Differential clusters of modifiable risk factors for impaired fasting glucose <i>versus</i> impaired glucose tolerance in adults 50 years of age and older
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to identify modifiable risk factors associated with isolated impaired fasting glucose (IFG), isolate impaired glucose tolerance (IGT), or combined IFG-IGT in men and women aged 50 years and older. METHODS: Cross-sectional analyses were performed in 703 men and women aged between 50 and 80 years old from NHANES (2007-2008). Outcome variables: IFG and IGT (ADA 2003), estimated body composition, cardiometabolic profile, and socio-demographic, dietary, and lifestyle factors. RESULTS: First, 235 had normal glucose tolerance (men = 38.3%, women = 61.7%), 243 had IFG (men = 61.7%, women = 38.3%), 67 had IGT (men = 40.3%, women = 59.7%) and 158 had both conditions (men = 57.0%, women = 43.0%). The only common determinant of both IFG and IGT was triglyceride levels. High total fat mass index (FMI) and high total fat-free mass index (FFMI) were independently associated with IFG; while high C-reactive protein (CRP) levels were independently associated with IGT. Finally, combined IFG-IGT was associated with inadequate fiber intake, high FMI, FFMI, and CRP levels. CONCLUSIONS: Middle-age and older individuals presented different modifiable risk factors depending on whether they had IFG or IGT. IFG was associated with deteriorated body composition and lipids, whereas IGT was associated with deteriorated lipids and inflammatory factors. IFG-IGT, on the other hand, was associated with a larger number of risk factors, including worsen body composition, cardiometabolic and dietary factors. To prevent the transition to type 2 diabetes, specific clinical interventions targeting these risk factors should be considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".