DESCRIPTIVE EPIDEMIOLOGYDESCRIPTIVE EPIDEMIOLOGYfor Public Health Professionals for Public Health Professionals

Part 1Part 1

Ian R.H. Rockett, PhD, MPHDepartment of Community Medicine

West Virginia University School of Medicine

Prepared under the auspices of the Prepared under the auspices of the Southeast Public Health Training Southeast Public Health Training Center, University of North Carolina, Center, University of North Carolina, Chapel Hill, 2005.Chapel Hill, 2005.

irockett@hsc.wvu.edu

Learning ObjectivesLearning Objectives

1.1. To introduce some key historical contributors To introduce some key historical contributors to the evolution of epidemiologyto the evolution of epidemiology

2.2. To present basic models of disease and injuryTo present basic models of disease and injury

3.3. To address data sources, classification, and To address data sources, classification, and measurementmeasurement

4.4. To build a bridge between descriptive and To build a bridge between descriptive and analytic epidemiologyanalytic epidemiology

Performance ObjectivesPerformance Objectives

1.1. To be sensitive to the history of epidemiology To be sensitive to the history of epidemiology against the background of broad population against the background of broad population changechange

2.2. To identify mortality and morbidity data sourcesTo identify mortality and morbidity data sources

3.3. To calculate basic measuresTo calculate basic measures

4.4. To generate hypotheses from descriptive dataTo generate hypotheses from descriptive data

POPULATION TRANSITIONS POPULATION TRANSITIONS

and and HISTORYHISTORY

The Big Population Picture

Source: Joseph A. McFalls, Jr. Population: A Lively Introduction. Third edition. Population Bulletin 53(3); 1998: 38.

The Demographic Transition

The demographic transition framework illustrates population growth in terms of discrepancies and changes in two crude vital rates – mortality and fertility (ignores the third component of growth, migration)

Source: Joseph A. McFalls, Jr. Population: A Lively Introduction. Third edition. Population Bulletin 53(3); 1998: 39.

Top 10 Causes of Death in the U.S. , 1900Rank Cause of Death Deaths per

100,000 Percent of all Deaths

1 Pneumonia 202 12 2 Tuberculosis 194 11 3 Diarrhea and enteritis 140 8 4 Heart disease 137 8 5 Chronic nephritis

(Bright’s disease) 81 5

6 Unintentional injury (accidents)

76 4

7 Stroke 73 4 8 Diseases of early

infancy 72 4

9 Cancer 64 4 10 Diptheria 40 2

Top 10 Causes of Death in the U.S. , 2000Rank Cause of Death Deaths per

100,000 Percent of all Deaths

1 Heart Disease 258 30 2 Cancer 200 23 3 Stroke 60 7 4 Lung Diseases 45 5 5 Unintentional injury

(accidents) 34 4

6 Diabetes 25 3 7 Pneumonia and

influenza 24 3

8 Alzheimer’s Disease 18 2 9 Nephritis, Kidney

disease 14 2

10 Septicemia 12 1

Source: Ian R.H. Rockett. Population and Health: An Introduction to Epidemiology. Second edition. Population Bulletin 54(4); 1999: 9.

EPIDEMIOLOGYepi – upon

demos – people

logos – study

The scientific study of the distribution and determinants of health-related states or events in specified populations, and the application of resulting knowledge to the prevention and control of health problems

Epidemiology as a Liberal Art

An accessible low-technology science, which incorporates the “scientific method, analogic thinking, deductive reasoning, problem solving within constraints, and concern for aesthetic values”

David Fraser, New England Journal of Medicine, 316(6); 1987:309-314.

Some Epidemiologic History

HippocratesHippocrates

On Airs, On Airs, Waters, and Waters, and Places (5Places (5thth century BCEcentury BCE)

Hippocrates spearheaded a move away from looking to blame demons for disease and injury

FAST FORWARDFAST FORWARD

Enter John Graunt (1629-1674)

vocation – haberdasher (seller of men’s accessories)

avocation – father/founder of demography and epidemiology

Graunt counted rather than considered (Major Greenwood)

Among his observations, he noted:

regularity of biological phenomena in the mass

that more males are born than females and more males die

than females (annually)

Partial Translation

Ague = Malaria

Purples & Spotted Feaver = Meningococcal Meningitis

King’s Evil = Tuberculosis of the lymph glands of the neck

Age

17th century

2002

London, England

United States

0 100 100 6 64 99 16 40 99 26 25 98 36 16 97 46 10 95

56 6 91 66 3 81 76 1 63

Population Survivorship: Two Populations

Miasmatists Vs Contagionists

miasm – pathogenic emanation dispersed in the atmosphere

(malaria – bad ‘air’)

contagion – vehicle of person-to- person disease transmission (forerunner of germ theory)

EnterEnter JohnJohn Snow (1813-1858)Snow (1813-1858)

Spot Map of Fatal Cholera Cases in London, 1854

Source: Ian R.H. Rockett. Population and Health: An Introduction to Epidemiology. Second edition. Population Bulletin 54(4); 1999: 6.

Filippo Pacini, 1812-1883Filippo Pacini, 1812-1883