Relationship between zinc and glucose metabolism in Japanese adults

Relationship between zinc and glucose metabolism in Japanese adults | 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 Relationship between zinc and glucose metabolism in Japanese adults Machi Suka, Hiroko Tsuruta, Toshiko Takao, Hiroyuki Yanagisawa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7311121/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 Background: The association between decreased zinc and poor glycemic control has been revealed in diabetic patients. However, the involvement of zinc in glucose metabolism in healthy, non-diabetic individuals remains unclear. Methods: Company T employees and their spouses who underwent the milestone-age health checkups at the Tokyo Health Service Association were recruited in the study (n=533). The following variables were obtained from blood and urine samples and questionnaires: three zinc measures (serum zinc, urinary zinc, and zinc intake); two obesity-related measures (visceral fat and adiponectin); three insulin-related measures (insulin, HOMA-β, and HOMA-IR); and two glucose-related measures (fasting plasma glucose and HbA1c). Results: Correlation analysis between zinc measures revealed a significant correlation between serum zinc and urinary zinc, but not between the other pairs. Correlation analysis between zinc measures and obesity-, insulin-, and glucose-related measures revealed weak but significant correlations between serum zinc and adiponectin and HbA1c, as well as between urinary zinc and fasting plasma glucose and HbA1c. A path analysis using structural equation modeling confirmed that serum zinc was directly linked to urinary zinc and adiponectin, which affected blood glucose levels (HbA1c) directly and indirectly by influencing insulin secretion function (HOMA-β). Conclusion: This is the first study to statistically demonstrate the pathway linking zinc to blood glucose levels in healthy, non-diabetic adults using objective measurement data. Lower serum zinc levels were associated with lower adiponectin levels and lower insulin secretory function, resulting in higher blood glucose levels. zinc glucose metabolism structure equation modeling Japan Figures Figure 1 Figure 2 Figure 3 Introduction The National Health and Nutritional Survey data revealed that over 30% of Japanese adults had inadequate zinc intake, which is a significant health concern.[1] Zinc deficiency is not only prevalent in Japan, but also worldwide.[2] Zinc is an essential trace mineral necessary for sustaining life. More than 300 enzymes and 1000 transcription factors depend on zinc for their activities.[3] Zinc deficiency may present with clinical features such as hypogeusia, hair loss, and delayed wound healing. However, many individuals may have latent zinc deficiency without experiencing symptoms, which could elevate their risk of developing various diseases. Numerous investigators have reported higher urinary zinc excretion and lower serum zinc concentrations in diabetic patients, suggesting a link between zinc and diabetes.[4] A meta-analysis[5] revealed that zinc concentrations in whole blood are lower in diabetic patients than in healthy individuals. Additionally, the duration of diabetes appears to be associated with zinc concentrations in whole blood. However, these phenomena cannot be explained by lower dietary zinc intake in diabetic patients. Another meta-analysis[6] revealed that zinc supplementation has hypoglycemic and glycemic-modulating effects by decreasing fasting blood glucose, hemoglobin A1c (HbA1c), and homeostatic model assessment for insulin resistance (HOMA-IR). The beneficial effects of zinc supplementation on glycemic control have also been confirmed in diabetic patients.[7] There is no doubt that zinc is involved in glycemic control mechanisms, at least in diabetic patients. Zinc plays a role in the synthesis, storage, secretion, and action of insulin (i.e. a hormone that lowers blood glucose levels), as well as translocation of insulin into cells.[8,9] On the other hand, zinc regulates zinc‑α2‑glycoprotein, which increases adiponectin (i.e. a hormone that promotes insulin sensitization) directly and indirectly by increasing peroxisome proliferator-activated receptor gamma (PPARγ).[10] Moreover, adiponectin receptors (AdipoR1 and AdipoR2) contain a zinc ion which stabilizes their structure.[11] It is reasonable to assume that zinc deficiency affects glucose metabolism through impaired insulin function and enhanced insulin resistance. However, there is insufficient epidemiological evidence to conclude that zinc deficiency increases the incidence of diabetes in healthy, non-diabetic adults. The Nurses' Health Study[12] and the Australian Longitudinal Study on Women's Health[13] showed that women in the highest quintile of dietary zinc intake had a significantly lower risk of developing type 2 diabetes compared to those in the lowest quintile. However, it is uncertain whether self-reported estimates of zinc intake accurately reflect zinc sufficiency in the body, and further research based on objective zinc indicators is needed to conclude the relationship between zinc and glucose metabolism. This study was designed based on the hypothesis that zinc modulates blood glucose levels through adiponectin and insulin in healthy, non-diabetic adults. Serum zinc, urinary zinc, and zinc intake levels were measured simultaneously in Japanese men and women aged 35–64 years. Their correlations were analyzed with major factors involved in glucose metabolism, including obesity-, insulin-, and glucose-related measures. Furthermore, a path analysis using structural equation modeling was conducted to illustrate the relationship between the variables and statistically verify our hypothesis. Methods Participants Company T employees and their spouses undergo thorough health checkups at milestone ages (36, 40, 44, 48, 52, 56, 60, 62, and 64 years old). This study recruited participants who applied for the milestone-age health checkups at the Tokyo Health Service Association between April 2023 and March 2025. Participants received information about the study protocol along with the health checkup instructions. Only those who voluntarily agreed to participate in the study signed an informed consent form. The study protocol was approved by the ethics committee of the Tokyo Health Service Association (R6-4). A total of 630 people participated in the study over the two-year study period. Participants undergoing treatment for diabetes mellitus (n = 10) or chronic kidney disease (n = 4), as well as those with incomplete or missing data (n = 84), were excluded. Finally, 533 people were included in the analysis. Measures The milestone-age health checkup consisted of self-administered questionnaires, anthropometric measurements, imaging tests, and laboratory tests. Participants completed a standard health questionnaire asking about their medical history, subjective symptoms, and lifestyle habits, as well as a food frequency questionnaire. The daily intake of each nutrient for each participant was calculated based on the frequency of food consumption using a commercially available software (KENPAKUSHA Co., Ltd., Tokyo, JAPAN). Weight (in kilograms to the nearest 0.1 kg) and height (in centimeters to the nearest 0.1 cm) were measured with a participant lightly clothed and standing without shoes. Body mass index (BMI) was calculated by dividing weight (in kilograms) by height (in meters) squared. Visceral fat (in square centimeters) was measured on a computed tomography (CT) axial slice at the umbilical level.[14] Blood (collected on an empty stomach) and urine (collected as midstream urine) samples were immediately processed at the Tokyo Health Service Association laboratory, where both internal and external quality controls of laboratory data are routinely performed in accordance with established guidelines. For this study, insulin, adiponectin, serum zinc, and urinary zinc concentrations were measured in addition to the prescribed health checkup items. These measurements were outsourced to an external testing agency (Medecal Assist Inc., Saitama, JAPAN) on the day the samples were collected. This study assessed three zinc measures, as well as two obesity-related, three insulin-related, and two glucose-related measures, to examine the relationship between zinc and glucose metabolism. The zinc measures were serum zinc (µg/dL), urinary zinc (µg/gCr), and zinc intake (mg/kcal). The obesity-related measures were visceral fat (cm 2 ) and adiponectin (µg/mL). The insulin-related measures were insulin (µU/mL), homeostatic model assessment of beta cell function (HOMA-β), and HOMA-IR. HOMA-β was calculated using the formula 360×fasting insulin/(fasting glucose (mg/dL)–63). HOMA-IR calculated using the formula fasting glucose (mg/dL)×fasting insulin/405.[15] The glucose-related measures were fasting plasma glucose (FPG)(mg/dL) and HbA1c (%). Statistical Analysis All statistical analyses except the path analysis were performed using the SAS ver. 9.4 (SAS Institute, Cary, NC, USA). The path analysis was performed using IBM SPSS Amos V.22.0 (IBM Corp, Armonk, New York, USA). Significant levels were set at p < 0.05. Correlation analyses were conducted between zinc measures, as well as between zinc measures and obesity-, insulin-, and glucose-related measures. Spearman's correlation coefficients were calculated and scatter plots were illustrated for each pair of measures. A path analysis using structural equation modeling was conducted to test the hypothesis that zinc modulates blood glucose levels through adiponectin and insulin. Because FPG and insulin levels fluctuate reactively, the long-term indicators HbA1c and HOMA-β were incorporated into the model instead. The strength of relationship between variables was estimated as a standardized regression coefficient or a correlation coefficient. The initial model was improved by trimming paths with non-significant contributions. The final model consisted of paths with a path coefficient of > 0.05 or < − 0.05 (p 0.9 indicates a good fit, and for RMSEA, a value of < 0.08 is considered to be acceptable.[16] Results Table 1 shows the characteristics of the study participants. Among men, the younger age group (35–44 years old) accounted for the majority (56.4%), while among women, this age group was relatively small (16.4%). The percentage of obese people (BMI ≥ 25) was slightly lower than the national statistics for Japan (31.5% of men and 21.1% of women aged 20 or older).[17] Hypozincemia (serum zinc < 80 µg/dL) was found in 112 people (21.0%), with no significant differences by gender (19.3% of men and 23.7% of women, p = 0.230), age (20.2% of the 35–44 group, 21.9% of the 45–54 group, and 21.3% of the 55–64 group, p = 0.921) or BMI (25.0% of the < 18.5 group, 21.2% of the 18.5–24.9 group, and 19.5% of the 25 + group, p = 0.789). Table 1 Characteristics of the study participants Men Women N 326 207 Age, years 35-44 184 56.4% 34 16.4% 45-54 57 17.5% 94 45.4% 55-64 85 26.1% 79 38.2% BMI <18.5 5 1.5% 27 13.0% 18.5-24.9 231 70.9% 152 73.4% 25.0+ 90 27.6% 28 13.5% Abbreviations: BMI body mass index. Table 2 shows the correlations between zinc measures and obesity-, insulin-, and glucose-related measures. Comparisons of the means of the three zinc measures showed no significant differences by gender or BMI. On the other hand, the mean serum zinc was significantly lower in the older age groups (90.4 µg/dL for the 35–44 group, 89.3 µg/dL for the 45–54 group, and 86.8 µg/dL for the 55–64 group, p = 0.019), and the mean urinary zinc was significantly higher (0.33 µg/gCr for the 35–44 group, 0.36 µg/gCr for the 45–54 group, and 0.39 µg/gCr for the 55–64 group, p = 0.001). Correlation analysis between zinc measures (Fig. 1) revealed a significant correlation between serum zinc and urinary zinc, but not between the other pairs. Correlation analysis between zinc measures and obesity-, insulin-, and glucose-related measures (Fig. 2) revealed weak but significant correlations between serum zinc and adiponectin and HbA1c, as well as between urinary zinc and FPG and HbA1c. Table 2 Correlations between zinc measures and obesity- and insulin-related measures Correlation Mean (SD) Serum zinc Urinary zinc Zinc intake Serum zinc, µg/dL 89.0 (12.4) γs ― 0.43 0.07 p ― < 0.001 0.144 Urinary zinc, µg/gCr 0.36 (0.17) γs 0.43 ― 0.02 p < 0.001 ― 0.677 Zinc intake, mg/kcal 4.07 (0.50) γs 0.07 0.02 ― p 0.144 0.677 ― Visceral fat, cm 2 60.0 (41.3) γs 0.07 0.04 -0.07 p 0.085 0.329 0.142 Adiponectin, µg/mL 10.1 (5.0) γs -0.15 -0.01 0.03 p < 0.001 0.814 0.535 Insulin, µU/mL 7.5 (4.5) γs 0.06 0.03 0.03 p 0.166 0.538 0.527 HOMA-β 84.0 (44.6) γs 0.04 -0.04 0.05 p 0.304 0.389 0.301 HOMA-IR 1.81 (1.22) γs 0.06 0.03 0.02 p 0.140 0.308 0.733 FPG, mg/dL 95.7 (9.7) γs 0.03 0.11 -0.07 p 0.530 0.011 0.106 HbA1c, % 5.66 (0.33) γs 0.13 0.18 -0.04 p 0.003 < 0.001 0.434 Abbreviations: HOMA-β homeostatic model assessment of beta cell function, HOMA-IR homeostatic model assessment for insulin resistance, FPG fasting plasma glucose Values show Spearman’s rank correlation coefficients (γs) with serum zinc, urinary zinc, and zinc intake. Figure 3 shows the path diagram illustrating the direct and indirect effects of zinc on HbA1c. After trimming paths with non-significant contributions, the final model resulted in a better fit to the data (GFI 0.995; CFI 1.000; RMSEA 0.000 (90% CI 0.000-0.066)). Serum zinc was directly linked to urinary zinc and adiponectin, which affected HbA1c directly and indirectly by influencing HOMA-β. In other words, lower serum zinc levels were associated with lower adiponectin levels and lower insulin secretory function, resulting in higher blood glucose levels. Discussion Although numerous investigators have suggested a link between zinc and diabetes, there is little epidemiological evidence based on objective zinc indicators that can determine the relationship between zinc and glucose metabolism. This study measured and compared serum zinc, urinary zinc, and zinc intake in relation to major factors involved in glucose metabolism in Japanese adults. Furthermore, a path analysis using structural equation modeling was conducted to statistically verify the hypothesis that zinc modulates blood glucose levels through adiponectin and insulin. This study is the first to confirm, using objective measurement data, that zinc has a significant effect on glucose metabolism in healthy, non-diabetic adults. Zinc intake is commonly used in epidemiological studies to assess zinc sufficiency in the body.[ 8 , 12 , 13 ] However, no correlation was found with biological indicators of serum zinc or urinary zinc. Additionally, serum zinc and urinary zinc showed a significant correlation with HbA1c, but zinc intake did not. These results suggest that serum zinc or urinary zinc is a more suitable indicator when examining the relationship between zinc and glucose metabolism. In that case, the results of previous studies based on zinc intake may need to be interpreted with caution. Serum zinc is used as a diagnostic criterion for clinical zinc deficiency.[ ] Even among the healthy middle-aged adults of this study, approximately 20% had hypozincemia, or serum zinc levels below 80 µg/dL. The lack of a significant correlation between serum zinc and zinc intake indicated that hypozincemia was unlikely to be caused by low zinc intake alone. Some investigators have suggested that hyperglycemia hinders renal zinc reabsorption, thereby affecting zinc homeostasis and contributing to the pathogenesis of diabetes.[ , ] Actually, serum zinc as well as HbA1c exhibited a significant correlation with urinary zinc in this study. The Study of Women's Health Across the Nation[ ] and the Strong Heart Study[ ] showed that higher urinary zinc levels were significantly associated with an increased risk of developing diabetes. Unfortunately, these studies did not reveal an association between serum zinc and diabetes incidence because they lacked serum zinc measurements. This study was the first to tackle the unresolved issues of previous studies by creating a path diagram illustrating the relationship between serum zinc, urinary zinc, and HbA1c, based on objective measurement data. The result of the path analysis successfully verified the hypothesis that zinc modulates blood glucose levels through adiponectin and insulin. Lower serum zinc levels were associated with lower adiponectin levels and lower insulin secretory function, resulting in higher blood glucose levels. Zinc is necessary for normal insulin secretion and is known to regulate the insulin signaling pathway through several molecular mechanisms.[ 8 , 9 , 10 ] On the other hand, zinc is known to regulate PPARγ activity. This promotes an increase in adiponectin levels in the plasma, leading to improved insulin sensitivity in the liver and skeletal muscle and reduced glucose production in the liver.[ 10 ] Randomized clinical trials revealed that zinc supplementation raised adiponectin levels in diabetic patients.[ , ] Although the path diagram was derived from statistical analysis of measurement data, it was consistent with the existing evidence obtained from animal and human studies. The significant relationship between zinc and glucose metabolism in healthy, non-diabetic adults suggests that zinc homeostasis dysfunction may accompany elevated blood glucose levels, even within the normal to pre-diabetic range. To rigorously prove this suggestion, a cohort study must be conducted to monitor longitudinal changes in blood glucose levels. This is the first study to statistically demonstrate the pathway linking zinc to blood glucose levels in healthy, non-diabetic adults using objective measurement data. On the contrary, it has the following potential limitations. First, the study participants were limited to Company T employees and their spouses who underwent the milestone-age health checkups at the Tokyo Health Service Association. They appear to be healthier than the general public.[ 17 ] Caution should be exercised when applying the results of this study to Japan as a whole. Second, information on treatment was collected in the questionnaire, but the type of medication used was not asked. Some medications, including diuretics and angiotensin converting enzyme inhibitors, are known to increase the amount of zinc excreted in urine. The results of this study may have been influenced in some way by the use of medication. Third, the data were collected on a cross-sectional basis. The path diagram did not represent the causal relationship between the variables. Additional research is necessary to determine the impact of zinc on the occurrence of diabetes. Conclusion The association between decreased zinc and poor glycemic control has been revealed in diabetic patients. However, the involvement of zinc in glucose metabolism in healthy, non-diabetic individuals remains unclear. This study measured serum zinc, urinary zinc, and zinc intake levels in Japanese men and women aged 35–64 years, and analyzed their correlations with obesity-, insulin-, and glucose-related measures. A path analysis using structural equation modeling confirmed that serum zinc was directly linked to urinary zinc and adiponectin, which affected blood glucose levels (HbA1c) directly and indirectly by influencing insulin secretion function (HOMA-β). Declarations Funding This study was supported by research grants from the Japan Society of Health Evaluation and Promotion (2022), The Jikei University Graduate School of Medicine (2023), and the Japan Society for Menopause and Women's Health (2023). Competing interests The authors have no relevant financial or non-financial interests to disclose. Authors contributions MS was responsible for the design and conduct of the study, the collection, analysis, and interpretation of data, and the writing of the article. HT contributed to the collection of data. TT and HY contributed to the interpretation of data. All authors read and approved the final manuscript. Ethics approval The study protocol was approved by the ethics committee of the Tokyo Health Service Association (R6-4) and has been conducted in accordance with the Ethical Guidelines for Medical and Biological Research Involving Human Subjects by the Japanese Government and the Helsinki declaration. Consent to participate All participants received information about the study protocol, and those who signed the informed consent term were included in the study. Data availability The dataset of this study will not be shared because the Ethical Guidelines prohibit researchers from providing their research data to other third-party individuals. References Kogirima M, Ohta N, Kubo A, Komatsu M, Watanabe E. Nutritional Assessment of Zinc using the data of National Health and Nutrition Survey in Japan from 1946 to 2015. Trace Nutrients Research 2017;34:102-8. Skalny AV, Aschner M, Tinkov AA. Zinc. Adv Food Nutr Res 2021;96:251-310. Prasad AS. Discovery of human zinc deficiency: its impact on human health and disease. Adv Nutr 2013;4:176-90. de Carvalho GB, Brandão-Lima PN, Maia CS, Barbosa KB, Pires LV. Zinc's role in the glycemic control of patients with type 2 diabetes: a systematic review. Biometals 2017;30:151-62. Fernández-Cao JC, Warthon-Medina M, Hall Moran V, Arija V, Doepking C, Lowe NM. 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J Am Coll Nutr 1998;17:109-15. Bandeira VDS, Pires LV, Hashimoto LL, Alencar LL, Almondes KGS, Lottenberg SA, Cozzolino SMF. Association of reduced zinc status with poor glycemic control in individuals with type 2 diabetes mellitus. J Trace Elem Med Biol 2017;44:132-6. Wang X, Karvonen-Gutierrez CA, Herman WH, Mukherjee B, Harlow SD, Park SK. Urinary metals and incident diabetes in midlife women: Study of Women’s Health Across the Nation (SWAN). BMJ Open Diabetes Res Care 2020;8:e00123. Galvez-Fernandez M, Powers M, Grau-Perez M, Domingo-Relloso A, Lolacono N, Goessler W, Zhang Y, Fretts A, Umans JG, Maruthur N, Navas-Acien A. Urinary zinc and incident type 2 diabetes: prospective evidence from the Strong Heart Study. Diabetes Care 2022;45:2561-9. Soheylikhah S, Dehestani MR, Mohammadi SM, Afkhami-Ardekani M, Eghbali SA, Dehghan F. The effect of zinc supplementation on serum adiponectin concentration and insulin resistance in first degree relatives of diabetic patients. Iran J Diabetes Obes 2012;4:57-62. Alipoor E, Sehat M, Mohajeri‑Tehrani MR. Effects of zinc supplementation on serum adiponectin concentration and glycemic control in patients with type 2 diabetes. J Trace Elem Med Biol 2019;55:20‑5. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7311121","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":502153468,"identity":"601b7f30-9e46-422d-a976-e2f58e6e07c6","order_by":0,"name":"Machi Suka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYFACNgaGDzwSBgzMMB4xWhhnkKyFmYeBwYB4Z8nPSEv8bCNjYczPzsD44QcDXx5BLQY30g5L5/BImEk2MzBL9jCwFRPWIpHeANJiY3CYgUEa6MzEBsIOS2/+bQHUYn+Ygfk3UVoYbqQdk2YAOsyAmYGNOFsMzjxLs+zhkTCWOMzYZtljQIRf5NvTjG/87Kkz7O8/fPjGj4pjhEMMDBh7wCTQSQbHEojTwvADzqohVssoGAWjYBSMIAAA4HQvxAoUAZUAAAAASUVORK5CYII=","orcid":"","institution":"The Jikei University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Machi","middleName":"","lastName":"Suka","suffix":""},{"id":502153469,"identity":"84f9cdd7-862b-4159-86c5-8e75387c38ac","order_by":1,"name":"Hiroko Tsuruta","email":"","orcid":"","institution":"Tokyo Health Service Association","correspondingAuthor":false,"prefix":"","firstName":"Hiroko","middleName":"","lastName":"Tsuruta","suffix":""},{"id":502153471,"identity":"cefd14c2-d83a-4324-8358-8a7fbd4a2544","order_by":2,"name":"Toshiko Takao","email":"","orcid":"","institution":"East Japan Railway Company","correspondingAuthor":false,"prefix":"","firstName":"Toshiko","middleName":"","lastName":"Takao","suffix":""},{"id":502153473,"identity":"5783c9ed-20db-4309-8761-f3f93104822e","order_by":3,"name":"Hiroyuki Yanagisawa","email":"","orcid":"","institution":"The Jikei University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hiroyuki","middleName":"","lastName":"Yanagisawa","suffix":""}],"badges":[],"createdAt":"2025-08-06 15:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7311121/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7311121/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89560367,"identity":"67909a2b-c5b1-45ec-ae27-6c30c3ee247c","added_by":"auto","created_at":"2025-08-21 10:19:04","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55559,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between zinc measures\u003c/p\u003e\n\u003cp\u003eBlue dots are men. Red dots are women. The black line is linear regression between the two variables.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7311121/v1/6931294697dbd2e9d86fa68e.jpg"},{"id":89562908,"identity":"3532f775-d920-4f8b-9a6e-76435e86ed5b","added_by":"auto","created_at":"2025-08-21 10:27:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":571877,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between serum zinc and obesity- (A), insulin- (B), and glucose- (C) related measures\u003c/p\u003e\n\u003cp\u003eBlue dots are men. Red dots are women. The black line is linear regression between the two variables.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7311121/v1/a0daae9b26161bee5a9a1164.png"},{"id":89560368,"identity":"2a4b0a10-4a9f-44cc-94d5-1ad0b4fea672","added_by":"auto","created_at":"2025-08-21 10:19:04","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":74534,"visible":true,"origin":"","legend":"\u003cp\u003ePath diagram illustrating the direct and indirect effects of zinc on HbA1c\u003c/p\u003e\n\u003cp\u003eRectangles are observed variables. Ellipses are latent variables. Values on the single-headed arrows are standardized regression weights. Values on the double-headed arrows are correlation coefficients. Model fitness: goodness of fit index (GFI) 0.995; comparative fit index (CFI) 1.000; root mean square error of approximation (RMSEA) 0.000 (90% CI 0.000-0.066).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7311121/v1/41696263d1f884b2e18da198.jpg"},{"id":92456154,"identity":"46152c93-8d7b-4898-96d2-b1e2608cb9db","added_by":"auto","created_at":"2025-09-30 02:16:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":994398,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7311121/v1/801588e4-ce58-4dc9-8d37-9f9b4fdd9d15.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Relationship between zinc and glucose metabolism in Japanese adults","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe National Health and Nutritional Survey data revealed that over 30% of Japanese adults had inadequate zinc intake, which is a significant health concern.[1] Zinc deficiency is not only prevalent in Japan, but also worldwide.[2] Zinc is an essential trace mineral necessary for sustaining life. More than 300 enzymes and 1000 transcription factors depend on zinc for their activities.[3] Zinc deficiency may present with clinical features such as hypogeusia, hair loss, and delayed wound healing. However, many individuals may have latent zinc deficiency without experiencing symptoms, which could elevate their risk of developing various diseases.\u003c/p\u003e\u003cp\u003eNumerous investigators have reported higher urinary zinc excretion and lower serum zinc concentrations in diabetic patients, suggesting a link between zinc and diabetes.[4] A meta-analysis[5] revealed that zinc concentrations in whole blood are lower in diabetic patients than in healthy individuals. Additionally, the duration of diabetes appears to be associated with zinc concentrations in whole blood. However, these phenomena cannot be explained by lower dietary zinc intake in diabetic patients. Another meta-analysis[6] revealed that zinc supplementation has hypoglycemic and glycemic-modulating effects by decreasing fasting blood glucose, hemoglobin A1c (HbA1c), and homeostatic model assessment for insulin resistance (HOMA-IR). The beneficial effects of zinc supplementation on glycemic control have also been confirmed in diabetic patients.[7] There is no doubt that zinc is involved in glycemic control mechanisms, at least in diabetic patients.\u003c/p\u003e\u003cp\u003eZinc plays a role in the synthesis, storage, secretion, and action of insulin (i.e. a hormone that lowers blood glucose levels), as well as translocation of insulin into cells.[8,9] On the other hand, zinc regulates zinc‑α2‑glycoprotein, which increases adiponectin (i.e. a hormone that promotes insulin sensitization) directly and indirectly by increasing peroxisome proliferator-activated receptor gamma (PPARγ).[10] Moreover, adiponectin receptors (AdipoR1 and AdipoR2) contain a zinc ion which stabilizes their structure.[11] It is reasonable to assume that zinc deficiency affects glucose metabolism through impaired insulin function and enhanced insulin resistance. However, there is insufficient epidemiological evidence to conclude that zinc deficiency increases the incidence of diabetes in healthy, non-diabetic adults. The Nurses' Health Study[12] and the Australian Longitudinal Study on Women's Health[13] showed that women in the highest quintile of dietary zinc intake had a significantly lower risk of developing type 2 diabetes compared to those in the lowest quintile. However, it is uncertain whether self-reported estimates of zinc intake accurately reflect zinc sufficiency in the body, and further research based on objective zinc indicators is needed to conclude the relationship between zinc and glucose metabolism.\u003c/p\u003e\u003cp\u003eThis study was designed based on the hypothesis that zinc modulates blood glucose levels through adiponectin and insulin in healthy, non-diabetic adults. Serum zinc, urinary zinc, and zinc intake levels were measured simultaneously in Japanese men and women aged 35\u0026ndash;64 years. Their correlations were analyzed with major factors involved in glucose metabolism, including obesity-, insulin-, and glucose-related measures. Furthermore, a path analysis using structural equation modeling was conducted to illustrate the relationship between the variables and statistically verify our hypothesis.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eCompany T employees and their spouses undergo thorough health checkups at milestone ages (36, 40, 44, 48, 52, 56, 60, 62, and 64 years old). This study recruited participants who applied for the milestone-age health checkups at the Tokyo Health Service Association between April 2023 and March 2025. Participants received information about the study protocol along with the health checkup instructions. Only those who voluntarily agreed to participate in the study signed an informed consent form. The study protocol was approved by the ethics committee of the Tokyo Health Service Association (R6-4).\u003c/p\u003e\u003cp\u003eA total of 630 people participated in the study over the two-year study period. Participants undergoing treatment for diabetes mellitus (n\u0026thinsp;=\u0026thinsp;10) or chronic kidney disease (n\u0026thinsp;=\u0026thinsp;4), as well as those with incomplete or missing data (n\u0026thinsp;=\u0026thinsp;84), were excluded. Finally, 533 people were included in the analysis.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMeasures\u003c/h2\u003e\u003cp\u003eThe milestone-age health checkup consisted of self-administered questionnaires, anthropometric measurements, imaging tests, and laboratory tests. Participants completed a standard health questionnaire asking about their medical history, subjective symptoms, and lifestyle habits, as well as a food frequency questionnaire. The daily intake of each nutrient for each participant was calculated based on the frequency of food consumption using a commercially available software (KENPAKUSHA Co., Ltd., Tokyo, JAPAN). Weight (in kilograms to the nearest 0.1 kg) and height (in centimeters to the nearest 0.1 cm) were measured with a participant lightly clothed and standing without shoes. Body mass index (BMI) was calculated by dividing weight (in kilograms) by height (in meters) squared. Visceral fat (in square centimeters) was measured on a computed tomography (CT) axial slice at the umbilical level.[14] Blood (collected on an empty stomach) and urine (collected as midstream urine) samples were immediately processed at the Tokyo Health Service Association laboratory, where both internal and external quality controls of laboratory data are routinely performed in accordance with established guidelines. For this study, insulin, adiponectin, serum zinc, and urinary zinc concentrations were measured in addition to the prescribed health checkup items. These measurements were outsourced to an external testing agency (Medecal Assist Inc., Saitama, JAPAN) on the day the samples were collected.\u003c/p\u003e\u003cp\u003eThis study assessed three zinc measures, as well as two obesity-related, three insulin-related, and two glucose-related measures, to examine the relationship between zinc and glucose metabolism. The zinc measures were serum zinc (\u0026micro;g/dL), urinary zinc (\u0026micro;g/gCr), and zinc intake (mg/kcal). The obesity-related measures were visceral fat (cm\u003csup\u003e2\u003c/sup\u003e) and adiponectin (\u0026micro;g/mL). The insulin-related measures were insulin (\u0026micro;U/mL), homeostatic model assessment of beta cell function (HOMA-β), and HOMA-IR. HOMA-β was calculated using the formula 360\u0026times;fasting insulin/(fasting glucose (mg/dL)\u0026ndash;63). HOMA-IR calculated using the formula fasting glucose (mg/dL)\u0026times;fasting insulin/405.[15] The glucose-related measures were fasting plasma glucose (FPG)(mg/dL) and HbA1c (%).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses except the path analysis were performed using the SAS ver. 9.4 (SAS Institute, Cary, NC, USA). The path analysis was performed using IBM SPSS Amos V.22.0 (IBM Corp, Armonk, New York, USA). Significant levels were set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eCorrelation analyses were conducted between zinc measures, as well as between zinc measures and obesity-, insulin-, and glucose-related measures. Spearman's correlation coefficients were calculated and scatter plots were illustrated for each pair of measures. A path analysis using structural equation modeling was conducted to test the hypothesis that zinc modulates blood glucose levels through adiponectin and insulin. Because FPG and insulin levels fluctuate reactively, the long-term indicators HbA1c and HOMA-β were incorporated into the model instead. The strength of relationship between variables was estimated as a standardized regression coefficient or a correlation coefficient. The initial model was improved by trimming paths with non-significant contributions. The final model consisted of paths with a path coefficient of \u0026gt;\u0026thinsp;0.05 or \u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;0.05 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Model fitness was assessed by goodness of fit index (GFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA). For GFI and CFI, a value of \u0026gt;\u0026thinsp;0.9 indicates a good fit, and for RMSEA, a value of \u0026lt;\u0026thinsp;0.08 is considered to be acceptable.[16]\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable 1 shows the characteristics of the study participants. Among men, the younger age group (35\u0026ndash;44 years old) accounted for the majority (56.4%), while among women, this age group was relatively small (16.4%). The percentage of obese people (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25) was slightly lower than the national statistics for Japan (31.5% of men and 21.1% of women aged 20 or older).[17] Hypozincemia (serum zinc\u0026thinsp;\u0026lt;\u0026thinsp;80 \u0026micro;g/dL) was found in 112 people (21.0%), with no significant differences by gender (19.3% of men and 23.7% of women, p\u0026thinsp;=\u0026thinsp;0.230), age (20.2% of the 35\u0026ndash;44 group, 21.9% of the 45\u0026ndash;54 group, and 21.3% of the 55\u0026ndash;64 group, p\u0026thinsp;=\u0026thinsp;0.921) or BMI (25.0% of the \u0026lt;\u0026thinsp;18.5 group, 21.2% of the 18.5\u0026ndash;24.9 group, and 19.5% of the 25\u0026thinsp;+\u0026thinsp;group, p\u0026thinsp;=\u0026thinsp;0.789).\u003c/p\u003e\n\u003cp\u003eTable 1 Characteristics of the study participants\u003c/p\u003e\n\u003ctable border=\"1\" width=\"451\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e35-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e56.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e16.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e45-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e17.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e45.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e55-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e26.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e13.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e18.5-24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e70.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e73.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e25.0+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e27.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e13.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations:\u0026nbsp;BMI body mass index.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the correlations between zinc measures and obesity-, insulin-, and glucose-related measures. Comparisons of the means of the three zinc measures showed no significant differences by gender or BMI. On the other hand, the mean serum zinc was significantly lower in the older age groups (90.4 \u0026micro;g/dL for the 35\u0026ndash;44 group, 89.3 \u0026micro;g/dL for the 45\u0026ndash;54 group, and 86.8 \u0026micro;g/dL for the 55\u0026ndash;64 group, p\u0026thinsp;=\u0026thinsp;0.019), and the mean urinary zinc was significantly higher (0.33 \u0026micro;g/gCr for the 35\u0026ndash;44 group, 0.36 \u0026micro;g/gCr for the 45\u0026ndash;54 group, and 0.39 \u0026micro;g/gCr for the 55\u0026ndash;64 group, p\u0026thinsp;=\u0026thinsp;0.001). Correlation analysis between zinc measures (Fig.\u0026nbsp;1) revealed a significant correlation between serum zinc and urinary zinc, but not between the other pairs. Correlation analysis between zinc measures and obesity-, insulin-, and glucose-related measures (Fig.\u0026nbsp;2) revealed weak but significant correlations between serum zinc and adiponectin and HbA1c, as well as between urinary zinc and FPG and HbA1c.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelations between zinc measures and obesity- and insulin-related measures\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCorrelation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum zinc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrinary zinc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZinc intake\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum zinc, \u0026micro;g/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e―\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e―\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrinary zinc, \u0026micro;g/gCr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e―\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e―\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZinc intake, mg/kcal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e―\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e―\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVisceral fat, cm\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdiponectin, \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.535\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsulin, \u0026micro;U/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHOMA-\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(44.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHOMA-IR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFPG, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHbA1c, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gamma;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eAbbreviations: HOMA-\u0026beta; homeostatic model assessment of beta cell function, HOMA-IR homeostatic model assessment for insulin resistance, FPG fasting plasma glucose\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eValues show Spearman\u0026rsquo;s rank correlation coefficients (\u0026gamma;s) with serum zinc, urinary zinc, and zinc intake.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFigure\u0026nbsp;3 shows the path diagram illustrating the direct and indirect effects of zinc on HbA1c. After trimming paths with non-significant contributions, the final model resulted in a better fit to the data (GFI 0.995; CFI 1.000; RMSEA 0.000 (90% CI 0.000-0.066)). Serum zinc was directly linked to urinary zinc and adiponectin, which affected HbA1c directly and indirectly by influencing HOMA-\u0026beta;. In other words, lower serum zinc levels were associated with lower adiponectin levels and lower insulin secretory function, resulting in higher blood glucose levels.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough numerous investigators have suggested a link between zinc and diabetes, there is little epidemiological evidence based on objective zinc indicators that can determine the relationship between zinc and glucose metabolism. This study measured and compared serum zinc, urinary zinc, and zinc intake in relation to major factors involved in glucose metabolism in Japanese adults. Furthermore, a path analysis using structural equation modeling was conducted to statistically verify the hypothesis that zinc modulates blood glucose levels through adiponectin and insulin. This study is the first to confirm, using objective measurement data, that zinc has a significant effect on glucose metabolism in healthy, non-diabetic adults.\u003c/p\u003e\u003cp\u003eZinc intake is commonly used in epidemiological studies to assess zinc sufficiency in the body.[\u003csup\u003e8\u003c/sup\u003e ,\u003csup\u003e12\u003c/sup\u003e,\u003csup\u003e13\u003c/sup\u003e] However, no correlation was found with biological indicators of serum zinc or urinary zinc. Additionally, serum zinc and urinary zinc showed a significant correlation with HbA1c, but zinc intake did not. These results suggest that serum zinc or urinary zinc is a more suitable indicator when examining the relationship between zinc and glucose metabolism. In that case, the results of previous studies based on zinc intake may need to be interpreted with caution.\u003c/p\u003e\u003cp\u003eSerum zinc is used as a diagnostic criterion for clinical zinc deficiency.[\u003ca class=\"FNLink\" href=\"#Fn18\" id=\"#FNLinkFn18\"\u003e\u003c/a\u003e] Even among the healthy middle-aged adults of this study, approximately 20% had hypozincemia, or serum zinc levels below 80 \u0026micro;g/dL. The lack of a significant correlation between serum zinc and zinc intake indicated that hypozincemia was unlikely to be caused by low zinc intake alone. Some investigators have suggested that hyperglycemia hinders renal zinc reabsorption, thereby affecting zinc homeostasis and contributing to the pathogenesis of diabetes.[\u003ca class=\"FNLink\" href=\"#Fn19\" id=\"#FNLinkFn19\"\u003e\u003c/a\u003e,\u003ca class=\"FNLink\" href=\"#Fn20\" id=\"#FNLinkFn20\"\u003e\u003c/a\u003e] Actually, serum zinc as well as HbA1c exhibited a significant correlation with urinary zinc in this study. The Study of Women's Health Across the Nation[\u003ca class=\"FNLink\" href=\"#Fn21\" id=\"#FNLinkFn21\"\u003e\u003c/a\u003e] and the Strong Heart Study[\u003ca class=\"FNLink\" href=\"#Fn22\" id=\"#FNLinkFn22\"\u003e\u003c/a\u003e] showed that higher urinary zinc levels were significantly associated with an increased risk of developing diabetes. Unfortunately, these studies did not reveal an association between serum zinc and diabetes incidence because they lacked serum zinc measurements.\u003c/p\u003e\u003cp\u003eThis study was the first to tackle the unresolved issues of previous studies by creating a path diagram illustrating the relationship between serum zinc, urinary zinc, and HbA1c, based on objective measurement data. The result of the path analysis successfully verified the hypothesis that zinc modulates blood glucose levels through adiponectin and insulin. Lower serum zinc levels were associated with lower adiponectin levels and lower insulin secretory function, resulting in higher blood glucose levels. Zinc is necessary for normal insulin secretion and is known to regulate the insulin signaling pathway through several molecular mechanisms.[\u003csup\u003e8\u003c/sup\u003e,\u003csup\u003e9\u003c/sup\u003e,\u003csup\u003e10\u003c/sup\u003e] On the other hand, zinc is known to regulate PPARγ activity. This promotes an increase in adiponectin levels in the plasma, leading to improved insulin sensitivity in the liver and skeletal muscle and reduced glucose production in the liver.[\u003csup\u003e10\u003c/sup\u003e] Randomized clinical trials revealed that zinc supplementation raised adiponectin levels in diabetic patients.[\u003ca class=\"FNLink\" href=\"#Fn23\" id=\"#FNLinkFn23\"\u003e\u003c/a\u003e,\u003ca class=\"FNLink\" href=\"#Fn24\" id=\"#FNLinkFn24\"\u003e\u003c/a\u003e] Although the path diagram was derived from statistical analysis of measurement data, it was consistent with the existing evidence obtained from animal and human studies. The significant relationship between zinc and glucose metabolism in healthy, non-diabetic adults suggests that zinc homeostasis dysfunction may accompany elevated blood glucose levels, even within the normal to pre-diabetic range. To rigorously prove this suggestion, a cohort study must be conducted to monitor longitudinal changes in blood glucose levels.\u003c/p\u003e\u003cp\u003eThis is the first study to statistically demonstrate the pathway linking zinc to blood glucose levels in healthy, non-diabetic adults using objective measurement data. On the contrary, it has the following potential limitations. First, the study participants were limited to Company T employees and their spouses who underwent the milestone-age health checkups at the Tokyo Health Service Association. They appear to be healthier than the general public.[\u003csup\u003e17\u003c/sup\u003e] Caution should be exercised when applying the results of this study to Japan as a whole. Second, information on treatment was collected in the questionnaire, but the type of medication used was not asked. Some medications, including diuretics and angiotensin converting enzyme inhibitors, are known to increase the amount of zinc excreted in urine. The results of this study may have been influenced in some way by the use of medication. Third, the data were collected on a cross-sectional basis. The path diagram did not represent the causal relationship between the variables. Additional research is necessary to determine the impact of zinc on the occurrence of diabetes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe association between decreased zinc and poor glycemic control has been revealed in diabetic patients. However, the involvement of zinc in glucose metabolism in healthy, non-diabetic individuals remains unclear. This study measured serum zinc, urinary zinc, and zinc intake levels in Japanese men and women aged 35\u0026ndash;64 years, and analyzed their correlations with obesity-, insulin-, and glucose-related measures. A path analysis using structural equation modeling confirmed that serum zinc was directly linked to urinary zinc and adiponectin, which affected blood glucose levels (HbA1c) directly and indirectly by influencing insulin secretion function (HOMA-β).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eFunding\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by research grants from the Japan Society of Health Evaluation and Promotion (2022), The Jikei University Graduate School of Medicine (2023), and the Japan Society for Menopause and Women's Health (2023).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthors contributions\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eMS was responsible for the design and conduct of the study, the collection, analysis, and interpretation of data, and the writing of the article. HT contributed to the collection of data. TT and HY contributed to the interpretation of data. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eEthics approval\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the ethics committee of the Tokyo Health Service Association (R6-4) and has been conducted in accordance with the Ethical Guidelines for Medical and Biological Research Involving Human Subjects by the Japanese Government and the Helsinki declaration.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsent to participate\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAll participants received information about the study protocol, and those who signed the informed consent term were included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eData availability\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset of this study will not be shared because the Ethical Guidelines prohibit researchers from providing their research data to other third-party individuals.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKogirima M, Ohta N, Kubo A, Komatsu M, Watanabe E. Nutritional Assessment of Zinc using the data of National Health and Nutrition Survey in Japan from 1946 to 2015. Trace Nutrients Research 2017;34:102-8.\u003c/li\u003e\n\u003cli\u003eSkalny AV, Aschner M, Tinkov AA. Zinc. Adv Food Nutr Res 2021;96:251-310.\u003c/li\u003e\n\u003cli\u003ePrasad AS. Discovery of human zinc deficiency: its impact on human health and disease. Adv Nutr 2013;4:176-90.\u003c/li\u003e\n\u003cli\u003ede Carvalho GB, Brand\u0026atilde;o-Lima PN, Maia CS, Barbosa KB, Pires LV. Zinc's role in the glycemic control of patients with type 2 diabetes: a systematic review. Biometals 2017;30:151-62.\u003c/li\u003e\n\u003cli\u003eFern\u0026aacute;ndez-Cao JC, Warthon-Medina M, Hall Moran V, Arija V, Doepking C, Lowe NM. Dietary zinc intake and whole blood zinc concentration in subjects with type 2 diabetes versus healthy subjects: a systematic review, meta-analysis and meta-regression. J Trace Elem Med Biol 2018;49:241-51.\u003c/li\u003e\n\u003cli\u003eNazari M, Ashtary-Larky D, Nikbaf-Shandiz M, Goudarzi K, Bagheri R, Dolatshahi S, Omran HS, Amirani N, Ghanavati M, Asbaghi O. Zinc supplementation and cardiovascular disease risk factors: A GRADE-assessed systematic review and dose-response meta-analysis. J Trace Elem Med Biol 2023;79:127244.\u003c/li\u003e\n\u003cli\u003eNazari M, Nikbaf-Shandiz M, Pashayee-Khamene F, Bagheri R, Goudarzi K, Hosseinnia NV, Dolatshahi S, Omran HS, Amirani N, Ashtary-Larky D, Asbaghi O, Ghanavati M. Zinc supplementation in individuals with prediabetes and type 2 diabetes: a GRADE-Assessed systematic review and dose-response meta-analysis. Biol Trace Elem Res 2024;202:2966-90.\u003c/li\u003e\n\u003cli\u003eTamura Y. The role of zinc homeostasis in the prevention of diabetes mellitus and cardiovascular diseases. J Atheroscler Thromb 2021;28:1109-22.\u003c/li\u003e\n\u003cli\u003eAhmad R, Shaju R, Atfi A, Razzaque MS. Zinc and Diabetes: A Connection between Micronutrient and Metabolism. Cells 2024;13:1359.\u003c/li\u003e\n\u003cli\u003eYudhani RD, Pakha DN, Wiyono N and Wasita B: Molecular mechanisms of zinc in alleviating obesity: recent updates (review). World Acad Sci J 2024;6:70.\u003c/li\u003e\n\u003cli\u003eTanabe H, Fujii Y, Okada-Iwabu M, Iwabu M, Nakamura Y, Hosaka T, Motoyama K, Ikeda M, Wakiyama M, Terada T, Ohsawa N, Hato M, Ogasawara S, Hino T, Murata T, Iwata S, Hirata K, Kawano Y, Yamamoto M, Kimura-Someya T, Shirouzu M, Yamauchi T, Kadowaki T, Yokoyama S. Crystal structures of the human adiponectin receptors. Nature 2015;520:312-6.\u003c/li\u003e\n\u003cli\u003eSun Q, van Dam RM, Willett WC, Hu FB. Prospective study of zinc intake and risk of type 2 diabetes in women. Diabetes Care 2009;32:629-34.\u003c/li\u003e\n\u003cli\u003eVashum KP, McEvoy M, Shi Z, Milton AH, Islam MR, Sibbritt D, Patterson A, Byles J, Loxton D, Attia J. Is dietary zinc protective for type 2 diabetes? Results from the Australian longitudinal study on women's health. BMC Endocr Disord 2013;13:40.\u003c/li\u003e\n\u003cli\u003eNemoto M, Yeernuer T, Masutani Y, Nomura Y, Hanaoka S, Miki S, Yoshikawa T, Hayashi N, Ohtomo K. Development of automatic visceral fat volume calculation software for CT volume data. J Obes 2014;2014:495084.\u003c/li\u003e\n\u003cli\u003eMatthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta‐cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eMcDonald RP, Ho MH. Principles and practice in reporting structural equation analyses. Psychol Methods 2002;7:64-82.\u003c/li\u003e\n\u003cli\u003eMinistry of Health, Labour, and Welfare. National Health and Nutrition Survey 2023 (in Japanese). https://www.mhlw.go.jp/bunya/kenkou/kenkou_eiyou_chousa.html (Access July 21, 2025)\u003c/li\u003e\n\u003cli\u003eJapanese Society of Clinical Nutrition.\u0026nbsp;The treatment guideline of zinc deficiency 2024 (in Japanese)\u003cem\u003e.\u003c/em\u003e\u0026nbsp;https://www.jscn.gr.jp/pdf/aen2024.pdf (Access July 21, 2025)\u003c/li\u003e\n\u003cli\u003eChausmer AB. Zinc, insulin and diabetes. J Am Coll Nutr 1998;17:109-15.\u003c/li\u003e\n\u003cli\u003eBandeira VDS, Pires LV, Hashimoto LL, Alencar LL, Almondes KGS, Lottenberg SA, Cozzolino SMF. Association of reduced zinc status with poor glycemic control in individuals with type 2 diabetes mellitus. J Trace Elem Med Biol 2017;44:132-6.\u003c/li\u003e\n\u003cli\u003eWang X,\u0026nbsp;Karvonen-Gutierrez CA,\u0026nbsp;Herman WH,\u0026nbsp;Mukherjee B,\u0026nbsp;Harlow SD,\u0026nbsp;Park SK.\u0026nbsp;Urinary metals and incident diabetes in midlife women: Study of Women\u0026rsquo;s Health Across the Nation (SWAN). BMJ Open Diabetes Res Care 2020;8:e00123.\u003c/li\u003e\n\u003cli\u003eGalvez-Fernandez M, Powers M, Grau-Perez M, Domingo-Relloso A, Lolacono N, Goessler W, Zhang Y, Fretts A, Umans JG, Maruthur N, Navas-Acien A. Urinary zinc and incident type 2 diabetes: prospective evidence from the Strong Heart Study. Diabetes Care 2022;45:2561-9.\u003c/li\u003e\n\u003cli\u003eSoheylikhah S, Dehestani MR, Mohammadi SM, Afkhami-Ardekani M, Eghbali SA, Dehghan F. The effect of zinc supplementation on serum adiponectin concentration and insulin resistance in first degree relatives of diabetic patients. Iran J Diabetes Obes 2012;4:57-62.\u003c/li\u003e\n\u003cli\u003eAlipoor E, Sehat M, Mohajeri‑Tehrani MR. Effects of zinc supplementation on serum adiponectin concentration and glycemic control in patients with type 2 diabetes. J Trace Elem Med Biol 2019;55:20‑5.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"zinc, glucose metabolism, structure equation modeling, Japan","lastPublishedDoi":"10.21203/rs.3.rs-7311121/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7311121/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: The association between decreased zinc and poor glycemic control has been revealed in diabetic patients. However, the involvement of zinc in glucose metabolism in healthy, non-diabetic individuals remains unclear.\u003c/p\u003e\n\u003cp\u003eMethods: Company T employees and their spouses who underwent the milestone-age health checkups at the Tokyo Health Service Association were recruited in the study (n=533). The following variables were obtained from blood and urine samples and questionnaires: three zinc measures (serum zinc, urinary zinc, and zinc intake); two obesity-related measures (visceral fat and adiponectin); three insulin-related measures (insulin, HOMA-β, and HOMA-IR); and two glucose-related measures (fasting plasma glucose and HbA1c).\u003c/p\u003e\n\u003cp\u003eResults: Correlation analysis between zinc measures revealed a significant correlation between serum zinc and urinary zinc, but not between the other pairs. Correlation analysis between zinc measures and obesity-, insulin-, and glucose-related measures revealed weak but significant correlations between serum zinc and adiponectin and HbA1c, as well as between urinary zinc and fasting plasma glucose and HbA1c. A path analysis using structural equation modeling confirmed that serum zinc was directly linked to urinary zinc and adiponectin, which affected blood glucose levels (HbA1c) directly and indirectly by influencing insulin secretion function (HOMA-β).\u003c/p\u003e\n\u003cp\u003eConclusion: This is the first study to statistically demonstrate the pathway linking zinc to blood glucose levels in healthy, non-diabetic adults using objective measurement data. Lower serum zinc levels were associated with lower adiponectin levels and lower insulin secretory function, resulting in higher blood glucose levels.\u003c/p\u003e","manuscriptTitle":"Relationship between zinc and glucose metabolism in Japanese adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-21 10:18:59","doi":"10.21203/rs.3.rs-7311121/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":"a30abb3c-1ee3-4ee1-8bca-eb27fb9f6700","owner":[],"postedDate":"August 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-30T02:08:50+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-21 10:18:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7311121","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7311121","identity":"rs-7311121","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}