Project/Area Number |
19K20199
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 59040:Nutrition science and health science-related
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Research Institution | Aichi Medical University |
Principal Investigator |
王 超辰 愛知医科大学, 医学部, 講師 (00758063)
|
Project Period (FY) |
2019-04-01 – 2022-03-31
|
Project Status |
Discontinued (Fiscal Year 2021)
|
Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2020: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2019: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
|
Keywords | chrononutrition / NDNS / nutritional epidemiology / latent class analysis / correspondence analysis / NDNS RP / diabetes / Chrono-nutrition / Latent class analysis / Correspondence analysis / Circadian eating pattern / MLCA |
Outline of Research at the Start |
The importance of circadian rhythms has been recognized for long, while its impact on nutrition is still largely unknown. The existence of grazers, early, and late eaters according to the timing of energy intake has been revealed recently. We plan to find time and quantity circadian eating patterns in the general population using the existing databases through objective, data-driven statistical approaches. Furthermore, associations between these patterns and health outcomes will be explored and provide evidence for strategies in lifestyle intervention and in prevention of chronic diseases.
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Outline of Annual Research Achievements |
Our studies used the UK's nutrition survey data to understand the real-world food choices at different time in the day and the association with type 2 diabetes (T2D).
We identified low, moderate, high carbohydrate (CH) eaters in the adult population and estimated the associations between these eaters and T2D by survey-designed multivariable regression models. On average, low-CH eaters consumed the highest amount of total energy and had higher percentages of energy contributed by fat and alcohol, especially after 8 pm. Moderate CH-eaters consumed the lowest amount of total energy while their meals were eaten later in the day. High CH-eaters consumed most of their CH and energy earlier in the day and within the time slots of traditional mealtimes. Low-CH eaters had greater odds than high-CH eaters of having T2D in self-reported but not in previously undiagnosed diabetics.
Moreover, we used unsupervised learning techniques to understand how foods were chosen in the day of time. We identified relationships between foods and time and described how these associations may vary by T2D. We analyzed the contingency table which cross-classifying food groups with eating time slots by correspondence analysis (CA). CA biplots were generated to explore the associations between food groups and time of eating across diabetes strata. We found that foods consumed in the evening/night time tend to be highly processed, easily accessible, and rich in added sugar or saturated fat. Individuals with undiagnosed diabetes are more likely to consume unhealthy foods at night.
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