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The relation between health locus of control and multimorbidity: a case-control study
Personality and Individual Differences 30 (2001) 1189±1197
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The relation between health locus of control and multimorbidity: a case-control study Mario van der Linden, Marjan van den Akker *, Frank Buntinx Department of General Practice, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands Received 10 September 1999; received in revised form 4 April 2000
Abstract This paper describes a study on the relation between the health locus of control (HLOC) and a number of patient characteristics, with special interest for the presence of multimorbidity. Subjects (N=3745) completed a postal questionnaire with items about socio-demographic variables, socio-economic status, health locus of control and coping styles. Logistic regression analyses were used to investigate the relation between HLOC and multimorbidity, as well as the psycho-social determinants of HLOC. People who had no disease or only one disease during the registration period of 3 years scored higher on the internal locus and lower on the external locus than people who had two or more co-occurring diseases. Adjusting for age, sex, education, profession, family situation and coping styles changed the magnitude but not the presence of these relations. Hypotheses with respect to the direction of this relation are discussed. # 2001 Elsevier Science Ltd. All rights reserved. Keywords: Health locus of control; Multimorbidity; Case-control study
1. Introduction The Multidimensional Health Locus of Control Scales (Wallston, Wallston & DeVellis, 1978) assess individuals' attributions about in¯uences on health and illness. The health locus of control (HLOC) is divided in an internal, external and chance locus. Internal locus relates to control experienced over one's own health. External locus represents the attribution of one's own health to powerful others, such as doctors. People with a more chance-oriented locus believe that health and illness are a matter of luck. Wallston and Wallston (1981) based this three-dimensional scale on a two-dimensional one developed by Rotter in 1966 (Halfens & Philipsen, 1988; Levenson, * Corresponding author. Tel.: +31-43-388-2321; fax: +31-43-361-9344. E-mail address: [email protected] (M. van den Akker). 0191-8869/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved. PII: S0191-8869(00)00102-1
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1981; Talbot, Nouwen & Gauthier, 1996). The locus of control construct is based on the Social Learning Theory and is a joint function of the person's expectancy that the behaviour will lead to a particular outcome in a speci®c situation and the value of that outcome to the person in that situation (Wallston, 1992). Most of these studies have been investigating dierences in HLOC between people with and without a disease. De Valck and Vinck (1996) found a more internally-oriented belief in lung cancer patients compared to patients without lung cancer, and Gustafsson and Gaston-Johansson (1996) concluded that ®bromyalgia patients had a more externally-oriented belief compared to arthritis patients. Externally-oriented patients scored higher on the HLOC during a hospitalisation and internally-oriented patients scored the same before, during and after a hospitalisation (Halfens, 1995). Furthermore, relations were reported between a high score on the internal locus and a healthier life style, sports activities, compliance to treatments and functional status (HaÈrkaÈpaÈaÈ, JaÈrvikoski, Mellin, Hurri & Luoma, 1991; Norman, Bennett, Smith & Murphy, 1997; Wallhagen, Strawbridge, Kaplan & Cohen, 1994). Other studies investigated the determinants of the HLOC orientation: Furnham and Kirkcaldy (1997) concluded that women had a more internal vision of HLOC than men did and that age did not in¯uence the HLOC. Dupen, Higginbotham, Francis, Cruickshank and Gibson (1996), however, found higher scores on the external locus with increasing age in a group of asthma patients. Although information is available on the relation between HLOC and a number of determinants, including some speci®c diseases, no studies could be identi®ed on the relation between HLOC and a general susceptibility to disease. Therefore, a study was designed to identify the in¯uence of the HLOC on the presence of multimorbidity, as an indicator of general disease susceptibility, taking into account a number of patient-related characteristics that may act as confounders or eect-modi®ers. In this study the main outcome measure was the absence or presence of multimorbidity. In Western societies health is generally considered as one of the most important things in life. Therefore, we think it is justi®ed to evaluate the relation between HLOC and multimorbidity. We expected a low score on the internal locus of control to be related to increased prevalence of multimorbidity, based on previous reports on the relation between an internal locus of control and the presence of life style characteristics or speci®c diseases. Thus, the key questions of this study were: 1. How is the HLOC related to relevant patient related characteristics: age, sex, multimorbidity, education, profession, family situation, and coping style? 2. What is the relation between HLOC and multimorbidity, adjusted for the other relevant patient-related characteristics? 2. Methods 2.1. Materials For a large register-based nested case-control study on determinants of multimorbidity subjects were sampled from the Registration Network Family Practices (Registratie Net Huisarts praktijken, RNH) (Van den Akker, Buntinx, Metsemakers & Knottnerus, 2000). The RNH is a computerised
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and continuous database in which 42 Dutch general practitioners (GPs) from 15 practices participate. The GPs systematically collect data on all relevant chronic, recurrent or permanent health problems, which are coded according to the International Classi®cation of Primary Care (ICPC) (Lamberts & Wood, 1987), as well as background variables of a general population of over 60,000 registered subjects. The quality of the data is ascertained by instruction and training sessions, regional consensus groups, quality control experiments and special software programs, such as an automated thesaurus and automated checking for erroneous or missing entries (Metsemakers, HoÈppener, Knottnerus & Limonard, 1992). The case-control study focused on the relationship between multimorbidity and a number of potential determinants: demographic features, socio-economic status, life style, medical personal and family history, and psychological and sociological features. Cases were de®ned as subjects aged 20 or older who had two or more new diagnoses on their problem list in a period of three years. Controls were de®ned as subjects with no or only one new diagnosis on the problem list in this period. Cases and controls were sampled randomly from the RNH database. A total of 6113 subjects received a postal questionnaire. Of those 3745 (61.3%) completed and returned the questionnaire. Response was not dierent for the case and control groups (P>0.05). The responders resembled the initial sample quite well with regard to sex and type of health insurance. Subjects aged 20±29 years and those aged 80 or older were somewhat underrepresented among the responders compared with non-responders. Compared to non-responders, responders somewhat more often lived together with a partner or family and had a higher level of education. Responders were very comparable to non-responders with regard to the number and type of prevalent diseases. The non-response analysis has been described in more detail elsewhere (Van den Akker, Buntinx, Metsemakers & Knottnerus, 1998). Basic patient characteristics are described in Table 1. 2.2. Questionnaire The questionnaire was similar for cases and controls and covered socio-demographic, life style, psychological and sociological variables. The questionnaire has been described more extensively elsewhere (Van den Akker et al., 2000). The main parts of the original questionnaire that were used for this study are: demographic characteristics, socio-economic status, family situation, and coping style. Socio-demographic variables included family situation, and socio-economic status. Health locus of control (HLOC) was measured by the validated Dutch version (Halfens, 1995) of the Multidimensional Health Locus of Control Scale by Wallston and Wallston (1981). Each dimension has six items, to be answered on a 6-point Likert scale ranging from `absolutely disagree' to `absolutely agree'. The HLOC has three dimensions: the internal locus, the external locus, and the chance locus. In our population we found a good internal consistency for all three dimensions (Cronbach's a 0.74, 0.81, and 0.67 respectively). For the analyses locus scores were dichotomised (cut-o point 3.5), because analysis with a continuous variable presumes a proportional change in eect. Coping can be described as stress management or the adaptive reactions, thoughts and actions that are used to stand up to a stressor (Feij, van Kampen, Doorn, Resing & van den Berg, 1990). Coping was measured using the short coping list (15 items) (Sanderman & Ormel, 1992; Schaufeli
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Table 1 Basic characteristics of the study population Characteristic (valid N) Sex (N=3745) Males Females Age (N=3745) 20±39 40±59 60±79 80 Educational level (N=3742) Low Secondary High Type of health insurance (N=3745) Public Private Multimorbidity in selection period (N=3745) No Yes Internal locus (N=3478) Low High External locus (N=3489) Low High Chance locus (N=3475) Low High Active tackling coping (N=3500) Low High Waiting and avoiding coping (N=3473) Low High Palliative coping (N=3472) Low High Social support coping (N=3490) Low High Family situation (N=3510) Couple without children Parents with children living elsewhere Parents with children at home People living alone Profession (N=3597) Low blue High blue Low white High white Other
% 50.2 49.8 27.4 32.8 35.2 4.6 48.5 36.8 14.7 68.3 31.7 63.1 36.9 36.1 63.9 64.8 35.2 58.1 41.9 17.0 83.0 67.8 32.2 60.1 39.9 47.9 52.1 13.1 42.9 37.0 7.0 15.4 16.6 14.1 21.9 32.0
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& Van Dierendonck, 1992). Four coping styles can be distinguished: `active', `social support seeking', `avoiding', and `palliative' (Komproe, Rijken, Ros, Winnubst & t'Hart, 1997) (Cronbach's a 0.64, 0.84, 0.44, and 0.82 respectively). For each coping style a dichotomous score was calculated. 2.3. Analysis A correlation matrix for all variables, separately for the no morbidity and unimorbidity group and for the multimorbidity group, allows a quick look at dierences in magnitude and direction of bivariate correlations. Simple logistic regression resulted in crude odds ratios (OR) with their 95% con®dence interval (95% CI) for the relations between each of patients characteristics and each of the HLOC scales as the dependent variable (dichotomous). Also, simple logistic regression analysis was used to establish the crude relations between each of the HLOC scales (continuous) and morbidity and multimorbidity as the dependent variables respectively. Multivariate logistic regression analysis was used to study the independent in¯uence of each HLOC scale (continuous) on the presence or absence of morbidity and multimorbidity respectively, adjusted for a number of covariables (sex, age, education, profession, family situation and coping styles). The method permits adjustment for any confounding or modifying eects by the covariables, as well as for interaction between the independent variable and the covariables. 3. Results The relation between all variables was examined using a correlation matrix that is presented in Table 2. Men scored signi®cantly higher compared to women on both the internal and external locus (P<0.001, Table 3). The dierences, however, were very small (mean dierence internal locus=0.15 and external locus=0.20). There was no signi®cant dierence between the two sexes on the chance locus. Increasing age was related to a lower score on the internal locus and a higher score on the external locus and the chance locus. A higher educational level implied a higher score on the internal and a lower score on the external and chance locus. The higher the professional status, the lower people scored on external locus. There was no signi®cant dierence between people without children (singles and couples), people with children living at home and people with children who live on their own with respect to the HLOC. People who scored high on the coping style `Active tackling' had a signi®cantly higher score on the internal locus and a signi®cantly lower one on the external and chance locus compared to people who scored low on this coping style. People with high scores on the coping style `Waiting and avoiding' scored signi®cantly higher on the external locus and on the chance locus compared to people with a low score on this coping style. The group with a high score on the `Palliative coping style' scored signi®cantly higher on the internal locus and on the chance locus compared to people scoring low on this coping style. A high score on the `Seeking social support' coping style was related to a signi®cantly lower score on the external and chance locus.
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Active tackling Active tackling Waiting and avoiding Social support Palliative Sex Age category Educational level Profession Family situation External locus Internal locus Chance locus a
1.000 0.003 0.231** 0.165** 0.008 0.098* 0.185** 0.035 0.017 0.091** 0.045* 0.096**
Waiting and Social avoiding support 0.073** 1.000 0.034 0.143** 0.018 0.112** 0.096** 0.018 0.035 0.130** 0.019 0.113**
0.213** 0.031 1.000 0.159** 0.165** 0.147** 0.138** 0.030 0.031 0.064** 0.012 0.062**
Palliative Sex 0.103** 0.145** 0.102** 1.000 0.031 0.011 0.045* 0.011 0.041 0.010 0.037 0.020
0.010 0.074** 0.165** 0.063* 1.000 0.012 0.065** 0.106** 0.058** 0.041 0.086** 0.019
Age Educational Profession Family External Internal category level situation locus locus 0.161** 0.152** 0.130** 0.090** 0.090** 1.000 0.244** 0.197** 0.047** 0.355** 0.101** 0.138**
0.204** 0.113** 0.065* 0.057* 0.090** 0.117** 1.000 0.051* 0.040* 0.261** 0.049* 0.127**
0.034 0.082** 0.002 0.033 0.172** 0.226** 0.094** 1.000 0.015 0.055* 0.001 0.028
Note: *Correlation signi®cant at the 0.05 level (2-tailed); **correlation signi®cant at the 0.01 level (2-tailed).
0.098** 0.119** 0.052 0.004 0.136** 0.021 0.047 0.060* 1.000 0.064** 0.025 0.006
0.095** 0.101** 0.048 0.051 0.098** 0.314** 0.218** 0.088** 0.003 1.000 0.075** 0.219**
0.062* 0.022 0.024 0.060* 0.028 0.083** 0.024 0.041 0.035 0.061* 1.000 0.008
Chance locus 0.065* 0.083* 0.039 0.013 0.090** 0.052 0.082** 0.039 0.101** 0.238** 0.016 1.000
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Table 2 Correlation matrix responders with multimorbidity (upper right part) and responders without multimorbidity (lower left part)a
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Table 3 The relation between patient characteristics and HLOC. Reported are odds ratios (OR) and their 95% CI Internal
Sex Male Female Age 20±39 40±59 60±79 >80 Education Low Average High Profession Low blue High blue Low white High white Other Family situation Couple without children Parents with children living elsewhere Parents with children at home People living alone Coping styles Seeking social support + Palliative coping style + Active tackling + Waiting and avoiding +
External
Chance
OR
95% CI
OR
95% CI
OR
95% CI
1.00 0.77
0.69±0.88
1.00 0.77
0.67±0.88
1.00 1.06
0.93±1.21
1.00 0.84 0.57 0.59
0.70±1.00 0.47±0.67 0.40±0.86
1.00 2.04 7.23 7.59
1.65±2.51 5.98±8.87 5.13±11.24
1.00 1.54 2.22 3.62
1.29±1.83 1.86±2.65 2.46±5.32
1.00 1.13 1.35
0.98±1.32 1.10±1.66
1.00 0.39 0.22
0.34±0.46 0.17±0.28
1.00 0.62 0.45
0.54±0.72 0.36±0.55
1.00 1.09 1.00 1.16 0.90
0.85±1.40 0.78±1.30 0.92±1.46 0.72±1.12
1.00 1.38 0.60 0.56 1.18
1.08±1.77 0.46±0.78 0.44±0.71 0.95±1.47
1.00 1.42 0.95 0.83 1.30
1.11±1.81 0.74±1.23 0.66±1.05 1.05±1.61
1.00 0.66 0.99 0.91
0.55±0.81 0.81±1.20 0.66±1.26
1.00 3.08 1.04 1.20
2.51±3.79 0.84±1.29 0.86±1.69
1.00 1.73 1.12 1.06
1.43±2.10 0.93±1.37 0.78±1.46
1.00 1.00
0.87±1.15
1.00 0.80
0.69±0.92
1.00 0.88
0.76±1.00
1.00 1.22
1.06±1.41
1.00 1.10
0.95±1.27
1.00 1.19
1.04±1.37
1.00 1.34
1.11±1.60
1.00 0.60
0.50±0.72
1.00 0.72
0.60±0.86
1.00 0.99
0.86±1.15
1.00 1.73
1.49±2.00
1.00 1.58
1.36±1.82
The occurrence of new morbidity in the selection period was related to a lower score on the internal locus of control and a higher score on the external locus of control, not to the chance locus of control. These eects showed both in the crude and adjusted analyses. People with multimorbidity (cases) scored signi®cantly lower on the internal locus compared to people without multimorbidity (controls) (P<0.001), and signi®cantly higher on the external (P<0.001) and the chance (P<0.05) locus (Table 4).
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Table 4 Relation between morbidity and multimorbidity and HLOC, crude as well as adjusted for sex, age, education, profession, family situation and coping styles; odds ratios (and their 95% C.I) are reported
Internal External Chance
Morbidity crude
Morbidity adjusted
Multimorbidity crude
Multimorbidity adjusted
0.82 (0.75±0.88) 1.28 (1.17±1.34) 1.07 (0.99±1.15)
0.84 (0.77±0.92) 1.11 (1.02±1.21) 0.99 (0.91±1.07)
0.76 (0.70±0.83) 1.39 (1.30±1.49) 1.12 (1.04±1.20)
0.80 (0.74±0.88) 1.19 (1.09±1.29) 1.00 (0.92±1.09)
The adjusted odds ratio of the internal locus for people with multimorbidity compared to people without multimorbidity was 0.80 (95% CI: 0.74±0.88) (Table 4), for the external locus the adjusted odds ratio was 1.19 (95% CI: 1.09±1.29). There was no signi®cant relation between multimorbidity and the chance locus after adjustment (Table 4). In general, the adjusted odds ratios are smaller compared to the crude odds ratios. 4. Discussion This study focused on possible determinants of HLOC and the relation between HLOC and multimorbidity. Our results are in line with Furnham and Kirkcaldy (1997), showing that men scored higher on both the internal and external locus of control compared to women. We found a more important in¯uence of age, however, that was both statistically signi®cant and consistent for all age groups. Based on the literature we expected socio-economic status to be positively related to the internal locus and negatively to the external and chance locus. Using educational level as an indicator, this was con®rmed in our study. The professional status, however, did not show such strong and consistent relations. An explanation could be that the ®ve categories of professional status are not on an ordinal scale. The relation between the three HLOC scales and multimorbidity are signi®cant and reasonably strong at crude data analysis. After adjustment, however, the negative relation with the internal locus and the positive relation with the external locus were somewhat weaker, the adjusted odds ratio for chance was not statistically signi®cant. This is not surprising in view of the relations between the HLOC and the other patient characteristics. It is remarkable that we found similar, but weaker, relations for morbidity. It is not yet clear whether locus of control is a cause or a consequence of morbidity and multimorbidity and it is not possible to determine this using a cross-sectional study design. Possibly, illness in¯uences patients' beliefs regarding their own attribution to and control of health. On the other hand, it is plausible that the HLOC in¯uences the lifestyle of people and hence may (partially) be the cause of health or illness. Also, an indirect in¯uence of HLOC on health is possible, e.g. via stress, coping and/or immunological pathways. To investigate the direction of the association, one should prospectively follow a large group of healthy people. After a number of years cases with morbidity and cases with multimorbidity could be compared to each other as well as to healthy subjects regarding their scores on the
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HLOC. Furthermore, HLOC before and after the occurrence of morbidity/multimorbidity could be compared. This would indicate the direction of the relation. Such a study has been started as a result of this analysis. References De Valck, C., & Vinck, J. (1996). Health locus of control and quality of life in lung cancer patients. Patient Education and Counseling, 28, 179±186. Dupen, F., Higginbotham, N., Francis, L., Cruickshank, D., & Gibson, P. (1996). Validation of a new multidimensional health locus of control scale (from C) in asthma research. Psychol. Health, 11, 493±504. Feij, J., van Kampen, D., Doorn, C. D., Resing, W. C. M., & van den Berg, P. T. (1990). De relatie tussen ingrijpende gebeurtenissen, coping-stijlen en klachten [The relation between life events, coping styles and complaints]. Gezondheid en Gedrag, 18(4/5), 182±196. Furnham, A., & Kirkcaldy, B. (1997). Age and sex dierences in health beliefs and behaviors. Psychol. Reports, 80, 63±66. Gustafsson, M., & Gaston-Johansson, F. (1996). Pain intensity and health locus of control: a comparison of patients with ®bromyalgia syndrome and rheumatoid arthritis. Patient Education and Counseling, 29, 179±188. Halfens, R. (1995). Eect of hospital stay on health locus of control beliefs. Western Journal of Nursing Research, 17(2), 156±167. Halfens, R., & Philipsen, H. (1988). Een gezondheidsspeci®eke beheersingsorieÈntatieschaal. Betrouwbaarheid en validiteit van de MHLC [A health locus of control scale. Reliability and validity of the MHLC]. TSG, 66, 399±403. HaÈrkaÈpaÈaÈ, K., JaÈrvikoski, A., Mellin, G., Hurri, H., & Luoma, J. (1991). Health locus of control beliefs and psychological distress as predictors for treatment outcome in low-back pain patients: results of a 3-months follow-up of a controlled intervention study. Pain, 46, 35±41. Komproe, I., Rijken, M., Ros, W. J. G., Winnubst, J. A. M., & 't Hart, H. (1997). Available support and received support: dierent eects under stressful circumstances. Journal of Social and Personal Relationships, 14(1), 59±77. Lamberts, H., & Wood, M. (1987). International classi®cation of primary care. Oxford: Oxford University Press. Levenson, H. (1981). Dierentiating among internality, powerful others, and chance. In H. M. Lefcourt, Research with the locus of control construct, Vol. 1 (pp. 15±63). Academic Press. Metsemakers, J., HoÈppener, P., Knottnerus, J., & Limonard, C. B. G. (1992). Computerized health information in the Netherlands: a registration network of family practices. Br. J. Gen. Pract., 42(356), 102±106. Norman, P., Bennett, P., Smith, C., & Murphy, S. (1997). Health locus of control and leisure-time exercise. Person. Individ. Di., 23(5), 769±774. Sanderman, R., & Ormel, J. (1992). De Utrechtse Coping Lijst (UCL): validiteit en betrouwbaarheid [The Utrecht Coping List (UCL): validity and reliability]. Gedrag en Gezondheid, 20(1), 32±37. Schaufeli, W., & Van Dierendonck, D. (1992). De betrouwbaarheid en validiteit van de Utrechtse Coping Lijst. Een longitudinaal onderzoek bij schoolverlaters [The reliability and validity of the Utrecht Coping List. A longitudinal study among schoolleavers]. Gedrag en Gezondheid, 20(1), 38±45. Talbot, F., Nouwen, A., & Gauthier, J. (1996). Is health locus of control a 3-factor or a 2-factor construct? J. Clin. Psychol., 52(5), 559±568. Van den Akker, M., Buntinx, F., Metsemakers, J. F. M., & Knottnerus, J. A. (1998). Morbidity in responders and nonresponders in a register-based population survey. Fam. Pract., 15(3), 261±263. Van den Akker, M., Buntinx, F., Metsemakers, J. F. M., & Knottnerus, J. A. (2000). Marginal impact of psycho-social factors on multimorbidity: results of an explorative nested case-control study. Soc. Sci. Med., 50, 1679±1693. Wallhagen, M., Strawbridge, W. J., Kaplan, G. A., & Cohen, R. D. (1994). Impact of internal health locus of control on health outcomes for older men and women: a longitudinal perspective. Gerontologist, 34(3), 299±306. Wallston, B., & Wallston, K. A. (1981). Health locus of control scales. In H. M. Lefcourt, Research with the Locus of Control Construct: Vol. 1 Assessment methods. New York: Academic Press. Wallston, K., Wallston, B. S., & DeVellis, R. (1978). Development of the Multidimensional Health Locus of Control Scales (MHLC). Health Education Monographs, 6, 160±171. Wallston, K. (1992). Hocus-pocus, the focus isn't strictly on locus: Rotter's social learning theory modi®ed for health. Cognitive Therapy and Research, 16(2), 183±199.
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The relation between health locus of control and multimorbidity: a case-control study Mario van der Linden, Marjan van den Akker *, Frank Buntinx Department of General Practice, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands Received 10 September 1999; received in revised form 4 April 2000
Abstract This paper describes a study on the relation between the health locus of control (HLOC) and a number of patient characteristics, with special interest for the presence of multimorbidity. Subjects (N=3745) completed a postal questionnaire with items about socio-demographic variables, socio-economic status, health locus of control and coping styles. Logistic regression analyses were used to investigate the relation between HLOC and multimorbidity, as well as the psycho-social determinants of HLOC. People who had no disease or only one disease during the registration period of 3 years scored higher on the internal locus and lower on the external locus than people who had two or more co-occurring diseases. Adjusting for age, sex, education, profession, family situation and coping styles changed the magnitude but not the presence of these relations. Hypotheses with respect to the direction of this relation are discussed. # 2001 Elsevier Science Ltd. All rights reserved. Keywords: Health locus of control; Multimorbidity; Case-control study
1. Introduction The Multidimensional Health Locus of Control Scales (Wallston, Wallston & DeVellis, 1978) assess individuals' attributions about in¯uences on health and illness. The health locus of control (HLOC) is divided in an internal, external and chance locus. Internal locus relates to control experienced over one's own health. External locus represents the attribution of one's own health to powerful others, such as doctors. People with a more chance-oriented locus believe that health and illness are a matter of luck. Wallston and Wallston (1981) based this three-dimensional scale on a two-dimensional one developed by Rotter in 1966 (Halfens & Philipsen, 1988; Levenson, * Corresponding author. Tel.: +31-43-388-2321; fax: +31-43-361-9344. E-mail address: [email protected] (M. van den Akker). 0191-8869/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved. PII: S0191-8869(00)00102-1
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1981; Talbot, Nouwen & Gauthier, 1996). The locus of control construct is based on the Social Learning Theory and is a joint function of the person's expectancy that the behaviour will lead to a particular outcome in a speci®c situation and the value of that outcome to the person in that situation (Wallston, 1992). Most of these studies have been investigating dierences in HLOC between people with and without a disease. De Valck and Vinck (1996) found a more internally-oriented belief in lung cancer patients compared to patients without lung cancer, and Gustafsson and Gaston-Johansson (1996) concluded that ®bromyalgia patients had a more externally-oriented belief compared to arthritis patients. Externally-oriented patients scored higher on the HLOC during a hospitalisation and internally-oriented patients scored the same before, during and after a hospitalisation (Halfens, 1995). Furthermore, relations were reported between a high score on the internal locus and a healthier life style, sports activities, compliance to treatments and functional status (HaÈrkaÈpaÈaÈ, JaÈrvikoski, Mellin, Hurri & Luoma, 1991; Norman, Bennett, Smith & Murphy, 1997; Wallhagen, Strawbridge, Kaplan & Cohen, 1994). Other studies investigated the determinants of the HLOC orientation: Furnham and Kirkcaldy (1997) concluded that women had a more internal vision of HLOC than men did and that age did not in¯uence the HLOC. Dupen, Higginbotham, Francis, Cruickshank and Gibson (1996), however, found higher scores on the external locus with increasing age in a group of asthma patients. Although information is available on the relation between HLOC and a number of determinants, including some speci®c diseases, no studies could be identi®ed on the relation between HLOC and a general susceptibility to disease. Therefore, a study was designed to identify the in¯uence of the HLOC on the presence of multimorbidity, as an indicator of general disease susceptibility, taking into account a number of patient-related characteristics that may act as confounders or eect-modi®ers. In this study the main outcome measure was the absence or presence of multimorbidity. In Western societies health is generally considered as one of the most important things in life. Therefore, we think it is justi®ed to evaluate the relation between HLOC and multimorbidity. We expected a low score on the internal locus of control to be related to increased prevalence of multimorbidity, based on previous reports on the relation between an internal locus of control and the presence of life style characteristics or speci®c diseases. Thus, the key questions of this study were: 1. How is the HLOC related to relevant patient related characteristics: age, sex, multimorbidity, education, profession, family situation, and coping style? 2. What is the relation between HLOC and multimorbidity, adjusted for the other relevant patient-related characteristics? 2. Methods 2.1. Materials For a large register-based nested case-control study on determinants of multimorbidity subjects were sampled from the Registration Network Family Practices (Registratie Net Huisarts praktijken, RNH) (Van den Akker, Buntinx, Metsemakers & Knottnerus, 2000). The RNH is a computerised
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and continuous database in which 42 Dutch general practitioners (GPs) from 15 practices participate. The GPs systematically collect data on all relevant chronic, recurrent or permanent health problems, which are coded according to the International Classi®cation of Primary Care (ICPC) (Lamberts & Wood, 1987), as well as background variables of a general population of over 60,000 registered subjects. The quality of the data is ascertained by instruction and training sessions, regional consensus groups, quality control experiments and special software programs, such as an automated thesaurus and automated checking for erroneous or missing entries (Metsemakers, HoÈppener, Knottnerus & Limonard, 1992). The case-control study focused on the relationship between multimorbidity and a number of potential determinants: demographic features, socio-economic status, life style, medical personal and family history, and psychological and sociological features. Cases were de®ned as subjects aged 20 or older who had two or more new diagnoses on their problem list in a period of three years. Controls were de®ned as subjects with no or only one new diagnosis on the problem list in this period. Cases and controls were sampled randomly from the RNH database. A total of 6113 subjects received a postal questionnaire. Of those 3745 (61.3%) completed and returned the questionnaire. Response was not dierent for the case and control groups (P>0.05). The responders resembled the initial sample quite well with regard to sex and type of health insurance. Subjects aged 20±29 years and those aged 80 or older were somewhat underrepresented among the responders compared with non-responders. Compared to non-responders, responders somewhat more often lived together with a partner or family and had a higher level of education. Responders were very comparable to non-responders with regard to the number and type of prevalent diseases. The non-response analysis has been described in more detail elsewhere (Van den Akker, Buntinx, Metsemakers & Knottnerus, 1998). Basic patient characteristics are described in Table 1. 2.2. Questionnaire The questionnaire was similar for cases and controls and covered socio-demographic, life style, psychological and sociological variables. The questionnaire has been described more extensively elsewhere (Van den Akker et al., 2000). The main parts of the original questionnaire that were used for this study are: demographic characteristics, socio-economic status, family situation, and coping style. Socio-demographic variables included family situation, and socio-economic status. Health locus of control (HLOC) was measured by the validated Dutch version (Halfens, 1995) of the Multidimensional Health Locus of Control Scale by Wallston and Wallston (1981). Each dimension has six items, to be answered on a 6-point Likert scale ranging from `absolutely disagree' to `absolutely agree'. The HLOC has three dimensions: the internal locus, the external locus, and the chance locus. In our population we found a good internal consistency for all three dimensions (Cronbach's a 0.74, 0.81, and 0.67 respectively). For the analyses locus scores were dichotomised (cut-o point 3.5), because analysis with a continuous variable presumes a proportional change in eect. Coping can be described as stress management or the adaptive reactions, thoughts and actions that are used to stand up to a stressor (Feij, van Kampen, Doorn, Resing & van den Berg, 1990). Coping was measured using the short coping list (15 items) (Sanderman & Ormel, 1992; Schaufeli
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Table 1 Basic characteristics of the study population Characteristic (valid N) Sex (N=3745) Males Females Age (N=3745) 20±39 40±59 60±79 80 Educational level (N=3742) Low Secondary High Type of health insurance (N=3745) Public Private Multimorbidity in selection period (N=3745) No Yes Internal locus (N=3478) Low High External locus (N=3489) Low High Chance locus (N=3475) Low High Active tackling coping (N=3500) Low High Waiting and avoiding coping (N=3473) Low High Palliative coping (N=3472) Low High Social support coping (N=3490) Low High Family situation (N=3510) Couple without children Parents with children living elsewhere Parents with children at home People living alone Profession (N=3597) Low blue High blue Low white High white Other
% 50.2 49.8 27.4 32.8 35.2 4.6 48.5 36.8 14.7 68.3 31.7 63.1 36.9 36.1 63.9 64.8 35.2 58.1 41.9 17.0 83.0 67.8 32.2 60.1 39.9 47.9 52.1 13.1 42.9 37.0 7.0 15.4 16.6 14.1 21.9 32.0
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& Van Dierendonck, 1992). Four coping styles can be distinguished: `active', `social support seeking', `avoiding', and `palliative' (Komproe, Rijken, Ros, Winnubst & t'Hart, 1997) (Cronbach's a 0.64, 0.84, 0.44, and 0.82 respectively). For each coping style a dichotomous score was calculated. 2.3. Analysis A correlation matrix for all variables, separately for the no morbidity and unimorbidity group and for the multimorbidity group, allows a quick look at dierences in magnitude and direction of bivariate correlations. Simple logistic regression resulted in crude odds ratios (OR) with their 95% con®dence interval (95% CI) for the relations between each of patients characteristics and each of the HLOC scales as the dependent variable (dichotomous). Also, simple logistic regression analysis was used to establish the crude relations between each of the HLOC scales (continuous) and morbidity and multimorbidity as the dependent variables respectively. Multivariate logistic regression analysis was used to study the independent in¯uence of each HLOC scale (continuous) on the presence or absence of morbidity and multimorbidity respectively, adjusted for a number of covariables (sex, age, education, profession, family situation and coping styles). The method permits adjustment for any confounding or modifying eects by the covariables, as well as for interaction between the independent variable and the covariables. 3. Results The relation between all variables was examined using a correlation matrix that is presented in Table 2. Men scored signi®cantly higher compared to women on both the internal and external locus (P<0.001, Table 3). The dierences, however, were very small (mean dierence internal locus=0.15 and external locus=0.20). There was no signi®cant dierence between the two sexes on the chance locus. Increasing age was related to a lower score on the internal locus and a higher score on the external locus and the chance locus. A higher educational level implied a higher score on the internal and a lower score on the external and chance locus. The higher the professional status, the lower people scored on external locus. There was no signi®cant dierence between people without children (singles and couples), people with children living at home and people with children who live on their own with respect to the HLOC. People who scored high on the coping style `Active tackling' had a signi®cantly higher score on the internal locus and a signi®cantly lower one on the external and chance locus compared to people who scored low on this coping style. People with high scores on the coping style `Waiting and avoiding' scored signi®cantly higher on the external locus and on the chance locus compared to people with a low score on this coping style. The group with a high score on the `Palliative coping style' scored signi®cantly higher on the internal locus and on the chance locus compared to people scoring low on this coping style. A high score on the `Seeking social support' coping style was related to a signi®cantly lower score on the external and chance locus.
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Active tackling Active tackling Waiting and avoiding Social support Palliative Sex Age category Educational level Profession Family situation External locus Internal locus Chance locus a
1.000 0.003 0.231** 0.165** 0.008 0.098* 0.185** 0.035 0.017 0.091** 0.045* 0.096**
Waiting and Social avoiding support 0.073** 1.000 0.034 0.143** 0.018 0.112** 0.096** 0.018 0.035 0.130** 0.019 0.113**
0.213** 0.031 1.000 0.159** 0.165** 0.147** 0.138** 0.030 0.031 0.064** 0.012 0.062**
Palliative Sex 0.103** 0.145** 0.102** 1.000 0.031 0.011 0.045* 0.011 0.041 0.010 0.037 0.020
0.010 0.074** 0.165** 0.063* 1.000 0.012 0.065** 0.106** 0.058** 0.041 0.086** 0.019
Age Educational Profession Family External Internal category level situation locus locus 0.161** 0.152** 0.130** 0.090** 0.090** 1.000 0.244** 0.197** 0.047** 0.355** 0.101** 0.138**
0.204** 0.113** 0.065* 0.057* 0.090** 0.117** 1.000 0.051* 0.040* 0.261** 0.049* 0.127**
0.034 0.082** 0.002 0.033 0.172** 0.226** 0.094** 1.000 0.015 0.055* 0.001 0.028
Note: *Correlation signi®cant at the 0.05 level (2-tailed); **correlation signi®cant at the 0.01 level (2-tailed).
0.098** 0.119** 0.052 0.004 0.136** 0.021 0.047 0.060* 1.000 0.064** 0.025 0.006
0.095** 0.101** 0.048 0.051 0.098** 0.314** 0.218** 0.088** 0.003 1.000 0.075** 0.219**
0.062* 0.022 0.024 0.060* 0.028 0.083** 0.024 0.041 0.035 0.061* 1.000 0.008
Chance locus 0.065* 0.083* 0.039 0.013 0.090** 0.052 0.082** 0.039 0.101** 0.238** 0.016 1.000
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Table 2 Correlation matrix responders with multimorbidity (upper right part) and responders without multimorbidity (lower left part)a
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Table 3 The relation between patient characteristics and HLOC. Reported are odds ratios (OR) and their 95% CI Internal
Sex Male Female Age 20±39 40±59 60±79 >80 Education Low Average High Profession Low blue High blue Low white High white Other Family situation Couple without children Parents with children living elsewhere Parents with children at home People living alone Coping styles Seeking social support + Palliative coping style + Active tackling + Waiting and avoiding +
External
Chance
OR
95% CI
OR
95% CI
OR
95% CI
1.00 0.77
0.69±0.88
1.00 0.77
0.67±0.88
1.00 1.06
0.93±1.21
1.00 0.84 0.57 0.59
0.70±1.00 0.47±0.67 0.40±0.86
1.00 2.04 7.23 7.59
1.65±2.51 5.98±8.87 5.13±11.24
1.00 1.54 2.22 3.62
1.29±1.83 1.86±2.65 2.46±5.32
1.00 1.13 1.35
0.98±1.32 1.10±1.66
1.00 0.39 0.22
0.34±0.46 0.17±0.28
1.00 0.62 0.45
0.54±0.72 0.36±0.55
1.00 1.09 1.00 1.16 0.90
0.85±1.40 0.78±1.30 0.92±1.46 0.72±1.12
1.00 1.38 0.60 0.56 1.18
1.08±1.77 0.46±0.78 0.44±0.71 0.95±1.47
1.00 1.42 0.95 0.83 1.30
1.11±1.81 0.74±1.23 0.66±1.05 1.05±1.61
1.00 0.66 0.99 0.91
0.55±0.81 0.81±1.20 0.66±1.26
1.00 3.08 1.04 1.20
2.51±3.79 0.84±1.29 0.86±1.69
1.00 1.73 1.12 1.06
1.43±2.10 0.93±1.37 0.78±1.46
1.00 1.00
0.87±1.15
1.00 0.80
0.69±0.92
1.00 0.88
0.76±1.00
1.00 1.22
1.06±1.41
1.00 1.10
0.95±1.27
1.00 1.19
1.04±1.37
1.00 1.34
1.11±1.60
1.00 0.60
0.50±0.72
1.00 0.72
0.60±0.86
1.00 0.99
0.86±1.15
1.00 1.73
1.49±2.00
1.00 1.58
1.36±1.82
The occurrence of new morbidity in the selection period was related to a lower score on the internal locus of control and a higher score on the external locus of control, not to the chance locus of control. These eects showed both in the crude and adjusted analyses. People with multimorbidity (cases) scored signi®cantly lower on the internal locus compared to people without multimorbidity (controls) (P<0.001), and signi®cantly higher on the external (P<0.001) and the chance (P<0.05) locus (Table 4).
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Table 4 Relation between morbidity and multimorbidity and HLOC, crude as well as adjusted for sex, age, education, profession, family situation and coping styles; odds ratios (and their 95% C.I) are reported
Internal External Chance
Morbidity crude
Morbidity adjusted
Multimorbidity crude
Multimorbidity adjusted
0.82 (0.75±0.88) 1.28 (1.17±1.34) 1.07 (0.99±1.15)
0.84 (0.77±0.92) 1.11 (1.02±1.21) 0.99 (0.91±1.07)
0.76 (0.70±0.83) 1.39 (1.30±1.49) 1.12 (1.04±1.20)
0.80 (0.74±0.88) 1.19 (1.09±1.29) 1.00 (0.92±1.09)
The adjusted odds ratio of the internal locus for people with multimorbidity compared to people without multimorbidity was 0.80 (95% CI: 0.74±0.88) (Table 4), for the external locus the adjusted odds ratio was 1.19 (95% CI: 1.09±1.29). There was no signi®cant relation between multimorbidity and the chance locus after adjustment (Table 4). In general, the adjusted odds ratios are smaller compared to the crude odds ratios. 4. Discussion This study focused on possible determinants of HLOC and the relation between HLOC and multimorbidity. Our results are in line with Furnham and Kirkcaldy (1997), showing that men scored higher on both the internal and external locus of control compared to women. We found a more important in¯uence of age, however, that was both statistically signi®cant and consistent for all age groups. Based on the literature we expected socio-economic status to be positively related to the internal locus and negatively to the external and chance locus. Using educational level as an indicator, this was con®rmed in our study. The professional status, however, did not show such strong and consistent relations. An explanation could be that the ®ve categories of professional status are not on an ordinal scale. The relation between the three HLOC scales and multimorbidity are signi®cant and reasonably strong at crude data analysis. After adjustment, however, the negative relation with the internal locus and the positive relation with the external locus were somewhat weaker, the adjusted odds ratio for chance was not statistically signi®cant. This is not surprising in view of the relations between the HLOC and the other patient characteristics. It is remarkable that we found similar, but weaker, relations for morbidity. It is not yet clear whether locus of control is a cause or a consequence of morbidity and multimorbidity and it is not possible to determine this using a cross-sectional study design. Possibly, illness in¯uences patients' beliefs regarding their own attribution to and control of health. On the other hand, it is plausible that the HLOC in¯uences the lifestyle of people and hence may (partially) be the cause of health or illness. Also, an indirect in¯uence of HLOC on health is possible, e.g. via stress, coping and/or immunological pathways. To investigate the direction of the association, one should prospectively follow a large group of healthy people. After a number of years cases with morbidity and cases with multimorbidity could be compared to each other as well as to healthy subjects regarding their scores on the
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HLOC. Furthermore, HLOC before and after the occurrence of morbidity/multimorbidity could be compared. This would indicate the direction of the relation. Such a study has been started as a result of this analysis. References De Valck, C., & Vinck, J. (1996). Health locus of control and quality of life in lung cancer patients. Patient Education and Counseling, 28, 179±186. Dupen, F., Higginbotham, N., Francis, L., Cruickshank, D., & Gibson, P. (1996). Validation of a new multidimensional health locus of control scale (from C) in asthma research. Psychol. Health, 11, 493±504. Feij, J., van Kampen, D., Doorn, C. D., Resing, W. C. M., & van den Berg, P. T. (1990). De relatie tussen ingrijpende gebeurtenissen, coping-stijlen en klachten [The relation between life events, coping styles and complaints]. Gezondheid en Gedrag, 18(4/5), 182±196. Furnham, A., & Kirkcaldy, B. (1997). Age and sex dierences in health beliefs and behaviors. Psychol. Reports, 80, 63±66. Gustafsson, M., & Gaston-Johansson, F. (1996). Pain intensity and health locus of control: a comparison of patients with ®bromyalgia syndrome and rheumatoid arthritis. Patient Education and Counseling, 29, 179±188. Halfens, R. (1995). Eect of hospital stay on health locus of control beliefs. Western Journal of Nursing Research, 17(2), 156±167. Halfens, R., & Philipsen, H. (1988). Een gezondheidsspeci®eke beheersingsorieÈntatieschaal. Betrouwbaarheid en validiteit van de MHLC [A health locus of control scale. Reliability and validity of the MHLC]. TSG, 66, 399±403. HaÈrkaÈpaÈaÈ, K., JaÈrvikoski, A., Mellin, G., Hurri, H., & Luoma, J. (1991). Health locus of control beliefs and psychological distress as predictors for treatment outcome in low-back pain patients: results of a 3-months follow-up of a controlled intervention study. Pain, 46, 35±41. Komproe, I., Rijken, M., Ros, W. J. G., Winnubst, J. A. M., & 't Hart, H. (1997). Available support and received support: dierent eects under stressful circumstances. Journal of Social and Personal Relationships, 14(1), 59±77. Lamberts, H., & Wood, M. (1987). International classi®cation of primary care. Oxford: Oxford University Press. Levenson, H. (1981). Dierentiating among internality, powerful others, and chance. In H. M. Lefcourt, Research with the locus of control construct, Vol. 1 (pp. 15±63). Academic Press. Metsemakers, J., HoÈppener, P., Knottnerus, J., & Limonard, C. B. G. (1992). Computerized health information in the Netherlands: a registration network of family practices. Br. J. Gen. Pract., 42(356), 102±106. Norman, P., Bennett, P., Smith, C., & Murphy, S. (1997). Health locus of control and leisure-time exercise. Person. Individ. Di., 23(5), 769±774. Sanderman, R., & Ormel, J. (1992). De Utrechtse Coping Lijst (UCL): validiteit en betrouwbaarheid [The Utrecht Coping List (UCL): validity and reliability]. Gedrag en Gezondheid, 20(1), 32±37. Schaufeli, W., & Van Dierendonck, D. (1992). De betrouwbaarheid en validiteit van de Utrechtse Coping Lijst. Een longitudinaal onderzoek bij schoolverlaters [The reliability and validity of the Utrecht Coping List. A longitudinal study among schoolleavers]. Gedrag en Gezondheid, 20(1), 38±45. Talbot, F., Nouwen, A., & Gauthier, J. (1996). Is health locus of control a 3-factor or a 2-factor construct? J. Clin. Psychol., 52(5), 559±568. Van den Akker, M., Buntinx, F., Metsemakers, J. F. M., & Knottnerus, J. A. (1998). Morbidity in responders and nonresponders in a register-based population survey. Fam. Pract., 15(3), 261±263. Van den Akker, M., Buntinx, F., Metsemakers, J. F. M., & Knottnerus, J. A. (2000). Marginal impact of psycho-social factors on multimorbidity: results of an explorative nested case-control study. Soc. Sci. Med., 50, 1679±1693. Wallhagen, M., Strawbridge, W. J., Kaplan, G. A., & Cohen, R. D. (1994). Impact of internal health locus of control on health outcomes for older men and women: a longitudinal perspective. Gerontologist, 34(3), 299±306. Wallston, B., & Wallston, K. A. (1981). Health locus of control scales. In H. M. Lefcourt, Research with the Locus of Control Construct: Vol. 1 Assessment methods. New York: Academic Press. Wallston, K., Wallston, B. S., & DeVellis, R. (1978). Development of the Multidimensional Health Locus of Control Scales (MHLC). Health Education Monographs, 6, 160±171. Wallston, K. (1992). Hocus-pocus, the focus isn't strictly on locus: Rotter's social learning theory modi®ed for health. Cognitive Therapy and Research, 16(2), 183±199.