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Table 1 Variables included in this study

From: A machine learning screening model for identifying the risk of high-frequency hearing impairment in a general population

Data Sources

Category

Number of indicators

Candidate indicator (s)

Questionnaire-based indicators

Demographics

6

age, gender, marital status, education level, personal average monthly income, familial disease

Symptom histories

3

self-perceived hearing status, tinnitus, ear pain history in the past year

Disease histories

11

hypertension, diabetes, cerebral haemorrhage, arteriosclerosis, cerebral infection, anemia, migraine, coronary heart disease, otitis media, chronic kidney disease, tumors

Behavioral factors

7

smoking, secondhand smoking, alcohol drinking, hours of sleep, electronic volume, daily fruit and vegetable intaking, exercise frequency

Environmental exposure

4

workplace noise exposure, living noise exposure, work stress, life stress

Hearing cognitive situation

4

pay attention to your hearing, pay attention to hearing protection, regular hearing check, hearing protection skills

Blood parameters

Blood routine indices

21

eosinophil(EO), basophilic(BA), EO(%), hemoglobin(HGB), lymphocyte(LY), mean corpuscular hemoglobin concentration(MCHC), monocyte(MO), mean platelet volume(MPV), neutrophil(NE), blood platelet count(BPC), RDW, basophilic(%)((BASO(%)), hematocrit(HCT), LY(%), mean corpuscular hemoglobin(MCH), mean corpuscular volume(MCV), MO(%), NE (%), platelet distribution width(PDW), red blood cell(RBC), WBC

Hepatic function indices

12

triglyceride(TG), alanine aminotransferase(ALT), indirect bilirubin (IBIL), direct bilirubin(DBIL), albumin(ALB), total bilirubin(TBIL), blood urea nitrogen(BUN), aspartate aminotransferase(AST), total cholesterol(TC), LDL, HDL, creatinine(CR)