1. Epidemiological Approach
Prepared by I Gede Purnawinadi, S.Kep., Ns., M.Kes., CWCCA.

2. Epidemiological approach to a health problem
DESCRIPTIVE STAGE
Define
What is the problem?
Quantify
How many are affected?
Describe
Who is affected, Where and When does the problem occur?
ANALYTICAL STAGE
Analyze
But Why? How?
Identify causing factor(s)
What are the possible causes?
INTERVENTION STAGE
Design intervention
So what? Which intervention(s)?
Implement and evaluate intervention
Did it help?
DETERMINANTS

3. Teori Gordon

4. DETERMINANTS OF HEALTH
M. Roemer, 1993
CHARACTERISTIC
OF INDIVIDU:
Age, Sex, immunity,
Genetic, Background,
Habit, etc.
SOCIAL
ENVIRONMENT:
Education, Occupation,
Income, Relationships,
Urbanization, etc.
PHYSICAL
ENVIRONMENT:
Geography, Climate,
Housing, Food,
Water, etc.
HEALTH
STATUS:
Physical, Mental,
and Social
Well being
HEALTH SERVICES:
Promotion, Prevention, Protection,
Treatment, Rehabilitation, etc.

5. DETERMINANTS OF HEALTH Janelle Nichols

6. DETERMINANTS OF HEALTH (HL. Blum, 1981)
Heredity
Health
Status
Medical
Service
Environment
Life Style

8. Basic Epidemiology: Evaluating Quality of Evidence
Association vs. causality: criteria for causality
Epidemiological studies provide evidence for an association between an exposure and an outcome.
In 1965 Sir Austin Bradford Hill composed a list of criteria to help evaluate whether an observed association between an exposure and an outcome is likely to be causal. These are now commonly known as the Bradford Hill criteria. Although none of the criteria alone can prove that a relationship is causal, used together, they can help make an overall judgement about whether a causal relationship is likely.

9. The Bradford Hill criteria

11. Types of studies are used in epidemiology

13. Association vs. Causality
When interpreting findings from an epidemiological study it is essential to also consider whether an observed association between an exposure and an outcome is causal. To do this, we should explore whether there are other potential explanations for the association.
These explanations can include:
random error (chance)
systematic error in the way in which the study was conducted (bias)
confounding

14. Ratio Measures
Ratio Measures