The association between the essential metal mixture and fasting plasma glucose in Chinese community-dwelling elderly people.


Journal

Ecotoxicology and environmental safety
ISSN: 1090-2414
Titre abrégé: Ecotoxicol Environ Saf
Pays: Netherlands
ID NLM: 7805381

Informations de publication

Date de publication:
15 Sep 2023
Historique:
received: 01 05 2023
revised: 17 07 2023
accepted: 19 07 2023
medline: 20 9 2023
pubmed: 28 7 2023
entrez: 27 7 2023
Statut: ppublish

Résumé

Epidemiological studies about the effect of essential metal mixture on fasting plasma glucose (FPG) levels among elderly people are sparse. The object of this study was to examine the associations of single essential metals and essential metal mixture with FPG levels in Chinese community-dwelling elderly people. The study recruited 2348 community-dwelling elderly people in total. Inductively coupled plasma-mass spectrometry was adopted to detect the levels of vanadium (V), selenium (Se), magnesium (Mg), cobalt (Co), calcium (Ca), and molybdenum (Mo) in urine. The relationships between single essential metals and essential metal mixture and FPG levels were evaluated by linear regression and Bayesian kernel machine regression (BKMR) models, respectively. In multiple-metal linear regression models, urine V and Mg were negatively related to the FPG levels (β = - 0.016, 95 % CI: - 0.030 to - 0.003 for V; β = - 0.021, 95 % CI: - 0.033 to - 0.009 for Mg), and urine Se was positively related to the FPG levels (β = 0.024, 95 % CI: 0.014-0.034). In BKMR model, the significant relationships of Se and Mg with the FPG levels were also found. The essential metal mixture was negatively associated with FPG levels in a dose-response pattern, and Mg had the maximum posterior inclusion probability (PIP) value (PIP = 1.0000), followed by Se (PIP = 0.9968). Besides, Co showed a significant association with decreased FPG levels in older adults without hyperlipemia and in women. Both Mg and Se were associated with FPG levels, individually and as a mixture. The essential metal mixture displayed a linear dose-response relationship with reduced FPG levels, with Mg having the largest contribution to FPG levels, followed by Se. Further prospective investigations are necessary to validate these exploratory findings.

Sections du résumé

BACKGROUND BACKGROUND
Epidemiological studies about the effect of essential metal mixture on fasting plasma glucose (FPG) levels among elderly people are sparse. The object of this study was to examine the associations of single essential metals and essential metal mixture with FPG levels in Chinese community-dwelling elderly people.
METHODS METHODS
The study recruited 2348 community-dwelling elderly people in total. Inductively coupled plasma-mass spectrometry was adopted to detect the levels of vanadium (V), selenium (Se), magnesium (Mg), cobalt (Co), calcium (Ca), and molybdenum (Mo) in urine. The relationships between single essential metals and essential metal mixture and FPG levels were evaluated by linear regression and Bayesian kernel machine regression (BKMR) models, respectively.
RESULTS RESULTS
In multiple-metal linear regression models, urine V and Mg were negatively related to the FPG levels (β = - 0.016, 95 % CI: - 0.030 to - 0.003 for V; β = - 0.021, 95 % CI: - 0.033 to - 0.009 for Mg), and urine Se was positively related to the FPG levels (β = 0.024, 95 % CI: 0.014-0.034). In BKMR model, the significant relationships of Se and Mg with the FPG levels were also found. The essential metal mixture was negatively associated with FPG levels in a dose-response pattern, and Mg had the maximum posterior inclusion probability (PIP) value (PIP = 1.0000), followed by Se (PIP = 0.9968). Besides, Co showed a significant association with decreased FPG levels in older adults without hyperlipemia and in women.
CONCLUSIONS CONCLUSIONS
Both Mg and Se were associated with FPG levels, individually and as a mixture. The essential metal mixture displayed a linear dose-response relationship with reduced FPG levels, with Mg having the largest contribution to FPG levels, followed by Se. Further prospective investigations are necessary to validate these exploratory findings.

Identifiants

pubmed: 37499391
pii: S0147-6513(23)00793-5
doi: 10.1016/j.ecoenv.2023.115289
pii:
doi:

Substances chimiques

Blood Glucose 0
Cobalt 3G0H8C9362
Selenium H6241UJ22B
Vanadium 00J9J9XKDE
Calcium SY7Q814VUP
Magnesium I38ZP9992A
Molybdenum 81AH48963U
Metals 0
Complex Mixtures 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

115289

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

Auteurs

Pan-Pan Wang (PP)

School of Public Health, Department of Health Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China.

Jing-Yuan Lei (JY)

School of Public Health, Department of Health Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China.

Yuan Wang (Y)

School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China.

Hong-Li Wang (HL)

School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China.

Liang Sun (L)

Fuyang Center for Diseases Prevention and Control, Fuyang 236069, Anhui, China.

Bing Hu (B)

Fuyang Center for Diseases Prevention and Control, Fuyang 236069, Anhui, China.

Su-Fang Wang (SF)

School of Public Health, Department of Nutrition and Food Hygiene, Anhui Medical University, Hefei 230032, Anhui, China.

Dong-Mei Zhang (DM)

School of Health Services Management, Anhui Medical University, Hefei 230032, Anhui, China.

Gui-Mei Chen (GM)

School of Health Services Management, Anhui Medical University, Hefei 230032, Anhui, China.

Chun-Mei Liang (CM)

School of Public Health, Department of Health Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China.

Fang-Biao Tao (FB)

MOE Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), No. 81 Meishan Road, Hefei 230032, Anhui, China.

Lin-Sheng Yang (LS)

School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China. Electronic address: yanglinsheng@ahmu.edu.cn.

Qing-Si Wu (QS)

Department of Blood Transfusion, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, Anhui, China. Electronic address: wuqingsi@ahmu.edu.cn.

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Classifications MeSH