Associations of Heavy Metals with Metabolic Syndrome and Anthropometric Indices
Abstract
:1. Introduction
2. Materials and Methods
2.1. Subject Recruitment
2.2. Collection of Demographic, Medical, and Laboratory Data
2.3. Measurement of Blood and Urine Heavy Metals
2.4. Definition of MetS
2.5. Indices
2.6. Ethics Statement
2.7. Statistical Analysis
3. Results
3.1. Determinants of MetS
3.2. Determinants of Each Index
3.2.1. LAP
3.2.2. BRI
3.2.3. CI
3.2.4. VAI
3.2.5. BAI
3.2.6. AVI
4. Discussion
Author Contributions
Funding
Conflicts of Interest
References
- Mitchell, R.B. International Environmental Agreements: A Survey of Their Features, Formation, and Effects. Annu. Rev. Environ. Resour. 2003, 28, 429–461. [Google Scholar] [CrossRef] [Green Version]
- Masindi, V.; Muedi, K. Environmental contamination by heavy Metals. In Heavy Metals; Hosam El-Din, M., Saleh Refaat Aglan, F., Eds.; IntechOpen: Rijeka, Croatia, 2018. [Google Scholar] [CrossRef] [Green Version]
- Yusuf, M.; Elfghi, F.M.; Zaidi, S.A.; Abdullah, E.C.; Khan, M.A. Applications of graphene and its derivatives as an adsorbent for heavy metal and dye removal: A systematic and comprehensive overview. RSC Adv. 2015, 5, 50392–50420. [Google Scholar] [CrossRef]
- Martin, J.A.R.; De Arana, C.; Ramos-Miras, J.J.; Gil, C.; Boluda, R. Impact of 70 years urban growth associated with heavy metal pollution. Environ. Pollut. 2015, 196, 156–163. [Google Scholar] [CrossRef] [PubMed]
- Duffus, J.H. “Heavy metals” a meaningless term? (IUPAC Technical Report). Pure Appl. Chem. 2002, 74, 793–807. [Google Scholar] [CrossRef] [Green Version]
- Tchounwou, P.B.; Yedjou, C.G.; Patlolla, A.K.; Sutton, D.J. Heavy metal toxicity and the environment. Exp. Suppl. 2012, 101, 133–164. [Google Scholar] [CrossRef] [Green Version]
- Mohammed, A.S.; Kapri, A.; Goel, R. Heavy Metal Pollution: Source, Impact, and Remedies. In Biomanagement of Metal-Contaminated Soils. Environmental Pollution; Khan, M., Zaidi, A., Goel, R., Musarrat, J., Eds.; Springer: Dordrecht, The Netherlands, 2011; Volume 20, pp. 1–28. [Google Scholar] [CrossRef]
- Giacoppo, S.; Galuppo, M.; Calabro, R.S.; D’Aleo, G.; Marra, A.; Sessa, E.; Bua, D.G.; Potorti, A.G.; Dugo, G.; Bramanti, P.; et al. Heavy metals and neurodegenerative diseases: An observational study. Biol. Trace Elem. Res. 2014, 161, 151–160. [Google Scholar] [CrossRef]
- Mates, J.M.; Segura, J.A.; Alonso, F.J.; Marquez, J. Roles of dioxins and heavy metals in cancer and neurological diseases using ROS-mediated mechanisms. Free Radic. Biol. Med. 2010, 49, 1328–1341. [Google Scholar] [CrossRef]
- Alissa, E.M.; Ferns, G.A. Heavy metal poisoning and cardiovascular disease. J. Toxicol. 2011, 2011, 870125. [Google Scholar] [CrossRef]
- Rokadia, H.K.; Agarwal, S. Serum heavy metals and obstructive lung disease: Results from the National Health and Nutrition Examination Survey. Chest 2013, 143, 388–397. [Google Scholar] [CrossRef]
- Mohod, C.; Dhote, J. Review of heavy metals in drinking water and their effect on human health. Int. J. Innov. Res. Sci. Eng. Technol. 2013, 2, 2992–2996. [Google Scholar]
- Ringenberg, Q.S.; Doll, D.C.; Patterson, W.P.; Perry, M.C.; Yarbro, J.W. Hematologic effects of heavy metal poisoning. South Med. J. 1988, 81, 1132–1139. [Google Scholar] [CrossRef] [PubMed]
- Morais, S.; Costa, F.; Pereira, M. Heavy Metals and Human Health; IntechOpen: London, UK, 2012. [Google Scholar] [CrossRef] [Green Version]
- Saklayen, M.G. The Global Epidemic of the Metabolic Syndrome. Curr. Hypertens. Rep. 2018, 20, 12. [Google Scholar] [CrossRef] [Green Version]
- Hwang, L.-C.; Bai, C.-H.; Chen, C.-J. Prevalence of Obesity and Metabolic Syndrome in Taiwan. J. Formos. Med. Assoc. 2006, 105, 626–635. [Google Scholar] [CrossRef] [Green Version]
- Adejumo, E.N.; Adejumo, A.O.; Azenabor, A.; Ekun, A.O.; Enitan, S.S.; Adebola, O.K.; Ogundahunsi, O.A. Anthropometric parameter that best predict metabolic syndrome in South west Nigeria. Diabetes Metab. Syndr. 2019, 13, 48–54. [Google Scholar] [CrossRef] [PubMed]
- Cheng, C.H.; Ho, C.C.; Yang, C.F.; Huang, Y.C.; Lai, C.H.; Liaw, Y.P. Waist-to-hip ratio is a better anthropometric index than body mass index for predicting the risk of type 2 diabetes in Taiwanese population. Nutr. Res. 2010, 30, 585–593. [Google Scholar] [CrossRef]
- Huang, K.C.; Lin, W.Y.; Lee, L.T.; Chen, C.Y.; Lo, H.; Hsia, H.H.; Liu, I.L.; Shau, W.Y.; Lin, R.S. Four anthropometric indices and cardiovascular risk factors in Taiwan. Int. J. Obes. Relat. Metab. Disord. 2002, 26, 1060–1068. [Google Scholar] [CrossRef] [Green Version]
- Grundy, S.M. Obesity, metabolic syndrome, and cardiovascular disease. J. Clin. Endocrinol. Metab. 2004, 89, 2595–2600. [Google Scholar] [CrossRef]
- Rochlani, Y.; Pothineni, N.V.; Kovelamudi, S.; Mehta, J.L. Metabolic syndrome: Pathophysiology, management, and modulation by natural compounds. Ther. Adv. Cardiovasc. Dis. 2017, 11, 215–225. [Google Scholar] [CrossRef]
- Jaishankar, M.; Tseten, T.; Anbalagan, N.; Mathew, B.B.; Beeregowda, K.N. Toxicity, mechanism and health effects of some heavy metals. Interdiscip. Toxicol. 2014, 7, 60–72. [Google Scholar] [CrossRef] [Green Version]
- Khan, A.R.; Awan, F.R. Metals in the pathogenesis of type 2 diabetes. J. Diabetes Metab. Disord. 2014, 13, 16. [Google Scholar] [CrossRef] [Green Version]
- Rhee, S.Y.; Hwang, Y.C.; Woo, J.T.; Sinn, D.H.; Chin, S.O.; Chon, S.; Kim, Y.S. Blood lead is significantly associated with metabolic syndrome in Korean adults: An analysis based on the Korea National Health and Nutrition Examination Survey (KNHANES), 2008. Cardiovasc. Diabetol. 2013, 12, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ma, J.; Zhou, Y.; Wang, D.; Guo, Y.; Wang, B.; Xu, Y.; Chen, W. Associations between essential metals exposure and metabolic syndrome (MetS): Exploring the mediating role of systemic inflammation in a general Chinese population. Environ. Int. 2020, 140, 105802. [Google Scholar] [CrossRef] [PubMed]
- Rotter, I.; Kosik-Bogacka, D.; Dolegowska, B.; Safranow, K.; Lubkowska, A.; Laszczynska, M. Relationship between the concentrations of heavy metals and bioelements in aging men with metabolic syndrome. Int. J. Environ. Res. Public Health 2015, 12, 3944–3961. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tsang, C.; Taghizadeh, M.; Aghabagheri, E.; Asemi, Z.; Jafarnejad, S. A meta-analysis of the effect of chromium supplementation on anthropometric indices of subjects with overweight or obesity. Clin. Obes. 2019, 9, e12313. [Google Scholar] [CrossRef]
- Kim, H.N.; Song, S.W.; Choi, W.S. Association between serum zinc level and body composition: The Korean National Health and Nutrition Examination Survey. Nutrition 2016, 32, 332–337. [Google Scholar] [CrossRef]
- Ronco, A.M.; Gutierrez, Y.; Gras, N.; Muñoz, L.; Salazar, G.; Llanos, M.N. Lead and arsenic levels in women with different body mass composition. Biol. Trace Elem. Res. 2010, 136, 269–278. [Google Scholar] [CrossRef]
- Levey, A.S.; Stevens, L.A.; Schmid, C.H.; Zhang, Y.L.; Castro, A.F., 3rd; Feldman, H.I.; Kusek, J.W.; Eggers, P.; Van Lente, F.; Greene, T.; et al. A new equation to estimate glomerular filtration rate. Ann. Intern. Med. 2009, 150, 604–612. [Google Scholar] [CrossRef] [PubMed]
- Isomaa, B.; Henricsson, M.; Almgren, P.; Tuomi, T.; Taskinen, M.R.; Groop, L. The metabolic syndrome influences the risk of chronic complications in patients with type II diabetes. Diabetologia 2001, 44, 1148–1154. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tan, C.E.; Ma, S.; Wai, D.; Chew, S.K.; Tai, E.S. Can we apply the National Cholesterol Education Program Adult Treatment Panel definition of the metabolic syndrome to Asians? Diabetes Care 2004, 27, 1182–1186. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kahn, H.S. The “lipid accumulation product” performs better than the body mass index for recognizing cardiovascular risk: A population-based comparison. BMC Cardiovasc. Disord. 2005, 5, 26. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Thomas, D.M.; Bredlau, C.; Bosy-Westphal, A.; Mueller, M.; Shen, W.; Gallagher, D.; Maeda, Y.; McDougall, A.; Peterson, C.M.; Ravussin, E.; et al. Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obesity 2013, 21, 2264–2271. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Valdez, R. A simple model-based index of abdominal adiposity. J. Clin. Epidemiol. 1991, 44, 955–956. [Google Scholar] [CrossRef]
- Amato, M.C.; Giordano, C.; Galia, M.; Criscimanna, A.; Vitabile, S.; Midiri, M.; Galluzzo, A. Visceral Adiposity Index: A reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care 2010, 33, 920–922. [Google Scholar] [CrossRef] [Green Version]
- Bergman, R.N.; Stefanovski, D.; Buchanan, T.A.; Sumner, A.E.; Reynolds, J.C.; Sebring, N.G.; Xiang, A.H.; Watanabe, R.M. A better index of body adiposity. Obesity 2011, 19, 1083–1089. [Google Scholar] [CrossRef]
- Guerrero-Romero, F.; Rodríguez-Morán, M. Abdominal volume index. An anthropometry-based index for estimation of obesity is strongly related to impaired glucose tolerance and type 2 diabetes mellitus. Arch. Med. Res. 2003, 34, 428–432. [Google Scholar] [CrossRef]
- Stern, B.R.; Solioz, M.; Krewski, D.; Aggett, P.; Aw, T.C.; Baker, S.; Crump, K.; Dourson, M.; Haber, L.; Hertzberg, R.; et al. Copper and human health: Biochemistry, genetics, and strategies for modeling dose-response relationships. J. Toxicol. Environ. Health B Crit. Rev. 2007, 10, 157–222. [Google Scholar] [CrossRef]
- Wazir, S.M.; Ghobrial, I. Copper deficiency, a new triad: Anemia, leucopenia, and myeloneuropathy. J. Community Hosp. Intern. Med. Perspect. 2017, 7, 265–268. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gaetke, L. Copper toxicity, oxidative stress, and antioxidant nutrients. Toxicology 2003, 189, 147–163. [Google Scholar] [CrossRef]
- Frohlich, M.; Imhof, A.; Berg, G.; Hutchinson, W.L.; Pepys, M.B.; Boeing, H.; Muche, R.; Brenner, H.; Koenig, W. Association between C-reactive protein and features of the metabolic syndrome: A population-based study. Diabetes Care 2000, 23, 1835–1839. [Google Scholar] [CrossRef] [Green Version]
- Das, K.K.; Reddy, R.C.; Bagoji, I.B.; Das, S.; Bagali, S.; Mullur, L.; Khodnapur, J.P.; Biradar, M.S. Primary concept of nickel toxicity—An overview. J. Basic Clin. Physiol. Pharmacol. 2018, 30, 141–152. [Google Scholar] [CrossRef] [Green Version]
- Tomei, F.; Rosati, M.V.; Ciarrocca, M.; Marchetti, M.R.; Baccolo, T.P.; Anzelmo, V.; Tomao, E. Urban pollution and nickel concentration in serum. Int. J. Environ. Health Res. 2004, 14, 65–74. [Google Scholar] [CrossRef] [PubMed]
- Zambelli, B.; Ciurli, S. Nickel and human health. Met. Ions Life Sci. 2013, 13, 321–357. [Google Scholar] [CrossRef] [PubMed]
- Yang, A.M.; Bai, Y.N.; Pu, H.Q.; Zheng, T.Z.; Cheng, N.; Li, J.S.; Li, H.Y.; Zhang, Y.W.; Ding, J.; Su, H.; et al. Prevalence of metabolic syndrome in Chinese nickel-exposed workers. Biomed. Environ. Sci. 2014, 27, 475–477. [Google Scholar] [CrossRef] [PubMed]
- Public Health Service, Department of Health and Human Services. Toxicological Profile for Nickel (Draft for Public Comment); Agency for Toxic Substances and Disease Registry (ATSDR): Atlanta, GA, USA, 2005. [Google Scholar]
- Brocato, J.; Hernandez, M.; Laulicht, F.; Sun, H.; Shamy, M.; Alghamdi, M.A.; Khoder, M.I.; Kluz, T.; Chen, L.C.; Costa, M. In Vivo Exposures to Particulate Matter Collected from Saudi Arabia or Nickel Chloride Display Similar Dysregulation of Metabolic Syndrome Genes. J. Toxicol. Environ. Health A 2015, 78, 1421–1436. [Google Scholar] [CrossRef] [Green Version]
- Lusi, E.A.; Patrissi, T.; Guarascio, P. Nickel-resistant bacteria isolated in human microbiome. New Microbes New Infect. 2017, 19, 67–70. [Google Scholar] [CrossRef]
- Shin, N.R.; Whon, T.W.; Bae, J.W. Proteobacteria: Microbial signature of dysbiosis in gut microbiota. Trends Biotechnol. 2015, 33, 496–503. [Google Scholar] [CrossRef]
- Public Health Service, Department of Health and Human Services. Toxicological Profile for Lead (Draft for Public Comment); Agency for Toxic Substances and Disease Registry (ATSDR): Atlanta, GA, USA, 2019. [Google Scholar]
- Wani, A.L.; Ara, A.; Usmani, J.A. Lead toxicity: A review. Interdiscip. Toxicol. 2015, 8, 55–64. [Google Scholar] [CrossRef] [Green Version]
- Mitra, P.; Sharma, S.; Purohit, P.; Sharma, P. Clinical and molecular aspects of lead toxicity: An update. Crit. Rev. Clin. Lab. Sci. 2017, 54, 506–528. [Google Scholar] [CrossRef]
- Lan, C.C.; Yu, H.S.; Ko, Y.C. Chronic arsenic exposure and its adverse health effects in Taiwan: A paradigm for management of a global environmental problem. Kaohsiung J. Med. Sci. 2011, 27, 411–416. [Google Scholar] [CrossRef] [Green Version]
- Wang, S.L.; Chang, F.H.; Liou, S.H.; Wang, H.J.; Li, W.F.; Hsieh, D.P. Inorganic arsenic exposure and its relation to metabolic syndrome in an industrial area of Taiwan. Environ. Int. 2007, 33, 805–811. [Google Scholar] [CrossRef]
- Spratlen, M.J.; Grau-Perez, M.; Best, L.G.; Yracheta, J.; Lazo, M.; Vaidya, D.; Balakrishnan, P.; Gamble, M.V.; Francesconi, K.A.; Goessler, W.; et al. The Association of Arsenic Exposure and Arsenic Metabolism with the Metabolic Syndrome and Its Individual Components: Prospective Evidence from the Strong Heart Family Study. Am. J. Epidemiol. 2018, 187, 1598–1612. [Google Scholar] [CrossRef] [PubMed]
- Chen, J.W.; Wang, S.L.; Wang, Y.H.; Sun, C.W.; Huang, Y.L.; Chen, C.J.; Li, W.F. Arsenic methylation, GSTO1 polymorphisms, and metabolic syndrome in an arseniasis endemic area of southwestern Taiwan. Chemosphere 2012, 88, 432–438. [Google Scholar] [CrossRef] [PubMed]
- Public Health Service, Department of Health and Human Services. Toxicological Profile for Chromium (Draft for Public Comment); Agency for Toxic Substances and Disease Registry (ATSDR): Atlanta, GA, USA, 2012. [Google Scholar]
- Bai, J.; Xun, P.; Morris, S.; Jacobs, D.R., Jr.; Liu, K.; He, K. Chromium exposure and incidence of metabolic syndrome among American young adults over a 23-year follow-up: The CARDIA Trace Element Study. Sci. Rep. 2015, 5, 15606. [Google Scholar] [CrossRef] [PubMed]
- Son, J.; Morris, J.S.; Park, K. Toenail Chromium Concentration and Metabolic Syndrome among Korean Adults. Int. J. Environ. Res. Public Health 2018, 15, 682. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Public Health Service, Department of Health and Human Services. Toxicological Profile for Manganese (Draft for Public Comment); Agency for Toxic Substances and Disease Registry (ATSDR): Atlanta, GA, USA, 2012. [Google Scholar]
- Choi, M.K.; Bae, Y.J. Relationship between dietary magnesium, manganese, and copper and metabolic syndrome risk in Korean adults: The Korea National Health and Nutrition Examination Survey (2007–2008). Biol. Trace Elem. Res. 2013, 156, 56–66. [Google Scholar] [CrossRef] [PubMed]
- Zhou, B.; Su, X.; Su, D.; Zeng, F.; Wang, M.H.; Huang, L.; Huang, E.; Zhu, Y.; Zhao, D.; He, D.; et al. Dietary intake of manganese and the risk of the metabolic syndrome in a Chinese population. Br. J. Nutr. 2016, 116, 853–863. [Google Scholar] [CrossRef] [Green Version]
- Haussler, J.; Bader, M. An interference account of the missing-VP effect. Front. Psychol. 2015, 6, 766. [Google Scholar] [CrossRef] [Green Version]
- Curtis, L.H.; Hammill, B.G.; Bethel, M.A.; Anstrom, K.J.; Gottdiener, J.S.; Schulman, K.A. Costs of the metabolic syndrome in elderly individuals: Findings from the Cardiovascular Health Study. Diabetes Care 2007, 30, 2553–2558. [Google Scholar] [CrossRef] [Green Version]
- Scholze, J.; Alegria, E.; Ferri, C.; Langham, S.; Stevens, W.; Jeffries, D.; Uhl-Hochgraeber, K. Epidemiological and economic burden of metabolic syndrome and its consequences in patients with hypertension in Germany, Spain and Italy; a prevalence-based model. BMC Public Health 2010, 10, 529. [Google Scholar] [CrossRef] [Green Version]
- Grundy, S.M.; Cleeman, J.I.; Daniels, S.R.; Donato, K.A.; Eckel, R.H.; Franklin, B.A.; Gordon, D.J.; Krauss, R.M.; Savage, P.J.; Smith, S.C., Jr.; et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005, 112, 2735–2752. [Google Scholar] [CrossRef] [Green Version]
- Georgopoulos, P.G.; Roy, A.; Yonone-Lioy, M.J.; Opiekun, R.E.; Lioy, P.J. Environmental copper: Its dynamics and human exposure issues. J. Toxicol. Environ. Health B Crit. Rev. 2001, 4, 341–394. [Google Scholar] [CrossRef] [PubMed]
Characteristics | All (n = 2444) | Without MetS (n = 1618) | With MetS (n = 826) | p |
---|---|---|---|---|
Age (year) | 55.1 ± 13.2 | 52.9 ± 13.0 | 59.4 ± 12.6 | <0.001 |
Male gender (%) | 39.9 | 39.2 | 41.3 | 0.331 |
DM (%) | 10.5 | 4.2 | 22.8 | <0.001 |
Hypertension (%) | 25.3 | 16.9 | 41.8 | <0.001 |
BMI (kg/m2) | 25.0 ± 4.0 | 23.7 ± 3.4 | 27.5 ± 3.8 | <0.001 |
Waist circumference (cm) | 83.6 ± 10.6 | 80.0 ± 9.7 | 90.7 ± 8.8 | <0.001 |
Hip circumference (cm) | 96.5 ± 8.0 | 94.7 ± 7.4 | 100.0 ± 7.9 | <0.001 |
SBP (mmHg) | 132.1 ± 19.8 | 126.8 ± 18.4 | 142.3 ± 18.3 | <0.001 |
DBP (mmHg) | 77.5 ± 11.7 | 75.4 ± 11.0 | 81.6 ± 11.9 | <0.001 |
Laboratory parameters | ||||
Fasting glucose (mg/dL) | 99.9 ± 27.4 | 91.9 ± 16.5 | 115.5 ± 36.3 | <0.001 |
Triglyceride (mg/dL) | 105.0 (73.0–150.0) | 87.0 (65.0–115.0) | 161.0 (118.0–215.3) | <0.001 |
Total cholesterol (mg/dL) | 199.6 ± 37.5 | 199.7 ± 36.1 | 199.6 ± 40.1 | 0.966 |
HDL-cholesterol (mg/dL) | 53.0 ± 13.6 | 57.2 ± 13.3 | 44.7 ± 10.1 | <0.001 |
LDL-cholesterol (mg/dL) | 119.2 ± 34.0 | 119.0 ± 32.7 | 119.5 ± 36.4 | 0.771 |
Hemoglobin (g/dL) | 14.0 ± 1.6 | 13.9 ± 1.6 | 14.1 ± 1.7 | 0.003 |
eGFR (mL/min/1.73 m2) | 89.1 ± 16.3 | 91.8 ± 14.7 | 83.8 ± 18.1 | <0.001 |
Uric acid (mg/dL) | 5.7 ± 1.6 | 5.5 ± 1.5 | 6.2 ± 1.6 | <0.001 |
Heavy metals | ||||
Blood | ||||
Pb (µg/dL) | 1.6 (1.0–2.2) | 1.5 (1.0–2.2) | 1.6 (1.1–2.3) | 0.002 |
Urine | ||||
Ni (µg/L) | 2.4 (1.5–3.7) | 2.4 (1.5–3.7) | 2.5 (1.6–3.8) | 0.005 |
Cr (µg/L) | 0.1 (0.1–0.1) | 0.1 (0.1–0.1) | 0.1 (0.1–0.1) | 0.953 |
Mn (µg/L) | 1.7 (0.9–3.0) | 1.7 (0.9–2.9) | 1.7 (0.9–3.0) | 0.324 |
As (µg/L) | 78.9 (45.6–142.0) | 74.9 (42.9–131.9) | 87.8 (50.7–158.3) | <0.001 |
Cu (µg/dL) | 1.5 (1.0–2.0) | 1.4 (1.0–1.8) | 1.6 (1.2–2.1) | <0.001 |
LAP | 35.1 ± 34.5 | 21.6 ± 15.4 | 61.7 ± 44.7 | <0.001 |
BRI | 3.9 ± 1.3 | 3.4 ± 1.1 | 4.8 ± 1.2 | <0.001 |
Anthropometric indices | ||||
CI | 1.2 ± 0.1 | 1.2 ± 0.1 | 1.3 ± 0.1 | <0.001 |
VAI | 4.3 ± 4.8 | 2.8 ± 1.9 | 7.2 ± 6.9 | <0.001 |
BAI | 29.8 ± 5.0 | 28.8 ± 4.6 | 31.8 ± 5.2 | <0.001 |
AVI | 13.9 ± 4.3 | 13.3 ± 3.1 | 16.6 ± 3.2 | <0.001 |
Heavy Metals | Multivariable | |
---|---|---|
OR (95% CI) | p | |
Blood | ||
Pb (log per 1 µg/dL) | 0.857 (0.613–1.199) | 0.368 |
Urine | ||
Ni (log per 1 µg/L) | 1.193 (1.019–1.397) | 0.028 |
Cr (log per 1 µg/L) | 0.845 (0.487–1.466) | 0.549 |
Mn (log per 1 µg/L) | 1.035 (0.873–1.227) | 0.691 |
As (log per 1 µg/L) | 0.933 (0.717–1.215) | 0.608 |
Cu (log per 1 µg/dL) | 3.317 (2.254–4.883) | <0.001 |
Heavy Metals (Log-Transformation) | 0 (n = 475) | 1 (n = 574) | 2 (n = 569) | 3 (n = 464) | 4 (n = 266) | 5 (n = 96) | p for Trend |
---|---|---|---|---|---|---|---|
Blood | |||||||
Pb (µg/dL) | 0.12 ± 0.01 | 0.15 ± 0.01 | 0.18 ± 0.01 * | 0.19 ± 0.01 * | 0.20 ± 0.02 * | 0.15 ± 0.03 | <0.001 |
Urine | |||||||
Ni (µg/L) | 0.20 ± 0.03 | 0.22 ± 0.03 | 0.25 ± 0.02 | 0.27 ± 0.03 | 0.33 ± 0.03 | 0.28 ± 0.06 | 0.002 |
Cr (µg/L) | −0.97 ± 0.01 | −0.98 ± 0.01 | −0.96 ± 0.01 | −0.97 ± 0.01 | −0.96 ± 0.01 | −0.96 ± 0.02 | 0.432 |
Mn (µg/L) | 0.14 ± 0.02 | 0.13 ± 0.02 | 0.11 ± 0.02 | 0.15 ± 0.02 | 0.14 ± 0.03 | 0.17 ± 0.05 | 0.579 |
As (µg/L) | 1.84 ± 0.02 | 1.91 ± 0.02 * | 1.91 ± 0.01 * | 1.95 ± 0.02 * | 1.96 ± 0.02 * | 1.95 ± 0.04 | <0.001 |
Cu (µg/dL) | 0.09 ± 0.01 | 0.11 ± 0.01 | 0.13 ± 0.01 * | 0.17 ± 0.01 *† | 0.21 ± 0.01 *†# | 0.25 ± 0.03 *†#& | <0.001 |
Indices | Multivariable | |
---|---|---|
Unstandardized Coefficient β (95% CI) | p | |
LAP * | ||
Urine | ||
Ni (log per 1 µg/L) | 2.418 (0.288, 4.548) | 0.026 |
Cu (log per 1 µg/dL) | 9.508 (4.406, 14.609) | <0.001 |
BRI † | ||
Blood | ||
Pb (log per 1 µg/dL) | 0.190 (0.019, 0.362) | 0.030 |
Urine | ||
Cu (log per 1 µg/dL) | 0.223 (0.038, 0.407) | 0.018 |
CI † | ||
Urine | ||
Cu (log per 1 µg/dL) | 0.014 (0.002, 0.027) | 0.023 |
VAI * | ||
Urine | ||
Cu (log per 1 µg/dL) | 0.898 (0.149, 1.646) | 0.019 |
BAI † | ||
Blood | ||
Pb (log per 1 µg/dL) | 1.093 (0.241, 1.944) | 0.012 |
AVI † | ||
Blood | ||
Pb (log per 1 µg/dL) | 0.726 (0.120, 1.332) | 0.019 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Wen, W.-L.; Wang, C.-W.; Wu, D.-W.; Chen, S.-C.; Hung, C.-H.; Kuo, C.-H. Associations of Heavy Metals with Metabolic Syndrome and Anthropometric Indices. Nutrients 2020, 12, 2666. https://doi.org/10.3390/nu12092666
Wen W-L, Wang C-W, Wu D-W, Chen S-C, Hung C-H, Kuo C-H. Associations of Heavy Metals with Metabolic Syndrome and Anthropometric Indices. Nutrients. 2020; 12(9):2666. https://doi.org/10.3390/nu12092666
Chicago/Turabian StyleWen, Wei-Lun, Chih-Wen Wang, Da-Wei Wu, Szu-Chia Chen, Chih-Hsing Hung, and Chao-Hung Kuo. 2020. "Associations of Heavy Metals with Metabolic Syndrome and Anthropometric Indices" Nutrients 12, no. 9: 2666. https://doi.org/10.3390/nu12092666