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Psychosomatic Medicine 67:281-287 (2005)
© 2005 American Psychosomatic Society

ORIGINAL ARTICLES

Changes in Financial Strain Over Three Years, Ambulatory Blood Pressure, and Cortisol Responses to Awakening

Andrew Steptoe, DPhil, Lena Brydon, PhD and Sabine Kunz-Ebrecht, PhD

From the Department of Epidemiology and Public Health, University College London, London, United Kingdom.

Address correspondence and reprint requests to Andrew Steptoe, Department of Epidemiology and Public Health, University College London, 1–19 Torrington Place, London WC1E 6BT, United Kingdom. E-mail: a.steptoe{at}ucl.ac.uk


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Objective: Chronic psychosocial stress has been associated cross-sectionally with ambulatory blood pressure and with salivary cortisol, but there have been few longitudinal studies of the effects of changes in chronic stress. We assessed the influence of changes in financial strain on ambulatory blood pressure and salivary cortisol.

Methods: Data were analyzed from 160 men and women age 47 to 59 years at the first assessment (T1) who repeated ambulatory monitoring 3 years later (T2). We analyzed change in financial strain as a continuous variable, and specifically compared people who did and did not report an improvement in financial strain.

Results: Change in financial strain was associated with change in ambulatory systolic pressure after controlling for T1 ambulatory systolic pressure, gender, socioeconomic position, age, smoking, body mass index, and T1 financial strain (p = .041). Systolic pressure at T2 was lower in the improved financial strain (121.7 ± 11.2 mm Hg) than in the worse/no change group (125.5 ± 11.5 mm Hg; p = .029). The corresponding diastolic pressures averaged 78.5 ± 7.1 mm Hg and 80.7 ± 7.9 mm Hg, respectively (p = .061). The cortisol awakening response (difference between waking and 30 minutes later) was lower (p = .048) in men who reported improved financial strain, controlling for T1 cortisol response, socioeconomic position, age, smoking, time of waking, and T1 financial strain. There were no differences in the slope of cortisol decline over the day or in evening values.

Conclusion: These longitudinal data extend cross-sectional findings in showing associations between favorable changes in chronic stress and reduced cardiovascular and neuroendocrine activation in everyday life.

Key Words: ambulatory blood pressure • cortisol • chronic stress • financial strain

Abbreviations: CAR = cortisol awakening response; BMI = body mass index; SEP = socioeconomic position; CHD = coronary heart disease; CI = confidence interval.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Physiologicalmonitoring under the naturalistic conditions of everyday life is a powerful tool in the investigation of psychosocial influences on health. Two pivotal methods that have emerged over recent decades are ambulatory blood pressure monitoring and periodic cortisol sampling. Ambulatory blood pressure has been studied extensively in relation to chronic work stress. A review in 2000 identified 12 studies that documented cross-sectional associations between job strain (or its components high demands and low control) and ambulatory blood pressure recorded either during or after work (1). The literature concerning other chronic stressors is limited, but associations have been described between elevated ambulatory blood pressure and informal caregiving (2), combat-related posttraumatic stress disorder (3), and marital conflict (4).

Results for cortisol have been mixed, with no association with work stress being found in several studies using urinary measures (5,6). Salivary measures have allowed cortisol profiles over the day to be examined in more detail, and different components of circadian variation may be sensitive to chronic psychosocial stress. Cortisol levels are high early in the day, then decrease over the remainder of the day and evening. High levels of cortisol have been observed early in the morning but not at other times of day in people experiencing job strain (7), in informal caregivers (8), and in the adolescent offspring of mothers who have had postnatal depression (9). The cortisol awakening response (CAR) may be a particularly sensitive component, because the rise in cortisol over the first 15 to 45 minutes after waking up has been positively associated with self-reported general stress (10), job demands (11), overcommitment to work in men (12) and depressed mood (13). A low CAR has been reported in patients suffering from chronic fatigue syndrome (14) and from other health problems (15). Another component of the cortisol profile is the slope of decline over the day. A steeper decline has been associated with positive maternal relationships (16), whereas a flatter pattern has been observed in women with breast cancer (17) and in some studies of depression (18). Elevated levels of cortisol in the evening were recorded in one study of women undergoing divorce or separation (19), and were also positively associated with financial strain in a sample of long-term unemployed women, with a near significant effect in men (20).

These studies have all been cross-sectional. Potential confounding factors such as physical activity, smoking, body mass index (BMI), and socioeconomic position (SEP) have been controlled statistically. However, it is difficult to eliminate completely cofactors that might be associated both with stress exposure and physiological function, and the possibility of residual confounding remains. Longitudinal studies assessing changes in ambulatory blood pressure or cortisol in relation to changes in psychosocial strain are therefore valuable. Schnall et al. (21) described a 3-year follow-up of 195 men in relation to job strain. It was found that the subgroup who reported high job strain at baseline but not 3 years later showed significant decreases in ambulatory systolic and diastolic pressure at work and home after adjustment for age, BMI, smoking, and alcohol consumption. This suggests that an improvement in chronic stress led to a decline in ambulatory blood pressure. To our knowledge, no other longitudinal studies of changes in chronic stress exposure and changes in ambulatory blood pressure or cortisol have yet been published.

We therefore performed a 3-year follow-up of ambulatory monitoring in the psychobiology substudy of the Whitehall II study. This substudy was originally designed to investigate the influence of socioeconomic position and other factors on psychobiological function (22). We analyzed financial strain as an indictor of chronic psychosocial adversity. Financial strain measures were available at both time points in all participants, irrespective of whether they had retired. Perceived financial strain has been shown to be predictive of myocardial infarction and cardiac death in women in the Framingham study (23) and was associated with coronary heart disease (CHD) in the recent INTERHEART international study (24). Financial strain is also associated with lower SEP and poor residential conditions and neighborhood quality (25). However, in the office-based working cohort tested in this study, financial strain is more indicative of an imbalance between income and outgoings or material aspirations than of poverty. In line with the observations of Schnall et al. (21) concerning job strain, we focused on improvements in financial strain over the 3-year period. We hypothesized that if improved financial strain has beneficial biological consequences, it would be associated with lower blood pressure and a smaller CAR than would be recorded in people for whom financial strain had not changed or worsened. The slope of cortisol decline over the day and evening values were analyzed as well. In addition to this focused comparison, we also analyzed changes in financial strain as a continuous variable in relation to biological measures. Because financial strain is associated with SEP, we controlled for this factor and initial level of financial strain in the analyses. We also controlled for other variables likely to influence ambulatory blood pressure and cortisol. These include age, BMI, smoking status (26,27), and for the cortisol awakening response, time of waking up in the morning (28).


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Participants
Participants were 167 of the 220 people who took part in the Whitehall psychobiology substudy (22). They were white men and women, age 49 to 59 years at the time of first recruitment, and all were day workers based in the London area, with no history of CHD or diabetes and no previous diagnosis or treatment for hypertension. Women were not eligible if they were premenopausal, as defined by a series of questions concerning menstruation and physician diagnosis. The sample was systematically recruited to ensure representation of higher, intermediate, and lower-grade groups. The mean interval between assessment in the psychobiology substudy (T1) and the present follow up (T2) was 3 years and 21 days (SD, 110 days), ranging from 2 years 3 months to 3 years 1 month. Of the original sample of 220, 16 were not invited for repeat monitoring because they had withdrawn from the full Whitehall II study or because they had moved out of the London area and could not be scheduled for ambulatory monitoring. Four had been lost to the full Whitehall II study, and one had died. A further 21 declined to repeat ambulatory monitoring because of other medical problems such as cancer, or because they had found it too obtrusive or uncomfortable at T1. Eleven more agreed to participate, then withdrew or could not be scheduled before the end of the study.

Ambulatory Monitoring Procedures
Ambulatory blood pressure monitoring was performed at both T1 and T2 using the SpaceLabs 90217 monitor (Redmond, WA), an instrument that satisfies international instrumentation protocols (29). The monitor was fitted between 7:30 hours and 9:30 hours on a working day (depending on work schedules) at the participant’s place of work or in the laboratory at University College London. Participants wore the monitors for the remainder of the day and evening, and blood pressure was measured at 20-minute intervals. Each reading was accompanied by an entry in a diary in which the participant recorded location, activity over the past 5 minutes, and mood.

Saliva samples were collected using cotton dental rolls (Salivettes; Sarstedt, Leicester, UK) held in the mouth until saturated. On T1, measures were taken on waking up, 30 minutes later, and then within eight 30-minute time windows through the day and evening (8:00–8:30, 10:00–10:30... 22:00–22:30). At T2, samples were taken on waking up, 30 minutes later, and then at three further time points (10:00–10:30, 16:00–16:30, and 20:00–20:30). Tubes were returned to the investigators personally or by post, and cortisol was analyzed using an immunoassay (30). Cortisol in saliva remains stable for several weeks at room temperature, so degradation during the period of collection and delivery is unlikely (31).

Measures
Financial strain was assessed with an adaptation of the economic strain measure of Pearlin et al. (32). This assesses difficulty paying one’s bills, being able to replace items such as furniture or a car when needed, and being able to provide for one’s family in terms of food, clothing, and medical care. Eight items were presented, with response options ranging from 1= no difficulty to 3= very great difficulty (Cronbach’s {alpha} = 0.86). Information concerning marital status, personal income, smoking, and alcohol consumption was obtained by questionnaire. Personal income was assessed in eight categories: ≤£9,000, £10,000 to £14,999, £15,000 to £19,999, £20,000 to £24,999, £25,000 to £34,999, £35,000 to £49,000, £50,000 to £69,999, and ≥£70,000 (at the time of assessment, £1 was approximately equivalent to US$1.65). Smoking was analyzed as a binary variable, and participants were categorized on whether they drank alcohol daily or less than daily. At T1, blood pressure was also recorded under resting conditions in the laboratory after 30 minutes of inactivity using an A&D UA779 electronic sphygmomanometer. Height, body weight, and waist and hip circumference were measured using standard procedures.

Procedure
Participants were approached individually for the follow-up investigation at the time of their attendance at a screening session for the full Whitehall II cohort. They were reminded about their previous involvement in the psychobiology substudy and were asked whether they would be willing to perform a further day of blood pressure and saliva sampling. Appointments were scheduled with individuals who agreed to take part, and they were given the financial strain questionnaire to complete.

Data Reduction and Analysis
The ambulatory blood pressure recordings of five individuals were lost before downloading from monitors or were terminated prematurely at T2. Two other people did not have satisfactory data from T1, so analyses were performed on 160 participants. Changes in financial strain between T1 and T2 were computed, and in addition, two groups were created by dividing the sample into those who reported an improvement in financial strain (a decrease in financial strain scores between T1 and T2, N = 51) and those who reported no change or a deterioration in financial strain (N = 109). Improvement versus worse/no change was used as a between-subject grouping factor in the analyses.

Individual blood pressure readings were reviewed and outliers were excluded using the criteria described by Berardi et al. (33). The number of eligible blood pressure readings averaged 34.3 ± 5.7 at T1 and 31.0 ± 4.5 at T2 per person per day. Systolic and diastolic pressure was averaged across the complete sampling period to produce grand means. In addition, we divided the day into four periods, as in our previous analyses of T1 data (22), namely morning (7:50–11:00), midday (11:00–14:00), afternoon (14:00–17:00), and evening (17:00–22:30). There was no difference in the number of blood pressure readings contributing to analyses in the improvement and worse/no change financial strain groups. Blood pressure analyses were performed on 152 participants.

The relationship between financial strain and blood pressure at T1 was analyzed using linear regression, with age, gender, grade of employment, smoking status, and BMI as covariates. Alcohol consumption at T1 and T2 was not associated with blood pressure and so was not included in the analysis. Comparisons between the two financial strain change groups in background and T1 characteristics were made using analysis of variance and nonparametric statistics as appropriate. The relationship between changes in financial strain and actual income was addressed by assessing the income categories of participants at both T1 and T2.

The analyses of T2 blood pressure (systolic and diastolic) were performed on the overall mean levels using two methods. First, linear regressions were performed on T2 blood pressure, with change in financial strain as a continuous predictor variable, along with age, gender, T1 blood pressure, grade of employment, T2 smoking status, T2 BMI, and T1 financial strain. Results are presented as unstandardized regression coefficients (B) with 95% confidence intervals (CIs). Second, analysis of variance was performed with financial strain change group (improvement versus worse/no change) and gender as between-subject factors. The same covariates were included in these analyses. The statistical associations with financial strain are identical to those that emerge from analysis of blood pressure change scores between T1 and T2.

We separately analyzed the CAR, the slope of decline in cortisol over the day, and evening cortisol levels. The CAR was assessed by calculating the change between waking and 30 minutes later. Recent evidence indicates that cortisol awakening responses are incorrectly measured when participants fail to obtain samples at the correct times (34). Delay between waking and taking the first sample is particularly problematic, because the CAR may already have begun before assessment of the waking value. In an analysis of T1 data from this study, we showed that people who delayed more than 10 minutes in taking the waking sample produced significantly smaller CAR than those who were prompt with the waking sampling (35). In the present analysis, we therefore excluded participants from analyses if their diaries indicated a delay of more than 10 minutes. A total of 152 participants provided saliva samples both on waking and 30 minutes later from which cortisol could be analyzed, but 24 reported delays of more than 10 minutes. Of the remaining 128 participants, data from T1 were not available for 14, so the final analyses of cortisol awakening responses were performed with 114 participants. The CAR analyses were performed with financial strain change as a continuous variable in linear regression, and also with financial strain change group and gender as between-subject factors, and age, grade of employment, smoking status, time of waking, T1 financial strain, and T1 cortisol as covariates. Associations between the cortisol awakening response and financial strain at baseline were analyzed using linear regression, with age, gender, grade of employment, and time of waking as covariates.

The cortisol decline over the day was computed as the change between the waking and 8:00 to 8:30 PM values at both T1 and T2. The 8:00 to 8:30 PM value was also used as the measure of evening level. These data were analyzed in the same fashion as the CAR. Data are presented as means ± SDs.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
Comparisons were made between the men and women who took part in the 3-year follow-up and those who provided data on T1 only. There were no significant differences between these groups on any demographic, behavioral, or physiological variable, suggesting that the selection process was unlikely to have influenced the results of these analyses.

The two financial strain change groups are compared in Table 1. They did not differ in gender distribution, age, or marital status. The majority of participants were still in paid employment at T2, and the proportions who had retired or left work did not differ. There was a significant difference in the T1 grade of employment of the two groups ({chi}2 = 6.03; p = .049); participants who reported an improvement in financial strain were more likely to be of lower SEP in terms of grade of employment. The median income category of the two financial strain change groups was the same (£25,000-£34,999) at both T1 and T2, despite modest national inflation. However, analysis of change in income category showed a significant difference between groups ({chi}2 = 3.86; p for linear association = .050). Participants who reported an improvement in financial strain were more likely to have shifted to a higher income category. Nevertheless, it is notable that 39.2% of those who reported no change in financial strain also moved to a higher income category. The two groups did not differ in BMI, smoking, or alcohol consumption. As might be expected from the categorization procedure, repeated measures analysis of financial strain scores revealed a significant group by year interaction (F[1,156] = 118.0; p < .001). In post hoc analyses, the reduction in financial strain scores of the improved category was significant, as was the increase in scores in those who are classified as worse/no change (both p values <.001). At the biological level, there were no significant differences between groups in laboratory resting blood pressure, T1 ambulatory blood pressure, T1 CAR, cortisol decline over the day, or evening level. Participants reported waking at 6:15 AM on average at T2, and this did not differ between groups. There were no interactions between gender and financial strain change group in any of the analyses described in T2.


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  		TABLE 1. Characteristics of Financial Strain Groups

 

Ambulatory Blood Pressure
Financial strain and ambulatory systolic or diastolic pressure were not significantly associated at T1. The linear regression on T2 systolic pressure showed an association with change in financial strain (B = 1.09; CI = 0.05 to 2.13; p = .041) independently of age, grade of employment, BMI, smoking, T1 systolic pressure, and T1 financial strain. People who improved their financial situation showed a decline in systolic pressure, whereas deterioration in financial strain was associated with an increase in systolic pressure. In addition, there was a significant difference between financial strain change groups in average systolic pressure at T2 after adjusting for covariates (F[1,142] = 4.87; p = .029), together with a significant gender difference (F[1,142) = 12.8; p < .001), with no interaction between financial strain and gender. Systolic pressure adjusted for covariates averaged 121.7 ± 11.2 mm Hg in the improved financial strain group, compared with 125.5 ± 11.5 mm Hg in the worse/no change group, a mean difference of 3.8 mm Hg. In terms of changes between T1 and T2, this reflects a mean adjusted decrease in systolic pressure of 3.07 mm Hg in the improved financial strain group and a mean rise of 0.73 mm Hg in the worse/no change group. The pattern over the four periods of the day is illustrated in Figure 1, in which it is evident that the group difference was maintained throughout the day and evening. The main effect of time of day (F[3,447] = 9.03; p < .001) did not interact with financial strain.



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  		Figure 1. Systolic blood pressure at 3-year follow-up averaged into morning (07:50–10:50), midday (11:00–13:50), afternoon (14:00–16:50), and evening (17:00–22:30) periods in groups reporting improved financial strain (• solid line) and worse/no change in financial strain ({blacksquare} dashed line). Values are averaged across men and women and are adjusted for age, grade of employment, BMI, smoking status, baseline financial strain, and T1 systolic pressure from the corresponding time period. Error bars are SEM.

 

The analysis of diastolic pressure showed a similar pattern, although it was less pronounced. The linear regression on T2 diastolic pressure showed a positive but nonsignificant association with change in financial strain (B = 0.56; CI = –0.13 to 1.26; p = .11), and the difference between improved and worse/no change groups was of borderline significance after taking covariates into account (F[1,142] = 3.56; p = .061). The adjusted means were 78.5 ± 7.1 mm Hg and 80.7 ± 7.9 mm Hg in the improved and worse/no change groups, respectively. In the repeated measures analysis of covariance, there was a main effect of time of day (F[3,447] = 32.3; p < .001), but no interaction with financial strain change group (Figure 2). The difference in diastolic pressure corresponded to an average decrease between T1 and T2 of 2.00 mm Hg in the improved financial strain group and an increase of 0.20 mm Hg in the worse/no change group. There was no interaction between gender and financial strain change group in the analyses.



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  		Figure 2. Diastolic blood pressure at 3-year follow-up averaged into morning, midday, afternoon, and evening periods in groups reporting improved financial strain (• solid line) and worse/no change in financial strain ({blacksquare} dashed line). Values adjusted as for systolic blood pressure.

 

Cortisol Responses
Cortisol awakening responses, the cortisol decline over the day, and the cortisol evening level at T1 were not significantly associated with T1 financial strain. Cortisol values on waking at T2 did not vary with financial strain change group or gender, and averaged 15.9 ± 8.6 nmol/l. In regression analyses, no association between change in financial strain and change in the CAR was observed. However, in the comparison of improved and worse/no change groups, there was a significant financial strain change by gender interaction (F[1,103] = 4.46; p = .037), after adjustment for age, grade of employment, smoking, time of waking, T1 financial strain, and T1 cortisol response. Post hoc analyses were performed of men and women separately. The financial strain change effect was significant in men (p = .048) but not in women (p = .57), and this pattern of results is illustrated in Figure 3. Men who reported an improvement in financial strain had a lower CAR in comparison with those in the worse/no change group. Between T1 and T2, the CAR increased by an average of 8.95 nmol/l in the worse/no change group, compared with an increase 0.94 nmol/l in the improved financial strain group.



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  		Figure 3. Mean cortisol at 3-year follow-up on waking and 30 minutes later in groups reporting improved financial strain (• solid line) and worse/no change in financial strain ({blacksquare} dashed line). Values are adjusted for the corresponding T1 cortisol value, and age, grade of employment, smoking status, baseline financial strain, and time of waking in the morning.

 

The decline in cortisol over the day adjusted for covariates averaged 14.5 ± 11.1 nmol/l in the improved financial strain group and 13.0 ± 9.2 in the worse/no change group (p = .53). In addition, there was a gender difference (F[1,95] = 5.13; p = .026), because the decline over the day was greater among women than men (adjusted means 16.1 vs. 11.4 nmol/l). However, the gender difference did not interact with change in financial strain. Nor was there a difference in cortisol sampled at 8:00 to 8:30 PM in relation to change in financial strain. The levels adjusted for covariates averaged 3.26 ± 4.8 nmol/l in the improved group and 3.14 ± 2.7 nmol/l in the worse/no change group.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
This study investigated the association between chronic psychosocial adversity and biological function by assessing the impact of changes in financial strain on ambulatory blood pressure and cortisol. Financial strain was chosen as the marker of chronic adversity because it is relevant to all adults, whether or not they are in paid employment. However, it may not be experienced in isolation from other chronic stressors that were not measured in this study. The measure assessed the extent to which respondents felt that they had sufficient funds to live in the style they desired and is not a measure of poverty. Some previous studies have assessed financial strain in unemployed groups, in which issues of need are more prominent (20,36). As anticipated, the majority of participants who reported improvement in financial strain over the 3-year period were on lower incomes. People whose earnings are high are less likely to suffer from financial strain in the first place, so improvements are less likely. It is evident from Table 1 that the change in financial strain over the 3-year period partly reflected actual changes in income, because 54.3% of people in the improved group increased their income by at least one category. However, this also means that nearly half of those who reported an improvement in financial strain did not increase their income category, and more than a third of individuals who noted no change or a worsening of financial strain also increased income category. It is possible that improvements in financial strain reflected in part changes in financial commitments in this age group, such as paying off long-term housing mortgages, the completion of children’s education, or the fruition of annuities and pension schemes.

The results of these analyses suggest that there are associations between changes in financial strain and blood pressure and cortisol, but that these are generally nonlinear. Systolic pressure was the only variable to show a linear association with change in financial strain, but the contrast between improved and worse/no change groups performed most of the variance. This result is consistent with the finding of Schnall et al. (21) that changes in blood pressure were more striking in people reporting a positive improvement rather than deterioration in work stress. Differences were less robust for diastolic pressure, and this is a relatively common finding in studies of ambulatory blood pressure. For example, several studies of work stress have shown larger associations in systolic than diastolic pressure (1), and King et al. (2) observed differences only in systolic pressure between caregivers and noncaregivers.

Our results have some resemblance to the findings relating to lifestyle incongruity with blood pressure reported by Dressler (37) and Bindon et al. (38). Lifestyle incongruity or lifestyle stress describes the extent to which people’s style of living (symbolized by possession of material goods) is matched by their incomes or occupational class. In studies performed in Mexico, the West Indies, and Samoa, and with African Americans in the southern United States, Dressler has shown that greater lifestyle incongruity is associated with higher resting blood pressure independently of age, sex and BMI (37,38). Interestingly, this approach has been extended to developed societies. Dressler et al. (39) demonstrated that the discrepancy between material consumption and occupational status was associated with elevated serum cholesterol in a population sample in the United Kingdom. Inasmuch as our financial strain measure reflects an imbalance between income and outgoings, it has parallels with the lifestyle incongruity concept. However, it should be noted that in this study, we did not observe cross-sectional associations between financial strain and ambulatory blood pressure, but only associations with changes in financial strain.

The salivary cortisol results were again nonlinear, with group comparisons indicating that the CAR was lower in men reporting an improvement in financial strain compared with those in the worse/no change group. There was no difference in women. Cross-sectional studies have documented a positive association between the magnitude of the CAR and chronic stress (10,11,13). These findings provide corroboration from a longitudinal perspective. Grossi et al. (20) assessed salivary cortisol from 85 long-term unemployed men and women, divided on a different version of the Pearlin scale into high and low financial strain groups. Levels of cortisol averaged over four time points over the day, and cortisol measured at 10:00 PM, were greater in women reporting high financial strain. No differences were observed in cortisol levels on wakening, and this is consistent with the present findings. The reason for the absence of financial strain effects on women in the present study is not clear. However, in a previous analysis of the larger data set collected from this sample at T1, we discovered associations between the CAR and overcommitment to work in men but not women (12). It may be that in this sector of the population, the CAR is more sensitive to psychosocial factors in men than women.

The differences in blood pressure and CAR associated with changes in financial strain are relatively small. However, if the results of the study reflect habitual differences that are present in everyday life, even small effects are potentially clinically significant. Meta-analyses of prospective observational studies indicate that blood pressure variations of this magnitude as associated with significant differences in death rates from stroke, CHD, and other cardiovascular diseases (40). Additionally, ambulatory blood pressure is superior to clinic blood pressure in predicting target organ damage in hypertension (41), future hypertension in normotensives, CHD, and cerebrovascular disease (42,43). A heightened CAR is associated with abdominal obesity in men (44), whereas elevated cortisol levels early in the day predict future clinical depression in adolescents (45) and adult women (46).

This study has several limitations that need to be taken into account in the interpretation of the results. Data were collected from healthy middle-aged men and women, none of whom had diagnosed cardiovascular disease. Blood pressures were therefore relatively low, and patterns may be different in people with pre-existing disease. We analyzed only changes in financial strain. Other aspects of chronic psychosocial adversity undoubtedly have an impact on blood pressure and cortisol. Data were collected over a single day. Repeated measures might provide more robust estimates of the impact of changes in financial strain. Ambulatory blood pressure was not collected at night, so 24-hour assessments could not be made. Monitoring was accompanied by a series of ratings that interrupted ongoing activities, and ambulatory blood pressure monitoring itself may constrain people’s activities (47). The study was performed with white middle-aged office-based employed men and women; effects may be different in other groups. Although we took factors that have been associated with ambulatory blood pressure and salivary cortisol into account statistically, the possibility of residual confounding remains. Nevertheless, the results add to the evidence that psychosocial factors influence psychobiological function in everyday life, complementing cross-sectional findings by showing that longitudinal changes in adversity over a period of 3 years are accompanied by concurrent changes in blood pressure in both sexes and cortisol in men. The results are consistent with the notion that biological responses partly mediate the relationship between psychosocial factors and health.

We are grateful to Pamela J. Feldman, Natalie Owen, Bev Murray, Gonneke Willemsen, Caroline Wright, Lindsey Emmerson, and Elizabeth Cort for their involvement in data collection, and to Clemens Kirschbaum for analysis of cortisol data.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 
This research was supported by the Medical Research Council and the British Heart Foundation, United Kingdom.

Received for publication April 19, 2004; revision received September 30, 2004.

DOI:10.1097/01.psy.0000156932.96261.d2


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

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