Evidence map›Paper›PMID 30977011›Full record

SynthesisSleep & breathing = Schlaf & Atmung2019

Experimental sleep restriction effect on adult body weight: a meta-analysis.

Haiqing Yu, Jiao Lu, Pengli Jia, Can Liu, Jingmin Cheng

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Sleep & breathing = Schlaf & Atmung, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Observational
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Haiqing YuThe School of management, Shanxi Medical University, Taiyuan, 030001, China.
Jiao LuThe School of management, Shanxi Medical University, Taiyuan, 030001, China.
Pengli JiaThe School of management, Shanxi Medical University, Taiyuan, 030001, China.
Can LiuThe School of management, Shanxi Medical University, Taiyuan, 030001, China.
Jingmin ChengThe School of management, Shanxi Medical University, Taiyuan, 030001, China. 72-87@163.com.

Funding

The ministry of education's humanities and social sciences research project No. 18YJA630015
6 · The paper itself

Abstract

backgroundSleep is increasingly recognized as a potential risk for overweight and obesity. Observational studies have shown links between short sleep duration with weight gain. However, the findings from longitudinal studies in adults are conflicting. This review aimed to examine the effectiveness of experimental sleep restriction on adult body weight.

methodA systematic search was undertaken in MEDLINE, EMBASE, PsycINFO, and CENTRAL (Cochrane center register of controlled trials) to identify experimental studies examining the effectiveness of sleep restriction on body weight, and search period was from January 2005 to June 2018. Meta-analysis was applied by using the random model.

resultsA total of 275 adults from six experimental studies were included. The pooled standard mean difference in body weight and body fat was 0.44 (95% CI - 0.13 to 1.02) (Z = 1.51, p > 0.05) and 0.35 kg (95% CI - 0.19 to 0.88) (Z = 1.27, p > 0.05), respectively. The experimental sleep restriction did not result in significant differences in adult body weight or body fat. Subgroup analysis showed that there were differences in weight gain between genders and races.

conclusionThe finding from this review cannot support the hypothesis from observational studies that short sleep leads to weight gain.

Indexed as

Sleep DeprivationAdultBody WeightCorrelation of DataFemaleHumansMaleAdultBody weightMeta-analysisSleep

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.