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Bayesian spatial modelling of childhood cancer incidence in Switzerland using exact point data: a nationwide study during 1985-2015.
International Journal of Health Geographics ( IF 3.0 ) Pub Date : 2020-04-17 , DOI: 10.1186/s12942-020-00211-7
Garyfallos Konstantinoudis 1, 2 , Dominic Schuhmacher 3 , Roland A Ammann 4 , Tamara Diesch 5 , Claudia E Kuehni 1 , Ben D Spycher 1 , ,
Affiliation  

BACKGROUND The aetiology of most childhood cancers is largely unknown. Spatially varying environmental factors such as traffic-related air pollution, background radiation and agricultural pesticides might contribute to the development of childhood cancer. This study is the first investigation of the spatial disease mapping of childhood cancers using exact geocodes of place of residence. METHODS We included 5947 children diagnosed with cancer in Switzerland during 1985-2015 at 0-15 years of age from the Swiss Childhood Cancer Registry. We modelled cancer risk using log-Gaussian Cox processes and indirect standardisation to adjust for age and year of diagnosis. We examined whether the spatial variation of risk can be explained by modelled ambient air concentration of NO2, modelled exposure to background ionising radiation, area-based socio-economic position (SEP), linguistic region, duration in years of general cancer registration in the canton or degree of urbanisation. RESULTS For all childhood cancers combined, the posterior median relative risk (RR), compared to the national level, varied by location from 0.83 to 1.13 (min to max). Corresponding ranges were 0.96 to 1.09 for leukaemia, 0.90 to 1.13 for lymphoma, and 0.82 to 1.23 for central nervous system (CNS) tumours. The covariates considered explained 72% of the observed spatial variation for all cancers, 81% for leukaemia, 82% for lymphoma and 64% for CNS tumours. There was weak evidence of an association of CNS tumour incidence with modelled exposure to background ionising radiation (RR per SD difference 1.17; 0.98-1.40) and with SEP (1.6; 1.00-1.13). CONCLUSION Of the investigated diagnostic groups, childhood CNS tumours showed the largest spatial variation. The selected covariates only partially explained the observed variation of CNS tumours suggesting that other environmental factors also play a role.

中文翻译:


使用精确点数据对瑞士儿童癌症发病率进行贝叶斯空间建模:1985-2015 年期间的一项全国性研究。



背景技术大多数儿童癌症的病因学在很大程度上是未知的。空间变化的环境因素,如交通相关的空气污染、背景辐射和农业杀虫剂,可能会导致儿童癌症的发生。这项研究是首次使用居住地的精确地理编码对儿童癌症的空间疾病绘图进行调查。方法 我们纳入了瑞士儿童癌症登记处 1985 年至 2015 年期间在瑞士诊断出患有癌症的 5947 名 0-15 岁儿童。我们使用对数高斯 Cox 过程和间接标准化来对癌症风险进行建模,以根据年龄和诊断年份进行调整。我们研究了风险的空间变化是否可以通过模拟环境空气浓度、模拟背景电离辐射暴露、基于地区的社会经济地位(SEP)、语言区域、州内一般癌症登记持续时间(以年为单位)来解释或城市化程度。结果 对于所有儿童癌症的总和,与国家水平相比,后中位相对风险 (RR) 因地点而异,从 0.83 到 1.13(最小到最大)不等。白血病的相应范围为 0.96 至 1.09,淋巴瘤的相应范围为 0.90 至 1.13,中枢神经系统 (CNS) 肿瘤的相应范围为 0.82 至 1.23。所考虑的协变量解释了所有癌症观察到的空间变异的 72%、白血病的 81%、淋巴瘤的 82% 和中枢神经系统肿瘤的 64%。有微弱的证据表明中枢神经系统肿瘤发生率与模型暴露于背景电离辐射(RR/SD 差异 1.17;0.98-1.40)和 SEP(1.6;1.00-1.13)之间存在关联。结论 在所研究的诊断组中,儿童中枢神经系统肿瘤表现出最大的空间变异。 所选协变量仅部分解释了观察到的中枢神经系统肿瘤的变化,表明其他环境因素也发挥了作用。
更新日期:2020-04-22
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