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Related Concept Videos

Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
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Drugs exert their therapeutic effects by interacting with receptors, enzymes, or ion channels that are present throughout the human body. The strength and duration of the interaction between a drug and its target receptor are characterized by the selectivity and specificity of the drug. Selectivity refers to a drug's strong preference for its intended target over other targets. For instance, isoprenaline, a non-selective β-adrenergic agonist, interacts with both β1- and β2-adrenergic receptors...
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Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...
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Surveys02:16

Surveys

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...

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Social Threat-Safety Test Uncovers Psychosocial Stress-Related Phenotypes
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Interaction and exposure modification: are we asking the right questions?

Clarice R Weinberg1

  • 1National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA. weinber2@niehs.nih.gov

American Journal of Epidemiology
|February 7, 2012
PubMed
Summary

Complex diseases result from genetic and environmental factors, not just one cause. Understanding these joint effects using new models is crucial for advancing disease etiology research and intervention prediction.

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Area of Science:

  • Epidemiology
  • Genetics
  • Environmental Health

Background:

  • Most diseases result from a complex interplay of genetic susceptibility, environmental exposures, and chance.
  • Understanding the combined effects of these factors on disease etiology is a significant challenge in public health research.

Purpose of the Study:

  • To propose a conceptual framework for analyzing complex disease etiology.
  • To highlight the utility of parsimonious joint models in etiologic epidemiology.
  • To introduce the concept of exposure modification for understanding gene-environment interactions.

Main Methods:

  • Review and conceptualization of existing models in etiologic epidemiology.
  • Proposal of additive null models for specific etiologic scenarios.
  • Introduction of the concept of exposure modification for biologic interactions.

Main Results:

  • Additive null models can effectively characterize independent etiologic effects, particularly for rare conditions.
  • The concept of exposure modification offers a valuable lens for examining biologic interactions between genetic variants and environmental exposures.
  • Parsimonious joint models provide critical insights into disease pathogenesis.

Conclusions:

  • Advancing the understanding of complex disease etiology requires openness to parsimonious joint models.
  • These models are essential for characterizing combined genetic and environmental effects.
  • The proposed framework aids in predicting intervention effects and understanding disease origins.