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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.
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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
Representative terms from entire chapter:
north fse
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