Preventing Excessive Weight Gain and Maternal and Infant Fat Accretion by Increasing Fiber Intake and Changing the Maternal Microbiome During Pregnancy
Phase: NA
Conditions: Gestational Weight Gain, Maternal Fat Accretion, Infant Fat Accretion
Sponsor: University of Kansas Medical Center

Cover Page for Protocol 
 
 
Official study title: 
Preventing excessive weight gain and maternal and infant fat 
accretion by increasing fiber intake and changing the maternal 
microbiome during pregnancy 
NCT number: 
NCT04868110 
Document date: 
1/12/2022 
 
 
 
 
 
 
 
 

1 
 
 
Preventing excessive weight gain and maternal and infant fat accretion by 
increasing fiber intake and changing the maternal microbiome during pregnancy 
Principle Investigator: Dr. Holly Hull 
 
University of Kansas Medical Center 
Department of Dietetics and Nutrition 
3901 Rainbow Blvd, Kansas City, KS, 66160 
Phone: 913-588-5358 
 
KUMC IRB # STUDY00145397 
Protocol Version 11 
SPECIFIC AIMS 
Excessive gestational weight gain (GWG) is directly linked to greater fat accrual and retention1 shifting 83% of 
normal weight women into an overweight or obese BMI category at 1 yr post-pregnancy2. Excessive GWG, 
experienced by 56% of U.S. pregnant women3,4, increases offspring fat accrual and risk for overweight or 
obesity development, a characteristic of 31.8% of US children5. Excess adiposity levels drive disease 
development6, leading to the prediction of a rapid generational decline in life expectancy7 and a surge in 
medical care costs (~$150 billion/yr)8.  
 
During normal pregnancy, maternal metabolism shifts to support fetal growth9 likening to the development 
of the metabolic syndrome (MetS)10-13 including increases in: fat mass10,11, blood lipids12, coagulation13, 
inflammation, and insulin resistance12. No intervention has been design considering the MetS state of 
pregnancy. Further, prior interventions to prevent excessive GWG were designed based on successful non-
pregnant adult weight loss studies14, however, incremental weight gain is critical for fetal development. Meta-
analyses reported a minimal effect of prior interventions15-24 with limited maternal or infant health benefit17,22-29. 
A critical gap is testing an intervention designed to address the unique MetS state of pregnancy. To address 
this gap, we will test the effect of a high fiber (HFib) diet (>30g/day), designed to address the unique MetS 
state of pregnancy, to reduce GWG, fat accretion, and improve maternal diet quality.  
 
The benefits of a HFib diet are supported extensively in the literature. Fiber protects against increasing 
body weight30-33, promotes fat loss34-39, increases satiety40, and improves the metabolic and inflammatory 
profiles30,41-47. Evidence that a HFib diet can reduce body weight and fat mass independent of a reduction in 
energy intake was highlighted in a recent meta-analysis48 and a RCT in adults with MetS49,50. The effect is 
hypothesized in part to be mediated through the powerful prebiotic effect of fiber that favorably shifts the gut 
microbiota leading to reduced weight gain48, inflammation51, improved metabolic profile51, and prevention of fat 
accrual34-37,51. Our working hypothesis is that consuming a HFib diet (≥30 g/day) will reduce GWG and fat 
accretion by diluting energy density, reducing hunger thereby reducing energy intake, and changing the gut 
bacteria composition. Our pilot data (n=20) found a 12 wk HFib pregnancy intervention reduced Firmicutes and 
increased Bacteroidetes, which was associated with reduced weight gain and fat accretion52. Current fiber 
intake of pregnant women is 17.3 g/day53, well below the recommended intake (28 g/day54), and triggering fiber 
to be classified as a nutrient of concern55. Thus, increasing fiber intake has high potential for impact. However, 
RCTs in pregnant women are lacking to understand if this is an effective intervention strategy. 
      The project objective is to block randomize n=56 pregnant women to either a HFib diet or usual care. 
Eighteen weekly lessons will educate women on eating a HFib diet. To ensure fiber intake is met, daily snacks 
(10-12 g/day) will be provided. Weight gain, fat accretion, and stool microbiota will be measured twice during 
pregnancy (pre- and post-intervention) and assessed at 2 months, 6 months, and 12 months postpartum. 
Infant body composition will be measured at 2 weeks,2 months, 6 months, and 12 months. The aims are:   
 
Primary Aim 1: Assess the between group difference in maternal weight gain and fat accretion. H1: The 
HFib group will gain less weight and accrue less fat mass when compared to the control group.  
 
Primary Aim 2: Compare fiber intake and dietary quality between groups. H2: The HFib group will 
consume more fiber and have a higher diet quality during pregnancy and postpartum. 
 

2 
 
 
Secondary Aim 1: Characterize between group differences in the gut microbiome composition and 
diversity (alpha and beta). H1: The HFib group will have a greater change in gut microbiota composition, 
taxonomy, and diversity that will be detected during pregnancy and postpartum.  
 
Secondary Aim 2: Determine if there are between group differences in early infant fat accrual. H2: 
Offspring born to women in the HFib group will have lower fat accrual.  
 
Secondary Aim 3: Determine if there are differences in markers of metabolic, inflammatory, and brain health 
during pregnancy and postpartum. H3: The HFib group will be characterized by more favorable levels of 
metabolic, inflammatory, and brain health markers at all time points measured.  
 
Impact: Prior intervention design has not addressed the MetS state of normal pregnancy. Dietary fiber 
counteracts the components of the MetS. Increasing fiber intake may positively impact the drivers of poor 
maternal outcomes that prior studies failed to show. Our study has potential to succeed where others have 
failed because we designed treatment to target the metabolic shifts that occur during normal pregnancy. This 
proposal is innovative because we are measuring the intervention impact on fat accrual and the microbiota in 
mother and early offspring fat accrual. This proposal would fill a large research gap.  
 
RESEARCH STRATEGY 
A) SIGNIFICANCE  
A1) Why maternal excessive weight gain is an important problem: Overall, 55% of women gain excessive 
gestational weight3,4 though disparities exist within BMI groups; 62% of women with a high normal BMI (22-
24.9 kg/m2) and ~70% of overweight and obese women gain excessively3,4. Maternal overweight and 
excessive gestational weight gain (GWG) are associated with poor offspring outcomes including increased 
infant fat mass (FM)3,56 and increased FM in childhood57,58 and adulthood59. Research shows a strong 
relationship between maternal excessive GWG and offspring obesity development60,61, diabetes, and 
cardiovascular disease62,63. Maternal conditions related to excessive GWG include hypertension64,65 and 
gestational diabetes (GDM)66,67. Many women develop overweight or obesity during the childbearing years68. 
Women who gain excessively are more likely to retain 10 to 20 lbs at 12 months postpartum69. Effective 
interventions to prevent excessive GWG are desperately needed. 
 
Ideally, women would enter pregnancy at an appropriate body weight. However pre-conception interventions 
have yet to be tested, proven viable, or successful. Many primary care physicians do not counsel patients on 
weight loss, diet, and exercise due to inadequate resources and feelings of ineffectiveness70. This highlights 
the importance of interventions during pregnancy. Pregnancy is an important time period that “programs” 
disorders and a time when many pregnant women are more likely to adopt healthy behaviors for the well-being 
of their baby14. Several interventions have been completed with varying success and are discussed below.  
 
A2) Intervention lack of success: Four meta-analyses16,18,20,24 and five systematic reviews15,22-25 show limited 
success in published interventions. For interventions including diet and physical activity (PA), three71-73 found 
improvement in rate of adherence to IOM guidelines while ten74-83 did not see improvements in adherence. 
Studies compared differences by BMI groups and found effectiveness in normal weight but not 
overweight/obese participants84,85. Two studies in obese pregnant women provided counseling with a 
Registered Dietitian at one session86 or 10 sessions87 focusing on diet and found improved dietary quality87  
and reduced GWG86,87. The greatest success (80% gained <10.6 kg) was found in a study of overweight/obese 
women using personalization of diet and PA (walking program using pedometers) and consistent self-
monitoring72. This study was especially impressive as the intervention started at 16-20 wks and the entire 
cohort had already gained excessively.   
 
A3) Lessons from prior studies: Failed studies cite poor outcomes were due to PA not being desirable during 
pregnancy79, needing one provider delivering counseling to ensure consistent messages74, the intervention 
was not intensive enough75,84,85, too infrequent of contact75,79,84, the need to emphasize caloric restriction84, the 
intervention started too late78 or was too short79, the need to involve significant others76, and poor 
adherence75,81. Successful studies were intensive, set calorie and PA goals and used self-monitoring20. 

3 
 
 
Interventions predominantly based on diet only (e.g., a single goal (SG)) versus interventions changing multiple 
behaviors (e.g., multiple goal (MG)) were suggested to be the most effective20. This is hypothesized to be 
because the MG approach requires focus on several messages resulting in the intensity of the intervention 
being diluted, because there is better adherence in SG diet only interventions with only one behavior to focus 
on changing, and specific components in the SG diet interventions might have benefits not explored20.  
 
A4) Benefits of dietary fiber: One identified nutrient thought to exert this beneficial effect is dietary fiber. Data 
suggest that dietary fiber can aid in weight loss and maintenance88-90, promote satiety and reduce hunger40, 
reduce inflammation91, and exert clinical benefits by controlling glucose, insulin levels and lipid levels49,92. 
NHANES 2005-2010 data found in adult males and females the average intake of fiber is only 16.8 g/day93 
which is well below the recommended intake of 25 g/day for females and 38 g/day for males54. Studies report a 
high fiber diet in non-pregnant adults was rated as acceptable to maintain for six months40. The maternal 
physiologic state changes during the course of normal pregnancy to support the growth of the fetus9. As 
pregnancy progresses the metabolic adaptations occurring represent a transient excursion into a metabolic 
syndrome (MetS) like state, one that is analogous to the worsening of the metabolic profile seen during 
development of MetS. Dietary fiber exerts protective benefits on several components of metabolic syndrome94 
that could be beneficial during pregnancy.   
 
A5) Success of a SG intervention: In a large RCT funded by the NIH (R01 HL094575)50 in non-pregnant 
adults with MetS, the effectiveness of two interventions were compared for weight loss and metabolic changes; 
MG vs. SG. Both groups met face-to-face (FTF) in groups for 12 sessions over three months. The MG followed 
the American Heart Association dietary guidelines and the SG focused all lessons on achieving dietary fiber 
(no calorie or PA goals) intake ≥30 g/day. At 12 months, the MG group lost -2.7 kg, while the SG group lost -
2.1 kg and both groups saw improvements in dietary quality, insulin resistance, lipids, inflammation, glucose 
levels and blood pressure. Both groups decreased kcal/d, however the MG group had a greater decrease (-
464 versus -200 kcal at 12 months). Olendski49 tested the effectiveness two simple messages in a three group 
design: 1) calorie restriction + high fiber, 2) calorie restriction + low saturated fat and 3) MG intervention (a 
combination of restricted kcals, high fiber, and low fat). The intervention lasted 3 months with biweekly FTF 
individual meetings with a Dietitian. At six months, no between group difference was found for body weight lost; 
-7 lbs for MG, -9.1 lbs for fiber and, -10.2 lbs for saturated fat group. All groups improved dietary quality and 
cardiometabolic parameters. At six months, 83% of the fiber group were confident they could stick to their diet, 
whereas only 60% and 33% were confident in the saturated fat and MG groups, respectively (p=0.008). Taken 
together, no clear between group differences were found between a SG dietary fiber intervention and a MG 
intervention. This suggests in non-pregnant adults, both intervention types were effective. 
 
 A6) Promising new intervention approach: Encouraging appropriate GWG by improving dietary quality and 
encouraging PA are modifiable behaviors but the best practices to achieve these are unknown95.  FTF 
individual counseling is effective but expensive and difficult to scale up for dissemination96. Group based phone 
counseling (GBPC) is novel and efficiently uses both the time and resources of the providers and participants. 
Pregnant women report9 lack of time, resources and need for childcare as barriers to participating in lifestyle 
interventions. Participants “meet” as a group weekly by phone with a Registered Dietitian. GBPC interventions 
are effective for weight management in non-pregnant populations97,98 with studies finding equivalent weight 
loss for FTF versus GBPC99-101. GBPC allows participants to interact with each other in real time and supports 
participant desired anonymity99. No studies have used GBPC to encourage appropriate GWG in pregnant 
women or used a novel intervention to pregnancy, a SG dietary fiber intervention.   
 
B) Innovation: The proposed research is innovative because of the research team, the research design and 
idea, and the techniques used. Our team is using existing science to deliver interventions to high risk and high 
need patients. We are filling a research and clinical gap by packaging information that is already available into 
an effective intervention that in future studies can be embedded into routine clinical care. Using a SG 
intervention for weight loss and to improve metabolic health has been proven successful in non-pregnant 
adults but remains un-tested in pregnancy50. In pregnancy, the goal is not to induce weight loss, but blunt the 
rate of excessive gain. Promotion and adherence to a healthy lifestyle is of the utmost importance during 
pregnancy because we can positively impact the health of the mother and her baby.  

4 
 
 
 
C) Approach/Preliminary Studies 
C1) Preliminary study: multiple goal behavioral lifestyle intervention to reduce excessive GWG: Drs. 
Hull and Goetz were co-PIs funded on a pilot study to test the effectiveness of a multiple goal behavioral 
lifestyle intervention (vs. UC) to prevent excessive GWG using GBPC. The primary outcome was the 
proportion of women gaining excessively based on 2009 IOM recommendations69. The intervention ran from 
18 to 36 weeks and the intervention group met weekly by phone with a Dietitian for 60 minutes. All participants 
reported body weight weekly via text message. The curriculum included 18 lessons. Data are presented in 
Table 1. Fourteen women were enrolled into the multiple goal group and 12 women were enrolled into the UC 
group. We lost 3 subjects in the control group and lost zero subjects in the intervention. In the intervention 
group, 29% gained excessively while 78% of the UC group gained excessively. Additionally, the UC group 
gained more weight (p=0.010). Structured interviews were done in a sample of those completing the study 
(n=9). When asked, “What changes did you make due to the intervention?”, 33% responded, “consumed more 
fruits/vegetables” and “controlled portions” while 22% said “consumed less sugar”. When asked “What they 
liked about the program?”, 44% replied “monitoring body weight”. When asked “What they would recommend 
for future interventions?”, responses included, keep a variety of topics and set one goal for the entire program. 
The data are promising.   
  Table 1: Preliminary results from pilot study to prevent excessive GWG  
 
Pre-pregnancy BMI (kg/m2) 
GWG (kg) 
% gaining excessively 
Usual Care (n=9) 
29.3 ± 4.8 
18.4 ± 7.3 
78% 
Intervention (n=14) 
28.4 ± 8.6 
11.8 ± 4.0* 
29% 
Means ± SD 
*Significantly different from control group (p=0.010) 
 
C2) Population to be studied: Women between 9 to 19 weeks pregnant with a BMI 18.5 – 45.0 kg/m2 and 
between the ages of 18-45 years will be recruited from the University of Kansas Medical Center (KUMC) OB 
clinics. We will enroll all race/ethnic groups. Participant’s routine OB care will be managed by their primary 
Obstetrician. Any interventions, laboratory or other evaluations, and decisions regarding delivery will be made 
by the primary Obstetrician. Groups of 6-10 subjects will be block randomized to control or the intervention 
group to ensure adequate size for optimal group dynamics. The intervention will start at 12-20 wks and last 18 
weeks, ensuring intervention completion by 38 weeks in pregnancy. We will screen women to determine the 
current dietary fiber intake. If they are consuming 25 g/day of fiber or more, they will be excluded from the 
study. Women who do not have internet and phone access will be excluded from the study. Participants must 
be willing to consume provided snacks. Participants will also be excluded if they have history of gestational 
diabetes (GDM), diabetes, pre-eclampsia, hypertension,  heart disease, hypothyroidism, or other metabolic 
abnormalities, current hyperemesis gravidarum, eating disorder, smoking, or are pregnant with multiples. 
Women that develop any of these medical conditions during pregnancy will be accounted for in the final 
analysis. Deviations from inclusion criteria will be at the discretion of the PI. 
 
C3) Recruitment: We have access to the electronic clinic schedule, therefore we have the exact date and time 
of the recruit’s OB visit. We have worked directly with physicians and staff providing an in service at meetings 
to ensure a smooth recruiting process so that we do not impede clinic flow. Annually, 1800 women are 
managed in the OB clinics at KUMC. Additionally, we will recruit using an electronic flyer via social media. 
Individuals who have agreed to future contact from previous studies will also be approached if eligible via email 
or phone.  
   
C4) Curriculum development: The interventions were designed based on the theoretical framework of the 
social cognitive theory (SCT)102. Bandura proposed that people attain and then maintain patterns of behavior 
and that behavior is based on the interaction of personal, environmental and behavioral factors. The 
consistency of behavior provides the foundation for development of our intervention strategy. Within the SCT 
there are several constructs that are directly related to weight control programs103,104. Table 2 provides 
examples of the constructs and behavioral strategies and examples of how these will be used in the study.   
 
Table 2. Behavioral strategies used within the study 
Behavioral Strategy 
Examples of how used within the study 

5 
 
 
Behavior Shaping 
Participants are taught to modify their fiber intake according to recommendations. 
Goal Setting 
The Dietitian teaches sensible goal setting and assists participants to set personalized goals (e.g., 
fiber intake) to achieve appropriate GWG. 
Self-Monitoring 
Participants will report their body weight and fiber intake weekly & be taught self-monitoring. 
Feedback & Reinforcement 
Participants receive weekly feedback that includes reinforcement & strategies to overcome barriers. 
Social/Peer Support 
Group sessions provide peer support and interaction to model and teach behaviors. 
Stimulus Control 
Lessons provide coping & behavioral strategies to decrease cues for undesirable behaviors and to 
increase those for healthy behaviors. 
Relapse Prevention 
The Dietitian facilitates the development of a contingency plan to address high risk situations based 
on Marlatt and Gordon’s relapse prevention model 105 
 
C5) General intervention description: Group video conferencing will be used to deliver the intervention. The 
weekly 60-minute lessons for the Hfib group provide information on how to obtain ≥30 g/day of fiber (details 
below).  
 
C5a) General layout of the group sessions: The session will start with a review of the prior week’s goals, with 
support and encouragement from group members and the Dietitian (5-10 minutes). A group discussion will 
occur with group members relating and/or providing personal insight and support. The Dietitian will lead 
discussion and engage the women by asking opened ended questions, providing encouragement and 
troubleshooting as needed. Each week there will be a structured lesson with an assignment to be completed 
after the session (20-30 minutes). The last 10-20 minutes of the session will be devoted to goal setting, 
discussion, questions, and wrap-up. For best group dynamics on video, 5-10 women are optimal.  
 
C5b) Video System: Group sessions will be conducted using Zoom video conferencing system (Zoom Video 
Communications, Inc., San Jose, CA). Participants will be given a link with a password and instructed to call in 
5 minutes prior to group start. A log will be generated to track attendance. All conference calls will be recorded 
for quality assurance and to serve as additional training for the group leader.  
 
C5c) Hfib intervention details: The 60-minute weekly group sessions (18 total) will focus on eating a high fiber 
diet both during and after pregnancy. The dietary reference intake (DRI) for fiber during pregnancy is 28 g/day 
and 25 g/day for females of reproductive age54. The goal is for participants to gain within 2009 IOM 
recommendations69. To achieve this, all participants will be encouraged to consume ≥30 g/day of fiber. The 
Hfib intervention will receive a fiber goal (no calorie goal). This is intentional because we want to remove the 
driver of what is known to induce weight loss (calorie goal) and determine if a fiber goal without a calorie goal 
can blunt excess GWG. Because the goal is to keep the Hfib intervention simple, we are focusing on the one 
behavior with the best evidence to control weight gain; consuming ≥30 g/day fiber. Discussion will encourage 
problem solving, provide educational information, and social engagement during the video calls. Participants 
will be taught to track their daily total fiber intake in REDCap. Participants will be encouraged to follow a 
balanced diet emphasizing fruits and vegetables, whole grains, low-fat dairy and lean protein. General PA 
recommendations during pregnancy will be mentioned but no focus or reinforcement of this behavior will take 
place . All participants will be given a body weight scale and report body weight weekly. Participants will 
receive a notebook containing handouts and assignments specific to each weekly topic. Dietitians will facilitate 
the lessons and lead discussion.  
 
In order to improve adherence to a high fiber diet, all participants will receive daily high fiber snacks (see table 
3). In pregnant women, the average daily fiber intake is 15 g/day. Therefore, by providing two snacks, we will 
increase the fiber intake to close to the goal of ≥30 g/day fiber. The box will include multiple flavors of Kind 
bars, chickpeas and snap peas. Additionally, they will receive whole grain cereals including whole wheat 
puffins and wheat Chex.  All foods are shelf stable from 12 months to 18 months. The snacks will be pre-
portioned for one serving with recommendations to consume 2 snacks per day. Lessons will focus on how to 
increase fiber intake with education on foods that contain fiber, high fiber recipes, and how to make over 
current recipes to contain more fiber. Their weekly progress towards the fiber goal will be monitored closely 
through REDCap fiber tracker. If they are not meeting the daily fiber goal, a dietitian will call the participant to 
discuss barriers, troubleshoot any challenges associated with diet adherence and develop a plan to increase 
fiber intake.   

6 
 
 
 
Table 3. A list of high fiber snacks for one week. 
 
Day 1 
Day 2 
Day 3 
Day 4 
Day 5 
Day 6 
Day 7 
Snack 1 
Kind bar 
Snap peas 
Kind bar 
Chex  
Kind bar 
Snap peas 
Chex  
Snack 2 
Puffins 
Chex  
Chickpeas 
Snap peas 
Puffins 
Kind bar 
Chickpeas 
Fiber/day (g) 
12 
10 
12 
10 
12 
12 
10 
 
 
C5d) Monitoring & Compliance: Participants will submit a daily log electronically through REDCap (Research 
Electronic Data Capture) to report number of servings of high fiber food groups (e.g., fruits, vegetables, whole 
grains, legumes, nuts and seeds). Participants will be given a body weight scale and asked to report their body 
weight weekly.Research staff will review compliance weekly and contact participants who need support and 
provide accountability. Participants will be flagged for follow-up if they are not attending calls, not completing 
daily REDCap logs, or if they are consistently below their fiber goal as assessed by biweekly 24-hour recalls. 
Participants will also be contacted if they report a body weight change ± 5 pounds over two weeks. 
 
C5e) Usual care group: Those randomized to the UC group will be cared for by their obstetrician using 
standard treatment.  Standard treatment consists of attending regularly scheduled visits where patients are 
weighed and evaluated. The standard visit schedule is once monthly until 32 wks gestation, bi-weekly for 32-37 
wks gestation, weekly until delivery, and at 6 wks post-partum. At the first prenatal visit, they will receive the 
standard nutrition and physical activity counseling along with literature outlining recommendations provided by 
the obstetrics team. Women in the UC group will report body weight weekly via REDCap. In the multiple goal 
pilot study, the control group reported body weight weekly. This minimal contact did not impact the rate of 
excessive GWG, as the rate of excessive GWG in the control group was 78%. 
 
C5f) Adherence: Adherence will be assessed based on participants meeting their prescribed fiber goal 
(≥30g/day average) as well as by call attendance ≥75% (14 or more calls attended). Starting in week two of the 
intervention, one 24-hour dietary recall will be collected every two weeks (9 recalls total) to determine fiber 
intake. Participants will be considered adherent if their number of days meeting fiber goal/number of days 
reported is ≥75%. 
 
C6) Standard training and quality assurance: Dr. Goetz has considerable experience (over 10 years) 
delivering weight management interventions and as a trainer (R01 DK076063, HL11842, DK094833). Dr. 
Goetz will provide initial and ongoing training for the Dietitians who will lead the group sessions. Dr. Goetz will 
randomly select 20% of the calls and using the checklist, make sure >80% of the content was covered. If >80% 
of the content was not covered, the Dietitian will be re-trained focusing on deficient areas.   
 
C7) Maternal & infant assessments: Listed in Table 4 is an outline of study visits and procedures. In C7a-i, 
details are provided regarding maternal & infant outcomes that will be collected.  
 
Table 4. An outline of study visits and procedures.  
 
During Pregnancy 
Postpartum 
Study procedure 
Baseline: 
12-20wks 
End of Intervention: 
30-38wks 
2 
weeks 
2 
months 
6 
months 
12 
months 
Questionnaires 
• 
• 
• 
• 
• 
• 
Maternal anthropometrics 
• 
• 
• 
• 
• 
• 
Maternal body composition 
(BodPod, BIA) 
• 
• 
 
• 
• 
• 
Maternal vitals  
• 
• 
• 
• 
• 
• 
Maternal pregnancy test 
 
 
• 
• 
• 
• 
Maternal DXA scan 
 
 
 
• 
• 
• 
Maternal diet recalls 
• 
• 
• 
• 
• 
• 
Maternal veggie meter 
• 
• 
 
• 
• 
• 
Maternal olfactory testing 
• 
• 
 
• 
 
• 
Maternal urine 
• 
• 
• 
• 
• 
• 

7 
 
 
Maternal cognitive testing 
• 
• 
 
• 
• 
• 
Maternal stool 
• 
• 
 
• 
• 
• 
Maternal blood draw 
• 
• 
 
• 
• 
• 
Maternal actigraphy 
• 
• 
 
• 
• 
• 
Infant anthropometrics 
 
 
• 
• 
• 
• 
Infant skin folds 
 
 
• 
• 
• 
• 
Infant body composition 
(PeaPod) 
 
 
• 
• 
• 
 
Infant stool 
 
 
• 
• 
• 
• 
Infant DXA scan 
 
 
• 
 
 
• 
Infant diet recalls 
 
 
• 
• 
• 
• 
Breast milk  
 
 
 
• 
• 
 
Satisfaction survey (Hfib only) 
 
• 
 
 
 
 
Process evaluation (Hfib only) 
 
• 
 
 
 
 
 
C7a) Gestational weight gain: GWG will be calculated following the NIH LIFE-Moms protocol106. Self-reported 
pre-pregnancy weight will be replaced with baseline study measured body weight and subtracted from weight 
measured at 34 weeks to calculated GWG. When data are missing, we will extract body weight at delivery 
admission from the electronic medical record. GWG guidelines will be used to classify excessive GWG69.  
 
C7b) Questionnaires: Questionnaires will be given to assess maternal pregnancy and infant birth 
characteristics at study visits, via REDCap surveys, and over the phone throughout the study. Examples 
include maternal health (medical and obstetric history), self-reported race/ethnic background, income, 
education, household information (marital status, baby father’s health, etc.), hunger and satiety, emotional 
health, gastrointestinal health, supplement use, alcohol consumption, drug use, infant sex, birth weight, birth 
length, and gestational age, to name a few107-109. One survey will ask about liking or disliking of foods to assess 
perception of taste and olfaction, which can influence what foods people choose to eat. The survey will be 
taken through a link (https://uconn.co1.qualtrics.com/jfe/form/SV_aVFeLIsOTSVSCzk) which is hosted by the 
University of Connecticut and the corresponding data will be stored on their server. Once the survey has been 
scored, the results will be sent to the study team. No identifying information except a participant ID will be 
included in the survey. 
 
C7c) Satisfaction survey: Satisfaction will be measured with three questions measured on a 5-point Likert scale 
at the completion of the study: “How confident are you that you will stick to the study diet?”; “I am always 
hungry on this diet”; and “This diet is a benefit to my health”. Responses for the confidence question will be: 
not at all, not very, somewhat, very and extremely confident. Responses for the hunger and benefit to health 
questions will be: strongly agree, agree, neutral, disagree and strongly disagree.     
 
C7d) 24-hour dietary recall: Three multiple-pass 24-hour dietary recalls (2 weekday and 1 weekend day) will be 
collected by trained research staff at baseline, end of intervention, and 2, 6, and 12 months postpartum to 
characterize energy and nutrient intake (1 in person, 2 via phone per each visit using a standardized food 
amounts booklet). One 24-hour recall will be obtained every four weeks during the intervention to assess fiber 
goal adherence,  Multiple-pass 24-hour recalls accurately estimate dietary intake110,111 and contain less 
reporting bias than diet records110,112. One 24-hour dietary recall will be administered to the child’s caregiver at 
2 weeks, 2 months, 6 months, and 12 months to characterize the diet of the child. The recalls will be entered 
into the Nutrition Data System for Research (NDS-R, version 2020, Minneapolis, MN) for macro- and 
micronutrient analysis.   
 
C7e) Fecal Sample Collection: Stool will be collected five times throughout the study (baseline, end 
intervention, and 2, 6 and 12 months postpartum) from the mother and four times throughout the study from 
the infant (2 weeks, 2 months, 6 months, and 12 months).  OMNIgene GUT and OMNImet GUT stool collection 
kits (DNAGenotek, Canada) will be shipped to women with specific instructions on collection and storage at 
home. Women will bring collected samples to their study visit. DNA extraction will be completed at KUMC 
under the supervision of Dr. Matthew Taylor.  Library preparation and microbial profiling using 16S V4 
sequencing will be completed at KU Lawrence.  

8 
 
 
 
C7f) Anthropometry: Body weight will be assessed on the same calibrated scale (Detetco Scales, Webb City, 
MO) throughout the study duration for the mother and a calibrated pediatric scale for the infant (Scale-Tronix, 
White Plains, NY). Height will be measured using a wall mounted stadiometer (Accu-Hite, Seca Corp, Hanover, 
MD) for the mother and length using a length board (Shorr Productions) for the infant. Two or more 
measurements will be taken, and the average recorded. Infant head and waist circumferences will be 
measured two or more times, and the average recorded. 
 
C7g) Maternal and infant body composition: Maternal body composition will be assessed using the Selinger 
four-compartment model113 at baseline, end of intervention, and 2, 6, and 12 months postpartum. The 4C 
model includes body mass, body volume, total body water, and bone mineral content. Percent fat will be 
determined by the equation: %FM = ([2.747/BD] – [0.714*TBW/BW] + [1.129*B/BW] – 2.037) x 100; where BD 
is body density in kg/L, TBW is total body water in L, B is bone mineral in kg, and BW is body weight in kg11. 
Body mass will be measured by an electronic scale (Detetco Scales, Webb City, MO). Body volume will be 
assessed via air displacement plethysmography26 (BodPod®; CosMed, Concord, CA)114. Women will wear 
minimal tight-fitting clothing (e.g. one-piece swimsuit) and a fitted hat. Body density will be calculated as body 
mass/body volume. Total body water will be assessed using bioelectrical impedance analysis (BIA; Tanita, 
Inc., TBF-310, Tokyo, Japan)115. Bone mineral content will be measured by dual-energy X-ray absorptiometry 
(DXA; GE Healthcare, Lunar Prodigy, Madison, WI). DXA is contraindicated during pregnancy since radiation 
emission is considered harmful to the fetus116, so bone mineral content will be assessed at 2 weeks 
postpartum1,11,117. Infant body composition will be assessed via air displacement plethysmography26 (PeaPod®; 
CosMed, Concord, CA)114 at 2 weeks, 2 months, and 6 months (if infant ≤10kg). Infants are tested nude with a 
tight fitting hat3. Our Pea Pod® system has the larger tray allowing testing of infants with a body weight up to 10 
kg.  
 
C7h) Maternal and infant DXA: Dual energy x-ray absorptiometry (DXA; Prodigy, Madison, WI, encore software 
version 13.60) will be used to measure body composition and regional adipose tissue distribution. The DXA is 
located within the Dietetics & Nutrition Clinic inside the Smith West building at KUMC. Using specific anatomic 
landmarks as previously described, regions including the arms, legs and trunk will be demarcated118. 
Calculations for FM in each region and summed for regions comprising the central (trunk) and peripheral (arms 
plus legs) will be completed. If a child moves during the scan the scan may need to be re-done at the same or 
later visit, but no more than 6 total scans will be given over the duration of the study. 
 
Pregnant women violate the assumptions used in other body composition methods, so a four-
compartment model is performed where each component is measured separately to get a more accurate 
picture. The components include body mass, body volume, total body water, and bone mineral content. Since 
DXA is contraindicated in pregnancy, the bone mineral content component will be assessed via the DXA at 2 
month postpartum to determine body composition during pregnancy. At 2 months, 6 months, and 12 months 
postpartum, a maternal DXA scan will be obtained because DXA is the only precise technique for measuring 
the location of body fat. Other body composition techniques give an estimate of total body fat only. DXA gives 
a measurement of central and peripheral fat and has the capability to estimate visceral adipose tissue (VAT). 
Central body fat (fat located around the organs), especially VAT, carries a much higher disease risk than 
peripheral body fat (fat in the extremities). Adults with type 2 diabetes and cardiovascular disease have higher 
levels of centrally located fat, whereas fat located in the peripheral region is cardioprotective118,119. For the 
infants, DXA is the only precise technique for measuring amount and location of body fat longitudinally. The 
PeaPod® can only measure infants up to 10 kg, which most children will outgrow between 4-6 months old. We 
need a precise measurement of body composition we can compare across all our timepoints up to 12 months 
old.  While the DXA scan offers no direct benefit to the infant, the information obtained will yield generalizable 
knowledge of vital importance to this population. The prenatal period is shown in literature to be related to 
offspring obesity development and disease risk. Overall, 55% of women gain excessive gestational weight4. 
Excessive GWG leads to higher infant fat mass at birth3,56, and therefore higher childhood fat mass57,59-61. 
Overweight and obesity in childhood are related to disease development later in life, leading to the 
development of the metabolic syndrome, diabetes, and cardiovascular disease6,62,63. With the current obesity 
epidemic, it is critical to understand if we can intervene during the prenatal period to impact fat accumulation 

9 
 
 
and distribution in the infants, which are important drivers of obesity occurrence, disease risk, and severity of 
disease development.  
 
C7i) Process evaluation: Data will be collected throughout the intervention to assess barriers to recruitment 
and study retention, participant acceptability and intervention adherence, and how well the intervention was 
implemented. Participants that drop will be contacted and asked to complete a brief interview to provide 
feedback. Semi-structured interviews will be conducted at the final assessment (34 wks). Participants will be 
asked about their perception of the intervention including both positive and negative aspects and any 
challenges that were encountered, pros and cons of using group video counseling to promote healthy 
behaviors during pregnancy, and their overall satisfaction with the intervention. Interviews will be audio 
recorded and transcribed verbatim. Comments will be coded, categorized into themes and used to refine and 
further develop future interventions. 
 
C7j) Safety monitoring: All subjects will be given a body weight scale and report body weight weekly. This 
allows close supervision of progression of each participant to ensure the intervention is not overly effective and 
all women are gaining adequate body weight. If a woman gains or loses more than 5 lbs over a two-week 
period, she will be flagged and contacted. If she is in the Hfib group, total weight gain recommendations will be 
reviewed and her dietary habits and fiber intake will be reviewed and reinforced. Rapid weight changes or any 
other safety concerns will be reviewed by our study physician for safety purposes. The participant’s provider 
will be notified if physician deems necessary. 
 
C7k) Maternal blood draw: Maternal venous blood will be collected at 5 times through the study (baseline, end 
of intervention, 2 months, 6 months, and 12 months postpartum) after an overnight fast by a trained 
phlebotomist. A total of two 4-mL EDTA (lavender top) tubes (1 will be filled ½ full), one 10-mL EDTA, one 7.5-
mL serum (tiger top) tube, and one-8.5mL serum tubes will be collected. At the baseline visit and additional 
one 6-mL ACD (yellow top) plasma vacutainer will be collected for ApoE genotyping. All tubes will be placed on 
ice and processed within 24 hours, including aliquoting for analysis. All tubes will be appropriately labeled with 
the study identification number, date (mm/dd/yyyy), and time (24-hour time, hh:mm).  Blood samples will be 
analyzed to assess biomarkers related to cardiometabolic health (including serum lipids, glucose metabolism, 
and inflammation), gut metabolites (short chain fatty acids) and neuronal health (including assessment of 
underlying ApoE genetics). Samples will be sent to Quest Diagnostics for cardiometabolic markers (standard 
lipid panel (total cholesterol, triglycerides, HDL-C, LDL-C (calculated), Cholesterol/HDL ratio (calculated), and 
non-HDL-C (calculated)), hemoglobin A1C, plasma glucose, serum insulin, and high sensitivity- C-reactive 
protein). All other samples will be stored at −80°C for analysis. Batched samples will be analyzed at KUMC 
according to the protocols of the manufacturer using the following formats:, SIMOA (neurofilament-light and 
inflammatory cytokines), and polymerase chain reaction (ApoE genotype). Unused samples will be banked for 
future evaluations related to nutrition and brain healthincluding free cell RNA analysis at KUMC. 
 
C7l) Actigraphy: Maternal physical activity and sleep will be monitored using the ActiGraph wG3TX-BT. The 
device will be worn at the wrist for 7 days around 5/6 study visits (baseline, end of intervention, 2 months, 6 
months, and 12 months postpartum). Participants will not be able to view any device data. Participants will also 
be asked to keep a sleep and activity log during this time. Participants will be mailed the device and given 
instructions for use prior to each study visit, along with an activity and sleep tracker. Following the 7-day 
monitoring period, participants will return the device and log back to the study team. Data collected from the 
device are available at https://www.actigraphcorp.com/actigraph-wgt3x-bt/ and include raw acceleration, steps, 
METs, total sleep time, sleep efficiency, and others related to activity and sleep. Participants will download an 
application on a home device that will allow them to daily sync the activity information via Bluetooth and send it 
to the cloud-based data management platform https://actigraphcorp.com/centrepoint/. 
C7m) Maternal vitals:  Blood pressure & heart rate will be assessed 6 times throughout the study (baseline, 
end of intervention, 2 weeks 2 months, 6 months, and 12 months) using the Omron HEM 907XL IntelliSense 
Professional Digital Blood Pressure Monitor. Participants will be instructed to sit quietly for 5 minutes in the 
upright position with feet flat on the floor. After completing the period, blood pressure cuff will be placed around 

10 
 
 
the upper arm and assessment completed per manufacturer’s recommendations. The measurement will be 
repeated until 2 are within 5 mmhg agreement.  
C7n) Veggie meter: Maternal carotenoid skin content will be assessed at 5 time points (baseline, end of 
intervention, 2 months, 6 months, and 12 months) using the veggie meter. Participants will insert a finger into 
the machine. The machine uses LED light to detect pigments. Three measurements will be taken and 
averaged, each lasting 10-45 seconds.  
C7o) Maternal cognitive testing: The NIH Toolbox Cognition Battery will be used to assess cognitive function in 
several different domains, including executive function, language, episodic memory, processing speed, and 
attention 5 times throughout the study (baseline, end of intervention, 2 months, 6 months, and 12 months).   
The test will be administrated by a trained team member on an Apple iPad. Consistent with the toolbox 
recommendations, collected data will be emailed to a member of the study team and archived on the P-Drive. 
The record is not required to be kept on the iPad and can be expunged after confirmation that it has been 
archived on the P-Drive. 
C7p) Maternal olfactory testing: Participant olfaction will be evaluated at 4 times throughout the study 
(baseline, end of intervention, 2 months, and 12 months). Each patient will be tested with fourteen different 
scents using aromatherapy inhaling scents (rose, eucalyptus, clove, lemon, garlic, coffee, spearmint, orange, 
cinnamon, lavender, rosemary, anise, peppermint, and ginger). The scents will be available at two 
concentrations (1x and 2x), and the participants will be asked to nasally inhale each scent for 10 seconds. The 
participants will be presented with the 1x sticks and asked to state if a smell is present and to correctly identify 
the odor. If an odor is not detected or correctly identified, the 2x concentration of the same odor will be added 
to the remaining lot of inhalant sticks.   
C7q) Infant skinfolds: Skinfolds will be assessed 4 timepoints for the infant (2 weeks, 2 months,  6 months, and 
12 months). Six skinfolds will be measured to represent AT distribution in order to compare to larger trials that 
do not have DXA. All measurements will be collected using standardized procedures to our laboratory. All 
skinfolds will be identified using anatomical landmarks and taken on the right side of the body using Lange 
calipers (Beta Technology, Santa Cruz, CA). Skinfolds will be taken in order from head to toe and then 
repeated in that same order. If two skinfold measurements differ by more than 1 mm, a third measurement will 
be taken. The two measurements within 1 mm will be averaged and used for analysis. Biceps and triceps 
skinfolds will be measured at the midline of the anterior and posterior surface of the arm, respectively, on the 
mid-point between acromial process of the scapula and olecranon process of the ulna. Subscapular skinfold 
will be measured at the lower angle of the scapula. Suprailiac skinfold will be measured anteriorly to the 
midaxillary line and superiorly to the iliac crest, along the natural cleavage of the skin. The thigh skinfold will be 
measured at the mid-point between patella (knee cap) and inguinal crease at the anterior surface of the thigh. 
Flank skinfold will be measured immediately above the iliac crest at the mid-axillary line. Central FM will be 
calculated by adding the subscapular, suprailiac and flank skinfolds and dividing by three Peripheral FM will be 
calculated by adding the thigh, biceps and triceps skinfolds and dividing by three. 
 
C7r) Maternal urine & pregnancy test: Urine will be collected at all 6 maternal timepoints. Prior to maternal 
DXA at all post-partum visits (2 weeks, 2 months, 6 months, and 12 months), the urine will be used to perform 
a pregnancy test. Urine will be collected and aliquoted into 10, 2-mL cryovials and stored at -80°C. Urine will 
be used to test for polyfluoroalkyl substances. Unused samples will be banked for future evaluations related to 
nutrition and brain health at KUMC. 
C7t) Breastmilk analysis: Participants who choose to breast feed will be asked to pump one breast until empty, 
homogenize the breastmilk by stirring, and return 20-mL to the study team for nutrient analysis. Participants 
will be asked to do this at 1 month, 2 months, 3 months, 4 months, 5 months, and 6 months, freeze it, and 
return it to the study team at the 2-month and 6-month visits. The remainder of the breastmilk collected can be 
kept by the participant and fed to their infant. Any leftover sample after initial nutrient analysis will be banked 
for future evaluations related to nutrition and brain health and KUMC. 

11 
 
 
C8) Steps to maximize adherence and retention: We will be using incentives for study visits, incentives for 
reporting goals, and regular short-term performance and feedback.  
 
C8a) Incentive system: Participants will be compensated $100 for each of the 6 study visits: baseline, end 
intervention, 2 weeks postpartum, 2 months postpartum, 6 months postpartum, and 12 months postpartum 
totaling up to $600 for completion of all visits. Participants asked to return for repeat infant DXA (no more than 
2 at each study timepoint) will be compensated an additional $50. Compensation will be provided on a 
ClinCard, which is given at enrollment. After each visit study staff will load their unique card number with the 
respective pay. Participants can use the card anywhere Mastercard is accepted, and study staff does not have 
access to where the money will be spent.  
 
C8c) Monitoring retention: When participants miss a session or reporting of behaviors, they will be contacted 
and a standardized protocol according to attendance and adherence demands will be used to make every 
effort to retain the participant or encourage reporting. This will be documented and used for program 
evaluation.  
 
C9) Statistical analysis: The purpose of this study is to attain feasibility data therefore the small sample size 
does not afford the power to detect significance but to identify promising trends and relationships. 
 
 Analysis for Aim 1 H1: A t-test will be used to determine if there is a difference in maternal weight gain and fat 
accretion between the two groups. 
 
Analysis for Aim 2 H2: A t-test will be used to quantify if there is a difference in fiber intake and dietary quality 
between the two groups.  
 
Analysis for secondary Aim 1 H1: Repeated measures ANCOVA will be used to assess the difference in gut 
microbiome composition and diversity from baseline to study end between groups.  
 
Analysis for secondary Aim 2 H2: A t-test will be used to determine if there is a difference in infant fat accrual 
between groups.  
 
Analysis for secondary Aim 3 H3: A t-test will be used to determine if there is a difference in metabolic, 
inflammatory, and brain health markers.  
 
Process evaluation: A process evaluation will be completed.  
 
C10) Study challenges: A primary study challenge is the recruitment and retention. Dr. Hull has completed 
protocols successfully recruiting participants from the OB clinics at KUMC. Dr. Weiner, KUMC head of 
OBGYN, reports 1800 annual deliveries take place at KUMC with ~40% overweight. A second challenge is to 
assure the fidelity of the interventions. Dr. Goetz will listen to 20% of GBPC sessions and compare the content 
delivered to a standardized checklist. If less than 80% of content is covered, Dr. Goetz will re-train the Dietitian. 
A third challenge is to ensure subjects are attending sessions and reporting behaviors. We had a high degree 
of weekly reporting in our pilot study and anticipate a similar response rate in this pilot.  
 
C11) Expected results: We anticipate the Hfib intervention will successfully prevent excessive GWG. The Hfib 
intervention holds promise to be delivered in routine clinical care. If the results are positive, the next study 
would be to adapt and embed the Hfib intervention in routine clinical care. The literature supports preventing 
excessive GWG has a high likelihood to greatly improve the health of both mothers and their offspring however 
there is variable success in published interventions. This supports the need to design and test interventions 
informed by prior study failures.  
 
C12) Environment: The environment at KUMC is well suited to conduct this research.  
 

12 
 
 
References: 
1. 
Butte NF, Ellis KJ, Wong WW, Hopkinson JM, Smith EO. Composition of gestational weight gain 
impacts maternal fat retention and infant birth weight. American journal of obstetrics and gynecology. 
2003;189(5):1423-1432. 
2. 
Endres LK, Straub H, McKinney C, et al. Postpartum weight retention risk factors and relationship to 
obesity at 1 year. Obstetrics and gynecology. 2015;125(1):144-152. 
3. 
Hull HR, Thornton JC, Ji Y, et al. Higher infant body fat with excessive gestational weight gain in 
overweight women. American journal of obstetrics and gynecology. 2011;205(3):211 e211-217. 
4. 
Badon SE, Dyer AR, Josefson JL, Group HSCR. Gestational weight gain and neonatal adiposity in the 
Hyperglycemia and Adverse Pregnancy Outcome study-North American region. Obesity (Silver Spring). 
2014;22(7):1731-1738. 
5. 
Fryar CD, Carroll MD, Ogden CL. Prevalence of overweight and obesity among children and 
adolescents: United States, 1963-1965 through 2011-2012. Atlanta, GA2014. 
6. 
Llewellyn A, Simmonds M, Owen CG, Woolacott N. Childhood obesity as a predictor of morbidity in 
adulthood: a systematic review and meta-analysis. Obes Rev. 2016;17(1):56-67. 
7. 
Ahmad FB, Bastian B. Quarterly provisional estimates for selected indicators of mortality, 2015-Quarter 
1, 2017. National Center for Health Statistics. 2017. 
8. 
Cawley J, Meyerhoefer C, Biener A, Hammer M, Wintfeld N. Savings in Medical Expenditures 
Associated with Reductions in Body Mass Index Among US Adults with Obesity, by Diabetes Status. 
Pharmacoeconomics. 2015;33(7):707-722. 
9. 
Kaaja RJ, Greer IA. Manifestations of chronic disease during pregnancy. Jama. 2005;294(21):2751-
2757. 
10. 
Lassek WD, Gaulin SJ. Changes in body fat distribution in relation to parity in American women: a 
covert form of maternal depletion. Am J Phys Anthropol. 2006;131(2):295-302. 
11. 
Lederman SA, Paxton A, Heymsfield SB, Wang J, Thornton J, Pierson RN, Jr. Body fat and water 
changes during pregnancy in women with different body weight and weight gain. Obstetrics and 
gynecology. 1997;90(4 Pt 1):483-488. 
12. 
Knopp RH, Ruder HJ, Herrera E, Freinkel N. Carbohydrate metabolism in pregnancy. VII. Insulin 
tolerance during late pregnancy in the fed and fasted rat. Acta Endocrinol (Copenh). 1970;65(2):352-
360. 
13. 
Greer IA. Thrombosis in pregnancy: maternal and fetal issues. Lancet. 1999;353(9160):1258-1265. 
14. 
Phelan S. Pregnancy: a "teachable moment" for weight control and obesity prevention. American 
journal of obstetrics and gynecology. 2010;202(2):135 e131-138. 
15. 
Campbell F, Johnson M, Messina J, Guillaume L, Goyder E. Behavioural interventions for weight 
management in pregnancy: a systematic review of quantitative and qualitative data. BMC Public Health. 
2011;11:491. 
16. 
Streuling I, Beyerlein A, von Kries R. Can gestational weight gain be modified by increasing physical 
activity and diet counseling? A meta-analysis of interventional trials. The American journal of clinical 
nutrition. 2010;92(4):678-687. 
17. 
International Weight Management in Pregnancy Collaborative G. Effect of diet and physical activity 
based interventions in pregnancy on gestational weight gain and pregnancy outcomes: meta-analysis 
of individual participant data from randomised trials. BMJ (Clinical research ed. 2017;358:j3119. 
18. 
Gardner B, Wardle J, Poston L, Croker H. Changing diet and physical activity to reduce gestational 
weight gain: a meta-analysis. Obes Rev. 2011;12(7):e602-620. 
19. 
Vincze L, Rollo M, Hutchesson M, et al. Interventions including a nutrition component aimed at 
managing gestational weight gain or postpartum weight retention: a systematic review and meta-
analysis. JBI database of systematic reviews and implementation reports. 2019;17(3):297-364. 
20. 
Thangaratinam S, Rogozinska E, Jolly K, et al. Effects of interventions in pregnancy on maternal weight 
and obstetric outcomes: meta-analysis of randomised evidence. BMJ (Clinical research ed. 
2012;344:e2088. 
21. 
Peaceman AM, Clifton RG, Phelan S, et al. Lifestyle Interventions Limit Gestational Weight Gain in 
Women with Overweight or Obesity: LIFE-Moms Prospective Meta-Analysis. Obesity (Silver Spring, 
Md. 2018;26(9):1396-1404. 

13 
 
 
22. 
Muktabhant B, Lumbiganon P, Ngamjarus C, Dowswell T. Interventions for preventing excessive weight 
gain during pregnancy. The Cochrane database of systematic reviews. 2012;4:CD007145. 
23. 
Tanentsapf I, Heitmann BL, Adegboye AR. Systematic review of clinical trials on dietary interventions to 
prevent excessive weight gain during pregnancy among normal weight, overweight and obese women. 
BMC Pregnancy Childbirth. 2011;11:81. 
24. 
Oteng-Ntim E, Varma R, Croker H, Poston L, Doyle P. Lifestyle interventions for overweight and obese 
pregnant women to improve pregnancy outcome: systematic review and meta-analysis. BMC medicine. 
2012;10:47. 
25. 
Thangaratinam S, Rogozinska E, Jolly K, et al. Interventions to reduce or prevent obesity in pregnant 
women: a systematic review. Health technology assessment. 2012;16(31):iii-iv, 1-191. 
26. 
Cahill AG, Haire-Joshu D, Cade WT, et al. Weight Control Program and Gestational Weight Gain in 
Disadvantaged Women with Overweight or Obesity: A Randomized Clinical Trial. Obesity (Silver 
Spring, Md. 2018;26(3):485-491. 
27. 
Trak-Fellermeier MA, Campos M, Melendez M, et al. PEARLS randomized lifestyle trial in pregnant 
Hispanic women with overweight/obesity: gestational weight gain and offspring birthweight. Diabetes, 
metabolic syndrome and obesity : targets and therapy. 2019;12:225-238. 
28. 
Dodd JM, Louise J, Deussen AR, et al. Effect of metformin in addition to dietary and lifestyle advice for 
pregnant women who are overweight or obese: the GRoW randomised, double-blind, placebo-
controlled trial. The lancet Diabetes & endocrinology. 2019;7(1):15-24. 
29. 
Kunath J, Gunther J, Rauh K, et al. Effects of a lifestyle intervention during pregnancy to prevent 
excessive gestational weight gain in routine care - the cluster-randomised GeliS trial. BMC medicine. 
2019;17(1):5. 
30. 
Ludwig DS, Pereira MA, Kroenke CH, et al. Dietary fiber, weight gain, and cardiovascular disease risk 
factors in young adults. JAMA. 1999;282(16):1539-1546. 
31. 
Newby PK, Muller D, Hallfrisch J, Qiao N, Andres R, Tucker KL. Dietary patterns and changes in body 
mass index and waist circumference in adults. The American journal of clinical nutrition. 
2003;77(6):1417-1425. 
32. 
McKeown NM, Meigs JB, Liu S, Saltzman E, Wilson PW, Jacques PF. Carbohydrate nutrition, insulin 
resistance, and the prevalence of the metabolic syndrome in the Framingham Offspring Cohort. 
Diabetes care. 2004;27(2):538-546. 
33. 
Schulze MB, Liu S, Rimm EB, Manson JE, Willett WC, Hu FB. Glycemic index, glycemic load, and 
dietary fiber intake and incidence of type 2 diabetes in younger and middle-aged women. The American 
journal of clinical nutrition. 2004;80(2):348-356. 
34. 
Davis JN, Hodges VA, Gillham MB. Normal-weight adults consume more fiber and fruit than their age- 
and height-matched overweight/obese counterparts. J Am Diet Assoc. 2006;106(6):833-840. 
35. 
Howarth NC, Huang TTK, Roberts SB, McCrory MA. Dietary fiber and fat are associated with excess 
weight in young and middle-aged US adults. Journal of the American Dietetic Association. 
2005;105(9):1365-1372. 
36. 
Kristensen M, Toubro S, Jensen MG, et al. Whole grain compared with refined wheat decreases the 
percentage of body fat following a 12-week, energy-restricted dietary intervention in postmenopausal 
women. The Journal of nutrition. 2012;142(4):710-716. 
37. 
Tucker LA, Thomas KS. Increasing total fiber intake reduces risk of weight and fat gains in women. J 
Nutr. 2009;139(3):576-581. 
38. 
Rhodes ET, Pawlak DB, Takoudes TC, et al. Effects of a low-glycemic load diet in overweight and 
obese pregnant women a pilot randomized controlled trial. American Journal of Clinical Nutrition. 
2010;92(6):1306-1315. 
39. 
Maple-Brown LJ, Roman NM, Thomas A, Presley LH, Catalano PM. Perinatal factors relating to 
changes in maternal body fat in late gestation. J Perinatol. 2013;33(12):934-938. 
40. 
Turner TF, Nance LM, Strickland WD, Malcolm RJ, Pechon S, O'Neil PM. Dietary adherence and 
satisfaction with a bean-based high-fiber weight loss diet: a pilot study. ISRN Obes. 2013;2013:915415. 
41. 
Weickert MO, Roden M, Isken F, et al. Effects of supplemented isoenergetic diets differing in cereal 
fiber and protein content on insulin sensitivity in overweight humans. The American journal of clinical 
nutrition. 2011;94(2):459-471. 

14 
 
 
42. 
Davy BM, Davy KP, Ho RC, Beske SD, Davrath LR, Melby CL. High-fiber oat cereal compared with 
wheat cereal consumption favorably alters LDL-cholesterol subclass and particle numbers in middle-
aged and older men. The American journal of clinical nutrition. 2002;76(2):351-358. 
43. 
Pereira MA, Jacobs DR, Jr., Pins JJ, et al. Effect of whole grains on insulin sensitivity in overweight 
hyperinsulinemic adults. The American journal of clinical nutrition. 2002;75(5):848-855. 
44. 
Fukagawa NK, Anderson JW, Hageman G, Young VR, Minaker KL. High-carbohydrate, high-fiber diets 
increase peripheral insulin sensitivity in healthy young and old adults. The American journal of clinical 
nutrition. 1990;52(3):524-528. 
45. 
McKeown NM, Meigs JB, Liu S, Wilson PW, Jacques PF. Whole-grain intake is favorably associated 
with metabolic risk factors for type 2 diabetes and cardiovascular disease in the Framingham Offspring 
Study. The American journal of clinical nutrition. 2002;76(2):390-398. 
46. 
Lutsey PL, Jacobs DR, Jr., Kori S, et al. Whole grain intake and its cross-sectional association with 
obesity, insulin resistance, inflammation, diabetes and subclinical CVD: The MESA Study. Br J Nutr. 
2007;98(2):397-405. 
47. 
Marshall JA, Bessesen DH, Hamman RF. High saturated fat and low starch and fibre are associated 
with hyperinsulinaemia in a non-diabetic population: the San Luis Valley Diabetes Study. Diabetologia. 
1997;40(4):430-438. 
48. 
Jovanovski E, Mazhar N, Komishon A, et al. Can dietary viscous fiber affect body weight independently 
of an energy-restrictive diet? A systematic review and meta-analysis of randomized controlled trials. 
The American journal of clinical nutrition. 2020;111(2):471-485. 
49. 
Olendzki BC, Ma Y, Schneider KL, et al. A simple dietary message to improve dietary quality: Results 
from a pilot investigation. Nutrition (Burbank, Los Angeles County, Calif. 2009;25(7-8):736-744. 
50. 
Ma Y, Olendzki BC, Wang J, et al. Single-component versus multicomponent dietary goals for the 
metabolic syndrome: a randomized trial. Ann Intern Med. 2015;162(4):248-257. 
51. 
Paul HA, Bomhof MR, Vogel HJ, Reimer RA. Diet-induced changes in maternal gut microbiota and 
metabolomic profiles influence programming of offspring obesity risk in rats. Sci Rep. 2016;6:20683. 
52. 
Herman A, Taylor M, Yu G, Hull HR. A high fiber diet during pregnancy favorably impacts the 
microbiota. Obesity (Silver Spring, Md. 2019;22(1S). 
53. 
Bailey RL, Pac SG, Fulgoni VL, 3rd, Reidy KC, Catalano PM. Estimation of Total Usual Dietary Intakes 
of Pregnant Women in the United States. JAMA Netw Open. 2019;2(6):e195967. 
54. 
Dietary reference intakes for energy, carbohydrates, fiber, fat, fatty acids, cholesterol, protein and 
amino acids. Institute of Medicine Panel on Macronutrients;2005. 
55. 
Millen BE. Scientific report of the 2015 Dietary Guidelines Advisory Committee.  February 2015. 
56. 
Hull HR, Dinger MK, Knehans AW, Thompson DM, Fields DA. Impact of maternal body mass index on 
neonate birthweight and body composition. American journal of obstetrics and gynecology. 
2008;198(4):416 e411-416. 
57. 
Crozier SR, Inskip HM, Godfrey KM, et al. Weight gain in pregnancy and childhood body composition: 
findings from the Southampton Women's Survey. The American journal of clinical nutrition. 
2010;91(6):1745-1751. 
58. 
Kaar JL, Crume T, Brinton JT, Bischoff KJ, McDuffie R, Dabelea D. Maternal Obesity, Gestational 
Weight Gain, and Offspring Adiposity: The Exploring Perinatal Outcomes among Children Study. The 
Journal of pediatrics. 2014;165(3):509-515. 
59. 
Reynolds RM, Osmond C, Phillips DIW, Godfrey KM. Maternal BMI, Parity, and Pregnancy Weight 
Gain: Influences on Offspring Adiposity in Young Adulthood. J Clin Endocr Metab. 2010;95(12):5365-
5369. 
60. 
Sridhar SB, Darbinian J, Ehrlich SF, et al. Maternal gestational weight gain and offspring risk for 
childhood overweight or obesity. American journal of obstetrics and gynecology. 2014;211(3):259 e251-
258. 
61. 
Mourtakos SP, Tambalis KD, Panagiotakos DB, et al. Maternal lifestyle characteristics during 
pregnancy, and the risk of obesity in the offspring: a study of 5,125 children. BMC Pregnancy 
Childbirth. 2015;15:66. 
62. 
Reilly JJ, Armstrong J, Dorosty AR, et al. Early life risk factors for obesity in childhood: cohort study. 
BMJ (Clinical research ed. 2005;330(7504):1357. 

15 
 
 
63. 
Parsons TJ, Power C, Manor O. Fetal and early life growth and body mass index from birth to early 
adulthood in 1958 British cohort: longitudinal study. BMJ (Clinical research ed. 2001;323(7325):1331-
1335. 
64. 
Cnattingius S, Bergstrom R, Lipworth L, Kramer MS. Prepregnancy weight and the risk of adverse 
pregnancy outcomes. The New England journal of medicine. 1998;338(3):147-152. 
65. 
Michlin R, Oettinger M, Odeh M, et al. Maternal obesity and pregnancy outcome. Isr Med Assoc J. 
2000;2(1):10-13. 
66. 
Linne Y, Barkeling B, Rossner S. Natural course of gestational diabetes mellitus: long term follow up of 
women in the SPAWN study. Bjog. 2002;109(11):1227-1231. 
67. 
Catalano PM, Roman NM, Tyzbir ED, Merritt AO, Driscoll P, Amini SB. Weight gain in women with 
gestational diabetes. Obstetrics and gynecology. 1993;81(4):523-528. 
68. 
Williamson DF, Kahn HS, Remington PL, Anda RF. The 10-year incidence of overweight and major 
weight gain in US adults. Arch Intern Med. 1990;150(3):665-672. 
69. 
Weight gain during pregnancy: Reexamining the guidelines. Washington (DC): Institute of Medicine, 
National Research Council, Committee to Reexamine IOM Pregnancy Weight Guidelines;2009. 
70. 
Leverence RR, Williams RL, Sussman A, Crabtree BF, Clinicians RN. Obesity counseling and 
guidelines in primary care: a qualitative study. Am J Prev Med. 2007;32(4):334-339. 
71. 
Claesson IM, Sydsjo G, Brynhildsen J, et al. Weight gain restriction for obese pregnant women: a case-
control intervention study. BJOG. 2008;115(1):44-50. 
72. 
Mottola MF, Giroux I, Gratton R, et al. Nutrition and exercise prevent excess weight gain in overweight 
pregnant women. Med Sci Sports Exerc. 2010;42(2):265-272. 
73. 
Hui A, Back L, Ludwig S, et al. Lifestyle intervention on diet and exercise reduced excessive gestational 
weight gain in pregnant women under a randomised controlled trial. BJOG. 2012;119(1):70-77. 
74. 
Asbee SM, Jenkins TR, Butler JR, White J, Elliot M, Rutledge A. Preventing excessive weight gain 
during pregnancy through dietary and lifestyle counseling: a randomized controlled trial. Obstetrics and 
gynecology. 2009;113(2 Pt 1):305-312. 
75. 
Guelinckx I, Devlieger R, Mullie P, Vansant G. Effect of lifestyle intervention on dietary habits, physical 
activity, and gestational weight gain in obese pregnant women: a randomized controlled trial. The 
American journal of clinical nutrition. 2010;91(2):373-380. 
76. 
Huang TT, Yeh CY, Tsai YC. A diet and physical activity intervention for preventing weight retention 
among Taiwanese childbearing women: a randomised controlled trial. Midwifery. 2011;27(2):257-264. 
77. 
Ilmonen J, Isolauri E, Poussa T, Laitinen K. Impact of dietary counselling and probiotic intervention on 
maternal anthropometric measurements during and after pregnancy: a randomized placebo-controlled 
trial. Clinical nutrition (Edinburgh, Scotland). 2011;30(2):156-164. 
78. 
Jackson RA, Stotland NE, Caughey AB, Gerbert B. Improving diet and exercise in pregnancy with 
Video Doctor counseling: a randomized trial. Patient education and counseling. 2011;83(2):203-209. 
79. 
Gray-Donald K, Robinson E, Collier A, David K, Renaud L, Rodrigues S. Intervening to reduce weight 
gain in pregnancy and gestational diabetes mellitus in Cree communities: an evaluation. CMAJ : 
Canadian Medical Association journal = journal de l'Association medicale canadienne. 
2000;163(10):1247-1251. 
80. 
Olson CM, Strawderman MS, Reed RG. Efficacy of an intervention to prevent excessive gestational 
weight gain. American journal of obstetrics and gynecology. 2004;191(2):530-536. 
81. 
Kinnunen TI, Aittasalo M, Koponen P, et al. Feasibility of a controlled trial aiming to prevent excessive 
pregnancy-related weight gain in primary health care. BMC Pregnancy Childbirth. 2008;8:37. 
82. 
Shirazian T, Monteith S, Friedman F, Rebarber A. Lifestyle modification program decreases pregnancy 
weight gain in obese women. American journal of perinatology. 2010;27(5):411-414. 
83. 
Dodd JM, Turnbull D, McPhee AJ, et al. Antenatal lifestyle advice for women who are overweight or 
obese: LIMIT randomised trial. BMJ (Clinical research ed. 2014;348:g1285. 
84. 
Phelan S, Phipps MG, Abrams B, Darroch F, Schaffner A, Wing RR. Randomized trial of a behavioral 
intervention to prevent excessive gestational weight gain: the Fit for Delivery Study. The American 
journal of clinical nutrition. 2011;93(4):772-779. 
85. 
Polley BA, Wing RR, Sims CJ. Randomized controlled trial to prevent excessive weight gain in 
pregnant women. Int J Obes Relat Metab Disord. 2002;26(11):1494-1502. 

16 
 
 
86. 
Thornton YS, Smarkola C, Kopacz SM, Ishoof SB. Perinatal outcomes in nutritionally monitored obese 
pregnant women: a randomized clinical trial. Journal of the National Medical Association. 
2009;101(6):569-577. 
87. 
Wolff S, Legarth J, Vangsgaard K, Toubro S, Astrup A. A randomized trial of the effects of dietary 
counseling on gestational weight gain and glucose metabolism in obese pregnant women. Int J Obes 
(Lond). 2008;32(3):495-501. 
88. 
Lairon D. Dietary fiber and control of body weight. Nutrition, metabolism, and cardiovascular diseases : 
NMCD. 2007;17(1):1-5. 
89. 
Slavin JL. Dietary fiber and body weight. Nutrition (Burbank, Los Angeles County, Calif. 
2005;21(3):411-418. 
90. 
Howarth NC, Saltzman E, Roberts SB. Dietary fiber and weight regulation. Nutrition reviews. 
2001;59(5):129-139. 
91. 
Hermsdorff HH, Barbosa KB, Volp AC, et al. Vitamin C and fibre consumption from fruits and 
vegetables improves oxidative stress markers in healthy young adults. Br J Nutr. 2012;107(8):1119-
1127. 
92. 
Grundy SM, Cleeman JI, Daniels SR, et al. Diagnosis and management of the metabolic syndrome: an 
American Heart Association/National Heart, Lung, and Blood Institute scientific statement: Executive 
Summary. Crit Pathw Cardiol. 2005;4(4):198-203. 
93. 
Ning H, Van Horn L, Shay CM, Lloyd-Jones DM. Associations of dietary fiber intake with long-term 
predicted cardiovascular disease risk and C-reactive protein levels (from the National Health and 
Nutrition Examination Survey Data [2005-2010]). Am J Cardiol. 2014;113(2):287-291. 
94. 
Carlson JJ, Eisenmann JC, Norman GJ, Ortiz KA, Young PC. Dietary fiber and nutrient density are 
inversely associated with the metabolic syndrome in US adolescents. J Am Diet Assoc. 
2011;111(11):1688-1695. 
95. 
Phelan S, Jankovitz K, Hagobian T, Abrams B. Reducing excessive gestational weight gain: lessons 
from the weight control literature and avenues for future research. Women's health. 2011;7(6):641-661. 
96. 
Setse R, Grogan R, Cooper LA, Strobino D, Powe NR, Nicholson W. Weight loss programs for urban-
based, postpartum African-American women: perceived barriers and preferred components. Maternal 
and child health journal. 2008;12(1):119-127. 
97. 
van Wier MF, Ariens GA, Dekkers JC, Hendriksen IJ, Smid T, van Mechelen W. Phone and e-mail 
counselling are effective for weight management in an overweight working population: a randomized 
controlled trial. BMC Public Health. 2009;9:6. 
98. 
Svetkey LP, Stevens VJ, Brantley PJ, et al. Comparison of strategies for sustaining weight loss: the 
weight loss maintenance randomized controlled trial. Jama. 2008;299(10):1139-1148. 
99. 
Donnelly JE, Smith BK, Dunn L, et al. Comparison of a phone vs clinic approach to achieve 10% weight 
loss. Int J Obes (Lond). 2007;31(8):1270-1276. 
100. 
Donnelly JE, Goetz J, Gibson C, et al. Equivalent weight loss for weight management programs 
delivered by phone and clinic. Obesity (Silver Spring, Md. 2013;21(10):1951-1959. 
101. 
Befort CA, Donnelly JE, Sullivan DK, Ellerbeck EF, Perri MG. Group versus individual phone-based 
obesity treatment for rural women. Eat Behav. 2010;11(1):11-17. 
102. 
Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory. . Englewood Cliffs, 
New Jersey: Prentice-Hall; 1986. 
103. 
Bandura A. Self-Efficacy: The Exercise of Control. New York: WH Freeman and Co; 1997. 
104. 
Bandura A. Social cognitive theory: an agentic perspective. Annu Rev Psychol. 2001;52:1-26. 
105. 
Marlatt G. Relapse Prevention: Maintenance Strategies in the Treatment of Addictive Behavior. New 
York: Guilford Press; 1985. 
106. 
Clifton RG, Evans M, Cahill AG, et al. Design of lifestyle intervention trials to prevent excessive 
gestational weight gain in women with overweight or obesity. Obesity (Silver Spring, Md. 
2016;24(2):305-313. 
107. 
Dewi M, Carlson SE, Gustafson KM, Sullivan DK, Wick JA, Hull HR. Programming of infant 
neurodevelopment by maternal obesity: potential role of maternal inflammation and insulin resistance. 
Asia Pac J Clin Nutr. 2017;26(Suppl 1):S36-S39. 
108. 
Carlson SE, Colombo J. Docosahexaenoic Acid and Arachidonic Acid Nutrition in Early Development. 
Adv Pediatr. 2016;63(1):453-471. 

17 
 
 
109. 
Hidaka BH, Thodosoff JM, Kerling EH, Hull HR, Colombo J, Carlson SE. Intrauterine DHA exposure 
and child body composition at 5 y: exploratory analysis of a randomized controlled trial of prenatal DHA 
supplementation. The American journal of clinical nutrition. 2018;107(1):35-42. 
110. 
Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US Department of 
Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. The 
American journal of clinical nutrition. 2003;77(5):1171-1178. 
111. 
Blanton CA, Moshfegh AJ, Baer DJ, Kretsch MJ. The USDA Automated Multiple-Pass Method 
accurately estimates group total energy and nutrient intake. The Journal of nutrition. 
2006;136(10):2594-2599. 
112. 
Hebert JR, Hurley TG, Chiriboga DE, Barone J. A comparison of selected nutrient intakes derived from 
three diet assessment methods used in a low-fat maintenance trial. Public Health Nutr. 1998;1(3):207-
214. 
113. 
Selinger A. The body as a three component system. [University of Illinois at Urbana, doctoral thesis]. 
Ann Arbor, Michigan, University of Illinois at Urbana; 1977. 
114. 
Dempster P, Aitkens S. A new air displacement method for the determination of human body 
composition. Med Sci Sports Exerc. 1995;27(12):1692-1697. 
115. 
Widen EM, Strain G, King WC, et al. Validity of bioelectrical impedance analysis for measuring changes 
in body water and percent fat after bariatric surgery. Obesity surgery. 2014;24(6):847-854. 
116. 
Pregnancy and medical radiation. Annals of the ICRP. 2000;30(1):iii-viii, 1-43. 
117. 
Marshall NE, Murphy EJ, King JC, et al. Comparison of multiple methods to measure maternal fat mass 
in late gestation. The American journal of clinical nutrition. 2016;103(4):1055-1063. 
118. 
Yim JE, Heshka S, Albu JB, Heymsfield S, Gallagher D. Femoral-gluteal subcutaneous and 
intermuscular adipose tissues have independent and opposing relationships with CVD risk. J Appl 
Physiol. 2008;104(3):700-707. 
119. 
Gallagher D, Kelley DE, Yim JE, et al. Adipose tissue distribution is different in type 2 diabetes. The 
American journal of clinical nutrition. 2009;89(3):807-814. 
 
 
 

18 
 
 
PROTECTION OF HUMAN SUBJECTS 
This study will enroll pregnant women and their offspring. This study will block randomize 6-10 women into one 
of the following groups: a high fiber dietary intervention or UC. The primary aim is to assess the difference in 
maternal weight gain and fat accrual. All subjects will be given a body weight scale and report weekly their 
body weight. This allows close supervision of progression of each participant to ensure the intervention is not 
overly effective and all women are gaining adequate body weight. If a woman gains or loses more than 5 
pounds over a two-week period, she will be contacted and her diet habits and fiber intake will be reviewed. 
Additionally, she will be asked if she is willing to provide her Obstetrician contact information and would like us 
to contact her Obstetrician. If so, a report will be sent to her Obstetrician. Infant growth will be charted and 
marked for review if crossing of two or more major percentile lines occurs. During pregnancy, maternal diet and 
body composition will be measured. A maternal DXA scan will be obtained at 2 weeks, 2 months, 6 months, 
and 12 months postpartum. Infant birth characteristics will be extracted from the electronic medical record. 
Infant body weight and body composition will be measured at 2 weeks, 2 months, 6 months, and 12 months 
using the Pea Pod. An infant DXA scan will be obtained at 2 weeks, 6 months, and 12 months. 
 
RISKS TO HUMAN SUBJECTS 
Human Subjects Involvement, Characteristics, and Design 
(1) Patient recruitment and informed consent. All recruitment, consent, and data forms for the study 
proposal will be approved prior to any enrollment. Informed consent for continued testing is obtained by 
a trained research team member with NIH-approved Human Subjects’ protection certification. Consent 
includes the standard elements: a study description, the potential risks, benefits and options for 
nonparticipation. All subjects are informed they are free to withdraw from the study without changes in 
their usual care. Consent is documented as a signed form and will be kept in a locked file at the study 
office. The study is conducted in accordance with ethical principles founded in the Declaration of 
Helsinki. The IRB review includes a review of all appropriate study documentation to safeguard the 
rights, safety and well-being of the subjects. The protocol, informed consent, written information given 
to the subjects, safety updates, annual progress reports, and any revisions to these documents are 
provided to the IRB by the principal investigators. The method of obtaining and documenting the 
informed consent and the contents of the consent will occur either in person or online and comply with 
GCP and all applicable regulatory requirement(s). 
(2) Describe the characteristics of the subject populations and identify criteria for inclusion and exclusion. 
Subjects will consist of pregnant women and their infants. Pregnant women will be consented for their 
participation and the participation of their infant in the study. Women will be between the ages 18-45 
years old; all racial/ethnic groups will be recruited between 9-19 weeks pregnant; can be first or greater 
pregnancy; BMI range: 18.5-45 kg/m2. If they are consuming 25 g/day of fiber or more, they will be 
excluded from the study. Women who do not have internet and phone access will be excluded from the 
study. Participants must be willing to consume provided snacks. Participants will also be excluded if 
they have history of gestational diabetes (GDM), diabetes, pre-eclampsia, hypertension, heart disease, 
hypothyroidism, or other metabolic abnormalities, current hyperemesis gravidarum, eating disorder, 
smoking, or are pregnant with multiples. Deviations from inclusion criteria will be at the discretion of the 
PI. Women that develop any of these medical conditions during pregnancy will be accounted for in the 
final analysis. This will be conducted at the University of Kansas Medical Center. We will recruit 56 
pregnant women who are between 9-19 weeks in gestation. These women will be patients from the 
University of Kansas OBGYN clinic. The race/ethnic breakdown of participants will be 12.5% Hispanic, 
30% Black, 40% White, 12.5% Asian and 5% classified as other. Following randomization and baseline 
testing, the intervention will begin and follow up measures will be acquired during pregnancy for 
outcome measures. 
(3) Identify the sources of research material to be obtained from subjects. In addition to data collected 
directly from participants infant birth characteristics (e.g., sex, gestational age at birth, birth weight, birth 
length, etc.) and health information up to 1 year of age and maternal delivery characteristics and 1 year 
pre- and post-partum health information will be extracted from the medical record. All participants will 
be assigned a nonidentifiable subject number. Data collected will be kept in Dr. Hull’s locked research 
laboratory. Only study personnel and Dr. Hull have keys to access this area. Electronic data will be kept 

19 
 
 
on a password protected computer in Dr. Hull's laboratory on the shared drive. Only personnel 
approved by HSC and on the protocol will have access to the data. 
(4) Describe all potential risks. No appreciable risk of physical, psychological, social, legal or other harm is 
expected. Blood will need to be drawn and may be associated with pain and the usual risks of blood 
letting. We are investigating between groups if differences are found for metabolic changes that occur 
during pregnancy. Many of the metabolic parameters we are exploring must be investigated in a fasted 
state or this would introduce error in the metabolic parameter (insulin, glucose, lipid panel, HbA1C, 
inflammatory markers). Measures will be collected at the CTSU Rainbow location and follow all safety 
protocols to ensure participant safety. In past protocols, we collect a fasting blood draw and took every 
precaution so that no harm comes to the mother or her baby. Women are instructed on the days 
leading up to their blood draw to drink plenty of water and to eat dinner and an evening snack if they 
are hungry the night before the blood draw. Appointments are scheduled first thing in the morning and 
we provide food and juice so that mothers eat immediately following the blood draw. We recorded no 
adverse events following this protocol. We have had no adverse events. All protocols are IRB approved 
and have undergone heavy scrutiny due to the special population we are working with.  The DXA does 
emit radiation. In the moms, In the infants, three total body DXA scans will be completed over 12 
months. The amount of radiation exposure for one DXA scan is equal to 0.001 mSV or the equivalent of 
exposure to 3 hours of natural background radiation. As a comparison, one chest x-ray is equal to 0.1 
mSV or 10 days of exposure to natural background radiation. Over the course of 12 months, the total 
radiation exposure will be under a day of background radiation exposure. This is minimal especially 
considered it is spread over 12 months.  
 
(5) Describe the procedures for protecting against or minimizing any potential risks. N/A. There are no 
known risks. 
(6) Discuss why the risks are reasonable in relation to anticipated benefits. N/A. No known risks. 
(7) Plan for monitoring and reporting problems. Adverse events will be assessed every 4 weeks during the 
dietary recalls during the 18-week intervention in the high-fiber group only. Baseline measurements will 
not be assessed for adverse events. Only adverse events related to gaining or losing too much weight 
or allergic reactions to the study food will be recorded. Research staff will immediately report any 
adverse events to the study PI for review. The study physician will review maternal and infant abnormal 
findings. If recommended by the study physician, abnormal findings will be communicated to the 
participant’s physicians or infant’s pediatrician.   
(8) Plan for handling study withdrawal/discontinuation. Participants may discontinue study participation at 
any time in the study. Participants will be asked to sign a withdrawal consent. If participant does not 
sign a withdrawal consent, only data collected prior to withdrawal will be used.  
 
Adequacy of Protection Against Risks 
Describe plans for the recruitment of subjects and the consent procedures to be followed. Recruitment will be 
open to all pregnant women that meet the study inclusion criteria. The KUMC IRB will review and approve this 
study prior to implementation. Recruitment will only be performed under the supervision of the PI by trained 
research personnel who have completed human subjects and HIPAA training. Personnel will identify subjects 
who might be eligible by screening their electronic medical record in O2. Only medical information related to 
inclusion/exclusion criteria will be looked at. If determined eligible, research personnel will visit the patient at 
their scheduled clinic visit. OBGYN clinic staff will introduce study to potential subjects. Research personnel 
will discuss the study in detail and determine final eligibility. Participants missed at their OBGYN visit will be 
contacted via phone. If participants are interested, they will be followed up with via phone or email to determine 
enrollment and complete the informed consent. Informed consent will be obtained via phone or in person at the 
first study visit.  
The women will be informed that the purpose of the study is to determine if a high fiber diet can help 
them gain the right amount of weight during pregnancy and that they will be placed in an intervention or control 
group. They will be told that if they participate in the study, regardless of their group assignment, that they will 
need to be seen two times during their pregnancy and four times after pregnancy. Further, they will be told if 
they are randomized to the intervention group they will be required to attend weekly video calls and report 
goals weekly to the study coordinator for 18 weeks. 
 

20 
 
 
Consent forms and HIPPA disclosure information per IRBs will be given to all subjects and their signatures 
witnessed. The consent forms will include a description of the study, nature of the data collection, the potential 
benefits and adverse reactions anticipated. Women will be assigned to group by random assignment provided 
by study statistician. The subjects will be told that their usual care would not be changed, 
withdrawn, or reduced if they chose to withdraw from the study at any time. The research team personnel will 
abide by all tenets of the University confidentiality policies, as well as the Privacy Protection for Research 
Subjects. All research staff will remain current in their NIH required Human Subjects protection and HIPAA 
certification. 
 
Case Report Forms on all women will include medical information pertinent to the study (e.g., smoking history, 
blood pressure, pregnancy history, age, race, etc.) in addition to the information directly related to the study 
(e.g., height, pre-pregnancy and clinic weights, blood pressure, EDD by ultrasound or LMP, etc.). To maintain 
patient privacy, all case report forms, study reports and communications will identify the patient by the 
assigned patient number only. The medical record and originals of outcome data will be the source documents 
for the study. Any changes to the case report forms necessitated because they at are odds with source 
documents will be initialed and dated by the Study Coordinators; and all Case Report Forms will be reviewed 
and approved by signature of the PI. Data monitors and auditors from the IRBs, and regulatory authorities will 
have access to the patient’s original medical records for verification of data gathered on the case report forms 
and to audit the data collection process. Subjects will be made aware of persons who may see their protected 
health information in the informed consent document and may choose not to enroll in the study based on the 
information provided them in accord with 2003 HIPAA regulations. The patient’s confidentiality will be 
maintained and will not be made publicly available to the extent permitted by the applicable laws and 
regulations. 
 
Data monitors and auditors from the IRBs, and regulatory authorities will have access to the patient’s original 
medical records for verification of data gathered on the case report forms and to audit the data collection 
process. Subjects will be made aware of persons who may see their protected health information in the 
informed consent document and may choose not to enroll in the study based on the information provided them 
in accord with 2003 HIPAA regulations. The patient’s confidentiality will be maintained and will not be made 
publicly available to the extent permitted by the applicable laws and regulations. 
 
The investigators will conduct the study in compliance with the protocol given approval by the KUMC IRB. Any 
changes to the protocol will require written approval from these committees prior to implementation, except 
when the modification is needed to eliminate an immediate hazard(s) to patients or if the change(s) involves 
only logistical or administrative aspects of the trial. Any departures from the protocol will be fully documented in 
the case report form and source documentation. IRB review occurs each year and newly dates consent forms 
are issued. The Research Assistant will keep the study binder that includes all communication with the IRB and 
CVs for all study personnel, and study personnel approved roles. The ultimate responsibility for ensuring that 
the study binders are in order will fall to the PI (Hull). 
 
Patient recruitment and informed consent. All recruitment, consent and data forms for the study proposal 
will be submitted to the KUMC IRB prior to enrollment using templates and educational materials formatted as 
previously IRB-approved in the pilot study. Informed consent will be obtained by trained research personnel 
who have completed the NIH-approved Human Subjects’ protection certification. Consent includes the 
standard elements: a study description, the potential risks, benefits and options for non-participation. All 
participants will be informed that they are free to withdraw from the study without changes in their usual care. 
Consent will be documented as a signed form and will be kept in a locked file at the study office. The study will 
be conducted in accordance with ethical principles founded in the Declaration of Helsinki. The IRB will review 
all appropriate study documentation to safeguard the rights, safety and well-being of the subjects. The 
protocol, informed consent, written information given to the subjects, safety updates, annual progress reports, 
and any revisions to these documents will be provided to the IRBs by the investigator. The method of obtaining 
and documenting the informed consent and the contents of the consent will comply with GCP and all 
applicable regulatory requirement(s). 
 

21 
 
 
Study personnel will identify subjects who might be eligible under a waiver issued by the IRB to look only at 
medical information related to inclusion/exclusion criteria for the study. No personal health information will be 
recorded until consent for the study is obtained in writing. 
 
Protection against risk. Although no appreciable risk of physical or mental harm is expected to result from 
the protocol, procedures for dealing with adverse effects are established. Subjects will be instructed to report 
immediately to the study coordinator if any health problem occurs and to call the PI (Hull) at any time if they 
have questions are concerns. In such an event, it is the PI responsibility to answer those concerns honestly 
and to reiterate to the subject that they should continue in the trial only if they feel entirely comfortable with it. 
Subjects who choose to withdraw from the study will be reassured if they indicate the desire to withdraw. 
 
Subjects will be protected against the risk of breaking confidentiality by decoupling of names from databases. 
Each participant will be assigned a numerical study ID and informed consent forms that include the subject’s 
signature will be stored separately in locked file cabinets. For ensuring confidentiality, these are generally 
acknowledged to be the best methods known for ensuring that names are not associated with data. Only 
selected research staff will have access to the subjects’ data. Subjects’ informed consent includes the HIPAA 
compliance documentation approved by the KUMC IRB. Research team personnel will abide by all tenets of 
the University confidentiality policies as well as the Privacy Protection for Research Subjects. 
 
Potential Benefits of Proposed Research 
Describe all potential benefits. There are no direct benefits for participation in the study outside of contributing 
to the knowledge and formulation towards interventions that are successful at helping women to achieve 
appropriate GWG. This study could contribute to ways to improve maternal and infant health outcomes of 
pregnant women by improving GWG by identifying novel methods that can be used to encourage appropriate 
GWG. 
 
Importance of Knowledge to be Gained 
We are targeting recruitment of pregnant women who have a pre-pregnancy BMI 18.5 – 45.0 kg/m2. We are 
specifically targeting women at high risk of excessive GWG during pregnancy. Data show 56% of women gain 
excessively3,4. Excessive gestational weight gain (GWG) is associated with poor outcomes. Based on our data, 
we anticipate the following distribution among the 3 pre-pregnancy weight categories selected (BMI <24.9 = 
40%; BMI 25-25.9 = 34%; BMI >30 = 26%). Due to the adverse health that is related to excessive GWG, it is 
imperative to seek interventions to prevent excessive GWG. 
Data Safety and Monitoring Plan 
Data security: All participants will be assigned a non-identifiable subject number. Data collected will be kept in 
Dr. Hull’s locked research laboratory. Only study personnel and Dr. Hull have keys to access this area. 
Electronic data will be kept on a password protected computer in Dr. Hull's laboratory on the shared drive. Only 
personnel approved by HSC and on the protocol will have access to the data. 
 
Data and safety monitoring plan: Monitoring will be handled by the PI and the research team.  
 
INCLUSION OF WOMEN, MINORITIES, AND CHILDREN 
 
Inclusion of Women: We are targeting pregnant women who have a pre-pregnancy BMI 18.5 – 45.0 kg/m2. We 
are specifically targeting women at high risk of excessive GWG during pregnancy and at high risk of retaining a 
significant amount of body weight postpartum. Data show 56% of women gain excessively3,4 and that 
excessive gestational weight gain (GWG) is associated with poor outcomes. 
 
Inclusion of Minorities: We are including all racial/ethnic groups in this study. There will be no exclusion criteria 
based on race or ethnicity. 
 
Inclusion of Children: The study will include offspring born to women participating in the study. 

22