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National Research Council (US) Panel on Understanding Divergent Trends in Longevity in High-Income Countries; Crimmins EM, Preston SH, Cohen B, editors. International Differences in Mortality at Older Ages: Dimensions and Sources. Washington (DC): National Academies Press (US); 2010.

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International Differences in Mortality at Older Ages: Dimensions and Sources.

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14The Divergent Life-Expectancy Trends in Denmark and Sweden—and Some Potential Explanations

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INTRODUCTION

A priori it could be expected that Denmark was among the countries with the longest life expectancy in the world for both men and women due to the fact that other Nordic countries are among the world's leaders in life expectancy. In the period 1950-1980, life expectancy in Denmark was indeed among the highest in the world, but at the beginning of the new millennium its relative position in the world with regard to life expectancy had changed. In 2000, a life-expectancy chart for 20 Organisation for Economic Co-operation and Development (OECD) countries put Denmark close to the bottom. In particular, the difference between Denmark and its Nordic neighbor, Sweden, countries separated by only a few miles of water, is intriguing. Sweden maintained its position among the world leaders in life expectancy throughout the 20th century and made significant gains in comparison to Denmark. The life-expectancy difference between Sweden and Denmark grew from marginal in the 1950s to 3 years in the early 1990s (Juel, 2008). Starting in the mid-1990s, life expectancy in Denmark (as well as in Sweden) increased annually at a rate corresponding to that of the best-performing countries, although Denmark has been unable to catch up.

This chapter describes the trends in overall mortality and cause-specific mortality, suggests some underlying determinants of reduced life span in Denmark, and compares Denmark with other countries, in particular Sweden. The chapter consists of two parts: a descriptive section with data describing the secular trends and a discussion section that provides a number of possible explanations for the Danish trajectory, which shows improvement-stagnation-improvement but no catch-up for life expectancy at birth and at age 65.

SECULAR TRENDS

Life Expectancy in Denmark

In the 1950s, Denmark was a world leader in life expectancy for both men and women, along with Sweden and the Netherlands, which are usually considered to be very similar to Denmark in many aspects of society. A parallel increase in life expectancy for these three countries, most pronounced for women, was seen during the three decades leading up to 1980, which marked the beginning of a stagnation period of 10-15 years in Denmark (see Figure 14-1a). The Netherlands experienced a later and shorter stagnation period, and Sweden continued with positive development throughout the 20th century. From the mid-1990s, Denmark experienced an annual increase in life expectancy corresponding to that of the best-performing countries, but Danish longevity has not been able to catch up with Sweden. Denmark's trajectory—improvement-stagnation-improvement but no catch-up—is found also for life expectancy at age 65 (see Figure 14-1b) and at age 80 for men. For women at age 80, however, the trajectory is not so clear (see Figure 14-1c). This development over the second half of the 20th century means that Denmark's position in life expectancy dropped from rank 3 among 20 OECD countries in the 1950s to rank 17 for men and 20 for women in 2000, while Sweden maintained its position near the top, especially for men (see Figure 14-2) (Juel, 2008).

Six multiline graphs showing life expectancy in Denmark and other high-income countries: (a) at birth (b) age 65 (c) age 80

FIGURE 14-1

Life expectancy in Denmark and other high-income countries. At birth At age 65 At age 80

Bar graph showing Denmark™s and Sweden′s rank in life expectancy at birth among 20 OECD countries

FIGURE 14-2

Denmark's and Sweden's rank in life expectancy at birth among 20 OECD countries.

Another informative way to illustrate this development is by looking at the annual increase in life expectancy. Oeppen and Vaupel (2002) show that “best-practice” life expectancy, that is, the highest value recorded in a single country in a given year, rose by about 2.5 years every decade (2.43 years) for women, starting in 1840. Male life-expectancy improvements occurred at the slightly slower pace of 2.22 years per decade. A comparison of Denmark's life-expectancy improvement increases with these best-practice increases (see Figure 14-3a) shows that, in the middle and at the end of the 20th century, Denmark had attained best-practice life-expectancy increases for women, while for men best-practice increases were only seen at the end of the period. In the late 1980s and the early 1990s, Denmark's life-expectancy improvement rates were close to zero. The pattern at age 65 is similar to the patterns described above but less pronounced and are even less so at age 80 (see Figures 14-3b and 14-3c).

Ten plots of annual increase in life expectancy: (a) at birth (b) age 65 (c) age 80

FIGURE 14-3

Annual increase in life expectancy. At birth At age 65 At age 80

In Sweden, life expectancy at birth for women in 2007 reached 83 years; for women who survived to age 83, remaining life expectancy was 7.5 additional years. Life disparity can be measured as the average remaining life expectancy at the ages when death occurs: in Sweden, a female death shortly after birth would contribute 83 years, whereas a death at age 83 would contribute 7.5 years. The average of such values, weighted by the number of deaths at each age, gives a life disparity of 9 (Zhang and Vaupel, 2009). Zhang and Vaupel (unpublished) performed analyses of the correlation between life disparity in a specific year and life expectancy in that year for men and women in 33 countries and regions. They found that during the 168 years from 1840 to 2007, 113 holders of record life expectancy also had the lowest life disparity. Countries with long life expectancy tend to have low life disparity because these countries have been successful in reducing premature deaths—doing so increases life expectancy and reduces life disparity. That is, efforts to avert deaths that occur at ages well below the life expectancy of a population appear to be especially effective in increasing life expectancy—and, simultaneously, reducing life disparity. Analyses of life disparity in Denmark show that a slowing of progress in reducing differentials in life spans occurred at about the same time as the slowing of progress in increasing life expectancy (see Figures 14-4a and 14-4b).

Life expectancy (e0) and life disparity (eƒ) over time for Danish women and men.

FIGURE 14-4

Life expectancy (e0) and life disparity (e) over time for Danish women and men. Men Women NOTE: Life disparity is a measure of discrepancies in life spans; it is calculated as the average remaining life expectancy at the ages of death (Zhang (more...)

Cause-Specific Mortality in Denmark

Analyses of cause-specific mortality for men and women in Denmark show that mortality rates from major causes of death, such as heart disease, have declined since the 1970s. However, lung cancer mortality increased for women throughout the second half of the 20th century. For men the increase was more pronounced until around 1980, when the rate stabilized. For alcohol-related mortality, an increase is seen from 1970 onward for both genders, again most pronounced for men. Denmark is now among the countries with the highest tobacco- and alcohol-related mortality rates in 20 OECD countries (see Figures 14-5a and 14-5b), when alcohol-related deaths are calculated from alcohol-related diagnoses from death certificates and tobacco-related deaths are calculated from the method of Peto et al. (1992).

Two bar graphs showing Denmark™s rank among the 20 OECD countries for (a) tobacco-related mortality (b) liver cirrhosis

FIGURE 14-5

Denmark's rank among the 20 OECD countries for (a) tobacco-related mortality and (b) liver cirrhosis. Tobacco-related mortality Liver cirrhosis

These cause-specific mortality rates correspond to the trend in the incidence of major underlying diseases. Figure 14-6 shows the dramatic increase in lung cancer among women in Denmark compared with other countries in the same time period. Figure 14-7 shows the dramatic decline in heart disease mortality in all the study countries, with Denmark, however, still having the highest mortality among women at the end of the period.

Multiline graph showing lung cancer mortality for women ages 35-74 (age standardized rates)

FIGURE 14-6

Lung cancer mortality for women ages 35-74 (age-standardized rates).

Two multiline graphs showing heart disease mortality at ages 35-74 (age-standardized rates): (a) men (b) women

FIGURE 14-7

Heart disease mortality at ages 35-74 (age-standardized rates). Men Women

Peto et al. (1992) developed a method that uses absolute age- and sex-specific lung cancer rates to indicate the approximate proportions of deaths due to tobacco not only from lung cancer itself but also, indirectly, from vascular disease and various other categories of disease. This method was applied by Brønnum-Hansen and Juel (2000) to Danish data from the early 1990s, and it shows that 35 percent of deaths among men and 25 percent of deaths among women were attributable to cigarette smoking. Brønnum-Hansen and Juel (2000) also applied a simulation model (Prevent), in which a multifactorial generalization of the etiological fraction is used, including information on several diseases and time dimensions simultaneously. The two methods are fundamentally different, but they give approximately the same results. The Prevent model estimated that 33 percent of deaths among men and 23 percent of deaths among women in the early 1990s were from chronic bronchitis, emphysema, ischemic heart disease, lung cancer, and stroke caused by cigarette smoking.

Life Expectancy in Denmark and Sweden

A comparison of life expectancy in Denmark and Sweden is particularly interesting due to their differences (their very divergent life-expectancy trends) and their similarities (close geographical and cultural proximity, both being Scandinavian welfare state countries, and having quite similar languages). In fact, Sweden is called broderfolket (“the brother people”) in Denmark, and the two countries are separated by only a few miles of water (see Figure 14-8). The divergent trend of the two countries is illustrated in the OECD rankings in Figure 14-2 and in Lexis surface diagrams (Andreev, 2002). The surface diagrams show that, since 1980, Sweden has had lower or equal mortality at practically all ages for all cohorts. For children and teenagers, the Swedish advantages go back to the 1960s and 1970s. For Danish women, a clear cohort effect is seen with very high mortality, especially after age 40, for women born between the two world wars compared with similar Swedish women.

Map of Nordic countries with a 3-year difference in life expectancy: A few miles of water separate Denmark and Sweden.

FIGURE 14-8

Neighboring Nordic countries with a 3-year difference in life expectancy: A few miles of water separate Denmark and Sweden.

Juel (2008) estimated how much smoking- and alcohol-related mortality could explain the differences in life expectancy and mortality patterns in Denmark and Sweden. Smoking-related mortality was estimated by the Peto et al. (1992) method, and alcohol-related mortality was estimated by selecting deaths for which the diagnosis was related to alcohol (alcohol intoxication, alcoholism, cirrhosis of the liver, and pancreatitis).

Based on data from 1997-2001, Juel shows that smoking- and alcohol-related mortality could explain nearly all the difference between Danish and Swedish men and approximately three-quarters of the difference between Danish and Swedish women.

Distribution of Lifestyle Risk Factors

National comparable survey data are available for the period when Denmark went from stagnating to increasing in life expectancy. Four nationally representative health interview surveys among adult Danes were conducted in 1987, 1994, 2000, and 2005 (Ekholm et al., 2009). Individuals were sampled from the centralized civil register (CRS) (Pedersen et al., 2006). The CRS, which has existed in Denmark for more than 40 years, is a nationwide civil register whose purposes are to administrate the unique personal identification number system, to administer general personal data reported from national registration offices to the CRS, and to forward personal data in a technically/economically suitable manner in accordance with the Register's Act and other legislation governing civil registration. Each cohort of Danes in the health interview surveys consists of a nationally representative sample, with oversampling of some counties. For each cohort, information was collected by face-to-face home interviews in three waves. A detailed description is provided in Ekholm et al. (2009).

The analyses presented here are based on Danish men and women between the ages of 35 and 64. After the age of 35, most individuals have finished their education, and before the age of 65, most are still labor force participants. The participation rates were 80 percent, 78 percent, 74 percent, and 67 percent in the four cohorts, respectively. Behavioral variables included were alcohol consumption, smoking behavior, physical activity, and body mass index (BMI). Smoking habits were defined as “never smoker,” “former smoker,” “light smoker,” and “heavy smoker” (≥ 15 cigarettes a day). Alcohol consumption was defined on the basis of a combination of number of drinks the last weekday and number of drinks the last weekend. High alcohol consumption is defined as drinking above moderate drinking limits (21 units of alcohol for men and 14 for women per week). Physical activity during leisure time was categorized as none (sedentary), little (light exercise), and moderate/heavy (regular exercise more than 4 hours per week or competitive sport). From self-reported information on body weight and body height, the BMI was calculated as weight in kilograms divided by the square of height in meters. BMI was categorized as “underweight” (BMI < 18.5), “normal weight” (18.5 ≤ BMI < 25), “overweight” (25 ≤ BMI < 30), and “obese” (BMI ≥ 30). The development from 1987 to 2005 is shown in Figures 14-9 through 14-12. The figures show that the improvement in Danish life expectancy that occurred in the mid-1990s co-occurs with a decrease in three mortality risk factors: smoking, alcohol consumption, and sedentary lifestyle, while one risk factor, the obesity rate, goes up, albeit to a low level compared with, for example, the United States (see Chapter 6, in this volume). A recent study shows the great impact of these risk factors on Danish life expectancy (Juel, Sorensen, and Bronnum-Hansen, 2008).

Two-line graph showing proportion (%) of smokers in Denmark among men and women ages 35-64

FIGURE 14-9

Proportion (%) of smokers in Denmark among men and women ages 35-64. SOURCE: National Institute of Public Health, Copenhagen. Figures from the National Health Interview Surveys (2009).

Two-line graph showing alcohol consumption in Denmark among men and women ages 35-64.

FIGURE 14-10

Alcohol consumption in Denmark among men and women ages 35-64. NOTE: Proportion (%) drinking over moderate drinking limits. Alcohol consumption was defined on the basis of a combination of the number of drinks consumed the last weekday and the number (more...)

Two-line graph showing proportion (%) of obese persons in Denmark among men and women ages 35-64

FIGURE 14-11

Proportion (%) of obese persons in Denmark among men and women ages 35-64. NOTES: From self-reported information on body weight and body height, the BMI was calculated as weight in kilograms divided by the square of height in meters. BMI was categorized (more...)

Two-line graph showing proportion (%) of sedentary persons in Denmark for men and women ages 35-64

FIGURE 14-12

Proportion (%) of sedentary persons in Denmark among men and women ages 35-64. NOTE: Physical activity during leisure time was categorized as none (sedentary), little (light exercise), and moderate/heavy (regular exercise more than 4 hours per week or (more...)

The Health Care System

There has been a long-standing debate concerning the extent to which the level of investment in the Danish health care system could account for part of the difference in life expectancy in Denmark and Sweden. Both countries base their health care policy on the Scandinavian universal welfare state model, with free and equal access to health care. Using the OECD figures for health care expenditures (see http://www.oecd.org [accessed June 8, 2010]), Denmark and Sweden have very similar expenditures when measured as a percentage of each nation's gross domestic product (GDP). It has been argued, however, that in Denmark, unlike Sweden and many other countries, elder care (nursing homes and municipal support) is part of the official health care budget and thus raises health care expenditures by its inclusion (Søgaard, 2008). Considering that elder care is very well developed in Denmark, this entails substantial expenditures. It has been argued that if elder care were subtracted out, the real investment in more traditional health care, including hospitals, would result in a much lower figure for Denmark's health care expenditures as a percentage of GDP (Søgaard, 2008). The difference in, for example, case fatality rates for acute myocardial infarction among men ages 35-74, which is higher in Denmark (see Figure 14-13), could be due to a poorer performance of the Danish health care system, a system that might perform better with more investment. But it could also be due to the higher smoking and alcohol use in Denmark compared with Sweden, as both smoking and alcohol are known to worsen the prognosis for a wide variety of diseases.

Two-line graph showing case-fatality rates on days 1-28 for acute myocardial infarction among men ages 35-74 in Denmark and Sweden, 1987-1999

FIGURE 14-13

Health care indicator: Case-fatality rates on days 1-28 for acute myocardial infarction among men ages 35-74 in Denmark and Sweden, 1987-1999.

To avoid the impact of patient lifestyle factors on the outcome, we studied neonatal mortality. Of course, maternal lifestyle factors influence neonatal mortality, but that influence is likely to be smaller than the impact of lifestyle on the individual herself. Neonatal survival chances are highly dependent on specialized medical care, which is typically administered by neonatal intensive care units, in which technologies, such as continuous positive airway pressure and surfactant therapy, have pushed the limit of viability downward (Goldenberg and Rouse, 1998). Using comparable data from the Danish, Norwegian, and Swedish national birth registries (Petersen et al., 2008), we studied neonatal mortality—defined as death within the first 28 days of life among live births, using comparable definitions in all three data sets, stratified for gestational age—and found an intriguing pattern (see Figure 14-14).

Three scatterplots of neonatal mortality (0-28 days) per 1,000 births: a) term newborns (37-42 weeks) (b) moderately preterm (33-36 weeks) (c) very preterm (28-32 weeks)

FIGURE 14-14

Neonatal mortality (0-28 days) per 1,000 births. Term newborns (37-42 weeks) Moderately preterm (33-36 weeks) Very preterm (28-32 weeks)

For children born at term, there were similar mortality rates in the three Scandinavian countries in the 1980s. In Denmark, the neonatal mortality has remained practically unchanged since that period, whereas there has been a decline in the other two Scandinavian countries. Among moderately preterm births (at 33-36 weeks), Denmark had higher mortality throughout the period but experienced a decline of a similar magnitude as the other two Scandinavian countries. Finally, for the very preterm births (at 28-32 weeks), Denmark had substantially higher mortality in the 1980s than the other two countries but caught up in the late 1990s. The result for the newborns born at term and the moderately preterm are compatible with a scenario suggesting that there is less effective health care in Denmark than in Sweden (or Norway), although a spillover of maternal effect (e.g., smoking) in Denmark cannot be excluded. However, the pattern of very preterm mortality in Denmark is not in accordance with that scenario, although it must be considered that the choice of intensity in the treatment of very preterm babies is not only a question of resources but also of ethical considerations and evaluation of the prognosis (EXPRESS Group, 2009). Apart from the effect of medical intervention following preterm birth, some of the change in association between gestational age and neonatal mortality might be due to elective termination of pregnancies, such as after screening early in pregnancy (Liu et al., 2002). However, the proportion of babies born before week 32 is similar in Sweden and Denmark (Petersen et al., 2009).

DISCUSSION

Smoking—The Major Explanation

The data presented above on cause-of-death trajectories, the disease incidence pattern, and the fractions of death estimated to be attributable to smoking using fundamentally different methods all suggest that smoking is the major explanation for the divergent Danish life expectancy trend compared with Sweden. This is in line with the work of Wang and Preston (2009) showing that cohort differences in smoking account for important anomalies in the recent age-sex pattern of mortality change in the United States.

An important question is: Why do Danes smoke more than people in comparable countries? An unusual explanation was suggested by Kesteloot (2001): “Halting of the decline in mortality occurred about 5 years after the ascension to the throne of Denmark by Queen Margrethe II. The queen is very popular in Denmark and a known cigarette smoker. As a role model for women, the Queen's example could offer an explanation for the unusual mortality in Danish women.” However, the excess mortality for Danish women born between the two world wars had previously been extensively studied (Jacobsen et al., 2000, 2001, 2004, 2006; Juel, 2000; Juel, Bjernegaard, and Madsen, 2000), and studies document that the stagnation started well before the queen took the throne. A more likely explanation is the liberal Danish tobacco policy; it was not until 2007 that smoking was prohibited in restaurants, and there are still exceptions (smoking is allowed in small restaurants).

Lifestyle and Health Care—Other Likely Contributors

The increase in alcohol-related deaths in Denmark and fractions of death estimated to be attributable to alcohol use suggest an important role also for alcohol, especially when comparing Denmark and Sweden. There are also some indications that investment in health care is lower in Denmark than in Sweden. The prognosis for both heart disease and cancer (see Figure 14-13 and Specht and Lundberg, 2001) is poorer, although it cannot be ruled out that the higher smoking prevalence and alcohol consumption, as well as other lifestyle factors, play a role in this development. Finally, analyses of life disparity (i.e., differences in life span) in Denmark suggest a slowing of progress in reducing life disparity occurring at roughly the same time as the slowing of progress in increasing life expectancy. That is, Danish life expectancy may have stagnated, at least in part, because the Danes did not continue to reduce inequalities in the length of life in the 1970s and 1980s.

What Caused the Change in Life Expectancy in Denmark?

The change from stagnation to improvement in life expectancy in the mid-1990s coincided with a decrease in the prevalence of major lifestyle risk factors: smoking, alcohol consumption, and sedentary lifestyle, which correspond to the changes seen in disease incidence. The obesity rate went up in the same time period, but only to a low level when compared with the United States. Denmark's generally positive development in lifestyle risk factors occurs despite a widespread reluctance toward “paternalistic policy” in the country. As an example, smoking was not prohibited in restaurants in Denmark until 2007. Also co-occurring with the change from stagnation to improvement in life expectancy in the mid-1990s, Denmark instituted what is called the “Heart Plan,” which allocated substantial national funding to improve cardiovascular disease treatments.

The reason for the improvement in life expectancy in the early 1990s is mainly decreasing cardiovascular mortality, probably attributable to a better lifestyle profile for most Danes, more behavioral and medical disease prevention services, and better medical and surgical treatment.

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Copyright © 2010, National Academy of Sciences.
Bookshelf ID: NBK62583

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