PO.PS01.12 · 人群科学
韩国甲状腺癌发病率与环境致癌物排放的空间关联
Spatial association between thyroid cancer incidence and environmental carcinogen emissions in Korea
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：甲状腺癌是韩国最常诊断的癌症，自2016年以来发病率再度回升。环境和职业暴露——包括二氧化氮（NO₂）、颗粒物（PM2.5）、臭氧（O₃）等空气污染物以及甲苯和汞等工业化学品——已被报道为潜在的风险因素。本研究考察了韩国各地区甲状腺癌发病率的区域差异是否可由社区层面致癌物排放的差异来解释。
方法：本生态学研究覆盖韩国229个区，以2014-2018年甲状腺癌发病率（ICD-10：C73）为结局。暴露变量为污染物排放与转移登记册（PRTR）中报告的区级致癌物质年度排放量，汇总为三个反映潜伏期的时段（2004-2008；2009-2013；2004-2013）。缺失的排放值采用贝叶斯空间假设进行空间插值。协变量包括人口统计学（性别比、25-44岁人口比例）、行为（吸烟、肥胖）和社会经济指标（每千人口医师数、基本生活保障受益人比率）。采用集成嵌套拉普拉斯近似（INLA）拟合具有BYM2空间结构的贝叶斯分层泊松模型。采用WAIC评估模型拟合度，并估算各暴露时段的相对风险（RR）。
结果：更高的区级致癌物排放与甲状腺癌发病率增加相关。在基线模型中，对数转换排放量每增加1个单位，各暴露时段对应的RR范围为1.037至1.051。空间插值排放数据集显示出相似的关联（RR 1.037-1.041）。在控制人口统计学、行为和社会经济因素的校正模型中，关联方向保持一致，原始排放数据的RR介于1.023至1.028之间，插值数据为1.024-1.025。在城市化和工业化地区识别出高相对风险的空间聚集区。
结论：在考虑空间依赖性和社区层面协变量后，致癌物质排放较高的区表现出更高的甲状腺癌发病率。这些发现支持了工业设施造成的环境污染导致甲状腺癌区域差异这一假设，且5-10年的潜伏窗口具有相关性。未来研究应纳入个体层面更精细的暴露评估、改进的时间匹配，以及针对高风险地区的针对性预防或筛查策略的关联。
查看英文原文 English abstract
Background: Thyroid cancer is the most commonly diagnosed cancer in Korea, with a recent resurgence in incidence since 2016. Environmental and occupational exposures-including air pollutants such as nitrogen dioxide (NO₂), particulate matter (PM2.5), ozone (O₃), and industrial chemicals such as toluene and mercury-have been reported as potential risk factors. This study examined whether regional variation in thyroid cancer incidence across Korea can be explained by differences in community-level carcinogenic emissions.
Methods: An ecological study was conducted across 229 districts in Korea, using thyroid cancer incidence (ICD-10: C73) from 2014-2018 as the outcome. Exposure variables were district-level annual emissions of carcinogenic substances reported in the Pollutant Release and Transfer Register (PRTR), aggregated into three latency-reflective periods (2004-2008; 2009-2013; 2004-2013). Missing emission values were spatially interpolated using Bayesian spatial assumptions. Covariates included demographic (sex ratio, proportion aged 25-44), behavioral (smoking, obesity), and socioeconomic indicators (number of physicians per 1,000 population, basic livelihood recipient rate). Bayesian hierarchical Poisson models with BYM2 spatial structure were fitted using Integrated Nested Laplace Approximation (INLA). Model fit was assessed using WAIC, and relative risks (RRs) were estimated for each exposure period.
Results: Higher district-level carcinogen emissions were associated with increased thyroid cancer incidence. In baseline models, a 1-unit increase in log-transformed emissions corresponded to RRs ranging from 1.037 to 1.051 across exposure periods. Spatially interpolated emission datasets showed similar associations (RR 1.037-1.041). In adjusted models controlling for demographic, behavioral, and socioeconomic factors, associations remained directionally consistent, with RRs between 1.023 and 1.028 for raw emission data and 1.024-1.025 for interpolated data. Spatial clusters of high relative risk were identified in urbanized and industrialized regions.
Conclusions: Districts with higher emissions of carcinogenic substances exhibited increased thyroid cancer incidence after accounting for spatial dependence and community-level covariates. These findings support the hypothesis that environmental pollution from industrial facilities contributes to regional disparities in thyroid cancer and that latency windows of 5-10 years are relevant. Future research should incorporate refined exposure assessments at the individual level, improved temporal matching, and linkage to targeted prevention or screening strategies for high-risk regions.
利益披露 Disclosure
T. Kim, None..
S. Lee, None..
S. Park, None.