ORIGINAL INVESTIGATION. Obesity and Unhealthy Life-Years in Adult Finns

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1 Obesity and Unhealthy Life-Years in Adult Finns An Empirical Approach ORIGINAL INVESTIGATION Tommy L. S. Visscher, PhD; Aila Rissanen, MD, PhD; Jacob C. Seidell, PhD; Markku Heliövaara, MD, PhD; Paul Knekt, PhD; Antti Reunanen, MD, PhD; Arpo Aromaa, MD, PhD Background: Obesity is more strongly related to morbidity and disability than to mortality. Obese individuals are thus expected to have more unhealthy life-years than normal-weight persons. The objective of the present study was to quantify the number of excess unhealthy life-years in obese individuals. Methods: A representative cohort of Finnish men and women aged 20 to 92 years was followed for 15 years. Participation rate was 83%. Obesity was defined as a body mass index of 30.0 or higher. The number of unhealthy life-years due to premature work disability, hospitalization for coronary heart disease, and need for long-term medication was calculated per category of body mass index. Results: During the follow-up of 15 years, obese men who never smoked aged 20 to 64 years had, on average, 0.63 more years of work disability, 0.36 more years of coronary heart disease, and 1.68 more years of longterm medication use, than normal-weight counterparts. Obese women had, respectively, 0.52, 0.46, and 1.49 more years from these conditions than normal weight women. The excess risks of morbidity and disability due to obesity were highest in the youngest age groups and exceeded those of mortality in all age groups. Obese men and women 65 years and older who never smoked had, respectively, 1.71 and 1.41 excess unhealthy life-years (not statistically significant) due to premature need for long-term medication compared with normal-weight subjects, but no excess unhealthy life-years due to coronary heart disease. Conclusions: Obesity has a lifetime impact on disability and morbidity. A further increase in obesity will lead to an increase in unhealthy life-years and in direct and indirect health care costs. Arch Intern Med. 2004;164: Author affiliations are listed at the end of this article. The authors have no relevant financial interest in this article. OBESITY OFTEN RUNS A long and disabling course with important health and economic consequences. 1,2 It is now well accepted that obesity contributes to the total burden of disease due to its role in the onset of cardiovascular diseases and type 2 diabetes mellitus. 3-6 Furthermore, evidence is accumulating that overweight individuals more often develop disabilities and have a lower quality of life than normal-weight individuals. 7-9 CME course available at A study on obese women from Sweden reported a 10% productivity loss due to obesity-related sick leave and work disability. 10 The direct health care costs due to obesity have been estimated at around 6% of the total health care expenditure in the United States 11 and at 1% to 5% in western European countries, where the prevalence of obesity is lower than in the United States. 12 These direct health care cost estimates may be overestimations, however, as obesity not only induces disease and disability but also reduces longevity. 13 Obese individuals are likely to have an excess of unhealthy life-years, because obesity has a more pronounced effect on morbidity and disability than on mortality. 2 To learn more about the public health impact of obesity, it is important to know how many unhealthy years of life obese persons have due to premature onset of morbidity and disability. Oster et al 14 calculated that a 10% sustained weight loss could reduce the number of life-years with hypertension by 1.2 to 2.9 years and the number of life-years with type 2 diabetes mellitus by 0.5 to 1.7 years. These calculations were based on mathematical modeling, rather than on empirical data. 1413

2 The main aim of the present study was to calculate the number of unhealthy life-years, defined as the years of premature work disability, coronary heart disease, and the need for long-term medication in obese subjects, using measured body weight at baseline and longitudinal data from national registers on work disability, coronary heart disease, and need for long-term medication. METHODS STUDY POPULATION Between 1973 and 1977, the Social Insurance Institution s Mobile Clinic Unit carried out multiphase health examinations in 12 municipalities in 4 geographic regions of Finland. 15 The main emphasis was on the risk factors for cardiovascular disorders. In each of the 4 regions, all inhabitants or a random sample of inhabitants of 1 rural municipality and one urban or semiurban municipality as well as the employees of 1 factory were invited to attend the examination. A total of men and women participated in the examinations. The mean age of participants was 45.0 years (range, years). Participation rate was 83%. For the purpose of the present study the main emphasis is on analyses regarding those who never smoked, because the relation between body mass index () and all-cause mortality may be different between smoking categories. 16,17 Neversmokers are the most relevant subjects for studies on the impact of obesity. Quitting smoking still is a more important clinical and public health message for smokers than preventing or treating obesity. In order to get an overall impression of the impact of obesity, analyses have also been performed for the whole study population, when all smoking categories were combined. MEASUREMENTS A questionnaire with items addressing educational level, medical history, alcohol use, smoking, and physical activity was sent to the subjects together with the invitation to the medical checkup, for completion before the examination. The answers to this self-filled questionnaire were checked and completed, if necessary, by a specially trained nurse at the health examination. BASELINE Baseline measures were performed between 1973 and Body height and weight were measured at baseline when subjects were wearing light clothing. Body mass index was calculated as weight in kilograms divided by the square of height in meters. Four categories of were defined according to the World Health Organization guidelines 18 : under 18.5 was considered as underweight, between 18.5 and 24.9 as normal weight, between 25.0 and 29.9 as moderate overweight, and a between 30.0 and 39.9 as obesity. The few subjects who had a above 40.0 (severe obesity) were included in the obesity category. A total of 8 subjects had missing values on. As part of the health examination, systolic and diastolic blood pressures were measured. The length of education was classified in 3 categories: less than 9 years; 9 to 13 years; and more than 13 years. The overall alcohol consumption was calculated by multiplying the reported intake of beer, wine, and stronger alcoholic drinks during the preceding month by the average alcohol content of each beverage. For this study 4 categories were defined as follows: 0, less than 100, 100 to 500, and 500 or more grams of ethanol per month. The subjects were asked to classify their leisure-time activity during the usual week into 1 of 3 categories: (1) none or little; (2) walking, cycling, or related light activities, at least 4 hours per week; and (3) ball games, jogging, or related activities at least 3 hours per week or regular vigorous activities. Four categories of smoking habits were defined: (1) never smokers, (2) those who quit smoking in the past, (3) those who smoked fewer then 20 cigarettes per day at baseline or cigars only, and (4) those who smoked 20 cigarettes or more per day at baseline. FOLLOW-UP For the purpose of this study, the end of follow-up was defined 15 years after baseline (the period) ie, between 1988 and Subjects aged 20 to 64 years were followed up regarding work disability, hospitalization due to coronary heart disease, need for long-term medication, and allcause mortality until the end of follow-up, the time of death, or reaching age 65 years, whatever came first. Work disability is irrelevant after age 65 years, since 65 is the general age of retirement in Finland. To be able to compare results between end points in those who were younger than 65 years, all end points studied in this age category were not followed after age 65 years. Subjects 65 years or older were followed up for 15 years regarding all end points, except work disability. Diagnoses of all end points during follow-up were made independently and unaware of the body weight measured at baseline. WORK DISABILITY Work disability is defined as receiving any work disability pension from the National Social Insurance Institution. All Finns are being granted a disability pension if they are expected to be work disabled during the rest of their lifetimes. Both baseline and follow-up data on work disability were derived by linkage of data to the Finnish Social Insurance Institution, using the unique Social Security Code assigned to each Finnish citizen. During the follow-up most work disability pensions were from musculoskeletal disorders (41%), cardiovascular diseases (22%), mental disorders (14%), diseases of the neurologic system (including eyes and ears) (5%), neoplasms (5%), and respiratory diseases (4%). The rest (9%) were due to traumatic injuries, congenital malformations, endocrine diseases (mostly diabetes), infections, skin diseases, gastrointestinal diseases, urogenital diseases, and nondefinite symptoms. Subjects who were work disabled at baseline were excluded from the analyses on work disability. CORONARY HEART DISEASE Cardiovascular disease history at baseline was obtained using specific questions: Have you ever had, according to a physician s diagnosis,... myocardial infarction,... coronary heart disease,... arterial hypertension,... cerebral stroke? The onset of coronary heart disease was defined as being hospitalized for coronary heart disease during the follow-up. Hospitalization data were derived from the National Board of Health, using the unique Social Security Code assigned to each Finnish citizen. Subjects who had a history of cardiovascular diseases at baseline were excluded from the analyses on hospitalization due to coronary heart disease. NEED FOR LONG-TERM MEDICATION The need for long-term medication was defined as receiving any reimbursement of medication for chronic diseases. In Finland, reimbursed drug therapy is provided to all inhabitants for a number of chronic diseases, including common complications of obesity. Eligibility requires a comprehensive medical 1414

3 Table 1. Baseline ( ) Characteristics and Person-Years During Follow-up in the Social Insurance Mobile Clinic Study for All Smoking Categories Combined and for Those Who Never Smoked Age 65 y Age 65 y Men Women Men Women All Subjects subjects , mean (SD) 25.1 (3.5) 24.9 (4.5) 25.6 (3.8) 27.6 (4.6) category, No. (%) (1.0) 288 (3.5) 25 (2.6) 24 (1.9) (51.6) 4489 (53.9) 426 (43.9) 379 (29.0) (38.9) 2426 (29.1) 402 (41.4) 523 (40.1) (8.5) 1124 (13.5) 117 (12.1) 379 (29.0) Total person-years Subjects Who Never Smoked No. (%) of subjects 2599 (29.2) 6239 (74.9) 308 (31.8) 1251 (95.9), mean (SD) 24.9 (3.5) 25.3 (4.6) 26.5 (3.6) 27.6 (4.7) category, No. (%) (1.0) 171 (2.7) 3 (1.0) 21 (1.7) (54.1) 3110 (49.9) 104 (33.8) 356 (28.5) (37.5) 1982 (31.8) 153 (49.6) 507 (40.5) (7.4) 976 (15.6) 48 (15.6) 367 (29.3) Work disability at baseline, No. (%) 149 (5.7) 652 (10.4) NA NA Coronary heart disease at baseline, No. (%) 286 (11.0) 1202 (19.3) 131 (42.5) 682 (54.4) Need for long-term medication at baseline, No. (%) 219 (8.4) 1037 (16.6) 103 (33.4) 672 (53.7) Total person-years Abbreviations:, body mass index (calculated as weight in kilograms divided by the square of height in meters); NA, not applicable (because age of retirement is 65 years in Finland). certificate written by the attending physician, and the evidence must be verified by an advisory physician of the National Social Insurance Institution. Both baseline and follow-up data on the need for long-term medication were derived by linkage of data to the Social Insurance Institution s population register, using the unique Social Security Code assigned to each Finnish citizen. Most chronic diseases entitled to specially reimbursed medication meet commonly applied criteria, and the specificity of data is very high. During the follow-up most reimbursed medications were for treatment of hypertension (41%), cardiac failure (13%), asthma (9%), coronary heart disease (7%), and diabetes (5%). The rest (25%) were for 35 different less common chronic diseases. Subjects who had reimbursed medication at baseline were excluded from the analyses on need for long-term medication. UNHEALTHY LIFE-YEARS Unhealthy life-years were defined using 3 different criteria work disability, coronary heart disease, and need for longterm medication. Unhealthy life-years were defined as the number of years that subjects were alive after onset of these conditions until censoring, that is death, end of 15 years of follow-up period, or age 65 years (for those who were younger than 65 years at baseline). We chose severe end points to assume that nobody recovered from these conditions after onset and thus contributed unhealthy life-years only after developing the end point. STATISTICAL ANALYSIS Relative risks for the onset of work disability, hospitalization due to coronary heart disease, need for long-term medication, and all-cause mortality per category of have been calculated by using the Cox proportional hazards model (proc phreg, SAS, version 6.12; SAS Institute, Cary, NC). Adjustments were made for age, education, alcohol intake, and smoking (when smoking categories were combined). Additional adjustments were made for leisure-time physical activity, diastolic blood pressure, serum cholesterol level, and self-reported diabetes. Separate analyses were performed for those younger than 65 years and those 65 years and older. Relative risks were also calculated for age categories 20 to 34, 35 to 44, 45 to 54, and 55 to 64 years, to assess whether obesity has a lifetime impact on the incidence of morbidity and disability. Average number of unhealthy life-years in each category was estimated by the analysis of covariance (proc glm, SAS version 6.12), adjusting for age, educational categories, alcohol intake, and smoking (when smoking categories were combined). Again, separate analyses were performed for subjects younger than 65 years and subjects 65 years and older. Unhealthy life-years were also calculated for age categories 20 to 34, 35 to 44, 45 to 54, and 55 to 64 years. Interaction between age and has been tested by including the age category category term in the model and comparing this model with the model without the interaction term by the likelihood ratio test. The underweight category has been excluded when calculating the statistical interaction. To avoid potential overestimating of the impact of obesity on unhealthy life-years, we chose to exclude subjects with the studied end point at baseline. If the studied end point is present at baseline one is not sure whether the obesity status is the cause or the consequence of the studied end point. RESULTS A total of 8.5% of the men and 13.5% of the women aged 20 to 64 years were obese (Table 1). Moderate overweight and obesity were more common in subjects 65 years and older than in younger subjects. Smoking was uncommon among women at baseline between 1973 and 1415

4 Table 2. Relative Risks in Finnish Men Who Never Smoked Aged Younger Than 65 Years and 65 Years and Older During the Follow-up of 15 Years* Age, y No. of Men Events , especially among those 65 years and older. Among men and women aged 20 to 64 years who never smoked, obesity was prevalent among 7.4% and 15.6% of the subjects, respectively. Among men and women 65 years and older who never smoked, obesity was prevalent among 15.6% and 29.3% of the subjects, respectively (Table 1). Presence of work disability, cardiovascular diseases, and the need for long-term medication at baseline was more common among subjects with obesity than in normalweight subjects (data not shown). RELATIVE RISKS Relative Risk (95% CI) ( ) 2.3 ( ) ( ) 7.4 ( ) ( ) 2.8 ( ) ( ) 1.4 ( ) ( ) 3.1 ( ) 65 NA ( ) 2.5 ( ) ( ) 1.9 ( ) ( ) 3.7 ( ) ( ) 2.0 ( ) ( ) 2.9 ( ) ( ) 1.4 ( ) ( ) 2.8 ( ) ( ) 5.1 ( ) ( ) 2.4 ( ) ( ) 2.1 ( ) ( ) 5.2 ( ) ( ) 2.7 ( ) All-Cause Mortality ( ) 1.6 ( ) ( ) ( ) 3.0 ( ) ( ) 1.1 ( ) ( ) ( ) 1.4 ( ) Abbreviations:, body mass index (calculated as weight in kilograms divided by the square of height in meters); CI, confidence interval; NA, not applicable (because age of retirement is 65 years in Finland). *Adjustments were made for age, educational level, geographic region, and alcohol use. A total of 17 men who never smoked had missing data on these variables. Subjects younger than 65 years at baseline were not followed up after age 65 years. Subjects with the condition at baseline were excluded from the analyses. less than 18.5 is not presented because of low numbers. No subject died in this category. In both men (Table 2) and women (Table 3) aged 20 to 64 years who never smoked, obesity was more strongly related to the onset of work disability, coronary heart disease, and need for long-term medication than to allcause mortality. Obesity was not related to increased mortality in women (Table 3). The adjustment for educational level, geographic region, alcohol intake, and physical activity had negligible effect on relative risks (data not shown). Further adjustment for diastolic blood pressure, serum cholesterol level, and baseline presence of diabetes resulted in somewhat lower relative risks (data not shown). Relative risks of moderate overweight and obesity for work disability, coronary heart disease, and need for long-term medication were generally higher in the younger than in the older men (Table 2) and women (Table 3). P values for interaction between age and categories were.11,.13, and.05 among men and.13,.01, and.01 among women for onset of work disability, coronary heart disease, and long-term medication, respectively. No clear age gradient was seen for the relation between obesity and all-cause mortality in men. (P values for interaction between age and categories were.68 among men and.05 among women for mortality.) Also, in men 65 years and older who never smoked, obesity was more strongly related to both the onset of coronary heart disease and the need for long-term medication than to all-cause mortality (Table 2). In women aged 65 years who never smoked, obesity was related to the need for long-term medication, not to the onset of coronary heart disease and all-cause mortality (Table 3). UNHEALTHY LIFE-YEARS Among subjects aged 20 to 64 years who never smoked, moderate overweight and obesity were associated with an increased number of unhealthy life-years during the follow-up period of 15 years. Obese men aged 20 to 64 years who never smoked had 0.63 more years of work disability, 0.36 more years of coronary heart disease, and 1.68 more years of long-term medication compared with normal-weight men (Table 4). Obese women aged 20 to 64 years who never smoked had 0.52, 0.46, and 1.49 more unhealthy life-years due to premature onset of these respective conditions than normal-weight women (Table 5). The number of unhealthy life-years increased with age and was highest in the obesity category ( 30) in nearly all analyses at age 20 to 64 years (Tables 4 and 5). Subjects 65 years and older had more unhealthy lifeyears than subjects aged 20 to 64 years. Among men and women 65 and older who never smoked, obesity was not associated with an increased number of unhealthy lifeyears due to coronary heart disease. Obese men and women 65 years and older who never smoked had, respectively, 1.71 and 1.41 more years of long-term medication than their normal-weight counterparts (Tables 4 and 5). These differences in elderly men and women did not reach statistical significance. ALL SMOKING CATEGORIES COMBINED When the few smoking women were added to the analyses, relative risks of and average numbers of unhealthy life-years due to the different end points were only slightly different as when never smoking women were analyzed 1416

5 Table 3. Relative Risks in Finnish Women Who Never Smoked Aged Younger Than 65 Years and 65 Years and Older During the Follow-up of 15 Years* Age, y Women Events Relative Risk (95% CI) ( ) 1.6 ( ) ( ) 1.5 ( ) ( ) 2.4 ( ) ( ) 1.5 ( ) ( ) 1.3 ( ) 65 NA ( ) 2.7 ( ) ( ) 4.1 ( ) ( ) 2.6 ( ) ( ) 2.6 ( ) ( ) 2.2 ( ) ( ) 0.8 ( ) ( ) 2.3 ( ) ( ) 1.9 ( ) ( ) 2.6 ( ) ( ) 2.3 ( ) ( ) 2.3 ( ) ( ) 1.3 ( ) All-Cause Mortality ( ) 1.0 ( ) ( ) ( ) 0.7 ( ) ( ) 1.4 ( ) ( ) 0.7 ( ) ( ) 0.9 ( ) Abbreviations:, body mass index (calculated as weight in kilograms divided by the square of height in meters); CI, confidence interval; NA, not applicable (because age of retirement is 65 years in Finland). *Adjustments were made for age, educational level, geographic region, and alcohol use. A total of 65 women who never smoked had missing data on these variables. Subjects younger than 65 years at baseline were not followed up after age 65 years. Subjects with the condition at baseline were excluded from the analyses. less than 18.5 is not presented because of low numbers. No subject died in this category. separately. Only the average numbers of unhealthy lifeyears in women 65 years and older decreased somehow, but the difference in unhealthy life-years between categories remained similar (data not shown). When the smoking men were added to the analyses, relative risks of the different end points became smaller among men aged 20 to 65 years, not among men 65 and older (Table 6). The average numbers of unhealthy lifeyears became slightly higher among men aged 20 to 65 years when smokers were added to the analyses, but the differences between categories remained the same (Table 6). Among men 65 years and older, the average numbers of unhealthy life-years were higher when smoking men were added to the analyses, but the differences between categories were similar as in men from this age category who never smoked (Table 6). Table 4. Average Unhealthy Life-Years Due to Work Disability,, and the Need for Long-term Medication in Men Who Never Smoked During the Follow-up of 15 Years* Life-Years (95% CI) Age, y ( ) 0.58 ( ) 1.00 ( ) ( ) 0.22 ( ) 0.70 ( ) ( ) 0.58 ( ) 0.70 ( ) ( ) 1.28 ( ) 1.57 ( ) ( ) 0.95 ( ) 1.44 ( ) 65 NA ( ) 0.56 ( ) 0.64 ( ) ( ) 0.18 ( ) 0.43 ( ) ( ) 0.63 ( ) 0.92 ( ) ( ) 1.31 ( ) 0.77 ( ) ( ) 0.33 ( ) 0.72 ( ) ( ) 2.89 ( ) 2.48 ( ) ( ) 1.36 ( ) 2.38 ( ) ( ) 0.80 ( ) 2.46 ( ) ( ) 1.59 ( ) 2.83 ( ) ( ) 2.37 ( ) 3.09 ( ) ( ) 0.77 ( ) 0.70 ( ) ( ) 3.79 ( ) 4.31 ( ) Abbreviations:, body mass index (calculated as weight in kilograms divided by the square of height in meters); CI, confidence interval; NA, not applicable (because age of retirement is 65 years in Finland). *Adjustments were made for age, educational level, geographic region, and alcohol use. A total of 17 men who never smoked had missing data on these variables. Subjects younger than 65 years at baseline were not followed up after age 65 years. Subjects with the condition at baseline were excluded from the analyses. less than 18.5 is not presented because of low numbers. COMMENT This is, to our knowledge, the first prospective study to quantify the number of unhealthy life-years in relation to moderate overweight and obesity. The results indicate that obesity is associated with an increased number of unhealthy life-years assessed by different criteria, ie, work disability, coronary heart disease, and especially need for long-term medication. The relative risks of all these sequelae were greatest in the youngest subjects, emphasizing the lifetime impact of early-onset obesity. The present study also shows that obesity substantially increases the number of unhealthy life-years in older adults. Several studies have documented increased relative risks of chronic diseases in categories of overweight. Relative risks were generally higher for morbidity and disability than for all-cause mortality. 2 This was confirmed in the present study. Based on results of the Framingham Study, attributable fractions were calculated to show that if everybody could maintain optimal weight, there would be 25% less coronary heart disease and 35% fewer strokes or episodes of heart failure. 19 The attributable fraction of overweight ( 25) for type 1417

6 Table 5. Average Unhealthy Life-Years Due to Work Disability, and the Need for Long-term Medication in Women Who Never Smoked During the Follow-up of 15 Years* Life-Years (95% CI) Age, y ( ) 0.86 ( ) 1.04 ( ) ( ) 0.19 ( ) 0.12 ( ) ( ) 0.69 ( ) 1.25 ( ) ( ) 1.62 ( ) 1.75 ( ) ( ) 0.65 ( ) 0.84 ( ) 65 NA ( ) 0.33 ( ) 0.64 ( ) ( ) 0.20 ( ) 0.44 ( ) ( ) 0.33 ( ) 0.93 ( ) ( ) 0.53 ( ) 0.97 ( ) ( ) 0.02 ( ) 0.12 ( ) ( ) 1.61 ( ) 1.83 ( ) ( ) 1.72 ( ) 2.44 ( ) ( ) 1.32 ( ) 1.38 ( ) ( ) 1.30 ( ) 2.81 ( ) ( ) 2.67 ( ) 3.68 ( ) ( ) 0.51 ( ) 0.85 ( ) ( ) 4.56 ( ) 6.32 ( ) Abbreviations:, body mass index (calculated as weight in kilograms divided by the square of height in meters); CI, confidence interval; NA, not applicable (because age of retirement is 65 year in Finland). *Adjustments were made for age, educational level, geographic region, and alcohol use. A total of 65 women who never smoked had missing data on these variables. Subjects younger than 65 years at baseline were not followed up after age 65 years. Subjects with the condition at baseline were excluded from the analyses. less than 18.5 is not presented because of low numbers. 2 diabetes mellitus has been calculated to be 64% in US men and 77% in women. 6,20,21 Other studies have calculated the public health impact of obesity by calculating the economic costs of its consequences. These economic studies should take into account the relation between obesity and increased mortality rates. 11 Thompson and colleagues did take into account the relation between obesity and reduced longevity when calculating the lifetime costs for treatment of hypertension, hypercholesterolemia, type 2 diabetes mellitus, coronary heart disease, and stroke, among men aged 45 to 54 years. These costs were $29600 and $36500 among those with values of 32.5 and 37.5, respectively, compared with $19600 among those with a of These calculations were based on mathematical modeling, rather than on empirical data. The results from the present study could be helpful in new calculations of obesity-related costs. We cannot explain why obesity was not related to mortality among women in most age categories. An earlier study on Dutch men and women aged 30 to 54 years concluded that obesity is related to all-cause mortality in men, but not in women. 22 The relatively low mortality rate may be one explanatory factor. Other large studies reported that relative risks of obesity for mortality are higher in the younger men and women than in older age groups. 17,23 Further, obesity, defined by levels of, was weakly related to the onset of coronary heart disease in men 65 years and older and not in elderly women. Obesity was not related to an increased number of unhealthy life-years due to coronary heart disease in both elderly men and women. In elderly populations, may not be the best indicator of body fatness as body height and body composition change with aging. The waist circumference may be a more useful predictor of all-cause mortality, as we previously have shown in men who had never smoked. 24 In addition, a large waist circumference seems to indicate increased body fatness and health risk in the elderly, as has been shown for both men and women. 25 The interpretation of the average numbers of unhealthy life-years due to work disability, coronary heart disease, and need for long-term medication is made difficult by the severely skewed distributions, as relatively few subjects experienced one of these end points during the follow-up (Tables 2 and 3). The distribution of numbers of unhealthy life-years could not be normalized by log transformation, as the majority of subjects had, consequently, no unhealthy life-years during the follow-up. The skewed distribution necessitates a cautious interpretation of the confidence intervals around the average number of unhealthy life-years. However, it is unlikely that the increased number of unhealthy lifeyears in the obese is found by coincidence, as our analyses were based on more than 2500 never-smoking men and more than 6000 never-smoking women contributing more than person-years. We found the relation between high and unhealthy life-years in all age categories between 20 and 65 years, and we found dose-response relations on and number of unhealthy life-years for most analyses. The impact of obesity is likely to be underestimated in the present study, because we chose to exclude subjects who had the chronic conditions of interest already at baseline. This is because we cannot exclude the possibility that obesity in these subjects is the consequence rather than the cause of the chronic condition. These subjects, in whom obesity was more common than in subjects without the chronic condition, would have contributed unhealthy life-years only. This study has important methodological strengths. We measured body weight in a representative population sample of Finns. Participation rate was high. Follow-up data were complete because of the unique personal identity code, which is used in all health registers in Finland. All carefully defined end point measures were defined independently from baseline, as data on work disability, coronary heart disease, need for long-term medication, and all-cause mortality were collected from independent databases. Further, misclassification of the studied end points is unlikely because of the severe nature of persistent work disability, coronary heart disease, and need for long-term medication. In additional analyses we adjusted for several risk factors of disease and disability. Only the adjustment for diabetes, diastolic blood pressure, and serum cholesterol level 1418

7 Table 6. Relative Risks of and Average Unhealthy Life-Years Due to,, and the Need for Long-term Medication in Men From All Smoking Categories Combined During the Follow-up of 15 Years* Relative Risk (95% CI) Average Unhealthy Life-Years (95% CI) Age, y Men Events ( ) 1.7 ( ) 0.70 ( ) 0.80 ( ) 1.19 ( ) 65 NA ( ) 1.6 ( ) 0.48 ( ) 0.67 ( ) 0.83 ( ) ( ) 1.3 ( ) 1.62 ( ) 1.83 ( ) 1.89 ( ) ( ) 2.5 ( ) 0.83 ( ) 1.45 ( ) 2.52 ( ) ( ) 2.4 ( ) 1.56 ( ) 2.31 ( ) 3.21 ( ) All-Cause Mortality ( ) 1.3 ( ) ( ) 1.6 ( ) Abbreviations: body mass index (calculated as weight in kilograms divided by the square of height in meters); CI, confidence interval; NA, not applicable (because age of retirement is 65 years in Finland). *Adjustments were made for age, educational level, geographic region, alcohol use, and smoking. A total of 80 men had missing data on these variables. Subjects younger than 65 years at baseline were not followed up after age 65 years. Subjects with the condition at baseline were excluded from the analyses. less than 18.5 is not presented because of low numbers. lowered the relative risks. Adjustment for these risk factors, however, is not appropriate as they are in the causal chain between obesity and coronary heart disease and all-cause mortality. 26 Because we excluded persons with the studied condition at baseline from the analyses, we suggest that most part of the difference in unhealthy life-years between obese and normal-weight subjects that are presented in this study could be directly attributed to obesity. The number of unhealthy life-years due to obesityrelated conditions depend on the relative risks of obesity for the different conditions and mortality, the incidence rates of the conditions and mortality, a possible interaction between obesity status and the chronic condition on mortality, and on case-fatality of the chronic conditions. Our methodology is innovative and contributes to the existing literature because it is the first study taking into account these mortality-related issues, based on empirical data. The present study shows that obesity is more strongly related to disability and morbidity than to all-cause mortality. Obesity is having a large impact on the public in all adult age categories. Obese individuals have more unhealthy life-years due to work disability, coronary heart disease, and need for long-term medication. A further increase in the prevalence of overweight and obesity will lead to an increase in obesity-related health care costs due to an increase in number of unhealthy life-years. Accepted for publication July 18, From the Department of Health and Disability, National Public Health Institute, Helsinki, Finland (Drs Visscher, Heliövaara, Knekt, Reunanen, and Aromaa); Department for Nutrition and Health, Faculty of Earth and Life Sciences, Free University Amsterdam, Amsterdam, the Netherlands (Drs Visscher and Seidell); Centre for Prevention and Health Services Research, National Institute for Public Health and the Environment, Bilthoven, the Netherlands (Dr Visscher); Knowledge Center Overweight, Free University Medical Center, Amsterdam, the Netherlands (Drs Visscher and Seidell); Obesity Research Unit, Helsinki University Central Hospital, Helsinki, Finland (Dr Rissanen); and Department of Internal Medicine, Free University Medical Center, Amsterdam, the Netherlands (Dr Seidell). Correspondence: Tommy L. S. Visscher, PhD, Department for Nutrition and Health, Faculty of Earth and Life Sciences, Free University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands REFERENCES 1. Thompson D, Edelsberg J, Colditz GA, Bird AP, Oster G. Lifetime health and economic consequences of obesity. Arch Intern Med. 1999;159: Visscher TLS, Seidell JC. The public health impact of obesity. Annu Rev Public Health. 2001;22: Manson JE, Colditz GA, Stampfer MJ, et al. A prospective study of obesity and risk of coronary heart disease in women. N Engl J Med. 1990;322: Rimm EB, Stampfer MJ, Giovannucci E, et al. Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men. Am J Epidemiol. 1995;141: Carey VJ, Walters EE, Colditz GA, et al. Body fat distribution and risk of noninsulin-dependent diabetes mellitus in women: the Nurses Health Study. Am J Epidemiol. 1997;145: Chan JM, Rimm EB, Colditz GA, Stampfer MJ, Willett WC. Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men. Diabetes Care. 1994;17: Felson DT, Zhang Y, Hannan MT, et al. Risk factors for incident radiographic knee osteoarthritis in the elderly: the Framingham Study. Arthritis Rheum. 1997;40: Rissanen A, Heliövaara M, Knekt P, Reunanen A, Aromaa A, Maatela J. Risk of disability and mortality due to overweight in a Finnish population. BMJ. 1990; 301: Lean MEJ, Han TS, Seidell JC. Impairment of health and quality of life in people with large waist circumference. Lancet. 1998;351:

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