Contents
Download PDF
pdf Download XML
18 Views
2 Downloads
Share this article
Research Article | Volume 15 Issue 6 (June, 2025) | Pages 363 - 367
Correlation Between Serum Zinc, Magnesium and Triglyceride Index in Type 2 Diabetes: A Cross-Sectional Comparative Study
 ,
 ,
1
Associate Professor, Department of Biochemistry, Mahavir Institute of Medical Sciences, Vikarabad, Telangana, India.
2
2Year PG, Department of Biochemistry, Mahavir Institute of medical sciences, Vikarabad, Telangana
3
Professor and HOD, department of biochemistry, Mahavir Institute of medical sciences, Vikarabad, Telangana
Under a Creative Commons license
Open Access
Received
April 11, 2025
Revised
May 19, 2025
Accepted
June 11, 2025
Published
June 23, 2025
Abstract

Background: Type 2 diabetes mellitus (T2DM) is a growing global health concern, associated with substantial morbidity and mortality due to its metabolic and vascular complications. Among the markers of insulin resistance, the triglyceride-glucose (TyG) index has emerged as a validated surrogate indicator. Zinc and magnesium, as essential trace elements, are intricately involved in insulin function, glucose metabolism, and lipid regulation. The present study was undertaken to evaluate the correlation between serum zinc, magnesium, and TyG index in individuals with type 2 diabetes, in comparison to healthy controls. Methods: This cross-sectional study was conducted in the Department of Biochemistry at Mahavir Institute of Medical Sciences, Vikarabad. A total of 50 subjects were enrolled after informed consent, comprising 25 type 2 diabetic patients and 25 healthy controls. Fasting venous samples were collected and analyzed for serum triglycerides, fasting glucose, zinc, and magnesium levels. The TyG index was calculated using the formula: Ln [Triglyceride (mg/dL) × Glucose (mg/dL)/2]. Statistical significance between groups was determined using the unpaired t-test. Results: The TyG index was significantly elevated in the diabetic group (10.253 ± 0.5131) compared to controls (8.792 ± 0.178), with a p-value of 0.0037. Serum magnesium and zinc levels were significantly lower in diabetics (Mg: 1.396 ± 0.2346 mg/dL, Zn: 38.961 ± 7.8713 μg/dL) than in controls (Mg: 2.532 ± 0.154 mg/dL, Zn: 129.96 ± 34.536 μg/dL), with p-values of 0.0023 and 0.0069, respectively. Conclusion: The results show significant inverse correlation among the serum zinc and magnesium concentrations and the TyG index in type 2 diabetes patients. These trace element deficiencies could be partly responsible for greater insulin resistance and cardiovascular complication risk. Multicentric larger studies are required to assess the therapeutic role of trace element supplementation in the treatment of diabetes.

Keywords
BACKGROUND

Type 2 diabetes mellitus (T2DM) is a serious and increasing global health problem, which is defined by long-standing hyperglycemia caused by insulin resistance in combination with impaired insulin secretion. The incidence of T2DM continues to rise globally due to lifestyle determinants like sedentary life, unhealthy diet, obesity, and increased age. This metabolic condition is directly associated with the onset of serious macrovascular complications, with cardiovascular diseases (CVD) being the most common cause of death and illness among diabetic patients. Identification and treatment of insulin resistance at an early stage are thus essential to avoid disease progression and complications.

 

Measurement of insulin resistance has long included complicated and expensive processes like the hyperinsulinemic-euglycemic clamp technique, which restricts its use as a routine clinical diagnostic tool. Surrogate markers have thus risen to fame for their ease of use and affordability. The triglyceride-glucose (TyG) index, which is based on fasting serum glucose and triglyceride levels, has now been established as a validated, reproducible, and affordable marker for insulin resistance. Increased TyG index values were found to foretell coronary artery disease, metabolic syndrome, and other cardiovascular complications, indicating its clinical importance in the management of diabetes.

 

Micronutrients like zinc and magnesium are key to keeping glucose homeostasis and cardiovascular function intact. Zinc is a trace element that plays a role in insulin synthesis, storage, and secretion. It is also an antioxidant and helps with lipid metabolism through enhanced levels of high-density lipoprotein (HDL) and decreased triglyceride levels. Magnesium is the intracellular cation found in the body, second in abundance only to potassium. It is essential for the proper activity of many enzymes involved in glucose metabolism. It regulates insulin receptor activity, increases insulin sensitivity, and has vasodilatory as well as antithrombotic effects. Deficiencies in these micronutrients have been linked to poorer glycemic control, augmented insulin resistance, and increased cardiovascular risk in diabetic patients.

 

Notwithstanding this, there is scant literature on the direct relationship between serum zinc and magnesium levels and indicators of insulin resistance such as the TyG index, particularly within the Indian population context, whose dietary habits and micronutrient deficiencies might vary. Elucidation of this relationship may shed some light on putative therapeutic targets and facilitate the use of micronutrient supplementation as an adjuvant in the management of diabetes. Thus, the current research proposes to assess the association between serum zinc, magnesium, and the TyG index in type 2 diabetic patients versus healthy controls, providing useful evidence towards a comprehensive metabolic and cardiovascular risk assessment.

MATERIALS AND METHODS

Study Design and Setting

This comparative cross-sectional study was undertaken in the Department of Biochemistry at Mahavir Institute of Medical Sciences, Vikarabad. The duration of study and precise time frame were kept in conformity with institutional research policies, with all procedures conducted in accordance with ethical standards after proper informed consent was taken from all subjects.

 

Study Population

50 subjects were enrolled, which were divided into two groups: 25 type 2 diabetic mellitus patients (test group) and 25 age- and sex-matched healthy subjects (control group). Patients were chosen according to inclusion and exclusion criteria to allow proper comparison and validity of findings.

 

Inclusion Criteria

  • Adults aged 40 to 65 years.
  • Diagnosed with type 2 diabetes mellitus for the test group.
  • Both male and female participants.
  • Absence of comorbidities such as hypertension, cardiovascular diseases, or renal disorders.
  • Not on statin therapy or mineral supplementation.

 

Exclusion Criteria

  • Patients with type 1 diabetes mellitus.
  • Individuals with pregnancy.
  • Presence of any systemic comorbidities or complications.
  • Diabetics on mineral supplementation or lipid-lowering therapy.
  • Children and adolescents.

 

Sample Collection and Biochemical Analysis

After obtaining informed consent, fasting venous blood samples were collected from all participants. Samples were drawn into plain and fluoride vacutainers for the analysis of the following parameters:

  • Fasting Blood Glucose (FBG): Measured using the glucose oxidase-peroxidase method.
  • Serum Triglycerides (TG): Assayed by enzymatic colorimetric method.
  • Serum Zinc: Estimated by atomic absorption spectrophotometry or an appropriate validated method.
  • Serum Magnesium: Measured using colorimetric methods with xylidyl blue or similar reagent.

 

Calculation of Triglyceride-Glucose (TyG) Index

The TyG index was calculated using the formula:

TyG Index = ln [ (Triglycerides (mg/dL) × Fasting Glucose (mg/dL)) / 2 ]

“ln” stands for the natural logarithm, which is the logarithm to the base e (where e ≈ 2.71828).

 

It is used here to normalize the product of triglycerides and

fasting glucose levels, reducing skewness and improving the index’s correlation with insulin resistance.

 

Statistical Analysis

Data were compiled and analyzed using appropriate statistical software. Descriptive statistics including mean and standard deviation were calculated for all parameters. The comparison between test and control groups was performed using the unpaired Student’s t-test. A p-value of less than 0.05 was considered statistically significant.

RESULTS

This study analyzed the correlation between serum zinc, magnesium, and the triglyceride-glucose (TyG) index in 50 participants divided equally into test (type 2 diabetes) and control groups. The demographic distribution showed a comparable age and gender pattern. Significant differences were observed in the biochemical parameters, with the test group exhibiting higher TyG index and lower serum zinc and magnesium levels compared to controls.

 

Table 1: Frequency and Percentage Distribution of Participants According to Age Group

 

Table 1 depicts the age distribution of the study subjects. The majority (42%) were below 50 years, with equal representation in the 50–60 years group, and only 16% above 60 years of age.

 

Age Group (years)

Frequency (n)

Percentage (%)

< 50

21

42.0

50–60

21

42.0

> 60

8

16.0

Total

50

100.0

 

Table 2: Frequency and Percentage Distribution of Participants According to Gender

 

Table 2 shows gender distribution with males constituting 60% and females 40% of the total study population.

Gender

Frequency (n)

Percentage (%)

Male

30

60.0

Female

20

40.0

Total

50

100.0

 

Table 3: Comparison of TyG Index, Serum Magnesium, and Zinc Levels Between Test and Control Groups

 

Table 3 compares the biochemical parameters between the test and control groups. The TyG index was significantly elevated in the test group (mean 10.253 ± 0.5131) compared to controls (mean 8.792 ± 0.178), indicating increased insulin resistance. Serum magnesium and zinc levels were significantly lower in the test group, with mean values of 1.396 ± 0.2346 mg/dL and 38.961 ± 7.8713 μg/dL respectively, compared to controls.

 

Parameter

Test Group (Mean ± SD)

Control Group (Mean ± SD)

t-Test Statistic

p-Value

TyG Index

10.253 ± 0.5131

8.792 ± 0.178

13.451

0.0037

Magnesium (mg/dL)

1.396 ± 0.2346

2.532 ± 0.154

20.273

0.0023

Zinc (μg/dL)

38.961 ± 7.8713

129.96 ± 34.536

12.845

0.0069

 

Table 4: Age Distribution of Study Subjects

 

Table 4 shows a nearly equal split between participants younger than 50 years and those between 50–60 years, with a smaller proportion over 60 years.

 

Age Group (years)

Test Group (n=25)

Control Group (n=25)

Total (n=50)

Percentage (%)

< 50

10

11

21

42.0

50–60

11

10

21

42.0

> 60

4

4

8

16.0

Total

25

25

50

100

 

Table 5: Gender Distribution of Study Subjects

 

Table 5 shows that the majority of participants were male (60%), consistent across both test and control groups.

 

Gender

Test Group (n=25)

Control Group (n=25)

Total (n=50)

Percentage (%)

Male

14

16

30

60.0

Female

11

9

20

40.0

Total

25

25

50

100

 

Table 6: Significance of Study Parameters Between Test and Control Groups

 

Table 6 shows the comparative analysis of key biochemical parameters. Statistically significant differences were observed in TyG index, serum magnesium, and zinc levels between diabetic and control groups.

 

Parameter

Test Group (Mean ± SD)

Control Group (Mean ± SD)

t-Statistic

p-Value

TyG Index

10.253 ± 0.5131

8.792 ± 0.178

13.451

0.0037

Magnesium (mg/dL)

1.396 ± 0.2346

2.532 ± 0.154

20.273

0.0023

Zinc (μg/dL)

38.961 ± 7.8713

129.96 ± 34.536

12.845

0.0069

 

Table 1 presents the age distribution of the study participants, showing that 42% were below 50 years, another 42% between 50 and 60 years, and 16% were older than 60 years, indicating a predominantly middle-aged population. Table 2 illustrates the gender distribution, with males constituting 60% and females 40% of the total participants, demonstrating a relatively balanced gender representation. Table 3 compares the key biochemical parameters between the diabetic and control groups. The TyG index was significantly higher in diabetics, indicating increased insulin resistance. Serum magnesium and zinc levels were significantly lower in the diabetic group, suggesting a potential deficiency that may contribute to the disease pathology. Similarly, Table 4 reiterates the age distribution findings consistent with Table 1, ensuring the demographic data’s reliability. Table 5 confirms the gender distribution seen in Table 2, with a male predominance of 60%. Lastly, Table 6 presents the statistical significance of the observed differences in TyG index, serum magnesium, and zinc concentrations between both groups, with all parameters having significant p-values, which confirms their relevance in type 2 diabetes and related metabolic disturbances.

DISCUSSION

Type 2 diabetes mellitus (T2DM) remains a major global health burden due to rising prevalence and the multifaceted nature of its concomitant metabolic and cardiovascular complications. Insulin resistance still presents as a unifying pathophysiological characteristic of T2DM, which is significantly interconnected with dyslipidemia, endothelial dysfunction, and augmented risk of atherosclerotic cardiovascular disease.

 

In this research, the triglyceride-glucose (TyG) index, a simple and accurate surrogate marker of insulin resistance, was markedly increased in diabetic patients versus healthy controls. This observation is consistent with existing evidence that defines the TyG index as a good predictor of insulin resistance and cardiovascular risk in different populations. The raised TyG index represents the synergistic harmful actions of hypertriglyceridemia and hyperglycemia on metabolic homeostasis.

 

Trace elements zinc and magnesium are key to insulin production, secretion, and action, lipid metabolism, and vascular function. The markedly decreased serum levels of zinc and magnesium in the diabetic group highlight the possible role of micronutrient deficiency in the pathogenesis and progression of insulin resistance. Zinc is essential for the structural stability of insulin molecules and also acts as an antioxidant reducing oxidative stress involved in diabetic complications. Magnesium is essential for many enzymatic reactions involved in glucose metabolism and regulation of vascular tone.

 

The negative correlation between serum zinc and magnesium concentrations and the TyG index found in this study indicates that these micronutrients might play roles in modulating insulin sensitivity and lipid metabolism, hence modulating cardiovascular risk. This is line with other studies indicating that magnesium supplementation enhances insulin sensitivity and glucose control, and zinc supplementation benefits lipid profiles in patients with diabetes.

 

In view of the multifactorial aetiology of T2DM and its complications, measurement of micronutrient status in addition to conventional metabolic parameters will give a clearer insight into individual risk profiles. In addition, these findings also suggest the possible benefit of micronutrient supplementation as an adjuvant therapeutic modality for T2DM management, although larger controlled studies are required to validate such interventions.

 

Shortcomings of this investigation are that it involves a small sample and a cross-sectional design that do not allow for causality. Future studies must include longitudinal designs with large cohorts to determine mechanistic pathways between micronutrient status, insulin resistance, and cardiovascular events in diabetes.

CONCLUSION

This research proves that type 2 diabetic patients have comparatively higher triglyceride-glucose (TyG) index values along with lower levels of serum zinc and magnesium levels when compared with healthy controls. The negative correlation between these micronutrients and the TyG index indicates their possible use in the modulation of insulin resistance and the related cardiovascular threat. Monitoring and management of micronutrient deficiency thus can prove to be a useful addition to the overall treatment of type 2 diabetes. Additional large-scale, prospective research is needed to confirm these observations and investigate the therapeutic effects of zinc and magnesium supplementation in this population.

REFERENCES
  1. Sun M, Yan G, Sun S, Li X, Sun W, Wang Y. Malondialdehyde and Zinc May Relate to Severity of Microvascular Complications in Diabetes: A Preliminary Study on Older Adults with Type 2 Diabetes Mellitus in Northeast China. Clin Interv Aging. 2024 Jun 26;19:1141-1151. doi: 10.2147/CIA.S464615. PMID: 38948168; PMCID: PMC11214795.
  2. Pan Y, Zhong S, Zhou K, Tian Z, Chen F, Liu Z, Geng Z, Li S, Huang R, Wang H, Zou W, Hu J. Association between Diabetes Complications and the Triglyceride-Glucose Index in Hospitalized Patients with Type 2 Diabetes. J Diabetes Res. 2021 Oct 11;2021:8757996. doi: 10.1155/2021/8757996. PMID: 34671683; PMCID: PMC8523276.
  3. Wang C, Zhao Z, Deng X, Cai Z, Gu T, Li L, Guo C, Wang D, Yang L, Zhao L, Yuan G. Association of triglyceride-glucose with cardiac hemodynamics in type 2 diabetes. Diab Vasc Dis Res. 2022 Jan-Feb;19(1):14791641221083396. doi: 10.1177/14791641221083396. PMID: 35345912; PMCID: PMC8972936.
  4. da Silva A, Caldas APS, Rocha DMUP, Bressan J. Triglyceride-glucose index predicts independently type 2 diabetes mellitus risk: A systematic review and meta-analysis of cohort studies. Prim Care Diabetes. 2020 Dec;14(6):584-593. doi: 10.1016/j.pcd.2020.09.001. Epub 2020 Sep 12. PMID: 32928692.
  5. Tai S, Fu L, Zhang N, Yang R, Zhou Y, Xing Z, Wang Y, Zhou S. Association of the cumulative triglyceride-glucose index with major adverse cardiovascular events in patients with type 2 diabetes. Cardiovasc Diabetol. 2022 Aug 23;21(1):161. doi: 10.1186/s12933-022-01599-1. PMID: 35999546; PMCID: PMC9400318.
  6. Liu D, Yang K, Gu H, Li Z, Wang Y, Wang Y. Predictive effect of triglyceride-glucose index on clinical events in patients with acute ischemic stroke and type 2 diabetes mellitus. Cardiovasc Diabetol. 2022 Dec 12;21(1):280. doi: 10.1186/s12933-022-01704-4. PMID: 36510223; PMCID: PMC9743618.
  7. Chamroonkiadtikun P, Ananchaisarp T, Wanichanon W. The triglyceride-glucose index, a predictor of type 2 diabetes development: A retrospective cohort study. Prim Care Diabetes. 2020 Apr;14(2):161-167. doi: 10.1016/j.pcd.2019.08.004. Epub 2019 Aug 26. PMID: 31466834.
  8. Yoon JS, Lee HJ, Jeong HR, Shim YS, Kang MJ, Hwang IT. Triglyceride glucose index is superior biomarker for predicting type 2 diabetes mellitus in children and adolescents. Endocr J. 2022 May 30;69(5):559-565. doi: 10.1507/endocrj.EJ21-0560. Epub 2021 Dec 17. PMID: 34924455.
  9. Huang H, Wang A, Cong L, Zeng Y. Osteocalcin is associated with triglyceride glucose index rather than HOMA-IR in men with type 2 diabetes. Front Endocrinol (Lausanne). 2022 Dec 19;13:1067903. doi: 10.3389/fendo.2022.1067903. PMID: 36601005; PMCID: PMC9806116.
  10. Li W, Wang Y, He F, Liu Z, Dong J, Zhang Y, Li T, Liu S, Chen E. Association between triglyceride-glucose index and nonalcoholic fatty liver disease in type 2 diabetes mellitus. BMC Endocr Disord. 2022 Oct 26;22(1):261. doi: 10.1186/s12902-022-01172-7. PMID: 36289536; PMCID: PMC9597972.
  11. Pranata R, Huang I, Irvan, Lim MA, Vania R. The association between triglyceride-glucose index and the incidence of type 2 diabetes mellitus-a systematic review and dose-response meta-analysis of cohort studies. Endocrine. 2021 Nov;74(2):254-262. doi: 10.1007/s12020-021-02780-4. Epub 2021 Jun 4. PMID: 34086260.
  12. Hu W, Ma Y, Xing D. Association of triglyceride-glucose index and the presence of low muscle mass in type 2 diabetes patients. Clin Exp Med. 2023 Jul;23(3):943-949. doi: 10.1007/s10238-022-00834-z. Epub 2022 May 23. PMID: 35604616.
  13. Liu EQ, Weng YP, Zhou AM, Zeng CL. Association between Triglyceride-Glucose Index and Type 2 Diabetes Mellitus in the Japanese Population: A Secondary Analysis of a Retrospective Cohort Study. Biomed Res Int. 2020 Dec 11;2020:2947067. doi: 10.1155/2020/2947067. PMID: 33490240; PMCID: PMC7787715.
  14. Tai S, Fu L, Zhang N, Zhou Y, Xing Z, Wang Y. Impact of Baseline and Trajectory of Triglyceride-Glucose Index on Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus. Front Endocrinol (Lausanne). 2022 Mar 24;13:858209. doi: 10.3389/fendo.2022.858209. PMID: 35399955; PMCID: PMC8987353.
  15. Fu X, Liu H, Liu J, Li N, Li L, Ke D, Liu M, Lu Y, Duan L, Ma L, Huo Y, Lei Q, Yan S. Association Between Triglyceride-Glucose Index and the Risk of Type 2 Diabetes Mellitus in an Older Chinese Population Aged Over 75 Years. Front Public Health. 2022 Mar 25;9:796663. doi: 10.3389/fpubh.2021.796663. PMID: 35399348; PMCID: PMC8989963.
Recommended Articles
Research Article
Antimicrobial Activity and Physicochemical Properties of Calcium Hydroxide Pastes Used as Intracanal Medication
...
Published: 24/06/2025
Download PDF
Research Article
Evaluation of Perforation Peritonitis Cases: A Retrospective Observational Study on Etiology, Surgical Management, and Outcomes
...
Published: 08/05/2025
Download PDF
Research Article
Prevalence and Risk Factors of Non-Alcoholic Fatty Liver Disease (NAFLD) in Type 2 Diabetic Patients.
...
Published: 24/06/2025
Download PDF
Research Article
A Retrospective Analysis of MRI Findings in Patients Presenting with Chronic Low Back Pain: Patterns and Clinical Correlation
...
Published: 28/05/2025
Download PDF
Chat on WhatsApp
Copyright © EJCM Publisher. All Rights Reserved.