Fahey Erin, Lehna Carlee, Hanchette Carol, Coty Mary-Beth
From the *University of Louisville School of Nursing, Kentucky; and †Department of Geography and Geosciences, University of Louisville, Kentucky.
J Burn Care Res. 2016 Jul-Aug;37(4):e303-9. doi: 10.1097/BCR.0000000000000303.
The purpose of this study was to evaluate whether the sample of older adults in a home fire safety (HFS) study captured participants living in the areas at highest risk for fire occurrence. The secondary aim was to identify high risk areas to focus future HFS interventions. Geographic information systems software was used to identify census tracts where study participants resided. Census data for these tracts were compared with participant data based on seven risk factors (ie, age greater than 65 years, nonwhite race, below high school education, low socioeconomic status, rented housing, year home built, home value) previously identified in a fire risk model. The distribution of participants and census tracts among risk categories determined how well higher risk census tracts were sampled. Of the 46 census tracts where the HFS intervention was implemented, 78% (n = 36) were identified as high or severe risk according to the fire risk model. Study participants' means for median annual family income (P < .0001) and median home value (P < .0001) were significantly lower than the census tract means (n = 46), indicating participants were at higher risk of fire occurrence. Of the 92 census tracts identified as high or severe risk in the entire county, the study intervention was implemented in 39% (n = 36), indicating 56 census tracts as potential areas for future HFS interventions. The Geographic information system-based fire risk model is an underutilized but important tool for practice that allows community agencies to develop, plan, and evaluate their outreach efforts and ensure the most effective use of scarce resources.
本研究的目的是评估家庭消防安全(HFS)研究中的老年人样本是否涵盖了居住在火灾发生风险最高地区的参与者。次要目的是确定高风险区域,以便为未来的家庭消防安全干预措施提供重点。使用地理信息系统软件来识别研究参与者居住的普查区。将这些普查区的人口普查数据与基于先前在火灾风险模型中确定的七个风险因素(即年龄大于65岁、非白人种族、高中以下学历、社会经济地位低、租房、房屋建造年份、房屋价值)的参与者数据进行比较。风险类别中参与者和普查区的分布决定了高风险普查区的抽样情况。在实施家庭消防安全干预措施的46个普查区中,根据火灾风险模型,78%(n = 36)被确定为高风险或严重风险。研究参与者的家庭年收入中位数(P <.0001)和房屋价值中位数(P <.0001)的均值显著低于普查区均值(n = 46),表明参与者发生火灾的风险更高。在全县被确定为高风险或严重风险的92个普查区中,39%(n = 36)实施了研究干预措施,这表明有56个普查区是未来家庭消防安全干预措施的潜在区域。基于地理信息系统的火灾风险模型是一种未得到充分利用但对实践很重要的工具,它使社区机构能够制定、规划和评估其外展工作,并确保最有效地利用稀缺资源。