Table 1 Characteristics of the studies included in the meta-analysis
Study | Year | Country | Type of study | Cases with MetS | Total sample size | Mean age | Population | MetS definition | Selenium measurement | Gender (%males) | Sample type | Adjustment |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Huang | 2021 | China | Cross-sectional | 628 | 2109 | 60.18 ± 11.77 | Community-based | IDF | ICP-MS | Both (42.3%) | Urine | Age, gender, and BMI |
Feng | 2020 | China | Cohort | 254 | 1970 | 41.8 ± 10.2 | Community-based | Chinese criteria | ICP-MS | Male | Serum | Age, smoking, alcohol drinking, physical activity, education status, and family history |
Arnaud | 2010 | France | Cross-sectional | 293 | 1902 | 49.1 ± 7.5 | Community-based, diabetic-free population | IDF | Atomic absorption spectrometry | Both (66%) | Serum | Age, group, social status, physical activity, energy intake, alcohol consumption, smoking and hormonal status |
Lu | 2019 | Taiwan | Case-control | 709 | 1165 | 64.9 ± 10.3 | Hospital-based | NCEP-ATP III | ICP-MS | Both (36%) | Serum | Age, gender, current smoking status, current drinking status, physical activity, BMI, and HOMA-IR |
Schneider-Matyka | 2023 | Poland | Case-control | 72 | 390 | 52.59 ± 5.05 | Community-based | IDF | Spectrofluorimetry | Female | Serum | NR |
Fang | 2018 | China | Case-control | 125 | 698 | 65.35 ± 7.86 | Community-based | Chinese criteria | Atomic absorption spectrometry | Both (36%) | Serum | Smoking habit, alcohol consumption, physical activity and medication use at baseline |
Guo | 2019 | China | Cross-sectional | 80 | 145 | 39 ± 12 | Hospital-based | NCEP-ATP III | ICP-MS | Male | Serum | Age |
Deng | 2023 | China | Cross-sectional | 278 | 1451 | NR | Community-based | NR | NR | Male | Serum | NR |
Jang | 2018 | Republic of Korea | Cross-sectional | 40 | 500 | ≥ 35 | Community-based | NCEP-ATP III | Neutron activation analysis | Both (NR) | Toenail | Age, sex, education level, smoking status, physical activity level, alcohol consumption status and total energy intake, family history of diabetes, hypertension and cardiovascular disease |
Ma | 2020 | China | Cross-sectional | 526 | 3272 | 58.14 ± 10.49 | Community-based | NCEP-ATP III | ICP-MS | Both (26.4%) | Urine | Age, BMI, gender, race, education, smoking status, drinking status, traffic time, passive smoke status, city, medications, diet frequency, and physical activity status |
Zhou | 2020 | China | Case-control | 1279 | 2558 | 55.56 ± 10.46 | Community-based | The Joint Interim Statement | ICP-MS | Both (64%) | Serum | Sex, age, BMI, smoking, drinking, physical activity, and education level |
Pang | 2024 | China | Cross-sectional | 395 | 852 | 72.86 ± 5.87 | Community-based | NR | ICP-MS | Both (36.7%) | Serum | Gender, waistline, eGFR, age, smoke, drink, serum creatinine, health satisfaction |
Kelishadi | 2014 | Iran | Case-control | 160 | 320 | 15.3 ± 2.6 | Community-based | NCEP-ATP III | Atomic absorption spectrometry | Both (nr) | Serum | Age and sex |
Lu | 2016 | Taiwan | Case-control | 418 | 847 | 65.2 ± 9.6 | Hospital-based, patients with diabetes mellitus | IDF | ICP-MS | Both (64%) | Serum | NR |
Huang | 2022 | China | Cross-sectional | 149 | 1277 | 62.51 ± 8.44 | Hospital-based | Chinese criteria | ICP-MS | Both (44.3%) | Serum | Age, sex, smoking, drinking status and eGFR |
Yuan | 2015 | China | Case-control | 204 | 408 | 64.0 ± 6.4 | Community-based | Chinese criteria | Atomic absorption spectrometry | Both (44.1%) | Serum | Gender and age |
Guo | 2023 | China | Case-control | 292 | 584 | 73.4 ± 5.74 | Community-based | Chinese criteria | ICP-MS | Both (32.2%) | Serum | Age, sex, smoking status, drinking status. |
Zhang | 2020 | China | Case-control | 428 | 1033 | 60.1 ± 5.8 | Community-based | IDF | ICP-MS | Both (49.2%) | Serum | Education level, smoking status, alcohol intake status, BMI, physical activity, family history of disease. |