What do we need for robust, quantitative health impact assessment?

Area of Science:

• Public Health
• Epidemiology
• Health Policy

Background:

• Health Impact Assessment (HIA) is crucial for understanding decision consequences.
• Ensuring the robustness of HIA conclusions is vital for decision-makers.
• Quantitative estimates can enhance HIA influence but require careful consideration of validity and importance.

Purpose of the Study:

• To present the first published practical guidance for performing robust, quantitative Health Impact Assessment.
• To outline essential steps for reliable quantification of potential health impacts.
• To address concerns regarding the quantification of health effects in HIA.

Main Methods:

• Profiling affected populations and gathering evidence for postulated health impacts.
• Mapping causal pathways, selecting outcome measures, and developing statistical models.
• Explicitly stating assumptions and uncertainties, and conducting sensitivity analyses.

Main Results:

• Guidance covers population profiling, evidence acquisition, and subgroup analysis.
• Methods for quantifying impacts include causal pathway mapping and statistical modeling.
• Acknowledges data scarcity and inadequacy, stressing the need for explicit assumptions and sensitivity analyses.

Conclusions:

• Robust quantitative HIA requires careful methodology, including explicit assumptions and sensitivity analyses.
• Both qualitative and quantitative elements are necessary for a thorough and valuable HIA.
• HIA must be robust to effectively inform real-world decisions, even when facing scientific challenges.