PLoS One. 2026 Oct 28;21(10):e0357804. doi: 10.1371/journal.pone.0357804. eCollection 2026.
ABSTRACT
This study aimed to investigate climate-sensitive temporal patterns associated with premature mortality due to cardiovascular diseases (CVD), ischemic heart disease (IHD), and acute myocardial infarction (AMI) in a large subtropical city in southern Brazil. Daily premature mortality records (ages 30-69) from 2010 to 2019 were analyzed together with meteorological data, including temperature, humidity, atmospheric pressure, precipitation, wind, and solar radiation, as well as temporally aggregated climatic indicators. An exploratory analytical framework combining multivariate analysis, clustering, and classification rule mining was applied to identify temporal patterns and combinations of climatic conditions associated with mortality outcomes. The approach was designed to support pattern discovery and hypothesis generation rather than causal inference.Linear associations between individual climatic variables and mortality were weak. However, exploratory analyses revealed distinct climate-sensitive temporal patterns. Premature IHD mortality was more frequently associated with colder temperatures, elevated long-term humidity, and specific combinations of atmospheric pressure and temperature. In contrast, AMI mortality showed associations with intermediate maximum temperatures, lower atmospheric pressure, and moderate levels of solar radiation. The classification models demonstrated moderate performance across outcomes, with the highest accuracy observed for AMI, indicating that complex temporal patterns may not be captured by linear analyses alone. The findings demonstrate that climate-sensitive temporal patterns in premature cardiovascular mortality can be identified using exploratory, data-driven approaches. Although causal relationships were not assessed, the results highlight the value of integrating climatic indicators and temporal aggregation into exploratory environmental health research and hypothesis generation. This framework is transparent, reproducible, and applicable to other urban settings, particularly in low- and middle-income countries facing increasing climate variability.
PMID:42950001 | DOI:10.1371/journal.pone.0357804