Week 3: Epidemiological Research Design
Learning Objectives:
Description & Comparison of the strengths and weaknesses of the common epidemiologic
study designs
Classification & Basic characteristics of research methods
Evaluation of Levels of evidence
Interpretation of the study validity & the impact of bias, confounding, reliability and effect
modification on causal inference in epidemiologic research
Critical appraisal of epidemiologic research
Contents
Introduction ............................................................................................................................................ 1
Study Design ........................................................................................................................................... 3
Experimental studies........................................................................................................................... 3
Randomized Controlled Trial (RCT) ..................................................................................................... 4
Observational studies ......................................................................................................................... 5
Cohort study.................................................................................................................................... 5
Case-control study .......................................................................................................................... 7
Cross-sectional study ...................................................................................................................... 8
Basic research methodology and relevant design considerations ....................................................... 10
Hierarchy of evidence ........................................................................................................................... 12
Validity in Study Designs ....................................................................................................................... 14
Internal Validity ................................................................................................................................. 15
Selection bias ................................................................................................................................ 15
Information bias ............................................................................................................................ 17
, Confounding .................................................................................................................................. 19
Effect modification or Interaction................................................................................................. 21
Reliability....................................................................................................................................... 22
External Validity ................................................................................................................................ 24
Critical appraisal of epidemiological research ...................................................................................... 24
Applicability of epidemiological evidence/research in public health practice and policy................ 27
References ............................................................................................................................................ 29
,Introduction
The key consideration of descriptive epidemiology – shown in Week 1 and Week 2- is
evaluation of frequency and pattern of health outcome by examining the person, place, and
time in relation to health outcome. Analytical epidemiology builds up on it and uses data
gathered by descriptive epidemiology as to look for patterns suggesting causal relationships.
It has been said that epidemiology by itself can never prove that a particular exposure caused
a particular outcome. It is because establishing an association does not necessarily mean that
the exposure is a cause of the outcome, i.e. that it is something that has an effect or a
consequence. Still, establishing a valid association between exposure and outcome is a
necessary first step that must be accomplished before assessing whether the relationship is
causal. Since a determination that a relationship is causal is a judgment, there is often
disagreement, particularly since causality often implies some degree of responsibility for the
outcome, or may create a demand for public health action, and this often has legal and financial
consequences (LaMorte 2019a).
Irrespective of whether epidemiologists aim to study occurrence and distribution of diseases
and health outcomes or they plan to further examine associations or hypothesized causal
relationship between a particular exposure and a particular outcome, a first step is to define
the hypothesis based on the research question and decide which study design will be best
suitable to answer that research question. In Week 3 we will learn about study designs. In
continuation, we will define research methodology which is the way in which data are
collected and analysed (Fink 2012, p. 301). We will also define levels of evidence (hierarchy
of evidence) which are assigned to studies based on the methodological quality of their
design, validity, and applicability. Additionally, we will pay special attention to the concept
of validity, which highlights the need to eliminate or minimize the effects of extraneous
influences, variables, and explanations that might detract from a study’s ultimate findings.
1
, Finally, having these terms understood, one will be able to undertake a critical appraisal of
epidemiological research, that is to accurately assess the quality and relevance of evidence
presented in a paper and its applicability to decision making and recommendations in (public)
health practice.
Before embarking further into Week 3 topic, please find below terminology essential to
understanding of the concepts relevant to Week 3 (some terms were already introduced in
Week 2):
Baseline: The amount of a particular disease that is usually present in a community is referred
to as the baseline- note that it is the observed level and not necessarily zero (Dicker 2006).
Source population: the population out of which the cases arose.
Incident case: a person who is newly diagnosed as a case.
Prevalent case: a person who has a health outcome of interest that was diagnosed in the past.
Cause: To be a cause, the factor: i) must precede the effect, ii) can be either a host or
environmental factor (e.g., characteristics, conditions, actions of individuals, events, natural,
social or economic phenomena) and iii) may be positive (presence of a causative exposure) or
negative (lack of a preventive exposure) (LaMorte 2019a).
Random allocation: each subject under study has an equal chance of being assigned to any one
of the exposures.
Reliability: Implies that the same data would have been collected each time over repeated tests/
observations (not to be confused with accuracy).
Internal Validity: the extent to which the observed results represent the truth in the population
we under study and, thus, are not affected by methodological errors.
2
Learning Objectives:
Description & Comparison of the strengths and weaknesses of the common epidemiologic
study designs
Classification & Basic characteristics of research methods
Evaluation of Levels of evidence
Interpretation of the study validity & the impact of bias, confounding, reliability and effect
modification on causal inference in epidemiologic research
Critical appraisal of epidemiologic research
Contents
Introduction ............................................................................................................................................ 1
Study Design ........................................................................................................................................... 3
Experimental studies........................................................................................................................... 3
Randomized Controlled Trial (RCT) ..................................................................................................... 4
Observational studies ......................................................................................................................... 5
Cohort study.................................................................................................................................... 5
Case-control study .......................................................................................................................... 7
Cross-sectional study ...................................................................................................................... 8
Basic research methodology and relevant design considerations ....................................................... 10
Hierarchy of evidence ........................................................................................................................... 12
Validity in Study Designs ....................................................................................................................... 14
Internal Validity ................................................................................................................................. 15
Selection bias ................................................................................................................................ 15
Information bias ............................................................................................................................ 17
, Confounding .................................................................................................................................. 19
Effect modification or Interaction................................................................................................. 21
Reliability....................................................................................................................................... 22
External Validity ................................................................................................................................ 24
Critical appraisal of epidemiological research ...................................................................................... 24
Applicability of epidemiological evidence/research in public health practice and policy................ 27
References ............................................................................................................................................ 29
,Introduction
The key consideration of descriptive epidemiology – shown in Week 1 and Week 2- is
evaluation of frequency and pattern of health outcome by examining the person, place, and
time in relation to health outcome. Analytical epidemiology builds up on it and uses data
gathered by descriptive epidemiology as to look for patterns suggesting causal relationships.
It has been said that epidemiology by itself can never prove that a particular exposure caused
a particular outcome. It is because establishing an association does not necessarily mean that
the exposure is a cause of the outcome, i.e. that it is something that has an effect or a
consequence. Still, establishing a valid association between exposure and outcome is a
necessary first step that must be accomplished before assessing whether the relationship is
causal. Since a determination that a relationship is causal is a judgment, there is often
disagreement, particularly since causality often implies some degree of responsibility for the
outcome, or may create a demand for public health action, and this often has legal and financial
consequences (LaMorte 2019a).
Irrespective of whether epidemiologists aim to study occurrence and distribution of diseases
and health outcomes or they plan to further examine associations or hypothesized causal
relationship between a particular exposure and a particular outcome, a first step is to define
the hypothesis based on the research question and decide which study design will be best
suitable to answer that research question. In Week 3 we will learn about study designs. In
continuation, we will define research methodology which is the way in which data are
collected and analysed (Fink 2012, p. 301). We will also define levels of evidence (hierarchy
of evidence) which are assigned to studies based on the methodological quality of their
design, validity, and applicability. Additionally, we will pay special attention to the concept
of validity, which highlights the need to eliminate or minimize the effects of extraneous
influences, variables, and explanations that might detract from a study’s ultimate findings.
1
, Finally, having these terms understood, one will be able to undertake a critical appraisal of
epidemiological research, that is to accurately assess the quality and relevance of evidence
presented in a paper and its applicability to decision making and recommendations in (public)
health practice.
Before embarking further into Week 3 topic, please find below terminology essential to
understanding of the concepts relevant to Week 3 (some terms were already introduced in
Week 2):
Baseline: The amount of a particular disease that is usually present in a community is referred
to as the baseline- note that it is the observed level and not necessarily zero (Dicker 2006).
Source population: the population out of which the cases arose.
Incident case: a person who is newly diagnosed as a case.
Prevalent case: a person who has a health outcome of interest that was diagnosed in the past.
Cause: To be a cause, the factor: i) must precede the effect, ii) can be either a host or
environmental factor (e.g., characteristics, conditions, actions of individuals, events, natural,
social or economic phenomena) and iii) may be positive (presence of a causative exposure) or
negative (lack of a preventive exposure) (LaMorte 2019a).
Random allocation: each subject under study has an equal chance of being assigned to any one
of the exposures.
Reliability: Implies that the same data would have been collected each time over repeated tests/
observations (not to be confused with accuracy).
Internal Validity: the extent to which the observed results represent the truth in the population
we under study and, thus, are not affected by methodological errors.
2
