Evidence map›Paper›PMID 34070862›Full record

SynthesisNutrients2021

Pre-Sleep Casein Supplementation, Metabolism, and Appetite: A Systematic Review.

Justin Dela Cruz, David Kahan

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Nutrients, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 44% of its field
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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Review
  4. Review
  5. Article
  6. Article
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

2 authors at 1 institution in 1 country.

Justin Dela CruzSchool of Exercise and Nutritional Sciences, San Diego State University, San Diego, CA 92182, USA.
David KahanSchool of Exercise and Nutritional Sciences, San Diego State University, San Diego, CA 92182, USA.ORCID 0000-0002-3135-2215
San Diego State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein intake is an important factor for augmenting the response to resistance training in healthy individuals. Although food intake can help with anabolism during the day, the period of time during sleep is typically characterized by catabolism and other metabolic shifts. Research on the application of nighttime casein protein supplementation has introduced a new research paradigm related to protein timing. Pre-sleep casein supplementation has been attributed to improved adaptive response by skeletal muscle to resistance training through increases in muscle protein synthesis, muscle mass, and strength. However, it remains unclear what the effect of this nutritional strategy is on non-muscular parameters such as metabolism and appetite in both healthy and unhealthy populations. The purpose of this systematic review is to understand the effects of pre-sleep casein protein on energy expenditure, lipolysis, appetite, and food intake in both healthy and overweight or obese individuals. A systematic review following PRISMA guidelines was conducted in CINAHL, Cochrane, and SPORTDiscus during March 2021, and 11 studies met the inclusion criteria. A summary of the main findings shows limited to no effects on metabolism or appetite when ingesting 24-48 g of casein 30 min before sleep, but data are limited, and future research is needed to clarify the relationships observed.

Indexed as

Dietary SupplementsAppetiteCaseinsDrug Administration ScheduleHumansResistance TrainingSleepCaseinsappetitecaseinexercisemetabolismsleep

Identifiers

PMID34070862
PMCPMC8229753
OpenAlexW3164615963

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.