Accelerometry-Measured Physical Activity and Inflammation after Gestational Diabetes
Bibliographic record
Abstract
PURPOSE: Gestational diabetes mellitus (GDM) is associated with adverse metabolic outcomes after delivery. Physical activity practice improves the inflammatory profile; however, whether this association exists in women with prior GDM remains unknown. Our objective was to examine the cardiometabolic and inflammatory risk factors associated with accelerometer-based measures of physical activity in women with prior GDM. METHODS: Ninety-six women who had GDM between 2003 and 2010 were tested 2.9 ± 2.2 yr after delivery. The physical activity practice was measured with ActiGraph GT3X (ActiGraph™, Pensacola, FL) accelerometers worn ≥ 5 d, and the time spent weekly in moderate to vigorous physical activity (MVPA) was derived. The waist circumference was measured and the inflammatory marker or cytokine concentrations were measured in fasting plasma by the xMAP technology using the Bio-Plex 200 system. The lipid profile was also measured from fasting blood samples. RESULTS: Only 31% of women accumulated at least 150 min of MVPA per week. No association was observed between the MVPA practice and any of the metabolic measurements in the whole group of women. The MVPA did not differ in groups stratified by waist circumference <88 or ≥ 88 cm. In women with waist circumference <88 cm, the MVPA was negatively correlated with circulating concentrations of C-reactive protein (r = -0.51, P = 0.006), leptin (r = -0.40, P = 0.008), plasminogen activator inhibitor-1 (r = -0.32, P = 0.04), and triglycerides (r = -0.44, P = 0.003). No association was seen with plasma interleukin-6; tumor necrosis factor-α; and total, LDL, or HDL cholesterol concentrations. CONCLUSION: These analyses suggest that in the years after delivery, longer time spent in MVPA practice is associated with a lower cardiometabolic risk only in women with prior GDM who do not have abdominal obesity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".