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Psychosomatics 50:59-68, January-February 2009
doi: 10.1176/appi.psy.50.1.59
© 2009 Academy of Psychosomatic Medicine
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Alexithymia and Health-Related Quality of Life in a General Population

Aino K. Mattila, M.D., Samuli I. Saarni, M.D., M.Soc.Sc., Jouko K. Salminen, M.D., Ph.D., Heini Huhtala, M.Sc., Harri Sintonen, Ph.D., and Matti Joukamaa, M.D., Ph.D.

Received January 29, 2007; revised May 16, 2007; accepted May 18, 2007. From the Tampere School of Public Health, University of Tampere, Tampere, Finland; the Dept. of Psychiatry, Tampere University Hospital, Tampere, Finland; the National Public Health Institute, Dept. of Mental Health and Alcohol Research, Helsinki, Finland; the National Public Health Institute, Dept. of Health and Functional Capacity, Laboratory for Population Research, Turku, Finland; and the Dept. of Public Health, University of Helsinki, Helsinki, Finland. Send correspondence and reprint requests to Aino K. Mattila, M.D., Tampere School of Public Health, FIN-33014, University of Tampere, Tampere, Finland. e-mail: aino.mattila{at}uta.fi
© 2009 The Academy of Psychosomatic Medicine


  ABSTRACT

 
TOP
 ABSTRACT
INTRODUCTION
 METHOD
 RESULTS
 DISCUSSION
 REFERENCES
 
BACKGROUND: Alexithymia is thought to reflect a deficit in the cognitive processing of emotion, and, therefore, it may predispose individuals to both psychological and somatic symptoms. OBJECTIVE: The authors investigated the relationship between alexithymia and health-related quality of life (HRQoL) in a nationally representative population sample of 5,418 subjects, age 30 to 97 years. METHOD: Alexithymia was measured with the 20-item Toronto Alexithymia Scale (TAS–20) and HRQoL measured with the 15D, a generic HRQoL measure. RESULTS: Alexithymia was significantly associated with lower HRQoL independently of other variables. The TAS–20 subfactor Difficulties Identifying Feelings was the strongest common denominator between alexithymia and HRQoL. CONCLUSION: Alexithymia may be a predisposing factor to poorer HRQoL.


  INTRODUCTION

 
TOP
 ABSTRACT
 INTRODUCTION
METHOD
 RESULTS
 DISCUSSION
 REFERENCES
 
Alexithymia is a personality construct characterized by difficulties in experiencing and verbalizing emotions, impoverishment of fantasy, and poor capacity for symbolic thought.1–3 It is thought to reflect a deficit in the cognitive processing of emotion, and alexithymic individuals are thought to lack mental representation of emotions.4–6 These deficiencies are believed to cause an inability to regulate emotions and affects and therefore to predispose alexithymic individuals to both psychological and somatic symptoms.

Alexithymic individuals may misinterpret the somatic sensations associated with emotional arousal as symptoms of disease;7 in other words, they may have a tendency to somatize. The association between alexithymia, somatization, and somatoform disorders has been corroborated by several studies, even though there has been some inconsistency in the findings, possibly because of the differing methods used in different studies.7,8 Alexithymia may be associated with somatization by way of misinterpreting the somatic sensations associated with emotional arousal as symptoms of disease;3,7,8 it has also been conjectured that the failure to experience complex emotional states is associated with exaggerated or dysregulated autonomic activation.7 On the other hand, alexithymia has also been associated with several medical conditions, such as inflammatory bowel disease,9 essential hypertension,10 migraine,11 and diabetes mellitus.12 Moreover, alexithymia has been found to be an independent risk factor for death in middle-aged men.13

The prevalence of alexithymia in working-age populations is 9%–17% for men and 5%–10% for women.14–17 The prevalence figures of alexithymia in older age-groups are notably higher; over 20%, or even over 30% in the oldest populations.17–19 Besides older age, alexithymia is also associated with male sex, lower socioeconomic status, fewer years of education, single marital status, and poorer perceived health.14–17,20

Alexithymia has been shown to be associated with various mental disorders, including depression.15 According to some earlier studies, it is more prevalent among depressed persons, and alexithymia scores decrease as depression is alleviated. Therefore, it has been claimed that alexithymia may be a state-dependent phenomenon.21–23 On the other hand, several studies have yielded evidence on both the absolute and the relative stability of alexithymia, in accordance with the original theoretical definition that alexithymia is a personality trait.3,9,24–28 Moreover, alexithymia is normally-distributed in the general population in both sexes.14 It is, however, reasonable to take depression into consideration in studies on alexithymia.

Health is an essential component of quality of life.29 A growing trend is to measure the outcomes of healthcare multidimensionally, including the subjective experience of the patient. Health economists require generic (non–disease-specific) single-dimensional utility measures to compare the costs and benefits of treating different diseases. The health-related quality of life (HRQoL) measurement aims to meet these demands.

Alexithymia has been associated with a lower overall quality of life (QOL) in the general population,15,30 in patients with coronary heart disease,31,32 patients with brain injury,33 and in outpatients with depression.34 A negative association between alexithymia and HRQoL has been found in unselected medically ill patients35 and in patients with inflammatory bowel disease,36 breast cancer,37 and with end-stage renal disease.38,39 In contrast to these, absence of alexithymia has been found to predict poorer postoperative QOL in ulcerative colitis patients.40 It is, however, somewhat difficult to compare the results of these studies, because alexithymia and HRQoL were assessed with a variety of measures. Moreover, all of the studies measuring HRQoL were conducted with relatively small (N=46–105) clinical samples.

As far as we know, only one meeting abstract has been published dealing with the associations between alexithymia and HRQoL in a general population.41 In a population sample of 1,285 subjects age 18–64 years, alexithymia, measured with the 20-item Toronto Alexithymia Scale (TAS–20), was significantly associated with poorer HRQoL, as measured with the RAND–36.41 Alexithymic individuals had lower levels of physical functioning, more role limitations due to physical health, more limitations due to emotional problems, less energy, poorer emotional well-being, poorer social functioning, more pain, and poorer general health than the nonalexithymic persons. However, confounding factors were not controlled for in this study.

We studied the associations between alexithymia, as measured with the TAS–20, and HRQoL, measured with a generic HRQoL measure, the 15D, in a nationally representative sample of 5,418 individuals in the age-range of 30–97 years. In the present study, we controlled for sociodemographic variables, depression, functional capacity, and physician-verified somatic diagnoses. We hypothesized that alexithymia was negatively associated with HRQoL independently of these confounders.


  METHOD

 
TOP
 ABSTRACT
 INTRODUCTION
 METHOD
RESULTS
 DISCUSSION
 REFERENCES
 
Study Design and Sample
Our study is a part of The Health 2000 Study. The gathering of data took place in Finland in 2000–2001.42 It was designed according to the concept of a two-stage stratified cluster sampling and comprised adults age 30 years and over. The minimum age limit was set at 30 years because the prevalence of somatic diseases is low in younger age-groups. The study design and base results have been described in detail elsewhere42,43 and are available at www.ktl.fi/health2000.

The sample was drawn from all the five Finnish university hospital districts, each containing approximately 1 million inhabitants. All together, 80 health-center districts, 16 from each university hospital region, were selected by systematic sampling to participate in the study, thus forming 80 clusters. From each area, a random sample of subjects was drawn from the national population register, with double-sampling of people over 80 years of age.

The nationally representative sample comprised 8,028 persons. Of these, 6,770 participated in a health examination after an interview. The interview was used to gather basic background and sociodemographic information, as well as information on health-related factors. After the health examination, the participants were given a questionnaire including the TAS–20 and the 15D. Those 5,418 subjects (67.5% of the sample) who had received the questionnaires in their native language and who returned the TAS–20 completed and the 15D acceptably filled-in were included in our substudy.

Measures
Alexithymia was assessed with the Finnish or Swedish (the two official languages of Finland) version of the TAS–20, depending on the native language of the subjects. Among the different methods for measuring alexithymia, the TAS–20 is the most widely used and presumably the most carefully validated. Its internal consistency, test–retest reliability, as well as convergent, discriminant, and concurrent validity have been demonstrated to be good.44–48 The psychometric properties of both the Finnish version49 and the Swedish version50 of the TAS–20 have proven to be satisfactory. The total score of the TAS–20 ranges between 20 and 100 points. According to the recommendation by the developers of the scale, the cut-point for alexithymia was also used: subjects scoring ≥61 were defined as alexithymic.51 Also, the TAS–20 consists of three subscales, which reflect the three main facets of the alexithymia construct: subscale DIF assesses difficulties in identifying feelings (7 items; score range: 7–35), subscale DDF concerns difficulties in describing feelings (5 items; score range: 5–25), and subscale EOT reflects concrete, externally-oriented thinking or a preoccupation with the details of external events (8 items; score range: 8–40). In the present study, the Cronbach {alpha} coefficient was 0.85 for the TAS–20, 0.86 for the DIF, 0.72 for the DDF, and 0.67 for the EOT.

HRQoL was measured with the 15D, available at www.15d-instrument.net. This includes 15 dimensions: mobility, vision, hearing, breathing, sleeping, eating, speech, elimination, usual activities, mental functioning, discomfort and symptoms, depression, distress, vitality, and sexual activity.52–54 Each dimension has five grades of severity. In calculating the 15D health utility index (15D score), valuations elicited from the Finnish population using the multi-attribute utility method were used.53 The 15D scores range from 1 (no problems on any dimension) to 0 (being absolutely nonfunctional). According to the scale’s developer, a change of ≥0.02–0.03 points in the health utility index or 15D score is considered clinically noteworthy.54 The 15D compares favorably with similar instruments in most important properties.52–56 Subjects with ≥12 completed 15D dimensions were included, and missing values were predicted with linear-regression analysis, using the other 15D dimensions, along with age and sex, as independent variables, as recommended by the developer of the measure.52 The number of participants with one to three missing values was 293 (5.4% of the sample).

Sociodemographic Variables
Sociodemographic variables and sex were independent variables. Age was categorized into a six-class variable: 30–39, 40–49, 50–59, 60–69, 70–79, and ≥80 years. Marital status was divided into four categories: single, married/cohabiting, divorced/separated, and widowed. A three-class variable describing the level of education was combined from two variables containing information on basic education and vocational education. No vocational training beyond a vocational course or on-the-job training, with no matriculation examination, was classified as basic education. Completion of vocational school, as well as passing the matriculation examination but having no vocational training beyond a vocational course or on-the-job training, was defined as secondary education, regardless of basic education. Higher education comprised degrees from higher vocational institutions, polytechnics, and universities. The financial situation of the subjects was assessed by asking about the monthly income of the households in which they lived. The variable was divided into three categories: ≤10,000 FIM (Finnish markka), 10,001–20,000 FIM, and >20,000 FIM (≤1,680.7 euros, 1,680.8–3,361.3 euros, and >3,361.3 euros, respectively).

Depression, Somatic Diagnoses, and Functional Capacity
The comprehensive health examination included an assessment of 12-month prevalence of major depressive disorder or dysthymia,43 measured with the Munich (Germany), version of the Composite International Diagnostic Interview (M–CIDI)57 with DSM–IV58 criteria. The diagnoses were combined, thus yielding a dichotomized variable for depression: No Depression and Depression (dysthymia and/or major depression).

Somatic diagnoses were given by physicians (a total of 10 of these) after physical examinations that included a standard clinical examination, measurements of height and weight, a 12-lead resting ECG, blood pressure measurements, spirometry, bioimpedance and heel-bone density measurements; oral examination by a dentist; a variety of examinations of functional capacity (vision, hearing, reaction time, word memory, verbal fluency, hand grip-strength, balance); and tests related to joint functioning and joint movements.

The diagnoses were classified according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD–10).59 The reliability of the somatic diagnoses was rated as "possible" or "certain" by the examining physicians. Only those diagnoses defined as "certain" were included in our analyses. A three-class variable, "ICD–10 somatic diagnoses," was formed, as follows: No somatic diagnoses; 1 somatic diagnosis; and ≥2 somatic diagnoses.

In order to control for the severity of the diseases, the examining physicians also assessed the health-related functional capacity of the participants with a four-class variable, as follows: unimpaired, slightly impaired, considerably impaired, and almost totally/totally impaired functional capacity. This variable was reduced to a variable with three categories by combining the last two classes to a single category "severely impaired functional capacity."

Statistical Analyses
The means of the TAS–20 total scores, the three TAS subscale scores, and the 15D scores were calculated by performing adjusted Wald tests for equality between the comparison groups, for sex, age, marital status, education, income, ICD–10 diagnoses, functional capacity, M–CIDI depression, and 15D for the dichotomized TAS–20. The data were weighted, to take into account the sampling design.

A significance level of <0.05 was used in these analyses. The distribution of the 15D scores was skewed and demonstrated a ceiling effect at full health, ruling out the standard linear-regression methods. When the normality assumptions are violated, quantile-regression methods (e.g., Censored Least Absolute Deviations (CLAD) regression) are a robust alternative.60,61 Quantile-regression methods are based on minimizing least absolute deviations, whereas standard regression models are based on minimizing least squares.60,62 In practice, the non-normality of the 15D has been shown to be statistically nonsignificant, with CLAD results very close to those results obtained with traditional Tobit regression.61

We conducted three CLAD analyses with the 15D score as a dependent variable. In the first analysis, the TAS–20 total score; in the second analysis, the DIF, DDF, and EOT scores; and in the third analysis, dichotomized alexithymia were the alexithymia variables. All the analyses included sex, age, marital status, education, income, M–CIDI depression, the three-class variable for ICD–10 somatic diagnoses, and the three-class variable for functional capacity as confounders. The resulting coefficients are interpreted as estimates of the change in median 15D score associated with change in the independent variables. The confidence levels were set at 99% in these analyses. CLAD analyses accounted for the sampling design by using weights and a two-stage bootstrapping, in which the sampling design was accounted for by sampling the primary sampling units in the first stage and individuals in the second stage. Computations were carried out by use of the Stata Statistical Package, Version 9.1.63


  RESULTS

 
TOP
 ABSTRACT
 INTRODUCTION
 METHOD
 RESULTS
DISCUSSION
 REFERENCES
 
The means of the TAS–20, DIF, DDF, EOT, and 15D scores in different groups are shown in Table 1. All the alexithymia variables and the 15D scores differed significantly (p<0.001) among comparison groups except the DIF score between men and women.


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TABLE 1. Characteristics of the Participants and Scores of TAS–20, DIF, DDF, EOT, and 15D in Different Groups (means and 95% confidence intervals [CI]; adjusted Wald test for equalitya)



Alexithymia and the 15D were strongly associated. The results of the CLAD analyses are shown in Table 2. The TAS–20 and DIF scores, as well as the dichotomized TAS–20 were negatively associated with the 15D, whereas the DDF and EOT scores were not. M–CIDI Depression, two or more ICD-10 diagnoses, impaired functional capacity, advanced age, and lower income level were negatively associated with the 15D in all analyses. Male sex was positively associated with the 15D in the analysis with the TAS–20 score. Marital status and education were not significant in any of the models.


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TABLE 2. CLAD Analyses With the 15D Score as Dependent Variable (regression coefficient: β; 99% confidence interval [CI])




  DISCUSSION

 
TOP
 ABSTRACT
 INTRODUCTION
 METHOD
 RESULTS
 DISCUSSION
REFERENCES
 
The main finding of our study was the association between alexithymia and lower health-related quality of life (HRQoL), even when controlling for depression, somatic diagnoses, functional capacity, and sociodemographic variables.

Of the TAS–20 subscales, DIF (difficulties in identifying feelings) was significantly associated with HRQoL, whereas DDF (difficulties in describing feelings) and EOT (externally-oriented thinking) were not. Given that a 0.02–0.03 point change in the 15D score is considered clinically noteworthy,54 the results of the regression analyses (Table 2) can be interpreted to mean that every 10-point increase in the significant alexithymia variables represents a clinically noteworthy decrease in the 15D index (0.02 for the TAS–20 and 0.06 for DIF). Belonging to the alexithymic group, as assessed by the dichotomized TAS–20, is reflected as a 0.06-point difference in the 15D score. A decrease of 0.06 points on the 15D score is very substantial, as indicated by the fact that two or more physician-verified ICD–10 diagnoses, slightly impaired functional capacity, or age between 70 and 79 years were associated with smaller decreases of HRQoL in the analysis with the dichotomized TAS–20.

The 15D has three items primarily concerning mental well-being (mental functioning, depression, and distress). Therefore, it was to be expected that psychiatric disorders—here, dysthymia and/or major depression—were reflected in the results. Moreover, it has been shown in earlier studies that negative affectivity64 and depression65,66 are associated with poorer HRQoL.

As a measure of HRQoL, the 15D assesses a variety of dimensions that are predominantly physical in nature (mobility, vision, hearing, breathing, eating, speech, elimination). A few dimensions can be seen as belonging to both physical and mental domains or social domain (usual activities, discomfort and symptoms, vitality, sexual activity, and sleeping). Alexithymia has been associated with somatization,7,67 somatoform disorders,7,8 and with poorer perceived health.17,18 The concept of alexithymia encompasses the idea that alexithymic individuals may misinterpret the somatic sensations associated with emotional arousal as symptoms of somatic disease.7 It has also been claimed that alexithymia may affect illness-behavior through cognitive and social mechanisms and so contribute to somatic symptoms.68 Thus, it is conceivable that alexithymic individuals’ subjective conceptions of their overall health and different aspects of it are reflected on the HRQoL measures independently of objectively diagnosed ailments.

The negative association between alexithymia and HRQoL seems to be driven primarily by the DIF subfactor. In a few earlier studies, the DIF factor has been associated with somatization7,67 and somatoform disorders.7,69 It has also been associated with increased healthcare utilization.70 It seems that individuals with difficulties in identifying feelings are prone to misinterpreting their somatic sensations. They also rate their health poorer than those without this characteristic. Our results suggest that alexithymic individuals with difficulties in identifying their feelings are at risk for reporting poorer HRQoL.

Because of the cross-sectional design of our study, we cannot draw any affirmative conclusions as to whether alexithymia predisposes to poorer HRQoL or whether poor HRQoL predisposes to alexithymia. However, if alexithymia is considered to be a relatively stable personality trait, one could assume that it is a risk factor for poorer HRQoL.

Naturally, we cannot rule out the possibility that alexithymia is a secondary phenomenon, a defensive state reaction, resulting from prolonged mental stress and suffering caused by poorer health. This hypothesis is supported by some earlier studies.35 There is also a third conceivable explanation: the association of alexithymia with some somatic diseases is reflected in poorer HRQoL. Prospective studies controlling for mental disorders and somatic diagnoses are needed in order to establish the causative pathways.

According to earlier studies, alexithymia is associated with poorer HRQoL in various medical conditions.35–39 Our findings concerning the general population are consistent with the findings by Salminen et al.41 The association of alexithymia with health is not only an issue of subjective suffering but may also contribute to health outcomes. There is evidence that alexithymic individuals, because of maladaptive coping strategies, may be prone to engage in unhealthy behavior, such as binge-eating or alcohol abuse.71 On the other hand, alexithymia has been found to be associated with increased risk of death, independently of other well-known risk-factors.13

It has also been shown that alexithymia may have a negative impact on the doctor–patient relationship by evoking negative reactions in caregivers.72 This, combined with reporting poorer HRQoL than other patients with otherwise similar health-problems, may have a deleterious effect on the patients’ status in healthcare. So far, alexithymic characteristics have been considered to be difficult to modify.2 Beresnevaite73 has, however, reported promising results with coronary heart disease patients: group psychotherapy was better at decreasing alexithymia than was simple patient education.

Our study is based on a large, representative population survey. Contrary to most surveys, ours used a burdensome physical examination and a structured mental health interview to verify diagnoses. Given this, our response rate can be considered high. However, as in all surveys, those most ill were the most likely to drop out. We used advanced statistical modeling, survey-adjusted CLAD regression, to estimate the association between alexithymia and HRQoL. The CLAD procedure is generally less sensitive in finding statistically significant differences; that is, it produces wider confidence intervals than standard linear or Tobit regressions;61 this emphasizes the robustness of our findings.

We conducted our study with the TAS–20 as a measure of alexithymia. In recent years, there has been some criticism of the TAS–20. This has focused especially on the difficulties in replicating its factor structure and the associations of the TAS with negative affectivity.74,75 It has also been noted that there are differences between the TAS–20 subfactors: EOT having repeatedly been the most problematic of them.47 On the other hand, in our study, the Cronbach {alpha} for EOT, 0.67, was quite satisfactory as compared with several other studies.

Lane et al.4 questioned the ability of the TAS–20 to detect the most severe cases of alexithymia. Suslow et al.76 found that DDF seems to evaluate aspects of social shame, rather than difficulties in symbolizing one’s emotions. However, the TAS–20 is the most widely used measure of alexithymia and, so far, is the only alexithymia scale validated in Finnish. As for measuring HRQoL, it has been found that in affectively disturbed people, the scores may be influenced by affective bias, poor insight, and recent life events.77 These methodological limitations are to be kept in mind when assessing the results of our study.

The study used interviews, which may have had some effect on the self-reported data, because the interviews and health examinations preceded the completion of the self-report scales. We also created quite a crude variable for the ICD–10 somatic diagnoses. It encompassed a wide variety and combination of diagnoses that were obviously not comparable with each other in terms of severity and disease burden. To take into account this shortcoming, we also used physician-verified assessments of the functional capacity of the participants. We believe that, for the purposes of this study, these variables together enabled us to control for the health status of the subjects and thus increased the credibility of the results.

In conclusion, our results suggest that alexithymia is strongly associated with poorer HRQoL and that the TAS–20 subfactor DIF is the strongest common denominator between alexithymia and HRQoL. Alexithymia may have a direct impact on HRQoL, but it is also possible that alexithymia affects HRQoL measurement via a somatization mechanism. In either case, it seems that poorer HRQoL may sometimes be associated with difficulties in emotional processing, not only with health problems and circumstantial factors. Because alexithymia is normally distributed in the general population,14 at least some alexithymic features are quite common. Therefore, we deem it important to take alexithymia into consideration when assessing the HRQoL of various population groups, especially elderly persons, because the prevalence of alexithymia is quite high in the oldest populations. Even though alexithymia as a personality construct may be relatively unamenable to change, people with strong alexithymic features may benefit from caregivers’ understanding of the special difficulties they have in dealing with their health problems.


  REFERENCES

 
TOP
 ABSTRACT
 INTRODUCTION
 METHOD
 RESULTS
 DISCUSSION
 REFERENCES
 

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