The term 'disparity' generally refers to inequality or some kind of difference between groups. Health researchers differ in the ways they define a health disparity. Here are some definitions of disparities related to cancer:

1. Center to Reduce Cancer Health Disparities, National Cancer Institute

   “A difference in the incidence, prevalence, mortality, and burden of cancer and related adverse health conditions that exist among specific population groups in the United States.” NCI Center to Reduce Cancer Health Disparities (CRCHD)

2. Minority Health and Health Disparities Research and Education Act of 2000

   “A population is a health disparity population if...there is a significant disparity in the overall rate of disease incidence, prevalence, morbidity, mortality, or survival rates in the population as compared to the health status of the general population.” [Minority Health and Health Disparities Research and Education Act of 2000 (47, page 2498)]

3. NIH Strategic Research Plan

   “Health disparities are differences in the incidence, prevalence, mortality, and burden of diseases and other adverse health conditions that exist among specific population groups in the United States.” [NIH Strategic Research Plan and Budget to Reduce and Ultimately Eliminate Health Disparities, Vol. 1, Fiscal Years 2002–2006]

4. Dr. David Satcher Former U.S. Surgeon General

   “For all the medical breakthroughs we have seen in the past century, there remain significant disparities in the medical conditions of racial groups in this country...[W]hat we have done through [Healthy People 2010] is to make a commitment—really, for the first time in the history of our government—to eliminate, not just reduce, some of the health disparities between majority and minority populations.” [Dr. David Satcher Former U.S. Surgeon General, 1999 (48, page 18–19)]

 What differences do you observe in these definitions of cancer disparities?

 What are the measurement issues inherent in the various definitions of health disparities we have reviewed? If you were going to define how to measure health disparity what kind of issues might come to your mind?

Elimination of Health Disparities

Eliminating health disparities has been adopted as a goal at several US health-related agencies.

“The second goal of Healthy People 2010, to eliminate health disparities, includes differences that occur by gender, race or ethnicity, education or income, disability, geographic location, or sexual orientation.” https://www.cdc.gov/nchhstp/healthdisparities/

If the goal is to eliminate a disparity, we must ask how a disparity is identified and measured. Otherwise, how will we know if we have succeeded?

Some important documents from the US government for researches involved with health disparities that attempt to answer how to identify and measure disparity are listed below:

The NCI lists 13 issues to be considered when attempting to measure health disparities.

Issues in Evaluating Measures of Cancer Health Disparities

1. Is it relative or absolute disparities that you are interested in?
2. Are you talking about total disparity or differences in social groups?
3. Reference groups - who will you be referring to?
4. Do the social groups have a “natural” order?
5. How many social groups will you use?
6. Should you vary the groups based on population size?
7. What part does the socioeconomic dimension play?
8. Do you monitor populations over time?
9. How do you handle transfers?
10. Subgroup consistency
11. Decomposability
12. Scale independence
13. Transparency / Interpretability for policymakers

Geography is not specifically mentioned in this list. Yet the definition for the elimination of health disparities includes geographic location. What units of geography should be associated with a disparity? How do we measure geographic disparity?

The NCI monograph provides examples of some types of disparity. (this document is posted in Week 8 materials)

The blue lines below track stomach cancer mortality over a seventy-year period, by gender. Substantial decreases in stomach cancer mortality are observed in both men and women over this time period. The absolute disparity, i.e. the difference between men and women in stomach cancer mortality, is indicated by the lower red line which has been continually decreasing since about 1945. However, if the relative disparity is considered by dividing the stomach cancer mortality of males by that of females (top red line), the disparity has actually been increasing.

What do you conclude about the trend in disparities in stomach cancer mortality for men versus women?

It depends ... certainly, males have higher mortality but the absolute difference has been getting smaller over time, while the relative difference has increased. Obviously, the choice of absolute or relative difference will affect the interpretation of the data.

Let's consider an example of total disparity versus a social group disparity by education level. Mean Body Mass Index (BMI) is indicated for various levels of education.

In this case, we can see that those with less than an eighth-grade education had the highest mean BMI. The difference between the lowest and highest education levels is only about two or three points, however, the red line shows you the distribution within each of these categories. So, if you look at the 'less than 8th-grade educational level' group, the 10th percentile has a BMI of 36 and the 90th percentile have a BMI of about 22.

Although the total disparity doesn't look large, the disparity within each of the groups is large. It would be useful to consider the distribution within each of these groups as well, not just a single mean value for each group. You can see for college groups there is not quite as much variability. The range and variability within groups may be more informative than the absolute disparity.

Another illustration of total disparity versus social group disparity is to put forward an example with two different hypothetical societies, A and B. The average life expectancy is equal in these two societies. However, Society A has a much tighter distribution than does Society B. Also, while the average life expectancy is the same, you can see that there is a distinct difference between Group 1 and Group 2 within Society A and less difference between the groups in Society B.

We might conclude that Society A and B have the same life expectancy based on their average values or we may recognize that groups within the societies have different distributions. The disparity between groups in Society A is greater than the disparity between groups in Society B. On the other hand, if you consider the magnitude of the disparity within Society A (the spread of the curve) compared to that of Society B, without regard to subgroups, it appears that disparity is greater in Society B because the curve is wider.

Obviously, the decision of the reference group in disparity research is critical.

Reference Groups

Figure 6 below shows incident cervical cancer in the total SEER population and within various racial/ethnic groups. The relative risk of incident cervical cancer among Hispanics as compared to the total population and to some groups is also noted. For example, the RR of 1.75 compares the rate among Hispanics to that of the total population (16.8/9.6). When we compare Hispanics to non-Hispanic whites the RR increases to 2.21 because non-Hispanic whites have a lower rate of incident cervical cancer than does the total population.

The choice of which group to use as a reference is not just a matter of playing with numbers to get the desired value...it really has to do with your definition of equality. Do you wish to eliminate disparity so group members have health outcomes in general that match those of the total population? Or is your objective that all groups will match the group with the best health outcome? In this example, the American Indian/Alaska natives have the lowest incident rate of cervical cancer. Shall this be the reference group?

Here are some examples of reference groups or values that have been used in studies of disparity:

• the average population member
• a fixed target rate
• social groups and “natural ordering”
• the best-off group/person/rate
• all those better off

All Those Better Off – Reference Group

Suppose you decide to compare to 'all those better off' using the graph below.

Number of Social Groups

Patterns in disparities are affected by the selection of the social groups for comparison. For example, in the graph below, if the comparison was made between African-Americans and whites only, the absolute difference in screening decreases between 1987 and 1992 and then stays about the same from 1992 to 1998. With the inclusion of the Hispanic data, we see a different pattern. The absolute differences in screening rates for Hispanics compared to whites are larger in 1992 and 1996 than in 1987. So in one type of comparison, disparity decreases while in another, disparity increases. Once again, the choice of the reference group and the number of comparisons will affect the results and conclusions. Consider well which comparisons you wish to make, which disparities you wish to ameliorate.

Population Size

Population size has an effect as well. This graph displays the percentage change in population size by race and Hispanic origin over a 20 year period. Asian Pacific Islanders have increased by 204% and the non-Hispanic whites 7.9%. The differences in population change will affect the proportions of these groups in the population as a whole.

How do we measure poverty?

• Do we use personal income or wealth?
• Do we use personal socioeconomic status or socioeconomic position?
• Shall we calculate an index of personal measures?

These examples are from Freeman HP, Horsch KJ. Cancer and the Poor: A Report to the Nation. Atlanta, GA: American Cancer Society.

Addressing Disparity Questions

NCI proposes these steps:

1. Inspect the subgroup data - Always an important first step. Use frequency plots, stem & leaf plots, or box plots - look at the data.
2. Determine the disparity question
   • Example: What is the disparity in mammography screening across all education groups? The comparison uses a summary measure.
   • What is the disparity for those with [<8 years] of education? Here, use an individual group measure.
3. Choose a measure of health disparity

1. Relative Concentration Index

   The relative concentration index takes into account the relative distribution of each of the groups within that social group.

   \(R C I=\frac{2}{\mu}\left[\sum_{i=1}^{\prime} p_{i} \mu_{i} R_{j}\right]-1\)

   where \(p_i\) is the group's population share, \(\mu_i\) is the group's mean health, and \(R_j\) is the relative rank of the \(j^{th}\) socioeconomic group, which is defined as:

   \(R_1=\sum_{i=1}^{\prime} p_{\gamma} -\dfrac{1}{2}p_{i}\)

   where \(p_j\) is the cumulative share of the population up to and including group j, and \(p_i\) is the share of the population in group j.

   This is an ordered group because it takes into account a cumulative share, i.e. taking into account the size of the population up to that point.

   The relative concentration index is meant to summarize relative disparity for the groups, not to compare any two groups.

2. Absolute Concentration Index

   The absolute concentration index takes the relative concentration index from above and multiplies it by \(\mu\), the mean level of health in the population.

   \(ACI=\mu RCI\)

Let's look again at the plot of education level groups with both of these indices applied to the data. The relative disparity wanders but is not much different in 2002 than it was in 1990. On the other hand, the absolute disparity continues to increase, indicating improvement. The absolute disparity is a reflection of the difference between the groups of the entire population. Whereas the relative disparity tells us about the relative disparity across all groups in the population, taking into account the size of each group.

We might conclude that the difference between groups is getting smaller over time as measured by the absolute disparity. But disparities relative to other groups have not changed very much over time. There are many more measures that have been used to summarize disparity, including Jenny coefficients or the slope index of inequality.

Kreiger, N., Williams, D. Changing to the 2000 Standard Million: Are Declining Racial/Ethnic and Socioeconomic Inequalities in Health Real Progress or Statistical Illusion? American Journal of Public Health. 91:8, August 2001.

For many years, US health statistics were standardized to the 1940 population. Now the 2000 US population is used, which is considerably older than the 1940 cohort. Diseases of the elderly will be more prominent in the 2000 population. When comparing groups, age-adjusting by the 2000 population can diminish relative risks as compared to what they were using the 1940 population. These authors provide examples where the population used for standardization affects a measure of disparity. Thus, when standardizing health statistics, be aware of the choice of the standard population and how that choice may affect the perception of health disparities.

Kreiger and Williams focus on the 2000 US population standard. There is also a WHO standard; Canada and other countries have their own standards.

In summary, when making comparisons, the choice of the reference is critical!