Evidence map›Paper›PMID 25960772›Full record

ArticleDiabetology & metabolic syndrome2014

Effects of diet and exercise interventions on diabetes risk factors in adults without diabetes: meta-analyses of controlled trials.

J A D Ranga Niroshan Appuhamy, Ermias Kebreab, Mitchell Simon, Rickey Yada, Larry P Milligan, James France

Open access · goldAbstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 28% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Promotion of healthy nutrition in clinical practice: A cross-sectional survey of practices and barriers among physiotherapists in southeast Nigeria.Hong Kong physiotherapy journal : official publication of the Hong Kong Physiotherapy Association Limited = Wu li chih liao · 2016
    Article
  10. 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

6 authors at 3 institutions in 2 countries.

J A D Ranga Niroshan AppuhamyDepartment of Animal and Poultry Science, Centre for Nutrition Modelling, University of Guelph, Guelph, N1G 2 W1 Ontario Canada ; Department of Animal Science, University of California, One Shield Avenue, Davis, CA 95616 USA.
Ermias KebreabDepartment of Animal Science, University of California, One Shield Avenue, Davis, CA 95616 USA.
Mitchell SimonDepartment of Animal Science, University of California, One Shield Avenue, Davis, CA 95616 USA.
Rickey YadaFaculty of Land and Food Systems, University of British Columbia, Vancouver, V6T 1Z4 Canada.
Larry P MilliganDepartment of Animal and Poultry Science, Centre for Nutrition Modelling, University of Guelph, Guelph, N1G 2 W1 Ontario Canada.
James FranceDepartment of Animal and Poultry Science, Centre for Nutrition Modelling, University of Guelph, Guelph, N1G 2 W1 Ontario Canada.
University of Guelph · CAUniversity of California, Davis · USUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsFasting insulin (FI), fasting glucose (FG), systolic blood pressure (SBP), high density lipoproteins (HDL), triacylglycerides (TAG), and body mass index (BMI) are well-known risk factors for type 2 diabetes. Reliable estimates of lifestyle intervention effects on these factors allow diabetes risk to be predicted accurately. The present meta-analyses were conducted to quantitatively summarize effects of diet and exercise intervention programs on FI, FG, SBP, HDL, TAG and BMI in adults without diabetes. MATERIALS AND

methodsMEDLINE and EMBASE were searched to find studies involving diet plus exercise interventions. Studies were required to use adults not diagnosed with type 2 diabetes, involve both dietary and exercise counseling, and include changes in diabetes risk factors as outcome measures. Data from 18, 24, 23, 30, 29 and 29 studies were used for the analyses of FI, FG, SBP, HDL, TAG and BMI, respectively. About 60% of the studies included exclusively overweight or obese adults. Mean age and BMI of participants at baseline were 48 years and 30.1 kg/m(2). Heterogeneity of intervention effects was first estimated using random-effect models and explained further with mixed-effects models.

resultsAdults receiving diet and exercise education for approximately one year experienced significant (P <0.001) reductions in FI (-2.56 ± 0.58 mU/L), FG (-0.18 ± 0.04 mmol/L), SBP (-2.77 ± 0.56 mm Hg), TAG (-0.258 ± 0.037 mmol/L) and BMI (-1.61 ± 0.13 kg/m(2)). These risk factor changes were related to a mean calorie intake reduction of 273 kcal/d, a mean total fat intake reduction of 6.3%, and 40 minutes of moderate intensity aerobic exercise four times a week. Lifestyle intervention did not have an impact on HDL. More than 99% of total variability in the intervention effects was due to heterogeneity. Variability in calorie and fat intake restrictions, exercise type and duration, length of the intervention period, and the presence or absence of glucose, insulin, or lipid abnormalities explained 23-63% of the heterogeneity.

conclusionsCalorie and total fat intake restrictions coupled with moderate intensity aerobic exercises significantly improved diabetes risk factors in healthy normoglycemic adults although normoglycemic adults with glucose, insulin, and lipid abnormalities appear to benefit more.

Identifiers

PMID25960772
PMCPMC4424492
OpenAlexW2146581721

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.