Schmittdiel Julie A, Dyer Wendy T, Marshall Cassondra J, Bivins Roberta
Research Scientist at the Kaiser Permanente Northern California Division of Research in Oakland (
Senior Data Consultant at the Kaiser Permanente Northern California Division of Research in Oakland (
Perm J. 2018;22:18-096. doi: 10.7812/TPP/18-096.
Research on predictors of clinical outcomes usually focuses on the impact of individual patient factors, despite known relationships between neighborhood environment and health.
To determine whether US census information on where a patient resides is associated with diabetes development among patients with prediabetes.
Retrospective cohort study of all 157,752 patients aged 18 years or older from Kaiser Permanente Northern California with laboratory-defined prediabetes (fasting plasma glucose, 100 mg/dL-125 mg/dL, and/or glycated hemoglobin, 5.7%-6.4%). We assessed whether census data on education, income, and percentage of households receiving benefits through the US Department of Agriculture's Supplemental Nutrition Assistance Program (SNAP) was associated with diabetes development using logistic regression controlling for age, sex, race/ethnicity, blood glucose levels, and body mass index.
Progression to diabetes within 36 months.
Patients were more likely to progress to diabetes if they lived in an area where less than 16% of adults had obtained a bachelor's degree or higher (odds ratio [OR] =1.22, 95% confidence interval [CI] = 1.09-1.36), where median annual income was below $79,999 (OR = 1.16 95% CI = 1.03-1.31), or where SNAP benefits were received by 10% or more of households (OR = 1.24, 95% CI = 1.1-1.4).
Area-level socioeconomic and food assistance data predict the development of diabetes, even after adjusting for traditional individual demographic and clinical factors. Clinical interventions should take these factors into account, and health care systems should consider addressing social needs and community resources as a path to improving health outcomes.
尽管已知邻里环境与健康之间存在关联，但临床结局预测因素的研究通常侧重于个体患者因素的影响。
确定美国人口普查中患者居住地点的信息是否与糖尿病前期患者的糖尿病发生有关。
对加利福尼亚州北部凯撒医疗集团18岁及以上的所有157752例实验室确诊为糖尿病前期（空腹血糖100mg/dL - 125mg/dL和/或糖化血红蛋白5.7% - 6.4%）的患者进行回顾性队列研究。我们使用逻辑回归分析，在控制年龄、性别、种族/族裔、血糖水平和体重指数的情况下，评估关于教育、收入以及通过美国农业部补充营养援助计划（SNAP）获得福利的家庭百分比的人口普查数据是否与糖尿病发生有关。
36个月内进展为糖尿病。
如果患者居住在以下地区，则更有可能进展为糖尿病：成年人中获得学士学位或更高学位的比例低于16%的地区（优势比[OR]=1.22，95%置信区间[CI]=1.09 - 1.36）；年中位数收入低于79999美元的地区（OR = 1.16，95% CI = 1.03 - 1.31）；或10%或更多家庭领取SNAP福利的地区（OR = 1.24，95% CI = 1.1 - 1.4）。
即使在调整了传统的个体人口统计学和临床因素之后，地区层面的社会经济和食品援助数据仍可预测糖尿病的发生。临床干预应考虑这些因素，医疗保健系统应考虑将满足社会需求和社区资源作为改善健康结局的途径。
