Abstract
The purpose of this study was to assess the association of blood pressure (BP) measurements with the risk of cardiovascular disease (CVD) and examine whether central systolic BP (CSBP) predicts CVD better than brachial BP measurements (SBP and pulse pressure [PP]). Based on a cross‐sectional study conducted in 2009‐2010 with follow‐up in 2016‐2017 among 35‐ to 64‐year‐old subjects in China, we evaluated the performance of non‐invasively predicted CSBP over brachial BP measurements on the first CVD events. Each BP measurement, individually and jointly with another BP measurement, was entered into the multivariate Cox proportional‐hazards models, to examine the predictability of central and brachial BP measurements. Mean age of participants (n = 8710) was 50.1 years at baseline. After a median follow‐up of 6.36 years, 187 CVD events occurred. CSBP was a stronger predictor for CVD than brachial BP measurements (CSBP, 1‐standard deviation increment HR = 1.49, 95%CI: 1.31‐1.70). With CSBP and SBP entering into models jointly, the HR for CSBP and SBP was 1.28 (1.04‐1.58) and 1.22 (0.98‐1.50), respectively. With CSBP and PP entering into models jointly, the HR for CSBP and PP was 1.51 (1.28‐1.78) and 0.98 (0.83‐1.15), respectively. For subgroup analysis, the association of CSBP with CVD was stronger than brachial BP measurements in women, those with hypertension and obesity. In the middle‐aged Chinese population, noninvasively estimated CSBP may offer advantages over brachial BP measurements to predict CVD events, especially for participants with higher risk. These findings suggest prospective assessment of CSBP as a prevention and treatment target in further trials.
Keywords: cardiovascular disease, central systolic blood pressure, Chinese, cohort study
1. INTRODUCTION
Hypertension is a leading risk factor and predictor for cardiovascular disease (CVD).1, 2, 3, 4 For primary prevention of hypertension, it is important to identify high‐risk population, especially in less developed countries.5 Currently, the measurement of brachial blood pressure (BP) is still the standard for diagnosis and management of hypertension and has been a key element in predicting CVD and target organ damage.6, 7, 8 Available evidence indicates that systolic BP (SBP) is a superior predictor of coronary heart disease9 and congestive heart disease10 than diastolic BP (DBP). Although elevated pulse pressure (PP) is increasingly being regarded as a risk factor of CVD,11 its importance relative to SBP needs to be clarified.12, 13
Blood pressure in the central arties, such as the ascending aorta common carotid arteries,12 is highlighted as the “true pressure” directly related to loads on target organs such as heart and brain.14 Meanwhile, commonly available technology measuring BP in peripheral arteries, such as the brachial and radial arteries, reports higher BP values than in central arteries.15 In the last decades, advances in the technology have allowed central BP measured noninvasively,16, 17, 18 and an increasing body of evidence has emerged that central aortic pressure had greater prognostic importance than brachial BP in hypertensive patients,19, 20 in non‐hypertensive population,5 or in general population in the United States.21 However, whether central SBP can improve the ability to predict CVD than brachial BP has been poorly studied in the Chinese population.
The aim of this study was to assess whether central SBP is a better marker of risk for CVD than routine brachial BP—namely, brachial SBP, and PP, using the data from the CVD‐China study, a large community‐based cohort survey.
2. METHODS
2.1. Subjects
The CVD‐China study enrolled men and women aged 35‐64 years in 2009‐2010. The design and baseline characteristics of study participants have described previously.22 Briefly, a random cluster sampling method was used to obtain 11 623 individuals during the baseline survey. For the present study, 9 out 12 study sites (n = 8965) completed the follow‐ups until 2016‐2017.
In this study, we excluded participants who were with history of CVD (n = 172) and those missing data for brachial SBP, DBP, or central SBP (n = 12) and those without measurements of height, weight, demographic characteristics (annual household income, urban/rural status, etc), or laboratory test in baseline (n = 71). In total, this resulted in a final analytic sample of 8710 participants (3902 men and 4808 women). The schematic flow of this study is displayed in Figure 1. The study adhered to the Declaration of Helsinki. The Ethics Review Board of Fuwai Hospital approved this study (IRB approval number: 2014534). Written informed consent was obtained from all participants prior to data collection.
Figure 1.
Schematic flow of this prospective cohort study
2.2. Measurements
Anthropometric measurements and vital statistics were collected by trained staff according to a standardized protocol. Height was measured to the nearest 0.5 cm using a standard right‐angle device without shoes, and weight was measured to nearest 0.1 kg by using Omron HBF‐306C Body Fat Analyzer in light clothing without shoes. Body mass index (BMI) was calculated as weight divided by the square of height (kg/m2). Low household income was defined as whose annual income was lower than the average income in the local. Current smoker was defined as participants who have consumed more than 20 packets of cigarettes (equivalent to 0.5 kg tobacco leaves) in their lifetime and currently smoke cigarettes. Alcohol consumption was defined as drinking at least one beverage per week.
Brachial BP was measured thrice on the right arm with participants in the seated position after at least 5 minutes of rest, using a calibrated mercury sphygmomanometer. Cuff sizes were appropriate to the participant's arm circumference. Participants were advised to refrain from coffee, tea, alcohol, cigarette, and exercise for at least 30 minutes before examination. The average of the three readings was used for these analyses. Brachial PP was defined as the difference between the brachial SBP and DBP. As previously described,23 the central SBP was measured using the BPro device with A‐Pulse CASP software (Health STATS), which can obtain an accurate measurement compared with invasively measured central SBP.24, 25
Venous blood samples were collected after dinner at least 8 hours and analyzed in the same core clinical laboratory (Beijing CIC Clinical Laboratory). Plasma fasting blood glucose (FBG) was measured by the glucose oxidase‐peroxidase method; total cholesterol (TC) was measured by the method of glucose oxidase‐polymerization. All the blood specimens were tested using a Hitachi biochemical instrument (Hitachi). Diabetes mellitus was defined as participants with the previous diagnosis of diabetes and current usage of antidiabetic medications (insulin or hypoglycemic agents), and or an FBG level of ≥7.0 mmol/L.
2.3. Cardiovascular outcome measurements
Follow‐up interviews were conducted via clinical visits, telephone, or delivery of medical records until the occurrence of CVD events, withdrawal from the study, or the database was locked for analysis (year of 2017). The primary outcome was CVD events, including coronary heart disease events26 (myocardial infarction [I21, I22]) and stroke events27 (subarachnoid hemorrhage [I60], intracerebral hemorrhage [I61], other nontraumatic intracranial hemorrhage [I62], cerebral infarction [I63] and stroke, not specified as hemorrhage or infarction [I64]). All the CVD events were adjudicated by the local and Fuwai Hospital endpoint assessment committee blindly using standardized definitions. Only the first event in an individual patient was counted in the final analysis.
2.4. Statistical analysis
Continuous variables were presented as means and standard deviations (SDs), and categorical variables were presented as frequencies and percentages. One‐way ANOVA and chi‐square tests were used to compare the baseline characteristics of study participants by quartiles of central SBP.
Cox proportional‐hazards model was used to compare the association of different BP measurements with CVD. Each BP measurement, individually and jointly with another BP variable respectively, was entered into the multivariate models in quartile (where the lowest quartile was used as the reference) or in 1 SD increment.12, 28 Models were adjusted for age, gender, urban/rural, annual household income, smoking status, alcohol consumption, diabetes mellitus, heart rate, waist circumference, TC, and use of antihypertensive medications. Before conducting the multivariate regression, a diagnosis for multicollinearity among covariates was assessed. We also performed subgroup analysis, for defined features including men/women, with hypertension or without hypertension, with or without obesity (BMI ≥ 28 kg/m2), to compare the predictive ability between central SBP and brachial BP measurements. All the analyses were carried out using SAS version 9.4 (SAS Institute Inc). A two‐sided P values of <.05 was considered statistically significant.
3. RESULTS
3.1. Descriptive characteristics
Baseline characteristics of the study population overall (n = 8710) and stratified by quartile of central SBP are presented in Table 1. The mean age of the study population was 50.1 years (SD = 8.0), and 44.8% were men. BMI increased from 23.0 kg/m2 in the lowest central SBP quartile (Q1) to 25.8 kg/m2 in the highest quartile (Q4). Higher central SBP quartiles are also associated with higher BP, higher glucose, and lipid values. History of DM was triple time in the highest central SBP quartile as the lowest.
Table 1.
Baseline characteristics of participants by central systolic pressure quartile
| Variable | Overall | Central systolic blood pressure, mm Hg | P for trend | |||
|---|---|---|---|---|---|---|
| Q1 (<108) | Q2 (108 to <119) | Q3 (119 to <131) | Q4 (≥131) | |||
| N (%) | 8710 | 2055 (23.6) | 2214 (25.4) | 2141 (24.6) | 2300 (26.4) | |
| Age (y) | 50.1 ± 8.0 | 47.0 ± 7.8 | 49.1 ± 7.9 | 50.6 ± 7.8 | 53.4 ± 7.2 | <.001 |
| Men (%) | 3902 (44.8) | 843 (41.0) | 1025 (46.3) | 1021 (47.7) | 1013 (44.0) | .022 |
| Urban (%) | 2392 (27.5) | 605 (29.4) | 614 (27.7) | 615 (28.7) | 558 (24.3) | <.001 |
| Low household income (%) | 4682 (53.8) | 991 (48.2) | 1193 (53.9) | 1175 (54.9) | 1323 (57.5) | <.001 |
| Current smoker (%) | 2713 (31.2) | 648 (31.5) | 733 (33.1) | 649 (30.3) | 683 (29.7) | .028 |
| Alcohol consumption (%) | 1577 (18.1) | 325 (15.8) | 396 (17.9) | 396 (18.5) | 460 (20.0) | <.001 |
| Body mass index, kg/m2 | 24.6 ± 3.7 | 23.0 ± 3.2 | 24.2 ± 3.3 | 25.3 ± 3.6 | 25.8 ± 3.9 | <.001 |
| Waist circumference, cm | 82.3 ± 10.7 | 77.3 ± 9.8 | 81.3 ± 10.2 | 84.1 ± 10.4 | 86.1 ± 10.5 | <.001 |
| Fasting blood glucose, mmol/L | 5.86 ± 1.68 | 5.53 ± 1.30 | 5.75 ± 1.49 | 5.94 ± 1.67 | 6.19 ± 2.05 | <.001 |
| Total cholesterol, mmol/L | 4.76 ± 0.95 | 4.60 ± 0.91 | 4.71 ± 0.91 | 4.81 ± 0.94 | 4.92 ± 1.02 | <.001 |
| Brachial SBP, mm Hg | 129.7 ± 20.4 | 111.3 ± 10.7 | 122.2 ± 11.2 | 131.8 ± 12.3 | 151.5 ± 19.2 | <.001 |
| Brachial DBP, mm Hg | 81.9 ± 11.4 | 73.2 ± 8.0 | 78.8 ± 8.4 | 83.5 ± 8.9 | 91.1 ± 11.5 | <.001 |
| Brachial pulse pressure, mm Hg | 47.9 ± 14.2 | 38.1 ± 8.6 | 43.4 ± 9.7 | 48.4 ± 10.7 | 60.5 ± 15.3 | <.001 |
| Heart rate, beat/min | 75.8 ± 11.1 | 75.8 ± 10.3 | 75.9 ± 10.8 | 76.0 ± 11.3 | 75.5 ± 11.7 | .370 |
| Any hypertension medications (%) | 1049 (12.0) | 40 (2.0) | 119 (5.4) | 245 (11.4) | 645 (28.0) | <.001 |
| Diabetes mellitus (%) | 906 (10.4) | 106 (5.2) | 198 (8.9) | 256 (12.0) | 346 (15.0) | <.001 |
Data are mean ± standard deviation, or number (percentage).
Abbreviations: DBP, diastolic blood pressure; SBP, systolic blood pressure.
3.2. Cardiovascular events in relation to central SBP, brachial SBP, and PP
Median length of follow‐up for the population was 6.36 years (inter‐quartile range 25%‐75% 5.93‐6.77 years), and 187 CVD events occurred (87 coronary artery disease events and 107 stroke events). Figure 2 illustrates the Kaplan‐Meier curves for CVD stratified by central SBP (panel A) and other brachial BP measurements (panel B, panel C). There was a progressive increase in CVD by central SBP and brachial BP measurements (Log‐rank test, P < .001). As seen in Table 2, after adjustments for traditional CVD risk factors, all the BP measurements were associated with higher risk of CVD, while central SBP had the highest adjusted HR for CVD (HR per SD increment, 1.49, 95% CI:1.31‐1.70, P < .001).
Figure 2.
Kaplan‐Meier Curve. A, Survival rate from cardiovascular disease (CVD) by quartile of central SBP; B, Survival rate from CVD by quartile of brachial SBP; C, Survival rate from CVD by quartile of brachial pulse pressure. Panel A for central SBP: 1st Quartile: <108 mm Hg; 2nd Quartile: 108 to <119 mm Hg; 3rd Quartile: 119 to <131 mm Hg; 4th Quartile: ≥131 mm Hg. Panel B for brachial SBP: 1st Quartile: <116 mm Hg; 2nd Quartile: 116 to <127 mm Hg; 3rd Quartile: 127 to <141 mm Hg; 4th Quartile: ≥141 mm Hg. Panel C for brachial pulse pressure: 1st Quartile: <39 mm Hg; 2nd Quartile: 39 to <46 mm Hg; 3rd Quartile: 46 to <56 mm Hg; 4th Quartile: ≥56 mm Hg
Table 2.
Risk of CVD according to baseline BP measures (HR (95% CI))
| BP quartile (mm Hg) | Model 1 | Model 2 | Model 3 | Model 4 |
|---|---|---|---|---|
| Central SBP | ||||
| Q1 (<108) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Q2 (108 to <119) | 2.14 (1.05‐4.34) | 1.55 (0.76‐3.17) | 1.37 (0.67‐2.81) | 1.53 (0.75‐3.12) |
| Q3 (119 to <131) | 4.25 (2.21‐8.19) | 2.55 (1.31‐4.95) | 2.03 (1.03‐4.02) | 2.46 (1.26‐4.82) |
| Q4 (≥131) | 8.69 (4.67‐16.18) | 3.87 (2.02‐7.42) | 2.42 (1.17‐5.03) | 3.57 (1.79‐7.12) |
| Per SD increment | 1.82 (1.63‐2.03) | 1.49 (1.31‐1.70) | 1.28 (1.04‐1.58) | 1.51 (1.28‐1.78) |
| Brachial SBP | ||||
| Q1 (<116) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | |
| Q2 (116 to <127) | 1.77 (0.90‐3.50) | 1.33 (0.67‐2.63) | 1.15 (0.58‐2.29) | |
| Q3 (127 to <141) | 3.59 (1.94‐6.64) | 2.01 (1.07‐3.76) | 1.54 (0.81‐2.94) | |
| Q4 (≥141) | 7.99 (4.49‐14.23) | 3.27 (1.77‐6.01) | 1.90 (0.95‐3.80) | |
| Per SD increment | 1.86 (1.67‐2.07) | 1.47 (1.29‐1.68) | 1.22 (0.98‐1.50) | |
| Brachial PP | ||||
| Q1 (<39) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | |
| Q2 (39 to <46) | 1.23 (0.68‐2.25) | 1.05 (0.57‐1.92) | 0.94 (0.51‐1.72) | |
| Q3 (46 to <56) | 2.45 (1.44‐4.16) | 1.64 (0.96‐2.81) | 1.28 (0.74‐2.22) | |
| Q4 (≥56) | 4.99 (3.05‐8.17) | 2.24 (1.33‐3.81) | 1.37 (0.77‐2.41) | |
| Per SD increment | 1.62 (1.45‐1.81) | 1.24 (1.09‐1.42) | 0.98 (0.83‐1.15) | |
Model 1: Crude HR. Model 2: Adjusted for age, gender, urban/rural, annual household income, smoking status, alcohol consumption, diabetes mellitus, heart rate, waist circumference, total cholesterol, and use of antihypertensive medications. Model 3: Model 2 and further adjusted for brachial SBP; Model 4: Model 2 and further adjusted for brachial PP.
Abbreviations: BP, blood pressure; CVD, cardiovascular disease; HR, hazard ratio; PP, pulse pressure; SBP, systolic blood pressure; SD, standard deviation.
3.3. Predictive ability on cardiovascular events
The multicollinearity diagnosis indicated that central SBP and brachial BP measurements had a value of variance inflation <3. To compare the strength of the associations, central SBP and another brachial BP parameter were entered in the multivariate Cox proportional‐hazards models jointly and HRs were calculated. While central SBP and brachial SBP were entered the model jointly, the HR (95% CI) for central SBP and brachial SBP was 1.28 (1.04‐1.58, P = .018) and 1.22 (0.98‐1.50, P = .064), respectively. With central SBP and brachial PP entered the model jointly, the HR (95% CI) for central SBP and brachial PP was 1.51 (1.28‐1.78, P < .001) and 0.98 (0.83‐1.15, P = .808), respectively (Table 2).
3.4. Subgroup analysis
Subgroups were defined and analyzed according to gender, status of hypertension, and obesity to examine whether central SBP predicts CVD better than brachial BP measurements (Table 3). Central SBP had the highest adjusted HR for CVD in women (HR of per increment of SD mm Hg, 95% CI: 1.56 [1.29‐1.89]), in the hypertensive (HR, 95% CI: 1.34 [1.15‐1.56]) and the obese (HR, 95% CI: 1.61 [1.26‐2.05]). Furthermore, when central SBP and another brachial BP variable entered into the multivariate Cox proportional‐hazards model jointly, we found that the association of central SBP with CVD was stronger than brachial BP measurements in women, the hypertensive, and the obese.
Table 3.
Risk of CVD according to baseline BP measures (subgroup analysis) (HR (95% CI))
| BP measures (per SD increment, mm Hg) | Model 1 | Model 2 | Model 3 | Model 4 |
|---|---|---|---|---|
| Men | ||||
| Central SBP | 1.77 (1.52‐2.07) | 1.42 (1.18‐1.70) | 1.13 (0.86‐1.50) | 1.47 (1.18‐1.83) |
| Brachial SBP | 1.86 (1.60‐2.16) | 1.49 (1.24‐1.78) | 1.35 (1.03‐1.78) | |
| Brachial PP | 1.54 (1.32‐1.80) | 1.17 (0.98‐1.41) | 0.94 (0.75‐1.17) | |
| Women | ||||
| Central SBP | 1.91 (1.63‐2.24) | 1.56 (1.29‐1.89) | 1.49 (1.09‐2.03) | 1.54 (1.20‐1.98) |
| Brachial SBP | 1.85 (1.58‐2.17) | 1.46 (1.20‐1.78) | 1.07 (0.78‐1.46) | |
| Brachial PP | 1.72 (1.48‐2.01) | 1.32 (1.10‐1.60) | 1.02 (0.80‐1.30) | |
| Without hypertension | ||||
| Central SBP | 1.31 (1.00‐1.72) | 0.99 (0.74‐1.34) | 0.97 (0.69‐1.38) | 1.00 (0.73‐1.38) |
| Brachial SBP | 1.47 (1.08‐2.02) | 1.03 (0.74‐1.43) | 1.05 (0.71‐1.54) | |
| Brachial PP | 1.28 (0.96‐1.71) | 0.97 (0.72‐1.32) | 0.97 (0.70‐1.34) | |
| With hypertension | ||||
| Central SBP | 1.40 (1.21‐1.62) | 1.34 (1.15‐1.56) | 1.31 (1.05‐1.63) | 1.40 (1.16‐1.68) |
| Brachial SBP | 1.33 (1.15‐1.54) | 1.25 (1.07‐1.45) | 1.04 (0.83‐1.29) | |
| Brachial PP | 1.25 (1.07‐1.46) | 1.13 (0.95‐1.33) | 0.93 (0.76‐1.13) | |
| Without obesity a | ||||
| Central SBP | 1.75 (1.54‐2.00) | 1.43 (1.22‐1.67) | 1.03 (0.81‐1.33) | 1.34 (1.10‐1.64) |
| Brachial SBP | 1.91 (1.68‐2.16) | 1.57 (1.35‐1.83) | 1.53 (1.20‐1.95) | |
| Brachial PP | 1.65 (1.45‐1.87) | 1.31 (1.13‐1.53) | 1.11 (0.91‐1.34) | |
| With obesity a | ||||
| Central SBP | 1.77 (1.43‐2.20) | 1.61 (1.26‐2.05) | 2.07 (1.42‐3.03) | 1.94 (1.41‐2.67) |
| Brachial SBP | 1.50 (1.20‐1.88) | 1.26 (0.97‐1.63) | 0.72 (0.49‐1.06) | |
| Brachial PP | 1.40 (1.12‐1.76) | 1.13 (0.88‐1.46) | 0.75 (0.54‐1.04) | |
Model 1: Crude HR. Model 2: Adjusted for age, gender, urban/rural, annual household income, smoking status, alcohol consumption, diabetes mellitus, heart rate, waist circumference, total cholesterol, and use of antihypertensive medications. Model 3: Model 2 and further adjusted for brachial SBP; Model 4: Model 2 and further adjusted for brachial PP.
Abbreviations: BP, blood pressure; CVD, cardiovascular disease; HR, hazards ratio; PP, pulse pressure; SBP, systolic blood pressure; SD, standard deviation.
With obesity and without obesity was divided by BMI ≥ 28 kg/m2 (China criteria).
4. DISCUSSION
In the study, we found that all the BP measurements were significantly associated with CVD events. Moreover, central SBP was a better predictor of CVD events than brachial BP measurements (brachial SBP and PP), especially for participants with higher risk, such as women, hypertension, and obesity.
As we know, brachial BP measurements are determined by arterial compliance and total peripheral resistance.29 The effect of brachial BP on outcomes, like CVD, has been firmly established,6, 30, 31 embodied in guidelines for CVD prevention.32, 33 However, the central BP was determined not only by cardiac output and peripheral vascular resistance, but also by the stiffness of conduit arteries as well as timing and magnitude of the reflected wave.34, 35 Since central SBP can be assessed noninvasively, it has been indicated in population‐based study from the United States and Italy21, 36 or China.12, 37 The Strong Heart Study,21 a population‐based longitudinal study, showed that central BP predicted cardiovascular events more strongly than BP measurements (HR = 1.15 per 10 mm Hg, P < .001 vs HR = 1.10 per 10 mm Hg, P = .008) after adjustment for age, gender, and other confounders. The study36 conducted by Pini et al among individuals living in Italy demonstrated that higher carotid SBP but not brachial pressures independently predicted cardiovascular mortality (HR = 1.37 per 10 mm Hg, P < .001). In addition, the survey12 conducted among Taiwanese participants (1272 normotensive and untreated hypertensive, aged 30‐79 years) found that only central SBP consistently independently predicted cardiovascular mortality (HR = 1.30 per 10 mm Hg); meantime, with two BP variables jointly entering the multivariable models, only central SBP was consistently the significant independent predictor of cardiovascular mortality. Our results were in line with that of previous studies, after adjusting risk factors, central SBP had the highest adjusted HR for CVD (HR per SD increment, 1.49, 95% CI:1.31‐1.70); after both entered the multivariate models jointly, only central SBP was significantly associated with CVD events.
Previous studies indicated that central BP may offer advantages over brachial BP measurements in CVD or in coronary artery disease in women, but not men.38, 39 Therefore, we wondered whether the central SBP still had a higher predictive ability for CVD than brachial BP measurements in different subgroups. We conducted subgroup analysis and then divided participants into men/women, with/without hypertension, and with/without obesity. Interestingly, we only found that central SBP is more strongly related to CVD events among women, participants with hypertension, and participants with obesity. The possible reasons, due to menopause, in women showed a greater age‐related increase in proximal aortic stiffness.40 In addition, previous studies indicated that among participants with hypertension and obesity had elevated central arterial stiffness and abnormal central hemodynamics which reflected impairment of arterial structure and function therefore increased the risk of CVD.41, 42, 43
To the best of our knowledge, this is the first community‐based study to compare central SBP with brachial BP measurements in relation to the CVD events in Chinese population. Moreover, we found that the central SBP predicted CVD events more strongly than brachial BP measurements among Chinese population. There are also some limitations in our study. On the one hand, central DBP is not available for our device, and central DBP and central PP were not available in our study. On the other hand, the duration of follow‐up was slightly shorter and hence the small number of CVD events. We had limited statistical power to examine the associations according to specific cardiovascular outcomes, such as coronary heart disease and stroke. With longer follow‐up, higher statistical power was expected to expand our findings in future years.
5. CONCLUSION
In conclusion, the data from the present study clearly demonstrated that central SBP and brachial BP measurements are significantly associated with CVD events. Furthermore, central SBP is more strongly related to CVD events in middle‐aged Chinese population, especially for high‐risk population. These findings suggest prospective measurement of noninvasively estimated central SBP as a prevention and treatment target in future trial.
CONFLICT OF INTEREST
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
AUTHOR CONTRIBUTIONS
Zengwu Wang, Zuo Chen, Linfeng Zhang, and Xin Wang involved in study design; Zengwu Wang, Zuo Chen, Linfeng Zhang, Xin Wang, Ying Dong, Congyi Zheng, Yuting Kang, and Linlin Jiang involved in data collection. Ying Dong and Linlin Jiang interpreted the analysis and wrote the manuscript. Zengwu Wang and Zugui Zhang conducted critical revision of the manuscript for important intellectual content. Ying Dong and Linlin Jiang contributed equally to this work. All authors gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy.
LIST OF INVESTIGATORS OF THE CHINA‐CVD STUDY
For a partial listing of colleagues see below (provinces sorted in alphabetical order):
Beijing: Huiqing Cao, Xiaoxia Wang and Tian Fang, Institute of Molecular Medicine, Pecking University, Beijing, China; Xiaoyan Han and Zhe Li, Chaoyang District Center for Disease Control and Prevention, Beijing, China.
Heilongjiang: Ye Tian, Lihang Dong, Fengyu Sun and Fucai Yuan, First Affiliated Hospital of Harbin Medical University, Heilongjiang, China.
Jiangsu: Xin Zhou, Yunyang Zhu, Yi He and Qingping Xi, Jintan Institute of Hygiene, Jiangsu, China.
Shaanxi: Ruihai Yang, Jun Yang, Yong Ren, Maiqi Dan, Yiyue Wang, Daming Yu and Ru Ju, Hanzhong Hospital, Shanxi, China.
Shanxi: Dongshuang Guo, Yuxian Hospital, Shanxi, China.
Sichuan: Dahua Tan, Zhiguo Zheng, Jingjing Zheng and Yang Xu, Deyang Institute of Hygiene, Sichuan, China.
Xinjiang: Dongsheng Wang and Tao Chen, Autonomous Region Yining Center for Disease Control and Prevention, Xinjiang Uygur Autonomous Region, China.
Yunnan: Meihui Su and Yongde Zhang, Yunnan Center for Disease Prevention and Control, Yunnan, China.
Zhejiang: Zhanhang Sun and Chen Dai, Zhoushan Cardiovascular Institute, Zhejiang, China.
ACKNOWLEDGMENTS
We thank all our colleagues involved in the survey (List of investigators of the China‐CVD study) and gratefully acknowledge Suning Li and Haizhou Yao for help in maintaining the data.
Dong Y, Jiang L, Wang X, et al. Central rather than brachial pressures are stronger predictors of cardiovascular outcomes: A longitudinal prospective study in a Chinese population. J Clin Hypertens. 2020;22:623–630. 10.1111/jch.13838
Ying Dong and Linlin Jiang contributed equally to this work and are joint first authors.
Funding information
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. The study was supported by National Natural Science Foundation of China (81373070) and Chinese National Specific Fund for Health‐scientific Research in Public Interest (200902001).
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