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Relationship between alexithymia and variability of blood pressure measured with ABPM in hypertensive patients
General Hospital Psychiatry 60 (2019) 1–5
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Relationship between alexithymia and variability of blood pressure measured with ABPM in hypertensive patients
T
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Malgorzata Piotrowska-Półrolnika, Paweł Holasb, , Izabela Krejtza, Bartosz Symonidesc a
Psychology Department, SWPS University of Social Sciences and Humanities, Warsaw, Poland Faculty of Psychology, University of Warsaw, Warsaw, Poland c Department of Internal Medicine, Hypertension and Angiology, Medical University of Warsaw, Warsaw, Poland b
1. Introduction Hypertension (HT) is an important public health concern given that it affects 1.13 billion people worldwide [1]. It is marked by an adrenergic dysregulation, manifested by an increased level of noradrenaline in plasma and increased muscle tone due to hyperactivity of the sympathetic nerves [2]. Importantly, psychological factors such as alexithymic personality traits are linked to emotional dysregulation (e.g., [3]), which results in a dysregulation of the autonomic nervous system. In line with this assumption, research shows a high correlation (r = 0.8) between alexithymia and the norepinephrine/cortisol ratio in males [4]. Excessive activation of the sympathetic nervous system may cause, among others, exaggerated responses of heart rate and blood pressure to psychological stimuli [5]. Indeed, experimental psychophysiological studies document an increased resting sympathetic tone in alexithymic individuals or a greater heart rate or blood pressure (BP) reactivity to stressors (for review see [6]). Alexithymia, an emotional blindness, is manifested by difficulties in identifying and expressing feelings, in distinguishing emotions from bodily sensations, and in an externally orientated style of thinking [7,8]. As Mann [9] pointed out, psychosomatic research in HT is marked by the inconsistency of results from study to study, which could be attributed, first of all, to the inaccurate diagnosis of HT. The traditionally (and still commonly used) auscultatory technique for the assessment of BP is not only inaccurate, but it also only provides a ‘snapshot’ of BP behaviour in circumstances that may adversely affect the level of BP [10]. Ambulatory blood pressure monitoring (ABPM) provides the average of BP readings over a 24-h period. It allows for measurement of BP in real-life settings and during the night time [11]. ABPM is method recommended for out-of-office BP measurement and allows for the identification of suspected white-coat or masked HT [11]. ABPM is a better predictor than office BP of HT-mediated organ damage [12] and future cardiovascular outcomes including myocardial infarction or stroke [13,14]. Patients with a reduced night-time dip in BP have an increased cardiovascular risk [15]. Although, previous research has established an association between alexithymia and HT, we are
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aware of only one study exploring a link between alexithymia and BP as measured with ABPM; furthermore, this study was published in a nonEnglish language journal [16]. Therefore, the aim of the present study was to investigate the relationship between alexithymia and repeated 24-hour measurement of blood pressure with ABMP in patients with primary HT and in the control group of healthy individuals. Based on previous research, we hypothesized that (1) hypertensive patients would have elevated levels of alexithymia and their subscales compared to those of healthy control individuals; (2) that the level of alexithymia would be positively associated with BP independently of other variables; (3) that daily and nocturnal BP would be associated with alexithymia; and (4) and finally, that those individuals with low nocturnal drop of BP would have elevated alexithymia compared to that of others. 2. Method 2.1. Participants The following two groups of people were included in this study: individuals with primary HT (group hypertensive) and healthy persons (non-hypertensive group). 2.1.1. Hypertensive group Fifty-five participants with diagnosed primary HT (29 women and 27 men) ranging from ages 19–67 (M = 42.1; SD = 13.42) were tested. The exclusion criteria were the co-occurrences of HT comorbidities such as diabetes, myocardial infarction, cerebral stroke history or renal insufficiency. The mean daily (time of daily activity) systolic blood pressure (SBP) within this group was 130.05 (SD = 11.257), and the mean diastolic blood pressure (DBP) was 80.922 (SD = 8.06). The mean blood pressure values over 24 h was 122.59 (SD = 10.809) for SBP and 74.369 (SD = 7.699) for DBP. 67.9% participants with primary HT declared that they were treated for HT (N = 38) and 62.5% declared that they regularly took medications for HT prescribed by physicians (N = 35),
Corresponding author at: Faculty of Psychology, University of Warsaw, Krakowskie Przedmiescie 26/28, 00 927 Warsaw, Poland. E-mail address: [email protected] (P. Holas).
https://doi.org/10.1016/j.genhosppsych.2019.04.014 Received 8 January 2019; Received in revised form 17 March 2019; Accepted 23 April 2019 0163-8343/ © 2019 Published by Elsevier Inc.
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measures were collected during 24 h for each individual. Each participant wore a special cuff on the non-dominant arm and a small digital BP device on the waist belt. The BP device was connected to a cuff around the participant's upper arm. The ABPM is small enough for participants to not interfere with normal functioning during the day and with sleeping during night.
Table 1 Characteristics of the analytic sample.
TAS-20 score ≥ 49 Age Gender (females) Level of education Primary education Secondary education Higher education Overweight (BMI > 30) Marital status Married Not married Widowed Divorced
Hypertensive group (n = 39)
Non-hypertensive group (n = 37)
Group differences
30 42.86 (SE = 13.53) 23
7 36.67 (SE = 11.47) 26
Chi2 = 25.57⁎⁎⁎ t = 2.13⁎
3
1
Chi2 = 2.14
16
12
19 11
24 2
23 13 1 1
17 18 0 0
2.2.2. Questionnaires The level of alexithymia was measured with The Toronto Alexithymia Scale (TAS-20) [19,20]. TAS-20 has three scales: Difficulty Describing Emotions (DDE), Difficulty Describing Feelings (DDF) and The Difficulty Identifying Feeling (DIF). The [DELETED] version of the Tas-20 Total Score internal validity was good (alfa cronbacha = 0.904), the same for Difficulty Describing Feelings subscale (alfa cronbacha = 0.741), Difficulty Identifying Feeling subscale (alfa cronbacha = 0.835), and the Externally-Oriented Thinking subscale (alfa cronbacha = 0.837). TAS-20 was used, inter alia, in a study on the psychological aspects of HT [21]. An additional study supports that TAS-20 is applicable to intercultural research, and alexithymia can be treated as a universal trait that extends beyond cultural differences [22]. The clinical and demographic data was collected with the use of a clinical-demographic questionnaire (clinical data include information about diseases co-occurring with HT, such as cerebral stroke, heart attack and diabetes, sleeping time at night with ABPM, weight, height, demographic data include age, gender, education level) (Table 1).
Chi2 = 1.36
Chi2 = 6.99⁎⁎
Chi2 = 3.59
Note: Significant differences between number of participants with TAS high level, age and overweight. No significant differences between marital status, level of education and gender. ⁎ p < 0.05. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001.
with mean number of medication (M = 2.18; SD = 1.734). The duration of HT ranged from 0 to 35 years (M = 6.819; SD = 6.767), and the length of pharmacological treatment for the disease ranged from 0 to 20 years. Among the hypertensive group, 16 participants (6 women and 10 men) were suspected to have white-coat HT. Their raised BP was found in physician office using the auscultatory technique, whereas we found their mean daily SBP to be < 135 and DBP < 85 by ABPM assessment. The white-coat effect group was excluded from the analysis. A total of 39 participants was further selected, which included those that all took hypertensive drugs, had SBP higher or equal to 135 and/or DBP higher than or equal to 85. BMI of people suffering from HT was higher than the BMI of control group (see Table 1), what is consistent with the high comorbidity of HT and obesity (e.g. [17]).
2.3. Procedure After being presented with information about the study, participants signed the informed consent form. Next, participants were equipped with the ABPM device for 24 h. At home, participants filled in the TAS20 scale and provided demographic and clinical information. After 24 h, the ABPM device and questionnaires were collected back at the laboratory. The institutional review board (IRB) of the authors' institution approved the research procedure. 3. Results The results were analysed using the Student's t-test for independent variables. There were statistically significant differences in the average level of alexithymia (TAS total score) between the healthy control and primary hypertensive group (t (74) = 7.644; p < 0.001; Cohen's d = 0.307). The mean level of alexithymia in participants with primary HT was M = 59.41 (SD = 12.76), which was higher than that in the healthy control group [M = 37.59 (SD = 12.09)]. Cohen's d coefficient indicates the medium relationship between alexithymia and primary HT. The results for TAS scales are presented in Table 2. Grabe and colleagues [21] divided the participants into two groups using the quintiles of the alexithymia score (≥49 for the top 20% of the participants). In our study, 30 participants in the hypertensive group (76.92%) had high TAS values (TAS ≥ 49) and nine had TAS values that were lower than 49, compared to seven (19.92%) and 30 participants, in the control group, respectively. There were statistically significant positive correlations between the level of alexithymia (total score and subscales) and daily and night (individual sleeping time) systolic and diastolic blood pressure values (Table 2). Therefore, higher alexithymia levels correlated with higher 24-h BP values.
2.1.2. Non-hypertensive group This group included 37 healthy participants (26 females and 11 males) ranging from ages 18–62 (M = 36.27; SD = 11.56). Gender distribution, education level and age range was matched with those of the HT group. The mean daily (time of daily activity) SBP within this group was 115.529 (SD = 9.375), and the mean DBP was 72.794 (SD = 6.938). The mean blood pressure values over 24 h were 107.011 (SD = 8.073) for SBP and 65.66 (SD = 5762) for DBP. 2.2. Measures 2.2.1. The Ambulatory Blood Pressure Monitoring, ABPM The Ambulatory Blood Pressure Monitoring, ABPM [18] encompassed taking BP measurements every 20 min during the day (6:00 a.m. to 10:00 p.m.) and every 30 min at night (10:00 p.m. to 6:00 a.m.). According to the nomenclature, measurements should be made every 15–30 min [18]. The ABPM allows for assessment of systolic and DBP, heart rate and, among others, night drop in BP. The day and night BP data were measured, taking into account the individual sleep hours (on the day of measurement) for each participant. The use of such a procedure increases the reliability of measures and provides a more accurate differentiation between the average and the highest BP values during the sleep period and daily activities. Altogether, approximately 60 BP
3.1. Multilevel modelling The data (hypertensive and non-hypertensive group) were conceptualized as a three-level model: ABPM measures nested within day (daily activity vs night activity) and day nested within persons. The data were analysed using multilevel models with the HLM program 2
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Table 2 Statistics for t-tests for differences in the average level of alexithymia between the healthy control and primary hypertensive group and correlation between alexithymia (total score and subscales) and daily and night (sleeping time) systolic and diastolic BP. t-Test statistics
TAS DDF DIF EOT
Correlations statistics
t-Test
df
Coeff. (SE)
Cohen's d
M SBP sleeping time
M DBP sleeping time
M SBP daily activity
M DBP daily activity
7.644 4.19 2.911 13.871
74 74 74 74
2.854 0.956 1.393 0.990
0.307⁎⁎⁎ 0.974⁎⁎⁎ 0.695⁎⁎ 3.225⁎⁎⁎
0.386⁎⁎ 0.238⁎ 0.170 0.516⁎⁎⁎
0.359⁎⁎ 0.232⁎ 0.138 0.488⁎⁎⁎
0.472⁎⁎⁎ 0.352⁎⁎ 0.244⁎ 0.568⁎⁎⁎
0.331⁎⁎ 0.221 0.152 0.428⁎⁎⁎
Note: TAS: Total Alexithymia Score, DDF: Difficulty Describing Feeling, DIF: Difficulty Identifying Feeling, EOT: Externally-Oriented Thinking. ⁎ p < 0.05. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001.
[23]. The analyses followed the guidelines and procedures described by Nezlek [24].
Table 3 Group differences in blood pressure during daily activity and sleeping time. Blood pressure
χ2
Mean (SE)
3.2. Descriptive statistics of blood pressure We started with unconditional models (no predictors at either level of analysis). These models estimated the mean blood pressure and estimated the variance for each level of analysis. The model (1) is below. Within-person (level 1)
Systolic Daily activity Sleeping time Diastolic Daily activity Sleeping time
ABPM = β0k + rjk Between-persons (level 2)
⁎⁎ ⁎⁎⁎
β0k = γ00 + u 0k There were j ABPM measurements nested within k persons. The variance of r0jk is the within-ABPM (level-1) variance and the variance of u00k is the between-persons. Mean SBP was 119.22 and DBP was 73.33. The results indicated that DBP showed more variability within individual (DBP = 110.64) ambulatory blood pressure measurements (level-1) than between persons (level-2; SBP = 65.76). However, the variance for SBP (SBP within-ABPM = 168.39; SBP between-persons = 162.09) was similarly distributed among levels of analysis, which suggested higher possibility for between-persons differences in systolic than DBP.
Control
Hypertensive
117.07 (1.78) 102.68 (1.90)
128.146 (2.02) 112.99 (2.24)
16.89⁎⁎⁎ 12.37⁎⁎⁎
73.876 (1.24) 60.21 (1.08)
79.11 (1.38) 66.33 (1.52)
7.94⁎⁎ 0.79⁎⁎
p < 0.01. p < 0.001.
Table 4 Relationships between alexithymia and blood pressure. Alexithymia
Daily activity TAS DDF DIF EOT Sleeping time TAS DDF DIF EOT Final model Daily activity Group TAS Group × TAS Sleeping time Group TAS Group × TAS
3.3. Group differences between daily and night blood pressure Next, we examined differences between primary hypertensive and healthy controls in their mean daily and night blood pressure. To estimate differences in blood pressure between daily activity and sleeping time, we added two dummy coded predictors at the level-1 model (day and night), and we dropped the intercept from the level 1 equation (see [24], p.100). The between-group differences were also estimated by adding two dummy coded variables defining control and hypertensive groups to the person-level model, as shown in the model below (2). Within-person (level 1)
SBP
DBP
Coeff. (SE)
t-Test
Coeff. (SE)
t-Test
6.84 5.63 3.98 7.43
(1.17) (1.29) (1.52) (1.07)
5.85⁎⁎⁎ 4.38⁎⁎⁎ 2.61⁎ 6.96⁎⁎⁎
3.31 2.66 1.91 3.64
(1.02) (0.10) (1.10) (0.84)
3.26⁎⁎ 2.73⁎⁎ 1.61 4.35⁎⁎⁎
6.85 5.50 3.59 7.83
(1.18) (1.35) (1.47) (1.18)
5.81⁎⁎⁎ 4.09⁎⁎⁎ 2.43⁎ 6.45⁎⁎⁎
3.95 3.18 2.21 4.40
(0.86) (0.86) (1.05) (0.80)
4.62⁎⁎⁎ 3.71⁎⁎⁎ 2.11⁎ 5.52⁎⁎⁎
2.38 (1.61) 5.56 (1.47) −0.80 (1.47)
1.50 3.79⁎⁎⁎ <1
0.96 (1.10) 2.82 (1.20) −1.02 (1.20)
<1 2.34⁎ <1
1.95 (1.81) 5.78 (1.57) 0.11 (1.57)
1.08 3.69⁎⁎⁎ <1
1.20 (1.10) 3.30 (1.00) −0.22 (1.00)
1.14 3.28⁎⁎ <1
Note: TAS: Total Alexithymia Score, DDF: Difficulty Describing Feeling, DIF: Difficulty Identifying Feeling, EOT: Externally-Oriented Thinking. ⁎ p < 0.05. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001.
SBP = β1 (day) + β2 (night) + r Between-persons (level 2)
β1 = γ11 (Control) + γ11 (Hypertensive) + u1 β2 = γ21 (Control) + γ22 (Hypertensive) + u2
the level of alexithymia and blood pressure (see also [25]). In order to examine this relationship, we added a standardized alexithymia variable to the person-level model (see Table 4). As predicted, alexithymia was a significant predictor of blood pressure values. Higher alexithymia scores correlated with higher blood pressure measurements both during the day and sleeping time. This was true for the total score of alexithymia as well as its subscales, except for the subscale Difficulty in Identifying Feeling, which was not significantly
The analyses showed significant between group differences both in daily and night activity (Table 3). The primary hypertensive group had systematically higher blood pressure values compared to those of the healthy controls. 3.4. Relationships between alexithymia and blood pressure Our primary prediction concerned the positive relationship between 3
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an HT group compared with 16% alexithymic individuals in a healthy control sample. Jula et al. [25] similarly reported higher TAS-26 scores in newly diagnosed, untreated hypertensive individuals, compared with normotensive controls (TAS-26 is an earlier version of the TAS-20). Historically, psychosomatic studies in HT were focused mainly on consciously experienced negative emotional reactions, with anger and anxiety in particular, whereas little work has been done to assess the relationship of blood pressure and emotions that are not consciously experienced [9]. In our study, the association of HT with alexithymia, a personality concept related to repression [28], was evaluated. The results contribute to the growing evidence that elevation of blood pressure can be related to low emotional awareness, an emotional dysregulation that has an impact on autonomic nervous system dysfunctions. Our findings, however, extend previous research by evidencing that alexithymia is positively related to blood pressure values obtained during 24-hour measurements in both hypertensive and normotensive individuals. This was true for the total score of alexithymia, as well as for its three subscales: Difficulty Describing Emotions, Difficulty Describing Feelings and The Difficulty Identifying Feeling. Alexithymia was related to both daily and nocturnal BP. Importantly, alexithymia was found to be a significant predictor of blood pressure values, and when two predictors of blood pressure values were taken into multilevel modelling analysis: group (HT vs. normotensive) and alexithymia, only alexithymia was found to be a significant predictor of BP values. Therefore, alexithymia was a main predictor of blood pressure values both in normotensive and treated hypertensive individuals. These results highlight the importance of conducting further longitudinal, observational, and intervention research to better understand the predictive role of alexithymia and poor emotional awareness in relation to the risk for primary HT and its evolution. Future studies should also evaluate behavioural interventions intended to target emotional awareness and to increase adaptive emotional regulation in hypertensive individuals. In subsequent studies, it would be important to check whether emotional regulation training would translate into better control of BP in patients suffering from primary HT. The current study has certain limitations. Although we documented that alexithymia is associated with HT, our study is cross-sectional in nature and cannot prove the causality of the reported association. Future studies may benefit from the evaluation of longitudinal effects of alexithymia on the incidence and course of HT. Furthermore, alexithymia predicted BP values in the HT group, even though 62.5% of them took medication for HT regularly. Data regarding drug adherence was not collected in this study. There are some indications that alexithymia has negative effects on drug adherence in several medical conditions such as asthma [29]. It has recently been shown that the majority of studied individuals in treatment-resistant HT were poorly or non-adherent, and that these patients were characterized by elevated alexithymia [30]. Future studies should evaluate the association of alexithymia, drug adherence and BP control in HT (e.g. [31]). Despite these limitations, our study provides more insight on important issues regarding the link between emotional dysregulation in the form of alexithymia and primary HT.
related to daily DBP. In a final step, we tested the model with groups and alexithymia were included as predictors of blood pressure values, along with their interaction term (see Table 4). The interaction term was added uncentered, and it was calculated by multiplying the contrast coded variable defying group (code: −1 for controls, +1 for hypertensive individuals) by standardized values of Total Alexithymia Scores. When introduced together into the model, only alexithymia significantly predicted blood pressure values. Within-person (level 1)
SBP = β1 (day) + β2 (night) r Between-persons (level 2)
β1 = γ10 + γ11 (group) + γ12 (alexithymia) + γ12 (interaction) + u1 β2 = γ20 + γ21 (group) + γ22 (alexithymia) + γ23 (interaction) + u2 3.5. Group differences in alexithymia In order to verify if there are differences in the values of alexithymia between dippers and nondippers in levels of alexithymia in HT vs. control groups, a series of t-tests for independent groups were performed, and in cases where the normality of distribution was not met, their nonparametric equivalent, the Mann-Whitney U test was used. For each person, the average systolic and diastolic BP values were measured during the day and night and were calculated. Based on this, the average night BP value means were measured during a person's sleep time and the average daily BP value means were measured during the daily activity time. Taking into account that the declared hours of sleep are unique — for ABPM, constant calculations for the day (6 a.m.–10 p.m.) and night (10 p.m.–6 a.m.) are usually used. On the basis of the collected results, it was assessed whether people with primary HT differed from the control group in levels of alexithymia and whether there was a link between alexithymia and BP values. In both HT and control groups, the number of individuals were counted who had a higher or equal to 10% drop of BP (dippers) and those who had a lower than 10% drop of BP (non-dippers). There were 39.3% (n = 22) non dippers in the HT group and 27% (n = 10) in the control group. Night drop was also calculated, just like the average, for individual participants sleep activities time. There were no significant differences in the values of alexithymia between dippers and nondippers (t (74) = 0.327; p = 0.745). The correlation between the percentage of nocturnal pressure drop and alexithymia was also not significant (r = −0.024; p = 0.839). 4. Discussion The relationship between alexithymia and variability of blood pressure was investigated using the 24-hour ABPM method for patients with primary HT and normotensive controls. The following hypotheses were addressed: (1) hypertensive patients would have elevated levels of alexithymia and their subscales compared to those of healthy controls; (2) the level of alexithymia would correlate positively with BP independently of other variables; (3) daily and nocturnal BP would be associated with alexithymia; and (4) and finally, individuals with low nocturnal drops of BP would have elevated alexithymia compared to that of others. In line with our prediction, hypertensive patients exhibited elevated levels of alexithymia compared to those of the control group. Similarly, hypertensive patients were more frequently alexithymic than normal control individuals (76.92% compared to 19.92%, respectively). Our results corroborate the findings of four previous studies on an association between alexithymia and HT [21,25–27]. For example, Todarello et al. [27] reported that 55% of alexithymic individuals belonged to
5. Conclusion In summary, the current results demonstrate statistically significant differences in the levels of alexithymia between hypertensive and normotensive participants and a significant positive correlation between alexithymia and BP values in both groups. To conclude, emotional dysregulation in the form of alexithymia (i.e., poor ability to identify, experience and express emotions) is associated with increased blood pressure and predicts BP values, irrespective of its normal or hypertensive range.
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Acknowledgement
0000000000000355. [15] European Society of Hypertension practice guidelines for ambulatory blood pressure: Journal of Hypertension. https://journals.lww.com/jhypertension/Abstract/ 2014/07000/European_Society_of_Hypertension_practice.2.aspx, Accessed date: 7 January 2019. [16] Lyshova OV, Provotorov VM, Chernov I. Clinical characteristics of hypertensive disease in patients with alexithymia. Kardiologiia 2002;42(6):47–50. [17] Grundy SM. Obesity, metabolic syndrome, and cardiovascular disease. J Clin Endocrinol Metabol 2004;89(6):2595–600. https://doi.org/10.1210/jc.2004-0372. [18] Pickering TG, Shimbo D, Haas D. Ambulatory blood-pressure monitoring. New Engl J Med 2006;354(22):2368–74. https://doi.org/10.1056/NEJMra060433. [19] Bagby RM, Parker JD, Taylor GJ. The twenty-item Toronto Alexithymia Scale—I. Item selection and cross-validation of the factor structure. J Psychosom Res 1994;38(1):23–32. https://doi.org/10.1016/0022-3999(94)90005-1. [20] Bagby RM, Taylor GJ, Parker JD. The twenty-item Toronto alexithymia scale—II. Convergent, discriminant, and concurrent validity. J Psychosom Res 1994;38(1):33–40. https://doi.org/10.1016/0022-3999(94)90006-X. [21] Grabe HJ, Schwahn C, Barnow S, et al. Alexithymia, hypertension, and subclinical atherosclerosis in the general population. J Psychosom Res 2010;68(2):139–47. https://doi.org/10.1016/j.jpsychores.2009.07.015. [22] Taylor GJ, Bagby RM, Parker JDA. The 20-Item Toronto Alexithymia Scale: IV. Reliability and factorial validity in different languages and cultures. J Psychosom Res 2003;55(3):277–83. https://doi.org/10.1016/S0022-3999(02)00601-3. [23] Raudenbush SW, Bryk AS, Cheong YF, Congdon R, Du Toit M. Hierarchical linear and nonlinear modeling (HLM7). vol. 1112. Lincolnwood, IL: Scientific Software International; 2011. [24] Nezlek JB. Multilevel modeling for social and personality psychology. SAGE Publications Ltd; 2011. [25] Jula A, Salminen JK, Saarijärvi S. Alexithymia: a facet of essential hypertension. Hypertension 1999;33(4):1057–61. https://doi.org/10.1161/01.HYP.33.4.1057. [26] Rafanelli C, Ruini C. Assessment of psychological well-being in psychosomatic medicine. Psychosom Assess 2012;32:182–202. https://doi.org/10.1159/ 000330021. [27] Todarello O, Taylor GJ, Parker JDA, Fanelli M. Alexithymia in essential hypertensive and psychiatric outpatients: a comparative study. J Psychosom Res 1995;39(8):987–94. https://doi.org/10.1016/0022-3999(95)00506-4. [28] Cumes-Rayner DP, Price J. Understanding hypertensive behaviour—I. Preference not to disclose. J Psychosom Res 1989;33(1):63–74. [29] Chugg K, Barton C, Antic R, Crockett A. The impact of alexithymia on asthma patient management and communication with health care providers: a pilot study. J Asthma 2009;46(2):126–9. https://doi.org/10.1080/02770900802468525. [30] Georges C, Berra E, Capron A, et al. [op. 2b. 07] assessment of drug adherence and psychological profile in patients with apparently treatment-resistant hypertension. J Hypertens 2017;35:e16–7. https://doi.org/10.1097/01.hjh.0000523024. 83956.1d. [31] Petit G, Berra E, Georges CMG, et al. Impact of psychological profile on drug adherence and drug resistance in patients with apparently treatment-resistant hypertension. Blood Press 2018;27(6):358–67. https://doi.org/10.1080/08037051. 2018.1476058.
The project was funded with the BST grant WP/2015/B/50 of the [DELETED]. References [1] WHO | World health statistics 2017: monitoring health for the SDGs. WHO. http:// www.who.int/gho/publications/world_health_statistics/2017/en/. Accessed January 7, 2019. [2] Mancia G, Grassi G. The autonomic nervous system and hypertension. Circ Res 2014;114(11):1804–14. https://doi.org/10.1161/CIRCRESAHA.114.302524. [3] Piotrowska-Półrolnik MA, Krejtz I, Holas P. Emotional regulation and the occurrence and course of hypertension. J Educ Health Sport 2017;7(5):315–28. https:// doi.org/10.5281/zenodo.580863. [4] Spitzer C, Brandl S, Rose H-J, Nauck M, Freyberger HJ. Gender-specific association of alexithymia and norepinephrine/cortisol ratios. A preliminary report. J Psychosom Res 2005;59(2):73–6. https://doi.org/10.1016/j.jpsychores.2004.07. 006. [5] Schwartz AR, Gerin W, Davidson KW, et al. Toward a causal model of cardiovascular responses to stress and the development of cardiovascular disease. Psychosom Med 2003;65(1):22. https://doi.org/10.1097/01.PSY.0000046075.79922.61. [6] Lumley MA, Neely LC, Burger AJ. The assessment of alexithymia in medical settings: implications for understanding and treating health problems. J Pers Assess 2007;89(3):230–46. https://doi.org/10.1080/00223890701629698. [7] Nemiah JC. Alexithymia: a view of the psychosomatic process. Mod Trends Psychosom Med 1976;3:430–9. [8] Taylor GJ, Bagby RM, Parker JD. Disorders of affect regulation: Alexithymia in medical and psychiatric illness. Cambridge University Press; 1999. [9] Mann SJ. Psychosomatic research in hypertension: the lack of impact of decades of research and new directions to consider. J Clin Hypertens 2012;14(10):657–64. https://doi.org/10.1111/j.1751-7176.2012.00686.x. [10] O'Brien E. Twenty-four-hour ambulatory blood pressure measurement in clinical practice and research: a critical review of a technique in need of implementation. J Intern Med. 2011;269(5):478–495. doi:https://doi.org/10.1111/j.1365-2796.2011. 02356.x. [11] 2018 ESC/ESH Guidelines for the management of arterial hypertension | European Heart Journal | Oxford Academic. https://academic.oup.com/eurheartj/article/39/ 33/3021/5079119, Accessed date: 7 January 2019. [12] Gaborieau V, Delarche N, Gosse P. Ambulatory blood pressure monitoring versus self-measurement of blood pressure at home: correlation with target organ damage. J Hypertens 2008;26(10):1919. https://doi.org/10.1097/HJH.0b013e32830c4368. [13] Banegas JR, Ruilope LM, de la Sierra A, et al. Relationship between clinic and ambulatory blood-pressure measurements and mortality. New Engl J Med 2018;378(16):1509–20. https://doi.org/10.1056/NEJMoa1712231. [14] Roush GC, Fagard RH, Salles GF, et al. Prognostic impact from clinic, daytime, and night-time systolic blood pressure in nine cohorts of 13 844 patients with hypertension. J Hypertens 2014;32(12):2332. https://doi.org/10.1097/HJH.
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Relationship between alexithymia and variability of blood pressure measured with ABPM in hypertensive patients
T
⁎
Malgorzata Piotrowska-Półrolnika, Paweł Holasb, , Izabela Krejtza, Bartosz Symonidesc a
Psychology Department, SWPS University of Social Sciences and Humanities, Warsaw, Poland Faculty of Psychology, University of Warsaw, Warsaw, Poland c Department of Internal Medicine, Hypertension and Angiology, Medical University of Warsaw, Warsaw, Poland b
1. Introduction Hypertension (HT) is an important public health concern given that it affects 1.13 billion people worldwide [1]. It is marked by an adrenergic dysregulation, manifested by an increased level of noradrenaline in plasma and increased muscle tone due to hyperactivity of the sympathetic nerves [2]. Importantly, psychological factors such as alexithymic personality traits are linked to emotional dysregulation (e.g., [3]), which results in a dysregulation of the autonomic nervous system. In line with this assumption, research shows a high correlation (r = 0.8) between alexithymia and the norepinephrine/cortisol ratio in males [4]. Excessive activation of the sympathetic nervous system may cause, among others, exaggerated responses of heart rate and blood pressure to psychological stimuli [5]. Indeed, experimental psychophysiological studies document an increased resting sympathetic tone in alexithymic individuals or a greater heart rate or blood pressure (BP) reactivity to stressors (for review see [6]). Alexithymia, an emotional blindness, is manifested by difficulties in identifying and expressing feelings, in distinguishing emotions from bodily sensations, and in an externally orientated style of thinking [7,8]. As Mann [9] pointed out, psychosomatic research in HT is marked by the inconsistency of results from study to study, which could be attributed, first of all, to the inaccurate diagnosis of HT. The traditionally (and still commonly used) auscultatory technique for the assessment of BP is not only inaccurate, but it also only provides a ‘snapshot’ of BP behaviour in circumstances that may adversely affect the level of BP [10]. Ambulatory blood pressure monitoring (ABPM) provides the average of BP readings over a 24-h period. It allows for measurement of BP in real-life settings and during the night time [11]. ABPM is method recommended for out-of-office BP measurement and allows for the identification of suspected white-coat or masked HT [11]. ABPM is a better predictor than office BP of HT-mediated organ damage [12] and future cardiovascular outcomes including myocardial infarction or stroke [13,14]. Patients with a reduced night-time dip in BP have an increased cardiovascular risk [15]. Although, previous research has established an association between alexithymia and HT, we are
⁎
aware of only one study exploring a link between alexithymia and BP as measured with ABPM; furthermore, this study was published in a nonEnglish language journal [16]. Therefore, the aim of the present study was to investigate the relationship between alexithymia and repeated 24-hour measurement of blood pressure with ABMP in patients with primary HT and in the control group of healthy individuals. Based on previous research, we hypothesized that (1) hypertensive patients would have elevated levels of alexithymia and their subscales compared to those of healthy control individuals; (2) that the level of alexithymia would be positively associated with BP independently of other variables; (3) that daily and nocturnal BP would be associated with alexithymia; and (4) and finally, that those individuals with low nocturnal drop of BP would have elevated alexithymia compared to that of others. 2. Method 2.1. Participants The following two groups of people were included in this study: individuals with primary HT (group hypertensive) and healthy persons (non-hypertensive group). 2.1.1. Hypertensive group Fifty-five participants with diagnosed primary HT (29 women and 27 men) ranging from ages 19–67 (M = 42.1; SD = 13.42) were tested. The exclusion criteria were the co-occurrences of HT comorbidities such as diabetes, myocardial infarction, cerebral stroke history or renal insufficiency. The mean daily (time of daily activity) systolic blood pressure (SBP) within this group was 130.05 (SD = 11.257), and the mean diastolic blood pressure (DBP) was 80.922 (SD = 8.06). The mean blood pressure values over 24 h was 122.59 (SD = 10.809) for SBP and 74.369 (SD = 7.699) for DBP. 67.9% participants with primary HT declared that they were treated for HT (N = 38) and 62.5% declared that they regularly took medications for HT prescribed by physicians (N = 35),
Corresponding author at: Faculty of Psychology, University of Warsaw, Krakowskie Przedmiescie 26/28, 00 927 Warsaw, Poland. E-mail address: [email protected] (P. Holas).
https://doi.org/10.1016/j.genhosppsych.2019.04.014 Received 8 January 2019; Received in revised form 17 March 2019; Accepted 23 April 2019 0163-8343/ © 2019 Published by Elsevier Inc.
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measures were collected during 24 h for each individual. Each participant wore a special cuff on the non-dominant arm and a small digital BP device on the waist belt. The BP device was connected to a cuff around the participant's upper arm. The ABPM is small enough for participants to not interfere with normal functioning during the day and with sleeping during night.
Table 1 Characteristics of the analytic sample.
TAS-20 score ≥ 49 Age Gender (females) Level of education Primary education Secondary education Higher education Overweight (BMI > 30) Marital status Married Not married Widowed Divorced
Hypertensive group (n = 39)
Non-hypertensive group (n = 37)
Group differences
30 42.86 (SE = 13.53) 23
7 36.67 (SE = 11.47) 26
Chi2 = 25.57⁎⁎⁎ t = 2.13⁎
3
1
Chi2 = 2.14
16
12
19 11
24 2
23 13 1 1
17 18 0 0
2.2.2. Questionnaires The level of alexithymia was measured with The Toronto Alexithymia Scale (TAS-20) [19,20]. TAS-20 has three scales: Difficulty Describing Emotions (DDE), Difficulty Describing Feelings (DDF) and The Difficulty Identifying Feeling (DIF). The [DELETED] version of the Tas-20 Total Score internal validity was good (alfa cronbacha = 0.904), the same for Difficulty Describing Feelings subscale (alfa cronbacha = 0.741), Difficulty Identifying Feeling subscale (alfa cronbacha = 0.835), and the Externally-Oriented Thinking subscale (alfa cronbacha = 0.837). TAS-20 was used, inter alia, in a study on the psychological aspects of HT [21]. An additional study supports that TAS-20 is applicable to intercultural research, and alexithymia can be treated as a universal trait that extends beyond cultural differences [22]. The clinical and demographic data was collected with the use of a clinical-demographic questionnaire (clinical data include information about diseases co-occurring with HT, such as cerebral stroke, heart attack and diabetes, sleeping time at night with ABPM, weight, height, demographic data include age, gender, education level) (Table 1).
Chi2 = 1.36
Chi2 = 6.99⁎⁎
Chi2 = 3.59
Note: Significant differences between number of participants with TAS high level, age and overweight. No significant differences between marital status, level of education and gender. ⁎ p < 0.05. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001.
with mean number of medication (M = 2.18; SD = 1.734). The duration of HT ranged from 0 to 35 years (M = 6.819; SD = 6.767), and the length of pharmacological treatment for the disease ranged from 0 to 20 years. Among the hypertensive group, 16 participants (6 women and 10 men) were suspected to have white-coat HT. Their raised BP was found in physician office using the auscultatory technique, whereas we found their mean daily SBP to be < 135 and DBP < 85 by ABPM assessment. The white-coat effect group was excluded from the analysis. A total of 39 participants was further selected, which included those that all took hypertensive drugs, had SBP higher or equal to 135 and/or DBP higher than or equal to 85. BMI of people suffering from HT was higher than the BMI of control group (see Table 1), what is consistent with the high comorbidity of HT and obesity (e.g. [17]).
2.3. Procedure After being presented with information about the study, participants signed the informed consent form. Next, participants were equipped with the ABPM device for 24 h. At home, participants filled in the TAS20 scale and provided demographic and clinical information. After 24 h, the ABPM device and questionnaires were collected back at the laboratory. The institutional review board (IRB) of the authors' institution approved the research procedure. 3. Results The results were analysed using the Student's t-test for independent variables. There were statistically significant differences in the average level of alexithymia (TAS total score) between the healthy control and primary hypertensive group (t (74) = 7.644; p < 0.001; Cohen's d = 0.307). The mean level of alexithymia in participants with primary HT was M = 59.41 (SD = 12.76), which was higher than that in the healthy control group [M = 37.59 (SD = 12.09)]. Cohen's d coefficient indicates the medium relationship between alexithymia and primary HT. The results for TAS scales are presented in Table 2. Grabe and colleagues [21] divided the participants into two groups using the quintiles of the alexithymia score (≥49 for the top 20% of the participants). In our study, 30 participants in the hypertensive group (76.92%) had high TAS values (TAS ≥ 49) and nine had TAS values that were lower than 49, compared to seven (19.92%) and 30 participants, in the control group, respectively. There were statistically significant positive correlations between the level of alexithymia (total score and subscales) and daily and night (individual sleeping time) systolic and diastolic blood pressure values (Table 2). Therefore, higher alexithymia levels correlated with higher 24-h BP values.
2.1.2. Non-hypertensive group This group included 37 healthy participants (26 females and 11 males) ranging from ages 18–62 (M = 36.27; SD = 11.56). Gender distribution, education level and age range was matched with those of the HT group. The mean daily (time of daily activity) SBP within this group was 115.529 (SD = 9.375), and the mean DBP was 72.794 (SD = 6.938). The mean blood pressure values over 24 h were 107.011 (SD = 8.073) for SBP and 65.66 (SD = 5762) for DBP. 2.2. Measures 2.2.1. The Ambulatory Blood Pressure Monitoring, ABPM The Ambulatory Blood Pressure Monitoring, ABPM [18] encompassed taking BP measurements every 20 min during the day (6:00 a.m. to 10:00 p.m.) and every 30 min at night (10:00 p.m. to 6:00 a.m.). According to the nomenclature, measurements should be made every 15–30 min [18]. The ABPM allows for assessment of systolic and DBP, heart rate and, among others, night drop in BP. The day and night BP data were measured, taking into account the individual sleep hours (on the day of measurement) for each participant. The use of such a procedure increases the reliability of measures and provides a more accurate differentiation between the average and the highest BP values during the sleep period and daily activities. Altogether, approximately 60 BP
3.1. Multilevel modelling The data (hypertensive and non-hypertensive group) were conceptualized as a three-level model: ABPM measures nested within day (daily activity vs night activity) and day nested within persons. The data were analysed using multilevel models with the HLM program 2
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Table 2 Statistics for t-tests for differences in the average level of alexithymia between the healthy control and primary hypertensive group and correlation between alexithymia (total score and subscales) and daily and night (sleeping time) systolic and diastolic BP. t-Test statistics
TAS DDF DIF EOT
Correlations statistics
t-Test
df
Coeff. (SE)
Cohen's d
M SBP sleeping time
M DBP sleeping time
M SBP daily activity
M DBP daily activity
7.644 4.19 2.911 13.871
74 74 74 74
2.854 0.956 1.393 0.990
0.307⁎⁎⁎ 0.974⁎⁎⁎ 0.695⁎⁎ 3.225⁎⁎⁎
0.386⁎⁎ 0.238⁎ 0.170 0.516⁎⁎⁎
0.359⁎⁎ 0.232⁎ 0.138 0.488⁎⁎⁎
0.472⁎⁎⁎ 0.352⁎⁎ 0.244⁎ 0.568⁎⁎⁎
0.331⁎⁎ 0.221 0.152 0.428⁎⁎⁎
Note: TAS: Total Alexithymia Score, DDF: Difficulty Describing Feeling, DIF: Difficulty Identifying Feeling, EOT: Externally-Oriented Thinking. ⁎ p < 0.05. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001.
[23]. The analyses followed the guidelines and procedures described by Nezlek [24].
Table 3 Group differences in blood pressure during daily activity and sleeping time. Blood pressure
χ2
Mean (SE)
3.2. Descriptive statistics of blood pressure We started with unconditional models (no predictors at either level of analysis). These models estimated the mean blood pressure and estimated the variance for each level of analysis. The model (1) is below. Within-person (level 1)
Systolic Daily activity Sleeping time Diastolic Daily activity Sleeping time
ABPM = β0k + rjk Between-persons (level 2)
⁎⁎ ⁎⁎⁎
β0k = γ00 + u 0k There were j ABPM measurements nested within k persons. The variance of r0jk is the within-ABPM (level-1) variance and the variance of u00k is the between-persons. Mean SBP was 119.22 and DBP was 73.33. The results indicated that DBP showed more variability within individual (DBP = 110.64) ambulatory blood pressure measurements (level-1) than between persons (level-2; SBP = 65.76). However, the variance for SBP (SBP within-ABPM = 168.39; SBP between-persons = 162.09) was similarly distributed among levels of analysis, which suggested higher possibility for between-persons differences in systolic than DBP.
Control
Hypertensive
117.07 (1.78) 102.68 (1.90)
128.146 (2.02) 112.99 (2.24)
16.89⁎⁎⁎ 12.37⁎⁎⁎
73.876 (1.24) 60.21 (1.08)
79.11 (1.38) 66.33 (1.52)
7.94⁎⁎ 0.79⁎⁎
p < 0.01. p < 0.001.
Table 4 Relationships between alexithymia and blood pressure. Alexithymia
Daily activity TAS DDF DIF EOT Sleeping time TAS DDF DIF EOT Final model Daily activity Group TAS Group × TAS Sleeping time Group TAS Group × TAS
3.3. Group differences between daily and night blood pressure Next, we examined differences between primary hypertensive and healthy controls in their mean daily and night blood pressure. To estimate differences in blood pressure between daily activity and sleeping time, we added two dummy coded predictors at the level-1 model (day and night), and we dropped the intercept from the level 1 equation (see [24], p.100). The between-group differences were also estimated by adding two dummy coded variables defining control and hypertensive groups to the person-level model, as shown in the model below (2). Within-person (level 1)
SBP
DBP
Coeff. (SE)
t-Test
Coeff. (SE)
t-Test
6.84 5.63 3.98 7.43
(1.17) (1.29) (1.52) (1.07)
5.85⁎⁎⁎ 4.38⁎⁎⁎ 2.61⁎ 6.96⁎⁎⁎
3.31 2.66 1.91 3.64
(1.02) (0.10) (1.10) (0.84)
3.26⁎⁎ 2.73⁎⁎ 1.61 4.35⁎⁎⁎
6.85 5.50 3.59 7.83
(1.18) (1.35) (1.47) (1.18)
5.81⁎⁎⁎ 4.09⁎⁎⁎ 2.43⁎ 6.45⁎⁎⁎
3.95 3.18 2.21 4.40
(0.86) (0.86) (1.05) (0.80)
4.62⁎⁎⁎ 3.71⁎⁎⁎ 2.11⁎ 5.52⁎⁎⁎
2.38 (1.61) 5.56 (1.47) −0.80 (1.47)
1.50 3.79⁎⁎⁎ <1
0.96 (1.10) 2.82 (1.20) −1.02 (1.20)
<1 2.34⁎ <1
1.95 (1.81) 5.78 (1.57) 0.11 (1.57)
1.08 3.69⁎⁎⁎ <1
1.20 (1.10) 3.30 (1.00) −0.22 (1.00)
1.14 3.28⁎⁎ <1
Note: TAS: Total Alexithymia Score, DDF: Difficulty Describing Feeling, DIF: Difficulty Identifying Feeling, EOT: Externally-Oriented Thinking. ⁎ p < 0.05. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001.
SBP = β1 (day) + β2 (night) + r Between-persons (level 2)
β1 = γ11 (Control) + γ11 (Hypertensive) + u1 β2 = γ21 (Control) + γ22 (Hypertensive) + u2
the level of alexithymia and blood pressure (see also [25]). In order to examine this relationship, we added a standardized alexithymia variable to the person-level model (see Table 4). As predicted, alexithymia was a significant predictor of blood pressure values. Higher alexithymia scores correlated with higher blood pressure measurements both during the day and sleeping time. This was true for the total score of alexithymia as well as its subscales, except for the subscale Difficulty in Identifying Feeling, which was not significantly
The analyses showed significant between group differences both in daily and night activity (Table 3). The primary hypertensive group had systematically higher blood pressure values compared to those of the healthy controls. 3.4. Relationships between alexithymia and blood pressure Our primary prediction concerned the positive relationship between 3
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an HT group compared with 16% alexithymic individuals in a healthy control sample. Jula et al. [25] similarly reported higher TAS-26 scores in newly diagnosed, untreated hypertensive individuals, compared with normotensive controls (TAS-26 is an earlier version of the TAS-20). Historically, psychosomatic studies in HT were focused mainly on consciously experienced negative emotional reactions, with anger and anxiety in particular, whereas little work has been done to assess the relationship of blood pressure and emotions that are not consciously experienced [9]. In our study, the association of HT with alexithymia, a personality concept related to repression [28], was evaluated. The results contribute to the growing evidence that elevation of blood pressure can be related to low emotional awareness, an emotional dysregulation that has an impact on autonomic nervous system dysfunctions. Our findings, however, extend previous research by evidencing that alexithymia is positively related to blood pressure values obtained during 24-hour measurements in both hypertensive and normotensive individuals. This was true for the total score of alexithymia, as well as for its three subscales: Difficulty Describing Emotions, Difficulty Describing Feelings and The Difficulty Identifying Feeling. Alexithymia was related to both daily and nocturnal BP. Importantly, alexithymia was found to be a significant predictor of blood pressure values, and when two predictors of blood pressure values were taken into multilevel modelling analysis: group (HT vs. normotensive) and alexithymia, only alexithymia was found to be a significant predictor of BP values. Therefore, alexithymia was a main predictor of blood pressure values both in normotensive and treated hypertensive individuals. These results highlight the importance of conducting further longitudinal, observational, and intervention research to better understand the predictive role of alexithymia and poor emotional awareness in relation to the risk for primary HT and its evolution. Future studies should also evaluate behavioural interventions intended to target emotional awareness and to increase adaptive emotional regulation in hypertensive individuals. In subsequent studies, it would be important to check whether emotional regulation training would translate into better control of BP in patients suffering from primary HT. The current study has certain limitations. Although we documented that alexithymia is associated with HT, our study is cross-sectional in nature and cannot prove the causality of the reported association. Future studies may benefit from the evaluation of longitudinal effects of alexithymia on the incidence and course of HT. Furthermore, alexithymia predicted BP values in the HT group, even though 62.5% of them took medication for HT regularly. Data regarding drug adherence was not collected in this study. There are some indications that alexithymia has negative effects on drug adherence in several medical conditions such as asthma [29]. It has recently been shown that the majority of studied individuals in treatment-resistant HT were poorly or non-adherent, and that these patients were characterized by elevated alexithymia [30]. Future studies should evaluate the association of alexithymia, drug adherence and BP control in HT (e.g. [31]). Despite these limitations, our study provides more insight on important issues regarding the link between emotional dysregulation in the form of alexithymia and primary HT.
related to daily DBP. In a final step, we tested the model with groups and alexithymia were included as predictors of blood pressure values, along with their interaction term (see Table 4). The interaction term was added uncentered, and it was calculated by multiplying the contrast coded variable defying group (code: −1 for controls, +1 for hypertensive individuals) by standardized values of Total Alexithymia Scores. When introduced together into the model, only alexithymia significantly predicted blood pressure values. Within-person (level 1)
SBP = β1 (day) + β2 (night) r Between-persons (level 2)
β1 = γ10 + γ11 (group) + γ12 (alexithymia) + γ12 (interaction) + u1 β2 = γ20 + γ21 (group) + γ22 (alexithymia) + γ23 (interaction) + u2 3.5. Group differences in alexithymia In order to verify if there are differences in the values of alexithymia between dippers and nondippers in levels of alexithymia in HT vs. control groups, a series of t-tests for independent groups were performed, and in cases where the normality of distribution was not met, their nonparametric equivalent, the Mann-Whitney U test was used. For each person, the average systolic and diastolic BP values were measured during the day and night and were calculated. Based on this, the average night BP value means were measured during a person's sleep time and the average daily BP value means were measured during the daily activity time. Taking into account that the declared hours of sleep are unique — for ABPM, constant calculations for the day (6 a.m.–10 p.m.) and night (10 p.m.–6 a.m.) are usually used. On the basis of the collected results, it was assessed whether people with primary HT differed from the control group in levels of alexithymia and whether there was a link between alexithymia and BP values. In both HT and control groups, the number of individuals were counted who had a higher or equal to 10% drop of BP (dippers) and those who had a lower than 10% drop of BP (non-dippers). There were 39.3% (n = 22) non dippers in the HT group and 27% (n = 10) in the control group. Night drop was also calculated, just like the average, for individual participants sleep activities time. There were no significant differences in the values of alexithymia between dippers and nondippers (t (74) = 0.327; p = 0.745). The correlation between the percentage of nocturnal pressure drop and alexithymia was also not significant (r = −0.024; p = 0.839). 4. Discussion The relationship between alexithymia and variability of blood pressure was investigated using the 24-hour ABPM method for patients with primary HT and normotensive controls. The following hypotheses were addressed: (1) hypertensive patients would have elevated levels of alexithymia and their subscales compared to those of healthy controls; (2) the level of alexithymia would correlate positively with BP independently of other variables; (3) daily and nocturnal BP would be associated with alexithymia; and (4) and finally, individuals with low nocturnal drops of BP would have elevated alexithymia compared to that of others. In line with our prediction, hypertensive patients exhibited elevated levels of alexithymia compared to those of the control group. Similarly, hypertensive patients were more frequently alexithymic than normal control individuals (76.92% compared to 19.92%, respectively). Our results corroborate the findings of four previous studies on an association between alexithymia and HT [21,25–27]. For example, Todarello et al. [27] reported that 55% of alexithymic individuals belonged to
5. Conclusion In summary, the current results demonstrate statistically significant differences in the levels of alexithymia between hypertensive and normotensive participants and a significant positive correlation between alexithymia and BP values in both groups. To conclude, emotional dysregulation in the form of alexithymia (i.e., poor ability to identify, experience and express emotions) is associated with increased blood pressure and predicts BP values, irrespective of its normal or hypertensive range.
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Acknowledgement
0000000000000355. [15] European Society of Hypertension practice guidelines for ambulatory blood pressure: Journal of Hypertension. https://journals.lww.com/jhypertension/Abstract/ 2014/07000/European_Society_of_Hypertension_practice.2.aspx, Accessed date: 7 January 2019. [16] Lyshova OV, Provotorov VM, Chernov I. Clinical characteristics of hypertensive disease in patients with alexithymia. Kardiologiia 2002;42(6):47–50. [17] Grundy SM. Obesity, metabolic syndrome, and cardiovascular disease. J Clin Endocrinol Metabol 2004;89(6):2595–600. https://doi.org/10.1210/jc.2004-0372. [18] Pickering TG, Shimbo D, Haas D. Ambulatory blood-pressure monitoring. New Engl J Med 2006;354(22):2368–74. https://doi.org/10.1056/NEJMra060433. [19] Bagby RM, Parker JD, Taylor GJ. The twenty-item Toronto Alexithymia Scale—I. Item selection and cross-validation of the factor structure. J Psychosom Res 1994;38(1):23–32. https://doi.org/10.1016/0022-3999(94)90005-1. [20] Bagby RM, Taylor GJ, Parker JD. The twenty-item Toronto alexithymia scale—II. Convergent, discriminant, and concurrent validity. J Psychosom Res 1994;38(1):33–40. https://doi.org/10.1016/0022-3999(94)90006-X. [21] Grabe HJ, Schwahn C, Barnow S, et al. Alexithymia, hypertension, and subclinical atherosclerosis in the general population. J Psychosom Res 2010;68(2):139–47. https://doi.org/10.1016/j.jpsychores.2009.07.015. [22] Taylor GJ, Bagby RM, Parker JDA. The 20-Item Toronto Alexithymia Scale: IV. Reliability and factorial validity in different languages and cultures. J Psychosom Res 2003;55(3):277–83. https://doi.org/10.1016/S0022-3999(02)00601-3. [23] Raudenbush SW, Bryk AS, Cheong YF, Congdon R, Du Toit M. Hierarchical linear and nonlinear modeling (HLM7). vol. 1112. Lincolnwood, IL: Scientific Software International; 2011. [24] Nezlek JB. Multilevel modeling for social and personality psychology. SAGE Publications Ltd; 2011. [25] Jula A, Salminen JK, Saarijärvi S. Alexithymia: a facet of essential hypertension. Hypertension 1999;33(4):1057–61. https://doi.org/10.1161/01.HYP.33.4.1057. [26] Rafanelli C, Ruini C. Assessment of psychological well-being in psychosomatic medicine. Psychosom Assess 2012;32:182–202. https://doi.org/10.1159/ 000330021. [27] Todarello O, Taylor GJ, Parker JDA, Fanelli M. Alexithymia in essential hypertensive and psychiatric outpatients: a comparative study. J Psychosom Res 1995;39(8):987–94. https://doi.org/10.1016/0022-3999(95)00506-4. [28] Cumes-Rayner DP, Price J. Understanding hypertensive behaviour—I. Preference not to disclose. J Psychosom Res 1989;33(1):63–74. [29] Chugg K, Barton C, Antic R, Crockett A. The impact of alexithymia on asthma patient management and communication with health care providers: a pilot study. J Asthma 2009;46(2):126–9. https://doi.org/10.1080/02770900802468525. [30] Georges C, Berra E, Capron A, et al. [op. 2b. 07] assessment of drug adherence and psychological profile in patients with apparently treatment-resistant hypertension. J Hypertens 2017;35:e16–7. https://doi.org/10.1097/01.hjh.0000523024. 83956.1d. [31] Petit G, Berra E, Georges CMG, et al. Impact of psychological profile on drug adherence and drug resistance in patients with apparently treatment-resistant hypertension. Blood Press 2018;27(6):358–67. https://doi.org/10.1080/08037051. 2018.1476058.
The project was funded with the BST grant WP/2015/B/50 of the [DELETED]. References [1] WHO | World health statistics 2017: monitoring health for the SDGs. WHO. http:// www.who.int/gho/publications/world_health_statistics/2017/en/. Accessed January 7, 2019. [2] Mancia G, Grassi G. The autonomic nervous system and hypertension. Circ Res 2014;114(11):1804–14. https://doi.org/10.1161/CIRCRESAHA.114.302524. [3] Piotrowska-Półrolnik MA, Krejtz I, Holas P. Emotional regulation and the occurrence and course of hypertension. J Educ Health Sport 2017;7(5):315–28. https:// doi.org/10.5281/zenodo.580863. [4] Spitzer C, Brandl S, Rose H-J, Nauck M, Freyberger HJ. Gender-specific association of alexithymia and norepinephrine/cortisol ratios. A preliminary report. J Psychosom Res 2005;59(2):73–6. https://doi.org/10.1016/j.jpsychores.2004.07. 006. [5] Schwartz AR, Gerin W, Davidson KW, et al. Toward a causal model of cardiovascular responses to stress and the development of cardiovascular disease. Psychosom Med 2003;65(1):22. https://doi.org/10.1097/01.PSY.0000046075.79922.61. [6] Lumley MA, Neely LC, Burger AJ. The assessment of alexithymia in medical settings: implications for understanding and treating health problems. J Pers Assess 2007;89(3):230–46. https://doi.org/10.1080/00223890701629698. [7] Nemiah JC. Alexithymia: a view of the psychosomatic process. Mod Trends Psychosom Med 1976;3:430–9. [8] Taylor GJ, Bagby RM, Parker JD. Disorders of affect regulation: Alexithymia in medical and psychiatric illness. Cambridge University Press; 1999. [9] Mann SJ. Psychosomatic research in hypertension: the lack of impact of decades of research and new directions to consider. J Clin Hypertens 2012;14(10):657–64. https://doi.org/10.1111/j.1751-7176.2012.00686.x. [10] O'Brien E. Twenty-four-hour ambulatory blood pressure measurement in clinical practice and research: a critical review of a technique in need of implementation. J Intern Med. 2011;269(5):478–495. doi:https://doi.org/10.1111/j.1365-2796.2011. 02356.x. [11] 2018 ESC/ESH Guidelines for the management of arterial hypertension | European Heart Journal | Oxford Academic. https://academic.oup.com/eurheartj/article/39/ 33/3021/5079119, Accessed date: 7 January 2019. [12] Gaborieau V, Delarche N, Gosse P. Ambulatory blood pressure monitoring versus self-measurement of blood pressure at home: correlation with target organ damage. J Hypertens 2008;26(10):1919. https://doi.org/10.1097/HJH.0b013e32830c4368. [13] Banegas JR, Ruilope LM, de la Sierra A, et al. Relationship between clinic and ambulatory blood-pressure measurements and mortality. New Engl J Med 2018;378(16):1509–20. https://doi.org/10.1056/NEJMoa1712231. [14] Roush GC, Fagard RH, Salles GF, et al. Prognostic impact from clinic, daytime, and night-time systolic blood pressure in nine cohorts of 13 844 patients with hypertension. J Hypertens 2014;32(12):2332. https://doi.org/10.1097/HJH.
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