Descriptive Epidemiology
Principles of Epidemiology Lecture 6
Dona Schneider, PhD, MPH, FACE
Objectives of Descriptive Epidemiology
To evaluate trends in health and disease and allow comparisons among countries and subgroups within countries To provide a basis for planning, provision and evaluation of services
To identify problems to be studied by analytic methods and to test hypotheses related to those problems
Epidemiology (Schneider)
Descriptive Studies
Relatively inexpensive and less time-consuming than analytic studies, they describe
Who gets sick and/or who does not Where rates are highest and lowest Temporal patterns of disease Seasonality Secular trends which are affected by
Changes Changes Changes Changes Changes
in in in in in
diagnostic techniques the accuracy of the denominator data the age distribution of the population survival from improved treatment or disease mutation actual disease incidence
Epidemiology (Schneider)
Forecast of Cancer Deaths
600 500 510 443 382 268 211 41 65 85 118 158 311
Thousands of Deaths
400 300 200 100 0
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 Years
Forecast of cancer deaths if present trends continue (Data from the American Cancer Society)
Cancer Death Rates by Site, United States, 1930-87
Figure 5-1. Cancer death rates by site, United States, 1930-1987. Source: American Cancer Society (1991).
Possible Reasons for Changes in Trends
Artifactual
Errors in numerator due to
Changes in the recognition of disease Changes in the rules and procedures for classification of causes of death Changes in the classification code of causes of death Changes in accuracy of reporting age at death Errors in the denominator due to error in the enumeration of the population
Epidemiology (Schneider)
Death Rates for Individuals with Diabetes
Figure 3-27. Drop in death rates for diabetes among 55 to 64 year old men and women, United States, 1930-1960, due to changes in ICD coding. (From US Public Health Service publication no. 1000, series 3, No. 1. Washington, DC, US Government Printing Office, 1964.)
ICD-10
International Classification of Disease (ICD) 10th Revision
ICD-10
has 8,000 categories vs. only 4,000 for
ICD-9
ICD-10
uses 4 digit alphanumeric system where ICD-9 uses 4 digit numeric system only (much more detail available with ICD-10) for coding simplified create discontinuities!
Rules Will
Epidemiology (Schneider)
ICD-10 (cont.)
Notable improvements in the content and format of ICD-10 include:
The addition of information relevant to ambulatory and managed care encounters Expanded injury codes
The creation of combination diagnosis/symptoms codes to reduce the number of codes needed to fully describe a condition
Greater specificity in code assignment
Epidemiology (Schneider)
ICD-10 (cont.)
At present ICD-10 is widely used in Europe In the US, however, migration to ICD-10 is complicated by the fact that ICD-9-CM is embedded in hospital billing systems
NCHS developed a timeline to have ICD-10CM in use for morbidity diagnoses by 2001
Epidemiology (Schneider)
Possible Reasons for Changes in Trends (cont.)
Real
Changes in age distribution of the population Changes in survivorship
Changes in incidence of disease resulting from
Genetic factors Environmental factors
Epidemiology (Schneider)
Infant Mortality Rates by Race
Figure 3-3 Infant mortality rates by race: United States, 1950-1991. Source: Reprinted from National Center for Health Statistics, Advance Report of Final Mortality Statistics, 1991, Monthly Vital Statistics Report, Vol. 42, No. 2, p. 11, 1993.
Case Reports
Case reports (case series) – report of a single individual or a group of individuals with the same diagnosis
Advantages
You can aggregate cases from disparate sources to generate hypotheses and describe new syndromes
Example: hepatitis, AIDS, “pool fingers”
Limitations
You cannot test for statistical association because there is no relevant comparison group
Epidemiology (Schneider)
Cross-Sectional Studies
Cross sectional studies or prevalence studies measure disease and exposure simultaneously in a well-defined population
Advantages
Prevalence studies cut across the general population, not simply those seeking medical care
They are good for identifying the prevalence of common outcomes, such as arthritis, blood pressure or allergies You cannot determine whether exposure preceded disease
Limitations
Since you determine prevalent rather than incident cases, results will be influenced by survival factors
Remember: P = I x D
Factors Influencing Prevalence
Increased by:
Longer duration of the disease Prolongation of life of patients without cure Increase in new cases (increase in incidence) In-migration of cases
Decreased by:
Shorter duration of disease High case-fatality rate from disease
Decrease in new cases (decrease in incidence) In-migration of healthy people
Out-migration of healthy people In-migration of susceptible people Improved diagnostic facilities (better reporting)
Out-migration of cases Improved cure rate of cases
Prevalence of Congenital Malformations Across Maternal Age
Prevalence of Cigarette Smoking Among Successive Birth Cohorts
Comparing Cross-Sectional and Longitudinal Data
How you organize your data depends on your research question.
Cross Sectional Data
Cohort or
Longitudinal
45
40
A
B
B
C
C
D
D
E
E
F
Data
35 30
25
C D
E
D E
F
E F
G
F G
H
G H
I
1955
1960
1965
1970
1975
Year of Examination
30 Year Olds in Successive Years
Correlational Studies
Correlational studies (ecological studies) use measures that represent characteristics of entire populations (areal aggregates) to describe outcomes in relation to some factor of interest such as age, time, utilization of services, or exposures ADVANTAGES
You can generate hypotheses for case-control studies and environmental studies
You can target high-risk populations, timeperiods, or geographic regions for future studies
Epidemiology (Schneider)
Correlational Studies (cont.)
LIMITATIONS
Because data are for groups, you cannot link disease and exposure in individuals
Example: Percentage of teenagers taking drivers education and fatal teenage car accidents study done by National Safety Council
You cannot control for potential confounders Data represent average exposures rather than individual exposures, so you cannot determine a dose-response relationship Caution must be taken to avoid drawing inappropriate conclusions, or ecological fallacy
Epidemiology (Schneider)
Breast Cancer Mortality and Dietary Fat Intake