The Effect of a Low Glycemic Index Diet on Glucose Challenge Test Results in Women at Risk for Gestational
Diabetes Mellitus
by
Katherine Marie Southgate
A thesis submitted in conformity with the requirements for the degree of Master of Science (M.Sc.)
Graduate Department of Nutritional Sciences University of Toronto
© Copyright by Katherine Marie Southgate 2012
ii
The Effect of a Low Glycemic Index Diet on Glucose Challenge
Test Results in Women at Risk for Gestational Diabetes Mellitus
Katherine Marie Southgate
Master of Science
Graduate Department of Nutritional Sciences University of Toronto
2012
Abstract
Gestational Diabetes Mellitus develops in 3.7-18% of Canadian women, and can cause
serious maternal-fetal complications. Low-GI foods have been shown to increase β-cell function
in subjects with impaired glucose tolerance. Theoretically, this effect should improve glucose
tolerance and reduce the risk of gestational hyperglycemia. Thus, we aimed to explore the
effects of a low-GI diet on glucose challenge test (GCT) results in women at risk for GDM.
Women were randomized to receive education during pregnancy focused on incorporation of
low- or medium- to high-GI foods. Key foods were provided to assist compliance. Information
was obtained from medical records and questionnaires. Ninety-four (94) women completed the
study. After adjustment for confounding variables, there was no significant difference in GCT
values between intervention groups. Results suggest that low-GI foods do not affect blood
glucose control during pregnancy.
iii
Acknowledgments
“A mother’s joy begins when new life is stirring inside…when a tiny heartbeat is heard for the
very first time, and a playful kick reminds her that she is never alone.”
- Anonymous
After coming across this quote while conducting my research at the obstetrical clinics of
Mount Sinai Hospital, I knew I had to include it in my thesis. To me, it symbolizes the
wonderful privilege it was working with the participants of this study on their journey towards
motherhood, and of the incredible clinic staff who offered their support, kindness and humour
when needed. To them, I offer my deepest appreciation.
During my time at U of T, I met some wonderful and brilliant students who I am proud to
now call my friends. Together, we shared great times, food and laughs. I am truly grateful for
your friendship and support. My graduate experience would not have been the same without you
all.
I would like to thank my family, but especially my mom and significant other. I could
never express how much your support and endless love means to me. Your unwavering
confidence in my abilities has given me the strength to achieve anything. My success is yours.
I also wish to express sincere gratitude to my committee members for their input and
guidance, while overseeing the completion of this thesis. And most importantly, I would like to
thank my supervisor, Dr. Thomas Wolever. Your work inspired me to embark on this journey,
and your invaluable input and enthusiasm guided me through.
Thank you.
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Table of Contents
Acknowledgments ............................................................................................................ iii
Table of Contents ............................................................................................................. iv
List of Tables ................................................................................................................... vii
List of Figures ................................................................................................................... ix
List of Appendices ............................................................................................................. x
List of Abbreviations ....................................................................................................... xi
Chapter 1 Introduction and Literature Review ............................................................ 1
1.1 Introduction ...................................................................................................................... 1
1.2 Maternal Carbohydrate Metabolism in Normoglycemic Pregnancies ....................... 2
1.2.1 Increased Insulin Resistance ....................................................................................... 2
1.2.2 Increased Insulin Secretion ......................................................................................... 2
1.2.3 Increased Hepatic Glucose Production ........................................................................ 3
1.3 Gestational Diabetes Mellitus ......................................................................................... 3
1.3.1 Pathophysiology, Risk Factors and Outcomes ............................................................. 3
1.3.2 Treatment, Screening and Diagnosis ........................................................................... 4
1.4 The Glucose Challenge Test ............................................................................................. 6
1.4.1 Confounding Effect of Diurnal Variation ................................................................... 6
1.4.2 Confounding Effect of Fasting Interval ....................................................................... 7
1.4.3 Confounding Effect of Race-Ethnicity ........................................................................ 8
1.4.4 Confounding Effect of Height ..................................................................................... 9
1.5 Prevention of Maternal Hyperglycemia ........................................................................ 9
1.5.1 Pre-pregnancy Dietary Variables and Risk of Maternal Hyperglycemia .................. 10
1.5.2 Dietary Variables During Pregnancy and Risk of Maternal Hyperglycemia ............ 12
1.6 A Low Glycemic Index Diet for the Prevention of Maternal Hyperglycemia .......... 14
1.6.1 The Glycemic Index .................................................................................................. 14
1.6.2 A Low Glycemic Index Diet During Pregnancy ....................................................... 15
1.6.3 Biologic Plausibility .................................................................................................. 16
v
Chapter 2 Research Question ....................................................................................... 18
2.1 Rationale .......................................................................................................................... 18
2.2 Hypothesis ........................................................................................................................ 19
2.3 Objectives ......................................................................................................................... 19
Chapter 3 Materials and Methods ................................................................................ 20
3.1 Study Design .................................................................................................................... 20
3.2 Study Participants ........................................................................................................... 20
3.2.1 Eligibility Criteria and Screening .............................................................................. 20
3.2.2 Recruitment and Informed Consent ........................................................................... 21
3.2.3 Randomization and Concealment .............................................................................. 22
3.3 The Dietary Intervention ................................................................................................ 23
3.3.1 Standard Obstetrical Care .......................................................................................... 24
3.3.2 Dietary Counselling ................................................................................................... 25
3.3.3 The Recommended Foods Lists ................................................................................. 26
3.3.4 Key Foods .................................................................................................................. 27
3.4 Data Collection ................................................................................................................ 27
3.4.1 Data Sources .............................................................................................................. 27
3.4.2 Pre-testing of Study Questionnaires ........................................................................... 28
3.4.3 Anthropometrics and Gestational Age ....................................................................... 29
3.4.4 Physical Activity Level ............................................................................................. 29
3.4.5 Medical Symptoms and Medication/Dietary Supplement Use .................................. 30
3.4.6 Study Diet Acceptability ............................................................................................ 31
3.4.7 Participant Adherence ................................................................................................ 31
3.4.8 Screening for and Diagnosis of GDM and/or IGT of Pregnancy .............................. 33
3.5 Statistical and Analytical Procedures ........................................................................... 33
3.5.1 Power and Sample Size Analysis ............................................................................... 33
3.5.2 Statistical Software and Analysis ............................................................................... 34
Chapter 4 Results ........................................................................................................... 37
4.1 Descriptive Statistics ....................................................................................................... 37
4.1.1 Maternal Baseline Characteristics, Compared by Intervention Group ...................... 37
vi
4.1.2 Participant Physical Activity Levels Before and During the Study Period by
Intervention Group ..................................................................................................... 42
4.1.3 Daily Nutrient Intake and Servings of Recommended Foods at Baseline and During
the Study Period by Intervention Group .................................................................... 42
4.1.4 GCT and OGTT Outcomes, Compared by Intervention Group ................................. 48
4.2 Participant Symptoms at Baseline and Change in Symptom Severity During the
Study Period, Compared by Intervention Group ....................................................... 49
4.3 Maternal Weight Gain, Compared by Intervention Group ...................................... 52
4.4 GCT Values, Compared by Intervention Group ........................................................ 53
4.5 Acceptability Ratings Between Participants’ Regular and Intervention Diets,
Compared by Intervention Group ................................................................................ 54
Chapter 5 Discussion ..................................................................................................... 56
5.1 Overview and Discussion ............................................................................................... 56
5.2 Strengths and Limitations ............................................................................................. 61
5.3 Future Directions ........................................................................................................... 62
5.4 Conclusions ..................................................................................................................... 62
References ........................................................................................................................ 64
Appendix A Recruitment Script and Handout ............................................................ 73
Appendix B Group Education Class Presentation Slides ........................................... 76
Appendix C Recommended Food Lists ........................................................................ 82
Appendix D Data Entry Form ...................................................................................... 84
Appendix E Initial Visit Questionnaire ........................................................................ 91
Appendix F Final Visit Questionnaire ......................................................................... 99
Appendix G Participants’ Significant Medical History ............................................ 108
Appendix H Participants’ Medication/Dietary Supplement Intake ........................ 111
vii
List of Tables
TABLE 1.1 Maternal risk factors for GDM TABLE 3.1 Study timeline TABLE 3.2 Sample size estimation for differences in GCT values from 0.51-1.47 mmol/L TABLE 4.1 Maternal characteristics at baseline, compared by intervention group TABLE 4.2 Study inclusion criteria (GDM risk factors), compared by intervention group TABLE 4.3 Participants’ total number of study inclusion criteria (GDM risk factors), compared by intervention group TABLE 4.4
Activity level at baseline and change in activity level during the study by intervention group
TABLE 4.5 Daily nutrient intakes from recommended foods by intervention group at baseline and during the study TABLE 4.6 Daily intake of recommended foods by intervention group at baseline and during the study
TABLE 4.7 GCT and OGTT outcomes by intervention group
TABLE 4.8 Symptoms at baseline and change in symptom severity during the study by intervention group
TABLE 4.9 Comparison of mean maternal weekly weight gain during the study with recommended target ranges by intervention group TABLE 4.10 Acceptability ratings between participants’ study and regular diets by intervention group TABLE G.1 Maternal baseline significant medical history, compared by intervention group
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TABLE H.1 Maternal baseline medications and dietary supplements, compared by intervention group
ix
List of Figures
FIGURE 1.1 CDA guidelines for screening and diagnosis of GDM FIGURE 4.1 Study flow diagram FIGURE 4.2 Maternal weight gain (kg) during the study period, compared by intervention group
FIGURE 4.3 Mean GCT values (mmol/L), compared by intervention group
x
List of Appendices
APPENDIX A Recruitment Script and Handout APPENDIX B Group Education Class Presentation Slides APPENDIX C Recommended Foods Lists APPENDIX D Study Visits Data Entry Form APPENDIX E Initial Visit Questionnaire APPENDIX F Final Visit Questionnaire
xi
List of Abbreviations
β beta
ACHOIS Australian Carbohydrate Intolerance Study
ANCOVA analysis of covariance
ANOVA analysis of variance
avCHO available carbohydrate(s)
BMI body mass index
CDA Canadian Diabetes Association
CFGHE Canada’s Food Guide to Healthy Eating
CHO carbohydrate
CI confidence interval
DI disposition index
EDD estimated due date
FPG fasting plasma glucose
GCT glucose challenge test
GDM gestational diabetes mellitus
GI glycemic index
GL glycemic load
HAPO Hyperglycemia and Adverse Pregnancy Outcomes
IGT impaired glucose tolerance
IOM Institute of Medicine
IRS-1 insulin receptor substrate 1
IQR interquartile range
LGA large-for-gestational age
LSD least-significant difference
NHSII Nurses’ Health Study II
OGTT oral glucose tolerance test
OR odds ratio
PCOS polycystic ovary syndrome
PG plasma glucose
xii
PPV positive predictive value
RAPA Rapid Assessment of Physical Activity Instrument
ROC receiver-operator characteristic
SD standard deviation
SEM standard error of the mean
SFFQ semiquantitative food-frequency questionnaire
SGA small-for-gestational age
Mathematical Symbols and Operators
> greater than
≥ greater than or equal to
< less than
≤ less than or equal to
χ2 Chi-square test statistic
η2 Eta-squared
Σ sum
df degrees of freedom
F F-ratio (test statistic used in ANOVA)
N, n the sample size. N denotes the total sample size, whereas n denotes the
size of a particular group.
P the probability value or significance of a test
r Pearson’s correlation coefficient
R2 coefficient of determination
t test statistic for Student’s t-test
U test statistic for the Mann-Whitney test
1
Chapter 1
Introduction and Literature Review
1.1 Introduction With its prevalence increasing worldwide (1-6), gestational diabetes mellitus or GDM is
now recognized as an increasing complication of pregnancy for women across several ethnicities.
Numerous studies have established the adverse affects of maternal hyperglycemia on pregnancy
outcomes, which extend beyond the prenatal period for both mother and baby (7-10).
Furthermore, evidence indicates that during pregnancy, progressively increasing plasma glucose
(PG) concentrations below levels diagnostic of GDM and impaired glucose tolerance (IGT), are
also associated with graded increases in adverse maternal-fetal outcomes (11, 12). As a result,
the diagnosis and treatment of GDM is now a part of standard prenatal care (13), yet research
regarding its prevention remains limited.
It is currently unknown whether GDM can be prevented through dietary and/or lifestyle
interventions. A weight reducing diet and exercise are the main strategies used to prevent the
development of diabetes (14); however, weight loss during pregnancy is not recommended (15).
As glucose intolerance typically begins mid-pregnancy, and increases as pregnancy progresses,
the second trimester may be the ideal time to initiate dietary advice aimed at the prevention of
maternal hyperglycemia (16). Both the increasing prevalence of GDM and its established
adverse perinatal outcomes indicate the need to assess the impact of dietary advice in the
prevention of glucose intolerance during pregnancy (16).
The glycemic index (GI) is a qualitative measure that classifies the type of carbohydrate
(CHO) according to the postprandial blood glucose response it elicits (17). Because of this,
dietary advice focused on the GI may be a simple and effective strategy towards maternal
glucose control in pregnancy. To our knowledge however, no intervention studies examining the
effect of consuming a low-GI diet on blood glucose control specifically in women at risk for the
development of GDM currently exists.
2
1.2 Maternal Carbohydrate Metabolism in Normoglycemic Pregnancies
Pregnancy is characterized by three profound adaptations in maternal CHO metabolism:
(1) an increase in insulin resistance; (2) an increase in insulin secretion; and (3) an increase in
hepatic glucose production (18, 19). Hyperglycemia during pregnancy, including both GDM and
IGT, develops when abnormalities in these metabolic adaptions occur.
1.2.1 Increased Insulin Resistance
Increased insulin resistance, developing most notably in skeletal muscle rather than
adipose tissue, begins in the second trimester and gradually progresses throughout the remainder
of pregnancy (18). Using the euglycemic-hyperinsulinemic clamp, Catalano et al. reported a
47% and 56% increase in insulin resistance in the third trimester of gestation for obese and
normal weight women respectively (18, 20). Although not fully understood, this increase in
insulin resistance is thought to be caused by pregnancy-induced factors affecting both post
receptor alterations in glucose transport through reduced glucose transporter type 4 expression
and distribution; and intracellular metabolism in insulin-sensitive tissues through reduced insulin
receptor tyrosine kinase activity, reduced expression of insulin receptor substrate 1 (IRS-1), and
reduced tyrosine phosphorylation of IRS-1 (18, 21).
1.2.2 Increased Insulin Secretion
Both basal and postprandial insulin secretion increase steadily from the first to third
trimesters, with a doubling in the basal and 24-hour mean insulin concentrations observed by the
third trimester (19). Early in the second trimester, first-phase insulin secretion (the change in
insulin concentration relative to the increase in glucose concentration from zero to five minutes
after intravenous glucose administration) is increased by 120% (19). With the progression of
pregnancy, an increase in both first and second phase insulin secretions ranging from 3 to 3.5-
fold greater than their initial concentrations occurs (18, 19). Although the precise mechanism(s)
responsible for the alterations in insulin secretion during pregnancy remain uncertain, in vitro rat
3
studies have implicated human placental lactogen, human growth hormone, and prolactin with
increases in pancreatic islet cell mass (18).
1.2.3 Increased Hepatic Glucose Production
Compared to non-pregnant women, basal endogenous hepatic glucose production is
enhanced by 16-30% (19). This is due to the decrease in basal glucose concentrations (0.56-0.83
mml/L) associated with a doubling of insulin concentrations in the third trimester, and the need
to meet increasing energy demands of the placenta and fetus (19). It is recognized that the
majority of glucose produced during this time (65-85%) is through gluconeogenesis (19).
1.3 Gestational Diabetes Mellitus
1.3.1 Pathophysiology, Risk Factors and Outcomes
Gestational diabetes is defined as CHO intolerance of variable severity with onset or first
recognition during the present pregnancy, independent of the glycemic status after delivery (13).
While the exact cause has yet to be elucidated, both GDM and IGT of pregnancy occur when
pancreatic β-cell insulin output fails to adequately compensate for the degree of tissue insulin
resistance (22). When compared to normoglycemic pregnancies, women with GDM have greater
insulin resistance; inadequate suppression of hepatic glucose production post meal consumption;
and an inadequate increase in first-phase insulin response (18, 19, 23).
The Canadian Diabetes Association (CDA) reports a 3.7% prevalence of GDM among
the Canadian non-Aboriginal population, with this prevalence increasing to 8-18% in the
Canadian Aboriginal population (14). Table 1.1 lists the numerous risk factors for GDM that
have been identified. When left untreated, GDM is associated with negative outcomes for both
mother and infant, which extend well beyond the perinatal period. For the infant, these include
but are not limited to, an increased risk of infant respiratory distress syndrome (IRDS) (7, 8);
being large-for-gestational age (LGA) (8, 24); shoulder dystocia (7, 8, 24); hypoglycemia (7);
4
future obesity; and future type 2 diabetes mellitus (10, 25). Mothers with GDM, when compared
to those with normoglycemic pregnancies, have been found in a recent meta-analysis to have a
seven-fold increased risk of developing future type 2 diabetes mellitus (9). Furthermore, results
of both the Toronto Tri-Hospital Gestational Diabetes Project (11), and the Hyperglycemia and
Adverse Pregnancy Outcomes (HAPO) trial (12) indicate a continuum of risk for adverse
maternal-fetal outcomes associated with increasing levels of CHO intolerance even below
diagnostic thresholds for GDM and IGT .
TABLE 1.1 Maternal risk factors for GDM1(13, 14, 26)
• Previous history of GDM or glucose intolerance • A family history of diabetes • Previous macrosomia (birth weight >4000 g) • Previous unexplained stillbirth • Previous neonatal hypoglycemia, hypocalcemia, or hyperbilirubinemia • Age ≥35 years • Pre-pregnancy BMI ≥25 kg/m2 • Repeated glycosuria in pregnancy • Polyhydramnios • Suspected macrosomia • Acanthosis nigricans • PCOS • Member of a high risk population including women of Aboriginal, Hispanic, South
Asian, Asian, and African descent. 1 BMI, body mass index; GDM, gestational diabetes mellitus; PCOS, polycystic ovary syndrome.
1.3.2 Treatment, Screening and Diagnosis
Results of two large, randomized controlled trials conducted in Australia (ACHOIS trial)
(27) and the United States (28) prove that treatment of GDM with dietary advice, blood glucose
monitoring, and insulin as required, significantly improves adverse perinatal complications. As a
result, current Canadian clinical practice guidelines (14) recommend the timely detection of
GDM through a two stage screening and diagnostic test (Figure 1.1). During the first stage, a
one hour 50 g glucose challenge test (GCT) is administered between 24 and 28 weeks of
gestation; those women who test positive on the GCT progress to stage two, where a diagnostic
oral glucose tolerance test (OGTT) is performed. Of note, many aspects of disagreement persist
5
in the areas of both screening and diagnosis for hyperglycemia in pregnancy, with international
bodies recommending slightly different tests and threshold values (7).
FIGURE 1.1 CDA guidelines for screening and diagnosis of GDM1
11hPG, 1 hour plasma glucose; 2hPG, 2 hour plasma glucose; 3hPG, 3 hour plasma glucose; CDA, Canadian Diabetes Association; FPG, fasting plasma glucose; GCT, glucose challenge test; GDM, gestational diabetes mellitus; IGT, impaired glucose tolerance; OGTT, oral glucose tolerance test. 2 In view of the controversies about diagnostic tests, other accepted methods may be used.
All pregnant women between 24-28 weeks’ gestation
If multiple risk factors for GDM are present, screen during the first trimester of pregnancy and reassess during subsequent trimesters
GCT: A 50 g glucose load followed by a 1hPG, given at any time of day
1hPG ≥10.3 mmol/L 1hPG = 7.8-10.2 mmol/L 1hPG <7.8 mmol/L
75 g OGTT2 Measure FPG, 1hPG
and 2hPG levels
FPG≥ 5.3 mmol/L 1hPG≥ 10.6 mmol/L 2hPG≥ 8.9 mmol/L
If 1 value is met or exceeded
IGT of pregnancy
If 2 values are met or exceeded GDM Normal
Reassess during subsequent trimesters if multiple risk factors for
GDM are present
6
1.4 The Glucose Challenge Test Initially proposed by O’Sullivan et al. in 1973 (29) and recommended at the First
International Workshop-Conference on GDM (13), adoption of the one hour 50 g GCT as a
screening tool for hyperglycemia during pregnancy is now widespread. Using the GCT,
approximately 84% of Canadian and 94-97% of American obstetricians now practice universal
prenatal screening for gestational hyperglycemia (13). Although opinions differ as to the optimal
threshold for the GCT (30), many professional bodies including both the CDA (14) and the
Society of Obstetricians and Gynaecologists of Canada (13) endorse a threshold value of 7.8
mmol/L. At this threshold, the sensitivity and specificity of the GCT for detection of GDM is
79% and 87% respectively (29). Accepted because of its cost effectiveness; ease of
administration; and sensitivity, the GCT is administered without regard to the time of day, and
timing or content of last caloric intake. As a result, several factors can confound the results of
this test. These are discussed in the following sections.
1.4.1 Confounding Effect of Diurnal Variation
Glucose tolerance is known to deteriorate in the afternoon (31, 32). Two studies (33, 34)
have examined the effect of diurnal variation on the GCT results in pregnant women. Findings
from a 2002 study indicate that a significantly greater percentage of women tested in the
afternoon had a positive GCT (31.3%) when compared to those women tested in the morning
(17.0%), yet a greater percentage of the women from the morning GCT group were ultimately
diagnosed with GDM (40% versus 31.5%) (34). Wong et al. (33) reported similar findings.
Despite similar mean GCT blood glucose concentrations between groups, a significantly greater
number of women with a positive GCT performed in the morning were diagnosed with GDM
[positive predictive value (PPV) 49.6%] versus those with a positive GCT performed after
midday (PPV 42.6%) (33).
This deterioration in glucose tolerance after midday has been associated with a decrease
in insulin sensitivity, insufficient insulin secretion, and an increase in insulin disposal, thought to
be controlled by circadian rhythms in cortisol levels (35). Indeed, plasma cortisol levels are
highest in the morning, with concentrations decreasing throughout the day (36). An in vivo
7
inverse relationship has been shown between plasma cortisol levels and PG and serum insulin
concentrations (35).
1.4.2 Confounding Effect of Fasting Interval
The greatest proportion of studies investigating potential GCT confounders has focused
on the time interval between the last meal consumed and GCT administration, known simply as
the fasting interval (37-40). Employing a randomized cross-over design, Coustan et al. (37) first
investigated this phenomenon in 1986 among pregnant women with and without GDM. A
significantly higher mean GCT result was observed for women with GDM when taking the test
in the fasting versus the fed (GCT administered one hour postprandial using a standard mixed
meal) state (9.7 mmol/L vs. 8.6 mmol/L; P = 0.011), but not in those with normoglycemic
pregnancies (37). Noted major limitations by the authors of this study included the investigation
of only one fasting time interval; and the use of a standard mixed meal, thus rendering results
nontransferable to clinical practice, where the nutrient composition of women’s meals prior to
the GCT is unknown (37). As a result, subsequent studies attempted to explore these limitations.
Results from a prospective study conducted in normoglycemic pregnant women without
regard to the composition of their last meal before GCT administration varied from those
reported by Coustan et al. (38). In this study, although normoglycemic participants completing
their GCT in the fasting (GCT administered greater than three hours postprandial) rather than fed
(GCT administered less than three hours postprandial) state experienced a significant increase in
mean GCT results, this result was seen only in obese normoglycemic participants (38). Women
with GDM were excluded from this study making it impossible to determine what effect, if any,
the experimental conditions would have had on this group.
The effects of fasting and two different fed states (GCT administration either one or two
hours postprandial) on GCT results, using a standard mixed meal was explored by a matched
case-control study (39). A higher false positive rate was observed in the normoglyemic pregnant
controls who completed the GCT in the fasting (58%) versus fed (25%) states (39). As per prior
findings, significantly higher mean GCT concentrations were observed in the fasting
normoglycemic pregnant controls (7.8 mmol/L) when compared to those normoglycemic
8
controls who were fed both one (6.7 mmol/L) and two hours (6.3 mmol/L) prior to GCT
administration (39). However, in contrast to Coustan et al., no difference was observed between
the fasted and one hour postprandial fed state (39). A significantly higher mean GCT result was
only observed in women with GDM who took the GCT in the fasted (10.45 mmol/L) versus 2
hour postprandial fed state (39). This dissimilarity may be explained by the composition of the
standard meals provided in each study; Coustan et al. provided a standard meal containing a
lower proportion of CHO (35% versus 50%), and a higher proportion of fat (47% versus 35%)
and protein (19% versus 15%). Also, both studies failed to report the amount of available CHO
in each standard meal, which may have also contributed to the difference in results observed.
Involving 3836 pregnant women, the Toronto Tri-Hospital Gestational Diabetes Project
(40) was the largest and most conclusive study investigating fasting interval. A significant J-
shaped relationship was found in mean GCT results as per fasting interval, with GCT results
initially declining as the fasting interval increased and then starting to rise again at the three to
four hour fasting interval (40). Through the use of receiver-operator characteristic (ROC)
curves, new GCT thresholds based on fasting interval were proposed, and these new thresholds
were shown to have a significant reduction in the overall misclassification rates of GCTs through
a decrease in false positive tests (40).
Together, results from these studies indicate an improvement in GCT glucose tolerance
for women with and without GDM when pre-GCT administration fasting intervals range between
one to three hours. Known in the literature as the Staub-Traugott effect (39), this improvement is
of sufficient size to significantly alter the sensitivity and specificity of the GCT (40). However,
studies to date have failed to clearly elucidate whether this effect, as seen in pregnancy, is due to
enhanced insulin secretion, improved insulin sensitivity, or a combination of both (38, 39).
1.4.3 Confounding Effect of Race-Ethnicity
Given the recognized variation in prevalence of GDM among different ethnic
populations, it is reasonable to believe that race-ethnicity may have an impact on the efficiency
of the GCT as a screening test. Although research in this area is limited, results from both
Esakoff et al.’s (41) retrospective study, and Nahum and Huffaker’s (42) prospective study
9
indicate race-ethnicity as a confounding variable with respect to GCT results. These studies
found a significant and independent effect of ethnicity on GCT results (P = 0.02) after
controlling for parity, ponderal index, height, age, fetal gender and smoking status (42); and
varying sensitivity and specificity of the GCT by ethnicity as analyzed by ROC curve analysis (P
<0.001) after controlling for maternal age, body mass index (BMI), parity, education, and
insurance status (41). To maximize the sensitivity and specificity of the GCT in different race-
ethnicities, both studies recommend race-specific GCT thresholds. Lowered thresholds are
proposed for women of African American descent and higher thresholds are proposed for women
of Asian descent (41, 42).
1.4.4 Confounding Effect of Height
One study has reported on the confounding effect of height on GCT values. Jang et al.
(43) conducted an observational study on 9005 pregnant Korean women to investigate whether
short stature contributed to the risk of GDM. The age and BMI adjusted GCT values were
highest in the shortest height quartile (≤157 cm), and decreased significantly as the height
increased to the tallest quartile (≥163 cm) (43). Similarly, a significant and negative association
was observed between the frequency of a positive GCT and height quartile; 28.6% of women in
the shortest quartile of height had a positive GCT result, compared to 17.8% of women in the
tallest quartile of height who experienced a positive GCT (43).
1.5 Prevention of Maternal Hyperglycemia Until recently, research pertaining to hyperglycemia during pregnancy has been largely
devoted to its diagnosis and treatment; however, interest in its prevention through modifiable
factors such as physical activity and diet is now emerging (16, 44-46). A limited number of
studies now exist which examine the effects of dietary variables, both prior to- (47-50) and
during pregnancy (51-57), in association with the risk of maternal hyperglycemia. Since dietary
counselling during pregnancy has been shown to effectively change maternal food and nutrient
intake (58, 59), prevention of maternal hyperglycemia through the manipulation of dietary
factors is a logical route for exploration.
10
1.5.1 Pre-pregnancy Dietary Variables and Risk of Maternal Hyperglycemia
A limited number of studies have investigated pre-pregnancy dietary variables and their
association with the development of GDM (47-50). Findings are primarily from single
prospective cohort studies using dietary intake data from the Nurses’ Health Study II (NHSII). A
large prospective observational study, the NHSII includes 116,671 female nurses in the United
States (48). Through the use of biennial mailed questionnaires, which gather data on health-
related behaviours and disease incidence, this cohort has been continually followed since 1989
(48). Dietary information obtained from over 13,000 women in 1991 with a validated 133-food
item semi-quantitative food-frequency questionnaire (SFFQ) to assesses dietary intake in the
previous year, and subsequent documented incident cases of GDM in defined years were used by
these studies to assess the association of pregravid diet on risk of GDM (47-49). Collective
results strongly associate a dietary pattern coined by authors as the Western pattern, with an
increased risk of GDM (47-49). This positive association is largely attributed to three dietary
factors within the Western pattern; (1) high red and processed meat intake (47); (2) low fibre and
high glycemic load (GL) intake (48); and (3) high sugar-sweetened cola intake (49).
When compared with women who consumed less than two servings of red meat per
week, those who consumed more than six servings of red meat per week had a significant 1.55-
fold increase in the risk of GDM after adjustment for known risk factors for type 2 diabetes;
GDM; fatty acids; cholesterol; and other components of the Western pattern (including refined
grain products, snacks, sweets and desserts, French fries and pizza) (47). Also, when compared
to women who consumed less than two servings of processed meat per week, those who
consumed more than six servings of processed meat per week had a significant 1.41-fold increase
in the risk of GDM (47).
After adjustment for a host of covariates including age, BMI, physical activity and dietary
factors, Zhang et al. (48) observed that a diet low in cereal fibre and high in dietary GL was
associated with a significant 2.15-fold increased risk of GDM compared to a diet high in cereal
fibre and low in dietary GL. Of note, in the model adjusted for parity, age, and BMI, a
significant association in this study was seen between dietary GI and risk of GDM. Those
women consuming the highest quintile of GI intake (>80.7) were found to be at a significant
11
1.30-fold increased risk of GDM compared to those consuming the lowest quintile (<72.9);
however this significance was lost in the fully adjusted model [relative risk = 1.40, 95%
confidence interval (CI) 1.00–1.68] (48). Last, in their fully adjustment model, Chen et al. (49)
observed a 22% increased risk of GDM for women who consumed more than five servings per
week of sugar-sweetened cola, when compared to those who consumed less than three servings
per month.
To date, only Moses et al. (50) has assessed the impact of pregravid diet on risk of GDM
in a cohort different from the NHSII. This study is also the first to assess pregravid dietary
variables and their potential impact on recurrence of GDM. Although the sample size was small
(14 women with a recurrence of GDM and 21 women without), dietary intake obtained from a
dietary history interview and a three day food record indicate that when compared to those
women without a recurrence of GDM, women who have GDM in successive pregnancies
consumed a significantly higher proportion of calories from fat; a significantly lower proportion
of calories from CHO; and a significantly lower intake of fibre (g) (50). However, no significant
difference was observed in the types of fat (including saturated, polyunsaturated and
monounsaturated) consumed by both groups of women (50).
Thus, for a minimum of one year proceeding pregnancy, high intakes of red meats;
processed meats; and sugar-sweetened colas combined with low a low fibre intake and high
dietary GL appear to be associated with a greater risk of GDM. In a similar fashion, once
diagnosed with GDM, dietary intake that is high in fat, and low in CHO and fibre prior to
subsequent pregnancies, may increase the risk of recurrence of GDM. However, all associations
discussed here are observational in nature and primarily drawn from the same population of
women; therefore, further randomized clinical investigations are required before strong
conclusions with respect to these dietary variables may be drawn. Of note, was the findings
observed by Zhang et al. (48) for dietary GI. Although the significance of association for GI
with risk of GDM was lost in the fully adjusted model, the strong trend towards risk seen with
this variable is of interest and warrants potential investigation.
12
1.5.2 Dietary Variables During Pregnancy and Risk of Maternal Hyperglycemia
Most research investigating dietary risk factors for GDM have focused on dietary
variables during the prenatal period. Many of these studies (51-55), although not all (56, 57),
have found an association between dietary fat intake during pregnancy and risk of GDM;
however the direction of these associations differs depending on the type of fat assessed.
Specifically, after controlling for potential pregravid and gravid confounders, studies conducted
by both Bo et al.(51), and Tovar et al. (52) showed significant and positive associations between
saturated fat intake and risk of GDM. Bo et al. showed a 1.3-fold increased risk for IGT and
GDM with every 10% increase in saturated fat as a percentage of total fat intake (51), while
Tovar et al. showed that higher intakes of saturated fat as a percentage of total energy were
associated with a 1.3-fold increased risk of having a positive GCT (52). Of note, both Bo et al.
and Tovar et al. failed to control for one type of fat versus others in final analysis; in final
analyses, Tovar et al. also failed to assess and/or adjust for the potential confounding effects of
recognized GCT covariates discussed in sections 1.4.1 to 1.4.3 of this work.
In contrast to these results, a recent study (53) found a significant 1.61-fold increased risk
of GDM associated with higher total fat intakes (% of total energy) during the second trimester;
however no significant associations were observed in the fully adjusted model for any specific
type of fat (including saturated, trans, monounsaturated and polyunsaturated). A significant
negative association was also observed between CHO intake and risk of GDM [odds ratio (OR)
= 0.60, 95% CI 0.40–0.90] (53). Saldana et al. (54) confirmed these results by use of
substitution models. For every one percent of total calories in CHO substituted with the same
amount in fat, a significant 10% increase in risk for both IGT and GDM was observed (54).
However, as individual types of fat were not assessed in this study, it is impossible to assess what
role, if any, specific types of fat might have played in this positive association observed.
Two studies observed a significant and independent negative association between
polyunsaturated fat intake and risk of GDM (51, 55); however in their fully adjusted model, one
of the studies (51) found that this significance remained only in women without conventional
risk factors for GDM. Using different endpoints, both Wang et al. (55) and Tovar et al. (52)
observed an independent and negative association between polyunsaturated to saturated (P:S) fat
13
ratio and risk of hyperglycemia during pregnancy. Comparing the dietary intake in pregnancy of
56 women diagnosed with GDM to 77 women with normoglycemic pregnancies matched for
maternal age; gestational age; height; and parity, a significant negative association was found
between P:S fat ratio and risk of IGT and GDM (P = 0.03) (55). Tovar et al. reported a negative
association between P:S fat ratio and risk of a positive GCT (OR = 0.10, 95% CI 0.02–0.45)
(52); however as noted before, caution is used in interpreting findings from this study as types of
fat were not controlled for in final analyses.
Fibre intake was found to be independently and significantly associated with risk of
gestational hyperglycemia. In their fully adjusted model, Tovar et al. (52) found an independent
and negative association between fibre intake (g) and risk of a positive GCT (OR = 0.9, 95% CI
0.84–0.99). After adjustment for age, BMI, familial diabetes, height and percentage of saturated
fat, Bo et al. (51) also reported a significant negative association between fibre intake (g) and the
risk of both IGT of pregnancy and GDM (P = 0.043). However, authors noted that this
association was quite small (β = –0.008).
No significant associations between any dietary variables examined and risk of maternal
hyperglycemia was reported by two studies (56, 57). Although one of these studies (56) did
observe a significant and positive association between increasing intake of omega-3 fatty acids
and risk of GDM, the authors of this study attributed these results to chance.
Much like the studies assessing the association of pre-pregnancy dietary variables and
risk of maternal hyperglycemia, these studies examining diet during pregnancy are observational
in nature, thus making it impossible to infer causality in their findings. Difficulty in assessing the
totality of these results is further increased by the use of different cut-off criteria for assessment
and diagnosis of hyperglycemia during pregnancy used by these studies and each study
controlling for different covariates. Despite this, these results do suggest that during pregnancy
higher intakes of both total and saturated fat; lower intakes of polyunsaturated fat and a P:S fat
ratio may be associated with an increased risk of maternal hyperglycemia. Conversely, higher
intakes of CHO and fibre may offer a potential protective effect.
14
1.6 A Low Glycemic Index Diet for the Prevention of Maternal Hyperglycemia While strong conclusions on the role of dietary variables consumed either before or
during pregnancy in the prevention of maternal hyperglycemia cannot be drawn from the
collective results presented above, it is apparent through assessment of this body of literature that
a large void in research exists. Despite the observed potential protective effect of CHO, no
studies have attempted to elucidate the potential relationship between type of CHO and the risk
of hyperglycemia, although such studies exist for fat. The GI is a qualitative measure that
classifies the type of CHO according to the postprandial blood glucose response it elicits (17).
Therefore, intervention studies using diets comprised of foods with varying GIs is needed to
clarify the observed protective effect on risk of maternal hyperglycemia, which consumption of
CHO appears to have. Indeed, a recent meta-analysis (45) on interventions for preventing GDM
concluded that advice on a low-GI index diet during pregnancy might be beneficial, but that
better designed studies, providing high-quality data are needed before definitive conclusions can
be drawn.
1.6.1 The Glycemic Index
Formally defined as “the incremental area under the blood glucose response curve
elicited by a 50 g available carbohydrate portion of a food expressed as a percentage of the
response after 50 g anhydrous glucose taken by the same subject” (60), the GI simply describes
by numerical classification, how different CHO foods affect our bodies’ postprandial blood
glucose levels. The GI of foods is divided into three major classifications; low (GI ≤55),
medium (GI 56-69), and high (GI ≥70). When compared with medium- or high-GI foods, those
foods with a low-GI elicit lower postprandial blood glucose responses (61), with the GI being a
significant determinant of the glycemic response to mixed meals (62). Evidence indicates that
despite recognized pregnancy-induced changes to gastrointestinal function, the GI of foods is not
altered during this time (63). Despite being a topic of constant debate since it’s introduction in
the late 1970’s, several recent meta-analyses have indicated a low-GI diet to be effective for both
men and non-pregnant women in the dietary prevention and treatment of numerous chronic
diseases including diabetes (64), obesity (65), and coronary heart disease (66). Internationally,
15
several diabetes associations endorse the GI (67-69). In Canada, use of the GI is supported by
the CDA who, in their current Clinical Practice Guidelines, recommended that individuals with
type 1 or type 2 diabetes choose low-GI foods more often to aid in optimal glycemic control
(14). It is reasonable to assume that because of their effects on blood glucose response, low-GI
foods may be of benefit for women at risk for gestational hyperglycemia, who may be unable to
naturally compensate for the progressive state of glucose intolerance beginning mid-pregnancy
(16).
1.6.2 A Low Glycemic Index Diet During Pregnancy
Several randomized controlled trials have established the positive benefits which
consumption of low-GI foods during pregnancy provide (70-74). Clapp (71) conducted a small
study (n = 20) with pregnant women who ultimately completed uncomplicated pregnancies.
Participants consumed a low-GI before pregnancy and at eight weeks gestation were then
randomized to continue with their low-GI diet or switch to a high-GI diet for the remainder of
pregnancy. Both diets were reportedly similar in macronutrient distribution. Women in the
high-GI group experienced significantly higher means in several perinatal outcome variables
including birth weight (4.17 versus 3.33 kg); ponderal index (2.74 versus 2.47 g/cm3 × 100);
head circumference (36.6 versus 34.5 cm); and maternal weight gain (18.6 versus 10.4 kg).
In their study that randomized 62 women to a low-GI or a high-GI from the beginning of
their second trimester until birth, Moses et al. (70) also observed that infants born to those
women in the high-GI group had a higher prevalence of LGA (33.3 versus 3.1%); were of a
greater birth centile (69 versus 48); and had a greater ponderal index (2.74 × 100 versus 2.62
g/cm3 × 100). However, in contrast to Clapp’s findings, maternal weight gain did not differ
between the two groups (70). In their two year follow-up study, Moses et al. (75) found that the
initial significant difference in infant size between the groups persisted. After adjustments for
both group and age, LGA was found to be a significant predictor of current infant weight (75).
Children of women in the high-GI group were more likely to be heavier, but not taller when
compared to children of women in the low-GI group (75). Of note, despite their awareness
regarding the potential benefits of a low-GI diet during pregnancy all of the women (including
nine who were currently pregnant) had reverted back to their original pre-pregnancy diets (75).
16
This suggests that to sustain the incorporation of low-GI foods in successive pregnancies, dietary
education may be required before and during each pregnancy (76).
Although the long-term feasibility of a low-GI diet appears to be questionable,
achievement of a low-GI diet for the duration of pregnancy is certainly attainable, and highly
accepted among women. Several randomized studies have reported a significant change in
dietary GI between baseline and follow-up (GI difference between 6 to 8 points) for those in the
low-GI group (70, 73); and at follow-up (GI difference between 2.9 and 9 points) between those
randomized to the low- and high-GI diets (58, 70, 72, 73, 77). Additionally, studies conducted
by Moses et al. (70) and Grant et al. (72) found no statistical difference between dietary
intervention groups with respect to reported acceptability of the intervention diets. In fact, when
compared to those women in the high-GI group, women randomized to the low-GI diet in Moses
et al. were significantly more likely to agree that their low-GI diet was easy to follow (P <0.048)
(70).
One study has reported adverse effects associated with consumption of a low-GI diet
during pregnancy. Scholl et al. (78) found that when compared to those women in the highest
quintile of GI intake, those women consuming the lowest quintile gave birth to infants with a
significantly lower birth weight by a reduction of approximately 116 g, and had a significant
1.75-fold increased risk of having a small-for-gestational age (SGA) infant. Although large in
size (n = 1, 082), this study was observational in nature, and subsequent randomized trials have
found no significant difference of birth weights or prevalence of SGA infants between women
consuming either a low- or high-GI diet in both pregnant women with (77) and without GDM
(70). No other adverse maternal or fetal outcomes for the consumption of a low-GI diet during
pregnancy have been reported.
1.6.3 Biologic Plausibility
Evidence as to the possible mechanism by which a low-GI diet may improve glycemic
control and prevent hyperglycemia during pregnancy is provided by a 2002 study conducted by
Wolever and Mehling (79). In this randomized controlled trial, 34 men and non-pregnant
women with IGT were randomized to high-CHO-high-GI, high-CHO-low-GI, or low-CHO-high-
17
monounsaturated-fat diets for four months (79). Results indicate that the disposition index (DI)
(an index of the ability of the β-cell to increase insulin secretion to compensate for changes in
insulin sensitivity) in those participants consuming the high-CHO-low-GI diet improved
significantly (50%) relative to the other two intervention diets, and remained significant after
controlling for differences in the baseline DIs between the groups (79). This change in DI was
observed without a corresponding change in insulin resistance, thus indicating that improved β-
cell responsiveness (defined as an increase in insulin secretion for a given change in PG
concentration) is responsible for the difference in DI found (79). Since it is thought that both
GDM and IGT of pregnancy result when abnormalities in insulin sensitivity and β-cell
responsiveness occur, theoretically the improvement in β-cell responsiveness seen in this study
should improve glucose tolerance during pregnancy, and hence, reduce the risk of maternal
hyperglycemia in women at increased risk.
18
Chapter 2
Research Question
2.1 Rationale Current recommendations regarding GDM focus on its early detection and treatment. As
such, many obstetrical practices use a two stage screening and diagnostic test including a GCT
and OGTT (as necessary). Although practical, with good sensitivity and specificity, the GCT
has several recognized confounding factors including diurnal variation, fasting interval, race-
ethnicity, and height.
The increasing prevalence of GDM calls for preventative measures; however, research in
this area is only just emerging. Cumulative results from observational studies investigating
dietary variables consumed both before, and during pregnancy, suggest that increased intakes of
both total and saturated fat, and decreased intakes of polyunsaturated fat may increase the risk of
maternal hyperglycemia. In contrast, an increased intake of CHO and fibre may elicit a
protective effect. Together, these results indicate a void in research pertaining to the type of
CHO and its effect on the risk of GDM; perhaps the negative association observed between CHO
intake and risk of GDM is due to an increased consumption of low-GI foods.
Randomized controlled trials focused on diets composed of either low- or high-GI foods
during pregnancy have found a high-GI diet to be significantly associated with greater birth size
and ponderal index. In addition, achievement of a low-GI diet during pregnancy has been found
to be both attainable, and highly accepted among women. This, combined with the existence of
evidence for the mechanism by which low-GI foods may increase glucose tolerance during
pregnancy, justifies the need for an intervention trial exploring the effects of a low-GI diet during
pregnancy on blood glucose concentrations in women at an increased risk for GDM. Thus, this
research aims to expand upon the current understanding of the effects of consuming a low-GI
diet during pregnancy, and to fill a void by examining the relationship between consumption of a
low-GI diet and GCT results in women at risk for the development of GDM.
19
2.2 Hypothesis Women at risk for GDM consuming a diet composed of low-GI foods will have lower
GCT blood glucose concentrations and lower incidences of GDM and IGT than those consuming
a diet composed of medium- to high-GI foods.
2.3 Objectives Objective 1
Compare the GCT plasma glucose values of participants consuming a diet composed of
low-GI foods (the L-GI group) and of medium- to high-GI foods (the M/H-GI group).
Objective 2
Compare the following outcomes between those in the L-GI group and those in the M/H-GI
group:
(1) GCT outcome (test negative, test positive)
(2) Incidence of GDM
(3) Incidence of IGT of pregnancy
(4) Symptoms
(5) Maternal weight gain
(6) Study diet acceptability
20
Chapter 3
Materials and Methods
3.1 Study Design This study had a randomized, open-label, active-control design. The dietary intervention
was introduced as a supplement to standard obstetrical care. Two groups of pregnant women at
risk for GDM, and receiving standard obstetrical care were placed on two diets of varying
glycemic indices and compared with respect to GCT plasma glucose concentrations. All
materials and methods utilized in this study were reviewed and approved by the Research Ethics
Boards at both Mount Sinai Hospital and the University of Toronto.
3.2 Study Participants
3.2.1 Eligibility Criteria and Screening
In their most recent guidelines (14), the CDA has identified risk factors for Gestational
Diabetes. With the exception of having a pre-pregnancy BMI ≥30 kg/m2, all risk factors
identified by the CDA form the inclusion criteria for this study. In light of evidence obtained by
Naylor et al. (26), in association with the Toronto Tri-Hospital Gestational Diabetes Project, the
pre-pregnancy BMI risk factor was lowered to 25 kg/m2 for study inclusion. Findings from this
study indicate a pre-pregnancy BMI ≥25 kg/m2 to be a significant, independent clinical risk
factor for gestational glucose intolerance (OR = 3.2, 95% CI 2.1-4.8) (26). Prior to their clinic
appointments, the charts of patients from ten obstetrical offices at Mount Sinai Hospital were
screened for study eligibility.
21
Inclusion Criteria – patients over 12 weeks gestation, who meet one of the following criteria;
(1) ≥35 years of age
(2) Pre-pregnancy BMI ≥25 kg/m2
(3) Member of a high-risk population including women of Aboriginal, Hispanic, South
Asian, Asian and African descent.
(4) History of polycystic ovary syndrome (PCOS)
(5) Previous diagnosis of GDM
(6) Previous delivery of a macrosomic infant
(7) Use corticosteroids
(8) Have acanthosis nicricans
Exclusion Criteria – patients who meet one of the following criteria;
(1) Pre-existing diabetes (type 1 or type 2) prior to pregnancy
(2) Currently receiving or have recently received pregnancy nutrition counselling from a
Registered Dietitian
(3) Have an acute or chronic illness, or medication use which may affect CHO metabolism
(4) Language/literacy barriers which cannot be overcome via available resources
(5) Pregnant with multiples
(6) >18 weeks gestation
3.2.2 Recruitment and Informed Consent
Potential participants were approached for study recruitment at their first or second
obstetrical appointment, which took place at the start of their second trimester. Study Dietitians
not known by these patients, made initial contact using both a recruitment script and handout
(Appendix A) for consistency in recruitment procedures. Care was taken to ensure that potential
participants understood that study participation was voluntary and in addition to their standard
obstetrical care. If eligible, interested patients could agree to see one of the Study Dietitians that
same day for explanation of the study protocol and completion of the consent process. If
undecided regarding study participation, potential participants were informed they could either
22
take the recruitment sheet home with them and contact the Study Dietitians with their questions,
or leave their contact information for the Study Dietitians to call them at a later date.
The Study Dietitians, with the help of translation when required, obtained written
informed consent. Consent was obtained from interested participants prior to 18 weeks
gestation; however, from the time of recruitment (ranging between 12-17 weeks gestation) and
the 18 week gestation cut-off period, potential participants were allowed as much time as
required to decide whether they were interested in participating. Those who agreed to
participate, following completion of written informed consent, were randomized into either the
L-GI or M/H-GI groups.
3.2.3 Randomization and Concealment
Post consent, participants were randomly assigned to one of two intervention diets using
a random number generator in Lotus 1-2-3, 1997 edition (Lotus Development Corporation,
Cambridge, MA). To enhance allocation concealment, permuted blocks of randomly varied size
and a 1:1 allocation ratio was used (80, 81). Treatment assignments, sealed in sequentially
numbered opaque envelopes, were kept by the Study Dietitians and opened in the presence of
each participant in order the day they completed the consent form. Generation of the randomized
allocation sequence and creation of the allocation envelopes was done by the primary
investigator of the study, Dr. Thomas Wolever, who was not involved in the daily study
operations.
Due to the nature of the study, both the participants and Study Dietitians could not be
blinded as to which intervention group participants were randomized to; however, the Study
Dietitians were aware of the need to maintain impartiality and equivalent treatment between
groups. All other clinic personnel caring for the participants, including personnel who handled
and analyzed blood samples, were blinded regarding intervention group allocation.
23
3.3 The Dietary Intervention The dietary intervention was introduced as a supplement to standard obstetrical care.
Experimental procedures included two key elements: (1) dietary counselling, including the
provision of recommended foods lists and certain key foods (bread and rice); and (2) self-
administered questionnaires. Participants were considered part of the study from recruitment
until the results of their GCT and OGTT (if clinically indicated) were obtained. This equated to
a maximum total study inclusion period of 16 weeks. After consent was obtained, participants
were exposed to the intervention diet for a maximum of 16 weeks; however, the number of total
study visits varied from three to six depending on when participants entered the study and when
their GCT was performed. The following table outlines the timing and components of each
study visit, which participants in both intervention groups underwent during study enrollment.
Specific details of this table and standard obstetrical care at Mount Sinai Hospital are reviewed
in the following chapters.
TABLE 3.1
Study timeline1
Group Nutrition Class
Regular Clinic Visit Check-Ins GCT
Study Visit Number(s) 1 2-5 6 Weeks Gestation 12-18 14-24 24-28 Time (extra time for study visit) 1 hr 30 min 15 min 15 min Group nutrition education X Key foods (bread and rice) pick-up X X Symptoms Questionnaire X X Medication/Supplements Questionnaire X X Activity Level Questionnaire (RAPA) X X FFQ X X Diet Acceptability Questionnaire X
1FFQ, food frequency questionnaire; GCT, glucose challenge test; RAPA, Rapid Assessment of Physical Activity questionnaire. Boxes marked with an ‘X’ indicate what occurred for participants at each study visit.
24
3.3.1 Standard Obstetrical Care
All obstetrical patients at Mount Sinai Hospital have routine prenatal visits at
approximately 12, 16, 20, 24, and 28 weeks gestation; biweekly visits from 28 weeks onwards;
and weekly visits from 36 weeks gestation until delivery. In accordance with the CDA clinical
practice guidelines (14), all pregnant women between 24 and 28 weeks gestation are screened for
GDM using a one hour 50 g GCT. During this test, patients consume 300 mL of GlucoDex
(Rougier Pharma, Mirabel, QC, Canada) containing 50 g of dextrose at any time of day, in either
the fasting or fed state. A blood sample is then drawn one hour after the glucose load. As per
CDA threshold values (14), the GCT is considered positive if the PG is ≥7.8 mmol/L; GCT
values ≥10.3 mmol/L are used to presume the presence of GDM, while GCT values ranging
between 7.8–10.2 mmol/L require the patient to undergo a diagnostic OGTT.
An OGTT is performed between 28-32 weeks gestation in the morning after an overnight
fast ranging between eight to ten hours. Depending on which Mount Sinai laboratory patients
attend, a 75 g or 100 g OGTT is administered. During the 75 g OGTT, patients consume 300 mL
of GlucoDex (Rougier Pharma, Mirabel, QC, Canada) containing 75 g of dextrose. Blood
samples are drawn at fasting, one hour, and two hours after the glucose load. Canadian Diabetes
Association (14) PG threshold values of 5.3 mmol/L [fasting PG (FPG)]; 10.6 mmol/L (one hour
PG); and 8.9 mmol/L (two hour PG) are used. During the 100 g OGTT, patients consume 300
mL of GlucoDex (Rougier Pharma, Mirabel, QC, Canada) containing 100 g of dextrose.
Blood samples are drawn at fasting, one hour, two hours, and three hours after the glucose load.
National Diabetes Data Group (82) conversion of original O’Sullivan values from whole blood
to PG thresholds of 5.8 (FPG); 10.6 (one hour PG); 9.2 (two hour PG); and 8.0 (three hour PG)
are used. For both the 75 g and 100 g OGTT, IGT of pregnancy is diagnosed if any one PG
value meets or exceeds a defined threshold; GDM is diagnosed if any two PG values meet or
exceed their respective thresholds.
All blood samples are analyzed centrally at Mount Sinai Hospital. Plasma glucose is
measured using the hexokinase enzymatic method (Roche/Hitachi MODULAR ANALYTICS P
800 MODULE, Roche Diagnostics Canada, Laval, QC, Canada), with an estimated coefficient of
variation of 5.0% for day-to-day precision. Unless diagnosed with GDM, registered dietetic
counselling for this group of women is currently not part of standard care.
25
3.3.2 Dietary Counselling
Prior work (58) indicates that small group (N = 2-6) dietary counselling led by a
Registered Dietitian is effective in significantly reducing the GI of maternal diets during
pregnancy. In this study, participants at their initial study visit attended a group education class
focused on healthy eating during pregnancy. Separate classes, led by one of the Study Dietitians,
were held for those participants randomized into either the L-GI or M/H-GI groups. As women
were recruited on an ongoing basis, class sizes varied from one participant to a maximum group
size occurring in this study of five. The class was divided into three parts of varying length and
detail: (1) a brief description of the women’s changing bodies and their babies’ developmental
milestones during the second trimester; (2) education regarding nutrients of common concern
and current Canadian dietary guidelines to support a healthy pregnancy; and (3) instructions
regarding the intervention diet (focused on either the low- or medium/high-GI diet depending on
which group participants attending the class were randomized to). A presentation, along with
participant interaction and the provision of supporting written materials (including Canada’s
Food Guide to Healthy Eating (CFGHE) and the recommended foods lists) comprised these
classes. Used during both education regarding dietary guidelines to support a healthy pregnancy
and the intervention diet, CFGHE allowed for simple integration of the intervention diet into
participants’ knowledge of CFGHE recommended dietary intakes during pregnancy. No specific
or individual recommendations were made about fat, protein, CHO, fibre or total energy intake.
Complete details regarding all topics covered in each class can be found in Appendix B.
Instruction regarding the intervention diet took approximately one third of the total
teaching time (15-20 min). During this, the concept of the GI was introduced. In particular,
participants learned the impact of varying glycemic indices on blood sugar values, and the
effects of cooking and processing on the GI. Participants were also introduced to their
recommended foods lists and instructed to substitute 100% of their current dietary starch choices
with either the low- or medium/high-GI starchy foods contained on their list.
After this education class and until the GCT, participants were met at their routine
obstetrical appointments for in-person maintenance visits. During these visits, adherence to the
intervention diet was discussed and participants received solutions to challenges they
encountered following the study protocol including dietary counselling regarding the GI of
26
starchy foods they wished to consume, and appropriate replacements for starchy food items they
were craving. The Study Dietitians were also available for participants outside of scheduled
study visits, providing answers to both email and telephone queries.
3.3.3 The Recommended Foods Lists
Previous studies (72, 83) focused on low-GI education had success in altering the dietary
GI of participants by incorporating key food substitution lists. This food substitution method has
been successfully used in our lab to direct the food intake of study participants during the
intervention period (72). In our study, women were asked to select their starch choices from a
food substitution list referred to as the recommended foods list (Appendix C) specific to their
assigned intervention group. This list was adapted from the work of a previous research study
conducted in our lab (72), which was also focused on a low-GI diet during pregnancy. Portion
sizes for each recommended food item were listed as per CFGHE serving sizes (84) beside each
food. Both lists recommended foods recognized by Health Canada as healthy during pregnancy
when consumed as part of a balanced diet (85) and tried to match food items recommended with
respect to dietary fibre. As described in the previous section, subjects were encouraged to
choose 100% of their daily starch food choices from their assigned list, while aiming to achieve
CFGHE recommended daily number of food guide servings for women aged 19-50. To assist
participants, recommended food list items were organized according to their respective CFGHE
food groups, with category headings colour coded as per CFGHE (84).
When developing the lists, the GI of each food item was obtained largely from published
international tables using glucose as the reference value (86). The GI of food items not found in
these tables was obtained from alternate published resources (87-89) or our own unpublished
data. Those foods having a low-GI were assigned to the L-GI group recommended foods list,
while those having a medium/high-GI were assigned to the M/H-GI group recommended foods
list. The L-GI group recommended list contained 27 foods with an average GI of 43; 26 food
items comprised the M/H-GI group recommended list with an average GI of 73. Little dietary
change was expected to occur for the M/H-GI group, as their recommended food items were
typical of those consumed in the North American diet.
27
3.3.4 Key Foods
To support both study recruitment and protocol compliance, participants were provided
throughout the intervention period with either low- or medium/high-GI bread and rice specific to
their assigned intervention group. These items were selected because it was believed that bread
and rice constitute the main starchy food items consumed by Canadian women. Those in the L-
GI group received Stonemill Bakehouse Sprouted 3 Grains & Oatmeal Bread (GI = 48) and
Bistro Express® Original Converted® Brand Rice (GI = 48). Those in the M/H-GI group
received Dempster’s® Wholegrains Multigrain Bread (GI = 71) and Selection® Long Grain
Brown Rice (GI = 66). Participants were allotted with enough key foods to last between study
visits. Per week, one loaf of bread and either three 250 g bags of the Bistro Express® rice or one
900 g bag of the Selection® brown rice as per their intervention groups was generally provided;
however, this was flexible depending on participants’ specific needs. If desired, patients were
able to substitute the key food items for their own bread and/or rice, provided that it complied
with the GI of their intervention group.
3.4 Data Collection
3.4.1 Data Sources
This study utilized three sources of information.
(1) Participants’ Medical Charts – The following information was obtained via participants’
medical charts;
• Name
• Age
• Date of birth (DOB)
• Medical record number
• Ethnic origin
• Phone number
• Prescription medication and/or dietary supplement use and changes
28
• Gestational age
• GCT and OGTT (if clinically indicated) values
• Development of GDM and IGT of pregnancy
• Weight at study entry
• Weight gain until delivery
• Medical history
(2) Oral Communication with Participants – The following information was obtained via oral
communication with participants;
• Changes in prescription medications and/or dietary supplement use
• Study questions and/or concerns
• Time of last meal or drink (other than water) prior to the GCT
(3) Self-administered Study Questionnaires – The following information was obtained via
self-administered study questionnaires;
• Usual activity level and changes in activity level during the study period
• Medical symptoms
• Prescription medication and/or dietary supplement use and changes in medication and/or
dietary supplement use during the study period
• Study diet acceptability
• Usual consumption of the recommended food items
3.4.2 Pre-testing of Study Questionnaires
All self-administered questionnaires used in this study were pre-tested with ten
obstetrical patients from Mount Sinai Hospital, who met the eligibility criteria for participation in
this study. During one-on-one interviews, these patients were asked to complete a copy of the
questionnaires. Feedback regarding reading clarity, content and ease of completion was obtained
by concurrent questioning-based pre-testing (90), whereby the women thought aloud during
completion of the questionnaires. The pre-testing was stopped after ten patients were
interviewed as no new information regarding how to enhance the questionnaires was being
29
obtained. Revisions to the questionnaires were then made based on suggestions elicited in these
interviews.
3.4.3 Anthropometrics and Gestational Age
Height (cm or m) and pre-gravid body weight (lbs or kg) were determined by participant
recall and recorded at the initial study visit. After this, participants’ weight was measured and
recorded throughout the study period at each routine obstetrical visit as part of standard care.
Individual clinics with separate scales were responsible for weighing their patients; seven of the
clinics used beam balance scales (Health o meter®, Boca Raton, FL, United States), two used
spring scales (Health o meter®, Boca Raton, FL, United States), and one used a digital spring
scale (Thinner® Bathroom Scales, Conair®, Woodbridge, ON, Canada). Patients were weighed
on the same scale belonging to their obstetric clinic for the duration of the study period. Pre-
pregnancy BMI was calculated as pre-gravid weight (kg) / height (m)2, and weight gain during
the study period was calculated as the difference between the first measured study weight (study
entry weight) and the weight at the GCT. All anthropometric measurements obtained throughout
the study period were recorded on page 2 of the data entry form (Appendix D).
Estimated due date (EDD), by either last menstrual period or early ultrasound, was
recorded in participant’s medical charts by their obstetrician at their first obstetrical visit.
Gestational age at study visits was calculated as the difference between the EDD and the date of
the study visits by an electronic gestational age calculator (91) provided by Auckland District
Health Board (Auckland, New Zealand).
3.4.4 Physical Activity Level
Participants’ usual physical activity levels were determined at both the initial (Appendix
E, pages 1-2) and final study visits (Appendix F, pages 1-2) by the Rapid Assessment of Physical
Activity (RAPA) instrument (92). Developed by the University of Washington, Health
Promotion Research Centre the RAPA is deigned for personal, clinical practice and research use
(92). Selected for use in this study due to its ease of administration and interpretation, the RAPA
30
is a nine-item questionnaire assessing strength, flexibility, and level of physical activity (92).
This study did not use the strength and flexibility components of the questionnaire, reducing the
number of questions to seven. However, omission of these components did not affect the
integrity of the RAPA as they are independently scored from the physical activity component.
Questions contained in the physical activity component have ‘Yes’ or ‘No’ response options;
total scoring involves simply choosing the question with the highest score with an affirmative
response (92). Each score then corresponds to one of five summary categories of physical
activity ranging from sedentary to active (92). Validity and reliability testing amongst a diverse
group of older adults (N = 115) consisting primarily (72%) of women found the RAPA to have
81% sensitivity and 69% specificity compared with the Community Health Activities Model
Program for Seniors, a survey previously validated against an objective measure of physical
activity (92). The RAPA was found to have a sixth grade readability level as assessed by the
Homan-Hewitt Readability Formula (92).
3.4.5 Medical Symptoms and Medication/Dietary Supplement Use
Both the medical symptoms and medications/dietary supplements intake questionnaires
were adapted from those used in a previous research study (93) also focused on a low-GI diet.
The medical symptoms questionnaire asked participants about the presence and severity of 18
medical symptoms at both their initial (Appendix E, page 3) and final study visits (Appendix F,
page 3). Participants were provided with none, mild, moderate or severe response options and
their corresponding definitions to assist with questionnaire completion. The readability of this
questionnaire was found to be at the seventh grade level as assessed by the Flesch-Kincaid Grade
Level Formula.
At their initial visit, participants were asked to indicate the dose, frequency, reason for
consumption, and start date for any prescription medication(s) and/or nutritional supplement(s)
they were taking (Appendix E, page 4). After this, at each study visit, participants were asked by
one of the Study Dietitians about any changes to their medication(s) and/or supplement(s). All
information obtained from participants was recorded by the Study Dietitians on the changes in
31
medications data entry forms (Appendix D, pages 3-6) and cross-referenced with participants’
medical charts. At the final study visit, participants completed a medication change questionnaire
(Appendix F, page 4). This questionnaire asked participants to list changes in their medication
and/or dietary supplement regime from their last study visit, including the dose, frequency,
change or stop date, and reason. The initial visit medication/supplement questionnaire was
found to have an eleventh grade readability level as assessed by the Flesch-Kincaid Grade Level
Formula. The final visit medication change questionnaire was assessed at the sixth grade level.
3.4.6 Study Diet Acceptability
At their final study visit, a diet acceptability questionnaire created specifically for use in
this study assessed participants’ opinions regarding their intervention diet (Appendix F, page 9).
This questionnaire was created for use in this study, with input from both academics and research
clinicians being incorporated during the development process. There is a total of six questions
divided into three sections, with each section using Likert item response options. In section one,
participants were asked to compare the difficulty of following their study diet to their regular
diet. Using a six-point Likert item, response options ranged from very easy to very hard, with a
no answer option also provided. In section two, participants were asked to compare their study
diet to their regular diet against four variables of interest, taste; ease of cooking/preparation; ease
of purchasing; and price. Each variable used a four-point Likert item ranging from better to
worse, with a no answer option provided. Section three required participants to rate the
cooking/preparation time of their study diet when compared to their regular diet. Using a four-
point Likert item, response options ranged from less time to more time, with a no answer option
provided. This questionnaire was found to have a fourth grade readability level as assessed by
the Flesch-Kincaid Grade Level Formula.
3.4.7 Participant Adherence
A SFFQ created specifically for use in this study measured participants’ dietary
adherence at both the initial (Appendix E, pages 5-8) and final study visits (Appendix F, pages 5-
8). A random combination of all 53 food items from the recommended food lists for both
32
intervention groups comprised this SFFQ. A frequency scale for intake of food items was
adapted from the Harvard 80out SFFQ (94) and provided participants with a range of intake
frequencies ranging from never up to two to three times per day. On both the initial and final
SFFQs, participants were asked to indicate their frequency of consumption for the intervention
food items during the three months before and during the study period respectively.
Research has indicated factors that positively influence participant adherence (95-98). As
per these findings, this study employed the following techniques to enhance adherence
throughout the study period:
• Participants were educated about the rationale for the intervention dietary change, while
being attentive to their individual educational needs and focusing only on necessary
information.
• Participants were engaged and made a part of the study process by providing food choice
through the recommended foods lists. These lists also allowed participants to tailor their
intervention diet to suit their individual lifestyles.
• Key food items were provided.
• The study was designed to have minimal impact on participants’ lifestyles by scheduling
follow-up visits and the final study visit during standard obstetrical appointments;
creating a simple intervention consisting of only dietary counselling and self-
administered questionnaires; and keeping the study duration as short as possible.
• A positive relationship with participants with created and maintained by being easily
accessible for answers to concerns and queries.
• Social support was encouraged through welcoming family members to the group
education session and educating both participants and their family members as
appropriate.
• Adherence with the study protocol was routinely assessed during follow-up
appointments, with solutions to barriers reported during this time being addressed.
33
3.4.8 Screening for and Diagnosis of GDM and/or IGT of Pregnancy
Screening for and diagnosis of GDM and IGT of pregnancy followed standard obstetrical
care as outlined in section 3.3.1 of this chapter. On the day of their GCT, participants were
asked the time of their last meal or drink (other than water) before their GCT to determine the
fasting time-to-GCT interval. This information, including the outcome of the GCT and OGTT
(if indicated) were recorded in the data entry form (Appendix D, page 2).
3.5 Statistical and Analytical Procedures
3.5.1 Power and Sample Size Analysis
GCT test results were obtained from 44 charts of obstetrical patients from Mount Sinai
Hospital who met the eligibility criteria for participation in this study [mean = 6.63 mmol/L,
standard deviation (SD) = 1.58]. Based on these values and using the t-distribution, the table
below shows the difference in GCT values, which can be detected with 80% power for a total
number of participants varying from 50 to 400.
TABLE 3.2 Sample size estimation for differences in GCT values from 0.51-1.47 mmol/L1
Total Number of Participants Required Detectable Difference in GCT Values (mmol/L)
50 1.47 100 1.03 150 0.84 200 0.73 300 0.59 400 0.51
1GCT, glucose challenge test.
34
The impact of a low-GI diet on GCT blood glucose concentration is currently unknown.
Therefore, there was no way of deducing what difference was to be expected. However, we
believed it was feasible to recruit 200 participants over 15 months, i.e. approximately 100
subjects randomized to the L-GI group and 100 randomized to the M/H-GI group. This number
of subjects would provide a statistical power of 80% (two-sided alpha value of 0.05) to detect a
difference in GCT values of 0.73 mmol/L. Such a difference would be clinically significant as
an increase in GCT values of 0.8-1.0mmol/L was found to be associated with significantly
increased incidence of adverse maternal-fetal outcomes in participants of the Toronto Tri-
Hospital Gestational Diabetes Project (11).
3.5.2 Statistical Software and Analysis
Data analysis was preformed on the 45 women who remained in each intervention group
using IBM® SPSS® Statistics version 20.0 (Armonk, New York, United States). Descriptive
statistics included a comparison of maternal characteristics; maternal rates of GDM risk factors;
and physical activity levels both before and during the study period by intervention group. The
Shapiro-Wilk test for normality and calculation of skew and kurtosis was performed on the
maternal characteristic continuous variables. Variables found to have approximately normal
distributions were compared using Independent samples t tests (two-tailed) and Wilcoxon-Mann
Whitney U tests were used for continuous variables whose distributions were skewed.
Categorical variables were compared by Pearson’s chi-square test, or Fisher’s exact test when
expected cell counts were less than five . Maternal rates of GDM risk factors and GCT and
OGTT (when indicated) outcomes are reported as counts and percentages. Physical activity
levels both before and during the study period were compared by Person’s chi-square test, or
Fisher’s exact test when appropriate.
A comparison of participant symptoms at baseline and change in symptom severity
during the study period, and the acceptability ratings between participants’ regular and study
diets were both done by Person’s chi-square test or Fisher’s exact test when appropriate.
35
The dietary GI calculated is only for the starchy food items on the recommended food
lists, termed here as the dietary GI from recommended foods, and was calculated by the
following formula;
Σ[GI of food item × number of servings consumed per day of food item × available CHO
(avCHO) per serving of food item] ÷ Σ(avCHO per day)
Analysis of daily nutrient intakes and servings of the recommended food items at both
baseline and during the study period was done by two-way mixed analysis of variance
(ANOVA), looking at the effect of time, intervention group and their interaction. A significant
difference was only considered significant if a significant interaction was present. An interaction
was interpreted as the effect of time differing between groups. Post-hoc comparisons were made
by Fisher’s least significant difference (LSD) test. All data is reported on non-transformed
variables.
For both intervention groups, a comparison of mean maternal weekly weight gain (kg)
with recommended target ranges was made by Pearson’s chi-square test. Based on pre-
pregnancy BMI, these target ranges are for recommended weekly weight gain during the second
and third trimesters of pregnancy as per the Institute of Medicine’s (IOM) most recent guidelines
(15); BMI <18.5 kg/m2 = 0.44-0.58 kg/wk; BMI 18.5-24.9 kg/m2 = 0.35-0.50 kg/wk; BMI 25.0-
29.9 kg/m2 = 0.23-0.33 kg/wk; and BMI ≥30 kg/m2 = 0.17-0.27 kg/wk.
Unadjusted means for both maternal weight gain (kg) during the study period, and GCT
values (mmol/L) were compared using Independent samples t tests (two-tailed). To assess the
independent effect of intervention group on both of these outcomes, analysis of covariance
(ANCOVA) was applied. Potential confounders were selected by means of literature [maternal
weight gain during the study period (99); GCT values (33, 34, 37-43)] and evaluation of the data
through scatterplots. Due to the significant difference found in distributions between
intervention groups at baseline, parity was also considered a confounding variable. It was
estimated that ten cases of data were required for each predictor in the model (100) and, due to
power limits with the sample size obtained, not all identified confounders could be adjusted for.
Thus, in the selection of final models, variables were exchanged for one another within the limits
of sample size and evaluated by both their significance and effect on the coefficient of
36
determination (R2) for the model; final models presented contain the covariates deemed as most
important within the limits of sample size. The final model studying the association of
intervention group with maternal weight gain (kg) during the study period (outcome variable)
controlled for height (continuous); parity (categorical); and race-ethnicity (categorical). The
final model studying the association of intervention group with GCT values (outcome variable)
controlled for fasting interval (continuous); time of day the GCT was performed (continuous);
gestational age at the time of the GCT (continuous); height (continuous); and parity (categorical).
To evaluate for potential collinearity among covariates, correlation coefficients were calculated
and it was demonstrated that non were highly correlated (no correlations were above 0.30).
Variables with skewed distributions were transformed, and data analysis was repeated with no
significance found; therefore, all data is reported on non-transformed variables.
Continues variables for both daily nutrient intakes and servings of recommended foods
are expressed as mean ± standard error of measure (SEM). All other continuous variables are
expressed as mean ± SD or median and interquartile range (IQR) and categorical variables as
percentages. Partial eta squared (η2), effect size (r) and R2 are reported for ANCOVAs. A P-
value less than 0.05 was considered statistically significant; all P-values are two sided.
37
Chapter 4
Results
4.1 Descriptive Statistics
4.1.1 Maternal Baseline Characteristics, Compared by Intervention Group
This study recruited for a 10-month period starting in February 2010. As shown in
Figure 4.1, 496 women were approached for study participation; 118 were randomized to the L-
GI (n = 56) or M/H-GI (n = 62) diet; and 28 (24%) withdrew. Reasons provided for participation
refusal and withdrawal are listed in Figure 4.1. Participation for those women who remained in
the study (L-GI, n = 45; M/H-GI, n = 45) spanned from February 2010 to April 2011.
At baseline, women in both intervention groups had a mean age and gestation of
approximately 35 years and 14 weeks respectively. Median pre-pregnancy BMIs for women in
the L-GI group (median = 22.9, IQR = 7.42) and M/H-GI group (median = 23.4, IQR = 6.25)
were classified as normal. In total, 49 women (44%) were Caucasian. Participation in this study
occurred during their first pregnancy (primigravida) for 18 of the 52 (32%) women in the L-GI
group and 16 of the 62 (26%) women in the M/H-GI group. Almost half (L-GI, n = 27/56; M/H-
GI, n = 28/62) of the women in both intervention groups were primiparious [having previously
delivered a fetus ≥24 weeks gestation (101)] and 89% of the women in both groups (L-GI, n =
50/56; M/H-GI, n = 55/62) had no previous macrosomic infants [birth weight >4000 g (13)].
The highest rate of significant medical history occurred in the genitourinary category for women
in both intervention groups (L-GI, n = 17/56; M/H-GI, n = 18/62). Ninety-three percent (n =
87/94) of the women reported taking a prenatal vitamin. A detailed description of participants’
significant medical history and medication/dietary supplement intake can be found in
Appendices G and H respectively. As shown in Table 4.1, the difference in distribution of
baseline characteristics between intervention groups was tested using Independent samples t
38
tests; Wilcoxon-Mann Whitney U tests; Pearson’s chi-square tests; or Fisher’s exact tests as
appropriate. A significant difference in the distribution of parity was found between the
intervention groups at baseline [χ2(2) = 6.28, P = 0.04]; a larger proportion of women in the L-
GI group were nulliparous (n = 27/56 versus n = 23/62), while a larger proportion of women in
the M/H-GI group were multiparous (n = 11/62 versus n = 2/56). No other significant
differences in baseline characteristics were found between intervention groups.
FIGURE 4.1 Study flow diagram
Approached for Study Participation (n = 496)
Enrollment (N = 118)
Refused (n = 280) No response (n = 119) Not interested (n = 83) No time (n = 56) Could not comply with diet (n = 22) Ineligible (n = 98) Failed inclusion criteria (n = 60) Failed exclusion criteria (n = 38)
Randomization Low-GI Diet
(n = 56) Medium/High-GI Diet
(n = 62)
Follow-up
Withdrew (n = 11) No time (n = 5) Couldn’t comply with diet (n = 3) Fetal demise (n = 1) Lost to follow-up (n = 2)
Withdrew (n = 17) No time (n = 8) Couldn’t comply with diet (n = 4) Embryonic/fetal demise (n = 2) Lost to follow-up (n = 1) Other (n = 2)
Analysis Analyzed (n = 45) Analyzed (n = 45)
39
TABLE 4.1 Maternal characteristics at baseline, compared by intervention group1 L-GI
(n = 56) M/H-GI (n = 62) P
Demographic characteristics Age (y) 35.9 ± 3.82 35.1 ± 3.6 0.28 Race-ethnicity3 C:A:O (%) 46:25:29 42:30:28 0.83 Measures Gestational age (wks) 14.8 ± 1.7 14.9 ± 1.9 0.73 Height (m) 1.64 ± 0.06 1.64 ± 0.07 0.77 Pre-pregnancy weight (kg) 63.0 (18.5)4 62.1 (20.2) 0.86 Pre-pregnancy BMI (kg/m2) 22.9 (7.42) 23.4 (6.25) 0.64 Study entry weight (kg) 65.2 (14.9) 66.9 (21.0) 0.87 Study entry BMI (kg/m2) 23.9 (7.63) 25.7 (6.52) 0.67 Gravida P:M (%) 32:68 26:74 0.45 Parity 0:1:>1 (%) 48:48:4 37:45:18 0.04 Previous macrosomia6 N:Y (%) 89:11 89:11 0.92 Significant medical history (% present) Cardiovascular 14 11 0.63 Dermatological 0 2 1.005 Endocrine 21 27 0.45 Gastrointestinal 7 5 0.715 Genitourinary 30 29 0.88 Hematological 5 3 0.675 Hepatic 9 3 0.255 Lymphatic 0 0 - Musculoskeletal 9 7 0.735 Neurological 2 10 0.125 Renal 5 3 0.675 Respiratory 11 10 0.85 Medications7 (% taking) Anti-hypertensive 2 0 1.005 Anti-thyroid 2 0 1.005 Anti-nausea 6 6 1.005 Anti-reflux 2 2 1.005 Bronchodilators 9 0 0.125 Thyroid hormone replacement 9 13 0.50 Dietary supplements7 (% taking) Adult multivitamins 2 4 1.005 Prenatal vitamins 94 92 1.005 Folic acid 19 9 0.14
(Continued)
40
TABLE 4.1 (Continued) Maternal characteristics at baseline, compared by intervention group1 L-GI
(n = 56) M/H-GI (n = 62) P
Dietary supplements7 (% taking) Omega 3 19 21 0.80 Vitamin D 28 19 0.33
1 A, Asian; BMI, body mass index; C, Caucasian; O, other; L, light; L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group; N, No; O, other; P, primigravida; M, multigravida; Mod, moderate; V, vigorous; Y, Yes. Means ± SDs were compared by Independent samples t test. Skewed distributions (median, interquartile range) were compared by Wilcoxon-Mann Whitney U test. Categorical variables (%) were compared by Pearson’s chi-square test or Fisher’s exact test when expected cell counts <5. 2 Mean ± SD (all such values). 3 Low-GI group, n = 52; M/H-GI group, n = 60. 4 Median; interquartile range in parentheses (all such values). 5 Compared by Fisher’s exact test. 6 Defined as weight >4000 g. 7 Low-GI group, n = 47; M/H-GI group, n = 47.
Table 4.2 lists the rates of study inclusion criteria (GDM risk factors), compared by
intervention group. Among the women recruited, being greater than or equal to 35 had the
highest rate of prevalence; 77 of the 118 women (65%) met this risk factor. Approximately half
of all the women (n = 55/118) were also considered members of a high-risk ethnicity (women of
Aboriginal, Hispanic, South Asian, Asian and African descent). No women recruited had
acanthosis nigricans.
Table 4.3 lists the total number of study inclusion criteria (GDM risk factors) possessed
by participants. The majority of women in the L-GI group possessed a total of one GDM risk
factor (n = 30/56), compared to the M/H-GI group where the highest percentage of women (n =
29/62) possessed two. No women possessed six or more risk factors.
41
TABLE 4.2 Study inclusion criteria (GDM risk factors), compared by intervention group1 L-GI
(n = 56) M/H-GI (n = 62)
Total (n = 118)
n % n % n % Age ≥35 38 68 39 63 77 65 Pre-pregnancy BMI ≥252 18 36 20 36 38 36 Member of a high-risk ethnicity3 26 50 29 48 55 49 PCOS 1 2 4 7 5 4 Previous GDM 4 7 2 3 6 5 Previous macrosomia 6 11 7 11 13 11 Corticosteroid use 2 4 0 0 2 2 Acanthosis nigricans 0 0 0 0 0 0
1 BMI, body mass index; GDM, gestational diabetes mellitus; L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group; PCOS, polycystic ovary syndrome. 2 Low-GI group, n = 50; M/H-GI group, n = 55. 3 Low-GI group, n = 52; M/H-GI group, n = 60.
TABLE 4.3 Participants’ total number of study inclusion criteria (GDM risk factors), compared by intervention group1 L-GI
(n = 56) M/H-GI (n = 62)
Total (n = 118)
n % n % n % One 30 54 28 45 58 49 Two 16 29 29 47 45 38 Three 7 13 4 7 11 9 Four 2 4 1 2 3 3 Five 1 2 0 0 1 1 Six 0 0 0 0 0 0 Seven 0 0 0 0 0 0 Eight 0 0 0 0 0 0
1 BMI, body mass index; GDM, gestational diabetes mellitus; L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group.
42
4.1.2 Participant Physical Activity Levels Before and During the Study Period by Intervention Group
Table 4.4 describes participants’ activity levels at baseline, and the change in activity
level during the study period by intervention group. At baseline, 70% (n = 66/94) of participants
had a moderate activity level. At the GCT, 43% (n = 40/94) of women reported a change in
activity level during the study period, with the majority of women in both groups (L-GI, n =
10/19; M/H-GI, n = 16/21) being less active. Statistical analysis by Pearson’s chi-square test or
Fisher’s exact test (when appropriate) revealed no significant difference in the distribution
between intervention groups with respect to either baseline activity levels or the change in
activity level during the study period.
TABLE 4.4
Activity level at baseline and change in activity level during the study by intervention group1
L-GI M/H-GI n % n % P Baseline activity level Light:Moderate:Vigorous 47 9:66:26 47 9:75:17 0.592 Change in activity level during study Less active:More active 19 53:47 21 76:24 0.12
1 L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group. Categorical variables (%) were compared by Pearson’s chi-square test or Fisher’s exact test when expected cell counts <5. 2 Compared by Fisher’s exact test.
4.1.3 Daily Nutrient Intake and Servings of Recommended Foods at Baseline and During the Study Period by Intervention Group
Table 4.5 lists the daily nutrient intakes from the recommended foods by intervention
group. There was a significant interaction between the intervention diet and time on the dietary
GI from recommended foods [F(1,88) = 72.41]. Post-hoc comparison by Fisher’s LSD test
indicate that for those in the L-GI group, the dietary GI from recommended foods significantly
decreased from baseline (mean = 55.3, SEM = 1.3) to follow-up (mean = 47.6, SEM = 0.7),
while the dietary GI from recommended foods for those in the M/H-GI group significantly
43
increased from baseline (mean = 58.6, SEM = 1.0) to follow-up (mean = 65.0, SEM = 1.0). Of
note, post-hoc analysis also revealed that dietary GI from recommended foods was significantly
different between intervention groups at baseline; women in the L-GI group had a significantly
lower dietary GI (mean = 55.3, SEM = 1.3) than women in the M/H-GI group (mean = 58.6,
SEM = 1.0).
There was a significant interaction between the intervention group and time on the energy
intake (kcal) from both the recommended low-GI [F(1,88) = 32.62] and medium/high-GI foods
[F(1,88) = 35.19]. Post-hoc comparisons by Fisher’s LSD test indicate that for those in the L-GI
group, mean energy intake (kcal) from recommended low-GI foods significantly increased from
baseline (mean = 168, SEM = 24) to follow-up (mean= 296, SD = 23), while mean energy intake
(kcal) from recommended medium/high-GI foods significantly decreased from baseline (mean =
168, SEM = 21) to follow-up (mean = 25, SEM = 5). No significant difference in the mean
energy intake from recommended low-GI and medium/high-GI foods was observed for those in
the M/H-GI group from baseline to follow-up.
A significant interaction between the intervention diet and time on the intake of avCHO
(g) from both the recommended low-GI [F(1,88) = 41.34] and medium/high-GI foods [F(1,88) =
35.11] was found. Post-hoc comparisons by Fisher’s LSD test indicate that for those in the L-GI
group, mean avCHO (g) intake from recommended low-GI foods significantly increased from
baseline (mean = 25.8, SEM = 3.6) to follow-up (mean= 48.3, SEM = 3.7), while mean avCHO
(g) intake from recommended medium/high-GI foods significantly decreased from baseline (x =
31.4, SEM = 3.9) to follow-up (mean = 4.6, SEM = 0.9). No significant difference was observed
from baseline to follow-up in the mean avCHO (g) intake from recommended low-GI or
medium/high-GI foods for those in the M/H-GI group.
A significant interaction between the intervention diet and time on the intake of fibre (g)
from both the recommended low-GI [F(1,88) = 10.79] and medium/high-GI foods [F(1,88) =
34.48] was found. Post-hoc comparison by Fisher’s LSD test indicate that for those in the L-GI
group, mean fibre (g) intake from recommended low-GI foods significantly increased from
baseline (mean = 6.0, SEM = 1.1) to follow-up (mean = 9.6, SEM = 1.0), while fibre (g) intake
from recommended medium/high-GI foods significantly decreased from baseline (mean = 2.7,
SEM = 0.3) to follow-up (mean = 0.5, SEM = 0.1). No significant difference was observed from
44
baseline to follow-up in the mean fibre (g) intake from recommended low-GI or medium/high-GI
foods for those in the M/H-GI group.
No significant interaction was found between the intervention group and time on the total
energy intake (kcal) from recommended foods [F(1,88) = 0.00]; the total avCHO (g) from
recommended foods [F (1,88) = 0.08]; and total fibre (g) intake from recommended foods [F
(1,88) = 1.05]. This indicates that these variables were similar between intervention groups at
both baseline and during the study.
45
TABLE 4.5 Daily nutrient intakes from recommended foods by intervention group at baseline and during the study1 P
L-GI M/H-GI D T D x T Dietary GI (%) Baseline 55.3 ± 1.3a 58.6 ± 1.0b <0.01 0.42 <0.01 Follow-Up 47.6 ± 0.7c 65.0 ± 1.0d Energy (kcal) Baseline 336 ± 342 299 ± 26 0.27 0.54 0.98 Follow-Up 322 ± 24 286 ± 29 Energy from Low-GI foods (kcal) Baseline 168 ± 24a 127 ± 13a,b
<0.01 0.02 <0.01 Follow-Up 296 ± 23c 75 ± 13b Energy from M/H-GI foods (kcal) Baseline 168 ± 21a 172 ± 18a
<0.01 <0.01 <0.01 Follow-Up 25 ± 5b 211 ± 22a
avCHO (g) Baseline 57.2 ± 5.8 51.6 ± 4.4 0.43 0.42 0.78 Follow-Up 53.0 ± 3.8 49.5 ± 5.1 avCHO from Low-GI foods (g)
Baseline 25.8 ± 3.6b 20.0 ± 2.0a,b
<0.01 0.01 <0.01 Follow-Up 48.3 ± 3.7c 11.0 ± 1.9a
avCHO from M/H-GI foods (g)
Baseline 31.4 ± 3.9a 31.6 ± 3.3a
<0.01 <0.01 <0.01 Follow-Up 4.6 ± 0.9b 38.6 ± 4.0a
Fibre (g) Baseline 8.7 ± 1.2 7.2 ± 0.7 0.03 0.48 0.31 Follow-Up 10.1 ± 1.0 6.9 ± 0.8 (Continued)
46
TABLE 4.5 (Continued) Daily nutrient intakes from recommended foods by intervention group at baseline and during the study1 P
L-GI M/H-GI D T D x T Fibre from Low-GI foods (g) Baseline 6.0 ± 1.1a 4.2 ± 0.6a,b <0.01 0.10 <0.01 Follow-Up 9.6 ± 1.0c 3.0 ± 0.5b Fibre from M/H-GI foods (g) Baseline 2.7 ± 0.3a 3.0 ± 0.3a,b
<0.01 0.02 <0.01 Follow-Up 0.5 ± 0.1c 3.9 ± 0.4b
1 avCHO, available carbohydrate; D, diet; T, time; GI, glycemic index; L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group. Means ± SEM were compared by two-way mixed ANOVA. Post-hoc analysis performed with Fisher’s LSD test. Values in a row with different superscript letters are significantly different, P < 0.05 (indicated only when there is a significant diet × time interaction). 2 Mean ± SEM (all such values).
47
Table 4.6 lists the daily serving intake of recommended foods by intervention group. A
significant interaction between the intervention diet and time on the total consumption of all
recommended foods (servings/day) [F(1, 88) = 4.70] was found. Post-hoc comparison by Fisher’s
LSD test indicate that at baseline, women in the L-GI group consumed significantly more servings
per day (mean = 2.8, SEM = 0.3) of the recommended foods than those women in the M/H-GI group
(mean = 2.5, SEM = 0.2); and this significant difference remained at follow-up (L-GI, mean = 2.9,
SEM = 0.2; M/H-GI, mean = 2.4, SEM = 0.2).
There was a significant interaction between the intervention diet and time on the
consumption of recommended low-GI foods (servings/day) [F(1,88) = 9.22]. Post-hoc comparison
by Fisher’s LSD test indicate that, at baseline (L-GI, mean = 1.2, SEM = 0.1; M/H-GI, mean = 0.9,
SEM = 0.1) and follow-up (L-GI, mean = 2.7, SEM = 0.2; M/H-GI, mean = 0.5, SEM = 0.1), women
in the L-GI group consumed more servings per day of the recommended low-GI foods than those in
the M-GI group. Also, those in the L-GI group significantly increased their daily consumption of
recommended low-GI foods from baseline to follow-up, while those in the M/H-GI group
significantly decreased their consumption.
There was a significant interaction between the intervention diet and time on the intake of the
key bread (servings/day) provided [F(1,88) = 16.17]. Post-hoc comparison by Fisher’s LSD test
indicate that at baseline, women in the L-GI group consumed significantly less servings per day of
the key bread (mean = 0.1, SEM = 0.1) than those women in the M/H-GI group (mean = 0.5, SEM =
0.1). However, at follow-up those women in the L-GI group consumed significantly more servings
per day of the key bread (mean = 0.9, SEM = 0.1) than those women in the M/H-GI group (mean =
0.7, SEM = 0.1).
No significant interaction was found between the intervention diet and time on the
consumption of recommended medium/high-GI foods (servings/day) [F(1,88) = 0.00], and the
consumption of key rice provided (servings/day) [F(1,88) = 2.03]. This indicates that the daily
serving intake of these foods was similar between intervention groups at both baseline and during
the study.
48
TABLE 4.6 Daily intake of recommended foods by intervention group at baseline and during the study1 P L-GI M/H-GI D T D x T All foods (servings/day) Baseline 2.8±0.3a 2.5±0.2b
0.16 0.93 0.03 Follow-Up 2.9±0.2a 2.4±0.2b
Low-GI foods (servings/day) Baseline 1.2±0.1a 0.9±0.1b
<0.01 <0.01 <0.01 Follow-Up 2.7±0.2c 0.5±0.1d
M/H-GI foods (servings/day) Baseline 1.6±0.22 1.6±0.2
<0.01 <0.01 1.00 Follow-Up 0.2±0.1 1.9±0.2 Key bread (servings/day) Baseline 0.1±0.1a 0.5±0.1b
0.35 <0.01 <0.01 Follow-Up 0.9±0.1c 0.7±0.1d
Key rice (servings/day) Baseline 0.0±0.0 0.1±0.0
0.06 <0.01 0.16 Follow-Up 0.2±0.0 0.2±0.1 1 D, diet; T, time; GI, glycemic index; L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group. Means ± SEM were compared by two-way mixed ANOVA. Post-hoc analysis performed with Fisher’s LSD test. Values in a row with different superscript letters are significantly different, P < 0.05 (indicated only when there is a significant diet × time interaction). 2 Mean ± SEM (all such values).
4.1.4 GCT and OGTT Outcomes, Compared by Intervention Group
All women who remained in the study completed the GCT and OGTT (when required) as per
standard obstetrical care. At the time of the GCT, there was no significant difference in the
gestational age (wks) of women in the L-GI group (mean = 27.5 wks, SD = 1.3) versus the M/H-GI
group (mean = 27.5 wks, SD = 1.3). There was also no significant difference in the period of time
(wks) that women in the L-GI group (mean = 11.1 wks, SD = 1.8) or M/H-GI group (mean = 11.2
wks, SD = 1.7) were on the intervention diet. Table 4.7 describes the outcomes for both of these
tests by intervention group. A total of seven women (L-GI, n = 1; M/H-GI, n = 6) completed a 75 g
OGTT and ten women (L-GI, n = 8; M/H-GI, n = 2) women completed a 100 g OGTT.
Approximately one in five women from both groups (L-GI, n = 9/45; M/H-GI, n = 8/45) tested
positive on the GCT and, as such, completed the OGTT. Oral glucose tolerance test results indicate
that three of the 45 women (7%) in the L-GI group were diagnosed with GDM, compared to no
49
women in the M/H-GI group. However, only two of the 45 women (4%) in the L-GI group were
diagnosed with IGT, compared to four of the 45 women (9%) in the M/H-GI group.
TABLE 4.7 GCT and OGTT outcomes by intervention group1
L-GI M/H-GI Total n % n % n % GCT Test negative2:Test positive3 45 80:20 45 82:18 90 81:19 OGTT Normal:IGT4:GDM5 9 44:22:33 8 50:50:0 17 47:35:18
1 GCT, glucose challenge test; GDM, gestational diabetes mellitus; IGT, impaired glucose tolerance of pregnancy; L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group; OGTT, oral glucose tolerance test. 2 Defined as the patient having normal glucose tolerance. 3 Defined as an abnormal blood glucose value (≥ 7.8 mmol/L); the patient is required to then complete the second stage of the screening process, the OGTT. 4 Defined as any one abnormal blood glucose value: fasting ≥5.8 mmol/L; 1 hour ≥10.6 mmol/L; 2 hour ≥9.2 mmol/L; 3 hour ≥8.1 mmol/L. 5 Defined as any two abnormal blood glucose values: fasting ≥5.8 mmol/L; 1 hour ≥10.6 mmol/L; 2 hour ≥9.2 mmol/L; 3 hour ≥8.1 mmol/L.
4.2 Participant Symptoms at Baseline and Change in Symptom Severity During the Study Period, Compared by Intervention Group
Table 4.8 indicates participants’ symptoms at baseline and the change in symptom severity
during the study period by intervention group. At baseline, the most frequently reported symptom
was fatigue; 94% (n = 88/94) of all women reported experiencing this symptom to some degree.
Hiccups were reported least (12%, n = 11/94). At the GCT, the greatest number of women reported
a change during the study period in nausea severity (63%, n = 59/94), with the majority of women in
both groups (L-GI, n = 22/29; M/H-GI, n = 25/30) reporting less nausea. Using Pearson’s chi-square
test, a significant difference in the distribution of reported hunger during the study between the
intervention groups [χ2(1) = 4.73, P = 0.03] was found. At the GCT, 19 of the 21 (91%) women in
the L-GI group whose hunger rating changed over the study period reported less hunger, compared
to only 13 of the 21 (62%) participants with less hunger in the M/H-GI group. Statistical analysis by
50
Pearson’s chi-square test or Fisher’s exact test (when appropriate) revealed no other significant
differences in distributions between intervention groups for any baseline symptoms or changes in
symptom severity during the study period.
51
TABLE 4.8 Symptoms at baseline and change in symptom severity during the study by intervention group1
% with Symptom at Baseline
Change in Symptom Severity During Study More Severe:Less Severe than at baseline
L-GI:M/H-GI2 L-GI M/H-GI % P n % n % P Headache 72:72 1.00 25 24:76 22 18:82 0.733
Fatigue 89:98 0.203 21 19:81 26 15:85 1.003
Diarrhea 13:19 0.40 8 50:50 7 86:14 0.283
Vomiting/throwing up 30:30 1.00 9 22:78 8 25:75 1.003
Hunger 81:92 0.14 21 10:91 21 38:62 0.03
Hiccups 13:11 0.75 7 43:57 5 60:40 1.003
Become exhausted quickly 81:85 0.58 20 35:65 20 45:55 0.52 Palpitation/throbbing of heart 30:38 0.38 16 69:31 13 54:46 0.473
Feelings of worry/anxiety 55:57 0.84 19 47:53 18 39:61 0.60 Constipation4 63:70 0.46 20 35:65 20 40:60 0.74 Lack of energy 87:96 0.273 21 33:67 24 33:67 1.00 Pains in joints or limbs 32:47 0.14 22 73:27 24 75:25 0.86 Reduced ability to concentrate4 50:51 0.92 12 42:58 19 47:53 0.76 Flatulence or gas in abdomen 70:83 0.14 29 35:66 21 43:57 0.55 Nausea 62:72 0.27 29 24:76 30 17:83 0.48 Indigestion/heartburn 51:49 0.84 18 56:44 24 71:29 0.31 Gloomy/sad thoughts5 28:35 0.46 14 50:50 15 47:53 0.86 Increased appetite/hunger 81:89 0.25 25 20:80 24 38:63 0.18
1 L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group. Categorical variables were compared by Pearson’s chi-square test or Fisher’s exact test when expected cell counts <5. 2 Low-GI group, n = 47; M/H-GI group, n = 47. 3 Compared by Fisher’s exact test. 4 Low-GI group, n = 46. 5 M/H-GI group, n = 46.
52
4.3 Maternal Weight Gain, Compared by Intervention Group Table 4.9 shows the mean maternal weekly weight gain (kg), compared to recommended
target ranges proposed by the IOM in their latest guidelines (15). Approximately half of the
women in both groups (L-GI, n = 25/45; M/H-GI, n = 23/45) had an average weekly weight gain
above their recommended target range. Statistical analysis using Pearson’s chi-square test
indicates no significant difference in the distribution of women who gained below, within, or
above average weekly weight gain targets between intervention groups.
TABLE 4.9
Comparison of mean maternal weekly weight gain during the study with recommended target ranges by intervention group1
L-GI M/H-GI n % n % P Maternal average weight gain (kg/wk) Below target:Within target:Above target2 45 22:22:56 45 24:24:51 0.92
1 L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group. Categorical variables (%) were compared by Pearson’s chi-square test. 2 Based on weight gain guidelines during pregnancy recommended by the Institute of Medicine (15).
Shown in Figure 4.2, the unadjusted mean maternal weight gain (kg) during the study
period for those in the L-GI group (mean = 5.9 kg, SD = 3.2) was not significantly different from
those in the M/H-GI group (mean = 5.7 kg, SD = 3.1) [t(88) = -0.40, P = 0.69]. After adjustment
by ANCOVA for height (m) [F(1,74) = 1.78, P = 0.19, r = 0.15]; parity [F(2,74) = 0.76, P =
0.47, partial η2 = 0.02]; and race-ethnicity [F(2,74) = 0.71, P = 0.49, partial η2 = 0.02], no
significant difference remained between intervention groups [F(1,74) = 0.07, P = 0.79, partial η2
= <0.00]. The adjusted R2 for the final model was 0.06.
53
FIGURE 4.2 Maternal weight gain (kg) during the study period, compared by intervention group1
1 L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group. Error bars represent the
95% CI. Weight gain during the study period is calculated as the GCT weight minus the weight at study entry.
4.4 GCT Values, Compared by Intervention Group Shown in Figure 4.3, the unadjusted mean GCT values (mmol/L) for those in the L-GI
group (mean = 6.4 mmol/L, SD = 1.5) was not significantly different from those in the M/H-GI
group (mean = 6.5 mmol/L, SD = 1.2) [t(88) = 0.54, P = 0.59]. After adjustment by ANCOVA
for fasting interval (hrs) [F(1,80) = 12.94, P = <0.00, r = 0.37]; time of day the GCT was
performed (hrs) [F(1,80) = 13.53, P = <0.00, r = 0.38]; gestational age at the time of GCT (wks)
[F(1,80) = 8.11, P = 0.01, r = 0.30]; height (m) [F(1,80) = 9.05, P = <0.00, r = 0.32]; and parity
[F(2,80) = 3.37, P = 0.04, partial η2 = 0.08], no significant difference remained between
intervention groups [F(1,80) = 1.58, P = 0.21, partial η2 = 0.02]. The adjusted R2 for the final
model was 0.32.
54
FIGURE 4.3 Mean GCT values (mmol/L), compared by intervention group1
1 GCT, glucose challenge test; L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet
group. Error bars represent the 95% CI.
4.5 Acceptability Ratings Between Participants’ Regular and Intervention Diets, Compared by Intervention Group
Table 4.10 compares acceptability ratings between participants’ intervention and regular
diets. Statistical analysis by Pearson’s chi-square test or Fisher’s exact test as appropriate found
a significant difference in the distribution of acceptability ratings between intervention groups
for almost all measured acceptability factors including compliance [χ2(2) = 25.36, P = <0.00];
ease of cooking/preparation [χ2(2) = 11.65, P = <0.00]; ease of purchasing [χ2 (2) = 10.53, P =
0.01]; price [χ2(2) = 7.17, P = 0.02]; and cooking/preparation time [χ2(2) = 10.48, P = 0.01].
Compared to their regular diets, 20 of the 45 women (44%) in the L-GI group reported their
intervention diet as harder to follow, in contrast to only three of the 45 women (7%) in the M/H-
GI group who reported their intervention diet as harder to follow. Sixteen (16) of the 45 women
55
(36%) in the L-GI group reported their intervention diet as easier to cook/prepare than their
regular diet, compared with only three of the 45 women (7%) in the M/H-GI who reported their
intervention diet as easier to cook/prepare. Twenty-four percent (24%) of the women (n = 11/44)
in the L-GI group found their intervention diet worse to purchase than their regular diet
compared to only 2% (n = 1/45) of the women in the M/H-GI who found their intervention diet
worse to purchase. Five (5) out of 42 women (12%) in the L-GI group reported the price of their
intervention diet as worse than their regular diet, compared to none of the women in the M/H-GI
group. Twenty-seven percent (27%) of the women (n = 12/45) in the L-GI group reported less
cooking/preparation time for their intervention diet than their regular diet, compared to only 7%
(n = 2/44) women in the M/H-GI group who reported less cooking/preparation time for their
intervention diet. No significant difference was found in the distribution of reported taste
between intervention groups.
TABLE 4.10 Acceptability ratings between participants’ intervention and regular diets by intervention group1 L-GI M/H-GI (n = 45) (n = 45) % % P Compliance Easier:Same:Harder to follow than regular diet 29:27:44 80:13:7 <0.00 Taste2 Better:Same:Worse than regular diet 11:68:21 9:87:4 0.063
Ease of cooking/preparation Better:Same:Worse than regular diet 36:56:9 7:82:11 <0.003 Ease of purchasing4 Better:Same:Worse than regular diet 18:58:24 14:84:2 0.01 Price5 Better:Same:Worse than regular diet 14:74:12 7:93:0 0.023 Cooking/preparation time Less:Same:More time than regular diet 27:53:20 7:84:9 0.01
1 L-GI, low-glycemic index diet group; M/H-GI, medium/high-glycemic index diet group. Categorical variables were compared by Pearson’s chi-square test or Fisher’s exact test when expected cell counts <5. 2 Low-GI group, n = 44. 3 Compared by Fisher’s exact test. 4 M/H-GI group, n = 44. 5 Low-GI group, n = 42; M/H-GI group, n = 44.
56
Chapter 5
Discussion
5.1 Overview and Discussion The primary objective of this thesis was to investigate the effects of a low-GI diet on the
GCT values in women at risk for GDM. This study had a randomized, open-label, active-control
design, where the dietary intervention was introduced as a supplement to standard obstetrical
care.
Objective 1
Compare the GCT plasma glucose values of participants consuming a diet composed of
low-GI foods (the L-GI group) and of medium- to high-GI foods (the M/H-GI group).
Results: In both the unadjusted and final models, no significant difference in GCT values was
found between participants in either the L-GI group (6.4 mmol/L) or M/H-GI group (6.5
mmol/L).
Objective 2
Compare the following outcomes between those in the L-GI group and those in the M/H-GI
group:
(1) GCT outcome (test negative, test positive)
Results: Eighty-percent (80%; n = 36) of those in the L-GI group tested negative on the GCT,
while 20% (n = 9) tested positive. Eighty-two percent (82%; n = 37) of those in the M/H-GI
group tested negative on the GCT, while 18% (n = 8) tested positive. In total, 17 of the 90
women who completed the study (19%) tested positive on the GCT.
57
(2) Incidence of GDM
Results: Thirty-three percent (33%; n = 3/9) of those in the L-GI group, who tested positive on
the GCT, were diagnosed with GDM (6.7% of all women in the L-GI group). No women in the
M/H-GI group, who tested positive on the GCT, were diagnosed with GDM.
(3) Incidence of IGT of pregnancy
Results: Twenty-two percent (22%; n = 2/8) of the women in the L-GI group who tested positive
on the GCT were diagnosed with IGT of pregnancy (2.2% of all women in the L-GI group).
Half (n = 4/8) of the women in the M/H-GI group who tested positive on the GCT were
diagnosed with IGT of pregnancy (8.9% of all women in the M/H-GI group).
(4) Symptoms
Results: At the GCT, a significantly greater proportion of women in the L-GI group whose
hunger rating changed over the study period reported less hunger, compared to women in the
M/H-GI group. No other significant differences in distributions between intervention groups for
any baseline symptoms or changes in symptom severity during the study period were found.
(5) Maternal weight gain
Results: When analyzed as a categorical variable for the proportion of women who gained
below, within, or above recommended weekly weight gain targets; no difference in the
distribution between intervention groups was found. When analyzed as a continuous variable for
maternal weight gain during the study period, no significant difference between the L-GI group
and M/H-GI group was found in either the unadjusted or final models.
(6) Study diet acceptability
Results: A significant difference in the distribution of acceptability ratings between intervention
groups was found for compliance; ease of cooking/preparation; ease of purchasing; price; and
cooking/preparation time. When compared to those in the M/H-GI group, more women in the L-
GI group rated their intervention diet as harder to follow, harder to purchase, and more
expensive, but easier to cook/prepare and requiring less cooking/preparation time than their usual
diet.
58
Contrary to our hypothesis, this trial of a diet composed of low-GI versus medium- to
high-GI foods found no differences in GCT values. Mean GCT values obtained for the
intervention groups were identical to the mean GCT value (6.5 mmol/L) reported in the Toronto
Tri-Hospital Gestational Diabetes Project (40). In addition, the total rate of positive GCTs found
in this study was identical to the rate reported in a large multispecialty clinic in the United States
(102). Similar to findings from previous studies, (1) fasting interval; (2) time of day the GCT
was performed; and (3) height were all found to have a medium and independent effect on GCT
values. Gestational age at the time of the GCT and parity were also found to have medium and
small independent effects on GCT values respectively.
One explanation for the similar GCT values found between intervention groups may be
found in the participants’ dietary intake data. During the study, the dietary GI from
recommended foods fell significantly for women in the L-GI group (by ≈7 units) and increased
significantly (≈5 units) for women in the M/H-GI group. Women in the L-GI group achieved
this through consuming significantly more low-GI, and less medium/high-GI recommended
starchy foods from baseline to follow-up, with women in the M/H-GI group achieving this
through consuming more medium/high-GI, and less low-GI recommended starchy foods from
baseline to follow-up. Despite this however, the total intake of recommended low- or
medium/high-GI foods averaged only 2.7 servings per day for those in the L-GI group and 1.9
servings per day for those in the M/H-GI group. Since participants were instructed to substitute
100% of their current dietary starch choices with either the low- or medium/high GI starchy
foods contained on their list, this low intake may have been caused by women either failing to
consume their recommended six to seven daily grain servings as per CFGHE; by women eating a
large amount of starchy foods items not found on their recommended lists; or a combination of
both. Subjects in the low-GI and high-GI groups from Wolever et al. (79), which provided
biologic plausibility for this study, consumed an average of three servings of key foods per day.
Thus, perhaps the lower consumption of recommended low-GI and medium/high-GI starchy
foods observed here failed to produce the significant difference expected in GCT values between
those in the L-GI and M/H-GI groups.
The overall incidence of GDM and IGT of pregnancy in our study population was 3.3%
and 6.7% respectively. Indeed, as this incidence of GDM is similar to that reported in the
Canadian population (14), it appears that despite the aim of this study to recruit women at high
59
risk for GDM, women who did participate were not representative of those with an actual
increased risk. Further to this point, over half of the women recruited had only one recognized
risk factor for GDM. A retrospective review (102) found that 92.4% of women who completed
pregnancies with normal glucose tolerance had at least one risk factor for GDM including
obesity, prior macrosomia or unexplained fetal death, maternal age ≥ 25 years, family history of
diabetes, or Hispanic or African ethnicity. Of the women recruited in this study with only one
recognized risk factor, 55.2% (n = 32/58) were recruited because of late maternal age (age ≥35
years). However, an American study conducted from 1999-2002 found that approximately only
six percent of women (n = 434/7658) over the age of 35 actually developed GDM (103). Thus,
late maternal age appears to be a much smaller predictive risk factor for GDM than other
recognized risk factors such as previous history of GDM, which has a reported recurrence rate of
30-84% in subsequent pregnancies (104). In this study, no women recruited with a single
recognized risk factor were recruited because of previous GDM. Since the benefits of
consuming a low-GI diet in pregnancy are thought to occur for those women who, due to higher
degrees of insulin resistance and β-cell deficiency, are unable to maintain normoglycemia during
pregnancy, the normal characteristics in our participants may have contributed to the similar
GCT values observed between intervention groups.
The lack of difference between GCT values seen in this study may also relate to the
timing and duration of the dietary intervention employed. On average, women in both the L-GI
and M/H-GI groups were exposed to their intervention diet for approximately two and a half
months. Indeed, a significant change in DI occurred for subjects consuming their low-GI diet for
a period of four months, almost double the exposure time seen in this study (79). Further,
women in the Zhang study – where results for a low-GI diet during pregnancy, although non-
significant in the fully adjusted model, did warrant further investigation into a L-GI diet for
blood glucose control during pregnancy – consumed a low-GI diet for a minimum of one year
(48). In contrast, dietary intervention was initiated for women in this study at the start of the
second trimester.
Consistent with previous results found in non-pregnant overweight women (105), women
in the L-GI group reported a significant decrease in reported hunger from baseline to follow-up.
Since low-GI foods are digested more slowly than medium/high-GI foods, the satiating effects of
low-GI foods are thought to result from slowed rates of nutrient absorption, which though
60
hormonal cascades, ultimately result in prolonged energy homeostasis, and a decrease in hunger
(106). However, since hormone and metabolic responses to the low- and medium/high-GI foods
consumed was not assessed in this study, it is impossible to know whether the reported hunger
found here for women in the L-GI group occurred by this mechanism.
Similar to results reported by a study investigating a low-GI diet on pregnancy outcomes
in women with GDM (77), this study found no difference between intervention groups in the
distribution of women who gained below, within, or above recommended weekly weight gain
targets. When compared with results from a recent study investigating weight gain in pregnancy
among 6233 Canadian women (107), the total proportion of women who gained below (23%
versus 19%), within (23% versus 33%), and above (53% versus 49%) recommended targets was
also similar. However, in contrast to these studies who measured weight gain for the duration of
pregnancy, weight gain in our study was measured only until the GCT. Since rates of weight
gain can vary throughout pregnancy, it is impossible to know if these similarities observed would
remain if weight gain in this study continued to be measured until the end of pregnancy. Of note,
when compared to the results from another study also focused on low-GI foods during pregnancy
(77), a greater proportion of women in our L-GI group gained above recommended weekly
weight gain targets (56% versus 25%). However, weight gain in this noted study was again
measured for the duration of pregnancy. As mentioned above, since rates of weight gain can
vary throughout pregnancy, it is impossible to know whether the greater proportion of women in
the L-GI group in this study who gained above recommended weight gain targets would have
remained at delivery.
In contrast with other studies performed during pregnancy that found no difference in
acceptability ratings between women consuming a diet composed of low-GI or medium/high-GI
foods (70, 72), intervention diet acceptability results in this study favoured the medium/high-GI
diet for ease of compliance; ease of purchasing; and price. This contrast may be explained by a
difference in provision of free food items during the study. Compared to our study, these prior
studies provided participants with a larger amount of free foods as per their intervention group
allocation, including a free monthly hamper of key foods (70), and $20 per week worth of non-
perishable study food items (72).
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5.2 Strengths and Limitations This study has a number of strengths and limitations, which should be considered when
interpreting the findings. To date, this study is the only randomized intervention trial
investigating the effects of a low-GI diet during pregnancy on GCT values. Women assigned to
the L-GI group were able to lower the GI of recommended starchy food items and maintain this
change for the duration of the study period. All of the women who participated in this study
completed their GCT and OGTT (as required), with all of the blood samples being processed by
the same laboratory within Mount Sinai Hospital.
Several limitations to this study are recognized. Since the Study Dietitians and
participants were not blinded, the presence of investigator bias and intervention group
contamination cannot be ruled out. However, with widespread knowledge in today’s society
about the GI, it was impossible to blind women as to which intervention group they were
randomized to. Therefore, during the group education class, it was explained to all women that
the best diet for preventing maternal hyperglycemia was unknown, and that helping to answer
this question was the purpose of this study. In addition, pre-pregnancy weight and height were
both self-reported by participants. Although, studies document that self-reported height (108)
and weight (108, 109) give an accurate representation of measured height and weight in women
of reproductive age, the literature also suggests that overweight women tend to underestimate
their weight (110) and underweight women tend to overestimate their weight (111). As a result,
this may have affected the number of women classified as below, within, and above weekly
weight gain targets. The FFQs used in this study consisted solely of those food items contained
in the recommended food lists. Although useful for assessing dietary intervention compliance,
we were unable to assess the overall dietary GI or intake of other starchy food items not
contained in the recommended food lists provided. Last, the sample size obtained in the present
investigation failed to meet required power estimates. In turn, this prevented full adjustment for
all recognized confounders of the results obtained for gestational weight gain and GCT values.
As such the final models used were unable to account for much of the variation observed in the
results found. Indeed the adjusted R2 obtained for the ANCOVA on GCT values was 0.32,
indicating that only 32% of the variability in GCT values found was accounted for by the final
covariates used, thus leaving 68% of the variability unexplained. The adjusted R2 obtained for
the ANCOVA on maternal weight gain during the study period was 0.06, indicating that only 6%
62
of the variability in maternal weight gain was accounted for by the final covariates used, thus
leaving 94% of the variability unexplained.
5.3 Future Directions As previously noted, the present investigation had a number of recognized limitations.
Therefore, to clarify whether the consumption of a diet during pregnancy composed of low-GI
foods may have beneficial effects on glycemic control, a future trial should be conducted which
focuses on (1) recruiting women at a known high risk of GDM (i.e. women who have had GDM
in a previous pregnancy, or have multiple recognized risk factors for GDM); (2) employing a
larger intervention, where low-GI foods encompass a larger proportion of the diet; (3) initiating
the dietary intervention at an earlier time point, such as prior to pregnancy or during the first
trimester; and (4) employing a more rigorous assessment of food intake, such as repeated 24 hour
recalls.
Finally, this study identified that provision of increased amounts of free-of-charge
intervention food items may have a confounding effect on the perceived acceptability of low-GI
diets during pregnancy. Thus, to help elucidate this relationship, a randomized controlled trial
providing low-GI dietary counselling versus low-GI dietary counselling plus the provision of
recommended foods should be employed.
5.4 Conclusions
In conclusion, this study found that when initiated in the second trimester, consumption
of a diet containing low-GI foods had no effect on either GCT values or maternal weight gain.
Mixed acceptability results for a low-GI diet during pregnancy were obtained. When compared
to those in the M/H-GI group, more women in the L-GI group rated their intervention diet as
harder to follow, harder to purchase, and more expensive, but easier to cook/prepare and
requiring less cooking/preparation time than their usual diet. Thus, it appears that dissatisfaction
of low-GI diets during pregnancy may be primarily related to the shopping experience, and if
consumption of a low-GI diet proves beneficial, greater support in this area when teaching about
63
the diet may minimize these reported adverse acceptance ratings. Despite this, both reported
symptoms and dietary intake data indicate that a low-GI diet is ultimately safe and sustainable
during pregnancy. The findings of this study provide pilot data for future studies investigating a
low-GI diet during pregnancy and the prevention of maternal hyperglycemia. These findings are
important at a time when the prevalence of GDM is increasing and thus, so is the need to find
effective and acceptable preventative strategies.
64
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Appendix A Recruitment Script and Handout
Recruitment Script
“Hi, my name is __________________ and I am a Dietitian conducting a study here at
this clinic with pregnant women who may be at risk for high blood sugars during pregnancy. If
you would like to take one [the recruitment sheet], this sheet will tell you more about the study
and, if you’re interested in being a part of it, what to do. Joining this study is optional, and, if
you choose not to join, your care at this clinic won’t change in any way.”
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Recruitment Handout
75
76
Appendix B Group Education Class Presentation Slides
Slides Common to Both Intervention Group Education Classes
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L-GI Group Education Class Slides
M/H-GI Group Education Class Slides
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Appendix C Recommended Food Lists
L-GI Group
Version 2 29-Jan-10
Recommended Foods Low GI Group
Potatoes 1 Food Guide Serving Sweet Potato 1/2 medium or 1/2 cup Precooked, Cold, White Potato (example: potato salad) 1/2 medium or 1/2 cup
Grains, Breads, Cereals 1 Food Guide Serving Ready Rice (provided) 1/2 cup cooked Barley 1/2 cup cooked Bulgur Wheat 1/2 cup cooked Pasta 1/2 cup cooked Parboiled Rice 1/2 cup cooked Barley Soup 1 cup Stone Mill Bread (provided) 1 slice Dimpflmeier Pumpernickel Bread 1 slice Dimpflmeier 100% Rye Bread 1 slice Dimpflmeier Linseed Bread 1 slice Bran Buds with Psyllium 1/3 cup or 30 g All Bran 1/2 cup or 30 g Red River Cereal, hot 3/4 cup cooked Oatmeal, large flake 3/4 cup cooked Quaker Oat Bran 3/4 cup cooked Legumes (Beans, Peas, Lentils) 1 Food Guide Serving Baked Beans (Veggie) 3/4 cup cooked or canned Baked Beans 3/4 cup cooked or canned Kidney Beans 3/4 cup cooked or canned Navy Beans 3/4 cup cooked or canned Pinto Beans 3/4 cup cooked or canned Split Peas (green, yellow) 1/2 cup cooked or canned Chick Peas/Garbanzo beans 3/4 cup cooked or canned Pigeon Peas 1/2 cup cooked or canned Lentils (red, brown, green) 3/4 cup cooked or canned Lentil Soup 1 cup
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M/H-GI Group
Version 2 29-Jan-10
Recommended Foods Medium to High GI Group
Potatoes 1 Food Guide Serving White Baked Potato 1/2 medium or 1/2 cup Mashed Potatoes 1/2 cup Instant Mashed Potatoes 1/2 cup cooked Boiled Potatoes 1/2 medium or 1/2 cup Potato Leek Soup 1 cup Grains, Breads, Cereals, Crackers 1 Food Guide Serving Brown Rice (provided) 1/2 cup cooked White Polished Rice 1/2 cup cooked Couscous 1/2 cup cooked Cornmeal 1/2 cup cooked or 20 g Dempster’s Whole Grain Bread (provided) 1 slice Light Rye Bread 1 slice Corn Bran 3/4 cup or 30 g Shredded Wheat’n Bran Spoon Size 1/2 cup or 30 g Shredded Wheat Spoon Size 1/2 cup or 30 g Shredded Wheat 1/2 cup or 30 g Cream of Wheat 3/4 cup cooked or 1 packet of instant Instant Oatmeal (no sugar added) 3/4 cup cooked or 1 packet Cheerios 3/4 cup or 30 g Corn Flakes 1 1/4 cups or 30 g Rice Krispies 1 cup or 30 g Special K, Original 1 1/4 cups or 30 g Bran Flakes 3/4 cup or 30 g Soda Crackers 10 crackers Stoned Wheat Thins 10 crackers Melba Toast (whole wheat) 6 toasts Ryvita Snack Bread 3 toasts
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Appendix D Data Entry Form
Low GI/GDM Risk Study Page 1 of 7
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
Medical History and Ethnic Origin Data Entry Form
Medical History
Body System Significant No (") 0 Yes(") 1 If YES specify condition
Cardiovascular Endocrine Gastrointestinal / hepatic Lymphatic / hematological Respiratory Neurological Renal / genitourinary Musculoskeletal Dermatological Other
Country of Origin:
!1 Aboriginal (Inuit, First Nations, Métis, Aborigine, Maori, Canadian)
!2 African/Black (Afro-Caribbean, Kenyan, Canadian)
!3 Australasian/Pacific Islander (Australian, New Zealander, Figin, Canadian)
!4 Caribbean (Jamaican, Antiguan, Trinidadian, Canadian)
!5 Central Asian (Uzbek, Afghan, Canadian)
!6 East Asian (Chinese, Japanese, Korean, Canadian)
!7 European/White (British, Russian, Greek, Canadian)
!8 Latin American (Brazilian, Peruvian, Nicaraguan, Canadian)
!9 Middle Eastern/West Asian (Israeli, Palestinian, Armenian, Iraqi, Canadian)
!10 North American (American, Mexican, Canadian)
!11 South Asian (Indian, Indo-Caribbean, Canadian)
!12 South-East Asian (Filipino, Laotian, Canadian)
!13 Mixed Heritage (Those with two or more ethnic backgrounds) !14 Other: _______________________________________________
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Low GI/GDM Risk Study Page 2 of 7
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
Study Visits Data Entry Form Informed consent: 12-18 wks gestation
Signed: _____/_____/_____ !!.! weeks gestation dd mm yy
Height: !!!.! cm OR !!.! ft !! inches Body weight: !!!.! kg OR !!!.! lbs Pre-pregnancy Body Weight: !!!.! kg OR !!!.! lbs PAPP-A result: !!.!! MoM
Initial Study Visit: 12-18 wks gestation Date : _____/_____/_____
!!.! weeks gestation dd mm yy Body weight: !!!.! kg OR !!!.! lbs Alpha Feto Protein (AFP): !!.!! MoM
Study Visits Coinciding with Regular Clinic Visits: 14-24 wks gestation Date : _____/_____/_____
!!.! weeks gestation dd mm yy Body weight: !!!.! kg OR !!!.! lbs
Study Visits Coinciding with Regular Clinic Visits: 14-24 wks gestation Date : _____/_____/_____
!!.! weeks gestation dd mm yy
Body weight: !!!.! kg OR !!!.! lbs Study Visits Coinciding with Regular Clinic Visits: 14-24 wks
gestation Date : _____/_____/_____ !!.! weeks gestation dd mm yy
Body weight: !!!.! kg OR !!!.! lbs Study Visits Coinciding with Regular Clinic Visits: 14-24 wks
gestation Date : _____/_____/_____ !!.! weeks gestation dd mm yy
Body weight: !!!.! kg OR !!!.! lbs Final Study Visit at time of GCT: 24-28 wks gestation
Date : _____/_____/_____ !!.! weeks gestation dd mm yy
Body weight: !!!.! kg OR !!!.! lbs Time of GCT: _________ ! AM ! PM Time of last meal: _____________
GCT value: !!.! mmol/L Developed GDM: !0 No
OGTT values: (fasting) !!.! mmol/L !1 Yes
(1hr) !!.! mmol/L
(2 hr) !!.! mmol/L Developed IGT: !0 No
(3hr) !!.! mmol/L !1 Yes
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Low GI/GDM Risk Study Page 3 of 7
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
Study Visits Coinciding with Regular Clinic Visits: 14-24 wks gestation
Changes in Medications Data Entry Form
Date of visit: _____/_____/_____ dd mm yy
Since the last visit, has there been any change in the prescription drugs, or nutritional supplements you are taking? No ! 0 Yes ! 1 If “yes” list under appropriate category*: (Only list changes. If there is no change, leave blank.)
Name Dose Frequency Start Date (dd/mm/yy) Reason
Prescription drugs ___/___/___
___/___/___
___/___/___
___/___/___
Nutritional supplements ___/___/___
___/___/___
___/___/___
___/___/___
* If subject changed dose or frequency record new dose/frequency and date started. If subject stopped taking medication, enter “0” for dose and the date stopped.
87
Low GI/GDM Risk Study Page 4 of 7
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
Study Visits Coinciding with Regular Clinic Visits: 14-24 wks gestation
Changes in Medications Data Entry Form
Date of visit: _____/_____/_____ dd mm yy
Since the last visit, has there been any change in the prescription drugs, or nutritional supplements you are taking? No ! 0 Yes ! 1 If “yes” list under appropriate category*: (Only list changes. If there is no change, leave blank.)
Name Dose Frequency Start Date (dd/mm/yy) Reason
Prescription drugs ___/___/___
___/___/___
___/___/___
___/___/___
Nutritional supplements ___/___/___
___/___/___
___/___/___
___/___/___
* If subject changed dose or frequency record new dose/frequency and date started. If subject stopped taking medication, enter “0” for dose and the date stopped.
88
Low GI/GDM Risk Study Page 5 of 7
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
Study Visits Coinciding with Regular Clinic Visits: 14-24 wks gestation
Changes in Medications Data Entry Form
Date of visit: _____/_____/_____ dd mm yy
Since the last visit, has there been any change in the prescription drugs, or nutritional supplements you are taking? No ! 0 Yes ! 1 If “yes” list under appropriate category*: (Only list changes. If there is no change, leave blank.)
Name Dose Frequency Start Date (dd/mm/yy) Reason
Prescription drugs ___/___/___
___/___/___
___/___/___
___/___/___
Nutritional supplements ___/___/___
___/___/___
___/___/___
___/___/___
* If subject changed dose or frequency record new dose/frequency and date started. If subject stopped taking medication, enter “0” for dose and the date stopped.
89
Low GI/GDM Risk Study Page 6 of 7
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
Study Visits Coinciding with Regular Clinic Visits: 14-24 wks gestation
Changes in Medications Data Entry Form
Date of visit: _____/_____/_____ dd mm yy
Since the last visit, has there been any change in the prescription drugs, or nutritional supplements you are taking? No ! 0 Yes ! 1 If “yes” list under appropriate category*: (Only list changes. If there is no change, leave blank.)
Name Dose Frequency Start Date (dd/mm/yy) Reason
Prescription drugs ___/___/___
___/___/___
___/___/___
___/___/___
Nutritional supplements ___/___/___
___/___/___
___/___/___
___/___/___
* If subject changed dose or frequency record new dose/frequency and date started. If subject stopped taking medication, enter “0” for dose and the date stopped.
90
Low GI/GDM Risk Study Page 7 of 7
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
Final Visit
Termination
Reason for termination: !1 Study completed according to protocol. ! Early termination (choose PRIMARY reason): !2 Unable to follow protocol. Details: ________________________ !3 Concurrent illness. Specify: ______________________________ !4 Lost to follow-up !5 Other, specify: Investigator’s statement: I certify that all the information entered into this Case Report Form by myself is complete and accurate. Investigator signature Date
91
Appendix E Initial Visit Questionnaire
FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 1 of 8
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!"#$%$&'!($)$%"#$%$&'!($)$%"#$%$&'!($)$%"#$%$&'!($)$%!!!!
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!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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!!!! University of Washington Health Promotion Research Center Copyright 2006 Funded in part by the Centers for Disease Control and Prevention Reproduced with permission
92
FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 2 of 8
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!"#$%$&'!($)$%"#$%$&'!($)$%"#$%$&'!($)$%"#$%$&'!($)$%!!!!
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!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
University of Washington Health Promotion Research Center Copyright 2006 Funded in part by the Centers for Disease Control and Prevention Reproduced with permission
!!!!!!!!!!!!!!!!
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FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 3 of 8
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!
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!!!!
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Mild = The symptom does not get in the way of your normal activities. Moderate = The symptom gets in the way of your normal activities, but does not stop them fully. Severe = The symptom stops you from doing your normal activities.
!
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!!!!
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FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 4 of 8
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
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FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 5 of 8
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
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FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 6 of 8
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
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F,A#%'!"EA&,%;'GA.%'H1I7'.?/'.""6%;J' !' !' !' !' !' !' !' !'C$*E%<''H1I7'.?/'.""6%;J' !' !' !' !' !' !' !' !'G%$;<'GA.%''H1I7'.?/'.""6%;J' !' !' !' !' !' !' !' !'C?EK?*'F,%$#'H1I7'.?/'.""6%;J' !' !' !' !' !' !' !' !'C*"5-'GA.%'H1I7'.?/'.""6%;J' !' !' !' !' !' !' !' !'!$&#$'H1I7'.?/'.""6%;J' !' !' !' !' !' !' !' !'D"?&."?&'H1I7'.?/'.""6%;J' !' !' !' !' !' !' !' !'D"*-'L%$E'H1I7'.?/'.""6%;'"*'7M'KJ' !' !' !' !' !' !' !' !'!$*N"AE%;'GA.%'H1I7'.?/'.""6%;J' !' !' !' !' !' !' !' !'C$*E%<'O"?/'H1'.?/J' !' !' !' !' !' !' !' !'O#"-%'LAEE'C*%$;''H1'&EA.%J' !' !' !' !' !' !' !' !'P%0/&#%*Q&'F,"E%'@*$A-'C*%$;'H1'&EA.%J' ' !' !' !' !' !' !' !' !'PA0/RE0%A%*'!?0/%*-A.6%E'C*%$;''H1'&EA.%J' !' !' !' !' !' !' !' !'PA0/RE0%A%*'1MMS'G<%'C*%$;''H1'&EA.%J' !' !' !' !' !' !' !' !'+AK,#'G<%'C*%$;'H1'&EA.%J' !' !' !' !' !' !' !' !'PA0/RE0%A%*'+A-&%%;'C*%$;'H1'&EA.%J' ' !' !' !' !' !' !' !' !'C*$-'C?;&'5A#,'!&<EEA?0'H1I3'.?/'"*'3M'KJ' !'''' !'''' !'''' !'''' !'''' !'''' !'''' !''''D"*-'C*$-'H3I8'.?/'"*'3M'KJ' !'''' !'''' !'''' !'''' !'''' !'''' !'''' !''''
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Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(,*"*#-&,*"*#-&,*"*#-&,*"*#-&'('('('(,"#./*"&,"#./*"&,"#./*"&,"#./*"&(
((((((((
0*1*"(0*1*"(0*1*"(0*1*"(((((((
2*&&(2*&&(2*&&(2*&&(34#%(34#%(34#%(34#%(5%.*(5%.*(5%.*(5%.*(((((6*"(6*"(6*"(6*"(75%34(75%34(75%34(75%34((
88889999:(:(:(:(((((6*"(6*"(6*"(6*"(75%34(75%34(75%34(75%34((
;%.*(;%.*(;%.*(;%.*(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/((
====9999>(>(>(>(((((6666*"(*"(*"(*"(<**/(<**/(<**/(<**/((
????9999@(@(@(@(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/((
;%.*(;%.*(;%.*(;%.*(((((6*"(6*"(6*"(6*"(((((+#A(+#A(+#A(+#A((
====9999:(:(:(:(((((6*"(6*"(6*"(6*"(((((+#A(+#A(+#A(+#A((
B*+(B$1*"(,*"*#-'(453(C:D>(.E6(.55/*+F( !(((( !(((( !(((( !(((( !(((( !(((( !(((( !((((G4"*++*+(H4*#3I%()"#%(G655%(G$J*(C8D=(.E6(5"(:K(LF( !(((( !(((( !(((( !(((( !(((( !(((( !(((( !((((ME#/*"(;#3()"#%(C:D>(.E6(.55/*+F( !(((( !(((( !(((( !(((( !(((( !(((( !(((( !((((G4"*++*+(H4*#3(G655%(G$J*(C8D=(.E6(5"(:K(LF( !(((( !(((( !(((( !(((( !(((( !(((( !(((( !((((G4"*++*+(H4*#3(C8D=(.E6(5"(:K(LF( !(((( !(((( !(((( !(((( !(((( !(((( !(((( !((((,"*#7(5N(H4*#3(C:D>(.E6(.55/*+(5"(8(6#./*3(5N($%&3#%3F(
!(((( !(((( !(((( !(((( !(((( !(((( !(((( !((((O%&3#%3(;#37*#-((C%5(&EL#"(#++*+F(C:D>(.E6(.55/*+(5"(8(6#./*3F(
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Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(,*"*#-&,*"*#-&,*"*#-&,*"*#-&'('('('(,"#./*"&,"#./*"&,"#./*"&,"#./*"&(
((((((((
0*1*"(0*1*"(0*1*"(0*1*"(((((((
2*&&(2*&&(2*&&(2*&&(34#%(34#%(34#%(34#%(5%.*(5%.*(5%.*(5%.*(((((6*"(6*"(6*"(6*"(75%34(75%34(75%34(75%34((
88889999:(:(:(:(((((6*"(6*"(6*"(6*"(75%34(75%34(75%34(75%34((
;%.*(;%.*(;%.*(;%.*(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/((
====9999>(>(>(>(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/((
????9999@@@@((((((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/((
;%.*(;%.*(;%.*(;%.*(((((6*"(6*"(6*"(6*"(((((+#A(+#A(+#A(+#A((
====9999:(:(:(:(((((6*"(6*"(6*"(6*"(((((+#A(+#A(+#A(+#A((
;34*"B((C75D%3B( !( !( !( !( !( !( !( !(
2*ED7*&2*ED7*&2*ED7*&2*ED7*&(F)*#%&'(G*#&'(2*%3$-&H(F)*#%&'(G*#&'(2*%3$-&H(F)*#%&'(G*#&'(2*%3$-&H(F)*#%&'(G*#&'(2*%3$-&H((((
((((((((
0*1*"(0*1*"(0*1*"(0*1*"((((((
(
2*&2*&2*&2*&&(&(&(&(34#%(34#%(34#%(34#%(5%.*(5%.*(5%.*(5%.*(6*"(6*"(6*"(6*"(75%34((75%34((75%34((75%34((((((
88889999:(:(:(:(((((6*"(6*"(6*"(6*"(((((75%34(75%34(75%34(75%34(((((
;%.*(;%.*(;%.*(;%.*(6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/(((((
====9999>(>(>(>(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/(((((
????9999@(@(@(@(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/(((((
;%.*(;%.*(;%.*(;%.*(6*"(6*"(6*"(6*"(((((+#A(+#A(+#A(+#A(((((
====9999:(:(:(:(((((6*"(6*"(6*"(6*"(((((+#A(+#A(+#A(+#A(((((
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
99
Appendix F Final Visit Questionnaire
FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 1 of 9
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!"#$%&"#$%&"#$%&"#$%&!'#(#)!'#(#)!'#(#)!'#(#)!!!!
!!!!*%+#,!-((.((/.$)!01!234(#5%&!-5)#6#)4*%+#,!-((.((/.$)!01!234(#5%&!-5)#6#)4*%+#,!-((.((/.$)!01!234(#5%&!-5)#6#)4*%+#,!-((.((/.$)!01!234(#5%&!-5)#6#)4!!!!
!!!!234(#5%&!-5)#6#)#.(234(#5%&!-5)#6#)#.(234(#5%&!-5)#6#)#.(234(#5%&!-5)#6#)#.(!%7.!%5)#6#)#.(!83.7.!409!/06.!%$,!#$57.%(.!4097!3.%7)!7%).!%:06.!#)(!7.()#$;!7%).<!83.)3.7!409!,0!)3./!107!+&.%(97.<!807=<!07!)7%$(+07)%)#0$>!!?3.!10&&08#$;!@9.()#0$(!%(=!%:09)!)3.!%/09$)!%$,!#$).$(#)4!01!+34(#5%&!%5)#6#)4!409!3%6.!,0$.!,97#$;!)3#(!()9,4,97#$;!)3#(!()9,4,97#$;!)3#(!()9,4,97#$;!)3#(!()9,4>>>>!!?3.!#$).$(#)4!01!)3.!%5)#6#)4!#(!7.&%).,!)0!)3.!%/09$)!01!.$.7;4!409!9(.!)0!,0!)3.(.!%5)#6#)#.(>!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
234(#5%&!-5)#6#)4!A5%&.234(#5%&!-5)#6#)4!A5%&.234(#5%&!-5)#6#)4!A5%&.234(#5%&!-5)#6#)4!A5%&.!!!!!!!!
!!!! University of Washington Health Promotion Research Center Copyright 2006 Funded in part by the Centers for Disease Control and Prevention Reproduced with permission
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Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!"#$%&"#$%&"#$%&"#$%&!'#(#)!'#(#)!'#(#)!'#(#)!!!!
!!!!*%+#,!-((.((/.$)!01!234(#5%&!-*%+#,!-((.((/.$)!01!234(#5%&!-*%+#,!-((.((/.$)!01!234(#5%&!-*%+#,!-((.((/.$)!01!234(#5%&!-5)#6#)45)#6#)45)#6#)45)#6#)4!!!!
!!!!73%)!#(!4089!8(8%&!+34(#5%&!%5)#6#)4!,89#$:!)3#(!()8,4,89#$:!)3#(!()8,4,89#$:!)3#(!()8,4,89#$:!)3#(!()8,4;!;!;!;!!!!!!!!!!!!!<3.5=!>!%$(?.9!0$!.%53!&#$.<3.5=!>!%$(?.9!0$!.%53!&#$.<3.5=!>!%$(?.9!0$!.%53!&#$.<3.5=!>!%$(?.9!0$!.%53!&#$.!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
University of Washington Health Promotion Research Center Copyright 2006 Funded in part by the Centers for Disease Control and Prevention Reproduced with permission
!!!!!!!!!!!!!!!!
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Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!"#$%&"#$%&"#$%&"#$%&!'#(#)!'#(#)!'#(#)!'#(#)!!!!
!!!!*+,-).,(!/01()#.$$%#21*+,-).,(!/01()#.$$%#21*+,-).,(!/01()#.$$%#21*+,-).,(!/01()#.$$%#21!!!!
!3&1%(1!2%)1!)41!(1512#)+!.6!+.02!17-12#1$81!.6!)41!6.&&.9#$:!;02#$:!)4#(!()0;+;02#$:!)4#(!()0;+;02#$:!)4#(!()0;+;02#$:!)4#(!()0;+<!
!Mild = The symptom does not get in the way of your normal activities. Moderate = The symptom gets in the way of your normal activities, but does not stop them fully. Severe = The symptom stops you from doing your normal activities.
!! *='=>?@A!B"!*AC3@BC*='=>?@A!B"!*AC3@BC*='=>?@A!B"!*AC3@BC*='=>?@A!B"!*AC3@BC!!!!! D.$1D.$1D.$1D.$1!!!!!!!! C#&;C#&;C#&;C#&;!!!!!!!! C.;12%)1C.;12%)1C.;12%)1C.;12%)1!!!!!!!! *15121*15121*15121*15121!!!!!!!!!EF!G1%;%841! !! !! !! !!!HF!"%)#:01! !! !! !! !!!IF!J#%2241%! !! !! !! !!!KF!'.,#)#$:[email protected]#$:!0-! !! !! !! !!!MF!G0$:12! !! !! !! !!!NF!G#880-(! !! !! !! !!!OF!@1$;!).!P18.,1!174%0()1;!Q0#8R&+! !! !! !! !!!SF!3%&-#)%)#[email protected]#$:!.6!41%2)! !! !! !! !!!TF!"11&#$:(!.6!9.22+L%$7#1)+! !! !! !! !!EUF!V.$()#-%)#.$! !! !! !! !!EEF!W%8R!.6!1$12:+! !! !! !! !!EHF!3%#$(!#$!X.#$)(!.2!&#,P(! !! !! !! !!EIF!>1;081;!%P#&#)+!).!8.$81$)2%)1! !! !! !! !!EKF!"&%)0&1$81!.2!:%(!#$!%P;.,1$! !! !! !! !!EMF!D%0(1%! !! !! !! !!ENF!?$;#:1()#.$LG1%2)P02$! !! !! !! !!EOF!Y&..,+L*%;!)4.0:4)(! !! !! !! !!ESF!?$821%(1;!%--1)#)1L40$:12! !! !! !! !!
!!!!
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FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 4 of 9
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!
"#$%&!'#(#)"#$%&!'#(#)"#$%&!'#(#)"#$%&!'#(#)!!!!
!!!!
*+%$,-(!#$!.-/#0%)#1$(*+%$,-(!#$!.-/#0%)#1$(*+%$,-(!#$!.-/#0%)#1$(*+%$,-(!#$!.-/#0%)#1$(!!!!
!
2#$0-!)+-!&%()!3#(#)4!+%(!)+-5-!6--$!%$7!0+%$,-!#$!)+-!85-(05#8)#1$!/59,(4!15!$9)5#)#1$%&!
(988&-:-$)(!719!%5-!)%;#$,<!!! ! ! ! !! ! =1!!!!! >-(!!!!
!
?@!A7-(B!&#()!9$/-5!%885185#%)-!0%)-,157C!!
!
• D$&7!&#()!0+%$,-(E!!?@!)+-5-!#(!$1!0+%$,-4!&-%3-!6&%$;E!
• ?@!719!+%3-!0+%$,-/!7195!:-/#0%)#1$!/1(-!15!@5-F9-$074!5-015/!)+#(!$-G!/1(-!15!@5-F9-$07!%$/!)+-!/%)-!)+-!0+%$,-!()%5)-/E!
• ?@!719!+%3-!()188-/!)%;#$,!%!:-/#0%)#1$4!G5#)-!AHB!@15!)+-!/1(-!%$/!)+-!/%)-!719!()188-/!)+-!:-/#0%)#1$E!
!
=%:-=%:-=%:-=%:-!!!! I1(-I1(-I1(-I1(-!!!! "5-F9-$07"5-F9-$07"5-F9-$07"5-F9-$07!!!!
*+%$,-!15!*+%$,-!15!*+%$,-!15!*+%$,-!15!
2)182)182)182)18!I%)-!I%)-!I%)-!I%)-!!!!
J//K::K77LJ//K::K77LJ//K::K77LJ//K::K77L!!!!
M-%(1$M-%(1$M-%(1$M-%(1$!!!!
N5-(05#8)#1$!/59,(N5-(05#8)#1$!/59,(N5-(05#8)#1$!/59,(N5-(05#8)#1$!/59,(!!!!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
=9)5#)#1$%&!(988&=9)5#)#1$%&!(988&=9)5#)#1$%&!(988&=9)5#)#1$%&!(988&-:-$)(-:-$)(-:-$)(-:-$)(!!!!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
! !! OOOKOOOKOOO!
!
!
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FOR OFFICE USE ONLY Low GI/GDM Risk Study Page 5 of 9
Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!"#$%&"#$%&"#$%&"#$%&!'#(#)!'#(#)!'#(#)!'#(#)!!!!
!!!!"**+!",-./-$01!2/-()#*$$%#,-"**+!",-./-$01!2/-()#*$$%#,-"**+!",-./-$01!2/-()#*$$%#,-"**+!",-./-$01!2/-()#*$$%#,-!!!!
!3$!)4-!5*&&*6#$7!(-0)#*$8!9&-%(-!+-(0,#:-!4*6!*5)-$!*$!%;-,%7-*$!%;-,%7-*$!%;-,%7-*$!%;-,%7-!1*/!4%;-!/(-+!)4-!%<*/$)!(9-0#5#-+!++++/,#$7!)4#(!()/+1/,#$7!)4#(!()/+1/,#$7!)4#(!()/+1/,#$7!)4#(!()/+1=!=!=!=!!>&-%(-!#$+#0%)-!1*/,!%;-,%7-!)*)%&!/(-)*)%&!/(-)*)%&!/(-)*)%&!/(-8!)%?#$7!)4-!9*,)#*$!(#@-!#$)*!%00*/$)=!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!AB%<9&-CAB%<9&-CAB%<9&-CAB%<9&-C!35!1*/!-%)!D!(�-!*5!64*&-!7,%#$!:,-%+!)6#0-!9-,!6--?E!<%,?!F!(�-!9-,!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!6--?!)*!,-9,-(-$)!1*/,!%;-,%7-!)*)%&!#$)%?-=!
"GGHI!JKH!JLGMKNI"GGHI!JKH!JLGMKNI"GGHI!JKH!JLGMKNI"GGHI!JKH!JLGMKNI!!!! J'AOJPA!3KNJQA!HMO3KP!INMHRJ'AOJPA!3KNJQA!HMO3KP!INMHRJ'AOJPA!3KNJQA!HMO3KP!INMHRJ'AOJPA!3KNJQA!HMO3KP!INMHR!!!!
P,%#$(8!S,-%+(8!P,%#$(8!S,-%+(8!P,%#$(8!S,-%+(8!P,%#$(8!S,-%+(8!T-,-%&(T-,-%&(T-,-%&(T-,-%&(8!8!8!8!T,%0?-,(T,%0?-,(T,%0?-,(T,%0?-,(!!!!
!!!!!!!!
K-;-,!K-;-,!K-;-,!K-;-,!!!!!!!
U-((!U-((!U-((!U-((!)4%$!)4%$!)4%$!)4%$!*$0-!*$0-!*$0-!*$0-!!!!!9-,!9-,!9-,!9-,!<*$)4!<*$)4!<*$)4!<*$)4!!!!!
FFFFVVVVW!W!W!W!!!!!9-,!9-,!9-,!9-,!<*$)4!<*$)4!<*$)4!<*$)4!!!!!
G$0-!G$0-!G$0-!G$0-!!!!!9-,!9-,!9-,!9-,!6--?!6--?!6--?!6--?!!!!!
XXXXVVVVY!Y!Y!Y!!!!!9-,!9-,!9-,!9-,!6--?!6--?!6--?!6--?!!!!!
ZZZZVVVV[![![![!!!!!9-,!9-,!9-,!9-,!6--?!6--?!6--?!6--?!!!!!
G$0-!G$0-!G$0-!G$0-!!!!!9-,!9-,!9-,!9-,!!!!!+%1!+%1!+%1!+%1!!!!!
XXXXVVVVW!W!W!W!!!!!9-,!9-,!9-,!9-,!!!!!+%1!+%1!+%1!+%1!!!!!
H-<9()-,\(!]4*&-!P,%#$!S,-%+!!^F!(�-_!!!! !!!! !! !! !! "! !! !! !! !!
!! !
"GGHI!JKH!JLGMKNI"GGHI!JKH!JLGMKNI"GGHI!JKH!JLGMKNI"GGHI!JKH!JLGMKNI!!!! J'AOJPA!3KNJQA!HMO3KP!INMHRJ'AOJPA!3KNJQA!HMO3KP!INMHRJ'AOJPA!3KNJQA!HMO3KP!INMHRJ'AOJPA!3KNJQA!HMO3KP!INMHR!!!!
>*)%)*-(>*)%)*-(>*)%)*-(>*)%)*-(!!!!
!!!!!!!!
K-;-,!K-;-,!K-;-,!K-;-,!!!!!!!!!!
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Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(,*"*#-&,*"*#-&,*"*#-&,*"*#-&'('('('(,"#./*"&,"#./*"&,"#./*"&,"#./*"&(
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Version 2 29-Jan-10
!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(!"#$%&'()"*#+&'(,*"*#-&,*"*#-&,*"*#-&,*"*#-&'('('('(,"#./*"&,"#./*"&,"#./*"&,"#./*"&(
((((((((
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;%.*(;%.*(;%.*(;%.*(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/((
====9999>(>(>(>(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/((
????9999@(@(@(@(((((6*"(6*"(6*"(6*"(<**/(<**/(<**/(<**/((
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====9999::::((((((((6*"(6*"(6*"(6*"(((((+#A(+#A(+#A(+#A((
;34*"B((C75D%3B( !( !( !( !( !( !( !( !(
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((
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Subject Initials !!! Subject ID No. !!!
Version 2 29-Jan-10
!!!!"#$%&!'#(#)"#$%&!'#(#)"#$%&!'#(#)"#$%&!'#(#)!!!!
!*#+)!,--+.)%/#&#)0!12+()#3$$%#4+*#+)!,--+.)%/#&#)0!12+()#3$$%#4+*#+)!,--+.)%/#&#)0!12+()#3$$%#4+*#+)!,--+.)%/#&#)0!12+()#3$$%#4+!!!!
!!!!5&+%(+!-36.%4+!0324!()270!7#+)!)3!0324!4+82&%4!7#+)9!
!!!
:36.%4+7!)3!0324!4+82&%4!7#+);:36.%4+7!)3!0324!4+82&%4!7#+);:36.%4+7!)3!0324!4+82&%4!7#+);:36.%4+7!)3!0324!4+82&%4!7#+);!!!!! '+40!'+40!'+40!'+40!
<%(0<%(0<%(0<%(0!!!!!!!!<%(0!<%(0!<%(0!<%(0!!!!!
=+#)>+4!=+#)>+4!=+#)>+4!=+#)>+4!<%(0!$34!<%(0!$34!<%(0!$34!<%(0!$34!?%47!?%47!?%47!?%47!!!!!
?%47?%47?%47?%47!!!!!!!!'+40!'+40!'+40!'+40!?%47?%47?%47?%47!!!!!!!!
=3!=3!=3!=3!,$(@+4!,$(@+4!,$(@+4!,$(@+4!!!!!
?3@!>%47!@%(!#)!)3!A3&&3@!0324!()270!7#+)B!! !! !! !! !! !! !!
!!
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D+))+4!D+))+4!D+))+4!D+))+4!!!!!=+#)>+4!=+#)>+4!=+#)>+4!=+#)>+4!D+))+4!$34D+))+4!$34D+))+4!$34D+))+4!$34!!!!E34(+!E34(+!E34(+!E34(+!!!!!
E34(+!E34(+!E34(+!E34(+!!!!! =3!=3!=3!=3!,$(@+4!,$(@+4!,$(@+4!,$(@+4!!!!!
F%()+! !! !! !! !!<%(+!3A!-33G#$8H.4+.%4%)#3$! !! !! !! !!<%(+!3A!.24->%(#$8! !! !! !! !!54#-+! !! !! !! !!
!!
:36.%4+7!)3!0324!4+82&%4!7#+)C!4%)+!0324!()270!7#+)!#$!)+46(!3A;:36.%4+7!)3!0324!4+82&%4!7#+)C!4%)+!0324!()270!7#+)!#$!)+46(!3A;:36.%4+7!)3!0324!4+82&%4!7#+)C!4%)+!0324!()270!7#+)!#$!)+46(!3A;:36.%4+7!)3!0324!4+82&%4!7#+)C!4%)+!0324!()270!7#+)!#$!)+46(!3A;!!
I+((!I+((!I+((!I+((!!!!!F#6+!F#6+!F#6+!F#6+!!!!!
=+#)>+4!=+#)>+4!=+#)>+4!=+#)>+4!J34+!$34!J34+!$34!J34+!$34!J34+!$34!I+((I+((I+((I+((!!!!F#6+!F#6+!F#6+!F#6+!!!!!
J34+!J34+!J34+!J34+!!!!!F#6+!F#6+!F#6+!F#6+!!!!!
=3!=3!=3!=3!,$(@+4!,$(@+4!,$(@+4!,$(@+4!!!!!
:33G#$8H.4+.%4%)#3$!)#6+! !! !! !! !!
108
Appendix G Participants’ Significant Medical History
TABLE G.1 (Continued) Maternal baseline significant medical history, compared by intervention group1
Low (n = 56)
M/H (n = 62)
Cardiovascular Heart murmur 3 3 History of pregnancy-induced hypertension 3 3 Hypercholesterolemia 1 0 Hypertension 1 1 TOTAL 8 7 Dermatological History of hives 0 1 Endocrine GDM in previous pregnancy 4 2 Hyperthyroidism 1 0 Hypothyroidism 5 7 Increased proteinuria 1 0 Ovarian cyst(s) 0 3 PCOS 1 4 Thyroidectomy 0 1 Thyroid nodules 0 1 TOTAL 12 182 Gastrointestinal Chronic constipation 0 1 Gastric bypass 0 1 GERD 1 0 History of hemorrhoids 1 0 Peptic ulcer disease 1 0 Previous bowel obstruction 1 1 TOTAL 4 3 Genitourinary Bartholian’s cyst 1 0 Bicornut uterus 0 1 Blocked fallopian tubes 0 1
(Continued)
109
TABLE G.1 (Continued)
Maternal baseline significant medical history, compared by intervention group1
Low (n = 56)
M/H (n = 62)
Genitourinary Endometriosis 0 1 Fibroids 3 5 Frequent yeast infections 1 0 Genital herpes 1 3 History of bacterial vaginosis 0 1 History of cerclage 1 1 HPV 1 4 Previous abnormal pap smear 2 4 Previous cervical cancer 0 1 Previous chlamydia 2 0 Previous rectal fistula 1 0 Previous STI 0 1 Recurrent UTI 8 5 Trichomoniasis 0 1 Uterine wall polyp 0 1 TOTAL 212 302 Hematological Anemia 0 2 B12 deficiency 1 0 Thalassemia 1 0 Thalassemia carrier 0 1 Thrombocytopenia (rifampin induced) 1 0 TOTAL 3 32 Hepatic Cholestasis in previous pregnancy 1 0 Chronic hepatitis B 1 0 Gilbert’s syndrome 0 1 Hepatitis A 0 1 Hepatitis A as a child 0 1 Hepatitis as a child 1 0 Hepatitis B carrier 2 0 TOTAL 5 32 Musculoskeletal Congenital spinal fusion T12-L2 1 0 Hip surgery 0 1
(Continued)
110
TABLE G.1 (Continued)
Maternal baseline significant medical history, compared by intervention group1
Low (n = 56)
M/H (n = 62)
Musculoskeletal History of back pain 1 1 Knee surgery 1 0 Previous collar bone fracture – surgery 1 0 Previous tailbone fracture 0 2 Previous vertebrae fracture 0 1 Spina bifida occulta 1 0 TOTAL 5 52 Neurological Chiara malformation 0 1 Migraines 0 3 Numbness and nerve pain in legs 0 1 Previous blood clot evacuation – head trauma 0 1 Pseudocholinesterase deficiency 1 0 TOTAL 1 6 Renal Congenital single kidney 1 0 History of kidney stones 1 0 IgA nephropathy 1 0 Previous kidney infection 0 1 Previous kidney infection during pregnancy 0 1 TOTAL 3 2 Respiratory Asthma 5
4
Childhood asthma 1 0 History of tuberculosis 0 1 Previous spontaneous pneumothorax 0 1 TOTAL 6 6
1 Low, low-glycemic index diet group; M/H, medium/high-glycemic index diet group. 2 Individual participants counted under more than one condition in this category.
111
Appendix H Participants’ Medication/Dietary Supplement Intake
TABLE H.1 (Continued)
Maternal baseline medications and dietary supplements, compared by intervention group1
Medications and Dietary Supplements Low (n = 47)
M/H (n = 47)
Anti-hypertensive Trandate (labetalol hydrochloride) 1 0 Anti-thyroid Propylthiouracil (PTU) 1 0 Anti-nausea Diclectin 3 3 Anti-reflux Nexium (exomeprazole; proton pump inhibitor) 1 0 Zantac (ranitidine; H2-blocker) 0 1 TOTAL 1 1 Bronchodilators Bricanyl Turbuhaler (terbutaline sulfate; β2-agonist) 1 0 Flovent HFA Aerosol (fluticasone propionate; corticosteroid) 1 0 Symbicort (budesonide and formoterol; corticosteroid and β2-agonist respectively) 1 0
Ventolin (salbutamol aerosol; β2-agonist) 1 0 TOTAL 4 0 Thyroid hormone replacement Eltroxin aka Synthroid (levothyroxine sodium) 4 6 Adult multivitamins Jamieson Regular Vitamin Multivitamin 0 1 Multivitamin 1 0 Swiss NaturalsTM Adult Multi Vitamin and Mineral Fruit Flavoured Chewable Tablet 0 1
TOTAL 1 2 Prenatal vitamins Centrum Materna Prenatal and Postpartum Vitamin and Mineral Supplement 25 20
Exact Prenatal and Post-Partum Vitamin and Mineral Supplement 0 1
Garden of Life Vitamin Code Raw PrenatalTM 1 0 (Continued)
112
1 Low, low-glycemic index diet group; M/H, medium/high-glycemic index diet group.
TABLE H.1 (Continued) Maternal baseline medications and dietary supplements, compared by intervention group1
Medications and Supplements Low (n = 47)
M/H (n = 47)
Prenatal vitamins Health Balance Prenatal Multivitamins 0 3 Jamieson Prenatal Natural Source Vitamin 5 1 Life Brand Spectrum Prenatal/Postpartum Vitamin and Mineral 2 4
Loblaws Prenatal Vitamin 0 1 Melaleuca Vitality Multivitamin & MineralTM – Prenatal 0 1 New Chapter Multi for TwoTM aka Perfect Prenatal Whole-Food Multi-Vitamin 1 0
Platinum Naturals EasyMulti Prenatal enriched with DHA 0 1 PregVit® 5 5 PregVit folic 5 0 2 Prenatal Vitamin 1 0 Progressive Multivitamins Prenatal Formula 1 0 Quest Prenatal Vitamin 0 1 Rexall Maternal Vitamin 0 1 Sisu Supreme Multi Expecting Prenatal Vitamin 2 1 Thorne Basic Prenatal 1 1 TOTAL 44 43 Other vitamins/fatty acids of interest Folic acid 9 4 Omega-3 fatty acids 9 10 Vitamin D 13 9