Psychosocial work characteristics and perceived ...

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Journal of Occupational Health Psychology 2001, Vol. 6, No. 3, 171-181

Psychosocial work characteristics and perceived control in relation to cardiovascular rewind at night Renate Rau University, Sweden

Anastasia Georgiades and Mats Fredrikson Stockholm Uppsala University, Sweden Carola Lemne and Ulf de Faire Karolinska Institute Stockholm, Sweden

This study examined the effects of psychosocial work characteristics on cardiovascular rewind at night. Ambulatory 24-hour recordings of blood pressure (BP) and heart rate (HR) of 75 borderline hypertensive and 74 normotensive men were related to diary ratings of perceived control (PC), and to scores of psychological demand (P), control (C), and social support (S) at work determined by an occupational classification system. Multiplicative interaction terms for job strain (P x C), isostrain (P x C x S) and job strain x perceived control (P x C x PC) were calculated. The interaction between P x C x PC predicted diastolic BP at night, but not at work. A delayed latency to attain the lowest systolic BP during the night was found for jobs with high job strain and isostrain. Low perceived control and social support were associated with higher HR at work and at night. A logistic regression analysis indicated that the interaction between P x C x PC, and the bodymass index were independently associated with borderline hypertension.

Classification according to the Karasek model The job demand/decision latitude model proposed by Karasek and co-workers (Karasek, 1979; Karasek & Theorell, 1990; Karasek et al., 1998) has influenced the study of work related determinants of cardiovascular disease. This model states that work related stress or ‘job strain’ occurs when job demands are high and decision latitude is low. Since methods have become available for ambulatory monitoring of physiological changes, such as blood pressure and heart rate, a growing number of studies include monitoring of cardiovascular changes over 24 hours, including times at work, leisure and sleep. If job strain plays a role in the development of sustained hypertension, it should be possible to demonstrate that job strain can cause a rise in blood pressure not only during work but also during ________________________________________ Renate Rau, guest researcher at the Departments of Biopsychology and of Work and Organizational Psychology, Stockholm University; Anastasia Georgiades (now at Duke Medical School, North Carolina) and Mats Fredrikson, Department of Psychology, Uppsala University; Carola Lemne and Ulf de Faire, Department of Epidemiology, Karolinska Institute Stockholm. The study was supported in part by grants from the Bank of Sweden Tercentenary Foundation and the Deutsche Forschungsgemeinschaft (RA 745/1-1). Correspondence concerning this article should be addressed to Renate Rau, who is now at the University of Technology, Dresden, Faculty of Natural Sciences and Mathematics, Department of Work and Organizational Psychology, Mommsenstraße 13, 01062 Dresden, Germany. Electronic mail may be sent to [email protected].

leisure time and at night. However, studies analysing the effect of high strain on physiological changes during leisure time and at night have come to different and partly contradictory results. Data reported by Theorell, de Faire et al. (1991), Gellman, Massie & Spitzer (1990), Pickering, Schnall et al. (1991) and Fox, Dwyer & Ganster (1993) indicate that sympathetic nervous system activity may increase at work in high strain jobs and remain elevated at night, thus hampering rewind. Rewind was defined by mean blood pressure and mean heart rate at rest after work. In borderline hypertensives, Theorell, de Faire et al. (1991) did not find an association between job strain and systolic blood pressure, while diastolic blood pressure was elevated at work and during sleep in those with high job strain occupations. The effect of the exposure to job strain on ambulatory blood pressure was investigated in a three-year follow-up study by Schnall et al. (1998). Using 24-hour ambulatory blood pressure monitoring on two occasions 3 years apart, they found that the group with high job strain at both baseline and follow-up had higher systolic (11 mmHg) and diastolic (7 mmHg) blood pressure at work and at home as compared to the group that did not have high job strain at either assessment. On the other hand, in longitudinal studies by Theorell, Knox, Svensson, and Waller (1985), Theorell et al. (1988) and Landsbergis et al. (1994), the exposure to high job strain was associated with elevated ambulatory systolic blood pressure at work but not during leisure time. An explanation for the differing results regard-

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ing to the relationship between job strain and cardiovascular activity during the time after work may be the relatively undifferentiated use of the labels ‘lei sure time’ and ‘time at home’. There are also results contrary to Karasek’s job demand/decision latitude model. For example, Fletcher and Jones (1993) and Rau (1996) found lowered systolic blood pressure in individuals with high job demands. However, the interaction between decision latitude and job demand had no effect on blood pressure, which is central to the Karasek model (Karasek & Theorell, 1990). Furthermore, Schaubroeck & Merrit (1997) reported that neither the variables job demand or control used separately, nor the interaction between the two, were predictive of blood pressure in a regression analysis. However, after calculating a three-way interaction between job demand, control and self-efficacy, they found highly significant effects on systolic and diastolic blood pressure.

Social support at work The job demand/decision latitude model has been supplemented with a factorlabeled ‘work related social support’ (Johnson & Hall, 1988). The combination of job strain and low social support has been labeled ‘isolated high strain’. Two long term casecontrol studies have been published, one over a period of 9 years by Johnson, Hall & Theorell (1989) and the other over a period of 3 years by Hammar, Alfredsson & Johnson (1998). They reported that cardiovascular disease and mortality in male employees was significantly associated with isolated high strain. In addition, ambulatory systolic blood pressure at work and at home and the risk of hypertension was associated with isolated high strain in male employees (Landsbergis et al., 1994). A direct impact of social support on systolic blood pressure was reported by Theorell (1992). In a long term study over 4 months, Theorell showed that variations in social support at work were associated with variations in mean systolic blood pressure during a working day. During periods of poor social support the systolic blood pressure was higher and vice versa. Unden, Orth-Gomer & Elofsson (1991) also reported higher systolic blood pressure values in individuals with low social support as compared to individuals with high social support. However, the result was based on one measurement of blood pressure in a supine position after only 5 minutes of rest. In addition, Unden, OrthGomer, and Elofsson (1991) observed that poor social support at work was associated with a heightened heart rate throughout the day and night. Theorell and

Karasek (1996) suggested that this reflects the activation of the sympathoadrenal system by feelings of loneliness.

Perceived control In addition to work strain and social support, the development of hypertension and coronary heart disease might also be affected by perceived control at work. While decision latitude is defined independently of individual perceptions, perceived control reflects the subjective experience of control. Ganster (1989, p. 3) defined control as the individual’s “...ability to exert some influence over one’s environment, so that the environment becomes more rewarding or less threatening”. A perceived lack of control affects the individual’s beliefs about his/her ability to cope effectively with the larger environment (Glass & Mcknight, 1996). Gerin et al. (1992) suggested that low perceived control is related to increased perceptions of stress. Low control has been associated with elevated blood pressure and heart rate as compared to situations with high control (Gerin et al., 1995) and also with delayed recovery (Dienstbier, 1989; Haynes et al., 1991). The aim of the present study was to explore the relationship between job strain and changes in blood pressure and heart rate during work and during sleep (following an ordinary work day). The following hypotheses were tested: ‘Strain hypothesis’ H 1: Occupations with high psychological demand and low control (defined as high job strain occupations), are associated with elevated heart rate and blood pressure at work. As a consequence, heart rate and blood pressure will remain elevated throughout the night; in other words, job strain will lead to a slower rewind of heart rate and blood pressure levels during sleep. ‘Perceived control-strain hypothesis’ H 2: High perceived control will buffer the negative effects of job strain on blood pressure and heart rate during work and at night. ‘Isostrain hypothesis’ H 3: The combination of job strain and low social support which is described as ‘isostrain’ by Johnson, Hall & Theorell (1989) will strengthen the elevation of blood pressure and heart rate, and delay the rewind of blood pressure and heart rate during the night. Hypothesis H 4: If job strain plays a role in the development of sustained hypertension, it should be possible to demonstrate that level of job strain predicts blood pressure status.

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Method Participants Analyses were performed using data from 149 participants identified in a blood pressure screening program started in 1985 (Georgiades et al., 1996). All men aged between 35 and 55 years in the small town of Akersberga, north of Stockholm were asked by mail to visit the primary health center to have their blood pressure measured. Of a total sample of 2694 men, 193 were found to have borderline hypertension, defined as a supineDBP of 85 to 94 mm Hg measured on at least two separate occasions. Of the 193, 170 agreed to participate and signed written consent forms to that effect. The participants had yearly checkups DBP within the borderline range and 75 of these participated in the present study together with 74 age-matched control participants from the original population who had aDBP less than or equal to 80 mm Hg. The blood pressure of control participants was measured on two occasions a few weeks apart, both at the initial screening and before entering this study (for further details see Lemne et al., 1994 and Georgiades, 1997).

Occupational Classification Characteristics of individual work setting and the occupation of each subject were determined by means of questions regarding work tasks and job titles. The answers were analysed using the occupational group based classification system of Johnson et al. (1990). This system is based on 12 084 randomly selected, employed Swedish citizens aged between 25 and 74 years interviewed about their work conditions. The classification system consists of the following three psychosocial work dimensions: psychological demands (“Is your job hectic?” and “Is your job psychologically demanding?”); control (12 questions about influence over a number of factors at work, such as planning, selection of supervisor, setting of work pace, planning vacations, flexibility of work hours, and possibility of learning new things and experiencing personal fulfilment); and social support (4 questions regarding the possibility of interacting with co-workers and habits of seeing colleagues outside work). In addition, there are two physical work dimensions: physical job demands (5 questions about unsuitable work postures, heavy lifting, perspiration, dirtiness and accident risk); and hazardous work (7 questions about noise, vibration, cold, draft, ventilation, lighting). All of the scales were standardized in such a way that the scores ranged from 0 to 10.

Procedure All participants were tested for 24 hours during a normal working day. Both the borderline hypertensive group and the normotensive group performed their regular work for eight hours, with leisure time in the afternoon and the evening followed by sleep. Participants arrived at the labo-

ratory between 9 and 10 am. The ambulatory equipment was put on and then they were given instructions for blood pressure reading (keep the arm as motionless as possible) and answering diary questions. After a laboratory test (not presented in this paper), participants were dismissed.

Recording of setting and perceived control At each measurement, the participants were asked to record their location (e.g. at home, at work, in the garden etc.), position (standing, sitting, lying), and activity (e.g. reading, repairing something, doing the housework etc.) in a diary. In addition, participants repeatedly reported their level of perceived control in a diary during the whole day until going to bed. The Perceived Control dimension was rated on a nine-point scale from ‘not at all’ to ‘completely’.

Recording of cardiovascular activity SBP, DBP and HR were recorded using an ambulatory monitoring system (Pressurometer-IV, model 1990, Del Mar Avionics). Blood pressure readings were taken by the Korotkoff method. A microphone was placed over the brachial artery of the left arm under the blood pressure cuff. The blood pressure monitor was programmed to take blood pressure and HR (in beats per minute [bpm]) every 15 minutes throughout 24 hours. The 24 hour data was stored in a memory unit and then transferred to a computer that constructed an individual data file. Artifacts (defined as any of the following: SBP < 50 mmHg, SBP > 250 mmHg, DBP > SBP, DBP < 30 mmHg, DBP > 150 mmHg and HR < 40 bpm) were excluded. The 24 hour period consisted of all measurements taken during 24 hours, but with the laboratory measurements excluded. Posture (supine, sitting, standing) and levels of physical activity have a strong influence on ambulatory blood pressure and heart rate (Pickering, 1991). In order to ensure the comparability between work and home data, all analyses are based on data recorded during sitting or lying, and excluding high levels of physical activity. Because not all participants worked in the sitting position, the sample size for recordings at work is smaller (n = 81) than for home (n = 104).

Statistical Analyses Working hours as well as night-time sleeping hours were defined by the participants’ diary entries. The first three hours of sleep during the night (12 readings of blood pressure and heart rate) were defined as the recovery period. Data from the recovery period were required to be complete without any missing readings. All readings for SBP and DBP and for HR within each period of time (work, night and recovery period during the night) were averaged to represent that period. In addition, the lowest blood pressure and HR level (lowest value) recorded during the night as well as the time to reach the lowest level (latency period) were analysed. Hierarchical linear regression analyses were generated to examine if occupational categorization of psychological

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Journal of Occupational Health Psychology 2001, Vol. 6, No. 3, 171-181 demand, control, social support at work and diary-rated perceived control at work predicted the mean blood pressure and the heart rate levels at work as well as at night. The effects of the variables age and bodymass index were controlled for by including them in the first block of the hierarchical linear regression analyses. Bodymass index was calculated as weight (in kilogram) / length (in meters)2. Physical activity is an important determinant of ambulatory blood pressure and heart rate levels (Pickering, 1993), and therefore block 2 exclusively contained physical job demands at work. In block 3, the main effects of psychological demand, control, social support, and perceived control at work were entered. The two-way product terms, i.e. psychological demand x control (defined as ‘job strain’), perceived control x social support, were entered in block 4, while block 5 contained the three-way product terms, i.e. psychological demand x control x social support (defined as ‘isostrain’) and psychological demand x control x perceived control. The product terms were constructed by rescoring the scales so that a high score represented an adverse condition. The raw values of psychological demand, control, social support and perceived control were transformed into z-scores (resulting in a mean value of zero and a standard deviation of one). Before calculating the product terms, a constant had to be added in order to avoid negative values. As a result, the two-way product term ‘job strain’ is high if psychological demand is high and control is low, while the three-way product term ‘isostrain’ is high if psychological demand is high and control and social support are low. Each block of the hierarchical regression analyses was based on the forward method. Thus, only the variables with a significant utility for the dependent variable in each block remained in the equation. Prediction of blood pressure status was assessed using stepwise forward logistic regression analysis (method: forward Wald). The variables included in the logistic regression analyses were the same as described above for the hierarchical regression analyses. Between-group differences were performed to assess the relations between blood pressure status (normotensive versus borderline hypertensive) and biological variables (age, bodymass index, family history of cardiovascular disease) as well as psychosocial work characteristics. Between-group differences for continuous variables were assessed using two-sample t-tests and for discrete variables using chi-squared tests. Two-way analyses of variance (ANOVA) were performed on SBP and DBP, and heart rate to study the effect of blood pressure status on mean blood pressure and heart rate levels at work as well as during the night. To evaluate rewind, each of the 12 night values of the recovery period were subjected to a repeatedmeasures multivariate analysis of variance (MANOVA) including SBP and DBP and heart rate. All ANOVAs included the participants’ age, bodymass index and the physical job demands as covariates.

All psychosocial work characteristics were correlated with each other (see Table 1). There were significant associations between the variables psychological demand, control and physical job demand. These correlations can indicate collinearity and must be considered in the discussion of the results.

Results Prediction of cardiovascular response at work and at night Heart rate levels Results of the hierarchical linear regression analyses for the prediction of HR are shown in Table 2. Neither age, bodymass index (block 1) nor physical job demands (block 2) had any significant effect on HR during work time or night time. In block 3 (occupationally classified psychological demands, control, and social support as well as diaryrated perceived control), the variables perceived control and social support significantly predicted HR during work (R2 = .15), during the recovery period

(R2 = .17) and during the night (R2 = .11). In addition, HR during the night was significantly predicted in block 4 by the two-way product of perceived control and social support (R2 = .16). There were no further significant interaction effects in blocks 4 or 5. The lowest HR and the latency time to attain the lowest HR level during sleep were not predicted by any of the tested variables. Blood pressure levels

Results of the regression analyses for the prediction of blood pressure levels are shown in Table 3 for SBP and Table 4 for DBP. From the variables of the first block, SBP at work was only predicted by bodymass index (ÄR2 = .09), whereas SBP during the night (ÄR2 = .13) and during the recovery period (ÄR2 = .13), as well as the lowest SBP (ÄR2 = .06), were only predicted by age. In the second block, physi cal job demand was entered. This block was highly predictive of systolic blood pressure during work, night time, and recovery period (work: ÄR2 = .09, R2 = .18; night: Ä R2 = .07, R2 = .20; recovery: ÄR2 = .10, R2 = .23). No other block of variables predicted SBP. However, the latency to attain the lowest systolic blood pressure was significantly predicted by the variable social support entered in the third block (ÄR2 = .06), by ‘job strain’ entered in the fourth block (ÄR2 = .05), as well as by ‘isostrain’ entered in the fifth block (ÄR2 =.06, R2=.17).

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Table 1 Intercorrelations Between Scales of the Occupational Job Index, and Relationship Between these Scales and Perceived Control at Work Scale

1

2

3

4

5

1. psychological demand -.628*** .335*** -.504*** .088 2. control -.095 -.766*** .033 3. social support -.053 -.134 4. physical job demand --.153 5. perceived control at work -Note. N = 104; *** p < .001; Presented are the Spearman rank correlation coefficients. Table 2 Results of the Hierarchical Regression Analyses for Predicting Heart Rate (HR) HR

Variable

ÄR2

R2

B

B’

at work Block 1-2 Block 3 Step 1 Step 2 Block 4-5

no variable significantly associated perceived control (PC) social support (S) no variable significantly associated

.10 .05

.10 -1.58** -1.69** .15 -3.22*

recovery Block 1-2 period Block 3 Step 1 Step 2 Block 4-5

no variable significantly associated perceived control (PC) social support (S) no variable significantly associated

.10 .07

.10 .17

-1.41**

Block 1-2 Block 3 Step 1 Step 2 Block 4 Step 3 Block 5

no variable significantly associated perceived control (PC) social support (S) PC x S no variable significantly associated

.05 .06 .05

.05 -0.82* .11 -2.40* .16 -2.61*

-13.38* -35.25*

Block 1-5

no variable significantly associated

at night

lowest value

latency Block 1-5 no variable significantly associated period Note. N = 81; * p < .05; ** p < .01; Only significant variables are presented. B = unstandardized beta-coefficient at the current step B’ = unstandardized beta-coefficient at the highest significant step DBP during work time was also significantly predicted by bodymass index entered in the first block (ÄR2 = .08), and by physical job demand entered in the second block (ÄR2 = .05). In the third block, the main effects of psychological demand, control, social support and perceived control were entered. Only the variable perceived control predicted DBP at work (ÄR2 = .05, R2 = .19). No further variables predicted DBP during work time. Age and bodymass index (the variables of the first block) did not predict any nocturnal DBP measurements. Physical job demand (block 2) signifi-

cantly predicted DBP during the recovery period (ÄR2 = .09) and during the night (ÄR2 = .08). None of the main effects entered in the third block or the two-way product terms entered in block 4 were significantly associated with DBP during the recovery period or night time. However, the three-way product term ‘psychological demand x control x perceived control’ was significantly associated with DBP during the recovery period (ÄR2 = .08, R2 = .16) and during the night (ÄR2 = .06, R2 = .13). The lowest DBP obtained during the night was significantly predicted by physical job demands

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(block 2 with ÄR2 = .07) and by the variables of the third block, psychological demand (ÄR2 = .05) and social support (ÄR2 = .09, R2 = .22).

The third block exclusively predicted the latency to attain the lowest DBP level. Within this block, only the variable psychological demand was significantly associated with the latency (R2 = .07).

Table 3 Results of the Hierarchical Regression Analyses for Predicting Systolic Blood Pressure (SBP) ÄR2

R2

at work Block 1 Step 1 bodymass Index Block 2 Step 2 physical job demand Block 3-5 no variable significantly associated

.09 .09

.09 1.60** .18 2.38**

recovery Block 1 Step 1 age period Block 2 Step 2 physical job demand Block 3-5 no variable significantly associated

.13 .10

.13 -0.69** -0.63** .23 1.79**

at night

Block 1 Step 1 age Block 2 Step 2 physical job demand Block 3-5 Step 3 no variable significantly associated

.13 .07

.13 -0.69** -0.64** .20 1.54*

lowest value

Block 1 Step 1 age Block 2-5 no variable significantly associated

.06

.06 -.050*

Variable

SBP

latency period

B

Block 1-2 no variable significantly associated Block 3 Step 1 social support .06 .06 -3.79* Block 4 Step 2 job strain (P x C) .05 .11 0.30* Block 5 Step 3 isostrain (P x C x S) .06 .17 0.27* Note. Only significant variables are presented. N = 81; * p < .05; ** p < .01; P = psychological demand; C = control; S = social support B = unstandardized beta-coefficient at the current step B’ = unstandardized beta-coefficient at the highest significant step

Blood pressure status Age, bodymass index, and psychosocial work characteristics of the normotensive and the borderline-hypertensive group are presented in Table 5, with the between-groups differences shown under the headings t for t-tests. The bodymass index in borderline hypertensives was significantly higher than in normotensives. However, age [t (104) = 0.46, ns] and family history of cardiovascular health diseases [÷2 (2, N = 96) = 2.64, ns, no information was available from 8 participants] did not differ between borderline hypertensives and normotensives. The jobs of borderline hypertensives were characterized by significantly higher physical job demands and lower control than the jobs of normotensives. At work, borderline hypertensives perceived significantly less control than normotensives. We performed two-way analyses of variance to study if blood pressure status affected mean blood

B’ 1.65**

29.91* -2.58*

pressure or HR during work hours and night time. SBP as well as DBP at work, during the whole night, and during the recovery period differed significantly between borderline hypertensives and normotensives, with higher values for borderline hypertensives than normotensives (F-values ranging between 17.45 and 6.98; ps < .0001 - .01). Neither a significant time effect nor another significant interaction between blood pressure status and decrease in blood pressure were observed for the twelve measurements during the recovery period. There was no significant difference between borderline hypertensives and normotensives in the time (latency) required to attain the lowest SBP [4 hours 17 minutes for borderline hypertensives and 3 hours 55 minutes for normotensives, F (1, 97) = 0.57, ns]. However, the lowest SBP in normotensives (87.8 mmHg) was significantly lower than for borderline hypertensives (93.7 mmHg) with F (1, 97) = 5.53 and p < .05. Normotensives attained their lowest DBP after 3 hours, while borderline hypertensives

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needed 3 hours and 42 minutes [F (1, 97) = 4.62, p < .05]. The lowest DBP attained was significantly higher in borderline hypertensives (54.9 mmHg) than in normotensives [49.6 mmHg; F (1, 97) = 5.26, p < .05]. HR recorded at work, at night and during recovery, as well as the lowest HR and HR latency, did not differ between borderline hypertensives and normotensives. Finally, binary logistic regression was used to identify variables associated with risk of borderline hypertension. Age and bodymass index, physical job demands, psychosocial work characteristics (psychological demand, control, social support) and

perceived control as well as the two-way and threeway interaction terms ‘psychological demand x control’ (strain), ‘perceived control x social support’, ‘psychological demand x control x social support’ (isostrain) and ‘psychological demand x control x perceived control’ were entered in the regression model. Table 6 shows the result of the stepwise binary logistic regression (method: forward Wald). Two factors were associated with borderline hypertension in the logistic regression analysis: the interaction of strain with perceived control at work, and the bodymass index. In detail, the -2 Log Likelihood (-2 L L) of the initial log likelihood function

Table 4: Results of the Hierarchical Regression Analyses for Predicting Diastolic Blood Pressure (DBP) ÄR2 R2

Variable

DBP

at work Block 1 Step 1 bodymass index Block 2 Step 2 physical job demand Block 3 Step 3 perceived control Block 4-5 no variable significantly associated recovery Block 1 Step 1 no variable significantly associated period Block 2 Step 2 physical job demand Block 3-4 no variable significantly associated Block 5 Step 3 P x C x PC at night

lowest value

Block 1 Step 1 no variable significantly associated Block 2 Step 2 physical job demand Block 3-4 no variable significantly associated Block 5 Step 3 P x C x PC Block 1 Block 2 Block 3 Block 4-5

Step 1 Step 2 Step 3 Step 4

no variable significantly associated physical job demand psychological demand social support no variable significantly associated

B

B’

.08 .08 1.00** 0.97** .05 .13 1.15* 1.01 .05 .19 -1.04*

.09 .09 1.35** 1.02* .08 .16 0.02** .08 .08 1.22*

0.95*

.06 .13 0.02* .07 .07 1.42* 2.57** .05 .12 1.86* 2.66** .09 .22 -4.21**

Block 1-2 no variable significantly associated Block 3 Step 1 psychological demand .07 .07 -1.38* Block 4-5 no variable significantly associated Note. Only significant variables are presented. N = 81; * p < .05; ** p < .01; P = psychological demand; C = control; PC = perceived control; B = unstandardized beta-coefficient at the current step; B’ = unstandardized beta-coefficient at the highest significant step latency period

was 111.91. After entering the three-way interaction term ‘strain x perceived control’ at the first step, the -2 Log Likelihood decreased. The chi-squared value of the model (and also of the first step) was highly significant (-2LL = 98.78, ÷2model = ÷2step = 13.13, p < .001). At step two, the bodymass index was entered in the model. This resulted in a further decrease of -2 Log Likelihood which was significant (-2LL =

93.67, ÷2model = 18.24, p < .0001; ÷2step = 5.11, p < .05). No further variables were entered in the regression model. Entering the three-way interaction term ‘strain x perceived control’ and bodymass index in the regression model, 38 out of 47 observed normoten sives (= 80.9 %) were correctly predicted, whereas 9 were falsely predicted. In contrast, out of 35 bor-

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derline hypertensives, 21 (= 60%) were correctly predicted and 14 falsely predicted. The overall percentage correctly predicted was 72 %. In contrast,

blind estimation of the most frequent category (that is normotension) for all cases would yield a correct percentage of 58.0 %.

Table 5 Age, Bodymass Index (BMI), and Occupational Characteristics as well as Perceived Control at Work of Normotensives (NT) and Borderline Hypertensives (BHT) NT (n = 54)

Variable

BHT (n = 50)

t - test

M

SD

M

SD

t

p

50.3 24.1

5.87 2.61

49.9 25.6

5.66 2.72

0.46 -2.76

.650 .007 **

physical job demand 2.5 1.70 3.2 1.87 psychological demand 5.3 1.41 4.9 1.54 control 6.1 1.23 5.4 1.45 social support 9.1 0.86 9.1 0.67 perceived control at work 7.6 1.63 6.4 2.40 Note. N = 104; *p < .05, two-tailed. **p < .01, two-tailed.

-2.06 1.31 2.80 -2.60 2.75

.042 * .194 .006 ** .795 .007 **

age (in years) BMI

Table 6 Wald Statistic to Test the Significance for Each of the Independent Variables in the Logistic Regressio n Model for Prediction Blood Pressure Status variables entered in the model P x C x PC bodymass index

B

SE

Wald

df

p

R

Exp(B)

.008 .213

.002 .098

10.96 4.72

1 1

*** *

.283 .156

1.008 1.027

Note. N = 104; * p < .05; *** p < .001. Dependent variable is the blood pressure status, which is coded 1 = borderline hypertensive, 0 = normotensive. The independent variables are age, bodymass index, physical job demand, psychological demand (P), control (C), social support (S), perceived control (PC), the two-way interaction terms P x C, and PC x S, the three-way interaction terms P x C x S and, P x C x PC.

Discussion Results from the present study show that selfrated perception of control during working hours is an important predictor of HR and DBP, not only during work, but also during night time. This corresponds partly with results from Melamed et al. (1998), who tested whether the responsivity of ambulatory blood pressure to work load is moderated by perceived job control (in 79 normotensive men). Melamed et al. observed a SBP response to increased work load only for workers with low perceived job control. Furthermore, low job control was independently associated with higher systolic ambulatory blood pressure. In contrast to the ‘strain hypothesis’ (H 1), there was no evidence that the interaction between psychological demands and control had any association with blood pressure or HR levels during work or night time. In addition, psychological demand, con-

trol and perceived control used as separate variables in the hierarchical regression analyses had no predictive power for blood pressure during night time. However, a three-way product term of strain and perceived control was predictive of DBP during recovery and night-time, but not during work. The higher the result of the multiplicative interaction term between job strain and perceived control, the higher the DBP during recovery and night time. Thus, the results support the hypothesis (H 2) that high perceived control may buffer the negative effects of job strain on blood pressure and HR. In addition to the effects of psychological demand and control, the effects of social support at work on cardiovascular activity and recovery were examined. Social support was related to HR levels, with high social support being associated with lower HR at work, at night and during recovery at night. These results are consistent with Unden,


Orth-Gomer & Elofsson (1991) who reported higher HRs in individuals with low social support at work even though their definition of social support differs slightly from ours. Lepore, Allen & Evans (1993) argue that social support decreases the appraisal of the stressor. Thus, if work is conceived as a stressor, high social support would attenuate the stress-response, possibly by reducing sympathetic drive. But since social support was also associated with a lower HR during recovery at night, acute stress might not be needed for social support to have cardiovascular buffering effects. On the other hand, social support at work could have protective effects extending into sleep due to lower work-related HR. Beside the buffering effects of social support for HR, there were also buffering effects for the lowest DBP values. The lowest DBP value during night time showed a downward tendency with increasing social support at work. Hypothesis H 3, that isostrain may lead to delayed cardiovascular recovery, was only supported by the latency to obtain the lowest SBP during night time. Hierarchical multiple regression analysis showed that social support, job strain and isostrain were independent predictors of SBP latency, supporting the strain hypothesis H 1 and the isostrain hypothesis H 3 for the night time values but not for work hours. Comparison between these results and other studies examining social support by adding it to the job strain model are difficult. There are only a few studies, and they do not include the night time period. The most comparable study was carried out by Landsbergis et al. (1994). They examined the impact of job strain and isostrain on ambulatory blood pressure and the risk of hypertension. Their results indicated that the risk of hypertension slightly increased when adding social support to the job strain model. Job strain as well as isostrain exhibited significant associations with SBP at work and at home. However, results of the Landsbergis’ study differ from our study since we found no relationship between the level of SBP and job strain or isostrain. The observation that the cardiovascular activity during work hours was not associated with job strain or isostrain is contrary to most published studies (Theorell, de Faire et al., 1991; Light, Turner & Hinderliter, 1992; Landsbergis et al., 1994; Cesana et al. 1996; Schnall et al., 1998; Laflamme et al., 1998; see also review article by Theorell & Karasek, 1996). Only a few previous studies support our results (Pieper, LaCroix & Karasek, 1989; Albright et al., 1992; Schaubroeck. & Merrit, 1997). One

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reason for the contrary findings could be the high intercorrelations between the job title scales. The high negative correlation between psychological demand and physical job demand limits the explanatory value of psychological demand in the regression model, since the influence of physical activity on the cardiovascular response is stronger than that of psychological demands (Pickering, 1991; van Egeren, 1991). Multiple regression analysis showed that the physical job demands were significantly associated with SBP and DBP during work and night, but not with the HR. This is surprising since all statistical data analyses in the present study were based on data recorded in the sitting or lying position and thus were not influenced by physical activity. It should be noted that physical job demands were classified according to occupational group based classification system (Johnson et al., 1990), whereas physical activity was defined from the diary. An explanation might be that the effects of physical job demands on blood pressure were transferred to the working time without direct physical activity (work in sitting position) and even to the night. The strong influence of the physical job demands on the blood pressure could cover the effects of the other tested variables. As expected, borderline hypertensives as compared to normotensives had higher SBP and DBP during work time and night time and displayed a delayed blood pressure recovery. Furthermore, the latency to attain the lowest DBP was longer for borderline hypertensives than normotensives. Additionally, borderline hypertensives had higher physical job demands, less control and less perceived control at work than normotensives. It is possible that the prevalence of borderline hypertension is higher in occupations with high physical job demand and low control. In addition, borderline hypertensives tended to experience less control at work. However, the high psychological demand/low control jobs could hide another important variable, namely social class. Individuals within low socioeconomic status groups are more likely to have high psychological demand/low control jobs than people within higher socio-economic status groups. It is well known that individuals with low socio-economic status are at higher risk of developing coronary heart disease (e.g. Albright et al., 1992, Pickering, 1999). Results from the logistic regression showed support for the hypothesis H 4, i.e. that level of job strain can predict blood pressure status. With the exception of bodymass index, blood pressure status


was only predicted by the three-way interaction between strain and perceived control (psychological demand x control x perceived control). Participants with high job strain had higher blood pressure or became borderline hypertensive, when they perceived less control at work. As already discussed above, the perception of control at work seems to play an important role in the relationship between work-related stress and cardiovascular responses. High perceived control at work may have a potentially beneficial effect, or alternatively, low perceived control may have a negative impact on the cardiovascular system. Gerin et al. (1995) showed that in the waking state, when effort is held constant, increased perceived control can attenuate car diovascular reactivity, suggesting that high levels of control can have a protective effect on the cardiovascular system, especially when an individual is under high levels of stress. In conclusion, the results of this study show that an interaction between high job strain (measured with an occupational inference system) and low perceived control leads to a slower rewind of DBP but not of SBP during the night. Furthermore, HR and blood pressure during work and at night were influenced by the variables ‘social support’ and ‘perceived control at work’. The factor job strain did not have an effect on blood pressure or HR at work. The finding that physical job demands were predictive of blood pressure during different periods of the whole working day indicates that there may be a carryover of the effects of the work environment with high physical job demands to the environment with low physical job demands and even to the night. Therefore, future studies should examine occupational populations with less or no physical job demands in order to obtain more ‘pure’ job strain effects.

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