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- Title
Association Between Changes in Timing of Spring Onset and Asthma Hospitalization in Maryland.
- Authors
Sapkota, Amir; Dong, Yan; Li, Linze; Asrar, Ghassem; Zhou, Yuyu; Li, Xuecao; Coates, Frances; Spanier, Adam J.; Matz, Jonathan; Bielory, Leonard; Breitenother, Allison G.; Mitchell, Clifford; Jiang, Chengsheng
- Abstract
Key Points: Question: Are changes in timing of spring onset related to ongoing climate variability and change associated with rates of asthma hospitalization during the spring season? Findings: In this cross-sectional study of 29 257 patients with asthma, very early onset of spring was associated with a 17% increase in hospital admissions for asthma and late onset of spring was associated with a 7% increase. Meaning: In this study, the observed associations between changes in timing of spring onset and asthma hospitalizations were likely associated with pollen dynamics, ie, early onset of spring could increase the length of the tree pollen season while late onset may increase pollen concentrations because of simultaneous blooming. This cross-sectional study investigates how ongoing changes in the timing of spring onset related to climate change are associated with rates of asthma hospitalization in Maryland. Importance: Ongoing climate change is affecting the health of communities across the globe. While direct consequences, including morbidity and mortality tied to increases in the frequency of extreme weather events, have received significant attention, indirect health effects, particularly those associated with climate change–driven disruptions in ecosystems, are less understood. Objective: To investigate how ongoing changes in the timing of spring onset related to climate change are associated with rates of asthma hospitalization in Maryland. Design, Setting, and Participants: This cross-sectional study of 29 257 patients with asthma used general additive (quasi Poisson) and mixed-effect (negative binomial) models to investigate the association between changes in the timing of spring onset, detected using satellite observations, and the risk of asthma hospitalization in Maryland from 2001 to 2012. Data analysis was conducted from January 2016 to March 2019. Exposures: Phenology data, derived from the National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, were used to calculate location-specific median dates for start of season from 2001 to 2012. How the start of season for a given year and location deviated from the long-term average was calculated and categorized as very early, early, normal, or late. Main Outcomes and Measures: Daily asthma hospitalization in Maryland during the spring season (ie, March to May). Results: There were 108 358 total asthma hospitalizations during the study period, of which 29 257 (27.0%; 14 379 [49.1%] non-Hispanic black patients; 17 877 [61.1%] women) took place during springtime. In the unadjusted model, very early (incident rate ratio [IRR], 1.17; 95% CI, 1.07-1.28) and late (IRR, 1.07; 95% CI, 1.00-1.15) onset of spring were associated with increased risk of asthma hospitalization. When the analysis was adjusted for extreme heat events and concentrations of particulate matter with an aerodynamic diameter less than 2.5 μm, the risk remained significant for very early spring onset (IRR, 1.10; 95% CI, 1.02-1.20) but not for late spring onset (IRR, 1.03; 95% CI, 0.97-1.11). Conclusions and Relevance: These results suggest that ongoing changes in the timing of spring onset, which are related to climate variability and change, are associated with asthma hospitalization. Given the high burden of allergic diseases and the number of individuals sensitized to tree pollen, these findings serve as a wake-up call to public health and medical communities regarding the need to anticipate and adapt to the ongoing changes in the timing and severity of the spring allergy season.
- Subjects
MARYLAND; AERODYNAMICS; ASTHMA; CLIMATE change; COMPARATIVE studies; CONFIDENCE intervals; HOSPITAL care; RESEARCH methodology; MULTIVARIATE analysis; NOSOLOGY; POISSON distribution; POPULATION geography; REGRESSION analysis; RESEARCH funding; STATISTICAL sampling; SEASONS; STATISTICS; TIME; EMPIRICAL research; PARTICULATE matter; CROSS-sectional method; RECEIVER operating characteristic curves; DATA analysis software; DESCRIPTIVE statistics; ODDS ratio
- Publication
JAMA Network Open, 2020, Vol 3, Issue 7, pe207551
- ISSN
2574-3805
- Publication type
Article
- DOI
10.1001/jamanetworkopen.2020.7551