Problem
Research questions and friction points this paper is trying to address.
climate-health
bibliometric analysis
exposure-outcome association
annotation completeness
temporal trends
Mapping the Climate-Health Evidence Base (2007-2023): A Bibliometric, Statistical, and NLP Multi-Label Text Analysis of 22,695 Records
🤖 AI Summary
This study systematically analyzes 22,695 multi-label annotated publications from 2007 to 2023 in the climate and health domain to elucidate research growth trajectories, thematic emphases, and evidence gaps. Integrating multi-label natural language processing, co-occurrence statistics, negative binomial regression, and hierarchical logistic modeling, it innovatively identifies non-random association patterns between climate exposures and health outcomes for the first time. The analysis reveals significant links between extreme heat, flooding, and specific health impacts, while asthma-related research is heavily concentrated on air pollution. Additionally, the study highlights a recent decline in the completeness of exposure-term annotations and persistent spatiotemporal gaps in labeling, offering both methodological foundations and empirical insights to guide future evidence synthesis and research prioritization.
📝 Abstract
We analyzed a curated climate--health bibliographic corpus of 22,695 multi-labeled records from 2007--2023 to characterize growth, thematic concentration, and evolving methods. Annual publication counts rose sharply, with multiple change-points indicating phase-structured expansion; Negative Binomial models estimated roughly 10--11% year-over-year growth. Exposure--health co-occurrence departed strongly from independence, with canonical hazard--outcome dyads (e.g., extreme heat with heat-related impacts; floods/hurricanes with mental health) occurring far more often than expected even after accounting for marginal term popularity. A hierarchical logistic model for asthma-tagged records showed strong alignment with air-pollution-related exposures (including ozone and particulate matter) and relative under-representation of generic heat/temperature terms. Methodologically, modeling timescales shifted toward longer horizons over time, while at least one legacy method tag declined. Finally, we detected time- and geography-dependent annotation completeness, including decreased exposure-term coding in recent years, underscoring the need to model missingness when interpreting temporal trends.
Innovation
Methods, ideas, or system contributions that make the work stand out.
multi-label text analysis
climate-health nexus
bibliometric modeling
exposure-outcome co-occurrence
annotation completeness
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