Community credit scores and community socioeconomic deprivation in association with type 2 diabetes across an urban to rural spectrum in Pennsylvania: a case–control study

Melissa N. Poulsen, Annemarie G. Hirsch, Lorraine Dean, J. Pollak, Joseph Dewalle, Katherine Moon, Meghann Reeder, K. Bandeen-Roche, Brian S Schwartz
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Abstract

Area-level credit scores (the mean of credit scores for persons in a community) may be a unique indicator of community-level socioeconomic conditions associated with health outcomes. We analysed community credit scores (CCS) in association with new onset type 2 diabetes (T2D) across a geographically heterogeneous region of Pennsylvania and evaluated whether associations were independent of community socioeconomic deprivation (CSD), which is known to be related to T2D risk.In a nested case–control study, we used medical records to identify 15 888 T2D cases from diabetes diagnoses, medication orders and laboratory test results and 79 435 diabetes-free controls frequency matched on age, sex and encounter year. CCS was derived from Equifax VantageScore V.1.0 data and categorised as ‘good’, ‘high fair’, ‘low fair’ and ‘poor’. Individuals were geocoded and assigned the CCS of their residential community. Logistic regression models adjusted for confounding variables and stratified by community type (townships (rural/suburban), boroughs (small towns) and city census tracts). Independent associations of CSD were assessed through models stratified by high/low CSD and high/low CCS.Compared with individuals in communities with ‘high fair’ CCS, those with ‘good’ CCS had lower T2D odds (42%, 24% and 12% lower odds in cities, boroughs and townships, respectively). Stratified models assessing independent effects of CCS and CSD showed mainly consistent associations, indicating each community-level measure was independently associated with T2D.CCS may capture novel, health-salient aspects of community socioeconomic conditions, though questions remain regarding the mechanisms by which it influences T2D and how these differ from CSD.
宾夕法尼亚州从城市到农村的社区信用评分和社区社会经济贫困与 2 型糖尿病的关系:一项病例对照研究
地区级信用分数(一个社区内个人信用分数的平均值)可能是衡量与健康结果相关的社区级社会经济条件的独特指标。在一项嵌套病例对照研究中,我们利用医疗记录从糖尿病诊断、用药单和实验室检测结果中识别出 15 888 例 2 型糖尿病病例,并根据年龄、性别和就诊年份对 79 435 例无糖尿病对照进行了频率匹配。CCS来自Equifax VantageScore V.1.0数据,分为 "良好"、"尚可"、"尚可偏低 "和 "较差"。对个人进行地理编码并分配其居住社区的 CCS。逻辑回归模型对混杂变量进行了调整,并按社区类型(乡镇(农村/郊区)、区(小城镇)和城市人口普查区)进行了分层。通过高/低CSD和高/低CCS分层模型评估了CSD的独立相关性。与CCS "高一般 "社区的个人相比,CCS "好 "社区的个人患T2D的几率较低(城市、行政区和乡镇的几率分别低42%、24%和12%)。评估CCS和CSD独立影响的分层模型主要显示了一致的关联,表明每个社区水平的测量值都与T2D有独立的关联。CCS可能捕捉到了社区社会经济条件中新的、有利于健康的方面,但它对T2D的影响机制以及这些机制与CSD有何不同仍存在疑问。
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