Assessing health disparities in children using a modified housing-related socioeconomic status measure: a cross-sectional study.
Assessing health disparities in children using a modified housing-related socioeconomic status measure: a cross-sectional study.
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使用修改后的与住房相关的社会经济地位指标评估儿童的健康差异：一项横断面研究。
DOI：
10.1136/bmjopen-2016-011564
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发表时间：
2016
期刊：
影响因子：
2.9
通讯作者：
Juhn,YoungJ
中科院分区：
文献类型：
--
作者：
Ryu,Euijung;Wi,Chung-Il;Crow,SheriS;Armasu,SebastianM;Wheeler,PhilipH;Sloan,JeffA;Yawn,BarbaraP;Beebe,TimothyJ;Williams,ArthurR;Juhn,YoungJ
社会经济地位（SES）是一个公认的危险因素，许多健康结果。最近，我们开发了一种基于4个住房相关特征（称为房屋）的SES测量方法，并证明了其评估健康差异的能力。在这项研究中，我们的目的是评估是否可以使用较少的住房相关特征来提供类似的SES.Study设置和participantsWe进行了一项横断面研究，使用来自美国中西部两个县的1-17岁儿童的父母/监护人 （明尼苏达州奥姆斯特德县n=728，密苏里州杰克逊县n=701）。在制定住房计划时使用的与住房有关的特征（评估的房屋价值，平方英尺，卧室数量和浴室数量）从当地政府评估员办公室获得，以及与SES已知关联的其他SES测量和健康结果。（肥胖、低出生体重和吸烟暴露）从电话调查中收集。住房的特点，最大的贡献预测的健康outcomes被添加到制定一个修改后的HOUSES index.ResultsAmong的4个住房特征中使用的原始HOUSES，最强的贡献预测健康结果观察评估的住房价值和平方英尺（合并贡献范围为89%和96%之间）。根据这一观察结果，这两个被用来计算修改后的HOUSES指数。修改后的房屋和其他SES措施之间的相关性与两个地点的原始房屋相当。与最初的HOUSES公式一致，在吸烟暴露中观察到与改良HOUSES的最强关联（OR=0.24，95%CI 0.11至0.49，用于比较最高家庭与最低家庭的参与者;总体p<0.001）结论修改后的HOUSES只需要2个现成的住房特征，从而提高了使用该指数作为SES代理的可行性，多个社区，特别是在美国中西部地区。
ObjectivesSocioeconomic status (SES) is a well-established risk factor for many health outcomes. Recently, we developed an SES measure based on 4 housing-related characteristics (termed HOUSES) and demonstrated its ability to assess health disparities. In this study, we aimed to evaluate whether fewer housing-related characteristics could be used to provide a similar representation of SES.Study setting and participantsWe performed a cross-sectional study using parents/guardians of children aged 1–17 years from 2 US Midwestern counties (n=728 in Olmsted County, Minnesota, and n=701 in Jackson County, Missouri).Primary and secondary outcome measuresFor each participant, housing-related characteristics used in the formulation of HOUSES (assessed housing value, square footage, number of bedrooms and number of bathrooms) were obtained from the local government assessor's offices, and additional SES measures and health outcomes with known associations to SES (obesity, low birth weight and smoking exposure) were collected from a telephone survey. Housing characteristics with the greatest contribution for predicting the health outcomes were added to formulate a modified HOUSES index.ResultsAmong the 4 housing characteristics used in the original HOUSES, the strongest contributions for predicting health outcomes were observed from assessed housing value and square footage (combined contribution ranged between 89% and 96%). Based on this observation, these 2 were used to calculate a modified HOUSES index. Correlation between modified HOUSES and other SES measures was comparable to the original HOUSES for both locations. Consistent with the original HOUSES formula, the strongest association with modified HOUSES was observed with smoking exposure (OR=0.24 with 95% CI 0.11 to 0.49 for comparing participants in highest HOUSES vs lowest group; overall p<0.001).ConclusionsThe modified HOUSES requires only 2 readily available housing characteristics thereby improving the feasibility of using this index as a proxy for SES in multiple communities, especially in the US Midwestern region.