Steffen Møllegaard Iversen

Prevalence of Fasting Hyperglycemia and Known Non-Insulin-Dependent Diabetes Mellitus Classified by Plasma C-Peptide: Fredericia Survey of Subjects 60–74 Yr Old

A Danish population of 5699 individuals (60–74 yr old) was screened by fasting blood glucose (FBG) and interviewed about known diabetes. The distribution of FBG in individuals not known to have diabetes showed no sex difference or significant variation with age. Fasting hyperglycemia (FH), defined as FBG ≥ 7 mM in subjects without a history of diabetes, was found in 1.7% of men and women. Known diabetes (KD) had a prevalence of 3.9 and 5.0% in men and women, respectively. The prevalence rates of FH and KD increased significantly with age. In the two subgroups, plasma C-peptide was measured after overnight fasting and subsequently 6 min after an intravenous injection of glucagon. Based on the distribution of the C-peptide concentrations in non-insulin-treated KD subjects, lower limits for non-insulin-dependent diabetes mellitus (NIDDM) of 0.30 pmol/ml for fasting C-peptide and 0.60 pmol/ml for stimulated C-peptide were arbitrarily chosen. According to these cutoff points, only 38.5% of KD subjects treated with insulin had insulin-dependent diabetes mellitus, corresponding to 9.3% of all KD subjects. After exclusion of these patients, the prevalence of recognized NIDDM was 3.5% in men and 4.5% in women. All FH subjects except one had C-peptide values in the NIDDM interval. A close agreement between fasting and glucagon-stimulated C-peptide was seen. In epidemiological studies with an expected high prevalence of NIDDM, we propose to use fasting C-peptide for classification of patients with insulin-treated diabetes.

Simple thinking using complex math vs. complex thinking using simple math—A study using model eliciting activities to compare students' abilities in standardized tests to their modelling abilities

Traditional mathematics assessments often fail to identify students who can powerfully and effectively apply mathematics to real-world problems, and many students who excel on traditional assessments often struggle to implement their mathematical knowledge in real-world settings (Lesh & Sriraman, 2005a). This study employs multi-tier design-based research methodologies to explore this phenomenon from a models and modeling perspective. At the researcher level, a Model Eliciting Activity MEA) was developed as a means to measure student performance on a complex real-world task. Student performance data on this activity and on traditional pre- and post-tests were collected from approximately 200 students enrolled in a second semester calculus course in the Science and Engineering department of the University of Southern Denmark during the winter of 2005. The researchers then used the student solutions to the MEA to develop tools for capturing and assessing the strengths and weaknesses of the mathematical models present in these solutions. Performance on the MEA, pre- and post-test were then analyzed both quantitatively and qualitatively to identify trends in the subgroups corresponding to those described by lesh and Sriraman.