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# Health Disparity Measures

Measuring health disparities is essential for informing targeted efforts to reduce disparities. Health disparities can be measured between racial or ethnic groups, geographic regions, gender identities, socioeconomic statuses, or other group statuses (e.g., migrant or refugee status, experience of homelessness, incarceration). Changes in measures over time can indicate progress or setbacks in eliminating health disparities. Different disparity measures can provide different results in magnitude and direction.1-6 The measures described in this document represent a subset of commonly used measures in public health.2,4-5,7 No gold standard measure exists, so the literature recommends measuring disparities in both absolute and relative terms to help ensure robustness of findings.1-2,4

Pairwise measures show disparities between two groups. Examples of pairwise measures include:5,8-9

### 𝑅𝑎𝑡𝑒1 − 𝑅𝑎𝑡𝑒2

Group 2 is the comparison group, such as the group with the lowest rate.
Knowing the direction (positive or negative) of the rate difference is also important.

### 𝑅𝑎𝑡𝑒2

Group 2 is the comparison group, such as the group with the lowest rate.
If Rate1 > Rate2, the rate ratio will be greater than 1.
If Rate1 = Rate2, the rate ratio will be equal to 1.
If Rate1 < Rate2, the rate ratio will be less than 1.

Composite measures show disparities in a whole population. Examples of composite measures include:

### Population Attributable Proportion (PAP)2,8,10

This is the proportion of cases attributable to disparities between groups.

Rateoverall is the rate in the total population.
Ratelowest is the rate in the group with the lowest rate (i.e. the comparison group).
If Ratelowest = 0, all cases are attributable to disparities, and the PAP will equal 1.
If Rateoverall  = Ratelowest, no cases are attributable to disparities, and the PAP will equal 0.

### Absolute and Relative Indices of Disparity5,8,10-11

Index of Disparity
0 = No disparity; higher values indicate greater disparity.

Ratei is the rate in group i.
Rateoverall is the rate in the total population.
N is the total number of groups.

If only the numerator is used (i.e., you choose not to divide by Rateoverall), this measure is the absolute index of disparity.

If you choose to divide by Rateoverall, this measure is the relative index of disparity, expressed as a percentage of the overall rate.

Population-Weighted Index of Disparity*
This index of disparity is weighted by the population size of each group.

Populationi is the number of people in group i.
Populationoverall is the total number of people, equaling the sum of all Populationi.
*There are equity considerations to account for when deciding whether to weight measures or not.4,12

### Gini Coefficient7-8,10,13

0 = No disparity; 1 = maximum disparity

Groups are ranked from 1 to N by their rates.
Xi is the cumulative percentage of the population after including group i.
Yi is the cumulative percentage of cases/diagnoses after including group i.
X0 and Y0 are both 0.
N is the total number of groups.

The blue line plots Xi and Yi from the table below. The black line shows the hypothetical situation of no disparity, where each group’s share of cases equals their share of the population. The Gini Coefficient would equal 0.

The table was adapted from HIV case data in McCree et al. 2020.13 The above figure plots data from this table in blue.
Group Cases Rate Population Cumulative % of Pop. (Xi) Cumulative % of Cases (Yi)
Native Hawaiian/Other Pacific Islander 1 0.5 213,000 0.2 0.03
White 425 0.5 80,189,000 64.6 13.1
Asian 48 0.8 6,400,000 69.8 14.6
American Indian/Alaska Native 10 1.1 901,000 70.5 14.9
Hispanic/Latino 644 3.2 20,252,000 86.7 34.7
Multiple Races 99 5.2 1,908,000 88.3 37.7
Black/African American 2027 13.9 14,583,000 100.0 100.0
Total 3254 2.6 124,446,000 100.0 100.0

The Gini Coefficient is also equal to A/(A+B). The larger the gap (area A) between the no disparity line (in black) and the actual data (in blue), the greater the disparities in the total population.

This fact sheet was prepared by Joy Ortega (CDC/IOD/OS), Kristy Hayes (CDC/GHC/OD), Donna Hubbard McCree (CDC/NCHHSTP/OD), Harrell Chesson (CDC/NCHHSTP/DSTDP), and Ranell Myles (CDC/NCHHSTP/OD).

Disclaimer

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