Evidence map›Paper›PMID 39516361›Full record

SynthesisInternational journal of obesity (2005)2025

Combined lifestyle factors and metabolic syndrome risk: a systematic review and meta-analysis.

Yunyang Deng, Qingling Yang, Chun Hao, Harry Haoxiang Wang, Tongyu Ma, Xiangyan Chen, Fei-Wan Ngai, Yao Jie Xie

Abstract readSystematic ReviewMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in International journal of obesity (2005), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Review
  7. Lifestyle factors and cardiometabolic risk.Chinese medical journal · 2026
    Review
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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

8 authors.

Yunyang DengDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77, Stockholm, Sweden.
Qingling YangSchool of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Chun HaoSchool of Public Health, Sun Yat-Sen University, Guangzhou, China.
Harry Haoxiang WangSchool of Public Health, Sun Yat-Sen University, Guangzhou, China.ORCID 0000-0002-0361-6527
Tongyu MaDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China.ORCID 0000-0003-1831-2857
Xiangyan ChenDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Fei-Wan NgaiSchool of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Yao Jie XieSchool of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China. grace.yj.xie@polyu.edu.hk.ORCID 0000-0001-9289-4985

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesThe metabolic syndrome is a complex condition influenced by many factors including lifestyle. Recently, more and more studies explored the relationships between combined lifestyle factors (often measured as lifestyle scores/indices) and metabolic syndrome due to the co-occurrence of these factors. These scores/indices considered potential interactions among lifestyle factors, offering a more comprehensive understanding of their relationship with metabolic syndrome. However, no review/meta-analysis has been conducted to summarize existing evidence. Thus, this study aimed to synthesize the associations between lifestyle scores/indices and metabolic syndrome in cross-sectional and cohort studies. SUBJECTS/

methodsA literature search was performed in Embase and Medline. Multivariable-adjusted estimates were synthesized using random-effects models. In research where higher scores indicated better health, we used original estimates directly. In studies where higher scores denoted poorer health, we first calculated the coefficients and standard errors based on original estimates. Afterward, we reversed coefficients' directions and recalculated new estimates. Thus, the pooled estimates compared the healthiest with the least-healthy lifestyles (the highest vs. lowest scores/indices). Subgroup analyses were conducted based on study design, region, baseline time, baseline age, sex, health status, metabolic syndrome diagnosis, and lifestyles' number. Sensitivity analyses were performed by including only high-quality studies and employing leave-one-out analyses.

resultsNineteen studies from 16 publications were included. Physical activity, diet, and smoking were the top three included lifestyle factors. Compared to participants with the least-healthy lifestyles, those with the healthiest lifestyles had a 43% lower metabolic syndrome risk (95% confidence interval = 0.41-0.73). In subgroup analyses, healthy lifestyle scores/indices were inversely associated with both metabolic syndrome prevalence in cross-sectional studies (Odds ratio = 0.62; 95% confidence interval = 0.51-0.73) and metabolic syndrome incidence in cohort studies (Odds ratio = 0.40; 95% confidence interval = 0.11-0.68). The inverse association was consistent in other subgroup and sensitivity analyses.

conclusionsAdherence to a healthy lifestyle pattern was beneficial to metabolic syndrome prevention.

Indexed as

Life StyleMetabolic SyndromeHumansRisk Factors

Identifiers

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Registered trials

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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.