Howell Carrie R, Zhang Li, Clay Olivio J, Dutton Gareth, Horton Trudi, Mugavero Michael J, Cherrington Andrea L
Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.
School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States.
JMIR Public Health Surveill. 2024 Aug 7;10:e53371. doi: 10.2196/53371.
Adverse social determinants of health (SDoH) have been associated with cardiometabolic disease; however, disparities in cardiometabolic outcomes are rarely the result of a single risk factor.
This study aimed to identify and characterize SDoH phenotypes based on patient-reported and neighborhood-level data from the institutional electronic medical record and evaluate the prevalence of diabetes, obesity, and other cardiometabolic diseases by phenotype status.
Patient-reported SDoH were collected (January to December 2020) and neighborhood-level social vulnerability, neighborhood socioeconomic status, and rurality were linked via census tract to geocoded patient addresses. Diabetes status was coded in the electronic medical record using International Classification of Diseases codes; obesity was defined using measured BMI ≥30 kg/m2. Latent class analysis was used to identify clusters of SDoH (eg, phenotypes); we then examined differences in the prevalence of cardiometabolic conditions based on phenotype status using prevalence ratios (PRs).
Complete data were available for analysis for 2380 patients (mean age 53, SD 16 years; n=1405, 59% female; n=1198, 50% non-White). Roughly 8% (n=179) reported housing insecurity, 30% (n=710) reported resource needs (food, health care, or utilities), and 49% (n=1158) lived in a high-vulnerability census tract. We identified 3 patient SDoH phenotypes: (1) high social risk, defined largely by self-reported SDoH (n=217, 9%); (2) adverse neighborhood SDoH (n=1353, 56%), defined largely by adverse neighborhood-level measures; and (3) low social risk (n=810, 34%), defined as low individual- and neighborhood-level risks. Patients with an adverse neighborhood SDoH phenotype had higher prevalence of diagnosed type 2 diabetes (PR 1.19, 95% CI 1.06-1.33), hypertension (PR 1.14, 95% CI 1.02-1.27), peripheral vascular disease (PR 1.46, 95% CI 1.09-1.97), and heart failure (PR 1.46, 95% CI 1.20-1.79).
Patients with the adverse neighborhood SDoH phenotype had higher prevalence of poor cardiometabolic conditions compared to phenotypes determined by individual-level characteristics, suggesting that neighborhood environment plays a role, even if individual measures of socioeconomic status are not suboptimal.
不良健康社会决定因素（SDoH）与心脏代谢疾病相关；然而，心脏代谢结果的差异很少是由单一风险因素导致的。
本研究旨在根据机构电子病历中患者报告的数据和社区层面的数据确定SDoH表型并对其进行特征描述，并按表型状态评估糖尿病、肥胖症及其他心脏代谢疾病的患病率。
收集患者报告的SDoH（2020年1月至12月），并通过人口普查区将社区层面的社会脆弱性、社区社会经济地位和农村地区与地理编码的患者地址相联系。使用国际疾病分类代码在电子病历中对糖尿病状态进行编码；肥胖症定义为测量的体重指数（BMI）≥30kg/m²。采用潜在类别分析来确定SDoH集群（如，表型）；然后我们使用患病率比（PRs）根据表型状态检查心脏代谢疾病患病率的差异。
共有2380例患者的完整数据可供分析（平均年龄53岁，标准差16岁；n = 1405，59%为女性；n = 1198，50%为非白人）。约8%（n = 179）报告住房不安全，30%（n = 710）报告资源需求（食物、医疗保健或公用事业），49%（n = 1158）居住在高脆弱性人口普查区。我们确定了3种患者SDoH表型：（1）高社会风险，主要由自我报告的SDoH定义（n = 217，9%）；（2）不良社区SDoH（n = 1353，56%），主要由不良社区层面指标定义；（3）低社会风险（n = 810，34%），定义为个体和社区层面风险低。具有不良社区SDoH表型的患者被诊断为2型糖尿病（PR 1.19，95%CI 1.06 - 1.33）、高血压（PR 1.14，95%CI 1.02 - 1.27）、外周血管疾病（PR 1.46，95%CI 1.09 - 1.97）和心力衰竭（PR 1.46，95%CI 1.20 - 1.79）的患病率更高。
与由个体层面特征确定的表型相比，具有不良社区SDoH表型的患者心脏代谢状况不佳的患病率更高，这表明社区环境发挥了作用，即使个体社会经济地位指标并非不理想。
