A preliminary investigation into the effect of continuous vigorous exercise and

lifestyle-embedded physical activity upon

acute glycaemic regulation

Ash Routen1, Ann Rowlands2 & Dale Esliger2

1Institute of Sport & Exercise Science, University of Worcester, UK.

2School of Sport and Health Sciences, University of Exeter, UK.

Introduction• Consensus that physical activity/exercise reduces the risk of developing

insulin resistance, glucose intolerance and overt type 2 Diabetes (Bassuk et al., 2005, Healy et al., 2006).

• Majority of research is of a experimental design with long term follow-up, detailing chronic adaptations to exercise in diabetics.

• Continuous glucose monitoring (CGM) has emerged as a new tool for diabetics help maintain normoglycaemia. CGM provides ‘acute’ information on ambulatory, postprandial and/or nocturnal glucose excursions (Hay et al., 2003).

• To date only two studies implementing CGM within exercise protocols, charting acute glucose responses to exercise may allow optimal intervention (Klonoff, 2005).

Aim

Two concurrent aims:-

• To determine the effect of continuous exercise and lifestyle-embedded (intermittent bouts) physical activity (as measured by accelerometry) on the regulation of interstitial glucose (as measured by CGM).

• To determine the feasibility of CGM data collection alongside exercise protocols.

Methods

• One physically active non-diabetic male [age: 22 y; mass: 71.5 kg; height: 181 cm].

• 8 days CGM (iPro, Medtronic, Northridge, USA) and accelerometry data collection (Actigraph GT1Ms, Actigraph USA).

• 3 trial conditions: • Sedentary control (< 2500 steps, pedometer controlled).• Continuous exercise condition (2 x 30 min treadmill running at 70%

HRmax).• lifestyle-embedded physical activity condition (100 min of physical activity

including: stair climbing, brisk walking outside etc.).

Table 1. Experimental Design

Day Condition

0 Insert and check CGM device

1 Nutrition Control Day

2 Sedentary Condition

3 Washout Day

4 Continuous Condition

5 Washout Day

6 Lifestyle Condition

7 Washout Day and Finish

Figure 1. Medtronic MiniMed (SOF-SENSOR) glucose sensor

Figure 1.1. CGMS iPro digital recorder attached to SOF-SENSOR

Results

Seden

tary

Continuous

Lifest

yle

4.9

5.1

5.3

5.5

5.7

5.9 Sedentary

Continuous

Lifestyle

Figure 2. 24 hour mean glucose levels for the sedentary, continuous exerciseand lifestyle-embedded physical activity condition. Values are mean ± S.E.M.

Glu

co

se

(m

mo

l.L

-1)

Results continued…

-2 2 +

4 +

6 +

4.5

5.0

5.5

6.0

6.5

7.0Continuous

Lifestyle

Figure 2.1. Mean glucose levels 2 hours pre-6 hours post lastactivity bout. Values are mean ± S.E.M.

Time (hours)

Glu

co

se

(m

mo

l.L-1

)

Results continued…

• The relationship between physical activity counts (as measured by accelerometry) and glucose values was assessed during various parameters (e.g. exercise, postprandial) via Pearson's correlation analysis. The alpha level was set at <0.05.

• A strong positive correlation was identified during the continuous exercise bouts (R= 0.75, P = 0.02).

Discussion• Tighter glycaemic control potentially due to elevated glucose uptake

resulting from increased GLUT-4 translocation to cellular membrane (Kennedy et al., 1999; Sigal et al., 2004).

• Greater uptake in continuous vs. lifestyle condition as muscle glucose uptake is greater at higher intensities - increased GLUT-4, blood flow etc. (Romijn et al., 1993).

• Positive correlation during continuous bouts may be due to increased hepatic glucose production (Wasserman et al., 1996).

• However 5 min time delay between interstitial glucose and blood glucose , so time lag correlations may prove more accurate (Klonoff, 2005).

Conclusion/Future Research• Day to day glucose regulation in a normoglycaemic individual may

be achieved through undertaking vigorous intensity aerobic exercise.

• Lifestyle physical activity (of the same energy expenditure), a suitable alternative for unwilling and unable.

• CGM data collection is feasible.

• Limited by single participant design and normoglycaemic population.

• Future studies should increase sample size and include pre-diabetic and overt diabetic populations.

Bassuk, S. S., & Manson, J. E. (2005). Epidemiological evidence for the role of physical activity in reducing risk of type 2 diabetes and cardiovascular disease. J Appl Physiol, 99(3), 1193-1204.

Hay, L. C., Wilmshurst, E. G., & Fulcher, G. (2003). Unrecognized hypo- and hyperglycemia in well-controlled patients with type 2 diabetes mellitus: the results of continuous glucose monitoring. Diabetes Technol Ther, 5(1), 19-26.

Healy, G. N., Dunstan, D. W., Shaw, J. E., Zimmet, P. Z., & Owen, N. (2006). Beneficial associations of physical activity with 2-h but not fasting blood glucose in Australian adults: the AusDiab study. Diabetes Care, 29(12), 2598-2604.

Kennedy, J. W., Hirshman, M. F., Gervino, E. V., Ocel, J. V., Forse, R. A., Hoenig, S. J., et al. (1999). Acute exercise induces GLUT4 translocation in skeletal muscle of normal human subjects and subjects with type 2 diabetes. Diabetes, 48(5), 1192-1197.

References

Klonoff, D. C. (2005). A review of continuous glucose monitoring technology. Diabetes Technol Ther, 7(5), 770-775.Romijn, J. A., Coyle, E. F., Sidossis, L. S., Gastaldelli, A., Horowitz, J. F.,

Endert, E., et al. (1993). Regulation of endogenous fat and carbohydrate metabolism in relation to exercise intensity and duration. Am J Physiol, 265(3 Pt 1), E380-391.Sigal, R. J., Kenny, G. P., Wasserman, D. H., & Castaneda-Sceppa, C. (2004). Physical activity/exercise and type 2 diabetes. Diabetes Care, 27(10), 2518-2539.Wasserman, D. H. (1996). Regulation of extramuscular fuel sources during exercise. In L. B. Rowell & J. T. Sheperd (Eds.), Handbook of Physiology. Columbia: Bermedica Production.