Abstract 15859: Interrupting Prolonged Sitting Reduces Resting Blood Pressure and Plasma Norepinephrine in Adults With Type 2 Diabetes
Bibliographic record
Abstract
Interrupting prolonged sitting with frequent short bouts of light-intensity physical activity reduces blood pressure (BP) in overweight, non-diabetic adults, however, the effects in adults with type 2 diabetes (T2D) have not been investigated. This study examined the effects of two types of activity breaks (light-intensity walking or simple resistance activities) compared to continuous, uninterrupted sitting on resting BP and plasma norepinephrine (NE) in adults with T2D. In a randomized crossover trial, 24 inactive adults with T2D (14 male; 62 ± 6 y; BMI 33.0 ± 3.4 kg/m 2 ) consumed standardized breakfast and lunch meals during 3 x 8 h conditions (6-day washout): i) SIT: uninterrupted sitting (control); ii) LW: sitting + 3 min bouts of Light-intensity Walking (3.2 km/h every 30 min); and iii) SRA: sitting + 3 min bouts of Simple Resistance Activities (half-squats, calf raises, gluteal contractions and knee raises) every 30 min. Resting seated BP was measured hourly (mean of 3 recordings, performed ≥ 25 min after activity). Venous blood was drawn every 30 min for the plasma NE assay, ≥ 25 min after activity. As illustrated in figures 1A and 1B, compared to SIT, both LW and SRA reduced BP ( P < 0.001); with the effect being more pronounced with SRA ( P < 0.01 vs. LW). Similarly, compared to SIT, both LW and SRA reduced plasma NE concentrations, with SRA significantly lower than LW ( P < 0.01). In conclusion, simple interruptions to sitting lowered resting BP and plasma NE concentration in adults with T2D. Reduced sympathetic vasoconstrictor tone may contribute to the observed hypotensive effect. With the ubiquity of sedentary behaviours and the low adherence to structured exercise, this approach is a practical strategy which may contribute to BP control.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".