Submitted:
24 January 2024
Posted:
26 January 2024
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Materials and Methods
2.1. Study Design

2.2. Setting and Recruitment
2.3. Participants
2.3.1. Screening
| Inclusion Criteria |
| 1) 18-39 years old. |
| 2) BMI 30-49.99 kg/m2. |
| 3) Own and use a smartphone, computer, or tablet with access to the Internet. |
| 4) Score ≥ 14 on the Perceived Stress Score (PSS) at screening. |
| Exclusion Criteria |
| 1) Have a personal or family history of EOCRC. |
| 2) Have taken antibiotics in the previous 2 months. |
| 3) Have an inflammatory bowel disease or genetic predisposition to EOCRC or CRC (e.g., Lynch syndrome). |
| 4) Any cancer diagnosis or cancer treatment in the past 12 months. |
| 5) Consume >50 grams ethanol daily (approximately 4-5, 12 ounces beers). |
| 6) Use combustible tobacco. |
| 7) Have history of bariatric surgery or bowel resection. |
| 8) Have an active infection. |
| 9) Have type 1 or type 2 diabetes, immunodeficiency/autoimmune disorder, or inflammatory bowel disease. |
| 10) Use fiber or pre-/probiotic supplements >3 days per week. |
| 11) Currently taking corticosteroids medication – inhaled, topical, or oral in the past 2 months (affects cortisol measures). |
| 12) Are on a weight-loss diet or involved in a formal weight-loss program or are not weight stable for 3 months (+/- 4.5 kg) prior to the study. |
| 13) Females who are pregnant/trying to become pregnant. |
| 14) Have schizophrenia (medication can affect study outcomes). |
| 15) Have an eating window of <10 hours/day or are currently following an intermittent fasting pattern. |
| 16) Night shift workers (shift passes midnight). |
| 17) Present a history of eating disorder. |
| 18) Currently taking weight loss medication. |
| 19) Illegal drug use in the past month (not marijuana). |
2.3.2. Inclusion Criteria
2.3.3. Exclusion Criteria
2.3.4. Randomization
2.4. Interventions
2.4.1. Time-Restricted Eating (TRE)
2.4.2. Mindfulness
| Week 1 | Week 2 | Week 3 | Week 4 | Week 5 | Week 6 | Week 7 | Week 8 |
| 1: The Big Idea (10 minutes) |
5: A Habit You Actually Want (10 minutes) |
9: Into the Still point (11 minutes) |
13: Body Wisdom (14 minutes) |
17: The Waxy Build-up (13 minutes) |
21: The Happiness Hit (11 minutes) | 25: Meditation Muscle Groups (13 minutes) |
29: Cosmic Burpee (11 minutes) |
| 2: Homebase (9 minutes) |
6: The Concentration Gym (11 minutes) |
10: Eye of the Hurricane (10 minutes) |
14: A Space Odyssey (13 minutes) |
18: Welcome to the Party (10 minutes) | 22: Strong Compassion (11 minutes) | 26: The Do-Nothing Project (10 minutes) |
30: Take the Power Back (13 minutes) |
| 3: Pop out of your thoughts (10 minutes) |
7: The Sweet Spot (10 minutes) |
11: Electric Clarity (11 minutes) |
15: Roller Coaster (13 minutes) |
19: Slow Motion (10 minutes) |
23: (Self) Love Bomb (13 minutes) | 27: No Agenda (10 minutes) |
- |
| 4: Inner Smoothness (11 minutes) |
8: Even Flow (10 minutes) |
12: Sanity Day (14 minutes) |
16: Free and Clear (14 minutes) |
20: Better at Everything (11 minutes) | 24: Connected from the Inside (11 minutes) |
28: The Answer (10 minutes) | - |
2.4.3. TRE & Mindfulness
2.4.4. Control
2.5. Intervention Fidelity
2.6. Data Collection and Measures
2.6.1. Body Weight and Body Composition
2.6.2. Dietary Intake
2.6.3. Physical Activity and Sleep Behavior
2.6.4. Circulating Biomarkers
2.6.5. Blood Pressure, Heart Rate, and Heart Rate Variability
2.6.6. Stool Collection
2.6.7. Microbial Amplicon Sequencing and Bioinformatics Processing
2.6.8. Colonic Inflammation
2.6.9. Hair Cortisol (HCORT)
2.6.10. Adverse Event Monitoring
2.6.11. Covariates That Could Influence Adherence and Intervention Effects
2.6.12. Power and Sample Size
2.6.13. Data Management
2.7. Data Analytic Plan
2.8. Design Considerations
2.8.1. Participant Retention
2.8.2. Participant Safety
2.8.3. Identified a Priori Limitations
2.8.4. Identified a Priori Innovations
3. Discussion and Conclusion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- Sinicrope, F.A., Increasing Incidence of Early-Onset Colorectal Cancer. New England Journal of Medicine, 2022. 386(16): p. 1547-1558. [CrossRef]
- Petrick, J.L., et al., Racial Disparities and Sex Differences in Early- and Late-Onset Colorectal Cancer Incidence, 2001–2018. Frontiers in Oncology, 2021. 11. [CrossRef]
- Boland, C.R., A. Goel, and S.G. Patel, The genetic and epigenetic landscape of early-onset colorectal cancer. Colorectal Cancer, 2020. 9(3): p. CRC23. [CrossRef]
- White, A., et al., A review of sex-related differences in colorectal cancer incidence, screening uptake, routes to diagnosis, cancer stage and survival in the UK. BMC Cancer, 2018. 18(1): p. 906. [CrossRef]
- Rebersek, M., Gut microbiome and its role in colorectal cancer. BMC Cancer, 2021. 21(1): p. 1325. [CrossRef]
- Li, H., et al., Associations of Body Mass Index at Different Ages With Early-Onset Colorectal Cancer. Gastroenterology, 2022. 162(4): p. 1088-1097.e3. [CrossRef]
- 2022 Adult Obesity Facts May 17, 2022 [cited 2023 11.16.2023]; Available from: https://www.cdc.gov/obesity/data/adult.html#print.
- Stone, T.W., M. McPherson, and L. Gail Darlington, Obesity and Cancer: Existing and New Hypotheses for a Causal Connection. EBioMedicine, 2018. 30: p. 14-28. [CrossRef]
- Sahoo, S. and C.R. Khess, Prevalence of depression, anxiety, and stress among young male adults in India: a dimensional and categorical diagnoses-based study. J Nerv Ment Dis, 2010. 198(12): p. 901-4. [CrossRef]
- Fawzy, M. and S.A. Hamed, Prevalence of psychological stress, depression and anxiety among medical students in Egypt. Psychiatry Res, 2017. 255: p. 186-194. [CrossRef]
- Mravec, B., M. Tibensky, and L. Horvathova, Stress and cancer. Part I: Mechanisms mediating the effect of stressors on cancer. J Neuroimmunol, 2020. 346: p. 577311. [CrossRef]
- Coelho, M., et al., Antiproliferative effects of β-blockers on human colorectal cancer cells. Oncol Rep, 2015. 33(5): p. 2513-20. [CrossRef]
- Hanahan, D., Hallmarks of Cancer: New Dimensions. Cancer Discovery, 2022. 12(1): p. 31-46. [CrossRef]
- Eckerling, A., et al., Stress and cancer: mechanisms, significance and future directions. Nat Rev Cancer, 2021. 21(12): p. 767-785. [CrossRef]
- Feller, L., et al., Chronic Psychosocial Stress in Relation to Cancer. Middle East Journal of Cancer, 2019. 10(1): p. 1-8. [CrossRef]
- Yan, Y.-X., et al., Investigation of the Relationship Between Chronic Stress and Insulin Resistance in a Chinese Population. Journal of epidemiology, 2016. 26(7): p. 355-360. [CrossRef]
- Xiao, Y., et al., Chronic stress, epigenetics, and adipose tissue metabolism in the obese state. Nutrition & metabolism, 2020. 17: p. 88-88. [CrossRef]
- Liu, Y.-Z., Y.-X. Wang, and C.-L. Jiang, Inflammation: The Common Pathway of Stress-Related Diseases. Frontiers in human neuroscience, 2017. 11: p. 316-316. [CrossRef]
- Foster, J.A., L. Rinaman, and J.F. Cryan, Stress & the gut-brain axis: Regulation by the microbiome. Neurobiol Stress, 2017. 7: p. 124-136. [CrossRef]
- Cani, P.D., et al., Involvement of gut microbiota in the development of low-grade inflammation and type 2 diabetes associated with obesity. Gut Microbes, 2012. 3(4): p. 279-88. [CrossRef]
- Wells, J.M., et al., Homeostasis of the gut barrier and potential biomarkers. Am J Physiol Gastrointest Liver Physiol, 2017. 312(3): p. G171-g193. [CrossRef]
- Song, M., A.T. Chan, and J. Sun, Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer. Gastroenterology, 2020. 158(2): p. 322-340. [CrossRef]
- Gabel, K., et al., Effects of 8-hour time restricted feeding on body weight and metabolic disease risk factors in obese adults: A pilot study. Nutr Healthy Aging, 2018. 4(4): p. 345-353. [CrossRef]
- Moro, T., et al., Effects of eight weeks of time-restricted feeding (16/8) on basal metabolism, maximal strength, body composition, inflammation, and cardiovascular risk factors in resistance-trained males. J Transl Med, 2016. 14(1): p. 290. [CrossRef]
- Jamshed, H., et al., Early Time-Restricted Feeding Improves 24-Hour Glucose Levels and Affects Markers of the Circadian Clock, Aging, and Autophagy in Humans. Nutrients, 2019. 11(6). [CrossRef]
- Sutton, E.F., et al., Early Time-Restricted Feeding Improves Insulin Sensitivity, Blood Pressure, and Oxidative Stress Even without Weight Loss in Men with Prediabetes. Cell Metab, 2018. 27(6): p. 1212-1221 e3. [CrossRef]
- Nehra, D., S. K.L, and V. Kumar, Mindfulness Based Stress Reduction: An Overview. 2013. p. 197-231. [CrossRef]
- Zhao, L., et al., Effect of Chronic Psychological Stress on Liver Metastasis of Colon Cancer in Mice. PLoS One, 2015. 10(10): p. e0139978. [CrossRef]
- Abdullah, M., et al., Gut Microbiota Profiles in Early- and Late-Onset Colorectal Cancer: A Potential Diagnostic Biomarker in the Future. Digestion, 2021. 102(6): p. 823-832. [CrossRef]
- Fulwiler, C., et al., Mindfulness-Based Interventions for Weight Loss and CVD Risk Management. Curr Cardiovasc Risk Rep, 2015. 9(10). [CrossRef]
- Xia, T., et al., A feasibility study on low-dose mindfulness-based stress reduction intervention among prediabetes and diabetes patients. Complement Ther Med, 2022. 65: p. 102810. [CrossRef]
- Bower, J.E., et al., Mindfulness meditation for younger breast cancer survivors: a randomized controlled trial. Cancer, 2015. 121(8): p. 1231-40. [CrossRef]
- Ponte Márquez, P.H., et al., Benefits of mindfulness meditation in reducing blood pressure and stress in patients with arterial hypertension. J Hum Hypertens, 2019. 33(3): p. 237-247. [CrossRef]
- Mind- and Body-Based Interventions Improve Glycemic Control in Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis. Journal of Integrative and Complementary Medicine. 0(0): p. null. [CrossRef]
- Yang, J., S. Tang, and W. Zhou, Effect of Mindfulness-Based Stress Reduction Therapy on Work Stress and Mental Health of Psychiatric Nurses. Psychiatr Danub, 2018. 30(2): p. 189-196. [CrossRef]
- Cherkin, D.C., et al., Effect of Mindfulness-Based Stress Reduction vs Cognitive Behavioral Therapy or Usual Care on Back Pain and Functional Limitations in Adults With Chronic Low Back Pain: A Randomized Clinical Trial. Jama, 2016. 315(12): p. 1240-9. [CrossRef]
- Pflugeisen, B.M., et al., Assessment of clinical trial participant patient satisfaction: a call to action. Trials, 2016. 17(1): p. 483. [CrossRef]
- Cohen, S., T. Kamarck, and R. Mermelstein, A global measure of perceived stress. Journal of Health and Social Behavior, 1983. 24: p. 385-396. [CrossRef]
- Torres, L., et al., Retention, Fasting Patterns, and Weight Loss With an Intermittent Fasting App: Large-Scale, 52-Week Observational Study. JMIR Mhealth Uhealth, 2022. 10(10): p. e35896. [CrossRef]
- Huberty, J.L., et al., Testing the Pragmatic Effectiveness of a Consumer-Based Mindfulness Mobile App in the Workplace: Randomized Controlled Trial. JMIR Mhealth Uhealth, 2022. 10(9): p. e38903. [CrossRef]
- Riegler, G. and I. Esposito, Bristol scale stool form. A still valid help in medical practice and clinical research. Tech Coloproctol, 2001. 5(3): p. 163-4. [CrossRef]
- Callahan, B.J., et al., Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses. F1000Res, 2016. 5: p. 1492. [CrossRef]
- Paulson, J.N., et al., Differential abundance analysis for microbial marker-gene surveys. Nat Methods, 2013. 10(12): p. 1200-2. [CrossRef]
- Shannon, C.E., A mathematical theory of communication. The Bell system technical journal, 1948. 27(3): p. 379-423. [CrossRef]
- Lozupone, C. and R. Knight, UniFrac: a New Phylogenetic Method for Comparing Microbial Communities. Applied and Environmental Microbiology, 2005. 71(12): p. 8228-8235. [CrossRef]
- Oksanen, J., et al., The Vegan Package. 2007.
- McMurdie, P.J. and S. Holmes, phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One, 2013. 8(4): p. e61217. [CrossRef]
- Mallick, H., et al., Multivariable Association Discovery in Population-scale Meta-omics Studies. bioRxiv, 2021: p. 2021.01.20.427420. [CrossRef]
- Bryce, C. and M. Bucaj, Fecal Calprotectin for the Evaluation of Inflammatory Bowel Disease. Am Fam Physician, 2021. 104(3): p. 303-304.
- Meyer, J., et al., Extraction and analysis of cortisol from human and monkey hair. J Vis Exp, 2014(83): p. e50882. [CrossRef]
- Meyer, J.S. and M.A. Novak, Minireview: Hair cortisol: a novel biomarker of hypothalamic-pituitary-adrenocortical activity. Endocrinology, 2012. 153(9): p. 4120-7. [CrossRef]
- Kalliokoski, O., F.K. Jellestad, and R. Murison, A systematic review of studies utilizing hair glucocorticoids as a measure of stress suggests the marker is more appropriate for quantifying short-term stressors. Scientific Reports, 2019. 9(1): p. 11997. [CrossRef]
- Slominski, R., C.R. Rovnaghi, and K.J. Anand, Methodological Considerations for Hair Cortisol Measurements in Children. Ther Drug Monit, 2015. 37(6): p. 812-20. [CrossRef]
- Brown, E.G., L. Wood, and S. Wood, The medical dictionary for regulatory activities (MedDRA). Drug Saf, 1999. 20(2): p. 109-17. [CrossRef]
- Spitzer, R.L., et al., A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med, 2006. 166(10): p. 1092-7. [CrossRef]
- Kroenke, K., et al., The PHQ-8 as a measure of current depression in the general population. J Affect Disord, 2009. 114(1-3): p. 163-73. [CrossRef]
- Taylor, M.J. and P.J. Cooper, Body size overestimation and depressed mood. Br J Clin Psychol, 1986. 25 ( Pt 2): p. 153-4. [CrossRef]
- Sallis, J.F., et al., The development of scales to measure social support for diet and exercise behaviors. Prev Med, 1987. 16(6): p. 825-36. [CrossRef]
- Stunkard, A.J. and S. Messick, The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J Psychosom Res, 1985. 29(1): p. 71-83. [CrossRef]
- Dahlem, N.W., G.D. Zimet, and R.R. Walker, The Multidimensional Scale of Perceived Social Support: a confirmation study. J Clin Psychol, 1991. 47(6): p. 756-61. [CrossRef]
- Buysse, D.J., et al., The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res, 1989. 28(2): p. 193-213. [CrossRef]
- Maxwell, S.E. and H.D. Delaney, Designing experiments and analyzing data : a model comparison perspective. 2nd ed. 2004, Mahwah, N.J.: Lawrence Erlbaum Associates.
- Davis, C.S., Statistical methods for the analysis of repeated measurements. Springer texts in statistics. 2002, New York: Springer. xxiv, 415 p. [CrossRef]
- Vonesh, E.F. and M.A. Schork, Sample sizes in the multivariate analysis of repeated measurements. Biometrics, 1986. 42(3): p. 601-10. [CrossRef]
- Overall, J.E. and S.R. Doyle, Estimating sample sizes for repeated measurement designs. Control Clin Trials, 1994. 15(2): p. 100-23. [CrossRef]
- Rencher, A.C., Multivariate statistical inference and applications. Wiley series in probability and statistics Texts and references section. 1998, New York: Wiley. xx, 559 p.
- Harris, P.A., et al., Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform, 2009. 42(2): p. 377-81. [CrossRef]
- Goldberg, S.B., et al., Hair cortisol as a biomarker of stress in mindfulness training for smokers. Journal of alternative and complementary medicine (New York, N.Y.), 2014. 20(8): p. 630-634. [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).