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首页> 外文期刊>Preventive Medicine: An International Journal Devoted to Practice and Theory >Evaluating the utility of self-reported questionnaire data to screen for dysglycemia in young adults: Findings from the US National Health and Nutrition Examination Survey
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Evaluating the utility of self-reported questionnaire data to screen for dysglycemia in young adults: Findings from the US National Health and Nutrition Examination Survey

机译：评估自我报告的问卷数据对年轻成年人泌尿外科筛查的效用：来自美国国家健康和营养考试调查的调查结果

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摘要

Dysglycemia, including prediabetes and type 2 diabetes, is dangerous and widespread. Yet, the condition is transiently reversible and sequelae preventable, prompting the use of prediction algorithms to quickly assess dysglycemia status through self-reported data. However, as current algorithms have largely been developed in older populations, their application to younger adults is uncertain considering associations between risk factors and dysglycemia vary by age. We sought to identify sex-specific predictors of current dysglycemia among young adults and evaluate their ability to screen for prediabetes and undiagnosed diabetes. We analyzed 2005-2014 data from the National Health and Nutrition Examination Survey for 3251 participants aged 20-39, who completed an oral glucose tolerance test (OGTT), had not been diagnosed with diabetes, and, for females, were not pregnant. Sex-specific stepwise logistic models were fit with predictors identified from univariate analyses. Risk scores were developed using adjusted odds ratios and model performance was assessed using area under the curve (AUC) measures. The OGTT identified 906 (27.9%) and 78 (2.4%) participants with prediabetes or undiagnosed diabetes, respectively. Predictors of dysglycemia status for males were BMI, age, race, and first-degree family history of diabetes, and, in addition to those, education, delivered baby weight, waist circumference, and vigorous physical activity for females. Our male- and female-specific models demonstrated improved validity to assess dysglycemia presence among young adults relative to the widely-used American Diabetes Association test (AUC = 0.69 vs. 0.61; 0.92 vs. 0.71, respectively). Thus, age-specific scoring algorithms employing questionnaire data show promise and are effective in identifying dysglycemia among young adults.
机译：困难患者，包括前奶脂和2型糖尿病，是危险和普遍的。然而，该病症是瞬时可逆和后遗症的可预防，促使使用预测算法通过自我报告的数据快速评估障碍血糖状态。然而，由于目前的算法在很大程度上在较旧的群体中开发出来，他们对年轻成年人的应用是不确定的，考虑到风险因素和软血糖之间的关联因年龄而异。我们试图识别年轻成年人中当前肿瘤血糖的性别特异性预测因子，并评估它们筛选前奶油和未确诊糖尿病的能力。我们分析了2005 - 2014年，来自国家卫生和营养考试调查的数据，为3251岁的参与者进行了20-39岁的参与者，他完成了口服葡萄糖耐量试验（OGTT），未被诊断出患有糖尿病，而且为女性，没有怀孕。性别特定的逐步物流模型适合从单变量分析中识别的预测器。使用调整的差异比率开发风险评分，并使用曲线（AUC）措施下的面积评估模型性能。 OGTT分别鉴定了906（27.9％）和78名（2.4％）参与者分别与前奶油病或未确诊的糖尿病。患有患者的嗜失性血糖状态的预测因素是BMI，年龄，种族和糖尿病的一级家族史，以及除了那些教育，提供婴儿体重，腰围和女性的剧烈体力活动之外。我们的男性和女性特定模型表明，在相对于广泛使用的美国糖尿病协会测试中评估年轻成年人的患有嗜毒血症存在的有效性（AUC = 0.69 V.0.61; 0.92与0.71分别）。因此，使用调查问卷数据显示的年龄特异性评分算法展示并有效地识别年轻成年人中的患有患有血糖。

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