Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Effects of dipping and psychological traits on morning surge in blood pressure in healthy people


Despite the role of anxiety, depression and hostility in the pathogenesis of cardiovascular diseases, their impact on two significant cardiovascular risk factors, nocturnal dipping and morning surge in blood pressure (MSBP), are largely ignored and primarily studied in clinical populations. This study examined the effects of dipping and psychological traits on MSBP in healthy people. Nocturnal dipping and MSBP were derived from 24-h ambulatory BP obtained in 77 men and 79 women, mean age 32.8 (s.d.: 7.4). Differences in depression, anxiety and hostility were examined by questionnaires. Higher levels of dipping (P<0.0001) and depressive symptoms (P=0.01) independently contributed to increased MSBP. Dipping interacts with depression (P=0.04), hostility (P=0.01) and anxiety (P=0.04) in determining MSBP. Low dippers with higher scores on the psychological traits showed higher MSBP than high dippers. A significant MSBP interaction was found between sex and depressive symptoms (P=0.05), anxiety (P<0.0001) and hostility (P=0.01) with higher scores associated with increased MSBP observed in males. Findings underscore depression as a predictor of MSBP independent of dipping. The clinically significant relationship between dipping and non-dipping patters, psychological traits and MSBP requires further investigation.


Twenty-four hour blood pressure (BP) shows a distinct circadian pattern with an approximate 10–20% decline during sleep, known as ‘dipping,’ followed by an increase in BP concurrent with arousal from sleep, known as the morning surge in BP (MSBP).1 Approximately 25% of people with hypertension are classified as non-dippers in whom the normal nocturnal fall of pressure is reduced or absent.1 Non-dipping and excessive surge in BP have been associated with an increased risk for cardiovascular events including heart attack, stroke and sudden death.2, 3 MSBP has been associated with the change in BP after an afternoon siesta,4 suggesting that a sudden rise in pressure may pose a risk regardless of time of day. Excessive MSBP has been proposed to trigger stroke via shear stress on atherosclerotic cerebral vessels; however, increased sympathetic nervous system activity and platelet hyperactivity, hypercoagulability, blood viscosity and increased vascular spasm may be contributing factors.5, 6 Excessive MSBP, however, is observed in dippers compared with non-dippers and is associated with increased cardiovascular sequelae.1 This seemingly contradictory result highlights the ambiguous relationship between surge and dipping, and suggests the need for further investigation of these important risk factors.

Additional factors known to influence cardiovascular events include hostility,7 depression8 and anxiety.7, 9 Psychological risk factors including hostility and depression are reported to impact hypertension risk indirectly via biobehavioral pathways including unhealthy behaviours such as smoking, increased caloric and alcohol intake, and by increasing biological reactivity to stress, inflammation, expression of metabolic syndrome10, 11, 12 and MSBP. Depression has been shown to predict the incidence of vascular diseases beyond that provided by age, sex, ambulatory BP, lifestyle and environmental conditions with adverse vascular outcomes associated with longer periods of depressive mood.13 In a 10-year follow-up study of the first National Health and Nutrition Examination Survey, the Center for Epidemiological Studies Depression scale predicted a greater than 70% excess risk of incident cardiovascular disease risk in both men and women.14 Anxiety has also been associated with greater cardiovascular mortality and morbidity in various populations including community-based samples, although the majority of studies are limited to men and Caucasian populations.14 Hostile individuals with advanced cardiovascular disease may be particularly susceptible to stress-induced increases in sympathetic activity and inflammation.15 Furthermore, recent findings demonstrate that even mild levels of adverse psychological states such as depression, anxiety and hostility may be linked to increased cardiovascular risk via impaired vasodilation.16

Only one paper has examined the relationship between personality and MSBP. We previously reported that individual differences in hostility were related to different patterns of BP during sleep and the early morning hours in hypertensive patients.17 The results revealed significant differences between low and high hostility patients for overall levels of systolic BP (SBP) during sleep. Specifically, patients with low hostility scores had the greater rate of rise of early morning BP, because they had reached lower nocturnal baseline levels, whereas high-scoring individuals showed a gradual rise in BP during sleep that continues into the waking hours. Findings suggest vulnerability to different cardiovascular risk factors for the two groups: the non-dipping pattern of high hostility subjects has been associated with more target organ damage, whereas low hostility individuals may be more prone to cerebrovascular accidents due to the larger MSBP. The data suggested the need for further study of the significance of hostility and other personality traits, and how the interrelationship of these factors may relate to the mechanisms of MSBP and the risk of cardiovascular events.

As to age and sex, a recent investigation in primary hypertensive individuals reported that MSBP was strongly correlated with age, although sex was unrelated to MSBP.18 However, morning diastolic BP (DBP) and mean arterial pressure were lower in women, and morning pulse pressure was higher suggesting that the effects of both age and sex on MSBP should be considered.18 In addition to hemodynamic characteristics reportedly differing by sex,19 the relationship between negative emotions and cardiovascular events has been shown to be influenced by sex.20

The major aims of the present study are to examine the effects of dipping and psychological traits on MSBP in a healthy population, and the interrelationship of these factors in predicting MSBP. To follow-up our previous work,17 we examined the effects of anxiety, depression and hostility on MSBP in a large sample of healthy individuals and determined whether the effects were related to sex. The effects of dipping and of psychological traits were examined in the same statistical models to determine and control for the interaction of these factors in predicting MSBP.

Materials and methods

The data were obtained in a study of psychosocial factors and ambulatory BP in a large sample of healthy people (see Goldstein et al., 2006).21


The subjects were healthy adults, 77 men and 79 women, age 22–50 (mean 32.8, s.d.=7.4), who were all employed full-time. They were screened for significant health problems and use of drugs or medications that affect cardiovascular functions. Subjects with body mass index (BMI) 32 kg m−2 and a prior diagnosis of hypertension were excluded as were post-menopausal women and women who were pregnant or lactating within the previous 12 months. All subjects gave informed consent, approved by the UCLA Institutional Review Board.


After an initial telephone screening, subjects were seen on three separate sessions. During the initial session, subjects provided information on demographics and health and filled out questionnaires on individual characteristics. Height and weight were measured. Twenty-four hour ambulatory BP was obtained in sessions two and three, 1 week apart.

Ambulatory BP

Ambulatory monitoring was done on one work day and one off work day, counterbalanced. Recordings commenced as close as possible to the beginning time of the usual work day for each participant, in the morning hours. Subjects returned on the following day after each session to have the monitor removed.

BP was recorded by the Accutracker II (Suntech Medical Instruments, Raleigh, NC, USA), used widely in clinical and research studies, with established reliability and validity.22, 23 On each measurement occasion, single readings of SBP and DBP and heart rate were obtained. SBP was used in estimating MSBP. Subjects were told to keep their arms still at their sides each time the instrument operated, whatever their posture or activity at the time. The recorder was programmed to operate on a variable schedule three times an hour during waking hours and once an hour during sleep, based on each subject's estimates of time of going to sleep and awakening. For each subject, ambulatory data were first edited for artifacts based on Accutracker-reading codes (insufficient electrocardiogram or Korotkoff sounds) and extreme values (>200/120 or <70/40 mm Hg). Editing was done entirely by set rules.24 Using a stem-and-leaf plot (Systat, Evanston, IL, USA) for each subject's distribution of SBP readings, we identified and excluded far outside values.25

Classification of each reading as wake or sleep was based on diary entries and post-session reports. Only nighttime sleep values were included in the sleep category and daytime wake values in the wake category. The average number of readings per subject was 122.2 (13.6) during wake and 20.8 (6.3) during sleep. Number of readings did not differ as a function of the major variables of the study.

Morning surge

Several different methods of estimating MSBP have been reported, such as the change in mean SBP between the mean of the 2 or 3 h immediately before waking up, and the mean of the 2 or 3 h after awakening or the slope of the hourly change in SBP for the respective 4 or 6 h. In our previous study,17 inspection of the 6 hourly SBP means (3 pre- and 3 post-awakening) indicated that the pattern of SBP change did not follow a linear course. The successive variations from reading to reading can also affect the linearity of the slope, which makes it independent of the significant portion of the change. For these reasons, we chose the change in SBP between the mean of the 3 pre- and 3 post-awakening hours as the measure of MSBP. The 3-h means are likely more stable indices than 2-h means. When two or more readings occurred within a given hour, these readings were averaged.

In the analyses, the measure of dipping (SBPDIP) was the percentage change in SBP (usually a decrease) from the mean of waking SBP readings to the mean of sleep readings.

Personality measures

The following tests were administered: (a) Spielberger Trait Anxiety Inventory (STAI), a measure of dispositional anxiety;26 (b) Center for Epidemiologic Studies Depression Scale (CES-D) (total score), a measure of depressive symptoms;27 (c) Cook–Medley Hostility sub-scale (CM) of the Minnesota Multiphasic Personality Inventory, a measure of indirect or cynical hostility.28

Statistical analysis

As mean work day and non-work day SBPs were similar (126.3 mm Hg and 125.7 mm Hg, respectively) and highly intercorrelated (r=0.52; P<0.0001), models were run combining data from both days. Considering that sleep duration is known to affect morning surge29 and can differ during work and non-working days, hours of sleep computed separately for the 2 days and Pearson correlation were performed to test its relationship with MSBP and SBPDIP. The same was done for number of awakenings per night.

Sex differences were analysed by two-sample t-test. The data were analysed using General Linear Models with MSBP (increase in SBP) as the dependant variable. As preliminary analyses did not show age, or ethnicity effects, these factors were not included in the models. Four analyses with the same format were conducted. Example of the first one is as follows: the independent variables were Sex, BMI, SBPDIP, CES-D, SBPDIP*CES-D, Sex*CES-D and BMI* CES-D. As the Sex*SBPDIP, Sex*BMI and BMI*SBP interactions were not significant in any of the analyses, they were excluded from the final models. In the second analysis, STAI was substituted for CES-D, in the third analysis, CM was substituted for CES-D and in the fourth analysis, SBP during wake (SBP wake) was substituted for CES-D. To test the contribution of each variable in the prediction of MSBP, a complete regression model was performed with sex, BMI, SBP wake, SBPDIP, CES-D, STAI, CM and their two-way interactions. Figures depicting significant interactions of continuous variables were drawn following Aiken and West.30 As recommended, the continuous variables were centred around their means to control for multicollinearity.


Neither sleep duration nor number of awakenings was related to MSBP or SBPDIP. Table 1 shows sex differences for the demographic, physiological and personality variables. Men had a higher BMI, t=–2.98; P<0.0001, and women had higher CES-D scores, t=–2.62; P=0.01, and lower baseline SBP, t=−6.86; P<0.0001 and DBP, t=–4.36; P<0.0001. Anxiety (STAI) was positively correlated with depressive symptoms (CES-D; r=0.58) and hostility (CM; r=0.46). A positive relationship was also found between depressive symptoms and hostility (r=0.39).

Table 1 Sex differences for demographic, physiological and personality variables and overall mean of SBP during wake and during sleep and 24-h SBP, for the entire sample (last three rows)

The analyses showed significant main effects of SBPDIP in all GLM models, P<0.0001. Specifically, a higher SBPDIP was associated with higher MSBP. Depressive symptoms, as measured by the CES-D, had a main effect on MSBP, F=7.62; P=0.01, the more depressed, the greater the MSBP. Figure 1 depicts the main effects of SBPDIP and CES-D.

Figure 1

Main effects of SBPDIP and depression (CES-D) on morning surge (MSBP). Endpoints of the lines in the graph represent one standard deviation above and below the mean for SBPDIP and CES-D score.

With regard to sex, a significant STAI × Sex interaction, F=12.99; P<0.0001 was found. Specifically, higher levels of anxiety were associated with higher MSBP only in male subjects and women showed the opposite effect. Similarly, differences in sex patterns emerged for hostility, indicated by the significant Sex × CM interaction, F=11.07; P<0.0001. Higher hostility was associated with a higher surge only in men, whereas women showed the opposite pattern. A CES-D × Sex interaction also emerged with depressed men showing higher levels of MSBP compared with depressed women, F=3.78; P=0.05. Figure 2 shows the two-way effects for sex and personality factors.

Figure 2

Interactions between personality measures and sex in relation to morning surge (MSBP). Endpoints of the lines in the graph represent one standard deviation above and below the mean for STAI, CES-D and CM scores.

With regard to SBPDIP, significant interactions were found with depression, F=4.17; P=0.04, anxiety, F=4.98; P=0.03 and hostility, F=8.19; P<0.0001. High SBPDIP was consistently associated with higher surge, independently of personality traits. However, for low SBPDIP, higher levels of anxiety, depressive symptoms and hostility are associated with higher surge (Figure 3). The interaction between SBPDIP and SBP during wake was also significant in determining MSBP, F=7.20; P=0.01, with higher surge for subjects with high dipping and high SBP during wake.

Figure 3

Interaction between hostility (CM) × SBPDIP, anxiety (STAI) × SBPDIP, depression (CES-D) × SBPDIP and SBPWAKE × SBPDIP in relation to morning surge (MSBP). Endpoints of the lines in the graph represent one standard deviation above and below the mean for CM, STAI, CES-D scores, SBPWAKE and SBPDIP.

No other significant main effects or interactions were found. To summarise, results suggest that SBP dip and depressive symptoms independently contribute to MSBP. Whereas men were more affected by the influence of anxiety and hostility, the effect of depressive symptoms was the same for both sexes. Finally, higher levels of anxiety, depressive symptoms and hostility were associated with higher MSBP only in subjects with low SBPDIP.

Table 2 shows the results of the regression model for MSBP, demonstrating that SBPDIP (P<0.0001), CES-D (P=0.04), CM × SBPDIP (P=0.01), and CM × STAI (P<0.0001), CM × CES-D (P=0.03) and Sex × SBP wake (P=0.03) are independent predictors of MSBP, with 57% of the variance of MSBP accounted for by the model.

Table 2 Summary of the regression analysis for the prediction of morning surge


Dipping and the MSBP have important consequences for cardiovascular disease risk and morbidity, and psychological factors have also been shown to relate to morning surge. In this study, we demonstrated that depressive symptoms and SBP dipping independently contribute to morning surge in a healthy population.

In the present study, depression had a main effect on morning surge showing that a higher surge was associated with higher levels of depressive symptoms. Previous research demonstrated that depression is an independent risk factor for cardiovascular events, and that depressive mood is associated with adverse cardiovascular outcomes.11, 13, 31 In line with recent findings by Cooper et al.16 our results suggest that although the subjects were not clinically depressed, even higher scores on a scale of depression may be a cardiovascular health risk. There is clinical evidence supporting the use of behavioral32 and pharmacological interventions targeting depression to improve cardiovascular prognosis.33, 34 Given the well established relationship between depression and cardiovascular disease,35 there needs to be a greater awareness of the role of depression as a cardiovascular risk factor in a normotensive population. In addition, longitudinal studies are needed to determine whether interventions aimed at decreasing depression have a positive impact on cardiovascular risk in a normotensive population.

SBP dipping was the strongest predictor of morning BP surge accounting for 30% of the variance, the greater the dip the greater the surge. This is paradoxical as the literature proposes that a lack of dipping is associated with hypertension and an increased risk of cardiovascular mortality. However, data on the relevance of dipping for cardiovascular health are ambiguous. Three large-scale prospective studies provide evidence suggesting that non-dipping is associated with a higher risk of cardiovascular events than dipping.36, 37 In another prospective study of normal adults without a history of cerebrovascular disease, dipping and BP level were independent predictors of the risk of cardiovascular mortality. Non-dippers were shown to be at approximately double the risk of cardiovascular events as dippers, although the influence of psychological traits was not reported.38 However, Bjorklund et al.39 report that nighttime BP and dipping were no better at predicting risk than daytime pressure. In a study of 24-h BP in a Japanese population including normotensive and hypertensive samples, BP levels were the same in both dippers and non-dippers. Daytime BP was higher in the hypertensive dippers than in the non-dippers even though their risk was lower.36 Thus, findings seem to suggest that both dipping and non-dipping can have a role as risk factors.

In the present study, dipping interacts with the psychological traits of depression, hostility and anxiety in determining morning surge. Specifically, low dippers with high scores on these psychological traits showed higher surge; for participants with high dipping, surge appears to be less affected by these traits.

Psychological states of depression and anxiety have been associated with difficulty in falling asleep and poor quality of sleep,17, 40 and altered amounts of stage 4 sleep may influence both non-dipping and morning surge.17, 41 In addition, sleep disorders have been associated with non-dipping BP patterns.17, 42 Depression in men has been associated with disrupted diurnal BP variation with a tendency to the non-dipping pattern,43 an additional cardiovascular disease risk factor in normotensives.44 In a study of elders with depressive symptoms, nighttime SBP fall was lower compared with non-depressed elders, with a significantly higher incidence of non-dipping.45

Present findings further show that the magnitude of the morning surge observed in male subjects with higher hostility ratings was greater compared with females. Men have frequently been reported to have higher levels of hostility compared with women,7 with abnormal beta adrenergic dysfunction in healthy males.46 In our study of morning surge in hypertensive patients with low versus high hostility scores,17 we found that high hostility subjects had higher BP during the 3 h before getting up, and the slope of their BP appeared steeper before rising, compared with low hostility subjects.

Although sex has not been considered a significant factor in research on morning surge,18 our findings indicate that sex interacts with psychological traits in affecting surge and should be further evaluated in a normotensive population. A recent investigation in primary hypertensive individuals reported that surge was strongly correlated with age, although sex did not influence surge.18 However, in women, morning DBP and mean arterial pressure were lower while morning pulse pressure was higher.18 In addition, in women, an association between BP variation and cardiac abnormalities has been reported in hypertensive dippers and non-dippers.47 These findings suggest that the effects of age and sex on surge should be considered further in hypertensive patients.

In our study, ethnicity was not a significant factor. Research examining racial differences in cardiovascular disease suggests that differences in dipping rather than surge may contribute to observed racial disparity and may reflect psychosocial and socioeconomic as opposed to genetic influences. For example, in a recent study of hypertensive and normotensive women and men, findings suggest that everyday discrimination is associated with less nocturnal dipping, controlled for known covariates of demographic and life-style factors.48

Present results suggest that no single biological or psychological mechanism influences BP dipping and surge. As a limitation, sleep quality or social support were not evaluated in this study. Further research is needed on these and other factors, including stress, income, exposure to violence and crime, diet, family structure, community resources, education, job stability, built environment, physical activity, health maintenance behaviour and health care access.49 However, present data offer some insight into the complexity of the factors related to nighttime BP dipping patterns and surge in normotensive individuals, providing an opportunity for which interventions can be encouraged. The association between non-dipping BP patterns, morning BP surge and psychological profiles provides further support for the potential of the positive benefits of psychological interventions that may convert a non-dipping BP profile to a dipping BP profile in normotensive individuals.

In conclusion, BP surge and dipping should be regarded as complex phenomena, the proper evaluation of which may yield important pathophysiological information. As shown by several studies, both dipping and non-dipping are likely to have clinical significance. The present study identified the impact of depressive symptoms on morning BP surge in a normotensive population that is independent of dipping. This finding needs greater attention in as much as alterations in nocturnal BP fall may reflect altered cardiovascular regulation in combination with various psychological profiles. Lastly, these findings add to the growing body of evidence highlighting the relevance of psychological risk factors in cardiovascular research.


  1. 1

    Cuspidi C, Meani S, Salerno M, Valerio C, Fusi V, Severgnini B et al. Cardiovascular target organ damage in essential hypertensives with or without reproducible nocturnal fall in blood pressure. J Hypertens 2004; 22: 273–280.

    CAS  Article  Google Scholar 

  2. 2

    Stolarz-Skrzypek K, Thijs L, Richart T, Li Y, Hansen TW, Boggia J et al. Blood pressure variability in relation to outcome in the International Database of Ambulatory blood pressure in relation to Cardiovascular Outcome. Hypertens Res 2010; 33: 757–766.

    Article  Google Scholar 

  3. 3

    Eguchi K, Hoshide S, Ishikawa J, Pickering TG, Schwartz JE, Shimada K et al. Nocturnal nondipping of heart rate predicts cardiovascular events in hypertensive patients. J Hypertens 2009; 27: 2265–2270.

    CAS  Article  Google Scholar 

  4. 4

    Bursztyn M, Ginsberg G, Hammerman-Rozenberg R, Stessman J . The siesta in the elderly: risk factor for mortality? Arch Intern Med 1999; 159: 1582–1586.

    CAS  Article  Google Scholar 

  5. 5

    Zakopoulos NA, Tsivgoulis G, Barlas G, Papamichael C, Spengos K, Manios E et al. Time rate of blood pressure variation is associated with increased common carotid artery intima-media thickness. Hypertension 2005; 45: 505–512.

    CAS  Article  Google Scholar 

  6. 6

    von Kiñnel R, Jain S, Mills PJ, Nelesen RA, Adler KA, Hong S et al. Relation of nocturnal blood pressure dipping to cellular adhesion, inflammation and hemostasis. J Hypertens 2004; 22: 2087–2093.

    Article  Google Scholar 

  7. 7

    Linden W, Chambers L, Maurice J, Lenz JW . Sex differences in social support, self-deception, hostility, and ambulatory cardiovascular activity. Health Psychol 1993; 12: 376–380.

    CAS  Article  Google Scholar 

  8. 8

    Surtees PG, Wainwright NWJ, Khaw KT, Day NE . Functional health status, chronic medical conditions and disorders of mood. Br J Psychiatry 2003; 183: 299–303.

    Article  Google Scholar 

  9. 9

    Shen BJ, Avivi YE, Todaro JF, Spiro III A, Laurenceau JP, Ward KD et al. Anxiety characteristics independently and prospectively predict myocardial infarction in men: the unique contribution of anxiety among psychologic factors. J Am Coll Cardiol 2008; 51: 113–119.

    Article  Google Scholar 

  10. 10

    Bonnet F, Irving K, Terra JL, Nony P, Berthezène F, Moulin P . Anxiety and depression are associated with unhealthy lifestyle in patients at risk of cardiovascular disease. Atherosclerosis 2005; 178: 339–344.

    CAS  Article  Google Scholar 

  11. 11

    Sher Y, Lolak S, Maldonado J . The impact of depression in heart disease. Curr Psychiatry Rep 2010; 12: 255–264.

    Article  Google Scholar 

  12. 12

    Williams RB, Barefoot JC, Schneiderman N . Psychosocial risk factors for cardiovascular disease: more than one culprit at work. JAMA 2003; 290: 2190–2192.

    CAS  Article  Google Scholar 

  13. 13

    Yamanaka G, Otsuka K, Hotta N, Murakami S, Kubo Y, Matsuoka O et al. Depressive mood is independently related to stroke and cardiovascular events in a community. Biomed Pharmacother 2005; 59: S31–S39.

    Article  Google Scholar 

  14. 14

    Marano G, Harnic D, Lotrionte M, Biondi-Zoccai G, Abbate A, Romagnoli E et al. Depression and the cardiovascular system: increasing evidence of a link and therapeutic implications. Expert Rev Cardiovasc Ther 2009; 7: 1123–1147.

    Article  Google Scholar 

  15. 15

    Brydon L, Strike PC, Bhattacharyya MR, Whitehead DL, McEwan J, Zachary I et al. Hostility and physiological responses to laboratory stress in acute coronary syndrome patients. J Psychosom Res 2010; 68: 109–116.

    Article  Google Scholar 

  16. 16

    Cooper DC, Milic MS, Tafur JR, Mills PJ, Bardwell WA, Ziegler MG et al. Adverse impact of mood on flow-mediated dilation. Psychosom Med 2010; 72: 122–127.

    Article  Google Scholar 

  17. 17

    Pasic J, Shapiro D, Motivala S, Hui KK . Blood pressure morning surge and hostility. Am J Hypertens 1998; 11: 245–250.

    CAS  Article  Google Scholar 

  18. 18

    Sun N, Xi Y, Jing S, Lu X . Morning blood pressure surge varies with age and gender in hypertensive individuals. Int J Cardiol 2009; 135: 272–273.

    Article  Google Scholar 

  19. 19

    August P, Oparil S . Hypertension in women. J Clin Endocrinol Metab 1999; 84: 1862–1866.

    CAS  Article  Google Scholar 

  20. 20

    Haukkala A, Konttinen H, Laatikainen T, Kawachi I, Uutela A . Hostility, anger control, and anger expression as predictors of cardiovascular disease. Psychosom Med 2010; 72: 556–562.

    Article  Google Scholar 

  21. 21

    Goldstein IB, Shapiro D, Guthrie D . Ambulatory blood pressure and family history of hypertension in healthy men and women. Am J Hypertens 2006; 19: 486–491.

    Article  Google Scholar 

  22. 22

    Appel LJ, Whelton PK, Seidler AJ, Patel AR, Klag MJ . The accuracy and precision of the accutracker ambulatory blood pressure monitor. Am J Epidemiol 1990; 132: 343–354.

    CAS  Article  Google Scholar 

  23. 23

    Griffin SE, Robgers RA, Heyward VH . Blood pressure measurement during exercise: a review. Med Sci Sports Exerc 1997; 29: 149–159.

    CAS  Article  Google Scholar 

  24. 24

    Goldstein IB, Jamner L, Shapiro D . Ambulatory blood pressure and heart rate in healthy male paramedics during a workday and a nonworkday. Health Psychol 1992; 11: 48–54.

    CAS  Article  Google Scholar 

  25. 25

    Tukey JW . Exploratory Data Analysis. Addison-Wesley: Reading, 1977.

    Google Scholar 

  26. 26

    Spielberger CD, Gorsuch RL, Lushene PR, Vagg PR, Jacobs AG . Manual for the State-Trait Anxiety Inventory (Form Y). Consulting Psycholosits Press: Palo Alto, 1983.

    Google Scholar 

  27. 27

    Radloff L . The CES-D scale: a self-report depression scale for research in the general population. Appl Psych Meas 1977; 1: 385–401.

    Article  Google Scholar 

  28. 28

    Cook WW, Medley DM . Proposed hostility and pharisaic-virtue scales for the MMPI. J Appl Psychol 1954; 38: 414–418.

    Article  Google Scholar 

  29. 29

    Schillaci G, Verdecchia P, Zampi I, Battistelli M, Bartoccini C, Porcellati C . Non-invasive ambulatory BP monitoring during the night: randomised comparison of different reading intervals. J Hum Hypertension 1994; 8: 23–27.

    CAS  Google Scholar 

  30. 30

    Aiken LS, West SC . Multiple Regression: Testing And Interpreting Interactions. Sage: Newbury Park CA, 1991.

    Google Scholar 

  31. 31

    Taylor CB . Depression, heart rate related variables and cardiovascular disease. Int J Psychophysiol 2010; 78: 80–88.

    Article  Google Scholar 

  32. 32

    Mendes de Leon CF, Powell LH, Kaplan BH . Change in coronary-prone behaviors in the recurrent coronary prevention project. Psychosom Med 1991; 53: 407–419.

    CAS  Article  Google Scholar 

  33. 33

    Sauer WH, Berlin JA, Kimmel SE . Selective serotonin reuptake inhibitors and myocardial infarction. Circulation 2001; 104: 1894–1898.

    CAS  Article  Google Scholar 

  34. 34

    Schlienger RG, Meier CR . Effect of selective serotonin reuptake inhibitors on platelet activation: can they prevent acute myocardial infarction? Am J Cardiovasc Drugs 2003; 3: 149–162.

    CAS  Article  Google Scholar 

  35. 35

    Sowden GL, Huffman JC . The impact of mental illness on cardiac outcomes: a review for the cardiologist. Int J Cardiol 2009; 132: 30–37.

    Article  Google Scholar 

  36. 36

    Ohkubo T, Hozawa A, Yamaguchi J, Kikuya M, Ohmori K, Michimata M et al. Prognostic significance of the nocturnal decline in blood pressure in individuals with and without high 24-h blood pressure: the Ohasama study. J Hypertens 2002; 20: 2183–2189.

    CAS  Article  Google Scholar 

  37. 37

    Clement DL, De Buyzere ML, De Bacquer DA, de Leeuw PW, Duprez DA, Fagard RH et al. Prognostic value of ambulatory blood-pressure recordings in patients with treated hypertension. New Engl J Med 2003; 348: 2407–2415.

    Article  Google Scholar 

  38. 38

    Kobayashi S, Okada K, Koide H, Bokura H, Yamaguchi S . Subcortical silent brain infarction as a risk factor for clinical stroke. Stroke 1997; 28: 1932–1939.

    CAS  Article  Google Scholar 

  39. 39

    Bjorklund K, Lind L, Zethelius B, Berglund L, Lithell H . Prognostic significance of 24-h ambulatory blood pressure characteristics for cardiovascular morbidity in a population of elderly men. J Hypertens 2004; 22: 1691–1697.

    Article  Google Scholar 

  40. 40

    Cavelaars M, Tulen JHM, Man‘t Veld AJ, Gelsema ES, van den Meiracker AH . Assessment of body position to quantify its effect on nocturnal blood pressure under ambulatory conditions. J Hypertens 2000; 18: 1737–1743.

    CAS  Article  Google Scholar 

  41. 41

    Friedman O, Logan AG . Nocturnal blood pressure profiles among normotensive, controlled hypertensive and refractory hypertensive subjects. Can J Cardiol 2009; 25: e312–e316.

    Article  Google Scholar 

  42. 42

    Barenbrock M, Spieker C, Hausberg M, Rahn KH, Zidek W, Kisters K . Studies on diurnal blood pressure variation in kidney diseases associated with excessive salt and water retention. J Hum Hypertens 1999; 13: 269–273.

    CAS  Article  Google Scholar 

  43. 43

    Kario K, Schwartz JE, Davidson KW, Pickering TG . Gender differences in associations of diurnal blood pressure variation, awake physical activity, and sleep quality with negative affect: the work site blood pressure study. Hypertension 2001; 38: 997–1002.

    CAS  Article  Google Scholar 

  44. 44

    Amici A, Cicconetti P, Sagrafoli C, Baratta A, Passador P, Pecci T et al. Exaggerated morning blood pressure surge and cardiovascular events. A 5-year longitudinal study in normotensive and well-controlled hypertensive elderly. Arch Gerontol Geriatr 2009; 49: e105–e109.

    CAS  Article  Google Scholar 

  45. 45

    Caltagirone C, Spalletta G, Cangelosi M, Gianni W, Assisi A, Brancati AM et al. Decreased nocturnal systolic blood pressure fall in older subjects with depression. Aging Clin Exp Res 2009; 21: 292–297.

    Article  Google Scholar 

  46. 46

    Dimsdale JE, Mills P, Patterson T, Ziegler M, Dillon E . Effects of chronic stress on beta-adrenergic receptors in the homeless. Psychosom Med 1994; 56: 290–295.

    CAS  Article  Google Scholar 

  47. 47

    Schmieder RE, Rockstroh JK, Aepfelbacher F, Schulze B, Messerli FH . Gender-specific cardiovascular adaptation due to circadian blood pressure variations in essential hypertension. Am J Hypertens 1995; 8: 1160–1166.

    CAS  Article  Google Scholar 

  48. 48

    Tomfohr L, Cooper DC, Mills PJ, Nelesen RA, Dimsdale JE . Everyday discrimination and nocturnal blood pressure dipping in black and white Americans. Psychosom Med 2010; 72: 266–272.

    Article  Google Scholar 

  49. 49

    Routledge F, Fetridge-Durdle J . Nondipping blood pressure patterns among individuals with essential hypertension: a review of the literature. Eur J Cardiovasc Nurs 2007; 6: 9–26.

    Article  Google Scholar 

Download references


We gratefully acknowledge the assistance in data preparation of C Murakami, D Lopez, and S Lee. This research was supported by Research Grant HL-52102, National Heart Lung and Blood Institute.

Author information



Corresponding author

Correspondence to L FitzGerald.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

FitzGerald, L., Ottaviani, C., Goldstein, I. et al. Effects of dipping and psychological traits on morning surge in blood pressure in healthy people. J Hum Hypertens 26, 228–235 (2012).

Download citation


  • blood pressure
  • morning surge
  • depression
  • dipping
  • normotensive

Further reading


Quick links