Health Risk Assessment and Causation

March 30
Eric Delmelle

Chapter Overview

Defining Risk: Understanding risk as the probability of an event occurring, often implying harm.
Concepts of Causation: Reviewing causation from historical and contemporary perspectives.
Quantifying Association: Using ratio and difference measures to quantify associations.

Assessing Causal Effect: Applying attributable risk and its variants.
Competing Risks: Explaining how competing risks affect mortality patterns.
Risk Perception and Communication: Recognizing the critical role of risk perception and communication in public health.

Central Task: Assessing health risks core function in pop. health.
Broad Usage of “Risk”: The term describes the probability of adverse outcomes, risk factors, and health consequences.
Risk Factors vs. Risk Markers: Distinguishing between factors that cause disease and those that indicate its presence.
Health Risk Appraisal (HRA): Using quantitative procedures to estimate mortality and morbidity risks.
Health Risk Assessment: Evaluating scientific data on hazardous environmental agents ⇔ human exposure.

Hazard Identification: Identifying harmful agents and describing toxicity.
Dose-Response Assessment: Modeling exposure and health effect size variations.
Exposure Assessment: Identifying exposed populations, exposure routes, and dose characteristics.
Risk Characterization: Integrating data to estimate harm likelihood.

Flint resident lives in uncertainty after lead exposure youtube-link
Japan Declares Crisis As Fukushima Reactor Begins Falling Into Ocean And Radiation Levels Soar youtube-link

Dose-Response Assessment: Modeling exposure and health effect size variations.

Exposure Assessment: Identifying exposed populations, exposure routes, and dose characteristics.

Exposure Assessment: Identifying exposed populations, exposure routes, and dose characteristics.

Necessary Cause: A cause that must be present for an effect to occur.
Sufficient Cause: A cause that inevitably produces the effect.
Remote vs. Proximate Causes: Understanding causal chains and effect proximity.

Bradford Hill’s Criteria:
- 1 Strength & Consistency – A strong and repeated association across studies increases the likelihood of causation.
- 2 Specificity & Temporality – The cause should lead to a specific effect, and the effect must occur after the cause.
- 3 Biological Gradient & Plausibility – A dose-response relationship should exist, and the cause should make biological sense.
- 4 Coherence & Experiment – The evidence should align with existing knowledge, and experiments should support the causal link.
- 5 Analogy– If similar factors cause similar effects, the association is more credible.

Ratio Measures: Relative risk, risk ratio, rate ratio, odds ratio.
Difference Measures: Risk difference or attributable risk.
Relative Risk (RR): \(RR = \frac{I_1}{I_0}\)
Odds Ratio (OR): \(OR = \frac{(a/c)}{(b/d)} = \frac{ad}{bc}\)
Risk Difference (RD): \(RD = I_1 - I_0\)
Attributable Risk Among the Exposed [AR(E)]: \(AR(E) = \frac{(I_1 - I_0)}{I_1} = \frac{(RR - 1)}{RR}\)
Population Attributable Risk (PAR): \(PAR = \frac{(I - I_0)}{I} = \frac{P(RR - 1)}{P(RR - 1) + 1}\)

Definition: Recognizes that individuals are exposed to multiple risks, where one event prevents another.
Importance: Essential for understanding mortality trends and disease impact.
Statistical Approaches: Methods to estimate death probability in competing risks.

Subjectivity of Risk: Public perception differs from expert assessments.
Social Construction of Risk: Influences include social, cultural, and political factors.
Factors Influencing Risk Acceptance: Fair distribution, benefits, alternatives, voluntary vs. imposed risks, and control.
Biases in Probability Assessment: Representativeness, anchoring, and availability.
Effective Risk Communication: Public involvement, planning, listening, honesty, coordination, media engagement, clarity, and compassion.