Skip to main content

Advertisement

Log in

Association of Urinary Zinc Concentrations with Dyslipidemia and Its Subtypes: Baseline Data from the Chinese Multi-Ethnic Cohort (CMEC) Study

  • Published:
Biological Trace Element Research Aims and scope Submit manuscript

Abstract

This study elucidates the association between urinary zinc concentration and the risk of developing dyslipidemia and its subtypes in China’s ethnic minority residents. Based on the baseline survey data of the Chinese Multi-Ethnic Cohort (CMEC) study, 10,620 subjects were included in the study. Logistic regression analysis evaluated the relationship between urinary zinc concentration and dyslipidemia and its subtypes. After adjustment, compared with urinary zinc concentration quartile 1 (Q1), the odds ratios (ORs) and 95% confidence intervals (95% CIs) of dyslipidemia participants in the quartile 2 (Q2), quartile 3 (Q3), and quartile 4 (Q4) groups were 1.091 (0.963, 1.237), 1.151 (1.051, 1.304), and 1.393 (1.230, 1.579), respectively (P for trend < 0.001). While that of hypertriglyceridemia participants in the Q2, Q3, and Q4 groups were 1.130 (0.979, 1.306), 1.283 (1.113, 1.480), and 1.483 (1.287, 1.709), respectively (P for trend < 0.001). Lastly, the ORs and 95% CIs of hyperbetalipoproteinemia participants in the Q2, Q3, and Q4 groups were 1.166 (0.945, 1.439), 1.238 (1.007, 1.522), and 1.381 (1.126, 1.695), respectively (P for trend < 0.002). This study found that urinary zinc concentrations were not associated with hypercholesterolemia and hypoalphalipoproteinemia. The dose–response relationship was non-linear between urinary zinc concentration and dyslipidemia, hypertriglyceridemia and hyperbetalipoproteinemia (P for trend < 0.001). In the stratified analysis, urinary zinc levels were positively associated with the risk of dyslipidemia, hypertriglyceridemia, and hyperbetalipoproteinemia in male, ≥ 60 years old, Miao nationality, hypertension, diabetes, and BMI ≥ 24.0 kg/m2 subgroups. Our study provides some possible evidence that elevated urinary zinc concentrations are associated with an increased risk of dyslipidemia, hypertriglyceridemia, hyperbetalipoproteinemia.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data Availability

The data of this study are available from the corresponding author upon reasonable request.

References

  1. (2016) 2016 Chinese guideline for the management of dyslipidemia in adults. Zhonghua Xin Xue Guan Bing Za Zhi 44(10):833–853. https://doi.org/10.3760/cma.j.issn.0253-3758.2016.10.005

  2. Haslam DE, Peloso GM, Herman MA, Dupuis J, Lichtenstein AH, Smith CE, McKeown NM (2020) Beverage consumption and longitudinal changes in lipoprotein concentrations and incident dyslipidemia in US Adults: the Framingham heart study. J Am Heart Assoc 9(5):e014083. https://doi.org/10.1161/jaha.119.014083

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Huang YQ, Shen G, Lo K, Huang JY, Liu L, Chen CL, Yu YL, Sun S, Zhang B, Feng YQ (2020) Association of circulating selenium concentration with dyslipidemia: results from the NHANES. J Trace Elem Med Biol 58:126438. https://doi.org/10.1016/j.jtemb.2019.126438

    Article  CAS  PubMed  Google Scholar 

  4. Magriplis E, Panagiotakos D, Mitsopoulou AV, Karageorgou D, Bakogianni I, Dimakopoulos I, Micha R, Michas G, Chourdakis M, Chrousos GP, Roma E, Zampelas A (2019) Prevalence of hyperlipidaemia in adults and its relation to the Mediterranean diet: the Hellenic National Nutrition and Health Survey (HNNHS). Eur J Prev Cardiol 26(18):1957–1967. https://doi.org/10.1177/2047487319866023

    Article  PubMed  Google Scholar 

  5. Vizmanos B, Betancourt-Nuñez A, Márquez-Sandoval F, González-Zapata LI, Monsalve-Álvarez J, Bressan J, de Carvalho VF, Figueredo R, López LB, Babio N, Salas-Salvadó J (2020) Metabolic syndrome among young health professionals in the multicenter Latin America metabolic syndrome study. Metab Syndr Relat Disord 18(2):86–95. https://doi.org/10.1089/met.2019.0086

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Kuwabara M, Kuwabara R, Niwa K, Hisatome I, Smits G, Roncal-Jimenez CA, MacLean PS, Yracheta JM, Ohno M, Lanaspa MA, Johnson RJ, Jalal DI (2018) Different risk for hypertension, diabetes, dyslipidemia, and hyperuricemia according to level of body mass index in Japanese and American subjects. Nutrients 10(8). https://doi.org/10.3390/nu10081011

  7. Huang Q, Jiang H, Zhang B, Wang H, Jia X, Huang F, Wang L, Wang Z (2019) Threshold-effect association of dietary cholesterol intake with dyslipidemia in Chinese adults: results from the China Health and Nutrition Survey in 2015. Nutrients 11(12). https://doi.org/10.3390/nu11122885

  8. Prasad AS (2014) Zinc: an antioxidant and anti-inflammatory agent: role of zinc in degenerative disorders of aging. J Trace Elem Med Biol 28(4):364–371. https://doi.org/10.1016/j.jtemb.2014.07.019

    Article  CAS  PubMed  Google Scholar 

  9. Huang X, Jiang D, Zhu Y, Fang Z, Che L, Lin Y, Xu S, Li J, Huang C, Zou Y, Li L, Wu D, Feng B (2017) Chronic high dose zinc supplementation induces visceral adipose tissue hypertrophy without altering body weight in mice. Nutrients 9(10). https://doi.org/10.3390/nu9101138

  10. Phiri FP, Ander EL, Lark RM, Joy EJM, Kalimbira AA, Suchdev PS, Gondwe J, Hamilton EM, Watts MJ, Broadley MR (2021) Spatial analysis of urine zinc (Zn) concentration for women of reproductive age and school age children in Malawi. Environ Geochem Health 43(1):259–271. https://doi.org/10.1007/s10653-020-00700-5

    Article  CAS  PubMed  Google Scholar 

  11. Chen L, Guo Q, Wang Q, Luo C, Chen S, Wen S, Tan A, Yang W, Bao W, Hu FB, Liu L (2020) Association between plasma strontium, a bone-seeking element, and type 2 diabetes mellitus. Clin Nutr 39(7):2151–2157. https://doi.org/10.1016/j.clnu.2019.08.033

    Article  CAS  PubMed  Google Scholar 

  12. Zhang T, Chang X, Liu W, Li X, Wang F, Huang L, Liao S, Liu X, Zhang Y, Zhao Y (2017) Comparison of sodium, potassium, calcium, magnesium, zinc, copper and iron concentrations of elements in 24-h urine and spot urine in hypertensive patients with healthy renal function. J Trace Elem Med Biol 44:104–108. https://doi.org/10.1016/j.jtemb.2017.06.006

    Article  CAS  PubMed  Google Scholar 

  13. Wang Y, Jia XF, Zhang B, Wang ZH, Zhang JG, Huang FF, Su C, Ouyang YF, Zhao J, Du WW, Li L, Jiang HR, Zhang J, Wang HJ (2018) Dietary zinc intake and its association with metabolic syndrome indicators among chinese adults: an analysis of the China Nutritional Transition Cohort Survey 2015. Nutrients 10(5). https://doi.org/10.3390/nu10050572

  14. Jenner A, Ren M, Rajendran R, Ning P, Huat B, Watt F, Halliwell B (2007) Zinc supplementation inhibits lipid peroxidation and the development of atherosclerosis in rabbits fed a high cholesterol diet. Free Radic Biol Med 42(4):559–566. https://doi.org/10.1016/j.freeradbiomed.2006.11.024

    Article  CAS  PubMed  Google Scholar 

  15. Lynch C, Patson B, Goodman S, Trapolsi D, Kimball S (2001) Zinc stimulates the activity of the insulin- and nutrient-regulated protein kinase mTOR. Am J Physiol Endocrinol Metab 281(1):E25-34. https://doi.org/10.1152/ajpendo.2001.281.1.E25

    Article  CAS  PubMed  Google Scholar 

  16. Mocchegiani E, Giacconi R, Malavolta M (2008) Zinc signalling and subcellular distribution: emerging targets in type 2 diabetes. Trends Mol Med 14(10):419–428. https://doi.org/10.1016/j.molmed.2008.08.002

    Article  CAS  PubMed  Google Scholar 

  17. Tang X, Shay N (2001) Zinc has an insulin-like effect on glucose transport mediated by phosphoinositol-3-kinase and Akt in 3T3-L1 fibroblasts and adipocytes. J Nutr 131(5):1414–1420. https://doi.org/10.1093/jn/131.5.1414

    Article  CAS  PubMed  Google Scholar 

  18. Ginsberg H (2000) Insulin resistance and cardiovascular disease. J Clin Investig 106(4):453–458. https://doi.org/10.1172/jci10762

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. tom Dieck H, Döring F, Fuchs D, Roth H, Daniel H (2005) Transcriptome and proteome analysis identifies the pathways that increase hepatic lipid accumulation in zinc-deficient rats. J Nutr 135(2):199–205. https://doi.org/10.1093/jn/135.2.199

    Article  CAS  PubMed  Google Scholar 

  20. Wei C, Luo Z, Hogstrand C, Xu Y, Wu L, Chen G, Pan Y, Song Y (2018) Zinc reduces hepatic lipid deposition and activates lipophagy via Zn/MTF-1/PPARα and Ca/CaMKKβ/AMPK pathways. FASEB J:fj201800463. https://doi.org/10.1096/fj.201800463

  21. Coverdale J, Khazaipoul S, Arya S, Stewart A (1864) Blindauer C (2019) Crosstalk between zinc and free fatty acids in plasma. Biochim Biophys Acta 4:532–542. https://doi.org/10.1016/j.bbalip.2018.09.007

    Article  CAS  Google Scholar 

  22. Weigand E, Egenolf J (2017) A moderate zinc deficiency does not alter lipid and fatty acid composition in the liver of weanling rats fed diets rich in cocoa butter or safflower oil. J Nutr Metab 2017:4798963. https://doi.org/10.1155/2017/4798963

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wu N, Yang G, Tian C, Yi W, He S, Eskedar G, Xu F, Xie X, Xiang S, Du M, Bu Y, Ying C (2019) Effects of green tea polyphenols on trace metals level of rats on food restriction and high-fat diet. J Trace Elem Med Biol 51:91–97. https://doi.org/10.1016/j.jtemb.2018.10.002

    Article  CAS  PubMed  Google Scholar 

  24. Wang X, Karvonen-Gutierrez CA, Herman WH, Mukherjee B, Park SK (2022) Metals and risk of incident metabolic syndrome in a prospective cohort of midlife women in the United States. Environ Res 210:112976. https://doi.org/10.1016/j.envres.2022.112976

    Article  CAS  PubMed  Google Scholar 

  25. Olechnowicz J, Tinkov A, Skalny A, Suliburska J (2018) Zinc status is associated with inflammation, oxidative stress, lipid, and glucose metabolism. J Physiol Sci 68(1):19–31. https://doi.org/10.1007/s12576-017-0571-7

    Article  CAS  PubMed  Google Scholar 

  26. Cunha TA, Vermeulen-Serpa KM, Grilo EC, Leite-Lais L, Brandão-Neto J, Vale SHL (2022) Association between zinc and body composition: an integrative review. J Trace Elem Med Biol 71:126940. https://doi.org/10.1016/j.jtemb.2022.126940

    Article  CAS  PubMed  Google Scholar 

  27. Severo JS, Morais JBS, Beserra JB, de Farias LM, dos Santos LR, de Sousa Melo SR, do NascimentoNogueira N, do NascimentoMarreiro D (2019) Effect of zinc supplementation on lipid profile in obese people: a systematic review. Curr Nutr Food Sci 15:551–556. https://doi.org/10.2174/1573401314666180420094522

    Article  CAS  Google Scholar 

  28. Severo JS, Morais JBS, Beserra JB, Cruz KJC, de Oliveira ARS, dos Santos LR, de Matos Neto EM, de Macedo GFS, de Jesus e Silva de Almendra Freitas B, Henriques GS, do NascimentoMarreiro D (2020) Biomarkers of cardiovascular risk in obese women and their relationship with zinc status. Curr Nutr Food Sci 16:734–742. https://doi.org/10.2174/1573401315666191125113128

    Article  CAS  Google Scholar 

  29. Du L, Hong F, Luo P, Wang Z, Zeng Q, Guan H, Liu H, Yuan Z, Xu D, Nie F, Wang J (2022) Patterns and demographic correlates of domain-specific physical activities and their associations with dyslipidaemia in China: a multiethnic cohort study. BMJ Open 12(4):e052268. https://doi.org/10.1136/bmjopen-2021-052268

    Article  PubMed  PubMed Central  Google Scholar 

  30. Zhao X, Hong F, Yin J, Tang W, Zhang G, Liang X, Li J, Cui C, Li X (2021) Cohort profile: the China multi-ethnic cohort (CMEC) study. Int J Epidemiol 50(3):721–721l. https://doi.org/10.1093/ije/dyaa185

    Article  PubMed  Google Scholar 

  31. Liu X, Bragg F, Yang L, Kartsonaki C, Guo Y, Du H, Bian Z, Chen Y, Yu C, Lv J, Wang K, Zhang H, Chen J, Clarke R, Collins R, Peto R, Li L, Chen Z (2018) Smoking and smoking cessation in relation to risk of diabetes in Chinese men and women: a 9-year prospective study of 0·5 million people. Lancet Public Health 3(4):e167–e176. https://doi.org/10.1016/s2468-2667(18)30026-4

    Article  PubMed  PubMed Central  Google Scholar 

  32. Millwood IY, Li L, Smith M, Guo Y, Yang L, Bian Z, Lewington S, Whitlock G, Sherliker P, Collins R, Chen J, Peto R, Wang H, Xu J, He J, Yu M, Liu H (2017) Alcohol consumption in 0.5 million people from 10 diverse regions of China: prevalence, patterns and socio-demographic and health-related correlates. Int J Epidemiol 46(6):2103. https://doi.org/10.1093/ije/dyx210

    Article  PubMed  PubMed Central  Google Scholar 

  33. Du H, Bennett D, Li L, Whitlock G, Guo Y, Collins R, Chen J, Bian Z, Hong LS, Feng S, Chen X, Chen L, Zhou R, Mao E, Peto R, Chen Z (2013) Physical activity and sedentary leisure time and their associations with BMI, waist circumference, and percentage body fat in 0.5 million adults: the China Kadoorie Biobank study. Am J Clin Nutr 97(3):487–496. https://doi.org/10.3945/ajcn.112.046854

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Kshirsagar AV, Chiu YL, Bomback AS, August PA, Viera AJ, Colindres RE, Bang H (2010) A hypertension risk score for middle-aged and older adults. J Clin Hypertens (Greenwich) 12(10):800–808. https://doi.org/10.1111/j.1751-7176.2010.00343.x

    Article  PubMed  Google Scholar 

  35. Liu LS (2011) 2010 Chinese guidelines for the management of hypertension. Zhonghua Xin Xue Guan Bing Za Zhi 39(7):579–615

    PubMed  Google Scholar 

  36. Kazi TG, Afridi HI, Kazi N, Jamali MK, Arain MB, Jalbani N, Kandhro GA (2008) Copper, chromium, manganese, iron, nickel, and zinc levels in biological samples of diabetes mellitus patients. Biol Trace Elem Res 122(1):1–18. https://doi.org/10.1007/s12011-007-8062-y

    Article  CAS  PubMed  Google Scholar 

  37. Moore RET, Rehkämper M, Kreissig K, Strekopytov S, Larner F (2018) Determination of major and trace element variability in healthy human urine by ICP-QMS and specific gravity normalisation. RSC Adv 8(66):38022–38035. https://doi.org/10.1039/c8ra06794e

    Article  CAS  Google Scholar 

  38. Jiang Q, Xiao Y, Long P, Li W, Yu Y, Liu Y, Liu K, Zhou L, Wang H, Yang H, Li X, He M, Wu T, Yuan Y (2021) Associations of plasma metal concentrations with incident dyslipidemia: Prospective findings from the Dongfeng-Tongji cohort. Chemosphere 285:131497. https://doi.org/10.1016/j.chemosphere.2021.131497

    Article  CAS  PubMed  Google Scholar 

  39. Asghari S, Hosseinzadeh-Attar MJ, Alipoor E, Sehat M, Mohajeri-Tehrani MR (2019) Effects of zinc supplementation on serum adiponectin concentration and glycemic control in patients with type 2 diabetes. J Trace Elem Med Biol 55:20–25. https://doi.org/10.1016/j.jtemb.2019.05.007

    Article  CAS  PubMed  Google Scholar 

  40. Cho HW, Kim SH, Park MJ (2020) An association of blood mercury levels and hypercholesterolemia among Korean adolescents. Sci Total Environ 709:135965. https://doi.org/10.1016/j.scitotenv.2019.135965

    Article  CAS  PubMed  Google Scholar 

  41. Li X, Guan Y, Shi X, Ding H, Song Y, Li C, Liu R, Liu G (2013) Effects of high zinc levels on the lipid synthesis in rat hepatocytes. Biol Trace Elem Res 154(1):97–102. https://doi.org/10.1007/s12011-013-9702-z

    Article  CAS  PubMed  Google Scholar 

  42. Lu CW, Lee YC, Kuo CS, Chiang CH, Chang HH, Huang KC (2021) Association of serum levels of zinc, copper, and iron with risk of metabolic syndrome. Nutrients 13(2). https://doi.org/10.3390/nu13020548

  43. Peng Y, Li Z, Yang X, Yang L, He M, Zhang H, Wei X, Qin J, Li X, Lu G, Zhang L, Yang Y, Zhang Z, Zou Y (2020) Relation between cadmium body burden and cognitive function in older men: a cross-sectional study in China. Chemosphere 250:126535. https://doi.org/10.1016/j.chemosphere.2020.126535

    Article  CAS  PubMed  Google Scholar 

  44. Zhong Q, Wu H, Niu Q, Jia P, Qin Q, Wang X, He J, Yang W, Huang F (2021) Exposure to multiple metals and the risk of hypertension in adults: a prospective cohort study in a local area on the Yangtze River, China. Environ Int 153:106538. https://doi.org/10.1016/j.envint.2021.106538

    Article  CAS  PubMed  Google Scholar 

  45. Marreiro D, Fisberg M, Cozzolino S (2004) Zinc nutritional status and its relationships with hyperinsulinemia in obese children and adolescents. Biol Trace Elem Res 100(2):137–149. https://doi.org/10.1385/bter:100:2:137

    Article  PubMed  Google Scholar 

  46. Tubek S (2006) Urinary zinc excretion is normalized in primary arterial hypertension after perindopril treatment. Biol Trace Elem Res 114:127–133. https://doi.org/10.1385/bter:114:1:127

    Article  CAS  PubMed  Google Scholar 

  47. Banaszak M, Górna I, Przysławski J (2021) Zinc and the innovative zinc-α2-glycoprotein adipokine play an important role in lipid metabolism: a critical review. Nutrients 13(6). https://doi.org/10.3390/nu13062023

  48. Błażewicz A, Klatka M, Astel A, Partyka M, Kocjan R (2013) Differences in trace metal concentrations (Co, Cu, Fe, Mn, Zn, Cd, And Ni) in whole blood, plasma, and urine of obese and nonobese children. Biol Trace Elem Res 155(2):190–200. https://doi.org/10.1007/s12011-013-9783-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. King JC, Brown KH, Gibson RS, Krebs NF, Lowe NM, Siekmann JH, Raiten DJ (2015) Biomarkers of nutrition for development (BOND)-zinc review. J Nutr 146(4):858s–885s. https://doi.org/10.3945/jn.115.220079

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The investigators are grateful to the dedicated participants and all research staff of the study.

Funding

This research was supported by the National Natural Science Foundation of China (No. 82173566) and the National Key R&D Program of China (NO.2017YFC0907301).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, JZ; methodology, JZ and QY; investigation, LP and XZ; experiments, LZ and ZX; statistical analysis JZ, LL, and DX; writing original draft preparation, JZ; writing—review and editing, JZ, LL, and FH; administration, FH and TY; all authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Feng Hong.

Ethics declarations

Ethics Approval and Consent to Participate

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Medical Ethics Committee of Sichuan University (K2016038) and the Ethics Committee of The Affiliated Hospital of Guizhou Medical University (2018[094]). Informed consent was obtained from all subjects involved in the study.

Consent for Publication

Not applicable.

Conflict of Interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOC 472 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhong, J., Liu, L., Zhang, L. et al. Association of Urinary Zinc Concentrations with Dyslipidemia and Its Subtypes: Baseline Data from the Chinese Multi-Ethnic Cohort (CMEC) Study. Biol Trace Elem Res 201, 3592–3602 (2023). https://doi.org/10.1007/s12011-022-03454-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12011-022-03454-6

Keywords

Navigation