Poulsen Melissa N, Hirsch Annemarie G, Dean Lorraine, Pollak Jonathan, DeWalle Joseph, Moon Katherine, Reeder Meghann, Bandeen-Roche Karen, Schwartz Brian S
Department of Population Health Sciences, Geisinger, Danville, Pennsylvania, USA.
Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
BMJ Public Health. 2024 Mar 28;2(1):e000744. doi: 10.1136/bmjph-2023-000744. eCollection 2024 Jun.
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.
地区层面的信用评分（社区中个人信用评分的均值）可能是与健康结果相关的社区层面社会经济状况的独特指标。我们分析了宾夕法尼亚州一个地理环境多样的地区内社区信用评分（CCS）与新发2型糖尿病（T2D）之间的关联，并评估了这些关联是否独立于社区社会经济剥夺（CSD），已知CSD与T2D风险相关。
在一项巢式病例对照研究中，我们利用医疗记录从糖尿病诊断、用药医嘱和实验室检测结果中识别出15888例T2D病例，并选取79435例无糖尿病的对照，根据年龄、性别和就诊年份进行频数匹配。CCS源自益百利信用评分V.1.0数据，并被分类为“良好”“较高一般”“较低一般”和“较差”。对个体进行地理编码，并赋予其居住社区的CCS。采用逻辑回归模型对混杂变量进行调整，并按社区类型（乡镇（农村/郊区）、自治市镇（小镇）和城市普查区）进行分层。通过按高/低CSD和高/低CCS分层的模型评估CSD的独立关联。
与CCS为“较高一般”的社区中的个体相比，CCS为“良好”的社区中的个体患T2D的几率较低（在城市、自治市镇和乡镇中，几率分别低42%、24%和12%）。评估CCS和CSD独立效应的分层模型显示出主要一致的关联，表明每个社区层面的指标都与T2D独立相关。
CCS可能反映了社区社会经济状况中与健康相关的新的重要方面，不过关于其影响T2D的机制以及这些机制与CSD有何不同仍存在问题。
