Feasibility and user acceptability of Breezing™, a mobile indirect calorimetry device, in pregnant women with overweight or obesity.

Emerging evidence has suggested that prenatal resting energy expenditure (REE) may be an important determinant of gestational weight gain. Advancements in technology such as the real-time, mobile indirect calorimetry device (Breezing™) have offered the novel opportunity to continuously assess prenatal REE while also potentially capturing fluctuations in REE. The purpose of this study was to examine feasibility and user acceptability of Breezing™ to assess weekly REE from 8-36 weeks gestation in pregnant women with overweight or obesity participating in the Healthy Mom Zone intervention study. Participants (N=27) completed REE assessments once per week from 8-36 gestation using Breezing™. Feasibility of the device was calculated as compliance (# of weeks used/total # of weeks). User acceptability was measured by asking women to report on the device's enjoyability and barriers. Median compliance was 68%. However, when weeks women experienced technical difficulties (11 of 702 total events) and the device was unavailable were removed (13 of 702 total events), median compliance increased to 71%. Over half (56%) of the women reported that the device was enjoyable or they had neutral feelings about it whereas the remaining 44% reported that it was not enjoyable. The most common barrier reported (44%) was the experience of technical issues. Study compliance data suggest the feasibility of using Breezing™ to assess prenatal REE is promising. However, acceptability data suggest future interventionists should develop transparent and informative protocols to address any barriers prior to implementing the device to increase use.

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.

Influence of C14 alkane stress on antioxidant defense capacity, mineral nutrient element accumulation, and cadmium uptake of ryegrass.

In order to explore the influence of C14 alkane on physiological stress responses, mineral nutrient elements uptake, cadmium (Cd) transfer, and uptake characteristics of Lolium perenne L. (ryegrass), a series of pot trials were conducted which included a moderate level of Cd (2.182 mg·kg-1) without (control) and with five levels of C14 alkane (V/m, 0.1%, 0.2%, 0.5%, 1%, 2%). Biomass and Cd content in the root and shoot, chlorophyll content, antioxidant enzymes activity, and mineral nutrient elements in the shoot of ryegrass were determined at the end of the experiment. The results indicated that Cd uptake significantly elevated at 0.1% C14 alkane treatment, then gradually decreased with the increase of C14 alkane concentration. Compared with the control, chlorophyll content was significantly suppressed and malondialdehyde (MDA) concentration obviously increased. Superoxide dismutase (SOD) activity and catalase (CAT) activity significantly increased to prevent the C14 alkane stress. With the increase of C14 alkane, the Mn concentration gradually increased; Mg and Fe significantly decreased. Correlation analysis showed that Mn was positively correlated with SOD (with the exception of 2% treatment) and CAT (p < 0.01), and negatively correlated with Cd uptake (p < 0.01). It implied that the increase of Mn induced by C14 alkane stress was an important reason for the decrease of Cd uptake.

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.

Influence of electrical fields enhanced phytoremediation of multi-metal contaminated soil on soil parameters and plants uptake in different soil sections.

The influence of electrical fields on phytoremediation of multi-metal (Cd, Cu, and Zn) naturally contaminated soils has been investigated based on different soil sections. After ryegrass and hybrid penisetum were sowed for 30 d, electrical fields were applied during 30 days with the switching polarity every 30 min and continuing for 16 h d-1. After electrokinetic (EK) assisted phytoremediation process, soil electrical conductivity (EC) in anode section and available soil potassium (K) in cathode section were obviously elevated. Plants biomass in middle and cathode sections were increased in both plants, especially in middle section the overall biomass of hybrid penisetum increased by 68.8%. The influence of electrical field on the contents of heavy metals in plants was different depending on the species of plants, kind of heavy metals and soil section. For Cd, Cu, and Zn co-contaminated soils, shoot metals accumulation in middle section in both plants were improved at least about 20% (with the exception of Zn in ryegrass). Electrical fields had the most significant effect on copper absorption by ryegrass and shoot Cu accumulation were elevated 32.5% in all the section. The soil EC maybe an important factor that affected electrical fields enhanced plants growth, plant metals concentrations and remediation efficiency.

Bioremediation of polycyclic aromatic hydrocarbons contaminated soil under the superimposed electric field condition.

An innovative superimposed electric field (SEF) was designed with the aim to achieve uniform removal of polycyclic aromatic hydrocarbons (PAHs) in soil. Also the influence of SEF on the bioremediation efficiency of PAHs was investigated in compared with the common electric field (CEF). Five experiments were conducted in this study, namely EK-CEF (applied CEF), EKB-CEF (CEF enhanced bioremediation), EK-SEF (applied SEF), EKB-SEF (SEF enhanced bioremediation), and Bio (bioremediation). The results indicated that electric field with periodically reversed polarity could effectively prevent the occurrence of large changes in soil pH, temperature, and electric current. The electric field intensity of SEF was concentrated in the range of 0.5-1.5 V/cm, and the difference between the maximum and minimum PAHs removal percentage in EK-SEF was just 5.4%, in comparison to 14.8% in EK-CEF. The bioremediation promoting effect did not show significant difference between SEF and CEF. Compared to Bio, the removal percentages of the 5-ring and 6-ring PAHs attributed to the degrading bacteria were much higher in EKB-SEF and EKB-CEF. Moreover, the microbial number increased with the distance away from electrodes, and the microbial community changed correspondingly. All these would be resulted in differences removal efficiencies among different PAHs components. Despite its intrinsic advantages, the influence of SEF on soil physicochemical and biological properties needs further study.

Characteristics of organic carbon metabolism and bioremediation of petroleum-contaminated soil by a mesophilic aerobic biopile system.

An innovative mesophilic aerobic biopile technology was explored to improve the bioremediation efficiency of petroleum-contaminated soil. Under the suitable soil conditions (C:N:P at 100:5:1 and soil moisture content at 18%), the soil pH was hold in the range of 7.4 to 6.8 throughout the bioremediation process, the mesophilic (30 °C-40 °C) and forced aeration (3 h-on/1 h-off) conditions were the critical factors to enhancing petroleum biodegradation. The consumption of bioavailable organic carbon (BAC) which was one of the most important factors regulating microbial metabolism, was positively related (R2 = 0.85, 40 °C) with the rate of petroleum removal. The 50% threshold of BAC could be regarded as the signal for supplementing the soil nutrients in the mesophilic aerobic biopiles to favor petroleum removal. The optimal conditions (40 °C, 3 h-on/1 h-off) maximized the utilization of BAC, promoted the petroleum degradation, and remained the microbial abundance and community composition stable to the greatest extent. In addition, the accumulation of aliphatic acids affected the microbial activity, which limited the efficiency of petroleum degradation to a certain extent. Jointly considering the energy consumption, time cost and soil conditions maintenance, a cost-effective biopile technology was obtained by temperature and aeration regulation and BAC supplementation, which could be applied to engineering application.

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.

Enhancement of electrokinetic-bioremediation by ryegrass: Sustainability of electrokinetic effect and improvement of n-hexadecane degradation.

Phytoremediation-assisted electrokinetic-bioremediation is a novel technology for soil remediation. We aimed to study the effects of a plant (ryegrass) on electrokinetic-bioremediation in n-hexadecane-contaminated soil. After treatment for 40 days, the n-hexadecane degradation ratio of electrokinetic-bioremediation-ryegrass (EK-Bio-RG) was 4.86% higher than that of electrokinetic-bioremediation (EK-Bio) (p < 0.05), with a maximum constant degradation rate (107.23 ± 4.62 mg kg-1· d-1). Owing to the improved electrical conductivity, 73.28% of the initial current was maintained on the 40th day in EK-Bio-RG, which was 1.62 times that in EK-Bio. Furthermore, ryegrass reduced the soil zeta potential, which indicated the alleviation of the soil electric double layer compression and prevention of the aggregation of small soil colloids into larger ones. The fine colloidal structure was conducive to mass transfer in electrokinetic-bioremediation. An analysis of the microbial community showed that the degradation of n-hexadecane was mainly attributable to gram-positive bacteria, and a new microbial community was gradually constructed in the rhizosphere, which still metabolized n-hexadecane. The results indicated that the sustainability of the electrokinetic effect was improved combined with ryegrass, and the harmonious micro-environment in the rhizosphere was constructed which furtherly optimized the EK-Bio technology to remediate organics-polluted soil.

Change in soil ion content and soil water-holding capacity during electro-bioremediation of petroleum contaminated saline soil.

This study investigated changes in soil ion content and soil water-holding capacity during electro-bioremediation (EK-Bio) of petroleum contaminated saline soil (ion content of 3.92 g/kg). The results indicated that the soil ions surrounded the electrodes with increasing time, thus changing the soil water-holding capacity. According to the Van Genuchten model fitting results, the soil residual water content (θr) increased with the soil ion content, which represented a capacity decrease of the soil water supply. At the end of the EK-Bio experiment, the θr values in the soil near (site A) and far from (site B) the electrodes were 19.1 % and 12.1 %, where the soil ion content was 7.92 g/kg and 0.55 g/kg, respectively. The ion aggregation process significantly impacted the growth of soil microbial. The bacteria numbers decreased when the soil ion content was high (7.41 g/kg, site A) and low (0.84 g/kg, site B) after 70 days of treatment. The applied electric field significantly enhanced the bioremediation efficiency. However, the biodegradation promotion effect was the weakest at site A. The synergistic effect between the applied electric field and degrading bacteria was delayed.

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.

Enhanced electrokinetic remediation and simulation of cadmium-contaminated soil by superimposed electric field.

The 'focusing' effect has become a limiting factor for the removal of heavy metals from soils by electrokinetic (EK) remediation. A superimposed electric field EK (SE-EK) method is proposed to address this problem. Two sets of fixed electrodes placed at different positions were switched to move the 'focusing' region of Cd to the cathode by controlling the location of the pH jumping front. Moreover, a model was established to simulate and optimize the process of Cd transport in soil under the superimposed electric field. Results showed that, after 35 d of SE-EK remediation, Cd was mainly accumulated in the soil section near the cathode (S5), where the acid and alkaline fronts converged. The removal rate of Cd in the soil sections from S1 to S4 reached 87.60%, which was 6.13 times that in conventional EK remediation. Meanwhile, the energy utilization efficiency in SE-EK was 6.38 times that in conventional EK. The pH changes and Cd distribution during the SE-EK experiment were simulated well, with good agreement between the modeled and experimental data. The removal of Cd in SE-EK remediation could therefore be optimized through simulating the distribution of Cd in five situations with differences in switching time and electrode position. This research provides valuable technical support for effective EK remediation of heavy metal contaminated soil.

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.

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.

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.

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

BACKGROUND: High gestational weight gain is a major public health concern as it independently predicts adverse maternal and infant outcomes. Past interventions have had only limited success in effectively managing pregnancy weight gain, especially among women with overweight and obesity. Well-designed interventions are needed that take an individualized approach and target unique barriers to promote healthy weight gain. OBJECTIVE: The primary aim of the study is to describe the study protocol for Healthy Mom Zone, an individually tailored, adaptive intervention for managing weight in pregnant women with overweight and obesity. METHODS: The Healthy Mom Zone Intervention, based on theories of planned behavior and self-regulation and a model of energy balance, includes components (eg, education, self-monitoring, physical activity/healthy eating behaviors) that are adapted over the intervention (ie, increase in intensity) to better regulate weight gain. Decision rules inform when to adapt the intervention. In this randomized controlled trial, women are randomized to the intervention or standard care control group. The intervention is delivered from approximately 8-36 weeks gestation and includes step-ups in dosages (ie, Step-up 1 = education + physical activity + healthy eating active learning [cooking/recipes]; Step-up 2 = Step-up 1 + portion size, physical activity; Step-up 3 = Step-up 1 + 2 + grocery store feedback, physical activity); 5 maximum adaptations. Study measures are obtained at pre- and postintervention as well as daily (eg, weight), weekly (eg, energy intake/expenditure), and monthly (eg, psychological) over the study period. Analyses will include linear mixed-effects models, generalized estimating equations, and dynamical modeling to understand between-group and within-individual effects of the intervention on weight gain. RESULTS: Recruitment of 31 pregnant women with overweight and obesity has occurred from January 2016 through July 2017. Baseline data have been collected for all participants. To date, 24 participants have completed the intervention and postintervention follow-up assessments, 3 are currently in progress, 1 dropped out, and 3 women had early miscarriages and are no longer active in the study. Of the 24 participants, 13 women have completed the intervention to date, of which 1 (8%, 1/13) received only the baseline intervention, 3 (23%, 3/13) received baseline + step-up 1, 6 (46%, 6/13) received baseline + step-up 1 + step-up 2, and 3 (23%, 3/13) received baseline + step-up 1 + step-up 2 +step-up 3. Data analysis is still ongoing through spring 2018. CONCLUSIONS: This is one of the first intervention studies to use an individually tailored, adaptive design to manage weight gain in pregnancy. Results from this study will be useful in designing a larger randomized trial to examine efficacy of this intervention and developing strategies for clinical application. REGISTERED REPORT IDENTIFIER: RR1-10.2196/9220.

State Estimation Under Correlated Partial Measurement Losses: Implications for Weight Control Interventions.

The growing prevalence of obesity and related health problems warrants immediate need for effective weight control interventions. Quantitative energy balance models serve as powerful tools to assist in these interventions, as a result of their ability to accurately predict individual weight change based on reliable measurements of energy intake and energy expenditure. However, the data collected in most existing weight interventions is self-monitored; these measurements often have significant noise or experience losses resulting from participant non-adherence, which in turn, limits accurate model estimation. To address this issue, we develop a Kalman filter-based estimation algorithm for a practical scenario where on-line state estimation for weight, or energy intake/expenditure is still possible despite correlated partial data losses. To account for non-linearities in the models, an algorithm based on extended Kalman filtering is also developed for sequential state estimation in the presence of missing data. Simulation studies are presented to illustrate the performance of the algorithms and the potential benefits of these techniques in real-life interventions.

Semi-physical Identification and State Estimation of Energy Intake for Interventions to Manage Gestational Weight Gain.

Excessive gestational weight gain (i.e., weight gain during pregnancy) is a significant public health concern, and has been the recent focus of novel, control systems-based interventions. This paper develops a control-oriented dynamical systems model based on a first-principles energy balance model from the literature, which is evaluated against participant data from a study targeted to obese and overweight pregnant women. The results indicate significant under-reporting of energy intake among the participant population. A series of approaches based on system identification and state estimation are developed in the paper to better understand and characterize the extent of under-reporting; these range from back-calculating energy intake from a closed-form of the energy balance model, to a constrained semi-physical identification approach that estimates the extent of systematic under-reporting in the presence of noise and possibly missing data. Additionally, we describe an adaptive algorithm based on Kalman filtering to estimate energy intake in real-time. The approaches are illustrated with data from both simulated and actual intervention participants.