Department of Recreation, Park, and Tourism Studies, School of Public Health, Indiana University, Bloomington, IN, USA.
Department of Epidemiology and Biostatistics, School of Public Health, Indiana University, Bloomington, IN, USA.
J Community Health. 2019 Dec;44(6):1111-1119. doi: 10.1007/s10900-019-00691-0.
The purpose of this study was two-fold. First, we sought to identify spatial clusters of self-reported tick-borne disease (TBD) diagnosis in Indiana. Secondly, we determined the significant predictors of self-reported TBD diagnosis in a sample of Indiana residents. Study participants were selected from existing online panels maintained by Qualtrics and completed a cross-sectional survey (n = 3003). Our primary outcome of interest was self-reported TBD diagnosis (Yes/No). Cases and background population were aggregated to the county level. We used a purely spatial discrete Poisson model in SatScan® to determine significant clusters of high-risk TBD diagnosis counties. We also used X tests in bivariate analyses, to identify potential predictor variables for inclusion in an initial model, and backward elimination selection method to identify the final model. Two clusters of counties with significant high relative risk of self-reported TBD diagnosis in the southeast and southwest of Indiana were detected. Males in Indiana were more likely to self-report TBD diagnosis compared to females. Study participants who conducted a thorough tick check after being outdoors were significantly less likely to report TBD diagnosis compared to those who did not. Increased positive perceptions of TBD personal protective measures were associated with reduced self-reported TBD diagnosis. Older study participants were less likely to self-report TBD diagnosis compared to younger participants. The identification of two clusters of TBD diagnosis in southern Indiana is consistent with a northern spread of TBDs and suggests a need for continued surveillance of the counties in the vicinity of the observed clusters. Future studies should be designed to identify risk factors for TBD diagnosis in the affected counties of Indiana.
本研究旨在实现两个目标。首先，我们试图确定印第安纳州报告的蜱传疾病（TBD）诊断的空间聚集。其次，我们确定了印第安纳州居民样本中报告的 TBD 诊断的显著预测因素。研究参与者从 Qualtrics 维护的现有在线小组中选择，并完成了一项横断面调查（n=3003）。我们感兴趣的主要结果是自我报告的 TBD 诊断（是/否）。病例和背景人群被汇总到县一级。我们使用 SatScan®中的纯空间离散泊松模型来确定具有高风险 TBD 诊断的县的显著聚类。我们还在双变量分析中使用 X 检验，以确定潜在的预测变量，包括在初始模型中，并使用向后消除选择方法来确定最终模型。在印第安纳州东南部和西南部发现了两个具有显著高相对风险的 TBD 诊断的县集群。与女性相比，印第安纳州的男性更有可能自我报告 TBD 诊断。与未进行彻底蜱检查的人相比，在户外活动后进行彻底蜱检查的研究参与者报告 TBD 诊断的可能性显著降低。对 TBD 个人防护措施的积极看法与降低自我报告的 TBD 诊断相关。与年轻参与者相比，年龄较大的研究参与者自我报告 TBD 诊断的可能性较低。在印第安纳州南部发现的两个 TBD 诊断集群与 TBD 的北部传播一致，表明需要继续监测观察到的集群附近的县进行监测。未来的研究应旨在确定印第安纳州受影响县 TBD 诊断的风险因素。
