Chen Ping Hui, Chu Po-Ching, Huang Ching-Chun, Chen Chi-Hsien, Guo Yue Leon, Su Ta-Chen, Chen Pau-Chung
Department of Environmental and Occupational Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan.
Department of Environmental and Occupational Medicine, National Taiwan University Hospital, Taipei, Taiwan.
Front Rehabil Sci. 2025 Apr 7;6:1545460. doi: 10.3389/fresc.2025.1545460. eCollection 2025.
Underreporting of occupational diseases (ODs) could be attributed to poor medical accessibility, which is rarely discussed previously. Our cross-sectional study aims to evaluate how OD reporting is impeded by long travel distance/time (TD/TT) to the nearest major occupational medicine clinics.
Using data from the Network of Occupational Diseases and Injuries Service (NODIS), Taiwan's OD surveillance system, and the annual Manpower Survey from 2008 to 2018, we calculate each district's incidence rate of ODs (IROD) and expected IROD based on industries and job titles. Each town's TD/TT to the nearest major occupational medicine clinics is estimated by Google Maps' Distance Matrix API. The quasi-Poisson regression model is used to investigate the effect of TD and TT on IROD, while industries and job titles are adjusted by offsetting expected IROD. A subgroup analysis is then carried out to check the effect of employment status, sickness absence, and reporting years.
A total of 3,420 cases of definite ODs are included in our study. Using the quasi-Poisson regression model, after adjusting industry types and job titles, TD and TT have a significant effect on IROD. As TD/TT increases by 10 km/10 min, IROD decreases by 10.90%/10.73%. It is estimated that ∼200 OD cases per year or 40% of ODs are therefore underreported. In the subgroup analysis, only mildly sick workers are still significantly affected by TD and TT.
Our study shows how poor medical accessibility leads to underreporting, especially for mildly sick cases, and up to 40% of ODs could be underreported. Using this method, we can evaluate the cost-effectiveness of adding reporting hospitals in areas with poor medical accessibility.
职业病报告不足可能归因于医疗可及性差,而这一点此前鲜有讨论。我们的横断面研究旨在评估到最近的主要职业医学诊所的长途旅行距离/时间(TD/TT)如何阻碍职业病报告。
利用台湾职业病与伤害服务网络(NODIS)的数据、职业病监测系统以及2008年至2018年的年度人力调查,我们根据行业和职位计算每个地区的职业病发病率(IROD)和预期IROD。每个城镇到最近的主要职业医学诊所的TD/TT通过谷歌地图的距离矩阵应用程序编程接口进行估算。采用准泊松回归模型研究TD和TT对IROD的影响,同时通过抵消预期IROD对行业和职位进行调整。然后进行亚组分析,以检验就业状况、病假和报告年份的影响。
我们的研究共纳入3420例确诊的职业病病例。使用准泊松回归模型,在调整行业类型和职位后,TD和TT对IROD有显著影响。随着TD/TT每增加10公里/10分钟,IROD分别降低10.90%/10.73%。据估计,因此每年约有200例职业病病例未报告,占职业病总数的40%。在亚组分析中,只有轻症患者仍受TD和TT的显著影响。
我们的研究表明医疗可及性差如何导致报告不足,尤其是轻症病例,高达40%的职业病可能未被报告。使用这种方法,我们可以评估在医疗可及性差的地区增加报告医院的成本效益。