Non-Targeted Self-Measurement of Blood Pressure: Association with Self-Medication, Unscheduled Emergency Visits and Anxiety
by
, , , , ,
Glessiane de Oliveira Almeida
1,*
,
Felipe J. Aidar
2,3,4,5
,
Dihogo Gama de Matos
2,
Paulo Francisco de Almeida-Neto
6,
Enaldo Vieira de Melo
7,
José Augusto Soares Barreto Filho
1,7,8,9,
Marcos Antonio Almeida-Santos
7,9,
Victor Batista Oliveira
1,7,
Rebeca Rocha de Almeida
1,
Suelen Maiara dos Santos
1,
Larissa Monteiro Costa Pereira
1,
Juliana Santos Barbosa
1 and
Antônio Carlos Sobral Sousa
1,7,8,9,10 1
Postgraduate Program in Health Sciences, Federal University of Sergipe, UFS, Sergipe 49100-000, Brazil
2
Group of Studies and Research of Performance, Sport, Health and Paralympic Sports (GEPEPS), Federal University of Sergipe, UFS, Sergipe 49100-000, Brazil
3
Department of Physical Education, Federal University of Sergipe, UFS, Sergipe 49100-000, Brazil
4
Program of Physical Education, Federal University of Sergipe, UFS, Sergipe 49100-000, Brazil
5
Program of Physiological Science, Federal University of Sergipe, UFS, Sergipe 49100-000, Brazil
6
Health Sciences Center, Department of Physical Education, Federal University of Rio Grande do Norte, Natal UFRN 59064-741, Brazil
7
Department of Medicine, UFS), Federal University of Sergipe, UFS, Sergipe 49100-000, Brazil
8
Teaching and Research Center of São Lucas Hospital/Rede D’Or—São Luiz de Aracaju, Sergipe 49015-400, Brazil
9
Division of Cardiology, University Hospital of Federal University of Sergipe, UFS, Sergipe 49100-000, Brazil
10
Postgraduate Program in Health and Environment, Tiradentes University, UNIT, Aracaju, Sergipe 49032-490, Brazil
*
Author to whom correspondence should be addressed.
Medicina 2021, 57(1), 75; https://0-doi-org.brum.beds.ac.uk/10.3390/medicina57010075
Submission received: 31 October 2020
/
Revised: 11 January 2021
/
Accepted: 12 January 2021
/
Published: 17 January 2021
(This article belongs to the Special Issue Cardiovascular Disease: Management, Treatment Recommendations, and Future Research)
Abstract
:Background and Objective: The routine practice of self-medication of blood pressure (BP) not oriented with pulse devices may not be precisely useful in the control of BP and can lead the patient to self-medicate in error. Thus, we need to evaluate the non-oriented self-assessment of BP in real-life circumstances in hypertensive patients. The objective of this study was to evaluate in hypertensive patients the association of BP self-measurement with its control, as well as the presence of anxiety disorders, the occurrence of unscheduled visits to the emergency room, and self-medication. Materials and Methods: An observational study was carried out with 1000 hypertensive volunteers (age: 61.0 ± 12.5). Using a questionnaire, sociodemographic and clinical data on BP control were collected. Anxiety was assessed by the State-Trait Anxiety Inventory (STAI). Results: The group that performed non-oriented self-measurement of BP, showed that they had higher frequencies of self-medication (57.9%, p < 0.05) and more unscheduled visits to the emergency room (68%, p < 0.05). In addition, a lower level of BP control (46.8%, p < 0.05) was associated with higher levels of anxiety (52.3%, p < 0.05) in the group that performed non-oriented self-measurements of BP. Conclusion: The practice of non-oriented self-assessment of BP was associated with negative factors such as high levels of anxiety and higher frequencies of self-medication and unscheduled emergency visits.
1. Introduction
Systemic arterial hypertension is considered a public health problem because it is associated with a high risk of mortality [1]. Factors such as self-medication [2], self-measurement and BP control influence non-adherence to treatment due to a lack of knowledge and guidance [3,4]. There are several pharmacological and non-pharmacological therapeutic measures that can be applied to control hypertension. However, the general population’s knowledge of hypertension and BP control is still not ideal and, therefore, effective strategies must be developed to improve BP control and treatment adherence [4].
One of the strategies used by hypertensive patients to achieve these goals is self-measurement of BP at home with the aid of digital devices. Some studies have shown that BP self-measurement allows for a better and/or similar BP prognosis and control than measurements performed in a health care setting [5,6,7,8]. In addition, BP self-measurement is more attractive to the patients than the usual procedure of making medical appointments [4]. However, despite the patient’s preference for using the digital device to measure systemic blood pressure, whether for the convenience of carrying out a greater number of measurements during the day, the reliability of BP measurements, that is, the measurement performed by the patient himself, is not unanimously accepted [4,9]. This is due to the great variation that occurs in BP due to the lack of posture during the measurement, interferences of the situations experienced by the patient, exposure to stressful events, such as anxiety, throughout the day [10].
Studies indicate that this self-measurement procedure, when controlled and instructed by the clinician, has positive effects on the diagnosis and adherence to the patient’s treatment [11,12,13], other studies [4,9] indicate that it interferes with the control of BP. Such researches aimed to evaluate self-measurement of blood pressure in a controlled and instructed way, regarding the position and indication of correct measurements, by health professionals. However, these investigations were not conducted with the aim of evaluating the association of BP self-measurement in patients with anxiety disorder, for example. It is known that anxiety is one of the factors that influence the increase in blood pressure. Thus, it is suggested that hypertensive patients with anxiety disorder and who perform self-measurement may result in higher occurrences of unscheduled visits to the emergency room and self-medication.
Therefore, the present study aimed to evaluate in hypertensive patients the association of BP self-measurement with its control, as well as the presence of anxiety disorders, the occurrence of unscheduled visits to the emergency room, and self-medication.
2. Methods
The present study was characterized as cross-sectional and observational with an analytical character, carried out between June 2017 and October 2019 in the city of Aracaju-Sergipe, Brazil. The sample was carried out in a non-random manner with the evaluation of 1000 consecutively selected patients to minimize sampling bias. As an inclusion criterion, patients from 18 years of age, both sexes and diagnosed with systemic arterial hypertension were defined. Those with mental disorders that could compromise the answers to the questionnaires were excluded. Initially, 1507 subjects were invited to participate in the research and 1000 responded that they would accept it. It was found that there were no duplicate or incomplete responses, and 1000 responses were readable for the final analysis (Figure 1). The classification of age groups was defined based on intervals used by Wang et al. [14]. The sample was divided into the following groups: <45 years, (39.57 ± 4.28; 57% female and 43% male), 45–54 years (49.71 ± 2.89; 55% female and 45% male), 55–64 years (59.80 ± 2.98; 56% female and 44% male) and ≥65 years (72.49 ± 6.06; 59% female and 41% male).
Data collection was performed through the application of a specific questionnaire for research, which included data related to the patient’s sociodemographic and clinical aspects, quantification of unscheduled visits to the emergency services, self-medication and BP self-assessment. Self-medication related to antihypertensive treatment was considered as the use by the patient of an extra dose of an antihypertensive without a recommendation by a health care professional, the use of another non-prescribed antihypertensive, the non-use of an antihypertensive or not following the prescribed dose. The criterion for a self-measurement was the patient’s report of their frequency of use of the blood pressure (BP) measuring device per day and/or week. An unscheduled visit to the emergency room was based on the patient’s report of visits to the emergency room because of high BP in the last 12 months, as confirmed by their medical records. The control of BP was defined by means of ambulatory blood pressure monitoring (ABPM) or the average of the measurements in the last three consultations that were taken by three assistant physicians according to the College of Cardiology and the cardiology guidelines.
The State-Trait Anxiety Inventory (STAI) was applied by a trained psychologist and information on clinical data and patient identification was collected by a nurse at the Federal University of Sergipe.
The sample consisted of hypertensive patients aged 18 or over, of both sexes, followed up on an outpatient basis at three hospital institutions in the city of Aracaju-Sergipe, Brazil. One of these institutions exclusively serves users of the public health service and two serve the private sector. Those diagnosed with a mental disorder based on the answers to the questionnaires were excluded from the research. Patients who consented to participate in the present study signed an Informed Consent Form. This study was approved by the Research Ethics Committee involving human beings under the number CAAE: 60473316.9.0000.5546.
2.1. Procedures
Data collection was performed through the application of a specific questionnaire covering the following topics: (1) Patient identification and sociodemographic elements (gender, age, income, education, marital status, self-medication, unscheduled visits to the emergency room, information on BP self-checking). The social class and education were inserted in the questionnaire according to the classification used by the Brazilian Institute of Geography and Statistics (IBGE). IBGE is a public institute of the Brazilian federal administration, which provides the geographic and statistical information of Brazil and classifies the social class by family income group, in which class A corresponds to above 20 minimum wages; B: 10 to 20 minimum wages; C: 4 to 10 minimum wages; D: 2 to 4 minimum wages; E: Up to 2 minimum wages. Education is classified as: elementary, high school, university, graduation program and never studied. (2) Clinical data: a cardiologist evaluation based on the average of the last three measurements performed in the last three consultations according to the College of Cardiology and the cardiology and/or ABPM guidelines for the classification of controlled and uncontrolled BP, in addition to the identification of the comorbidities of such patients. BP values were considered for the diagnosis of systemic arterial hypertension (SAH) according to the recommendations of the 2017 guideline, in which the American Society of Cardiology [15] classifies blood pressure levels differently and suggests a definition for stage 1 blood pressure values. Systolic blood pressure (SBP) between 130–139 mmHg or diastolic blood pressure (DBP) between 80–89 mmHg; Stage 2 hypertension includes subjects with SBP values greater than 140 mmHg or DBP equal to or greater than 90 mmHg. The category of normal blood pressure was defined as SBP less than 120 mmHg and DBP less than 80 mmHg, and elevated BP was classified as SBP between 130–139 mmHg and DBP higher than 90 mmHg. This categorization is justified based on observational data related to the association between diastolic and systolic blood pressure and risk of cardiovascular diseases. To dichotomize the variable in controlled and uncontrolled hypertension, the procedure was carried out through ABPM or by the average of the measurements from the last three consultations performed by three medical assistants according to the College of Cardiology and the guidelines of Brazilian cardiology [16]. The cutoff point for uncontrolled hypertension was between SBP: 130–139 mmHg or DBP between 80–89 mmHg. Anxiety: the STAI was applied by a trained psychologist to all research volunteers. STAI aims to assess anxiety as a characteristic of the state (E) and personality (T). It is a self-assessment instrument, comprising two parallel scales, each with 20 items [17]. On STAI, on the T scale according to the sieve, the stipulated average is 45.34 to 55.22 and on the E scale the expected average is 43.64. The internal consistency of both scales was determined based on Cronbach’s alpha. The E scale showed a Cronbach’s alpha of 0.91, while the T scale was 0.894. Therefore, the instruments showed high internal validity when compared to the general population, with an index between 5.6% and 1.8%. Values above 0.8 indicate a high consistency, although coefficients above 0.60 have demonstrated adequate consistency [18].
2.2. Statistics
The continuous variables were described as mean and standard deviation. As for the categorical variables, absolute frequencies and percentages, and 95% confidence intervals were used to summarize them when relevant. The Shapiro–Wilk test was used to assess the assumption of normality. To test hypotheses related to categorical variables, Pearson’s chi-square test or Fisher’s exact test were used when most appropriate. The comparison between groups (with self-assessment versus without self-assessment; controlled vs. uncontrolled hypertension) was performed using Student’s t test for independent data in the case of quantitative variables. The Breslow–Day test was applied to assess whether the intensity of the relationship between anxiety (trait and state) and gender is dependent on the age groups. To analyze the factors associated with the outcome variables (self-measurement of systemic BP, uncontrolled hypertension, self-medication, unscheduled visits and trait anxiety), the logistic regression technique was used using the “forward stepwise” and “backward stepwise” method, considering entry in the model p = 0.25 and remaining in the model p = 0.05. Then, simple and adjusted odds ratios were calculated. The Statistical Package for Social Sciences version 24.0 was used to perform the statistical calculations for testing. The estimates were made with the following parameters: power = 80%. The effect size (Cohen’s D for continuous variables and Cohen’s h for categorical variables) was defined as small (<0.20), medium (between 0.20 and 0.50), large (between 0.50 and 0.80) and very large (>1, 20) [19]. The two-tailed p value less than 0.05 was taken as the criterion of statistical significance.
3. Results
The patients had a mean age of 61.0 ± 12.5 with a minimum of 27 years and a maximum of 100 years. It was observed that 50% of the patients were followed up in the cardiology outpatient clinic of the Teaching Hospital of the Federal University of Sergipe and the other half in the supplementary network. The clinical characteristics shown in Table 1 are typical of this patient population.
3.1. Variables Outcomes
It was observed during the study period that there was a high frequency of self-measurement of BP (44.7%), uncontrolled hypertension (36.8%), self-medication (41.3%), unplanned visits to the emergency room (38.4%), and anxiety (51.6%), as shown in Table 2.
3.2. Difference between Sociodemographic and Clinical Characteristics of Patients who Self-Measured Blood Pressure (BP)
Table 3 shows the data of patients with and without self-measurement of blood pressure in relation to sociodemographic characteristics. Self-measurement significantly associated with social class was observed.
The data of patients with and without self-measurement of blood pressure in relation to sociodemographic characteristics by age groups can be seen in Table A1. It was observed self-measurement significantly associated with gender (45–54 years), marital status (≥65 years) and social class (<45 years).
3.3. Comparison between Self-Assessment and Non-Self-Assessment
Data from patients with and without self-measurement of blood pressure in relation to clinical characteristics is shown in Table 4. Self-measurement significantly associated with comorbidities, diabetes mellitus, dyslipidemia, coronary artery disease, stroke, peripheral obstructive arterial disease, use of medication for comorbidities, self-medication, unscheduled visit, BP control, and anxiety state was observed.
Data from patients with and without self-measurement of blood pressure in relation to clinical characteristics age groups was showed in Table A2. It was observed that self-measurement was significantly associated with self-medication, unscheduled visit and BP control for patients under 45 years old, dyslipidemia, self-medication, unscheduled visit, BP control and anxiety state for 45- to 54-year-old patients, comorbidities, diabetes mellitus, use of medication for comorbidities, self-medication, unscheduled visit, BP control and anxiety state for 55- to 64-year-old patients and diabetes mellitus, dyslipidemia, coronary artery disease, peripheral obstructive arterial disease, self-medication, unscheduled visit and BP control for patients above 65 years old.
3.4. Difference between Sociodemographic and Clinical Characteristics of Patients with Controlled and Uncontrolled BP
The values of patients with controlled BP and uncontrolled BP in terms of sociodemographic characteristics, are shown in Table 5. Controlled BP significantly associated with gender was observed.
The values of patients with controlled BP and uncontrolled BP in terms of sociodemographic characteristics by age groups, as shown in Table A3. It was observed that controlled BP was significantly associated with education in <45-year-old patients and gender in 55- to 64-year-old patients and ≥65-year-old patients.
The values of patients with controlled and uncontrolled BP in terms of clinical characteristics are seen in Table 6. Controlled BP significantly associated with type of hospital, comorbidities, diabetes mellitus, dyslipidemia, peripheral obstructive arterial disease, use of medication for comorbidities, self-medication, unscheduled visit, and trait and anxiety state was observed.
The values of patients with controlled and uncontrolled BP in terms of clinical characteristics by age group, are seen in Table A4. It was observed that BP-control was significantly associated with stroke, unscheduled visit and anxiety traits in <45-year-old patients, dyslipidemia, use of medication for comorbidities, unscheduled visit and trait anxiety state for 45- to 54-year-old patients, comorbidities, diabetes mellitus, dyslipidemia, use of medication for comorbidities, and trait anxiety state for 55- to 64-year-old patients, comorbidities, diabetes mellitus, dyslipidemia, peripheral obstructive arterial disease, Use of medication for comorbidities, self-medication and unscheduled visits for ≥65-year-old patients.
In Table A5, the association between anxiety (trait and state), gender and age groups was observed. It was seen an association between gender and trait anxiety in <45-, 55–64, ≥65-year-old and in general and with state anxiety in <45-, ≥65-year-old and in general. There was an effort to identify whether the association of trait and state anxiety and gender are dependent of age groups applying the Breslow-Day test. The p-values of 0.423 for state anxiety and 0.187 for trait anxiety were observed, which lead us to believe that the relationship between gender and anxiety are independent of age group. The conclusion was that female patients are more anxious (trait and state) than Male patients independent of age groups.
3.5. Association between Anxiety and Gender by Age Groups
In multivariable logistic regression, the factors associated with non-BP control were: self-measurement, self-medication, unscheduled visits, state anxiety, a female prevalence, the presence of comorbidities, the use of medication for comorbidities and trait/state anxiety (Table 7).
The odds ratio of not BP and trait anxiety and state anxiety controlled for gender, use of medication for comorbidities, self-measurement of BP, self-medication and state anxiety or trait anxiety respectively were estimated (Table 8). It was noted that state/trait anxiety was an associated factor of not controlling arterial hypertension even on the presence of gender, use of medication for comorbidities, self-measurement of BP, and self-medication.
4. Discussion
BP measurement is an important procedure that must be performed for any medical evaluation, regardless of specialty [20], and in view of the previous information, the main findings of this study were that patients who performed self-measurements had less control over their BP, self-medicated more frequently, had a greater presence of state anxiety and attended the emergency room more frequently because of their BP. These findings seem to point out that there is a lack of knowledge on the part of patients, regarding the self-measurement of blood pressure, and its implications when performing this procedure. Thus, a more effective explanation of how to use the pressure device would minimize the worsening of existing diseases.
The result of this research differs from some studies [4,21,22,23] on self-measurement and BP control. In the aforementioned studies, patients were instructed on the use, calibration and validation of the blood pressure device before use, in addition to the correct position and BP values for control. However, in the present study, the sample was observed in real-life circumstances, with no guidance on how to use the device. In this case, the objective was to observe how the population has been using the blood pressure device without guidance. Another important point is that factors such as association with anxiety, self-medication and visits to the emergency room were not investigated in the studies cited.
Research has shown that women constitute the majority of the hypertensive population followed in primary health care [9,24]. Thus, we found that women have higher frequencies of BP self-measurement (60.2%), that is, they seek greater health care. On the other hand, they presented worse BP control (65.2%). Data from the National Survey on Access, Use and Promotion of Rational Use of Medicines in Brazil (PNAUM) point out that females have a greater influence on the practice of self-medication [25], a predictive factor for non-adherence to medication [2] and, consequently, a factor that implies the lack of BP control. In addition, the appearance of physical and psychological disorders such as anxiety, insomnia, tiredness, and irritability are more common in women than in men, in addition to the decrease in the production of estrogens, changes in the lipid profile, weight gain and sedentary lifestyle [9].
One of the main causes of self-medication is the need to relieve symptoms [26] and psychosocial factors [27]. Among the most described symptoms are headache, atypical chest pain, dyspnea, acute psychological stress, anxiety and panic syndrome. When patients associate these symptoms with high BP, this condition is characterized as a false hypertensive crisis [1]. Among psychiatric disorders, anxiety is the most prevalent in the general population, with prevalence rates between 5.6% and 18.1% [28]. In women, this prevalence is higher than in men, being a risk factor for elevated BP [9,29,30,31], which can constitute a barrier to non-BP control [9,32]. According to a study by the Global Burden of Disease [33], the sixth leading cause of disability in the world is related to mental disorders, and individuals affected with anxiety symptoms have lower quality of life and worse psychosocial factor. Individuals with such symptoms tend to present a pattern of recurrence to the disorder and an increasing urgency leading to a chronic course and worsening of other illnesses.
In some studies that analyzed the profile of individuals who seek health services in this country, it was observed that there is a predominance of users who seek urgent care with chronic diseases, such as arterial hypertension, with greater severity due to their lack of control of the condition [34,35].
It needs to be taken into account that hypertension is the main treatable cardiovascular risk factor [36,37,38]. Hypertension tends to significantly increase the risk of myocardial infarct, stroke, kidney damage, and other pathologies [39]. In this sense, ineffective control, especially of hypertension, and cardiovascular problems, would be linked to therapeutic inertia, the use of incorrect dosages and/or inappropriate combinations of medication, low adherence to treatment [3], an unhealthy lifestyle (smoking, alcohol abuse, excess of fat and salt in the diet, sedentary habits, and being overweight), use of self-assessments in medical guidance and indication, and the prescription of other drugs that can induce hypertension, even when self-administered.
5. Study Limitation
Regarding the limitations of this study, it should be noted that there was no randomization for the use or non-use of the blood pressure device because the devices used were obtained by the patients, which can lead to errors resulting from the use of the device, mistakes regarding knowledge about the device and other distortions.
Another limitation of the study is that there was no standardization regarding the performance of ABPM, since not all patients underwent the exam which can interfere with some results. It is suggested for future work, randomized studies to assess the influence of self-measurement with self-medication, unscheduled visits to the hospital and anxiety disorders.
6. Conclusions
Patients who self-assessed BP had the lowest blood pressure control, self-medicated more frequently, had a greater presence of state anxiety and had more emergency room visits because of their blood pressure. The factors associated with non-BP control were: self-medication, unscheduled visits to the hospital, state of anxiety, prevalence of females, the presence of comorbidities, especially diabetes mellitus and dyslipidemia, and the use of medications for comorbidities.
Thus, the lack of knowledge about the disease and its implications, as well as the wrong guidance on the use of the pressure device are key factors in this chain of events and not BP control. Therefore, it is wise to discourage the use of digital pressure devices in patients to whom adequate guidance has not been given and the clinical picture has been observed, especially if such a patient suffers from an anxiety disorder. In addition, it is wise to invest in public policies aimed at capacitors, informing the population about the proper use of the blood pressure device and pointing out the importance of a multidisciplinary approach in the management of hypertensive patients with anxiety disorder.
Author Contributions
Investigation, Methodology, Writing—original draft, G.d.O.A., Conceptualization, Writing—review & editing, F.J.A., Conceptualization, Writing – review & editing, D.G.d.M., Data curation, Formal analysis, P.F.d.A.-N., Methodology, Project administration, E.V.d.M., Investigation, Validation, J.A.S.B.F., Formal analysis, Methodology, M.A.A.-S., Resources, Visualization, V.B.O., Project administration, Writing—original draft, R.R.d.A., Funding acquisition, Software, S.M.d.S., Resources, Writing—original draft, L.M.C.P., Software, Supervision, J.S.B., Funding acquisition, Project administration, A.C.S.S. All authors have read and agreed to the published version of the manuscript.
Funding
Coordination for the Improvement of Higher Education Personnel/Foundation for the Support of Research and Technological Innovation of the State of Sergipe.
Institutional Review Board Statement
This study was approved by the Research Ethics Committee involving human beings under the number CAAE: 60473316.9.0000.5546, approved in 5 June 2017.
Informed Consent Statement
Patients who consented to participate in the present study signed an Informed Consent Form.
Data Availability Statement
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to ethical restrictions.
Conflicts of Interest
The authors declare no conflict of interest.
Appendix A. Supplementary Tables
Table A1.
Comparison between Patients with and without Self-Measurement of Blood Pressure Regarding Sociodemographic Characteristics by Age Group.
Table A1.
Comparison between Patients with and without Self-Measurement of Blood Pressure Regarding Sociodemographic Characteristics by Age Group.
| Variables | Age Group | <45 | 45–54 | 55–64 | ≥65 | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Self-Measurement | Self-Measurement | Self-Measurement | Self-Measurement | ||||||||||||||
| With | Without | With | Without | With | Without | With | Without | ||||||||||
| (n = 47) | (n = 62) | p | h | (n = 76) | (n = 103) | p | h | (n = 134) | (n = 157) | p | h | (n = 190) | (n = 231) | p | h | ||
| Hospital | Public | 24 (51.1) | 26 (41.9) | 0.438 | 0.183 | 42 (55.3) | 51 (49.5) | 0.454 | 0.115 | 64 (47.8) | 84 (53.5) | 0.348 | −0.115 | 89 (46.8) | 120 (51.9) | 0.328 | −0.102 |
| Private | 23 (48.9) | 36 (58.1) | −0.183 | 34 (44.7) | 52 (50.5) | −0.115 | 70 (52.2) | 73 (46.5) | 0.115 | 101 (53.2) | 111 (48.1) | 0.102 | |||||
| Gender | Female | 23 (48.9) | 39 (62.9) | 0.174 | −0.282 | 49 (64.5) | 50 (48.5) | 0.048 | 0.323 | 81 (60.4) | 81 (51.6) | 0.155 | 0.179 | 116 (61.1) | 132 (57.1) | 0.428 | 0.080 |
| Male | 24 (51.1) | 23 (37.1) | 0.282 | 27 (35.5) | 53 (51.5) | −0.323 | 53 (39.6) | 76 (48.4) | −0.179 | 74 (38.9) | 99 (42.9) | −0.080 | |||||
| Marital Status | Married | 21 (44.7) | 30 (48.4) | 0.961 | −0.074 | 48 (63.2) | 69 (67) | 0.678 | −0.080 | 89 (66.4) | 99 (63.1) | 0.802 | 0.070 | 113 (59.5) | 138 (59.7) | 0.010 | −0.005 |
| Divorced | 7 (14.9) | 10 (16.1) | −0.034 | 15 (19.7) | 14 (13.6) | 0.166 | 18 (13.4) | 23 (14.6) | −0.035 | 22 (11.6) | 24 (10.4) | 0.038 | |||||
| Single | 17 (36.2) | 18 (29) | 0.152 | 10 (13.2) | 12 (11.7) | 0.046 | 18 (13.4) | 19 (12.1) | 0.040 | 13 (6.8) | 32 (13.9) | −0.233 | |||||
| Widowed | 0 (0) | 1 (1.6) | −0.255 | 0 (0) | 1 (1) | −0.197 | 5 (3.7) | 11 (7) | −0.147 | 36 (18.9) | 37 (16) | 0.077 | |||||
| Live with a partner | 2 (4.3) | 3 (4.8) | −0.028 | 3 (3.9) | 7 (6.8) | −0.127 | 4 (3) | 5 (3.2) | −0.012 | 6 (3.2) | 0 (0) | 0.357 | |||||
| Social class | A | 0 (0) | 2 (3.2) | 0.031 | −0.361 | 4 (5.3) | 5 (4.9) | 0.201 | 0.019 | 6 (4.5) | 13 (8.3) | 0.616 | −0.157 | 19 (10) | 29 (12.6) | 0.111 | −0.081 |
| B | 3 (6.4) | 14 (22.6) | −0.480 | 6 (7.9) | 18 (17.5) | −0.293 | 20 (14.9) | 18 (11.5) | 0.102 | 18 (9.5) | 34 (14.7) | −0.162 | |||||
| C | 14 (29.8) | 15 (24.2) | 0.126 | 18 (23.7) | 17 (16.5) | 0.180 | 21 (15.7) | 26 (16.6) | −0.024 | 40 (21.1) | 29 (12.6) | 0.229 | |||||
| D | 17 (36.2) | 11 (17.7) | 0.421 | 26 (34.2) | 26 (25.2) | 0.197 | 36 (26.9) | 37 (23.6) | 0.076 | 41 (21.6) | 49 (21.2) | 0.009 | |||||
| E | 13 (27.7) | 20 (32.3) | −0.100 | 22 (28.9) | 37 (35.9) | −0.149 | 51 (38.1) | 63 (40.1) | −0.042 | 72 (37.9) | 90 (39) | −0.022 | |||||
| Education | Never studied | 0 (0) | 0 (0) | 0.090 | <0.001 | 2 (2.6) | 3 (2.9) | 0.376 | −0.017 | 8 (6) | 6 (3.8) | 0.202 | 0.100 | 27 (14.2) | 36 (15.6) | 0.971 | −0.039 |
| Fundamental | 7 (14.9) | 10 (16.1) | −0.034 | 13 (17.1) | 26 (25.2) | −0.200 | 42 (31.3) | 49 (31.2) | 0.003 | 67 (35.3) | 77 (33.3) | 0.041 | |||||
| High school | 25 (53.2) | 19 (30.6) | 0.461 | 34 (44.7) | 38 (36.9) | 0.160 | 34 (25.4) | 56 (35.7) | −0.224 | 50 (26.3) | 59 (25.5) | 0.018 | |||||
| University | 11 (23.4) | 27 (43.5) | −0.431 | 20 (26.3) | 32 (31.1) | −0.105 | 43 (32.1) | 43 (27.4) | 0.103 | 41 (21.6) | 54 (23.4) | −0.043 | |||||
| Graduate Studies | 4 (8.5) | 6 (9.7) | −0.041 | 7 (9.2) | 4 (3.9) | 0.220 | 7 (5.2) | 3 (1.9) | 0.184 | 5 (2.6) | 5 (2.2) | 0.031 | |||||
p: statistical significance (chi-square test). A = high social class, B = high middle class. C = middle social class. D = low middle class. D = poor social class. h—effect size Cohen’s D for continuous variables and Cohen’s h for categorical variables.
Table A2.
Comparison between Patients with and without Self-Measurement of Blood Pressure Regarding Clinical Characteristics.
Table A2.
Comparison between Patients with and without Self-Measurement of Blood Pressure Regarding Clinical Characteristics.
| Age Group | <45 | 45–54 | 55–64 | ≥65 | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Self-Measurement | Self-Measurement | Self-Measurement | Self-Measurement | |||||||||||||
| With | Without | With | Without | With | Without | With | Without | |||||||||
| (n = 47) | (n = 62) | p | h | (n = 76) | (n = 103) | p | h | (n = 134) | (n = 157) | p | h | (n = 190) | (n = 231) | p | h | |
| Comorbidities | 7 (14.9) | 17 (27.4) | 0.162 | −0.310 | 39 (51.3) | 45 (43.7) | 0.364 | 0.153 | 83 (61.9) | 72 (45.9) | 0.007 | 0.324 | 127 (66.8) | 133 (57.6) | 0.056 | 0.191 |
| Diabetes mellitus | 1 (2.1) | 4 (6.5) | 0.388 | −0.221 | 14 (18.4) | 15 (14.6) | 0.541 | 0.104 | 40 (29.9) | 28 (17.8) | 0.018 | 0.284 | 65 (34.2) | 49 (21.2) | 0.003 | 0.292 |
| Dyslipidemia | 5 (10.6) | 12 (19.4) | 0.289 | −0.247 | 33 (43.4) | 22 (21.4) | 0.002 | 0.478 | 51 (38.1) | 45 (28.7) | 0.104 | 0.200 | 93 (48.9) | 79 (34.2) | 0.003 | 0.300 |
| Coronary artery disease | 1 (2.1) | 2 (3.2) | 1.000 | −0.068 | 4 (5.3) | 7 (6.8) | 0.761 | −0.065 | 18 (13.4) | 14 (8.9) | 0.261 | 0.144 | 40 (21.1) | 30 (13) | 0.035 | 0.216 |
| Chronic kidney Disease | 0 (0) | 0 (0) | 1 (1.3) | 1 (1) | 1.000 | 0.033 | 4 (3) | 3 (1.9) | 0.707 | 0.070 | 2 (1.1) | 9 (3.9) | 0.121 | −0.192 | ||
| Stroke | 3 (6.4) | 1 (1.6) | 0.313 | 0.256 | 5 (6.6) | 1 (1) | 0.085 | 0.321 | 12 (9) | 9 (5.7) | 0.365 | 0.124 | 9 (4.7) | 6 (2.6) | 0.294 | 0.115 |
| Depression | 1 (2.1) | 0 (0) | 0.431 | 0.293 | 2 (2.6) | 2 (1.9) | 1.000 | 0.046 | 5 (3.7) | 4 (2.5) | 0.737 | 0.068 | 3 (1.6) | 5 (2.2) | 0.734 | −0.043 |
| Cardiac insufficiency | 0 (0) | 1 (1.6) | 1.000 | −0.255 | 2 (2.6) | 9 (8.7) | 0.120 | −0.274 | 6 (4.5) | 7 (4.5) | 1.000 | 0.001 | 9 (4.7) | 11 (4.8) | 1.000 | −0.001 |
| COPD | 0 (0) | 0 (0) | 0.000 | 2 (2.6) | 1 (1) | 0.575 | 0.128 | 4 (3) | 2 (1.3) | 0.419 | 0.121 | 3 (1.6) | 4 (1.7) | 1.000 | −0.012 | |
| POAD | 1 (2.1) | 0 (0) | 0.431 | 0.293 | 1 (1.3) | 0 (0) | 0.425 | 0.230 | 3 (2.2) | 1 (0.6) | 0.337 | 0.141 | 14 (7.4) | 5 (2.2) | 0.016 | 0.254 |
| Use of medicationfor comorbidities | 7 (14.9) | 16 (25.8) | 0.236 | −0.273 | 32 (42.1) | 44 (42.7) | 1.000 | −0.012 | 73 (54.5) | 61 (38.9) | 0.009 | 0.314 | 111 (58.4) | 120 (52.2) | 0.237 | 0.126 |
| Purchase of the medicine | ||||||||||||||||
| Health center (free) | 12 (25.5) | 12 (19.4) | 0.561 | 0.148 | 25 (32.9) | 40 (38.8) | 0.238 | −0.124 | 44 (32.8) | 44 (28) | 0.586 | 0.105 | 63 (33.2) | 83 (35.9) | 0.484 | −0.058 |
| Popular pharmacy | 9 (19.1) | 9 (14.5) | 0.124 | 18 (23.7) | 14 (13.6) | 0.261 | 35 (26.1) | 40 (25.5) | 0.015 | 50 (26.3) | 49 (21.2) | 0.120 | ||||
| Pharmacy (full amount) | 26 (55.3) | 41 (66.1) | −0.222 | 33 (43.4) | 49 (47.6) | −0.083 | 55 (41) | 73 (46.5) | −0.110 | 77 (40.5) | 99 (42.9) | −0.047 | ||||
| Self-medication | 22 (46.8) | 11 (17.7) | 0.002 | 0.637 | 33 (43.4) | 27 (26.2) | 0.017 | 0.364 | 84 (62.7) | 53 (33.8) | <0.001 | 0.587 | 120 (63.2) | 63 (27.3) | <0.001 | 0.738 |
| Unscheduled visit | 31 (66) | 5 (8.1) | <0.001 | 1.320 | 55 (72.4) | 18 (17.5) | <0.001 | 1.172 | 91 (67.9) | 29 (18.5) | <0.001 | 1.049 | 127 (66.8) | 28 (12.1) | <0.001 | 1.203 |
| BP control | 21 (44.7) | 55 (88.7) | <0.001 | −0.992 | 39 (51.3) | 82 (79.6) | <0.001 | −0.608 | 66 (49.3) | 114 (72.6) | <0.001 | −0.484 | 83 (43.7) | 172 (74.5) | <0.001 | −0.638 |
| Anxiety trait | 30 (63.8) | 27 (43.5) | 0.052 | 0.410 | 47 (61.8) | 51 (49.5) | 0.129 | 0.249 | 80 (59.7) | 86 (54.8) | 0.408 | 0.100 | 84 (44.2) | 111 (48.1) | 0.434 | −0.077 |
| Anxiety state | 23 (48.9) | 21 (33.9) | 0.121 | 0.307 | 42 (55.3) | 40 (38.8) | 0.034 | 0.331 | 78 (58.2) | 69 (43.9) | 0.019 | 0.286 | 91 (47.9) | 93 (40.3) | 0.139 | 0.154 |
Data expressed in absolute numbers and percentage in parentheses; p: statistical significance (chi-square test). h—effect size Cohen’s h. COPD—chronic obstructive pulmonary disease; POAD–peripheral obstructive arterial disease.
Table A3.
Comparison between Patients with Controlled BP and Uncontrolled BP in Terms of Sociodemographic Characteristics.
Table A3.
Comparison between Patients with Controlled BP and Uncontrolled BP in Terms of Sociodemographic Characteristics.
| Age Group | <45 | 45–54 | 55–64 | ≥65 | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Variables | Controlled BP | Controlled BP | Controlled BP | Controlled BP | |||||||||||||
| Yes | No | Yes | No | Yes | No | Yes | No | ||||||||||
| (n = 76) | (n = 33) | p | h | (n = 121) | (n = 58) | p | h | (n = 180) | (n = 111) | p | h | (n = 255) | (n = 166) | p | h | ||
| Hospital | Public | 31 (40.8) | 19 (57.6) | 0.143 | −0.337 | 58 (47.9) | 35 (60.3) | 0.150 | −0.250 | 85 (47.2) | 63 (56.8) | 0.119 | −0.191 | 123 (48.2) | 86 (51.8) | 0.487 | −0.071 |
| Private | 45 (59.2) | 14 (42.4) | 0.337 | 63 (52.1) | 23 (39.7) | 0.250 | 95 (52.8) | 48 (43.2) | 0.191 | 132 (51.8) | 80 (48.2) | 0.071 | |||||
| Gender | Female | 42 (55.3) | 20 (60.6) | 0.677 | −0.108 | 67 (55.4) | 32 (55.2) | 1.000 | 0.004 | 87 (48.3) | 75 (67.6) | 0.002 | −0.392 | 135 (52.9) | 113 (68.1) | 0.002 | −0.311 |
| Male | 34 (44.7) | 13 (39.4) | 0.108 | 54 (44.6) | 26 (44.8) | −0.004 | 93 (51.7) | 36 (32.4) | 0.392 | 120 (47.1) | 53 (31.9) | 0.311 | |||||
| Marital Status | Married | 37 (48.7) | 14 (42.4) | 0.928 | 0.126 | 79 (65.3) | 38 (65.5) | 0.625 | −0.005 | 120 (66.7) | 68 (61.3) | 0.509 | 0.113 | 150 (58.8) | 101 (60.8) | 0.168 | −0.041 |
| Divorced | 11 (14.5) | 6 (18.2) | −0.100 | 19 (15.7) | 10 (17.2) | −0.041 | 22 (12.2) | 19 (17.1) | −0.139 | 31 (12.2) | 15 (9) | 0.102 | |||||
| Single | 24 (31.6) | 11 (33.3) | −0.037 | 17 (14) | 5 (8.6) | 0.172 | 23 (12.8) | 14 (12.6) | 0.005 | 26 (10.2) | 19 (11.4) | −0.040 | |||||
| Widowed | 1 (1.3) | 0 (0) | 0.230 | 1 (0.8) | 0 (0) | 0.182 | 8 (4.4) | 8 (7.2) | −0.119 | 47 (18.4) | 26 (15.7) | 0.074 | |||||
| Live with a partner | 3 (3.9) | 2 (6.1) | −0.097 | 5 (4.1) | 5 (8.6) | −0.187 | 7 (3.9) | 2 (1.8) | 0.128 | 1 (0.4) | 5 (3) | −0.224 | |||||
| Social class | A | 2 (2.6) | 0 (0) | 0.612 | 0.326 | 8 (6.6) | 1 (1.7) | 0.329 | 0.257 | 12 (6.7) | 7 (6.3) | 0.599 | 0.015 | 29 (11.4) | 19 (11.4) | 0.411 | −0.002 |
| B | 13 (17.1) | 4 (12.1) | 0.142 | 19 (15.7) | 5 (8.6) | 0.219 | 25 (13.9) | 13 (11.7) | 0.065 | 36 (14.1) | 16 (9.6) | 0.139 | |||||
| C | 22 (28.9) | 7 (21.2) | 0.179 | 21 (17.4) | 14 (24.1) | −0.168 | 33 (18.3) | 14 (12.6) | 0.159 | 37 (14.5) | 32 (19.3) | −0.128 | |||||
| D | 18 (23.7) | 10 (30.3) | −0.149 | 33 (27.3) | 19 (32.8) | −0.120 | 45 (25) | 28 (25.2) | −0.005 | 51 (20) | 39 (23.5) | −0.085 | |||||
| E | 21 (27.6) | 12 (36.4) | −0.188 | 40 (33.1) | 19 (32.8) | 0.006 | 65 (36.1) | 49 (44.1) | −0.164 | 102 (40) | 60 (36.1) | 0.079 | |||||
| Education | Never studied | 0 (0) | 0 (0) | 0.048 | <0.001 | 3 (2.5) | 2 (3.4) | 0.815 | −0.057 | 7 (3.9) | 7 (6.3) | 0.747 | −0.111 | 34 (13.3) | 29 (17.5) | 0.217 | −0.115 |
| Fundamental | 14 (18.4) | 3 (9.1) | 0.275 | 25 (20.7) | 14 (24.1) | −0.083 | 54 (30) | 37 (33.3) | −0.072 | 89 (34.9) | 55 (33.1) | 0.037 | |||||
| High school | 25 (32.9) | 19 (57.6) | −0.501 | 50 (41.3) | 22 (37.9) | 0.069 | 60 (33.3) | 30 (27) | 0.138 | 69 (27.1) | 40 (24.1) | 0.068 | |||||
| University | 31 (40.8) | 7 (21.2) | 0.428 | 34 (28.1) | 18 (31) | −0.064 | 53 (29.4) | 33 (29.7) | −0.006 | 60 (23.5) | 35 (21.1) | 0.059 | |||||
| Graduate Studies | 6 (7.9) | 4 (12.1) | −0.142 | 9 (7.4) | 2 (3.4) | 0.179 | 6 (3.3) | 4 (3.6) | −0.015 | 3 (1.2) | 7 (4.2) | −0.196 | |||||
Data expressed in absolute numbers and percentage in parentheses; p: statistical significance (chi-square test). h—effect size Cohen’s D for continuous variables and Cohen’s h for categorical variables. A = high social class, B = high middle class. C = middle social class. D = low middle class. D = poor social class.
Table A4.
Comparison between Patients with Controlled BP and Uncontrolled BP in Terms of Clinical Characteristics by Age Groups.
Table A4.
Comparison between Patients with Controlled BP and Uncontrolled BP in Terms of Clinical Characteristics by Age Groups.
| Age Group | <45 | 45–54 | 55–64 | ≥65 | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Controlled BP | Controlled BP | Controlled BP | Controlled BP | |||||||||||||
| Yes | No | Yes | No | Yes | No | Yes | No | |||||||||
| (n = 76) | (n = 33) | p | h | (n = 121) | (n = 58) | p | h | (n = 180) | (n = 111) | p | h | (n = 255) | (n = 166) | p | h | |
| Comorbidities | 17 (22.4) | 7 (21.2) | 1.000 | 0.028 | 52 (43) | 32 (55.2) | 0.150 | −0.245 | 83 (46.1) | 72 (64.9) | 0.002 | −0.380 | 145 (56.9) | 115 (69.3) | 0.011 | −0.258 |
| Diabetes mellitus | 4 (5.3) | 1 (3) | 1.000 | 0.113 | 18 (14.9) | 11 (19) | 0.519 | −0.109 | 34 (18.9) | 34 (30.6) | 0.023 | −0.274 | 57 (22.4) | 57 (34.3) | 0.010 | −0.267 |
| Dyslipidemia | 12 (15.8) | 5 (15.2) | 1.000 | 0.018 | 30 (24.8) | 25 (43.1) | 0.016 | −0.390 | 50 (27.8) | 46 (41.4) | 0.021 | −0.289 | 91 (35.7) | 81 (48.8) | 0.008 | −0.266 |
| Coronary artery disease | 3 (3.9) | 0 (0) | 0.552 | 0.400 | 7 (5.8) | 4 (6.9) | 0.749 | −0.046 | 18 (10) | 14 (12.6) | 0.564 | −0.083 | 43 (16.9) | 27 (16.3) | 0.894 | 0.016 |
| Chronic kidney Disease | 0 (0) | 0 (0) | <0.001 | 1 (0.8) | 1 (1.7) | 0.544 | −0.081 | 2 (1.1) | 5 (4.5) | 0.110 | −0.217 | 7 (2.7) | 4 (2.4) | 1.000 | 0.021 | |
| Stroke | 0 (0) | 4 (12.1) | 0.007 | −0.711 | 2 (1.7) | 4 (6.9) | 0.088 | −0.274 | 15 (8.3) | 6 (5.4) | 0.485 | 0.116 | 6 (2.4) | 9 (5.4) | 0.111 | −0.162 |
| Depression | 0 (0) | 1 (3) | 0.303 | −0.350 | 2 (1.7) | 2 (3.4) | 0.596 | −0.116 | 6 (3.3) | 3 (2.7) | 1.000 | 0.037 | 5 (2) | 3 (1.8) | 1.000 | 0.011 |
| Cardiac insufficiency | 0 (0) | 1 (3) | 0.303 | −0.350 | 8 (6.6) | 3 (5.2) | 1.000 | 0.061 | 7 (3.9) | 6 (5.4) | 0.569 | −0.072 | 14 (5.5) | 6 (3.6) | 0.484 | 0.090 |
| COPD | 0 (0) | 0 (0) | <0.001 | 1 (0.8) | 2 (3.4) | 0.246 | −0.191 | 5 (2.8) | 1 (0.9) | 0.413 | 0.145 | 2 (0.8) | 5 (3) | 0.118 | −0.172 | |
| POAD | 1 (1.3) | 0 (0) | 1.000 | 0.230 | 0 (0) | 1 (1.7) | 0.324 | −0.263 | 1 (0.6) | 3 (2.7) | 0.157 | −0.181 | 6 (2.4) | 13 (7.8) | 0.014 | −0.259 |
| Use of medication for comorbidities | 15 (19.7) | 8 (24.2) | 0.616 | −0.109 | 44 (36.4) | 32 (55.2) | 0.023 | −0.380 | 74 (41.1) | 60 (54.1) | 0.039 | −0.260 | 123 (48.2) | 108 (65.5) | 0.001 | −0.350 |
| Purchase of the medicine | ||||||||||||||||
| Health Center (free) | 16 (21.1) | 8 (24.2) | 0.090 | −0.076 | 39 (32.2) | 26 (44.8) | 0.274 | −0.260 | 48 (26.7) | 40 (36) | 0.175 | −0.202 | 90 (35.3) | 56 (33.7) | 0.811 | 0.033 |
| Popular pharmacy | 9 (11.8) | 9 (27.3) | −0.396 | 23 (19) | 9 (15.5) | 0.092 | 46 (25.6) | 29 (26.1) | −0.013 | 57 (22.4) | 42 (25.3) | −0.069 | ||||
| Pharmacy (Full amount) | 51 (67.1) | 16 (48.5) | 0.379 | 59 (48.8) | 23 (39.7) | 0.184 | 86 (47.8) | 42 (37.8) | 0.201 | 108 (42.4) | 68 (41) | 0.028 | ||||
| Self-medication | 20 (26.3) | 13 (39.4) | 0.182 | −0.280 | 39 (32.2) | 21 (36.2) | 0.615 | −0.084 | 71 (39.4) | 66 (59.5) | 0.001 | −0.403 | 91 (35.7) | 92 (55.4) | <0.001 | −0.399 |
| Unscheduled visit | 13 (17.1) | 23 (69.7) | <0.001 | −1.123 | 35 (28.9) | 38 (65.5) | <0.001 | −0.751 | 51 (28.3) | 69 (62.2) | <0.001 | −0.694 | 62 (24.3) | 93 (56) | <0.001 | −0.660 |
| Anxiety trait | 33 (43.4) | 24 (72.7) | 0.006 | −0.604 | 58 (47.9) | 40 (69) | 0.010 | −0.430 | 91 (50.6) | 75 (67.6) | 0.005 | −0.348 | 114 (44.7) | 81 (48.8) | 0.425 | −0.082 |
| Anxiety state | 28 (36.8) | 16 (48.5) | 0.292 | −0.236 | 44 (36.4) | 38 (65.5) | <0.001 | −0.592 | 75 (41.7) | 72 (64.9) | <0.001 | −0.469 | 104 (40.8) | 80 (48.2) | 0.159 | −0.149 |
Data expressed in absolute numbers and percentage in parentheses; p: statistical significance (chi-square test). h—effect size Cohen’s h. COPD—chronic obstructive pulmonary disease; POAD—peripheral obstructive arterial disease.
Table A5.
Association between Patients with Anxiety (Trait and State) in Terms of Clinical Characteristics Gender and Age Groups.
Table A5.
Association between Patients with Anxiety (Trait and State) in Terms of Clinical Characteristics Gender and Age Groups.
| Trait Anxiety | State Anxiety | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Age Group | Positive | Negative | p | OR (CI95%) | Positive | Negative | p | OR (CI95%) | Total | |
| <45 | Gender | |||||||||
| Female | 41 (71.9) | 21 (40.4) | 0.001 | 3.783 (1.699–8.422) | 32 (72) | 30 (46.2) | 0.006 | 3.111 (1.366–7.088) | 62 (56.9) | |
| Male | 16 (28.1) | 31 (59.6) | 12 (27.3) | 35 (53.8) | 47 (43.1) | |||||
| 45–54 | Gender | |||||||||
| Female | 57 (58.2) | 42 (51.9) | 0.398 | 1.291 (0.714–2.335) | 49 (59.8) | 50 (51.5) | 0.271 | 1.396 (0.770–2.529) | 99 (55.3) | |
| Male | 41 (41.8) | 39 (48.1) | 33 (40.2) | 47 (48.5) | 80 (44.7) | |||||
| 55–64 | Gender | |||||||||
| Female | 101 (60.8) | 61 (48.8) | 0.041 | 1.630 (1.020–2.606) | 89 (60.5) | 73 (49.3) | 0.091 | 1.492 (0.938–2.376) | 162 (55.7) | |
| Male | 65 (39.2) | 64 (52.1) | 58 (39.5) | 71 (49.3) | 129 (44.3) | |||||
| ≥65 | Gender | |||||||||
| Female | 131 (67.2) | 117 (51.8) | 0.001 | 1.907 (1.282–2.836) | 120 (65.2) | 128 (54.0) | 0.020 | 1.597 (1.074–2.374) | 248 (58.9) | |
| Male | 64 (32.8) | 109 (48.2) | 64 (64.8) | 109 (46.0) | 173 (41.1) | |||||
| Breslow-Day Test | 0.187 | 0.423 | ||||||||
| Gender | ||||||||||
| General | Female | 330 (64) | 241 (49.8) | <0.001 | 1.834 (1.421–2.367) | 290 (63.5) | 281 (51.7) | <0.001 | 1.628 (1.262–2.099) | |
| Male | 186 (36) | 243 (50.2) | 167 (36.5) | 262 (48.3) | ||||||
Data expressed in absolute numbers and percentage in parentheses; p: statistical significance (chi-square test or Breslow–Day test). OR—odds ratio. CI95%—95% confidence interval.
References
- Malachias, M.V.B.; Barbosa, E.C.D.; Martim, J.F.V.; Rosito, G.B.A.; Toledo, J.Y.; PassarelliJúnior, O. 7ª Diretriz Brasileira de Hipertensão Arterial: Capítulo 14–CriseHipertensiva. Arq. Bras. Cardiol. 2016, 107, 79–83. [Google Scholar] [CrossRef]
- Hyman, D.J. Hypertension: Does Polypharmacy Lead to Non adherence or Non adherence to Polypharmacy? Hypertension 2017, 69, 1017–1018. [Google Scholar] [CrossRef]
- Hyman, D.J.; Pavlik, V. Medication adherence and resistant hypertension. J. Hum. Hypert. 2015, 29, 213–218. [Google Scholar] [CrossRef] [PubMed]
- Casiglia, E.; Tikhonoff, V.; Albertini, F.; Palatini, P. Poor Reliability of Wrist Blood Pressure Self-Measurement at Home. Hypertens. J. 2016, 68, 896–903. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sang-Ho, J.; Sung-Ai, K.; Kyoung-Ha, P.; Hyun-Sook, K.; Sang-Jin, H.; Woo-Jung, P. Self-blood pressure monitoring is associated with improved awareness, adherence, and attainment of target blood pressure goals: Prospective observational study of 7751 patients. J. Clin. Hypertens. 2019, 21, 1298–1304. [Google Scholar]
- Margolis, K.L.; Asche, S.E.; Bergdall, A.R.; Dehmer, S.P.; Groen, S.E.; Kadrmas, H.M.; Kerby, T.J.; Klotzle, K.J.; Maciosek, M.V.; Michels, R.D.; et al. Effect of Home Blood Pressure Telemonitoring and Pharmacist Management on Blood Pressure Control: The HyperLink Cluster Randomized Trial. NIH: Public Access Author Manuscript. JAMA 2015, 310, 46–56. [Google Scholar] [CrossRef] [Green Version]
- Boggia, J.; Thijs, L.; Hansen, T.W.; Kikuya, M.; Björklund-Bodegård, K.; Dolan, E. International Database on Ambulatory blood pressure in relation to Cardiovascular Outcomes Investigators. Ambulatory blood pressure monitoring in 9357 subjects from 11 populations highlights missed opportunities for cardiovascular prevention in women. Hypertension 2011, 57, 397–405. [Google Scholar] [CrossRef] [Green Version]
- Little, P.; Barnett, J.; Barnsley, L.; Marjoram, J.; Fitzgerald-Barron, A.; Mant, D. Comparison of acceptability of and preferences for diferente methods of measuring blood pressure in primary care. BMJ 2002, 325, 258–259. [Google Scholar] [CrossRef] [Green Version]
- Silva, S.S.B.E.; Oliveira, S.F.S.B.; Pierin, A.M.G. O controle da hipertensão arterial emmulheres e homens: Umaanálisecomparativa. Rev. Esc. Enferm. USP 2016, 50, 50–58. [Google Scholar] [CrossRef] [Green Version]
- de Souza, W.K.S.B.; Jardim, P.C.B.V.; Porto, L.B.; Araújo, F.A.; Sousa, A.L.L.; Salgado, C.M. Comparação e correlação entre automedida, medida casual e monitorizaçãoambulatorial da pressão arterial. Arq. Bras. Cardiol. 2011, 97, 148–155. [Google Scholar] [CrossRef] [Green Version]
- Boubouchairopoulou, N.; Karpettas, N.; Athanasakis, K.; Kollias, A.; Protogerou, A.D.; Achimastos, A.; Stergiou, G.S. Cost estimation of hypertension management based on home blood pressure monitoring alone or combined office and ambulatory blood pressure measurements. J. Am. Soc. Hypertens. JASH 2014, 8, 732–738. [Google Scholar] [CrossRef] [PubMed]
- Ribeiro, C.C.M.; Lamas, J.L.T. Comparação entre as técnicas de mensuração da pressão arterial em um e emdois tempos. Rev. Bras. Enferm. 2012, 65, 630–636. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Malta, D.C.; Gonçalves, R.P.F.; Machado, Í.E.; de Fátima Freitas, M.I.; Azeredo, C.; Szwarcwald, C.L. Prevalência da hipertensão arterial segundodiferentescritériosdiagnósticos, Pesquisa Nacional de Saúde. Rev. Bras. Epidemiol. 2018, 21, 1980–5497. [Google Scholar] [CrossRef] [PubMed]
- Wang, C.; Yuan, Y.; Zheng, M.; Pan, A.; Wang, M.; Zhao, M.; Li, Y.; Yao, S.; Chen, S.; Wu, S.; et al. Association of age of onset of hypertension with cardiovascular diseases and mortality. J. Am. Coll. Cardiol. 2020, 75, 2921–2930. [Google Scholar] [CrossRef] [PubMed]
- Whelton, P.K.; Carey, R.M.; Aronow, W.S.; Casey, D.E.J.; Collins, K.J.; Himmelfarb, C.D.; De Palma, S.M.; Gidding, S.; Jamerson, K.A.; Jones, D.W.; et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J. Am. Coll. Cardiol. 2018, 71, 127–248. [Google Scholar]
- Sociedade Brasileira de Cardiologia; Sociedade Brasileira de Hipertensao; Sociedade Brasileira de Nefrologia. VI Diretrizes Brasileiras de Hipertensão. Arq. Bras. Cardiol. 2010, 95, 1–3. [Google Scholar]
- Spielberger, C.D.; Biaggio, A.; Natalício, L.F. Inventário de Ansiedade Traço/estado: Manual de Psicologia Aplicada; CEPA: Rio de Janeiro, Brazil, 1979. [Google Scholar]
- Biaggio, A.M.; Natalicio, L. Manual of the Trait Anxiety Inventory-State (STAI); Applied Psychology Centre CEPA: Rio de Janeiro, Brazil, 1979. [Google Scholar]
- Cohen, J. Statistical power analysis for the behavioral sciences; Lawrence Erlbaum, Associates: Hillsdale, NJ, USA, 1988. [Google Scholar]
- Maynarde, I.G.; Jardin, T.V.; Souza, W.K.S.B.; Rocca, A.R.; Lin, B.Y.C.; Santos, N.M.C.; Sampao, D.P.S.; Serafim, X.L.M.; Jardim, P.C.B.V. A Pressão Arterial dos PacientesEstáSendoMedidaRotineiramentenosConsultóriosMédicos? Int. J. Cardiov. Sci. 2017, 30, 293–298. [Google Scholar]
- Mcmanus, R.J.; Mant, J.; Haque, M.S.; Bray, E.P.; Bryan, S.; Greenfield, S.M.; Jones, M.I.; Jowett, S.; Little, P.; Penaloza, C.; et al. Effect of self-monitoring and medication self-titration on systolic blood pressure in hypertensive patients at high risk of cardiovascular disease: The TASMIN-SR randomized clinical trial. J. Am. Med. Assoc. 2014, 312, 799–808. [Google Scholar] [CrossRef]
- Godwin, M.; Lam, M.; Birtwhistle, R.; Birtwhistle, R.; Delva, D.; Seguin, R.; Casson, I.; MacDonald, S. A primary care pragmatic cluster randomized trial of the use of home blood pressure monitoring on blood pressure levels in hypertensive patients with above target blood pressure. Fam. Pract. 2010, 27, 135–142. [Google Scholar] [CrossRef]
- Mcmanus, R.J.; Mant, J.; Roalfe, A.; Oakes, R.A.; Bryan, S.; Pattison, H.M.; Hobbs, F.D. Targets and self monitoring in hypertension: Randomised controlled trial and cost effectiveness analysis. BMJ 2005, 331, 493–498. [Google Scholar] [CrossRef] [Green Version]
- Gomes, T.J.O.; Rocha, S.M.V.; Santos, A.A. Blood pressure control in patients treated by the Hiperdia program in a Family Health Unit. Rev. Bras. Hipertensão 2010, 17, 132–139. [Google Scholar]
- Mengue, S.S.; Bertoldi, A.D.; Boing, A.C.; Tavares, N.U.L.; Dal Pizzo, T.S.; Oliveira, M.A.; Arrais, P.S.D.; Ramos, L.R.; Farias, M.R.; LuizaV, L.; et al. Pesquisa Nacional sobreAcesso, Utilização e Promoção do UsoRacional de Medicamentos (PNAUM): Métodos do inquéritodomiciliar. Rev. Saude Publica 2016, 50, 1–13. [Google Scholar]
- Naves, J.O.S.; Castro, L.L.C.; Carvalho, C.M.S.; Merchán-Hamann, E. Self-medication: A qualitative approach to your motivations. CiênciaSaúdeColetiva 2010, 15, 1751–1762. [Google Scholar]
- Yusuf, S.; Hawken, S.; Ounpuu, S.; Dans, T.; Avezum, A.; Lanas, F.; McQueen, M.; Budaj, A.; Pais, P.; Varigos, J.; et al. INTERHEART StudyInvestigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (The INTERHEART study): Case-control study. Lancet 2004, 364, 937–952. [Google Scholar] [CrossRef]
- Desousa, D.A.; Moreno, A.L.; Gauer, G.; Manfro, G.G.; Koller, S.H. Revisãosistemática de instrumentos para avaliação de ansiedadenapopulaçãobrasileira. Avaliação Psicológica 2013, 12, 397–410. [Google Scholar]
- de Souza, G.N.P.; Alves, R.J.R.; Souza, L.P.S.; Rosa, A.J. Prevalência de sintomasdepressivos e/ouansiososempessoas com hipertensão arterial sistêmica e/ou diabetes mellitus. Revista Portuguesa de Enfermagem de Saúde Mental 2018, 20, 43–50. [Google Scholar]
- Lacerda, M.S.; Cirelli, M.A.; de Barros, A.L.B.L.; de Lima Lopes, J. Ansiedade, estresse e depressão de familiares de pacientes com insuficiênciacardíaca. Revista da Escola de Enfermagem da USP 2017, 51, 1–8. [Google Scholar]
- Costa, M.G.S.; Dimenstein, M.D.B.; Leite, J.F. Condições de vida, gênero e saúde mental entre trabalhadorasruraisassentadas. Estud. Psicol. 2014, 19, 145–154. [Google Scholar]
- Cuevas, A.G.; Williams, D.R.; Albert, M.A. Psychosocial factors and hypertension: A review of the literature. Cardio Clin. 2017, 35, 223–230. [Google Scholar] [CrossRef] [Green Version]
- Whiteford, H.A.; Degenhardt, L.; Rehm, J.; Baxter, A.J.; Ferrari, A.J.; Erskine, H.E.; Charlson, F.J.; Norman, R.E.; Flaxman, A.D.; Johns, N.; et al. Global burden of disease attributable to mental and substance use disorders: Findings from the Global Burden of Disease Study 2010. Lancet 2013, 382, 1575–1586. [Google Scholar] [CrossRef]
- Hachem, M.E.; Siddiqui, M.; Thomas, S.J.; Dudenbostel, T.; Valaiyapathi, B.; Judd, E.; Patel, P.; Gupta, P.; Tomaszewski, M.; Oparil, S.; et al. Hypertensive Medications is Associated with Higher BP and Anxiety Levels. Hypertension 2018, 72, 369–374. [Google Scholar] [CrossRef]
- Moreira, J.P.L.; Moraes, J.R.; Luiz, R.R. Use of medical appointments and systemic arterial hypertension in urban and rural areas of Brazil, according to data from PNAD 2008. Rev. Ciência Saúde 2011, 16, 3781–3793. [Google Scholar]
- Baena-Díez, J.M.; Félix, F.J.; Grau, M. Treatment and control of risk factors according to coronary risk in the Spanish setting of the studio DARIOS. Rev. Española Cardiol. 2011, 64, 766–773. [Google Scholar] [CrossRef] [PubMed]
- Dorans, K.S.; Mills, K.T.; Liu, Y.; He, J. Trends in prevalence and control of hypertension according to the 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline. J. Am. Heart Assoc. 2018, 7, 1–12. [Google Scholar] [CrossRef] [Green Version]
- Brunström, M.; Carlberg, B. Association of blood pressure lowering with mortality and cardiovascular disease across blood pressure levels a systematic review and meta-analysis. JAMA Intern. Med. 2018, 178, 28–36. [Google Scholar] [CrossRef] [Green Version]
- Murray, C.J.L.; Lopez, A.D. Measuring the global burden of disease. N. Engl. J. Med. 2013, 369, 448–457. [Google Scholar] [CrossRef] [Green Version]
Figure 1.
Sample recruitment.
Table 1.
General characteristics of hypertensive patients.
| Characteristics | Values |
|---|---|
| Age | |
| <45 | 109 (10.9%) |
| 45–54 | 179 (17.9%) |
| 55–64 | 291 (29.1%) |
| ≥65 | 421 (42.1%) |
| Social class | |
| A | 78 (7.8%) |
| B | 131 (13.1%) |
| C | 180 (18%) |
| D | 243 (24.3%) |
| E | 368 (36.8%) |
| Marital Status | |
| Married | 607 (60.7%) |
| Divorced | 133 (13.3%) |
| Single | 139 (13.9%) |
| Widowed | 91 (9.1%) |
| Live with a partner | 30 (3.0%) |
| Education | |
| Never studied | 82 (8.2%) |
| Fundamental | 291 (29.1%) |
| High school | 315 (31.5%) |
| University | 271 (27.1%) |
| Graduate Studies | 41 (4.1%) |
| Comorbidities | |
| Yes | 523 (52.3%) |
| No | 368 (36.8%) |
| Use of medicines for comorbidities | |
| Yes | 464 (46.4%) |
| No | 535 (53.5%) |
Values expressed in absolute frequencies (n) and percentage in parentheses (%). A = High social class, B = High middle class. C = Middle social class. D = low middle class. D = Poor social class.
Table 2.
Estimation of frequency of self-measurement, control of arterial hypertension, self-medication and Unscheduled urgent visit.
Table 2.
Estimation of frequency of self-measurement, control of arterial hypertension, self-medication and Unscheduled urgent visit.
| Values | 95 % CI | |
|---|---|---|
| HOSPITAL | ||
| Public | 500 (50.0 %) | ----- |
| Private | 500 (50.0%) | ----- |
| SBP Public (mm Hg) | 137.6 ± 15.6 | 136.2–138.9 |
| DBP Public (mm Hg) | 78.5 ± 13.3 | 77.3–79.6 |
| SBP Private (mm Hg) | 133.1 ± 13.4 | 132.0–134.3 |
| DBP Private (mm Hg) | 77.6 ± 13.0 | 76.4–78.7 |
| Self-measurement | 447 (44.7%) | 41.8–47.7 |
| Controlled hypertension | 632 (63.2%) | 60.0–66.1 |
| Self-medication | 413 (41.3%) | 38.5–44.3 |
| Unscheduled urgent visit | 384 (38.4%) | 35.3–41.5 |
| Anxiety | ||
| Trait | 516 (51.6%) | 48.6–54.7 |
| State | 457 (45.7%) | 42.8–48.9 |
Values expressed in n (%) and 95% CI = 95% confidence interval. SBP = systolic blood pressure. DBP = diastolic blood pressure.
Table 3.
Comparison between patients with and without self-measurement of blood pressure regarding sociodemographic characteristics.
Table 3.
Comparison between patients with and without self-measurement of blood pressure regarding sociodemographic characteristics.
| Self-Measurement | ||||
|---|---|---|---|---|
| Sociodemographic | With | Without | p | h |
| Characteristics | (n = 447) | (n = 553) | ||
| Age (years) | 61.1 (12.2) | 61.0 (12.7) | 0.98 | 0.008 |
| <45 | 47 (10.5) | 62 (11.2) | 0.872 | −0.022 |
| 45–54 | 76 (17) | 103 (18.6) | −0.042 | |
| 55–64 | 134 (30) | 157 (28.4) | 0.035 | |
| ≥65 | 190 (42.5) | 231 (41.8) | 0.015 | |
| Hospital | ||||
| Public | 219 (49.0) | 281 (50.8) | 0.567 | −0.036 |
| Private | 228 (51.0) | 272 (49.2) | 0.036 | |
| Gender | ||||
| Female | 269 (60.2) | 302 (54.6) | 0.077 | 0.113 |
| Male | 178 (39.8) | 251 (45.4) | −0.113 | |
| Marital Status | ||||
| Married | 271 (60.6) | 336 (60.8) | 0.904 | −0.003 |
| Divorced | 62 (13.9) | 71 (12.8) | −0.002 | |
| Single | 58 (13.0) | 81 (14.6) | −0.048 | |
| Widowed | 41 (9.2) | 50 (9.0) | 0.004 | |
| Live with a partner | 15 (3.4) | 15 (2.7) | 0.037 | |
| Social class | ||||
| A | 29 (6.5) | 49 (8.6) | 0.017 | −0.089 |
| B | 47 (10.5) | 84 (15.2) | −0.14 | |
| C | 93 (20.8) | 87 (15.7) | 0.131 | |
| D | 120 (26.8) | 123 (22.2) | 0.107 | |
| E | 158 (35.3) | 210 (38.0) | −0.054 | |
| Education | ||||
| Never studied | 37 (8.3) | 45 (8.1) | 0.592 | 0.005 |
| Fundamental | 129 (28.9) | 162 (29. 3) | −0.01 | |
| High school | 143 (32.0) | 172 (31.1) | 0.019 | |
| University | 115 (25.7) | 156 (28.2) | −0.056 | |
| Graduate Studies | 23 (5.1) | 18 (3.3) | 0.095 | |
Age expressed as mean and standard deviation; other data expressed in absolute numbers and percentage in parentheses; p: statistical significance (chi-square test and Student’s t-test). A = high social class, B = high middle class. C = middle social class. D = low middle class. D = poor social class. h—Effect size Cohen’s D for continuous variables and Cohen’s h for categorical variables.
Table 4.
Comparison between patients with and without self-measurement of blood pressure regarding clinical characteristics.
Table 4.
Comparison between patients with and without self-measurement of blood pressure regarding clinical characteristics.
| Self-Measurement | ||||
|---|---|---|---|---|
| Clinical Features | With | Without | p | h |
| (n = 447) | (n = 553) | |||
| Comorbidities | 256 (57.3) | 267 (48.3) | 0.005 | 0.18 |
| Diabetes mellitus | 120 (26.8) | 96 (17.4) | <0.001 | 0.23 |
| Dyslipidemia | 182 (54.5) | 158 (28.6) | <0.001 | 0.256 |
| Coronary artery disease | 63 (14.1) | 53 (9.6) | 0.026 | 0.14 |
| Chronic kidney disease | 7 (1.6) | 13 (2.4) | 0.378 | −0.057 |
| Stroke | 29 (6.5) | 17 (3.1) | 0.01 | 0.162 |
| Depression | 11 (2.5) | 11 (2.0) | 0.613 | 0.032 |
| Cardiac insufficiency | 17 (3.8) | 28 (5.1) | 0.339 | −0.061 |
| Chronic obstructive pulmonary disease | 9 (2.0) | 7 (1.3) | 0.349 | 0.059 |
| Peripheral obstructive arterial disease | 19 (4.3) | 6 (1.1) | 0.001 | 0.207 |
| Use of medication for comorbidities | 223 (49.9) | 241 (43.7) | 0.05 | 0.126 |
| Purchase of the medicine | ||||
| Health center (free) | 144 (32.2) | 179 (32.4) | 0.155 | −0.029 |
| Popular pharmacy | 112 (25.1) | 112 (20.3) | 0.096 | |
| Pharmacy (full amount) | 191 (42.7) | 262 (47.4) | −0.129 | |
| Self-medication | 259 (57.9) | 154 (27.8) | <0.001 | 0.115 |
| Unscheduled visit | 304 (68) | 80 (14.5) | <0.001 | −0.093 |
| BP control | 209 (46.8) | 423 (76.5) | <0.001 | 0.618 |
| Anxiety | ||||
| Trait | 241 (53.9) | 275 (49.7) | 0.188 | 0.084 |
| State | 234 (52.3) | 223 (40.3) | <0.001 | 0.242 |
Data expressed in absolute numbers and percentage in parentheses; p: statistical significance (chi-square test). h—Effect size Cohen’s h.
Table 5.
Comparison between patients with controlled BP and uncontrolled BP in terms of sociodemographic characteristics.
Table 5.
Comparison between patients with controlled BP and uncontrolled BP in terms of sociodemographic characteristics.
| Controlled BP | ||||
|---|---|---|---|---|
| Characteristics | Yes | No | p | h |
| (n = 632) | (n = 368) | |||
| Age (years) | 60.5 ± 12.6 | 62.0 ± 12.2 | 0.058 | 0.121 |
| <45 | 76 (12) | 33 (9) | 0.174 | 0.1 |
| 45–54 | 121 (19.1) | 58 (15.8) | 0.089 | |
| 55–64 | 180 (28.5) | 111 (30.2) | −0.037 | |
| ≥65 | 255 (40.3) | 166 (45.1) | −0.096 | |
| Gender | ||||
| Female | 331 (52.4) | 240 (65.2) | <0.001 | −0.262 |
| Male | 301 (47.6) | 128 (34.8) | 0.262 | |
| Marital Status | ||||
| Married | 386 (61.1) | 221 (60.1) | 0.82 | 0.021 |
| Divorced | 83 (13.1) | 50 (13.6) | −0.001 | |
| Single | 90 (14.2) | 49 (13.3) | 0.027 | |
| Widowed | 57 (9.0) | 34 (9.2) | −0.008 | |
| Live with a partner | 16 (2.5) | 14 (3.8) | −0.073 | |
| Social class | ||||
| A | 51 (8.1) | 27 (7.3) | 0.33 | 0.027 |
| B | 93 (14.7 | 38 (10.3) | 0.133 | |
| C | 113 (17.9) | 67 (18.2) | −0.008 | |
| D | 147 (23.3) | 96 (26.1) | −0.066 | |
| E | 228 (36.1) | 140 (38.0) | −0.041 | |
| Education | ||||
| Never studied | 44 (7.0) | 38 (10.3) | 0.32 | −0.12 |
| Fundamental | 182 (28.8) | 109 (29.6) | −0.018 | |
| High school | 204 (32.3) | 111 (30.2) | 0.045 | |
| University | 178 (28.2) | 93 (25.3) | 0.065 | |
| Graduate Studies | 24 (3.8) | 17 (4.6) | −0.041 | |
Data expressed in absolute numbers and percentage in parentheses; p: statistical significance (chi-square test). h—Effect size Cohen’s D for continuous variables and Cohen’s h for categorical variables. A = high social class, B = high middle class. C = middle social class. D = low middle class. D = poor social class.
Table 6.
Comparison between patients with controlled BP and uncontrolled BP in terms of clinical characteristics.
Table 6.
Comparison between patients with controlled BP and uncontrolled BP in terms of clinical characteristics.
| Controlled BP | ||||
|---|---|---|---|---|
| Clinical Characteristics | Yes | No | p | h |
| (n = 632) | (n = 368) | |||
| Hospital | ||||
| Public | 297 (47.0) | 203 (55.2) | 0.013 | −0.163 |
| Private | 335 (53.0) | 165 (44.8) | 0.163 | |
| Comorbidites | ||||
| Total comorbidites | 297 (47.0) | 226 (61.4) | <0.001 | −0.29 |
| Diabetes mellitus | 113 (17.9) | 103 (28.0) | <0.001 | −0.242 |
| Dyslipidemia | 183 (29.0) | 157 (42.7) | <0.001 | −0.287 |
| Coronary artery disease | 71 (11.2) | 45 (12.2) | 0.636 | −0.031 |
| Chronic kidney disease | 10 (1.6) | 10 (2.7) | 0.216 | −0.079 |
| Stroke | 23 (3.6) | 23 (6.3) | 0.057 | −0.121 |
| Depression | 13 (2.1) | 9 (2.4) | 0.686 | −0.026 |
| Cardiac insufficiency | 29 (4.6) | 16 (4.3) | 0.859 | 0.012 |
| Chronic obstructive | 8 (1.3) | 8 (2.2) | 0.27 | −0.07 |
| pulmonary disease | ||||
| Peripheral obstructive | 8 (1.3) | 17 (4.6) | 0.001 | −0.208 |
| arterial disease | ||||
| Use of medication | 256 (40.5) | 208 (56.7) | <0.001 | −0.322 |
| for comorbidities | ||||
| Self-medication | 221 (35.0) | 192 (52.2) | <0.001 | −0.349 |
| Purchase of the medicine | ||||
| Health center (free) | 193 (30.5) | 130 (35.3) | 0.065 | −0.102 |
| Popular pharmacy | 135 (21.4) | 89 (24.2) | −0.067 | |
| Pharmacy (Full amount) | 304 (48.1) | 149 (40.5) | 0.153 | |
| Unscheduled visit | 161 (25.5) | 223 (60.6) | <0.001 | −0.726 |
| Anxiety | ||||
| Trait | 296 (46.8) | 220 (59.8) | <0.001 | −0.260 |
| State | 251 (39.7) | 206 (56.0) | <0.001 | −0.327 |
Data expressed in absolute numbers and percentage in parentheses; p: statistical significance (chi-square test). h—Effect size Cohen’s h.
Table 7.
Unadjusted odds ratio for factors associated with non-control of BP.
| Factors Associated with not Controlling Blood Pressure | |||
|---|---|---|---|
| Variable | Odds Ratio | 95% CI | p |
| Age | 1.09 | 1.000–1.021 | 0.059 |
| Female | 1.705 | 1.308–2.223 | <0.001 |
| Social Class | |||
| B | 0.772 | 0.424–1.406 | 0.397 |
| C | 1.12 | 0.642–1.952 | 0.69 |
| D | 1.234 | 0.724–2.101 | 0.44 |
| E | 1.16 | 0.695–1.935 | 0.57 |
| Comorbidities | |||
| Total comorbidities | 1.795 | 1.382–2.332 | <0.001 |
| Diabetes mellitus | 1.785 | 1.316–2.422 | <0.001 |
| Dyslipidemia | 1.826 | 1.395–2.388 | <0.001 |
| Use of medication for comorbidities | 1.921 | 1.481–2.493 | <0.001 |
| Purchase of Medicine | |||
| Popular pharmacy | 1.374 | 1.022–1.848 | 0.036 |
| Pharmacy (full amount) | 1.345 | 0.965–1.874 | 0.08 |
| Self-medication | 2.029 | 1.561–2.636 | <0.001 |
| Anxiety | |||
| Trait | 1.687 | 1.300–2.189 | <0.001 |
| State | 1.93 | 1.488–2.504 | <0.001 |
| Unscheduled visit | 4.499 | 3.417–5.924 | <0.001 |
| Self-measurement | 3.705 | 2.827–4.856 | <0.001 |
95% CI = 95% confidence interval. Logistic regression where the dependent variable is the lack of blood pressure control and the other independent variables; p: statistical significance (Fisher’s exact test, chi² test and Student’s t-test). B = high middle class. C = middle social class. D = low middle class. D = poor social class.
Table 8.
Adjusted odds ratio and their respective 95% CI for factors associated with non-BP control.
Table 8.
Adjusted odds ratio and their respective 95% CI for factors associated with non-BP control.
| Adjusted Odds Ratio | 95% CI | P | |
|---|---|---|---|
| Trait Anxiety | |||
| Female | 1.544 | 1.161–2.053 | 0.003 |
| Use of medication for comorbidities | 1.749 | 1.324–2.311 | <0.001 |
| Self-measurement of BP | 3.254 | 2.441–4.338 | <0.001 |
| Self-medication | 1.357 | 1.018–1.810 | 0.038 |
| State anxiety | 1.587 | 1.200–2.098 | 0.001 |
| State Anxiety | |||
| Female | 1.509 | 1.133–2.009 | 0.005 |
| Use of medication for comorbidities | 1.815 | 1.375–2.396 | <0.001 |
| Self-measurement of BP | 3.352 | 2.515–4.468 | <0.001 |
| Self-medication | 1.389 | 1.041–1.853 | 0.025 |
| Trait anxiety | 1.605 | 1.211–2.127 | 0.001 |
95% CI = 95% confidence interval. Logistic regression: not controlling arterial hypertension as dependent variable; independent variables: female gender, use of medication for comorbidity, self-measurement, self-medication, state/trait anxiety.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Almeida, G.d.O.; Aidar, F.J.; Matos, D.G.d.; Almeida-Neto, P.F.d.; Melo, E.V.d.; Barreto Filho, J.A.S.; Almeida-Santos, M.A.; Oliveira, V.B.; Almeida, R.R.d.; Santos, S.M.d.; et al. Non-Targeted Self-Measurement of Blood Pressure: Association with Self-Medication, Unscheduled Emergency Visits and Anxiety. Medicina 2021, 57, 75. https://0-doi-org.brum.beds.ac.uk/10.3390/medicina57010075
AMA Style
Almeida GdO, Aidar FJ, Matos DGd, Almeida-Neto PFd, Melo EVd, Barreto Filho JAS, Almeida-Santos MA, Oliveira VB, Almeida RRd, Santos SMd, et al. Non-Targeted Self-Measurement of Blood Pressure: Association with Self-Medication, Unscheduled Emergency Visits and Anxiety. Medicina. 2021; 57(1):75. https://0-doi-org.brum.beds.ac.uk/10.3390/medicina57010075
Chicago/Turabian StyleAlmeida, Glessiane de Oliveira, Felipe J. Aidar, Dihogo Gama de Matos, Paulo Francisco de Almeida-Neto, Enaldo Vieira de Melo, José Augusto Soares Barreto Filho, Marcos Antonio Almeida-Santos, Victor Batista Oliveira, Rebeca Rocha de Almeida, Suelen Maiara dos Santos, and et al. 2021. "Non-Targeted Self-Measurement of Blood Pressure: Association with Self-Medication, Unscheduled Emergency Visits and Anxiety" Medicina 57, no. 1: 75. https://0-doi-org.brum.beds.ac.uk/10.3390/medicina57010075
