Objective Determination of Eating Occasion Timing: Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity

Collin J. Popp; Chan Wang; Adam Hoover; Louis A. Gomez; Margaret Curran; David E. St-Jules; Souptik Barua; Mary Ann Sevick; Samantha Kleinberg

doi:10.1177/19322968231197205

Objective Determination of Eating Occasion Timing: Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity

Collin J. Popp, Chan Wang, Adam Hoover, Louis A. Gomez, Margaret Curran, David E. St-Jules, Souptik Barua, Mary Ann Sevick, Samantha Kleinberg

Stevens Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Background: Accurately identifying eating patterns, specifically the timing, frequency, and distribution of eating occasions (EOs), is important for assessing eating behaviors, especially for preventing and managing obesity and type 2 diabetes (T2D). However, existing methods to study EOs rely on self-report, which may be prone to misreporting and bias and has a high user burden. Therefore, objective methods are needed. Methods: We aim to compare EO timing using objective and subjective methods. Participants self-reported EO with a smartphone app (self-report [SR]), wore the ActiGraph GT9X on their dominant wrist, and wore a continuous glucose monitor (CGM, Abbott Libre Pro) for 10 days. EOs were detected from wrist motion (WM) using a motion-based classifier and from CGM using a simulation-based system. We described EO timing and explored how timing identified with WM and CGM compares with SR. Results: Participants (n = 39) were 59 ± 11 years old, mostly female (62%) and White (51%) with a body mass index (BMI) of 34.2 ± 4.7 kg/m². All had prediabetes or moderately controlled T2D. The median time-of-day first EO (and interquartile range) for SR, WM, and CGM were 08:24 (07:00-09:59), 9:42 (07:46-12:26), and 06:55 (04:23-10:03), respectively. The median last EO for SR, WM, and CGM were 20:20 (16:50-21:42), 20:12 (18:30-21:41), and 21:43 (20:35-22:16), respectively. The overlap between SR and CGM was 55% to 80% of EO detected with tolerance periods of ±30, 60, and 120 minutes. The overlap between SR and WM was 52% to 65% EO detected with tolerance periods of ±30, 60, and 120 minutes. Conclusion: The continuous glucose monitor and WM detected overlapping but not identical meals and may provide complementary information to self-reported EO.

Original language	English
Pages (from-to)	266-272
Number of pages	7
Journal	Journal of diabetes science and technology
Volume	18
Issue number	2
DOIs	https://doi.org/10.1177/19322968231197205
State	Published - Mar 2024

ASJC Scopus subject areas

Bioengineering
Internal Medicine
Biomedical Engineering
Endocrinology, Diabetes and Metabolism

Keywords

chrononutrition
fasting
intermittent fasting
meal detection
meal timing
wearable sensors

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1177/19322968231197205

Cite this

Popp, C. J., Wang, C., Hoover, A., Gomez, L. A., Curran, M., St-Jules, D. E., Barua, S., Sevick, M. A., & Kleinberg, S. (2024). Objective Determination of Eating Occasion Timing: Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity. Journal of diabetes science and technology, 18(2), 266-272. https://doi.org/10.1177/19322968231197205

@article{66907cc108004c7eb4f923643b4a3854,

title = "Objective Determination of Eating Occasion Timing: Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity",

abstract = "Background: Accurately identifying eating patterns, specifically the timing, frequency, and distribution of eating occasions (EOs), is important for assessing eating behaviors, especially for preventing and managing obesity and type 2 diabetes (T2D). However, existing methods to study EOs rely on self-report, which may be prone to misreporting and bias and has a high user burden. Therefore, objective methods are needed. Methods: We aim to compare EO timing using objective and subjective methods. Participants self-reported EO with a smartphone app (self-report [SR]), wore the ActiGraph GT9X on their dominant wrist, and wore a continuous glucose monitor (CGM, Abbott Libre Pro) for 10 days. EOs were detected from wrist motion (WM) using a motion-based classifier and from CGM using a simulation-based system. We described EO timing and explored how timing identified with WM and CGM compares with SR. Results: Participants (n = 39) were 59 ± 11 years old, mostly female (62%) and White (51%) with a body mass index (BMI) of 34.2 ± 4.7 kg/m2. All had prediabetes or moderately controlled T2D. The median time-of-day first EO (and interquartile range) for SR, WM, and CGM were 08:24 (07:00-09:59), 9:42 (07:46-12:26), and 06:55 (04:23-10:03), respectively. The median last EO for SR, WM, and CGM were 20:20 (16:50-21:42), 20:12 (18:30-21:41), and 21:43 (20:35-22:16), respectively. The overlap between SR and CGM was 55% to 80% of EO detected with tolerance periods of ±30, 60, and 120 minutes. The overlap between SR and WM was 52% to 65% EO detected with tolerance periods of ±30, 60, and 120 minutes. Conclusion: The continuous glucose monitor and WM detected overlapping but not identical meals and may provide complementary information to self-reported EO.",

keywords = "chrononutrition, fasting, intermittent fasting, meal detection, meal timing, wearable sensors",

author = "Popp, {Collin J.} and Chan Wang and Adam Hoover and Gomez, {Louis A.} and Margaret Curran and St-Jules, {David E.} and Souptik Barua and Sevick, {Mary Ann} and Samantha Kleinberg",

note = "Publisher Copyright: {\textcopyright} 2023 Diabetes Technology Society.",

year = "2024",

month = mar,

doi = "10.1177/19322968231197205",

language = "English",

volume = "18",

pages = "266--272",

journal = "Journal of diabetes science and technology",

issn = "1932-2968",

publisher = "Diabetes Technology Society",

number = "2",

}

Popp, CJ, Wang, C, Hoover, A, Gomez, LA, Curran, M, St-Jules, DE, Barua, S, Sevick, MA & Kleinberg, S 2024, 'Objective Determination of Eating Occasion Timing: Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity', Journal of diabetes science and technology, vol. 18, no. 2, pp. 266-272. https://doi.org/10.1177/19322968231197205

Objective Determination of Eating Occasion Timing: Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity. / Popp, Collin J.; Wang, Chan; Hoover, Adam et al.
In: Journal of diabetes science and technology, Vol. 18, No. 2, 03.2024, p. 266-272.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Objective Determination of Eating Occasion Timing

T2 - Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity

AU - Popp, Collin J.

AU - Wang, Chan

AU - Hoover, Adam

AU - Gomez, Louis A.

AU - Curran, Margaret

AU - St-Jules, David E.

AU - Barua, Souptik

AU - Sevick, Mary Ann

AU - Kleinberg, Samantha

PY - 2024/3

Y1 - 2024/3

N2 - Background: Accurately identifying eating patterns, specifically the timing, frequency, and distribution of eating occasions (EOs), is important for assessing eating behaviors, especially for preventing and managing obesity and type 2 diabetes (T2D). However, existing methods to study EOs rely on self-report, which may be prone to misreporting and bias and has a high user burden. Therefore, objective methods are needed. Methods: We aim to compare EO timing using objective and subjective methods. Participants self-reported EO with a smartphone app (self-report [SR]), wore the ActiGraph GT9X on their dominant wrist, and wore a continuous glucose monitor (CGM, Abbott Libre Pro) for 10 days. EOs were detected from wrist motion (WM) using a motion-based classifier and from CGM using a simulation-based system. We described EO timing and explored how timing identified with WM and CGM compares with SR. Results: Participants (n = 39) were 59 ± 11 years old, mostly female (62%) and White (51%) with a body mass index (BMI) of 34.2 ± 4.7 kg/m2. All had prediabetes or moderately controlled T2D. The median time-of-day first EO (and interquartile range) for SR, WM, and CGM were 08:24 (07:00-09:59), 9:42 (07:46-12:26), and 06:55 (04:23-10:03), respectively. The median last EO for SR, WM, and CGM were 20:20 (16:50-21:42), 20:12 (18:30-21:41), and 21:43 (20:35-22:16), respectively. The overlap between SR and CGM was 55% to 80% of EO detected with tolerance periods of ±30, 60, and 120 minutes. The overlap between SR and WM was 52% to 65% EO detected with tolerance periods of ±30, 60, and 120 minutes. Conclusion: The continuous glucose monitor and WM detected overlapping but not identical meals and may provide complementary information to self-reported EO.

AB - Background: Accurately identifying eating patterns, specifically the timing, frequency, and distribution of eating occasions (EOs), is important for assessing eating behaviors, especially for preventing and managing obesity and type 2 diabetes (T2D). However, existing methods to study EOs rely on self-report, which may be prone to misreporting and bias and has a high user burden. Therefore, objective methods are needed. Methods: We aim to compare EO timing using objective and subjective methods. Participants self-reported EO with a smartphone app (self-report [SR]), wore the ActiGraph GT9X on their dominant wrist, and wore a continuous glucose monitor (CGM, Abbott Libre Pro) for 10 days. EOs were detected from wrist motion (WM) using a motion-based classifier and from CGM using a simulation-based system. We described EO timing and explored how timing identified with WM and CGM compares with SR. Results: Participants (n = 39) were 59 ± 11 years old, mostly female (62%) and White (51%) with a body mass index (BMI) of 34.2 ± 4.7 kg/m2. All had prediabetes or moderately controlled T2D. The median time-of-day first EO (and interquartile range) for SR, WM, and CGM were 08:24 (07:00-09:59), 9:42 (07:46-12:26), and 06:55 (04:23-10:03), respectively. The median last EO for SR, WM, and CGM were 20:20 (16:50-21:42), 20:12 (18:30-21:41), and 21:43 (20:35-22:16), respectively. The overlap between SR and CGM was 55% to 80% of EO detected with tolerance periods of ±30, 60, and 120 minutes. The overlap between SR and WM was 52% to 65% EO detected with tolerance periods of ±30, 60, and 120 minutes. Conclusion: The continuous glucose monitor and WM detected overlapping but not identical meals and may provide complementary information to self-reported EO.

KW - chrononutrition

KW - fasting

KW - intermittent fasting

KW - meal detection

KW - meal timing

KW - wearable sensors

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U2 - 10.1177/19322968231197205

DO - 10.1177/19322968231197205

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SN - 1932-2968

VL - 18

SP - 266

EP - 272

JO - Journal of diabetes science and technology

JF - Journal of diabetes science and technology

IS - 2

ER -

Objective Determination of Eating Occasion Timing: Combining Self-Report, Wrist Motion, and Continuous Glucose Monitoring to Detect Eating Occasions in Adults With Prediabetes and Obesity

Abstract

ASJC Scopus subject areas

Keywords

UN SDGs

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