- Email: [email protected]
Impact of selected risk factors on expected lifetime without long-standing, limiting illness in Denmark
Preventive Medicine 45 (2007) 49 – 53 www.elsevier.com/locate/ypmed
Impact of selected risk factors on expected lifetime without long-standing, limiting illness in Denmark Henrik Brønnum-Hansen a,⁎, Knud Juel a , Michael Davidsen a , Jan Sørensen b a
b
National Institute of Public Health, Øster Farimagsgade 5 A, DK 1399 Copenhagen K, Denmark Centre for Applied Health Services Research and Technology Assessment, University of Southern Denmark, Denmark Available online 31 March 2007
Abstract Objective. To estimate the impacts of tobacco smoking, high alcohol consumption, physical inactivity and overweight on expected lifetime with and without long-standing, limiting illness. Methods. Life tables for each level of exposure to the risk factors were constructed, mainly on the basis of the Danish National Cohort Study. Expected lifetime without long-standing, limiting illness was estimated for exposed and unexposed persons by combining life tables and prevalence data from the Danish Health Interview Survey 2000 (14,503 participants aged 25+). Results. The life expectancy of 25-year-olds was 9–10 years shorter for heavy smokers than for those who never smoke, and all the lifetime lost would have been without long-standing, limiting illness. Similarly, all 5 years of expected lifetime lost by men with high alcohol consumption would have been without illness. The expected lifetime without long-standing, limiting illness was 8–10 years shorter among sedentary than physically active people. Obesity shortened lifetime without illness by 5 years for men and ten years for women. Conclusion. The results of this study could be used in health policy-making, as the potential gains in public health due to interventions against these risk factors could be evaluated, when the prevalence of exposure to the risk factor is available. © 2007 Elsevier Inc. All rights reserved. Keywords: Denmark; Health expectancy; Life expectancy; Long-standing illness; Risk factor
Introduction Reductions in exposure to risk factors can lead to decreased incidence and mortality and can lengthen total lifetime and lifetime in good health. Composite measures of mortality and morbidity in subpopulations exposed to specific risk factors are suitable for evaluating the impact of risk factors on health. Estimates of the potential health gains resulting from risk factor elimination could guide priority setting in health policy-making. Health expectancy is a composite measure representing the average lifetime in various health states. While the impact of lifestyle-related risk factors on life expectancy has been studied in many populations, health expectancy has been estimated in only a few studies. Ferrucci et al. (1999) reported strong evidence for improved disability-free life expectancy among Americans aged 65 or older who abstained from smoking and ⁎ Corresponding author. Fax: +45 39 20 80 10. E-mail address: [email protected] (H. Brønnum-Hansen). 0091-7435/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.ypmed.2007.03.010
had regular physical activity. In another study (Østbye and Taylor, 2004), on the effects of smoking, physical inactivity, alcohol consumption and weight among middle-aged and older Americans, it was concluded that smoking cessation contributed mostly in additional years of healthy life for middle-aged persons. The effect of obesity on life-years with disability among adult Americans was evaluated in two studies (Peeters et al., 2004; Reynolds et al., 2005), and a study of obesity and unhealthy life-years among adult Finns was published recently (Visscher et al., 2004). The health benefit of smoking cessation was evaluated in a Dutch study, in which life expectancy with and without disability was estimated (Nusselder et al., 2000). The effect of smoking on health expectancy among Danes has also been reported (Brønnum-Hansen and Juel, 2001, 2004). Recently, a comprehensive study on risk factors and public health in Denmark was published, in which a wide range of measures related to mortality, morbidity and economic consequences were calculated for up to 19 behavioral, biological and social risk factors (Juel et al., 2006). This
50
H. Brønnum-Hansen et al. / Preventive Medicine 45 (2007) 49–53
paper reports part of the report. Our purpose was to quantify the impact of four risk factors on health by estimating expected lifetime with and without long-standing, limiting illness among Danes aged 25 classified by level of exposure to the risk factor. The risk factors chosen were lifestyle-related and highly prevalent: smoking, high alcohol consumption, physical inactivity and overweight or obesity.
Methods Health interview survey For the Danish Health Interview Survey 2000, a random sample of 22,486 persons (including people living in institutions) was drawn from the Danish Civil Registration System. Professionals from the Danish National Institute of Social Research interviewed 16,690 persons (74.2% of the sample), of whom 14,503 were aged 25 or more. Details and results of the survey have been reported previously (National Institute of Public Health, 2002; Davidsen and Kjøller, 2002). The interviewees were categorized as ‘never’ smokers, ex-smokers, moderate smokers (1–14 cigarettes per day) and heavy smokers (≥15 cigarettes per day). Alcohol consumption was classified according to the recommendations of the Danish National Board of Health as low (<1 unit per week), moderate (1–14 and 1–21 units weekly for women and men, respectively) and high (> 14 and 21 units per week for women and men, respectively). The effect of physical inactivity on health was estimated for sedentary people and compared with that for people who performed light, moderate or vigorous physical activity for at least four hours per week. Three levels of body mass index (BMI) were used: normal weight (18.5 ≤ BMI < 25.0), moderate overweight (25.0 ≤ BMI < 30.0) and obesity (30.0 ≤ BMI). Long-standing illness was measured from answers to the question, ‘Do you suffer from any long-standing illness, long-standing after-effect of injury, any disability or other long-standing condition?’ Whenever long-standing illness was reported, its nature was clarified by means of an open question and the interviewees were asked if the disease implied restrictions on their daily life or at work; long-standing illness was considered to be limiting only if it was stated to cause restrictions. About 96% of the diseases were reported to have been diagnosed by a physician (National Institute of Public Health, 2002).
Mortality data On the basis of the unique individual person number, the Danish National Cohort Study (Helweg-Larsen et al., 2003) was established by linkage of data from the Danish Health Interview Surveys for 1987, 1991, 1994 and 2000 with those in the Danish Civil Registration System and other national registers. This made it possible to estimate relative risks for death by level of risk factor. For some analyses subpopulations defined by specific exposure levels were excluded. As the causal relationship between physical activity and health goes in both directions, persons who were disabled at baseline (9.3%) were excluded from the analysis of physical activity. As persons with an illness might lose weight, those who were underweight (BMI < 18.5) at baseline (0.6% of men and 4.0% of women) were excluded from the analysis of overweight and obesity. As to alcohol intake, we studied only the effect of high alcohol consumption and not that of abstention which in Denmark is low (3% among men and 7% among women). Thus, we excluded individuals with low alcohol consumption from the analysis of the effect of alcohol consumption. The health of persons with high alcohol consumption was compared with that of persons who drank moderately. To construct risk factor level-specific life tables, let P0 signify the sex- and age-specific prevalence of unexposed persons, Pi that for risk factor exposure level i and RRi the relative risk (RR0 = 1). Then, the sex- and age-specific death rate is given by D = ∑Pi × RRi × D0, from which the death rate of unexposed persons, D0, was calculated. The sex- and age-specific death rates for unexposed persons, D0, were multiplied by the relative risks, RRi, giving the sex- and agespecific death rates for risk factor exposure level i. Finally, risk factor levelspecific life tables were constructed. Because of the particularly long-term effect
of smoking, an indirect method was used to estimate life tables by smoking category on the basis of the strong relation between smoking and lung cancer (Peto et al., 1992), which has been described in the Danish context previously (Brønnum-Hansen and Juel, 2001). In the present study, however, we used a less conservative confounder adjustment of 30% (Ezzati and Lopez, 2006), instead of a 50% reduction in excess risk.
Estimation of expected lifetime with and without long-standing, limiting illness Expected lifetime with and without long-standing, limiting illness per level of exposure to risk factors was calculated by Sullivan's method (1971), in which life table figures were combined with prevalence of health status. The expected number of years lived in the age intervals 25–29, 30–34, …, ≥80 were multiplied by the age-specific proportions of long-standing, limiting illness. The expected lifetime with long-standing illness of 25-year-olds was then calculated by adding these years for all age groups and dividing the sum by the number of survivors at age 25. Lifetime without long-standing illness was estimated by subtracting lifetime with long-standing illness from life expectancy. By relating expected lifetime without long-standing illness to life expectancy, a measure of the proportion of lifetime without long-standing illness was established. The only source of randomness was assumed to arise from the health survey proportions, and confidence intervals were estimated from the formulae suggested by the International Network on Health Expectancy (Jagger et al., 2001).
Results The life expectancy of 25-year-old men who never smoke was 53.6 years and that of men who smoke heavily was 44.9 years (Table 1). For women, the life expectancy of ‘never’ smokers and heavy smokers was 57.4 and 47.0 years, respectively. Thus, the reduction in life expectancy for persons who smoke heavily as compared with those who never smoke was 8.7 years for men and 10.4 years for women (Table 2). Heavy smokers had 10.5 fewer years without long-standing, limiting illness than ‘never’ smokers (men: 41.9 and 31.5 years; women: 40.2 and 29.7 years), and the proportion of expected lifetime without long-standing, limiting illness was reduced from 78.3% to 70.2% for men and from 70.0% to 63.3% for women (Table 1). Men who smoke moderately could expect to live 5.0 years less than ‘never’ smokers and to live 6.9 fewer years without long-standing, limiting illness and 1.9 more years with illness (Table 2). Women who smoke moderately could expect to lose 5.3 years of life but to live as many years with long-standing illness as ‘never’ smokers (17.2 years); thus, all the life-years lost would be years without illness. Men with high alcohol consumption (more than 21 units weekly) could expect to live 4.7 fewer years and 5.0 fewer years without illness than men who drink between 1 and 21 units a week. Women with high alcohol consumption (more than 14 units a week) could expect a reduction in lifetime of 4.0 years but only 0.8 fewer years without illness than those who drink 1– 14 units weekly. Thus, the proportion of expected lifetime without long-standing, limiting illness was greater for women with high alcohol consumption (73.1%) than for moderate consumers (69.4%). Life expectancy at the age of 25 was a little more than 5 years shorter for sedentary than for physically active persons. Expected lifetime without long-standing, limiting illness for sedentary men and women was 8.3 and 10.3 years less than that
H. Brønnum-Hansen et al. / Preventive Medicine 45 (2007) 49–53
51
Table 1 Life expectancy, expected lifetime with and without long-standing, limiting illness and proportion of expected lifetime without long-standing, limiting illness of 25-year-old Danes in 2000 by level of exposure to risk factors Risk factor
Prevalence %
Men Smoking Never Ex-smoker Moderate smoker Heavy smoker Alcohol consumption Moderate High Physical activity Active Inactive Overweight Normal weight Moderate overweight Obese Women Smoking Never Ex-smoker Moderate smoker Heavy smoker Alcohol consumption Moderate High Physical activity Active Inactive Overweight Normal weight Moderate overweight Obese
Life expectancy (years)
Expected lifetime without long-standing illness
Expected lifetime with long-standing illness
Proportion of expected lifetime without longstanding illness
Years
95% CI
Years
95% CI
%
95% CI
(32) (28) (16) (24)
53.6 51.2 48.5 44.9
41.9 36.7 35.0 31.5
(40.8;43.1) (35.7;37.8) (33.7;36.2) (30.5;32.6)
11.6 14.5 13.5 13.4
(10.5;12.8) (13.4;15.5) (12.3;14.8) (12.3;14.4)
78.3 71.8 72.1 70.2
(76.1;80.4) (69.8;73.8) (69.5;74.7) (67.9;72.6)
(71) (14)
52.2 47.5
39.2 34.2
(38.6;39.9) (32.8;35.6)
13.0 13.3
(12.4;13.6) (11.9;14.7)
75.1 72.0
(73.9;76.3) (69.0;74.9)
(80) (13)
53.2 47.9
41.8 33.5
(41.1;42.4) (32.1;35.0)
11.5 14.3
(10.8;12.1) (12.9;15.8)
78.5 70.0
(77.3;79.7) (67.0;73.1)
(46) (43) (11)
50.7 50.7 48.7
36.8 38.2 31.9
(36.0;37.6) (37.4;39.0) (30.1;33.7)
13.9 12.5 16.8
(13.1;14.7) (11.7;13.3) (15.0;18.6)
72.5 75.3 65.5
(71.0;74.1) (73.8;76.9) (61.8;69.1)
(41) (24) (18) (17)
57.4 56.0 52.2 47.0
40.2 37.8 35.0 29.7
(39.3;41.2) (36.6;39.0) (33.6;36.3) (28.4;31.0)
17.2 18.2 17.2 17.3
(16.3;18.2) (17.0;19.4) (15.9;18.5) (16.0;18.6)
70.0 67.5 67.0 63.3
(68.4;71.7) (65.4;69.6) (64.5;69.5) (60.5;66.1)
(64) (8)
56.8 52.8
39.4 38.6
(38.6;40.2) (36.5;40.6)
17.4 14.2
(16.6;18.2) (12.1;16.2)
69.4 73.1
(67.9;70.8) (69.2;77.0)
(77) (12)
58.6 53.5
44.0 33.7
(43.1;44.9) (32.0;35.4)
14.6 19.8
(13.7;15.5) (18.1;21.5)
75.1 63.0
(73.6;76.6) (59.8;66.2)
(59) (27) (10)
55.7 55.0 52.5
39.9 36.0 29.9
(39.1;40.7) (34.9;37.2) (28.1;31.8)
15.9 18.9 22.5
(15.1;16.7) (17.8;20.1) (20.7;24.3)
71.5 65.6 57.1
(70.1;73.0) (63.5;67.6) (53.6;60.5)
CI: Confidence interval.
Table 2 Life expectancy and expected lifetime without long-standing, limiting illness lost among 25-year-old Danes in 2000 due to exposure to risk factors Risk factor
Men
Women
Life Expected Life Expected expectancy lifetime expectancy lifetime lost (years) without lost (years) without long-standing long-standing illness lost illness lost (years) (years) Smoking Ex-smoker Moderate smoker Heavy smoker Alcohol consumption High Physical activity Inactive Overweight Moderate overweight Obese
2.4 5.0 8.7
5.2 6.9 10.4
1.5 5.3 10.4
2.5 5.2 10.5
4.7
5.0
4.0
0.8
5.3
8.3
5.1
10.3
0.0
− 1.4
0.7
3.9
2.0
4.9
3.2
10.0
for physically active persons. Obese men and women could expect 2.0 years and 3.2 years shorter life expectancy than men and women with normal weight. The difference in lifetime without long-standing, limiting illness was 4.9 years and 10.0 years for men and women, respectively. Moderate overweight did not reduce life expectancy for men but tended to increase expected lifetime without illness by 1.4 years. For women, however, moderate overweight reduced life expectancy by 0.7 years and reduced lifetime without illness by almost 4 years. Discussion Our quantification of the consequences of exposure to the selected risk factors on health expectancy cannot be compared with those found in (the few) other studies on this topic (Ferrucci et al., 1999; Nusselder et al., 2000; Peeters et al., 2004; Visscher et al., 2004; Østbye and Taylor, 2004; Franco et al., 2005; Reynolds et al., 2005), mainly because of differences in the choice of health expectancy measures and age groups and
52
H. Brønnum-Hansen et al. / Preventive Medicine 45 (2007) 49–53
in the definitions of exposure. The overall conclusion, however, is that smoking is the most important preventable risk factor for serious health-damaging effects. The conclusions are consistent with those of a similar study in which the impact of risk factors on quality-adjusted life years (QALYs) were estimated (Brønnum-Hansen et al., in press). Thus, the ranking of the risk factors as to loss of QALYs was the same as of expected lifetime without long-standing, limiting illness. However, while high alcohol consumption reduced life expectancy by 4–5 years, an opposite effect was seen on expected lifetime with long-standing, limiting illness. We have no explanation for the finding that the proportion of expected lifetime without illness was higher among women who exceeded the recommended maximum alcohol intake than among women who followed the recommendation. The conclusion could not be confirmed by using other healthrelated measures of the impact of high alcohol consumption (Juel et al., 2006). For instance, the apparent inconsistency was not seen for the effect of high alcohol consumption on QALYs (Brønnum-Hansen et al., in press). We did not analyze the effect of low alcohol consumption (i.e. no alcohol intake the week before interview), in a group composed of persons who seldom or never drink alcohol and former alcoholics. The prevalence of alcohol abstention is low in Denmark: about 3% among men and 7% among women (Grønbæk, 2004). Previous Danish estimates of reduced life expectancy due to smoking (Brønnum-Hansen and Juel, 2001) were roughly 2 years shorter for heavy smokers than that found in this study. This result is due to use of a less conservative confounder adjustment, 30% (Ezzati and Lopez, 2006) instead of 50% reduction of excess risk, as originally suggested by Peto and colleagues (1992). The main reason for classifying non-smokers as ‘never’ and ex-smokers was to define the unexposed group as precisely as possible by eliminating ex-smokers, who represent a heterogeneous group that includes persons who were light smokers for a short period and former heavy smokers who became ill because of smoking. We found a protective effect of moderate overweight for men but not for women. The appropriateness of BMI and of (equal) classification of weight groups for men and women has been questioned (McGee, 2005). We consider that exclusion of underweight people (0.6% of men and 4.0% of women) from the analysis of the health consequence of overweight had a negligible effect, although some underweight people might have been persons who had been overweight or obese but who had lost weight due to overweight-related diseases. As regards the analysis of the impact of physical inactivity on health, the consequence of excluding individuals who were disabled at the time of interview (9.3%) might have been to underestimate the effect, as disability can be caused by a sedentary lifestyle. We consider this underestimation to be less serious than the overestimation that would result from the inclusion of disabled persons who were more likely to suffer from long-standing illness and to be physically inactive than persons who were not disabled. The definitions of exposure to risk factors might also have biased the results. Three groups of physically active persons were
combined and compared with sedentary persons. If more physical activity increases lifetime without long-standing illness and reduces the mortality risk, then combining persons with light, moderate and vigorous activity will result in an underestimate of the potential health benefits of a lifestyle change for sedentary individuals. The method also disregards the potential benefits that persons with light and moderate physical activity might achieve from more physical activity. It is difficult, however, to classify individuals in terms of physical activity precisely in population-based surveys, and people may change their activity levels more rapidly than their smoking habits and weight. Life tables by risk factor level were constructed from the Danish National Cohort Study by individual follow-up data on deaths among health survey participants. Changes in exposure to risk factors during follow-up were unknown and might have biased the estimates of relative risk for death to some extent. Nevertheless, our estimates were in agreement with those of other studies. Sullivan's method for estimating health expectancy is simple and directly applicable when life tables and sex- and agespecific prevalence of the health state exist for the population. A limitation is that the prevalence reflects previous trends in mortality and disease incidence and recovery. One way of overcoming this problem is to gather longitudinal data and apply multistate life table methods. Considering the hypothetical situation reflected by elimination of risk factor exposure, the limitations of Sullivan's method are negligible. Self-reported lifestyle-related (and unhealthy) habits are expected to be underreported. For instance, persons with high alcohol consumption might underreport their drinking, and overweight people might underreport their weight. Such misclassification might result in underestimates of health differences between exposed and unexposed persons. Another shortcoming of the study was the 19–26% nonresponse rate in the health interview surveys. In general, individuals with abuse problems or who are in poor health are more likely to be non-responders than persons with no such problems. Thus, non-response might in some cases result in underestimates of differences between exposed and unexposed persons. The size of the health interview survey samples did not allow adjustment for clustering of exposures to risk factors. For instance, the analysis did not take into account the fact that persons with high alcohol consumption are more likely to be smokers, overweight and physically inactive or that the prevalence of obesity is higher among sedentary than among physically active people. Furthermore, socially disadvantaged groups are more likely to have unhealthy lifestyles than advantaged groups. Nevertheless, the results might help to identify subpopulations at high risk, and this would not necessarily be easier if the results were established from a multivariate model including adjustments for other risk factors. Conclusions The increased mortality and loss of life years due to exposure to risk factors are compounded by an even higher loss of lifetime
H. Brønnum-Hansen et al. / Preventive Medicine 45 (2007) 49–53
without illness. Thus, in general, the healthy life years of exposed persons are reduced to a greater extent than total life years, and healthy lifetime is transformed into years with illness. A reduction in exposure to risk factors can therefore lengthen lifetime and compress morbidity. Smoking is the most hazardous risk factor and is highly prevalent in Denmark, although the rate has been declining for some years; however, overweight is increasing and, in combination with physical inactivity, constitutes a growing public health challenge for the future. References Brønnum-Hansen, H., Juel, K., 2001. Abstention from smoking extends life and compresses morbidity: a population based study of health expectancy among smokers and never smokers in Denmark. Tob. Control 10, 273–278. Brønnum-Hansen, H., Juel, K., 2004. Impact of smoking on the social gradient in health expectancy in Denmark. J. Epidemiol. Community Health 58, 604–610. Brønnum-Hansen, H., Juel, K., Davidsen, M., Sørensen, J. (in press). Impact of selected risk factors on quality-adjusted life expectancy in Denmark. Scand. J. Public Health. Davidsen, M., Kjøller, M., 2002. The Danish health and morbidity survey— design and analysis. Stat. Transit. 5, 927–942. Ezzati, M., Lopez, A.D., 2006. Smoking and oral tobacco use. In: Ezzati, M., Lopez, A.D., Rodgers, A., Murray, C.J.L. (Eds.), Comparative Quantification of Health Risks. WHO, Geneva, pp. 883–957. Ferrucci, L., Izmirlian, G., Leveille, S., Phillips, C.L., Corti, M.C., Brock, D.B., Guralnik, J.M., 1999. Smoking, physical activity, and active life expectancy. Am. J. Epidemiol. 149, 645–653. Franco, O.H., de Laet, C., Peeters, A., Jonker, J., Mackenbach, J.P., Nusselder, W. J., 2005. Effects of physical activity on life expectancy with cardiovascular disease. Arch. Intern. Med. 165, 2355–2360. Grønbæk, M.N., 2004. Alcohol intake in Denmark—public health challenges and scientific questions. Ugeskr. Læger 166, 1573–1576.
53
Helweg-Larsen, K., Kjøller, M., Davidsen, M., Rasmussen, N.K., Madsen, M., Kamper-Jørgensen, F., 2003. The Danish National Cohort Study (DANCOS). Dan. Med. Bull. 50, 177–180. Jagger, C., Hauet, E., Brouard, N., 2001. Health expectancy calculation by the Sullivan method: a practical guide. European concerted action on the harmonization of health expectancy calculations in Europe. EURO-REVES, 2001:29. REVES Paper no. 408. Leicester, Paris. Juel, K., Sørensen, J., Brønnum-Hansen, H., 2006. Risikofaktorer og folkesundhed i Danmark (Risk Factors and Public Health in Denmark). National Institute of Public Health, Copenhagen. (in Danish). McGee, D.L., 2005. Body mass index and mortality: a meta-analysis based on person-level data from twenty-six observational studies. Ann. Epidemiol. 15, 87–97. National Institute of Public Health, 2002. Sundhed og sygelighed i Danmark 2000 og udviklingen siden 1987. (The Danish Health Interview Survey 2000 and the Development since 1987). National Institute of Public Health, Copenhagen (in Danish). Nusselder, W.J., Looman, C.W., Marang-van de Mheen, P.J., van de Mheen, H., Mackenbach, J.P., 2000. Smoking and the compression of morbidity. J. Epidemiol. Community Health 54, 566–574. Østbye, T., Taylor, D.H., 2004. The effect of smoking on years of healthy life (YHL) lost among middle-aged and older Americans. Health Serv. Res. 39, 531–552. Peeters, A., Bonneux, L., Nusselder, W.J., de Laet, C., Barendregt, J.J., 2004. Adult obesity and the burden of disability throughout life. Obes. Res. 12, 1145–1151. Peto, R., Lopez, A.D., Boreham, J., Thun, M., Heath, C.J., 1992. Mortality from tobacco in developed countries: indirect estimation from national vital statistics. Lancet 339, 1268–1278. Reynolds, S.L., Saito, Y., Crimmins, E.M., 2005. The impact of obesity on active life expectancy in older American men and women. Gerontologist 45, 438–444. Sullivan, D.F., 1971. A single index of mortality and morbidity. Health Serv. Ment. Health Adm. Health Rep. 86, 347–354. Visscher, T.L., Rissanen, A., Seidell, J.C., Heliovaara, M., Knekt, P., Reunanen, A., Aromaa, A., 2004. Obesity and unhealthy life-years in adult Finns. An empirical approach. Arch. Intern. Med. 164, 1413–1420.
Impact of selected risk factors on expected lifetime without long-standing, limiting illness in Denmark Henrik Brønnum-Hansen a,⁎, Knud Juel a , Michael Davidsen a , Jan Sørensen b a
b
National Institute of Public Health, Øster Farimagsgade 5 A, DK 1399 Copenhagen K, Denmark Centre for Applied Health Services Research and Technology Assessment, University of Southern Denmark, Denmark Available online 31 March 2007
Abstract Objective. To estimate the impacts of tobacco smoking, high alcohol consumption, physical inactivity and overweight on expected lifetime with and without long-standing, limiting illness. Methods. Life tables for each level of exposure to the risk factors were constructed, mainly on the basis of the Danish National Cohort Study. Expected lifetime without long-standing, limiting illness was estimated for exposed and unexposed persons by combining life tables and prevalence data from the Danish Health Interview Survey 2000 (14,503 participants aged 25+). Results. The life expectancy of 25-year-olds was 9–10 years shorter for heavy smokers than for those who never smoke, and all the lifetime lost would have been without long-standing, limiting illness. Similarly, all 5 years of expected lifetime lost by men with high alcohol consumption would have been without illness. The expected lifetime without long-standing, limiting illness was 8–10 years shorter among sedentary than physically active people. Obesity shortened lifetime without illness by 5 years for men and ten years for women. Conclusion. The results of this study could be used in health policy-making, as the potential gains in public health due to interventions against these risk factors could be evaluated, when the prevalence of exposure to the risk factor is available. © 2007 Elsevier Inc. All rights reserved. Keywords: Denmark; Health expectancy; Life expectancy; Long-standing illness; Risk factor
Introduction Reductions in exposure to risk factors can lead to decreased incidence and mortality and can lengthen total lifetime and lifetime in good health. Composite measures of mortality and morbidity in subpopulations exposed to specific risk factors are suitable for evaluating the impact of risk factors on health. Estimates of the potential health gains resulting from risk factor elimination could guide priority setting in health policy-making. Health expectancy is a composite measure representing the average lifetime in various health states. While the impact of lifestyle-related risk factors on life expectancy has been studied in many populations, health expectancy has been estimated in only a few studies. Ferrucci et al. (1999) reported strong evidence for improved disability-free life expectancy among Americans aged 65 or older who abstained from smoking and ⁎ Corresponding author. Fax: +45 39 20 80 10. E-mail address: [email protected] (H. Brønnum-Hansen). 0091-7435/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.ypmed.2007.03.010
had regular physical activity. In another study (Østbye and Taylor, 2004), on the effects of smoking, physical inactivity, alcohol consumption and weight among middle-aged and older Americans, it was concluded that smoking cessation contributed mostly in additional years of healthy life for middle-aged persons. The effect of obesity on life-years with disability among adult Americans was evaluated in two studies (Peeters et al., 2004; Reynolds et al., 2005), and a study of obesity and unhealthy life-years among adult Finns was published recently (Visscher et al., 2004). The health benefit of smoking cessation was evaluated in a Dutch study, in which life expectancy with and without disability was estimated (Nusselder et al., 2000). The effect of smoking on health expectancy among Danes has also been reported (Brønnum-Hansen and Juel, 2001, 2004). Recently, a comprehensive study on risk factors and public health in Denmark was published, in which a wide range of measures related to mortality, morbidity and economic consequences were calculated for up to 19 behavioral, biological and social risk factors (Juel et al., 2006). This
50
H. Brønnum-Hansen et al. / Preventive Medicine 45 (2007) 49–53
paper reports part of the report. Our purpose was to quantify the impact of four risk factors on health by estimating expected lifetime with and without long-standing, limiting illness among Danes aged 25 classified by level of exposure to the risk factor. The risk factors chosen were lifestyle-related and highly prevalent: smoking, high alcohol consumption, physical inactivity and overweight or obesity.
Methods Health interview survey For the Danish Health Interview Survey 2000, a random sample of 22,486 persons (including people living in institutions) was drawn from the Danish Civil Registration System. Professionals from the Danish National Institute of Social Research interviewed 16,690 persons (74.2% of the sample), of whom 14,503 were aged 25 or more. Details and results of the survey have been reported previously (National Institute of Public Health, 2002; Davidsen and Kjøller, 2002). The interviewees were categorized as ‘never’ smokers, ex-smokers, moderate smokers (1–14 cigarettes per day) and heavy smokers (≥15 cigarettes per day). Alcohol consumption was classified according to the recommendations of the Danish National Board of Health as low (<1 unit per week), moderate (1–14 and 1–21 units weekly for women and men, respectively) and high (> 14 and 21 units per week for women and men, respectively). The effect of physical inactivity on health was estimated for sedentary people and compared with that for people who performed light, moderate or vigorous physical activity for at least four hours per week. Three levels of body mass index (BMI) were used: normal weight (18.5 ≤ BMI < 25.0), moderate overweight (25.0 ≤ BMI < 30.0) and obesity (30.0 ≤ BMI). Long-standing illness was measured from answers to the question, ‘Do you suffer from any long-standing illness, long-standing after-effect of injury, any disability or other long-standing condition?’ Whenever long-standing illness was reported, its nature was clarified by means of an open question and the interviewees were asked if the disease implied restrictions on their daily life or at work; long-standing illness was considered to be limiting only if it was stated to cause restrictions. About 96% of the diseases were reported to have been diagnosed by a physician (National Institute of Public Health, 2002).
Mortality data On the basis of the unique individual person number, the Danish National Cohort Study (Helweg-Larsen et al., 2003) was established by linkage of data from the Danish Health Interview Surveys for 1987, 1991, 1994 and 2000 with those in the Danish Civil Registration System and other national registers. This made it possible to estimate relative risks for death by level of risk factor. For some analyses subpopulations defined by specific exposure levels were excluded. As the causal relationship between physical activity and health goes in both directions, persons who were disabled at baseline (9.3%) were excluded from the analysis of physical activity. As persons with an illness might lose weight, those who were underweight (BMI < 18.5) at baseline (0.6% of men and 4.0% of women) were excluded from the analysis of overweight and obesity. As to alcohol intake, we studied only the effect of high alcohol consumption and not that of abstention which in Denmark is low (3% among men and 7% among women). Thus, we excluded individuals with low alcohol consumption from the analysis of the effect of alcohol consumption. The health of persons with high alcohol consumption was compared with that of persons who drank moderately. To construct risk factor level-specific life tables, let P0 signify the sex- and age-specific prevalence of unexposed persons, Pi that for risk factor exposure level i and RRi the relative risk (RR0 = 1). Then, the sex- and age-specific death rate is given by D = ∑Pi × RRi × D0, from which the death rate of unexposed persons, D0, was calculated. The sex- and age-specific death rates for unexposed persons, D0, were multiplied by the relative risks, RRi, giving the sex- and agespecific death rates for risk factor exposure level i. Finally, risk factor levelspecific life tables were constructed. Because of the particularly long-term effect
of smoking, an indirect method was used to estimate life tables by smoking category on the basis of the strong relation between smoking and lung cancer (Peto et al., 1992), which has been described in the Danish context previously (Brønnum-Hansen and Juel, 2001). In the present study, however, we used a less conservative confounder adjustment of 30% (Ezzati and Lopez, 2006), instead of a 50% reduction in excess risk.
Estimation of expected lifetime with and without long-standing, limiting illness Expected lifetime with and without long-standing, limiting illness per level of exposure to risk factors was calculated by Sullivan's method (1971), in which life table figures were combined with prevalence of health status. The expected number of years lived in the age intervals 25–29, 30–34, …, ≥80 were multiplied by the age-specific proportions of long-standing, limiting illness. The expected lifetime with long-standing illness of 25-year-olds was then calculated by adding these years for all age groups and dividing the sum by the number of survivors at age 25. Lifetime without long-standing illness was estimated by subtracting lifetime with long-standing illness from life expectancy. By relating expected lifetime without long-standing illness to life expectancy, a measure of the proportion of lifetime without long-standing illness was established. The only source of randomness was assumed to arise from the health survey proportions, and confidence intervals were estimated from the formulae suggested by the International Network on Health Expectancy (Jagger et al., 2001).
Results The life expectancy of 25-year-old men who never smoke was 53.6 years and that of men who smoke heavily was 44.9 years (Table 1). For women, the life expectancy of ‘never’ smokers and heavy smokers was 57.4 and 47.0 years, respectively. Thus, the reduction in life expectancy for persons who smoke heavily as compared with those who never smoke was 8.7 years for men and 10.4 years for women (Table 2). Heavy smokers had 10.5 fewer years without long-standing, limiting illness than ‘never’ smokers (men: 41.9 and 31.5 years; women: 40.2 and 29.7 years), and the proportion of expected lifetime without long-standing, limiting illness was reduced from 78.3% to 70.2% for men and from 70.0% to 63.3% for women (Table 1). Men who smoke moderately could expect to live 5.0 years less than ‘never’ smokers and to live 6.9 fewer years without long-standing, limiting illness and 1.9 more years with illness (Table 2). Women who smoke moderately could expect to lose 5.3 years of life but to live as many years with long-standing illness as ‘never’ smokers (17.2 years); thus, all the life-years lost would be years without illness. Men with high alcohol consumption (more than 21 units weekly) could expect to live 4.7 fewer years and 5.0 fewer years without illness than men who drink between 1 and 21 units a week. Women with high alcohol consumption (more than 14 units a week) could expect a reduction in lifetime of 4.0 years but only 0.8 fewer years without illness than those who drink 1– 14 units weekly. Thus, the proportion of expected lifetime without long-standing, limiting illness was greater for women with high alcohol consumption (73.1%) than for moderate consumers (69.4%). Life expectancy at the age of 25 was a little more than 5 years shorter for sedentary than for physically active persons. Expected lifetime without long-standing, limiting illness for sedentary men and women was 8.3 and 10.3 years less than that
H. Brønnum-Hansen et al. / Preventive Medicine 45 (2007) 49–53
51
Table 1 Life expectancy, expected lifetime with and without long-standing, limiting illness and proportion of expected lifetime without long-standing, limiting illness of 25-year-old Danes in 2000 by level of exposure to risk factors Risk factor
Prevalence %
Men Smoking Never Ex-smoker Moderate smoker Heavy smoker Alcohol consumption Moderate High Physical activity Active Inactive Overweight Normal weight Moderate overweight Obese Women Smoking Never Ex-smoker Moderate smoker Heavy smoker Alcohol consumption Moderate High Physical activity Active Inactive Overweight Normal weight Moderate overweight Obese
Life expectancy (years)
Expected lifetime without long-standing illness
Expected lifetime with long-standing illness
Proportion of expected lifetime without longstanding illness
Years
95% CI
Years
95% CI
%
95% CI
(32) (28) (16) (24)
53.6 51.2 48.5 44.9
41.9 36.7 35.0 31.5
(40.8;43.1) (35.7;37.8) (33.7;36.2) (30.5;32.6)
11.6 14.5 13.5 13.4
(10.5;12.8) (13.4;15.5) (12.3;14.8) (12.3;14.4)
78.3 71.8 72.1 70.2
(76.1;80.4) (69.8;73.8) (69.5;74.7) (67.9;72.6)
(71) (14)
52.2 47.5
39.2 34.2
(38.6;39.9) (32.8;35.6)
13.0 13.3
(12.4;13.6) (11.9;14.7)
75.1 72.0
(73.9;76.3) (69.0;74.9)
(80) (13)
53.2 47.9
41.8 33.5
(41.1;42.4) (32.1;35.0)
11.5 14.3
(10.8;12.1) (12.9;15.8)
78.5 70.0
(77.3;79.7) (67.0;73.1)
(46) (43) (11)
50.7 50.7 48.7
36.8 38.2 31.9
(36.0;37.6) (37.4;39.0) (30.1;33.7)
13.9 12.5 16.8
(13.1;14.7) (11.7;13.3) (15.0;18.6)
72.5 75.3 65.5
(71.0;74.1) (73.8;76.9) (61.8;69.1)
(41) (24) (18) (17)
57.4 56.0 52.2 47.0
40.2 37.8 35.0 29.7
(39.3;41.2) (36.6;39.0) (33.6;36.3) (28.4;31.0)
17.2 18.2 17.2 17.3
(16.3;18.2) (17.0;19.4) (15.9;18.5) (16.0;18.6)
70.0 67.5 67.0 63.3
(68.4;71.7) (65.4;69.6) (64.5;69.5) (60.5;66.1)
(64) (8)
56.8 52.8
39.4 38.6
(38.6;40.2) (36.5;40.6)
17.4 14.2
(16.6;18.2) (12.1;16.2)
69.4 73.1
(67.9;70.8) (69.2;77.0)
(77) (12)
58.6 53.5
44.0 33.7
(43.1;44.9) (32.0;35.4)
14.6 19.8
(13.7;15.5) (18.1;21.5)
75.1 63.0
(73.6;76.6) (59.8;66.2)
(59) (27) (10)
55.7 55.0 52.5
39.9 36.0 29.9
(39.1;40.7) (34.9;37.2) (28.1;31.8)
15.9 18.9 22.5
(15.1;16.7) (17.8;20.1) (20.7;24.3)
71.5 65.6 57.1
(70.1;73.0) (63.5;67.6) (53.6;60.5)
CI: Confidence interval.
Table 2 Life expectancy and expected lifetime without long-standing, limiting illness lost among 25-year-old Danes in 2000 due to exposure to risk factors Risk factor
Men
Women
Life Expected Life Expected expectancy lifetime expectancy lifetime lost (years) without lost (years) without long-standing long-standing illness lost illness lost (years) (years) Smoking Ex-smoker Moderate smoker Heavy smoker Alcohol consumption High Physical activity Inactive Overweight Moderate overweight Obese
2.4 5.0 8.7
5.2 6.9 10.4
1.5 5.3 10.4
2.5 5.2 10.5
4.7
5.0
4.0
0.8
5.3
8.3
5.1
10.3
0.0
− 1.4
0.7
3.9
2.0
4.9
3.2
10.0
for physically active persons. Obese men and women could expect 2.0 years and 3.2 years shorter life expectancy than men and women with normal weight. The difference in lifetime without long-standing, limiting illness was 4.9 years and 10.0 years for men and women, respectively. Moderate overweight did not reduce life expectancy for men but tended to increase expected lifetime without illness by 1.4 years. For women, however, moderate overweight reduced life expectancy by 0.7 years and reduced lifetime without illness by almost 4 years. Discussion Our quantification of the consequences of exposure to the selected risk factors on health expectancy cannot be compared with those found in (the few) other studies on this topic (Ferrucci et al., 1999; Nusselder et al., 2000; Peeters et al., 2004; Visscher et al., 2004; Østbye and Taylor, 2004; Franco et al., 2005; Reynolds et al., 2005), mainly because of differences in the choice of health expectancy measures and age groups and
52
H. Brønnum-Hansen et al. / Preventive Medicine 45 (2007) 49–53
in the definitions of exposure. The overall conclusion, however, is that smoking is the most important preventable risk factor for serious health-damaging effects. The conclusions are consistent with those of a similar study in which the impact of risk factors on quality-adjusted life years (QALYs) were estimated (Brønnum-Hansen et al., in press). Thus, the ranking of the risk factors as to loss of QALYs was the same as of expected lifetime without long-standing, limiting illness. However, while high alcohol consumption reduced life expectancy by 4–5 years, an opposite effect was seen on expected lifetime with long-standing, limiting illness. We have no explanation for the finding that the proportion of expected lifetime without illness was higher among women who exceeded the recommended maximum alcohol intake than among women who followed the recommendation. The conclusion could not be confirmed by using other healthrelated measures of the impact of high alcohol consumption (Juel et al., 2006). For instance, the apparent inconsistency was not seen for the effect of high alcohol consumption on QALYs (Brønnum-Hansen et al., in press). We did not analyze the effect of low alcohol consumption (i.e. no alcohol intake the week before interview), in a group composed of persons who seldom or never drink alcohol and former alcoholics. The prevalence of alcohol abstention is low in Denmark: about 3% among men and 7% among women (Grønbæk, 2004). Previous Danish estimates of reduced life expectancy due to smoking (Brønnum-Hansen and Juel, 2001) were roughly 2 years shorter for heavy smokers than that found in this study. This result is due to use of a less conservative confounder adjustment, 30% (Ezzati and Lopez, 2006) instead of 50% reduction of excess risk, as originally suggested by Peto and colleagues (1992). The main reason for classifying non-smokers as ‘never’ and ex-smokers was to define the unexposed group as precisely as possible by eliminating ex-smokers, who represent a heterogeneous group that includes persons who were light smokers for a short period and former heavy smokers who became ill because of smoking. We found a protective effect of moderate overweight for men but not for women. The appropriateness of BMI and of (equal) classification of weight groups for men and women has been questioned (McGee, 2005). We consider that exclusion of underweight people (0.6% of men and 4.0% of women) from the analysis of the health consequence of overweight had a negligible effect, although some underweight people might have been persons who had been overweight or obese but who had lost weight due to overweight-related diseases. As regards the analysis of the impact of physical inactivity on health, the consequence of excluding individuals who were disabled at the time of interview (9.3%) might have been to underestimate the effect, as disability can be caused by a sedentary lifestyle. We consider this underestimation to be less serious than the overestimation that would result from the inclusion of disabled persons who were more likely to suffer from long-standing illness and to be physically inactive than persons who were not disabled. The definitions of exposure to risk factors might also have biased the results. Three groups of physically active persons were
combined and compared with sedentary persons. If more physical activity increases lifetime without long-standing illness and reduces the mortality risk, then combining persons with light, moderate and vigorous activity will result in an underestimate of the potential health benefits of a lifestyle change for sedentary individuals. The method also disregards the potential benefits that persons with light and moderate physical activity might achieve from more physical activity. It is difficult, however, to classify individuals in terms of physical activity precisely in population-based surveys, and people may change their activity levels more rapidly than their smoking habits and weight. Life tables by risk factor level were constructed from the Danish National Cohort Study by individual follow-up data on deaths among health survey participants. Changes in exposure to risk factors during follow-up were unknown and might have biased the estimates of relative risk for death to some extent. Nevertheless, our estimates were in agreement with those of other studies. Sullivan's method for estimating health expectancy is simple and directly applicable when life tables and sex- and agespecific prevalence of the health state exist for the population. A limitation is that the prevalence reflects previous trends in mortality and disease incidence and recovery. One way of overcoming this problem is to gather longitudinal data and apply multistate life table methods. Considering the hypothetical situation reflected by elimination of risk factor exposure, the limitations of Sullivan's method are negligible. Self-reported lifestyle-related (and unhealthy) habits are expected to be underreported. For instance, persons with high alcohol consumption might underreport their drinking, and overweight people might underreport their weight. Such misclassification might result in underestimates of health differences between exposed and unexposed persons. Another shortcoming of the study was the 19–26% nonresponse rate in the health interview surveys. In general, individuals with abuse problems or who are in poor health are more likely to be non-responders than persons with no such problems. Thus, non-response might in some cases result in underestimates of differences between exposed and unexposed persons. The size of the health interview survey samples did not allow adjustment for clustering of exposures to risk factors. For instance, the analysis did not take into account the fact that persons with high alcohol consumption are more likely to be smokers, overweight and physically inactive or that the prevalence of obesity is higher among sedentary than among physically active people. Furthermore, socially disadvantaged groups are more likely to have unhealthy lifestyles than advantaged groups. Nevertheless, the results might help to identify subpopulations at high risk, and this would not necessarily be easier if the results were established from a multivariate model including adjustments for other risk factors. Conclusions The increased mortality and loss of life years due to exposure to risk factors are compounded by an even higher loss of lifetime
H. Brønnum-Hansen et al. / Preventive Medicine 45 (2007) 49–53
without illness. Thus, in general, the healthy life years of exposed persons are reduced to a greater extent than total life years, and healthy lifetime is transformed into years with illness. A reduction in exposure to risk factors can therefore lengthen lifetime and compress morbidity. Smoking is the most hazardous risk factor and is highly prevalent in Denmark, although the rate has been declining for some years; however, overweight is increasing and, in combination with physical inactivity, constitutes a growing public health challenge for the future. References Brønnum-Hansen, H., Juel, K., 2001. Abstention from smoking extends life and compresses morbidity: a population based study of health expectancy among smokers and never smokers in Denmark. Tob. Control 10, 273–278. Brønnum-Hansen, H., Juel, K., 2004. Impact of smoking on the social gradient in health expectancy in Denmark. J. Epidemiol. Community Health 58, 604–610. Brønnum-Hansen, H., Juel, K., Davidsen, M., Sørensen, J. (in press). Impact of selected risk factors on quality-adjusted life expectancy in Denmark. Scand. J. Public Health. Davidsen, M., Kjøller, M., 2002. The Danish health and morbidity survey— design and analysis. Stat. Transit. 5, 927–942. Ezzati, M., Lopez, A.D., 2006. Smoking and oral tobacco use. In: Ezzati, M., Lopez, A.D., Rodgers, A., Murray, C.J.L. (Eds.), Comparative Quantification of Health Risks. WHO, Geneva, pp. 883–957. Ferrucci, L., Izmirlian, G., Leveille, S., Phillips, C.L., Corti, M.C., Brock, D.B., Guralnik, J.M., 1999. Smoking, physical activity, and active life expectancy. Am. J. Epidemiol. 149, 645–653. Franco, O.H., de Laet, C., Peeters, A., Jonker, J., Mackenbach, J.P., Nusselder, W. J., 2005. Effects of physical activity on life expectancy with cardiovascular disease. Arch. Intern. Med. 165, 2355–2360. Grønbæk, M.N., 2004. Alcohol intake in Denmark—public health challenges and scientific questions. Ugeskr. Læger 166, 1573–1576.
53
Helweg-Larsen, K., Kjøller, M., Davidsen, M., Rasmussen, N.K., Madsen, M., Kamper-Jørgensen, F., 2003. The Danish National Cohort Study (DANCOS). Dan. Med. Bull. 50, 177–180. Jagger, C., Hauet, E., Brouard, N., 2001. Health expectancy calculation by the Sullivan method: a practical guide. European concerted action on the harmonization of health expectancy calculations in Europe. EURO-REVES, 2001:29. REVES Paper no. 408. Leicester, Paris. Juel, K., Sørensen, J., Brønnum-Hansen, H., 2006. Risikofaktorer og folkesundhed i Danmark (Risk Factors and Public Health in Denmark). National Institute of Public Health, Copenhagen. (in Danish). McGee, D.L., 2005. Body mass index and mortality: a meta-analysis based on person-level data from twenty-six observational studies. Ann. Epidemiol. 15, 87–97. National Institute of Public Health, 2002. Sundhed og sygelighed i Danmark 2000 og udviklingen siden 1987. (The Danish Health Interview Survey 2000 and the Development since 1987). National Institute of Public Health, Copenhagen (in Danish). Nusselder, W.J., Looman, C.W., Marang-van de Mheen, P.J., van de Mheen, H., Mackenbach, J.P., 2000. Smoking and the compression of morbidity. J. Epidemiol. Community Health 54, 566–574. Østbye, T., Taylor, D.H., 2004. The effect of smoking on years of healthy life (YHL) lost among middle-aged and older Americans. Health Serv. Res. 39, 531–552. Peeters, A., Bonneux, L., Nusselder, W.J., de Laet, C., Barendregt, J.J., 2004. Adult obesity and the burden of disability throughout life. Obes. Res. 12, 1145–1151. Peto, R., Lopez, A.D., Boreham, J., Thun, M., Heath, C.J., 1992. Mortality from tobacco in developed countries: indirect estimation from national vital statistics. Lancet 339, 1268–1278. Reynolds, S.L., Saito, Y., Crimmins, E.M., 2005. The impact of obesity on active life expectancy in older American men and women. Gerontologist 45, 438–444. Sullivan, D.F., 1971. A single index of mortality and morbidity. Health Serv. Ment. Health Adm. Health Rep. 86, 347–354. Visscher, T.L., Rissanen, A., Seidell, J.C., Heliovaara, M., Knekt, P., Reunanen, A., Aromaa, A., 2004. Obesity and unhealthy life-years in adult Finns. An empirical approach. Arch. Intern. Med. 164, 1413–1420.