Can Wearable Technology Help Guide Dieting Safety?

Can Wearable Technology Help Guide Dieting Safety? | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Case Report Can Wearable Technology Help Guide Dieting Safety? Maya Tang, Joseph Powell, Xiao Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5619684/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : The safety of dietary interventions is often unmonitored. Wearable technology can track elevations in resting heart rate (RHR), a marker of physiologic stress, which may provide safety information that is incremental to self-reported data. Methods : A single subject was placed on an isocaloric diet for four weeks. In weeks # 1 and 4, timing of food consumption was unregulated. In week #2, food was consumed during a three-hour feeding window (one-meal-a-day, OMAD). During week #3, food was consumed at six intervals, spaced three hours apart (6-meal diet). A Fitbit Versa™ was worn continuously, and questionnaires were administered twice daily. Results : Meal frequency did not affect the subject’s weight. Hunger scores from morning and night were widely split on OMAD and relatively constant on the 6-meal diet. Energy, happiness, irritability, and sleep scores were more favorable on the 6-meal diet than on OMAD. RHR extracted from the wearable device was lower during the 6-meal diet than during OMAD, especially in the late afternoon, evening, and nighttime (p<0.05). Lower RHR during the 6-meal diet corresponded to more favorable questionnaire scores. Conclusions : Changes in RHR patterns acquired by wearable technology are promising indicators of physiologic stress during dietary interventions. Wearable technology can provide physiologic data that are complementary to questionnaire scores or timed manual measurements. Nutrition & Dietetics dieting wearable technology resting heart rate Figures Figure 1 Figure 2 Figure 3 1. Introduction Dieting is primarily initiated as a means to promote weight loss. However, more recently, multiple diets have been promoted as providing additional health benefits, independent of weight loss [ 1 ]. For example, the intermittent fasting diet is a popular contemporary diet that has been studied in both animals and humans. This diet has been shown to have a metabolic and mortality benefit in animal models [ 2 , 3 ]. It has beneficial effects on human metabolism, including a positive impact on obesity, hypertension, insulin resistance, and inflammation [ 4 – 6 ]. In addition, it has been shown to lower cardiovascular risk and cancer risk [ 1 , 7 ]. The grazing diet, which consists of several small meals a day, has not been studied as well in the scientific community [ 8 ]. However, it is a very popular diet that receives a lot of attention on the internet. The impact of these types of diets on any given individual’s physiology is not well ascertained. Wearable technology provides an interesting method to track physiologic parameters such as heart rate, heart rate variability, activity tracking, and sleep tracking. Wearable devices have been used to monitor resting heart rate, which has been validated as a marker of both physiologic and mental stress [ 9 , 10 , 11 , 12 ]. The impact of dietary changes on physiologic markers of stress has not been well studied. Wearable technology provides a potential tool to track the impact of dieting on physiologic markers of stress in real time while an individual is making a dietary change [ 13 ]. If wearable technology proves to be useful in monitoring individuals during dietary changes, this information can be incorporated into dieting applications that help individuals track the success and safety of their diet plans. The aim of this study is to examine the effect of meal frequency on well-being and stress, using a combination of questionnaires, manually obtained vital signs, and physiologic data from wearable devices. If alteration of meal frequency in an isocaloric diet induces physiologic stress, then resting heart rate will increase. Furthermore, wearable technology data will provide incremental benefit in monitoring the safety of diets above questionnaire-based data. 2. Materials and Methods Patient Information This pilot study was conducted on a single study participant and was approved by the Case Western Reserve University’s Institutional Review Board, STUDY20240653. The study subject was a 48-year-old female with no underlying health conditions. The study subject signed voluntary informed consent to participate in a dietary intervention study utilizing wearable technology and manually collected data from questionnaires and vital sign measurements. For one month prior to collection of data, the study subject ceased consumption of all caffeinated foods and beverages. Furthermore, prior to data collection, the study subject’s usual diet was recorded, and the average daily caloric intake was used to construct the study diet. Study Diet The study diet was isocaloric and consisted of the following items: 1 string cheese, 1 low-fat yogurt, 75 grams of a broccoli, cauliflower, carrot vegetable blend, 1 jam sandwich (2 slices Italian bread, 1 tbsp strawberry jam, ½ tbsp butter), 1 Stouffer’s® Cheese French Bread pizza, and 5 cups of herbal non-caffeinated tea (no sugar or additives allowed). Diet Administration Week #1 of the study was a run-in control period to ensure reliable and consistent acquisition of data. During week #2, the study subject consumed the study diet in one-meal-a-day (OMAD), timed between 4-7pm. In week #3, the study diet was consumed over 6 time-intervals, spaced 3 hours apart (7am, 10am, 1pm, 4 pm, 7 pm, and 10pm). Week #4 was the second, wash-out, control period. During weeks #1 and 4, the timing of the study participant’s meals was not pre-specified, but the isocaloric diet was maintained. The timing of study beverages was not regulated during the study in order to avoid dehydration. Manual Data Collection The study participant collected data manually at 7am and 7pm. This data included vital sign information: systolic blood pressure (mm Hg), diastolic blood pressure (mm Hg), heart rate (bpm), oxygen saturation (%), and weight (lbs). Blood pressure and heart rate information were obtained using an automated blood pressure cuff placed on the upper arm. Oxygen saturation was obtained from a pulse oximeter placed on the subject’s finger. Weight was recorded from a digital scale. Well-being was gauged by a series of self-reported scales (Table 1 ). Sleepiness was assessed by two established sleep scales: the Epworth Sleepiness Scale (ESS) [ 14 ] Table 1 Scales for self-reported questionnaires. Score Hunger Irritability Energy Happiness 1 dizzy, nauseated, ill Stays angry contstantly No energy Very unhappy 2 extremely hungry Stays angry for long periods of time Tired, able to do few tasks Mildly unhappy 3 Hungry, stomach growling Angry for short periods of time Not tired, lacking motivation Neutral 4 “I could eat” Loses temper easily Mildly energetic Mildly happy 5 Not full but not hungry - neutral Loses temper when mildly provoked Very energetic Very happy 6 Full stomach but not satisfied Loses temper when heavily provoked 7 Satisfied Calm and positive most of the day 8 Uncomfortably full Calm and positive throughout the day 9 Stuffed, very uncomfortable Remains calm and positive when mildly provoked 10 Physically ill, nauseous, sick Remains calm and positive even when heavily provoked Wearable Data Collection A wearable device (Fitbit Versa™) was worn continuously during the study period, with the exception of a brief daily charging period that coincided with the study subject’s morning shower. Resting heart rate data was extracted from the wearable devices. Wearable data from minute time points was plotted over 24 hours and plotted on an hourly basis with box and whisker plots with a 1.5 interquartile range as the whisker boundary. Data were also analyzed in specific time periods: 7am to 7pm, 7pm to 7 am, 3pm to 11pm, and 11pm to 7am. Statistical Analysis Wilcoxon Rank Sum tests were used to compare the significance of the difference in resting heart rate between OMAD and the 6-meal diet, with p < 0.05 as the determinant of significance. All analyses were performed using R version 4.2.2 and Matlab R2019a. 3. Results Manually recorded vital signs, averaged for each week of the study period, are shown in Table 2. Heat rate data showed variation between morning and evening. Weight also fluctuated during the day but did not change substantially during the study period. Table 2. Averaged vital signs during study periods. Systolic BP (mmHg) Diastolic BP (mmHg) Heart rate (bpm) Oxygen Saturation (%) Weight (lb) Control 7am 94 61 89 98 93.9 Control 7pm 102 62 78 99 95.7 OMAD 7am 98 64 97 98 92.1 OMAD 7pm 105 65 83 99 94.3 6 meal 7am 96 63 101 98 91.5 6 meal 7pm 104 64 76 99 94.2 Control-2 7am 94 62 99 98 92.2 Control-2 7pm 106 66 70 100 94.9 1 Abbreviations: BP, blood pressure; OMAD, one meal a day. Quality of life data from self-reported questionnaires are shown in Figure 1. Hunger scores were widely split on OMAD (hungry in the morning and very full in the evening). In contrast, during the 6-meal diet, hunger scores were relatively constant. Energy, happiness, and irritability scores were more favorable on the 6-meal diet than on OMAD. Sleepiness was greater in the evening during OMAD than the 6-meal diet. Resting heart rate over a 24-hour period, extracted from the wearable device, is shown in Figure 2. Resting heart rate appeared overall lower during evening/night hours during the 6-meal diet. There were more oscillations in heart rate during the OMAD diet. The difference in resting heart rate between OMAD and the 6-meal diet was analyzed in 6 time periods: 24-hour (daily), 7am-7pm, 7pm-7am, 7am-3pm, 3pm-11pm, 11pm-7am (Figure 3). 4. Discussion Two contemporary, popular diets were assessed for their effects on subjective well-being and objective changes in resting heart rate (RHR). In the literature, the intermittent-fasting diet has been touted to have many health benefits beyond its effect on weight loss. One-meal-a-day (OMAD) is an extreme form of the intermittent fasting diet, during which all food is consumed in a very restricted time interval once a day. Other forms of intermittent fasting include a broader feeding interval of 8-10 hours a day or fasting for 2/7 days per week. In contrast, the grazing diet consists of several small meals a day. The impact of meal frequency on subjective and objective measures of well-being is not well reported. This study demonstrates that subjective scores of well-being were higher during the 6-meal diet intervention than during OMAD. More frequent meal timing led to greater energy and happiness, and less irritability and sleepiness. Interestingly, these subjective perceptions of well-being corresponded to an objectively lower RHR collected by wearable devices. Elevations in RHR have been shown to be indicative of physiologic and psychologic stress [9,10]. As such, this n=1 study indicated that for this study participant, the 6-meal diet produced less stress and greater well-being than the OMAD diet. While previous studies may be able to demonstrate the health benefits of a particular diet in a large population, wearable devices may be able to provide direct measures of the impact of a particular diet on an individual. This type of information may be useful in tailoring a diet plan to individuals with different metabolic needs and different underlying health conditions. Wearable devices are capable of collecting heart rate data continuously. This feature was instrumental in detecting a difference in the RHR between the 2 diets. In fact, the greatest impact on RHR was seen during sleeping hours. The manually collected heart rates at 7am and 7pm were an insensitive measure of the impact of diet on resting heart rate. This may be explained by the observation from the wearable devices that heart rate fluctuated significantly during different time periods of the day. Heart rate data collected manually at 2 time points may be influenced by the time of day, activity, position, proximity to meal consumption, and random sampling errors. Moreover, heart rate during sleep is completely missed by manual collection. This time interval, which had the least variability in heart rate, may be a very useful indicator of the impact on diet on physiologic stress. The wearable devices also showed some oscillations in heart rate during a 24-hour period, especially during the OMAD diet. The impact of diet on circadian rhythms is another physiologic parameter that can be captured by wearable devices with continuous heart rate monitoring. At this time, many diet plans utilize apps on smart phones in order to help people monitor their progress on the diet [11]. People can record information such as food intake, weight, and exercise times. Calorie and nutrition information is built-in to many of these apps, which helps to maintain a consistent and balanced diet. Wearable devices show promise in being able to integrate with diet apps to provide physiologic data that could guide the safety of the diet. This study was a pilot study that had several limitations. The study was conducted on a single individual over a 1-month study period. Since the study diet was highly regulated and was tailored to the study subject’s usual daily caloric intake, the pilot study was most feasible with a single subject. Single subject studies can be very useful in precision medicine. They help us to generate hypotheses and can demonstrate the effects of an intervention on an individual. Larger studies will likely require some tailoring of study diets to individual preferences and tolerability. This was particularly evident in the OMAD diet. Consumption of an entire day’s calories in a 3-hour time window had physical limitations that may vary from one individual to another. Each diet was maintained for a period of 1 week. In future studies, the diet duration would ideally be longer (e.g. 1-2 months) with a longer wash out period in between dietary interventions. It was not easy for the study participant to maintain the diet employed in this study for long periods of time due to the highly restricted food choices. If a study of longer duration is conducted, it may be necessary to offer study participants a greater variety of foods that still achieve an isocaloric diet. The reproducibility of the data observed in this study will need to be measured. The reproducibility of the findings using 2 distinct wearable devices and repeated tests of the same device would also increase the accuracy of the data. 5. Conclusion Changes in patterns of resting heart rate acquired by wearable technology are promising indicators of physiologic stress during dietary interventions. Data from this pilot study support the hypothesis that physiologic stress induced by alterations in meal-timing could be detected by an increase in resting heart rate. Furthermore, wearable devices provide physiologic data about the safety of dietary interventions that are complementary to information obtained by questionnaires and times manual measurements. Although further studies are needed, hopefully, in the future, data from wearable devices can be coupled with information in dieting/fitness apps to help individuals monitor the safety of their diet plans. Declarations Author Contributions: Conceptualization, M.M.T. and X.L.; methodology, J.R.P, X.L.; software, J.R.P.; validation, X.X., Y.Y. and Z.Z.; formal analysis, M.M.T., J.R.P..; investigation, X.L..; resources, X.L.; data curation, M.M.T..; writing—original draft preparation, M.M.T..; writing—review and editing, J.R.P., X.L..; supervision, X.L..; funding acquisition, X.L.. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by National Institutes of Health, grant number 1R01HL159170. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Case Western Reserve University (STUDY20240653 and date of approval July 2nd, 2024). Informed Consent Statement: Informed consent was obtained from subject involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper. Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request. Acknowledgments: None. Conflicts of Interest: The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. References Wei W, Jiang W, Huang J, Xu J, Wang X, Jiang X, Wang Y, Li G, Sun C, Li Y, Han T (2021) Association of Meal and Snack Patterns With Mortality of All-Cause, Cardiovascular Disease, and Cancer: The US National Health and Nutrition Examination Survey, 2003 to 2014. J Am Heart Assoc 10:e020254 Fuse Y, Hirao A, Kuroda H, Otsuka M, Tahara Y, Shibata S (2012) Differential roles of breakfast only (one meal per day) and a bigger breakfast with a small dinner (two meals per day) in mice fed a high-fat diet with regard to induced obesity and lipid metabolism. J Circadian Rhythms 10:4 Swindell WR (2012) Dietary restriction in rats and mice: a meta-analysis and review of the evidence for genotype-dependent effects on lifespan. Ageing Res Rev 11:254–270 Lopez-Minguez J, Gómez-Abellán P, Garaulet M (2019) Timing of Breakfast, Lunch, and Dinner. Effects on Obesity and Metabolic Risk. Nutrients 11:2624 Paoli A, Tinsley G, Bianco A, Moro T (2019) The Influence of Meal Frequency and Timing on Health in Humans: The Role of Fasting. Nutrients 11:719 Smeets AJ, Westerterp-Plantenga MS (2008) Acute effects on metabolism and appetite profile of one meal difference in the lower range of meal frequency. Br J Nutr 99:1316–1321 de Cabo R, Mattson MP (2019) Effects of Intermittent Fasting on Health, Aging, and Disease. N Engl J Med 381:2541–2551 Dashti HS, Mogensen KM, Recommending Small (2017) Frequent Meals in the Clinical Care of Adults: A Review of the Evidence and Important Considerations. Nutr Clin Pract 32:365–377 Chalmers T, Hickey BA, Newton P, Lin CT, Sibbritt D, McLachlan CS, Clifton-Bligh R, Morley J, Lal S (2021) Stress Watch: The Use of Heart Rate and Heart Rate Variability to Detect Stress: A Pilot Study Using Smart Watch Wearables. Sens (Basel) 22:151 Hickey BA, Chalmers T, Newton P, Lin CT, Sibbritt D, McLachlan CS, Clifton-Bligh R, Morley J, Lal S (2021) Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review. Sens (Basel) 21:3461 Li X, Dunn J, Salins D, Zhou G, Zhou W, Schüssler-Fiorenza Rose SM, Perelman D, Colbert E, Runge R, Rego S, Sonecha R, Datta S, McLaughlin T, Snyder MP (2017 Jan) Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information. PLoS Biol 15(1):e2001402. 10.1371/journal.pbio.2001402 eCollection 2017 Jan. PubMed PMID: 28081144; PubMed Central PMCID: PMC5230763 Mishra T, Wang M, Metwally AA, Bogu GK, Brooks AW, Bahmani A, Alavi A, Celli A, Higgs E, Dagan-Rosenfeld O, Fay B, Kirkpatrick S, Kellogg R, Gibson M, Wang T, Hunting EM, Mamic P, Ganz AB, Rolnik B, Li X, Snyder MP (2020 Dec) Pre-symptomatic detection of COVID-19 from smartwatch data. Nat Biomed Eng 4(12):1208–1220. 10.1038/s41551-020-00640-6 Epub 2020 Nov 18. PubMed PMID: 33208926 Limketkai BN, Mauldin K, Manitius N, Jalilian L, Salonen BR (2021) The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition. Curr Surg Rep 9:20 Johns MW (1991) A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 14(6):540–545 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 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5619684","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":388756039,"identity":"96ca01e3-5ebb-436b-8427-b1b25477ac9a","order_by":0,"name":"Maya Tang","email":"","orcid":"","institution":"Hathaway Brown School","correspondingAuthor":false,"prefix":"","firstName":"Maya","middleName":"","lastName":"Tang","suffix":""},{"id":388756040,"identity":"846434c5-93f3-4085-976c-65c81c32c816","order_by":1,"name":"Joseph Powell","email":"","orcid":"https://orcid.org/0000-0002-0798-2196","institution":"Case Western Reserve University","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Powell","suffix":""},{"id":388756041,"identity":"70e85671-885c-4209-9d13-b44a674f36e8","order_by":2,"name":"Xiao Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYFAC5oYDCQb/5GA8YrQwNh74UHDAmCQtzQdnfDiQ2EC0FoMbiQ2HeQzupPe3H3/4gKHCGqYXN5DsOQjS8ix3xpkcYwOGM+mEtfCzN4K0MOduYMhhk2BsO0xYCxszI1hLugH/8+c/GP8RoQVky8EZBocTDCQSzBiA2onzy4EPBmmGM268MZZIOJZuTFCLwY3kwx8S/tjI8/enP/zwocZalqAWVJBAmvJRMApGwSgYBbgAACF9RLdHZIGNAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-6413-3481","institution":"Case Western Reserve University","correspondingAuthor":true,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-12-10 22:38:30","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":true,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5619684/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5619684/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71220620,"identity":"52ae7afa-4b13-4c4c-a832-8adca4db0984","added_by":"auto","created_at":"2024-12-12 09:11:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":448213,"visible":true,"origin":"","legend":"\u003cp\u003eQuality of life data from self-reported questionnaires over study periods.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5619684/v1/99f00f8c657d8cc29bed7f2d.png"},{"id":71218907,"identity":"1695a237-130c-4975-b0c4-50f82b8d2c55","added_by":"auto","created_at":"2024-12-12 09:03:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":128901,"visible":true,"origin":"","legend":"\u003cp\u003eResting heart rate from wearable device over a 24-hour period.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5619684/v1/0c77c895a2d5612f51c8b3de.png"},{"id":71218898,"identity":"8885010a-f85b-4fae-ac82-ca308ff75b3c","added_by":"auto","created_at":"2024-12-12 09:03:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56249,"visible":true,"origin":"","legend":"\u003cp\u003eWearable analysis of resting heart rate at specific time intervals of study periods.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5619684/v1/4e0a92133f03cc61a19e714a.png"},{"id":71220859,"identity":"0db6bd6f-df24-4553-ad1e-ac86e6bac463","added_by":"auto","created_at":"2024-12-12 09:19:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1170455,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5619684/v1/40dfbbc1-b4cb-4e54-b966-c34cb2249ebf.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eCan Wearable Technology Help Guide Dieting Safety?\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDieting is primarily initiated as a means to promote weight loss. However, more recently, multiple diets have been promoted as providing additional health benefits, independent of weight loss [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. For example, the intermittent fasting diet is a popular contemporary diet that has been studied in both animals and humans. This diet has been shown to have a metabolic and mortality benefit in animal models [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It has beneficial effects on human metabolism, including a positive impact on obesity, hypertension, insulin resistance, and inflammation [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition, it has been shown to lower cardiovascular risk and cancer risk [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The grazing diet, which consists of several small meals a day, has not been studied as well in the scientific community [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, it is a very popular diet that receives a lot of attention on the internet.\u003c/p\u003e \u003cp\u003eThe impact of these types of diets on any given individual\u0026rsquo;s physiology is not well ascertained. Wearable technology provides an interesting method to track physiologic parameters such as heart rate, heart rate variability, activity tracking, and sleep tracking. Wearable devices have been used to monitor resting heart rate, which has been validated as a marker of both physiologic and mental stress [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The impact of dietary changes on physiologic markers of stress has not been well studied. Wearable technology provides a potential tool to track the impact of dieting on physiologic markers of stress in real time while an individual is making a dietary change [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. If wearable technology proves to be useful in monitoring individuals during dietary changes, this information can be incorporated into dieting applications that help individuals track the success and safety of their diet plans. The aim of this study is to examine the effect of meal frequency on well-being and stress, using a combination of questionnaires, manually obtained vital signs, and physiologic data from wearable devices. If alteration of meal frequency in an isocaloric diet induces physiologic stress, then resting heart rate will increase. Furthermore, wearable technology data will provide incremental benefit in monitoring the safety of diets above questionnaire-based data.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cem\u003ePatient Information\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThis pilot study was conducted on a single study participant and was approved by the Case Western Reserve University\u0026rsquo;s Institutional Review Board, STUDY20240653. The study subject was a 48-year-old female with no underlying health conditions. The study subject signed voluntary informed consent to participate in a dietary intervention study utilizing wearable technology and manually collected data from questionnaires and vital sign measurements. For one month prior to collection of data, the study subject ceased consumption of all caffeinated foods and beverages. Furthermore, prior to data collection, the study subject\u0026rsquo;s usual diet was recorded, and the average daily caloric intake was used to construct the study diet.\u003c/p\u003e\u003cp\u003e\u003cem\u003eStudy Diet\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe study diet was isocaloric and consisted of the following items: 1 string cheese, 1 low-fat yogurt, 75 grams of a broccoli, cauliflower, carrot vegetable blend, 1 jam sandwich (2 slices Italian bread, 1 tbsp strawberry jam, \u0026frac12; tbsp butter), 1 Stouffer\u0026rsquo;s\u0026reg; Cheese French Bread pizza, and 5 cups of herbal non-caffeinated tea (no sugar or additives allowed).\u003c/p\u003e\u003cp\u003e\u003cem\u003eDiet Administration\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWeek #1 of the study was a run-in control period to ensure reliable and consistent acquisition of data. During week #2, the study subject consumed the study diet in one-meal-a-day (OMAD), timed between 4-7pm. In week #3, the study diet was consumed over 6 time-intervals, spaced 3 hours apart (7am, 10am, 1pm, 4 pm, 7 pm, and 10pm). Week #4 was the second, wash-out, control period. During weeks #1 and 4, the timing of the study participant\u0026rsquo;s meals was not pre-specified, but the isocaloric diet was maintained. The timing of study beverages was not regulated during the study in order to avoid dehydration.\u003c/p\u003e\u003cp\u003e\u003cem\u003eManual Data Collection\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe study participant collected data manually at 7am and 7pm. This data included vital sign information: systolic blood pressure (mm Hg), diastolic blood pressure (mm Hg), heart rate (bpm), oxygen saturation (%), and weight (lbs). Blood pressure and heart rate information were obtained using an automated blood pressure cuff placed on the upper arm. Oxygen saturation was obtained from a pulse oximeter placed on the subject\u0026rsquo;s finger. Weight was recorded from a digital scale. Well-being was gauged by a series of self-reported scales (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Sleepiness was assessed by two established sleep scales: the Epworth Sleepiness Scale (ESS) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eScales for self-reported questionnaires.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHunger\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIrritability\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnergy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHappiness\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edizzy, nauseated, ill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStays angry contstantly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo energy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVery unhappy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eextremely hungry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStays angry for long periods of time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTired, able to do few tasks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMildly unhappy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHungry, stomach growling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAngry for short periods of time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot tired, lacking motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ldquo;I could eat\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLoses temper easily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMildly energetic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMildly happy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot full but not hungry - neutral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLoses temper when mildly provoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVery energetic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVery happy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull stomach but not satisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLoses temper when heavily provoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalm and positive most of the day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUncomfortably full\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalm and positive throughout the day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStuffed, very uncomfortable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRemains calm and positive when mildly provoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysically ill, nauseous, sick\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRemains calm and positive even when heavily provoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cem\u003eWearable Data Collection\u003c/em\u003e \u003c/p\u003e \u003cp\u003eA wearable device (Fitbit Versa\u0026trade;) was worn continuously during the study period, with the exception of a brief daily charging period that coincided with the study subject\u0026rsquo;s morning shower. Resting heart rate data was extracted from the wearable devices. Wearable data from minute time points was plotted over 24 hours and plotted on an hourly basis with box and whisker plots with a 1.5 interquartile range as the whisker boundary. Data were also analyzed in specific time periods: 7am to 7pm, 7pm to 7 am, 3pm to 11pm, and 11pm to 7am.\u003c/p\u003e \u003cp\u003e \u003cem\u003eStatistical Analysis\u003c/em\u003e \u003c/p\u003e \u003cp\u003eWilcoxon Rank Sum tests were used to compare the significance of the difference in resting heart rate between OMAD and the 6-meal diet, with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the determinant of significance. All analyses were performed using R version 4.2.2 and Matlab R2019a.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eManually recorded vital signs, averaged for each week of the study period, are shown in Table 2. Heat rate data showed variation between morning and evening. Weight also fluctuated during the day but did not change substantially during the study period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Averaged vital signs during study periods.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"702\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSystolic BP (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiastolic BP (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart rate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(bpm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOxygen Saturation (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(lb)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eControl 7am\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e93.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eControl 7pm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e95.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eOMAD 7am\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e92.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eOMAD 7pm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e94.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e6 meal 7am\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e91.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e6 meal 7pm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e94.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eControl-2 7am\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e92.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eControl-2 7pm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e94.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Abbreviations: BP, blood pressure; OMAD, one meal a day.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQuality of life data from self-reported questionnaires are shown in Figure 1. Hunger scores were widely split on OMAD (hungry in the morning and very full in the evening). In contrast, during the 6-meal diet, hunger scores were relatively constant. Energy, happiness, and irritability scores were more favorable on the 6-meal diet than on OMAD. Sleepiness was greater in the evening during OMAD than the 6-meal diet.\u003c/p\u003e\n\u003cp\u003eResting heart rate over a 24-hour period, extracted from the wearable device, is shown in Figure 2.\u003c/p\u003e\n\u003cp\u003eResting heart rate appeared overall lower during evening/night hours during the 6-meal diet. There were more oscillations in heart rate during the OMAD diet. The difference in resting heart rate between OMAD and the 6-meal diet was analyzed in 6 time periods: 24-hour (daily), 7am-7pm, 7pm-7am, 7am-3pm, 3pm-11pm, 11pm-7am (Figure 3).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTwo contemporary, popular diets were assessed for their effects on subjective well-being and objective changes in resting heart rate (RHR). \u0026nbsp;In the literature, the intermittent-fasting diet has been touted to have many health benefits beyond its effect on weight loss. One-meal-a-day (OMAD) is an extreme form of the intermittent fasting diet, during which all food is consumed in a very restricted time interval once a day. Other forms of intermittent fasting include a broader feeding interval of 8-10 hours a day or fasting for 2/7 days per week. In contrast, the grazing diet consists of several small meals a day. \u0026nbsp;The impact of meal frequency on subjective and objective measures of well-being is not well reported.\u003c/p\u003e\n\u003cp\u003eThis study demonstrates that subjective scores of well-being were higher during the 6-meal diet intervention than during OMAD. \u0026nbsp;More frequent meal timing led to greater energy and happiness, and less irritability and sleepiness. \u0026nbsp;Interestingly, these subjective perceptions of well-being corresponded to an objectively lower RHR collected by wearable devices. Elevations in RHR have been shown to be indicative of physiologic and psychologic stress [9,10]. \u0026nbsp;As such, this n=1 study indicated that for this study participant, the 6-meal diet produced less stress and greater well-being than the OMAD diet. \u0026nbsp;While previous studies may be able to demonstrate the health benefits of a particular diet in a large population, wearable devices may be able to provide direct measures of the impact of a particular diet on an individual. \u0026nbsp;This type of information may be useful in tailoring a diet plan to individuals with different metabolic needs and different underlying health conditions.\u003c/p\u003e\n\u003cp\u003eWearable devices are capable of collecting heart rate data continuously. \u0026nbsp;This feature was instrumental in detecting a difference in the RHR between the 2 diets. \u0026nbsp;In fact, the greatest impact on RHR was seen during sleeping hours. \u0026nbsp;The manually collected heart rates at 7am and 7pm were an insensitive measure of the impact of diet on resting heart rate. \u0026nbsp; This may be explained by the observation from the wearable devices that heart rate fluctuated significantly during different time periods of the day. \u0026nbsp;Heart rate data collected manually at 2 time points may be influenced by the time of day, activity, position, proximity to meal consumption, and random sampling errors. Moreover, heart rate during sleep is completely missed by manual collection. \u0026nbsp;This time interval, which had the least variability in heart rate, may be a very useful indicator of the impact on diet on physiologic stress. The wearable devices also showed some oscillations in heart rate during a 24-hour period, especially during the OMAD diet. The impact of diet on circadian rhythms is another physiologic parameter that can be captured by wearable devices with continuous heart rate monitoring.\u003c/p\u003e\n\u003cp\u003eAt this time, many diet plans utilize apps on smart phones in order to help people monitor their progress on the diet [11]. People can record information such as food intake, weight, and exercise times. Calorie and nutrition information is built-in to many of these apps, which helps to maintain a consistent and balanced diet. \u0026nbsp;Wearable devices show promise in being able to integrate with diet apps to provide physiologic data that could guide the safety of the diet.\u003c/p\u003e\n\u003cp\u003eThis study was a pilot study that had several limitations. \u0026nbsp;The study was conducted on a single individual over a 1-month study period. \u0026nbsp;Since the study diet was highly regulated and was tailored to the study subject\u0026rsquo;s usual daily caloric intake, the pilot study was most feasible with a single subject. \u0026nbsp; Single subject studies can be very useful in precision medicine. They help us to generate hypotheses and can demonstrate the effects of an intervention on an individual. \u0026nbsp;Larger studies will likely require some tailoring of study diets to individual preferences and tolerability. \u0026nbsp;This was particularly evident in the OMAD diet. \u0026nbsp; Consumption of an entire day\u0026rsquo;s calories in a 3-hour time window had physical limitations that may vary from one individual to another. \u0026nbsp;Each diet was maintained for a period of 1 week. In future studies, the diet duration would ideally be longer (e.g. 1-2 months) with a longer wash out period in between dietary interventions. \u0026nbsp;It was not easy for the study participant to maintain the diet employed in this study for long periods of time due to the highly restricted food choices. If a study of longer duration is conducted, it may be necessary to offer study participants a greater variety of foods that still achieve an isocaloric diet. \u0026nbsp;The reproducibility of the data observed in this study will need to be measured. \u0026nbsp;The reproducibility of the findings using 2 distinct wearable devices and repeated tests of the same device would also increase the accuracy of the data. \u0026nbsp;\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eChanges in patterns of resting heart rate acquired by wearable technology are promising indicators of physiologic stress during dietary interventions. \u0026nbsp;Data from this pilot study support the hypothesis that physiologic stress induced by alterations in meal-timing could be detected by an increase in resting heart rate. \u0026nbsp;Furthermore, wearable devices provide physiologic data about the safety of dietary interventions that are complementary to information obtained by questionnaires and times manual measurements. \u0026nbsp; Although further studies are needed, hopefully, in the future, data from wearable devices can be coupled with information in dieting/fitness apps to help individuals monitor the safety of their diet plans.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, M.M.T. and X.L.; methodology, J.R.P, X.L.; software, J.R.P.; validation, X.X., Y.Y. and Z.Z.; formal analysis, M.M.T., J.R.P..; investigation, X.L..; resources, X.L.; data curation, M.M.T..; writing\u0026mdash;original draft preparation, M.M.T..; writing\u0026mdash;review and editing, J.R.P., X.L..; supervision, X.L..; funding acquisition, X.L.. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by National Institutes of Health, grant number 1R01HL159170.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eThe study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Case Western Reserve University (STUDY20240653 and date of approval July 2nd, 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u0026nbsp;\u003c/strong\u003eInformed consent was obtained from subject involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e None.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflicts of interest. \u0026nbsp;The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWei W, Jiang W, Huang J, Xu J, Wang X, Jiang X, Wang Y, Li G, Sun C, Li Y, Han T (2021) Association of Meal and Snack Patterns With Mortality of All-Cause, Cardiovascular Disease, and Cancer: The US National Health and Nutrition Examination Survey, 2003 to 2014. J Am Heart Assoc 10:e020254\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuse Y, Hirao A, Kuroda H, Otsuka M, Tahara Y, Shibata S (2012) Differential roles of breakfast only (one meal per day) and a bigger breakfast with a small dinner (two meals per day) in mice fed a high-fat diet with regard to induced obesity and lipid metabolism. J Circadian Rhythms 10:4\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSwindell WR (2012) Dietary restriction in rats and mice: a meta-analysis and review of the evidence for genotype-dependent effects on lifespan. Ageing Res Rev 11:254\u0026ndash;270\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez-Minguez J, G\u0026oacute;mez-Abell\u0026aacute;n P, Garaulet M (2019) Timing of Breakfast, Lunch, and Dinner. Effects on Obesity and Metabolic Risk. Nutrients 11:2624\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaoli A, Tinsley G, Bianco A, Moro T (2019) The Influence of Meal Frequency and Timing on Health in Humans: The Role of Fasting. Nutrients 11:719\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmeets AJ, Westerterp-Plantenga MS (2008) Acute effects on metabolism and appetite profile of one meal difference in the lower range of meal frequency. Br J Nutr 99:1316\u0026ndash;1321\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Cabo R, Mattson MP (2019) Effects of Intermittent Fasting on Health, Aging, and Disease. N Engl J Med 381:2541\u0026ndash;2551\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDashti HS, Mogensen KM, Recommending Small (2017) Frequent Meals in the Clinical Care of Adults: A Review of the Evidence and Important Considerations. Nutr Clin Pract 32:365\u0026ndash;377\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChalmers T, Hickey BA, Newton P, Lin CT, Sibbritt D, McLachlan CS, Clifton-Bligh R, Morley J, Lal S (2021) Stress Watch: The Use of Heart Rate and Heart Rate Variability to Detect Stress: A Pilot Study Using Smart Watch Wearables. Sens (Basel) 22:151\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHickey BA, Chalmers T, Newton P, Lin CT, Sibbritt D, McLachlan CS, Clifton-Bligh R, Morley J, Lal S (2021) Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review. Sens (Basel) 21:3461\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Dunn J, Salins D, Zhou G, Zhou W, Sch\u0026uuml;ssler-Fiorenza Rose SM, Perelman D, Colbert E, Runge R, Rego S, Sonecha R, Datta S, McLaughlin T, Snyder MP (2017 Jan) Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information. PLoS Biol 15(1):e2001402. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pbio.2001402\u003c/span\u003e\u003cspan address=\"10.1371/journal.pbio.2001402\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003eeCollection 2017 Jan. PubMed PMID: 28081144; PubMed Central PMCID: PMC5230763\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMishra T, Wang M, Metwally AA, Bogu GK, Brooks AW, Bahmani A, Alavi A, Celli A, Higgs E, Dagan-Rosenfeld O, Fay B, Kirkpatrick S, Kellogg R, Gibson M, Wang T, Hunting EM, Mamic P, Ganz AB, Rolnik B, Li X, Snyder MP (2020 Dec) Pre-symptomatic detection of COVID-19 from smartwatch data. Nat Biomed Eng 4(12):1208\u0026ndash;1220. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41551-020-00640-6\u003c/span\u003e\u003cspan address=\"10.1038/s41551-020-00640-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003eEpub 2020 Nov 18. PubMed PMID: 33208926\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLimketkai BN, Mauldin K, Manitius N, Jalilian L, Salonen BR (2021) The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition. Curr Surg Rep 9:20\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohns MW (1991) A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 14(6):540\u0026ndash;545\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDisclaimer/Publisher\u0026rsquo;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\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"3821082b-2245-406b-9501-a67e89c617a7","identifier":"10.13039/100000002","name":"National Institutes of Health","awardNumber":"1R01HL159170","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Case Western Reserve University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"dieting, wearable technology, resting heart rate","lastPublishedDoi":"10.21203/rs.3.rs-5619684/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5619684/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The safety of dietary interventions is often unmonitored. Wearable technology can track elevations in resting heart rate (RHR), a marker of physiologic stress, which may provide safety information that is incremental to self-reported data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A single subject was placed on an isocaloric diet for four weeks. In weeks # 1 and 4, timing of food consumption was unregulated. In week #2, food was consumed during a three-hour feeding window (one-meal-a-day, OMAD). During week #3, food was consumed at six intervals, spaced three hours apart (6-meal diet). A Fitbit Versa™ was worn continuously, and questionnaires were administered twice daily.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Meal frequency did not affect the subject’s weight. Hunger scores from morning and night were widely split on OMAD and relatively constant on the 6-meal diet. Energy, happiness, irritability, and sleep scores were more favorable on the 6-meal diet than on OMAD. RHR extracted from the wearable device was lower during the 6-meal diet than during OMAD, especially in the late afternoon, evening, and nighttime (p\u0026lt;0.05). Lower RHR during the 6-meal diet corresponded to more favorable questionnaire scores.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Changes in RHR patterns acquired by wearable technology are promising indicators of physiologic stress during dietary interventions. Wearable technology can provide physiologic data that are complementary to questionnaire scores or timed manual measurements.\u003c/p\u003e","manuscriptTitle":"Can Wearable Technology Help Guide Dieting Safety?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-12 09:03:44","doi":"10.21203/rs.3.rs-5619684/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8ad9b1f3-7fb7-413b-a614-befcdfb3b5dd","owner":[],"postedDate":"December 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":41432959,"name":"Nutrition \u0026 Dietetics"}],"tags":[],"updatedAt":"2024-12-12T09:03:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-12 09:03:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5619684","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5619684","identity":"rs-5619684","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}