Approval for this study was obtained from the Ethics Committee of the Dalian Municipal Central Hospital (YN2017-042-01). All patients with essential hypertension from September 2017 to September 2020 were enrolled in the Cardiology Outpatient department, Dalian Central Hospital, affiliated to Dalian Medical University. Inclusion criteria were: (1) Age range from 18 to 80 years; (2) Newly diagnosed with essential hypertension. The diagnostic criteria for essential hypertension were in accordance with 2010 Chinese guidelines for the management of hypertension [8]. The office BP before treatment was $\ge$140/90 mmHg (1 mmHg = 0.133 kpa), and the home blood pressure monitoring (HBPM) was $\ge$135/85 mmHg, or the 24 h mean BP of ambulatory blood pressure monitoring (ABPM) was $\ge$130/80 mmHg, with a daytime mean BP of ABPM $\ge$135/85 mmHg, and a night mean BP of ABPM of $\ge$120/70 mmHg. (3) The patient agreed to participate in the study and signed informed consent. Exclusion criteria [9]: (1) Individuals with obvious intellectual, hearing or physical impairment who was unable to cooperate. (2) Patients with a family history of mental illness. (3) Patients with malignant tumors. (4) Patients with cardiac insufficiency. (5) Individuals with recent use of psychoactive drugs. (6) Individuals who recently suffered a family tragedy. (7) Patients with occult hypertension, refractory hypertension, stroke, coronary heart disease, severe anemia, severe liver, and secondary hypertension, including obstructive sleep apnoea, renal parenchymal disease, atherosclerotic renovascular disease, fibromuscular dysplasia, primary aldosteronism, phaeochromocytoma, Cushing’s syndrome, thyroid disease, hyperparathyroidism and coarctation of the aortic. (8) Patients with severe trauma and a surgical history in the previous six months.

All patients were given regular and systematic drug therapy for 3 months in accordance with the requirements of the 2010 Chinese guidelines [8] the 2013 European Society of Hypertension (ESH)/European Society of Cardiology (ESC) guidelines [10] and 2018 ESC/ESH guidelines [11] for the management of arterial hypertension. The addition or subtraction of medications had been stopped for at least a month. Follow-up visits were made in the outpatient department every two weeks. The increase or decrease in drug treatment was based on the OBP, HBPM and patient symptoms. The increase or adjustment of drugs was stopped whenever BP in the clinic was 140/90 mmHg or HBPM was 135/85 mmHg, or when excessive hypotensive symptoms such as dizziness and fatigue appeared. The combination drugs were in single-drug dosage forms, and the dosage used was the internationally accepted conventional dosage. Non-pharmacological treatments, such as lifestyle changes, were also recommended for patients.

The method recommended by the 2010 Chinese guidelines for the management of hypertension [8] was used to measure the sitting BP of subjects in the morning. This was performed with a standard desktop mercury sphygmomanometer (30704005, Yuwell Group, Jiangsu, China) regularly calibrated by a professional doctor in a consulting room.

A Spacelabs Healthcare Automatic 24 h Ambulatory Blood Pressure Monitor (90217, Spacelabs Healthcare Ltd. Seattle, Washington, USA) was used, with standardized measurement performed according to the 2010 Chinese guidelines for the management of hypertension [8, 12]. If the invalid pseudo-error and blank data were found to exceed 30% of the total number, the data was considered invalid and measurements were made again the next day. The patient’s daily life and treatment process remained unchanged during monitoring, with the left upper limb remaining relatively stationary during each measurement.

The upper arm electronic sphygmomanometer (HEM7136, OMRON Corporation, Kyoto, Japan) was used in accordance with the 2010 Chinese guidelines for the management of hypertension [8]. Patients were asked to measure BP every morning and evening, after sitting for 5 to 10 minutes before measurement. BP was measured in the sitting position in order to keep the sphygmomanometer and heart at the same level during measurement. The measurement was performed 2 or 3 times repeatedly and the average value was taken. The BP from each measurement was recorded in detail.

Subjects were divided into two groups according to the OBP after 3 months of treatment: (1) The essential hypertension group with the white coat effect (white coat effect group). In these subjects, the difference between the systolic blood pressure (SBP) in the office and the 24 h mean SBP was 20 mmHg or more, and the difference between the diastolic blood pressure (DBP) in the office and the 24 h mean DBP was 10 mmHg or more. (2) The essential hypertension group without the white coat effect (control group). In these subjects, the difference between the SBP in the office and the 24 h mean SBP was less than 20 mmHg, and the difference between the DBP in the office and the 24 h mean DBP was less than 10 mmHg.

The data including gender, age, ethnicity, marital status, number of antihypertensive drugs used, and average daily cost of antihypertensive drugs was collected by uniformly trained professionals in accordance with uniform collection procedures through the uniform epidemiological questionnaires.

The Self-rating Anxiety Scale (SAS) and Beck Anxiety Inventory (BAI) were used to determine the level of anxiety. The survey was conducted in the form of a questionnaire by the same trained medical staff and was given in a quiet special room. The purely academic purpose of the survey was fully explained to the patients before the survey, so as to eliminate the patients’ defensive psychology. After seeking the consent of patients, the two scales were filled in by the patients themselves, and a few patients with a low educational level and/or poor vision were assessed independently according to their own and assisted answers. Before taking the questionnaire, how to fill in the scale correctly and the meaning of each item were explained to each patient, and then they were asked to fill in the questionnaire by making an independent self-assessment of their actual feelings of the last week. Furthermore, all patients had been informed of their OBP and ambulatory BP results before the investigation.

The SAS [13, 14] contains 20 items that measure the frequency of anxiety symptoms. The score was divided into four levels: 1 (no or little time), 2 (a small part of the time), 3 (a considerable amount of time), and 4 (most or all of time), and corresponding to 1, 2, 3, or 4 points, respectively. The score of items 5, 9, 13, 17, and 19 were in reverse, and the other items were scored in sequence, as shown in Appendix Table 5. The accumulated score of each item was the raw score. After the following formula conversion, Y = int (1.25x), in which the raw score was multiplied by 1.25 and the integral part was taken, the standard score was calculated. The anxiety severity was defined as follows: a score of 25–49 represented no anxiety; a score of 50–59 represented mild anxiety; a score of 60–69 represented moderate anxiety; and a score of 70–100 represented severe anxiety. The national normal mean of raw scores was 29.78 $\pm$ 0.46 (n = 1158), and the upper limit of the total raw score was 40.

The BAI [14] includes 21 different anxiety symptoms and mainly evaluates the extent to which subjects are bothered by different anxiety symptoms. The subject filling in the questionnaire was required to select the extent to which each symptom bothered them, which was divided into 1 point, representing no influence, 2 points, representing mild influence, 3 points, representing moderate influence, and 4 points, representing serious influence (Appendix Table 6). The scores of all items were accumulated to obtain raw scores, which were then converted into standard scores using the formula: Y = int (1.19x) and taking the integral part. The standard score of 45 was the threshold of judgment, and the higher the score, the more anxious the individual.

Both scales were used, and anxiety was confirmed when the scores were higher than their standard scores.

SPSS Statistics (version 24.0, SPSS Statistics, International Business Machines Corporation, Armonk, NY, USA) was used for statistical analysis. The measurement data were presented as the mean $\pm$ standard deviation (SD). If they were normally distributed, a t test was used for comparison between groups. Otherwise, a nonparametric rank sum test was used. The counting data were presented as rates or composition ratios, and a Chi-square test or Fisher’s exact probability method was used for comparison between groups. A logistic regression model was used to analyze other possible influencing factors of the white coat effect. If the p value was 0.05, it was considered statistically significant.

There was no significant difference in office SBP (169.1 $\pm$ 5.5 mmHg vs. 168.6 $\pm$ 6.2 mmHg, p = 0.433) and DBP (111.3 $\pm$ 5.5 mmHg vs. 111.0 $\pm$ 4.5 mmHg, p = 0.574) between the two groups before initiation of treatment. After treatment, the office BP in the white coat effect group was significantly higher than that in the control group. The difference of SBP between them was (29.7 $\pm$ 5.3) mmHg, and that of DBP was (14.4 $\pm$ 4.2) mmHg. The office BP of the white coat group was significantly higher than the value of ABPM after treatment. The difference between office SBP and 24 h mean SBP in the white coat effect group was (42.9 $\pm$ 8.0) mmHg, and that in the control group was (15.2 $\pm$ 3.1) mmHg. The difference between them was statistically significant (p 0.001). The difference between office DBP and 24 h mean DBP in the white coat effect group was (21.1 $\pm$ 6.8) mmHg, and that in the control group was (7.3 $\pm$ 1.9) mmHg. Likewise, the difference between them was statistically significant (p 0.001) (for details see Appendix Table 7).

The highest raw score of SAS in the control group was 58, and the lowest score was 20, with an average of 25.7 $\pm$ 8.0. The highest standard score was 72, the lowest was score 25, and the average score was 31.8 $\pm$ 9.9. Among them, there were 48 cases with a standard score of $\ge$50. The highest raw score of SAS in the white coat effect group was 50, and the lowest score was 20, with an average score of 26.2 $\pm$ 6.8. The highest standard score was 63, the lowest score was 25, and the average score was 32.8 $\pm$ 8.5. Among them, there were 11 cases that had a standard score of $\ge$50. There was no statistically significant difference between the white coat effect group and the control group in either raw score or standard score (Table 1).

The highest raw score of BAI in the control group was 58, and the lowest score was 21, with an average of 26.7 $\pm$ 7.9. The highest standard score was 69, the lowest was score 24, and the average score was 31.2 $\pm$ 9.5. Among them, there were 48 cases that had a standard score $\ge$45, and all of them had an SAS standard score $\ge$50. The highest raw score of BAI in the white coat effect group was 51, and the lowest score was 21, with an average of 26.9 $\pm$ 7.0. The highest standard score was 60, the lowest score was 24, and the average score was 31.4 $\pm$ 8.3. Among them, there were 11 cases that had a standard score $\ge$45, and all of them had an SAS standard score $\ge$50. There was no statistically significant difference between the white coat effect group and the control group (p $>$ 0.05) for either the raw score or standard score (Table 1).

The respondents were all Han Chinese, and the medication use was summarized in the Appendix Table 8. The proportion of females, age, daily cost of antihypertensive drugs, and number of antihypertensive drugs in the white coat effect group were significantly higher than those in the control group (p 0.05). However, there was no statistically significant difference in the marital status between the two groups (p $\mathrm{>}$ 0.05) (Table 2).

With the white coat effect as the dependent variable, and anxiety, gender, age, daily cost of antihypertensive drugs, number of antihypertensive drugs, and marital status as independent variables, logistic regression analysis was performed (Table 3). The results showed that gender, age, number of antihypertensive drugs and cost per tablet were factors related to the white coat effect (Table 4).