臺灣的世界衛生組織 AWaRe 抗生素使用的時空分布及影響因子之探討

Abstract

前言 抗微生物抗藥性 (Antimicrobial Resistance, AMR) 已成為全球公共衛生的重要議題，而抗生素的不當使用為其主要推動因素。世界衛生組織 (World Health Organization, WHO) 提出了抗生素察覺分類（AWaRe classification，以下簡稱世衛察覺分類），將抗生素分為Access、Watch及Reserve類別，以促進合理使用。此外，也強調了需以 One Health 為架構來全面應對 AMR 問題。本研究旨在探討臺灣世衛察覺分類中Watch或Reserve類抗生素使用 (Antibiotics Use, AMU) 的時空分布及其影響因素。 材料與方法 本研究使用全民健康保險資料庫 (National Health Insurance Research Database, NHIRD) 2005 至 2020 年之門、急診資料，處方率的定義為該年度每十萬人口中使用 Watch 或 Reserve 類抗生素的人數，搭配 2023 世衛察覺分類將抗生素使用情形分為三種類別：AMU 1 為處方中使用 Watch 或 Reserve 類抗生素者（納入 630,534 至 1,104,855 人）、AMU 2 為 7 至 14 天內回診並被重複開立 Watch 或 Reserve 類抗生素處方者（納入 112,422 至 187,537 人）以及 AMU 3 為因急性支氣管炎就診且處方中使用 Watch 或 Reserve 類抗生素者（納入 345,760 至 605,858 人）。以 One Health 為架構，分別以蔬菜水果產量（單位：公噸）、牛、豬、雞依照體重加權換算雞等值重量（單位：公噸）、內陸養殖漁業產量（單位：公噸）、平均每日門急診就診量（單位：人次）作為農業、畜牧業、漁業、醫療業等經濟活動指標，進一步探討這些經濟活動及PM10濃度對抗生素使用的影響。首先使用 WHO 2000 年標準人口將處方率進行年齡標準化，繪製年度趨勢圖及依 2015 至 2019 年處方率的五分位為標準做分類的縣市地理分布熱度圖。進一步採用廣義相加模型 (Generalised Additive Model, GAM) 繪製時間平滑曲線、空間分布情形，並同時控制時間趨勢及縣市間空間異質性，評估暴露因子與各縣市處方率的影響。最後使用配對 t 檢定比較 COVID-19 疫情期間抗生素處方率的變化。資料清理與前處理於衛生福利部資料科學中心以 SAS 9.4 進行，後續分析與作圖使用R 4.4.2 完成。 結果 研究發現，臺灣 Watch 或 Reserve 類抗生素處方率與國際抗生素消耗的趨勢相似，在 2006 年達最低後逐年增加，2019 年達最高峰（AMU 1：每十萬人口 2,920 人至 4,876 人；AMU 2：每十萬人口 522 人至 843 人；AMU 3：每十萬人口 1,615 人至 2,831 人），2020 年因疫情因素而下降（AMU 1：每十萬人口 3,356 人；AMU 2：每十萬人口 679 人；AMU 3：每十萬人口 2,021 人）。性別上女性處方率（AMU 1：每十萬人口 3,119 至 5,002 人之間；AMU 2：每十萬人口 522 至 844 人之間；AMU 3：每十萬人口 1,735 至 2,934 人之間）高於男性（AMU 1：每十萬人口 2,607 至 4,517 人之間；AMU 2：每十萬人口 500 至 822 人之間；AMU 3：每十萬人口 1,453 至 2,615 人之間），各年齡層以 0－18 歲及 65 歲以上處方率最高。地理分布上呈現明顯的地理不均分布，臺南市、臺中市與宜蘭縣長期處於高處方率區域，且不同縣市的抗生素使用存在顯著差異。大部分縣市在三個時間段均呈穩定上升，僅有新竹縣市的處方率呈下降趨勢。One Health 相關因子的模式中，以放入門急診每日就診人次、內陸養殖漁業產量及 PM10 濃度的模式為最佳 (R2=0.79, -REML=1790.50)，門急診每日就診人次、內陸養殖漁業產量與 AMU 1 的抗生素處方率呈顯著正相關，門診人次增加可能加劇抗生素濫用；而畜牧及養殖產業也可能透過環境選擇壓力促使抗藥性細菌傳播間接導致更高的抗生素處方率。 結論 本研究首次整合 WHO AWaRe 分類及 One Health 因子，呈現臺灣廣效型抗生素處方率逐年增加且地理分布不均的現象，並確認醫療利用、畜牧及養殖活動為重要影響因素，建議政策制定者應根據地區特性擬定差異化的管理措施。此外，即使臺灣的 Access 抗生素使用比例已達到 WHO 標準，但仍可從本研究中發現抗生素濫用的情形，因此建議推動加強基層診所抗生素處方管理，並提升畜牧與養殖業抗生素使用監測。

Introduction Antimicrobial resistance (AMR) has become a critical global public health issue, primarily driven by inappropriate antibiotic use. The World Health Organization (WHO) developed the AWaRe classification system, categorizing antibiotics into Access, Watch, and Reserve groups, to promote rational antibiotic use. Additionally, the WHO emphasizes employing the One Health framework to comprehensively address AMR. This study aims to investigate the spatiotemporal distribution of Watch or Reserve antibiotics use (AMU) according to the WHO AWaRe classification and associated influencing factors in Taiwan. Materials and Methods This study utilized outpatient and emergency department data from Taiwan's National Health Insurance Research Database (NHIRD) spanning 2005 to 2020. The prescription rate in this study was defined as the population using the antibiotics per 100,000, combined with the WHO AWaRe 2023 classification list to categorize the AMU into three situations: prescriptions containing Watch or Reserve antibiotics (AMU 1, include 630,534 to 1,104,855 people), repeated visits with recurrent prescriptions of Watch or Reserve antibiotics (AMU 2, include 112,422 to 187,537 people), and visits for acute bronchitis receiving prescriptions containing Watch or Reserve antibiotics (AMU 3, 345,760 to 605,858 people). Under the One Health framework, the fruit and vegetables production (unit: t), combined weight equivalents of cattle, pigs, and chickens (unit: t), inland aquaculture production (unit: t) and daily outpatient and emergency visit volumes (unit: person-times) were used as indicators of economic activities in agriculture, animal husbandry, fisheries, and healthcare, respectively. Then, exploring the impact of these economic activities and PM10 concentrations on AMU. First, we age-standardized prescription rates using the WHO 2000 standard population and then produced annual trend charts and heat maps of the geographic distribution of counties and cities categorized by quintiles of prescription rates from 2015 to 2019. The study analyzed temporal trends and geographical distributions of prescription rates for Watch or Reserve antibiotics and examined the influence of agricultural, livestock, inland aquaculture, healthcare economic activities, and PM10 concentration on antibiotic use. Generalized additive models (GAM) were employed for statistical analysis, and paired t-tests were used to compare changes in antibiotic prescription rates during the COVID-19 pandemic. Data cleaning and preprocessing were conducted using SAS 9.4 at the Ministry of Health and Welfare Data Science Center, while subsequent analysis and visualization were performed using R version 4.4.2. Results The prescription rate of Watch or Reserve antibiotics in Taiwan reached the lowest point in 2006 and gradually increased, peaking in 2019 (AMU 1: 2,920 increase to 4,876 per 100,000 people; AMU 2: 522 increase to 843 per 100,000 people; AMU 3: 1,615 increase to 2,831 per 100,000 people) before declining in 2020 due to the COVID-19 pandemic (AMU 1: 3,356 per 100,000 people; AMU 2: 679 per 100,000 people; AMU 3: 2,021 per 100,000 people). Women had higher prescription rates than men(AMU 1: 3,119 to 5,002 vs 2,607 to 4,517; AMU 2: 522 to 844 vs 500 to 822; AMU 3: 1,735 to 2,934 vs 1,453 to 2,615), and the highest rates were observed among age groups 0-18 and over 65 years. Geographically, Tainan City, Taichung City, and Yilan County consistently exhibited high prescription rates, with significant regional variations. Among One Health-related factors, daily outpatient and emergency visits, livestock, and inland aquaculture production were positively correlated with antibiotic prescription rates. Among the models including One Health related factors, the optimal model comprised daily outpatient and emergency department visits, inland aquaculture production, and PM10 concentration (R² = 0.79, -REML = 1790.50). Daily outpatient and emergency department visits and inland aquaculture production exhibited significant positive correlations with the prescription rates of AMU 1. Increased outpatient visits may intensify antibiotic misuse, while livestock and aquaculture industries may indirectly elevate antibiotic prescription rates by facilitating the spread of antimicrobial-resistant bacteria through environmental selection pressures. Conclusion This study is the first to integrate the WHO AWaRe classification and One Health factors to reveal an increasing trend and geographical disparities in broad-spectrum antibiotic prescription rates in Taiwan. It identifies healthcare utilization, livestock, and aquaculture activities as significant influencing factors. Policymakers are advised to implement region-specific management strategies to address these variations effectively. Although Taiwan’s use of Access category antibiotics has met WHO targets, evidence of antibiotic misuse persists, highlighting the need to strengthen antibiotic prescription management in primary care settings and enhance surveillance of antibiotic use in livestock and aquaculture industries.