Healthy Mom Zone: A Gestational Weight Gain Management Intervention (HMZ)

Control Systems Engineering for Optimizing a Prenatal Weight Gain Intervention

The purpose is to establish feasibility of delivering an individually-tailored, behavioral intervention to manage gestational weight gain [GWG] that adapts to the unique needs and challenges of overweight/obese pregnant women [OW/OBPW] and will utilize control systems engineering to optimize this intervention; in other words, make this intervention manage GWG in OW/OBPW as effectively and efficiently as possible.

Study Overview

• Status: Completed
• Conditions: Physical Activity; Overweight and Obesity; Eating Behavior; Weight Change, Body
• Intervention / Treatment: Behavioral: Intervention group; Behavioral: Control group

Detailed Description

The research proposed here will establish the dosage of components needed to impact GWG and develop an efficient (optimized) intervention to effectively manage GWG in OW/OBPW before a randomized controlled trial (RCT) can be implemented. The aims of the proposed research are: to establish feasibility of delivering an individually-tailored behavioral intervention for managing GWG in OW/OBPW. Two studies will be conducted to establish feasibility. Study 1 will examine viability of delivering dosages/sequencing of components (education, goal-setting, self-monitoring, HE/PA), GWG/HE/PA self-monitoring using e-health technology mechanisms, and data collection by delivering varied dosages to OW/OBPW over a brief, 4-week period followed by focus groups to evaluate user acceptability. The investigators will then make necessary revisions to the intervention. Study 2 will pilot test intervention delivery with decision rules for when/how to adapt dosages for an individual and randomization/retention/data collection procedures with treatment and control groups in a new cohort of OW/OBPW. Also, the investigators aim to use feasibility data collected from Aim 1 and control systems engineering to build a model that characterizes the effects of energy balance and planned/self-regulatory behaviors on GWG over time and use this model to develop an optimized intervention. The investigators will identify a dynamical model from feasibility data collected in Aim 1 that considers how changes in GWG responds to changes in energy intake, PA, and planned/self-regulatory behaviors. Model predictive control (a decision-making method from control systems engineering) will inform how the dosage adaptations are decided. The investigators will then identify a customized intervention plan for each woman based on her levels of energy intake, PA, planned/self-regulatory behaviors and the extent to which she is meeting GWG goals over pregnancy. This will lead to final program modifications and result in an individually-tailored, optimized intervention. The investigators will test the efficacy of this optimized intervention for managing GWG in OW/OBPW in a future RCT. This innovative research will develop an individually-tailored, optimized intervention that effectively and efficiently manages GWG in OW/OBPW and that will eventually be available to all pregnant women (via e-health technology) to improve the health of mothers and infants and impact the etiology of obesity and cardiovascular disease at a critical time in the life cycle.

• Study Type: Interventional
• Enrollment (Actual): 31
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Pennsylvania
    • University Park, Pennsylvania, United States, 16802
      • Noll Laboratory

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 40 years (Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Pregnant women
• Overweight or obese [body mass index range 24- >40 (if BMI (kg/m^2) is > 40, consultation with woman's health care provider (PCP/OBGYN) will be made to determine eligibility and ensure she does not have any contraindications to exercise) PI Danielle Downs will have communication with Dr. Hovick from MNPG to give information on the woman. The investigators also have a physician consent form (see Physician Patient Consent to Participate in documents) that the physician will complete as to whether the woman is eligible or not eligible to participate.
• Normal weight women with a BMI range of 18.0 to 23.9 can be enrolled in to the study as control participants (same measures of data collection, no opportunity for intervention).
• Ages 18-40 years [based on pilot data this group comprises >85% of the live births in Central Pennsylvania]
• 1st, 2nd or 3rd pregnancy 6-16 weeks gestation
• Able to read, understand, and speak English
• Residing in and around State College, PA
• 1st and 2nd time pregnant mothers [none or one other live or still born, biological children > 25 weeks gestation prior to this pregnancy; it may be conceivable that a woman has a blended family due to a mixed marriage and she will not be excluded if she is a parent to a guardian, foster child, or step child]
• Access to a computer or willingness to come onsite to complete study materials
• Infants born to participants who are 6-10 weeks old

Exclusion Criteria:

• Having more than one live or stillborn child > 25 weeks gestation; late-term pregnancy loss
• Diabetes at study entry [while future adaptations of this study will target women with diabetes, for the pilot study, they will be excluded to control for this confound]
• Contraindications to exercise in pregnancy [Hemodynamically significant heart disease, Restrictive lung disease, Incompetent cervix/cerclage, Persistent second [or third] trimester bleeding, Placenta previa after 26 weeks of gestation, Premature labor during the current pregnancy, Ruptured membranes, Preeclampsia/pregnancy-induced hypertension] per the ACOG guidelines [ACOG Committee on Obstetric Practice. [(2015, December). ACOG Committee opinion. Number 650: Physical Activity and Exercise During Pregnancy and the Postpartum Period. Obstetrics and Gynecology, 126,(6), 135-142].
• Having a body mass index less than 18 or over 40 (exclusion only if physician doesn't provide consent for BMI is over 40)
• Not planning to live in the area for the study duration
• Severe allergies or dietary restrictions that would preclude eating healthy foods
• Not able to read, understand, and/or speak English
• Cognitively impaired
• Currently smoking
• Infants not born to participants
• Infants younger than 6 weeks old

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Intervention group; Participants receive the allocated intervention to help manage gestational weight gain that includes education on weight regulation, healthy eating, physical activity, and goal setting.	Behavioral: Intervention group; During the intervention, all participants will start out at the Baseline level. The baseline level will last 2 weeks and there will be an assessment to determine weight gain over those 2 weeks. If weight gain has succeeded the recommended amount, participants will be adapted up to a new level of intervention that includes education on GWG, healthy eating and physical activity. After every 4 weeks, an assessment will be performed and adaptations up will be made if necessary. Adaptations include addition of exercise sessions, healthy eating recipe demonstrations, and meal replacements. Participants will weigh themselves daily, wear an activity monitor, record their diet, and complete paper and online surveys.
Active Comparator: Control group; Participants do not receive the allocated intervention but self-monitor their behaviors, complete study tasks and receive prenatal care as normal.	Behavioral: Control group; Participants will follow the same self-monitoring/assessment schedule but will not receive the GWG, healthy eating, and physical activity education or adaptations.; Other Names: Prenatal care as usual

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Gestational Weight Change	Gestational weight change will be measured daily at home using the FitBit Aria Wi-Fi Smart Scale (www.fitbit.com; weights will be wirelessly uploaded to online program). Gestational weight change will be standardized: target weight gain will be determined for each woman based on BMI (kg/m^2) status (OW = 15-25 lb, OB = 11-20 lb). For the criterion measure to determine when to adapt the intervention, weight gain will be calculated to determine if a woman is gaining < her goal (-), at the exact amount of her goal (0), or > her goal (+). Pre-pregnancy weight and gestational weight change from the first prenatal visit to the last pre-delivery weight will also be obtained from clinical records. Overweight/obese pregnant women (OW/OBPW) often exceed the GWG guidelines, managing weight gain in this population is critical. Participants weigh themselves daily using a WiFi connected scale. Outcome measure reported at mean change from pre- to post-intervention.	Daily data was collected starting at baseline (pre-intervention), through study completion Month 6 (post-intervention). Also measured daily for one week at 6-weeks postpartum. Outcome measure reported at mean change from pre- to post-intervention.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Theory of Planned Behavior (Motivational Determinants of Healthy Eating)	The Theory of Planned Behavior will inform our dynamical model in order to create individualized interventions for OW/OBPW. Beliefs: These items were developed to assess Theory of Planned Behavior (TPB) behavioral, control, and normative beliefs. Main Constructs: The Theory of Planned Behavior (TPB) Healthy Eating Main Constructs measure is a 38-item measure developed to assess the main constructs of the TPB (i.e., attitude, subjective norm (SN), perceived behavioral control (PBC), intention) as they relate to healthy eating behavior. Scoring for the TPB is the sum of each subscale. Attitude and Limit Attitude range of scores: 7-49 - higher score means greater/more positive attitude; SN and Limit SN range: 3-21 - higher score greater/more positive subjective norm; PBC and Limit PBC range: 3-21 - higher score greater/more positive PBC; Intention range: 6-42 - higher score greater/more positive intention. Results reported reflect mean changes from pre-intervention to post-intervention.	Data was collected each month starting at baseline (pre-intervention), through study completion at Month 6 (post-intervention). Pre-intervention, Month 1, Month 2, Month 3, Month 4, Month 5, Month 6, post-intervention.
Theory of Planned Behavior (Motivational Determinants of Physical Activity)	The Theory of Planned Behavior will inform our dynamical model in order to create individualized interventions for OW/OBPW. Beliefs: These items were developed to assess Theory of Planned Behavior (TPB) behavioral, control, and normative beliefs. Main Constructs: The Theory of Planned Behavior (TPB) Healthy Eating Main Constructs measure is a 38-item measure developed to assess the main constructs of the TPB (i.e., attitude, subjective norm (SN), perceived behavioral control (PBC), intention) as they relate to healthy eating behavior. Scoring for the TPB is the sum of each subscale. Attitude range of scores: 7-49 - higher score means greater/more positive attitude; SN range: 3-21 - higher score greater/more positive subjective norm; PBC range: 3-21 - higher score greater/more positive PBC; Intention range: 6-42 - higher score greater/more positive intention. Results reported reflect mean changes from pre-intervention to post-intervention.	Data was collected each month starting at baseline (pre-intervention), through study completion at post-intervention - Pre-intervention, Month 1, Month 2, Month 3, Month 4, Month 5, Month 6, post-intervention.
Self-regulation of Healthy Eating	Self-regulation of HE will be measured in order to inform our dynamical model and to how well OW/OBPW are at regulating their energy intake and expenditure and how it impacts their GWG. These items were taken from Ryan Rhodes items for self-regulation of PA and adapted for HE behaviors. Ryan has indicated that these items work really well as an index for HE self-regulation because these behaviors are naturally inter-connected but to look at specific self-regulatory behaviors: self-monitoring, goal-setting, action planning, coping planning, scheduling, affective There are also 2 sets of 8 questions-first 8 examine prospective behaviors while the second set assesses retrospective behaviors. Retrospective scores range from 11-55 and Prospective scores range from 11-55. Total scores range from 22-110. A higher score indicates higher levels of HE self-regulation. Results are mean difference of pre- and post-intervention week.	Data was collected bi-weekly starting at baseline (pre-intervention), through study completion at Month 6 (post-intervention). Pre-intervention week, week 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, and post-intervention week.
Self-regulation of Physical Activity	Self-regulation of PA will be measured in order to inform our dynamical model and to how well OW/OBPW are at regulating their energy intake and expenditure and how it impacts their GWG. These items are taken from Ryan Rhodes. Ryan has indicated that these items work really well as an index because these behaviors are naturally inter-connected but to look at specific self-regulatory behaviors: Item #1: self-monitoring, Item #2: goal-setting, Item # 3: action planning, Item #4: coping planning, Item #5: scheduling, Item #6, 7, 8, 9: cuing, Items 10 & 11: affective. There are also 2 sets of 8 questions-first 8 examine prospective behaviors while the second set assesses retrospective behaviors. Retrospective scores range from 11-55 and Prospective scores range from 11-55. Total scores for overall self-regulation range from 22-110. A higher score indicates higher levels of PA self-regulation. Results reported reflect mean changes from pre to post-intervention week.	Data was collected bi-weekly starting at baseline (pre-intervention), through study completion at Month 6 (post-intervention). Pre-intervention week, week 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, and post-intervention week.
Objective Activity Monitor UP Jawbone	Women will be wearing the UP Jawbone for the entire six week intervention. UP will track how the participants sleep, move and eat. Women will be wearing the UP Jawbone in counterbalance with the Actigraph wGt3X-BTI. The specific outcome measure used from the activity monitor is calories (kcals) burned during physical activity/exercise. Outcome measure reported at mean change from pre- to post-intervention.	Daily data was collected starting at pre-intervention, through study completion post-intervention. Daily for a total of 6 months. Outcome measure reported at mean change from pre- to post-intervention.
Energy Intake	Estimated energy intake (kcals) from physical activity (kcals) and weight (GWG). Outcome measure reported as mean change of energy intake calories from pre to post-intervention.	Daily energy intake was estimated starting at pre-intervention through post-intervention. Each day for 6 months. Outcome measure reported as mean change of energy intake calories from pre to post-intervention.
MyFitnessPal	MyFitness Pal: Web-based and smartphone app dietary intake tracker. Women tracked their diets every day for 6 months and every day for one week at their 6 week postpartum period. Energy intake or calories (kcal) consumed each day were measured. Outcome measure reported as mean change of energy intake calories from pre to post-intervention.	Data was collected 3 days a week, each week from pre-intervention through post-intervention. A total of 72 days over 6 months. Outcome measure reported as mean change of energy intake calories from pre-intervention week to post-intervention week.
Three Factor Eating Questionnaire	The Three Factor Eating Questionnaire is a 51-item questionnaire to measure three dimensions of human eating behavior: 1) dietary restraint, or cognitive control of eating behavior, 2) dietary disinhibition, or disinhibition of cognitive control of eating, and 3) susceptibility to hunger. The investigators are only using 18 items of the revised TFEQ. These items are known as TFEQ-R18 as reported in (de Lauzon et al., 2004). The TFEQ is examined by subscale scores and not by a total score. Subscale scores for the cognitive restraint scale range from 3-12; higher scores indicate higher levels of cognitive restraint of eating. Uncontrolled eating scale range from 9-36; higher scores indicate higher levels of uncontrolled eating behaviors. Emotional eating scale range from 6-24; higher scores indicate higher levels of emotional eating behaviors. Outcome measure results are reported as the score during the post-intervention week.	Data was collected monthly starting at pre-intervention, through post-intervention - Pre-intervention, Month 1, Month 2, Month 3, Month 4, Month 5, Month 6, post-intervention.
Leisure Time Exercise Questionnaire	The Leisure-Time Exercise Questionnaire (LTEQ) is a 3 item questionnaire to measure the amount and intensity of exercise a person engages in during a one week period. Reported scores are multiplied by 15 to get total min/week for each type and then adding those values together to total min of weekly exercise. Higher scores reflect more minutes of physical activity. Results reported reflect mean changes from pre- to post-intervention.	Data was collected monthly starting at pre-intervention, through post-intervention - Pre-intervention, Month 1, Month 2, Month 3, Month 4, Month 5, Month 6, post-intervention.
Pittsburgh Sleep Quality Index	Pittsburgh Sleep Quality Index: The Pittsburgh Sleep Quality Index (PSQI) is an 18-item measure developed by Smyth (2003) to measure the quality and patterns of sleep in older adults. It differentiates "poor" from "good" sleep by measuring seven areas: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication and daytime dysfunction over the last month. Scores can range from 0-21. An overall sleep quality score greater than or equal to 5 reflects poor sleep quality. The outcome reported is overall sleep quality. Results reported reflect mean at post-intervention.	Data was collected monthly starting at pre-intervention, through post-intervention - Pre-intervention, Month 1, Month 2, Month 3, Month 4, Month 5, Month 6, post-intervention.
Sleep Behaviors (Activity Monitor) - Nighttime Sleep Duration	UP Jawbone activity monitor: women wear the monitor during the night and measures sleep duration. This outcome reports mean nighttime sleep duration over the entire study duration.	Data was collected each day starting at pre-intervention, through post-intervention - a total of 6 months of daily data collection.
Fetal Measure: Ultrasounds [Fetal Growth]	Ultrasounds are conducted each month to measure fetal growth. Ultrasounds were completed for fetal growth measures as well to ensure adequate growth for those in the study. If there were any flags for growth restriction concerns, participant's physicians were alerted. These ultrasounds were used as safety checks and to ensure proper fetal growth. No group analyses were conducted nor were there any comparisons between groups. Data reported is the sum of all flagged ultrasounds over the study duration.	Each month - Month 1, Month 2, Month 3, Month 4, Month 5, and Month 6. Data reported is the sum of all flagged ultrasounds over the study duration.
Infant Birthweight	The infant's birth weight will be obtained through medical records or self-report from mother.	Assessed at time of birth - data abstracted at 6-week postpartum session.
Infant Length	The infant's birth length will be obtained through medical records or self-report from mother	Assessed at time of birth - data abstracted at 6-week postpartum session.
Resting Metabolic Rate	The Breezing Device: An indirect calorimetry analyzer that measures the rate of oxygen consumption and carbon dioxide production and determines how much energy the body is burning due to the metabolism of nutrients (named Resting Energy Expenditure, REE), and the type of nutrients the body uses to produce energy (Energy source = respiratory quotient, RQ). Developed at Arizona State University. The Breezing is a cellphone-size, battery operated, portable technology that syncs with smartphones. This tracker takes a traditional laboratory-based measurement and makes it faster, more affordable and mobile. Breezing has a 99.8% correlation with the gold standard method, Douglas Bag. Outcome measure is reported as an average over the entire study period.	Data was collected weekly from pre-intervention to post-intervention - Pre-intervention, week 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 ,15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, post-intervention.
Body Area Satisfaction Scale	The Body Area Satisfaction Scale (BASS) measure is a 9-item subscale originating from the Multidimensional Body-Self Relations Questionnaire (MBSRQ), which is a 69-item self-report inventory for the assessment of self-attitudinal aspects of the construct of body-image. The BASS assesses one's personal satisfaction with body parts such as arms, legs, and face in which participants rate their degree of body satisfaction with each specified body party from 1 (very dissatisfied) to 5 (very satisfied). The first 8 of the 9 items are added together for a total score. Scores range from 8-40. A higher score indicates higher body satisfaction. Outcome measure is reported as the score at post-intervention.	Data was collected monthly starting at pre-intervention, through study post-intervention - Pre-intervention, Month 1, Month 2, Month 3, Month 4, Month 5, Month 6, and post-intervention. Outcome measure is reported as the score at post-intervention.
Center for Epidemiological Studies Depression Scale	Center for Epidemiological Studies Depression Scale (CESD): Measures current levels of depressive symptomology. A cut off score of 16 is used to determine case status (depressed versus not depressed). A higher score (above 16) represents depressive symptomology. A total CES-D score can be calculated [Total CES-D Score = sum (items 1-20)]. Scores range from 0-60. Outcome reported is the mean scores at the post-intervention time period.	Data was collected monthly starting at pre-intervention, through study post-intervention - Pre-intervention, Month 1, Month 2, Month 3, Month 4, Month 5, Month 6, and post-intervention. Results are the mean scores at the post-intervention time period.
State-Trait Anxiety Inventory	The State-Trait Anxiety Inventory (STAI) is a 20-item questionnaire to measure state and trait anxiety. The State version of the STAI is being used for the current study. This scale consists of twenty items that evaluate how respondents feel "right now, at this moment." In responding to the STAI State-Anxiety scale, participants choose the response statement that best describes the intensity of their feelings: (1) not at all; (2) somewhat; (3) moderately so; (4) very much so. The state version of the STAI can also be used to evaluate how someone felt at a particular time in the recent past and how they anticipated to feel either in a specific situation that is likely to be encountered in the future or in a variety of hypothetical situations. Scores can range: 20-80. A total score is used to determine anxiety. A higher score indicates higher anxiety. Outcome reported is the mean scores at the post-intervention time period.	Data was collected monthly starting at pre-intervention through post-intervention: Pre-intervention, Month 1, Month 2, Month 3, Month 4, Month 5, Month 6, and Post-intervention. Results reported reflect mean scores at the post-intervention time period.
Perceived Stress Scale	The Perceived Stress Scale (PSS) is a 10-item scale developed by Cohen (1988) that measures the degree to which situations in one's life are appraised as stressful. The PSS was designed for use with community samples with at least a junior high-school education. The 14 items are easy to understand and the response alternatives (never, almost never, neutral, sometimes, fairly often, very often) are simple to grasp. The questions are quite general in nature and hence relatively free of content specific to any sub-population group. Scores range from 0-40. A higher score indicates higher levels of perceived stress.	Assessed weekly at pre-intervention week, week 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, and post-intervention. Post-intervention mean scores reported.
Sleep Behaviors (Activity Monitor) - Nighttime Awakenings	UP Jawbone activity monitor: women wear the monitor during the night. The monitor measures number of awakenings. This outcome reports mean nighttime awakenings per night over the entire study duration (pre- to post-intervention).	Data was collected each day starting at pre-intervention, through post-intervention - a total of 6 months of daily data collection.

Collaborators and Investigators

• Sponsor: Penn State University
• Collaborators: National Heart, Lung, and Blood Institute (NHLBI); Arizona State University
• Investigators: Principal Investigator: Danielle S Downs, Ph.D., The Pennsylvania State University

Publications and helpful links

General Publications

• Symons Downs D, Savage JS, Rivera DE, Smyth JM, Rolls BJ, Hohman EE, McNitt KM, Kunselman AR, Stetter C, Pauley AM, Leonard KS, Guo P. Individually Tailored, Adaptive Intervention to Manage Gestational Weight Gain: Protocol for a Randomized Controlled Trial in Women With Overweight and Obesity. JMIR Res Protoc. 2018 Jun 8;7(6):e150. doi: 10.2196/resprot.9220.
• Guo P, Rivera DE, Pauley AM, Leonard KS, Savage JS, Downs DS. A "Model-on-Demand" Methodology For Energy Intake Estimation to Improve Gestational Weight Control Interventions. Proc IFAC World Congress. 2018;51(15):144-149. doi: 10.1016/j.ifacol.2018.09.105. Epub 2018 Oct 8.
• Rauff EL, Downs DS. A Prospective Examination of Physical Activity Predictors in Pregnant Women with Normal Weight and Overweight/Obesity. Womens Health Issues. 2018 Nov-Dec;28(6):502-508. doi: 10.1016/j.whi.2018.09.003. Epub 2018 Oct 15.
• Rauff EL, Downs DS. Mobile Health Technology in Prenatal Care: Understanding OBGYN Providers' Beliefs about Using Technology to Manage Gestational Weight Gain. J Technol Behav Sci. 2019 Mar;4(1):17-24. doi: 10.1007/s41347-018-0068-0. Epub 2018 Aug 15.
• Pauley AM, Hohman E, Savage JS, Rivera DE, Guo P, Leonard KS, Symons Downs D. Gestational Weight Gain Intervention Impacts Determinants of Healthy Eating and Exercise in Overweight/Obese Pregnant Women. J Obes. 2018 Oct 1;2018:6469170. doi: 10.1155/2018/6469170. eCollection 2018.
• Guo P, Rivera DE, Savage JS, Hohman EE, Pauley AM, Leonard KS, Downs DS. System Identification Approaches For Energy Intake Estimation: Enhancing Interventions For Managing Gestational Weight Gain. IEEE Trans Control Syst Technol. 2020 Jan;28(1):63-78. doi: 10.1109/TCST.2018.2871871. Epub 2018 Oct 12.
• Freigoun MT, Rivera DE, Guo P, Hohman EE, Gernand AD, Downs DS, Savage JS. A Dynamical Systems Model of Intrauterine Fetal Growth. Math Comput Model Dyn Syst. 2018;24(6):661-687. doi: 10.1080/13873954.2018.1524387. Epub 2018 Oct 7.
• Guo P, Rivera DE, Savage JS, Downs DS. State Estimation Under Correlated Partial Measurement Losses: Implications for Weight Control Interventions. Proc IFAC World Congress. 2017 Jul;50(1):13532-13537. doi: 10.1016/j.ifacol.2017.08.2347. Epub 2017 Oct 18.
• Downs DS. Obesity in Special Populations: Pregnancy. Prim Care. 2016 Mar;43(1):109-20, ix. doi: 10.1016/j.pop.2015.09.003. Epub 2016 Jan 12.
• Devlin CA, Huberty J, Downs DS. Influences of prior miscarriage and weight status on perinatal psychological well-being, exercise motivation and behavior. Midwifery. 2016 Dec;43:29-36. doi: 10.1016/j.midw.2016.10.010. Epub 2016 Oct 29.
• Guo P, Rivera DE, Downs DS, Savage JS. Semi-physical Identification and State Estimation of Energy Intake for Interventions to Manage Gestational Weight Gain. Proc Am Control Conf. 2016 Jul;2016:1271-1276. doi: 10.1109/ACC.2016.7525092. Epub 2016 Aug 1.
• Downs DS, Devlin CA, Rhodes RE. The Power of Believing: Salient Belief Predictors of Exercise Behavior in Normal Weight, Overweight, and Obese Pregnant Women. J Phys Act Health. 2015 Aug;12(8):1168-76. doi: 10.1123/jpah.2014-0262. Epub 2014 Nov 19.
• Savage JS, Downs DS, Dong Y, Rivera DE. Control systems engineering for optimizing a prenatal weight gain intervention to regulate infant birth weight. Am J Public Health. 2014 Jul;104(7):1247-54. doi: 10.2105/AJPH.2014.301959. Epub 2014 May 15.
• Dong Y, Deshpande S, Rivera DE, Downs DS, Savage JS. Hybrid Model Predictive Control for Sequential Decision Policies in Adaptive Behavioral Interventions. Proc Am Control Conf. 2014 Jun;2014:4198-4203. doi: 10.1109/ACC.2014.6859462.
• Downs DS, Savage JS, Rauff EL. Falling Short of Guidelines? Nutrition and Weight Gain Knowledge in Pregnancy. J Womens Health Care. 2014;3:1000184. doi: 10.4172/2167-0420.1000184.
• Dong Y, Rivera DE, Downs DS, Savage JS, Thomas DM, Collins LM. Hybrid Model Predictive Control for Optimizing Gestational Weight Gain Behavioral Interventions. Proc Am Control Conf. 2013:1970-1975. doi: 10.1109/acc.2013.6580124.
• Dong Y, Rivera DE, Thomas DM, Navarro-Barrientos JE, Downs DS, Savage JS, Collins LM. A Dynamical Systems Model for Improving Gestational Weight Gain Behavioral Interventions. Proc Am Control Conf. 2012:4059-4064. doi: 10.1109/acc.2012.6315424.
• McNitt KM, Hohman EE, Rivera DE, Guo P, Pauley AM, Gernand AD, Symons Downs D, Savage JS. Underreporting of Energy Intake Increases over Pregnancy: An Intensive Longitudinal Study of Women with Overweight and Obesity. Nutrients. 2022 Jun 1;14(11):2326. doi: 10.3390/nu14112326.
• Rosinger AY, Bethancourt HJ, Pauley AM, Latona C, John J, Kelyman A, Leonard KS, Hohman EE, McNitt K, Gernand AD, Downs DS, Savage JS. Variation in urine osmolality throughout pregnancy: a longitudinal, randomized-control trial among women with overweight and obesity. Eur J Nutr. 2022 Feb;61(1):127-140. doi: 10.1007/s00394-021-02616-x. Epub 2021 Jul 3.
• Guo P, Rivera DE, Dong Y, Deshpande S, Savage JS, Hohman EE, Pauley AM, Leonard KS, Downs DS. Optimizing Behavioral Interventions to Regulate Gestational Weight Gain With Sequential Decision Policies Using Hybrid Model Predictive Control. Comput Chem Eng. 2022 Apr;160:107721. doi: 10.1016/j.compchemeng.2022.107721. Epub 2022 Feb 8.
• Leonard KS, Pauley AM, Hohman EE, Guo P, Rivera DE, Savage JS, Buman MP, Symons Downs D. Identifying ActiGraph non-wear time in pregnant women with overweight or obesity. J Sci Med Sport. 2020 Dec;23(12):1197-1201. doi: 10.1016/j.jsams.2020.08.003. Epub 2020 Aug 11.
• Ranghetti, L, Rivera, DE, Guo, P, Visioli, A, Savage Williams, J, Symons Downs, D. A control-based observer approach for estimating energy intake during pregnancy. Int J Robust Nonlinear Control. 2022; 1- 23. doi:10.1002/rnc.6019
• Savage JS, Hohman EE, McNitt KM, Pauley AM, Leonard KS, Turner T, Pauli JM, Gernand AD, Rivera DE, Symons Downs D. Uncontrolled Eating during Pregnancy Predicts Fetal Growth: The Healthy Mom Zone Trial. Nutrients. 2019 Apr 21;11(4):899. doi: 10.3390/nu11040899.
• Downs DS, Savage JS, Rivera DE, Pauley AM, Leonard KS, Hohman EE, Guo P, McNitt KM, Stetter C, Kunselman A. Adaptive, behavioral intervention impact on weight gain, physical activity, energy intake, and motivational determinants: results of a feasibility trial in pregnant women with overweight/obesity. J Behav Med. 2021 Oct;44(5):605-621. doi: 10.1007/s10865-021-00227-9. Epub 2021 May 5.
• Leonard KS, Symons Downs D. Low prenatal resting energy expenditure and high energy intake predict high gestational weight gain in pregnant women with overweight/obesity. Obes Res Clin Pract. 2022 Jul-Aug;16(4):281-287. doi: 10.1016/j.orcp.2022.07.003. Epub 2022 Jul 13.
• Pauley AM, Hohman EE, Leonard KS, Guo P, McNitt KM, Rivera DE, Savage JS, Downs DS. Short Nighttime Sleep Duration and High Number of Nighttime Awakenings Explain Increases in Gestational Weight Gain and Decreases in Physical Activity but Not Energy Intake among Pregnant Women with Overweight/Obesity. Clocks Sleep. 2020 Nov 14;2(4):487-501. doi: 10.3390/clockssleep2040036.

Helpful Links

• Youtube video describing the intervention

Study record dates

Study Major Dates

• Study Start (Actual): July 8, 2014
• Primary Completion (Actual): January 11, 2018
• Study Completion (Actual): March 30, 2018

Study Registration Dates

• First Submitted: May 6, 2019
• First Submitted That Met QC Criteria: May 7, 2019
• First Posted (Actual): May 10, 2019

Study Record Updates

• Last Update Posted (Actual): May 24, 2023
• Last Update Submitted That Met QC Criteria: April 25, 2023
• Last Verified: April 1, 2023

More Information

Terms related to this study

• Keywords: gestational weight gain; pregnancy weight regulation; individually tailored intervention
• Additional Relevant MeSH Terms: Overnutrition; Nutrition Disorders; Overweight; Body Weight; Body Weight Changes; Weight Gain; Gestational Weight Gain
• Other Study ID Numbers: 00003752; 5R01HL119245-05 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Data sharing plan per NIH guidelines per investigator user agreement and distribution agreement. Non-identified data, no hard-copy data can leave study site. Confidentiality agreements established.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ICF; ANALYTIC_CODE; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No