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Keywords:

  • Gestational diabetes mellitus;
  • health behaviours;
  • obesity;
  • pregnancy;
  • weight

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Funding
  9. References

Please cite this paper as: Harrison C, Lombard C, Teede H. Understanding health behaviours in a cohort of pregnant women at risk of gestational diabetes mellitus: an observational study. BJOG 2012;119:731–738.

Objective  To assess health behaviours, physical activity levels, weight gain and development of gestational diabetes mellitus (GDM) in high-risk women.

Design  An observational sub-study of a larger randomised controlled trial.

Setting  A large tertiary hospital in Australia.

Population  Ninety-seven women (mean age 31.7 ± 4.5 years; body mass index 30.3 ± 5.9 kg/m2) at risk of developing GDM.

Methods  Women were identified as at risk of GDM based on a validated screening tool. Baseline measures were completed at 12–15 weeks of gestation and repeated at 26–28 weeks of gestation.

Main outcome measures  Anthropometric (weight and height) and physical activity assessment (Yamax pedometer and International physical activity questionnaire), questionnaires (self-efficacy) and GDM screening.

Results  By 28 weeks of gestation, there was a high GDM prevalence of 26% using the recent International Association of Diabetes and Pregnancy Study Group criteria. Weight gain in overweight (body mass index 25–29.9 kg/m2) and obese (body mass index >30.0 kg/m2) women exceeded minimum total weight gain recommendations set by the Institute of Medicine (< 0.01). Physical activity levels were low and declined during pregnancy (5437 ± 2951 steps/day to 4096 ± 2438 steps/day, respectively, < 0.001). Despite reduced activity levels, increased weight gain and high GDM incidence many women did not accurately perceive GDM risk and were confident in their ability to control weight. A significant association with physical activity, weight and GDM outcome was not observed.

Conclusions  Overweight and obese pregnant women at risk for developing GDM demonstrate excessive weight gain and a reduced level of physical activity observed from early pregnancy to 28 weeks of gestation. Results highlight the need for targeted intervention in women at risk for developing GDM. Australian New Zealand Clinical Trial Registry Number: ACTRN12608000233325.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Funding
  9. References

In line with escalating obesity rates worldwide, approximately one-third of young women entering pregnancy are overweight or obese1,2 presenting a significant public health challenge. Overweight and obesity is linked with an increased risk of maternal (miscarriage, gestational diabetes mellitus [GDM]) and neonatal complications (stillbirth, macrosomia).1 Additionally, excessive gestational weight gain (GWG), especially if superimposed on pre-existing excess weight, increases the risk of pregnancy complications3 and of long-term obesity development. GDM, a common complication, is strongly associated with obesity1 affecting ∼10% of women in pregnancy.2,4 GDM presents a significant health risk to women both during and following pregnancy with up to 60% of women with a history of GDM developing type II diabetes (DM2) within 10 years.5,6 Therefore, preventive strategies applied in early pregnancy aimed at reducing excess GWG and GDM are of particular importance and have the potential to improve health both during and after pregnancy.

Regular moderate physical activity is recommended as a preventive health strategy and in pregnancy is linked to a reduced risk of GDM,7 excess GWG and complications during labour.8,9 Despite the potential benefits, there are few studies that evaluate physical activity levels objectively during pregnancy, with previous epidemiological estimates predominantly using less sensitive tools, including subjective retrospective recall.10–12 Further, evaluation of physical activity, GWG and lifestyle behaviours (risk perception and attitudes towards health) in high-risk women (overweight women or those at high-risk of GDM) is limited, yet understanding health-related behaviours is vital to inform development of effective preventive approaches in high-risk pregnancy settings.

We have recently demonstrated that women at high risk of GDM can be identified simply in early pregnancy at hospital booking using a validated screening tool.13 This tool is based on established GDM risk factors including maternal age and weight, ethnicity and previous obstetric and family history.13 Additionally, we have also demonstrated the accuracy of objective measures of physical activity in pregnancy against less sensitive subjective measures, including recall questionnaires.14 Implementing these robust measures in a high-risk group of women would be beneficial to explore health-related behaviours in this currently limited area of research and inform on future interventions in this setting.

Therefore, we aimed to recruit women at high risk of GDM based on established risk factors and a validated screening tool.13 We aimed to objectively assess physical activity and factors associated with inactivity, including GWG, risk perception and their association with GDM development from early pregnancy to GDM screening (26–28 weeks of gestation) to better understand health behaviours in this high-risk setting. In recruiting a high-risk group we hypothesised increased GDM incidence, high GWG and reduced physical activity levels.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Funding
  9. References

Subjects

This study involved a subset of women recruited for a larger randomised controlled trial aiming to improve diet and physical activity in pregnancy (intervention) versus standard information only (controls) from early pregnancy (12–15 weeks of gestation) to 6 weeks postpartum in women at risk of developing GDM. This study focuses on those women allocated to the control group. Women were recruited by invitation from a maternity clinic at a large Australian tertiary hospital. Eligibility criteria included increased risk for developing GDM based on risk factors including previous history of GDM, maternal age, increased body mass index (BMI), first-degree family history of DM2 or high-risk ethnicity group. These risk factors were incorporated into a validated risk prediction tool as previously described.13 Exclusion criteria included diagnosed type 1 or 2 diabetes, a BMI > 45 kg/m2, non-English-speaking women, women with pre-existing chronic medical conditions or multiple pregnancy. Group allocation was achieved through computer-generated randomised sequencing performed by a senior biostatistician.

To describe and better understand physical activity behaviours in a population of women at risk of developing GDM, we included all women randomised to the control group in this sub-study. Women allocated to the control group received generic written information relating to diet and physical activity in early pregnancy based on Australian population guidelines15,16 with no intervention or study support. The intervention group was not included in this study because the intervention is anticipated to alter the natural history of lifestyle change in pregnancy. The Southern Health Research Advisory and Ethics Committee approved the study and all participants gave written informed consent.

Measures

Recruited control women completed all assessments at baseline, between 12–15 weeks of gestation and then at 26–28 weeks of gestation all measurements were repeated and GDM screening was performed.

Anthropometrics

Anthropometric assessment included weight on an electronic scale, calibrated biannually, to the nearest 0.1 kg (Tanita model BWB-800 Digital Scale, Wedderburn Scales, Melbourne, Vic., Australia) and height measured by a registered nurse unaware of participant allocation.

Pedometer

The Yamax Digiwalker SW-700 Pedometer (Yamax Corporation, Tokyo, Japan) was used to assess the number of free-living steps per day as a valid, reliable and accurate tool to measure relative step count in free living and controlled conditions in non pregnant populations.17 Pedometer readings were accumulated for a minimum of three and up to seven consecutive days during waking hours (excluding water activities), including at least one weekend day, which has previously shown to be sufficient for estimating weekly physical activity.18 To provide a realistic estimation of usual physical activity levels, participants were instructed to partake in normal daily activities, representative of their routine. The pedometer was sealed to blind participants to their step count and limit motivation to increase walking as previously reported.19 A full day was considered as wearing the device for at least eight daytime hours and a half day was considered as <8 hours but more than 3 hours. If worn for <3 hours a day, this was treated as a missing day. A simple exercise diary was provided to record usage times and all participants were advised on correct usage.

International physical activity questionnaire (IPAQ) long version

The IPAQ was used to assess physical activity across a variety of different domains including leisure-time, domestic, work and transport-related physical activity and has previously been validated in a non-pregnant adult population.17 Within each domain the IPAQ assesses exercise intensity including walking, moderate and vigorous physical activity that is performed daily for at least ten consecutive minutes over 7 days. Weekly average metabolic equivalent (MET) scores were calculated for total physical activity, as well as for walking, moderate and vigorous activity performed per week as a continuous variable, as previously described.20

Psychosocial measures

Several questions relating to risk perception, motivation and behavioural change based on components of a Stage of Change scale21 were developed by a senior clinical psychologist. The validated Exercise Confidence Scale22 was adapted to measure self-efficacy towards regular exercise. Scores were based on a five-point Likert scale and a mean for each of the seven domains was generated. An additional question including; ‘How confident are you that you can control your weight gain during pregnancy if you wished?’ (ten-point Likert scale) was asked at baseline to measure self-efficacy towards weight gain during pregnancy.

GDM screening

All women underwent GDM screening with a non-fasting 75-g glucose challenge test at 26–28 weeks of gestation.23 Women with a positive result (1-hour venous plasma glucose level ≥ 8.0 mmol/l) proceeded to a 2-hour 75-g oral glucose tolerance test. GDM was diagnosed based on the Australasian Diabetes in Pregnancy Society (ADIPS) criteria including the presence of either a fasting venous plasma glucose level of ≥5.5 mmol/l or a 2-hour level of ≥8.0 mmol/l.23 Recently released guidelines for GDM diagnosis from the International Association of Diabetes and Pregnancy Study Groups (IADPSG) were also used to assess GDM outcome. Using these latter criteria, GDM is diagnosed in the presence of either a fasting venous plasma glucose of ≥5.1 mmol/l, a 1-hour glucose of ≥10.0 mmol/l or a 2-hour glucose level of ≥8.5 mmol/l.24

Statistics

All data collected were analysed using spss Data Analysis version 18.0 (SPSS Inc., Chicago, IL, USA). Paired t-tests were used to compare change over time for all variables assessed. Physical activity data collected were processed to report average daily steps or MET/min. Spearman correlation was used to assess the relationship between estimates of activity measured, including daily step count and daily total, light and moderate MET/min. Sample t-tests were performed to assess rate of weight gained per week against Institute of Medicine recommendations.25 Exploratory analysis using logistic regression was performed to test for independent variables associated with the development of GDM at 28 weeks of gestation. Independent variables included country of birth (Australian or non-Australian born), pedometer steps/day (baseline, 28 weeks of gestation and change over time) and weight/BMI (baseline, 28 weeks of gestation and change over time) with all results adjusted for confounding co-variates including age and baseline BMI. All results are presented as mean (±SD) unless otherwise stated with 95% confidence intervals reported for mean differences in main outcome measures. As this was a prospective cohort study, no sample size calculation was performed.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Funding
  9. References

Demographics

In all, 107 control participants were recruited and results were available for 97 women who completed anthropometry for weight gain outcome at both baseline and 28 weeks of gestation, except for questionnaires (n = 92 baseline; n = 87 at 28 weeks) and pedometer data (n = 84 baseline; n = 73 at 28 weeks). As demographic and outcome variables did not significantly differ between women who completed all measures and women who partially completed measures, we chose to present baseline demographic results for all 97 women. The mean age and BMI of participants was 31.7 (±4.5) years and 30.0 (±5.8) kg/m2, respectively. At 26–28 weeks of gestation, the average BMI was 32.7 (±5.8) kg/m2. Demographic characteristics of the study group are presented in Table 1.

Table 1.   Demographic characteristics of participants (n = 107)
Variablen (%)
Age (years)
≥18–2945 (42)
30–3439 (36)
35–3920 (19)
>403 (3)
Body mass index (kg/m2)
>23–24.9917 (16)
25–29.9950 (47)
>30.0040 (37)
Country of birth
Australia41 (38)
Southern/Central Asia37 (35)
South East Asia15 (14)
Other14 (13)
Education
Year 10–1114 (13)
Year 129 (8)
Certificate/diploma33 (31)
University degree or higher51 (48)
Work
Full time29 (27)
Part time35 (33)
No paid work43 (40)
Income ($)
<40,00035 (33)
40,000–60,00019 (18)
60,000–80,00013 (12)
>80,00023 (21)
Unsure/declined17 (16)
Previous GDM
No98 (92)
Yes9 (8)
Prevalence GDM
No79 (74)
Yes28 (26)

Physical activity

Participants wore the pedometer for an average of 4.7 (±1.8) and 5.2 (±1.7) days at baseline and 28 weeks, respectively. Mean daily steps estimated by the pedometer and daily MET/min estimated by the IPAQ are presented in Table 2. There was significant decline in total mean daily steps estimated by the pedometer (< 0.001) from baseline to 28 weeks. There was no significant change over time in total (P = 0.50), light (P = 0.41) or moderate (P = 0.28) MET/min or time spent sitting (hours/day, P = 0.8) estimated by the IPAQ. No correlation was found between pedometer estimates of physical activity and total MET/min estimated by the IPAQ at baseline or 28 weeks. There was a weak correlation between light MET/min and steps per day at baseline (r2 = 0.24, = 0.049) and 28 weeks (r2 = 0.33, < 0.05). No vigorous MET/min were detected at baseline or 28 weeks of gestation.

Table 2.   Activity levels assessed by the pedometer and IPAQ at baseline and 28 weeks of gestation
VariableBaseline28 weeksMean change (95% CI)
  1. All results presented as mean (SD) unless otherwise stated. MET, metabolic equivalent.

  2. *Complete data available for n = 65.

  3. **Significantly declined from baseline (< 0.001).

  4. ***Complete data available for n = 75.

Pedometer steps*5437 (2951)4096 (2438)−1340 (−2074 to −606)**
IPAQ Baseline***
Total MET/min544.73 (1103.77)477.56 (710.90)−67.17 (−264.94 to 130.61)
Light/walk MET/min151.14 (271.48)194.32 (397.73)43.18 (−61.03 to 147.40)
Moderate MET/min290.43 (597.72)223.28 (329.66)−67.14 (−190.25 to 55.96)
Sitting time (hours/day)4.95 (2.93)5.02 (2.92)0.07 (−1.00 to 1.09)

Gestational diabetes outcome and weight gain

Prevalence of GDM was 16% (n = 15) using ADIPS criteria and 26% (n = 25) using the revised IADPSG,24 compared with a background population risk of ∼10%,2,4 confirming a high GDM risk group. At baseline, using the original WHO BMI classification,26 the majority of women were either overweight (47.4%; BMI 25.0–29.99 kg/m2) or obese (37.1%; BMI >30 kg/m2; Table 3). Weight significantly increased from baseline to 28 weeks (< 0.001). Weight gain (kg) was stratified according to baseline BMI using the original World Health Organization (WHO) BMI classifications26 and was transformed to represent average weekly weight gain (kg). Between sub-groups percentage exceeding minimum recommendations for total weight gain according to Institute of Medicine (IOM) recommendations increased with increasing BMI. In comparison to 20% of women with a normal BMI, 55% of overweight and 60% of obese women had exceeded minimum recommendations by 28 weeks gestation. When compared with IOM recommendations for weekly weight gain during the second trimester,25 rate of weight gain was significantly higher in pre-existing overweight (25–29.9 kg/m2; < 0.001) and obese (> 30.0 kg/m2; < 0.05) women (Table 3).

Table 3.   Total and weekly weight gain in comparison to Institute of Medicine recommendations
BMI classification*Proportion, n (%)IOM total weight gain recommendations (kg)Total weight gain at 28 weeks (kg)IOM recommended weekly weight gain (2nd trimester**; kg)Actual weekly weight gain (2nd trimester; kg)
  1. *World Health Organization original classification was used for IOM guideline comparison:25 healthy (≤ 25.0 kg/m2), overweight (25–29.9 kg/m2) and obese (≥30.0 kg/m2). For inclusion, BMI in high-risk ethnic groups had to be >23 kg/m2 (reclassified by WHO as overweight38).

  2. **Based on IOM revised recommendations and accounting for a mean gain of 0.75 kg in the first trimester.25

  3. Significantly higher than obese subgroup: ***< 0.05 and ****< 0.001.

  4. Significantly higher than recommended weight gain in kilos per week ******< 0.01 and *****< 0.001.

Healthy15 (15.5)11.3–15.98.32 ± 2.74***0.450.54
Overweight46 (47.4)6.8–11.37.63 ± 3.69****0.270.49*****
Obese36 (37.1)5.0–9.15.25 ± 2.600.230.32******

Despite reduced physical activity and increased weight gain from baseline to 28 weeks of gestation, these factors were not significantly associated with GDM development and there was no significant differences between women who were diagnosed with GDM and those not diagnosed with GDM. Further, increased weight gain was not found to be significantly associated with reduced physical activity levels.

Exercise self-efficacy

At baseline, 42% of women were not confident they could put together time to exercise regularly (three times per week for 30 minutes), whereas 32% were moderately confident and 25% were very confident. The mean overall exercise self-efficacy was 2.32 ± 0.80 out of 5. Similar results persisted at 28 weeks of gestation.

Risk perceptions, health behaviours and self-efficacy towards gestational diabetes and weight gain

At baseline, 76% of women believed that they were at slight to high risk of gaining excess gestational weight. Seventy-five percent of women planned to take action to reduce their risk of gaining excess weight when they first become pregnant and a further 53% believed that they were taking actions to reduce excess weight gain by the time of baseline (12–15 weeks of gestation). In response to confidence about controlling weight gain, 67% of women were ≥60% confident that they could control their weight gain during pregnancy, with 50% of these women scoring 8 or more out of 10 (10 being totally confident). In relation to GDM risk, 50% of women did not believe that they were at any risk for developing GDM in pregnancy with a further 33% believing that they were at slight risk only.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Funding
  9. References

Currently, there is limited understanding of health-related behaviours encompassing weight gain, physical activity and psychosocial factors during pregnancy both in high-risk groups and at a broader population level. To address this gap, we recruited pregnant women at increased GDM risk using a validated risk prediction tool in early pregnancy. Here we report a high GDM prevalence and document physical activity levels far lower than recommended population guidelines that decline further with advancing gestation. We also report GWG much higher than IOM recommendations in an already overweight and obese group of pregnant women. Despite the majority (∼80%) of women being aware that they were at risk of gaining excess weight, many were not confident that they could find time to regularly exercise, 30 minutes three times per week, yet were confident that they could control their weight gain during pregnancy. Interestingly, in a group of women at high risk of GDM development, 50% believed that they were not at any risk of developing GDM in early pregnancy with a further 30% believing that they were at slight risk only, highlighting the need for more accurate risk perception in high risk groups.

As a study population, this high-risk group of women were twice as likely to be obese or above the age of 40 in early pregnancy and were 20 times more likely to have had a history of previous GDM in comparison to pregnant women from the same local government area, as previously described.2 Selecting a group of high-risk women offers the opportunity to study health-related behaviours, physical activity levels, risk perception and adverse lifestyle during pregnancy including excess GWG. This high risk identification strategy also enables targeted interventions to be implemented in early pregnancy. With an average background GDM prevalence of ∼8–10%,2,4 here we show ability to recruit a high-risk group with a GDM prevalence two times greater at ∼17% using the ADIPS criteria. Implementing the recent IADPSG criteria further increased prevalence by 10% in line with the lowered blood glucose threshold levels required for GDM diagnosis.24 With an increased proportion of women diagnosed with GDM using IADPSG guidelines, implications at a clinical level include greater resources, staff and medical intervention.27 The balance between identifying and reducing the risk of adverse outcome by capturing those with lower blood glucose levels on IADPSG criteria and the healthcare resource impacts is topical with universal adoption of IADPSG guidelines yet to be reached, despite international consensus on GDM diagnosis being a primary objective of the recommendations.

With previous studies predominantly using inaccurate self-recalled measures of physical activity and a lack of studies specifically focusing on women at high risk of developing GDM, objective assessment of physical activity levels in this setting was needed.14 In comparison to baseline, our results showed a significant decline in objective pedometer estimates of physical activity at 26–28 weeks (Table 2). However, no significant change in subjective IPAQ estimates of physical activity or sitting time was observed, suggesting that this subjective measure may not be sufficiently sensitive to detect change in this setting, as suggested previously.14 There are limited previous studies that have assessed physical activity in pregnancy objectively28–33 and even fewer that have used pedometers to assess activity levels in this setting.29–31,34 Women in the previous studies were either of normal29–31,34 or obese34 BMI and otherwise healthy. In these studies, reported activity levels varied between ∼700031 and 900034 steps/day at 20–22 weeks of gestation which is 35–50% higher than steps/day reported in the current study. Using indices developed by Tudor-Locke and Bassett,35 47% and 67% of participants were classified as sedentary at baseline and 28 weeks respectively in the current study. In comparison, Symons Downs et al.31 reported 23% of participants as sedentary at 20 weeks of gestation. The increased rates of physical inactivity in women at risk of GDM in this study reflect the recruitment of a high-risk group.

Coupled with reduced physical activity levels at baseline and 28 weeks of gestation was a low level of self-efficacy in relation to regular exercise. Although it may be expected that reduced physical activity levels would be associated with reduced exercise self-efficacy, these results importantly highlight the need for effective lifestyle change and intervention in this high-risk setting. Providing physical activity advice in early pregnancy, particularly in high-risk groups, may address barriers towards exercise and improve the likelihood of exercising regularly. Improving physical activity is important in this setting because sedentary behaviours before pregnancy have previously been linked to increased GDM7 and may also contribute to excess GWG.

Overweight and obese women in the current study had a significantly higher weekly weight gain when compared with recently published IOM pregnancy weight gain recommendations.25 Further, 55% of overweight and 60% of obese women had already exceeded minimum IOM weight gain recommendations by 26–28 weeks of pregnancy, increasing the risk weight retention following pregnancy. Interestingly, excess GWG occurred despite the majority of women reporting increased awareness of risk of gaining excess weight during pregnancy and reporting that they had taken some actions to reduce their risk at baseline. Excess GWG increases health risks during pregnancy and is a predictor for subsequent development of overweight and obesity long-term,36 even in women who began pregnancy at a normal BMI.37 A recent longitudinal study in over 2000 women reported a three times greater likelihood of becoming overweight and having central adiposity 16 years after pregnancy if GWG was above IOM recommendations in comparison to GWG within the recommendations.36 Increased GWG above IOM guidelines in mid-pregnancy was also positively associated with increased likelihood of overweight and obesity following pregnancy.36 As a preventable risk factor, these observations further support the need for effective education and improved monitoring for high-risk overweight and obese women. Despite this, available guidelines for clinical weight management during pregnancy in both Australia and the UK are ambiguous. Although the guidelines emphasise the need for effective education incorporating behaviour change, regular physical activity and dietary modification for obese women for optimal weight control, they do not recommend regular antenatal weight monitoring as standard practice.38,39 At a clinical level, with many women unlikely to be regularly weighed and unlikely to be aware of IOM GWG recommendations, this is likely to contribute to the excessive weight gains reported here and by others. Effective education is particularly important in overweight and obese women who may not be aware of the more stringent IOM guidelines for total weight gain.

It is important for women during pregnancy to have accurate risk perception and optimise their health behaviours including physical activity levels to limit excess GWG and reduce pregnancy complications including GDM. By perceiving risk of weight gain and displaying relative confidence in their ability to control weight, yet displaying poorer health behaviours (reduced physical activity and excessive GWG) this may indicate that women do not understand the importance of, nor prioritise, regular activity during pregnancy. Additional contributors to reduced activity may include barriers such as discomfort, cultural or safety beliefs,40 however many of these factors can be improved with effective education. The inaccurate risk perception reported here indicates that women have inadequate insight into their health, potentially as the result of a lack of information about gestational weight gain, activity and risk of GDM in early pregnancy. This inaccurate risk perception was particularly evident for GDM risk, where the majority of women did not perceive any risk of developing GDM in early pregnancy, despite having several pre-existing risk factors for development. These results are similar to previous studies reporting inadequate risk perception of DM2 in women with a history of GDM, despite recognising GDM as a risk factor for future DM2 development.41 Although supporting the need for education alone, increasing evidence suggests that intervention is also needed to induce lifestyle-related behaviour change. Hence, these results also highlight the need to raise awareness relating to healthy lifestyle choices in early pregnancy, incorporating effective messages (regular physical activity and appropriate weight gain) with other probable successful components potentially including behavioural change, goal setting, engaging social support and self-monitoring.

There are strengths and limitations to the current study. Strengths include screening and selectively targeting a confirmed high-risk group of women to better understand health-related behaviours during pregnancy. As a study group, the cohort was ethnically diverse, enabling a broader perspective on measured outcomes. Additional strengths include objective assessment of physical activity using the pedometer to provide a more accurate insight into activity levels in a high-risk group. However, some limitations of the pedometer should be noted and include the inability to measure water-related activities, as well as considerations including the morphological changes with advancing gestation potentially increasing the tilt angle of the pedometer, thereby increasing the likelihood of missed step counts.31 Additionally, although pedometer use is feasible during pregnancy, to our knowledge it is yet to be specifically validated for use in pregnancy. In selectively targeting women at risk of GDM, we may inform interventions in this group; however the results may not be generalisable to all pregnant women. Despite minimal intervention with emphasis on standard care only, as the women were recruited into a larger randomised controlled trial, this may have indirectly altered health behaviours and therefore the sample may be less representative of high-risk pregnant women at a population level. Additional limitations include the inability to detect a significant relationship between physical activity and GDM outcome or increased weight gain, which may have been detected with an increased sample size and increased numbers of GDM-positive women.

Conclusions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Funding
  9. References

In summary, evaluation of physical activity levels, GWG and health behaviours in pregnant women at risk for developing GDM demonstrates a markedly reduced level of physical activity, which further declines over pregnancy, excess GWG, increased GDM prevalence, poor risk perception and suboptimal health-related behaviours. These results highlight the need for effective education and targeted intervention strategies in higher-risk women from preconception and early pregnancy that aim to improve pregnancy health behaviours including increased self-efficacy towards physical activity levels and optimisation of GWG. Early intervention may assist in reducing the risk of adverse health outcomes in later pregnancy, including GDM.

Disclosure of interests

The authors have nothing to disclose. No financial disclosures were reported by the authors of this paper.

Contribution to authorship

CLH researched data and wrote the manuscript, CBL and HJT both contributed to the discussion and reviewed and edited the manuscript.

Details of ethics approval

The Southern Health Research Advisory and Ethics Committee approved the study and all participants gave written informed consent. Approval date 1 April 2008; project number 07216C. Clinical Trial Registration: Australian New Zealand Clinical Trial Registry Number: ACTRN12608000233325. Registered 7 May 2008 (http://www.anzctr.org.au).

Funding

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Funding
  9. References

This project is supported by a BRIDGES Grant from the Global Diabetes Foundation. BRIDGES, an International Diabetes Foundation project is supported by an educational grant from Eli Lilly and Company. (Project Number: LT07-121). The Jack Brockhoff Foundation also provided funding for this study. Cheryce Harrison is a Jean Hailes Foundation research fellow. Helena Teede is an NHMRC research fellow.

Acknowledgements

The authors would like to acknowledge Melanie Gibson-Helm for coordinating data collation, Lauren Snell for data collection and Eldho Paul for statistical assistance.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Funding
  9. References
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