» Articles » PMID: 34501978

Occupational Noise Exposure and Incidence of High Fasting Blood Glucose: A 3-Year, Multicenter, Retrospective Study

Overview
Publisher MDPI
Date 2021 Sep 10
PMID 34501978
Citations 2
Authors
Affiliations
Soon will be listed here.
Abstract

The role of hazardous occupational noise exposure on the development of prediabetes is not well researched. We aimed to elucidate exposure to hazardous occupational noise as an independent risk factor for high fasting blood glucose (FBG). Participants exposed/non-exposed to occupational noise were recruited from the Common Data Model cohorts of 2013/2014 from two centers and were followed-up for 3 years. Multivariate time-dependent Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) and were adjusted for various covariates. Pooled HRs were calculated. Among the 43,858 participants of this retrospective cohort study, 37.64% developed high FBG. The mean (standard deviation) age in the cohort was 40.91 (9.71) years. In the fully adjusted models, the HRs of high FBG in the two centers were 1.35 (95% CI: 1.24-1.48) and 1.22 (95% CI: 1.17-1.28), and the pooled HR was 1.28 (95% CI: 1.16-1.41). A Kaplan-Meier plot of high FBG incidence by occupational noise exposure showed significant results ( < 0.001). We found that occupational noise exposure is significantly associated with high FBG. Preventing exposure to hazardous noise in the work environment may help reduce the risk for prediabetes among workers.

Citing Articles

Kurtosis Assessment of Cardiovascular Disease Risk Caused by Complex Noise in Coal Mines.

Du Y, Tao X, Chu F, Zou Y, Wang J, Ding Y Noise Health. 2025; 26(123):543-552.

PMID: 39787556 PMC: 11813247. DOI: 10.4103/nah.nah_29_24.


Occupational and Environmental Noise Exposure and Extra-Auditory Effects on Humans: A Systematic Literature Review.

Lee Y, Lee S, Lee W Geohealth. 2023; 7(6):e2023GH000805.

PMID: 37303697 PMC: 10248481. DOI: 10.1029/2023GH000805.


Analysis of Noise Exposure Level and Influencing Factors of Small and Micro-Scale Enterprises in Beijing, China.

Aihua L, Yan Y, Zhiqiang C, Li H, Guixin Y, Zihuan W Inquiry. 2022; 59:469580221142486.

PMID: 36510397 PMC: 9751162. DOI: 10.1177/00469580221142486.

References
1.
van Kempen E, Kruize H, Boshuizen H, Ameling C, Staatsen B, de Hollander A . The association between noise exposure and blood pressure and ischemic heart disease: a meta-analysis. Environ Health Perspect. 2002; 110(3):307-17. PMC: 1240772. DOI: 10.1289/ehp.02110307. View

2.
Seo M, Lee W, Kim S, Kang J, Kang J, Kim K . 2018 Korean Society for the Study of Obesity Guideline for the Management of Obesity in Korea. J Obes Metab Syndr. 2019; 28(1):40-45. PMC: 6484940. DOI: 10.7570/jomes.2019.28.1.40. View

3.
Yang X, Kong A, Luk A, Ozaki R, Ko G, Ma R . Validation of methods to control for immortal time bias in a pharmacoepidemiologic analysis of renin-angiotensin system inhibitors in type 2 diabetes. J Epidemiol. 2014; 24(4):267-73. PMC: 4074630. DOI: 10.2188/jea.je20130164. View

4.
Wilson M . Prediabetes: Beyond the Borderline. Nurs Clin North Am. 2017; 52(4):665-677. DOI: 10.1016/j.cnur.2017.07.011. View

5.
Hostalek U . Global epidemiology of prediabetes - present and future perspectives. Clin Diabetes Endocrinol. 2019; 5:5. PMC: 6507173. DOI: 10.1186/s40842-019-0080-0. View