Table 1.
General characteristics of included studies
| Author, Year | Study design | Sample size | Study population | Mean Age (SD) | metal | Concentration mean (sd) /quartiles | measurement | sampling | |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Arredondo et al. 2011 | Case control |
MetS: 185 Control: 120 |
Chile |
MetS: 54.2 (12.3) Control: 53.6 (10.1) |
Iron (μg/dL) |
MetS: 146.6 (59.2) Controls: 121.3 (51.9) |
atomic absorption spectrometry with graphite furnace, Simaa 6100, Perkin Elmer | Blood Sample |
| 2 | Lee et al. 2012 | Cross sectional |
3783 > = 20 years old No MetS:3082 MetS:701 |
Representative sample of the non-institutionalized civilian population of South Korea |
No MetS: 42.32 (0.294) MetS: 48.36 (0.574) |
Cadmium (µg/dL) |
Q1: ≤ 0.819 Q2:0.819–1.359 Q3: > 1.359 |
Cd and Pb were measured by graphite furnace atomic absorption spectrometry with Zeeman background correction (A AnalystTM 600; Perkin Elmer) |
Blood Sample |
| Lead (µg/dL) |
Q1: ≤ 2.362 Q2:2.362–3.282 Q3: > 3.282 |
||||||||
| Mercury (µg/dL) |
Q1: ≤ 3.979 Q2:3.979–6.460 Q3: > 6.460 |
Hg was measured using the gold-amalgam collection method with DMA-80 (Milestone, Bergamo, Italy) |
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| 3 | Rhee et al. 2013 | Cross-sectional | 1405 > = 20 years old | South Korea |
No MetS: 40.3 (13.7) MetS: 47.1 (13.3) |
lead (μg/dL) |
Q1 = 0.42–1.73 Q2 = 1.74–2.35 Q3 = 2.35–3.06 Q4 = 3.07–19.43 |
Trace element EDTA tubes (BD, Franklin Lakes, NJ, USA) | Blood sample |
|
Mercury (μg/dL) |
Mets: 4.96 (4.62–5.32) Control:4.62 (4.49–4.76) |
Blood sample | |||||||
|
Cadmium (μg/dL) |
Mets: 0.88 (0.82–0.95) Control:0.85 (0.83–0.88) |
Blood sample | |||||||
| Manganese (μg/dL) |
Mets: 1.33 (1.28–1.38) Control:1.29 (1.27–1.31) |
Blood sample | |||||||
| 4 | Jin et al. 2013 | Cross sectional |
1493 > = 20 years’ old No MetS:1351 MetS:142 |
China | 50.7(9.8) |
lead (μg/dL) |
MetS: 0.17 (0.10) Controls: 0.15 (0.10) |
Inductively Coupled Plasma atomic emission Spectrometry (ICP-AES) | Blood Sample |
|
Cadmium (μg/dL) |
MetS: 17.16 (6.82) Controls: 14.49 (6.74) |
||||||||
|
Manganese (μg/dL) |
MetS: 0.23 (0.12) Controls: 0.23 (0.13) |
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|
Chromium (μg/dL) |
MetS: 5.72 (2.49) Controls: 6.36 (2.71) |
||||||||
|
Copper (mg/dL) |
MetS: 1.05 (0.36) Controls: 0.99 (0.21) |
||||||||
|
Magnesium (mg/dL) |
MetS: 0.20 (0.09) Controls: 0.19 (0.09) |
||||||||
| Iron (mg/dL) |
MetS: 15.52 (7.29) Controls: 15.84 (7.54) |
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| 5 | Eom et al. 2014 | Cross-sectional | 2114 > 19 years old | healthy adults | 45.5 (14.6) |
mercury (μg/dL) |
Q1: < 2.99 Q2:2.99–4.88 Q3: ≥ 4.88 |
Thermal Decomposition Amalgamation Atomic Absorption Spectrophotometer (TDA/AAS) | Blood sample |
| 6 | Tavakoli-Hoseini et al. 2014 | Case control |
MetS: 176 Control: 209 |
Individuals aged 35–65 years |
MetS: 54(7.9) Controls: 52.7(9.7) |
Iron (μg/dL) |
MetS: 133.2(64.8) Controls:102.4(44.7) |
Serum ferritin levels were assayed with the using of commercial kits by standard enzyme-linked immunosorbent assay (Stat Fax 2100) |
Blood sample |
| 7 | Moon et al. 2014 | Cross-sectional |
3950 > = 20 years old No MetS:3045 MetS:605 |
South Korea |
No MetS: 40.3 (13.7) MetS: 47.1 |
lead (μg/dL) |
Q1 = 123 ± 1.01 Q2 = 1.9 ± 1.00 Q3 = 2.5 ± 1.01 Q4 = 3.79 ± 1.01 |
Graphite-furnace atomic absorption spectrometry background correction (Perkin Elmer A Analyst was used for blood lead and cadmium A gold-amalgam collection method with a DMA-80 was used for blood mercury |
Blood sample |
|
Mercury (μg/dL) |
Q1 = 1.88 ± 1.01 Q2 = 3.15 ± 1.00 Q3 = 4.65 ± 1.00 Q4 = 8.73 ± 1.01 |
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|
Cadmium (μg/dL) |
Q1 = 0.37 ± 1.01 Q2 = 0.78 ± 1.00 Q3 = 1.17 ± 1.00 Q4 = 1.94 ± 1.01 |
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| 8 | Chung et al. 2015 | Cross sectional |
Male: 2,976 Female: 3,074 |
participants in the KNHANES-V |
Male: 46.3(0.6) Female: 47.8(0.7) |
mercury (μg/dL) |
Q1: ≤ 2.841 Q2:2.842–4.253 Q3:4.254–6.48 Q4: > 6.481 |
a cold-vapor atomic absorption spectrometric method using a dedicated mercury analyzer (M-6000A, CETAC Technologies, USA) |
Blood sample |
| 9 | Rotter et al. 2015 | Cross-sectional |
MetS: 161 Control: 152 |
Volunteers men in north-western Poland | 61.3(6.3) |
lead (μg/dL) |
MetS: 75.17 (21.4) Controls: 73.82 (21.7) |
Inductively Coupled Plasma Mass Spectrometry using PerkinElmer ICP-MS | Blood sample |
|
Mercury (μg/dL) |
MetS: 4.59(0.92) Controls: 4.51 (080) |
||||||||
|
Cadmium (μg/dL) |
MetS:1.55 (0.32) Controls: 1.53 (0.34) |
||||||||
| Manganese (μg/dL) |
MetS: 1.90 (1.17) Controls: 1.79 (1.14) |
||||||||
|
Chromium (μg/dL) |
MetS: 0.46 (0.18) Controls: 0.47 (0.25) |
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|
Copper (mg/L) |
MetS: 1.08 (0.18) Controls: 1.09 (0.18) |
||||||||
| Magnesium (mg/L) |
MetS: 20.6 (2.05) Controls: 21.28 (2.37) |
||||||||
| Iron (mg/L) |
MetS: 1.19 (0.45) Controls: 1.23 (0.43) |
||||||||
| 10 | Han et al. 2015 | Cross sectional |
200, 30–64 years’ old Men:96 Women:104 |
Healthy volunteers | 51(7.3) |
Cadmium (μg/dL) |
NA |
Graphite-furnace atomic absorption spectrometry background correction (Perkin Elmer A Analyst |
Blood Sample |
| 11 | Kilani et al. 2015 | Cohort |
6733 participants aged 35–75 years Men: 3189 Female: 3544 |
Participants in CoLaus study |
Men: 50.1(10.3) Women: 44(5.5) |
Iron (μg/dL) | NA |
Iron was assessed by colorimetric method (ferrozine, BioSystems) |
Blood sample |
| 12 | Ghamarchehreh et al. 2016 | Case control |
MetS: 143 Control: 156 |
Patients with NAFLD | 44.99(12.77) | Iron (μg/dL) |
MetS: 151.86(490.62) Controls:108.92(39.37) |
– | Blood Sample |
| 13 | Lee et al. 2016 | Cross sectional | 9880 | Civilian population of South Korea | At least 20 years old |
Cadmium (µg/dL) |
Q1: ≤ 0.720 Q2:0.720–1.172 Q3: > 1.172 |
atomic absorption spectrometry with graphite furnace (Zeeman background correction analyst 600, Perkin Elmer, Turku, Finland) | Blood Sample |
|
Lead (µg/dL) |
Q1: ≤ 2.199 Q2:2.199–3.011 Q3: > 3.011 |
||||||||
|
Mercury (µg/dL) |
Q1: ≤ 3.521 Q2:3.521–5.933 Q3: > 5.933 |
Gold-amalgam collection method with DMA-80 (Milestone, Bergamo, Italy) | |||||||
| 14 | Lee et al. 2017 | Cross-sectional |
1827 > = 20 years old No MetS:1408 MetS:419 |
South Korea | - |
Lead (μg/dL) |
Q1: ≤ 1.48 Q2:1.48–2.57 Q3: > 2.57 |
Graphite-furnace atomic absorption spectrometry background correction (Perkin Elmer A Analyst was used for blood lead and cadmium A gold-amalgam collection method with a DMA-80 was used for blood mercury |
Blood sample |
|
Mercury (μg/dL) |
Q1: ≤ 2.10 Q2:2.10–4.87 Q3: > 4.87 |
||||||||
|
Cadmium (μg/dL) |
Q1: ≤ 0.57 Q2:0.57–1.31 Q3: > 1.31 |
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| 15 | El Sayed et al. 2017 | case–control |
Total: 30 No MetS:15 MetS:15 |
patients having metabolic syndrome and healthy volunteer | 60.47(4.47) |
magnesium (mg/dL) |
MetS: 1.03 (0.31) Controls: 2.19 (0.31) |
colorimetric methods from biodiagnostic CO (Diagnostic and Research Reagents) | Blood Sample |
| Copper (μg/dL) |
MetS: 69.73(14.69) Controls: 105.93(30.56) |
||||||||
| 16 | Stechemesser et al. 2017 | Cross sectional |
Total: 107 No MetS:53 MetS:54 |
Austria | 56.4(6.4) | Iron (μg/dL) |
MetS: 99.8(32.2) Controls:108.3(34.5) |
–- | Blood Sample |
| 17 | Park et al. 2018 | Cross sectional |
2833 > = 20 years’ old No MetS:2265 MetS:568 |
participants in the 7th KNHANES |
Female: 60.07 Male: 53.80 |
lead (μg/dL) |
Q1: < 2 Q2:2- < 3 Q3: 3- < 4 Q4: ≥ 4 |
atomic absorption spectrophotometry using the PerkinElmer AAnalsyt 600 |
Blood Sample |
| 18 | Lee et al. 2018 | Cross sectional |
4530 > = 20 years’ old No MetS:3619 MetS:911 |
participants in the 6th KNHANES | 44.7 (14.7) |
Mercury (μg/dL) |
Q1 = 1.59 ± 1.30 Q2 = 2.67 ± 1.12 Q3 = 3.40 ± 1.13 Q4 = 7.62 ± 1.43 |
a gold-amalgam collection method with a DMA-80 | Blood Sample |
| 19 | Guo et al. 2019 | Case–Control |
145 male No MetS:65 MetS:80 |
Participants who refer to Physical Examination Center affiliated with Capital Medical University, China |
39(12) |
Cadmium (μg/dL) |
Q1: ≤ 0.11 Q2:0.53 Q3: 1.13 Q4: ≥ 3.35 |
Inductively coupled plasma mass spectrometry (ICP-MS) |
Blood Sample |
| lead(μg/dL) |
Q1: ≤ 27.6 Q2:59.9 Q3: 78.5 Q4: ≥ 100.8 |
||||||||
|
Copper (mg/L) |
Q1: ≤ 0.57 Q2:0.68 Q3: 0.73 Q4: ≥ 1.108 |
||||||||
| 20 | Fang et al. 2019 | A nested case–control |
698 > = 18 years’ old No MetS:349 MetS:349 |
individuals who developed metabolic syndrome during a 3-year follow-up |
64.5(7.8) |
Copper (mg/L) |
Female: Q1: < 0.90 Q2:0.90–0.98 Q3: > 0.98 Male: Q1: < 0.87 Q2:0.87–0.94 Q3: > 0.94 |
flame atomic absorption spectrometry (SpectrAA240FS; Varian, USA) |
Blood Sample |
| 21 | Shim et al. 2019 | Cross sectional |
5251 > = 20 years’ old No MetS:4673 MetS:578 |
Participants in Korean National Environmental Health Survey II (2012–2014, KNEHS) |
61.59(0.50) |
lead (μg/dL) |
MetS: 0.759(0.487) Controls:0.713(0.482) |
Graphite-furnace atomic absorption spectrometry background correction (Perkin Elmer A Analyst was used for blood lead A gold-amalgam collection method with a DMA-80 was used for blood mercury |
Blood Sample |
|
mercury (μg/dL) |
MetS: 1.165(0.664) Controls:1.18(0.640) |
||||||||
| 22 | Bulka et al. 2019 | Cross sectional | Total: 1088 | non-institutionalized civilian resident population of the U.S |
Female: 47.3 Male: 52.7 |
lead (μg/dL) |
NA |
inductively coupled plasma mass spectrometry (ICP-MS) |
Blood Sample |
|
methylmercury (μg/dL) | |||||||||
|
Cooper (μg/dL) | |||||||||
|
Manganese (μg/dL) | |||||||||
| 23 | Kaminska et al. 2020 | Cross sectional |
169 No MetS:47 MetS:122 |
women between 44–65 years from general population | 54.49(5.65) |
lead (μg/dL) |
MetS: 5.64 (2.03) Controls: 8.01 (4.38) |
inductively coupled plasma optical emission spectrometry (ICP-OES |
Blood Sample |
| 24 | Chen et al. 020 | Case–Control |
4282 > = 18 years’ old No MetS:2141 MetS:2141 |
general population undergoing a routine health checkup |
52.6(10.8) |
Chromium (μg/dL) |
Q1: < 3.27 Q2:3.28–4.46 Q3: 4.47–5.87 Q4: > 5.87 |
inductively coupled plasma mass spectrometry (ICP-MS) |
Blood Sample |
| 25 | Wen, et al. 020 | Cross sectional |
2444 > = 20 years’ old No MetS:1618 MetS:826 |
general population in southern Taiwan | 55.1(13.2) |
lead (μg/dL) |
MetS: 1.6 (1.1–2.3) Controls: 1.5 (1.0,2.2) |
Graphite-furnace atomic absorption spectrometry background correction (Perkin Elmer) |
Blood Sample |
| 26 | Park et al. 2020 | Cross-sectional | 823,19–29 years old | Republic of Korea | 23.57 |
lead (μg/dL) |
MetS: 1.57 (0.821) Controls: 1.34 (0.548) |
atomic absorption spectrophotometry on a PerkinElmer Analyst 600 |
Blood sample |
|
Mercury (μg/dL) |
MetS: 3.29 (2.105) Controls: 2.95 (1.848) | ||||||||
|
Cadmium (μg/dL) |
MetS: 0.73 (0.428) Controls: 0.57 (0.325) | ||||||||
| 27 | Lo et al. 2021 | Cross-sectional |
3335 > = 18 years’ old Male: 1605 Female: 1730 |
participants in the United States National Health and Nutrition Examination Survey 2011–2016 |
–– | Manganese (μg/dL) |
Q1: < 7.63 Q2:7.63–9.42 Q3: 9.42–11.91 Q4: > 11.91 |
Inductively Coupled Plasma Mass Spectrometry using PerkinElmer ICP-MS | Blood sample |
| 28 | Duc et al. 2021 | Cross sectional |
60256 > = 20 years’ old Men:27429 Women:32827 |
participated in the KNANES 2009–2103 and 2016– 2017 surveys |
40.8(22.8) |
Lead (μg/dL) |
MetS: 2.34 (1.22) Controls: 1.96 (1.03) |
Graphite-furnace atomic absorption spectrometry background correction (Perkin Elmer A Analyst was used for blood lead and cadmium A gold-amalgam collection method with a DMA-80 was used for blood mercury |
Blood Sample |
|
Mercury (μg/dL) |
MetS: 4.78 (3.87) Controls: 3.83 (3.37) |
||||||||
|
Cadmium (μg/dL) |
MetS: 1.26 (0.69) Controls: 0.93 (0.64) |
||||||||
| 29 | Lu et al. 2021 | Case–Control |
1165 > = 18 years’ old No MetS:446 MetS:709 |
participants enrolled at a medical center in Northern Taiwan 2007–2017 | 65.7 | Cu (μg/L) |
MetS: 1101.2 (322.5) Controls: 949.5 (253.3) |
Inductively Coupled Plasma Mass Spectrometry using PerkinElmer ICP-MS | Blood Sample |
| Fe (μg/L) |
MetS: 1370 (577.7) Controls: 1051.6 (403.6) |