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Relationship Between Zinc, Selenium, and Magnesium Status and Markers of Metabolically Healthy and Unhealthy Obesity Phenotypes

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Abstract

Our objective was to investigate the relationship between zinc, selenium, and magnesium status and markers of metabolically healthy and unhealthy obesity phenotypes. This was a cross-sectional study with 140 women: metabolically healthy obese women (n = 35), metabolically unhealthy obese women (n = 28), and normal-weight women (n = 77). We have calculated the body mass index, waist-hip ratio, waist-height ratio and some adiposity indices. Additionally, we evaluated endocrine-metabolic parameters and estimated the dietary intake of energy, macronutrients, zinc, selenium, and magnesium. The mineral concentrations in plasma, erythrocytes, and urine were assessed. In obese patients, there was a significant decrease in dietary zinc, selenium, and magnesium intake per kilogram of body weight, as well as lower mineral concentrations in both plasma and erythrocytes. Additionally, these patients exhibited higher urinary mineral levels compared to the control group, regardless of whether they had healthy or unhealthy phenotypes. We observed a significant correlation between deficiencies in zinc, selenium, and magnesium and obesity-associated metabolic disorders, including dyslipidemias and redox status disturbances. This study highlights a connection between deficiencies in zinc, selenium, and magnesium and metabolic disorders linked to obesity, including dyslipidemias, alterations in redox status, and thyroid hormonal dysfunction.

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References

  1. World Health Organization (2016) Fact sheet on obesity and overweight. www.who.int/mediacentre/factsheets/fs311/en. Acess: 11/05/19

  2. Durward CM, Hartman TJ, Nickols-Richardson SM (2012) All-cause mortality risk of metabolically healthy obese individuals in NHANES III. J Obes 2012:1–12. https://doi.org/10.1155/2012/460321

    Article  CAS  Google Scholar 

  3. Blüher M (2020) Metabolically healthy obesity. Endocr Rev 3:bnaa004. https://doi.org/10.1210/endrev/bnaa004

    Article  Google Scholar 

  4. Mongraw-Chaffin M, Foster MC, Anderson CAM, Burke GL, Haq N, Kalyani RR, Ouyang P, Sibley CT, Tracy R, Woodward M, Vaidya D (2018) metabolically healthy obesity, transition to metabolic syndrome, and cardiovascular risk. J Am Coll Cardiol 17:1857–1865. https://doi.org/10.1016/j.jacc.2018.02.055

    Article  CAS  Google Scholar 

  5. Bray GA, Heisel WE, Afshin A, Jensen MD, Dietz WH, Long M et al (2018) The science of obesity management: an endocrine society scientific statement. Endocr Rev 39:79–132

    Article  PubMed  PubMed Central  Google Scholar 

  6. Morais JBS, Cruz KJC, de Oliveira ARS, Cardoso BEP, da Silva Dias TM, de Sousa Melo SR, Dos Santos LR, Severo JS, de Freitas ST, Henriques GS, da Silva MTB, Oliveira FE, do Nascimento Marreiro D (2023) Association between parameters of cortisol metabolism, biomarkers of minerals (Zn, Selenium, and Magnesium), and insulin resistance and oxidative stress in women with obesity. Biol Trace Elem Res 11. https://doi.org/10.1007/s12011-023-03639-7

  7. Fontenelle LC, Cardoso de Araújo DS, da Cunha Soares T, Clímaco Cruz KJ, Henriques GS, Marreiro DDN (2022) Nutritional status of selenium in overweight and obesity: a systematic review and meta-analysis. Clin Nutr 4:862–884. https://doi.org/10.1016/j.clnu.2022.02.007

    Article  CAS  Google Scholar 

  8. de Sousa Melo SR, Dos Santos LR, Morais JBS, Cruz KJC, de Oliveira ARS, da Silva NC, de Sousa GS, Payolla TB, Murata G, Bordin S, Henriques GS, do NascimentoMarreiro D, (2022) Leptin and its relationship with magnesium biomarkers in women with obesity. Biometals 4:689–697. https://doi.org/10.1007/s10534-022-00393-6

    Article  CAS  Google Scholar 

  9. Guerrero-Romero F, Rodriguez-Moran M (2013) Serum magnesium in the metabolically-obese normal-weight and healthy-obese subjects. Eur J Intern Med 7:639–43. https://doi.org/10.1016/j.ejim.2013.02.014

    Article  CAS  Google Scholar 

  10. Guerrero-Romero F, Morales-Gurrola G, Preza-Rodríguez L, Gómez-Barrientos A, Olivas-Martínez AI, Simental-Mendía LE (2022) Magnesium intake is associated with the metabolically healthy obese phenotype. J Investig Med 70:800–804. https://doi.org/10.1136/jim-2021-001841

    Article  PubMed  Google Scholar 

  11. Mirmiran P, Moslehi N, Hosseinpanah F, Sarbazi N, Azizi F (2020) Dietary determinants of unhealthy metabolic phenotype in normal weight and overweight/obese adults: results of a prospective study. Int J Food Sci Nutr 71:891–901. https://doi.org/10.1080/09637486.2020.1746955

    Article  CAS  PubMed  Google Scholar 

  12. Lee YA, Kim SH, Kim HN, Song SW (2020) Are there differences in hair mineral concentrations between metabolically healthy and unhealthy obese adults? Biol Trace Elem Res 2:311–318. https://doi.org/10.1007/s12011-019-01714-6

    Article  CAS  Google Scholar 

  13. Stenzel AP, Carvalho R, Jesus P, Bull A, Pereira S, Saboya C et al (2018) Serum antioxidant associations with metabolic characteristics in metabolically healthy and unhealthy adolescents with severe obesity: an observational study. Nutrients 10:1–9

    Article  Google Scholar 

  14. National Cholesterol Education Program (2002) Third report of the National Cholesterol Education Program (NCEP). Expert panel on detection, evaluation, and treatment of high blood cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 106:3143–3421

    Article  Google Scholar 

  15. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419

    Article  CAS  PubMed  Google Scholar 

  16. American Diabetes Association (ADA) (2017) Standards of medical care in diabetes. Diabetes Care 35:S11–S63. https://doi.org/10.2337/cd16-0067

    Article  Google Scholar 

  17. Brazil (2012) Ministry of Health. Resolution nº466/12. National Council for Research with Human Beings. Official Gazette of the Union. Brasília

  18. Brazil (2004) Ministry of health. Health care department. Primary health care department. Food and nutritional surveillance - sisvan: basic guidelines for collecting, processing, and analyzing data and information on health services. Ministry of Health, Brasília

  19. Ben-Noun LL, Sohar E, Laor A (2000) Neck circumference as a simple screening measure for identifying overweight and obese patients. Obes Res 9:470–477

    Article  Google Scholar 

  20. World Health Organization (2000) Obesity: preventing and managing the global epidemic. Technical report series, Geneva 894:9

  21. World Health Organization (2008) Waist Circumference and waist–hip ratio: report of a WHO expert consultation. Geneva

  22. Ben-Noun L, Laor A (2004) Relationship between changes in neck circumference and changes in blood pressure. Am J Hypertens 17:409–414

    Article  PubMed  Google Scholar 

  23. Elin RJ (1987) Assessment of magnesium status. Clin Chem 33:1965–1970

    Article  CAS  PubMed  Google Scholar 

  24. Wallace TM, Levy JC, Matthews DR (2004) Use and Abuse of HOMA Modeling. Diabetes Care 27:1487–1495

    Article  PubMed  Google Scholar 

  25. Andrade JP, Nobre F (2010) VI Diretriz Brasileira de Hipertensão. Arq Bras Cardiol 95:1–51

    Google Scholar 

  26. Friedewald WT, Levy RI, Fredrickson DS (1972) Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 18:499–502

    Article  CAS  PubMed  Google Scholar 

  27. Faludi AA, Izar MCO, Saraiva JFK et al (2017) Atualização da diretriz brasileira de dislipidemias e prevenção da aterosclerose. Arq Bras Cardiol 109:1–76

    Article  PubMed  Google Scholar 

  28. World Health Organization (1998) Obesity: preventing and managing the global epidemic. Report of a WHO Consulation on Obesity. Genebra (Suíça)

  29. Pitanga FJG, Lessa I (2006) Razão cintura-estatura como discriminador do risco coronariano de adultos. Rev Assoc Med Bras 52:157–161

    Article  PubMed  Google Scholar 

  30. Krakauer NY, Krakauer JC (2012) A new body shape index predicts mortality hazard independently of body mass index. PLoS ONE 7:e39504

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Thomas DM, Bredlau C, Bosy-Westphal A, Mueller M, Shen W, Gallagher D, Maeda Y, McDougall A, Peterson CM, Ravussin E, Heymsfield SB (2013) Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obesity 21:2264–2271

    Article  PubMed  Google Scholar 

  32. Bergman RN, Stefanovski D, Buchanan TA et al (2011) A better index of body adiposity. Obesity 19:1083–1089

    Article  PubMed  Google Scholar 

  33. Amato MC, Giordano C, Galia M et al (2010) Visceral Adiposity Index: a reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care 33:920–922

    Article  PubMed  PubMed Central  Google Scholar 

  34. Castelli WP, Abbot WD, Mcnamara PM (1983) Summary estimates of cholesterol used to predict coronary heart disease. Circulation 67:730–734

    Article  CAS  PubMed  Google Scholar 

  35. Ohkawa H, Ohishi N, Yagi K (1979) Assay of lipid peroxides in animal tissues by thiobarbituric acid reaction. Anal Biochem 95:351–358

    Article  CAS  PubMed  Google Scholar 

  36. Paglia DE, Valentine WN (1967) Studies on the quantitative and qualitative characterization of erythrocite glutathione peroxidase. J Lab Clin Med 70:159–169

    Google Scholar 

  37. Nieman LK, Biller BMK, Findling JW et al (2008) The diagnosis of Cushing’s syndrome: an endocrine society clinical practice guideline. J Clin Endocrinol Metab 93:1526–1540

    Article  CAS  PubMed Central  Google Scholar 

  38. Anção MS, Cuppari L, Draine AS, Singulem D (2002) Nutwin nutritional support program: version 1.5. Health Informatics Department, SPDM, Unifesp/EPM; 1 CDROM, São Paulo

  39. Institute of Medicine (1997) Food and nutrition board. Dietary reference intakes for calcium, phosphorus, magnesium, vitamin d and fluoride. National Academy Press, Washington

    Google Scholar 

  40. Institute of Medicine (2000) Dietary reference intakes for vitamin C, vitamin E, selenium, and carotenoids. National Academy Press, Washington

    Google Scholar 

  41. Institute of Medicine (2001) Dietary reference intakes for vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, silicon, vanadium, and zinc. National Academy Press, Washington

    Google Scholar 

  42. Institute of Medicine (2005) Food and nutition board. dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids. National Academy Press, Washington

    Google Scholar 

  43. Kipp AP, Strohm D, Brigelius-Flohé R et al (2015) Revised reference values for selenium intake. J Trace Elem Med Biol 32:195–199

    Article  CAS  PubMed  Google Scholar 

  44. Haubrock J, Nöthlings U, Volatier JL et al (2011) Estimating usual food intake distributions by using the multiple source method in the EPIC-Potsdam Calibration Study. J Nutr 141:914–920

    Article  CAS  PubMed  Google Scholar 

  45. Laureano GHC, Torman VB, Crispim SP, Dekkers AL, Camey SA (2016) Comparison of the ISU, NCI, MSM, and SPADE methods for estimating usual intake: a simulation study of nutrients consumed daily. Nutrients 8:166

    Article  PubMed  PubMed Central  Google Scholar 

  46. Harttig U, Haubrock J, Knüppel S, Boeing H; EFCOVAL Consortium (2011) The MSM program: web-based statistics package for estimating usual dietary intake using the Multiple Source Method. Eur J Clin Nutr 65:S87–91

  47. Souverein OW, Dekkers AL, Geelen A et al (2011) Comparing four methods to estimate usual intake distributions. Eur J Clin Nutr 65:S92-101

    Article  PubMed  Google Scholar 

  48. Fisberg RM, Marchioni DML, Slater B, Martini LA (2005) Food surveys: methods and scientific bases. Manole, São Paulo

    Google Scholar 

  49. Jaime PC, Latorre MRDO, Fornés NS, Zerbini CAF (2003) Comparative study among two methods for energy adjustment for nutrient intake. Nutrire 26:11–18

    Google Scholar 

  50. Willett WC, Howe GR, Kushi LH (1997) Adjustment for total energy intake in epidemiologic studies. AJCN 65:1220S-1228S

    CAS  Google Scholar 

  51. Whitehouse RC, Prasad AS, Rabbani PI, Cossack ZT (1982) Zinc in plasma, neutrophils, lymphocytes, and erythrocytes as determined by flameless atomic absorption spectrophotometry. Clin Chem 28:475–480

    Article  CAS  PubMed  Google Scholar 

  52. Gibson RS (2005) Assessment of chromium, copper and zinc status. In: Gibson RS (ed) Principles of Nutritional Assessment. Oxford University Press, New York, pp 711–30

    Chapter  Google Scholar 

  53. Guthrie HA, Picciano MF (1994) Micronutrient minerals. In: Guthrie HA, Picciano MF (eds). Human Nutrition, pp 351–7

  54. Thomson CD (2004) Assessment of requirements for selenium and adequacy of selenium status: a review. Eur J Nutr 58:391–402

    Article  CAS  Google Scholar 

  55. Vitoux D, Arnaud J, Chappuis P (1999) Are copper, zinc and selenium in erythrocytes valuable biological indexes of nutrition and pathology? J Trace Elem Med Biol 13:113–128

    Article  CAS  PubMed  Google Scholar 

  56. Topf JM, Murray PT (2003) Hypomagnesemia and hypermagnesemia. Rev Endocr Metab Disord 4:195–206

    Article  PubMed  Google Scholar 

  57. Tietz NW (1995) Clinical guide to laboratory test, 3rd edn. W.B. Saunders Company, Philadelphia

    Google Scholar 

  58. Harrell FE Jr (2011) Regression modeling strategies: with applications to linear models, logistic regression and survival analysis. Springer – Verlag, New York

    Google Scholar 

  59. Andreozzi VLR (2013) Function. aleskaandreozzi.weebly.com/scripts-in-r.html

  60. R Development Core Team (2019) R: a language and environment for statistical computing. Vienna, Austria: the R Foundation for Statistical. Computing. ISBN: 3–900051–07–0. URL http://www.R-project.org/

  61. Eckel N, Meidtner K, Kalle-Uhlmann T, Stefan N, Schulze MB (2016) Metabolically healthy obesity and cardiovascular events: a systematic review and meta-analysis. Eur J Prev Cardiol 23:956–966

    Article  PubMed  Google Scholar 

  62. Lin H, Zhang L, Zheng R, Zheng Y (2017) The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis A PRISMA-compliant article. Medicine 96:e8838

    Article  PubMed  PubMed Central  Google Scholar 

  63. Blüher M (2009) Adipose tissue dysfunction in obesity. Exp Clin Endocrinol Diabetes 117:241–250

    Article  PubMed  Google Scholar 

  64. Tsou MT, Yun CH, Lin JL, Sung KT, Tsai JP, Huang WH, Liu CY, Hou CJ, Tsai IH, Su CH, Hung CL, Hung TC (2020) Visceral adiposity, pro-inflammatory signaling and vasculopathy in metabolically unhealthy non-obesity phenotype. Diagnostics (Basel) 11:40. https://doi.org/10.3390/diagnostics11010040

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Yang HK, Lee SH, Han K, Kang B, Lee SY, Yoon KH, Kwon HS, Park YM (2015) Lower serum zinc levels are associated with unhealthy metabolic status in normal-weight adults: the 2010 Korea National Health and Nutrition Examination Survey. Diabetes Metab 41:282–290. https://doi.org/10.1016/j.diabet.2015.03.005

    Article  CAS  PubMed  Google Scholar 

  66. Marques Loureiro L, Lessa S, Mendes R, Pereira S, Saboya CJ, Ramalho A (2019) Does the metabolically healthy obese phenotype protect adults with class III obesity from biochemical alterations related to bone metabolism? Nutrients 11:2125. https://doi.org/10.3390/nu11092125

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Pelczyńska M, Moszak M, Bogdański P (2022) The role of magnesium in the pathogenesis of metabolic disorders. Nutrients 14:1714. https://doi.org/10.3390/nu14091714

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Piuri G, Zocchi M, Della Porta M, Ficara V, Manoni M, Zuccotti GV, Pinotti L, Maier JA, Cazzola R (2021) Magnesium in obesity, metabolic syndrome, and type 2 diabetes. Nutrients 13:320. https://doi.org/10.3390/nu13020320

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Rios-Lugo MJ, Madrigal-Arellano C, Gaytán-Hernández D, Hernández-Mendoza H, Romero-Guzmán ET (2020) Association of serum zinc levels in overweight and obesity. Biol Trace Elem Res 198:51–57. https://doi.org/10.1007/s12011-020-02060-8

    Article  CAS  PubMed  Google Scholar 

  70. Tinkov AA, Skalnaya MG, Ajsuvakova OP, Serebryansky EP, Chao JC, Aschner M, Skalny AV (2021) Selenium, zinc, chromium, and vanadium levels in serum, hair, and urine samples of obese adults assessed by inductively coupled plasma mass spectrometry. Biol Trace Elem Res 199:490–499. https://doi.org/10.1007/s12011-020-02177-w

    Article  PubMed  Google Scholar 

  71. Freitas EP, Cunha AT, Aquino SL, Pedrosa LF, Lima SC et al (2017) Zinc status biomarkers and cardiometabolic risk factors in metabolic syndrome: a case control study. Nutrients 22:E175

    Article  Google Scholar 

  72. Guerrero-Romero F, Flores-García A, Saldaña-Guerrero S, Simental-Mendía LE, Rodríguez-Morán M (2016) Obesity and hypomagnesemia. Eur J Int Med 34:29–33

    Article  CAS  Google Scholar 

  73. Cominetti C, Bortoli MC, Abdalla DSP, Cozzolino SMF (2011) Considerations about oxidative stress, selenium and nutrigenetics. Nutrire 36:131–153

    CAS  Google Scholar 

  74. Tsai JP (2017) The association of serum leptin levels with metabolic diseases. Ci Ji Yi Xue Za Zhi 29:192–196. https://doi.org/10.4103/tcmj.tcmj_123_17

    Article  PubMed  Google Scholar 

  75. Atabek ME, Kurtoglu S, Pirgon O (2006) Possible effect of leptin on renal magnesium excretion in adolescent patients with type 1 diabetes. Pediatr Int A48:393–7. https://doi.org/10.1111/j.1442-200X.2006.02227.x

    Article  CAS  Google Scholar 

  76. Azab SF, Saleh SH, Elsaeed WF, Elshafie MA, Sherief LM, Esh AM (2014) Serum trace elements in obese Egyptian children: a case-control study. Ital J Pediatr 20:20. https://doi.org/10.1186/1824-7288-40-20

    Article  CAS  Google Scholar 

  77. Zhu K, Nie S, Li C, Huang J, Hu X, Li W, Gong D et al (2013) Antidiabetic and pancreas-protective effects of zinc threoninate chelate in diabetic rats may be associated with its antioxidative stress ability. Biol Trace Elem Res 153:291–298

    Article  CAS  PubMed  Google Scholar 

  78. Brenneisen P, Steinbrenner H, Sies H (2005) Selenium, oxidative stress, and health aspects. Mol Aspects Med 26:256–267

    Article  CAS  PubMed  Google Scholar 

  79. Blache D, Devaux S, Joubert O, Loreau N, Schneider M, Durand P et al (2006) Long-term moderate magnesium-deficient diet shows relationships between blood pressure, inflammation and oxidant stress defense in aging rats. Free Radic Biol Med 41:277–284

    Article  CAS  PubMed  Google Scholar 

  80. Calviello G, Ricci P, Lauro L, Palozza P, Cittadini A (1994) Mg deficiency induces mineral content changes and oxidative stress in rats. Biochem Mol Biol Int 32:903–911

    CAS  PubMed  Google Scholar 

  81. Gueux E, Azais-Braesco V, Bussière L, Grolier P, Mazur A, Rayssiguier Y (1995) Effect of magnesium deficiency on triacylglycerol-rich lipoprotein and tissue susceptibility to peroxidation in relation to vitamin E content. Br J Nutr 74:849–856

    CAS  PubMed  Google Scholar 

  82. Zhu Z, Kimura M, Itokawa Y (1993) Selenium concentration and glutathione peroxidase activity in selenium and magnesium deficient rats. Biol Trace Elem Res 37:209–17. https://doi.org/10.1007/BF02783796

    Article  CAS  PubMed  Google Scholar 

  83. Olechnowicz J, Tinkov A, Skalny A, Suliburska J (2018) Zinc status is associated with inflammation, oxidative stress, lipid, and glucose metabolism. J Physiol Sci 68:19–31

    Article  CAS  PubMed  Google Scholar 

  84. Mejía-Rodríguez F, Shamah-Levy T, Villalpando S, García-Guerra A, Méndez-Gómez Humarán I (2013) Iron, zinc, copper and magnesium deficiencies in Mexican adults from the National Health and Nutrition Survey 2006. Salud Publica Mex 55:275–284

    Article  PubMed  Google Scholar 

  85. Gharipour M, Sadeghi M, Behmanesh M, Salehi M, Nezafati P, Gharpour A (2017) Selenium homeostasis and clustering of cardiovascular risk factors: a systematic review. Acta Biomed 88:263–270

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Gać P, Czerwińska K, Macek P, Jaremków A, Mazur G, Pawlas K, Poręba R (2021) The importance of selenium and zinc deficiency in cardiovascular disorders. Environ Toxicol Pharmacol 82:103553. https://doi.org/10.1016/j.etap.2020.103553

    Article  CAS  PubMed  Google Scholar 

  87. Schweizer U, Steegborn C (2015) New insights into the structure and mechanism of iodothyronine deiodinases. J Mol Endocrinol 55:R37-52

    Article  CAS  PubMed  Google Scholar 

  88. Hsu JM, Root AW, Duckett GE, Smith JC Jr, Yunice AA, Kepford G (1984) The effect of magnesium depletion on thyroid function in rats. J Nutr Aug 114:1510–7

    Article  CAS  Google Scholar 

  89. Ahn BI, Kim MJ, Koo HS, Seo N, Joo NS, Kim YS (2014) Serum zinc concentration is inversely associated with insulin resistance but not related with metabolic syndrome in nondiabetic Korean adults. Biol Trace Elem Res 160:169–175

    Article  CAS  PubMed  Google Scholar 

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Funding

This study was funded by the National Coordination of Higher Education Personnel Training Programs (CAPES – Brazil) (Finance Code 001).

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Authors and Affiliations

  1. Postgraduate Program in Food and Nutrition, Federal University of Piaui, Campus Minister Petrônio Portela, Ininga, Teresina, Piaui, Brazil

    Kyria Jayanne Clímaco Cruz, Ana Raquel Soares de Oliveira, Larissa Cristina Fontenelle, Jennifer Beatriz Silva Morais, Stéfany Rodrigues de Sousa Melo, Loanne Rocha dos Santos & Thayanne Gabryelle Visgueira de Sousa

  2. Planning and Institucional Development, Federal University of Pará, Belém, Pará, Brazil

    Suelem Torres de Freitas

  3. School of Nursing, Federal University of Minas Gerais, 6627 Pres. Antônio Carlos Ave. Pampulha, Belo Horizonte, Minas Gerais, Brazil

    Gilberto Simeone Henriques

  4. University of Sao Paulo, Sao Paulo, Brazil

    Silvana Bordin

  5. State University of Ceara, Fortaleza, Ceara, Brazil

    Carla Soraya Costa Maia

  6. Clinical Laboratory, Teresina, Piauí, Brazil

    Francisco Erasmo de Oliveira

  7. Department of Community Medicine, Federal University of Piaui, Teresina, Brazil

    Carlos Henrique Nery Costa

  8. Department of Physical Education, Federal University of Piaui, Campus Minister Petrônio Portela, Ininga, Teresina, Piaui, Brazil

    Emídio Marques de Matos Neto

  9. Department of Nutrition, Federal University of Piaui, Campus Minister Petrônio Portela, Ininga, Teresina, Piaui, Brazil

    Dilina do Nascimento Marreiro

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  1. Kyria Jayanne Clímaco Cruz
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  2. Ana Raquel Soares de Oliveira
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  3. Larissa Cristina Fontenelle
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  4. Jennifer Beatriz Silva Morais
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  7. Thayanne Gabryelle Visgueira de Sousa
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  8. Suelem Torres de Freitas
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Contributions

Cruz KJC, Oliveira ARS, Morais JBS, Santos LR, Melo SRS, Fontenelle LC have participated to the redaction and the review of the manuscript; Oliveira ARS, Cruz KJC, Morais JBS, Santos LR, Melo SRS, Fontenelle LC, Sousa TGV, Freitas ST, Henriques GS, Silva SAB, Maia CSC, Oliveira FE have participated to generation, collection, assembly, analysis and/or interpretation of data; Costa CHN, Matos EMN and Marreiro DN had supervised the paper, participated in the redaction and the review of the paper.

Corresponding author

Correspondence to Thayanne Gabryelle Visgueira de Sousa.

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Ethics Approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Federal University of Piauí (Date: 12 April 2017/No 2.014.100). Informed consent was obtained from all individual participants included in the study.

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The authors declare no competing interests.

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Cruz, K.J.C., de Oliveira, A.R.S., Fontenelle, L.C. et al. Relationship Between Zinc, Selenium, and Magnesium Status and Markers of Metabolically Healthy and Unhealthy Obesity Phenotypes. Biol Trace Elem Res (2023). https://doi.org/10.1007/s12011-023-03938-z

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