ABSTRACT
Environmental exposure to fine particulate matter PM2.5 is known to be associated with many hazardous health effects, including cardiovascular diseases (CVDs). To reduce the related health burden, it is crucial that policy-makers throughout the world set regulation levels according to their own evidence-based study outcomes. However, there appears to be a lack of decision-making methods for the control level of PM2.5 based on the burden of disease. In this study, 117,882 CVD-free participants (≥30-years-old) of the MJ Health Database were followed-up (for a median of 9 years) between 2007 and 2017. Each participant's residential address was matched to the 3× 3 km grid PM2.5 concentration estimates with a 5-year average for long-term exposure. We used a time-dependent nonlinear weight-transformation Cox regression model for the concentration-response function (CRF) between exposure to PM2.5 and CVD incidence. Town/district-specific PM2.5-attributable years of life in disability (YLDs) in CVD incidence were calculated by using the relative risk (RR) of the PM2.5 concentration level relative to the reference level. A cost-benefit analysis was proposed by assessing the trade-off between the gain in avoidable YLDs (given a reference level at u and considering mitigation cost) versus the loss in unavoidable YLDs by not setting at the lowest observed health effect level u0. The CRF varied across different areas with dissimilar PM2.5 exposure ranges. Areas with low PM2.5 concentrations and population sizes provided crucial information for the CVD health effect at the lower end. Additionally, women and older participants were more susceptible. The avoided town/district-specific YLDs in CVD incidence due to lower RRs ranged from 0 to 3000 person-years comparing the PM2.5 concentration levels in 2019 with the levels in 2011. Based on the cost-benefit analysis, an annual PM2.5 concentration of 13 µg/m3 would be optimal, which provides a guideline for the updated regulation level (currently at 15 µg/m3). The proposed cost-benefit analysis method may be applied to other countries/regions for regulation levels that are most suitable for their air pollution status and population health.
