Estimation of Future Mortality From Pleural Malignant Mesothelioma in Japan Based on an Age-Cohort Model

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1 AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 49:1 7 (26) Estimation of Future Mortality From Pleural Malignant Mesothelioma in Japan Based on an Age-Cohort Model Takehiko Murayama, PhD, 1 Ken Takahashi, MD, 2 Yuji Natori, MD, 3 and Norio Kurumatani, MD 4 Background Japanese consumption of asbestos increased rapidly after the 195s and lingered at a high level while the world s consumption decreased substantially after the 198s. Mesothelioma is due primarily to asbestos, and the number of deaths in Japan is expected to increase in the future. Method We estimated the future number of pleural mesothelioma deaths among males in Japan using an age-cohort model. Results Analyses showed that there would be about 1, deaths in Japan due to pleural mesothelioma in the next 4 years. Compared with the statistics in European countries, the ratio of expected death numbers to the population size is remarkably close to linear. The data-point for Japan was slightly lower than that which could be expected from the linear relationship. Conclusions The limited availability of data may result in underestimation. Taking into consideration the consumption pattern of asbestos in recent decades, the incorporation of later cohorts will improve the estimation. Am. J. Ind. Med. 49:1 7, 26. ß 25 Wiley-Liss, Inc. KEY WORDS: mesothelioma; age-cohort model; future mortality; asbestos; Japan INTRODUCTION In Japan, the consumption of asbestos, which is almost equal to the amount of asbestos imported due to negligible mining capacity, was minimal before World War II. It increased dramatically during the post-war catch-up period, reaching a peak level of 35, tons per year (T/yr) 1 Division of Multidisciplinary Studies, School of Science and Engineering,Waseda University,Tokyo, Japan 2 Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Fukuoka, Japan 3 Hirano Kameido Himawari Clinic,Tokyo, Japan 4 Department of Hygiene, Faculty of Medicine, Nara Medical University, Nara, Japan This work was mainly performed in Waseda University. *Correspondence to: Takehiko Murayama, A, Waseda University, 3-4-1Okubo, Shinjuku-ku,Tokyo , Japan. tmura@waseda.jp Accepted 4 October 25 DOI1.12/ajim Published online in Wiley InterScience ( in the first half of the 197s. Since then, it fluctuated around 25, 3, T/yr until 199, at which time a rapid decrease began. The recent figure is 43,318 tons in the year 22. In 23, the Japanese government began amending the related laws and regulations to prohibit in principle all asbestos use. The bulk of demand for asbestos came from the manufacture of asbestos cement panels. Given the fact that use of asbestos continued over such a long period, concern regarding the risk of mesothelioma is well justified [Takahashi et al., 1999]. Japan has no nationwide registries of this disease (a regional registry centered around the Osaka region is maintained by an expert panel), and the number of deaths was not available until 1995 when pleural mesothelioma was given its own classification code in the tenth revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-1). The statistics available since 1995 show a growing number of mesothelioma deaths and has raised considerable concern among the public [Asahi ß25Wiley-Liss,Inc.

2 2 Murayama et al. Shimbun (Newspaper), 1999; Mainichi Shimbun (Newspaper), 2]. The trend has also prompted the government to revise the compensation criteria for mesothelioma as an occupational disease [Japan Ministry of Health, Labor and Welfare, 23]. Hence the prediction of the future trend of this disease has important implications from both the public health and occupational health standpoint. It was in view of this background that we estimated the number of pleural mesothelioma deaths among Japanese males in the first half of the 21st century. DATA AND METHOD Source of Mortality Data In estimating future mortality, Peto et al. [1995] used data derived from the number of mesothelioma deaths registered by a UK Health Ministry system, and Kjaergaard and Andersson [2] used that of the Danish system. As Japan has no comparable registration system, the estimation requires the use of general vital statistics. As stated above, mesothelioma has been given an independent code since 1995 when ICD-1 was introduced, so the number of deaths before 1994 had to be estimated based on a translation of codes between ICD-1 and earlier versions of the ICD. Table I compares the translation scheme used in two preceding studies and the present one. Banaei et al. [2] multiplied a factor of.81 to the classification code of 163 (malignant neoplasm of the pleura) in ICD-9 to estimate deaths by pleural mesothelioma. Morinaga et al. [21] combined the codes of C45.9 (mesothelioma, unspecified) with C45. in ICD-1 to estimate deaths by pleural mesothelioma. Peto et al. [1999], in their exercise to compare future predictions in several European countries, adjusted the values according to the respective national conditions but basically used 163. in ICD-8 and 163 in ICD-9. This research suggested that data for these codes included deaths from mesothelioma during the period when ICD-8 was applied ( ), and when ICD-9 was applied ( ). The number of deaths in the 11 years between 1968 and 1978 in Japan, however, shows an unbridgeable gap in the vital statistics [Kurumatani et al., 22]. The number of deaths coded 163. (ICD-8) in the late 197s is about five times larger than deaths coded 163 (ICD-9) in This TABLE I. Comparison of Identification of Observed Number of Deaths in ICD-9 and ICD-1; Japanese Mesothelioma Cases (1) Banaeietal. [2] (2) Morinagaetal. [21] (3) Present research ICD (1^.68) ICD-1 C45. C45. þ C45.9 C45. would be caused by a conversion procedure in which a part of 163 (ICD-7) was improperly categorized as 163. (ICD-8). As the reason for this remains unclear, it was not possible to incorporate those data into our calculations. Thus, we focused on the number of deaths occurring after ICD-9 classified pleural mesothelioma and other pleural malignant neoplasms as code 163. Subsequently, ICD-1 divided this code into C45. (pleural mesothelioma) and C38.4 (pleural malignant neoplasm excluding mesothelioma). Supposing that the ratio of death numbers for these two codes was almost the same during the period of ICD-9, it was assumed that the code 163 in ICD-9 included pleural mesothelioma by the ratio of death numbers in these two codes. The number of deaths reported as C45. in the 6 years between 1995 and 2 was 1,734, and C38.4 in the same period was 127. Although the revision of the ICD may increase awareness of mesothelioma, the annual ratios of the two numbers in this period ranged between.5 and.11, and have not decreased. Thus, we assumed the number of deaths in the following manner. In the period between 1979 and 1994, when ICD-9 was applied, the data for code 163 (pleural malignant neoplasm) decreased by 6.8% (127/(1734 þ 127)). The data for C45. (pleural malignant mesothelioma) was used in the period when ICD-1 was applied. Figure 1 shows the trend of the deaths due to pleural malignant mesothelioma based on the above assumption. Prediction of the number of deaths based on the above model-required data on the future population of each cohort according to each age group. The Japan National Institute of Population and Social Security Research [22] provided the most reliable source of projections of future Japanese populations, based on the results of the population census of the year 2 and vital statistics. The data are available as the central year s population of each cohort. The latest cohort for parameter estimation is that born between 1955 and 1964, so it was not possible to predict younger cohorts. Prediction [Person] Male Female [Year] FIGURE 1. NumbersofdeathsfrompleuralmesotheliomainJapanduring1979^21.

3 Estimation of Future Mesothelioma Mortality in Japan 3 for the period when the latest cohort reaches over 8 years old would be not reliable; therefore, we limited the period of prediction to the years Statistical Model for Future Prediction To estimate future mortality, we applied the age-cohort model of Peto et al. [1995]. A detailed description of the model is given in Appendix A. Using this model, we estimated the parameters through a log-linear regression analysis assuming a Poisson distribution for the number of deaths. Theoretically, such analyses require data in which the years of birth and death are known. However, because the only available data in Japan are the annual number of deaths by 5-year age groups, we created a cohort grouped by birth and death years, and totaled the number of deaths for every 5-year period. This procedure put each cohort within a 1-year range. All mortality data during the 2 years between 198 and 1999 were used for the prediction. As death numbers had to be summed up for every 5 years, the data for 1979, 2, and 21 were excluded. The oldest cohort comprised those born in , and the latest in , with the age-groups of 5-years incorporating age-groups from to years. Annual data published by the Japanese government show the number of deaths by 5-year age groups and do not allow us to identify age in more detail. This leads to the necessity of making the range of each birth cohort 1- years, and a part of each cohort overlaps another. This is because the data used do not identify the age of death. However, it does not mean that the number of deaths in each birth cohort are counted twice. More specific procedures are given in the Appendix B. As the denominator of future deaths, the future population in Japan estimated and published by the Japanese government was employed. For log-linear regression analysis, a software module package in SPSS (version 1.), Advanced Models, was used. RESULTS Estimation of Parameters and Goodness of Fit of the Model Using the above procedure, we estimated the parameters and mortality rate that represented each age group, as well as the relative risks for each cohort. Because the parameter for the cohort of was the largest, the relative risks were calculated by using this cohort as the standard. Table II shows the observed and estimated number of deaths for each cell. To examine the goodness of fit of this model, the w 2 was applied. Applied to historical data, the result shows high goodness of fit for this model (w 2 ¼ 23.23, df ¼ 47, P ¼.9986). This suggests that the model accurately reproduces the observed number of deaths. Considering statistical errors with data dispersion, 95% confidence intervals (CI) were calculated for each parameter. Figure 2 shows the lifetime risk of each birth cohort calculated from the parameters estimated based on the life table of 196 [Japan Ministry of Health and Welfare, 1962]. The lifetime risk of each birth-cohort rose from the earliest birth-cohort, reached maximum at (95% CI: ) for the birth-cohort of , and decreased somewhat for the youngest birth cohort of Prediction of Number of Deaths Figure 3 shows the prediction curve for every 5 years during the period 2 239, which was connected to the curve showing observed numbers for every 5 years for the period Broken lines show the 95% CI of the predicted curve. It should be noted that in the figure, the prediction curve for the period is drawn, but it cannot be discerned from the observed curve. The CI for the prediction curve is thus drawn during the period The predicted curve shows that the total number of deaths in the 4 years between 2 and 239 reaches about 11,4, and the predicted number (43,15) in the 1 years between 23 and 239 would be 21. times the observed number (2,51) in the 1 years between 199 and The CIs of the predicted deaths widened in later years. The number of deaths will peak in the 5 years between 23 and 234, when the last cohort reaches 65 8 years. However, this analysis does not include generations younger than this cohort. In order to compare the results with predictions in other countries, we compiled the predicted number of deaths in the 35 years between 1995 and 229, and populations in Japan and some European countries (Fig. 4). For data in European countries, the results of Peto et al. [1999] were used. The figure shows that the ratio of expected death numbers to population size is remarkably close to linear, suggesting an almost uniform expected death rate across countries. The data-point for Japan was slightly lower than that which could be expected from the linear relationship. DISCUSSION Ultimately, the accuracy of the predictive model should be tested on an extrapolation basis, that is, by comparing predicted values with observed values outside the range of data incorporated into the statistical model. However, the goodness of fit of the model, as applied to the predicted and observed values within the range of data incorporated into the model, is an important condition that should be satisfied to the fullest extent possible. In this regard, it is noteworthy that the number of predicted and observed deaths before 1994 agreed well. Furthermore, there was close agreement of the future prediction for the Japanese population with the future

4 TABLE II. Estimation of Death Number by Cohort and Age Group; Japanese Mesothelioma Cases Age group and death rate 25^29 (.818) 3^34 (.7389) 35^39 (2.987) 4^44 (6.737) 45^49 (15.32) 5^54 (45.23) 55^59 (131.8) 6^64 (287.4) 65^69 (612.2) 7^74 (1345) 75^79 (2873) 8^84 (4212) 85^89 (7993) Cohort 1895^ (.758) ^ (.997) ^ (.191) ^ (.321) ^ (.398) ^ (.698) ^ (.111) ^ (.181) ^ (.258) ^ (.423) ^ (.831) ^ (1.) ^ (.7) The upper number in each cell is the observed number of deaths, and the lower is the number estimated by the model.the number in parentheses for each age group shows the death rate (per million per year for the195^1959 birth cohort), and the number for each cohort shows the risk relative to the death rate of cohort 195^

5 Estimation of Future Mesothelioma Mortality in Japan Lifetime Risk Cohort [Year] FIGURE 2. Lifetimeriskofdeath dueto mesothelioma amongthegeneral malepopulation (basedonthejapanese government life table of196). Lifetime risk means death rate due to pleural mesothelioma among the general male population. Each year represents a cohortwhichincludesitasamiddleyear. prediction conducted in several other countries in terms of the ratio of predicted future deaths to the population. However, the inferences remain limited because of the variation in the methodologies applied, notwithstanding the variable conditions regarding exposure and disease in different countries, but this observation seems to favor rather than disfavor the validity of the present prediction. This analysis incorporated 1-year birth-cohorts born between 1895 and 1964, and precluded younger birthcohorts. This was due solely to the limited availability of data imported volume of asbestos every 5 years [metric ton] predicted number of death every 5 years [person] FIGURE 3. EstimatedfuturedeathsfrompleuralmesotheliomainJapan.Bargraphshowstheimportedamountsofasbestosforthe 5-yearperiodstartingwiththeyearindicated(e.g.,198representsthe5-yearperiodof198^1984).Thesearealmostequaltotheamount ofasbestosconsumptionintheperiodsinceasbestosminingcapacityinjapanisnegligible.thesolidlineshowsthepredictedcurvewith eachdatapointrepresentingtheestimatednumberforthe5-yearperiodstartingwiththeyearindicated.brokenlinesshowthe95%ciofthe predictedcurve.

6 6 Murayama et al. Number of deaths due to mesothelioma 1 ) [person] Netherlands UK France Italy Germany Japan 1 Switzerland Population 2) [ million person] FIGURE 4. RelationbetweenpopulationandpredictedmesotheliomadeathsinJapan andeuropeancountries. 1) Numberofdeathsbetween1995and229. 2) Numberin1994. in Japan, but available data were utilized to their fullest using the present analytical method. However, the range of birth-cohorts incorporated will substantially alter the prediction. The present analysis did not account for the predicted number of deaths among younger generations who lived through the period in which Japan consumed large amounts of asbestos. It should be noted that Japan consumed asbestos at a level exceeding a hundred thousand tons annually even in the 199s. The risk predicted here therefore very likely underestimates the number of deaths that will actually occur. Another limiting factor was our inability to utilize the number of deaths prior to 1979 (the year before which ICD-8 was applied in Japan) due to constraints on the availability of published data in Japan. Thus, we could not calculate the number of deaths for the upper-left corner of the table. It is possible that if such calculations were possible, the accuracy of estimation could be improved. The parameter which shows the increase in mesothelioma was calculated using the least square method. For the age group from 45 to 79, the increase follows a power of 5.7, and the power is 4.5 for the age group from 4 to 6. Considering that asbestos exposures were predominantly caused by the occupational environment, data for age-groups under 6 should be used. Although, Peto et al. [1999] discuss diagnostic bias in quantitative terms, these results would depend on not only diagnostic bias, but also on the differences in the extent of exposure and age when exposure started among the birth cohorts. Considering the diverse patterns of asbestos exposure in Japan, the latter point should be emphasized more. Future research should first and foremost improve the precision of the prediction. The prediction can and should be refined by incorporating updated data as they become available. Secondly, the various underlying conditions in different countries in terms of exposure and disease status should be taken into account for the prediction. This may include the differences in the time-course of asbestos consumption, type of asbestos-fiber used, composition of products, preventive measures in occupational health, diagnostic procedures, susceptibility factors such as racial factors, etc. Among these factors, the time-course of asbestos consumption is perhaps the most relevant in the future prediction of mesothelioma based on birth-cohort analysis. Notably, asbestos has been used since the 194s in Europe, with the peak of consumption occurring in the 196s and 197s, while substantial use in Japan began only in the post-war era peaking in the 197s and 198s, and lingering since then. This study focuses on extrapolation of future deaths from past number of deaths, and does not directly refer to the relationship with asbestos consumption. One reason is that the cause of mesothelioma is fully limited to asbestos exposure, although there is no doubt that almost all deaths by mesothelioma are incurred by asbestos exposure. According to Hodgson et al. [25], however a simple birth cohort model may not correctly express future deaths from mesothelioma in later birth cohorts, and asbestos consumption must be incorporated into the statistical model. One of the problems is how to identify exposure level for each age group in each birth cohort. With updated mortality data, more sophisticated estimation should be implemented. REFERENCES Asahi Shimbun (Newspaper) August 1. 4p. Banaei A, Auvert B, Goldberg M, Gueguen A, Luce D, Goldberg S. 2. Future trends in mortality of French men from mesothelioma. Occup Environ Med 57: Hodgson JT, McElvenny DM, Darnton AJ, Price MJ, Peto J. 25. The expected burden of mesothelioma mortality in Great Britain from 22 to 25. Br J Cancer 92(3): Japan Ministry of Health, Labor and Welfare. 23. Notice on criteria of mesothelioma cases compensated by the government as occupational diseases. Japan Ministry of Health and Welfare Life Table No. 11. Japan National Institute of Population and Social Security Research. 22. Population projections for Japan. Kjaergaard J, Andersson M. 2. Incidence rates of malignant mesothelioma in Denmark and predicted future number of cases among men. Scand J Work Environ Health 26(2): Kurumatani N, Natori Y, Takahashi K, Murayama T. 22. Future trends in mortality of malignant pleural mesothelioma in Japan: Changes in classification of malignant mesothelioma from ICD7 through ICD1. Japan J Ind Health 44:328. Mainichi Shimbun (Newspaper). 2. December 29. 3p. Morinaga K, Kishimoto T, Sakatani M. 21. Asbestos-related lung cancer and mesothelioma in Japan. Ind Health 39: Peto J, Hodgson JT, Matthews FE, Jones JR Continuing increase in mesothelioma mortality in Britain. Lancet 345: Peto J, Decarli A, La VC, Levi F, Negri E The European mesothelioma epidemic. Br J Cancer 79:

7 Estimation of Future Mesothelioma Mortality in Japan 7 Rothman KJ, Greenland S, editors Modern epidemiology. Philadelphia: Lippincott-Raven Pub. 752p. Takahashi K, Huuskonen MS, Tossavainen A, Higashi T, Okubo T, Rantanen J Ecological relationship between mesothelioma incidence/mortality and asbestos consumption in ten Western countries and Japan. J Occup Health 41:8 11. APPENDIX A Statistical analysis techniques in epidemiology are mainly enumerated by age, cohort, and the observation period of death numbers as factors that influence the mortality ratio. Using these factors, the age-cohort, age-period, and age-period-cohort models were proposed [Rothman and Greenland, 1998]. Among these models, the last model was problematic in that the parameter could not be uniquely decided because there was insufficient data. From the viewpoint of the characteristics of mesothelioma and the restriction of data, the age-cohort model was applied. This model can be described as follows: y ab ¼ u a u b where y ab is the mortality ratio of each age group (a) in birth cohort (b), u a the mortality rate of each age group (a), and u b the relative risk (b) for a standard cohort. Based on this model, the parameter was estimated through loglinear regression analysis, according to the Poisson distribution. APPENDIX B Data published by the Japanese government provides the number of deaths by 5-year age categories, and did not allow us to identify age in more detail. Hence each birth cohort was constructed by 1-year age groups with 5-year overlaps. In the case of a group of year, old males who died between 1995 and 1999, the cohort includes those who were born on January 2, 1925, and died by January 1, 1995, but does not include those born on the same date and died between January 2 and December 31, This cohort also includes people who were born on December 31, 1925, and died between January 1 and December 31, Similarly, it includes individuals born on January 1, 1934, and died between January 1 and December 31, 1999, and those who were born on December 31, 1934 and died on December 31, It can be seen in Table III that the earlier group includes the earlier half of the birth group and the latter half is included in the later birth group. Thus, observation cases were not duplicated even though groups overlapped. TABLE III. Relationship Between Birth Cohort and Age Groups; Japanese Mesothelioma Deaths Year of death (Age Group) Year of birth * 1926 (Age) * * * * * * * * * Specific procedures are as follows. Birth cohorts (BC) spanning 1 years are constructed with an overlap of 5 years. Mortality rates are calculated based on the population size of each BC. Using the model, mortality rates by 5-year age category are calculated. Based on existing data on future estimated population, the population size of each BC is calculated for each 5-year age group. This is multiplied by the above mortality rate to obtain the expected number of deaths. However, each BC spans 1 years while the age-category spans 5 years, thus the year of death will span 15 years. This is because log-linear regression independently produced each factor, and the date when people born in the earliest year of each cohort and died at the youngest age of each age group is 15 years earlier than the date when people born in the latest year of the cohort and died at the oldest age of the age group. Hence, assuming that deaths will occur evenly during the 15- year period, the result is divided by three so that the number of deaths corresponds to a 5-year period for each BC. Because each BC moves along time with the overlap, the number of deaths is estimated taking into account the overlapping period.