背景:发育性创伤取决于几个因素,可能会导致以后的成人健康风险,并且是一个日益增加的公共卫生问题,尤其是在以农村人口为主的州。俄克拉荷马州仍然是美国ACE数量最高的州之一,因此,量化ACEs的更精细的研究方法对于确保全州范围内的适当干预措施至关重要.
目标:虽然在州一级已经存在测量离婚或虐待儿童等特定ACE的数据集,该州目前缺乏特定ACEs的单一来源,该来源可以纳入地区,以识别ACEs特别高的县。这个县的识别将允许评估逆境患病率随着时间的推移的趋势,指出应在何处进行有针对性的干预措施,以及哪些县经历了高ACE率的长期后果。因此,俄克拉荷马州逆境监测指数系统(OASIS)的模型诞生了-一种公共卫生工具,可以在县级绘制ACE图,并随时间按严重程度对其进行分级。
方法:六个ACE的县级数据(精神疾病,离婚,疏忽,虐待儿童,家庭暴力,和物质使用)是从俄克拉荷马州人类服务部收集的,俄克拉荷马州卫生部,和俄克拉荷马州社区心理健康中心2010-2018年。首先,a潜在ACEs评分(PAS)是通过对每个ACE的县比率进行标准化和求和来创建的。为了检查PAS的时间变化,进行了双变量回归分析.此外,ACEs严重程度指数(ASI)是作为ACEs严重程度随时间变化的标准化衡量标准.这包括根据每个ACE的严重程度对县进行评分,并对得分进行求和以生成每个县的总体ASI。捕获分析中包括的所有ACE的严重程度。
结果:在州一级,精神疾病和物质使用率最高。回归结果显着(F=5.269,P=0.022),表明县PAS逐年增加。ASI得分的结果范围从0到6,以及俄克拉荷马州的四个县(Adair,McCurtain,马斯科吉,和匹兹堡)得分为6分。
结论:OASIS涉及识别ACE最普遍的县,允许在这些“热点”县优先考虑干预措施。此外,回归分析表明,从2010年到2018年,俄克拉荷马州的ACE呈上升趋势。未来的努力应集中在向ASI增加额外的ACE和相关的不良结果率(如暴力,医疗障碍患病率,等。)在县级,ASI得分较高。
背景:
Developmental trauma depending on several factors may lead to later adult health risks and is an increasing public health concern, especially in states with predominantly rural populations.
Oklahoma remains one of the states in America with the highest count of adverse childhood experiences (ACEs); therefore, more refined research methods for quantifying ACEs are vital for ensuring proper statewide interventions.
While data sets already exist at the state level measuring specific ACEs like divorce or child abuse, the state currently lacks a single source for specific ACEs that can incorporate regions to allow for the identification of counties where ACEs are especially high. This county identification will allow for assessing trends in adversity prevalence over time to indicate where targeted interventions should be done and which counties experience amplified long-term consequences of high ACE rates. Thus, the model for the
Oklahoma Adversity Surveillance Index System (OASIS) was born-a public health tool to map ACEs at the county level and grade them by severity over time.
County-level data for 6 ACEs (mental illness, divorce, neglect, child abuse, domestic violence, and substance use) were collected from the Oklahoma Department of Human Services,
Oklahoma State Department of Health, and
Oklahoma Community Mental Health Centers for the years 2010 to 2018. First, a potential ACEs score (PAS) was created by standardizing and summing county rates for each ACE. To examine the temporal change in the PAS, a bivariate regression analysis was conducted. Additionally, an ACEs severity index (ASI) was created as a standardized measure of ACE severity across time. This included scoring counties based on severity for each ACE individually and summing the scores to generate an overall ASI for each county, capturing the severity of all ACEs included in the analysis.
Mental illness and substance use showed the highest rates at the state level. Results from the regression were significant (F1,76=5.269; P=.02), showing that county PAS showed an increase over years. The ASI scores ranged from 0 to 6, and 4
Oklahoma counties (Adair, McCurtain, Muskogee, and Pittsburg) received a score of 6.
OASIS involves the identification of counties where ACEs are most prevalent, allowing for the prioritization of interventions in these \"hot spot\" counties. In addition, regression analysis showed that ACEs increased in
Oklahoma from 2010 to 2018. Future efforts should center on adding additional ACEs to the ASI and correlating adverse outcome rates (such as violence and medical disorder prevalence) at the county level with high ASI scores.