Relationship between Nutrient Intake and Hearing Loss According to the Income Level of Working-Aged Adults: A Korean National Health and Nutrition Survey

Abstract

The relationship between hearing impairment and nutrition has been extensively investigated; however, few studies have focused on this topic in working-age adults by income level. Herein, we aimed to determine the differences in hearing impairment among working-age adults by income level and identify the nutritional factors that affect hearing loss in various socioeconomic groups. Seven-hundred-and-twenty participants had hearing impairment, while 10,130 had normal hearing. After adjustment for propensity score matching, income and smoking status were identified as significant variables. By assessing the relationship between hearing impairment and nutrient intake by income level using multiple regression analyses, significant nutrients differed for each income category. Carbohydrate and vitamin C levels were significant in the low-income group; protein, fat, and vitamin B1 levels were significant in the middle-income group; and carbohydrates were significant in the high-income group. Income was significantly associated with hearing impairment in working-age adults. The proportion of individuals with hearing impairment increased as income decreased. The association between hearing impairment and nutritional intake also differed by income level. Our findings may enable the establishment of health policies for preventing hearing impairment in working-age adults by income level.

Quantifying the Prevalence of Acute Vestibular Neuritis through Big Data Analysis

“…By aggregating and analyzing vast amounts of patient data, researchers can uncover valuable insights into the prevalence, risk factors, and clinical characteristics of AVN, facilitating more informed medical decision-making and improved patient care. However, the initial issue of analyzing the big data is "operational definition of the medical term in the big health data" [6].…”

“…Additionally, cases with concurrent diagnoses of Menière's disease or BPPV are excluded to ensure specificity to AVN. This carefully constructed operational definition serves as the cornerstone of our study, guiding the accurate identification and categorization of AVN cases within the HIRA data[6]. By providing a standardized framework for case identification, the operational definition reduces the risk of misclassification, enhances data integrity, and enables cross-study comparisons.…”