Background
According to the Merriam-Webster Dictionary, depression is a state of feeling sad, and fatigue is a state of weariness or exhaustion [
1]. Both states are described both as symptoms and as clinical syndromes. Conceptually, the two states overlap partly because fatigue is a symptom of the depressive syndrome, and their interrelationship is, therefore, of considerable clinical relevance, but rarely investigated. Major depressive episode (MDE) in the DSM-5 [
2] and Depressive episodes (F32) in the ICD-10 [
3] are defined as mental disorders, and both have fatigue or loss of energy as diagnostic criterion [
2] or a clinical guideline item [
3], respectively. Fatigue is a complex and unspecific symptom observed in several somatic diseases and mental disorders. Fatigue is a central symptom of both MDE and Depressive episodes (as well as) and of ICD-10 F48.0 Neurasthenia (not included in the DSM-5), as well of unclassified syndromes such as myalgic encephalopathy (ME) and chronic fatigue syndrome (CFS) [
4].
Depressive and fatigue syndromes are common, and of major clinical interest in both primary care and hospital settings. Assessment of these syndromes is primarily based upon patients’ reports, and several patient-reported outcome measures (PROMs) have been developed. To separate the two syndromes is also of considerable clinical interest since depression is quite amenable to treatment [
5] and carries an increased risk of suicide that is not found for the fatigue syndrome, which is less amenable to treatment [
6].
A Norwegian population-based study found a point prevalence of 11.4% for fatigue lasting for six months or more defined as chronic fatigue, based on self-report with the Fatigue Questionnaire [
7]. Based on a structured interview, the population-based 12-month prevalence of DSM-III-R MDE was 7.3% in the capital of Oslo [
8] and 3.7% in the rural Sogn and Fjordane county [
9]. To our knowledge, there are no Norwegian studies of the overlap between fatigue and depression. However, many studies have shown a high co-occurrence of fatigue and depression in the general population, and increased risk for fatigue in persons with depression and vice versa [
10,
11]. All these studies showed a higher prevalence in females compared to males.
Use of national population-based reference data for comparative purposes has become a widely used strategy for interpreting PROMs in diseased populations anchoring the results to such data. This provides the opportunity to assess the clinical significance of results adjusting for sex and age as well as other relevant characteristics.
The Wessely group in London developed the Fatigue Questionnaire (FQ), and the 11 fatigue items are shown in Table
1. The development was originally based upon a need for standardized assessment of fatigue as part of the CFS. The authors recognized a need for a standardized assessment of fatigue per se, so all items specific for the CFS were removed [
12]. The FQ has become widely used because of its coverage of the most relevant physical and mental fatigue symptoms and the instrument has demonstrated good psychometric properties. In Norway, the FQ has been commonly used in various disease groups since late 1990s. Population-based reference data from 1996 have been published [
7] and used for comparative purposes in several publications from various diseased samples [
13‐
15].
Table 1
The symptom items of the FQ and the PHQ-9 scales
1. Problems with tiredness | 1. Little interest or pleasure in doing things |
2. Needs more rest | 2. Feeling down, depressed, or hopeless |
3. Feels sleepy or drowsy | 3. Trouble falling or staying asleep |
4. Problems starting things | 4. Feeling tired or having little energy* |
5. Lacking energy | 5. Poor appetite or overeating |
6. Less strength in muscles | 6. Feeling bad about yourself |
7. Feels weak | 7. Trouble concentrating* |
8. Difficulty concentrating | 8. Changed psycho-motoric tempo |
9. Makes slips of tongue when speaking | 9. Better off dead or hurting oneself |
10. More difficult to find the correct word | |
11. Memory problems | |
The Spitzer group in New York developed the Patient Health Questionnaire-9 (PHQ-9) as part of their project of making diagnoses of mental disorders more feasible in primary care [
16,
17]. They gave the nine items under criterion A of the MDE criteria of the DSM-IV [
18] a self-rating format (Table
1). Originally developed for screening of depression in primary care, the PHQ-9 also has also become widely used in hospital settings. Several countries like Germany, Sweden, and South Korea have published reference data [
19‐
21]. The PHQ-9 has only recently been translated into Norwegian, and no Norwegian reference data have been published so far.
Both the FQ and the PHQ-9 were included in a recent representative Norwegian population survey collecting data on various PROMs [
22]. Data from this survey allowed us to: (1) Report 2015 reference data for the FQ and the PHQ-9 according to sex and age groups; (2) Compare the FQ reference scores from 2015 to those of 1996, and (3) Explore the relationship between the FQ and the PHQ-9 scores.
Discussion
Main findings
Males and females ≥ 60 years had significantly lower mean scores of mental and total fatigue in 2015 compared to 1996, and for the females that was the case also for physical fatigue. No other significant differences between age groups on FQ mean scores were observed over time. Concerning prevalence of CF, only females ≥ 60 years showed a reduction from 1996 to 2015. The increase in CF among females aged 18–29 we consider an artifact (see below). The same was relevant for the high PHQ-9 mean score and prevalence of MDE in that group. The prevalence rates of MDE based on PHQ-9 sum scores were higher than those based on the algorithm, but no significant differences were found between age groups in males, or between the age groups over 30 years in females. The shared variance between the FQ and the PHQ scales was 35%.
Representativity of the 2015 sample
The randomly drawn national 2015 sample was representative of the Norwegian population concerning age, sex and place of dwelling. However, the response rate was only 36%. The previous attrition analysis showed that significantly more women than men responded, and the participants were significantly older than the non-participants [
22]. About 21% of the population was between 18 and 29 years, but this age group only represented 5% of our sample. Hence, the number of participants in this age group was very low; only 36 males responding to the FQ and the PHQ-9, and 65 and 68 females, respectively. The significantly higher rates of males and females with CF in 2015 in this age group, indicate a bias towards more ill responders. Thus, we suggest that our FQ and PHQ-9 results for the 18–29 age group, should not be used as reference data.
In contrast, individuals aged 67 years or above were over-represented since they constituted 27% of the sample, while only representing 18% of the population. The high proportion of respondents over 70 years may reflect the increased life expectancy in Norway, and active and engaged persons constitute a larger proportion of this age group. Since fatigue and depression are characterized by lack of energy and initiative, which increases the risk of non-participation, our sample also carries a risk of under-reporting for this reason. We are not able to estimate of that factor on our findings.
Decline in response rate
The decline in response rate from 67% in 1996 to 36% in 2015 is in accordance with both national [
27] and international trends [
28] concerning mailed questionnaires. Several factors may be operating, but in general, the population has become more restrictive in sharing personal information. Another factor is that the general population nowadays is exposed to a higher rate of mailed and electronic questionnaires than previously, not only from the field of medicine.
In 2018, 96% of all Norwegian households with at least one person < 75 years had access to the Internet, and an alternative had been to make a digital rather than postal survey. However, that approach could trigger still more fear of spreading of sensitive information, and the response rate is not necessarily higher than in paper-based surveys [
29]. Web-based studies, therefore, do not solve the problem of sinking response rate to population-based health studies in Norway.
Findings of the PHQ-9
The first Norwegian reference data on the PHQ-9 showed lower mean PHQ-9 scores with increasing age for both sexes, and consistently higher mean scores in females for all age groups. The sex differences of the mean scores of the PHQ-9 were also observed in a German population based study [
30], but for both sexes, they observed an increase in mean PHQ-9 scores with age. The reason for the differences may be that their study had better representativity with 63% response rate.
In our study, closely the same pattern was observed for MDE defined by cut-off ≥ 10 with reduced prevalence with increasing age and female sex, but we did not find any other papers with such PHQ-9 population data.
MDE defined by the algorithm score showed lower prevalence rates than defined by cut-off score for all age groups and both sexes. The discrepancy of these prevalence rates of MDE presents a problem for the use of the PHQ-9 as a clinical screening instrument for depression. Especially since the discrepancy of prevalence rates between the dimensional and algorithmic definitions of MDE also was observed in studies from other countries [20213031] [
20,
21,
30,
31].
For PHQ-9 score ≥ 10 definitions of MDE, we observed no significant prevalence differences in males between our study and the others; while for females, our study had significantly higher prevalence than reported by Kocalevent et al. [
31]. Concerning total prevalence rates, our study found significantly higher rates than both Shin et al. [
21] and Kocalevent et al. [
31]. Based on the MDE algorithm, our prevalence rates did not differ significantly from the other studies concerning sex-based and total prevalence rates.
Fatigue changes over time
Several demographic and lifestyle-related changes have occurred in Norway during the last decades. Mean life expectancy has increased for both sexes to 81 years for males and 84 years for females in 2016. Self-reported health and activities of daily living have improved in persons above 70 years over the last two decades [
32]. Of today’s adult Norwegian population, 13% are daily smokers, obesity (BMI ≥ 30) 12, 32% consume alcohol once a week or more frequently, and 71% are physically active once a week or more [
33]. Fourteen per cent of the population are immigrants, making the Norwegian population more diverse than before. In addition, there are significant differences concerning socio-demographic variables in our 1996 and 2015 samples as shown in Table
2. In spite of these social changes and sample differences, the levels of physical, mental and total fatigue show only significant changes in the ≥ 60 year age group for both sexes. We consider the reduction of fatigue among elderly persons to be a consequence of their improved health status [
32].
The consistent increase in physical fatigue with age in males observed in 1996 [
7] was not observed in 2015. It is tempting to speculate that this finding could in part be explained by improved health in middle-aged men [
32].
Concerning the prevalence of CF, no significant changes were observed for males, but we observed a significant reduction among women ≥ 60 years, probably due to improved health in this group of women. The significant increase in the prevalence of CF among women aged 18–29 years, we consider due to sampling bias, and we remind about our concern to not use data from that age group as reference data for either sex.
The relationship between the FQ and the PHQ-9
As indicated in Table
1, three items concerning energy, tiredness, and concentration are common to both instruments. The correlation matrix between the FQ and the PHQ-9 (Table
6) mostly showed coefficients below 0.50, except for the PHQ-9 items #4 ‘Feeling tired or having little energy’ that had coefficients above 0.50 with four physical fatigue items (#1, 2, 3, and 5) related to tiredness, lack of energy, and need for rest. The 35% shared variance indicate that these PROMs could be used together, since 65% of their variance is separate.
Mechanisms of fatigue and depression
Our findings have confirmed the close relationship between fatigue and depression. Several explanations for this fact have been proposed. One of them is heredity, as documented in the study of a twin sample. Multivariate twin modeling estimated a common additive genetic component which explained 25%, and 20% of the variance in depression and fatigue, respectively. For depression, environmental factors explained 28% and for fatigue 54% of the variance [
34].
Another explanation concerns malfunctioning neural circuits and neurotransmitters [
10]. They build on the observation that treatment with antidepressants often is effective on the affective component of MDE, but less so on the lack of energy (fatigue) component. Therefore, antidepressants are considered to have different effects on the depression and fatigue neural circuits that may be due to different neurotransmitter profiles.
These and other potential explanations need further research.
Strength and limitations
We have produced Norwegian normative data for the FQ and the PHQ-9 scales. The FQ results show reduced fatigue in persons ≥ 60 years from 1996 to 2015 possibly reflecting improved general health in Norwegian during that period. The PHQ-9 data are new, but in line with the findings of other national samples [
20,
21,
30,
31].
Limitations are the response rate of 36% leading to low numbers of responders in the 18–29 years age group; thus, the FQ and PHQ-9 data reported by that age group should be considered critically.
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