Television Viewing Time and Mortality From Stroke and Coronary Artery Disease Among Japanese Men and Women　– The Japan Collaborative Cohort Study –

Abstract

Background: No study has examined the association between television (TV) viewing time and mortality from stroke and coronary artery disease (CAD) in Japanese.

Methods and Results: A total of 35,959 men and 49,940 women aged 40–79 years without a history of cardiovascular disease (CVD) and cancer were followed from 1988–1990 until 2009. During 19.2 median years of follow-up, there were 2,553 deaths from stroke, 1,206 from CAD and 5,835 from total CVD. Compared with viewing TV for <2 h/day, mortality from stroke, CAD and total CVD were higher for ≥6 h/day of TV viewing. The multivariable hazard ratios (HRs) for ≥6 h/day of TV viewing were 1.15 (95% confidence interval: 0.96–1.37) for stroke, 1.33 (1.03–1.72) for CAD and 1.19 (1.06–1.34) for total CVD. The corresponding HRs for each 1-h/day increment in TV viewing time were 1.01 (0.99–1.04), 1.04 (1.01–1.08) and 1.02 (1.01–1.04), respectively. The excess risk of mortality from CAD and total CVD was somewhat attenuated after further adjustment for potential mediators such as history of hypertension and diabetes: the multivariable HRs for ≥6 h/day of TV viewing were 1.24 (0.96–1.61) and 1.14 (1.02–1.28). The corresponding HRs for each 1-h/day increment in TV viewing time were 1.03 (1.00–1.07) and 1.01 (1.00–1.03).

Conclusions: Prolonged TV viewing was associated with a small but significant increase in mortality from CAD and total CVD in Japanese.

Television (TV) viewing is considered a common leisure-time sedentary behavior in many populations. Between 1995 and 2010, the proportion of people in Japan who spent more than 15 min viewing TV was approximately 90%.¹ Although there were some differences depending on age and sex, the average daily time spent viewing TV in Japan in 2010 was approximately 3–4 h.¹ The average daily time spent viewing TV in the United States was 5 h and 3.5–4 h in European countries and Australia, respectively.² Several recent prospective studies have suggested that TV viewing time is associated with increased mortality from cardiovascular disease (CVD) in American,^3,4 European⁵ and Australian⁶ adults, as well as with an increased risk of all-cause mortality^2–6 and cardiovascular events.^7,8 However, some previous studies showed non-significant associations between TV viewing time and CVD mortality.^9,10 Furthermore, no study has examined the effect of watching TV has on mortality from CVD in a Japanese population. Japanese have a much lower prevalence of overweight and obesity than do Western populations.^11,12 Therefore, we examined the association between TV viewing time and mortality from stroke, coronary artery disease (CAD) and total CVD among Japanese men and women in a large, prospective cohort.

Methods

Study Population

The baseline survey of the Japan Collaborative Cohort Study for Evaluation of Cancer Risk sponsored by Monbusho (JACC Study) was conducted between 1988 and 1990. In total, 110,585 subjects (46,395 men; 64,190 women) from 45 areas throughout Japan were enrolled at baseline.¹³ All non-institutionalized residents aged 40–79 years in communities were invited to participate in the survey. The participation rate was between 86% and 91%. In most regions, informed consent was obtained individually and directly from members of the cohort, while in several areas, informed consent was obtained at the community level after the purpose of the study and confidentiality of the data had been explained to community leaders and mayors. Most of the participants were people who had received a municipal health checkup. Of the 110,585 cohort participants, 5,850 subjects (2,574 men; 3,276 women) who reported a history of CVD and cancer were excluded. We also excluded 18,711 participants (7,815 men; 10,896 women) with missing information on time spent viewing TV and 125 participants (47 men; 78 women) with inappropriate data of TV viewing time (≥12 h). In total, 85,899 participants (35,959 men; 49,940 women) were included in the study (Figure).

Figure.

Flow chart of the selection of participants for the present study of the association between television viewing time and mortality from stroke, coronary artery disease (CAD) and cardiovascular disease (CVD) in Japanese. JACC Study, Japan Collaborative Cohort Study for Evaluation of Cancer Risk.

Mortality Surveillance

For mortality surveillance in each of the communities participating in the study, investigators conducted a systematic review of death certificates, all of which had been forwarded to the public health center in the area of residency. Mortality data were then centralized at the Ministry of Health and Welfare, and the underlying causes of death were coded for the National Vital Statistics according to the 10th revision of the International Classification of Diseases (ICD-10). Therefore, all deaths that occurred in the cohort were ascertained by death certificates at a public health center, with the exception of subjects who died after moving from their original community, in which case such subjects were censored. Cause-specific mortality was determined separately in terms of stroke (ICD-10 codes I60–I69), CAD (I20–I25) and total CVD (I01–I99). Follow-up was believed to be complete and accurate because of systematic examination of death certificates and residency status. By December 31, 2009 (4, 4 and 2 out of 45 areas terminated the follow-up in 1999, 2003 and 2008, respectively), 19,812 subjects were censored because they had died, and 4,882 subjects because they had moved out of the study area. The median follow-up period for the participants was 19.2 years. The study design was approved by the ethics committees of the Nagoya University School of Medicine and Osaka University.

Baseline Survey

The baseline data were collected by means of a self-administered questionnaire, and included information on demographic characteristics, medical history and lifestyle factors, such as smoking, alcohol consumption, diet and physical activity. We obtained the information on the average daily time spent viewing TV during the last year at baseline: ‘On average how many hours do you watch TV?’ The participants reported their time spent viewing TV a day: ‘approximately h/day.’ TV viewing time was then classified into 6 categories: <2 h, 2 h, 3 h, 4 h, 5 h and ≥6 h/day. The assessment of depressive symptoms has been described in detail elsewhere.¹⁴

Statistical Analysis

Statistical analyses were based on mortality rates of stroke, CAD and total CVD during the follow-up period of 1988–1990 to 2009 (4, 4 and 2 out of 45 areas terminated the follow-up in 1999, 2003 and 2008). Person-years of follow-up were calculated as beginning from the date of filling out the baseline questionnaire to time of death, moving out of the area, or the end of the follow-up, whichever came first.

Age- and sex-adjusted mean values and prevalence of cardiovascular risk factors were calculated according to the categories of TV viewing time. Tests for trends were conducted using the median value of each TV viewing time category. Hazard ratios (HRs) with 95% confidence intervals (CIs) for mortality from stroke, CAD and total CVD were calculated with reference to the risk associated with <2 h/day of TV viewing. These estimates were adjusted for age (a continuous variable), sex and other potential confounding factors by using a Cox proportional hazards model. The proportional hazards assumption was examined by log-rank test using lifetest procedure. The other potential confounding factors were included in Model 1: body mass index (BMI) (categorical variables: sex-specific quintiles), smoking status (categorical variables: never, ex-smoker and current smoker), alcohol consumption (categorical variables: non-drinker, ex-drinker, 1–22.9 and ≥23.0 g ethanol/day), hours of exercise (categorical variables: almost never, 1–2, 3–4 and ≥5 h/week), hours of walking (categorical variables: almost never, 0.5, 0.6–0.9, and ≥1 h/day), perceived mental stress (categorical variables: low, moderate, and high), education level (categorical variables: <13, 13–15, 16–18, and ≥19 years), fresh fish intake (categorical variables: almost never, 1–2times/month, 1–2times/week, 3–4times/week and almost every day), sleep duration (categorical variables: ≤4, 5, 6, 7, 8, 9 and ≥10 h/day) and depression symptoms (categorical variables: 0, 1 and ≥2 symptoms). We also adjusted history of hypertension (yes/no) and history of diabetes (yes/no) as potential mediators. All potential confounding factors and mediators were self-reported. The missing data for these confounding factors and mediators were included as categorical variables in the model. Statistical interactions were checked by using cross-product terms of TV viewing time and sex, age, BMI level, hours of exercise and hours of walking on all endpoints. SAS (version 9.4) was used for all statistical analyses. All reported P-values are two-sided, and significance level was set at P<0.05.

Results

Table 1 shows the baseline characteristics of the subjects according to TV viewing time. The respective distribution of <2, 2, 3, 4, 5 and ≥6 h/day of viewing TV was 18.3%, 29.5%, 27.6%, 12.0%, 8.1% and 4.5%, respectively. Compared with participants reporting <2 h/day TV viewing, those reporting ≥6 h/day tended to be older, smokers, unemployed and have a higher mean BMI, and were more likely to have depressive symptoms and a history of hypertension and diabetes, and were less likely to have perceived mental stress.

Table 1. Age- and Sex-Adjusted Baseline Characteristics According to TV Viewing Time

	TV viewing time (h/day)						P for trend
	<2	2	3	4	5	≥6
n	15,705	25,316	23,745	10,330	6,947	3,856
Men, %	41.5	45.0	44.2	39.3	33.9	29.9	<0.001
Age, years	55.3	56.1	57.4	58.7	61.1	63.1	<0.001
Mean BMI, kg/m2	22.5	22.7	22.9	22.9	23.2	23.1	<0.001
Current smoker, %	23.2	25.5	27.3	29.1	30.2	33.7	<0.001
Ethanol intake, g/day	28.7	29.3	28.3	28.5	29.0	30.8	0.75
College or higher education, %	16.8	13.7	11.9	11.8	10.8	12.1	<0.001
Exercise ≥5 h/week, %	6.1	6.2	5.4	5.3	5.8	4.2	<0.001
Walking ≥1 h/day, %	52.6	52.9	52.3	48.3	45.5	38.7	<0.001
High stress, %	25.5	21.6	19.6	18.6	18.8	21.4	<0.001
Sleep duration, h/day	7.21	7.27	7.29	7.26	7.27	7.26	<0.001
Unemployed, %	16.9	16.5	17.5	20.3	26.2	32.0	<0.001
Fresh fish intake, times/day	7.0	7.1	7.0	7.0	6.8	6.8	<0.001
History of hypertension, %	19.6	21.1	22.1	22.3	25.4	25.2	<0.001
History of diabetes, %	4.6	4.4	5.0	5.6	6.3	8.5	<0.001
Depressive symptoms ≥2, %	7.2	6.0	6.5	7.2	8.6	11.7	<0.001

BMI, body mass index; TV, television.

During 1,398,591 person-years of follow-up, 2,553 deaths from stroke (1,302 men; 1,251 women), 1,206 deaths from CAD (692 men; 514 women) and 5,835 deaths from total CVD (3,002 men; 2,833 women) occurred.

Table 2 shows the age- and sex-adjusted and multivariable HRs (95% CI) of mortality from stroke, CAD and total CVD according to TV viewing time. Compared with <2 h/day of TV viewing, ≥6 h/day of TV viewing was associated with increased age and sex-adjusted mortality from stroke, CAD and total CVD. After adjustment for CVD factors (Model 1), persons with TV viewing ≥6 h/day had higher mortality from CAD and total CVD: the multivariable HR was 1.33 (95% CI, 1.03–1.72) for CAD and 1.19 (95% CI, 1.06–1.34) for total CVD. The corresponding HRs for each 1-h increment in TV viewing time were 1.04 (95% CI, 1.01–1.08) and 1.02 (95% CI, 1.01–1.04). After further adjustment for the potential mediators (Model 2), the association of mortality from CAD was attenuated but that from total CVD remained statistically significant: the multivariable HRs for TV viewing ≥6 h/day vs. <2 h/day were 1.24 (95% CI, 0.96–1.61) for CAD and 1.14 (95% CI, 1.02–1.28) for total CVD. The corresponding HRs for each 1-h/day increment in TV viewing time were 1.03 (95% CI, 1.00–1.07) and 1.01 (95% CI, 1.00–1.03), respectively.

Table 2. HRs and 95% CIs of Mortality From Stroke, CAD and Total CVD According to TV Viewing Time

	TV viewing time (h/day)						HR for 1-h increment in TV viewing time	P for trend
	<2	2	3	4	5	≥6
Person-years	263,523	423,216	389,032	164,898	104,402	53,520
Stroke
No. of deaths	404	705	698	294	275	177
Age, sex-adjusted HR	1.00	1.04 (0.92–1.17)	0.99 (0.87–1.11)	0.89 (0.77–1.03)	1.12 (0.96–1.30)	1.20 (1.00–1.43)	1.02 (1.00–1.04)	0.25
Model 1	1.00	1.07 (0.95–1.21)	1.00 (0.88–1.13)	0.91 (0.78–1.06)	1.09 (0.93–1.27)	1.15 (0.96–1.37)	1.01 (0.99–1.04)	0.60
Model 2	1.00	1.06 (0.93–1.19)	0.98 (0.87–1.11)	0.89 (0.76–1.03)	1.06 (0.90–1.23)	1.10 (0.92–1.32)	1.01 (0.98–1.03)	0.97
CAD
No. of deaths	181	320	313	158	140	94
Age, sex-adjusted HR	1.00	1.04 (0.87–1.25)	0.99 (0.82–1.19)	1.09 (0.88–1.35)	1.34 (1.08–1.68)	1.56 (1.21–2.00)	1.07 (1.03–1.11)	<0.001
Model 1	1.00	1.03 (0.85–1.23)	0.94 (0.78–1.13)	1.03 (0.83–1.28)	1.20 (0.96–1.50)	1.33 (1.03–1.72)	1.04 (1.01–1.08)	0.02
Model 2	1.00	1.01 (0.84–1.21)	0.92 (0.77–1.11)	1.00 (0.81–1.24)	1.16 (0.92–1.45)	1.24 (0.96–1.61)	1.03 (1.00–1.07)	0.08
Total CVD
No. of deaths	923	1,538	1,576	741	625	432
Age, sex-adjusted HR	1.00	0.99 (0.91–1.07)	0.97 (0.90–1.06)	0.98 (0.89–1.08)	1.12 (1.01–1.24)	1.29 (1.15–1.45)	1.04 (1.02–1.05)	<0.001
Model 1	1.00	1.01 (0.93–1.09)	0.97 (0.89–1.05)	0.98 (0.89–1.08)	1.06 (0.96–1.18)	1.19 (1.06–1.34)	1.02 (1.01–1.04)	0.02
Model 2	1.00	1.00 (0.92–1.08)	0.95 (0.88–1.04)	0.96 (0.87–1.05)	1.03 (0.93–1.14)	1.14 (1.02–1.28)	1.01 (1.00–1.03)	0.14

Model 1: adjusted further for BMI, smoking, ethanol intake, education level, hours of sport, hours of walking, sleep duration, perceived mental stress, presence of job, frequency of fresh fish intake and depressive symptoms. Model 2: adjusted further for histories of hypertension and diabetes. CI, confidence interval; CAD, coronary artery disease; CVD, cardiovascular disease; HR, hazard ratio. Other abbreviations as in Table 1.

There was no significant interaction by sex, age, hours of walking and exercise, and BMI levels on the associations.

Discussion

In this large, prospective population-based cohort study of Japanese men and women, we observed that ≥6 h/day of TV viewing was associated with increased risk of mortality from CAD and total CVD. Each 1-h/day increment in TV viewing was associated with 4% increment in risk of mortality from CAD and 2% increment in risk of mortality from total CVD.

To our knowledge, this is the first study to show that longer TV viewing time may contribute to the increased mortality from CVD in Japanese. As shown in Table 3, the NIH-AARP Diet and Health Study of 24,0819 men and women aged 50–71 years suggested that, relative to <1 h/day, 3–4 h/day, 5–6 h/day and ≥7 h/day of viewing TV was associated with 15%, 36% and 85% greater risk of mortality from CVD, respectively, with similar risk in both sexes.³ The excess risk of mortality from CVD for ≥7 h/day of TV viewing remained, even among subjects with >7 h/week of moderate to vigorous physical activity (multivariable HR 2.00; 95% CI, 1.33–3.00). In the Multiethnic Cohort Study of 61,395 men and 73,201 women aged 45–75 years, the risk of mortality from CVD for ≥5 h/day of TV viewing was 20% higher in men and 33% higher in women compared with <1 h/day of TV viewing.⁴ The European Prospective Investigation into Cancer and Nutrition Norfolk Study of 5,729 men and 7,468 women suggested that each 1-h/day increment in time spent viewing TV was associated with an 8% increase in mortality from CVD.⁵ The Australian Diabetes, Obesity, and Lifestyle Study of 8800 men and women aged ≥25 years also reported that ≥4 h/day of TV viewing had an 80% increased risk of mortality from CVD compared with <2 h/day of TV viewing.⁶

Table 3. Summary of Studies on the Association Between TV Viewing Time and CVD

Reference	n	Age (years)	Duration of follow-up (years)	No. of CVD cases	HR (95% CI)	Adjustment factors
Warren et al, 20109	7,744 men	20–89	21	377 deaths	Q1 (<4 h/w): 1.00	Age, physical activity, smoking, alcohol intake, BMI, family history of CVD, hypertension, diabetes, and hypercholestrolemia
					Q2 (4–8 h/w): 1.02 (0.74–1.42)
					Q3 (8–12 h/w): 1.27 (0.90–1.78)
					Q4 (>12 h/w): 0.96 (0.68–1.36)
Dunstan et al, 20106	8,800 men and women	≥25	6.6 (median)	87 deaths	<2 h/day: 1.00	Age, sex, smoking, alcohol intake, education, total energy intake, Diet Quality Index, waist circumference, hypertension, total cholesterol, HDL-cholesterol, triglycerides, lipid-lowering medication use, glucose tolerance status, exercise time
					≥2–<4 h/day: 1.19 (0.72–1.99)
					≥4 h/day: 1.80 (1.00–3.25)
Wijndaele et al, 20115	13,197 men and women	Average: 61.5	9.5	373 deaths	per h/day: 1.08 (1.01–1.16)	Age, sex, education, smoking status, alcohol consumption, hypertension medication use, dyslipidemia medication use, history of diabetes, family histories of CVD and cancer, physical activity
					per h/day: 1.07 (0.99–1.15)	Adjusted further for waist circumference
Matthews et al, 20123	240,819 men and women	50–71	8.5	4,684 deaths	<1 h/day: 1.00	Age, sex, race, education, smoking, diet quality, moderate-vigorous physical activity
					1–2 h/day: 1.00 (0.86–1.16)
					3–4 h/day: 1.15 (1.00–1.33)
					5–6 h/day: 1.36 (1.17–1.59)
					≥7 h/day: 1.85 (1.56–2.20)
Kim et al, 20134	61,395 men	45–75	13.7 (median)	Men: 3,721 deaths	<1 h/day: 1.00	Age, race/ethnicity, education, smoking history, histories of diabetes and hypertension, energy intake, alcohol intake, physical activity, other sitting duration
					1–4 h/day: 0.99 (0.89–1.10)
					≥5 h/day: 1.20 (1.05–1.37)
	73,201 women			Women: 2,814 deaths	<1 h/day: 1.00
					1–4 h/day: 1.02 (0.90–1.15)
					≥5 h/day: 1.33 (1.14–1.55)
Ford et al, 201210	7,350 men and women	≥20	5.8 (median)	190 deaths	<1 h/day: 1.00	Age, sex, race/ethnicity, education, smoking, leisure-time physical activity, Healthy Eating Index score, alcohol consumption, health status and health insurance coverage, histories of diabetes, CVD and cancer
					1 h/day: 1.35 (0.59–3.07)
					2 h/day: 0.83 (0.42–1.64)
					3 h/day: 1.50 (0.65–3.46)
					4 h/day: 0.88 (0.38–2.05)
					≥5 h/day: 1.14 (0.51–2.54)
					per 1 h/day: 1.01 (0.88–1.15)
Stamatakis et al, 20117	4,512 men and women	≥35	4.3	215 events	<2 h/day: 1.00	Age, sex, ethnicity, BMI, smoking, social class, long-standing illness, marital status, occupational physical activity, hypertension, diabetes, moderate-vigorous physical activity
					2–<4 h/day: 2.23 (1.31–3.80)
					≥4 h/day: 2.25 (1.30–3.89)
Wijndaele et al, 20118	12,608 men and women	Average: 61.4	6.9	2,620 events	per h/day: 1.06 (1.03–1.08)	Age, sex, education, smoking status, alcohol consumption, medications for hypertension, dyslipidemia and depression, diabetes, family history of CVD, sleep duration, physical activity

HDL, high-density lipoprotein. Other abbreviations as in Tables 1,2.

Longer TV viewing time, or sedentary behavior, has been linked to CVD risk factors in adults, such as obesity,^15,16 adverse cardiometabolic biomarkers,^16–21 increased insulin resistance,^22,23 type 2 diabetes^2,15,24 and increased blood pressure.^16,17,20 In the present study, time spent viewing TV was associated with higher BMI, prevalent type 2 diabetes and hypertension at baseline. Also, our finding suggest that the association between TV viewing time and mortality from CVD may be mediated partly by hypertension and diabetes because the adjustment for these potential mediators attenuated the association substantially. Some previous studies showed the greater HR of incident or fatal CVD associated with TV viewing time compared with that in the present study.^3,6,7 Matthews et al³ reported that TV viewing of ≥7 h/day was associated with 85% greater risk of mortality from CVD. In that study, however, the HR was attenuated after adjustment for BMI: HR 1.63 (95% CI, 1.37–1.93). The findings reported by Dunstan et al⁶ and Stamatakis et al⁷ were derived from data for a small number of participants and with a short follow-up.

The strengths of the present study were its prospective design and the large population size, which enabled detection of associations between TV viewing time and mortality from stroke, CAD, and total CVD. The findings of the present study can be generalized, because our subjects were enrolled from the Japanese general population.

Study Limitations

First, some misclassification might have been caused by the fact that TV viewing time was self-reported. However, a review has shown that the reliability of self-reported TV viewing time is consistently moderate to high.²⁵ Second, although we adjusted for major cardiovascular risk factors, potential confounding by unmeasured factors might still remain. Prospective cohort studies have suggested that prolonged TV viewing is indicative of adverse mental health.^26,27 Although we included perceived mental stress and depressive symptoms, the significant associations remained. Finally, the mortality data may be liable to misclassification in the diagnosis of stroke and CAD. However, the widespread use of computer tomography in local hospitals since the 1980 s has probably made the diagnosis of stroke and its subtypes reported on death certificates sufficiently accurate.^28,29 For CAD, however, validation studies have shown that approximately one-quarter of deaths from ischemic heart disease as recorded on death certificates were misdiagnosed.^30,31 Therefore, the association between time spent viewing TV and mortality from ischemic heart disease may be diluted, and the real association could be stronger.

Conclusions

Our findings suggested that prolonged TV viewing may lead to a small but significant increase in mortality from CAD and total CVD in Japanese men and women.

Acknowledgments

The authors thank all staff members involved in this study for their valuable help in conducting the baseline survey and follow-up. This study was supported by Grants-in-aid for Scientific Research from the Ministry of Education, Science, Sports and Culture of Japan, Grants-in-Aid for Scientific Research on Priority Areas of Cancer, as well as Grants-in-Aid for Scientific Research on Priority Areas of Cancer Epidemiology from the Japanese Ministry of Education, Culture, Sports, Science and Technology: 61010076, 62010074, 63010074, 1010068, 2151065, 3151064, 4151063, 5151069, 6279102, 11181101, 17015022, 18014011, 20014026 and 20390156, and Comprehensive Research on Cardiovascular and Life-Style Related Diseases: H26-Junkankitou [Seisaku]-Ippan-001.

Disclosures

None.

Appendix

Dr Akiko Tamakoshi (present chairperson of the study group), Hokkaido University; Drs Mitsuru Mori & Fumio Sakauchi, Sapporo Medical University School of Medicine; Dr Yutaka Motohashi, Akita University School of Medicine; Dr Ichiro Tsuji, Tohoku University Graduate School of Medicine; Dr Yosikazu Nakamura, Jichi Medical School; Dr Hiroyasu Iso, Osaka University School of Medicine; Dr Haruo Mikami, Chiba Cancer Center; Dr Michiko Kurosawa, Juntendo University School of Medicine; Dr Yoshiharu Hoshiyama, University of Human Arts and Sciences; Dr Naohito Tanabe, Niigata University School of Medicine; Dr Koji Tamakoshi, Nagoya University Graduate School of Health Science; Dr Kenji Wakai, Nagoya University Graduate School of Medicine; Dr Shinkan Tokudome, National Institute of Health and Nutrition; Dr Koji Suzuki, Fujita Health University School of Health Sciences; Dr Shuji Hashimoto, Fujita Health University School of Medicine; Dr Shogo Kikuchi, Aichi Medical University School of Medicine; Dr Yasuhiko Wada, Faculty of Human Life and Environmental Science, Kochi Women’s University; Dr Takashi Kawamura, Kyoto University Center for Student Health; Dr Yoshiyuki Watanabe, Kyoto Prefectural University of Medicine Graduate School of Medical Science; Dr Kotaro Ozasa, Radiation Effects Research Foundation; Dr Tsuneharu Miki, Kyoto Prefectural University of Medicine Graduate School of Medical Science; Dr Chigusa Date, Faculty of Human Environmental Sciences, Nara Women’s University; Dr Kiyomi Sakata, Iwate Medical University; Dr Yoichi Kurozawa, Tottori University Faculty of Medicine; Dr Takesumi Yoshimura, Fukuoka Institute of Health and Environmental Sciences; Dr Yoshihisa Fujino, University of Occupational and Environmental Health; Dr Akira Shibata, Kurume University School of Medicine; Dr Naoyuki Okamoto, Kanagawa Cancer Center; and Dr Hideo Shio, Moriyama Municipal Hospital.

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