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Noise-induced hearing loss (NIHL) is a hearing impairment (HI) caused by various clinical factors. Identifying the relationship between NIHL and nutrient consumption could help in reducing the prevalence of hearing loss. The aim of this study was to analyze the relationship between NIHL and dietary factors using data of the Korea National Health and Nutrition Examination survey (KNHANES). The data were collected from The Fifth KNHANES 2010–2012. The survey was taken by a total of 10,850 participants aged 20–65 years. Air conduction audiometry was measured at 500, 1000, 2000, and 4000 Hz in both ears. Metabolic syndrome, noise exposure, alcohol consumption, smoking, income level, marital status, and nutritional intake were evaluated. The differences between non-HI and HI participants in the noise-exposed group showed statistically significant differences in age, sex, marital and smoking status, alcohol consumption, and fasting glucose and triglyceride levels (p<0.05). In a multiple regression analysis of the noise-exposed group, age showed a significant association with HI (OR: 0.604; 95% CI: 0.538–0.678) after adjusting for confounders. In multivariate analysis for dietary factors affecting HI in noise-exposed groups, retinol (OR: 1.356; 95% CI: 1.068–1.722), niacin (OR: 1.5; 95% CI: 1.022–2.201), and carbohydrates (OR: 0.692; 95% CI: 0.486–0.985) showed a significant association with NIHL. Age was identified as the only factor significantly affecting NIHL. When the dietary factors of the noise-exposed group were analyzed, high intake of niacin and retinol and low intake of carbohydrates appeared to reduce the risk of hearing loss.

Background:The sampling framework of the National Patient Sample of Health Insurance Review & Assessment Service is needed to be improved due to the current demographic structure. We proposed a sampling method and additional strata for extracting the National Patient Sample data due to the current demographic structure, such as low birth rate and aged population. Methods: A total of 36 strata were set by adding four strata compared to the existing one. The maximum rate of minimal sample number was defined among the entire strata. Based on the rate, we extracted a small-scale sample dataset consisting of about 400,000 people and a large-scale sample dataset of more than 700,000 people. Results:The representativeness of the high-frequency disease and the low-frequency disease was confirmed. For health expenditure, the representativeness of samples was confirmed in large-scale samples. However, the representativeness of small-scale samples was not confirmed in five strata. Conclusion:Using the maximum rate of minimal sample number can reflect the demographic structure changes and diverse medical utilization. Although lack of representativeness in the five strata of the small-scale sample, both the small-scale sample and the large-scale sample are necessary to improve data accessibility and a sustainable data provision system. It will be helpful in establishing health policies and conducting medical research.

Noise-induced hearing loss (NIHL) is a hearing impairment caused by various epidemiologic and clinical factors. Identifying the relationship between NIHL and nutrients could help reduce the prevalence of hearing loss. This study analyzed the relationship between NIHL and dietary factors using data of the Korea National Health and Nutrition Examination survey. The survey was taken by a total of 10,850 participants aged 20-65 years. Air conduction audiometry was measured at 500, 1000, 2000, and 4000Hz in both ears. Metabolic syndrome, noise exposure, drink, smoke, income, marital status, and nutritional intake were evaluated. The differences between non-HI and HI participants in noise-exposed group have shown statistically significant differences in age, sex, marital status, smoking status, alcohol consumption, fast glucose level, and triglyceride level (p<0.05). In a multiple regression analysis, the age factor showed a significant association with HI (OR: 0.604; 95% CI: 0.538-0.678). In multivariate analysis for dietary factors, Retinol (OR: 1.356; 95% CI: 1.068-1.722), Niacin (OR: 1.5; 95% CI: 1.022-2.201) and Carbohydrates (OR: 0.692; 95% CI: 0.486-0.985) showed a significant association with NIHL. When the dietary factors of the noise exposure group were analyzed, high intake of Niacin and Retinol and low intake of Carbohydrates appear to prevent hearing loss.

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.