Abstract
Introduction The objective of the present study was to examine the association between low-grade albuminuria and hearing impairment in the non-diabetic population. Materials and methods Data from the Korean National Health and Nutrition Examination Survey 2011–2013 were used in the analyses. Participants were excluded from this study if they were younger than 19 years old, or had urine albumin/creatinine ratio (UACR) ≥ 30 mg/g or diabetes mellitus. There were 10 608 participants included in this study. The participants were divided into three groups according to their UACR tertiles. Results There were 1560; 1561; and 1552 male and 1982; 1975; and 1978, female participants in the low, middle, and high tertile groups, respectively. The results indicated the association between low-grade albuminuria and the numbers of metabolic syndrome (MetS) components or Framingham risk score, and the presence of MetS or the proportions of participants at high cardiovascular risk. Univariate and multivariate linear regression analyses demonstrated an association between the UACR and average hearing threshold (AHT) that was observed in both sexes. Multivariate analyses showed that mean AHTs in the low, middle, and high tertile groups were, respectively, 16.127 dB, 17.139 dB, and 18.604 dB for men, and 14.842 dB, 15.100 dB, and 16.353 dB, respectively, for women. Low-frequency, mid-frequency, and high-frequency hearing thresholds according to UACR tertiles showed similar trends. In both sexes, multivariate logistic regression analyses revealed that participants in the low and middle tertile groups had a decreased risk for hearing loss compared to participants in the high tertile group. Conclusion Low-grade albuminuria was associated with hearing impairment in the non-diabetic participants of this study.
Low-grade albuminuria is associated with MetS and cardiovascular risk in the non-diabetic population.
Low-grade albuminuria is associated with hearing thresholds and hearing loss in the non-diabetic population.
Participants with low-grade albuminuria may be closely monitored for hearing impairment.
Key messages
Introduction
Hearing impairment is one of the most common public health problems. The prevalence of hearing impairment is rising rapidly with an increasingly aging population, noisy environment, and the growing use of listening devices (Citation1). A hearing impairment impedes communication, social behavior, and cognitive function (Citation2). Risk factors for hearing impairment include age, excess alcohol intake, certain medications, excess noise, smoking, vitamin deficiencies, or medical conditions (Citation3). The association of hearing impairment with metabolic disturbances and cardiovascular diseases is well known (Citation4–7). Cardiometabolic risk factors are associated with dysfunction of the cochlear microvascular endothelial cells, which leads to a hearing impairment.
Microalbuminuria is a well-known risk factor for chronic kidney disease (CKD) and cardiovascular disease and is a marker of endothelial dysfunction. Many studies have shown an association between microalbuminuria and cardiovascular or metabolic complications in the general population (Citation8–14). Recent studies have also shown that low-grade albuminuria with a urine albumin/creatinine ratio (UACR) <30 mg/g is associated with cardiovascular or metabolic complications in the general population or participants with variable comorbidities (Citation15–23). Consequently, low-grade albuminuria may be associated with hearing impairment through an increased cardiometabolic risk. Previous studies have shown conflicting results for the association between albuminuria and hearing impairment in participants with diabetes mellitus (DM) (Citation24–26). Although some studies have investigated an association between low-grade albuminuria and cardiovascular disease in the general population including participants with DM, few studies have demonstrated an association between low-grade albuminuria and hearing impairment in the non-diabetic population (Citation19–23). The objective of the present study was to examine the association between low-grade albuminuria and hearing impairment in the non-diabetic population.
Materials and methods
Study population
Data from the Korean National Health and Nutrition Examination Survey (KNHANES) 2011–2013 were used in the analyses. The KNHANES is a nationwide, multi-stage, stratified survey of a representative sample of the South Korean population, which is conducted by the Korea Centers for Disease Control and Prevention. There were 24 594 participants in the KNHANES survey. Participants were excluded from this study if they could not provide data regarding pure tone audiometry (n = 4581) or albuminuria (n = 1189), were younger than 19 years old (n = 5622), or had micro- or macro-albuminuria (UACR ≥30 mg/g; n = 1106) or DM (a self-reported history of a DM diagnosis, a fasting glucose level ≥126 mg/dL, or HbA1c level ≥6.5%; n = 1488). There were 10 608 participants included in this study. The institutional review board of the Yeungnam University Hospital approved this study. Informed consent was waived since the subjects’ records and information were anonymized and de-identified prior to the analysis.
Study variables
Clinical and laboratory data collected from the participants during the health examination included age, sex, body mass index (BMI; kg/m2), UACR (mg/g), systolic blood pressure (SBP; mmHg), diastolic blood pressure (DBP; mmHg), estimated glomerular filtration rate (eGFR; mL/min/1.73 m2), fasting blood glucose level (FBG; mg/dL), total cholesterol level (mg/dL), triglyceride level (TG; mg/dL), high-density lipoprotein (HDL) cholesterol level (mg/dL), waist circumference (WC; cm), alcohol consumption, smoking behavior, exposure to noise, physical activity, and hearing thresholds.
Urine albumin level was measured from random samples using a turbidimetric immunoassay (Hitachi Automatic Analyzer 7600, Hitachi, Tokyo, Japan). Urine creatinine level was measured using a colorimetric method (Hitachi Automatic Analyzer 7600, Hitachi, Tokyo, Japan). Urine albumin and creatinine concentrations were measured in the same laboratory for all surveys. The inter-assay coefficient of variation for all laboratory work was consistently low (<3.1%). UACR was calculated as the urine albumin-creatinine ratio in mg per g of creatinine (mg/g). The participants were divided into three groups according to their UACR tertiles. The serum creatinine levels were measured using a Hitachi Automatic Analyzer (alkaline picrate, Jaffé kinetic). The eGFR was calculated using the four-variable Modification of Diet in Renal Disease formula (Citation27). CKD was defined as an eGFR of <60 mL/min/1.73 m2. Blood pressure was measured three times by trained nurses using a mercury sphygmomanometer (Baumanometer; Baum, Copiague, NY, USA), with the participant in a seated position after a 5-min rest. The final blood pressure value was obtained by averaging the values of the second and third blood pressure measurements. Hypertension (HTN) was defined as SBP ≥140 mmHg, DBP ≥90 mmHg, a self-reported history of HTN, or the use of anti-hypertensive drugs. Smoking behaviors were classified as current smoker, ex-smoker, or non-smoker. Alcohol intake was defined by the Korean version of standard drinking, which was based on the World Health Organization (WHO) classification (Citation28,Citation29). We classified alcohol intake into three categories as follows: abstinence (not having had an alcoholic drink within the last year); moderate drinking (women, 0.1–19.99 g pure alcohol/day; men, 0.1–39.99 g pure alcohol/day); and heavy drinking (women, ≥20 g pure alcohol/day; men, ≥40 g pure alcohol/day). Physical activity was assessed by the presence of exercise, which was based on a previous study (Citation30). The presence of exercise was defined as moderate activity for more than 30 min for 5 days per week, or intense activity for more than 20 min for 3 days per week, or walking more than 30 min a day for more than 5 days per week. Metabolic syndrome (MetS) was defined by using the National Cholesterol Education Program Adult Treatment Panel (NECP-ATP) III guidelines (Citation31).
The Framingham risk (FR) score is a useful method for predicting an individual’s risk for developing cardiovascular disease over the next 10 years. The scores were calculated using the ATP III modified scoring system, as previously described (Citation32). Previous studies have verified the usefulness of the Framingham risk score in Asian populations (Citation33–35). Based on the FR score, the participants were categorized according to their 10-year risk for coronary heart disease as high risk (>20%), intermediate risk (10%–20%), and low risk (<10%).
Histories of exposure to explosives or occupational noise were classified as positive or negative, as previously described (Citation36). Briefly, an explosive noise was defined as a sudden loud noise such as an explosion or gunshot. Exposure to occupational noise was determined according to whether the participants had worked in a location with loud machinery for ≥3 months. Loud noise was defined by whether the participants had needed to raise his or her voice to have a conversation. The hearing thresholds were measured by using an automatic audiometer at 0.5, 1, 2, 3, 4, and 6 kHz. For both ears of each subject, the pure tone averages at 0.5 and 1 kHz were averaged to obtain the low-frequency (Low-Freq) value; those at 2 and 3 kHz, to obtain the mid-frequency (Mid-Freq) value; and those at 4 and 6 kHz, to obtain the high-frequency (High-Freq) value. In the present study, the average hearing threshold (AHT) was calculated as pure tone average at four frequencies (0.5, 1, 2, and 3 kHz). Hearing loss (HL) was defined according to an AHT >40 dB.
Statistical analyses
Data were analyzed using SPSS version 21 (SPSS, Chicago, IL, USA). Categorical variables were expressed as numbers and percentages. The continuous variables were expressed as mean ± standard deviation or standard error. Either the Pearson chi-square test or the Fisher exact test was used to analyze categorical variables. For continuous variables, the one-way analysis of variance was used to compare the means. Correlations were determined in order to assess the strength of the relationship between continuous variables. Linear regression analysis was performed to assess the independent predictors of AHT. Logistic regression analyses were used to estimate the odds ratios and 95% confidence intervals (CIs), which were used to determine the relationship between the UACR tertiles and HL.
Multivariate analysis was adjusted for age, alcohol intake, smoking habit, exposure to explosive or occupational noise, physical activity, HTN, BMI, and CKD. Multivariate analyses using analyses of covariance, multiple linear regression, or multiple logistic regression were used determine the independent predictors of hearing. The level of statistical significance was set at a p value of <0.05.
Results
Clinical characteristics of the participants
There were 1560; 1561; and 1552 male and 1982; 1975; and 1978 female participants in the low, middle, and high tertile groups, respectively. The mean UACR in the low, middle, and high tertile groups in men was 0.75 ± 0.52 mg/g (0.03–1.63 mg/g), 2.58 ± 0.62 mg/g (1.64–3.81 mg/g), and 9.21 ± 5.87 mg/g (3.82–29.92 mg/g), respectively, and in women these values were 1.00 ± 0.69 mg/g (0.04–2.20 mg/g), 3.53 ± 0.83 mg/g (2.21–5.19 mg/g), and 10.99 ± 5.93 mg/g (5.20–29.83 mg/g), respectively (). For both the sexes, the proportions of participants with HTN and CKD were greatest in the high tertile group. Similarly, age, BMI, FBG level, TG level, and WC were also greatest in the high tertile group. HDL cholesterol level was lower in the high tertile group compared to that in the other tertile groups.
Table I. Clinical characteristics of the participants according to UACR tertiles.
Association between cardiometabolic risk factors and UACR tertiles
shows the percentage of participants with MetS or MetS components in the low, middle, and high tertile groups. Those in the high tertile had the most MetS or MetS components. This was consistently observed in both sexes. demonstrates the FR classified according to the UACR tertiles. In men, the proportions of participants at high risk were 13.3%, 14.0%, and 25.4% in the low, middle, and high tertile groups, respectively. In women, the proportions of participants at high risk were 2.7%, 2.9%, and 4.8% in the low, middle, and high tertile groups, respectively. In both sexes, the FR was the highest in the high tertile group.
Figure 1. Identification of the presence of MetS components or MetS, according to UACR tertiles. (a) Men. (b) Women. (P < 0.001 for trend in all analyses). In men, the percentages of participants with MetS or MetS components in the low tertile group were 23.1% for FBG, 16.0% for HDL cholesterol, 29.3% for TG, 20.7% for WC, 36% for BP, and 15.1% for MetS. For those in the middle tertile group, the MetS or MetS components were 27.1% for FBG, 19.6% for HDL cholesterol, 33.0% for TG, 20.8% for WC, 38.4% for BP, and 19.7% for MetS. For those in the high tertile group, the MetS or MetS components were 33.6% for FBG, 20.8% for HDL cholesterol, 40.0% for TG, 26.8% for WC, 56.7% for BP, and 28.6% for MetS. In women, the percentages of participants with MetS or MetS components in the low tertile group were 13.5% for FBG, 30.1% for HDL cholesterol, 19.1% for TG, 36.2% for WC, 22.0% for BP, and 15.5% for MetS. For those in the middle tertile group, the MetS or MetS components were 16.6% for FBG, 32.6% for HDL cholesterol, 19.7% for TG, 35.8% for WC, 28.5% for BP, and 19.3% for MetS. For those in the high tertile group, the MetS or MetS components were 24.1% for FBG, 38.8% for HDL cholesterol, 24.6% for TG, 46.3% for WC, 48.6% for BP, and 31.8% for MetS. BP = blood pressure; FBG = fasting blood glucose; HDL = high-density lipoprotein; MetS = metabolic syndrome; TG = triglyceride; WC = waist circumference.
Figure 2. Identification of the Framingham risk according to the UACR tertiles. (P < 0.001 for trend in both genders). In men, the percentages of participants who were at high risk were 13.3%, 14.0%, and 25.4% in the low, middle, and high tertile groups, respectively. Those at intermediate risk were 29.1%, 32.4%, and 33.8% in the low, middle, and high tertile groups, respectively. Those at low risk were 49.0%, 44.2%, and 32.0% in the low, middle, and high tertile groups, respectively. In women, those at high risk were 2.7%, 2.9%, and 4.8% in the low, middle, and high tertile groups, respectively. Those at intermediate risk were 1.8%, 2.1%, and 6.8% in the low, middle, and high tertile groups, respectively. Those at low risk were 84.8%, 82.3%, and 71.7% in the low, middle, and high tertile groups, respectively.
FBG = fasting blood glucose; HDL = high-density lipoprotein; TG = triglyceride; WC = waist circumference; BP = blood pressure; MetS = metabolic syndrome.
Association between cardiometabolic risk factors and hearing thresholds
shows the correlation between the numbers of MetS components or the FR scores and the hearing thresholds. In men, the correlation coefficients for the FR scores were 0.352, 0.472, 0.529, and 0.450 for Low-Freq, Mid-Freq, High-Freq, and AHT, respectively, and in women these were 0.470, 0.562, 0.612, and 0.542 for Low-Freq, Mid-Freq, High-Freq, and AHT, respectively.
Table II. Correlations between hearing thresholds and numbers of MetS components or Framingham risk score.
Association between UACR and hearing thresholds
The univariate and multivariate linear regression analyses demonstrated an association between the UACR and AHT that was observed in both sexes (). Univariate analysis for both sexes exhibited the highest mean hearing thresholds in the high tertile group (). Multivariate analyses using the analysis of covariance showed that, at 95% CI, AHTs in the low, middle, and high tertile groups were 16.127 dB (15.490–16.764), 17.139 dB (16.503–17.775), and 18.604 (17.951–19.257), respectively, for men (). Low-Freq values in the low, middle, and high tertile groups were 13.064 (12.486–13.642), 13.733 (13.156–14.310), and 15.183 (14.591–15.776), respectively. Mid-Freq values in the low, middle, and high tertile groups were 19.190 (18.381–20.000), 20.545 (19.737–21.353), and 22.025 (21.195–22.855), respectively. High-Freq values in the low, middle, and high tertile groups were 33.760 (32.705–34.816), 35.806 (34.753–36.860), and 36.699 (35.616–37.781), respectively. In men, multivariate analyses revealed higher AHT and Low-Freq mean values in the high tertile group than in other tertile groups. Mid- and High-Freq values in the high tertile group were higher than those in the low tertile group.
Figure 3. Identification of the hearing thresholds according to UACR tertile. (a) Men. (b) Women. The multivariate analysis was adjusted for age, alcohol intake, smoking habit, exposure to explosive noise, exposure to occupational noise, hypertension, body mass index, and chronic kidney disease (P < 0.05 for trend in all analyses; *P < 0.05, compared to participants with low or middle UACR tertiles; †P < 0.05, compared to participants with low UACR tertile). The data are expressed as mean and standard error values. AHT = average hearing threshold; High-Freq = high frequency; Low-Freq = low frequency; Mid-Freq = middle frequency; UACR = urine albumin/creatinine ratio.
Table III. Linear regression analyses of average hearing threshold according to UACR.
In women, AHTs in the low, middle, and high tertile groups were 14.842 dB (14.318–15.367), 15.100 dB (14.577–15.623), and 16.353 dB (15.815–16.891), respectively (). Low-Freq values in the low, middle, and high tertile groups were 13.793 (13.274–14.312), 14.230 (13.713–14.748), and 15.222 (14.689–15.756), respectively. Mid-Freq values in the low, middle, and high tertile groups were 15.892 (15.303–16.481), 15.970 (15.382–16.557), and 17.483 (16.879–18.088), respectively. High-Freq values in the low, middle, and high tertile groups were 25.017 (24.323–25.711), 25.021 (24.329–25.713), and 26.423 (26.423–27.848), respectively. In women, multivariate analyses revealed higher AHT, Mid-, and High-Freq mean values in the high tertile group than in the other tertiles. The Low-Freq values in the high tertile group were higher than those in the low tertile group.
In men, univariate logistic regression indicated that participants in the low and middle tertile groups had a decreased (0.522, 95% CI 0.414–0.659, p < 0.001 and 0.468, 95% CI 0.369–0.595, p < 0.001, respectively) risk for HL compared to the participants in the high tertile group. The multivariate analysis revealed that participants in the low and middle tertile groups had a decreased (0.411, 95% CI 0.321–0.526, p < 0.001 and 0.374, 95% CI 0.291–0.482, p < 0.001, respectively) risk for HL compared to the participants in the high tertile group. In women, univariate logistic regression demonstrated that participants in the low and middle tertile groups had a decreased (0.683, 95% CI 0.519–0.897, P = 0.006 and 0.653, 95% CI 0.494–0.863, P = 0.003, respectively) risk for HL compared to the participants in the high tertile group. The multivariate analysis revealed that participants in the low and middle tertile groups had a decreased (0.634, 95% CI 0.477–0.844, P = 0.002 and 0.682, 95% CI 0.509–0.912, P = 0.010, respectively) risk for HL compared to the participants in the high tertile group.
Discussion
The results indicate the association between low-grade albuminuria and the numbers of MetS components or FR score as continuous variables, and the presence of MetS or FR as categorical variables. Univariate and multivariate linear regression analyses showed an association between UACR and Low-Freq, Mid-Freq, and High-Freq hearing thresholds. Univariate and multivariate logistic regression analyses showed an association between UACR tertiles and HL. These results indicate that low-grade albuminuria may be associated with hearing impairment through increased cardiometabolic risk in the non-diabetic population.
Microalbuminuria is an important risk factor for cardiometabolic complications in the general, diabetic, and non-diabetic populations. Regarding strong associations between the two variables, recent studies have focused on the association between low-grade albuminuria and cardiometabolic risk in various population groups (Citation15–23,Citation37,Citation38). We analyzed the association between low-grade albuminuria and MetS as a metabolic risk or the FR score as cardiovascular risk. The results revealed that inclusion in the high tertile group in both sexes is positively associated with the presence of MetS and a high or intermediate risk that is calculated using the FR score. In addition, numbers of MetS components and the FR score are associated with UACR as continuous variables.
Park et al. showed an association between low-grade albuminuria and MetS using the same registry (Citation23). Their study also produced similar results; however, it did not exclude DM participants. In the study by Park et al., DM and HTN were defined only by the presence or absence of medication rather than the diagnosis. Definite exclusion of DM patients or multivariate analyses after exact classification of DM patients would be essential, because the effect of low-grade albuminuria may vary significantly depending on DM status. The present study excluded the DM patients using thorough criteria for DM (self-reported history of a DM diagnosis, fasting glucose level ≥126 mg/dL, or HbA1c level ≥6.5%). A total of 1488 DM patients out of 10 608 total participants, or 14%, were excluded in the present study. Therefore, non-exclusion of definite DM patients may be an important confounder in the study by Park et al.
Regarding the association between low-grade albuminuria and FR score or MetS, low-grade albuminuria may induce hearing impairment through cochlear vasculopathies resulting from cardiometabolic complications. Shen et al. previously demonstrated the association between albuminuria and hearing impairment among participants with DM (Citation26). However, other studies exhibited a significant association between advanced nephropathy and hearing impairment in participants with DM, but only a modest effect of albuminuria on high-frequency hearing impairment (Citation24,Citation25). However, there may be some differences in the clinical implications between albuminuria among patients with and without DM. The present study enrolled non-diabetic participants. To our knowledge, no other study has evaluated the association between low-grade albuminuria and hearing impairment in the non-diabetic population. The results indicated an association between low-grade albuminuria and hearing thresholds or HL, in both sexes. Participants in the high tertile group, in particular, had higher hearing thresholds than those in the low tertile group. We defined HL as an AHT >40 dB and decreased HL odd ratios in participants who were classified in the low or middle tertile group compared with those in the high tertile group.
Previous studies have indicated an association between metabolic complications and hearing thresholds that were greater in women than in men (Citation39,Citation40). Sensorineural hearing loss related to metabolic complications is more evident in the high-frequency hearing threshold. The present study also demonstrated that correlation coefficients between hearing thresholds and numbers of MetS components were stronger in women than in men. Those correlations between hearing thresholds and the FR score were similar in both sexes. Correlation coefficients were greater with High-Freq values than with Low-Freq values.
This study had a few limitations. First, the study was limited by its retrospective nature. The ethnic differences were not evaluated. This study could not establish causality. Second, this study did not evaluate the sensitive components of hearing impairment such as speech discrimination. Third, we used a single urine spot sample to calculate the UACR. Fourth, selection bias may have been present due to the exclusion of 5770 participants without audiometric or UACR data, who comprised approximately 23.5% of the population. Further prospective analysis, including follow-up data and speech discrimination, will be needed to evaluate a possible strong correlation between low-grade albuminuria and hearing impairment.
In conclusion, low-grade albuminuria was associated with hearing impairment in the non-diabetic participants of this study. Therefore, participants with low-grade albuminuria may be closely monitored for hearing impairment.
Acknowledgements
Seok Hui Kang and Da Jung Jung contributed equally to this work.
Declaration of interest
All authors report no conflict of interest.
This work was supported by the Medical Research Center Program (2015R1A5A2009124) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning.
References
- Wallhagen MI, Strawbridge WJ, Cohen RD, Kaplan GA. An increasing prevalence of hearing impairment and associated risk factors over three decades of the Alameda Country Study. Am J Public Health. 1997;87:440–2.
- Lin FR, Yaffe K, Xia J, Xue QL, Harris TB, Purchase-Helzner E, et al. Hearing loss and cognitive decline in older adults. JAMA Intern Med. 2013;173:293–9.
- Walling AD, Dickson GM. Hearing loss in older adults. Am Fam Physician. 2012;85:1150–6.
- Rosen S, Olin P. Hearing loss and coronary heart disease. Arch Otolaryngol. 1965;82:236–43.
- Gates GA, Cobb JL, D’Agostino RB, Wolf PA. The relation of hearing in the elderly to the presence of cardiovascular disease and cardiovascular risk factors. Arch Otolaryngol Head Neck Surg. 1993;119:156–61.
- Shargorodsky J, Curhan SG, Eavey R, Curhan GC. A prospective study of cardiovasulcar risk factors and incident hearing loss in men. Laryngoscope. 2010;120:1887–91.
- Kang SH, Jung da J, Cho KH, Park JW, Yoon KW, Do JY. The association between metabolic syndrome or chronic kidney disease and hearing thresholds in Koreans: the Korean National Health and Nutrition Examination Survey 2009-2012. PLoS One. 2015;10:e0120372.
- Bigazzi R, Bianchi S, Baldari D. Microalbuminuria predicts cardiovascular events and renal insufficiency in patients with essential hypertension. J Hypertens. 1998;16:1325–33.
- Gerstein HC, Mann JF, Yi Q, Zinman B, Dinneen SF, Hoogwerf B, et al. Albuminuria and risk of cardiovascular events, death, and heart failure in diabetic and nondiabetic individuals. JAMA. 2001;286;421–6.
- Parving HH, Lehnert H, Bröchner-Mortensen J, Gomis R, Andersen S, Arner P. Irbesartan in Patients with Type 2 Diabetes and Microalbuminuria Study Group. The effect of irbesartan on the development of diabetic nephropathy in patients with type 2 diabetes. N Engl J Med. 2001;345:870–8.
- Malik AR, Sultan S, Turner ST, Kullo IJ. Urinary albumin excretion is associated with impaired flow- and nitroglycerin-mediated brachial artery dilatation in hypertensive adults. J Hum Hypertens. 2007;21:231–8.
- van der Velde M, Halbesma N, de Charro FT, Bakker SJ, de Zeeuw D, de Jong PE, et al. Screening for albuminuria identifies individuals at increased renal risk. J Am Soc Nephrol. 2009;20:852–62.
- Klausen KP, Parving HH, Scharling H, Jensen JS. The association between metabolic syndrome, microalbuminuria and impaired renal function in the general population: impact on cardiovascular disease and mortality. J Intern Med. 2007;262:470–8.
- Yuyun MF, Khaw KT, Luben R, Welch A, Bingham S, Day NE, et al. Microalbuminuria independently predicts all-cause and cardiovascular mortality in a British population: The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) population study. Int J Epidemiol. 2004;33:189–98.
- Danziger J. Importance of low-grade albuminuria. Mayo Clin Proc. 2008;83:806–12.
- Huang Y, Chen Y, Xu M, Gu W, Bi Y, Li X, et al. Low-grade albuminuria is associated with carotid intima-media thickness in Chinese type 2 diabetic patients. J Clin Endocrinol Metab. 2010;95:5122–8.
- Zhang J, Chen Y, Xu Y, Li M, Wang T, Xu B, et al. Low-grade albuminuria is associated with metabolic syndrome and its components in middle aged and elderly Chinese population. PLoS One. 2013;8:e65597.
- Katz DH, Selvaraj S, Aguilar FG, Martinez EE, Beussink L, Kim KY, et al. Association of low-grade albuminuria with adverse cardiac mechanics: findings from the hypertension genetic epidemiology network (HyperGEN) study. Circulation. 2014;129:42–50.
- Hong JW, Ku CR, Noh JH, Ko KS, Rhee BD, Kim DJ. Association between low-grade albuminuria and cardiovascular risk in Korean adults: the 2011-2012 Korean National Health and Nutrition Examination Survey. PLoS One. 2015;10:e0118866.
- Hillege HL, Fidler V, Diercks GF, van Gilst WH, de Zeeuw D, van Veldhuisen DJ, et al. Urinary albumin excretion predicts cardiovascular and noncardiovascular mortality in general population. Circulation. 2002;106:1777–82.
- Klausen KP, Scharling H, Jensen G, Jensen JS. New definition of microalbuminuria in hypertensive subjects: association with incident coronary heart disease and death. Hypertension. 2005;46:33–7.
- Ingelsson E, Sundstrom J, Lind L, Riserus U, Larsson A, Basu S, et al. Low-grade albuminuria and the incidence of heart failure in a community-based cohort of elderly men. Eur Heart J. 2007;28:1739–45.
- Park SY, Park YK, Cho KH, Choi HJ, Han JH, Han KD, et al. Normal range albuminuria and metabolic syndrome in South Korea: the 2011-2012 Korean National Health and Nutrition Examination Survey. PLoS One. 2015;10:e0125615.
- Dalton DS, Cruickshanks KJ, Klein R, Klein BE, Wiley TL. Association of NIDDM and hearing loss. Diabetes Care. 1998;21:1540–4.
- Bainbridge KE, Cheng YJ, Cowie CC. Potential mediators of diabetes-related hearing impairment in the U.S. population: National Health and Nutrition Examination Survey 1999-2004. Diabetes Care. 2010;33:811–16.
- Shen FC, Hsieh CJ. Severity of hearing impairment is positively associated with urine albumin excretion rate in patients with type 2 diabetes. J Diabetes Investig. 2014;5:743–7.
- Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999:130:461–70.
- Rehm J, Room R, Monteiro M, Gmel G, Graham K, Rehn N, et al. Alcohol use. In: Ezzati M, Lopez A, Rodgers A, Murray CJL, eds. Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors, pp. 9591108. Geneva: World Health Organization, 2004.
- The Korea Centers for Disease Control and Prevention: Alcohol drinking. [internet]. Available from: http://health.mw.go.kr/HealthPromotionArea/HealthInfo/View.do?idx= 5800 &subIdx = 3&searchCate=&searchType=&searchKey=&pageNo = 1
- Kim J, Chu SK, Kim K, Moon JR. Alcohol use behaviors and risk of metabolic syndrome in South Korean middle-aged men. BMC Public Health. 2011;11:489.
- Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnostic and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112:2735–52.
- Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation. 2002;106:3143–421.
- Suka M, Sugimori H, Yoshida K. Application of the updated Framingham risk score to Japanese men. Hypertens Res. 2001;24:685–9.
- Selvarajah S, Kaur G, Haniff J, Cheong KC, Hiong TG, van der Graaf Y, et al. Comparison of the Framingham Risk Score, SCORE and WHO/ISH cardiovascular risk prediction models in an Asian population. Int J Cardiol. 2014;176:211–18.
- Chia YC, Gray SY, Ching SM, Lim HM, Chinna K. Validation of the Framingham general cardiovascular risk score in a multiethnic Asian population: a retrospective cohort study. BMJ Open. 2015;5:e007324.
- Kang JW, Choi HS, Kim K, Choi JY. Dietary vitamin intake correlates with hearing thresholds in the older population: the Korean National Health and Nutrition Examination Survey. Am J Clin Nutr. 2014;99:1407–13.
- Wang TJ, Evans JC, Meigs JB, Rifai N, Fox CS, D’Agostino RB, et al. Low-grade albuminuria and the risks of hypertension and blood pressure progression. Circulation. 2005;111:1370–6.
- Arnlöv J, Evans JC, Meigs JB, Wang TJ, Fox CS, Levy D, et al. Low-grade albuminuria and incidence of cardiovascular disease events in nonhypertensive and nondiabetic individuals: the Framingham Heart Study. Circulation. 2005;112:969–75.
- Hederstierna C, Hultcrantz M, Collins A, Rosenhall U. Hearing in women at menopause. Prevalence of hearing loss, audiometric configuration and relation to hormone replacement therapy. Acta Otolaryngol. 2007;127:149–55.
- Hwang JH, Hsu CJ, Liu TC, Yang WS. Association of plasma adiponectin levels with hearing thresholds in adults. Clin Endocrinol. 2011;75:614–20.