McDaniel Cassidi C, Lo-Ciganic Wei-Hsuan, Garza Kimberly B, Kavookjian Jan, Fox Brent I, Chou Chiahung
Department of Health Outcomes Research and Policy, Harrison College of Pharmacy, Auburn University, Auburn, AL, United States.
Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, Gainesville, FL, United States.
Front Med (Lausanne). 2023 May 31;10:1158454. doi: 10.3389/fmed.2023.1158454. eCollection 2023.
Based on the long-lasting diabetes management challenges in the United States, the objective was to examine glycemic levels among a nationally representative sample of people with diabetes stratified by prescribed antihyperglycemic treatment regimens and contextual factors.
This serial cross-sectional study used United States population-based data from the 2015 to March 2020 National Health and Nutrition Examination Surveys (NHANES). The study included non-pregnant adults (≥20 years old) with non-missing A1C and self-reported diabetes diagnosis from NHANES. Using A1C lab values, we dichotomized the outcome of glycemic levels into <7% versus ≥7% (meeting vs. not meeting guideline-based glycemic levels, respectively). We stratified the outcome by antihyperglycemic medication use and contextual factors (e.g., race/ethnicity, gender, chronic conditions, diet, healthcare utilization, insurance, etc.) and performed multivariable logistic regression analyses.
The 2042 adults with diabetes had a mean age of 60.63 (SE = 0.50), 55.26% (95% CI = 51.39-59.09) were male, and 51.82% (95% CI = 47.11-56.51) met guideline-based glycemic levels. Contextual factors associated with meeting guideline-based glycemic levels included reporting an "excellent" versus "poor" diet (aOR = 4.21, 95% CI = 1.92-9.25) and having no family history of diabetes (aOR = 1.43, 95% CI = 1.03-1.98). Contextual factors associated with lower odds of meeting guideline-based glycemic levels included taking insulin (aOR = 0.16, 95% CI = 0.10-0.26), taking metformin (aOR = 0.66, 95% CI = 0.46-0.96), less frequent healthcare utilization [e.g., none vs. ≥4 times/year (aOR = 0.51, 95% CI = 0.27-0.96)], being uninsured (aOR = 0.51, 95% CI = 0.33-0.79), etc.
Meeting guideline-based glycemic levels was associated with medication use (taking vs. not taking respective antihyperglycemic medication classes) and contextual factors. The timely, population-based estimates can inform national efforts to optimize diabetes management.
基于美国长期存在的糖尿病管理挑战，本研究旨在调查按规定的降糖治疗方案和背景因素分层的全国代表性糖尿病患者样本中的血糖水平。
这项系列横断面研究使用了2015年至2020年3月美国国家健康与营养检查调查（NHANES）中基于人群的数据。该研究纳入了NHANES中年龄≥20岁、A1C数据无缺失且自我报告有糖尿病诊断的非妊娠成年人。利用A1C实验室值，我们将血糖水平结果分为<7%和≥7%（分别为达到与未达到基于指南的血糖水平）。我们按降糖药物使用情况和背景因素（如种族/民族、性别、慢性病、饮食、医疗保健利用、保险等）对结果进行分层，并进行多变量逻辑回归分析。
2042名糖尿病成年人的平均年龄为60.63岁（标准误=0.50），55.26%（95%置信区间=51.39-59.09）为男性，51.82%（95%置信区间=47.11-56.51）达到基于指南的血糖水平。与达到基于指南的血糖水平相关的背景因素包括报告“优秀”与“差”的饮食（调整后比值比=4.21，95%置信区间=1.92-9.25）以及无糖尿病家族史（调整后比值比=1.43，95%置信区间=1.03-1.98）。与达到基于指南的血糖水平几率较低相关的背景因素包括使用胰岛素（调整后比值比=0.16，95%置信区间=0.10-0.26）、使用二甲双胍（调整后比值比=0.66，95%置信区间=0.46-0.96）、医疗保健利用频率较低[例如，从不与≥每年4次相比（调整后比值比=0.51，95%置信区间=0.27-0.96）]、未参保（调整后比值比=0.51，95%置信区间=0.33-0.79）等。
达到基于指南的血糖水平与药物使用（使用与未使用相应降糖药物类别）和背景因素相关。这些基于人群的及时估计可为国家优化糖尿病管理的努力提供信息。
