Evidence map›Paper›PMID 39554997›Full record

ArticleJournal of Taibah University Medical Sciences2024

Exercise intensities and metabolic health: Targeting blood glucose, insulin, and C-peptide levels in adults with prediabetes in the postprandial state.

Saman Tauqir, Syed S Shah, Inayat Shah, Saqib Ali

Abstract read
In one paragraph

Article in Journal of Taibah University Medical Sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Trial
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Saman TauqirDepartment of Physiology, Institute of Basic Medical Sciences, Khyber Medical University, Peshawar, Pakistan.
Syed S ShahDepartment of Physiology, Institute of Basic Medical Sciences, Khyber Medical University, Peshawar, Pakistan.
Inayat ShahDepartment of Physiology, Institute of Basic Medical Sciences, Khyber Medical University, Peshawar, Pakistan.
Saqib AliDepartment of Biomedical Dental Sciences, College of Dentistry, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Exercise improves postprandial glycaemia and insulin sensitivity in individuals with prediabetes, but the optimal intensity for this metabolic regulation remains unclear. The current study aims to explore the impact of various exercise intensities on metabolic markers in prediabetic individuals to identify the optimal intensity for improving these indicators. Methods: In this crossover study, 25 prediabetic individuals participated in exercise sessions at 50 %, 60 %, 70 %, and 80 % intensities of their predicted maximum heart rate using a treadmill. Each session lasted for 30 min, including a 5-min warm-up and a 5-min cool-down period. Blood samples were collected at four distinct time points: during fasting, immediately before exercise, and 30 and 60 min post-exercise. These samples were analyzed for glucose, insulin, and C-peptide levels. The effects of exercise intensity on these parameters were evaluated using repeated measures ANOVA, with post hoc tests conducted to determine specific differences between the intensities. Results: The participants had an average age of 34.88 years, a mean height of 170 cm, and a BMI of 30.34 kg/m². A significant reduction in insulin and glucose levels post-exercise was observed at 70 % intensity (p ≤ 0.001). Despite high fasting blood glucose levels (110-115 mg/dL), significant reductions were noted at 30 and 60 min post-exercise (p ≤ 0.001). Insulin levels approached near baseline at 70 % intensity, from fasting (26.74 ± 20.83) to 60 min post-exercise (28.47 ± 20.79), indicating a positive response at this intensity. C-peptide levels also showed significant changes, with the 70 % intensity exercise bringing them closest to fasting levels by 60 min post-exercise. Conclusion: This study highlights the importance of exercise intensities in enhancing metabolic parameters in prediabetic individuals. Specifically, 70 % of the predicted maximum heart rate was beneficial, optimizing insulin sensitivity and potentially reducing the risk of progressing from prediabetes to diabetes.

Indexed as

Blood glucoseC-peptideExerciseExercise intensitiesInsulinPrediabetes

Identifiers

PMID39554997
PMCPMC11566840

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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.