Global CVD Trends and Regional Risk‐Profile Clustering Using GBD 2022 Data

Global CVD Trends

Abstract

Abstract
Background: Age-standardized cardiovascular disease (CVD) mortality declined sharply from 1990 to 2010 but has plateaued since. Concurrently, regional risk-factor burdens differ widely. We combine a robust longitudinal joinpoint analysis (1990–2022) with a rigorously validated 2022 cross-sectional clustering of eight leading CVD risk ASMRs across 21 GBD super-regions.
Methods:
Global Trend (1990–2022): Extracted “Cardiovascular diseases” ASMRs (Deaths, Age-standardized, Both sexes) for “Global” from the DISEASE CSV. We applied the segmented R package (version 1.4-0) for joinpoint regression [1], confirmed a breakpoint in 2010 (p < 0.01 via permutation test), and calculated annual percentage changes (APCs) with 95% CIs.
Risk-Profile Clustering (2022): Selected eight risks—high systolic blood pressure; tobacco smoking; high body-mass index; dietary risks; high LDL cholesterol; high fasting plasma glucose; ambient PM₂.₅ pollution; high temperature exposure—jointly accounting for >70% of global CVD DALYs [2]. We extracted their ASMRs for each of 21 GBD super-regions from the RISKS CSV, standardized to z-scores, and applied k-means (k = 3) using scikit-learn 1.2.0.
Validation: Silhouette = 0.48; elbow (inertia) plot and Tibshirani’s gap statistic also support k = 3.
Statistical Testing: Kruskal–Wallis tests (with Bonferroni correction) confirm significant ASMR differences for all eight risks across clusters (p < 0.001).

Conclusions: The 2010 joinpoint marks a “lost decade” in CVD progress. Risk-profile clusters highlight tailored metabolic, behavioral, or environmental priorities for each region.