Exploring associations between airborne pollen, air pollutants, and asthma-related public attention in Yan’an city: A digital epidemiology study based on Baidu index
- 1Yan’an Medical School of Yan’an University, Yan’an, China
- 2Department of Pediatrics, Yanan University Affiliated Hospital, Yan’an, China
- 3Yan’an University Hospital, Yan’an, China
Abstract
Background: Allergic asthma shows clear seasonal variation and is influenced by environmental factors. Internet search data provide a digital epidemiology tool for tracking asthma-related public attention at the population level.
Objective: To examine seasonal patterns and lagged temporal associations between airborne pollen, air pollutants, and asthma-related public attention in Yan’an City.
Methods: Airborne pollen monitoring data, meteorological parameters and concentrations of air pollutants were collected in the urban area of Yan’an City from March 1, 2023 to October 31, 2025. During the same period, Baidu Index data were retrieved for seven asthma-related search terms. Spearman correlation, Kruskal-Wallis H and cross-correlation function (CCF) analyses were used to assess temporal associations, group differences and lagged correlations. Generalized additive models (GAMs) were performed as sensitivity analyses to evaluate whether the observed associations remained after adjustment for meteorological variables and long-term temporal trends.
Results: Baidu Index showed clear seasonal fluctuations. Weak-to-moderate positive temporal associations were observed between asthma-related public attention and concentrations of dominant pollen taxa, including Asteraceae (particularly Artemisia), Chenopodiaceae and Poaceae, as well as air pollutants such as NO2 and SO2. CCF analysis showed the highest correlation coefficients at lag periods of approximately 5 days for Artemisia pollen, 7 days for Chenopodiaceae and Poaceae, and 4-5 days for NO2 and SO2. These lag patterns should be interpreted as exploratory. After adjustment for meteorological variables and long-term temporal trends, the GAMs analysis showed that temporal associations between the three dominant pollen taxa and asthma-related public attention remained statistically significant. NO2 showed only a marginal association (P = 0.049), whereas SO2 was not statistically significant (P = 0.547).
Conclusion: This ecological time-series analysis suggests seasonal and lagged temporal co-variation between airborne pollen, air pollution, and asthma-related public attention in Yan’an City. Pollen-related associations were more consistent, whereas pollutant-related associations were less robust.
Related
- Exploring the role of multivariate associations between brain networks and gut microbiota in (food) value-based decision-making
- Exploring the transcriptomic and metabolomic associations with fetal overgrowth in Holstein cattle derived from in vitro embryo production
- Serum ω-3 Fatty Acids and Cognitive Domains in Community-Dwelling Older Adults from the NuAge Study: Exploring the Associations with Other Fatty Acids and Sex
- Social isolation and intrinsic capacity among older Hispanic adults in the United States: Exploring associations across geographic and social contexts
- Airborne Sound Detection in Manduca sexta Caterpillars
BibTeX
@article{wang2026exploring,
title = {{Exploring associations between airborne pollen, air pollutants, and asthma-related public attention in Yan’an city: A digital epidemiology study based on Baidu index}},
author = {Xiaoya Wang and Bo Liu and Jingjing Lei and Yujie Yang and Wu Yan and Yuxuan Li and Yuanxia Li and Jinwei He},
journal = {Digital Health},
year = {2026},
month = sep,
doi = {10.1177/20552076261490735},
url = {https://doi.org/10.1177/20552076261490735},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Exploring associations between airborne pollen, air pollutants, and asthma-related public attention in Yan’an city: A digital epidemiology study based on Baidu index
AU - Xiaoya Wang
AU - Bo Liu
AU - Jingjing Lei
AU - Yujie Yang
AU - Wu Yan
AU - Yuxuan Li
AU - Yuanxia Li
AU - Jinwei He
PY - 2026
DA - 2026/09/21
JO - Digital Health
DO - 10.1177/20552076261490735
UR - https://doi.org/10.1177/20552076261490735
AB - Background: Allergic asthma shows clear seasonal variation and is influenced by environmental factors. Internet search data provide a digital epidemiology tool for tracking asthma-related public attention at the population level. Objective: To examine seasonal patterns and lagged temporal associations between airborne pollen, air pollutants, and asthma-related public attention in Yan’an City. Methods: Airborne pollen monitoring data, meteorological parameters and concentrations of air pollutants were collected in the urban area of Yan’an City from March 1, 2023 to October 31, 2025. During the same period, Baidu Index data were retrieved for seven asthma-related search terms. Spearman correlation, Kruskal-Wallis H and cross-correlation function (CCF) analyses were used to assess temporal associations, group differences and lagged correlations. Generalized additive models (GAMs) were performed as sensitivity analyses to evaluate whether the observed associations remained after adjustment for meteorological variables and long-term temporal trends. Results: Baidu Index showed clear seasonal fluctuations. Weak-to-moderate positive temporal associations were observed between asthma-related public attention and concentrations of dominant pollen taxa, including Asteraceae (particularly Artemisia), Chenopodiaceae and Poaceae, as well as air pollutants such as NO2 and SO2. CCF analysis showed the highest correlation coefficients at lag periods of approximately 5 days for Artemisia pollen, 7 days for Chenopodiaceae and Poaceae, and 4-5 days for NO2 and SO2. These lag patterns should be interpreted as exploratory. After adjustment for meteorological variables and long-term temporal trends, the GAMs analysis showed that temporal associations between the three dominant pollen taxa and asthma-related public attention remained statistically significant. NO2 showed only a marginal association (P = 0.049), whereas SO2 was not statistically significant (P = 0.547). Conclusion: This ecological time-series analysis suggests seasonal and lagged temporal co-variation between airborne pollen, air pollution, and asthma-related public attention in Yan’an City. Pollen-related associations were more consistent, whereas pollutant-related associations were less robust.
SN - 2055-2076
ER -