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Carbohydrate-deficient transferrin (CDT) is a useful biomarker to identify excessive alcohol consumption; however, few studies have validated the %CDT cut-off value in elderly men. This study estimated the optimal %CDT cut-off value that could identify excessive alcohol consumption in men aged ≥65 years.
This retrospective study included 120 men who visited the department of family medicine at Chungnam National University Hospital for health check-up between January 2010 and August 2013. At-risk drinking included heavy- and binge drinking. Heavy drinking was defined as more than seven standard drinks/wk, and binge drinking was defined as more than three standard drinks/d. The cut-off %CDT values for at-risk drinking were determined using receiver operating characteristic (ROC) curves.
Based on the ROC curves, the optimal %CDT cut-off values in ≥65-year-old men were 1.95% for at-risk drinking, 1.81% for heavy drinking, and 2.07% for binge drinking. The sensitivity, specificity, and positive and negative predictive values were 58.7%, 83.6%, 69.2%, and 76.2% for at-risk drinking, respectively. The AUROC were >0.7 for all three evaluated cut-offs.
Our results suggest that the %CDT cut-off value for at-risk drinking in elderly Korean men (≥65 years) should be readjusted to a lower value of 1.95%.
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Cardiovascular disease (CVD) has become the most common cause of mortality and morbidity worldwide. Health screening is associated with higher outpatient visits for detection and treatment of CVD-related diseases (diabetes mellitus, hypertension, and dyslipidemia). We examined the association between health screening, health utilization, and economic status.
A sampled cohort database from the National Health Insurance Corporation was used. We included 306,206 participants, aged over 40 years, without CVD (myocardial infarction, stroke, and cerebral hemorrhage), CVD-related disease, cancer, and chronic renal disease. The follow-up period was from January 1, 2003 through December 31, 2005.
Totally, 104,584 participants received at least one health screening in 2003–2004. The odds ratio of the health screening attendance rate for the five economic status categories was 1.27 (95% confidence interval [CI], 1.24 to 1.31), 1.05 (95% CI, 1.02 to 1.08), 1, 1.16 (95% CI, 1.13 to 1.19) and 1.50 (95% CI, 1.46 to 1.53), respectively. For economic status 1, 3, and 5, respectively, the diagnostic rate after health screening was as follows: diabetes mellitus: 5.94%, 5.36%, and 3.77%; hypertension: 32.75%, 30.16%, and 25.23%; and dyslipidemia: 13.43%, 12.69%, and 12.20%. The outpatient visit rate for attendees diagnosed with CVD-related disease was as follows for economic status 1, 3, and 5, respectively: diabetes mellitus: 37.69%, 37.30%, and 43.70%; hypertension: 34.44%, 30.09%, and 32.31%; and dyslipidemia: 18.83%, 20.35%, and 23.48%.
Thus, higher or lower economic status groups had a higher health screening attendance rate than the middle economic status group. The lower economic status group showed lower outpatient visits after screening, although it had a higher rate of CVD diagnosis.
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We previously proposed the Predictive Index for Osteoporosis as a new index to identify men who require bone mineral density measurement. However, the previous study had limitations such as a single-center design and small sample size. Here, we evaluated the usefulness of the Predictive Index for Osteoporosis using the nationally representative data of the Korea National Health and Nutrition Examination Survey.
Participants underwent bone mineral density measurements via dual energy X-ray absorptiometry, and the Predictive Index for Osteoporosis and Osteoporosis Self-Assessment Tool for Asians were assessed. Receiver operating characteristic analysis was used to obtain optimal cut-off points for the Predictive Index for Osteoporosis and Osteoporosis Self-Assessment Tool for Asians, and the predictability of osteoporosis for the 2 indices was compared.
Both indices were useful clinical tools for identifying osteoporosis risk in Korean men. The optimal cut-off value for the Predictive Index for Osteoporosis was 1.07 (sensitivity, 67.6%; specificity, 72.7%; area under the curve, 0.743). When using a cut-off point of 0.5 for the Osteoporosis Self-Assessment Tool for Asians, the sensitivity and specificity were 71.9% and 64.0%, respectively, and the area under the curve was 0.737.
The Predictive Index for Osteoporosis was as useful as the Osteoporosis Self-Assessment Tool for Asians as a screening index to identify candidates for dual energy X-ray absorptiometry among men aged 50–69 years.
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The Korean-Mini-Mental Status Examination (K-MMSE) is a dementia-screening test that can be easily applied in both community and clinical settings. However, in 20% to 30% of cases, the K-MMSE produces a false negative response. This suggests that it is necessary to evaluate the accuracy of K-MMSE as a screening test for dementia, which can be achieved through comparison of K-MMSE and Seoul Neuropsychological Screening Battery (SNSB)-II results.
The study included 713 subjects (male 534, female 179; mean age, 69.3±6.9 years). All subjects were assessed using K-MMSE and SNSB-II tests, the results of which were divided into normal and abnormal in 15 percentile standards.
The sensitivity of the K-MMSE was 48.7%, with a specificity of 89.9%. The incidence of false positive and negative results totaled 10.1% and 51.2%, respectively. In addition, the positive predictive value of the K-MMSE was 87.1%, while the negative predictive value was 55.6%. The false-negative group showed cognitive impairments in regions of memory and executive function. Subsequently, in the false-positive group, subjects demonstrated reduced performance in memory recall, time orientation, attention, and calculation of K-MMSE items.
The results obtained in the study suggest that cognitive function might still be impaired even if an individual obtained a normal score on the K-MMSE. If the K-MMSE is combined with tests of memory or executive function, the accuracy of dementia diagnosis could be greatly improved.
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Enquiry into smoking status and recommendations for smoking cessation is an essential preventive service. However, there are few studies comparing self-reported (SR) and cotinine-verified (CV) smoking statuses, using medical check-up data. The rates of discrepancy and under-reporting are unknown.
We performed a cross-sectional study using health examination data from Healthcare System Gangnam Center, Seoul National University Hospital in 2013. We analyzed SR and CV smoking statuses and discrepancies between the two in relation to sociodemographic variables. We also attempted to ascertain the factors associated with a discrepant smoking status among current smokers.
In the sample of 3,477 men, CV smoking rate was 11.1% higher than the SR rate. About 1 in 3 participants either omitted the smoking questionnaire or gave a false reply. The ratio of CV to SR smoking rates was 1.49 (95% confidence interval [CI], 1.38–1.61). After adjusting for confounding factors, older adults (≥60 years) showed an increased adjusted odds ratio (aOR) for discrepancy between SR and CV when compared to those in their twenties and thirties (aOR, 5.43; 95% CI, 2.69–10.96). Educational levels of high school graduation or lower (aOR, 2.33; 95% CI, 1.36–4.01), repeated health check-ups (aOR, 1.45; 95% CI, 1.03–2.06), and low cotinine levels of <500 ng/mL (aOR, 2.03; 95% CI, 1.33–3.09), were also associated with discordance between SR and CV smoking status.
Omissions and false responses impede the accurate assessment of smoking status in health check-up participants. In order to improve accuracy, it is suggested that researcher pay attention to participants with greater discrepancy between SR and CV smoking status, and formulate interventions to improve response rates.
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This study evaluated the utility of the Alcohol Use Disorders Identification Test Alcohol Consumption Questions (AUDIT-C) in screening at-risk drinking and alcohol use disorders among Korean college students.
For the 387 students who visited Chungnam National University student health center, drinking state and alcohol use disorders were assessed through diagnostic interviews. In addition, Alcohol Use Disorders Identification Test (AUDIT), AUDIT-C, and cut down, annoyed, guilty, eye-opener (CAGE) were applied. The utility of the questionnaires for the interview results were compared.
The areas under the receiver operating characteristic curves (AUROCs) of AUDIT-C for screening at-risk drinking were 0.927 in the male and 0.921 in the female participants. The AUROCs of AUDIT and CAGE were 0.906 and 0.643, respectively, in the male, and 0.898 and 0.657, respectively, in the female participants. The optimal screening scores of at-risk drinking in AUDIT-C were ≥6 in the male and ≥4 in the female participants; and in AUDIT and CAGE, ≥8 and ≥1, respectively, in the male, and ≥5 and ≥1 in the female participants. The AUROCs of AUDIT-C in screening alcohol use disorders were 0.902 in the male and 0.939 in the female participants. In the AUDIT and CAGE, the AUROCs were 0.936 and 0.712, respectively, in the male, and 0.960 and 0.844, respectively, in the female participants. The optimal screening scores of alcohol use disorders in AUDIT-C were ≥7 in the male and ≥6 in the female participants; and in AUDIT and CAGE, ≥10 and ≥1, respectively, in the male, and ≥8 and ≥1 in the female participants.
AUDIT-C is considered useful in screening at-risk drinking and alcohol use disorders among college students.
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The prevalence of alcohol use disorder (AUD) is very high in Korea. To identify AUD in the busy practice setting, brevity of screening tools is very important. We derived the brief Alcohol Use Disorders Identification Test (AUDIT) and evaluated its performance as a brief screening test.
One hundred male drinkers from Kangbuk Samsung Hospital primary care outpatient clinic and psychiatric ward for alcoholism treatment completed questionnaires including the AUDIT, cut down, annoyed, guilty, eye-opener (CAGE), and National Alcoholism Screening Test (NAST) from April to July, 2007. AUD (alcohol abuse and dependence), defined by a physician in accordance with Diagnostic and Statistical Manual of Mental Disorders-IV, was used as a diagnostic criteria. To derive the brief AUDIT, factor analysis was performed using the principal component extraction method with a varimax rotated solution. Receiver operating characteristic (ROC) curve analysis was performed to investigate the discrimination ability of the brief AUDIT. Areas under the ROC curve were compared performance of screening questionnaires with 95% confidence intervals.
The derived brief AUDIT consists of 4 items: frequency of heavy drinking (item 3), impaired control over drinking (item 4), increased salience of drinking (item 5), and alcohol-related injury (item 9). Brief AUDIT exhibited an AUD screening accuracy better than CAGE, and equally to that of NAST. Areas under the ROC curves were 0.87 (0.80-0.94), 0.76 (0.66-0.85), and 0.81 (0.73-0.90) for the brief AUDIT, CAGE, and NAST for AUD, and 0.97 (0.95-0.99), 0.93 (0.88-0.98) and 0.93 (0.88-0.98) for alcohol dependence.
The new brief AUDIT seems to be effective in detecting male AUD in the primary care setting in Korea. Further evaluation for women and different age groups is needed.
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Marital status is as an important sociodemographic variable for health studies. We assessed the association between marital status and health behavior in middle-aged Korean adults.
This is a cross-sectional study of 2,522 Korean middle-aged adults (1,049 men, 1,473 women) from the 2010 Korean National Health and Nutrition Examination Survey. The subjects were classified as living with a partner or living without a partner (never married, separated, widowed, and divorced). We assessed the relationship between marital status and five health behaviors (smoking, high-risk alcohol intake, regular exercise, regular breakfast consumption, and undergoing periodic health screening).
Age, income level, educational level, and occupational classification were all significantly associated with marital status. The risk of undergoing health screening (odds ratio [OR], 0.53; 95% confidence interval [CI], 0.32 to 0.90) and having regular breakfast (OR, 0.50; 95% CI, 0.27 to 0.92) were significantly lower in men living without a partner than with a partner. Women living without a partner had a higher smoking risk (OR, 2.27; 95% CI, 1.09 to 4.73) and a higher risk of high-risk alcohol consumption (OR, 5.33; 95% CI, 1.65 to 17.24) than their counterparts.
Korean middle-aged adults living with partners are more likely to have healthier behavior than living without a partner. The association between marital status and health behaviors differed by sex.
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In Korea, few studies have been performed on screening instruments for the detection of at-risk drinking and alcohol use disorders in the elderly. This study evaluated the validity of three screening instruments in elderly male drinkers.
The subjects were 242 Korean men aged ≥ 65 years. Face-to-face interviews were used to identify at-risk drinking and alcohol use disorders. At-risk drinking was defined according to the criteria for heavy or binge drinking of the National Institute on Alcohol Abuse and Alcoholism. Alcohol use disorder was diagnosed using the criteria of the Diagnostic and Statistical Manual of Mental Disorders IV-text revision. The Alcohol Use Disorder Identification Test (AUDIT), Short Michigan Alcoholism Screening Test-geriatric version (SMAST-G), and cut down, annoyed, guilty, eye-opener (CAGE) questionnaire were used as the alcohol-screening instruments. Based on the diagnostic interview results, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of the instruments were compared.
For identification of at-risk drinking, the AUDIT AUROC demonstrated greater diagnostic power than did those of SMAST-G and CAGE (both P < 0.001). In screening for alcohol use disorders, the AUDIT AUROC was also significantly higher than those of SMAST-G and CAGE (both P < 0.001). The sensitivity and specificity of screening for at-risk drinking with an AUDIT score ≥ 7 were 77.3% and 85.1%, respectively, whereas those for the alcohol use disorders with an AUDIT score ≥ 11 were 91.3% and 90.8%, respectively.
The results suggest that the AUDIT is the most effective tool in identifying problem drinkers among elderly male drinkers.
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