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Intelligence is negatively associated with the number of functional somatic symptoms
  1. E M Kingma,
  2. L M Tak,
  3. M Huisman,
  4. J G M Rosmalen
  1. Interdisciplinary Center for Psychiatric Epidemiology, University Medical Center Groningen, University of Groningen, The Netherlands
  1. Correspondence to Dr J G M Rosmalen, Interdisciplinary Center for Psychiatric Epidemiology, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands; J.G.M.Rosmalen{at}med.umcg.nl

Abstract

Background: Functional somatic symptoms (FSS), that is, symptoms that cannot be conclusively explained by organic pathology, have a poorly understood aetiology. Intelligence was studied as a risk factor for FSS. It was hypothesised that intelligence is negatively associated with the number of FSS. To investigate the specific role of intelligence in FSS as opposed to medically explained symptoms (MES), the association of intelligence with FSS was compared with that of intelligence with MES. It was also hypothesised that lifestyle factors and socioeconomic factors mediate the relationship between intelligence and both FSS and MES, whereas psychological distress is especially important for FSS.

Methods: All analyses were performed in a longitudinal study with two measurement waves in a general population cohort of 947 participants (age 33–79 years, 47.9% male). The Generalized Aptitude-Test Battery was used to derive an index for general intelligence, and the somatisation section of the Composite International Diagnostic Interview was used to measure the number of FSS and MES.

Results: General intelligence was significantly associated with the number of FSS. The association of intelligence and FSS but not MES was mediated by work situation: participants of lower intelligence who reported more FSS were more often (unwanted) economically inactive. No evidence was found for a mediating role of psychological distress in the association of intelligence with FSS, even though distress was an important predictor of FSS.

Conclusion: Intelligence is negatively associated with the number of FSS in the general population. Part of the association of intelligence with FSS is explained by a more unfavourable work situation for adults of lower intelligence.

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Functional somatic symptoms (FSS) are somatic symptoms that cannot be conclusively explained in terms of conventionally defined organic pathology.1 2 FSS constitute a major healthcare problem because they are common, disabling for patients and costly for society.3 4 5 Doctors often have difficulties in dealing with patients who present with FSS. They want to reassure the patients, but at the same time fail to provide an acceptable explanation for the occurrence of FSS. Most doctors explain FSS to be the result of psychological distress.6 7 Patients are often dissatisfied with psychological labels for their somatic symptoms8 and prefer a somatic diagnosis.9 This incorrect dualistic view of both patients and doctors on the nature of symptoms is a major obstacle to effective treatment.

Although the aetiology of FSS is poorly understood, it is becoming increasingly clear that the underlying processes are multifactorial. Recent research and theory in this area suggest complex interactions among biological, psychological and social factors in the development and perpetuation of FSS.10 11 12 Intelligence is an interesting vulnerability factor to study in the context of FSS, because it is associated with several risk factors for development and perpetuation of FSS. Although intelligence itself has never been studied as a risk factor for FSS, studies on related constructs such as lower education level suggest an association with the occurrence of somatic symptoms in general practice.13 14 15 16 17 18 19 In contrast to FSS, various studies have looked at the relationship between intelligence and various kinds of medically explained somatic health problems. These studies have consistently found a negative association between intelligence and somatic morbidity or mortality.20 21 22

Two commonly studied non-exclusive mediating mechanisms in the relationship between intelligence and health are socioeconomic factors and lifestyle factors.23 Intelligence is associated with more education, and thereafter with more professional occupations that might place the person in healthier environments. In addition, intelligence is associated with a healthier diet, more exercise, and less smoking and problem drinking. Both mechanisms seem to be involved in the relationship between intelligence and somatic morbidity and mortality; however, it is not known to which degree these mechanisms are involved in the development of FSS. A third potential mediator is psychological distress, since both intelligence and somatic symptoms are known to be associated with an increased prevalence of anxiety and depression.24 25 26 Given the fact that most doctors explain FSS to be the result of psychological distress,6 7 the question arises of whether its mediating role might be more important in the relationship between intelligence and FSS than between intelligence and medically explained symptoms (MES).

This study aims to clarify the association between intelligence and FSS in a population-based cohort. We hypothesise that intelligence is negatively associated with the number of FSS. We also hypothesise that socioeconomic factors, lifestyle factors and psychological distress mediate this relation. To investigate the specific role of intelligence in FSS as opposed to MES, we compared associations of intelligence with FSS with those of intelligence with MES. Whereas we expected more or less similar associations with both outcomes, we expected that distress would be a mediator of the association of intelligence with FSS but not with that of intelligence with MES.

Methods

Population

The current study has been performed in a cohort derived from PREVEND (Prevention of REnal and Vascular ENd stage Disease), a major population cohort study at the University Medical Center, Groningen, investigating microalbuminuria as a risk factor for renal and cardiovascular disease. The recruitment of participants for PREVEND has been described elsewhere.27 Basically, the PREVEND baseline population consisted of 8592 subjects randomly selected from the population of the city of Groningen with oversampling for albuminuria. Selection of subjects for the purpose of the current study was aimed at recruiting a sample representative of the general population of Groningen, while simultaneously rectifying PREVEND’s oversampling for albuminuria. Research assistants gave invitations to 2554 participants who visited the outpatient clinic of PREVEND. Measurements were completed by a total of 1094 participants (43%), forming the population cohort. PREVEND participants who were invited for the current study but did not participate and PREVEND participants who agreed to participate did not significantly differ concerning gender, age and scores on a 12-item neuroticism scale.28 Follow-up measurements, performed approximately 2 years later, were completed by a total of 976 participants. The study was approved by the medical ethics committee and was conducted in accordance with the guidelines of the declaration of Helsinki. Written informed consent was obtained from all participants.

Assessment of intelligence

At baseline, the intelligence of the participants was measured using the computerised version of the General Aptitude-Test Battery (GATB) version B 1002-B.29 The GATB consists of a combination of tests that measure nine aptitudes. The aptitude intelligence is measured by three tests: (1) a dimensional space test, (2) a vocabulary test and (3) an arithmetic reasoning test. All participants performed the intelligence test in groups of at most nine persons. Before the start of each test, a test assistant provided test instructions and provided computer help when necessary. Tests were not started before the test assistant was certain that all participants had successfully completed the practice sessions. To construct a general intelligence score, we summed standardised scores on each of the three subtests (a total of 1061 completed GATBs were available).

Assessment of somatic symptoms

Participants completed the somatisation section of the Composite International Diagnostic Interview (CIDI). The CIDI is a fully structured diagnostic interview developed by the World Health Organization and has adequate test–retest reliability and validity.30 A fully computerised version of the CIDI 2.1, suitable for self-administration, was applied. Trained interviewers were present for questions and for people who needed computer help. In the CIDI somatisation section, 43 FSS (listed in the appendix) are assessed by asking “have you ever had” this symptom. Symptoms are considered to be present when they meet severity criteria, that is, provoking a healthcare visit. If these criteria are met, the interview assesses in a hierarchical fashion whether a medical doctor diagnosed a symptom as due to physical illness or injury, or whether a symptom was caused by the use of medication, drugs or alcohol. If the participant reported that a medical doctor diagnosed the symptom as due to physical illness or injury, the symptom was scored as a MES. If all enquiries were negative for medical explanations, the symptom was scored as a FSS. Sexual indifference was excluded from the analyses since it is not surveyed in the CIDI whether or not this symptom provoked a healthcare visit. Participants first completed the CIDI lifetime version measuring lifetime FSS and lifetime MES (a total of 1088 completed CIDIs were available). Approximately 2 years later, participants were re-interviewed and completed the CIDI 12 month version, in which the occurrence of the 43 symptoms in the previous year is surveyed (964 completed CIDIs were available). Since we expect that the 12 month recall of symptoms is less likely to be affected by cognitive abilities than lifetime recall, we constructed sum scores of 12 month FSS and 12 month MES for our main analyses. Additionally, sum scores of new-onset FSS and MES were constructed by comparing the MES and FSS reported in the CIDI 12 month interview with those reported in the CIDI lifetime interview.

Assessment of lifestyle factors

Body mass index (BMI) was calculated as the ratio between weight and the square of height (kg/m2) measured at baseline. Smoking, alcohol consumption and exercise frequency were assessed by written self-report at baseline. Smoking was categorised as non-smoker, 1–5, 6–10, 11–15, 16–20 or more than 20 cigarettes/day. Alcohol consumption was categorised as never or almost never, 1–4 units/month, 2–7 units/week, 1–3 units/day and ⩾4 units/day. Exercise frequency was categorised as never, once/week, twice or more/week.

Assessment of socioeconomic factors

Information on income, educational level and work situation was retrieved from questionnaires that were filled in at the time of inclusion in PREVEND. Income was measured through the gross monthly household income (<1200, 1200–1799, 1800–2199, 2200–2799, 2800–3799, 3800–5800, or >5800 guilders) divided by the square root of the number of people living in the household.31 The variable educational level was made up of the following categories: not applicable, low, middle, or high educational level. Low educational level was defined as lower secondary education or less, middle educational level was defined as higher secondary education, and high educational level was defined as tertiary education. Working situation was categorised in the following categories: employed (ie, currently having a job), willingly unemployed (ie, housekeeping or retired) or unwillingly unemployed (ie, job seeker or unable to work).

Assessment of psychological distress

Psychological distress was measured using the Dutch translation of the 12-item General Health Questionnaire (GHQ-12) measuring current psychological distress.32 This questionnaire was completed at home before the visit to the research facilities at baseline. The GHQ-12 comprises 12 questions dealing with two major classes of phenomena: inability to continue to carry out one’s normal healthy functions and the appearance of new phenomena of a distressing nature (eg, not being able to enjoy day-to-day activities, losing sleep because of worrying, thinking of yourself as worthless). The respondent is asked whether he or she has recently experienced a particular symptom or item of behaviour on a scale ranging from “less than usual” to “much more than usual”. No items pertaining to somatic symptoms are included in the GHQ-12. The GHQ-12 exceeded the criterion for acceptable instrument internal consistency reliability of 0.70 or greater.33 We calculated a GHQ sum score using the traditional GHQ scoring method of 0–0–1–1.34 Missing data were imputed according to the method of corrected item mean substitution, if at least half of the items were completed.35

Statistical analyses

We used SPSS V.16.0 (SPSS Inc., Chicago, Illinois, USA) to perform our statistical analyses. Variables that were not normally distributed (sum scores of FSS and MES) were log transformed. The association between the log-transformed sum scores of FSS and MES was tested using Pearson’s correlation coefficient. We performed univariable linear regression analyses to test whether subject characteristics (age, sex, BMI, smoking, alcohol consumption, exercise frequency, income, educational level, work situation and psychological distress) were associated with general intelligence, 12 month FSS or 12 month MES. We performed multivariable linear regression analyses to test whether general intelligence was associated with the number of 12 month FSS or 12 month MES. In addition, we repeated these analyses using, instead of general intelligence, scores on the dimensional space subtest, vocabulary subtest and arithmetic reasoning subtest as separate predictors. Next, we performed multivariable regression analyses, including potential mediators of the associations with FSS and MES. Factors were included only if they proved to be associated with both intelligence and the outcome. Since FSS and MES are correlated, we repeated all analyses adjusting FSS for MES and vice versa. Additionally, we tested whether intelligence predicted new-onset FSS and MES applying the same steps. All multivariable analyses were adjusted for the potential confounders gender (0 = M and 1 = F) and age (in years to one decimal place), since these variables are both associated with intelligence36 37 38 39 and FSS.39 40 41 42

Results

Demographic characteristics

The current study cohort consisted of 947 participants for whom intelligence sores and symptom scores were available (47.9% males), with a mean age of 52.7 years (standard deviation (SD) 11.2 years, minimum 33 years, maximum 79 years). Of the participants, 25.5% had a certificate of lower educational level; 27.0% a certificate of middle educational level; and 43.1% a certificate of higher educational level. Test scores of general intelligence were normally distributed (skewness  = −0.099, kurtosis  = −0.476). The correlation between the sum scores of FSS and MES was 0.172 (p<0.001).

Associations between subject characteristics and intelligence

Table 1 summarises the univariable associations between subject characteristics and intelligence. Intelligence was significantly associated with lower age and being male. Considering lifestyle factors, higher intelligence was associated with having a lower BMI, less smoking, more alcohol consumption, and exercising. Higher intelligence was also associated with a higher educational level, a more favourable work situation and a higher income. However, intelligence was not associated with psychological distress (β = −0.019, t = −0.591, p = 0.554). This means that psychological distress could not be a mediator of the association of intelligence with both outcomes, and this factor was therefore not examined in multivariable analyses.

Table 1

Univariable associations between subject characteristics and intelligence

Associations between subject characteristics and somatic symptoms

Table 2 summarises the univariable associations between subject characteristics and the number of 12 month FSS and 12 month MES. Older age was related to having more MES but not FSS; women had more MES and FSS than men. Both FSS and MES were associated with a higher BMI, less consumption of alcohol and a lower exercise frequency. Smoking was associated with FSS but not with MES. All socioeconomic factors were negatively associated with both FSS and MES, indicating that participants with a lower income, a lower educational level and less favourable work situation more often reported somatic symptoms. Psychological distress was positively associated with both FSS and MES, but the effect size for FSS is about twice the size of the effect size for MES. When repeating these analyses using new-onset FSS and MES as an outcome, the results remained essentially the same.

Table 2

Univariable associations between subject characteristics and the number of 12 month FSSs and the number of 12 month MESs

Associations between intelligence and somatic symptoms

Table 3 summarises the multivariable associations between intelligence and the number of 12 months FSS and MES. Linear regression analyses indicated that general intelligence was negatively associated with the number of FSS (β = −0.084, t = −2.299, p = 0.022) and MES (β = −0.095, t = −2.652, p = 0.008). When studying the subtests that composed general intelligence, we found that the association was explained by the vocabulary subtest and the arithmetic reasoning subtest, but not by the dimensional space subtest. Introduction of the potential mediators into the model removed the association of intelligence with somatic symptoms, but evidence for mediation was limited to work situation in the relationship between intelligence and FSS.

Table 3

Multivariable associations between intelligence and 12 month FSSs and 12 month MESs (all adjusted for age† and gender‡)

Discussion

This study demonstrated that intelligence was negatively associated with the number of reported FSS and MES. The association of intelligence with FSS was mediated by the work situation of participants, suggesting that adult men and women of lower intelligence who report more functional somatic symptoms are more often (unwanted) economically inactive. In contrast to our expectations, no evidence was found for a mediating role of psychological distress in the association of intelligence with FSS, even though distress was an important predictor of FSS.

There are several strengths of this study. First, we collected detailed information on a large number of FSS and performed our analyses on a continuous variable for the number of FSS. In many studies concerning FSS, arbitrary cut-off scores are used despite the lack of consensus about where to put the cut-off and the loss of information as a result of artificial dichotomising of variables.40 43 Second, we measured both FSS and MES using the same instrument, enabling comparisons between these types of symptoms and their associations with intelligence. Third, generalisability of our results is good, because we used a large population cohort without applying strict inclusion criteria.

When interpreting our study results, the following limitations should be taken into account. First, we measured intelligence in adult participants. Although general intelligence is regarded as a trait that is stable from infancy into middle age,44 it cannot be excluded that reverse causality, in which somatic symptoms contribute to lower intelligence scores, is playing a role. We performed additional analyses (results not shown) including only new-onset symptoms (ie, onset after measurement of intelligence) as outcomes, which provided essentially the same results as the analyses that are reported here, indicating that the effect of reverse causality may have been negligible. However, this does not exclude the possibility that pre-existing morbidity causes both low intelligence scores and new somatic symptoms. Second, recall bias may have attenuated the reliability of the CIDI to measure FSS and MES,45 and recall bias is likely to be associated with intelligence because people with lower intelligence have lower memory capacity.46 We limited our analyses to symptoms that occurred in the last 12 months, which will have reduced the effect of recall bias. Moreover, it should be noted that the expected effect of recall bias on our results would be to reduce associations of intelligence with reported symptoms, indicating that our results are more likely to be underestimations rather than overestimates. Finally, the fact that we measured symptoms via self-report may be regarded as a limitation. However, symptoms were defined as being functional only if it was reported that a medical doctor had indicated that all enquiries were negative for medical explanations. Moreover, the finding that psychological distress as measured by GHQ-scores was much more strongly associated with FSS than with MES underlines the aetiological difference between the symptoms.

Our study demonstrates that intelligence is negatively associated with the number of FSS and MES. We are the first to study the direct relation between intelligence and FSS, but a negative association between intelligence and morbidity or mortality has been a consistent finding.20 21 22 Focusing on the association of intelligence with covariates, most of our results seemed to be in line with findings from previous studies. Socioeconomic factors and most lifestyle factors were negatively associated with intelligence. Only for alcohol consumption did we observe a positive association (ie, more alcohol consumption in those with higher intelligence). Some studies have found the same result,47 48 whereas other studies found the opposite.49 It should be realised that we used a continuous measure of alcohol consumption, mainly indicating social drinking (which might be related to higher socioeconomic status50) with only a minority being problem drinkers. Another unexpected finding might be that psychological distress was not related to intelligence. Our initial hypothesis that one of the major differences between the associations of intelligence with FSS and MES would be that the association with FSS was mediated by distress therefore was not confirmed. Previous studies on intelligence and GHQ scores have been contrasting, with either a negative association between childhood intelligence and the GHQ-28 in middle-aged women48 or no association between current intelligence and GHQ-30 scores in middle-aged participants from the Whitehall II study.22

The associations of socioeconomic and lifestyle factors with somatic symptoms were in the expected directions, with the exception of smoking in relation to MES. Despite its well-known association with morbidity and mortality,51 we observed no association between smoking and MES. This lack of association might be due to the fact that we measured somatic complaints and not diagnoses, and most complaints included in the CIDI are not associated with smoking-related diseases such as cardiovascular and pulmonary disease.

Our multivariable models show that the association of intelligence with FSS and MES is removed after adding lifestyle and socioeconomic factors into the model. However, there was only clear evidence for mediation of the association with FSS by work situation. The interpretation of these findings is not obvious, but one possibility is that participants without a job do not have a day-to-day distraction from their physical complaints. Furthermore, unemployment, and especially unwanted employment, is clearly linked to devastating individual effects, such as financial hardship.52 It could be hypothesised that the resulting psychological distress is responsible for the association between work situation and FSS. Although we did indeed find an association between psychological distress and FSS, this association was not responsible for the relationship between work situation and FSS.

Finally, our results indicate that verbal components of intelligence are more important than performance components of intelligence in predicting somatic complaints. One explanation for this finding could be that linguistic skills might be of more use when communicating with doctors and when seeking social support for somatic complaints or psychosocial stress. Psychosocial stress has been assumed to play a role in the development and perpetuation of FSS4 12 53 and MES.54

In conclusion, lower general intelligence was associated with a higher number of FSS and MES in the general population. Part of the association of intelligence with FSS was explained by a more unfavourable work situation for adults of lower intelligence.

What is already known on this subject

Recent research and theory in this area suggest complex interactions among biological, psychological and social factors in the development and perpetuation of functional somatic symptoms (FSSs). Intelligence is an interesting vulnerability factor to study in the context of FSSs, because it is associated with several risk factors for the development and perpetuation of FSSs.

What this study adds

Our results reveal a significant negative association between intelligence and the number of functional somatic symptoms (FSSs) in a general population cohort. Part of the association of intelligence with FSSs is explained by a more unfavourable work situation for adults of lower intelligence. No evidence was found for a mediating role of psychological distress in the association of intelligence with FSSs, even though distress was an important predictor of FSSs.

Appendix: List of 43 functional somatic symptoms surveyed in the Composite International Diagnostic Interview

Abdominal pain

Back pain

Joint pain

Pain in extremities

Chest pain

Headache

Pain during urination

Urinary retention

Burning sensation genitals

Pain symptoms additional sites

Vomiting other than during pregnancy

Vomiting throughout pregnancy

Nausea

Diarrhoea

Feeling bloated or full of gas

Intolerance of several foods

Blindness

Blurred vision

Deafness

Impaired balance

Impaired coordination

Loss of touch or pain sensation

Paralysis

Aphonia

Seizures

Dizziness

Loss of consciousness other than fainting

Amnesia

Double vision

Shortness of breath

Localised weakness

Skin blotches or discoloration

Bad taste in mouth or excessively coated tongue

Frequent urination

Numbness/tingling

Difficulty swallowing or lump in throat

Irregular menses

Excessive menstrual bleeding

Pain during menstruation

Pain during sexual intercourse

Unpleasant sexual intercourse

Other sexual problems including erectile or ejaculatory dysfunction

Sexual indifference

REFERENCES

Supplementary materials

Footnotes

  • Appendix available online only at http://jech.bmj.com/content/vol63/issue11

  • Funding Funding for this study was provided by the Netherlands Organisation for Scientific Research (Pionier 900-00-002). This organisation had no further role in the study design; in the collection and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.

  • Competing interests None.

  • Ethics approval Ethics approval was obtained from the Medical Ethics Committee of the University Medical Center Groningen.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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