Evidence map›Paper›PMID 31080628›Full record

ArticleBMC obesity2019

Towards personalised molecular feedback for weight loss.

Shilpa Tejpal, Narinder Sanghera, Vijayalaxmi Manoharan, Joan Planas-Iglesias, Kate Myler, Judith Klein-Seetharaman

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC obesity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
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

6 authors at 1 institution in 1 country.

Shilpa Tejpal1Systems Biology and Biomedicine, Division of Metabolic and Vascular Health, Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL UK.
Narinder Sanghera1Systems Biology and Biomedicine, Division of Metabolic and Vascular Health, Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL UK.
Vijayalaxmi Manoharan1Systems Biology and Biomedicine, Division of Metabolic and Vascular Health, Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL UK.
Joan Planas-Iglesias1Systems Biology and Biomedicine, Division of Metabolic and Vascular Health, Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL UK.
Kate Myler1Systems Biology and Biomedicine, Division of Metabolic and Vascular Health, Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL UK.
Judith Klein-Seetharaman1Systems Biology and Biomedicine, Division of Metabolic and Vascular Health, Medical School, University of Warwick, Gibbet Hill, Coventry, CV4 7AL UK.ORCID 0000-0002-4892-6828
University of Warwick · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNumerous diets, apps and websites help guide and monitor dietary behaviour with the goal of losing weight, yet dieting success is highly dependent on personal preferences and circumstances. To enable a more quantitative approach to dieting, we developed an integrated platform that allows tracking of life-style information alongside molecular biofeedback measurements (lactate and insulin).

methodsTo facilitate weight loss, participants (≥18 years) omitted one main meal from the usual three-meal routine. Daily caloric intake was restricted to ~1200KCal with one optional snack ≤250KCal. A mobile health platform (personalhealth.warwick.ac.uk) was developed and used to maintain diaries of food intake, weight, urine collection and volume. A survey was conducted to understand participants' willingness to collect samples, motivation for taking part in the study and reasons for dropout.

resultsMeal skipping resulted in weight loss after a 24 h period in contrast to 3-meal control days regardless of the meal that was skipped, breakfast, lunch or dinner (

conclusionIn a proof of concept study with a meal-skipping diet, we show that insulin and lactate values in urine correlate with weight loss, making these molecules potential candidates for quantitative feedback on food intake behaviour to people dieting.

Indexed as

App developmentBiomarkersInsulinLactateObesityWeight loss

Identifiers

PMID31080628
PMCPMC6501287
OpenAlexW2942929072

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.