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Abstract
Objectives To evaluate the associations between alpha-lipoic acid (ALA) intake and intermediate disease markers in overweight or obese adults.
Design Systematic review and meta-analysis.
Data sources PubMed, EMBASE, Medline, APA PsycINFO, SocINDEX, CINAHL, SSRN, SocArXiv, PsyArXiv, medRxiv, and Google Scholar (from inception to October 2024).
Eligibility criteria This study included English-language randomised controlled trials (RCTs) on adults (body mass index ≥25 kg/m²) to assess the impact of ALA on intermediate disease markers. Studies lacking outcome data, duplicates or inaccessible full texts were excluded.
Data extraction and synthesis Paired reviewers independently extracted the data. We used frequentist meta-analysis to summarise the evidence, employing the DerSimonian and Laird estimator to account for heterogeneity across study designs, settings and measurement methods. Heterogeneity was assessed via the I² statistic with CIs and τ² values. The risk of bias was independently assessed by two reviewers according to the Cochrane Handbook, covering domains such as randomisation, blinding and data completeness. Publication bias was assessed using Begg’s test, while funnel plots and Egger’s test were applied to outcomes with 10 or more studies.
Results This meta-analysis included 11 RCTs from an initial screening of 431 studies, encompassing a total of 704 adults. The meta-analysis results revealed no significant associations were detected between ALA supplementation and changes in intermediate disease markers, including triglyceride (TG) (standardised mean difference (SMD): −0.08, 95% CI: −0.24 to 0.09, p=0.36, I²=0.00%, τ²=0.00), total cholesterol (TC) (SMD: 0.08, 95% CI: −0.55 to 0.71, p=0.80, I²=87.50%, τ²=0.52), high-density lipoprotein cholesterol (HDL-C) (SMD: −0.05, 95% CI: −0.22 to 0.11, p=0.52, I²=0.00%, τ²=0.00), low-density lipoprotein cholesterol (LDL-C) (SMD: −0.13, 95% CI: −0.40 to 0.15, p=0.37, I²=0.00%, τ²=0.00), homeostasis model assessment of insulin resistance (HOMA-IR) (SMD: −0.23, 95% CI: −0.60 to 0.15, p=0.23, I²=26.20%, τ²=0.05) and fasting blood glucose (FBS) (SMD: 0.13, 95% CI: −0.16 to 0.41, p=0.39, I²=29.40%, τ²=0.04). According to the Grading of Recommendations Assessment, Development and Evaluation bias assessment approach, eight studies were rated as having low bias (grade A), and three studies were rated as having moderate bias (grade B). Begg’s test indicated no evidence of publication bias.
Conclusions No significant associations were detected between ALA intake and intermediate disease markers, including TG, TC, HDL-C, LDL-C, HOMA-IR and FBS levels, in overweight or obese adults. Further research is needed to explore the potential associations of ALA, especially in high-risk populations with metabolic disorders, by employing longer intervention durations, higher dosages and optimised formulations.
PROSPERO registration number CRD42023450239.
- Obesity
- Meta-Analysis
- Other metabolic, e.g. iron, porphyria
Data availability statement
All data relevant to the study are included in the article or uploaded as supplementary information. Further details can be obtained from the corresponding author.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Data availability statement
All data relevant to the study are included in the article or uploaded as supplementary information. Further details can be obtained from the corresponding author.
Footnotes
YL and JZ contributed equally.
Contributors YL: conceptualisation, methodology, literature search, full-text reading, data extraction, quality assessment, data analysis, writing-review and editing. JZ: literature search, full-text reading, data extraction, quality assessment, data analysis,writing-review and editing. HG: project administration, validation, supervision and is the guarantor of this work, taking full responsibility for the integrity and accuracy of the research. I used AI technology to assist with formatting adjustments and translation in the submission. The AI was used solely for improving the document’s layout, ensuring consistency with submission requirements and translating content where necessary. No content generation or substantive edits were conducted by the AI.
Funding This work was supported by the West China Nursing Discipline Development Special Fund Project, Sichuan University (grant number HXHL21003) and project of Technology and Training of Sichuan Province under grant number 2021JDKP0043.
Competing interests None declared.
Patient and public involvement None.
Provenance and peer review Not commissioned; externally peer reviewed.
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