Vital exhaustion and risk for cancer

A prospective cohort study on the association between depressive feelings, fatigue, and risk for cancer




Vital exhaustion, defined as feelings of depression and fatigue, has previously been investigated mainly as a risk factor for cardiovascular disease. The authors investigated the association between depressive feelings and fatigue as covered by the concept of vital exhaustion and the risk for cancer.


The sample consisted of 8527 persons aged 21–94 who had been examined in 1991–1994 within the Copenhagen City Heart Study. For the analysis, the sample was divided into quartiles on the basis of vital exhaustion scores. Cancer cases were ascertained by linkage to the Danish Cancer Registry. The mean length of follow-up was 8.6 years. Regression analyses for etiology-based groups of cancer sites were conducted on the basis of the Cox proportional hazards model, with adjustment for a number of confounding variables.


Cancer was diagnosed in 976 persons (12%) during follow-up. In comparison to those with the lowest scores, persons with the highest vital exhaustion scores had a significantly decreased risk for developing cancer at all sites (hazard ratio [HR], 0.80; 95% confidence interval [CI}, 0.66–0.96), smoking-related cancers (HR, 0.64; 95% CI, 0.46–0.90), and virus and immune-related cancers (HR, 0.51; 95% CI, 0.26–0.99). No significant change in risk was found for cancers related to alcohol consumption or hormones.


The results did not support the hypothesis that symptoms of fatigue and depression, as ascertained in the vital exhaustion index, increased the risk for cancer. Cancer 2005. © 2005 American Cancer Society.

The hypothesis that psychological factors cause cancer has widespread credence in the lay community and has also been the subject of research. Depressive mood and depression are among the psychological factors most widely implicated in cancer,1, 2 on the basis of the hypothesis that depression lowers immune function, thus increasing vulnerability to cancer.3 The results of epidemiologic studies on depression and cancer incidence are inconsistent. Some studies show a positive association,4–7 whereas others do not.8–10 Although the measure of depression used in these studies varied, it was usually based on self-evaluated psychometric scales. We recently reported two prospective population-based cohort studies with large samples in which depression was defined on the basis of two unbiased indicators: prescriptions for antidepressive medication and admission to a psychiatric hospital. The results of these two studies do not support the hypothesis of an independent influence of depression on the later occurrence of cancer.11, 12

The concept of vital exhaustion was originally developed in the context of risk factors for cardiac events, as it had been observed that myocardial infarct is often preceded by feelings of decreased energy, general malaise, and minor depression.13 Based on a large cohort study, Appels et al.14 developed a questionnaire to assess these symptoms. They gave the name “vital exhaustion” to the syndrome consisting of feelings of excessive fatigue and lack of energy, increased irritability, and a feeling of demoralization.15 In studies on the association between vital exhaustion and cardiac events, vitally exhausted persons had an increased relative risk for cardiac events such as myocardial infarct and angina pectoris.16, 17 A prospective study on vital exhaustion and ischemic heart disease based on the same data set as used in the analysis described in the current study showed that higher vital exhaustion scores were associated with myocardial infarct and all-cause mortality among both men and women.18

We investigated the association between depressive feelings and fatigue, measured with the vital exhaustion questionnaire, and cancer incidence in a prospective cohort design. To investigate the direct influence of vital exhaustion on cancer risk as well as the possible indirect influence conveyed by an unhealthy life style known to be associated with depression,19–21 the analyses were conducted using both a univariate model and a multivariate model with adjustment for a number of well known risk factors for cancer.


Study Sample

The data were obtained from the Copenhagen City Heart Study, which has been described in detail elsewhere22, 23 and is, therefore, outlined only briefly below. The study was initiated in 1976, by inviting 19,698 persons randomly selected within strata of age and gender from 2 districts of Copenhagen, Denmark, who were ≥ 20 years at the date of inclusion. At that time, the participants completed a self-administered questionnaire and also underwent a physical examination. A second survey was conducted in 1981–1983, in which 500 additional persons aged 20–24 years were invited to participate. The data used in the current study were obtained from a further follow-up of this cohort, in 1991–1994, when a further 3000 persons, aged 20–49 years, were invited to join the study. A total of 10,135 persons completed the questionnaire and underwent a physical examination (response rate, 61%).

We excluded 589 persons (6%) for whom a cancer diagnosis had been made before the date of the third survey of the Copenhagen City Heart Study (date of entry for the current study), a further 379 persons (4%) for whom data on ≥ 1 item in the vital exhaustion scale were missing, and 640 persons (6%) for whom data on ≥ 1 of the confounders included were missing, leaving 8527 persons (84%) whose data were eligible for the analyses.

Follow-Up for Cancer

Follow-up for cancer occurrence in the third survey began on the date of examination between October 10, 1991 and September 16, 1994 and ended on the date of diagnosis of a first primary cancer, emigration, death (from all causes), or November 30, 2002, whichever came first. Cancer cases were ascertained by linkage with the Danish Cancer Registry, which has documented all cases of malignant neoplasms in Denmark in a population-based registry since 1942.24 Registration of cancer cases is based on a modified Danish version of the International Classification of Diseases, seventh revision. Nonmelanoma skin carcinoma was not considered to be a first primary cancer, but any cancer occurring subsequently was regarded as a first primary cancer. For persons with two or more cancers, the first cancer was considered in the analysis according to the date of diagnosis as documented in the Danish Cancer Registry.

Variables Considered

Vital exhaustion was measured from a self-administered questionnaire consisting of 17 items from the Maastricht questionnaire developed by Appels et al.14 Separate analyses of the subscales of the Maastricht questionnaire could not be conducted because not all of the original 21 items were provided in the third survey of the Copenhagen City Heart Study. The answer categories of the items were yes, no, and I don't know. Each yes response was assigned two points, each I don't know response counted as one point, and each no response was assigned zero points. Vital exhaustion was calculated as the sum of all scores, with a possible range of 0–34 points. We found no published recommendations for cutoff points or normal population vital exhaustion scores. The sample quartile points were used in the regression analyses, and the sample was divided into not exhausted (first quartile; vital exhaustion sum score, 0–1), slightly exhausted (second quartile; score, 2–4), exhausted (third quartile; score, 5–11), and highly exhausted (fourth quartile; score, 12–34). We included information on physical activity during leisure time in 3 categories: sedentary, moderate activity (≤ 4 hours per week), and activity for > 4 hours per week.

Tobacco consumption was classified in 5 categories: never smoked, former smoker, and current smoker of 1–14, 15–24, and ≥ 25 g tobacco per day. For calculating tobacco consumption, 1 cigarette was considered to equal 1 g, 1 cheroot to equal 3 g, and 1 cigar to equal 5 g of tobacco.

Duration of smoking was divided into 5 categories: 0, 1–15, 16–30, 31–45, and > 45 years.

Alcohol consumption was separated into 4 categories: abstinent, < 1 drink per day, 1–2 drinks per day, and > 2 drinks per day.

Body mass index (BMI) was included as a linear variable.

Length of school education was divided into 3 categories: < 8 years (completed primary school), 8–11 years, and > 11 years. Annual household income (in Danish kroner) at date of inclusion was registered in 6 categories: < 100,000, 100,000–149,000, 150,000–199,000, 200,000–299,000, 300,000–399,000, and ≥ 400,000.

Cohabitation was considered as a dichotomous variable: living alone versus not living alone.

Statistical Analyses

The analyses of the relation between cancer incidence rates and vital exhaustion scores were based on gender-stratified Cox proportional hazard models, with age as the time axis to ensure that the estimations were based on comparisons of individuals of the same age. Time under study was included as a time-dependent variable and was modeled by a linear spline with boundaries at 1 year, 2 years, and 3 years after entry into the study to allow for a possible “healthy participants” effect. A linear spline was used to allow for a steady increase in the rate during the first 3 years and a possible slower, steady increase thereafter.25 Subjects who died of other causes than cancer were censored in the survival analysis.

In all the models, adjustment was made for physical activity, tobacco and alcohol consumption, BMI, school education, household income, and cohabitation status. Associations were estimated for the two genders separately and combined. For the combined analysis, we did not find a significant difference between the two genders, using the Wald test. In all the analyses, stratification according to gender was performed, so that the basic (underlying) hazards were gender specific.

Variables were entered linearly into the Cox model whenever possible. This is biologically more reasonable than the step functions corresponding to categories and, furthermore, increases the power of the analyses.26 The linearity of the associations was evaluated graphically by linear splines with three boundaries25 placed at the quartiles among cases. Only BMI could be entered as a linear variable.

For the Cox regression analyses, cancers were grouped by etiology, as smoking-related cancers, alcohol-related cancers, virus and immune-related cancers, and hormone-related cancers. Cancers were categorized into etiologic groups on the basis of established scientific evidence on cancer risk factors and etiology.27 Furthermore, this categorization is in accordance with the theories of the interaction between psychological factors and cancer. In the cancer-prone personality model, personality or psychological factors are assumed to impair the immune system and thereby influence cancer risk. In the personality–health behavior model, personality or psychological factors are assumed to predispose to life style factors that influence cancer risk.28 The categorization into etiologic groups on the basis of both life style and immunologic and hormonal factors applied in the current analyses fits the assumed mechanisms in both theories.

Two-sided 95% confidence intervals (CIs) for the hazard ratio were calculated based on the Wald test of the Cox regression parameter on the log-rate ratio scale. The procedure PHREG in SAS (release 8.2; SAS Institute, Inc., Cary, NC) on the TextPad platform was used for the statistical analyses.

To illustrate the extent to which the cancer risk of cohort members differed from that of the population of the Copenhagen municipality, the overall cancer incidence of the study cohort was compared with incidence rates for Greater Copenhagen stratified by gender, 5-year age groups, and calendar year. These rates were applied to the person-years under observation to obtain the number of cancers expected had the cohort members experienced the same rate of cancer as that observed in the population of Copenhagen. It is to be expected in a longitudinal cohort study that selection can occur with repeated measurements, resulting in selection bias in the constitution of the sample, especially in the subsample of persons who joined the cohort in earlier surveys. To investigate this effect, the sample was divided into long-term participants (who attended both the second examination in 1981–1983 and the third examination in 1991–1994) and persons newly recruited for the third survey. The cancer risk of the study sample in comparison with the Greater Copenhagen population was calculated only for all cancers owing to the smaller sample size of the newly recruited participants and the consequently small numbers of cancer cases in some of the etiology-based cancer groups. Tests of significance and CIs for the standardized incidence ratio (SIR), taken as the ratio of the observed to the expected numbers of cancers, were calculated by the indirect method of standardization.


Persons with a higher exhaustion score, especially those in the fourth quartile, were significantly more likely to be physically inactive, have a high tobacco consumption, live alone, earn less money, and have less school education than less vitally exhausted subjects (Table 1).

Table 1. Sample Characteristics at Date of Entry (n = 8527)
CharacteristicsVital exhaustion sum score
1st quartile 0–1 n = 2275 (%)2nd quartile 2–4 n = 2021 (%)3rd quartile 5–11 n = 2215 (%)4th quartile 12–34 n = 2016 (%)P valuea
  • yrs: years; SD: standard deviaiton.

  • a

    P values were calculated from chi-square tests or analyses of variance.

Mean age in yrs (SD)58.8 (14.8)56.8 (15.6)55.5 (15.6)57.6 (14.9)< 0.001
Physically inactive166 (7)173 (9)267 (12)384 (19)< 0.001
Tobacco consumption     
 Never smoked656 (29)543 (27)538 (24)450 (22)< 0.001
 Current smoker of >25 g/day134 (6)146 (7)173 (8)192 (10)< 0.001
Alcohol consumption     
 No daily consumption434 (19)394 (20)423 (19)524 (26)<0.001
 >2 drinks per day506 (22)472 (23)492 (22)422 (20.9)0.306
Mean body mass index (SD)25.6 (4.0)25.6 (4.3)25.4 (4.2)25.8 (4.9)0.038
Living alone742 (33)685 (34)807 (36)869 (43)< 0.001
School education <8 yrs726 (32)617 (31)674 (30)804 (40)< 0.001
Low household income362 (16)343 (17)414 (19)543 (27)< 0.001

The prevalence of high exhaustion scores was higher among women than men: 28% of the women but only 18% of the men were included in the highest quartile (data not shown) (cutoff points calculated on the whole sample). This distribution was also reflected in the difference in the scores for women (mean, 8.2; standard deviation [SD], 8.3) and for men (mean, 6.0; SD, 7.4; t value, 12.8; P < 0.001).

The mean length of follow-up was 8.6 years. During follow-up, cancer was diagnosed in 976 persons. The majority of the cancers were related to smoking or hormones (Table 2).

Table 2. Cancer Cases among 8527 Subjects in the Third Survey of the Copenhagen City Heart Study (1991–2002) (n = 8527)
CancersVital exhaustion sum score
1st quartile score 0–1 n = 2275 n (%)2nd quartile score 2–4 n = 2021 n (%)3rd quartile score 5–11 n = 2215 n (%)4th quartile score 12–34 n = 2016 n (%)n
  • a

    Cancers of the buccal cavity (C140–148), esophagus (C150), pancreas (C157), larynx (C161), lung (C162), kidney (C180), and urinary bladder (C181).

  • b

    Cancers of the tongue (C141), mouth (C143–144), pharynx (145–148), esophagus (C150), liver (C155), and larynx (C161).

  • c

    Cancers of the liver (C155), cerrvix (C171), non-Hodgkin lymphoma (C200, C202), and leukemia (C204).

  • d

    Cancers of the breast (C170), uterus (C172), ovary (C175), and prostate (C177).

Cancers at all sites297 (13)229 (11)253 (11)197 (10)976
Smoking-related cancersa104 (5)86 (4)88 (4)57 (3)335
Alcohol-related cancersb17 (1)13 (1)14 (1)12 (1)56
Virus and immune-related cancersc29 (1)15 (1)16 (1)14 (1}74
Hormone-related cancerd73 (3)62 (3)77 (4)66 (3)278

In the regression analyses, after adjustment for all confounding variables, there was no significant association between the vital exhaustion score and the risk for cancer at any site, for alcohol-related cancers, for hormone-related cancers, or for virus or immune-related cancers (Table 3). Nevertheless, the most exhausted persons had a significantly decreased risk for developing smoking-related cancers.

Table 3. Cancer Risk by Vital Exhaustion Score among 8527 Subjects in the Third Survey of the Copenhagen City Heart Study (1991–2002)
Exhaustion scoreCases/nAdjustment
NoneBehavioral factorsaSocioeconomic factorsbFullc
Hazard ratio95% CIHazard radio95% CIHazard ratio95% CIHazard ratio95% CI
  • 95%; CI: 95%; confidence interval.

  • a

    Physical activity during leisure time, tobacco consumption, duration of tobacco consumption, alcohol consumption, and body mass index.

  • b

    Years of school education, household income and cohabitation.

  • c

    Behavioral and socioeconomic factors combined.

  • d

    Cancers of the buccal cavity (C140–148), esophagus (C150), pancreas (C157), larynx (C161), lung (C162), kidney C180), and urinary bladder (C181).

  • e

    Cancers of the tongue (C141), mouth (C143–144), pharynx (C145–148), esophagus (C150), liver (C155), and larynx (C161).

  • f

    Cancers of the liver (C155), cervix (C171), non-Hodgkin lymphoma (C200, C202), and leukemia (C204).

  • g

    Cancers of the breast (C170), uterus (C172), ovary (C175), and prostate (C177).

All cancer sites        
 0–1 (Quartile 1)297/22751Reference1Reference1Reference1Reference
 2–4 (Quartile 2)229/20210.960.80–1.140.920.78–1.100.950.80–1.130.920.77–1.09
 5–11 (Quartile 3)253/22151.060.90––––1.19
 12–34 (Quartile 4)197/20160.890.74–1.070.810.67–0.980.870.72–1.040.800.66–0.96
Smoking-related cancersd         
 0–1 (Quartile 1)104/22751Reference1Reference1Reference1Reference
 2–4 (Quartile 2)98/20211.080.81–1.441.000.75–1.341.060.80–1.420.980.74–1.31
 5–11 (Quartile 3)76/22151.160.87–1.541.030.77–1.371.100.83–1.470.980.73–1.30
 12–34 (Quartile 4)57/20160.860.62–1.190.690.50–0.960.780.56–1.080.640.46–0.90
Alcohol-related cancerse         
 0–1 (Quartile 1)17/22751Reference1Reference1Reference1Reference
 2–4 (Quartile 2)13/20211.030.50–2.120.890.43–1.841.000.49–2,070.870.42–1.80
 5–11 (Quartile 3)14/22151.180.58–2.401.030.50––2.280.980.48–2.00
 12–34 (Quartile 4)12/20161.220.58–2.570.990.46––2,240.870.40–1.87
Virus and immune-related cancersf         
 0–1 (Quartile 1)29/22751Reference1Reference1Reference1Reference
 2–4 (Quartile 2)19/20210.610.33–1.130.600.32–1.110.610.32–1.130.590.32–1.11
 5–11 (Quartile 3)12/22150.620.34–1.160.590.32–1.090.620.34–1.150.580.31–1.09
 12–34 (Quartile 4)14/20160.590.31–1.130.520.27–1.000.580.30–1.110.510.26–0.99
Hormone-related cancersg         
 0–1 (Quartile 1)73/22751Reference1Reference1Reference1Reference
 2–4 (Quartile 2)69/20211.000.71–1.401.000.71–1.401.000.71–1.400.990.70–1.39
 5–11 (Quartile 3)70/22151.200.87–1.651.200.87–1.661.190.86–1.641.190.86–1.65
 12–34 (Quartile 4)66/20161.040.74–1.451.040.74–1.471.050.75–1.471.050.75–1.49

To eliminate the possibility that high vital exhaustion scores resulted from early symptoms of an undiagnosed cancer disease, all analyses were repeated after exclusion of the first year of follow-up, but this did not change the results (data not shown).

The comparison of the overall cancer risk of participants in the third survey of the Copenhagen City Heart Study, after exclusion only of those with a diagnosis of cancer before the date of entry, and that of the population of Copenhagen showed that long-term participants (second and third surveys, n = 7270; mean age, 64 years) had a significantly decreased risk (SIR, 0.57; 95% CI, 0.54–0.60). The cancer risk of newly recruited participants (only the third survey, n = 2865; mean age, 44 years) was also significantly reduced, but to a lesser extent (SIR, 0.77; 95% CI, 0.65–0.90).

A comparison of the baseline characteristics of long-term participants and the newly recruited subsample revealed minor differences in the confounding variables, but these did not provide an explanation for the results (data not shown). The hazard ratios for overall cancer risk were similar for the most exhausted quartiles among the long-term participants and the newly recruited subsample (data not shown).


To our knowledge, the current study presents the first prospective data evaluating whether a state of depressive affect and fatigue as measured with the vital exhaustion questionnaire influences cancer risk. Our analyses were based on a large, well defined cohort with almost complete follow-up, and the methodologically strong prospective design ensures that the data on exposure were collected independently of the outcome. All the analyses were conducted applying a univariate and a multivariate model, adjusted for a number of life style factors known to be associated with cancer risk.

We found a significantly higher prevalence of disadvantageous life style factors, such as high tobacco consumption and low physical activity, among the subjects with the highest vital exhaustion scores at baseline. This result corresponds to those of previous studies that showed an association between an unhealthy life style and depression19–21 and supports the assumption of an increased cancer risk for vitally exhausted subjects.

Our results do not, however, reveal a positive association between risk for cancers at all sites and vital exhaustion in the univariate or multivariate analyses. Furthermore, the results also do not show a clear pattern for cancer sites grouped etiologically and are contradictive to the research hypothesis. Although the persons with the highest exhaustion scores had normal risks for developing hormone-related and alcohol-related cancers, we unexpectedly found a decreased risk for all cancer sites as well as for virus and immune system-related cancers in this group. Both findings were, however, of borderline statistical significance. The study also showed a significantly decreased risk for developing smoking-related cancers among persons with the highest exhaustion scores. This result contradicts those of a previous a study by our group, which showed an association between depression and cancer risk only for tobacco-related cancers.12 Nevertheless, the findings of the current study correspond to those reported in recent reviews on psychosocial factors and cancer incidence, which concluded that there is no clear evidence for an association between depression and cancer risk.29, 30

Based on the result that both univariate and multivariate analyses lead to similar findings and generate decreased risk estimations, we deduce that there is neither a direct positive influence of vital exhaustion on cancer risk via an immune mechanism nor an indirect association promoted by unhealthy life style factors.

Although the vital exhaustion questionnaire was not constructed to measure depression, a number of items are similar to those in common depression scales: feeling dejected, feeling hopeless, difficulty in concentrating, listlessness, feel like crying. Although several symptoms of clinical depression are not covered by the vital exhaustion questionnaire, a factor analysis of the questionnaire still resulted in a three-factor solution including one factor labeled depressive affect,31 indicating an overlap between the vital exhaustion construct and depression. Furthermore, a recent analysis of the conceptual overlap of the vital exhaustion questionnaire and depression questionnaires found high correlations between the two kinds of instruments.32 The psychological state measured with the vital exhaustion questionnaire can therefore be considered an indicator of minor depressive feelings, making it an appropriate measure of the question addressed in the current study.

In a recent study on vital exhaustion, ischemic heart disease, and all-cause mortality carried out with the same cohort as used in the current study, elevated exhaustion scores were associated with a significantly increased risk for death from all causes.18 Thus, even if vital exhaustion is not associated with an increased risk for cancer, it is associated with other disadvantageous health outcomes, which may be promoted by the life style of vitally exhausted subjects. In addition, the finding of an association between vital exhaustion and all-cause mortality may partly explain the calculated lower cancer risk in the most exhausted subjects of the study sample because some of the exhausted subjects may have died of other causes before developing cancer.

Potential selection bias in the establishment of the cohort and the constitution of the study sample might limit interpretation of the results. The response rate (i.e., the number who completed the questionnaire and underwent a physical examination) in the first survey of the Copenhagen City Heart Study was 72%, and only 61% of the invited persons participated in the third survey. As the cohort was established mainly in 1976–1978 and follow-up measurements were made in 1981–1983 and 1991–1994, some selection bias was to be expected in the third period, when vital exhaustion scores were evaluated. The situation in which only relatively healthy subjects are likely to remain in a cohort in a study with repeated measurements and long follow-up, the healthy responder effect is a well known form of selection bias in epidemiologic studies.33 It can be assumed that persons with health problems or an unhealthy life style are less likely to participate in a study that includes a physical examination and it can also be assumed that persons with health problems that are not related to the heart tend not to participate in a study explicitly addressed to heart-related issues. The assumption that a healthy responder effect was active in our study is supported by the finding of a decreased cancer risk in the study sample compared with the population of the City of Copenhagen. Furthermore, this assumption is also supported by the finding of a previous study, which confirmed that the Copenhagen City Heart Study cohort has a lower risk of death from all causes than the population of the City of Copenhagen.34

We found a significantly decreased cancer risk for both long-term participants of the Copenhagen City Heart Study and the newly recruited subsample, with a smaller decrease for the newly recruited persons. This comparatively low cancer risk can be interpreted as an indicator of selection bias with regard to cancer-related factors. Furthermore, most of the study sample had joined the cohort long before vital exhaustion was assessed in the third survey, and the mean age of the long-term participants, 64 years, is well within the age range in which cancer becomes more likely. Although 976 cases of cancer occurred in the study sample during the follow-up, 589 persons had to be excluded because a cancer had been diagnosed before their date of entry. If vital exhaustion is a promoting factor in persons prone to cancer, the issue would be addressed more efficiently in a younger sample.

With regard to misclassification of exposure, the vital exhaustion questionnaire was designed to measure specific symptoms closely related to heart disease. The above-mentioned study on vital exhaustion and ischemic heart disease confirmed the appropriateness of the measure in this regard and showed a significantly increased risk for ischemic heart disease in the most exhausted subjects.18 Previous prospective studies on vital exhaustion and heart diseases showed that acute vital exhaustion is likely to be a short-term risk indicator for myocardial infarct,35 which suggests that the vital exhaustion questionnaire measures a current mental state the impact of which decreases over time. Nevertheless, exclusion of the first year of follow-up did not change the results of our study. We conclude that the psychological condition measured by the vital exhaustion questionnaire is not positively related to cancer risk in either the short or the long run.

If the vital exhaustion questionnaire does not measure a permanent trait but rather a current psychological condition, which might change frequently, it is likely that some persons were wrongly classified as exhausted or not exhausted because only a single measurement of vital exhaustion was made at baseline. In view of the long span over which cancer develops, it would be difficult to obtain predictive power for the risk of developing cancer later in life from a single baseline measurement of a presumably unstable mental state. The use of single measurements for predicting cancer occurrence years later is a crucial methodologic criticism of incidence studies on psychological factors and cancer risk,30 and this also applies to our study design. Repeated measurements of vital exhaustion might distinguish a subgroup of subjects who felt exhausted and depressed for longer periods, but this could not be addressed with the design used in the current study.

Misclassification of cancer cases in the current study is unlikely, as the 10-digit personal identification number assigned to all Danish residents by the Civil Registration System permits accurate linkage between registries. The outcomes in our study were classified by linking the identification numbers of study participants to the Danish Cancer Registry, a nationwide, population-based register of all cancer cases in Denmark since 1943. Comprehensive evaluation has shown that the Danish Cancer Registry is 95–99% complete and valid.36, 37


The results of the current study show that a state of high vital exhaustion is associated with an unhealthy life style. Nevertheless, vital exhaustion itself is not associated with an increased incidence of cancer. The results of this large, prospective, population-based study, therefore, do not support the hypothesis that subclinical depressive feelings, as measured by the vital exhaustion questionnaire, increase the risk for developing cancer.