2026-04-17T10:26:18Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/82882024-05-17T07:30:31Zcom_10259_5501com_10259_5086com_10259_2604com_10259_7877com_10259_7387col_10259_5502col_10259_8289col_10259_7419
Repositorio Institucional de la Universidad de Burgos
author
Barrero Ahedo, Jesús P.
author
López Perea, Eva María
author
Herrera, Sixto
author
Mariscal Saldaña, Miguel Ángel
author
García Herrero, Susana
2024-01-11T08:33:08Z
2024-01-11T08:33:08Z
2020-11
1661-7827
http://hdl.handle.net/10259/8288
10.3390/ijerph17218041
1660-4601
Hearing loss affects hundreds of millions of people all over the world, leading to several types of disabilities, ranging from purely physical to psychological and/or social aspects. A proper analysis to ascertain the main risk factors is essential in order to diagnose early and treat adequately. An exploratory analysis based on a heterogeneous sample of 1418 workers is presented in order to identify the main trigger factors for hearing loss. On the one hand, we recorded several medical and environmental parameters, and on the other, we created a model based on Bayesian networks in order to be able to infer the probability of hearing loss considering different scenarios. This paper focuses on three parameters: gender, age, and a family history of hearing problems. The results obtained allow us to infer or predict the best or worst auditory level for an individual under several different scenarios. The least relevant factor is the existence of a family history of deafness, followed by the gender factor, which slopes considerably toward better hearing for females, and most prominent of all, the age factor, given the large differences identified between the various age groups when the gender and family history of deafness variables remain constant.
eng
Atribución 4.0 Internacional
Hearing loss
Bayesian network
Gender
Age
Family history
Assessment and Modeling of the Influence of Age, Gender, and Family History of Hearing Problems on the Probability of Suffering Hearing Loss in the Working Population
info:eu-repo/semantics/article
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URL
https://riubu.ubu.es/bitstream/10259/8288/1/Barrero-ijerph_2020.pdf
File
MD5
14b3a7153e0473449e00d93e67a3d7fa
1306530
application/pdf
Barrero-ijerph_2020.pdf