Abstract
This study aimed to explore the relationship of thyroid‐stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) levels with hypertension subtypes. 1056 euthyroid adults were included as research samples. They underwent measurement of clinic blood pressure and 24‐hours ambulatory blood pressure monitoring. Then, they were divided into normotension (NT), white coat hypertension (WCH), masked hypertension (MHT), and sustained hypertension (SHT) groups. The 24‐hours dynamic electrocardiogram was performed to analyze the heart rate variability (HRV), so as to reflect the cardiac autonomic function. The relationship between hypertension subtypes, thyroid function, and HRV was analyzed. The TSH concentration was significantly higher in the SHT group than in the NT group (P = 0.001). The FT3 concentration was higher in the SHT group than in the NT and MHT groups (P = 0.013, P = 0.008), while the FT4 concentration was significantly higher in the WCH group than in the NT group (P = 0.002). The changes in HRV were observed between the SHT, WCH, and MHT groups and the NT groups, as well as between the SHT and the MHT groups. The multiple linear regression analysis also showed that FT3, HRV (RMSSD and PNN50), and blood pressure levels linearly correlated with one another (P < 0.05). Meanwhile, the linear regression analysis showed a linear negative correlation between FT4 and HRV (SDANN) in the WCH + NT group (P = 0.001). Thyroid function was closely related to hypertension subtypes such as WCH probably due to the changes in the cardiac autonomic function.
Keywords: masked hypertension, sustained hypertension, thyroid function, thyroid‐stimulating hormone, white coat hypertension
1. INTRODUCTION
A close and complicated relationship exists between thyroid function and hypertension.1, 2 Both hyperthyroidism and hypothyroidism can lead to an increase in blood pressure.3 Hyperthyroidism mainly leads to increased systolic blood pressure (SBP), while hypothyroidism mainly results in the elevation of diastolic blood pressure (DBP).4 Subclinical hyperthyroidism and hypothyroidism may have an effect on the increase in blood pressure, but the results of studies have been controversial.5, 6 A correlation between the thyroid function and blood pressure levels may exist in people with normal thyroid function. Thyroid‐stimulating hormone (TSH) was the most sensitive indicator of changes in thyroid function.7 Therefore, most clinical studies focused on the relationship between TSH and blood pressure levels.8, 9, 10 In 2018, the meta‐analysis of He et al showed the relationship of TSH with increased clinic systolic and diastolic blood pressures, but it could not explain the high heterogeneity in the results of analysis (I 2 = 90%).11 In addition, many recent clinical studies did not support the results.12, 13 Moreover, the effect of the two thyroid function indicators free triiodothyronine (FT3) and free thyroxine (FT4), which had a direct action, on the blood pressure was still not known.14 Based on the aforementioned uncertainties, it was speculated that previous studies of simply exploring the clinic blood pressure might not correctly reflect the relationship between thyroid function and blood pressure. The combination of clinic blood pressure and ambulatory blood pressure can better explore the relationship between thyroid function and blood pressure.
At present, the application of ambulatory blood pressure monitoring has become increasingly common.15 Combining the ambulatory blood pressure monitoring with clinic blood pressure measurement, the blood pressure can be divided into normotension pressure (NT) and three subtypes of hypertension: white coat hypertension (WCH), masked hypertension (MHT), and sustained hypertension (SHT).16, 17 This method of division has made significant progress compared with the traditional method of dividing hypertension and normal blood pressure based on only clinic blood pressure measurement.18 Especially, it can separately explain the mechanism of hypertension in the three different hypertension subtypes, avoiding the interference of the white coat and masked effects on the research results.19 Previous research results showed that changes in cardiac autonomic function played an important role in the occurrence and identification of hypertension subtypes such as white coat hypertension. For example, Fagard et al observed increased sympathetic activity and decreased parasympathetic modulation in white coat hypertension, but with normal autonomic cardiac regulation in masked hypertension.20 As we know, the thyroid function was closely related to the cardiac sympathetic function. High‐level thyroid hormones induced the cardiac sympathetic overactivity and increased ventricular repolarization dynamicity.21, 22, 23, 24 Whether the thyroid function was related to the occurrence of hypertension subtypes such as WCH due to the changes in cardiac autonomic function is still unknown. In addition, whether the relationship between TSH and ambulatory blood pressure levels was consistent with the results of the studies about clinic blood pressure requires further exploration. Therefore, this clinical study was designed to explore the relationship between thyroid function and hypertension subtypes such as WCH and MHT and investigate whether this relationship attributed to changes in cardiac autonomic function.
2. PARTICIPANTS AND METHODS
2.1. Study participants
From December 2017 to December 2018, 2437 outpatients were randomly selected from the Daping Hospital of the Army Military Medical University. The research samples were adults who had completed the examinations of thyroid function. They were further screened according to the following exclusion criteria: (a) participants using antihypertensive drugs; (b) participants using drugs that affect thyroid function, the list of the eliminated drugs was methimazole, propylthiouracil, levothyroxine, thyroxine, amiodarone, tyrosine kinase inhibitor, and interferon; (c) participants with abnormal thyroid function, thyroid cancer, thyroiditis, and thyrocele; (d) participants with secondary hypertension with definite etiology, just like renal parenchymal and renovascular hypertension, primary aldosteronism, pheochromocytoma, and Cushing syndrome; (e) participants with renal insufficiency or hepatic insufficiency (alanine aminotransferase ≥ 80 IU/L, serum creatinine ≥ 133 μmol/L); and (f) participants with organic heart diseases such as congenital heart disease and dilated cardiomyopathy. After the strict screening, 1056 participants with normal thyroid function were included as research samples. The study was reviewed and approved by the Ethics Committee of Daping Hospital and registered in the Chinese Clinical Trial Registry. The registration number was ChiCTR1800015507. The participants provided informed consent for this study.
2.2. Study grouping
The participants were grouped according to the results of clinic blood pressure measurement and ambulatory blood pressure monitoring. The basis for grouping was the criteria in the European Hypertension Practice Guide 2018, and the cutoff value of blood pressure elevation was set to the clinic blood pressure ≥ 140/90 mm Hg. For the ambulatory blood pressure, the daytime average blood pressure was ≥135/85 mm Hg, the nighttime average blood pressure was ≥120/70 mm Hg, and the 24‐hours average blood pressure was ≥130/80 mm Hg. The four groups were as follows: SHT, participants with elevated clinic and ambulatory blood pressures; WCH, participants with elevated clinic and normal ambulatory blood pressures; MHT, participants with normal clinic and elevated ambulatory blood pressures; and NT, participants with normal clinic and ambulatory blood pressures.25, 26
2.3. Methods
2.3.1. General data
The age, sex, smoking history, drinking history, diabetes history, history of hyperlipidaemia, history of hyperuricaemia, and family history of hypertension were collected using a questionnaire. The height and weight of the selected participants were measured in the field, and the body mass index (BMI) was calculated. (BMI) = weight (kg)/height2(m).27
2.3.2. Measurement of blood pressure
After the participants took a sitting position for rest in the clinic for 20 minutes, the blood pressure at their brachial artery was measured three times by specialized medical stuff using a mercury sphygmomanometer. The interval was not less than 12 hours, and the average value of blood pressure was taken as the clinic blood pressure. The 24‐hours ambulatory blood pressure monitoring was conducted using the ambulatory electrocardiogram (ECG) blood pressure recorder CB‐2301‐A (Wuxi, China). The blood pressure between 6:00 and 22:00 was measured as daytime blood pressure and that between 22:00 and 6:00 as the nighttime blood pressure. The patients were asked to work and rest according to this rule. The blood pressure was measured every 30 minutes in a whole day. The effective daytime blood pressure count was required to be more than 80%, and the nighttime blood pressure was required to have one effective blood pressure per hour. Each patient was instructed to avoid unusual physical activities and to keep their arm still during BP measurements. Average values for the 24‐hour, daytime, and nighttime systolic and diastolic BP levels, and for heart rate were extracted. The blood pressure variability was analyzed using the ambulatory blood pressure analysis software V6.1.9 (Wuxi, China), and the values of 24‐hours SBP standard deviation, 24‐hours DBP standard deviation, 24‐hours SBP coefficient of variation, and 24‐hours DBP coefficient of variation parameters were obtained. The clinic mean arterial pressure (Clinic MAP) was calculated from the clinic systolic and diastolic blood pressures. The 24‐hours mean arterial pressure (24‐hours MAP) was calculated from the mean values of 24‐hours systolic and diastolic blood pressures. The computational formula was (systolic blood pressure + 2 × diastolic blood pressure)/3.28, 29
2.3.3. Detection of thyroid function
After 12 hours of fasting, the blood was collected from each participant's anterior elbow vein at 6:00‐8:00 in the morning, and TSH, FT3, and FT4 levels were detected by electrochemiluminescence using a Beckman DXI800 automatic biochemical analyzer (Brea, USA). Participants with normal thyroid function were screened according to the parameters of the laboratory. The normal range of the laboratory test was set as follows: TSH, 0.34‐5.60 μIU/mL; FT3, 3.09‐7.42 pmol/L; and FT4, 7.64‐16.03 pmol/L.
2.3.4. Biochemical tests
The blood was collected from the anterior elbow vein after 12 hours of fasting. The total bilirubin, alanine aminotransferase, aspartate aminotransferase, total cholesterol, triglyceride, high‐density lipoprotein cholesterol, low‐density lipoprotein cholesterol, apolipoprotein B, fasting blood glucose, serum creatinine, and uric acid levels, as well as the glomerular filtration rate, were detected using the Beckman A5800 biochemical analyzer (Brea, USA).
2.3.5. Analysis of heart rate variability
The 24‐hours ambulatory electrocardiogram examination was performed using the ambulatory ECG blood pressure recorder CB‐2301‐A (Wuxi, China). The results were subjected to temporal domain analysis to analyze the heart rate variability using the ambulatory ECG analysis software V6.1.9 (Wuxi, China). The values of standard deviation of normal‐to‐normal RR intervals (SDNN), standard deviation of average normal‐to‐normal RR intervals (SDANN), root mean square of successive differences between adjacent RR intervals (RMSSD), and percentage of adjacent NN intervals differing by more than 50 ms (pNN50) parameters reflecting the cardiac autonomic nervous system were obtained.30 The increase in SDNN and SDANN reflected the weakening of cardiac sympathetic function, and the increase in RMSSD and PNN50 reflected the strengthening of cardiac vagus nerve function.31, 32
2.3.6. Statistical analysis
The research data were imported by the Epidata 3.1 software (Odense, Denmark) and analyzed in the SPSS 22.0 software (New York, USA). The enumeration data were calculated using the chi‐square test. If the measurement data conformed to the homogeneity of variance and normal distribution, one‐way analysis of variance or independent‐sample t test was selected according to the number of groups. If the data did not conform to the homogeneity of variance and normal distribution, the Kruskal‐Wallis rank‐sum test was used. The age, sex, BMI, smoking history, drinking history, family history of hypertension, diabetes, hyperlipidaemia, and hyperuricaemia were adjusted in the unconditional logistic regression analysis to further analyze the correlation between thyroid function and hypertension subtypes. Forward options were used to select the significant covariates, and the goodness of fit of logistic regression models was tested by Hosmer‐Lemeshow test. Multiple linear regression analysis was used to determine the linear relationship among thyroid function, blood pressure levels, and heart rate variability. The GraphPad Prism 7.0 software (La Jolla, USA) was used for drawing scientific figures.
3. RESULTS
This study was a cross‐sectional observational study. From December 2017 to December 2018, a total of 2437 adults who completed the thyroid function tests were involved in the study. After a detailed understanding of the medical history and examination results of the participants, 991 using antihypertensive drugs, 53 using drugs affecting the thyroid function, 247 with abnormal thyroid function or other thyroid diseases, 13 with secondary hypertension, 54 with liver and kidney dysfunction, and 23 with organic heart disease were excluded. Eventually, 1056 participants with normal thyroid function were included as research samples. Of these, 422 (40%) were in the NT group, 132 (12.5%) in the WCH group, 245 (23.2%) in the MHT group, and 257 (24.3%) in the SHT group. No statistically significant difference in sex was found between the four groups. The participants in the SHT and WCH groups were older than those in the NT group (62.5 ± 11.2 vs 60.5 ± 12.0, P = 0.035; 63.6 ± 11.6 vs 60.5 ± 12.0, P = 0.004, Table 1), and the BMI of the participants was significantly higher in the WCH, MHT, and SHT groups than in the NT group (P < 0.001, Table 1). Statistically significant differences in the family history of hypertension, diabetes, hyperlipidaemia, and hyperuricaemia were observed between groups (P = 0.001, P = 0.004, P = 0.014, P = 0.010, Table 1). The blood glucose and lipid levels in the WCH, MHT, and SHT groups increased to varying degrees compared with the NT group (P < 0.05, Table 1). The serum creatinine and uric acid levels increased in the SHT group compared with the NT group (68.8 ± 18.0 μmol/L vs 66.1 ± 17.3 μmol/L, P = 0.009; 344.7 ± 92.0 μmol/L vs 318.8 ± 84.8 μmol/L, P < 0.001). The detailed results are shown in Table 1.
Table 1.
General characteristics of outpatients stratified into four BP categories
| Parameters | NT | WCH | MHT | SHT | P value |
|---|---|---|---|---|---|
| Individuals (%) | 422 (40) | 132 (12.5) | 245 (23.2) | 257 (24.3) | ‐ |
| Female (%) | 217 (51.4) | 68 (51.5) | 121 (49.4) | 106 (41.2) | 0.060 |
| Age (y) | 60.5 ± 12.0 | 63.6 ± 11.6* | 62.3 ± 11.7 | 62.5 ± 11.2* | 0.014 |
| BMI (kg/m2) | 23.1 ± 3.1 | 24.0 ± 2.9* | 23.7 ± 3.1* | 24.8 ± 3.7* | <0.001 |
| Family history (% | 56 (13.3) | 29 (22.0) | 38 (15.5) | 64 (24.9) | 0.001 |
| Smoking (%) | 122 (28.9) | 33 (25) | 72 (29.4) | 82 (31.9) | 0.561 |
| Drinking (%) | 100 (23.7) | 23 (17.4) | 50 (20.4) | 60 (23.3) | 0.400 |
| Diabetes (%) | 44 (10.4) | 15 (11.4) | 42 (17.1) | 50 (19.5) | 0.004 |
| Hyperlipidaemia (%) | 184 (43.6) | 62 (47.0) | 119 (59.2) | 145 (56.4) | 0.014 |
| Hyperuricaemia (%) | 124 (29.4) | 41 (31.1) | 80 (32.7) | 107 (41.6) | 0.010 |
| Total bilirubin (μmol/L) | 13.3 ± 6.6 | 13.4 ± 7.1 | 12.4 ± 5.2 | 13.1 ± 5.1 | 0.206 |
| Alanine aminotransferase (IU/L) | 22.4 ± 13.3 | 22.8 ± 13.6 | 23.1 ± 14.8 | 24.8 ± 16.0 | 0.531 |
| Aspartate aminotransferase (IU/L) | 23.9 ± 10.5 | 24.4 ± 11.9 | 24.0 ± 10.7 | 25.1 ± 11.2 | 0.471 |
| Total cholesterol (mmol/L) | 4.1 ± 1.0 | 4.2 ± 1.0 | 4.3 ± 1.0 | 4.3 ± 1.1 | 0.100 |
| Triglyceride (mmol/L) | 1.5 ± 0.9 | 1.7 ± 1.1* | 1.6 ± 1.1* | 1.9 ± 1.6* | 0.001 |
| High‐density lipoprotein cholesterol (mmol/L) | 1.2 ± 0.3 | 1.2 ± 0.3 | 1.1 ± 0.3 | 1.1 ± 0.3 | 0.145 |
| Low‐density lipoprotein cholesterol (mmol/L) | 2.6 ± 0.7 | 2.7 ± 0.7 | 2.7 ± 0.7 | 2.8 ± 0.8* | 0.038 |
| Apolipoprotein B (g/L) | 0.8 ± 0.2 | 0.9 ± 0.2* | 0.9 ± 0.3* | 0.9 ± 0.3* | 0.016 |
| Glucose (mmol/L) | 5.3 ± 4.2 | 5.8 ± 2.8* | 5.7 ± 4* | 5.6 ± 1.6* | <0.001 |
| Serum creatinine (μmol/L) | 66.1 ± 17.3 | 66.5 ± 15.7 | 68.1 ± 16.6 | 68.8 ± 18.0* | 0.049 |
| Uric acid (μmol/L) | 318.8 ± 84.8 | 327.5 ± 86.2 | 324.8 ± 84.5 | 344.7 ± 92.0* | 0.003 |
| Glomerular filtration rate (mL/min/1.73m2) | 127.3 ± 27.7 | 124.1 ± 28.2 | 123.7 ± 29.1 | 122.9 ± 26.6 | 0.106 |
BMI, body mass index; BP, blood pressure; MHT, masked hypertension; NT, normotension; SHT, sustained hypertension; WCH, white coat hypertension.
P < 0.05 vs the NT group.
3.1. Blood pressure levels
The results of clinic blood pressure measurement and the 24‐hours ambulatory blood pressure monitoring are presented in Table 2. The clinic MAP was higher in the WCH group than in the MHT and NT groups (102.8 ± 7.4 mm Hg vs 87.9 ± 8.4 mm Hg, P < 0.001; 102.8 ± 7.4 mm Hg vs 85.0 ± 8.3 mm Hg, P < 0.001), but lower than in the SHT group (102.8 ± 7.4 mm Hg vs 109.5 ± 10.6 mm Hg, P = 0.003). The 24‐hours MAP was higher in the WCH group than in the NT group (84.0 ± 4.9 mm Hg vs 80.9 ± 5.1 mm Hg, P < 0.001), but lower than in the SHT and MHT groups (84.0 ± 4.9 mm Hg vs 95.5 ± 7.8 mm Hg, P < 0.001; 84.0 ± 4.9 mm Hg vs 90.2 ± 5.3 mm Hg, P < 0.001). The clinic MAP was higher in the MHT group than in the NT group (87.9 ± 8.4 mm Hg vs 85.0 ± 8.3 mm Hg, P = 0.002), but lower than in the SHT and WCH groups (87.9 ± 8.4 mm Hg vs 109.5 ± 10.6 mm Hg, P < 0.001; 87.9 ± 8.4 mm Hg vs 102.8 ± 7.4 mm Hg, P < 0.001). No statistically significant difference in the clinic systolic arterial pressure was found between the SHT and WCH groups (P > 0.05). Also, no statistically significant difference in the clinic diastolic arterial pressure was observed between the MHT and NT groups (P > 0.05).
Table 2.
Blood pressure and heart rate levels of outpatients stratified into four BP categories
| Parameters | NT | WCH | MHT | SHT | P value |
|---|---|---|---|---|---|
| Clinic BP measurement | |||||
| Systolic BP (mm Hg) | 112.8 ± 12.3# , △ , ▽ | 142.7 ± 11.2* , △ | 118.7 ± 13.2* , △ , ▽ | 148.7 ± 15.9* , △ | <0.001 |
| Diastolic BP (mm Hg) | 71.1 ± 8.3# , ▽ | 82.9 ± 11.0* , △ , ▽ | 72.5 ± 8.6# , ▽ | 89.8 ± 12.2* , # , △ | <0.001 |
| Clinic MAP (mm Hg) | 85.0 ± 8.3# , △ , ▽ | 102.8 ± 7.4* , △ , ▽ | 87.9 ± 8.4* , # , ▽ | 109.5 ± 10.6* , # , △ | <0.001 |
| Heart rate (bpm) | 76.8 ± 13.8▽ | 77.8 ± 14.1 | 77.1 ± 14.6▽ | 80.0 ± 14.4* , △ | <0.001 |
| 24‐h BP measurement | |||||
| Systolic BP (mm Hg) | 109.5 ± 7.2# , △ , ▽ | 114.9 ± 7.0* , △ , ▽ | 122.4 ± 9.9* , # , ▽ | 130.8 ± 11.6* , # , △ | <0.001 |
| Diastolic BP (mm Hg) | 66.6 ± 4.7# , △ , ▽ | 68.6 ± 4.8* , △ , ▽ | 74.1 ± 4.7* , # , ▽ | 77.8 ± 7.4* , # , △ | <0.001 |
| 24‐h MAP (mm Hg) | 80.9 ± 5.1# , △ , ▽ | 84.0 ± 4.9* , △ , ▽ | 90.2 ± 5.3* , # , ▽ | 95.5 ± 7.8* , # , △ | <0.001 |
| Heart rate (bpm) | 69.5 ± 7.8△ , ▽ | 69.9 ± 8.5△ , ▽ | 71.5 ± 8.9* , # | 72.8 ± 8.9* , # | <0.001 |
| Daytime BP measurement | |||||
| Systolic BP (mm Hg) | 111.1 ± 7.8# , △ , ▽ | 116.8 ± 7.6* , △ , ▽ | 122.8 ± 10.0* , # , ▽ | 131.5 ± 11.6* , # , △ | <0.001 |
| Diastolic BP (mm Hg) | 67.8 ± 5.2# , △ , ▽ | 70.0 ± 5.4* , △ , ▽ | 74.6 ± 5.1* , # , ▽ | 78.6 ± 7.8* , # , △ | <0.001 |
| Heart rate (bpm) | 71.8 ± 8.0△ , ▽ | 72.1 ± 8.7▽ | 73.5 ± 9.0* | 74.6 ± 9.1* , # | <0.001 |
| Nighttime BP measurement | |||||
| Systolic BP (mm Hg) | 104.3 ± 7.9# , △ , ▽ | 108.0 ± 7.0* , △ , ▽ | 120.6 ± 11.8* , # , ▽ | 128.8 ± 14.5* , # , △ | <0.001 |
| Diastolic BP (mm Hg) | 62.5 ± 4.9△ , ▽ | 63.5 ± 5.0△ , ▽ | 72.2 ± 5.6* , # | 75.1 ± 8.1* , # | <0.001 |
| Heart rate (bpm) | 61.9 ± 8.6△ , ▽ | 62.8 ± 8.9△ , ▽ | 65.0 ± 10.0* , # , ▽ | 66.6 ± 9.5* , # , △ | <0.001 |
| Blood pressure variability | |||||
| SBP standard deviation | 12.8 ± 3.3# , △ , ▽ | 13.6 ± 3.2* | 13.5 ± 3.5* , ▽ | 14.2 ± 3.5* , △ | <0.001 |
| DBP standard deviation | 8.9 ± 2.3△ , ▽ | 9.9 ± 8.1▽ | 9.4 ± 2.3* , ▽ | 10.0 ± 2.9* , # , △ | <0.001 |
| SBP coefficient of variation | 0.12 ± 0.03△ , ▽ | 0.12 ± 0.03△ , ▽ | 0.11 ± 0.04* , # | 0.14 ± 0.56* , # | <0.001 |
| DBP coefficient of variation | 0.13 ± 0.04 | 0.14 ± 0.10 | 0.13 ± 0.04 | 0.13 ± 0.08 | 0.058 |
| Heart rate variability | |||||
| SDNN | 130.7 ± 43.6# , △ , ▽ | 118.1 ± 43.3* , ▽ | 119.9 ± 43.3* , ▽ | 113.3 ± 43.9* , # , △ | <0.001 |
| SDANN | 110.5 ± 50.4# , △ , ▽ | 97.2 ± 35.2* | 98.1 ± 38.6* | 95.1 ± 43.1* | <0.001 |
| RMSSD | 71.7 ± 74.0# , ▽ | 56.9 ± 59.5* | 65.4 ± 62.8▽ | 58.7 ± 68.2* , △ | <0.001 |
| PNN50 (%) | 14.6 ± 20.1# , ▽ | 10.0 ± 16.5* , △ | 13.6 ± 20.3# , ▽ | 11.0 ± 18.3* , △ | <0.001 |
BP, blood pressure; MAP, mean arterial pressure; MHT, masked hypertension; NT, normotension; PNN50, percentage of adjacent NN intervals differing by more than 50 ms; RMSSD, root mean square of successive differences between adjacent RR intervals; SDANN, standard deviation of average normal‐to‐normal RR intervals; SDNN, normal‐to‐normal RR intervals; SHT, sustained hypertension; WCH, white coat hypertension.
P < 0.05 vs the NT group.
P < 0.05 vs the WCH group.
P < 0.05 vs the MHT group.
P < 0.05 vs the SHT group.
3.2. Heart rate and blood pressure variability
The heart rate variability changed in the WCH, MHT, and SHT groups compared with the NT group. Compared with the NT group, the values of SDNN, SDANN, RMSSD, and SDANN decreased in the WCH and SHT groups, while only the values of SDNN and SDANN decreased in the MHT group (P < 0.001, Table 2). Interestingly, the values of SDNN, RMSSD, and PNN50 also decreased in the SHT group compared with the MHT group (113.3 ± 43.9 vs 119.9 ± 43.3, P = 0.007; 58.7 ± 68.2 vs 65.4 ± 62.8, P = 0.003; 11.0 ± 18.3% vs 13.6 ± 20.3%, P = 0.007). The blood pressure variability (24‐hours SBP standard deviation, 24‐hours DBP standard deviation, and 24‐hours SBP coefficient of variation) increased in the WCH, MHT, and SHT groups compared with the NT group (P < 0.001, Table 2), while the blood pressure variability (24‐hours SBP standard deviation and 24‐hours DBP standard deviation) was significantly higher in the SHT group than in the MHT group (14.2 ± 3.5 vs 13.5 ± 3.5, P = 0.026; 10.0 ± 2.9 vs 9.4 ± 2.3, P = 0.011).
3.3. Thyroid function
The concentration of TSH was negatively related to the FT4 level in the total samples (P = 0.038, B = −0.099, 95% CI: −0.193 to −0.005). Statistically significant differences in TSH, FT3, and FT4 levels were found between groups (Table 3). The TSH concentration was higher in the SHT group than in the NT and WCH groups (2.4 ± 1.1 μIU/mL vs 2.1 ± 1.0 μIU/mL, P = 0.001; 2.4 ± 1.1 μIU/mL vs 2.1 ± 1.2 μIU/mL, P = 0.019; Figure 1A). The concentration of FT3 was higher in the SHT group than in the NT and MHT groups (5.2 ± 0.7 pmol/L vs 5.1 ± 0.7 pmol/L, P = 0.013; 5.2 ± 0.7 pmol/L vs 5.0 ± 0.7 pmol/L, P = 0.008; Figure 1B), while the concentration of FT4 was significantly higher in the WCH group than in the NT group (11.7 ± 1.8 pmol/L vs 11.1 ± 1.7 pmol/L, P = 0.002, Figure 1C). After adjusting for age, sex, BMI, family history of hypertension, smoking history, drinking history, diabetes, hyperlipidaemia, and hyperuricaemia, the logistic regression analysis showed that the statistical difference in the TSH level between the WCH and SHT groups disappeared (P = 0.078, Table 4), and the other differences were still statistically significant (P < 0.05, Table 4). All the goodness of fit of logistic regression models was well (Hosmer‐Lemeshow test, P > 0.05, Table 4).
Table 3.
Thyroid function of outpatients stratified into four BP categories
| Parameters | NT | WCH | MHT | SHT | P value |
|---|---|---|---|---|---|
| Thyroid‐stimulating hormone (μIU/mL) | 2.1 ± 1.0 | 2.1 ± 1.2 | 2.3 ± 1.2 | 2.4 ± 1.1 | 0.006 |
| Free triiodothyronine (pmol/L) | 5.1 ± 0.7 | 5.1 ± 0.7 | 5.0 ± 0.7 | 5.2 ± 0.7 | 0.032 |
| Free thyroxine (pmol/L) | 11.1 ± 1.7 | 11.7 ± 1.8 | 11.4 ± 1.8 | 11.3 ± 1.7 | 0.020 |
MHT, masked hypertension; NT, normotension; SHT, sustained hypertension; WCH, white coat hypertension.
Figure 1.
A, Thyroid‐stimulating hormone level of outpatients stratified into 4 BP categories; B, free triiodothyronine level of outpatients stratified into 4 BP categories; C, free thyroxine level of outpatients stratified into 4 BP categories; D, thyroid‐stimulating hormone level of outpatients stratified into clinic hypertension group (WCH + SHT), clinic normotension group (NT + MHT), ambulatory hypertension group (MHT + SHT), and ambulatory normotension group (NT + WCH). FT3, free triiodothyronine; FT4, free thyroxine; MHT, masked hypertension; NT, normotension; SHT, sustained hypertension; TSH, thyroid‐stimulating hormone; WCH, white coat hypertension
Table 4.
Logistic regression analysis after adjusting for confounding factors such as age, sex, BMI, smoking history, drinking history, family history of hypertension, diabetes, hyperlipidaemia, and hyperuricaemia
| Groups | Parameters | Logistic regression analysis | Hosmer‐Lemeshow test | |
|---|---|---|---|---|
| OR (95% CI) | P value | P value | ||
| Thyroid‐stimulating hormone | ||||
| SHT vs NT | Thyroid‐stimulating hormone | 1.352 (1.151‐1.588) | <0.001 | 0.616 |
| Sex | 0.669 (0.475‐0.944) | 0.022 | ||
| Age | 1.022 (1.007‐1.036) | 0.003 | ||
| BMI | 1.171 (1.112‐1.232) | <0.001 | ||
| Family history of hypertension | 0.518 (0.339‐0.793) | 0.002 | ||
| SHT vs WCH | Thyroid‐stimulating hormone | – | 0.078 | 0.494 |
| WCH + SHT vs NT + MHT | Thyroid‐stimulating hormone | – | 0.071 | 0.690 |
| MHT + SHT vs NT + WCH | Thyroid‐stimulating hormone | 1.226 (1.096‐1.371) | <0.001 | 0.406 |
| BMI | 1.093 (1.052‐1.136) | <0.001 | ||
| Diabetes | 0.597 (0.417‐0.857) | 0.005 | ||
| Free triiodothyronine | ||||
| SHT vs NT | Free triiodothyronine | 1.357 (1.050‐1.754) | 0.020 | 0.105 |
| Age | 1.028 (1.012‐1.043) | <0.001 | ||
| BMI | 1.159 (1.101‐1.220) | <0.001 | ||
| Family history of hypertension | 0.456 (0.299‐0.695) | <0.001 | ||
| Hyperuricaemia | 1.449 (1.026‐2.048) | 0.035 | ||
| SHT vs MHT | Free triiodothyronine | 1.329 (1.020‐1.732) | 0.035 | 0.546 |
| BMI | 1.093 (1.036‐1.154) | 0.001 | ||
| Family history of hypertension | 0.564 (0.358‐0.889) | 0.014 | ||
| Free thyroxine | ||||
| WCH vs NT | Free thyroxine | 1.215 (1.082‐1.364) | 0.001 | 0.505 |
| Age | 1.025 (1.007‐1.043) | 0.007 | ||
| BMI | 1.121 (1.051‐1.197) | 0.001 | ||
| Family history of hypertension | 0.496 (0.296‐0.834) | 0.008 | ||
CI, confidence interval; MHT, masked hypertension; NT, normotension; OR, odd ratio; SHT, sustained hypertension; WCH, white coat hypertension.
The TSH concentration significantly increased in the ambulatory hypertension group compared with the ambulatory normotension group (MHT + SHT vs NT + WCH, 2.3 ± 1.2 μIU/mL vs 2.1 ± 1.0 μIU/mL, P = 0.001; Figure 1D). The concentration of TSH was also higher in the clinic hypertension group than in the clinic normotension group (WCH + SHT VS NT + MHT, 2.3 ± 1.2 μIU/mL vs 2.1 ± 1.1 μIU/mL, P = 0.046; Figure 1D). After adjusting for confounding factors such as age, sex, BMI, family history of hypertension, smoking history, drinking history, diabetes, hyperlipidaemia, and hyperuricaemia, the logistic regression analysis showed that the former difference still existed, but with no statistically significant difference in the concentration of TSH between the WCH + SHT and NT + MHT groups (P < 0.001, P = 0.071, Table 4). The linear regression analysis showed that the TSH level linearly correlated with the 24‐hours MAP of the total sample (P = 0.005, B = 0.656, 95% CI: 0.203 to 1.110), but no correlation was found with the mean clinic arterial pressure (P = 0.156, B = 0.536 95% CI: −0.205 to 1.276; Figure 2). However, after excluding the WCH and MHT groups, the TSH concentration in the SHT + NT group linearly correlated with the mean clinic arterial blood pressure (P = 0.001, B = 1.744, 95% CI: 0.672‐2.816, Figure 2).
Figure 2.
Linear relationship between thyroid‐stimulating hormone and clinic mean arterial pressure. MAP, mean arterial pressure; MHT, masked hypertension; NT, normotension; SHT, sustained hypertension; TSH, thyroid‐stimulating hormone; WCH, white coat hypertension. *P < 0.05
3.4. Thyroid function, heart rate variability, and blood pressure levels
The multiple linear regression analysis showed a linear negative correlation between RMSSD and PNN50, which were representative for the enhancement of cardiac vagal function, and clinic MAP and 24‐hours MAP (P < 0.05, Table 5). FT3 linearly negatively correlated with RMSSD and PNN50 and linearly positively correlated with clinic MAP and 24‐hours MAP (P < 0.05, Table 5). This relationship corresponded to the changes in heart rate variability, FT3, and blood pressure levels in the SHT and MHT groups, as well as in the SHT and NT groups. The aforementioned findings suggested that elevated FT4 was an independent risk factor for WCH and that the WCH group also had a change in heart rate variability relative to the NT group. Meanwhile, the linear regression analysis showed a linear negative correlation between FT4 and indicator of heart rate variability SDANN in the WCH + NT group (P = 0.001, B = −3.990, 95% CI: −6.281 to −1.699). A linear positive correlation was found between FT4 and clinic systolic blood pressure in the WCH + NT group, but not with clinic diastolic blood pressure (P = 0.015, B = 0.010, 95% CI: 0.002 to 0.018; P = 0.917, B = 0.917, 95% CI: −0.015 to 0.013).
Table 5.
Multiple linear regression analyses of the relationship among heart rate variability, blood pressure levels, and free triiodothyronine
| Dependent | Independent | Unadjusted model | Adjusted model | ||||
|---|---|---|---|---|---|---|---|
| B | 95% CI | P value | B | 95% CI | P value | ||
| MAP | RMSSD | −0.027 | −0.039 to −0.015 | <0.001 | −0.024 | −0.035 to −0.012 | <0.001 |
| MAP | PNN50 | −0.085 | −0.128 to −0.043 | <0.001 | −0.074 | −0.115 to −0.032 | 0.001 |
| 24‐h MAP | RMSSD | −0.016 | −0.023 to −0.009 | <0.001 | −0.015 | −0.022 to −0.008 | <0.001 |
| 24‐h MAP | PNN50 | −0.047 | −0.073 to −0.020 | 0.001 | −0.041 | −0.066 to −0.015 | 0.002 |
| RMSSD | FT3 | −14.699 | −20.627 to −8.770 | <0.001 | −8.506 | −14.665 to −2.348 | 0.007 |
| PNN50 | FT3 | −3.120 | −4.810 to −1.430 | <0.001 | −1.852 | −3.608 to −0.097 | 0.039 |
| MAP | FT3 | 2.334 | 1.148 to 3.520 | <0.001 | 1.751 | 0.587 to 2.915 | 0.003 |
| 24‐h MAP | FT3 | 1.260 | 0.531 to 1.990 | 0.001 | 0.924 | 0.211 to 1.637 | 0.011 |
The age, sex, BMI, smoking history, drinking history, family history of hypertension, diabetes, hyperlipidaemia, and hyperuricaemia were adjusted in the adjusted model at multivariate analysis.
B, unstandardized coefficients; CI, confidence interval; FT3, free triiodothyronine; MAP, mean arterial pressure; PNN50, percentage of adjacent NN intervals differing by more than 50 ms; RMSSD, root mean square of successive differences between adjacent RR intervals.
4. DISCUSSION
The hypothalamic‐pituitary‐thyroid axis was an important component of the endocrine regulation system, which played a vital role in the neurohumoral regulation and was closely related to the blood pressure state of the body.33, 34 This study divided the hypertension subtypes into SHT, MHT, and WCH and further studied the relationship between the thyroid function and blood pressure status. It found that TSH, FT3, and FT4 levels not only were closely related to the occurrence of hypertension subtypes such as WCH but also could be used as points for differential diagnosis between different hypertension subtypes.
TSH was a sensitive indicator reflecting the changes in thyroid function.35 Some studies reported that the elevation of TSH concentrations could cause changes in vascular endothelial function and increased renal vascular resistance, which were closely related to the occurrence of hypertension.36 However, the results of these studies were always controversial.9 This study did not consider the traditional classification of hypertension, and, for the first time, confirmed the increase in TSH concentration in the SHT group compared with the NT group, but with no significant change in the WCH group compared with the NT group. The regression analysis also found that the TSH concentration was higher in the group with elevated ambulatory blood pressure than in the group with normal ambulatory blood pressure, but with no statistically significant difference between the clinic hypertension and normotension groups. The linear regression analysis also found that the TSH level linearly correlated with mean clinic arterial pressure only after excluding the WCH and MHT groups. The aforementioned results suggested that the previous controversy between the TSH level and blood pressure status might be caused by WCH and MHT. The TSH level could correctly reflect the state of ambulatory blood pressure, but the white coat effect and the masked effect caused it to not correctly reflect the clinic blood pressure.
FT3 and FT4 were the direct‐acting components of thyroid function, which were closely related to cardiac autonomic function and blood pressure status.37, 38, 39 Colomba et al found that thyroid function was closely related to heart rate variability that represented the cardiac autonomic function, which was consistent with the results of this study.40 FT3 was the most effective and active component of thyroid function.41 This study found statistically significant differences in FT3 and heart rate variability between the SHT group and MHT and NT groups. FT3 linearly negatively correlated with heart rate variability (RMSSD and PNN50) that represented the enhancement of vagus nerve function, and linearly positively correlated with clinic and 24‐hours MAP. It was presumed that FT3 might regulate the blood pressure of the body by changing the autonomic function of the heart, thus causing SHT. Moreover, the difference between MHT and SHT might be related to the masked effect of blood pressure caused by lower FT3 and a corresponding increase in vagus nerve function. The mechanism of action of WCH is still unclear.42 Recent studies reported that it might be related to the changes in autonomic nerve functions, emotional state, activation of renin‐angiotensin system, and other factors.43, 44 The most probable mechanism was changes in cardiac autonomic nerve functions resulting in WCH.21 The difference in heart rate variability between the WCH and NT groups in this study was consistent with that in previous studies. Also, a difference in FT4 was observed between the WCH and NT groups. Further, FT4 linearly negatively correlated with SDANN, an indicator of the weakening of cardiac sympathetic function, suggesting that FT4 might participate in the occurrence of WCH by regulating the cardiac autonomic nerve functions.
The association between thyroid function and blood pressure is very complex. Our result showed that the TSH concentration was negatively related to the FT4 level in the euthyroid individuals, but the effects of TSH and FT3/FT4 on blood pressure might be complementary. In a 9‐year longitudinal study, Abdi et al found that both TSH concentration and FT4 level were positively associated with elevated clinic blood pressure.12 Chen et al also found that serum TSH and FT3 were positively correlated with clinic systolic and diastolic blood pressure in school‐aged subjects without overt thyroid disease.14 In our study, the euthyroid adults were divided into four groups, and each group had unique thyroid function characteristics. The concentration of TSH was significantly higher in the SHT group, while the FT4 level was significantly higher in the WCH group, but not in the SHT group. White coat hypertension is often accompanied by elevated systolic blood pressure and changes in cardiac autonomic nervous function. Our results showed a linear positive correlation between FT4 and clinic systolic blood pressure in the WCH + NT group, but not in the total individuals. A linear negative correlation was also found between FT4 and indicator of cardiac autonomic nervous function SDANN in the WCH + NT group. These were consistent with the clinical characteristics of white coat hypertension. We speculated that FT4 might be an important risk factor for the white coat effect. The linear regression analysis showed that the TSH level linearly correlated with the 24‐hours MAP of the total sample, but no correlation was found with the clinic arterial pressure and heart rate variability. High TSH concentrations leading to elevated blood pressure should be caused by a number of factors, but not changes in cardiac autonomic nervous function. Positive association between TSH and pulse wave velocity was found in a study consisted of 1598 Finnish white young adults.45 In another cross‐sectional study, high normal TSH was found to be associated with the metabolic syndrome.46 These might be the important risk factors for TSH‐induced persistent elevation of blood pressure.
This study combined the clinic and ambulatory blood pressures, for the first time, to explore the relationship between hypertension subtypes such as WCH and thyroid function, thus helping in further identification and intervention of WCH, MHT, and SHT. However, it had some limitations. The study sample only included participants with normal thyroid function. As a cross‐sectional observational study, it could only use statistical methods such as linear regression analysis to speculate that the relationship between thyroid function and hypertension subtypes such as WCH might be related to the changes in cardiac autonomic nerve functions. In addition, we did not adequately consider the confounding factors. The information on sodium intake was not collected in this study, but it is well known that sodium intake strongly affects blood pressure. Sodium intake should be more informative to compare to the strength of thyroid function effect on the types of hypertension. However, further studies need to address the following questions: What is the relationship between TSH, FT3, and FT4 levels and hypertension subtypes such as WCH and MHT in the individuals with abnormal thyroid function; whether the white coat effect and the masked effect are affected by thyroid medication; and what is the influence of drugs affecting the thyroid function on the ambulatory and clinic blood pressures.
CONFLICT OF INTEREST
The authors declare that they have no actual or potential conflicts of interest.
AUTHOR CONTRIBUTIONS
Peng Cai designed the study. Yan Wang involved in formal analysis. Xukai Wang acquired funding. Peng Cai and Yan Peng analyzed statistically. Peng Cai, Li Li, YuXi Chen, and Wei Chu acquired the data. Peng Cai and Xukai Wang writing, reviewing, and editing the manuscript.
ACKNOWLEDGMENTS
The work was supported by the National Natural Science Foundation of China (No. 81370367).
Cai P, Peng Y, Chen Y, et al. Association of thyroid function with white coat hypertension and sustained hypertension. J Clin Hypertens. 2019;21:674–683. 10.1111/jch.13536
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