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Wang L, Chan V, Allman-Farinelli M, Davies A, Wellard-Cole L, Rangan A. The association between diet quality and chrononutritional patterns in young adults. Eur J Nutr 2024; 63:1271-1281. [PMID: 38386041 PMCID: PMC11139707 DOI: 10.1007/s00394-024-03353-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 02/09/2024] [Indexed: 02/23/2024]
Abstract
PURPOSE Young adults eat erratically and later in the day which may impact weight and cardiometabolic health. This cross-sectional study examined relationships between chrononutritional patterns and diet quality in two young adult populations: a university and community sample. METHODS Three days of dietary data were collected including food images captured using wearable cameras. Chrononutritional variables were extracted: time of first and last eating occasions, caloric midpoint (time at which 50% of daily energy was consumed), number of eating occasions per day, eating window, day-to-day variability of the above metrics, and evening eating (≥20:00h). The Healthy Eating Index for Australian Adults scored diet quality. Statistical analyses controlled for gender, body mass index, and socio-economic status. RESULTS No significant associations between chrononutritional patterns and diet quality were found for all participants (n = 95). However, differences in diet quality were found between university (n = 54) and community (n = 41) samples with average diet quality scores of 59.1 (SD 9.7) and 47.3 (SD 14.4), respectively. Of those who extended eating ≥20:00 h, university participants had better diet quality (62.9±SE 2.5 vs. 44.3±SE 2.3, p < 0.001) and discretionary scores (7.9±SE 0.9 vs. 1.6±SE 0.6, p < 0.001) than community participants. University participants consumed predominately healthful dinners and fruit ≥20:00h whereas community participants consumed predominately discretionary foods. CONCLUSION For the general young adult population, meal timing needs to be considered. Food choices made by this cohort may be poorer during evenings when the desire for energy-dense nutrient-poor foods is stronger. However, meal timing may be less relevant for young adults who already engage in healthy dietary patterns.
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Affiliation(s)
- Leanne Wang
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Virginia Chan
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Margaret Allman-Farinelli
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Alyse Davies
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Lyndal Wellard-Cole
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia
- Cancer Prevention and Advocacy Division, Cancer Council NSW, Sydney, NSW, 2011, Australia
| | - Anna Rangan
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia.
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia.
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Phoi YY, Bonham MP, Rogers M, Dorrian J, Coates AM. Construct validity and test-retest reliability of a chrononutrition questionnaire for shift work and non-shift work populations. Chronobiol Int 2024; 41:669-683. [PMID: 38666461 DOI: 10.1080/07420528.2024.2342937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 04/09/2024] [Indexed: 05/22/2024]
Abstract
The irregular eating patterns of both shift workers and evening chronotypes adversely affect cardiometabolic health. A tool that conveniently captures temporal patterns of eating alongside an indicator of circadian rhythm such as chronotype will enable researchers to explore relationships with diverse health outcome measures. We aimed to investigate the test-retest reliability and convergent validity of a Chrononutrition Questionnaire (CNQ) that captures temporal patterns of eating and chronotype in the general population (non-shift workers, university students, retirees, unemployed individuals) and shift work population. Participants attended two face-to-face/virtual sessions and completed the CNQ and food/sleep/work diaries. Outcomes included subjective chronotype, wake/sleep/mid-sleep time, sleep duration, meal/snack regularity, meal/snack/total frequency, times of first/last/largest eating occasions (EO), main meal (MM) 1/2/3, and duration of eating window (DEW). 116 participants enrolled (44.5 ± 16.5 years, BMI: 27.3 ± 5.8 kg/m2, 73% female, 52% general population); 105 completed the study. Reliability was acceptable for chronotype, sleep, and all temporal eating patterns except on night shifts. Convergent validity was good for chronotype and sleep except for certain shift/shift-free days. Generally, meal/snack regularity and frequency, and times of first/last EO showed good validity for the general population but not shift workers. Validity was good for DEW (except work-free days and afternoon shifts) and times of MM 1/2/3 (except afternoon and night shifts), while time of largest EO had poor validity. The CNQ has good test-retest reliability and acceptable convergent validity for the general and shift work population, although it will benefit from further validation, especially regarding regularity, frequency, and times of first and last eating occasions across more days amongst a larger sample size of shift workers. Use of the CNQ by researchers will expand our current understanding of chrononutrition as relationships between timing of food intake and the multitude of health outcomes are examined.
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Affiliation(s)
- Yan Yin Phoi
- Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity (ARENA) Research Centre, University of South Australia, Adelaide, Australia
| | - Maxine P Bonham
- Nutrition, Dietetics & Food, Be Active Sleep Eat (BASE) Facility, Monash University, Melbourne, Australia
| | - Michelle Rogers
- Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity (ARENA) Research Centre, University of South Australia, Adelaide, Australia
| | - Jillian Dorrian
- Justice and Society, Behaviour-Brain-Body Research Centre, University of South Australia, Adelaide, Australia
| | - Alison M Coates
- Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity (ARENA) Research Centre, University of South Australia, Adelaide, Australia
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Erickson ML, North R, Counts J, Wang W, Porter Starr KN, Wideman L, Pieper C, Dunn J, Kraus WE. Nightshift imposes irregular lifestyle behaviors in police academy trainees. SLEEP ADVANCES : A JOURNAL OF THE SLEEP RESEARCH SOCIETY 2023; 4:zpad038. [PMID: 38020732 PMCID: PMC10630191 DOI: 10.1093/sleepadvances/zpad038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/11/2023] [Indexed: 12/01/2023]
Abstract
Study Objective Shiftwork increases risk for numerous chronic diseases, which is hypothesized to be linked to disruption of circadian timing of lifestyle behaviors. However, empirical data on timing of lifestyle behaviors in real-world shift workers are lacking. To address this, we characterized the regularity of timing of lifestyle behaviors in shift-working police trainees. Methods Using a two-group observational study design (N = 18), we compared lifestyle behavior timing during 6 weeks of in-class training during dayshift, followed by 6 weeks of field-based training during either dayshift or nightshift. Lifestyle behavior timing, including sleep-wake patterns, physical activity, and meals, was captured using wearable activity trackers and mobile devices. The regularity of lifestyle behavior timing was quantified as an index score, which reflects day-to-day stability on a 24-hour time scale: Sleep Regularity Index, Physical Activity Regularity Index, and Mealtime Regularity Index. Logistic regression was applied to these indices to develop a composite score, termed the Behavior Regularity Index (BRI). Results Transitioning from dayshift to nightshift significantly worsened the BRI, relative to maintaining a dayshift schedule. Specifically, nightshift led to more irregular sleep-wake timing and meal timing; physical activity timing was not impacted. In contrast, maintaining a dayshift schedule did not impact regularity indices. Conclusions Nightshift imposed irregular timing of lifestyle behaviors, which is consistent with the hypothesis that circadian disruption contributes to chronic disease risk in shift workers. How to mitigate the negative impact of shiftwork on human health as mediated by irregular timing of sleep-wake patterns and meals deserves exploration.
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Affiliation(s)
| | - Rebecca North
- Center for the Study of Aging and Human Development, Duke University, Durham, NC, USA
| | - Julie Counts
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Will Wang
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Kathryn N Porter Starr
- Center for the Study of Aging and Human Development, Duke University, Durham, NC, USA
- Geriatric Research, Education, Clinical Center, Durham VA Health Care System, Durham, NC, USA
| | - Laurie Wideman
- Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, NC, USA
| | - Carl Pieper
- Center for the Study of Aging and Human Development, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Jessilyn Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - William E Kraus
- Center for the Study of Aging and Human Development, Duke University, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
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Hoopes EK, Witman MA, D'Agata MN, Brewer B, Edwards DG, Robson SM, Malone SK, Keiser T, Patterson F. Sleep Variability, Eating Timing Variability, and Carotid Intima-Media Thickness in Early Adulthood. J Am Heart Assoc 2023; 12:e029662. [PMID: 37776217 PMCID: PMC10727236 DOI: 10.1161/jaha.123.029662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 08/24/2023] [Indexed: 10/02/2023]
Abstract
Background Day-to-day variability in sleep patterns and eating timing may disrupt circadian rhythms and has been linked with various adverse cardiometabolic outcomes. However, the extent to which variability in sleep patterns and eating timing relate to atherosclerotic development in subclinical stages remains unclear. Methods and Results Generally healthy adults (N=62, 29.3±7.3 years, 66% female) completed 14 days of sleep and dietary assessments via wrist accelerometry and photo-assisted diet records, respectively. Variability in sleep duration, sleep onset, eating onset (time of first caloric consumption), eating offset (time of last caloric consumption), and caloric midpoint (time at which 50% of total daily calories are consumed) were operationalized as the SD across 14 days for each variable. Separate regression models evaluated the cross-sectional associations between sleep and eating variability metrics with end-diastolic carotid intima-media thickness (CIMT) measured via ultrasonography. Models adjusted for age, sex, systolic blood pressure, sleep duration, and total energy intake. Each 60-minute increase in sleep duration SD and sleep onset SD were associated with a 0.049±0.016 mm (P=0.003) and 0.048±0.017 mm (P=0.007) greater CIMT, respectively. Variability in eating onset and offset were not associated with CIMT; however, each 60-minute increase in caloric midpoint SD was associated with a 0.033±0.015 mm greater CIMT (P=0.029). Exploratory post hoc analyses suggested that sleep duration SD and sleep onset SD were stronger correlates of CIMT than caloric midpoint SD. Conclusions Variability in sleep patterns and eating timing are positively associated with clinically relevant increases in CIMT, a biomarker of subclinical atherosclerosis, in early adulthood.
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Affiliation(s)
| | | | | | | | | | | | | | - Thomas Keiser
- College of Health SciencesUniversity of DelawareNewarkDE
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5
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Rice A, Sather O, Wright KP, Vetter C, Martin MA, de la Iglesia HO. COVID-19 stay-at-home restrictions increase the alignment in sleep and light exposure between school days and weekends in university students. Sleep 2023; 46:zsad059. [PMID: 36883614 PMCID: PMC10334482 DOI: 10.1093/sleep/zsad059] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 02/24/2023] [Indexed: 03/09/2023] Open
Abstract
Younger adults have a biological disposition to sleep and wake at later times that conflict with early morning obligations like work and school; this conflict leads to inadequate sleep duration and a difference in sleep timing between school days and weekends. The COVID-19 pandemic forced universities and workplaces to shut down in person attendance and implement remote learning and meetings that decreased/removed commute times and gave students more flexibility with their sleep timing. To determine the impact of remote learning on the daily sleep-wake cycle we conducted a natural experiment using wrist actimetry monitors to compare activity patterns and light exposure in three cohorts of students: pre-shutdown in-person learning (2019), during-shutdown remote learning (2020), and post-shutdown in-person learning (2021). Our results show that during-shutdown the difference between school day and weekend sleep onset, duration, and midsleep timing was diminished. For instance, midsleep during school days pre-shutdown occurred 50 min later on weekends (5:14 ± 12 min) than school days (4:24 ± 14 min) but it did not differ under COVID restrictions. Additionally, we found that while the interindividual variance in sleep parameters increased under COVID restrictions the intraindividual variance did not change, indicating that the schedule flexibility did not cause more irregular sleep patterns. In line with our sleep timing results, school day vs. weekend differences in the timing of light exposure present pre- and post-shutdown were absent under COVID restrictions. Our results provide further evidence that increased freedom in class scheduling allows university students to better and consistently align sleep behavior between school days and weekends.
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Affiliation(s)
- Alicia Rice
- Department of Biology, University of Washington, Seattle, WA, USA
| | - Olivia Sather
- Department of Biology, University of Washington, Seattle, WA, USA
| | - Kenneth P Wright
- Sleep and Chronobiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Céline Vetter
- Circadian and Sleep Epidemiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Melanie A Martin
- Department of Anthropology, University of Washington, Seattle, WA, USA
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Erickson ML, North R, Counts J, Wang W, Porter Starr KN, Wideman L, Pieper C, Dunn J, Kraus WE. Nightshift Imposes Irregular Lifestyle Behaviors in Police Academy Trainees. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.07.23292363. [PMID: 37461704 PMCID: PMC10350160 DOI: 10.1101/2023.07.07.23292363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
Study Objective Shiftwork increases risk for numerous chronic diseases, which is hypothesized to be linked to disruption of circadian timing of lifestyle behaviors. However, empirical data on timing of lifestyle behaviors in real-world shift workers are lacking. To address this, we characterized the regularity of timing of lifestyle behaviors in shift-working police trainees. Methods Using a two-group observational study design (N=18), we compared lifestyle behavior timing during 6 weeks of in-class training during dayshift, followed by 6 weeks of field-based training during either dayshift or nightshift. Lifestyle behavior timing, including sleep/wake patterns, physical activity, and meals, was captured using wearable activity trackers and mobile devices. The regularity of lifestyle behavior timing was quantified as an index score, which reflects day-to-day stability on a 24h time scale: Sleep Regularity Index (SRI), Physical Activity Regularity Index (PARI) and Mealtime Regularity Index (MRI). Logistic regression was applied to these indices to develop a composite score, termed the Behavior Regularity Index (BRI). Results Transitioning from dayshift to nightshift significantly worsened the BRI, relative to maintaining a dayshift schedule. Specifically, nightshift led to more irregular sleep/wake timing and meal timing; physical activity timing was not impacted. In contrast, maintaining a dayshift schedule did not impact regularity indices. Conclusion Nightshift imposed irregular timing of lifestyle behaviors, which is consistent with the hypothesis that circadian disruption contributes to chronic disease risk in shift workers. How to mitigate the negative impact of shiftwork on human health as mediated by irregular timing of sleep/wake patterns and meals deserves exploration.
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Jacob R, Tremblay A, Provencher V, Panahi S, Mathieu MÈ, Drapeau V. Associations of timing of food intake with energy intake, eating behaviour traits and psychosocial factors in adults with overweight and obesity. Front Nutr 2023; 10:1155971. [PMID: 37324732 PMCID: PMC10267979 DOI: 10.3389/fnut.2023.1155971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/28/2023] [Indexed: 06/17/2023] Open
Abstract
Introduction Whether a late distribution of food intake impacts obesity through increased energy intake remains uncertain and the behavioural characterization of late eating needs to be further investigated. The first objective of this study was to assess the associations between late eating and body mass index (BMI) and total energy intake (TEI), and whether TEI mediates the association between late eating and BMI. The second objective was to assess the associations between late eating and eating behaviour traits or psychosocial factors and whether eating behaviour traits mediate the association between late eating and TEI. Methods Baseline data from 301 individuals (56% women, age = 38.7 ± 8.5 years; BMI = 33.2 ± 3.4 kg/m2), who participated in four weight loss studies were used in this cross-sectional study. Total energy intake was assessed using a three-day food record from which the percentage of TEI after 17:00 and after 20:00 was calculated. Eating behaviour traits and psychosocial factors were assessed with questionnaires. Pearson correlations and mediation analyses adjusted for age, sex, underreporting of energy intake, sleep duration and bedtime were performed. Results Percent TEI after 17:00 and after 20:00 were associated with TEI (r = 0.13, p = 0.03 for both), and TEI mediated the association between percent TEI after 17:00 and BMI (β = 0.01 ± 0.01, 95% CI: 0.001, 0.02). Percent TEI after 17:00 was associated with disinhibition (r = 0.13, p = 0.03) and percent TEI after 20:00 was associated with susceptibility to hunger (r = 0.13, p = 0.03), stress (r = 0.24, p = 0.002) and anxiety (r = 0.28, p = 0.0004). In women, disinhibition mediated the association between percent TEI after 17:00 and TEI (β = 3.41 ± 1.43, 95% CI: 0.92, 6.47). Susceptibility to hunger mediated the association between percent TEI after 20:00 and TEI (β = 0.96 ± 0.59, 95% CI: 0.02, 2.34) in men and women. Conclusion Late eating is associated with TEI and suboptimal eating behaviours which could contribute to explaining the association between timing of food intake and obesity.
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Affiliation(s)
- Raphaëlle Jacob
- School of Nutrition, Université Laval, Quebec, QC, Canada
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada
- Quebec Heart and Lung Institute Research Centre, Université Laval, Quebec, QC, Canada
| | - Angelo Tremblay
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada
- Quebec Heart and Lung Institute Research Centre, Université Laval, Quebec, QC, Canada
- Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, QC, Canada
| | - Véronique Provencher
- School of Nutrition, Université Laval, Quebec, QC, Canada
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada
| | - Shirin Panahi
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada
- Quebec Heart and Lung Institute Research Centre, Université Laval, Quebec, QC, Canada
- Department of Physical Education, Faculty of Education, Université Laval, Quebec, QC, Canada
| | - Marie-Ève Mathieu
- School of Kinesiology and Physical Activity Sciences, Faculty of Medicine, Université de Montréal, Quebec, QC, Canada
- Sainte-Justine University Health Centre Research Centre, Université de Montreal, Quebec, QC, Canada
| | - Vicky Drapeau
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada
- Quebec Heart and Lung Institute Research Centre, Université Laval, Quebec, QC, Canada
- Department of Physical Education, Faculty of Education, Université Laval, Quebec, QC, Canada
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Peterson L, Lee H, Huybrechts I, Biessy C, Neuhouser ML, Haaland B, Krick B, Gunter M, Schulze MB, Jannasch F, Coletta AM, Hardikar S, Chaix A, Bauer CX, Xiao Q, Playdon MC. Reliability estimates for assessing meal timing derived from longitudinal repeated 24-hour dietary recalls. Am J Clin Nutr 2023; 117:964-975. [PMID: 36921904 PMCID: PMC10206325 DOI: 10.1016/j.ajcnut.2023.02.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 02/17/2023] [Accepted: 02/27/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Regulating meal timing may have efficacy for improving metabolic health for preventing or managing chronic disease. However, the reliability of measuring meal timing with commonly used dietary assessment tools needs characterization prior to investigating meal timing and health outcomes in epidemiologic studies. OBJECTIVES To evaluate the reliability of estimating meal timing parameters, including overnight fasting duration, the midpoint of overnight fasting time, the number of daily eating episodes, the period with the largest percentage of daily caloric intake, and late last eating episode (> 09:00 pm) from repeated 24-h dietary recalls (24HRs). METHODS Intraclass correlation coefficients (ICC), Light's Kappa estimates, and 95% CIs were calculated from repeated 24HR administered in 3 epidemiologic studies: The United States-based Interactive Diet and Activity Tracking in AARP (IDATA) study (n = 996, 6 24HR collected over 12-mo), German EPIC-Potsdam Validation Study (European Prospective Investigation into Cancer and Nutrition Potsdam Germany cohort) (n = 134, 12 24HR collected over 12-mo) and EPIC-Potsdam BMBF-II Study (Federal Ministry of Education and Research, "Bundesministerium für Bildung und Forschung") (n = 725, 4 24HR collected over 36 mo). RESULTS Measurement reliability of overnight fasting duration based on a single 24HR was "poor" in all studies [ICC range: 0.27; 95% CI: 0.23, 0.32 - 0.46; 95% CI: 0.43, 0.50]. Reliability was "moderate" with 3 24HR (ICC range: 0.53; 95% CI: 0.47, 0.58 in IDATA, 0.62; 95% CI: 0.52, 0.69 in the EPIC-Potsdam Validation Study, and 0.72; 95% CI: 0.70-0.75 in the EPIC-Potsdam BMBF-II Study). Results were similar for the midpoint of overnight fasting time and the number of eating episodes. Reliability of measuring late eating was "fair" in IDATA (Light's Kappa: 0.30; 95% CI: 0.21, 0.39) and "slight" in the EPIC-Potsdam Validation study and the EPIC-Potsdam BMBF-II study (Light's Kappa: 0.19; 95% CI: 0.15, 0.25 and 0.09; 95% CI: 0.06, 0.12, respectively). Reliability estimates differed by sex, BMI, weekday, and season of 24HR administration in some studies. CONCLUSIONS Our results show that ≥ 3 24HR over a 1-3-y period are required for reliable estimates of meal timing variables.
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Affiliation(s)
- Lacie Peterson
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, United States; Department Nutrition, Dietetics and Food Sciences, Utah State University, Logan, UT, United States; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, United States
| | - Hyejung Lee
- Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, United States
| | - Inge Huybrechts
- International Agency for Research on Cancer, WHO, Lyon, France
| | - Carine Biessy
- International Agency for Research on Cancer, WHO, Lyon, France
| | - Marian L Neuhouser
- Cancer Prevention Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Benjamin Haaland
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT, United States; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, United States
| | - Benjamin Krick
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, United States; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, United States
| | - Marc Gunter
- International Agency for Research on Cancer, WHO, Lyon, France
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany; NutriAct - Competence Cluster Nutrition Research Berlin-Potsdam, Nuthetal, Germany; Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Franziska Jannasch
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany; NutriAct - Competence Cluster Nutrition Research Berlin-Potsdam, Nuthetal, Germany
| | - Adriana M Coletta
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, United States; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, United States; Department of Health and Kinesiology, University of Utah, Salt Lake City, UT, United States
| | - Sheetal Hardikar
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, United States; Department of Population Health Sciences, University of Utah, Salt Lake City, UT, United States; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, United States
| | - Amandine Chaix
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, United States; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, United States; Department of Health and Kinesiology, University of Utah, Salt Lake City, UT, United States
| | - Cici X Bauer
- Department of Biostatistics and Data Science, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Qian Xiao
- Department of Epidemiology, Human Genetics, and Environmental Science, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Mary C Playdon
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, United States; Department of Population Health Sciences, University of Utah, Salt Lake City, UT, United States; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, United States.
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Wang L, Chan V, Allman-Farinelli M, Davies A, Wellard-Cole L, Rangan A. Wearable Cameras Reveal Large Intra-Individual Variability in Timing of Eating among Young Adults. Nutrients 2022; 14:nu14204349. [PMID: 36297030 PMCID: PMC9611808 DOI: 10.3390/nu14204349] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/13/2022] [Accepted: 10/16/2022] [Indexed: 11/16/2022] Open
Abstract
Studies have shown that young adults follow less structured eating patterns compared with older cohorts. This may have implications for dietary assessment methods which rely on memory and structured meal patterns. Our aim was to describe the intra-individual variation of eating times in young adults aged 18−30 years. Participants (n = 41) wore an Autographer camera that captured first-person perspective images every 30 s for three consecutive days. All images were timestamped and those showing food consumption were used to extract data such as the timing of the first and last eating occasions (EOs), number of EOs per day, and length of eating window. Intra-individual variability was calculated from these data using composite phase deviation (CPD) and coefficient of variation (CV). The number of individuals with high or very high variability was 28 and 18 for timing of first and last EOs, respectively (CPD > 1.70), and 27 and 17 for number of EOs and eating window, respectively (CV > 20%). In this sample of young adults, the lack of regularity in eating patterns should be considered when selecting a dietary assessment method.
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Affiliation(s)
- Leanne Wang
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Virginia Chan
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Margaret Allman-Farinelli
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Alyse Davies
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
| | - Lyndal Wellard-Cole
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Cancer Prevention and Advocacy Division, Cancer Council NSW, Sydney, NSW 2011, Australia
| | - Anna Rangan
- Discipline of Nutrition and Dietetics, Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW 2006, Australia
- Correspondence:
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10
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Eating architecture in adults at increased risk of type 2 diabetes: associations with body fat and glycaemic control. Br J Nutr 2022; 128:324-333. [PMID: 34348822 DOI: 10.1017/s0007114521002944] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Eating architecture is a term that describes meal frequency, meal timing and meal size and the daily variation in each of these. The aim of this study was to determine the relationship between components of eating architecture on body fat and markers of glycaemic control in healthy adults at increased risk of type 2 diabetes (T2DM). Participants (n 73, 39 males, age 58·8 (8·1) years, BMI 33·4 (4·4) kg/m2) recorded food intake and wore accelerometers and continuous glucose monitors (CGM) for 7-14 d under free-living conditions. Body fat and glycated Hb (HbA1c) were also measured. The mean and day-to-day variation (calculated as the standard deviation during the monitoring period) of each component of eating architecture were calculated. Multivariable linear regression models were constructed for three separate outcome variables (body fat mass, mean CGM glucose and HbA1c) for each component of eating architecture before and after adjustment for confounders. Higher variability in the time of first meal consumption was associated with increased body fat mass after adjusting for confounders (β = 0·227, 95 % CI: 0·019, 0·434, P = 0·033). Increased variability in the time lag from waking to first meal consumption was also positively associated with increased HbA1c after adjustment (β = 0·285, 95 % CI: 0·040, 0·530, P = 0·023). Low day-to-day variability in first meal consumption was associated with lower body fat and improved glucose control in adults at increased risk of T2DM. Routine consumption of meals may optimise temporal regulation to anticipate and respond appropriately to a glucose challenge.
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11
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Gioia SC, Guirette M, Chen A, Tucker C, Gray BE, Vetter C, Garaulet M, Scheer FAJL, Saxena R, Dashti HS. How Accurately Can We Recall the Timing of Food Intake? A Comparison of Food Times from Recall-Based Survey Questions and Daily Food Records. Curr Dev Nutr 2022; 6:nzac002. [PMID: 35198846 PMCID: PMC8856939 DOI: 10.1093/cdn/nzac002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 12/07/2021] [Accepted: 01/06/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND There currently are no standard, low-cost, and validated methods to assess the timing of food intake. OBJECTIVES The aim of this study was to validate simple, recall-based questions that can characterize food timing in free-living populations. METHODS The concordance between recall-based survey questions and food times estimated from multiple daily food records was assessed in 249 generally healthy, free-living adults from the Shift Work, Heredity, Insulin, and Food Timing (SHIFT) Study. At baseline, participants were asked: "At what time do you first start and stop eating on weekdays/workdays and weekends/non-workdays?" and "At what time do you have your main meal on weekdays/workdays and weekends/non-workdays?" Participants were then asked to complete ≤14 d of food records noting the start time of each eating occasion. The timing of the first, last, and main (largest percentage calories) eating occasions were determined from food records. Wilcoxon matched pairs signed rank and Kendall's coefficient of concordance were used to compare differences and determine agreements between the methods for these food timing parameters, as well as for the midpoint between first and last eating occasion. RESULTS Eating occasions on work and free days showed significant agreements between the 2 methods, except for the main eating occasion on free days. Significant agreements were generally modest and ranged from 0.16 (workdays main eating occasion) to 0.45 (workdays first eating occasion). Generally, times based on recall were later than those estimated from food records, and the differences in estimated times were smaller on workdays compared with free days, and smaller for the first compared with the last eating occasion. Main eating occasions from food records often varied between lunch and dinner times, contributing to low concordance with recalled times. CONCLUSIONS Modest agreements were found between food times derived from simple, recall-based survey questions and food times estimated from multiple-day food records. Single administration of these questions can effectively characterize the overall timing of eating occasions within a population for chrononutrition research purposes.
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Affiliation(s)
- Siena C Gioia
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mélanie Guirette
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Friedman School of Nutrition Science and Policy at Tufts, Tufts University, Boston, MA, USA
| | - Angela Chen
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Chandler Tucker
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brianna E Gray
- Translational and Clinical Research Centers, Massachusetts General Hospital, Boston, MA, USA
| | - Céline Vetter
- Department of Integrative Physiology, University of Colorado, Boulder, CO, USA
- Broad Institute, Cambridge, MA, USA
| | - Marta Garaulet
- Department of Physiology, University of Murcia, Murcia, Spain
- IMIB-Arrixaca, Murcia, Spain
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Frank A J L Scheer
- Broad Institute, Cambridge, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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12
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Robbins R, Quan SF, Barger LK, Czeisler CA, Fray-Witzer M, Weaver MD, Zhang Y, Redline S, Klerman EB. Self-reported sleep duration and timing: A methodological review of event definitions, context, and timeframe of related questions. SLEEP EPIDEMIOLOGY 2021; 1:100016. [PMID: 35761957 PMCID: PMC9233860 DOI: 10.1016/j.sleepe.2021.100016] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Study Objectives Clinical and population health recommendations are derived from studies that include self-report. Differences in question wording and response scales may significantly affect responses. We conducted a methodological review assessing variation in event definition(s), context (i.e., work- versus free-day), and timeframe (e.g., "in the past 4 weeks") of sleep timing/duration questions. Methods We queried databases of sleep, medicine, epidemiology, and psychology for survey-based studies and/or publications with sleep duration/timing questions. The text of these questions was thematically analyzed. Results We identified 53 surveys with sample sizes ranging from 93 to 1,185,106. For sleep duration, participants reported nocturnal sleep (24/44), sleep in the past 24-hours (14/44), their major sleep episode (3/44), or answered unaided (3/44). For bedtime, participants reported time into bed (19/47), first attempt to sleep (16/40), or fall-asleep time (12/47). For wake-time, participants reported wake-up time (30/43), the time they "get up" (7/43), or their out-of-bed time (6/43). Context guidance appeared in 18/44 major sleep duration, 35/47 bedtime, and 34/43 wake-time questions. Timeframe was provided in 8/44 major sleep episode duration, 16/47 bedtime, and 10/43 wake-time questions. One question queried the method of awakening (e.g., by alarm clock), 18 questions assessed sleep latency, and 12 measured napping. Conclusion There is variability in the event definition(s), context, and timeframe of questions relating to sleep. This work informs efforts at data harmonization for meta-analyses, provides options for question wording, and identifies questions for future surveys.
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Affiliation(s)
- Rebecca Robbins
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Stuart F. Quan
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Laura K. Barger
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Charles A. Czeisler
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | | | - Matthew D. Weaver
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Ying Zhang
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Elizabeth B. Klerman
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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13
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Kant AK, Graubard BI. Clock Time of First Eating Episode and Prospective Risk of All-Cause Mortality in US Adults. J Nutr 2021; 152:217-226. [PMID: 34718676 PMCID: PMC8754512 DOI: 10.1093/jn/nxab327] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 07/07/2021] [Accepted: 09/10/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND There is increasing recognition that a morning or evening preference is associated with time of eating, metabolic health, and morbidity. However, few studies have examined the association of time of eating with mortality. OBJECTIVES To examine the association of time of first recalled ingestive episode with the prospective risk of all-cause mortality. METHODS We used mortality-linked data from the NHANES conducted in 1988-1994 and 1999-2014 (n = 34,609; age ≥ 40 years). The exposure was quartiles (Q1-Q4) of clock time of first eating episode self-reported in the baseline 24-hour dietary recall. The outcome was follow-up time from the date of NHANES examination to the date of death or end of the follow-up period (31 December 2015). We used proportional hazards regression methods to determine the independent association of time of first eating episode with relative hazard of all-cause mortality, with adjustments for multiple covariates and the complex survey design. Multiple linear regression methods were used to examine the associations of time of first eating episode with baseline cardiometabolic biomarkers and dietary attributes. RESULTS In this national cohort, with a median age of ∼55 years (95% CI: 54.6-55.4 years) at baseline and a median follow-up of 8.3 years (IQR, 8.75 years), there were 10,303 deaths. The median times of first eating episodes in Q1-Q4 were 05:45, 07:00, 08:00, and 10:00, respectively. Covariate-adjusted relative hazards of mortality in Q1 to Q3 of the time of the first eating episode were 0.88 (95% CI: 0.81-0.96), 0.88 (95% CI: 0.81-0.95), 0.94 (95% CI: 0.87-1.02), with Q4 as the referent (P = 0.0008). Qualitative dietary attributes were inversely related with the time of the first eating episode; however, BMI and serum concentrations of glycemic biomarkers increased with later times of first eating episode (P ≤ 0.0001). CONCLUSIONS Recall of an earlier time of the first eating episode by ≥40-year-old US participants was suggestive of a small relative survival advantage in this observational study.
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Affiliation(s)
| | - Barry I Graubard
- Division of Cancer Epidemiology and Genetics, Biostatistics Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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14
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Fischer D, Klerman EB, Phillips AJK. Measuring sleep regularity: Theoretical properties and practical usage of existing metrics. Sleep 2021; 44:6232042. [PMID: 33864369 PMCID: PMC8503839 DOI: 10.1093/sleep/zsab103] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 02/18/2021] [Indexed: 01/06/2023] Open
Abstract
STUDY OBJECTIVES Sleep regularity predicts many health-related outcomes. Currently, however, there is no systematic approach to measuring sleep regularity. Traditionally, metrics have assessed deviations in sleep patterns from an individual's average. Traditional metrics include intra-individual standard deviation (StDev), Interdaily Stability (IS), and Social Jet Lag (SJL). Two metrics were recently proposed that instead measure variability between consecutive days: Composite Phase Deviation (CPD) and Sleep Regularity Index (SRI). Using large-scale simulations, we investigated the theoretical properties of these five metrics. METHODS Multiple sleep-wake patterns were systematically simulated, including variability in daily sleep timing and/or duration. Average estimates and 95% confidence intervals were calculated for six scenarios that affect measurement of sleep regularity: 'scrambling' the order of days; daily vs. weekly variation; naps; awakenings; 'all-nighters'; and length of study. RESULTS SJL measured weekly but not daily changes. Scrambling did not affect StDev or IS, but did affect CPD and SRI; these metrics, therefore, measure sleep regularity on multi-day and day-to-day timescales, respectively. StDev and CPD did not capture sleep fragmentation. IS and SRI behaved similarly in response to naps and awakenings but differed markedly for all-nighters. StDev and IS required over a week of sleep-wake data for unbiased estimates, whereas CPD and SRI required larger sample sizes to detect group differences. CONCLUSIONS Deciding which sleep regularity metric is most appropriate for a given study depends on a combination of the type of data gathered, the study length and sample size, and which aspects of sleep regularity are most pertinent to the research question.
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Affiliation(s)
- Dorothee Fischer
- Sleep and Human Factors Research, Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany.,Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Elizabeth B Klerman
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Andrew J K Phillips
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
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