Individually Tailored, Adaptive Intervention to Manage Gestational Weight Gain: Protocol for a Randomized Controlled Trial in Women With Overweight and Obesity

Every sip counts: Understanding hydration behaviors and user-acceptability of digital tools to promote adequate intake during early and late pregnancy

Maintaining adequate hydration over the course of pregnancy is critical for maternal and fetal health and reducing risks for adverse pregnancy outcomes (e.g., preeclampsia, low placental and amniotic fluid volume). Recent evidence suggests that women may be at risk for under-hydration in the second and third trimesters when water needs begin to increase. Scant research has examined pregnant women's knowledge of hydration recommendations, water intake behaviors, and willingness to use digital tools to promote water intake. This study aimed to: 1) describe hydration recommendation knowledge and behaviors by the overall sample and early vs late pregnancy, and 2) identify habits and barriers of using digital tools. Pregnant women (N = 137; M age = 30.9 years; M gestational age = 20.9) completed a one-time, 45-minute online survey. Descriptive statistics quantified women's knowledge of hydration recommendations, behaviors, and attitudes about utilizing digital tools to promote adequate intake, and Mann-Whitney U and chi-squared tests were used to determine group differences. Most women lacked knowledge of and were not meeting hydration recommendations (63%, 67%, respectively) and were not tracking their fluid consumption (59%). Knowledge of hydration recommendations differed by time of pregnancy, such that women in later pregnancy reported 82 ounces compared to women in early pregnancy (49 ounces). Common barriers included: forgetting to drink (47%), not feeling thirsty (47%), and increased urination (33%). Most were willing to use digital tools (69%) and believed a smart water bottle would help them achieve daily fluid recommendations (67%). These initial findings suggest that pregnant women may benefit from useful strategies to increase knowledge, decrease barriers, and maintain adequate hydration, specifically earlier in pregnancy. These findings will inform the design of a behavioral intervention incorporating smart connected water bottles, wearables for gesture detection, and behavior modification strategies to overcome barriers, promote proper hydration and examine its impact on maternal and infant health outcomes.

Optimizing clinical nutrition research: the role of adaptive and pragmatic trials

Evidence-based nutritional recommendations address the health impact of suboptimal nutritional status. Efficacy randomized controlled trials (RCTs) have traditionally been the preferred method for determining the effects of nutritional interventions on health outcomes. Nevertheless, obtaining a holistic understanding of intervention efficacy and effectiveness in real-world settings is stymied by inherent constraints of efficacy RCTs. These limitations are further compounded by the complexity of nutritional interventions and the intricacies of the clinical context. Herein, we explore the advantages and limitations of alternative study designs (e.g., adaptive and pragmatic trials), which can be incorporated into RCTs to optimize the efficacy or effectiveness of interventions in clinical nutrition research. Efficacy RCTs often lack external validity due to their fixed design and restrictive eligibility criteria, leading to efficacy-effectiveness and evidence-practice gaps. Adaptive trials improve the evaluation of nutritional intervention efficacy through planned study modifications, such as recalculating sample sizes or discontinuing a study arm. Pragmatic trials are embedded within clinical practice or conducted in settings that resemble standard of care, enabling a more comprehensive assessment of intervention effectiveness. Pragmatic trials often rely on patient-oriented primary outcomes, acquire outcome data from electronic health records, and employ broader eligibility criteria. Consequently, adaptive and pragmatic trials facilitate the prompt implementation of evidence-based nutritional recommendations into clinical practice. Recognizing the limitations of efficacy RCTs and the potential advantages of alternative trial designs is essential for bridging efficacy-effectiveness and evidence-practice gaps. Ultimately, this awareness will lead to a greater number of patients benefiting from evidence-based nutritional recommendations.

App-Supported Lifestyle Interventions in Pregnancy to Manage Gestational Weight Gain and Prevent Gestational Diabetes: Scoping Review

BACKGROUND

Excessive gestational weight gain (GWG) and gestational diabetes mellitus (GDM) are common pregnancy complications that have been shown to be preventable through the use of lifestyle interventions. However, a significant gap exists between research on pregnancy lifestyle interventions and translation into clinical practice. App-supported interventions might aid in overcoming previous implementation barriers. The current status in this emerging research area is unknown.

OBJECTIVE

This scoping review aims to provide a comprehensive overview of planned, ongoing, and completed studies on eHealth and mobile health (mHealth) app-supported lifestyle interventions in pregnancy to manage GWG and prevent GDM. The review assesses the scope of the literature in the field; describes the population, intervention, control, outcomes, and study design (PICOS) characteristics of included studies as well as the findings on GWG and GDM outcomes; and examines app functionalities.

METHODS

The scoping review was conducted according to a preregistered protocol and followed established frameworks. Four electronic databases and 2 clinical trial registers were systematically searched. All randomized and quasi-randomized controlled trials (RCTs) of app-supported lifestyle interventions in pregnancy and related qualitative and quantitative research across the different study phases were considered for inclusion. Eligible studies and reports of studies were included until June 2022. Extracted data were compiled in descriptive analyses and reported in narrative, tabular, and graphical formats.

RESULTS

This review included 97 reports from 43 lifestyle intervention studies. The number of published reports has steadily increased in recent years; of the 97 included reports, 38 (39%) were trial register entries. Of the 39 identified RCTs, 10 efficacy or effectiveness trials and 8 pilot trials had published results on GWG (18/39, 46%); of these 18 trials, 7 (39%) trials observed significant intervention effects on GWG outcomes. Of all 39 RCTs, 5 (13%) efficacy or effectiveness trials reported GDM results, but none observed significant intervention effects on GDM. The RCTs included in the review were heterogeneous in terms of their PICOS characteristics. Most of the RCTs were conducted in high-income countries, included women with overweight or obesity and from all BMI categories, delivered multicomponent interventions, delivered interventions during pregnancy only, and focused on diet and physical activity. The apps used in the studies were mostly mHealth apps that included features for self-monitoring, feedback, goal setting, prompts, and educational content. Self-monitoring was often supported by wearable activity monitors and Bluetooth-connected weight scales.

CONCLUSIONS

Research in this field is nascent, and the effectiveness and implementability of app-supported interventions have yet to be determined. The complexity and heterogeneity of intervention approaches pose challenges in identifying the most beneficial app features and intervention components and call for consistent and comprehensive intervention and outcome reporting.

A control-based observer approach for estimating energy intake during pregnancy

Gestational weight gain outside of Institute of Medicine guidelines poses a risk to both the mother and her unborn child. Behavioral interventions such as Healthy Mom Zone (HMZ) that aim to regulate gestational weight gain require self-monitoring of energy intake, which is often significantly under-reported by participants. This paper describes the use of a control systems approach for energy intake estimation during pregnancy. It relies on an energy balance model that predicts gestational weight based on physical activity and energy intake, the latter treated as an unmeasured disturbance. Two control-based observer formulations relying on Internal Model Control and Model Predictive Control, respectively, are presented in this paper, first for a hypothetical participant, then on data collected from four HMZ participants. Results demonstrate the effectiveness of the method, with generally best results obtained when estimating energy intake over a weekly time period.

Process evaluation methods and results from the Health in Pregnancy and Postpartum (HIPP) randomized controlled trial

Background

Excessive gestational weight gain has increased over time and is resistant to intervention, especially in women living with overweight or obesity. This study described the process evaluation methods and findings from a behavioral lifestyle intervention for African American and white women living with overweight and obesity that spanned pregnancy (≤ 16 weeks gestation) through 6 months postpartum.

Methods

The Health in Pregnancy and Postpartum (HIPP) study tested a theory-based behavioral intervention (vs. standard care) to help women (N = 219; 44% African American, 29.1 ± 4.8 years) living with overweight or obesity meet weight gain guidelines in pregnancy and lose weight in postpartum. Participants completed process evaluation surveys at 32 weeks gestation (n = 183) and 6 months postpartum (n = 168) regarding their perceptions of most and least helpful aspects of the intervention. A database tracked delivery and receipt of intervention components (in-depth counseling session, telephone calls, podcasts). Descriptive statistics are used to report fidelity, dose, and participants’ perceptions. We also tested whether dose of behavioral intervention components was associated with gestational weight gain and 6-month postpartum weight retention with linear regression models controlling for baseline age and gestational weeks, receipt of Medicaid, race, parity, and marital status. A content analysis was used to code and analyze responses to open-ended survey questions.

Results

Over 90% of participants (both groups) would recommend the program to a friend. Implementation fidelity was moderately high and greater in pregnancy than postpartum for all intervention components. Dose received and participants’ ratings of the in-depth counseling session and telephone calls were more favorable than podcasts. The Facebook group was not perceived to be very helpful, likely because of low participant interaction. Although podcasts were created to reinforce call topics, this redundancy was viewed negatively by some. More calls completed and more podcasts downloaded related to lower gestational weight gain (p < .05).

Conclusion

Study findings underscore challenges in engaging this important but busy population, especially during the postpartum period.

Trial registration:

The study was registered at clinicaltrials.gov (NCT02260518) on 10/09/2014. https://clinicaltrials.gov/ct2/show/NCT02260518.

Low prenatal resting energy expenditure and high energy intake predict high gestational weight gain in pregnant women with overweight/obesity

INTRODUCTION

Recent evidence suggests that low resting energy expenditure (REE) is associated with gestational weight gain (GWG). However, little research has examined whether REE explains GWG beyond the contributions of energy intake (EI) and physical activity (PA). This study examined the extent to which EI, PA, and REE were associated with and explained second trimester GWG in pregnant women with overweight/obesity.

METHODS

Pregnant women with overweight/obesity (N = 26) participating in the Healthy Mom Zone study, a theoretically-based behavioral intervention that adapted the intervention dosage over time to regulate GWG completed weekly point estimates of EI (back-calculation), PA (wrist-worn activity monitor), and REE (mobile metabolism device) from 14- to 28-weeks gestation. Second trimester GWG was calculated as the weekly point estimate of weight from a Wi-Fi weight scale at gestational week 28 minus the weekly point estimate of weight at gestational week 14.

RESULTS

Partial correlations revealed second trimester EI and PA were not significantly associated with second trimester GWG, but low second trimester REE was significantly associated with high second trimester GWG. Hierarchical regression analyses showed the model of fat-free mass, EI, PA, and REE explained 56% of the variance in second trimester GWG. Low REE was the strongest determinant followed by high EI; fat-free mass and PA were not significant predictors.

CONCLUSIONS

While EI and PA remain important determinants of GWG, future researchers should explore the role of REE to inform individualized EI and PA goals to better regulate GWG.

Encouraging appropriate gestational weight gain in high-risk gravida: A randomized controlled trial

Trial Design

Excessive gestational weight gain (GWG) can increase pregnancy morbidity and is particularly problematic for women with pregestational obesity. A lifestyle modification intervention was introduced to gravida with obesity to decrease excessive GWG as compared to usual care (UC).

Methods

A randomized controlled trial was conducted to improve healthy lifestyle behaviors to manage appropriate GWG. Consenting participants with prepregnancy obesity and singletons ≤17 weeks were randomized to (1) Usual Care (UC): usual written educational materials and counseling by obstetric provider or (2) Enhanced Care (EC): UC plus (a) personalized letter from physician detailing appropriate GWG; (b) access to individualized GWG chart; (c) ongoing counseling with registered dietitian/nutritionist (RDN). The primary outcome was proportion with GWG ≤9.1 kg, as this is upper limit recommended by Institute of Medicine (IOM). Total GWG and GWG as less than/within/greater than IOM recommendations (in aggregate and stratified by obesity class), and pregnancy/neonatal outcomes were evaluated as secondary outcomes.

Results

Analyses included 105 participants in EC and 109 in UC arms. The groups had similar demographics: 46% with class I obesity, 26% class II, and 28% class III. There were no group differences for any GWG, pregnancy, or neonatal outcomes when analyzed in aggregate. As compared to those randomized to the EC arm, participants in UC arm with class I obesity gained 1.4 kg less and those with class II obesity were significantly more likely to gain within IOM guidelines (14.8% vs. 40.0%, adjusted p = 0.04). Participants with class III obesity randomized to EC arm were more likely to gain within IOM guidelines as compared to participants randomized to UC arm (29.0% vs. 6.7%, adjusted p = 0.02).

Conclusion

There were no differences in GWG observed between groups when analyzing participants in aggregate. However, a physician's letter detailing appropriate GWG, patient portal access to a personalized GWG chart, and RDN consultation were helpful for encouraging GWG within IOM guidelines for women with prepregnancy class III obesity. Women with class I or II obesity had better GWG outcomes without these additional interventions.

Underreporting of Energy Intake Increases over Pregnancy: An Intensive Longitudinal Study of Women with Overweight and Obesity

(1) Background: Energy intake (EI) underreporting is a widespread problem of great relevance to public health, yet is poorly described among pregnant women. This study aimed to describe and predict error in self-reported EI across pregnancy among women with overweight or obesity. (2) Methods: Participants were from the Healthy Mom Zone study, an adaptive intervention to regulate gestational weight gain (GWG) tested in a feasibility RCT and followed women (n = 21) with body mass index (BMI) ≥25 from 8−12 weeks to ~36 weeks gestation. Mobile health technology was used to measure daily weight (Wi-Fi Smart Scale), physical activity (activity monitor), and self-reported EI (MyFitnessPal App). Estimated EI was back-calculated daily from measured weight and physical activity data. Associations between underreporting and gestational age, demographics, pre-pregnancy BMI, GWG, perceived stress, and eating behaviors were tested. (3) Results: On average, women were 30.7 years old and primiparous (62%); reporting error was −38% ± 26 (range: −134% (underreporting) to 97% (overreporting)), representing an ~1134 kcal daily underestimation of EI (1404 observations). Estimated (back-calculated), but not self-reported, EI increased across gestation (p < 0.0001). Higher pre-pregnancy BMI (p = 0.01) and weekly GWG (p = 0.0007) was associated with greater underreporting. Underreporting was lower when participants reported higher stress (p = 0.02) and emotional eating (p < 0.0001) compared with their own average. (4) Conclusions: These findings suggest systemic underreporting in pregnant women with elevated BMI using a popular mobile app to monitor diet. Advances in technology that allow estimation of EI from weight and physical activity data may provide more accurate dietary self-monitoring during pregnancy.

Optimizing behavioral interventions to regulate gestational weight gain with sequential decision policies using hybrid model predictive control

Excessive gestational weight gain is a significant public health concern that has been the recent focus of control systems-based interventions. Healthy Mom Zone (HMZ) is an intervention study that aims to develop and validate an individually-tailored and "intensively adaptive" intervention to manage weight gain for pregnant women with overweight or obesity using control engineering approaches. This paper presents how Hybrid Model Predictive Control (HMPC) can be used to assign intervention dosages and consequently generate a prescribed intervention with dosages unique to each individuals needs. A Mixed Logical Dynamical (MLD) model enforces the requirements for categorical (discrete-level) doses of intervention components and their sequential assignment into mixed-integer linear constraints. A comprehensive system model that integrates energy balance and behavior change theory, using data from one HMZ participant, is used to illustrate the workings of the HMPC-based control system for the HMZ intervention. Simulations demonstrate the utility of HMPC as a means for enabling optimized complex interventions in behavioral medicine, and the benefits of a HMPC framework in contrast to conventional interventions relying on "IF-THEN" decision rules.

Variation in urine osmolality throughout pregnancy: a longitudinal, randomized-control trial among women with overweight and obesity

PURPOSE

Water needs increase during pregnancy, and proper hydration is critical for maternal and fetal health. This study characterized weekly hydration status changes throughout pregnancy and examined change in response to a randomized, behavioral intervention. An exploratory analysis tested how underhydration during pregnancy was associated with birth outcomes.

METHODS

The Healthy Mom Zone Study is a longitudinal, randomized-control trial intervention aiming to regulate gestational weight gain (GWG) in pregnant women with overweight/obesity (n = 27). Fourteen women received standard of care; 13 women additionally received weekly guidance on nutrition, physical activity, water intake, and health-promoting behaviors. Hydration status was measured weekly via overnight urine osmolality (Uosm) from ~ 8-36 weeks gestation; underhydration was dichotomized (Uosm ≥ 500 mOsm/kg). Gestational age- and sex-standardized birth weight and length z scores and percentiles were calculated. We used mixed-effect and linear regression models to test covariate-adjusted relationships.

RESULTS

No differences existed in Uosm or other characteristics between control and intervention women at baseline. Significant interactions (p = 0.01) between intervention and week of pregnancy on Uosm indicated intervention women maintained lower Uosm, whereas control women had a significant quadratic (inverse-U) relationship and greater Uosm in the second and early third trimesters. Results were consistent across robustness and sensitivity checks. Exploratory analyses suggest underhydration was associated with birth weight, but not length, in opposite ways in the second vs. third trimester.

CONCLUSION

A multi-component behavioral intervention helped women with overweight/obesity maintain better hydration throughout pregnancy. Future studies should confirm birth outcome results as they have important implications for early life nutrition.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03945266; registered May 10, 2019 retrospectively.

Urinary cortisol is lower in pregnant women with higher pre-pregnancy BMI

BACKGROUND/OBJECTIVES

Although cortisol levels increase during normal pregnancy, particularly high levels of cortisol or stress have been associated with adverse maternal/child outcomes. Obesity is associated with altered cortisol metabolism, but there is limited information on pregnancy-related changes in cortisol in pregnant women with overweight/obesity. The objective of this study was to examine weekly measures of urinary cortisol and perceived stress throughout ~10-36 weeks gestation, if levels differ by pre-pregnancy BMI categories, and whether concurrent measures of urinary cortisol and perceived stress are associated.

METHODS

Longitudinal observational data from Healthy Mom Zone, a gestational weight management intervention, and an ancillary fetal growth study were combined. Pregnant women with normal (n=7), overweight (n=11), or obese (n=14) pre-pregnancy BMI were recruited at >8 weeks gestation. Overnight urinary cortisol and Perceived Stress Scale were measured weekly from ~10-36 weeks gestation.

RESULTS

Higher pre-pregnancy BMI was associated with overall lower urinary cortisol throughout gestation, but rate of increase in urinary cortisol across pregnancy was similar across weight status groups. Women with obesity reported higher levels of overall perceived stress than normal weight women. Regardless of weight status, perceived stress was not associated with gestational age or cortisol.

CONCLUSIONS

Although women with obesity reported higher perceived stress, they had lower urinary cortisol than women with normal BMI, and gestation-related increases in cortisol were similar across weight groups and unrelated to perceived stress, suggesting that physiological factors that drive increases in cortisol as pregnancy may outweigh effects of stress and adiposity.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT03945266, identifier (NCT03945266).

Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review

BACKGROUND

Traditional psychological theories are inadequate to fully leverage the potential of smartphones and improve the effectiveness of physical activity (PA) and sedentary behavior (SB) change interventions. Future interventions need to consider dynamic models taken from other disciplines, such as engineering (eg, control systems). The extent to which such dynamic models have been incorporated in the development of interventions for PA and SB remains unclear.

OBJECTIVE

This review aims to quantify the number of studies that have used dynamic models to develop smartphone-based interventions to promote PA and reduce SB, describe their features, and evaluate their effectiveness where possible.

METHODS

Databases including PubMed, PsycINFO, IEEE Xplore, Cochrane, and Scopus were searched from inception to May 15, 2019, using terms related to mobile health, dynamic models, SB, and PA. The included studies involved the following: PA or SB interventions involving human adults; either developed or evaluated integrated psychological theory with dynamic theories; used smartphones for the intervention delivery; the interventions were adaptive or just-in-time adaptive; included randomized controlled trials (RCTs), pilot RCTs, quasi-experimental, and pre-post study designs; and were published from 2000 onward. Outcomes included general characteristics, dynamic models, theory or construct integration, and measured SB and PA behaviors. Data were synthesized narratively. There was limited scope for meta-analysis because of the variability in the study results.

RESULTS

A total of 1087 publications were screened, with 11 publications describing 8 studies included in the review. All studies targeted PA; 4 also included SB. Social cognitive theory was the major psychological theory upon which the studies were based. Behavioral intervention technology, control systems, computational agent model, exploit-explore strategy, behavioral analytic algorithm, and dynamic decision network were the dynamic models used in the included studies. The effectiveness of quasi-experimental studies involved reduced SB (1 study; P=.08), increased light PA (1 study; P=.002), walking steps (2 studies; P=.06 and P<.001), walking time (1 study; P=.02), moderate-to-vigorous PA (2 studies; P=.08 and P=.81), and nonwalking exercise time (1 study; P=.31). RCT studies showed increased walking steps (1 study; P=.003) and walking time (1 study; P=.06). To measure activity, 5 studies used built-in smartphone sensors (ie, accelerometers), 3 of which used the phone's GPS, and 3 studies used wearable activity trackers.

CONCLUSIONS

To our knowledge, this is the first systematic review to report on smartphone-based studies to reduce SB and promote PA with a focus on integrated dynamic models. These findings highlight the scarcity of dynamic model-based smartphone studies to reduce SB or promote PA. The limited number of studies that incorporate these models shows promising findings. Future research is required to assess the effectiveness of dynamic models in promoting PA and reducing SB.

TRIAL REGISTRATION

International Prospective Register of Systematic Reviews (PROSPERO) CRD42020139350; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=139350.

Low Resting Energy Expenditure Is Associated with High Gestational Weight Gain Only When Resting Energy Expenditure Fluctuates

Resting energy expenditure (REE) may be useful for individualizing energy intake (EI) and physical activity (PA) goals, and in turn, regulating gestational weight gain (GWG). Limited research, however, has examined the association between REE and GWG. This study examined (1) change in REE from 14 to 28 gestation, (2) time-varying associations between REE and GWG, and (3) EI and PA patterns during the weeks when REE and GWG were significantly associated. Pregnant women with overweight/obesity (N = 27) participating in the Healthy Mom Zone study completed weekly point estimates of EI (back-calculation), PA (wrist-worn activity monitor), REE (mobile metabolism device), and weight (Wi-Fi scale) from 14 to 28 weeks gestation. Analyses included descriptives and time-varying effect modeling. REE fluctuated, increasing on average from 14 to 28 weeks gestation, but decreased at gestational weeks 17, 20, 21, 23, 26, and 28. Most women increased in REE; however there was large between-person variability in the amount of change. Associations between REE and GWG were small but time-varying; low REE was associated with high GWG between gestational weeks 25 to 28 when there was observably larger fluctuation in REE. Moreover, over half of the women were categorized as having excessive EI and most as low active during this time. EI needs may be overestimated and PA needs may be underestimated when REE is fluctuating, which may increase the risk for high second trimester GWG. Researchers should consider the role of REE to inform EI and PA goals to regulate GWG.

A Review of the Clinician's Role in Women's Weight Management and Implications for Women's Health and Pregnancy Outcomes

Importance

Ten years have passed since the Institute of Medicine (IOM) released its recommendations for gestational weight gain (GWG), based on a woman's prepregnancy body mass index. Despite this, the majority of women do not gain the appropriate gestational weight; most women gain too much weight, and a small but substantial number gain too little.

Objective

We review the literature concerning GWG, the opinions and practices of clinicians in managing their patients' weight, and how these practices are perceived by patients. We also review several randomized control trials that investigate the efficacy of clinical intervention in managing GWG.

Evidence Acquisition

A literature review search was conducted with no limitations on the number of years searched.

Results

The number of clinicians who are aware of and use the IOM recommendations has increased, but the prevalence of inappropriate GWG has not decreased. Clinicians report feeling less than confident in their ability to have an impact on their patients' weight gain, and there are discrepancies between what clinicians and patients report regarding counseling. Many randomized control trials demonstrate a beneficial impact of clinical intervention, highlighting the importance of collaboration and technology to provide educational information and support throughout a pregnancy.

Conclusions

Pregnancy provides an opportunity for clinicians to have open and direct conversations with their patients about their weight. Providing clinicians with the tools, skillset, and confidence to assist in the management of GWG is essential to the health of women and their children, and warrants further investigation.

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

Interventions have modest impact on reducing excessive gestational weight gain (GWG) in pregnant women with overweight/obesity. This two-arm feasibility randomized control trial tested delivery of and compliance with an intervention using adapted dosages to regulate GWG, and examined pre-post change in GWG and secondary outcomes (physical activity: PA, energy intake: EI, theories of planned behavior/self-regulation constructs) compared to a usual care group. Pregnant women with overweight/obesity (N = 31) were randomized to a usual care control group or usual care + intervention group from 8 to 2 weeks gestation and completed the intervention through 36 weeks gestation. Intervention women received weekly evidence-based education/counseling (e.g., GWG, PA, EI) delivered by a registered dietitian in a 60-min face-to-face session. GWG was monitored weekly; women within weight goals continued with education while women exceeding goals received more intensive dosages (e.g., additional hands-on EI/PA sessions). All participants used mHealth tools to complete daily measures of weight (Wi-Fi scale) and PA (activity monitor), weekly evaluation of diet quality (MyFitnessPal app), and weekly/monthly online surveys of motivational determinants/self-regulation. Daily EI was estimated with a validated back-calculation method as a function of maternal weight, PA, and resting metabolic rate. Sixty-five percent of eligible women were randomized; study completion was 87%; 10% partially completed the study and drop-out was 3%. Compliance with using the mHealth tools for intensive data collection ranged from 77 to 97%; intervention women attended > 90% education/counseling sessions, and 68-93% dosage step-up sessions. The intervention group (6.9 kg) had 21% lower GWG than controls (8.8 kg) although this difference was not significant. Exploratory analyses also showed the intervention group had significantly lower EI kcals at post-intervention than controls. A theoretical, adaptive intervention with varied dosages to regulate GWG is feasible to deliver to pregnant women with overweight/obesity.

Associations between lifestyle interventions during pregnancy and childhood weight and growth: a systematic review and meta-analysis

BACKGROUND

Maternal health and lifestyle during pregnancy may be critical for the onset and progression of childhood obesity. Prenatal lifestyle interventions have been shown to positively affect maternal behaviors, gestational weight gain, and anthropometric outcomes in infants at birth. The influence of such interventions on child weight or growth beyond birth is unknown. We therefore examined the association between lifestyle interventions during pregnancy and anthropometric outcomes during childhood.

METHODS

A systematic literature search was conducted in three electronic databases, two clinical trial registers and further sources, without language or publication status restrictions. Additionally, 110 study authors were contacted to obtain unpublished data. Randomized controlled trials comparing any antenatal lifestyle or behavioral intervention to standard prenatal care, in women of any body mass index (BMI), with offspring anthropometric data at 1 month of age or older, were considered. Two reviewers independently extracted data and assessed the risk of bias using the Cochrane Collaboration's updated tool. Data on weight, length, and BMI, and corresponding z-scores, were stratified into six age ranges and weighted mean differences (WMD) with 95% confidence intervals (CI) were calculated in univariate and multivariate random-effects meta-analytical models.

RESULTS

Twenty trials comprising 11,385 women were included in this systematic review, of which 19 were combined in meta-analyses. Overall, lifestyle interventions during pregnancy were not associated with differences in weight, length, BMI, or corresponding z-scores, in children aged 1 month to 7 years (e.g. weight in 5 to 6 month old children, WMD: 0.02 kg; 95% CI: - 0.05 to 0.10 kg, I2 = 38%; 13 studies, 6667 participants). Findings remained consistent when studies were stratified by maternal baseline BMI or other risk factors, and intervention content and duration. Based on the GRADE criteria, the strength of the body of evidence was considered moderate.

CONCLUSION

Prenatal lifestyle interventions were not shown to influence childhood weight or growth. Nevertheless, women should be encouraged to pursue a healthy lifestyle during pregnancy. Further efforts to establish early prevention strategies for childhood obesity are urgently needed. Thus, large, high-quality studies with pre-planned, long-term follow-ups are warranted.

TRIAL REGISTRATION

PROSPERO CRD42018118678 .

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

Pregnant women are at a high risk for experiencing sleep disturbances, excess energy intake, low physical activity, and excessive gestational weight gain (GWG). Scant research has examined how sleep behaviors influence energy intake, physical activity, and GWG over the course of pregnancy. This study conducted secondary analyses from the Healthy Mom Zone Study to examine between- and within-person effects of weekly sleep behaviors on energy intake, physical activity, and GWG in pregnant women with overweight/obesity (PW-OW/OB) participating in an adaptive intervention to manage GWG. The overall sample of N = 24 (M age = 30.6 years, SD = 3.2) had an average nighttime sleep duration of 7.2 h/night. In the total sample, there was a significant between-person effect of nighttime awakenings on physical activity; women with >1 weekly nighttime awakening expended 167.56 less physical activity kcals than women with <1 nighttime awakening. A significant within-person effect was also found for GWG such that for every increase in one weekly nighttime awakening there was a 0.76 pound increase in GWG. There was also a significant within-person effect for study group assignment; study group appeared to moderate the effect of nighttime awakenings on GWG such that for every one increase in weekly nighttime awakening, the control group gained 0.20 pounds more than the intervention group. There were no significant between- or within-person effects of sleep behaviors on energy intake. These findings illustrate an important need to consider the influence of sleep behaviors on prenatal physical activity and GWG in PW-OW/OB. Future studies may consider intervention strategies to reduce prenatal nighttime awakenings.

Identifying ActiGraph non-wear time in pregnant women with overweight or obesity

OBJECTIVES

Non-wear time algorithms have not been validated in pregnant women with overweight/obesity (PW-OW/OB), potentially leading to misclassification of sedentary/activity data, and inaccurate estimates of how physical activity is associated with pregnancy outcomes. We examined: (1) validity/reliability of non-wear time algorithms in PW-OW/OB by comparing wear time from five algorithms to a self-report criterion and (2) whether these algorithms over- or underestimated sedentary behaviors.

DESIGN

PW-OW/OB (N = 19) from the Healthy Mom Zone randomized controlled trial wore an ActiGraph GT3x + for 7 consecutive days between 8-12 weeks gestation.

METHODS

Non-wear algorithms (i.e., consecutive strings of zero acceleration in 60-second epochs) were tested at 60, 90, 120, 150, and 180-min. The monitor registered sedentary minutes as activity counts 0-99. Women completed daily self-report logs to report wear time.

RESULTS

Intraclass correlation coefficients for each algorithm were 0.96-0.97; Bland-Altman plots revealed no bias; mean absolute percent errors were <10%. Compared to self-report (M = 829.5, SD = 62.1), equivalency testing revealed algorithm wear times (min/day) were equivalent: 60- (M = 816.4, SD = 58.4), 90- (M = 827.5, SD = 61.4), 120- (M = 830.8, SD = 65.2), 150- (M = 833.8, SD = 64.6) and 180-min (M = 837.4, SD = 65.4). Repeated measures ANOVA showed 60- and 90-min algorithms may underestimate sedentary minutes compared to 150- and 180-min algorithms.

CONCLUSIONS

The 60, 90, 120, 150, and 180-min algorithms are valid and reliable for estimating wear time in PW-OW/OB. However, implementing algorithms with a higher threshold for consecutive zero counts (i.e., ≥150-min) can avoid the risk of misclassifying sedentary data.

System Identification Approaches For Energy Intake Estimation: Enhancing Interventions For Managing Gestational Weight Gain

Excessive maternal weight gain during pregnancy represents a major public health concern that calls for novel and effective gestational weight management interventions. In Healthy Mom Zone (HMZ), an on-going intervention study, energy intake underreporting has been found to be an important consideration that interferes with accurate weight control assessment, and the effective use of energy balance models in an intervention setting. In this paper, a series of estimation approaches that address measurement noise and measurement losses are developed to better understand the extent of energy intake underreporting. These include back-calculating energy intake from an energy balance model developed for gestational weight gain prediction, a Kalman filtering-based approach to recursively estimate energy intake from intermittent measurements in real-time, and an approach based on semi-physical identification principles which features the capability of adjusting future self-reported energy intake by parameterizing the extent of underreporting. The three approaches are illustrated by evaluating with participant data obtained through the HMZ intervention study, with the results demonstrating the potential of these methods to promote the success of weight control. The pros and cons of the presented approaches are discussed to generate insights for users in future applications.

Uncontrolled Eating during Pregnancy Predicts Fetal Growth: The Healthy Mom Zone Trial

Excess maternal weight gain during pregnancy elevates infants' risk for macrosomia and early-onset obesity. Eating behavior is also related to weight gain, but the relationship to fetal growth is unclear. We examined whether Healthy Mom Zone, an individually tailored, adaptive gestational weight gain intervention, and maternal eating behaviors affected fetal growth in pregnant women (n = 27) with a BMI > 24. At study enrollment (6-13 weeks gestation) and monthly thereafter, the Three-Factor Eating Questionnaire was completed. Ultrasounds were obtained monthly from 14-34 weeks gestation. Data were analyzed using multilevel modeling. Higher baseline levels of uncontrolled eating predicted faster rates of fetal growth in late gestation. Cognitive restraint was not associated with fetal growth, but moderated the effect of uncontrolled eating on fetal growth. Emotional eating was not associated with fetal growth. Among women with higher baseline levels of uncontrolled eating, fetuses of women in the control group grew faster and were larger in later gestation than those in the intervention group (study group × baseline uncontrolled eating × gestational week interaction, p = 0.03). This is one of the first intervention studies to use an individually tailored, adaptive design to manage weight gain in pregnancy to demonstrate potential effects on fetal growth. Results also suggest that it may be important to develop intervention content and strategies specific to pregnant women with high vs. low levels of disinhibited eating.

Improving RNN Performance by Modelling Informative Missingness with Combined Indicators

Daily questionnaires from mobile applications allow large amounts of data to be collected with relative ease. However, these data almost always suffer from missing data, be it due to unanswered questions, or simply skipping the survey some days. These missing data need to be addressed before the data can be used for inferential or predictive purposes. Several strategies for dealing with missing data are available, but most are prohibitively computationally intensive for larger models, such as a recurrent neural network (RNN). Perhaps even more important, few methods allow for data that are missing not at random (MNAR). Hence, we propose a simple strategy for dealing with missing data in longitudinal surveys from mobile applications, using a long-term-short-term-memory (LSTM) network with a count of the missing values in each survey entry and a lagged response variable included in the input. We then propose additional simplifications for padding the days a user has skipped the survey entirely. Finally, we compare our strategy with previously suggested methods on a large daily survey with data that are MNAR and conclude that our method worked best, both in terms of prediction accuracy and computational cost.

Adaptive Intervention Designs to Promote Behavioral Change in Adults: What Is the Evidence?

PURPOSE OF REVIEW

Adaptive behavioral interventions tailor the type or dose of intervention strategies to individuals over time to improve saliency and intervention efficacy. This review describes the unique characteristics of adaptive intervention designs, summarizes recent diabetes-related prevention studies, which used adaptive designs, and offers recommendations for future research.

RECENT FINDINGS

Eight adaptive intervention studies were reported since 2013 to reduce sedentary behavior or improve weight management in overweight or obese adults. Primarily, feasibility studies were conducted. Preliminary results suggest that just-in-time adaptive interventions can reduce sedentary behavior or increase minutes of physical activity through repeated prompts. A stepped-down weight management intervention did not increase weight loss compared to a fixed intervention. Other adaptive interventions to promote weight management are underway and require further evaluation. Additional research is needed to target a broader range of health-related behaviors, identify optimal decision points and dose for intervention, develop effective engagement strategies, and evaluate outcomes using randomized trials.

A "Model-on-Demand" Methodology For Energy Intake Estimation to Improve Gestational Weight Control Interventions

Energy intake underreporting is a frequent concern in weight control interventions. In prior work, a series of estimation approaches were developed to better understand the issue of underreporting of energy intake; among these is an approach based on semi-physical identification principles that adjusts energy intake self-reports by obtaining a functional relationship for the extent of underreporting. In this paper, this global modeling approach is extended, and for comparison purposes, a local modeling approach based on the concept of Model-on-Demand (MoD) is developed. The local approach displays comparable performance, but involves reduced engineering e ort and demands less a priori information. Cross-validation is utilized to evaluate both approaches, which in practice serves as the basis for selecting parsimonious yet accurate models. The effectiveness of the enhanced global and MoD local estimation methods is evaluated with data obtained from Healthy Mom Zone, a novel gestational weight intervention study focused on the needs of obese and overweight women.

A Dynamical Systems Model of Intrauterine Fetal Growth

The underlying mechanisms for how maternal perinatal obesity and intrauterine environment influence fetal development are not well understood and thus require further understanding. In this paper, energy balance concepts are used to develop a comprehensive dynamical systems model for fetal growth that illustrates how maternal factors (energy intake and physical activity) influence fetal weight and related components (fat mass, fat-free mass, and placental volume) over time. The model is estimated from intensive measurements of fetal weight and placental volume obtained as part of Healthy Mom Zone (HMZ), a novel intervention for managing gestational weight gain in obese/overweight women. The overall result of the modeling procedure is a parsimonious system of equations that reliably predicts fetal weight gain and birth weight based on a sensible number of assessments. This model can inform clinical care recommendations as well as how adaptive interventions, such as HMZ, can influence fetal growth and birth outcomes.

Gestational Weight Gain Intervention Impacts Determinants of Healthy Eating and Exercise in Overweight/Obese Pregnant Women

High gestational weight gain (GWG) in overweight/obese pregnant women increases maternal-fetal complications. We conducted a 6-week GWG intervention based on an energy balance model that includes theories of planned behavior (TPB) and self-regulation constructs to promote exercise and healthy eating motivation and behaviors. The purposes of this proof-of-concept feasibility study were to examine: (1) the energy balance model constructs over the intervention, and (2) pre-post intervention, weekly, and dose-response changes in study constructs. Methods. Overweight/obese pregnant women (N=17) were randomized to 1 of 6 conditions, increasing in intensity, and included varied combinations of components (exercise sessions, healthy eating demonstrations, etc.). Exercise and healthy eating TPB (attitude, subjective norm, perceived behavioral control, intention), and self-regulation (prospective, retrospective) constructs were collected weekly. Exercise behavior, energy intake, and GWG were collected daily. Results. We observed: (a) significant increases in exercise TPB constructs, healthy eating attitude (limit unhealthy foods), exercise/healthy eating retrospective self-regulation; (b) significant decrease in healthy eating subjective norm (limit unhealthy foods); (c) trending increases for healthy eating perceived behavioral control (limit unhealthy foods), healthy eating prospective self-regulation, and energy intake; (d) significantly higher active time, steps, and energy expenditure at W3 relative to other weeks; (e) no significant increase in GWG; and, (f) a dose response effect such that women in more intensive dosages had greater gains in exercise and healthy eating perceived behavioral control (eat healthy/limit unhealthy foods). Conclusion. Brief exposure to a theoretically-driven, GWG intervention resulted in changes to exercise and healthy eating TPB and self-regulation motivational determinants, no significant increase in GWG, and suggests intervention intensity can strengthen perceived ability to engage in exercise/healthy eating behaviors; offering initial proof-of-concept for the intervention to regulate GWG in overweight/obese pregnant women. Future research will test this intervention over the course of pregnancy to understand long-term impact on maternal-fetal health outcomes.