Trueblood Amber B, Han Daikwon, Shipp Eva M, Cizmas Leslie H
Texas A&M Transportation Institute, Center for Transportation Safety, 3135 TAMU, College Station, TX 77845.
Texas A&M University School of Public Health, Department of Epidemiology & Biostatistics, 212 Adriance Lab Rd., College Station, TX 77843.
Environ Health Toxicol. 2018 Mar 26;33(2):e2018008. doi: 10.5620/eht.e2018008. eCollection 2018.
There is limited literature on the frequency and distribution of pesticide exposures, specifically with respect to demographic and environmental factors in the United States. The purpose of this exploratory study was to investigate geographic trends and factors associated with unintentional pesticide exposures in children and adolescents in Texas. The study used an ecological design with secondary data. A spatial scan statistic, based on a Poisson regression model, was employed to identify spatial clusters of unintentional pesticide-related poison center exposures. Next, logistic regression models were constructed to identify potential demographic and environmental factors associated with unintentional pesticide-related poison center exposures. There were 59,477 unintentional pesticide-related poison center exposures from 2000 to 2013. The spatial scan statistic found a change in the number of counties in the identified clusters (e.g. , aggregation of counties with higher than expected exposures) for two time periods (2000-2006; 2007-2013). Based on the logistic regression models, factors associated with unintentional pesticide-related poison center exposures were percent black or African American population, year structure built, and percent moved in the past 12 months. In conclusion, this study found certain demographic and environmental factors may be associated with unintentional pesticide-related poison center exposures. Through understanding trends and associated factors, public health professionals can design interventions for populations at higher risk of pesticide exposures. This study also supports the use of spatial methods being utilized to expand upon current analysis of poison center data. Future research should confirm and build upon these findings.
关于农药暴露的频率和分布，特别是在美国与人口统计学和环境因素相关的文献有限。这项探索性研究的目的是调查德克萨斯州儿童和青少年非故意农药暴露的地理趋势及相关因素。该研究采用生态设计并使用二手数据。基于泊松回归模型的空间扫描统计量被用于识别非故意农药相关中毒控制中心暴露的空间聚集区。接下来，构建逻辑回归模型以识别与非故意农药相关中毒控制中心暴露相关的潜在人口统计学和环境因素。2000年至2013年期间有59477次非故意农药相关中毒控制中心暴露。空间扫描统计量发现，在两个时间段（2000 - 2006年；2007 - 2013年），已识别聚集区（例如，暴露高于预期的县的聚集）中的县数量发生了变化。基于逻辑回归模型，与非故意农药相关中毒控制中心暴露相关的因素有黑人或非裔美国人人口百分比、建筑年份结构以及过去12个月内迁移的百分比。总之，本研究发现某些人口统计学和环境因素可能与非故意农药相关中毒控制中心暴露有关。通过了解趋势和相关因素，公共卫生专业人员可以为农药暴露风险较高的人群设计干预措施。本研究还支持利用空间方法来扩展当前对中毒控制中心数据的分析。未来的研究应证实并在此基础上进一步拓展这些发现。
