隨著人們對於空氣污染物的了解程度逐漸增加，對人體所知會造成健康影響的空氣污染物濃度亦逐漸降低。過敏性疾病屬於全球盛行率相當高之疾病，臺灣的海島型氣候使得民眾在過敏的情形上更加普遍與嚴重，其醫療費用之支出及醫療資源之消耗亦為沉重的負擔。過敏性疾病涵蓋範圍廣泛，包含呼吸道、皮膚與眼部等多種表現型態，且常存在交互影響，導致多項疾病併發。現有研究多聚焦於單一或少數常見的過敏性疾病，有助於釐清污染與特定疾病之關聯，但較難以全面評估空氣污染對整體過敏性疾病所造成之相關負擔。
本研究整合環境部空品測站、特殊性工業區空品測站及縣市環保局之空品測站監測數據，基於以空品微型感測器進行分群的智慧空污暴露推估模式，推估各鄉鎮市區的環境暴露濃度，旨在減少空品監測站數量以及空間分布限制所產生之誤差，提升暴露評估之精確度。自全民健康保險研究資料庫2017年至2022年之全人口檔，以ICD-10-CM之疾病診斷碼篩選出過敏性疾病之患者，並進行患者之居住地推估，將其與環境暴露資料進行串聯。本研究採用雙向病例交叉研究設計，運用條件式邏輯斯迴歸計算勝算比，以探討短期空氣污染物暴露對過敏性疾病急性發作風險之影響。
本研究共納入5,603,051名過敏性疾病患者，分析結果顯示女性患者比例較高，春季與冬季為好發季節，而考慮各年齡組別跨度後，0-6歲學齡前兒童之單位年齡佔比最高。過敏性疾病之急性發作風險與當日環境因子關聯最為密切，其中一氧化碳(CO)及二氧化氮(NO2)與急性發作風險呈穩定且顯著的正相關，相對濕度則呈負相關。在單一污染物模式中，多數污染物與急性發作風險呈正向關聯，而於多重污染物模式中，部分污染物之效應強度下降，顯示污染物間存在交互作用。年齡與地區分層分析指出，高齡族群及居住在北部、東部地區之人群對特定污染物較為敏感。此外，本研究亦觀察到明顯之季節性差異，可能反映季節性環境與行為因素之綜合影響。

The health effects of air pollution are increasingly recognized. In Taiwan, allergic diseases are highly prevalent, placing a substantial burden on healthcare. Since allergic diseases often present with interactions and comorbidities, a comprehensive assessment of their relationship with air pollution is crucial for understanding their overall health burden. This study assessed the impact of short-term air pollutant exposure on acute allergic disease exacerbations using 2017–2022 data from the National Health Insurance Research Database. Air pollution exposure was estimated at township levels using a smart clustering-based spatial interpolation model based on air quality microsensors, integrating data from multiple air quality monitoring stations. The residential locations of patients were inferred from healthcare records and subsequently linked to township-level environmental exposure data. A bidirectional case-crossover design with conditional logistic regression was applied to examine the associations between exposure and several allergic health outcomes. The analysis showed a higher proportion of female patients, with spring and winter identified as peak seasons. CO and NO2 were positively associated with exacerbation risk, while relative humidity was negatively associated. Single-pollutant models indicated most pollutants increased risk, whereas multi-pollutant models suggested interactions among pollutants. We also found that older adults and residents in northern and eastern regions were more sensitive to specific pollutants, and significant seasonal differences likely reflected combined environmental and behavioral influences.

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