| Literature DB >> 30426166 |
Mladen Savikj1,2, Brendan M Gabriel1, Petter S Alm1, Jonathon Smith1, Kenneth Caidahl3,4, Marie Björnholm3, Tomas Fritz3,4, Anna Krook1, Juleen R Zierath1,3,5, Harriet Wallberg-Henriksson6.
Abstract
AIMS/HYPOTHESIS: Exercise is recommended for the treatment and prevention of type 2 diabetes. However, the most effective time of day to achieve beneficial effects on health remains unknown. We aimed to determine whether exercise training at two distinct times of day would have differing effects on 24 h blood glucose levels in men with type 2 diabetes.Entities:
Keywords: Blood glucose level; Circadian rhythm; Continuous glucose monitoring; Exercise; High-intensity interval training; Type 2 diabetes
Mesh:
Substances:
Year: 2018 PMID: 30426166 PMCID: PMC6323076 DOI: 10.1007/s00125-018-4767-z
Source DB: PubMed Journal: Diabetologia ISSN: 0012-186X Impact factor: 10.122
Baseline characteristics
| Variable ( | Baseline data |
|---|---|
| Age (years) | 60 ± 2 |
| Time since diagnosis (years) | 11 ± 3 |
| BMI (kg/m2) | 27.5 ± 0.6 |
| WHR | 0.99 ± 0.01 |
| Body fat (%) | 26.4 ± 0.8 |
| Max heart rate (beats/min) | 158 ± 7 |
| Maximum power (W/kg) | 2.1 ± 0.1 |
Data are mean ± SEM
Blood chemistry analyses
| Blood chemistry | Pre-training | Post-morning | Post-afternoon |
|---|---|---|---|
| Glucose (mmol/l) | 7.3 ± 0.3 | 7.7 ± 0.4 | 7.5 ± 0.3 |
| Insulin (pmol/l) | 56.9 ± 9.3 | 71.4 ± 6.9 | 70.4 ± 11.6 |
| HbA1c (mmol/mol) | 48.3 ± 3.9 | 45.1 ± 2.1 | 46.1 ± 2.7 |
| HbA1c (%) | 6.6 ± 0.4 | 6.3 ± 0.2 | 6.4 ± 0.2 |
| Total cholesterol (mmol/l) | 4.2 ± 0.4 | 4.4 ± 0.3 | 4.2 ± 0.4 |
| HDL-cholesterol (mmol/l) | 1.2 ± 0.1 | 1.3 ± 0.1 | 1.2 ± 0.1 |
| LDL-cholesterol (mmol/l) | 2.4 ± 0.4 | 2.4 ± 0.4 | 2.3 ± 0.4 |
| Triacylglycerol (mmol/l) | 1.2 ± 0.2 | 1.6 ± 0.3 | 1.4 ± 0.2 |
| PTH (pmol/l)†† | 3.9 ± 0.2 | 4.4 ± 0.2 | 4.6 ± 0.3‡ |
| TSH (mU/l)†† | 1.4 ± 0.2 | 1.7 ± 0.2‡ | 1.9 ± 0.2‡ |
| T4 (pmol/l)† | 16.8 ± 0.6 | 16.1 ± 0.7 | 15.8 ± 0.7‡‡ |
| T3 (pmol/l) | 4.7 ± 0.2 | 4.8 ± 0.2 | 4.9 ± 0.1 |
Blood samples were obtained from fasting participants before (Pre-training) and after HIIT training for 2 weeks in the morning (Post-morning) or afternoon (Post-afternoon). Data are mean ± SEM. One-way ANOVA (†p < 0.1, ††p < 0.05), followed by Tukey’s post hoc test (‡p < 0.1, ‡‡p < 0.05 vs pre-training)
Fig. 1CGM-based glucose levels in response to HIIT. CGM-based glucose levels were assessed during the pre-training period and on exercise days (Exercise) and subsequent days (Rest). Blood glucose readings on Exercise days in (a) week 1 (n = 11) and (b) week 2 (n = 9), and on Rest days in (c) week 1 (n = 11) and (d) week 2 (n = 8). Red lines and symbols, morning exercise; blue lines and symbols, afternoon exercise; grey lines and symbols, matched pre-training days. Red arrows, time of morning exercise; blue arrows, time of afternoon exercise; grey arrows, snack offered. Using two-way ANOVA: §p < 0.05 for the effect of time; ¶p < 0.05 for the interaction between exercise and time. Using Tukey’s multiple comparison test: *p < 0.05 for the difference between exercise trials; †p < 0.05 for the difference between morning exercise trial and pre-training period; ‡p < 0.05 for the difference between afternoon exercise trial and pre-training period. Values are means + SEM