Associations of Hearing Loss Defined by Updated World Health Organization Criteria With Socioeconomic Status and Health Check‐Up‐Related Factors: A Population‐Based Cross‐Sectional Study in Japan
Yuri Akamatsu, Yasue Uchida, Mariko Shimono, Saiko Sugiura, Yukiko Nishita, Hiroshi Shimokata, Takeo Nakayama, Rei OtsukaABSTRACT
Aim
Hearing loss (HL) awareness remains insufficient, despite its high prevalence, adverse health effects, and annual hearing screening in the health check‐ups in Japan. This study aimed to examine the association of HL with socioeconomic status (SES), lifestyle, and health‐check‐up‐related factors.
Methods
This population‐based cross‐sectional study used data from the National Institute for Longevity Sciences Longitudinal Study of Aging collected in 2010–2012. HL was defined by the updated World Health Organization criteria, a four‐frequency (0.5, 1, 2, 4 kHz) pure‐tone average ≥ 20 dB in the better‐hearing ear. In order to evaluate the association of HL with SES, each lifestyle and health check‐up‐related factor, first, sex‐stratified binomial logistic regression analyses were performed, adjusted for age; then additional models were fitted, further adjusted for SES and occupational noise exposure.
Results
A total of 2325 individuals (50.6% male), mostly aged 40–79 years, were included. In both sexes, the noise exposure history and glycated hemoglobin (HbA1c) ≥ 6.5% were associated with HL. In males, lower SES, smoking‐related indicators (history and high cumulative exposure), excessive alcohol consumption, and elevated diabetes‐related indicators and γ‐glutamyl transpeptidase levels were associated with HL. Odds Ratios (ORs) for lower educational attainment and household income were 1.71 and 1.42, respectively, and OR for excessive alcohol consumption was 2.01 in the additional model.
Conclusions
HL was associated with lower SES, smoking, excessive alcohol consumption, and several metabolic factors, especially among males. Most of these factors are collected during health check‐ups. Health check‐up data may help to identify individuals at higher risk of HL.