Poster Presentation Australasian Diabetes in Pregnancy Society and Society of Obstetric Medicine Australia and New Zealand Joint Scientific Meeting 2021

The Effect Of Physical Activity On Glycaemic Control In Women With Gestational Diabetes (#81)

Cellina Ching 1 2 , Clara Chow 1 2 , David Simmons 3 4 , Ben Smith 5 , Mark McLean 3 6 , Dharmintra Pasupathy 7 , Vicki Flood 1 2 8 , Aravinda Thiagalinsam 1 2 , Suja Padmanabhan 1 2 , Vu T Tran 1 2 , Marina Ali 1 2 , Nicola Barrie 1 2 , Roslyn Hogan 1 2 , Simone Marschner 1 2 , N Wah Cheung 1 2
  1. Westmead Hospital, Westmead, NSW, Australia
  2. Westmead Applied Research Centre, University of Sydney, Sydney, NSW, Australia
  3. Western Sydney University, Sydney, NSW, Australia
  4. Campbelltown Hospital, Sydney, NSW, Australia
  5. University of Sydney, Sydney, NSW, Australia
  6. Blacktown Hospital, Sydney, NSW, Australia
  7. Obstetrics, Gynaecology and Neonatology, Westmead Clinical School, University of Sydney, Sydney, NSW, Australia
  8. Sydney School of Health Sciences, University of Sydney, Sydney, NSW, Australia

Background

Exercise is important in the management of women with gestational diabetes (GDM), but there are few studies of its role in improving glucose levels. The emergence of commercial activity monitors has allowed larger volumes of data to be obtained over longer time periods than has previously been achieved by clinically validated actigraphy. This allows more extensive examination of the relationship between physical activity and glycaemic control.

Method

Women enrolled in SMART MUMS WITH SMART PHONES 2 (SMs2), a randomised controlled trial of text messaging support for women after GDM, are provided with a wrist-worn activity monitor (Garmin Vivofit 4â) that tracks steps in their third trimester. The women check and record their fasting and 2 hour postprandial blood glucose levels (BGLs). Of the 180 women who are planned to be recruited for SMs2, we included those who had corresponding daily step and BGL records. Days with <1000 steps were excluded as it is likely that the activity monitor was not worn. We examined the association between steps with BGLs with a linear mixed effects model.  

Results

Ten women were included in this study. The mean age was 34.0±4.0 years and BMI 26.2±4.5 kg/m2. Amongst these women, there were 90 days with step and BGL data available.

The mean steps on the previous day was 4814.51±2574.57 and on the same day was 4798.20±2311.03. The mean fasting BGL was 5.05±0.43mmol/L, post breakfast BGL 5.86±0.57mmol/L, post lunch BGL 6.13±0.58mmol/L, post dinner BGL 6.42±0.69mmol/L and average postprandial BGL 6.10±0.47mmol/L.

There was a trend to increased steps on the previous day being associated with decreased fasting BGL, and for increased steps on the same day being associated with decreased post prandial BGL, with the highest effect after lunch. However, these trends did not meet statistical significance.

BGL

Estimated Change in BGL Per 1000 Steps (mmol/L)

(95%CI)

Linear Trend p-value

Fasting

-0.012

(-0.059, 0.035)

0.63

Post Breakfast

-0.061

(-0.195, 0.072)

0.36

Post Lunch

-0.082

(-0.191, 0.027)

0.14

Post Dinner

-0.046

(-0.228, 0.137)

0.62

Average Post Prandial

-0.044

(-0.110, 0.022)

0.19

* Fasting glucose versus steps recorded on the previous day, all other measurements versus steps on the same day
Table 1. Change in Glucose Per 1000 Steps

Conclusion

This study suggests a possible trend to an association between physical activity and improved glycaemia in GDM, which if sustained across the cohort would warrant a full trial of commercial activity monitors for all women with GDM.