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| Name | Class |
|---|---|
| National University of Malaysia | OTHER |
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Chronotype and chrononutrition, both are emerging research fields in nutritional epidemiology. However, its association with glycemic control in the global population is less clear. A better understanding of how activity/ eating time can influence glucose levels in prediabetic individuals may improve strategies for blood glucose control. The present paper aims to determine the associations of chronotype and chrononutrition with glucose tolerance among prediabetic individuals in Malaysia.
This is a prospective longitudinal study named Chrono-DMTM, that targets to recruit 166 newly diagnosed prediabetic individuals from the community clinics in Malacca, Malaysia. Respondents will be followed-up for 6 months: (1) baseline (1st oral glucose tolerance test (OGTT)); (2) second visit (at 3rd month); and (3) third visit (2nd OGTT at 6th month). Data collection includes sociodemographic and anthropometry measurements (weight, height, body fat, visceral fat, waist and hip circumference). Dietary intake and meal timing are collected using the 3-day dietary record while data on sleep pattern, light exposure, chronotype and chrononutrition will be collected using validated questionnaires. Physical activity will be captured using a validated IPAQ questionnaire and pedometer during periods of wearing Continuous glucose monitoring (CGM) sensor. CGM, fasting plasma glucose (FBG), OGTT and HbA1c are performed to assess glycemic outcomes.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control Group | Prediabetes patients aged 18-65 years old, who plan to continue healthcare services at a community clinic in Malacca, no literacy barries |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Lifestyle Intervention | Behavioral | Circadian misalignment contributes to the high glycemic outcome. To adjust meal timing earlier and avoid late-night meal eating patterns, to switch from the evening chronotype to morning chronotype possibility to reverse glucose fluctuation conditions. |
| Measure | Description | Time Frame |
|---|---|---|
| The change of baseline glycated hemoglobin (HbA1c) among prediabetes adults at 6 months. | The results displayed in unit (%) | Baseline to 6 months |
| The change of baseline fasting plasma glucose (FPG) among prediabetes adults at 6 months. | The results displayed in unit (mmol/L). | Baseline to 6 months |
| The change of baseline 2-hour post-load plasma glucose among prediabetes adults at 6 months. | The results displayed in unit (mmol/L). | Baseline to 6 months |
| The change of baseline continuous glucose monitoring (CGM) profile among prediabetes adults at 6 months. | The results displayed in glycemic variability. | Baseline to 6 months |
| Measure | Description | Time Frame |
|---|---|---|
| The change of eating misalignment among prediabetes adults at 6 months | By using the validated questionnaire Chrononutrition Profile Questionnaire (CPQ), the six different chrononutrition behaviors, which are breakfast skipping, largest meal, evening eating, evening latency, night eating, and eating window can be collected. The CP-Q is used to evaluate eating misalignment. Eating misalignment is discrepancies between when people prefer to eat and when participants actually eat. Discrepancies can be calculated by using the chrononutrition behavior values for the item of interest. These are then subtracted from the preference value as measured by the CP-Q. |
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Inclusion Criteria:
Exclusion Criteria:
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The proposed study will be conducted in community clinics in Malacca, Malaysia. Malacca is the capital of the coastal stage, located in southwestern Malaysia, with an estimated total population of 0.93 million in the year 2019 (Department of Survey and Mapping Malaysia, 2021). In 2019, National Health and Morbidity Survey reported that 17% of Malaccan adults had hyperglycemia and 13.7% of them had known diabetes. Malacca is 1 out of the top five states showing the highest prevalence of diabetes in Malaysia (IPH, NIH and MOH, 2019). Prediabetes and diabetes will be defined according to the latest Clinical Practice Guideline in Malaysia (WHO & IDF, 2006; ADA, 2020; MOH et al., 2020).
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Community Clinic Sungai Udang | Melaka Tengah | Melaka | 75350 | Malaysia | ||
| Community Clinic Ayer Keroh |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34444846 | Background | Wirth MD, Zhao L, Turner-McGrievy GM, Ortaglia A. Associations between Fasting Duration, Timing of First and Last Meal, and Cardiometabolic Endpoints in the National Health and Nutrition Examination Survey. Nutrients. 2021 Aug 3;13(8):2686. doi: 10.3390/nu13082686. | |
| 30510391 | Background | Mezitis NHE, Bhatnagar V. Chrononutrition Applied to Diabetes Management: A Paradigm Shift Long Delayed. Diabetes Spectr. 2018 Nov;31(4):349-353. doi: 10.2337/ds18-0014. No abstract available. |
| Label | URL |
|---|---|
| Effect of a 2-hour interval between dinner and bedtime on glycated haemoglobin levels in middle-aged and elderly Japanese people: a longitudinal analysis of 3-year health check-up data. | View source |
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The validation and reliability of Chrononutrition Profile Questionnaire planned to share with researchers but the other data are not shared with other researchers.
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP_ICF | Yes | Yes | Yes | Study Protocol, Statistical Analysis Plan, and Informed Consent Form | May 6, 2024 | May 6, 2024 | Prot_SAP_ICF_004.pdf |
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| ID | Term |
|---|---|
| D011236 | Prediabetic State |
| D003924 | Diabetes Mellitus, Type 2 |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| Baseline to 6 months |
| The change of chronotype among prediabetes adults at 6 months. | By using the validated questionnaire Munich Chronotype Questionnaire (MCTQ), participants will be categorized into morning type, evening type, and neither type for the chronotype category data. | Baseline to 6 months |
| Melaka Tengah |
| Melaka |
| 75450 |
| Malaysia |
| Community Clinic Ayer Molek | Melaka Tengah | Melaka | 75450 | Malaysia |
| Community Clinic Bukit Rambai | Melaka Tengah | Melaka | 75450 | Malaysia |
| Community Clinic Jalan Gereja | Melaka Tengah | Melaka | 75450 | Malaysia |
| Community Clinic Klebang Besar | Melaka Tengah | Melaka | 75450 | Malaysia |
| Community Clinic Seri Tanjung | Melaka Tengah | Melaka | 75450 | Malaysia |
| Community Clinic Tengkera | Melaka Tengah | Melaka | 75450 | Malaysia |
| Community Clinic Ujong Pasir | Melaka Tengah | Melaka | 75450 | Malaysia |
| Community Clinic Peringgit | Malacca | 75450 | Malaysia |
| Community Clinic Batu Berendam | Malacca | 77000 | Malaysia |
| 32761356 | Background | Hawley JA, Sassone-Corsi P, Zierath JR. Chrono-nutrition for the prevention and treatment of obesity and type 2 diabetes: from mice to men. Diabetologia. 2020 Nov;63(11):2253-2259. doi: 10.1007/s00125-020-05238-w. Epub 2020 Aug 6. |
| 26598903 | Background | Oda H. Chrononutrition. J Nutr Sci Vitaminol (Tokyo). 2015;61 Suppl:S92-4. doi: 10.3177/jnsv.61.S92. |
| 28143856 | Background | Jiang P, Turek FW. Timing of meals: when is as critical as what and how much. Am J Physiol Endocrinol Metab. 2017 May 1;312(5):E369-E380. doi: 10.1152/ajpendo.00295.2016. Epub 2017 Jan 31. |
| 29375081 | Result | Sakai R, Hashimoto Y, Ushigome E, Miki A, Okamura T, Matsugasumi M, Fukuda T, Majima S, Matsumoto S, Senmaru T, Hamaguchi M, Tanaka M, Asano M, Yamazaki M, Oda Y, Fukui M. Late-night-dinner is associated with poor glycemic control in people with type 2 diabetes: The KAMOGAWA-DM cohort study. Endocr J. 2018 Apr 26;65(4):395-402. doi: 10.1507/endocrj.EJ17-0414. Epub 2018 Jan 27. |
| 28549298 | Result | Imai S, Kajiyama S, Hashimoto Y, Yamane C, Miyawaki T, Ozasa N, Tanaka M, Fukui M. Divided consumption of late-night-dinner improves glycemic excursions in patients with type 2 diabetes: A randomized cross-over clinical trial. Diabetes Res Clin Pract. 2017 Jul;129:206-212. doi: 10.1016/j.diabres.2017.05.010. Epub 2017 May 16. |
| 30410377 | Result | Gouda M, Matsukawa M, Iijima H. Associations between eating habits and glycemic control and obesity in Japanese workers with type 2 diabetes mellitus. Diabetes Metab Syndr Obes. 2018 Oct 17;11:647-658. doi: 10.2147/DMSO.S176749. eCollection 2018. |
| 28128995 | Result | Anothaisintawee T, Lertrattananon D, Thamakaison S, Knutson KL, Thakkinstian A, Reutrakul S. Later chronotype is associated with higher hemoglobin A1c in prediabetes patients. Chronobiol Int. 2017;34(3):393-402. doi: 10.1080/07420528.2017.1279624. Epub 2017 Jan 27. |
| 41810501 | Derived | Chong GY, Kaur S, Abd Talib R, Loy SL, Tan HY, Binti Abdullah R, Binti Mahmud H, Siah WY, Kee CC, Koo HC. Exploration of the longitudinal associations between sleep behaviours, anthropometric measurements and body composition in adults with prediabetes. Chronobiol Int. 2026 Jun;43(6):911-923. doi: 10.1080/07420528.2026.2638533. Epub 2026 Mar 11. |
| 40832725 | Derived | Chong GY, Kaur S, Abd Talib R, Loy SL, Tan HY, Binti Abdullah R, Binti Mahmud H, Siah WY, Tan LK, Kee CC, Koo HC. Association between chrononutrition, sleep behaviours, and glycaemic outcomes in individuals with prediabetes: Findings from the Chrono-DMTM study. Chronobiol Int. 2025 Oct;42(10):1328-1340. doi: 10.1080/07420528.2025.2543298. Epub 2025 Aug 20. |
| 35922777 | Derived | Chong GY, Kaur S, Talib RA, Loy SL, Tan HY, Harjit Singh SS, Abdullah RB, Mahmud HB, Siah WY, Koo HC. Chronotype, chrononutrition and glucose tolerance among prediabetic individuals: research protocol for a prospective longitudinal study Chrono-DM. BMC Prim Care. 2022 Aug 4;23(1):193. doi: 10.1186/s12875-022-01815-7. |
| D004700 | Endocrine System Diseases |