# Presentation: 763595

## Epidemiology WorkshopOak Ridge Reservation Health Effect SubcommitteeJune 12, 2001

***Sherri Berger, MSPH***
***Lucy Peipins, PhD***
***Division of Health Studies***

## Workshop Outline

**What is Epidemiology and How is it Used?**
**Measures of Disease Frequency and Association**
**Measuring Exposure and Adverse Health Effects**
**Judging a Cause-Effect Relationship**

## Workshop Objectives

**Basic epidemiology concepts.**
**The importance of good measurement of exposure and disease.**
**When is an epidemiologic study appropriate?**

## What is Epidemiology?

**The study of the distribution and determinants of disease in populations.**
**(J. Last, Dictionary of Epidemiology, 1983)**

## Epidemiology: The Science of Public Health

**Three key aspects:**
**groups of people,**
**measurement, **
**comparison, **

## What Can Epidemiology Do?

**Determine the impact of disease in groups of people.  **
**Detect changes in disease occurrence in groups of people. **
**Measure relationships between exposure and disease.**
**Evaluate the efficacy of health interventions and treatments.**

**Notes:**
Number of cases in a city, county, state, etc of a particular disease

## What Can’t Epidemiology Do?

**Cannot tell an individual the cause of his or her disease.**
**One study cannot prove a particular exposure caused an illness.**
**Should not be conducted without good measurement of exposure and disease.**

## How Science Works

**Every epidemiologic study and every analysis is built on a body of knowledge and is done to expand that body of knowledge**

- Animal studies

- Case Reports

- Epidemiologic study

- Toxicologic Models

- Epi Study

- Epidemiologic study

- Is there a relationship between a particular exposure and a disease?

**Notes:**
Each study is a response to a body of knowledge and is done to expand that knowledge base

The knowledge base can be made up of case studies, animal studies, toxicological models, descriptive epidemiolgic studies and other analytic studies

This knowledge base determines what other studies need to be done – whether on what new population,or using new outcome measures, or using a different study design.  The study base also determines, to a great extent how the new data will be analyzed and interpreted.

(Example of EMF and lack of biological mechanism)

## Common Steps in Establishing a Relationship Between Exposure and Disease

**Physician reports series of cases **
**Descriptive analyses describe what is the problem, who is affected and where disease is occurring**
**Analytic studies test the exposure-disease hypothesis in a study group**
**Disease experimentally reproduced by exposure in animal studies**
**Observation that removing exposure lowers disease**

## Measures of Disease Frequency

**The most basic measure of disease frequency is a simple count of affected individuals.**
**	****	**
**	****However, counting is not enough!**
** **

**Why is a simple count not enough?**
**3 cases of cancer per year from a city of 1,000 people is very different than 3 cases per year from a city of 100,000 people**

**So, in epidemiology we must know:**
** **
**the size of the population from which the affected individuals come, and**
**the time period the information was collected.**

## Basic Measure of Disease Frequency

**Rate **
**an example: Incidence**

## Rate

**basic measure in epidemiology**
**the frequency with which an event occurs in a group of people**
**used to compare the occurrence of disease in different groups**

## Example: Rates

- Rate = _Number of events in a specified time period_
- 		       Average population during the time period
- ***the measure of time is a critical part of a rate!
**Such as, the number of newly diagnosed cases of breast cancer per 100,000 women during 1999.**

## Common Rates

_**mortality (death) rate**_** is the number of deaths in a defined group of people  during a specified time period.**
_**birth rate**_** is the number of live births in a defined group of people over a specified time period.**

## Incidence

**a type of rate**
**the number of new cases that develop in a group of individuals during a specific time period**

## Incidence (cont.)

- I =  _number of new events during a period of time_
- 		number of persons at risk during this time period

## Example: Incidence

**If there were 150,00 new cases of lung cancer in the United States during 1997, the incidence rate would be:**
- 	(150,000/260,000,000) = 0.000058
- 		0.000058 x 100,000 people
- 	= 58 cases per 100,000 people, per year

## Measures of Association

**How much greater the frequency of disease is in one group compared with another.**
** **
**Often presented in the form of a two-by-two table.**

## Two-By-Two Table

| a | b |
| --- | --- |
| c | d |

-     Disease
- Yes           No

- 		Yes
-     Exposure
-                          		No

- Total             a+c              b+d

- Total
- a+b
- c+d

- a+b+c+d

## Hypothetical Two-By-Two Table

| 70 | 300 |
| --- | --- |
| 15 | 700 |

-     Lung cancer
- Yes           No

- 		Yes
-     Smoking
-                          No

- Total             85              1,000

- Total
- 370
- 715

- 1,085

## Relative Risk (RR)

**Measures how likely the exposed group will develop a disease compared to the unexposed group.**
** **
**RR**** = ****	**_incidence in the exposed      _   = 	_a/(a+b)_
- 			incidence in the unexposed      		c/(c+d)

## Example: Hypothetical Study

|  |  | Lung cancer |  |  |
| --- | --- | --- | --- | --- |
|  |  | Yes | No | Total |
|  | Yes | 70 | 300 | 370 |
| Smoking | No | 15 | 700 | 715 |
|  | Total | 85 | 1,000 | 1,085 |

- Relative Risk = 	_70/(70+300)_   = 	9.0
- 				 15/(15+700)
**Which means...  participants who smoked were 9 times more likely to develop lung cancer than those who did not smoke.**

## Interpreting Measures of Association

**RR of 1.0 indicates that the occurrence of disease in the exposed an unexposed groups are identical:**
**No association observed between exposed and unexposed groups.**

## Interpreting Measures of Association (Continued)

**RR greater than 1.0 indicates a positive association, or an increased risk among the exposed.**
**RR less than 1.0 means that there is a decreased risk among the exposed group.**

## Standardized Mortality Ratios (SMRs)

**the ratio of the observed number of deaths to the expected number of deaths**
**a standard group of people is used to determine the expected number of deaths **
**the standard is often the US population, a state, or a county.**
**serves as the comparison group**
**	**

## SMRs (Continued)

**Calculation:**
- SMR = 	_observed deaths_
- 			expected deaths

## Example: Study of Smoking and Lung Cancer

**Our hypothetical study found 58 lung cancer deaths between 1948 and 1963:****  **
**based on US population rates, we know that 42.9 cancer deaths were expected in a similar population.**
- 				SMR = (58/42.9) =1.35
** **
** **

## Example: Study of Smoking and Lung Cancer (cont.)

**Our study group  had a risk of cancer mortality approximately 35% greater than those in the general population.**

## Measuring Exposure and Measuring Outcomes inEnvironmental Epidemiology 

**Contaminants in air, water, food, or soil come in contact with people through swallowing, breathing, or skin contact**
**Once the contaminant gets in the body, it can act at that point of entry or can be distributed throughout the body where it can act upon a target organ or organs**

## Measuring Exposure

**We can measure exposures or their surrogates along the entire path from emissions to body burden**
**	****Types of Data****	****	****	****	****Approximation to actual exposure**
**_________________________________________________________________________**
**1) Residence in a defined geographical ****	****	****	****Poorest**
**area (e.g. county) of a site****	****	****	****	****	****     |**
**2) Residence in a geographical area in ****	****	****	****     |**
**proximity to to a site where exposure is assumed****	****	****     |**
**3) Distance **_**or**_** duration of residence****	****	****	****	****     |**
**4) Distance **_**and**_** duration of residence****	****	****	****	****     |**
**5) Quantified surrogate of exposure (e.g. estimate****	****	****     |**
**of drinking-water use****	****	****	****	****	****     |**
**6) Quantified area measurements in vicinity of the ****	****	****     |**
**residence ****	****	****	****	****	****	****     |**
**7) Quantified personal measurement****	****	****	****	****Best****	**
**	****	****	****Baker D, et al., Environmental Epidemiology: A Textbook on Study Methods and Public Health Applications, 1999****	****	****	**

## What is an Outcome or Adverse Health Effect?

**Any change in health status or body function.**
**Wide spectrum of effects such as wheezing, change in immune function, changes in blood chemistry, DNA adducts, adverse birth outcomes, developmental disabilities, clinical disease and death**

## These changes can be...

## What Outcomes Do We Look For? Biologically plausible outcomes

**Contaminant****	****	****	****Target Organ System**
**Route of exposure **
**	**
**Toxicity or level****	****	****     Severity of Outcome**
**Alternative explanations****	****	****	****Confounding**
**	****	****	****               ****	****	**

## Health Effects are Not Uniquely Caused by Environmental Exposures

**25% of all pregnancies result in spontaneous abortions**
**2% of infants are born with developmental deformities**
**Among men, 1 in 2 will develop cancer in their lifetime (1 in 3 for women)**
**8-10% of children have asthma**

## Cancer

**Smoking is the leading cause of cancer in the U.S.**
**25% of Americans currently smoke**
**Can be a very long time between exposure and the development of disease – many exposures over that time**
**Cancer is not 1 disease – it is thought to be over 100 different disease in 40 anatomic sites**

## Measuring Adverse Health Effects

**Goal: to count *****all***** the cases in a particular exposed group or population and compare it with cases in an unexposed group or population**
**Where do we get this information?**

**Notes:**
In order to conduct a study, we need to count all the cases that have occurred in the exposed and unexposed population.  

## Data Sources

**death certificates**
**birth certificates**
**medical exams**
**hospital discharge data**
**questionnaires**
**disease registries**
**laboratory tests or biomarkers**

**Notes:**
We know the contaminant and we know from previous studies or animal data what health effect we might expect.  Let’s move on to where we might find information for measuring this adverse health effect?

## Data Sources:  Four Considerations

**Severity of illness**
**Accuracy of measuring disease-misclassification of the outcome**
**Availability of information on confounders or other risk factors**
**Cost and complexity and invasiveness**

**Notes:**
Each of these data sources has limitations.  Many have more than one.   Here are 4 (and there are more) considerations or constraints that these data sources force up us.  

## Death Certificates

**Readily available **
**not all conditions of interest result in death **
**considerable inaccuracy in diagnosis (error in major disease category is 25%, error within categories is 25%) **
**no data on other risk factors**

**Notes:**
This information is readily available.  Every state has a vital statistics department.  

##                    Registries

**Registries of reportable diseases such as TB, cancer, birth defects.  **
**Cancer incidence data is available for all states.  **
**No information on other risk factors.  **
**Completeness and timeliness may be an issue.      **

## Medical Exams and Biologic Tests

**Generally regarded as the “gold standard”**
**However, physician diagnosis may vary for outcomes with no standard case definition**

## Questionnaires

**May miss most severe outcomes**
**Some outcomes may only be measured through a questionnaire**
**Self-reports of illness or symptoms**** **

## Questionnaires, (cont.)

**Wording or type of administration may influence responses**
**Can collect data on other risk factors**
**Subject to recall and response bias**

## Measuring Outcomes: Other Considerations

**Timing and latency:  especially important in chronic disease**
**Individual variability by:  age, gender, pre-existing illnesses, genetic predisposition**
**Confounding and bias:  What are alternative explanations for the exposure-disease association? **

## Summary: Measuring Health Outcomes and Exposures

**The closer we can get to a measure of dose in the body, the more precise our exposure estimate will be.**
**Characteristics such as age or pre-existing illness modify or determine the health effects we might see.  **
**Sources of data on health effects and exposures are varied. **

## Basic Criteria for Considering a Health Study

**We need:**
**An exposure that can be measured.**
**A completed pathway.**
**An exposed population.**
**A measurable effect that is plausibly related to the exposure.**

## Basic Criteria for Considering a Health Study

**Will the epidemiologic study we are planning advance our knowledge about the relationship between exposure and disease?**

## How to Judge a Cause-Effect Relationship

**You’re given a paper that reports the results of a study, how do you interpret this study?**

## Strength of Association

**example: Relative Risk (RR)**
**the larger the risk, the more likely the relationship exists **
**less likely it is due to other factors, such as confounding**

## Consistency of Findings

**Has this association been seen with other studies, with other study designs, and in different groups of people?**
**If so, this strengthens the findings**

## Dose-Response Relationship

**As exposure increases, does the risk of disease increase?**

## Time Sequence

**the exposure MUST occur before the disease develops**
**this is an essential criteria**

## Biologic Plausibility

**does this make biologic sense?**
**is there a known mechanism by which an exposure can lead to disease?**

## Biologic Plausibility (cont.)

**Example: daily consumption of fatty foods increases risk of heart disease **
**there is a biologic mechanism **
**fatty foods raises LDL cholesterol, which increases the risk of heart disease**

## In Conclusion...

**these are not hard and fast rules (except time sequence)**
**there can be exceptions!**
**These tools help us judge the scientific literature – have the authors convinced us?**

**Epidemiology is an excellent tool if used correctly!**
**Joseph Mangano ******** Cancer Mortality near Oak Ridge, Tennessee**

**Notes:**
Epidemiology has received a great deal of criticism in recent years- some warranted, some not.  It is an excellent tool if used correctly.  In many cases, epidemiology has not been used correctly.  You cannot blame the hammer for not doing a good job cutting a board.