Causal Inference of Blood Pressure Reduction and Coronary Heart Disease Risk in the Framingham Study

TL;DR

This study applies causal inference methods to the Framingham Heart Study to accurately estimate the effect of blood pressure reduction on coronary heart disease risk, revealing that observational tools may overstate benefits.

Contribution

It introduces a causal inference approach using Pearl's do-calculus and g-computation to correct bias in estimating blood pressure reduction effects.

Findings

Estimated 20 mmHg systolic BP reduction reduces CHD risk by 3.4%.

Naive observational estimates overstate the benefit by approximately 22%.

Causal methods provide more accurate risk reduction estimates.

Abstract

Standard cardiovascular risk calculators, including the Framingham Risk Score and the ACC/AHA Pooled Cohort Equations, estimate the conditional probability P(CHD | SysBP = s) rather than the interventional quantity P(CHD | do(SysBP = s)). When confounding is present, this distinction has direct clinical consequences: observational estimates may systematically overstate the absolute benefit of antihypertensive treatment. We applied Pearl's do-calculus to the Framingham Heart Study Offspring Cohort (n = 4,240; primary analysis on 3,776 complete cases; 574 ten-year coronary heart disease events). A structurally corrected directed acyclic graph (DAG) was specified and evaluated using conditional independence testing. The average causal effect (ACE) of a 20 mmHg systolic blood pressure reduction was estimated by g-computation with bootstrap confidence intervals, corroborated by propensity score matching and inverse probability weighting. G-computation yielded an ACE of 3.40 percent absolute risk reduction (95 percent CI: 2.64 to 4.14), compared with a naive observational estimate of 4.14 percent, corresponding to an approximate 21.8 percent relative overestimation. Conditional average treatment effects were estimated using R-Learner and T-Learner metalearners. These findings suggest that observational cardiovascular risk tools may overestimate the absolute benefit of blood pressure reduction, with implications for clinical risk stratification and prescribing thresholds.