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A nationwide cohort study of educational background and major causes of death among the elderly population in Japan
Preventive Medicine 40 (2005) 444 – 451 www.elsevier.com/locate/ypmed
A nationwide cohort study of educational background and major causes of death among the elderly population in Japan Yoshihisa Fujino, M.D., Ph.D.a,*, Akiko Tamakoshi, M.D., Ph.D.b, Hiroyasu Iso, M.D., Ph.D.c, Yutaka Inaba, M.D., Ph.D.d, Tatsuhiko Kubo, M.D.a, Reiko Ide, D.D.S., Ph.D.a, Ai Ikeda, M.S.W., M.P.H.c, Takesumi Yoshimura, M.D., M.P.H., Ph.D.a for the JACC study group1 a
Department of Clinical Epidemiology, Institute of Industrial Ecological Science, University of Occupational and Environmental Health, Kitakyushu, Japan b Department of Preventive Medicine/Biostatistics and Medical Decision Making, Field of Social Life Science, Program in Health and Community Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan c Department of Public Health Medicine, Institute of Community Medicine, University of Tsukuba, Tsukuba, Japan d Department of Epidemiology and Environmental Health, Juntendo University School of Medicine, Tokyo, Japan Available online 21 August 2004
Abstract Background. This prospective cohort study examined the association between educational level and major causes of death in Japan. Method. A baseline survey was conducted between 1988 and 1990 among 110,792 inhabitants of 45 areas aged 40–79 years. Follow-up surveys were conducted annually and causes of death were identified from death certificates. The analysis was restricted to 16,715 men and 23,284 women. Results. During the follow-up period (377,139 person-years), 6628 deaths were recorded. Individuals with low levels of education had an increased overall risk of death [relative risk (RR) = 1.16, 95% confidence interval (CI): 1.08, 1.25, in men; RR = 1.26, 95% CI: 1.14, 1.39, in women], cancers (RR = 1.17, 95% CI: 1.04, 1.32, in men; RR = 1.10, 95% CI: 0.93, 1.30, in women), and death from external causes (RR = 1.81, 95% CI: 1.29. 2.54, in men; RR = 1.78, 95% CI: 1.18, 2.70, in women). Ischemic heart disease risk was marginally reduced in men with low levels of education (RR = 0.77, 95% CI: 0.58, 1.01). Conclusions. These results show that health inequalities exist in Japan, even though wealth inequalities are relatively low. Social and political initiatives will be needed to correct these inequities between different socioeconomic statuses. D 2004 The Institute For Cancer Prevention and Elsevier Inc. All rights reserved. Keywords: Japan; Prospective study; Education; Socioeconomic determinants of health; Mortality; Cancer; Coronary heart disease; External death
Introduction Socioeconomic status is commonly used as a proxy for environmental and lifestyle factors that relate to health * Corresponding author. Department of Clinical Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, 1-1, Iseigaoka, Yahatanishiku, Kitakyushu 8078555, Japan. Fax: +81 93 603 0158. E-mail address: [email protected] (Y. Fujino). 1 See acknowledgments for the investigators (name and affiliation) involved in the JACC Study.
status [1]. This approach initially attempted to identify biological causal relationships between environmental factors, lifestyle factors, and diseases. However, socioeconomic status has recently been recognized as a determinant of health, which is of relevance to the design of prevention strategies and health policies. Occupation, income, and education are often used as indices of socioeconomic status. However, previous reports have consistently shown that members of the higher socioeconomic group have better health status, regardless of the values of these indices [2–5].
0091-7435/$ - see front matter D 2004 The Institute For Cancer Prevention and Elsevier Inc. All rights reserved. doi:10.1016/j.ypmed.2004.07.002
Y. Fujino et al. / Preventive Medicine 40 (2005) 444–451
The primary example of health inequalities between socioeconomic groups is the contrast between rich and poor countries. There is a clear relationship between gross national product per capita and life expectancy [6]. The main reason for this trend is the direct association of poverty with malnutrition and infectious diseases, which results in a high burden of maternal, infant, and childhood diseases in poorer countries. However, even in developed countries in which infectious diseases are not dominant, chronic diseases and external causes of death are related to socioeconomic status [7]. Japan is one of the most affluent countries in terms of gross national income per capita and has the longest healthy life expectancy in the world [8]. In addition, wealth inequalities in Japan are thought to be lower than in other developed countries [6]. However, to our knowledge, few studies have examined the association between socioeconomic and health status in Japan. Therefore, it is of great importance to determine the impact of socioeconomic status on health among the Japanese population. This large cohort study, which involved a representative sample of the Japanese population from across the country, examined the association between educational level and the major causes of death in Japan.
Methods The Japan Collaborative Cohort Study for the Evaluation of Cancer Risk (JACC Study) is sponsored by the Ministry of Education, Science, Sports and Culture of Japan. The details of this cohort study have been described previously [9–12]. Briefly, a baseline survey was conducted between 1988 and 1990. The JACC study enrolled 127,477 apparently healthy inhabitants in these areas with completion of the questionnaire. Of 127,477 enrolled, 110,792 (46,465 men and 64,327 women), aged 40–79 years, were followed up. Twenty-four institutions from across the country participated in the study. The subjects answered a questionnaire concerning health-related lifestyle choices including smoking, alcohol consumption, occupation, diet, and medical history. Follow-up surveys were conducted annually to determine the vital status of the participants. For deceased subjects, the cause of death was recorded from the official death certificate held at the relevant regional health center and was classified according to the International Classification of Disease, 10th Revision (ICD-10). The present analysis also included follow-up data collected before 1999. The informed consent procedures were approved by the Ethics Committee of Medical Care and Research, University of Occupational and Environmental Health, Kitakyushu, Japan, and the Ethical Board of the Nagoya University School of Medicine, Japan. Causes of death were defined according to the ICD-10 classification as follows: cancer, C00-C97; respiratory system diseases, J00-J99; circulatory system diseases, I01–
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I51, I20–I25, and I60–I69: ischemic heart disease, I20–I25; cerebrovascular disease, I60–I69; respiratory system diseases, J00–J99; infectious/parasitic diseases, A00–B99; and injuries, poisoning, and other lesions from external causes, S00–T98. Data retrieval for analysis Four institutes involved the JACC study, which used a slightly different version of the questionnaire, did not ask educational level and then the subjects in these areas were excluded. Then, of 88,344 subjects, the 16,715 men (153,184 person-years) and 23,284 women (223,955 person-years) who were aged 18 years or above in 1949 were used for the analyses. This year was chosen as the Japanese educational system underwent significant changes after 1949, following World War II. A total of 6628 deaths (3,948 men and 2680 women) were identified among the subjects during the follow-up period. Educational background and covariates The subjects were assigned to three groups according to their level of education: those who attended school beyond the age of 18 years (high); those who attended school until the age of 16–17 years (intermediate); and those who attended school until the age of 15 years or below (low). Before 1949, it was not possible to classify schools into levels such as bprimary school,Q bjunior high school,Q and bhigh schoolQ as an index of educational level, as the Japanese educational system was highly complex and inconsistent. Furthermore, skipping grades and leaving school early were common before this date. The following additional baseline characteristics that might potentially be related to mortality were also considered: age (continuous variable); smoking status (never smoked, previous smoker, or current smoker); alcohol consumption (current habitual drinker, previous habitual drinker, or teetotaler); job status (employed, self-employed, or other); and type of job (office worker, manual worker, or other). Statistical analysis Cox proportional hazards regression analysis [13] was used to estimate the sex-specific relative risk (RR) of educational level for each of the major causes of death, adjusting for the potential confounding factors listed above. All calculations were performed using the SAS statistical software program [14].
Results Table 1 lists selected baseline characteristics of the study subjects by sex and educational background. Sub-
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jects of both sexes who were educated to a high level were less likely to smoke cigarettes and more likely to consume alcohol. Office workers were more common in the highly educated group than in the group with a low level of education. Tables 2 and 3 show that individuals of both sexes with a low level of education had an increased overall risk of death [RR = 1.16, 95% confidence interval (CI): 1.08, 1.25, in men; RR = 1.26, 95% CI: 1.14, 1.39, in women], as well as increased risks of cancer (RR = 1.17, 95% CI: 1.04, 1.32, in men), cerebrovascular disease (RR = 1.23, 95% CI: 1.01, 1.50, in men; RR = 1.44, 95% CI: 1.13, 1.83, in women), and death from external causes (RR = 1.81, 95% CI: 1.29. 2.54, in men; RR = 1.78, 95% CI: 1.18, 2.70, in women), compared with individuals with the high level of education. The risk of respiratory diseases in men (RR = 1.23, 95% CI: 1.01, 1.50) and the risk of circulatory system diseases in women (RR = 1.27, 95% CI: 1.08, 1.50) were also greater in the low education group than in the high education group. In men, the risk for ischemic heart disease showed a marginal decrease in the group with the low level of education compared with the group with the high level of education, although this was not statistically significant (RR = 0.77, 95% CI: 0.58, 1.01, P = 0.063). Similar results were obtained when the analysis was repeated after adjusting for smoking, alcohol, job status, and job type. We further analyzed the risk of the subjects who attended school below 12 years. Only 685 of 16,175 men and 1944 of 23,284 women attended school below 12 years, and the risk for total death was 1.32 (95% CI; 1.14, 1.52, P = 0.0002) in men and 1.53 (95% CI;.1.34, 1.75, P b 0.0001) in women compared with people who attended school 18 years or over.
Discussion Wealth inequality in Japan is lower than in other developed countries according to the Gini coefficient [15]. This coefficient is a measure of the income inequality in a society, the values of which range between 0 and 1, where 0 indicates perfect equality (that is, everybody has the same income) and 1 indicates perfect inequality (that is, one individual has all of the income and everybody else earns nothing). The World Development Report [8] listed the following Gini coefficients: 0.25 for Japan (1993), 0.36 for the United Kingdom (1995), and 0.41 for the United States (1997). Inequalities of wealth are a significant predictor of differences in life expectancy between countries [16]. In fact, the life expectancy at birth in Japan was reported to be the highest in the world in 2002, with a value of 81 years [8]. Great inequalities of wealth are linked to broader health outcomes, and theoretical models suggest that reducing the disparities in wealth distribution within a society improves the mean life expectancy [16,17]. The present study clearly showed that, even in Japan, the risk of death from most major causes is strongly related to socioeconomic status, which was measured here using educational level. However, the inequalities in health in this study were relatively small in magnitude compared with previous studies in other developed countries. This might be partly due to fewer inequalities in educational levels within the present subjects; about one half of the subjects were in the lowest education category. Kunst [18] reported substantial differences between countries in the size of the inequalities in mortality risk that are associated with educational level. This variation can be partly attributed to the inequalities in education that exist in some countries.
Table 1 Selected baseline characteristics according to educational background by sex Educational background (age) Male
n Person-year Mean age (SD) Smoking (%) Current Past Never Alcohol (%) Current Past Never Job status (%) Employed Self-employed Type of job (%) Office work Manual work
Female
V15
16–17
z18
V15
16–17
z18
7485 67,533 66.5 (5.7)
3834 35,540 65.5 (5.6)
5396 50,111 65.8 (5.7)
11,175 106,525 66.8 (5.7)
6230 60,362 65.4 (5.4)
5879 57,067 65.5 (5.4)
48.3 28.2 17.7
47.2 30.9 16.4
43.4 35.5 16.6
4.7 1.9 80.5
3.5 1.5 78.3
3.0 1.6 81.3
64.2 8.8 22.2
67.2 8.1 19.5
67.9 8.6 18.4
16.4 1.8 73.1
19.7 1.7 69.3
20.6 1.6 70.1
11.7 29.4
15.1 33.8
18.7 32.3
3.2 11.1
3.6 12.9
3.8 12.3
2.3 28.8
6.6 28.5
14.3 20.7
0.7 12.3
1.9 9.7
3.6 7.5
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Table 2 The RRs of educational background for each cause of death in males Educational background (age) 16–17
V15
Total death No. of cases = 3948 Age-adjusted RR Multivariate RRb Cancer No. of cases = 1508 Age-adjusted RR Multivariate RRb Circulatory system diseases No. of cases = 1175 Age-adjusted RR Multivariate RRb Ischemic heart disease No. of cases = 256 Age-adjusted RR Multivariate RRb Cerebrovascular disease No. of cases = 534 Age-adjusted RR Multivariate RRb Respiratory system diseases No. of cases = 551 Age-adjusted RR Multivariate RRb Infectious diseases No. of cases = 66 Age-adjusted RR Multivariate RRb External causes No. of cases = 215 Age-adjusted RR Multivariate RRb a b
RRa
95% CI
P
RRa
95% CI
P
1.16 1.14
1.08, 1.25 1.05, 1.22
b0.001 b0.001
1.06 1.06
0.97, 1.16 0.97, 1.16
0.184 0.201
1.17 1.15
1.04, 1.32 1.02, 1.29
0.008 0.026
1.06 1.05
0.92, 1.22 0.91, 1.21
0.437 0.520
1.06 1.04
0.93, 1.21 0.91, 1.19
0.430 0.581
1.01 1.01
0.86, 1.18 0.86, 1.19
0.923 0.881
0.77 0.77
0.58, 1.01 0.58, 1.02
0.063 0.068
0.90 0.90
0.65, 1.24 0.65, 1.25
0.507 0.541
1.23 1.20
1.01, 1.50 0.98, 1.46
0.044 0.082
1.05 1.05
0.82, 1.34 0.82, 1.34
0.713 0.698
1.23 1.21
1.01, 1.50 0.99, 1.47
0.041 0.067
1.15 1.15
0.90, 1.46 0.91, 1.47
0.266 0.243
0.72 0.71
0.41, 1.24 0.41, 1.24
0.233 0.232
0.86 0.87
0.46, 1.64 0.46, 1.65
0.655 0.669
1.81 1.75
1.29. 2.54 1.24, 2.47
b0.001 0.001
1.49 1.47
1.00, 2.23 0.98, 2.19
0.049 0.063
The reference group attended school beyond the age of 18 years. The model included age, smoking, alcohol, job status, and job type.
Previous studies in western countries have consistently revealed that a lower level of education is associated with an increased risk of ischemic heart disease [19–25]. However, in the present study, men in the low education group showed a marginal decrease in the risk of ischemic heart disease. This inconsistency might partly be a result of differences between Japan and other countries in the association between socioeconomic status and risk factors for ischemic heart disease. Martikainen et al. [26] compared socioeconomic differences in behavioral and biomedical risk factors in a Japanese and English cohort of middle-aged men. They found that more highly educated men in Japan had lower high-density lipoprotein cholesterol (HDL) levels, higher body mass indices (BMI), and higher waist-to-hip ratios than less educated men; however, the opposite associations were found among men in England. These results were backed up by another study in Japan [27], which confirmed that individuals with a higher level of education were more likely to be obese and sedentary.
This highlights an issue that arises in all studies examining the association between socioeconomic status and health: The magnitude and direction of health inequalities differ between health outcomes, even within the same society. This can bias results if the exact health outcome is not specified, as in the case of analyzing ball mortality.Q Opposite trends, such as that observed in ischemic heart disease in the present study, can mask the true magnitude of inequalities in health. In this study, the overall RR for death from all causes in men was 1.19 (95% CI: 1.10, 1.28) when the subjects who died from ischemic heart disease were excluded (data not shown); this value was 3% higher than before the data were excluded despite the fact that the number of deaths from ischemic heart disease was only 6% of the total number of deaths in the study population. Although our study did not aim to identify the causality between educational level and health outcomes, our findings have several implications. As noted previously [28,29], the association between socioeconomic status and health might be the result of a mixture of biological, lifestyle behavioral,
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Table 3 The RRs of educational background for each cause of death in females Educational background (age) 16–17
V15
Total death No. of cases = 2680 Age-adjusted RR Multivariate RRb Cancer No. of cases = 868 Age-adjusted RR Multivariate RRb Circulatory system diseases No. of cases = 992 Age-adjusted RR Multivariate RRb Ischemic heart disease No. of cases = 183 Age-adjusted RR Multivariate RRb Cerebrovascular disease No. of cases = 464 Age-adjusted RR Multivariate RRb Respiratory system diseases No. of cases = 231 Age-adjusted RR Multivariate RRb Infectious diseases No. of cases = 50 Age-adjusted RR Multivariate RRb External causes No. of cases = 170 Age-adjusted RR Multivariate RRb a b
RRa
95% CI
P
RRa
95% CI
P
1.26 1.23
1.14, 1.39 1.12, 1.36
b0.001 b0.001
1.04 1.03
0.92, 1.16 0.92, 1.15
0.543 0.635
1.10 1.09
0.93, 1.30 0.92, 1.29
0.280 0.329
1.02 1.02
0.84, 1.23 0.84, 1.24
0.867 0.822
1.27 1.23
1.08, 1.50 1.04, 1.44
0.003 0.013
1.05 1.03
0.87, 1.27 0.85, 1.25
0.619 0.743
1.01 1.01
0.71, 1.44 0.70, 1.44
0.959 0.974
0.84 0.84
0.54, 1.30 0.54, 1.30
0.428 0.435
1.44 1.38
1.13, 1.83 1.08, 1.75
0.003 0.009
1.03 1.01
0.77, 1.38 0.75, 1.35
0.830 0.953
1.10 1.10
0.84, 1.60 0.80, 1.52
0.363 0.550
0.78 0.78
0.53, 1.18 0.52, 1.17
0.252 0.225
1.23 1.21
0.59, 2.56 0.58, 2.54
0.579 0.607
1.35 1.33
0.60, 3.04 0.50, 3.01
0.471 0.487
1.78 1.83
1.18, 2.70 1.21, 2.77
0.006 0.004
1.18 1.17
0.72, 1.92 0.72, 1.91
0.510 0.533
The reference group attended school beyond the age of 18 years. The model included age, smoking, alcohol, job status, and job type.
environmental, and social factors rather than having one single cause. For example, differences in access to health care or health resources between different socioeconomic statuses might partly explain the overall results of the present study but are unlikely to have influenced ischemic heart disease. Lifestyle behaviors, including smoking, alcohol consumption, and diet, might also affect the differences in the risk of some causes of death, particularly cardiovascular disease and cancers; however, these factors are unlikely to explain the association between educational levels and external causes of death, which have less biological links with socioeconomic status. For each of the major causes of death analyzed, the ageadjusted RRs were similar to the multivariate RRs, which were adjusted for smoking, alcohol, job type, and job status. Although smoking generally has strong effects on health outcomes, particularly cancers and cardiovascular disease, it did not have an obvious confounding effect in the present study. The analysis might have failed to adjust for some other confounding factors, such as diet; however, the effects
of these factors are likely to be related to an individual’s level of exposure and therefore might not strongly influence the association between socioeconomic status and health. We previously reported [12] that educational level was associated with the risk of stomach cancer in Japan. Adjusting the analysis for smoking, alcohol, and dietary factors—including intake of salty foods, green tea, vegetables, and fruit, which are all thought to be strongly associated with stomach cancer—had little effect on the result: The more highly educated group showed a consistent decrease in the risk of stomach cancer (age-adjusted RR = 0.73; multivariate RR = 0.72). Perhaps more important for the association between socioeconomic status and health are ecological level characteristics [30,31]. Berkman [31] revealed that crucial ecological level factors that are related to the social environment are not adequately captured by investigations at an individual level. For example, the social and economic characteristics of a community influence local access to goods and services, the environment, the level of residential stability and crime, and
Y. Fujino et al. / Preventive Medicine 40 (2005) 444–451
the ability to maintain social control over individual behavior [32]. This is particularly relevant to the present study, in which external causes of death showed the biggest differences between the educational levels examined. Injuries, traffic accidents, chemical hazards, fire, and workplace hazards are all more likely to show associations at the ecological rather than the individual level. In the present study, the low education group had a significantly increased risk of death due to external causes. Lower levels of education can lead to insecure income, hazardous work conditions, and poor housing, all of which can increase the risks of road accidents, fire, injuries, and work place hazards [32–39]. Psychosocial factors, such as the presence of a social network, social support, and stress at home and in the work place, might also contribute to the association between educational level and risk of death by external causes, which included death by suicide in the present study. However, it was not possible to distinguish suicide from other external causes in the present data in order to more fully explore this issue. The main advantages of using educational level as an indicator of socioeconomic status are that it is easily recorded and remains stable over an individual’s lifetime [40]. In addition, educational level is less likely to be affected by health impairments that develop in adulthood, compared with other indicators of socioeconomic position such as occupation or income [31]. However, the fact that level of education is stable over the lifetime of an individual also has negative implications, as it can mask important changes in an individual’s circumstances after their education has been completed [40]. Another disadvantage of using educational level as an indicator of socioeconomic status is that older people tend to have a lower average level of education (cohort effect) [41,42]. In fact, the ratio of students remaining in education after the age of 15 years increased after 1950 and had reached 90% by 1974 [43]. However, this is unlikely to have influenced the results of the present study because the analyses were restricted to only those subjects who were aged 18 years or above in 1949. Nevertheless, it is also of interest to know the impact of other social and economic factors, such as income, that indicate individual’s position in the social structure that may influence on health in Japan, although the present data did not provide a measurement of income. In conclusion, this study reveals that health inequalities still exist in Japan, even though the inequalities of wealth are reduced compared with other developed countries. Previous studies have shown an association between socioeconomic status and infectious diseases in developing countries, although no association was found between these factors in the present study. In general, high living standards are well established in Japan, including basic hygiene facilities, water supplies, housing, transportation, the physical environment, and work conditions. However, according to the bneomaterialQ perspective [44], educational level still
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has an influence on the subsequent socioeconomic position and health of Japanese individuals. In particular, our study highlights an unacceptable inequality in the risk of death from external causes. Social and political initiatives are therefore needed to amend the inequity between different socioeconomic statuses, which cannot be addressed through intervention at the level of the individual [45].
Acknowledgments Grant sponsor: Ministry of Education, Science, Sports and Culture of Japan; 61010076, 62010074, 63010074, 1010068, 2151065, 3151064, 4151063, 5151069, 6279102, 11181101, 12218237. The present investigators involved in the JACC study and their affiliations are as follows: Dr. Yoshiyuki Ohno (the present chairman of the Monbusho ECC), Dr. Akiko Tamakoshi (Secretary General of the Monbusho ECC), and Dr. Hideaki Toyoshima, Nagoya University Graduate School of Medicine; Dr. Mitsuru Mori, Sapporo Medical University School of Medicine; Dr. Yutaka Motohashi, Akita University School of Medicine; Dr. Shigeru Hisamichi, Tohoku University Graduate School of Medicine; Dr. Yosikazu Nakamura, Jichi Medical School; Dr. Takashi Shimamoto, Institute of Community Medicine, University of Tsukuba; Dr. Haruo Mikami, Chiba Cancer Center; Dr. Shuji Hashimoto, School of Health Sciences and Nursing, University of Tokyo; Dr. Yutaka Inaba, Juntendo University School of Medicine; Dr. Heizo Tanaka, Medical Research Institute, Tokyo Medical and Dental University; Dr. Yoshiharu Hoshiyama, Showa University School of Medicine; Dr. Hiroshi Suzuki, Niigata University School of Medicine; Dr. Hiroyuki Shimizu, Gifu University School of Medicine; Dr. Shinkan Tokudome, Nagoya City University Medical School; Dr. Yoshinori Ito, Fujita Health University School of Health Sciences; Dr. Akio Koizumi, Graduate School of Medicine and Faculty of Medicine, Kyoto University; Dr. Takashi Kawamura, Kyoto University Center for Student Health; Dr. Yoshiyuki Watanabe, Kyoto Prefectural University of Medicine, Research Institute for Neurological Diseases & Geriatrics; Dr. Masahiro Nakao, Kyoto Prefectural University of Medicine; Dr. Takaichiro Suzuki, Research Institute, Osaka Medical Center for Cancer and Cardiovascular Diseases; Dr. Tsutomu Hashimoto, Wakayama Medical University; Dr. Takayuki Nose, Tottori University Faculty of Medicine; Dr. Norihiko Hayakawa, Research Institute for Radiation Biology and Medicine, Hiroshima University; Dr. Takesumi Yoshimura, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan; Dr. Katsuhiro Fukuda, Kurume University School of Medicine; Dr. Tomoyuki Kitagawa, Cancer Institute of Japanese Foundation for Cancer Research; Dr. Toshio Kuroki, Institute of Molecular Oncology, Showa University; Dr. Naoyuki Okamoto, Kanagawa Cancer Center; Dr. Teruo Ishibashi,
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Asama General Hospital; Dr. Hideo Shio, Shiga Medical Center; and Dr. Kazuo Tajima, Aichi Cancer Center Research Institute. The former investigators involved in the JACC study and their affiliations are as follows: Dr. Kunio Aoki, Aichi Cancer Center; Dr. Suketami Tominaga, Aichi Cancer Center Research Institute; Dr. Sadamu Anzai, Dr. Takeshi Kawaguchi, Dr. Kenichi Nakamura, Dr. Motofumi Masaki, Showa University School of Medicine; Dr. Shuugo Kanamori, Dr. Masachika Morimoto, Dr. Seishi Yoshimura, Shiga Medical Center for Adults; Dr. Sigetosi Kamiyama, Dr. Yukio Takizawa, Dr. Noriyuki Hachiya, Akita University School of Medicine; Dr. Keiichi Kawai, Dr. Shuichi Nakagawa, Dr. Hiroki Watanabe, Kyoto Prefectural University of Medicine; Dr. Minoru Kurihara, Research Institute for Radiation Biology and Medicine, Hiroshima University; Dr. Yoshio Komachi, Institute of Community Medicine, University of Tsukuba; Dr. Ruichiro Sasaki, Aichi Medical University; Dr. Minoru Sugita, Toho University School of Medicine; Dr. Iwao Sugimura, Asahikawa Kosei Hospital; Dr. Toshihiko Tanaka, Chigasaki Public Health Center; Dr. Tomio Hirohata, Kyushu University School of Medicine; Dr. Isaburo Fujimoto, Center for Adult Diseases, Osaka; Dr. Minoru Matsuzaki, Chigasaki Public Health and Welfare Center; Dr. Hirotsugu Miyake, Sapporo Medical University School of Medicine; Dr. Motoi Murata, Chiba Cancer Center; Dr. Shinsuke Morio, Kanagawa Cancer Center; Dr. Hiroshi Yanagawa, Jichi Medical School; and Dr. Shaw Watanabe, Tokyo University of Agriculture.
References [1] Slater C, Carlton B. Behavior, lifestyle, and socioeconomic variables as determinants of health status: implications for health policy development. Am J Prev Med 1985;1:25 – 33. [2] Marmot MG, Shipley MJ. Do socioeconomic differences in mortality persist after retirement? 25 year follow up of civil servants from the first Whitehall study. BMJ 1996;313:1177 – 80. [3] Shkolnikov VM, Leon DA, Adamets S, Andreev E, Deev A. Educational level and adult mortality in Russia: an analysis of routine data 1979 to 1994. Soc Sci Med 1998;47:357 – 69. [4] Backlund E, Sorlie PD, Johnson NJ. The shape of the relationship between income and mortality in the United States. Evidence from the National Longitudinal Mortality Study. Ann Epidemiol 1996;6:12 – 20 [discussion 21–22]. [5] Lynch JW, Kaplan GA, Cohen RD, Kauhanen J, Wilson TW, Smith NL, et al. Childhood and adult socioeconomic status as predictors of mortality in Finland. Lancet 1994;343:524 – 7. [6] World Bank. World Development Report 2000/2001: Attacking Poverty; 2000. [7] Marmot M. Introduction. In: Marmot M, Wilkinson R, editors. Social determinants of health. New York7 Oxford Univ. Press; 1999. [8] World Bank. World Development Indicators 2003: World Bank; 2003. [9] Ohno Y, Tamakoshi A. Japan collaborative cohort study for evaluation of cancer risk sponsored by Monbusho (JACC study). J Epidemiol 2001;11:144 – 50. [10] Iso H, Date C, Yamamoto A, Toyoshima H, Tanabe N, Kikuchi S, et al. Perceived mental stress and mortality from cardiovascular disease
[11]
[12]
[13] [14] [15]
[16] [17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25] [26]
[27]
[28] [29] [30] [31]
[32]
[33]
among Japanese men and women: the Japan Collaborative Cohort Study for Evaluation of Cancer Risk Sponsored by Monbusho (JACC Study). Circulation 2002;106:1229 – 36. Mizoue T, Yoshimura T, Tokui N, Hoshiyama Y, Yatsuya H, Sakata K, et al. Prospective study of screening for stomach cancer in Japan. Int J Cancer 2003;106:103 – 7. Fujino Y, Tamakoshi A, Ohno Y, Mizoue T, Tokui N, Yoshimura T. Prospective study of educational background and stomach cancer in Japan. Prev Med 2002;35:121 – 7. Cox DR, Oakes D. Analysis of Survival Data. New York7 Chapman & Hall; 1984. SAS Institute Inc.. SAS/STAT User’s Guide, Release 6.03. Cary (NC)7 SAS Institute; 1988. Pan American Health Organization. Measuring health inequalities: Gini coefficient and concentration index. Epidemiol Bull 2001; 22:3 – 4. Kawachi I. Income inequality and health. In: Berkman L, Kawachi I, editors. Social epidemiology. New York7 Oxford Univ. Press; 2000. Rodgers GB. Income and inequality as determinants of mortality: an international cross-section analysis. 1979. Int J Epidemiol 2002;31: 533 – 8. Kunst AE, Mackenbach JP. The size of mortality differences associated with educational level in nine industrialized countries. Am J Public Health 1994;84:932 – 7. Kilander L, Berglund L, Boberg M, Vessby B, Lithell H. Education, lifestyle factors and mortality from cardiovascular disease and cancer. A 25-year followup of Swedish 50-year-old men. Int J Epidemiol 2001;30:1119 – 26. Bobak M, Murphy M, Rose R, Marmot M. Determinants of adult mortality in Russia: estimates from sibling data. Epidemiology 2003;14:603 – 11. Dennis BH, Zhukovsky GS, Shestov DB, Davis CE, Deev AD, Kim H, et al. The association of education with coronary heart disease mortality in the USSR Lipid Research Clinics Study. Int J Epidemiol 1993;22:420 – 7. Pitsavos CE, Panagiotakos DB, Chrysohoou CA, Skoumas J, Stefanadis C, Toutouzas PK. Education and acute coronary syndromes: results from the CARDIO2000 epidemiological study. Bull World Health Organ 2002;80:371 – 7. Feldman JJ, Mauc DM, Kleinman JC, Cornoni-Huntley J. National trends in educational differentials in mortality. Am J Epidemiol 1989;129:919 – 33. Gonzalez MA, Rodriguez Artalejo F, Calero JR. Relationship between socioeconomic status and ischaemic heart disease in cohort and casecontrol studies: 1960–1993. Int J Epidemiol 1998;27:350 – 8. Brunner E. Commentary: education, education, education. Int J Epidemiol 2001;30:1126 – 8. Martikainen P, Ishizaki M, Marmot MG, Nakagawa H, Kagamimori S. Socioeconomic differences in behavioural and biological risk factors: a comparison of a Japanese and an English cohort of employed men. Int J Epidemiol 2001;30:833 – 8. Anzai Y, Ohkubo T, Nishino Y, Tsuji I, Hisamichi S. Relationship between health practices and education level in the rural Japanese population. J Epidemiol 2000;10:149 – 56. Marmot M, Wilkinson R. Social determinants of health. New York7 Oxford Univ. Press; 1999. Berkman L, Kawachi I. Social epidemiology. New York7 Oxford Univ. Press; 2000. Kawachi I, Kennedy BP. Health and social cohesion: why care about income inequality? BMJ 1997;314:1037 – 40. Berkman L. Kawachi, I. A historical framework for social epidemiology. In: Berkman L, Kawachi I, editors. Social epidemiology. New York7 Oxford Univ. Press; 2000. Cubbin C, LeClere FB, Smith GS. Socioeconomic status and injury mortality: individual and neighbourhood determinants. J Epidemiol Commun Health 2000;54:517 – 24. Fuller-Thomson E, Hulchanski JD, Hwang S. The housing/health
Y. Fujino et al. / Preventive Medicine 40 (2005) 444–451
[34] [35]
[36]
[37] [38]
[39]
relationship: what do we know? Rev Environ Health 2000;15: 109 – 133. Kirschenbaum A, Oigenblick L, Goldberg AI. Well being, work environment and work accidents. Soc Sci Med 2000;50:631 – 9. Weitoft GR, Haglund B, Hjern A, Rosen M. Mortality, severe morbidity and injury among long-term lone mothers in Sweden. Int J Epidemiol 2002;31:573 – 80. Hasselberg M, Laflamme L. Socioeconomic background and road traffic injuries: a study of young car drivers in Sweden. Traffic Injury Prevent 2003;4:249 – 54. Shai D, Lupinacci P. Fire fatalities among children: an analysis across Philadelphia’s census tracts. Public Health Rep 2003;118:115 – 26. O’Campo P, Rao RP, Gielen AC, Royalty W, Wilson M. Injuryproducing events among children in low-income communities: the role of community characteristics. J Urban Health 2000;77:34 – 49. Locke JA, Rossignol AM, Boyle CM, Burke JF. Socioeconomic
[40]
[41] [42]
[43] [44] [45]
451
factors and burn rates in persons hospitalized for burns in Massachusetts. Public Health Rep 1986;101:389 – 95. Zurayk H, Halabi S, Deeb M. Measures of social class based on education for use in health studies in developing countries. J Epidemiol Commun Health 1987;41:173 – 9. Liberatos P, Link BG, Kelsey JL. The measurement of social class in epidemiology. Epidemiol Rev 1988;10:87 – 121. van Loon AJ, Brug J, Goldbohm RA, van den Brandt PA, Burg J. Differences in cancer incidence and mortality among socio-economic groups. Scand J Soc Med 1995;23:110 – 20. Ministry of Education Culture Sports Science and Technology of Japan; 2003. Lymh J, Kaplan G. Socioeconomic position. In: Berkman L, Kawachi I, editors. Social epidemiology. New York7 Oxford Univ. Press; 2000. Shaw M. The accidental epidemiologist: losing the way or following social–epidemiological leads? Int J Epidemiol 2002;31:523 – 6.
A nationwide cohort study of educational background and major causes of death among the elderly population in Japan Yoshihisa Fujino, M.D., Ph.D.a,*, Akiko Tamakoshi, M.D., Ph.D.b, Hiroyasu Iso, M.D., Ph.D.c, Yutaka Inaba, M.D., Ph.D.d, Tatsuhiko Kubo, M.D.a, Reiko Ide, D.D.S., Ph.D.a, Ai Ikeda, M.S.W., M.P.H.c, Takesumi Yoshimura, M.D., M.P.H., Ph.D.a for the JACC study group1 a
Department of Clinical Epidemiology, Institute of Industrial Ecological Science, University of Occupational and Environmental Health, Kitakyushu, Japan b Department of Preventive Medicine/Biostatistics and Medical Decision Making, Field of Social Life Science, Program in Health and Community Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan c Department of Public Health Medicine, Institute of Community Medicine, University of Tsukuba, Tsukuba, Japan d Department of Epidemiology and Environmental Health, Juntendo University School of Medicine, Tokyo, Japan Available online 21 August 2004
Abstract Background. This prospective cohort study examined the association between educational level and major causes of death in Japan. Method. A baseline survey was conducted between 1988 and 1990 among 110,792 inhabitants of 45 areas aged 40–79 years. Follow-up surveys were conducted annually and causes of death were identified from death certificates. The analysis was restricted to 16,715 men and 23,284 women. Results. During the follow-up period (377,139 person-years), 6628 deaths were recorded. Individuals with low levels of education had an increased overall risk of death [relative risk (RR) = 1.16, 95% confidence interval (CI): 1.08, 1.25, in men; RR = 1.26, 95% CI: 1.14, 1.39, in women], cancers (RR = 1.17, 95% CI: 1.04, 1.32, in men; RR = 1.10, 95% CI: 0.93, 1.30, in women), and death from external causes (RR = 1.81, 95% CI: 1.29. 2.54, in men; RR = 1.78, 95% CI: 1.18, 2.70, in women). Ischemic heart disease risk was marginally reduced in men with low levels of education (RR = 0.77, 95% CI: 0.58, 1.01). Conclusions. These results show that health inequalities exist in Japan, even though wealth inequalities are relatively low. Social and political initiatives will be needed to correct these inequities between different socioeconomic statuses. D 2004 The Institute For Cancer Prevention and Elsevier Inc. All rights reserved. Keywords: Japan; Prospective study; Education; Socioeconomic determinants of health; Mortality; Cancer; Coronary heart disease; External death
Introduction Socioeconomic status is commonly used as a proxy for environmental and lifestyle factors that relate to health * Corresponding author. Department of Clinical Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, 1-1, Iseigaoka, Yahatanishiku, Kitakyushu 8078555, Japan. Fax: +81 93 603 0158. E-mail address: [email protected] (Y. Fujino). 1 See acknowledgments for the investigators (name and affiliation) involved in the JACC Study.
status [1]. This approach initially attempted to identify biological causal relationships between environmental factors, lifestyle factors, and diseases. However, socioeconomic status has recently been recognized as a determinant of health, which is of relevance to the design of prevention strategies and health policies. Occupation, income, and education are often used as indices of socioeconomic status. However, previous reports have consistently shown that members of the higher socioeconomic group have better health status, regardless of the values of these indices [2–5].
0091-7435/$ - see front matter D 2004 The Institute For Cancer Prevention and Elsevier Inc. All rights reserved. doi:10.1016/j.ypmed.2004.07.002
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The primary example of health inequalities between socioeconomic groups is the contrast between rich and poor countries. There is a clear relationship between gross national product per capita and life expectancy [6]. The main reason for this trend is the direct association of poverty with malnutrition and infectious diseases, which results in a high burden of maternal, infant, and childhood diseases in poorer countries. However, even in developed countries in which infectious diseases are not dominant, chronic diseases and external causes of death are related to socioeconomic status [7]. Japan is one of the most affluent countries in terms of gross national income per capita and has the longest healthy life expectancy in the world [8]. In addition, wealth inequalities in Japan are thought to be lower than in other developed countries [6]. However, to our knowledge, few studies have examined the association between socioeconomic and health status in Japan. Therefore, it is of great importance to determine the impact of socioeconomic status on health among the Japanese population. This large cohort study, which involved a representative sample of the Japanese population from across the country, examined the association between educational level and the major causes of death in Japan.
Methods The Japan Collaborative Cohort Study for the Evaluation of Cancer Risk (JACC Study) is sponsored by the Ministry of Education, Science, Sports and Culture of Japan. The details of this cohort study have been described previously [9–12]. Briefly, a baseline survey was conducted between 1988 and 1990. The JACC study enrolled 127,477 apparently healthy inhabitants in these areas with completion of the questionnaire. Of 127,477 enrolled, 110,792 (46,465 men and 64,327 women), aged 40–79 years, were followed up. Twenty-four institutions from across the country participated in the study. The subjects answered a questionnaire concerning health-related lifestyle choices including smoking, alcohol consumption, occupation, diet, and medical history. Follow-up surveys were conducted annually to determine the vital status of the participants. For deceased subjects, the cause of death was recorded from the official death certificate held at the relevant regional health center and was classified according to the International Classification of Disease, 10th Revision (ICD-10). The present analysis also included follow-up data collected before 1999. The informed consent procedures were approved by the Ethics Committee of Medical Care and Research, University of Occupational and Environmental Health, Kitakyushu, Japan, and the Ethical Board of the Nagoya University School of Medicine, Japan. Causes of death were defined according to the ICD-10 classification as follows: cancer, C00-C97; respiratory system diseases, J00-J99; circulatory system diseases, I01–
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I51, I20–I25, and I60–I69: ischemic heart disease, I20–I25; cerebrovascular disease, I60–I69; respiratory system diseases, J00–J99; infectious/parasitic diseases, A00–B99; and injuries, poisoning, and other lesions from external causes, S00–T98. Data retrieval for analysis Four institutes involved the JACC study, which used a slightly different version of the questionnaire, did not ask educational level and then the subjects in these areas were excluded. Then, of 88,344 subjects, the 16,715 men (153,184 person-years) and 23,284 women (223,955 person-years) who were aged 18 years or above in 1949 were used for the analyses. This year was chosen as the Japanese educational system underwent significant changes after 1949, following World War II. A total of 6628 deaths (3,948 men and 2680 women) were identified among the subjects during the follow-up period. Educational background and covariates The subjects were assigned to three groups according to their level of education: those who attended school beyond the age of 18 years (high); those who attended school until the age of 16–17 years (intermediate); and those who attended school until the age of 15 years or below (low). Before 1949, it was not possible to classify schools into levels such as bprimary school,Q bjunior high school,Q and bhigh schoolQ as an index of educational level, as the Japanese educational system was highly complex and inconsistent. Furthermore, skipping grades and leaving school early were common before this date. The following additional baseline characteristics that might potentially be related to mortality were also considered: age (continuous variable); smoking status (never smoked, previous smoker, or current smoker); alcohol consumption (current habitual drinker, previous habitual drinker, or teetotaler); job status (employed, self-employed, or other); and type of job (office worker, manual worker, or other). Statistical analysis Cox proportional hazards regression analysis [13] was used to estimate the sex-specific relative risk (RR) of educational level for each of the major causes of death, adjusting for the potential confounding factors listed above. All calculations were performed using the SAS statistical software program [14].
Results Table 1 lists selected baseline characteristics of the study subjects by sex and educational background. Sub-
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jects of both sexes who were educated to a high level were less likely to smoke cigarettes and more likely to consume alcohol. Office workers were more common in the highly educated group than in the group with a low level of education. Tables 2 and 3 show that individuals of both sexes with a low level of education had an increased overall risk of death [RR = 1.16, 95% confidence interval (CI): 1.08, 1.25, in men; RR = 1.26, 95% CI: 1.14, 1.39, in women], as well as increased risks of cancer (RR = 1.17, 95% CI: 1.04, 1.32, in men), cerebrovascular disease (RR = 1.23, 95% CI: 1.01, 1.50, in men; RR = 1.44, 95% CI: 1.13, 1.83, in women), and death from external causes (RR = 1.81, 95% CI: 1.29. 2.54, in men; RR = 1.78, 95% CI: 1.18, 2.70, in women), compared with individuals with the high level of education. The risk of respiratory diseases in men (RR = 1.23, 95% CI: 1.01, 1.50) and the risk of circulatory system diseases in women (RR = 1.27, 95% CI: 1.08, 1.50) were also greater in the low education group than in the high education group. In men, the risk for ischemic heart disease showed a marginal decrease in the group with the low level of education compared with the group with the high level of education, although this was not statistically significant (RR = 0.77, 95% CI: 0.58, 1.01, P = 0.063). Similar results were obtained when the analysis was repeated after adjusting for smoking, alcohol, job status, and job type. We further analyzed the risk of the subjects who attended school below 12 years. Only 685 of 16,175 men and 1944 of 23,284 women attended school below 12 years, and the risk for total death was 1.32 (95% CI; 1.14, 1.52, P = 0.0002) in men and 1.53 (95% CI;.1.34, 1.75, P b 0.0001) in women compared with people who attended school 18 years or over.
Discussion Wealth inequality in Japan is lower than in other developed countries according to the Gini coefficient [15]. This coefficient is a measure of the income inequality in a society, the values of which range between 0 and 1, where 0 indicates perfect equality (that is, everybody has the same income) and 1 indicates perfect inequality (that is, one individual has all of the income and everybody else earns nothing). The World Development Report [8] listed the following Gini coefficients: 0.25 for Japan (1993), 0.36 for the United Kingdom (1995), and 0.41 for the United States (1997). Inequalities of wealth are a significant predictor of differences in life expectancy between countries [16]. In fact, the life expectancy at birth in Japan was reported to be the highest in the world in 2002, with a value of 81 years [8]. Great inequalities of wealth are linked to broader health outcomes, and theoretical models suggest that reducing the disparities in wealth distribution within a society improves the mean life expectancy [16,17]. The present study clearly showed that, even in Japan, the risk of death from most major causes is strongly related to socioeconomic status, which was measured here using educational level. However, the inequalities in health in this study were relatively small in magnitude compared with previous studies in other developed countries. This might be partly due to fewer inequalities in educational levels within the present subjects; about one half of the subjects were in the lowest education category. Kunst [18] reported substantial differences between countries in the size of the inequalities in mortality risk that are associated with educational level. This variation can be partly attributed to the inequalities in education that exist in some countries.
Table 1 Selected baseline characteristics according to educational background by sex Educational background (age) Male
n Person-year Mean age (SD) Smoking (%) Current Past Never Alcohol (%) Current Past Never Job status (%) Employed Self-employed Type of job (%) Office work Manual work
Female
V15
16–17
z18
V15
16–17
z18
7485 67,533 66.5 (5.7)
3834 35,540 65.5 (5.6)
5396 50,111 65.8 (5.7)
11,175 106,525 66.8 (5.7)
6230 60,362 65.4 (5.4)
5879 57,067 65.5 (5.4)
48.3 28.2 17.7
47.2 30.9 16.4
43.4 35.5 16.6
4.7 1.9 80.5
3.5 1.5 78.3
3.0 1.6 81.3
64.2 8.8 22.2
67.2 8.1 19.5
67.9 8.6 18.4
16.4 1.8 73.1
19.7 1.7 69.3
20.6 1.6 70.1
11.7 29.4
15.1 33.8
18.7 32.3
3.2 11.1
3.6 12.9
3.8 12.3
2.3 28.8
6.6 28.5
14.3 20.7
0.7 12.3
1.9 9.7
3.6 7.5
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Table 2 The RRs of educational background for each cause of death in males Educational background (age) 16–17
V15
Total death No. of cases = 3948 Age-adjusted RR Multivariate RRb Cancer No. of cases = 1508 Age-adjusted RR Multivariate RRb Circulatory system diseases No. of cases = 1175 Age-adjusted RR Multivariate RRb Ischemic heart disease No. of cases = 256 Age-adjusted RR Multivariate RRb Cerebrovascular disease No. of cases = 534 Age-adjusted RR Multivariate RRb Respiratory system diseases No. of cases = 551 Age-adjusted RR Multivariate RRb Infectious diseases No. of cases = 66 Age-adjusted RR Multivariate RRb External causes No. of cases = 215 Age-adjusted RR Multivariate RRb a b
RRa
95% CI
P
RRa
95% CI
P
1.16 1.14
1.08, 1.25 1.05, 1.22
b0.001 b0.001
1.06 1.06
0.97, 1.16 0.97, 1.16
0.184 0.201
1.17 1.15
1.04, 1.32 1.02, 1.29
0.008 0.026
1.06 1.05
0.92, 1.22 0.91, 1.21
0.437 0.520
1.06 1.04
0.93, 1.21 0.91, 1.19
0.430 0.581
1.01 1.01
0.86, 1.18 0.86, 1.19
0.923 0.881
0.77 0.77
0.58, 1.01 0.58, 1.02
0.063 0.068
0.90 0.90
0.65, 1.24 0.65, 1.25
0.507 0.541
1.23 1.20
1.01, 1.50 0.98, 1.46
0.044 0.082
1.05 1.05
0.82, 1.34 0.82, 1.34
0.713 0.698
1.23 1.21
1.01, 1.50 0.99, 1.47
0.041 0.067
1.15 1.15
0.90, 1.46 0.91, 1.47
0.266 0.243
0.72 0.71
0.41, 1.24 0.41, 1.24
0.233 0.232
0.86 0.87
0.46, 1.64 0.46, 1.65
0.655 0.669
1.81 1.75
1.29. 2.54 1.24, 2.47
b0.001 0.001
1.49 1.47
1.00, 2.23 0.98, 2.19
0.049 0.063
The reference group attended school beyond the age of 18 years. The model included age, smoking, alcohol, job status, and job type.
Previous studies in western countries have consistently revealed that a lower level of education is associated with an increased risk of ischemic heart disease [19–25]. However, in the present study, men in the low education group showed a marginal decrease in the risk of ischemic heart disease. This inconsistency might partly be a result of differences between Japan and other countries in the association between socioeconomic status and risk factors for ischemic heart disease. Martikainen et al. [26] compared socioeconomic differences in behavioral and biomedical risk factors in a Japanese and English cohort of middle-aged men. They found that more highly educated men in Japan had lower high-density lipoprotein cholesterol (HDL) levels, higher body mass indices (BMI), and higher waist-to-hip ratios than less educated men; however, the opposite associations were found among men in England. These results were backed up by another study in Japan [27], which confirmed that individuals with a higher level of education were more likely to be obese and sedentary.
This highlights an issue that arises in all studies examining the association between socioeconomic status and health: The magnitude and direction of health inequalities differ between health outcomes, even within the same society. This can bias results if the exact health outcome is not specified, as in the case of analyzing ball mortality.Q Opposite trends, such as that observed in ischemic heart disease in the present study, can mask the true magnitude of inequalities in health. In this study, the overall RR for death from all causes in men was 1.19 (95% CI: 1.10, 1.28) when the subjects who died from ischemic heart disease were excluded (data not shown); this value was 3% higher than before the data were excluded despite the fact that the number of deaths from ischemic heart disease was only 6% of the total number of deaths in the study population. Although our study did not aim to identify the causality between educational level and health outcomes, our findings have several implications. As noted previously [28,29], the association between socioeconomic status and health might be the result of a mixture of biological, lifestyle behavioral,
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Table 3 The RRs of educational background for each cause of death in females Educational background (age) 16–17
V15
Total death No. of cases = 2680 Age-adjusted RR Multivariate RRb Cancer No. of cases = 868 Age-adjusted RR Multivariate RRb Circulatory system diseases No. of cases = 992 Age-adjusted RR Multivariate RRb Ischemic heart disease No. of cases = 183 Age-adjusted RR Multivariate RRb Cerebrovascular disease No. of cases = 464 Age-adjusted RR Multivariate RRb Respiratory system diseases No. of cases = 231 Age-adjusted RR Multivariate RRb Infectious diseases No. of cases = 50 Age-adjusted RR Multivariate RRb External causes No. of cases = 170 Age-adjusted RR Multivariate RRb a b
RRa
95% CI
P
RRa
95% CI
P
1.26 1.23
1.14, 1.39 1.12, 1.36
b0.001 b0.001
1.04 1.03
0.92, 1.16 0.92, 1.15
0.543 0.635
1.10 1.09
0.93, 1.30 0.92, 1.29
0.280 0.329
1.02 1.02
0.84, 1.23 0.84, 1.24
0.867 0.822
1.27 1.23
1.08, 1.50 1.04, 1.44
0.003 0.013
1.05 1.03
0.87, 1.27 0.85, 1.25
0.619 0.743
1.01 1.01
0.71, 1.44 0.70, 1.44
0.959 0.974
0.84 0.84
0.54, 1.30 0.54, 1.30
0.428 0.435
1.44 1.38
1.13, 1.83 1.08, 1.75
0.003 0.009
1.03 1.01
0.77, 1.38 0.75, 1.35
0.830 0.953
1.10 1.10
0.84, 1.60 0.80, 1.52
0.363 0.550
0.78 0.78
0.53, 1.18 0.52, 1.17
0.252 0.225
1.23 1.21
0.59, 2.56 0.58, 2.54
0.579 0.607
1.35 1.33
0.60, 3.04 0.50, 3.01
0.471 0.487
1.78 1.83
1.18, 2.70 1.21, 2.77
0.006 0.004
1.18 1.17
0.72, 1.92 0.72, 1.91
0.510 0.533
The reference group attended school beyond the age of 18 years. The model included age, smoking, alcohol, job status, and job type.
environmental, and social factors rather than having one single cause. For example, differences in access to health care or health resources between different socioeconomic statuses might partly explain the overall results of the present study but are unlikely to have influenced ischemic heart disease. Lifestyle behaviors, including smoking, alcohol consumption, and diet, might also affect the differences in the risk of some causes of death, particularly cardiovascular disease and cancers; however, these factors are unlikely to explain the association between educational levels and external causes of death, which have less biological links with socioeconomic status. For each of the major causes of death analyzed, the ageadjusted RRs were similar to the multivariate RRs, which were adjusted for smoking, alcohol, job type, and job status. Although smoking generally has strong effects on health outcomes, particularly cancers and cardiovascular disease, it did not have an obvious confounding effect in the present study. The analysis might have failed to adjust for some other confounding factors, such as diet; however, the effects
of these factors are likely to be related to an individual’s level of exposure and therefore might not strongly influence the association between socioeconomic status and health. We previously reported [12] that educational level was associated with the risk of stomach cancer in Japan. Adjusting the analysis for smoking, alcohol, and dietary factors—including intake of salty foods, green tea, vegetables, and fruit, which are all thought to be strongly associated with stomach cancer—had little effect on the result: The more highly educated group showed a consistent decrease in the risk of stomach cancer (age-adjusted RR = 0.73; multivariate RR = 0.72). Perhaps more important for the association between socioeconomic status and health are ecological level characteristics [30,31]. Berkman [31] revealed that crucial ecological level factors that are related to the social environment are not adequately captured by investigations at an individual level. For example, the social and economic characteristics of a community influence local access to goods and services, the environment, the level of residential stability and crime, and
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the ability to maintain social control over individual behavior [32]. This is particularly relevant to the present study, in which external causes of death showed the biggest differences between the educational levels examined. Injuries, traffic accidents, chemical hazards, fire, and workplace hazards are all more likely to show associations at the ecological rather than the individual level. In the present study, the low education group had a significantly increased risk of death due to external causes. Lower levels of education can lead to insecure income, hazardous work conditions, and poor housing, all of which can increase the risks of road accidents, fire, injuries, and work place hazards [32–39]. Psychosocial factors, such as the presence of a social network, social support, and stress at home and in the work place, might also contribute to the association between educational level and risk of death by external causes, which included death by suicide in the present study. However, it was not possible to distinguish suicide from other external causes in the present data in order to more fully explore this issue. The main advantages of using educational level as an indicator of socioeconomic status are that it is easily recorded and remains stable over an individual’s lifetime [40]. In addition, educational level is less likely to be affected by health impairments that develop in adulthood, compared with other indicators of socioeconomic position such as occupation or income [31]. However, the fact that level of education is stable over the lifetime of an individual also has negative implications, as it can mask important changes in an individual’s circumstances after their education has been completed [40]. Another disadvantage of using educational level as an indicator of socioeconomic status is that older people tend to have a lower average level of education (cohort effect) [41,42]. In fact, the ratio of students remaining in education after the age of 15 years increased after 1950 and had reached 90% by 1974 [43]. However, this is unlikely to have influenced the results of the present study because the analyses were restricted to only those subjects who were aged 18 years or above in 1949. Nevertheless, it is also of interest to know the impact of other social and economic factors, such as income, that indicate individual’s position in the social structure that may influence on health in Japan, although the present data did not provide a measurement of income. In conclusion, this study reveals that health inequalities still exist in Japan, even though the inequalities of wealth are reduced compared with other developed countries. Previous studies have shown an association between socioeconomic status and infectious diseases in developing countries, although no association was found between these factors in the present study. In general, high living standards are well established in Japan, including basic hygiene facilities, water supplies, housing, transportation, the physical environment, and work conditions. However, according to the bneomaterialQ perspective [44], educational level still
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has an influence on the subsequent socioeconomic position and health of Japanese individuals. In particular, our study highlights an unacceptable inequality in the risk of death from external causes. Social and political initiatives are therefore needed to amend the inequity between different socioeconomic statuses, which cannot be addressed through intervention at the level of the individual [45].
Acknowledgments Grant sponsor: Ministry of Education, Science, Sports and Culture of Japan; 61010076, 62010074, 63010074, 1010068, 2151065, 3151064, 4151063, 5151069, 6279102, 11181101, 12218237. The present investigators involved in the JACC study and their affiliations are as follows: Dr. Yoshiyuki Ohno (the present chairman of the Monbusho ECC), Dr. Akiko Tamakoshi (Secretary General of the Monbusho ECC), and Dr. Hideaki Toyoshima, Nagoya University Graduate School of Medicine; Dr. Mitsuru Mori, Sapporo Medical University School of Medicine; Dr. Yutaka Motohashi, Akita University School of Medicine; Dr. Shigeru Hisamichi, Tohoku University Graduate School of Medicine; Dr. Yosikazu Nakamura, Jichi Medical School; Dr. Takashi Shimamoto, Institute of Community Medicine, University of Tsukuba; Dr. Haruo Mikami, Chiba Cancer Center; Dr. Shuji Hashimoto, School of Health Sciences and Nursing, University of Tokyo; Dr. Yutaka Inaba, Juntendo University School of Medicine; Dr. Heizo Tanaka, Medical Research Institute, Tokyo Medical and Dental University; Dr. Yoshiharu Hoshiyama, Showa University School of Medicine; Dr. Hiroshi Suzuki, Niigata University School of Medicine; Dr. Hiroyuki Shimizu, Gifu University School of Medicine; Dr. Shinkan Tokudome, Nagoya City University Medical School; Dr. Yoshinori Ito, Fujita Health University School of Health Sciences; Dr. Akio Koizumi, Graduate School of Medicine and Faculty of Medicine, Kyoto University; Dr. Takashi Kawamura, Kyoto University Center for Student Health; Dr. Yoshiyuki Watanabe, Kyoto Prefectural University of Medicine, Research Institute for Neurological Diseases & Geriatrics; Dr. Masahiro Nakao, Kyoto Prefectural University of Medicine; Dr. Takaichiro Suzuki, Research Institute, Osaka Medical Center for Cancer and Cardiovascular Diseases; Dr. Tsutomu Hashimoto, Wakayama Medical University; Dr. Takayuki Nose, Tottori University Faculty of Medicine; Dr. Norihiko Hayakawa, Research Institute for Radiation Biology and Medicine, Hiroshima University; Dr. Takesumi Yoshimura, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan; Dr. Katsuhiro Fukuda, Kurume University School of Medicine; Dr. Tomoyuki Kitagawa, Cancer Institute of Japanese Foundation for Cancer Research; Dr. Toshio Kuroki, Institute of Molecular Oncology, Showa University; Dr. Naoyuki Okamoto, Kanagawa Cancer Center; Dr. Teruo Ishibashi,
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Asama General Hospital; Dr. Hideo Shio, Shiga Medical Center; and Dr. Kazuo Tajima, Aichi Cancer Center Research Institute. The former investigators involved in the JACC study and their affiliations are as follows: Dr. Kunio Aoki, Aichi Cancer Center; Dr. Suketami Tominaga, Aichi Cancer Center Research Institute; Dr. Sadamu Anzai, Dr. Takeshi Kawaguchi, Dr. Kenichi Nakamura, Dr. Motofumi Masaki, Showa University School of Medicine; Dr. Shuugo Kanamori, Dr. Masachika Morimoto, Dr. Seishi Yoshimura, Shiga Medical Center for Adults; Dr. Sigetosi Kamiyama, Dr. Yukio Takizawa, Dr. Noriyuki Hachiya, Akita University School of Medicine; Dr. Keiichi Kawai, Dr. Shuichi Nakagawa, Dr. Hiroki Watanabe, Kyoto Prefectural University of Medicine; Dr. Minoru Kurihara, Research Institute for Radiation Biology and Medicine, Hiroshima University; Dr. Yoshio Komachi, Institute of Community Medicine, University of Tsukuba; Dr. Ruichiro Sasaki, Aichi Medical University; Dr. Minoru Sugita, Toho University School of Medicine; Dr. Iwao Sugimura, Asahikawa Kosei Hospital; Dr. Toshihiko Tanaka, Chigasaki Public Health Center; Dr. Tomio Hirohata, Kyushu University School of Medicine; Dr. Isaburo Fujimoto, Center for Adult Diseases, Osaka; Dr. Minoru Matsuzaki, Chigasaki Public Health and Welfare Center; Dr. Hirotsugu Miyake, Sapporo Medical University School of Medicine; Dr. Motoi Murata, Chiba Cancer Center; Dr. Shinsuke Morio, Kanagawa Cancer Center; Dr. Hiroshi Yanagawa, Jichi Medical School; and Dr. Shaw Watanabe, Tokyo University of Agriculture.
References [1] Slater C, Carlton B. Behavior, lifestyle, and socioeconomic variables as determinants of health status: implications for health policy development. Am J Prev Med 1985;1:25 – 33. [2] Marmot MG, Shipley MJ. Do socioeconomic differences in mortality persist after retirement? 25 year follow up of civil servants from the first Whitehall study. BMJ 1996;313:1177 – 80. [3] Shkolnikov VM, Leon DA, Adamets S, Andreev E, Deev A. Educational level and adult mortality in Russia: an analysis of routine data 1979 to 1994. Soc Sci Med 1998;47:357 – 69. [4] Backlund E, Sorlie PD, Johnson NJ. The shape of the relationship between income and mortality in the United States. Evidence from the National Longitudinal Mortality Study. Ann Epidemiol 1996;6:12 – 20 [discussion 21–22]. [5] Lynch JW, Kaplan GA, Cohen RD, Kauhanen J, Wilson TW, Smith NL, et al. Childhood and adult socioeconomic status as predictors of mortality in Finland. Lancet 1994;343:524 – 7. [6] World Bank. World Development Report 2000/2001: Attacking Poverty; 2000. [7] Marmot M. Introduction. In: Marmot M, Wilkinson R, editors. Social determinants of health. New York7 Oxford Univ. Press; 1999. [8] World Bank. World Development Indicators 2003: World Bank; 2003. [9] Ohno Y, Tamakoshi A. Japan collaborative cohort study for evaluation of cancer risk sponsored by Monbusho (JACC study). J Epidemiol 2001;11:144 – 50. [10] Iso H, Date C, Yamamoto A, Toyoshima H, Tanabe N, Kikuchi S, et al. Perceived mental stress and mortality from cardiovascular disease
[11]
[12]
[13] [14] [15]
[16] [17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25] [26]
[27]
[28] [29] [30] [31]
[32]
[33]
among Japanese men and women: the Japan Collaborative Cohort Study for Evaluation of Cancer Risk Sponsored by Monbusho (JACC Study). Circulation 2002;106:1229 – 36. Mizoue T, Yoshimura T, Tokui N, Hoshiyama Y, Yatsuya H, Sakata K, et al. Prospective study of screening for stomach cancer in Japan. Int J Cancer 2003;106:103 – 7. Fujino Y, Tamakoshi A, Ohno Y, Mizoue T, Tokui N, Yoshimura T. Prospective study of educational background and stomach cancer in Japan. Prev Med 2002;35:121 – 7. Cox DR, Oakes D. Analysis of Survival Data. New York7 Chapman & Hall; 1984. SAS Institute Inc.. SAS/STAT User’s Guide, Release 6.03. Cary (NC)7 SAS Institute; 1988. Pan American Health Organization. Measuring health inequalities: Gini coefficient and concentration index. Epidemiol Bull 2001; 22:3 – 4. Kawachi I. Income inequality and health. In: Berkman L, Kawachi I, editors. Social epidemiology. New York7 Oxford Univ. Press; 2000. Rodgers GB. Income and inequality as determinants of mortality: an international cross-section analysis. 1979. Int J Epidemiol 2002;31: 533 – 8. Kunst AE, Mackenbach JP. The size of mortality differences associated with educational level in nine industrialized countries. Am J Public Health 1994;84:932 – 7. Kilander L, Berglund L, Boberg M, Vessby B, Lithell H. Education, lifestyle factors and mortality from cardiovascular disease and cancer. A 25-year followup of Swedish 50-year-old men. Int J Epidemiol 2001;30:1119 – 26. Bobak M, Murphy M, Rose R, Marmot M. Determinants of adult mortality in Russia: estimates from sibling data. Epidemiology 2003;14:603 – 11. Dennis BH, Zhukovsky GS, Shestov DB, Davis CE, Deev AD, Kim H, et al. The association of education with coronary heart disease mortality in the USSR Lipid Research Clinics Study. Int J Epidemiol 1993;22:420 – 7. Pitsavos CE, Panagiotakos DB, Chrysohoou CA, Skoumas J, Stefanadis C, Toutouzas PK. Education and acute coronary syndromes: results from the CARDIO2000 epidemiological study. Bull World Health Organ 2002;80:371 – 7. Feldman JJ, Mauc DM, Kleinman JC, Cornoni-Huntley J. National trends in educational differentials in mortality. Am J Epidemiol 1989;129:919 – 33. Gonzalez MA, Rodriguez Artalejo F, Calero JR. Relationship between socioeconomic status and ischaemic heart disease in cohort and casecontrol studies: 1960–1993. Int J Epidemiol 1998;27:350 – 8. Brunner E. Commentary: education, education, education. Int J Epidemiol 2001;30:1126 – 8. Martikainen P, Ishizaki M, Marmot MG, Nakagawa H, Kagamimori S. Socioeconomic differences in behavioural and biological risk factors: a comparison of a Japanese and an English cohort of employed men. Int J Epidemiol 2001;30:833 – 8. Anzai Y, Ohkubo T, Nishino Y, Tsuji I, Hisamichi S. Relationship between health practices and education level in the rural Japanese population. J Epidemiol 2000;10:149 – 56. Marmot M, Wilkinson R. Social determinants of health. New York7 Oxford Univ. Press; 1999. Berkman L, Kawachi I. Social epidemiology. New York7 Oxford Univ. Press; 2000. Kawachi I, Kennedy BP. Health and social cohesion: why care about income inequality? BMJ 1997;314:1037 – 40. Berkman L. Kawachi, I. A historical framework for social epidemiology. In: Berkman L, Kawachi I, editors. Social epidemiology. New York7 Oxford Univ. Press; 2000. Cubbin C, LeClere FB, Smith GS. Socioeconomic status and injury mortality: individual and neighbourhood determinants. J Epidemiol Commun Health 2000;54:517 – 24. Fuller-Thomson E, Hulchanski JD, Hwang S. The housing/health
Y. Fujino et al. / Preventive Medicine 40 (2005) 444–451
[34] [35]
[36]
[37] [38]
[39]
relationship: what do we know? Rev Environ Health 2000;15: 109 – 133. Kirschenbaum A, Oigenblick L, Goldberg AI. Well being, work environment and work accidents. Soc Sci Med 2000;50:631 – 9. Weitoft GR, Haglund B, Hjern A, Rosen M. Mortality, severe morbidity and injury among long-term lone mothers in Sweden. Int J Epidemiol 2002;31:573 – 80. Hasselberg M, Laflamme L. Socioeconomic background and road traffic injuries: a study of young car drivers in Sweden. Traffic Injury Prevent 2003;4:249 – 54. Shai D, Lupinacci P. Fire fatalities among children: an analysis across Philadelphia’s census tracts. Public Health Rep 2003;118:115 – 26. O’Campo P, Rao RP, Gielen AC, Royalty W, Wilson M. Injuryproducing events among children in low-income communities: the role of community characteristics. J Urban Health 2000;77:34 – 49. Locke JA, Rossignol AM, Boyle CM, Burke JF. Socioeconomic
[40]
[41] [42]
[43] [44] [45]
451
factors and burn rates in persons hospitalized for burns in Massachusetts. Public Health Rep 1986;101:389 – 95. Zurayk H, Halabi S, Deeb M. Measures of social class based on education for use in health studies in developing countries. J Epidemiol Commun Health 1987;41:173 – 9. Liberatos P, Link BG, Kelsey JL. The measurement of social class in epidemiology. Epidemiol Rev 1988;10:87 – 121. van Loon AJ, Brug J, Goldbohm RA, van den Brandt PA, Burg J. Differences in cancer incidence and mortality among socio-economic groups. Scand J Soc Med 1995;23:110 – 20. Ministry of Education Culture Sports Science and Technology of Japan; 2003. Lymh J, Kaplan G. Socioeconomic position. In: Berkman L, Kawachi I, editors. Social epidemiology. New York7 Oxford Univ. Press; 2000. Shaw M. The accidental epidemiologist: losing the way or following social–epidemiological leads? Int J Epidemiol 2002;31:523 – 6.