0.0002

3

?

SUM

5779

------

?

?

Go to the Massachusetts Cancer Registry web site and find the City & Town Series. Open the City and Town Supplement for 2005-2009 and scroll down until you find the report for Woburn. What are the SIRs for leukemia in males and females during this five-year period? What are the 95% confidence intervals for the SIRs? How would you interpret these SIRs?