6
Epidemiological Transitions in the Formerly Socialist Economies: Divergent Patterns of Mortality and Causes of Death

Christopher J.L. Murray and José Luis Bobadilla

Introduction

Eastern Europe and the New Independent States (NIS), known collectively as the Formerly Socialist Economies, are a unique demographic and epidemiological region.1 Mortality trends in the region over the last three decades appear to define a new pattern of the epidemiological transition, one that deviates from the collective experience of other developed countries and the middle-income countries of Latin America and Asia (Murray et al., 1992; Kingkade and Arriaga, in this volume). The goal of this chapter is to examine the levels, trends, and patterns of causes of death in the region, with an emphasis on identifying the patterns that may explain its unusual mortality experience.

Health or, more accurately, mortality in the Formerly Socialist Economies has been the focus of substantial and sustained academic interest since the mid-1970s (Anderson and Silver, 1988, 1989, 1990, 1991; Blum and Monnier, 1989; Cooper, 1981, 1983, 1985, 1987; Cooper and Sempos, 1984; Cooper and Schatzkin, 1982a, 1982b; Davis and Feshback, 1980; Deev and Oganov, 1989; Dutton, 1979, 1981; Eberstadt, 1990, 1993; Forster and Jozan, 1990; Jones and Grupp, 1983; Jozan, 1989; Medvedev, 1985; Meslé et al., 1993; Ryan, 1982, 1988; Treml, 1982).

Interpretation of the current pattern of age-specific mortality and causes of death in the region must be undertaken in light of its trends in mortality over the last two to three decades. Because the trends and explanations of trends for these countries have been contentious (as discussed in several other chapters in this volume), we try to clarify the situation by separating the discussion of changes in



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--> 6 Epidemiological Transitions in the Formerly Socialist Economies: Divergent Patterns of Mortality and Causes of Death Christopher J.L. Murray and José Luis Bobadilla Introduction Eastern Europe and the New Independent States (NIS), known collectively as the Formerly Socialist Economies, are a unique demographic and epidemiological region.1 Mortality trends in the region over the last three decades appear to define a new pattern of the epidemiological transition, one that deviates from the collective experience of other developed countries and the middle-income countries of Latin America and Asia (Murray et al., 1992; Kingkade and Arriaga, in this volume). The goal of this chapter is to examine the levels, trends, and patterns of causes of death in the region, with an emphasis on identifying the patterns that may explain its unusual mortality experience. Health or, more accurately, mortality in the Formerly Socialist Economies has been the focus of substantial and sustained academic interest since the mid-1970s (Anderson and Silver, 1988, 1989, 1990, 1991; Blum and Monnier, 1989; Cooper, 1981, 1983, 1985, 1987; Cooper and Sempos, 1984; Cooper and Schatzkin, 1982a, 1982b; Davis and Feshback, 1980; Deev and Oganov, 1989; Dutton, 1979, 1981; Eberstadt, 1990, 1993; Forster and Jozan, 1990; Jones and Grupp, 1983; Jozan, 1989; Medvedev, 1985; Meslé et al., 1993; Ryan, 1982, 1988; Treml, 1982). Interpretation of the current pattern of age-specific mortality and causes of death in the region must be undertaken in light of its trends in mortality over the last two to three decades. Because the trends and explanations of trends for these countries have been contentious (as discussed in several other chapters in this volume), we try to clarify the situation by separating the discussion of changes in

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--> child mortality (under age 5) from that of changes in adult mortality (over age 5). There are reasons to suspect that the changes and explanations for these two groups are fundamentally different. The publication in the Soviet Union of infant mortality rates for 1971-1975—showing an increase from 22.9 to 30.6 per 1,000 births, generated considerable discussion and analysis (Blum and Monnier, 1989). Publication of the infant mortality rate was discontinued by the Soviet government in the face of still worsening mortality after 1975. With glasnost, the rates were again published, with back figures given from 1980, when the rate was 27.3. For infant (under age 1) and child (ages 1-4) mortality in most of Eastern Europe (noteworthy exceptions being Romania and Bulgaria), we have long series of data for which there is widespread consensus that registration has been adequate for many years. The data show that changes in these rates over the last decades in Eastern Europe have not paralleled those in the former Soviet Union. Throughout the period following World War II, child mortality in Eastern Europe was similar to that in the rest of Europe, except in Romania and Bulgaria. In addition, the pace of improvement has been the same (except for an increase in Romania since 1985), with no evidence of worsening infant or child mortality during the last two decades. If the above increase in the Soviet Union in fact occurred, we must seek explanations for that change that are specific to the Soviet Union and not applicable to all Formerly Socialist Economies. The divergence in pattern also emphasizes the importance of examining time trends in the former Soviet Union by republic. In contrast with infant and child mortality, the patterns of adult mortality observed in Eastern Europe and the partial data for the Soviet Union tell a more consistent story. With regard to mortality among adult women, the levels over the last four decades have been higher in Eastern Europe than in the former Soviet Union, but the trends until 1980 were identical. Since then, trends in the two regions have diverged. Patchy data on age-specific mortality for the former Soviet Union suggest a pattern of stagnation or slow decline among most female age groups (Blum and Monnier, 1989; Eberstadt, 1993), whereas in Hungary and Poland, mortality among women aged 30-44 and 45-59 has increased slightly. The major demographic and epidemiological puzzle of the Formerly Socialist Economies is the sustained increase in adult male mortality, which has affected those aged 30-44, 45-59, and 60-69, and remarkably began in almost exactly the same year—1964—in all countries of the region. Partial data for the former Soviet Union indicate that similar developments occurred throughout the region at the same time (Anderson and Silver, 1990; Ryan, 1982; Cooper, 1981; Eberstadt, 1993). The increases in adult male mortality continued over nearly two decades and led to a 60 percent increase among some age groups in some countries. Cooper and colleagues (Cooper, 1981, 1983, 1985, 1987; Cooper and Sempos, 1984; Cooper and Schatzkin, 1982a, 1982b) have argued that other

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--> countries, such as the United States, Japan, and Chile, have experienced similar phases of increasing adult mortality. Yet while mortality among males aged 4559 increased from 1961 to 1968 in the United States, the length and the magnitude of the increase in the Formerly Socialist Economies are without parallel in demographic history (Stolnitz, 1974). Explanations for this unique mortality reversal in an industrialized region in the face of continued improvements in child health, at least in Eastern Europe, have included smoking, alcohol, occupational exposures, pollution, diet, the health care delivery system, and a cohort effect from hardships endured during World War II. Moreover, explanations for the increase in male mortality must simultaneously explain the improvements or at worst stagnation in female mortality in the former Soviet Union since 1980. The next section reviews the data sources and methods used for this study. The section that follows presents results of the analysis with respect to mortality patterns and years of life lost. This is followed by discussion of the unique mortality trends and cause-of-death patterns in the region of the Formerly Socialist Economies that includes the northern European former Soviet republics. The final section presents conclusions. Data Sources and Methods Before analyzing the patterns of causes of death based on vital registration data for the former Soviet republics and Eastern Europe, careful attention must be paid to the validity of those data. In the following sections, we evaluate the proportion of infant deaths captured in the vital registration system, the proportion of adult deaths recorded, and finally the quality of the attribution of deaths to particular causes. We also describe our method for calculating years of life lost due to premature mortality. Note that unless otherwise indicated, the analysis of mortality in this chapter refers to deaths that occurred in 1990. Underregistration and Alternative Definitions of Neonatal Deaths The Soviet definition of infant mortality is not the same as the World Health Organization (WHO) standard (see also the chapters by Shkolnikov et al. and by Kingkade and Arriaga, in this volume). As a consequence, the number of neonatal deaths—deaths before age 1 month—in the former Soviet republics is seriously underreported. The result is an underestimate of infant mortality, which is the sum of neonatal and post-neonatal mortality. In the present analysis, we correct neonatal mortality rates (NMR) for the former Soviet republics by using the relationship between NMR and post-neonatal mortality rates (PNMR) observed in countries with good vital statistics. We expect the PNMR (deaths between ages 1 and 12 months) to be unaffected by the Soviet definition of an infant death, except for possible age heaping at 1 month of age. We analyzed 1,327 pairs of NMR and PNMR available for 35 countries over

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--> Figure 6-1 Neonatal and post-neonatal mortality rates. (Data over a 40-year period from countries with good vital statistics registration.) These 1,327 data points are drawn from 35 countries over a period from 1945 to 1989. The R2 from the regression of NMR vs. the logit transformation of PNMR is .80 and both the coefficient and the constant from the equation are significant (p 8 0.001). The coefficient is .0166 and its standard error is 0.0002. The constant is 0.0555 and its standard error is 0.0005. a 40-year period.2 Figure 6-1 shows the relationship between the two rates. When the PNMR is transformed to its logit form,3 the relationship is linear. An ordinary least squares regression equation was fitted: NMR = .0555 + (-.0166 * logitPNMR) The R2 for the equation is 0.80, and the p-values for the slope and constant are each less than 0.001. The standard error of the constant is 0.0002, and the standard error for the slope is 0.0006. In addition, the residuals are homoskedastic. We estimated the corrected neonatal mortality rates (NMRc) by applying the PNMR for each of the former Soviet republics (thought to be accurate) to the above regression equation. Adding this newly generated NMRc to the PNMR yields a new estimate of the infant mortality rate, IMRc. It should be noted that all of the correction made to the infant mortality rates is due to correction of the neonatal mortality rate (from NMR to NMRc). Table 6-1 shows the NMRc and IMRc for all the former Soviet republics and the estimated proportion of underregistered neonatal and infant deaths; for NMR, this percentage varies from 26.6 percent in Turkmenistan to about 53.5 percent in Latvia. The different definition

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--> TABLE 6-1 Infant Mortality Reported and Corrected in the NIS, 1990   Reported Infant Mortality Rate (IMR) Reported Neonatal Mortality Rate (NMR) Reported Post-Neonatal Mortality Rate (PNMR) Corrected IMR Corrected NMR Percentage underestimation of reported IMR Percentage underestimation of reported NMR Republic Armenia 20.4 9.2 11.2 27.9 16.7 27.1 45.2 Azerbaijan 26.2 6.1 20.1 33.4 13.3 21.6 54.2 Belarus 11.8 7.3 4.6 19.4 14.8 38.8 50.8 Estonia 14.7 10.2 4.6 22.1 17.6 33.5 42.2 Georgia 19.6 9.9 9.7 27.0 17.3 27.6 43.1 Kazakstan 25.9 10.9 15.0 33.1 18.2 21.9 40.0 Kyrgyz 32.2 10.3 21.9 39.6 17.7 18.7 41.8 Latvia 11.1 6.4 4.8 18.4 13.7 39.6 53.5 Lithuania 10.7 6.8 3.9 18.1 14.3 41.0 52.1 Moldova 20.4 9.9 10.5 27.9 17.4 26.8 43.0 Russian Federation 17.8 10.6 7.2 25.1 17.9 29.2 41.0 Tajikistan 43.2 10.3 32.9 50.6 17.7 14.6 41.8 Turkmenistan 54.7 15.5 39.1 60.3 21.1 9.3 26.6 Ukraine 13.0 6.9 6.1 20.4 14.3 36.5 51.9 Uzbekistan 37.7 11.8 25.8 44.7 18.9 15.7 37.3 All Soviet Union 22.7 10.0 12.7 30.1 17.4 24.7 42.8

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--> of neonatal death may not account for all of this wide variation in the neonatal mortality rate; some variation may be due to higher rates of underreporting of neonatal deaths. Underregistration of Adult Deaths Most authors presume that registration of mortality in the Russian Federation, the Baltic states, and the other former Northern republics is complete. Anderson and Silver (1990, 1991, and in this volume), however, have analyzed regional mortality patterns in the former Soviet Union and concluded that there is substantial underregistration of adult deaths in the former Central Asian republics. To date, judgments that there has been substantial underreporting of deaths in certain republics have been based solely on the fact that observed mortality rates appear to be too low. Such assessments presuppose that the determinants of relative levels of adult mortality within the former Soviet Union or among industrialized countries are known. For example, Anderson and Silver (1990, 1991) report lower age-specific mortality in Tajikistan than in the United States for males; in the age groups over 70 years, the differences are as high as 20 to 50 percent. The authors conclude that lower adult mortality in Central Asia than in the United States is "implausible," although they provide no epidemiological justification for this judgment. Studies of adult mortality patterns (ages 15-59) in industrialized and developing countries have demonstrated wide variations in adult male and female mortality as measured by 45q15—the probability of death between ages 15 and 60. For example, in Japan, male 45q15 is 113 per 1,000, compared with 175 per 1,000 for all U.S. males, 300 for U.S. black males, and 187 for Finnish males (Murray et al., 1992). Given the wide range in adult mortality levels that is not easily explained by variables such as income per capita, it is not convincing to argue that there is significant underregistration in Central Asian states solely because their observed rates are lower than those of other states. To define further the extent of underregistration in different states of the former Soviet Union, we use the growth balance method and the Bennett-Horiuchi technique (United Nations, 1983). We apply the growth balance method using registered deaths in 1989 and the census population for 1989 by age for each republic. Application of this method depends on having a population that approximates a stable population with a long-term constant birth rate and no net migration. The relationship between Nx/Nx+ and Dx+/Nx+, however, is not linear for almost all republics; Nx is the population at age x, Nx is the population over age x, and Dx+ is deaths over age x. The age group "birth rate," Nx/Nx+, is markedly lower for the age groups 70-74 and 75-79 for most republics, which may reflect the World War II experience of this cohort. Excluding these age groups and 80+ years, the estimated coverage for the former Soviet Union com-

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--> TABLE 6-2 Estimated Coverage of Mortality Registration in the New Independent States, 1990   Growth Balance Method Bennett-Horiuchi Technique Bennett-Horiuchi 50+   Estimated coverage (%) Estimated coverage (%) Estimated coverage (%) Republic Female Male Female Male Female Male Latvia 77.5 83.3 109.2 106.0 106.1 105.8 Lithuania 71.3 82.9 107.5 106.1 105.4 104.7 Belarus 66.1 65.1 101.6 101.3 102.5 104.7 Estonia 83.4 79.4 103.1 103.4 102.4 104.5 Azerbaijan 73.1 62.3 80.8 93.0 85.7 103.8 Ukraine 71.5 80.4 103.5 101.3 102.0 103.5 Russian Federation 72.8 62.9 97.7 102.2 100.4 102.7 Georgia 64.9 59.0 89.6 96.8 91.4 97.5 Moldova 68.5 72.9 100.4 92.3 102.9 95.4 Kazakstan 79.3 73.2 80.4 83.2 84.7 91.9 Turkmenistan 104.6 88.0 82.5 81.3 86.2 90.9 Armenia 62.9 56.7 69.8 77.2 78.7 90.4 Uzbekistan 102.3 86.0 81.4 84.3 84.7 89.3 Kyrgyz 85.4 74.0 79.1 84.2 82.8 88.9 Tajikistan 86.7 124.0 74.7 82.6 79.3 87.6 All Soviet Union 103.0 102.3 97.2 99.5 98.8 101.9

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--> bined is 103 percent for females and 102 percent for males. Estimates of coverage using the growth balance method for each republic range from 65 to 120 percent, as shown in Table 6-2. These estimates follow no clear geographic pattern; Armenia, Georgia, Belarus, and Moldova have the lowest estimated coverage, rates below 70 percent. The assumptions underlying the growth balance method clearly do not hold at the republic level, making these estimates of coverage.4 The Bennett-Horiuchi technique for assessing vital registration completeness is a more powerful method that does not require assumption of a constant birth rate over the past 80 years, but does assume a closed population (Bennett and Horiuchi, 1981). As input, two censuses and all registered deaths by age and sex for the interval between the censuses are required. Censuses were conducted in each republic in 1979 and 1989; unfortunately, registered deaths by age and sex are available for the majority of years between 1979 and 1989, but not all. As a first approximation, we used the average number of registered deaths for each age group for all available years 1979-1989, multiplied by 10. For the former Soviet Union combined, the estimated completeness of registration for females is 99 percent and for males 102 percent. The estimated coverage may be somewhat exaggerated (over 100 percent, for example) because of overstatement of age at older ages (Bennett and Garson, 1983). Table 6-2 provides the estimated coverage of death registration for each republic by sex. The median estimated completeness is severely affected by internal migration; those republics, such as Lithuania, which had substantial net immigration over the period 1979 to 1989 show overregistration of deaths, while those with net emigration show underregistration. The third column of Table 6-2 shows the estimated completeness of death registration for the population over age 50, which may be less affected by migration between republics. To the extent that the approximations used in the application of the Bennett-Horiuchi technique are plausible, registration is over 90 percent in all locations except for males in Uzbekistan, Kyrgyz, and Tajikistan and females in Azerbaijan, Kazakstan, Turkmenistan, Armenia, Uzbekistan, Kyrgyz, and Tajikistan. The lower levels of vital registration coverage for many of the Central Asian republics and females in Azerbaijan are probably due to a combination of net emigration and lower completeness of vital registration. Given that vital registration for the Soviet Union as a whole is very close to complete, we suspect that internal migration in the former Soviet republics may play an important role in explaining the low coverage. Nevertheless, it is reasonable to suspect that vital registration coverage in Central Asia and Azerbaijan is lower than in other parts of the former Soviet Union. The estimates of registration coverage for all Central Asian republics, Georgia, and Azerbaijan are considerably lower for women than for men. This sex difference in vital registration coverage could be explained by more age overstatement by males than females or by sex bias in death registra-

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--> tion. Further work using more detailed data on migration between republics by age and sex is needed to improve the estimates of sex-specific underregistration. We conclude that for most republics, registration of adult deaths is 95 percent or more complete. Registration of adult deaths in the Central Asian republics is probably between 85 and 95 percent. Registration coverage of adult female deaths in Central Asia, Georgia, and Azerbaijan may be lower than that of adult male deaths. For our analysis, we have chosen not to adjust the reported levels of adult mortality based on the Bennett-Horiuchi technique. The 10 to 15 percent underestimation that may be present does not affect any of our major conclusions. Where appropriate, we draw attention to the effect corrections might have on the observed patterns of mortality and years of life lost. Classifications of Causes of Death There are two distinct sets of concerns with the attribution of causes of death in the republics of the former Soviet Union: the classification system and the quality of the coding of each individual death. The countries of Eastern Europe switched from the Soviet system of classifying causes of death after World War II; the NIS countries, however, have continued to use the Soviet system. Meslé et al. (1993) report that the Soviet system has undergone four major revisions since 1950; the last three revisions have been based on the International Classification of Diseases (ICD-7, ICD-8, and ICD-9), but contain many fewer causes (see also Kingkade and Arriaga, in this volume). The latest Soviet revision, in use since 1981, has also been slightly modified to include additional causes, such as AIDS (Goskomstat, 1987). Based on a translation of a bridge-coding manual prepared by the Soviet Central Statistical Administration (Goskomstat), we have mapped the Soviet codes to ICD-9. In turn, we have mapped the ICD-9 codes to the simplified list of diseases proposed by Murray and Lopez (1994). Without a formal bridge-coding exercise, whereby the same set of deaths is coded for both ICD-9 and the Soviet system, a potential error in interpretation is introduced. As discussed below, this is a significant problem only for complex groups of causes, such as cardiovascular diseases. In addition, poor diagnostic skill in the NIS may introduce systematic error in the cause-of-death data. One of the only objective indicators of the quality of cause-of-death attribution is the proportion of deaths coded by physicians (Lopez, 1989). Even in Central Asia, more than 99 percent of deaths are coded by physicians (Goskomstat, 1987). Follow-up studies (where coding was reviewed by a panel of experts) from 1965 in central Russia, 1979 in Russia, and 1981-1982 in Belarus and Turkmenistan reveal that the percentage over- or underestimation for most large groups of causes, such as cardiovascular disease, is very small, e.g., 3.1 to 2.3 percent. The largest errors are in coding of respiratory disease, with errors of 1 1.3 to 17.2 percent (see Shkolnikov et al., in this volume). Although nearly all registered deaths are coded by physicians, and the three

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--> follow-up studies demonstrate that the estimated population cause-specific mortality rates are reasonable, there may be substantial differences in diagnostic practice among countries. The results presented below, however, do not suggest that there is more diagnostic error in the data for the former Soviet republics than is observed for other developed countries. Years of Life Lost Due to Premature Mortality and Excess Years of Life Lost To capture the importance of death at different ages, we compute years of life lost due to premature mortality, using the methods outlined by Murray et al. (1994) and applied by Murray (1994).5 Estimation of years of life lost due to premature mortality provides a picture of the major causes of mortality, but not of avoidable premature death. To identify avoidable or excess years of life lost, we make comparisons with the rates of years of life lost observed for the Established Market Economies (Murray and Lopez, 1994). Excess years of life lost is then defined as the difference between observed years of life lost for each age and sex by cause and the number expected if the rates of the Established Market Economies are applied in a region. Excess years of life lost thus defined can be negative for a cause if the mortality rates by age and sex for a given disease are lower in a region than in the Established Market Economies.6 Results This section presents results for geographic patterns of mortality (1990), years of life lost due to premature mortality, and excess years of life lost for the Formerly Socialist Economies. Geographic Patterns of Mortality, 1990 Summary results for each of the NIS and Eastern European countries comprising the Formerly Socialist Economies are provided in Table 6-3a for males and 6-3b for females. These tables provide 5q0 (the probability of death between birth and age 5); 45q15 (the probability of death between ages 15 and 60); 10q60 (the probability of death between ages 60 and 70); and e(0), or life expectancy at birth. Within the group of Formerly Socialist Economies, 5q0 ranges from 15 to 95 per 1,000 for boys and 11 to 78 for girls. Among adults, male 45q15 ranges from 194 to 305 per 1,000 and female 45q15 from 94 to 155. The high level and extensive range of adult male mortality is most remarkable. Adult male mortality in the Russian Federation, for example, is equal to that of India, whereas adult Russian women enjoy mortality that is 52 percent lower than in India. The Formerly Socialist Economies are not a homogeneous group as most

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--> TABLE 6-3a Child and Adult Mortality in the Formerly Socialist Economies, Males, 1990   5q0 per thousand 45q15 per thousand 10q60 per thousand e(0) Country Armenia 38.8 194.8 267.7 67.7 Azerbaijan 65.5 238.9 289.2 65.1 Belarus 21.1 272.1 291.5 66.0 Estonia 22.9 269.6 315.2 64.9 Georgia 34.3 218.4 272.2 67.5 Kazakstan 47.5 293.0 338.7 63.0 Kyrgyz 63.1 267.7 301.4 63.1 Latvia 22.8 290.8 315.2 64.3 Lithuania 18.1 276.0 287.0 66.2 Moldova 37.2 270.6 296.6 65.2 Russian Federation 29.3 303.5 336.0 63.5 Tajikistan 85.8 193.7 238.0 65.2 Turkmenistan 94.6 269.6 321.9 61.1 Ukraine 26.3 270.3 308.0 65.2 Uzbekistan 70.0 225.8 264.8 64.7 Bulgaria 20.3 216.5 270.9 68.2 Czechoslovakia 14.9 242.6 329.2 67.3 Hungary 18.8 305.2 332.6 65.1 Poland 20.1 263.4 308.2 66.5 Romania 36.5 233.4 267.1 66.4 Yugoslavia 27.2 194.9 265.6 69.0   SOURCE: Vital registration data and adjusted mortality rates. analyses tacitly assume. Figure 6-2 shows child mortality (5q0) on the x-axis and adult male mortality (45q15) on the y-axis. Three clusters of countries can be identified by simple inspection: a group with moderate child and moderate adult mortality, a group with low child and low adult mortality, and a group with low child and high adult mortality. Remarkably, each of these clusters contains a set of geographically contiguous countries. In fact, the countries are arrayed on the diagram in a manner that approximates a map of the Formerly Socialist Economies. Accordingly, we have divided the countries into three groups, which we term Central Asia, South FSE (for Formerly Socialist Economies), and North FSE. Notably, Kazakstan, which is sometimes included with the four Central Asian republics, is on the demographic boundary with North FSE in terms of the child-adult mortality map. We have included it with North FSE because of its high adult mortality. Summary measures for each of the three regions are provided in Table 6-4. As the table shows, even if adult mortality is adjusted for underregistration, the Central Asian republics remain a distinct cluster with high child and moderate adult mortality.

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--> Figure 6-6b Hypertension and high total cholesterol among women. Source: World Health Organization (1994). of adult male mortality in the region than in other parts of Europe. Given that the systems in South FSE and Central Asia are probably similar to if not worse than those in North FSE, the health system is unlikely to be the primary contributor to the problem. However, it is quite possible that adult mortality would be much lower with a better health system. Of note, the marked decline in noncommunicable disease mortality experienced since 1980 in West Europe among males and females has not occurred in North FSE. Perhaps some of this is due to medical technology that has not come into common use in the latter region. Communism. In reviewing the list of likely explanations, Eberstadt (1990, 1993) has argued that not all of the increase in adult male mortality can be attributed to smoking, alcohol, diet, and pollution. Some, he argues, may be due to the communist system itself. Life under an oppressive communist regime may increase cardiovascular disease mortality. Clearly, similar excesses of adult male mortality are not present so far in South FSE, Central Asia, or for that matter China. On the other hand, the increase in adult male mortality in all these countries began at the same time (1964-1965), which is difficult to ascribe to coincidence. As the above discussion suggests, the set of causes that explains the unusual adult male mortality levels and trends in North FSE remains poorly defined. Further studies building on increasingly available data may elucidate the mix of factors responsible. Yet health reform and the design of a health policy response to the health problems in North FSE need not await these more sophisticated studies. Many of the problems, such as lung cancer, ischemic heart disease, and motor vehicle accidents, can be attacked now with cost-effective interventions.

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--> Conclusions Several conclusions emerge from the above analysis. First, the Formerly Socialist Economies are not a homogeneous group. Mortality indicators suggest that these countries can be divided into three groups: Central Asia, North FSE, and South FSE. There is no clear difference between the former republics of the Soviet Union and East European states in terms of mortality indicators within the South and North FSE regions. The three regions have distinct epidemiological profiles that call for different health sector policies. The current practice of generalizing across all Formerly Socialist Economies in many development agency reports should be discouraged. Second, in North FSE, adult male mortality is markedly higher than expected based on income per capita or achievements in child mortality. This excess is probably caused by many factors, but the major contributors are cardiovascular disease, unintentional and intentional injuries, and lung cancer. Efforts to address this unusual mortality and cause-of-death profile must focus on the extraordinary conditions of adult males in the region. Addressing the widening health gap between men and women and children in the same society must be the number one health priority for this region. Third, the fact that adult male mortality is so high in North FSE and has risen in most countries in that region since 1964 defines a new route in the epidemiological transition. In most Western, Latin American, and Asian countries with long series of vital registration data, development has been accompanied by mortality reduction at all ages (Feachem et al., 1992). There are some exceptions: adult male mortality rose modestly over a brief period in the United States from 1961 to 1968 and in the United Kingdom during the 1920s (Blane et al., 1990). These episodes of mortality increase, however, are of a different magnitude than the increases witnessed over 30 years in North FSE. The declines in age-specific mortality rates witnessed in nearly all these countries occurred despite rising levels of smoking, increased sedentary lifestyles, increasing fat intake, and other behavioral changes that are known to be risk factors for ischemic heart disease. Is the unfortunate experience of North FSE an historic anomaly, or is it a route of the epidemiological transition that could be repeated in some developing countries? The answer to that tantalizing question rests in the reasons for the mortality increase in North FSE. Evidence from Latin America suggests that reversals in mortality and morbidity are not uncommon (Frenk et al., 1996). Further work on defining the determinants of the North FSE mortality pattern and adverse trends is required before a reasoned answer can be provided. Fourth, practically all the Formerly Socialist Economies had systems of financing and health care provision based almost entirely on the state. The irony is that the greatest neglect in control interventions was for those adult diseases and injuries that fell unequivocally under the state's responsibility. Government failure seems to be one of the ultimate causes for the epidemiological profile

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--> described here, but government intervention is what is needed to counter it, at least for the public health component of the response to the mortality increase. The clinical services required to control communicable diseases and to treat injuries are largely in place in all the countries studied, but the quality of care leaves much to be desired. Policies for selection of the most cost-effective interventions and investments to improve the associated quality of care need to be implemented in the Formerly Socialist Economies. We conclude by reiterating that the main findings from this chapter and the conclusions presented above are unlikely to be affected by errors in the completeness of death registration or in the coding of causes of death. Acknowledgments The authors gratefully acknowledge the contributions to this study made by Alan Lopez, Robert Hartford, Francis Notzon, Xinjian Qiao, Magda Orzeszyna, and the World Bank's Eastern Europe division. References Anderson, B., and B. Silver 1988 The effect of the registration system on the seasonality of births: The case of the Soviet Union. Population Studies 42:303-320. 1989 Demographic sources of the changing ethnic composition of the Soviet Union. Population and Development Review 15(4):609-655. 1990 Trends in mortality of the Soviet population. Soviet Economy 6(3):191-251. 1991 Mortality Trends in the Working Ages: Soviet Regions in Comparative Perspective, 1959-1988. University of Michigan Research Report #91-208. Ann Arbor, MI: Population Studies Center. Bennett, N., and L. Garson 1983 The centenarian question and old-age mortality in the Soviet Union, 1959-1970. Demography 20(4):587-606. Bennett, N., and S. Horiuchi 1981 Estimating the completeness of death registration in closed populations. Population Index 47(2):207-221. Blane, D., G. Davey-Smith, and M. Bartley 1990 Social class differences in years of potential life lost: Size, trends and principal causes. British Medical Journal 301(1 September):429-432. Blum, A., and A. Monnier 1989 Recent mortality trends in the USSR: New evidence. Population Studies 43:211-241. Coale, A.J., and P. Demeny 1966 Regional Model Life Tables and Stable Populations. Princeton, NJ: Princeton University Press. Coale, A.J., P. Demeny, and B. Vaughan 1983 Regional Model Life Tables and Stable Populations, Second ed. New York: Academic Press. Cooper, R. 1981 Rising death rates in the Soviet Union. The impact of coronary heart disease. New England Journal of Medicine 304(21): 1259-1265.

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--> 1983 Epidemiologic features of recent trends in coronary heart disease in the Soviet Union. Journal of the American College of Cardiology 2(3):557-64. 1985 Smoking and health in the Soviet Union and Eastern Europe. New York State Journal of Medicine 85(7):413-415. 1987 Has the period of rising mortality in the Soviet Union come to an end? International Journal of Health Services 17(3):515-519. Cooper, R., and C. Sempos 1984 Recent mortality patterns associated with economic development in Eastern Europe and the USSR. Journal of the National Medical Association 76(2): 163-166. Cooper, R., and A. Schatzkin 1982a The pattern of mass disease in the USSR: A product of socialist or capitalist development. International Journal of Health Services 12(3):459-480. 1982b Recent trends in coronary risk factors in the USSR. American Journal of Public Health 72(5):431-440. Davis, C., and M. Feshbach 1980 Rising Infant Mortality in the Soviet Union in the 1970s. Series P 95-74. Washington D.C.: US Bureau of the Census. Deev, A.R., and R.G. Oganov 1989 Trends and determinants of the cardiovascular mortality in the Soviet Union. International Journal of Epidemiology 18(3 Supplement):S 137-S 144. Dutton, J. 1979 Changes in Soviet mortality patterns, 1959-77. Population and Development Review 5:267-291. 1981 Causes of Soviet adult mortality increases. Soviet Studies 33(4):548-559. Eberstadt, N. 1990 Health and mortality in Eastern Europe, 1965-85. Communist Economies 2(3):347-371. 1993 Mortality and the fate of Communist states. Communist Economies and Economic Transformations 5(4):499-517. Feachem, R.G., T. Kjellstrom, C.J.L. Murray, M. Over, and M.A. Phillips. eds. 1992 The Health of Adults in the Developing World. New York: Oxford University Press for the World Bank Frenk, J., J.L. Bobadilla.. and R. Lozano 1996 The epidemiological transition in Latin America. In I. M. Timaeus. J. Chackiel, and L. Ruzicka eds. Adult Mortality in Latin America. Oxford:Clarendon Press. Forster, D.P., and P. Jozan 1990 Health in Eastern Europe. Lancet 335:458-460. Goskomstat USSR (USSR Government Committee on Statistics) 1987 Alphabetical Index: Designated Causes of Death and Their Coding. Moscow: Goskomstat USSR. Jones, E., and F.W. Grupp 1983 Infant mortality trends in the Soviet Union. Population and Development Review 9(2):213-241. Jozan, P. 1989 Some features of mortality in postwar Hungary: The third epidemiological transition. Cahiers de Sociologie et de Démographie Médicales 29(1):21-42. Lopez, A. 1989 Causes of Death Among Adults Aged 15-59 Years. Geneva: Division of Global Epidemiological Surveillance and Health Situation Assessment, World Health Organization. Medvedev, Z.A. 1985 Negative trends in life expectancy in the USSR, 1964-1983. Gerontologist 25(2):201-208.

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--> Meslé, F., V. Shkolnikov, and J. Vallin 1993 Mortality by cause in the USSR in 1970-1987: The reconstruction of time series. European Journal of Population 8:281-308. Murray, C.J.L. 1994 Quantifying the burden of disease: The technical basis for disability adjusted life years. Bulletin of the World Health Organization 73(3) June. Murray, C.J.L., G. Yang, and C. Qiao 1992 Adult mortality: Levels, patterns and causes. In R.G. Feachem, T. Kjellstrom, C.J.L. Murray, M. Over, and M. Phillips, eds., Adult Health in Developing Countries. New York: Oxford University Press. Murray, C.J.L., and A.D. Lopez 1994 Quantifying the burden of disability: Data, methods, and results. Bulletin of the World Health Organization 73(3) June. Murray, C.J.L., A.D. Lopez, and D. Jamison 1994 Global burden of disease in 1990: Summary results, sensitivity analysis and future directions. Bulletin of the World Health Organization 73 (3)June. NTC 1992 World drinks trends 1992. Produktschap voor Gedistilleerde Dranken. Henley-on-Thames, England: NTC Publications Ltd. Peto, R., A.D. Lopez, J. Boreham, M. Thun, and C. Heath 1992 Mortality from tobacco in developed countries: Indirect estimation from national vital statistics. Lancet 339(23 May): 1268-1278. 1994 Mortality from Tobacco in Developed Countries. Oxford: Oxford University Press. Ryan, M. 1982 Aspects of male mortality. British Medical Journal 284:181-182. 1988 Infant mortality in the Soviet Union. British Medical Journal 296:850-851. Stolnitz, G.J. 1974 International Mortality Trends: Some Main Facts and Implications. Background paper for United Nations World Population Conference (E/Conf. 60/CBP/17), Bucharest. Treml, V.G. 1982 Death from alcohol poisoning in the USSR. Soviet Studies 34(4):487-505. United Nations 1983 Manual X: Indirect Techniques for Demographic Estimation. New York: United Nations. U.S. Department of Agriculture 1993 Foreign Agricultural Service—Tobacco, Cotton and Seeds Division. Unpublished data. Washington, D. C. World Bank 1993 World Bank Development Report 1993. Washington, DC: World Bank. World Health Organization 1994 Ecological analysis of the association between mortality and major risk factors of cardiovascular disease. International Journal of Epidemiology 23(3):505-516. Notes 1.   Table 1-1 in Chapter 1 of this volume shows the countries encompassed by various terms used to designate groupings of countries in the region. 2.   Data were provided by the U.S. National Center for Health Statistics. The countries analyzed were Australia, Austria, Belgium, Canada, Chile, Costa Rica, Cuba, Czechoslovakia, Denmark, England and Wales, Finland, France, German Democratic Republic, German Federal Republic, Greece. Hong Kong, Hungary, Ireland, Israel, Italy, Japan, The Netherlands, New Zealand, Northern Ireland,

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-->     Norway, Poland, Portugal, Puerto Rico, Scotland, Singapore, Sweden, Switzerland, the United States (separated into black and white populations), and Yugoslavia. 3.   The logit transformation was used to convert the data into a linear form required by ordinary least squares (OLS) regression. 4.   We also attempted to apply the generalized growth balance method, where intercensal growth rate data are used on the left-hand side of the growth balance equation. That method, however, did not perform well, and the results are not shown. 5.   We have chosen to measure the importance of each cause of death in this way to be consistent with the recent work on global patterns of causes of death and the burden of disease. The number of years of life lost due to a death at each age is based on the expectation of life at each age from model life table West, Level 26 (Coale and Demeny, 1966). Streams of lost life due to death at each age have been adjusted by incorporating age weights so that years of life that would have been lived as an adult aged 15-59 are given more weight than years of life at younger or older ages. Finally, the age-weighted streams of years of life lost due to premature mortality have been discounted at a rate of 3 percent. The method of calculating years of life lost is described more fully elsewhere (Murray, 1994). 6.   Established Market Economies include Portugal, Greece, Ireland, New Zealand, Spain, The United Kingdom, Australia, Italy, The Netherlands, Belgium, Austria, France, Canada, United States, Germany, Denmark, Finland, Norway, Sweden, Japan, Switzerland, and 14 other economies with a population of less than 500,000(World Bank, 1993). 7.   International dollars are calculated using purchasing power parity ratios, which reflect the relative values of currencies, taking into account local prices of goods and services.

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--> Annex Table 6-1

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--> ANNEX TABLE 6-1 Detailed Years of Life Lost Attributable to Major Causes by Country. 1990   North FSE Cause Belarus Estonia Kazakstan Latvia Lithuania I. Communicable, Maternal & Perinatal 66,149 11,237 476,597 19,533 19,984    Infectious and Parasitic 18,088 2,448 118,917 7,155 6,313       Tuberculosis 5,301 1,013 26,313 2,652 3,287       Diarrheal diseases 1,836 206 48,188 190 577       Meningitis 4,423 564 12,219 1,339 1,114       Hepatitis 488 80 6,688 203 258    Respiratory infections 19,153 2,304 218,373 3,239 2,653    Maternal 1,114 266 3,963 624 463    Perinatal 28,965 6,289 138,403 8,820 11,056 II. Noncommunicable 669,917 113,305 895,005 198,408 239,587    Malignant Neoplasm 179,428 30,589 238,674 52,429 64,623       Esophagus 2,907 571 20,155 1,013 963       Stomach 33,318 4,210 36,510 7,350 8,418       Colon/rectum 14,245 2,352 14,859 4,549 5,351       Lung 34,897 6,510 48,455 10,800 12,736       Breast 11,965 2,446 13,278 3,884 5,665       Cervix 3,486 858 6,479 1,079 2,092       Lymphoma/leukemia 15,637 2,479 18,625 4,185 5,848    Diabetes 4,848 1,161 9,321 1,820 1,859    Nutritional endocrine 3,221 751 7,944 1,326 1,577       anemia n.a. n.a. n.a. n.a. n.a.    Neuropsychiatric 18,940 2,875 25,270 4,582 9,786    Cardiovascular 348,719 62,343 408,485 109,363 122,562       Ischemic heart disease 209,245 38,071 198,752 62,725 83,576       Cerebrosvascular 95,599 17,997 131.578 34,979 27,163    Respiratory 43,827 3,046 60,223 5,659 10,809    Digestive 21,943 3,874 49,528 6,329 8,159       Cirrhosis 7,216 944 22,160 1,514 3,308    Genito-urinary 13,439 1,924 22,889 4,579 5,238    Congenital 29,656 4,849 65,321 10,663 12,850 III. Injuries 208,657 35,127 358,351 68,670 88,348    Unintentional 148,966 24,383 260,216 50,881 63,543       Motor vehicle accidents 58,154 9,770 95,762 24,698 28,876       Poisoning 30,830 3,579 35,285 4,502 7,480       Fall 8,497 2,160 12,718 4,536 6,480       Fire 4,261 1,355 10,446 3,143 1,594       Drowning 20,571 2,666 33,428 7,627 10,492    Intentional 59,691 10,744 98,135 17,790 24,805       Suicide 43,639 7,894 61,807 12,403 19,950       Homicide 16,052 2,851 36,328 5,386 4,856 Total 944,723 159,670 1,729,953 286,611 347,919 n.a. = not available

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--> Cause Moldova Russia Ukraine Czechoslovakia Hungary Poland I. Communicable, Maternal & Perinatal 70,673 1,598,546 391,568 89,917 67,032 268,350    Infectious and Parasitic 441,572 16,724 132,595 7,709 12,746 58,598       Tuberculosis 4,023 189,186 65,475 2,379 6,802 16,875       Diarrheal diseases 3,675 72,919 11,116 471 204 1,736       Meningitis 3,570 72,080 24,172 2,058 2,646 11,947       Hepatitis 1,739 14,021 4,242 452 255 2,917    Respiratory infections 28,123 430,214 92,995 38,080 14,350 55,440    Maternal 803 29,724 6,414 419 735 1,946    Perinatal 25,126 714,294 163,051 44,334 39,658 153,439 II. Noncommunicable 286,195 10,175,652 3,743,760 1,145,294 983,476 2,642,410    Malignant Neoplasm 66,131 2,803,127 1,007,144 345,048 282,013 716,789       Esophagus 1,182 77,677 18,676 5,621 6,865 11,934       Stomach 6,995 498,669 146,700 24,027 21,436 60,610       Colon/rectum 6,184 239,302 88,678 40,567 31,992 54,252       Lung 12,625 612,074 214,227 75,345 68,836 170,001       Breast 5,603 182,424 76,290 24,123 20,861 47,882       Cervix 1,763 61,894 24,685 7,593 7,330 25,166       Lymphoma/leukemia 7,082 218,590 83,729 40,007 29,118 80,889    Diabetes 3,156 80,844 28,024 19,744 14,753 47,162    Nutritional endocrine 2,508 50,686 23,220 4,671 5,423 15,138       anemia n.a. n.a. n.a. 926 968 3,201    Neuropsychiatric 8,879 253,833 98,402 28,484 31,097 78,273    Cardiovascular 122,115 5,363,031 1,935,622 590,377 485,998 1,312,738       Ischemic heart disease 68,277 2,734,970 1,040,814 307,213 202,391 401,671       Cerebrosvascular 38,736 1,788,185 584,283 155,493 130,658 185,295    Respiratory 14,271 496,772 222,545 29,397 36,917 67,271    Digestive 42,896 422,347 165,188 85,632 111,416 113,857       Cirrhosis 31,705 135,631 68,192 51,040 79,561 42,661    Genito-urinary 5,120 188,442 66,838 26,998 10,764 41,914    Congenital 18,734 419,457 162,183 26,207 21,241 98,009 III. Injuries 102,341 3,947,935 1,063,296 195,324 194,538 578,825    Unintentional 78,277 2,705,250 772,342 138,082 118,758 442,427       Motor vehicle accidents 35,964 1,035,106 318,948 50,208 56,716 197,840       Poisoning 8,255 513,406 152,005 9,628 4,917 57,200       Fall 4,570 128,088 41,749 29,205 25,846 44,266       Fire 2,239 84,070 16,998 2,532 3,281 7,938       Drowning 9,879 338,464 93,302 10,100 7,936 37,084    Intentional 24,064 1,242,685 290,954 57,256 75,699 136,406       Suicide 15,509 779,248 203,171 50,308 68,985 111,526       Homicide 8,555 463,436 87,783 6,945 6,710 24,925 Total 459,208 15,722,132 5,198,624 1,430,465 1,245,038 3,489,650

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-->   South FSE Cause Armenia Georgia Romania Yugoslavia I. Communicable, Maternal & Perinatal 72,732 97,963 357,400 200,552    Infectious and Parasitic 17,145 21,664 74,548 44,510       Tuberculosis 1,481 5,642 22,029 9,722       Diarrheal disease 8,544 5,600 9,848 22,735       Meningitis 487 2,169 13,936 3,917       Hepatitis 229 195 7,814 934    Respiratory infection 31,766 48,683 218,668 40,579    Maternal 496 1,120 17,015 1,090    Perinatal 24,283 27,085 n.a. 86,986 II. Noncommunicable 147,412 309,071 1,706,681 1,007,686    Malignant Neoplasm 37,464 60,458 366,894 265,926       Esophagus 590 831 3,128 4,108       Stomach 4,519 6,975 36,990 24,646       Colon/rectum 2,578 3,816 25,527 21,648       Lung 7,725 10,782 75,302 58,023       Breast 3,957 7,790 28,465 21,551       Cervix 981 2,182 22,240 5,602       Lymphoma/leukemia 4,224 6,584 50,424 31,688    Diabetes 3,742 5,671 16,974 19,513    Nutritional endocrine 1,482 1,100 9,413 5,955       anemia n.a. 1,587 1,133 579    Neuropsychiatric 3,490 4,723 74,187 33,871    Cardiovascular 69,500 194,385 866,168 482,130       Ischemic heart disease 43,951 117,140 263,727 118,260       Cerebrosvascular 18,167 67,699 239,944 129,940    Respiratory 6,964 9,905 98,059 28,992    Digestive 8,626 19,517 162,303 62,436       Cirrhosis 2,681 12,359 90,788 38,930    Genito-urinary 3,907 6,516 37,431 18,391    Congenital 10,481 4,998 94,913 27,458 III. Injuries 43,476 60,922 345,298 173,445    Unintentional 39,957 51,614 345,298 120,696       Motor vehicle accident 13,019 21,428 n.a. 58,307       Poisoning 1,058 2,981 n.a. 3,078       Fall 2,286 3,114 n.a. 7,928       Fire 968 3,427 n.a. 1,930       Drowning 1,217 4,360 n.a. 6,422    Intentional 3,519 9,308 n.a. 52,705       Suicide 1,556 4,202 n.a. 46,116       Homicide 1,963 5,106 n.a. 6,563 Total 263,620 467,956 2,409,391 1,381,675 n.a. = not available

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-->     Central Asia Cause Bulgaria Azerbaijan Kyrgyz Tajikistan Turkmenistan Uzbekistan I. Communicable, Maternal & Perinatal 65,612 319,242 237,419 488,018 329,818 1.332,535    Infectious and Parasitic 10,224 86,607 51,591 186,627 106,454 332,293       Tuberculosis 2,457 8,486 4,513 3,407 5,982 20.752       Diarrheal disease 1,412 50,758 24,586 123,555 72,083 160.521       Meningitis 1,869 1,648 5,966 9,615 3,584 18,297       Hepatitis 887 4,793 8,751 15,528 11,149 92,269    Respiratory infection 40,488 192,115 138,840 244,084 180,478 735.780    Maternal 633 980 1,076 1,549 1,417 5,464    Perinatal 14,318 46,270 46,861 74,741 47,350 264,254 II. Noncommunicable 677,313 338,135 200,982 197,974 187,624 818.701    Malignant Neoplasm 151,471 61,824 37,006 35,796 28,717 136.519       Esophagus 2,850 3,924 1,354 2,763 5,995 15,238       Stomach 18,603 10,834 7,039 6,294 3,437 19.421       Colon/rectum 16,218 3,909 2,546 3,603 1,796 8,070       Lung 31,869 10,114 6,551 4,669 2,651 16,257       Breast 12,174 3,661 2,087 1,831 1,154 7,160       Cervix 3,587 1,236 1,307 1,008 885 3.312       Lymphoma/leukemia 16,853 7,078 3,489 5,822 3,536 18,745    Diabetes 13,993 5,459 1,995 3,806 2,578 11,299    Nutritional endocrine 1,851 14,025 3,017 3,683 5,617 21,709       anemia n.a.   n.a.   n.a.      Neuropsychiatric 12,979 18,982 6,725 10,400 8,316 44,665    Cardiovascular 400,596 159,192 89,826 79,085 89,123 364,334       Ischemic heart disease 135,703 96,490 40,934 40,001 46,240 207,385       Cerebrosvascular 133,364 36,796 33,128 20,502 14,627 101,101    Respiratory 18,223 16,209 20,623 13,679 11,217 49,085    Digestive 33,828 21,128 16,547 26,353 21,106 73.640       Cirrhosis 17,686 11,517 9,208 7,344 8,143 38,588    Genito-urinary 14,570 10,227 6,691 9,930 5,098 34,930    Congenital 16,804 29,153 15,949 12,836 14,753 73,393 III. Injuries 103,975 68,343 85,988 63,409 55,146 299,622    Unintentional 77,604 61,040 68,889 56,390 45,768 247,091       Motor vehicle accident 31,643 25,424 26,833 15,242 14,501 82,672       Poisoning 5,115 2,331 6,339 2,839 2,423 11,109       Fall 7,517 2,864 3,642 3,782 2,467 10,527       Fire 2,312 5.743 1,163 4,805 3,828 14,929       Drowning 6,002 5,511 10,960 11,345 10,849 49,221    Intentional 26,400 7,303 17,099 7,019 9,377 52,531       Suicide 19,854 4,057 10,397 466 4,852 29,520       Homicide 6,508 3,245 6,703 2,553 4,525 23,011 Total 847,026 725,720 524,390 749,401 572,588 5,022,957