Browsing by Author "Pan, Zhaoxing"

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    Body mass index and variability in meal duration and association with rate of eating
    (Frontiers, 2022) Simon, Stacey L.; Pan, Zhaoxing; Marden, Tyson; Zhou, Wenru; Ghosh, Tonmoy; Hossain, Delwar; Thomas, J. Graham; McCrory, Megan A.; Sazonov, Edward; Higgins, Janine; University of Colorado Anschutz Medical Campus; University of Alabama Tuscaloosa; Brown University; Boston University
    BackgroundA fast rate of eating is associated with a higher risk for obesity but existing studies are limited by reliance on self-report and the consistency of eating rate has not been examined across all meals in a day. The goal of the current analysis was to examine associations between meal duration, rate of eating, and body mass index (BMI) and to assess the variance of meal duration and eating rate across different meals during the day. MethodsUsing an observational cross-sectional study design, non-smoking participants aged 18-45 years (N = 29) consumed all meals (breakfast, lunch, and dinner) on a single day in a pseudo free-living environment. Participants were allowed to choose any food and beverages from a University food court and consume their desired amount with no time restrictions. Weighed food records and a log of meal start and end times, to calculate duration, were obtained by a trained research assistant. Spearman's correlations and multiple linear regressions examined associations between BMI and meal duration and rate of eating. ResultsParticipants were 65% male and 48% white. A shorter meal duration was associated with a higher BMI at breakfast but not lunch or dinner, after adjusting for age and sex (p = 0.03). Faster rate of eating was associated with higher BMI across all meals (p = 0.04) and higher energy intake for all meals (p < 0.001). Intra-individual rates of eating were not significantly different across breakfast, lunch, and dinner (p = 0.96). ConclusionShorter beakfast and a faster rate of eating across all meals were associated with higher BMI in a pseudo free-living environment. An individual's rate of eating is constant over all meals in a day. These data support weight reduction interventions focusing on the rate of eating at all meals throughout the day and provide evidence for specifically directing attention to breakfast eating behaviors.
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    Energy intake estimation from counts of chews and swallows
    (Elsevier, 2015) Fontana, Juan M.; Higgins, Janine A.; Schuckers, Stephanie C.; Bellisle, France; Pan, Zhaoxing; Melanson, Edward L.; Neuman, Michael R.; Sazonov, Edward; University of Alabama Tuscaloosa; University of Colorado Anschutz Medical Campus; Clarkson University; INRAE; Institut National de la Sante et de la Recherche Medicale (Inserm); Universite Paris 13; heSam Universite; Conservatoire National Arts & Metiers (CNAM); Children's Hospital Colorado; Michigan Technological University
    Current, validated methods for dietary assessment rely on self-report, which tends to be inaccurate, timeconsuming, and burdensome. The objective of this work was to demonstrate the suitability of estimating energy intake using individually-calibrated models based on Counts of Chews and Swallows (CCS models). In a laboratory setting, subjects consumed three identical meals (training meals) and a fourth meal with different content (validation meal). Energy intake was estimated by four different methods: weighed food records (gold standard), diet diaries, photographic food records, and CCS models. Counts of chews and swallows were measured using wearable sensors and video analysis. Results for the training meals demonstrated that CCS models presented the lowest reporting bias and a lower error as compared to diet diaries. For the validation meal, CCS models showed reporting errors that were not different from the diary or the photographic method. The increase in error for the validation meal may be attributed to differences in the physical properties of foods consumed during training and validation meals. However, this may be potentially compensated for by including correction factors into the models. This study suggests that estimation of energy intake from CCS may offer a promising alternative to overcome limitations of self-report. (C) 2014 Elsevier Ltd. All rights reserved.
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    Improvement of Methodology for Manual Energy Intake Estimation From Passive Capture Devices
    (Frontiers, 2022) Pan, Zhaoxing; Forjan, Dan; Marden, Tyson; Padia, Jonathan; Ghosh, Tonmoy; Hossain, Delwar; Thomas, J. Graham; McCrory, Megan A.; Sazonov, Edward; Higgins, Janine A.; University of Colorado Anschutz Medical Campus; University of Alabama Tuscaloosa; Brown University; Boston University
    Objective: To describe best practices for manual nutritional analyses of data from passive capture wearable devices in free-living conditions. Method: 18 participants (10 female) with a mean age of 45 +/- 10 years and mean BMI of 34.2 +/- 4.6 kg/m(2) consumed usual diet for 3 days in a free-living environment while wearing an automated passive capture device. This wearable device facilitates capture of images without manual input from the user. Data from the first nine participants were used by two trained nutritionists to identify sources contributing to inter-nutritionist variance in nutritional analyses. The nutritionists implemented best practices to mitigate these sources of variance in the next nine participants. The three best practices to reduce variance in analysis of energy intake (EI) estimation were: (1) a priori standardized food selection, (2) standardized nutrient database selection, and (3) increased number of images captured around eating episodes. Results: Inter-rater repeatability for EI, using intraclass correlation coefficient (ICC), improved by 0.39 from pre-best practices to post-best practices (0.14 vs 0.85, 95% CI, respectively), Bland-Altman analysis indicated strongly improved agreement between nutritionists for limits of agreement (LOA) post-best practices. Conclusion: Significant improvement of ICC and LOA for estimation of EI following implementation of best practices demonstrates that these practices improve the reproducibility of dietary analysis from passive capture device images in free-living environments.
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    Reproducibility of Dietary Intake Measurement From Diet Diaries, Photographic Food Records, and a Novel Sensor Method
    (Frontiers, 2020) Fontana, Juan M.; Pan, Zhaoxing; Sazonov, Edward S.; McCrory, Megan A.; Graham Thomas, J.; McGrane, Kelli S.; Marden, Tyson; Higgins, Janine A.; Universidad Nacional Rio Cuarto; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET); University of Colorado Anschutz Medical Campus; Colorado School of Public Health; University of Alabama Tuscaloosa; Boston University; Brown University
    Objective:No data currently exist on the reproducibility of photographic food records compared to diet diaries, two commonly used methods to measure dietary intake. Our aim was to examine the reproducibility of diet diaries, photographic food records, and a novel electronic sensor, consisting of counts of chews and swallows using wearable sensors and video analysis, for estimating energy intake. Method:This was a retrospective analysis of data from a previous study, in which 30 participants (15 female), aged 29 +/- 12 y and having a BMI of 27.9 +/- 5.5, consumed three identical meals on different days. Four different methods were used to estimate total mass and energy intake on each day: (1) weighed food record; (2) photographic food record; (3) diet diary; and (4) novel mathematical model based on counts of chews and swallows (CCS models) obtained via the use of electronic sensors and video monitoring system. The study staff conducted weighed food records for all meals, took pre- and post-meal photographs, and ensured that diet diaries were completed by participants at the end of each meal. All methods were compared against the weighed food record, which was used as the reference method. Results:Reproducibility was significantly different between the diet diary and photographic food record for total energy intake (p= 0.004). The photographic record had greater reproducibility vs. the diet diary for all parameters measured. For total energy intake, the novel sensor method exhibited good reproducibility (repeatability coefficient (RC) of 59.9 (45.9, 70.4), which was better than that for the diet diary [RC = 79.6 (55.5, 103.3)] but not as repeatable as the photographic method [RC = 43.4 (32.1, 53.9)]. Conclusion:Photographic food records offer superior precision to the diet diary and, therefore, would be valuable for longitudinal studies with repeated measures of dietary intake. A novel electronic sensor also shows promise for the collection of longitudinal dietary intake data.
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    The spectrum of eating environments encountered in free living adults documented using a passive capture food intake wearable device
    (Frontiers, 2023) Breit, Matthew; Padia, Jonathan; Marden, Tyson; Forjan, Dan; Pan, Zhaoxing; Zhou, Wenru; Ghosh, Tonmoy; Thomas, Graham; McCrory, Megan A.; Sazonov, Edward; Higgins, Janine; University of Colorado Anschutz Medical Campus; University of Alabama Tuscaloosa; Brown University; Lifespan Health Rhode Island; Miriam Hospital; Boston University
    IntroductionThe aim of this feasibility and proof-of-concept study was to examine the use of a novel wearable device for automatic food intake detection to capture the full range of free-living eating environments of adults with overweight and obesity. In this paper, we document eating environments of individuals that have not been thoroughly described previously in nutrition software as current practices rely on participant self-report and methods with limited eating environment options. MethodsData from 25 participants and 116 total days (7 men, 18 women, M-age = 44 +/- 12 years, BMI 34.3 +/- 5.2 kg/mm(2)), who wore the passive capture device for at least 7 consecutive days (>= 12h waking hours/d) were analyzed. Data were analyzed at the participant level and stratified amongst meal type into breakfast, lunch, dinner, and snack categories. Out of 116 days, 68.1% included breakfast, 71.5% included lunch, 82.8% included dinner, and 86.2% included at least one snack. ResultsThe most prevalent eating environment among all eating occasions was at home and with one or more screens in use (breakfast: 48.1%, lunch: 42.2%, dinner: 50%, and snacks: 55%), eating alone (breakfast: 75.9%, lunch: 89.2%, dinner: 74.3%, snacks: 74.3%), in the dining room (breakfast: 36.7%, lunch: 30.1%, dinner: 45.8%) or living room (snacks: 28.0%), and in multiple locations (breakfast: 44.3%, lunch: 28.8%, dinner: 44.8%, snacks: 41.3%). DiscussionResults suggest a passive capture device can provide accurate detection of food intake in multiple eating environments. To our knowledge, this is the first study to classify eating occasions in multiple eating environments and may be a useful tool for future behavioral research studies to accurately codify eating environments.