Epidemiological Approach

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Presentation transcript:

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

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

Teori Gordon

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.

DETERMINANTS OF HEALTH Janelle Nichols

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

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.

The Bradford Hill criteria

Types of studies are used in epidemiology

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

Ratio Measures Ratio Measures