Short-Term PM_2.5 Exposure and Cardiovascular Mortality: A Global Exposure-Response Analysis to Inform Alert...

Short-term exposure to ambient fine particulate matter (PM_2.5) is an established risk factor for cardiovascular morbidity and mortality. However, existing air pollution alert systems are inefficient in protecting general populations, partly because of a lack of precise understanding of the nonlinear exposure-response relationship between PM_2.5 and cardiovascular mortality.

The aim of this study was to construct a globally representative nonlinear exposure-response function for short-term PM_2.5 exposure and cardiovascular mortality through a systematic meta-analysis of published global literature. On the basis of this function, the goal was to identify an optimal public health alert threshold that balances health protection benefits with societal disruption.

A systematic review and meta-analysis of 100 epidemiologic studies (comprising 123 effect estimates) up to May 2025 was conducted. An innovative 3-stage meta-regression model, combining spline functions and structural causal modeling theory, was used to estimate the nonlinear curve. On the basis of this curve, and integrated with global gridded data on PM_2.5 concentrations, population, and baseline mortality, the cardiovascular mortality burden attributable to PM_2.5 from 2000 to 2023 was quantified, and a receiver-operating characteristic-like curve analysis was used to determine the optimal alert value.

The meta-analysis confirmed that for every 10 μg/m³ increase in short-term PM_2.5 concentration, the pooled risk ratio for cardiovascular mortality was 1.0090 (95% CI: 1.0074-1.0106). The constructed exposure-response curve exhibited a supralinear pattern: the marginal risk was high at low concentrations, flattened at moderate concentrations (∼75-150 μg/m³), and rose sharply again above 150 μg/m³. In 2023, the global number of cardiovascular deaths attributable to PM_2.5 pollution episodes (exceeding the World Health Organization's first-stage interim target of 75 μg/m³) was estimated at 59,399 (95% CI: 38,126-82,413). The optimal alert value was estimated as 136 μg/m³ (95% CI: 129-148), which could prevent 73.2% (95% CI: 71.8%-76.6%) of attributable deaths while affecting only 32% of at-risk person-days.

A significant nonlinear relationship exists between short-term PM_2.5 exposure and cardiovascular mortality. The optimal alert value identified in this study provides critical evidence for developing more scientific, efficient, and health-oriented air pollution warning systems, thereby maximizing public health benefits while minimizing social disruption.