Randomized controlled trial for time-restricted eating in healthy volunteers without obesity.
Zhibo XieYuning SunYuqian YeDandan HuHua ZhangZhangyuting HeHaitao ZhaoHuayu YangYilei MaoPublished in: Nature communications (2022)
Time-restricted feeding (TRF) improves metabolic health. Both early TRF (eTRF, food intake restricted to the early part of the day) and mid-day TRF (mTRF, food intake restricted to the middle of the day) have been shown to have metabolic benefits. However, the two regimens have yet to be thoroughly compared. We conducted a five-week randomized trial to compare the effects of the two TRF regimens in healthy individuals without obesity (ChiCTR2000029797). The trial has completed. Ninety participants were randomized to eTRF (n=30), mTRF (n=30), or control groups (n=30) using a computer-based random-number generator. Eighty-two participants completed the entire five-week trial and were analyzed (28 in eTRF, 26 in mTRF, 28 in control groups). The primary outcome was the change in insulin resistance. Researchers who assessed the outcomes were blinded to group assignment, but participants and care givers were not. Here we show that eTRF was more effective than mTRF at improving insulin sensitivity. Furthermore, eTRF, but not mTRF, improved fasting glucose, reduced total body mass and adiposity, ameliorated inflammation, and increased gut microbial diversity. No serious adverse events were reported during the trial. In conclusion, eTRF showed greater benefits for insulin resistance and related metabolic parameters compared with mTRF. Clinical Trial Registration URL: http://www.chictr.org.cn/showproj.aspx?proj=49406 .
Keyphrases
- insulin resistance
- phase iii
- study protocol
- placebo controlled
- phase ii
- clinical trial
- double blind
- randomized controlled trial
- metabolic syndrome
- high fat diet induced
- open label
- adipose tissue
- high fat diet
- skeletal muscle
- type diabetes
- polycystic ovary syndrome
- healthcare
- weight loss
- public health
- glycemic control
- oxidative stress
- palliative care
- physical activity
- microbial community
- quality improvement
- health information
- pain management
- risk assessment
- blood glucose
- machine learning
- drug induced
- deep learning