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Journal Article

Citation

Abbasi-Ghahramanloo A, Janani L, Malakouti SK, Rabetian M, Rimaz S. Neuropsychiatr. Dis. Treat. 2019; 15: 2513-2520.

Affiliation

Radiation Biology Research Center, Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.

Copyright

(Copyright © 2019, Dove Press)

DOI

10.2147/NDT.S221858

PMID

31695386

PMCID

PMC6717848

Abstract

BACKGROUND: Risk taking behaviors are a serious risk to the health and safety of workers. The aims of this study were to identify the subgroups of workers on the basis of risk taking behaviors and assess the independent role of ADHD on the membership of participants in each latent class.

METHODS: This cross sectional study was performed on 2434 workers. The sample was selected through random cluster sampling from Kaveh Industrial City. All workers completed five sets of checklists and questionnaires. Data analysis was performed using chi-square, Fisher's exact test, and latent class analysis.

RESULTS: Four latent classes were identified; namely, 1) very low risk (65.6%), 2) low risk (27.8%), moderate risk (4.1%) and, high risk (2.5%). After adjusting for other studied covariates, having ADHD significantly increased the odds of membership in moderate risk class (OR=3.42, 95% CI: 2.21 -5.29) and high risk class (OR=3.10, 95% CI: 1.80 -5.34) compared to very low risk class. Also, having anxiety increased the odds of membership in latent class 2 (OR=1.28, 95% CI: 1.02-1.62), 3(OR=2.15, 95% CI: 1.51-3.10) and 4 (OR=2.06, 95% CI: 1.32-3.22) in comparison to class 1. Among all participants, 187 (7.7%) had ADHD and among studied variables, ADHD has the strongest role in the membership of subjects in different classes.

CONCLUSION: Results from the present study indicate that 6.6% of the workers fell under moderate or high risk class. Focusing on the treatment of ADHD with considering other comorbid factors such as anxiety may be helpful in designing and executing effective programs to reduce risk taking behaviors among workers.

© 2019 Abbasi-Ghahramanloo et al.


Language: en

Keywords

ADHD; latent class analysis; risk taking behaviors; workers

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