Cross-Sectional Association of Blood Selenium with Glycemic Biomarkers among U.S. Adults with Normoglycemia in the National Health and Nutrition Examination Survey 2013-2016

Jingli Yang; En Chen; Cheukling Choi; Kayue Chan; Qinghua Yang; Juwel Rana; Bo Yang; Chuiguo Huang; Aimin Yang; Kenneth Lo

doi:10.3390/nu14193972

Cross-Sectional Association of Blood Selenium with Glycemic Biomarkers among U.S. Adults with Normoglycemia in the National Health and Nutrition Examination Survey 2013-2016

Nutrients. 2022 Sep 24;14(19):3972. doi: 10.3390/nu14193972.

Authors

Jingli Yang^{1

2}, En Chen³, Cheukling Choi⁴, Kayue Chan⁴, Qinghua Yang⁵, Juwel Rana^{6

7}, Bo Yang⁸, Chuiguo Huang⁹, Aimin Yang⁹, Kenneth Lo^{4

10}

Affiliations

¹ College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China.
² School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD 4059, Australia.
³ Department of Clinical Laboratory Medicine, Institution of Microbiology and Infectious Diseases, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, China.
⁴ Department of Applied Biology and Chemical Technology, the Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon, Hong Kong SAR, China.
⁵ Department of Nephrology, Peking University International Hospital, Beijing 102206, China.
⁶ Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC H3A 1G1, Canada.
⁷ Department of Public Health, School of Health and Life Sciences, North South University, Dhaka 1229, Bangladesh.
⁸ Department of Epidemiology, Center for Global Cardiometabolic Health, School of Public Health, Brown University, Providence, RI 02912, USA.
⁹ Department of Medicine and Therapeutics, Prince of Wales Hospital, the Chinese University of Hong Kong, Hong Kong SAR, China.
¹⁰ Research Institute for Smart Ageing, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon, Hong Kong SAR, China.

Abstract

Selenium (Se) remains to have an inconsistent relationship with glycemic biomarkers and the risk of developing type 2 diabetes (T2D). Few studies have investigated the relationship between blood Se and glycemic biomarkers among people with normoglycemia. We conducted a cross-sectional analysis using the U.S. National Health and Nutrition Examination Survey 2013-2016. Multivariable linear regression models were developed to examine the associations of blood Se with glycemic biomarkers, namely, fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), insulin, and the oral glucose tolerance test (OGTT). Blood Se was treated as continuous (per log-10 increment) and categorical exposure (in quartiles) in separate regression models. We assessed the dose-response relationships by restricted cubic spline analysis. After excluding the participants with T2D or incomplete data, 2706 participants were analyzed. The highest quartile of blood Se was associated with increased FPG [adjusted β = 0.12, 95% Confidence Intervals (CI) = 0.04, 0.20], OGTT (adjusted β = 0.29, 95% CI = 0.02, 0.56), HbA1c (adjusted β = 0.04, 95% CI = 0.00, 0.07), and insulin (adjusted β = 2.50, 95% CI = 1.05, 3.95) compared with the lowest quartile. Positive associations were also observed between every log-10 increment of blood Se level and glycemic biomarkers, except for OGTT. A positive linear dose-response relationship existed between blood Se and FPG (P_overall = 0.003, P_nonlinear = 0.073) and insulin (P_overall = 0.004, P_nonlinear =0.060). BMI, age, and smoking status modified the associations of the highest quartile of Se (compared with the lowest quartile) with glycemic biomarkers. Overall, positive associations of blood Se with glycemic biomarkers were observed among U.S. adults with normoglycemia. These findings implied that people with normoglycemia need to be aware of the level of Se and other mineral intakes from diet and supplements. Further research is required to identify the mechanisms of excess Se in the progression of diabetes.

Keywords: blood selenium; cross-sectional; diabetes mellitus; glycemic biomarkers.

MeSH terms

Adult
Biomarkers
Blood Glucose / analysis
Cross-Sectional Studies
Diabetes Mellitus, Type 2* / epidemiology
Glycated Hemoglobin / analysis
Humans
Insulin
Nutrition Surveys
Selenium*

Substances

Biomarkers
Blood Glucose
Glycated Hemoglobin A
Insulin
Selenium

Grants and funding

This research was funded by natural science foundation of Hunan province (Grant number: No. 2021JJ70038). We confirm the independence of researchers from funders. The contents of this manuscript are the responsibility of the authors and do not reflect the views of the funding bodies.