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Development and two-city validation of a Temperature-Sensitive Air Quality Health Index incorporating synergistic effects of air pollution and thermal stress.

Created on 10 Sep 2026

Authors

Chuchu Luo, Haoxian He, Yiting Li, Nengzhou Chen, Chufang Wang, Yu Sun, Guang Hao, Xi Fu

Published in

Frontiers in public health. Volume 14. Pages 1806127. Epub Aug 26, 2026.

Abstract

Ambient air pollution and non-optimal temperatures are two major environmental risk factors that interact to amplify health risks. Current Air Quality Health Indices (AQHI) are vital public health tools for warning against air pollution risk, but fail to account for the synergistic health effects of air pollution and non-optimal temperature.
This study aimed to develop and validate a generalizable methodological framework for a Temperature-Sensitive Air Quality Health Index (TS-AQHI) that captures the synergistic effects of air pollution and temperature stress.
We first constructed the TS-AQHI using Weighted Quantile Sum (WQS) regression as a preprocessing step to estimate pollutant weights, which were then entered as a weighted index into a primary Generalized Additive Model (GAM) framework incorporating temperature, humidity, and multiplicative interaction terms with two-day-lagged exposures. We then applied this framework to daily mortality, air pollution, and meteorological data from Ningbo (2014-2017) and London (2014-2017). Model validation was performed through quartile-based risk categorization using Poisson regression, time-series alignment with mortality, seasonal stratification, and temperature-threshold comparisons, with the conventional AQHI serving as the benchmark.
TS-AQHI significantly outperformed the conventional AQHI. In Ningbo, TS-AQHI showed 52.7% higher excess mortality risk (ER) for high-risk groups (ER: 22.9, 95% CI: 21.1-24.7 vs. 15.0, 95% CI: 13.4-16.7). In London, TS-AQHI demonstrated substantially greater predictive power for high-risk groups (ER: 22.2, 95% CI: 20.7-23.8 vs. 7.7, 95% CI: 6.3-9.0). Stratified analyses found that TS-AQHI consistently explained a higher proportion of mortality variance across all subgroups, particularly among older adults (≥65 years; R2  = 25.1% vs. 20.5% for AQHI) and females (20.3% vs. 16.0%).
This study presents a novel health risk index that integrates the synergistic effects of temperature and multi-pollutant exposure. The TS-AQHI provides a more robust and sensitive tool for public health agencies, enabling more accurate and timely warnings against the increasing threat of concurrent environmental exposures.

PMID:
42719285
Bibliographic data and abstract were imported from PubMed on 10 Sep 2026.

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