# Presentation: 023886

## Measuring DisparitiesIn Health

- Concurrent Session 3212.0
- Monday, Nov. 11th   12:30 – 2:00 PM

## What Do We Mean By Disparity

- Jeffrey N. Pearcy, MS
- Kenneth G. Keppel, PhD

**Centers for Disease Control and Prevention**
**National Center for Health Statistics**

## Disparity

-    Semantics
- Components
-    Framework
- Determinants
- Limitations
-    Conclusions

**Notes:**
As we go through this outline, my hope is that you might keep these concepts in mind for the future when you may discuss, measure, or try to eliminate disparity

## Semantics

- Disparity
- “inequality or difference as in rank, amount, quality, etc.”
- Inequality
- “a difference or variation in size, amount, rank, quality, social position, etc.”
- Inequity
- “lack of justice; unfairness”

- Webster’s New World Dictionary   2nd Edition, 1994

**Notes:**
Here we have definitions of three terms most used in the discussion of differences in health.  Note the similarity...or lack of disparity...in the first two definitions – In contrast to the third.

These differences are consistent with the distinction noted by Roy Carr-Hill of the United Kingdom Health Equity Network who observed that.. “We also have to be beware of confusing the measurement of Inequality with the measurement of Inequity.  The former is a factual matter, the latter is an ethical judgment.”

More recently though, the distinction between the first two and the last has become blurred.  The American Heritage Dictionary (4th edition, 2000) includes in its definition of inequality “...Lack of equality, as of opportunity, treatment, or status” .  Which implies, to some extent, inequity.  The Cambridge International Dictionary of English (2002) explicitly links Disparity and Inequity in its definition of Disparity as “..a lack of equality and similarity, esp. in a way that is not fair.”

## Semantics (usage) 

- Outside United States
- “Inequality or Inequity” used
- In United States
- “Disparity, Inequality and Inequity” used ...
- Interchangeably
- Public Health Context
- Disparity is now “Value-Loaded”
- Alternative definition required ???

**Notes:**
   While there has been an apparent change in dictionary definitions, there has been lack of agreement on the usage of terms
   One set of distinct terms is generally used in Europe, and an (apparently) indistinct set in the United States.
   In the context of public health , the term Disparity takes additional meaning compared to its use in other biological and physical sciences, and has been used at times to mean  disadvantaged, inequitable, and unjust.
  As such, it follows to form an operational definition of disparity in public health that includes elements of both Inequality and Inequity.

## Disparity

- “In the context of public health and social science, has become value-loaded, and so can be distinguished from inequality.
-   As something different in meaning as applied here...”

**Notes:**
 “In the context of public health and social science, has become value-loaded, and so can be distinguished from inequality.

  As something different in meaning as applied here...”

## Disparity

- “...should be viewed as a train of events leading to a difference in:
- Access to, utilization of, or quality of care
- Health status, or
- Health outcome
- 	....that deserves scrutiny.”

**Notes:**
“...should be viewed as a train of events leading to a difference in:
Access to, utilization of, or quality of care
Health status, or
Health outcome
	....that deserves scrutiny.”

## Disparity

- “...such a difference should be evaluated in terms of inequality and inequity, since what is unequal is not necessarily inequitable.
-   In short, the term disparity in the context of public health embodies both inequality and inequity.”

**Notes:**
“...such a difference should be evaluated in terms of inequality and inequity, since what is unequal is not necessarily inequitable.

  In short, the term disparity in the context of public health embodies both inequality and inequity.”

As such, it follows to form an operational definition of disparity in public health that includes elements of both Inequality and Inequity.

## Components of Disparity

- Inequality
- How different are we?
- (measurement issues)
- Inequity
- Who should we be like?
- (another group)
- What should we be like?
- (some target)

**Notes:**
1) So, Inequality goes to the question of:  “How different are we?”.  
Measuring this difference can take a number of forms, but can be dealt with in an objective way, by taking differences, ratios, averages, etc.

2) In contrast, Inequity requires a decision about how much a difference should be reduced.  Whether that is in terms of which other group one should be like, or, in absolute terms, what level of outcome should be attained.

## Conceptual Frameworkof Disparity

- Adapted from Evans, Whitehead, Diderichsen, et al.  2001

- Inequality

- Inequity

**Notes:**
If disparity can be viewed as composed of elements of both inequality and inequity, then both elements should be considered separately in turn. If we can assume that inequity between populations cannot exist prior to, or without inequality, then the need to understand the underlying causes of inequality should be self-evident.
Consider Disparity in terms of a decision tree.  -  Ideally, this is the type of approach that should be taken
First, a determination of whether two or more groups are unequal must be made.  We have many statistics to do this (absolute diff., % diff, ratio, etc.),  but the most appropriate may not be readily apparent.  This problem, the selection of statistics, will be introduced in the presentations that follow. 
A question that should also be asked at this point is “how unequal are these?”  - - how big is the inequality?   And does the inequality rise to the level of disparity.  Presently we have no guidelines in this matter, and it may not be easy to determine.  
If the inequality is large, and is considered a disparity, we should ask a series of questions as to whether the inequality is unavoidable or potentially avoidable.  This could be made on the basis of a set of determinants of health such as those proposed by Whitehead, Braverman, Health Canada, or others.
Finally, an ethical judgment of must be made.  Whether an inequality, that is potentially avoidable, is acceptable, or whether it is unfair and unjust.
I believe that only when Disparity is considered in terms of its component parts, And only when we know what proportion of the inequality is avoidable, And only when truly ethical judgements of fairness are made, can we make the most effective use of our efforts to eliminate Disparity.

## Health Determinants(Health Canada)

- Income and Social Status
- Social Support Networks
- Education
- Employment and Working Conditions
- Social Environments
- Physical Environments
- Healthy Child Development
- Health Services

- Personal Health Practices / Coping Skills
- Biology and Genetic Endowment
- Gender
- Culture

- _Avoidable_

- _Unavoidable_

- http://www.hc-sc.gc.ca/hppb/phdd/determinants/index.html

**Notes:**
If we are to understand the nature of the Disparity, we should attempt to understand the reasons for the observed inequality

Here is a list of health determinants as proposed by Health Canada.  The link to their site provides a very good, and very understandable overview of how they view determinants of health.  It includes discussion of the context of each determinant, the complex interactions of determinants with health and other determinants, and evidence of effect.  I’ve separated their list into those that may be considered avoidable and others that may be unavoidable.

## Health Determinants(Whitehead)

-   _Unavoidable_
- Natural biological variation
- Behavior that is restricted
- Transient health advantage

-   _Avoidable_
- Home & work environment
- Behavior – freely chosen
- Access to care
- Health-related social mobility

- http://www.who.dk/eprise/main/WHO/Progs/HPA/Equity/20020319_1

**Notes:**
Another well known set of health determinants, is that described by Margaret Whitehead (2000).  The link to the article describes why determinants may be considered Avoidable or Unavoidable, how they impact health, and a European view on equity in health and how it can be achieved. 

## Effect of Determinants on Diseases

**Disease A**

**Disease B**

**Disease C**

_**Unavoidable**_

_**Avoidable**_

- (Hypothetical Example !!)

**Notes:**
Assume for now that some determinants of health are avoidable, but others are un-avoidable.  
It is well known empirically and clinically that determinants of health have different impacts on different diseases.  
For this example, let’s assume that only five determinants of health are responsible for each disease.  
The width of the bars indicates that each disease has equal incidence, say 200 / per 100,000.  
The different colors in each bar represent the portion of each disease caused by each determinant. 
 For Disease ‘A’, the avoidable portion in yellow, tan, and orange accounts for about 60% of the disease.  
While for Disease ‘B’ and Disease ‘C’ the avoidable portions are about 80% and 70% respectively.  
In this example, the inequality is zero, and so we might conclude that the disparity is zero.  
However, the avoidable portions of each disease are not equal, so we may conclude that there is a possible inequity.

## Effect of Determinants by Population

**Population**
** ****A**

**Population**
**B**

**Population**
**C**

_**Unavoidable**_

_**Avoidable**_

- (Hypothetical Example !!)

**Notes:**
This slide shows a more realistic hypothetical example based on the same 5 determinants of health.  
With each determinant contributing the same proportion of all determinants as in the previous slide.  
Here, determinants are shown having different effects on different populations – but for a single disease.   
In this example, the width of each bar indicates the incidence (about 200, 100, and 300 per 100,000) for populations ‘A’, ‘B’, and ‘C’ respectively.  
These are large inequalities in rates and we should conclude that disparity exists. (A)  
It also appears that the areas of each bar colored yellow, tan, and orange are very unequal.  
As these represent avoidable portion of the inequality, we may conclude that an inequity also exists. (B)

 The Inequality portion of the Disparity amounts to about 59 % of the rate for the total population.
(B) The Inequity part of the Disparity amounts to about 46 % of the rate for the total population.

## Limitations

- Idea of unavoidable determinants disputed
- Identification of all / or important determinants ??
- Avoidability / unavoidability may be continuous rather than categorical
- Measuring determinants is inexact...at best.
- Ethical – Inequity judgement is subjective

**Notes:**
There are a number important limitations to this conceptual model for measuring disparity.

Philosophical differences exist as to whether any determinants of health should be considered unavoidable.  Some also feel that all inequalities constitute inequities

Practical limitations include our ability to identify relevant determinants for specific diseases, and how these may vary across populations.

Empirical linkage between some determinants and health status has been made, but remains imprecise.  Some determinants of health are categorical – such as gender.  Others are probably continuous, such as culture and freely-chosen behavior, that are to a large extent unavoidable, but which may have an avoidable component.

Finally, ethics are a  subjective matter, and a judgement of what is inequitable will depend as much on who judges as how the judgement is made. 

## Limitations

- _Therefore_.......
- No way to distinguish (accurately)
- Inequality from Inequity
- So, we’re not reducing Disparity, but rather Inequality

**Notes:**
Although we may be able to conceptualize a detailed framework of the components of disparity, our ability to distinguish inequality from inequity is lacking.

What remains, from my point of view, is not measurement of and elimination of inequity.  Instead, at this point, all we can really do with confidence is to measure and reduce inequality.

## Conclusions

- Disparity...not so simple after all !!
- Inequality   ==   Inequity
- Complex interactions of ...
- Genetics
- Environment (physical, social, economic)
- Behavior

**Notes:**
In closing, if Disparity and its measurement is viewed broadly – inclusive of determinants of health, and the recognition of the difficulty of making objective, or even reasonable judgments about what is unfair or unacceptable – it should be apparent that it is not so simple at all.

It should be kept in mind that Inequality is not the same thing as Inequity.  As discussed earlier they should be seen as different in application to public health.   Popular usage and application of the term Disparity, as well as revised dictionary definition, indicates that it spans both inequality and inequity. 

Effective methods to reduce and eliminate all disparities do not exist.  Functional pathways leading to health disparities are directed by a complex interactions of Genetics, the Environment, Behavior, and other health determinants.  Although the ability to measure these is improving, the understanding of how they interact is only beginning to be understood.

## Conclusions

- Incomplete knowledge  ==  Inaction !
- Purposes of measurement
- Monitoring and Assessment
- Intervention and Improvement Programs
- P.D.G. affects choice of statistics

**Notes:**
Even though we do not fully understand the role of determinants of health, how to precisely measure them, or how to separate avoidable from unavoidable inequality ---reduction in Inequalities must be pursued vigorously.

From the slide showing Disparity between populations, recall that Total Disparity was greater (57 %) than Inequity (46 %).  So, even without knowing what is unavoidable, progress can be made.  But without knowing what part is unavoidable, we cannot know when Inequity and Disparity have been eliminated.

The function of measuring Disparity may be in terms of a more passive way such as in Monitoring how different groups are, or actively as part of an Intervention program.  Realizing though, that implicit in Intervention is an ethical judgment of “How things should be”

Finally, the choice of statistics to measure Disparity depend on the philosophical approach (or purpose), Data type or demographic group, and goal.