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

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.

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.

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.

Dynamic models of stress-smoking responses based on high-frequency sensor data

Self-reports indicate that stress increases the risk for smoking; however, intensive data from sensors can provide a more nuanced understanding of stress in the moments leading up to and following smoking events. Identifying personalized dynamical models of stress-smoking responses can improve characterizations of smoking responses following stress, but techniques used to identify these models require intensive longitudinal data. This study leveraged advances in wearable sensing technology and digital markers of stress and smoking to identify person-specific models of stress and smoking system dynamics by considering stress immediately before, during, and after smoking events. Adult smokers (n = 45) wore the AutoSense chestband (respiration-inductive plethysmograph, electrocardiogram, accelerometer) with MotionSense (accelerometers, gyroscopes) on each wrist for three days prior to a quit attempt. The odds of minute-level smoking events were regressed on minute-level stress probabilities to identify person-specific dynamic models of smoking responses to stress. Simulated pulse responses to a continuous stress episode revealed a consistent pattern of increased odds of smoking either shortly after the beginning of the simulated stress episode or with a delay, for all participants. This pattern is followed by a dramatic reduction in the probability of smoking thereafter, for about half of the participants (49%). Sensor-detected stress probabilities indicate a vulnerability for smoking that may be used as a tailoring variable for just-in-time interventions to support quit attempts.

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.

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.

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.

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.