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首页> 外文期刊>International Journal of Population Data Science >Identifying Household Level Risk Factors for Unintentional House Fire Incidents, Injuries and Fatalities
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Identifying Household Level Risk Factors for Unintentional House Fire Incidents, Injuries and Fatalities

机译:确定家庭意外火灾事故,伤害和死亡的风险因素

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ABSTRACTObjectivesUnintentional house fire incidents, injuries and deaths are a serious public health concern in the UK, which disproportionally affect certain groups in the population. Whilst house fires have decreased in recent years; growing financial pressures in the Fire and Rescue Services (FRSs) have resulted in funds dedicated to fire preventative activities becoming increasingly limited. To ensure ever limiting resources are targeted towards those households at greatest risk, it is essential the FRSs’ are accurately informed about the types of household at increased risk. The aim of this project is to undertake a large-scale case-control study, to identify the distinguishing household level risk factors associated with unintentional house fire incidents, injuries and deaths. ApproachUnintentional house fire incidents reported to the Welsh FRS between the years 2003-2008, were anonymised and incorporated into the Secure Anonymised Information Linkage (SAIL) Databank at the Farr Institute, Swansea University. 6943 case households (households which reported a fire to the FRS) were time-matched to 347,150 control households (case:control ratio 1:50). Individuals registered as living at these properties on the date of the fire were established using the Welsh Demographic Service (WDS) dataset. Household level variables will be created by linking case and control households to other demographic, health, educational and environmental datasets in SAIL. Conditional Logistic Regression will be used to estimate matched odds ratios and 95% confidence intervals. ResultsPotential risk factor variables were selected on the basis of a systematic review and theoretically plausible variables. Covariates include: household composition (e.g. age and gender of residents), socioeconomic status, educational attainment, smoking, alcohol consumption, mental health conditions, other health related conditions, mobility and sensory impairments and property related characteristics. Fire related circumstances (e.g. fire ignition source, presence of a smoke alarm) will also be investigated in logistic regression models exploring risk factors for injury and death. Results will be presented at the conference. ConclusionThis is the first large-scale analysis of risk factors for unintentional house fire incidents, injuries and deaths. The findings from this project will be translated into comprehensible infographics, designed to support the FRSs, other partner organisations and the general public, recognise high risk households in need of preventative interventions.
机译:摘要目标在英国,无意的房屋火灾,人身伤害和死亡是严重的公共卫生问题,对人口中的某些群体造成了不成比例的影响。近年来房屋火灾有所减少;消防和救援服务(FRS)中越来越大的财务压力导致用于灭火活动的资金越来越有限。为了确保将有限的资源用于那些面临最大风险的家庭,必须向FRS准确告知有关面临风险增加的家庭类型的信息。该项目的目的是进行大规模的病例对照研究,以识别与房屋意外火灾,伤害和死亡相关的不同的家庭风险因素。方法2003年至2008年间向威尔士FRS报告的意外房屋火灾事件被匿名化,并被合并到斯旺西大学法尔研究所的安全匿名信息链接(SAIL)数据库中。 6943个案例家庭(向FRS报告了火灾的家庭)与347150个对照家庭(案例:控制比率1:50)在时间上相匹配。使用威尔士人口统计服务(WDS)数据集确定在火灾发生时在这些财产上居住的个人。通过将案例和控制家庭与SAIL中的其他人口,健康,教育和环境数据集相关联,可以创建家庭级别变量。条件对数回归将用于估计匹配的优势比和95%的置信区间。结果根据系统评价和理论上合理的变量选择了潜在的危险因素变量。协变量包括:家庭组成(例如居民的年龄和性别),社会经济状况,受教育程度,吸烟,饮酒,精神健康状况,其他与健康有关的状况,流动性和感官障碍以及与财产有关的特征。还将在逻辑回归模型中研究与火灾相关的情况(例如,火灾点火源,烟雾报警器的存在),以探索伤害和死亡的风险因素。结果将在会议上发表。结论这是首次大规模分析意外房屋火灾,受伤和死亡的危险因素。该项目的调查结果将被翻译成易于理解的图表,旨在支持FRS,其他合作伙伴组织和公众,认识到需要预防干预的高风险家庭。

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