Association of Zinc Deficiency with Poor Glycemic Control in Patients with Type 2 Diabetes Mellitus

Association of Zinc Deficiency with Poor Glycemic Control in Patients with Type 2 Diabetes Mellitus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of Zinc Deficiency with Poor Glycemic Control in Patients with Type 2 Diabetes Mellitus Anil Khadka, Anit Lamichhane, Rabina Maharjan, Govardhan Joshi, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9412794/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance and impaired insulin secretion. Zinc (Zn), an essential micronutrient, plays a crucial role in insulin synthesis, secretion, and glucose homeostasis. Zinc deficiency is frequently observed in T2DM and may influence glycemic control. This study aimed to assess the relationship between zinc levels and glycemic control in individuals with type 2 diabetes. Methods: This case-control cross-sectional study was conducted among 200 subjects, including 100 type 2 diabetic cases and 100 controls attending the medicine OPD of Manmohan Memorial Medical College and Teaching Hospital, Kathmandu, Nepal. The standard protocol was used to estimate all biochemical parameters, including fasting blood sugar (FBS), postprandial blood sugar (PPBS), HbA1c, urea, creatinine, and zinc. Ethical approval was obtained from NEHCO-IRC. Results: Serum zinc levels were significantly lower in T2DM patients compared to healthy controls (86.69±17.82 vs. 96.87±14.86 µg/dl, p 7%) had significantly lower zinc levels than those with good control (82.83 ± 17.84 vs. 91.22±16.89 µg/dl, p = 0.018). A significant negative correlation was observed between zinc and HbA1c (r = −0.240, p = 0.016). Regression analysis revealed that each 1% increase in HbA1c was associated with a 2.19 µg/dl decrease in serum zinc. No significant association was found between zinc levels and duration of diabetes. Conclusion: Serum zinc levels are significantly reduced in T2DM patients and are inversely associated with HbA1c. Zinc deficiency may contribute to poor glycemic control, highlighting the importance of monitoring zinc status in T2DM management. Endocrinology & Metabolism T2DM Zinc Glycemic control Figures Figure 1 Figure 2 INTRODUCTION Type 2 diabetes mellitus(T2DM) is a chronic metabolic disorder characterized by insulin resistance and impaired insulin secretion, leading to hyperglycemia and associated metabolic complications. It is a major global health burden affecting millions of people worldwide. Among these micronutrient deficiencies, particularly Zinc (Zn) is prevalent among T2DM. Zn is an important micronutrient that helps many enzymes act as cofactors, protein folding, gene expression, neutralization of reactive oxygen species (ROS), cell signaling, cell division, apoptosis, and glucose homeostasis. Zinc (Zn) helps increase the expression of glucose transporter type 4 (GLUT-4), which improves glucose uptake into cells, and also plays an important role in the synthesis, storage, and release of insulin from pancreatic β-cells 3 . The zinc transporter ZnT8 helps maintain zinc balance in these cells, and its dysfunction can impair insulin production 3 . 4 . Zinc deficiency is commonly observed in patients with T2DM and is associated with β-cell dysfunction and poor glycemic control 5 . Emerging evidence suggests Zn dysregulation and T2DM have a bidirectional relationship, with each condition potentially worsening the other 6 . Therefore, this study aimed to investigate the association between serum Zn levels and glycemic control among T2DM cases METHODS Study design and Participants: This cross-sectional study was conducted in collaboration between Manmohan Memorial Medical College and Teaching Hospital (MMTH) and Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal, from December 2023 to May 2024. A total of 200 participants were included in the study. Inclusion and Exclusion Criteria: A total of 200 participants attending the Endocrinology OPD at MMTH were included in the study, comprising 100 patients with both newly diagnosed and long-term type 2 diabetes mellitus and 100 relatively healthy individuals. This study excluded individuals who had a history of chronic alcohol consumption, pregnant individuals, and those taking zinc or multivitamin supplements. Informed Consent: Written informed consent was obtained from all participants after thoroughly explaining the procedures to them in the Nepali language. Participants were guaranteed anonymity and confidentiality. Experimental Protocol: A pretest, self-administered questionnaire was used to collect the data. Five-milliliter fasting samples (8 to 12 hours of fasting) and postprandial (2 hours after a meal) blood samples were collected via venipuncture. The collected sample was separated into different sample collection tubes. A yellow vial (BD Vacutainer® SST™ Tubes) was used for serum separation, an EDTA vial (BD Vacutainer® SST™ Tubes) was used for glycated hemoglobin estimation, and a fluoride vial (BD Vacutainer® SST™ Tubes) was used for glucose estimation. The biochemistry parameters, such as fasting blood sugar, postprandial, urea, and creatinine, were analyzed by using a fully automated chemistry analyzer (VITROS® 350 Chemistry System, USA). Zinc was estimated via a semiautomated analyzer (AGD 200), and glycated hemoglobin was analyzed via a fully automated analyzer (Lifotronic analyzer). In this study, the levels of FBS, PPBS, urea, and creatinine are expressed in mg/dL, and the levels of zinc and glycated hemoglobin are expressed in µg/dl and percentage (%), respectively. Statistical analysis: The questionnaire collected all the data and recorded it in the Microsoft Excel 2019 database; all the data were analyzed via SPSS version 26. Independent T-tests, Spearman’s correlations, ANOVA, and linear regression were applied in SPSS. Normally, disturbed data, such as the mean and standard deviation, are taken. For normally distributed data, an independent T- test and analysis of variance (ANOVA) were used for mean comparisons. Linear regression analysis was conducted to predict the association between HbA1c and zinc. The statistical significance was defined as a p-value of less than 0.05. Ethical approval: Ethical consideration was obtained from NEHCO-IRC (Ref no: NEHCO-IRC/080/073) in October 2023. RESULTS A total of 200 individuals were included in this study; 100 were healthy controls, and 100 were in the T2DM group. The control group included 55 males and 45 females, whereas the T2DM group included 57 males and 43 females. Overall, both groups included a greater number of male participants than females did, with slightly higher counts in the T2DM group than in the control group. This pattern suggests a consistent male predominance in the study populations across both the control and diabetic groups, as shown in Figure 1. The comparison of variables between healthy controls and the T2DM cases revealed that the SBP, DBP, BMI, FBS, PPBS, Urea, Creatinine, and HbA1c level were significantly (p= <0.001) greater in T2DM cases as compared to healthy controls; conversely, serum Zinc levels were significantly lower in T2DM cases as compared to healthy controls as shown in Table 1. Table 1: Comparison of variables between healthy controls and T2DM cases. Variables Control (Mean ± SD) T2DM Cases (Mean ± SD) p-value BMI (kg/m 2 ) 24.08±2.97 25.83±3.62 <0.001 SBP (mmHg) 116.10±8.02 125.75±14.91 <0.001 DBP (mmHg) 77.58±7.25 81.90±7.74 <0.001 FBS (mg/dl) 86.92±8.45 137.41±61.37 <0.001 PPBS (mg/dl) 94.71±13.48 209.55±97.67 <0.001 Urea (mg/dl) 22.67±6.39 27.84±12.42 <0.001 Creatinine (mg/dl) 0.71±0.11 0.84±0.33 <0.001 HbA1c (%) 4.92±0.47 7.74±1.95 <0.001 Zn(µg/dl) 96.87±14.86 86.69±17.82 <0.001 Independent t tests, the correlation is significant at the 0.001 level. T2DM patients were further divided into good control (7.0%) groups on the basis of their HbA1c level. The biochemical parameters associated with good control and poor control were significantly increased in the poor control group, and the serum zinc level was significantly lower than that in the good control group, as shown in Table 2. Table 2: Comparison of biochemical parameters between good and poor glycemic control patients. Variables Good Control (Mean ± SD) Poor Control (Mean ± SD) p-value FBS (mg/dl) 105.78±24.31 164.35±70.18 <0.001 PPBS (mg/dl) 156.61±52.18 254.65±104.90 <0.001 Urea (mg/dl) 26.70±12.48 28.81±12.40 0.398 Creatinine (mg/dl) 0.808±0.325 0.866±0.336 0.385 Zn(µg/dl) 91.22±16.89 82.83±17.845 0.018 Independent t-test, significant at the 0.001 level, significant at the 0.05 level T2DM patients were further divided into three groups, i.e., 5 years, on the basis of the duration of diabetes. In this study, there was no significant association between the biochemical variables of these groups, as shown in Table 3. Table 3: Comparison of biochemical parameters across different durations of T2DM Variable Duration of diabetes N=100 P Value 5 Years(N=49) (Mean ±SD) FBS (mg/dl) 123.38±47.72 136.94 ±63.76 140 .51±63.76 0.633 PPBS (mg/dl) 202.00±118.74 245.69±115.81 202 .81±87.54 0.274 HbA1c (%) 7.77 ± 1.87 7.84 ±2.33 7.77 ±1.90 0.973 Urea (mg/dl) 28.00 ±16.48 29.69 ±14.43 27.38 ±11.03 0.801 Creatinine (mg/dl) 0.83±0.27 0.86 ±0.50 0.83 ±0.29 0.932 Zinc (µg/dl) 84.60±17.4 87.56±22.50 86.94±16.94 0.881 ANOVA Test, A further correlation between zinc and different variables, including HbA1c, FBS, PPBS, urea, and creatinine, was performed, where the zinc level was found to have a significant negative correlation with HbA1c, suggesting that the zinc levels significantly decreased with increasing HbA1c levels; however, no significant correlations were found between zinc and other variables, such as FBS, PPBS, urea, and creatinine, as shown in figure 2. Furthermore, the regression analysis shows the intercept was 103.64 (SE = 7.15, t = 14.49, p < 0.001), indicating that when HbA1c is zero, the predicted Zinc level is approximately 103.64 units. HbA1c showed a significant negative association with Zinc levels, with a coefficient of –2.19 (SE = 0.90, t = –2.44, p = 0.016). This suggests that each 1% increase in HbA1c is associated with an average decrease of about 2.19 units of Zinc. The 95% confidence interval for the HbA1c coefficient (–3.96 to –0.41) does not cross zero, further supporting the significance of this relationship. These results indicate that higher HbA1c levels are independently linked with lower serum Zinc concentrations, as shown in Table 4 . Table 4: Regression analysis of the contribution of HbA1c to the prediction of Zinc Variable Coefficient (β) Std. Error t-value p-value 95% CI Lower 95% CI Upper Intercept (const) 103.64 7.15 14.49 <0.001 89.44 117.83 HbA1c -2.19 0.90 -2.44 0.016 -3.96 -0.41 Linear regression; Dependent variable: HbA1c; Predictors: (Constant): zinc DISCUSSION Diabetes mellitus is a metabolic disorder that disrupts glucose, lipid, and protein metabolism, leading to hyperglycemia that significantly affects mineral balance 7 . Zinc is one of the essential minerals for glucose homeostasis as a cofactor. Zn supports glucose metabolism by promoting insulin synthesis, secretion from pancreatic β-cells, and storage. Zinc also contributes to cellular signaling pathways that enhance insulin sensitivity and glucose uptake 3,4 . Thus, adequate zinc levels are crucial for better glycemic control in diabetic patients. Our study shows that serum Zn is significantly decreased in the T2DM cases compared to the Control group, which is supported by various publications 8,9,10 . The observed zinc levels may be attributed to increased urine excretion, impaired absorption, altered zinc metabolism, and dietary restriction. Zinc levels did not show a statistically significant difference across the T2DM duration groups. This finding suggests that Zn deficiency may not be duration- dependent. A similar finding has been reported by Jayaweera et al 11 . However, Singh et al., who reported a consistent decline in mean serum zinc as diabetes duration increased, with the lowest levels in patients with >10 years of disease, 9 . These differences may be due to variations in population-specific dietary factors, glycemic control, and study population. Zinc levels were significantly lower in patients with poor glycemic control compared to those with good glycemic control. This finding suggests that zinc deficiency becomes more pronounced with worsening glycemic status in T2DM, which is supported by various publications 9,10 . Lower Zn levels in patients with poor glycemic control can aggravate insulin resistance and affect the pancreas's ability to produce insulin, creating a cycle of high blood sugar. Chronic hyperglycemia may impair intestinal Zn absorption and contribute to reduced serum zinc levels 12 . The Pearson correlation analysis shows a significantly negative association between zinc and HbA1c, which supports the various findings 13,14 . That finding suggests that lower zinc levels are more closely linked to long-term glycemic control rather than the acute glucose levels. It indicates that Zn may play a role in glucose metabolism and maintaining optimal insulin function. In contrast, serum Zn did not show a significant correlation with FBS, PPBS, suggesting that zinc status may be more closely linked to long-term glycemic markers rather than short-term fluctuations in blood glucose. The regression analysis demonstrated that HbA1c is a significant predictor of serum zinc levels. This finding is consistent with Al-Maroof RA 14. This indicates that for every 1% increase in HbA1c, serum zinc decreases by approximately 2.19 µg/dl, after accounting for other factors in the model. This negative association supports that poor glycemic control may contribute to zinc depletion. These findings highlight the importance of monitoring zinc in patients with poor glycemic control. CONCLUSION This study concludes that serum zinc levels are significantly lower in T2DM patients, especially those with poor glycemic control, and are negatively associated with HbA1c. Zinc deficiency appears independent of disease duration but may worsen with prolonged hyperglycemia, impacting insulin function. Monitoring and managing zinc status could be important for improving metabolic outcomes in T2DM Declarations Acknowledgement: We sincerely thank all participants who were involved in this study for their valuable cooperation. We are also grateful to the laboratory staff and our colleagues for their continuous support and assistance throughout the research. Special thanks to Manmohan Memorial Teaching Hospital for providing the necessary facilities and resources for successfully conducting this study. Author’s contribution: Anil Khadka and Anit Lamichhane conceived and designed the study, supervised the research process, and contributed to data interpretation and manuscript drafting. Rabina Maharjan, Susmita Humagain, Ganesh Kumar Oli, Laxmi Parsad Maharjan, and Kirja Shrestha performed data collection and data processing. Pabitra Bista and Sudip Khanal conducted data analysis. Govardhan Joshi, Rajesh Kumar Thakur, Mahendra Prasad Bhatt, and Sujan Gautam contributed to manuscript writing, review, and editing. Conflict of interest: None Data availability statement : The data are available from the corresponding author upon reasonable request Ethical consideration : Ethical issues (Plagiarism, data fabrication, & double publication) have been completely observed by the authors. Funding : None References Galicia-Garcia U, Benito-Vicente A, Jebari S, Larrea-Sebal A, Siddiqi H, Uribe KB et al (2020) Pathophysiology of Type 2 Diabetes Mellitus. Vol. 21, International Journal of Molecular Sciences. p. 6275 Foster M, Samman S (2012) Zinc and Regulation of Inflammatory Cytokines: Implications for Cardiometabolic Disease. Vol. 4, Nutrients. pp. 676–94 Zhao T, Huang Q, Su Y, Sun W, Huang Q, Wei W (2019) Zinc and its regulators in pancreas: T. Zhao et al. Inflammopharmacology 27(3):453–464 Poudel RR, Bhusal Y, Tharu B, Kafle NK (2017) Role of zinc in insulin regulation and diabetes. J Social Health Diabetes 5(02):83–87 da Silva Bandeira V, Pires LV, Hashimoto LL, de Alencar LL, Almondes KG, Lottenberg SA, Cozzolino SM (2017) Association of reduced zinc status with poor glycemic control in individuals with type 2 diabetes mellitus. J Trace Elem Med Biol 44:132–136 Klein E, Velina D, Mutallibzoda S, Tefikova S, Orlovtseva O, Kosenkov AN, Kulikov D, Nikitin I (2025) Zinc and Type 2 Diabetes: A Systematic Review with a Narrative Synthesis of Their Bidirectional Relationship and Clinical Perspectives for Personalized Nutritional Support. Diseases 13(12):396 Dubey P, Thakur V, Chattopadhyay M (2020) Role of minerals and trace elements in diabetes and insulin resistance. Nutrients 12(6):1864 Dasarathan R, Kumar S, Ganesh V, Chenthil KS (2017) Study of serum Zinc status among type 2 diabetes mellitus patients. Int J Adv Med 4(5):1344–1347 Singh M, Chandey M, Mohan G (2025) Study of serum zinc levels in type 2 diabetes mellitus and its complications. Eur J Cardiovasc Med 15:830–835 Rahmtalla SA, Modawe GA, Abdalla AM, Gurashi R, Hamad SF (2025) The Relationship between Serum Zinc and Glycemic Control among Type 2 Diabetic Patients in Khartoum State, Sudan. J Fac Med Baghdad 67(1):56–60 Jayaweera L, Shafras M, Navaratne A, Sanas M, Antonypillai C (2020) Serum zinc levels in diabetic patients with and without dyslipidaemia and cardiovascular diseases. Sri Lanka J Diabetes Endocrinol Metabolism. ;10(2) Bjørklund G, Dadar M, Pivina L, Doşa MD, Semenova Y, Aaseth J (2020) The role of zinc and copper in insulin resistance and diabetes mellitus. Curr Med Chem 27(39):6643–6657 Farooq M (2019) Zinc deficiency is associated with poor glycemic control. J Coll Physicians Surg Pak 29(3):253–257 Al-Maroof RA, Al-Sharbatti SS (2006) Serum zinc levels in diabetic patients and effect of zinc supplementation on glycemic control of type 2 diabetics. Saudi Med J 27(3):344–350 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9412794","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622835960,"identity":"09a50222-067e-4b80-b990-93d6e7b90fac","order_by":0,"name":"Anil 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08:42:04","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":true,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9412794/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9412794/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107259102,"identity":"a76f237e-264f-4957-8b89-713f4f845377","added_by":"auto","created_at":"2026-04-19 12:46:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29718,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBar diagram representing the males and females present in the study population\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9412794/v1/25addf4b78de7554698bb2ea.png"},{"id":107259103,"identity":"2abaf140-483b-46e3-991a-9b6d58627068","added_by":"auto","created_at":"2026-04-19 12:46:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":49737,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeatmap displaying the Spearman correlation matrix\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePearson correlation, *Significant at the 0.05 level\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9412794/v1/bf7e2d7e9ea75f384e05c622.png"},{"id":107484854,"identity":"cb388556-6175-490c-acfc-34b6c2536e15","added_by":"auto","created_at":"2026-04-22 02:33:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":675131,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9412794/v1/f46c0da3-b4d5-44d9-929f-c35a75f2f046.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAssociation of Zinc Deficiency with Poor Glycemic Control in Patients with Type 2 Diabetes Mellitus\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eType 2 diabetes mellitus(T2DM) is a chronic metabolic disorder characterized by insulin resistance and impaired insulin secretion, leading to hyperglycemia and associated metabolic complications. It is a major global health burden affecting millions of people worldwide. Among these micronutrient deficiencies, particularly Zinc (Zn) is prevalent among T2DM. Zn is an important micronutrient that helps many enzymes act as cofactors, protein folding, gene expression, neutralization of reactive oxygen species (ROS), cell signaling, cell division, apoptosis, and glucose homeostasis.\u003c/p\u003e \u003cp\u003eZinc (Zn) helps increase the expression of glucose transporter type 4 (GLUT-4), which improves glucose uptake into cells, and also plays an important role in the synthesis, storage, and release of insulin from pancreatic β-cells \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The zinc transporter ZnT8 helps maintain zinc balance in these cells, and its dysfunction can impair insulin production \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e.\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eZinc deficiency is commonly observed in patients with T2DM and is associated with β-cell dysfunction and poor glycemic control \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Emerging evidence suggests Zn dysregulation and T2DM have a bidirectional relationship, with each condition potentially worsening the other \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Therefore, this study aimed to investigate the association between serum Zn levels and glycemic control among T2DM cases\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy design and Participants:\u0026nbsp;\u003c/strong\u003eThis cross-sectional study was conducted in collaboration between Manmohan Memorial Medical College and Teaching Hospital (MMTH) and Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal, from December 2023 to May 2024. A total of 200 participants were included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and Exclusion Criteria:\u0026nbsp;\u003c/strong\u003eA total of 200 participants attending the Endocrinology OPD at MMTH were included in the study, comprising 100 patients with both newly diagnosed and long-term type 2 diabetes mellitus and 100 relatively healthy individuals. This study excluded individuals who had a history of chronic alcohol consumption, pregnant individuals, and those taking zinc or multivitamin supplements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent:\u0026nbsp;\u003c/strong\u003eWritten informed consent was obtained from all participants after thoroughly explaining the procedures to them in the Nepali language. Participants were guaranteed anonymity and confidentiality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Protocol:\u0026nbsp;\u003c/strong\u003eA pretest, self-administered questionnaire was used to collect the data. Five-milliliter fasting samples (8 to 12 hours of fasting) and postprandial (2 hours after a meal) blood samples were collected via venipuncture. The collected sample was separated into different sample collection tubes. A yellow vial (BD Vacutainer\u0026reg; SST\u0026trade; Tubes) was used for serum separation, an EDTA vial (BD Vacutainer\u0026reg; SST\u0026trade; Tubes) was used for glycated hemoglobin estimation, and a fluoride vial (BD Vacutainer\u0026reg; SST\u0026trade; Tubes) was used for glucose estimation. The biochemistry parameters, such as fasting blood sugar, postprandial, urea, and creatinine, were analyzed by using a fully automated chemistry analyzer (VITROS\u0026reg; 350 Chemistry System, USA). Zinc was estimated via a semiautomated analyzer (AGD 200), and glycated hemoglobin was analyzed via a fully automated analyzer (Lifotronic analyzer). In this study, the levels of FBS, PPBS, urea, and creatinine are expressed in mg/dL, and the levels of zinc and glycated hemoglobin are expressed in \u0026micro;g/dl and percentage (%), respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis:\u0026nbsp;\u003c/strong\u003eThe questionnaire collected all the data and recorded it in the Microsoft Excel 2019 database; all the data were analyzed via SPSS version 26. Independent T-tests, Spearman\u0026rsquo;s correlations, ANOVA, and linear regression were applied in SPSS. Normally, disturbed data, such as the mean and standard deviation, are taken. For normally distributed data, an independent T- test and analysis of variance (ANOVA) were used for mean comparisons. Linear regression analysis was conducted to predict the association between HbA1c and zinc. The statistical significance was defined as a p-value of less than 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u0026nbsp;\u003c/strong\u003eEthical consideration was obtained from NEHCO-IRC (Ref no: NEHCO-IRC/080/073) in October 2023.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 200 individuals were included in this study; 100 were healthy controls, and 100 were in the T2DM group. The control group included 55 males and 45 females, whereas the T2DM group included 57 males and 43 females. Overall, both groups included a greater number of male participants than females did, with slightly higher counts in the T2DM group than in the control group. This pattern suggests a consistent male predominance in the study populations across both the control and diabetic groups, as shown in Figure 1.\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\n\u003c/p\u003e\n\u003cp\u003eThe comparison of variables between healthy controls and the T2DM cases revealed that the SBP, DBP, BMI, FBS, PPBS, Urea, Creatinine, and HbA1c level were significantly (p= \u0026lt;0.001) greater in T2DM cases as compared to healthy controls; conversely, serum Zinc levels were significantly lower in T2DM cases as compared to healthy controls as shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Comparison of variables between healthy controls and T2DM cases.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable style=\"border-width: medium; border-style: none; border-color: currentcolor; border-image: initial; width: 100%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean ± SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eT2DM Cases\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean ± SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.08±2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.83±3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSBP (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e116.10±8.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e125.75±14.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDBP (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e77.58±7.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e81.90±7.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFBS (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86.92±8.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e137.41±61.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePPBS (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e94.71±13.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e209.55±97.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eUrea (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.67±6.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.84±12.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.71±0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.84±0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.92±0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.74±1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eZn(µg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e96.87±14.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86.69±17.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eIndependent t tests, the correlation is significant at the 0.001 level.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eT2DM patients were further divided into good control (\u0026lt;7.0%) and poor control (\u0026gt;7.0%) groups on the basis of their HbA1c level. The biochemical parameters associated with good control and poor control were significantly increased in the poor control group, and the serum zinc level was significantly lower than that in the good control group, as shown in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Comparison of biochemical parameters between good and poor glycemic control patients.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable style=\"border-width: medium; border-style: none; border-color: currentcolor; border-image: initial; width: 100%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGood Control\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean ± SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePoor Control\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean ± SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFBS (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e105.78±24.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e164.35±70.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePPBS (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e156.61±52.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e254.65±104.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eUrea (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.70±12.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.81±12.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.808±0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.866±0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eZn(µg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91.22±16.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82.83±17.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eIndependent t-test,\u0026nbsp;\u003c/em\u003e\u003cem\u003esignificant at the 0.001 level, significant at the 0.05 level\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eT2DM patients were further divided into three groups, i.e., \u0026lt;1 year, 1–5 years, and \u0026gt;5 years, on the basis of the duration of diabetes. In this study, there was no significant association between the biochemical variables of these groups, as shown in Table 3.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Comparison of biochemical parameters across different durations of T2DM\u003c/strong\u003e\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of diabetes \u003cem\u003eN=100\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;1 Year\u0026nbsp;\u003c/strong\u003e(N=19)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean ±SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e1-5 Years(N=32)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean ±SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;5 Years(N=49)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean ±SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFBS (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e123.38±47.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e136.94 ±63.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e140 .51±63.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePPBS (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e202.00±118.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e245.69±115.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e202 .81±87.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.77 ± 1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.84 ±2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.77 ±1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.973\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eUrea (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.00 ±16.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.69 ±14.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.38 ±11.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCreatinine (mg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83±0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.86 ±0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83 ±0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eZinc (µg/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e84.60±17.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e87.56±22.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86.94±16.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.881\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;ANOVA Test,\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA further correlation between zinc and different variables, including HbA1c, FBS, PPBS, urea, and creatinine, was performed, where the zinc level was found to have a significant negative correlation with HbA1c, suggesting that the zinc levels significantly decreased with increasing HbA1c levels; however, no significant correlations were found between zinc and other variables, such as FBS, PPBS, urea, and creatinine, as shown in figure 2.\u003c/p\u003e\n\u003cp\u003eFurthermore, the regression analysis shows the intercept was 103.64 (SE = 7.15, t = 14.49, p \u0026lt; 0.001), indicating that when HbA1c is zero, the predicted Zinc level is approximately 103.64 units. HbA1c showed a significant negative association with Zinc levels, with a coefficient of –2.19 (SE = 0.90, t = –2.44, p = 0.016). This suggests that each 1% increase in HbA1c is associated with an average decrease of about 2.19 units of Zinc. The 95% confidence interval for the HbA1c coefficient (–3.96 to –0.41) does not cross zero, further supporting the significance of this relationship. These results indicate that higher HbA1c levels are independently linked with lower serum Zinc concentrations, as shown in Table 4\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Regression analysis of the contribution of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eHbA1c to the prediction of Zinc\u003c/strong\u003e\u003c/p\u003e\n\u003ctable style=\"\" cellspacing=\"3\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient (β)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eStd. Error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003et-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI Lower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI Upper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIntercept (const)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e103.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e89.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e117.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHbA1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-3.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eLinear regression; Dependent variable: HbA1c; Predictors: (Constant): zinc\u003c/em\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eDiabetes mellitus is a metabolic disorder that disrupts glucose, lipid, and protein metabolism, leading to hyperglycemia that significantly affects mineral balance\u003csup\u003e7\u003c/sup\u003e. Zinc is one of the essential minerals for glucose homeostasis as a cofactor. Zn supports glucose metabolism by promoting insulin synthesis, secretion from pancreatic β-cells, and storage. Zinc also contributes to cellular signaling pathways that enhance insulin sensitivity and glucose uptake \u003csup\u003e3,4\u003c/sup\u003e. Thus, adequate zinc levels are crucial for better glycemic control in diabetic patients.\u003c/p\u003e\u003cp\u003eOur study shows that serum Zn is significantly decreased in the T2DM cases compared to the Control group, which is supported by various publications\u003csup\u003e8,9,10\u003c/sup\u003e. The observed zinc levels may be attributed to increased urine excretion, impaired absorption, altered zinc metabolism, and dietary restriction.\u003c/p\u003e\u003cp\u003eZinc levels did not show a statistically significant difference across the T2DM duration groups. This finding suggests that Zn deficiency may not be duration- dependent. A similar finding has been reported by Jayaweera et al \u003csup\u003e11\u003c/sup\u003e. However, Singh et al., who reported a consistent decline in mean serum zinc as diabetes duration increased, with the lowest levels in patients with \u0026gt;10 years of disease, \u003csup\u003e9\u003c/sup\u003e. These differences may be due to variations in\u0026nbsp;population-specific dietary factors, glycemic control, and study population.\u003c/p\u003e\u003cp\u003eZinc levels were significantly lower in patients with poor glycemic control compared to those with good glycemic control. This finding suggests that zinc deficiency becomes more pronounced with worsening glycemic status in T2DM, which is supported by various publications \u003csup\u003e9,10\u003c/sup\u003e. Lower Zn levels in patients with poor glycemic control can aggravate insulin resistance and affect the pancreas's ability to produce insulin, creating a cycle of high blood sugar. Chronic hyperglycemia may impair intestinal Zn absorption and contribute to reduced serum zinc levels\u003csup\u003e12\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\u003cp\u003eThe Pearson correlation analysis shows a significantly negative association between zinc and HbA1c, which supports the various findings \u003csup\u003e13,14\u003c/sup\u003e. That finding suggests that lower zinc levels are more closely linked to long-term glycemic control rather than the acute glucose levels. It indicates that Zn may play a role in glucose metabolism and maintaining optimal insulin function. In contrast, serum Zn did not show a significant correlation with FBS, PPBS, suggesting that zinc status may be more closely linked to long-term glycemic markers rather than short-term fluctuations in blood glucose.\u0026nbsp;\u003c/p\u003e\u003cp\u003eThe regression analysis demonstrated that HbA1c is a significant predictor of serum zinc levels. This finding is consistent with\u0026nbsp;Al-Maroof RA\u003csup\u003e\u0026nbsp; 14.\u003c/sup\u003e This indicates that for every 1% increase in HbA1c, serum zinc decreases by approximately 2.19 µg/dl, after accounting for other factors in the model. This negative association supports that poor glycemic control may contribute to zinc depletion. \u0026nbsp;These findings highlight the importance of monitoring zinc in patients with poor glycemic control.\u0026nbsp;\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study concludes that serum zinc levels are significantly lower in T2DM patients, especially those with poor glycemic control, and are negatively associated with HbA1c. Zinc deficiency appears independent of disease duration but may worsen with prolonged hyperglycemia, impacting insulin function. Monitoring and managing zinc status could be important for improving metabolic outcomes in T2DM\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003eWe sincerely thank all participants who were involved in this study for their valuable cooperation. We are also grateful to the laboratory staff and our colleagues for their continuous support and assistance throughout the research. Special thanks to Manmohan Memorial Teaching Hospital for providing the necessary facilities and resources for successfully conducting this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contribution:\u0026nbsp;\u003c/strong\u003eAnil Khadka and Anit Lamichhane conceived and designed the study, supervised the research process, and contributed to data interpretation and manuscript drafting. Rabina Maharjan, Susmita Humagain, Ganesh Kumar Oli, Laxmi Parsad Maharjan, and Kirja Shrestha performed data collection and data processing. Pabitra Bista and Sudip Khanal conducted data analysis. Govardhan Joshi, Rajesh Kumar Thakur, Mahendra Prasad Bhatt, and Sujan Gautam contributed to manuscript writing, review, and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e: The data are available from the corresponding author upon reasonable request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical consideration\u003c/strong\u003e: Ethical issues (Plagiarism, data fabrication, \u0026amp; double publication) have been completely observed by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: None\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGalicia-Garcia U, Benito-Vicente A, Jebari S, Larrea-Sebal A, Siddiqi H, Uribe KB et al (2020) Pathophysiology of Type 2 Diabetes Mellitus. Vol. 21, International Journal of Molecular Sciences. p. 6275\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoster M, Samman S (2012) Zinc and Regulation of Inflammatory Cytokines: Implications for Cardiometabolic Disease. Vol. 4, Nutrients. pp. 676\u0026ndash;94\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao T, Huang Q, Su Y, Sun W, Huang Q, Wei W (2019) Zinc and its regulators in pancreas: T. Zhao et al. Inflammopharmacology 27(3):453\u0026ndash;464\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoudel RR, Bhusal Y, Tharu B, Kafle NK (2017) Role of zinc in insulin regulation and diabetes. J Social Health Diabetes 5(02):83\u0026ndash;87\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eda Silva Bandeira V, Pires LV, Hashimoto LL, de Alencar LL, Almondes KG, Lottenberg SA, Cozzolino SM (2017) Association of reduced zinc status with poor glycemic control in individuals with type 2 diabetes mellitus. J Trace Elem Med Biol 44:132\u0026ndash;136\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlein E, Velina D, Mutallibzoda S, Tefikova S, Orlovtseva O, Kosenkov AN, Kulikov D, Nikitin I (2025) Zinc and Type 2 Diabetes: A Systematic Review with a Narrative Synthesis of Their Bidirectional Relationship and Clinical Perspectives for Personalized Nutritional Support. Diseases 13(12):396\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDubey P, Thakur V, Chattopadhyay M (2020) Role of minerals and trace elements in diabetes and insulin resistance. Nutrients 12(6):1864\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDasarathan R, Kumar S, Ganesh V, Chenthil KS (2017) Study of serum Zinc status among type 2 diabetes mellitus patients. Int J Adv Med 4(5):1344\u0026ndash;1347\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh M, Chandey M, Mohan G (2025) Study of serum zinc levels in type 2 diabetes mellitus and its complications. Eur J Cardiovasc Med 15:830\u0026ndash;835\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahmtalla SA, Modawe GA, Abdalla AM, Gurashi R, Hamad SF (2025) The Relationship between Serum Zinc and Glycemic Control among Type 2 Diabetic Patients in Khartoum State, Sudan. J Fac Med Baghdad 67(1):56\u0026ndash;60\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJayaweera L, Shafras M, Navaratne A, Sanas M, Antonypillai C (2020) Serum zinc levels in diabetic patients with and without dyslipidaemia and cardiovascular diseases. Sri Lanka J Diabetes Endocrinol Metabolism. ;10(2)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBj\u0026oslash;rklund G, Dadar M, Pivina L, Doşa MD, Semenova Y, Aaseth J (2020) The role of zinc and copper in insulin resistance and diabetes mellitus. Curr Med Chem 27(39):6643\u0026ndash;6657\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarooq M (2019) Zinc deficiency is associated with poor glycemic control. J Coll Physicians Surg Pak 29(3):253\u0026ndash;257\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Maroof RA, Al-Sharbatti SS (2006) Serum zinc levels in diabetic patients and effect of zinc supplementation on glycemic control of type 2 diabetics. Saudi Med J 27(3):344\u0026ndash;350\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Department of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"T2DM, Zinc, Glycemic control","lastPublishedDoi":"10.21203/rs.3.rs-9412794/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9412794/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntroduction\u003c/p\u003e\n\u003cp\u003eType 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance and impaired insulin secretion. Zinc (Zn), an essential micronutrient, plays a crucial role in insulin synthesis, secretion, and glucose homeostasis. Zinc deficiency is frequently observed in T2DM and may influence glycemic control. This study aimed to assess the relationship between zinc levels and glycemic control in individuals with type 2 diabetes.\u003c/p\u003e\n\u003cp\u003eMethods: This case-control cross-sectional study was conducted among 200 subjects, including 100 type 2 diabetic cases and 100 controls attending the medicine OPD of Manmohan Memorial Medical College and Teaching Hospital, Kathmandu, Nepal. The standard protocol was used to estimate all biochemical parameters, including fasting blood sugar (FBS), postprandial blood sugar (PPBS), HbA1c, urea, creatinine, and zinc. Ethical approval was obtained from NEHCO-IRC.\u003c/p\u003e\n\u003cp\u003eResults: Serum zinc levels were significantly lower in T2DM patients compared to healthy controls (86.69±17.82 vs. 96.87±14.86 µg/dl, p \u0026lt; 0.001). Patients with poor glycemic control (HbA1c \u0026gt; 7%) had significantly lower zinc levels than those with good control (82.83 ± 17.84 vs. 91.22±16.89 µg/dl, p = 0.018). A significant negative correlation was observed between zinc and HbA1c (r = −0.240, p = 0.016). Regression analysis revealed that each 1% increase in HbA1c was associated with a 2.19 µg/dl decrease in serum zinc. No significant association was found between zinc levels and duration of diabetes.\u003c/p\u003e\n\u003cp\u003eConclusion: Serum zinc levels are significantly reduced in T2DM patients and are inversely associated with HbA1c. Zinc deficiency may contribute to poor glycemic control, highlighting the importance of monitoring zinc status in T2DM management.\u003c/p\u003e","manuscriptTitle":"Association of Zinc Deficiency with Poor Glycemic Control in Patients with Type 2 Diabetes Mellitus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:46:07","doi":"10.21203/rs.3.rs-9412794/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e721abc2-a371-42f5-99c2-c8dd4f9fd35f","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66278083,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2026-04-19T12:46:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:46:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9412794","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9412794","identity":"rs-9412794","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}