BEPH_lesson05.pdf

Lesson 5 Types of epidemiological studies and models of causality Biostatistics, Epidemiology and Public Health Prof. Eugenia García Zaragozá, PhD Bachelor in Dentistry ACADEMIC YEAR 2023-2024 ÍNDICE TABLE OF CONTENTS CONTENIDOS 1. Epidemiology: definition 2. The history of epidemiology 3. Causa...

Lesson 5 Types of epidemiological studies and models of causality Biostatistics, Epidemiology and Public Health Prof. Eugenia García Zaragozá, PhD Bachelor in Dentistry ACADEMIC YEAR 2023-2024 ÍNDICE TABLE OF CONTENTS CONTENIDOS 1. Epidemiology: definition 2. The history of epidemiology 3. Causal inference in epidemiology 4. Descriptive epidemiology: Person, time and place The concept of population Epidemiological variables Measurement of disease frequency: Incidence and Prevalence 5. Types of studies in epidemiology 2 1. Epidemiology: “The study of the occurrence and distribution of health-related states or events in specified populations, including the study of the determinants influencing such states, and the application of this knowledge to control the health problems” Dictionary of Epidemiology, 2008 Epidemiology is the basic science of public health 3 1. Epidemiology: Types or strategies 1. DESCRIPTIVE EPIDEMIOLOGY: Estimates the magnitude or frequency of the state of health and its distribution in a defined population, in relation to the characteristics of person, place and time. 2. ANALYTICAL EPIDEMIOLOGY: Raises and tests hypotheses about the causal relationships between health phenomena and their determinants. 4 2. The history of epidemiology Seven land marks 5 3. Causal inference in epidemiology Causality 6 3. Causal inference in epidemiology Causality 7 3. Causal inference in epidemiology Causality The observed association may be due to the effects of: •Chance (random error) •Bias (systematic error) •Confounding ➢ Observed statistical association between a risk factor and a disease does not necessarily lead us to infer a causal relationship ➢The absence of an association does not necessarily imply the absence of a causal relationship 8 3. Causal inference in epidemiology Causal criteria 9 10 3. Causal inference in epidemiology Causal models 11 3. Causal inference in epidemiology Causal web 12 3. Causal inference in epidemiology Causal pies 13 3. Causal inference in epidemiology Causal models 14 3. Causal inference in epidemiology Graphical models 15 3. Causal inference in epidemiology Counterfactual model 16 4. Descriptive Epidemiology Definition Estimates the magnitude or frequency of the state of health and its distribution in a defined population, in relation to the characteristics of person, place and time. WHO WHERE WHEN WHAT 17 4. Descriptive Epidemiology Person, time and place 18 4. Descriptive Epidemiology Person, time and place 19 4. Descriptive Epidemiology The concept of population 20 4. Descriptive Epidemiology Epidemiological variables 21 4. Descriptive Epidemiology Epidemiological variables Number of new health-related events in a defined population within a specified period of time. It may be measured as a frequency count, a rate or a proportion Total number of individuals who have an attribute or disease divided by the population at risk of having that attribute or disease 22 4. Descriptive Epidemiology Relationship between prevalence, incidence and duration of disease 23 4. Descriptive Epidemiology Measurement of disease frequency: Incident times 24 4. Descriptive Epidemiology Measurement of disease frequency: Incident rates per time period 25 4. Descriptive Epidemiology Measurement of disease frequency: Prevalence 26 4. Descriptive Epidemiology Measurement of disease frequency: Prevalence 27 https://www.youtube.com/watch?v=cTp_ONVVrh8 28 5. Types of studies in Epidemiology Definitions 29 5. Types of studies in Epidemiology Definitions 30 5. Types of studies in Epidemiology Definitions 31 5. Types of studies in Epidemiology Definitions 32 5. Types of studies in Epidemiology 33 Remember ❑ ❑ ❑ DESCRIPTIVE EPIDEMIOLOGY estimates the distribution of a disease in a population in terms of PERSON, TIME and PLACE. Main epidemiological variables are INCIDENCE (new cases or risk of disease) and PREVALENCE (existing cases or burden of disease) ANALYTICAL EPIDEMIOLOGY tries to infer a causal relationship between a risk factor and an outcome. Satisfaction of the 9 Hill’s CAUSAL CRITERIA may lead to causation, but not satisfying them may not necessarily provide evidence against causality. Only TEMPORALITY is a necessary condition for determinig that an observed association is causal 34 REFERENCIAS BIBLIOGRAPHY BIBLIOGRÁFICAS -Merrill R.M., Introduction to Epidemiology, 2017, Seventh Edition. Chapter 2. Historic development in Epidemiology. https://samples.jbpub.com/9780763766221/66221_CH02_5398.pdf - Vineis P. and Kriebel D. Commentary: Causal models in epidemiology: past inheritance and genetic future. Environmental Health, 5:21, 2006, doi:10.1186/1476-069X-5-21 - Somerville M., Kumaran K., Anderson R. Public Health and Epidemiology at a Glance, First Edition. 2012. John Wiley & Sons, Ltd 35 Prof. Eugenia García Zaragozá, PhD [email protected] UCAM Universidad Católica de Murcia © © UCAM UCAM