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Background: Evidence has accumulated concerning the adverse effects of smoking on hearing acuity, but it is not clear whether smoking modifies the association between exposure to noise and hearing loss. Aims: To examine the synergistic effect of these variables on hearing. Methods: Data used were derived from periodic health examinations for 4624 steel company workers in Japan and included audiometry testing and information on smoking habits. Occupational exposure to noise was determined based on company records. Logistic regression was used to examine the dose-response association between smoking and hearing loss. The Cochran-Mantel-Haenszel method was used to calculate the prevalence rate ratio (PRR) of hearing loss for each combination of smoking and noise exposure factors, taking non-smokers not exposed to occupational noise as a reference. The interaction between smoking and noise exposure was assessed using a synergistic index, which equals 1 when the joint effect is additive. Results: Smoking was associated with increased odds of having high frequency hearing loss in a dose-response manner. The PRR for high frequency hearing loss among smokers exposed to occupational noise was 2.56 (95% CI 2.12 to 3.07), while the PRR for smokers not exposed to noise was 1.57 (95% CI 1.31 to 1.89) and the PRR for non-smokers exposed to noise was 1.77 (95% CI 1.36 to 2.30). The synergistic index was 1.16. Smoking was not associated with low frequency hearing loss. Conclusions: Smoking may be a risk factor for high frequency hearing loss, and its combined effect on hearing with exposure to occupational noise is additive.

Urinary 8-hydroxydeoxyguanosine (8-OH-dG) and 7-methylguanine (m 7 Gua) were measured by a column-switching high performance liquid chromatography method as markers of oxidative and methylating DNA damage, respectively. We investigated the associations between urinary 8-OH-dG or m 7 Gua and various lifestyle and demographic factors, such as age and sex. The urinary 8-OH-dG excretion level was positively correlated with cigarette smoking, but inversely correlated with fruit consumption, physical activity and total energy consumed per day. A multiple regression analysis revealed that daily physical activity and healthy meal combinations decreased the urinary 8-OH-dG level, whereas alcohol consumption increased it. In terms of the urinary m 7 Gua measurement, cigarette smoking, age and consumption of meat, fish, egg, soybean, etc. were positively correlated with the urinary m 7 Gua level, whereas body weight, BMI, physical activity, and dietary index score, which indicates good nutritional balance, were negatively correlated with the amount of m 7 Gua. Based on a multiple regression analysis, cigarette smoking and age correlated with the m 7 Gua level, while high BMI and healthy meal combinations have significant reducing effects on m 7 Gua level. Therefore, the urinary m 7 Gua level is considered to be a useful marker of DNA methylation, not only from smoking, but also from aging and unhealthy dietary habits. (Cancer Sci 2009; 100: 715-721) O xygen radicals are formed in cells by oxygen metabolism and various environmental agents, and they damage DNA, RNA, and proteins.(1) Among the many types of oxidative DNA damage, 8-hydroxydeoxyguanosine (8-OH-dG) is a major product and is frequently analyzed as a marker of cellular oxidative stress related to carcinogenesis, (2,3) because 8-OH-dG induces mutations, (4,5) is excreted in the urine, and it has been analyzed by high performance liquid chromatography-electrochemical detection (HPLC-ECD), (6,7) liquid chromatography-tandem mass spectrometry (LC-MS), (8) gas chromatography-mass spectrometry (GC-MS),and enzyme linked immunosorbent assay (ELISA).(10) However, the reproducibility and accuracy of its measurement are much higher with the HPLC-ECD and LC-MS/MS methods, as compared to the ELISA method. (11,12) We have reported that higher 8-OH-dG levels were observed in the lung DNA of smokers, (13) the liver DNA of chronic hepatitis patients, (14) and in the stomach DNA of patients infected with Helicobacter pylori.(15) It has also been reported that the urinary 8-OH-dG level is higher in cancer patients than in healthy people, (16) higher in smokers than in nonsmokers, (17) and lower in people who exercise moderately. (17) In addition, the urinary 8-OH-dG level was higher in men than in women, (7) and it negatively correlated to body mass index (BMI).(7) As an explanation for the relationship between a lean BMI and high urinary 8-OH-dG excretion, it has been suggested that lean persons have a higher metabolic rate than obese persons, (18) and therefore have higher oxidat...

The prospective association between smoking and hearing loss has not been well studied. To the best of our knowledge, our study is the largest to date investigating the association between smoking and incident hearing loss. Our results indicate that smoking is associated with increased risk of hearing loss in a dose-response manner. Quitting smoking virtually eliminates the excess risk of hearing loss, even among quitters with short duration of cessation. These results suggest that smoking may be a causal factor for hearing loss, although further research would be required to confirm this. If so, this would emphasize the need for tobacco control to prevent or delay the development of hearing loss.

ObjectiveRisk models and scores have been developed to predict incidence of type 2 diabetes in Western populations, but their performance may differ when applied to non-Western populations. We developed and validated a risk score for predicting 3-year incidence of type 2 diabetes in a Japanese population.MethodsParticipants were 37,416 men and women, aged 30 or older, who received periodic health checkup in 2008–2009 in eight companies. Diabetes was defined as fasting plasma glucose (FPG) ≥126 mg/dl, random plasma glucose ≥200 mg/dl, glycated hemoglobin (HbA1c) ≥6.5%, or receiving medical treatment for diabetes. Risk scores on non-invasive and invasive models including FPG and HbA1c were developed using logistic regression in a derivation cohort and validated in the remaining cohort.ResultsThe area under the curve (AUC) for the non-invasive model including age, sex, body mass index, waist circumference, hypertension, and smoking status was 0.717 (95% CI, 0.703–0.731). In the invasive model in which both FPG and HbA1c were added to the non-invasive model, AUC was increased to 0.893 (95% CI, 0.883–0.902). When the risk scores were applied to the validation cohort, AUCs (95% CI) for the non-invasive and invasive model were 0.734 (0.715–0.753) and 0.882 (0.868–0.895), respectively. Participants with a non-invasive score of ≥15 and invasive score of ≥19 were projected to have >20% and >50% risk, respectively, of developing type 2 diabetes within 3 years.ConclusionsThe simple risk score of the non-invasive model might be useful for predicting incident type 2 diabetes, and its predictive performance may be markedly improved by incorporating FPG and HbA1c.