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Associations of short sleep duration with appetite-regulating hormones and adipokines: A systematic review and meta-analysis.

Jianfei LinYanrui JiangGuanghai WangMin MengQi ZhuHao MeiShijian LiuFan Jiang
Published in: Obesity reviews : an official journal of the International Association for the Study of Obesity (2020)
In the current study, a systematic review and meta-analysis were conducted to summarize and assess whether short sleep duration is associated with appetite-regulating hormones and adipokine levels. Reference databases were searched for studies related to sleep and appetite-regulating hormones and adipokines. Qualitative and quantitative syntheses were conducted to evaluate the relationship between sleep duration and the level of appetite-regulating hormones and adipokines, including leptin, ghrelin, adiponectin, resistin, and orexin. Twenty-one of 3536 studies, covering a total of 2250 participants, met the inclusion criteria. Leptin, ghrelin, and adiponectin were included in the meta-analysis. Ghrelin levels were higher in the short sleep group (standard mean difference [SMD] = 0.14, 95% CI [0.03, 0.25], p = 0.01). Significant differences between the short sleep group and recommended sleep group were also noted in leptin level experimental subgroup studies (SMD = 0.19, 95% CI [0.03, 0.35], p = 0.02) and ghrelin level cross-sectional subgroup studies (SMD = 0.14, 95% CI [0.02, 0.27], p = 0.03). A rise in leptin and ghrelin levels were also observed in sleep deprivation groups (SMD = 0.24, 95% CI [0.10, 0.39], p = 0.001 and SMD = 0.18, 95% CI [0.04, 0.33], p = 0.01, respectively). In conclusion, short sleep duration is associated with an increased ghrelin level, while sleep deprivation had a significant effect on the levels of both leptin and ghrelin.
Keyphrases
  • sleep quality
  • physical activity
  • case control
  • systematic review
  • weight loss
  • cross sectional
  • body weight
  • metabolic syndrome
  • growth hormone
  • clinical trial
  • depressive symptoms
  • type diabetes
  • big data
  • deep learning