Kosteria Ioanna, Jarosz-Chobot Przemyslawa, de Beaufort Carine, Barrett Timothy G, Becker Marianne, Cameron Fergus, Castaño Luis A, Castro-Correia Cintia, Palmert Mark, Polanska Joanna, Särnblad Stefan, Skinner Timothy C, Svensson Jannet
Department of Endocrinology, Diabetes and Metabolism, First Department of Pediatrics, National and Kapodistrian University of Athens, Athens, Greece.
Faculty of Medicine, Department of Children's Diabetology, Medical University of Silesia, Katowice, Poland.
Horm Res Paediatr. 2025 Apr 24:1-9. doi: 10.1159/000545419.
This study examined the possible association between numeracy skills and glycemic outcomes in children with type 1 diabetes.
The study used a cross-sectional design and collected data from 7 centers of the Hvidoere Study Group. HbA1c was measured centrally. Numeracy was assessed using the specific 5-item Diabetes Numeracy Test (DNT-5) and the international, general Wordless Mathematical Test (WMT). The HbA1c predictive multivariate generalized linear model was constructed using the adjusted R-squared index for model selection. Pearson's correlation coefficient was calculated between observed and predicted HbA1c levels in the training and testing datasets.
Overall,306 adolescents aged 12-18 (mean age 14.96 ± 1.68) years and diabetes duration of 6.57 (±3.75) participated in this study. Numeracy skills, as assessed by the WMT but not DNT-5, predicted the HbA1c levels after adjustment for sociodemographic and clinical factors. The correlation between observed and predicted HbA1c levels was consistent in both datasets and was 0.34 (N = 155) and 0.37 (N = 61) for the training and test datasets, respectively (p = 0.412). The effect size for the WMT-based predictive model of HbA1c adjusted for clinical and socioeconomic factors was significantly higher (p < 0.05) than the single-parameter-based model.
Numeracy, as assessed by an international general math test, is a good predictor of HbA1c in children and adolescents with type 1 diabetes. The basic and short WMT is a potentially effective tool in personalized clinical pediatric diabetes practice. Therapy planning should consider adjusting therapy to compensate for lower numeracy skills and/or training to improve the patient's numerical proficiency.
本研究探讨1型糖尿病患儿的计算能力与血糖控制结果之间的可能关联。
本研究采用横断面设计,从7个Hvidoere研究小组中心收集数据。糖化血红蛋白(HbA1c)在中心实验室进行检测。计算能力通过特定的5项糖尿病计算能力测试(DNT-5)和国际通用的无文字数学测试(WMT)进行评估。使用调整后的R平方指数构建HbA1c预测多元广义线性模型以进行模型选择。在训练和测试数据集中计算观察到的和预测的HbA1c水平之间的Pearson相关系数。
总体而言,306名年龄在12至18岁(平均年龄14.96±1.68岁)、糖尿病病程为6.57(±3.75)年的青少年参与了本研究。经WMT而非DNT-5评估的计算能力,在调整社会人口统计学和临床因素后可预测HbA1c水平。在两个数据集中,观察到的和预测的HbA1c水平之间的相关性是一致的,训练数据集和测试数据集的相关系数分别为0.34(N = 155)和0.37(N = 61)(p = 0.412)。针对临床和社会经济因素调整后的基于WMT的HbA1c预测模型的效应大小显著高于单参数模型(p < 0.05)。
通过国际通用数学测试评估的计算能力是1型糖尿病儿童和青少年HbA1c的良好预测指标。简短的基础WMT在个性化临床儿科糖尿病实践中是一种潜在有效的工具。治疗计划应考虑调整治疗以弥补较低的计算能力和/或进行培训以提高患者的数字能力。