改善住房质量,降低哮喘发病率和医疗费用在雅典-克拉克县,GA

S. Harris, J. M. Johnston, M. Bowie, G. Adams
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摘要

背景:哮喘是一种慢性呼吸道疾病,通常由可控的环境因素发展而来,如空气质量差。我们的研究调查了影响室内空气质量的家中霉菌与佐治亚州雅典克拉克县哮喘患病率之间的关系。方法:雅典健康项目2016年对ACC 1354户家庭的调查数据用于检查ACC的室内空气质量和哮喘患病率。我们提供了描述性统计数据来检查哮喘患病率和哮喘预测因素,包括报告霉菌和害虫问题、吸烟率、,以及报告临床肥胖的家庭比例。我们还研究了人口特征,包括种族和民族、教育程度、住房所有权状况,以及185%联邦贫困线下的贫困家庭百分比。然后,我们采用逻辑回归分析来评估哮喘与住房质量之间的关系。结果:描述性统计数据显示,7%的ACC人口,17%的家庭,报告家中至少有一人被诊断为哮喘,9%的县人口在家中出现霉菌问题。Logistic回归分析显示,报告霉菌问题的家庭报告至少有一人被诊断患有哮喘的可能性高出11%。教育程度和肥胖也与哮喘显著相关,尽管对哮喘的预测不如霉菌。结论:ACC的室内空气质量与哮喘患病率之间存在很强的统计相关性。通过干预霉菌来改善住房质量有可能降低哮喘发病率,从而提高个人和社区的幸福感。我们的研究结果对乔治亚州和美国有影响,因为哮喘的患病率在整个州都是可比的。这项研究补充了大量关注室内空气质量与哮喘之间联系的文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Housing Quality to Reduce Asthma Rates and Healthcare Costs in Athens-Clarke County, GA
Background: Asthma is a chronic respiratory condition that often develops from controllable environmental factors, such as poor air quality. Our study examined the relationship between mold in the home, which compromises indoor air quality, and asthma prevalence in Athens-Clarke County (ACC), Georgia. Methods: Data from the Athens Wellbeing Project’s 2016 survey of 1,354 households in ACC was employed to examine indoor air quality and asthma prevalence in ACC. We provided descriptive statistics to examine asthma prevalence and asthma predictors, including the proportion of respondents reporting mold and pest problems, smoking prevalence, and the proportion of households reporting clinical obesity. We also examined demographic characteristics including race and ethnicity, educational attainment, home ownership status, and the percent of households in poverty at the 185% federal poverty line. We then employed a logistic regression analysis to assess the relationship between asthma and housing quality. Results: The descriptive statistics showed that seven percent of the ACC population, 17% of households, reported there was at least one individual in the home diagnosed with asthma and nine percent of the county population experienced mold problems in the home. Logistic regression analysis showed households that reported mold problems were 11% more likely to report at least one person in the household had been diagnosed with asthma. Educational attainment and obesity were also significantly associated with asthma, though not as predictive of asthma as mold. Conclusions: Strong statistical associations were found between indoor air quality and asthma prevalence in ACC. Improving housing quality by intervening on mold has the potential to reduce asthma rates, thereby increasing individual and community wellbeing. Our results have implications for the state of Georgia and the United States, as asthma prevalence is comparable throughout. This research adds to the body of literature focusing on the link between indoor air quality and asthma.
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