A Geotemporospatial and Causal Inference Epidemiological Exploration of Substance and Cannabinoid Exposure as Drivers of Rising US Pediatric Cancer Rates - Dataset

Data support a paper of this title:

A Geotemporospatial and Causal Inference Epidemiological Exploration of Substance and Cannabinoid Exposure as Drivers of Rising US Pediatric Cancer Rates

Data represent a compilation of various data inputs from numerous sources including the National Cancer Institute SEER*Stat National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database: NPCR and SEER Incidence – U.S. Cancer Statistics Public Use Research Database, 2019 submission (2001-2017), United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Released June 2020. Available at www.cdc.gov/cancer/public-use program; the National survey of Drug Use and Health conducted by the Substance Abuse and Mental Health Services Administration; and the US Census bureau.

Data also include inverse probability weights for cannabis exposure.

Data also include their geospatial linkage network constructed for all US states which makes Alaska and Hawaii spatially connected to the contiguous USA.

Data also include the R script used to conduct and prepare the analysis.

本数据集支撑一篇题为《美国儿科癌症发病率上升驱动因素：物质与大麻素暴露的地理时空因果推断流行病学探索》的学术论文。
本数据集整合了多来源的各类数据，具体包括：美国国家癌症研究所（National Cancer Institute, NCI）的SEER*Stat 国家癌症登记项目（National Program of Cancer Registries, NPCR）与监测、流行病学与最终结果（Surveillance, Epidemiology, and End Results, SEER）SEER*Stat 数据库：《NPCR与SEER发病率——美国癌症统计公共使用研究数据库》，2019年提交版（覆盖2001-2017年），由美国卫生与公众服务部（United States Department of Health and Human Services）、疾病控制与预防中心（Centers for Disease Control and Prevention, CDC）及美国国家癌症研究所联合发布，2020年6月公开，访问地址为www.cdc.gov/cancer/public-use program；由物质滥用与精神卫生服务管理局（Substance Abuse and Mental Health Services Administration, SAMHSA）开展的全国药物使用与健康调查（National Survey of Drug Use and Health）；以及美国人口普查局（US Census Bureau）提供的数据。
数据集还包含针对大麻暴露的逆概率权重（inverse probability weights）。
数据集还构建了覆盖全美各州的空间关联网络（geospatial linkage network），将阿拉斯加州与夏威夷州与美国本土48州实现空间连接。
数据集还包含用于开展分析与数据预处理的R脚本（R script）。