Temporal Relationship Between Elevated Blood Pressure and Arterial Stiffening Among Middle-Aged Black and White Adults

American Journal of Epidemiology The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. Vol. 183, No. 7 DOI: 10.1093/aje/kwv274 Advance Access publication: March 8, 2016 Original Contribution Temporal Relationship Between Elevated Blood Pressure and Arterial Stiffening Among Middle-Aged Black and White Adults The Bogalusa Heart Study Wei Chen*, Shengxu Li, Camilo Fernandez, Dianjianyi Sun, Chin-Chih Lai, Tao Zhang, Lydia Bazzano, Elaine M. Urbina, and Hong-Wen Deng * Correspondence to Dr. Wei Chen, Tulane University Health Sciences Center, 1440 Canal Street, Room 1504, New Orleans, LA 70112 (e-mail: wchen1@tulane.edu). Initially submitted March 2, 2015; accepted for publication July 23, 2015. This study assessed the temporal relationship between elevated blood pressure (BP) and arterial stiffness in a biracial (black-white) cohort of middle-aged adults aged 32 51 years from the semirural community of Bogalusa, Louisiana. Measurements of aortic-femoral pulse wave velocity (afpwv; n = 446) and large- and small-arterial compliance (n = 381) were obtained at 2 time points between 2000 and 2010, with an average follow-up period of 7 years. A cross-lagged path analysis model was used to examine the temporal relationship of elevated BP to arterial stiffness and elasticity. The cross-lagged path coefficients did not differ significantly between blacks and whites. The path coefficient (ρ 2 ) from baseline BP to follow-up afpwv was significantly greater than the path coefficient (ρ 1 ) from baseline afpwv to follow-up BP (ρ 2 = 0.20 vs. ρ 1 = 0.07 (P = 0.048) for systolic BP; ρ 2 = 0.19 vs. ρ 1 = 0.05 (P = 0.034) for diastolic BP). The results for this 1-directional path from baseline BP to follow-up afpwv were confirmed, although marginally significant, by using large- and small-artery elasticity measurements. These findings provide strong evidence that elevated BP precedes large-artery stiffening in middle-aged adults. Unlike the case in older adults, the large-arterial wall is not stiff enough in youth to alter BP levels during young adulthood. arterial elasticity; arterial stiffness; blood pressure; longitudinal analysis; temporal relationships Abbreviations: afpwv, aortic-femoral pulse wave velocity; BMI, body mass index; BP, blood pressure; DBP, diastolic blood pressure; HDI, Hypertension Diagnostics, Inc.; MESA, Multi-Ethnic Study of Atherosclerosis; SBP, systolic blood pressure; SVR, systemic vascular resistance. Editor s note:an invited commentary on this article appears on page 609. Hypertension and vascular stiffness contribute to morbidity and mortality from coronary heart disease, stroke, heart failure, and renal disease (1, 2). Blood pressure (BP) levels and arterial elasticity measures are hypertension-related traits and are influenced by aging processes and cardiovascular risk factors (3 6). The strong association between arterial stiffening and elevated BP levels suggests that this functional relationship is probably bidirectional, based on vascular biology and hemodynamics. The concept that arterial stiffness increases systolic BP, leading to an increase in pulse pressure due to alterations of the buffering function of the conduit arteries in older individuals, has been well established. However, existing data are inconsistent regarding whether elevated BP accelerates arterial stiffening during childhood and early adulthood due to increased wear and tear on the artery walls, subsequently leading to an increase in arterial stiffness (2, 7, 8). In particular, it is inadequately understood whether the answer to this chicken-and-egg question differs by age period during the development of hypertension. The Bogalusa Heart Study, a biracial (black-white), community-based long-term investigation of the early natural history of cardiovascular disease beginning in childhood 599

600 Chen et al. (9), provides a longitudinal database with both BP and arterial vascular alteration measurements. Utilizing data from this longitudinal cohort study, we examined the temporal relationship between elevated BP levels and vascular stiffening during young adulthood. METHODS Study cohort In the community of Bogalusa, Louisiana, 584 adult subjects were evaluated twice for aortic-femoral pulse wave velocity (afpwv), arterial elasticity measures, and cardiovascular risk factors at both baseline and follow-up examinations conducted during 2000 2002 and 2008 2010, respectively. After exclusion of 138 hypertensive persons who were receiving treatment at either baseline or follow-up, 446 subjects (342 whites and 104 blacks; 41.9% male; mean age = 43.3 years; age range 31.5 50.9 years at follow-up) were included in this analysis, with a follow-up period of 6.8 years, on average (range, 6.1 8.7 years). Among these 446 study subjects, there were still 78 hypertensive persons included in the analysis who were not receiving antihypertensive treatment. In addition, 381 subjects (277 whites and 104 blacks; 40.4% male; mean age = 44.5 years; age range 33.3 51.3 years at follow-up) had baseline and follow-up measurements of large- and small-arterial compliance available, with a follow-up period of 7.0 years, on average (range, 6.0 8.9 years). This sample (n = 381) was used to confirm the results for the BP-afPWV temporal relationship. In these 2 cohorts, a subset of 286 subjects had both afpwv and arterial compliance measurements available. All subjects in this study gave informed consent for each examination. Study protocols were approved by the Institutional Review Board of the Tulane University Health Sciences Center (New Orleans, Louisiana). BMI and BP measurements Replicate measurements of height and weight were obtained, and the mean values were used for analysis. Body mass index (BMI; weight in kilograms divided by the square of height in meters) was used as a measure of overall adiposity. BP levels were measured by 2 trained observers (3 replicates each) between 8:00 AM and 10:00 AM on subjects right arms while they rested in a relaxed, sitting position. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were recorded using a mercury sphygmomanometer. The fifth Korotkoff phase was used for DBP. The mean values of the 6 readings were used for analysis. Hypertension was defined as SBP 140 mm Hg or DBP 90 mm Hg or use of antihypertensive medication at the time of examination. Aortic-femoral pulse wave velocity We measured afpwv using a Toshiba digital ultrasound instrument (Xario SSA-660A; Toshiba America Medical Systems, Tustin, California). A nondirectional transcutaneous Doppler flow probe (Toshiba PSK25AT, 2.5 MHz; Toshiba America Medical Systems) was positioned at the suprasternal notch, and another probe (Toshiba PCK703AT, 7.5 MHz; Toshiba America Medical Systems) was positioned at the left femoral artery with the subject lying in a supine position. A computer system displayed and recorded output from the electrocardiogram and the 2 Doppler probes. The arterial flow waves from the 2 arterial sites were recorded, and the output was captured and stored in the computer system for subsequent scoring. After collection of the waveform data, the distance between the aorta and femoral arteries was measured with a caliper instrument to reduce the influence of body contours on the distance measured. The software averages the selected waveforms and determines the time from the R wave of the electrocardiogram to the foot of each waveform. The difference in timing between the 2 waves represents the time component of the velocity equation. We then calculated afpwv by dividing the distance traveled by the time differential between the 2 waveforms (10). In 46 re-screenees, afpwv was remeasured for reproducibility analysis. The correlation between the 2 measurements was 0.91 on the same day and 0.68 on different days. The day-to-day variations were influenced by both measurement errors and physiological fluctuations. Pulsatile arterial function Radial arterial pulse pressure waveforms were recorded by an acoustic transducer using the HD/PulseWave CR-2000 Research Cardiovascular Profiling System (Hypertension Diagnostics, Inc. (HDI), Eagan, Minnesota). A wrist stabilizer was used to gently immobilize the right wrist and stabilize the radial artery during measurements. For each subject, pressure waveforms were recorded for 30 seconds in the supine position, digitized at 200 samples per second, and stored in a computer. A modified windkessel ( air chamber ) model of the circulation was used to match the diastolic pressure decay of the waveforms and to quantify changes in arterial waveform morphology in terms of large-artery (capacitive) compliance (C 1, representative of the aorta and major branches), smallartery (oscillatory) compliance (C 2, representative of the distal part of the circulation, including small arteries and arterioles), and systemic vascular resistance (SVR; mean arterial pressure divided by cardiac output) (11). Four measurements were taken for each subject, and the mean values were used in the analyses. The intraclass correlation of the 4 measurements was 0.71 for C 1,0.85forC 2, and 0.93 for SVR. Considering that mean arterial pressure is included as a function of BP in the calculation of C 1 and C 2 by the HDI device, C 1 SVR (C 1 R) and C 2 SVR (C 2 R) were used in the current analysis to separate the BP component from the waveform information. C 1 R and C 2 R are measures closely related to largeand small-artery elasticity, respectively. Unlike the afpwv, for which a higher value is worse, higher values of C 1 R and C 2 R represent better vascular function. Statistical methods Analyses of covariance were performed using generalized linear models to test differences in continuous variables between blacks and whites and to calculate covariate-adjusted least-squares mean yearly rates of change in BP, afpwv, C 1 R, and C 2 R during the follow-up period.

Blood Pressure and Arterial Stiffness 601 The longitudinal changes in BP, afpwv, C 1 R,andC 2 R measured at 2 time points can be modeled using a crosslagged panel design. Cross-lagged panel analysis is a form of path analysis that simultaneously examines reciprocal, longitudinal relationships among a set of intercorrelated variables (12 15). A simplified, conceptual version of the model used in the current analysis is presented in the figures and tables. The path with ρ 1 describes the effect of baseline arterial function measures (afpwv, C 1 R, and C 2 R) on subsequent BP, and the path with ρ 2 describes the effect of baseline BP on subsequent arterial function measures. Prior to cross-lagged path analysis, the baseline and follow-up values of BP, afpwv, C 1 R,andC 2 R were adjusted for age, sex, BMI, heart rate, smoking, and diabetes in regression residual analyses and then standardized with z-transformation (mean = 0; standard deviation, 1) by race/ethnicity. Pearson correlation coefficients for the z-transformed quantitative variables of BP, afpwv, C 1 R, and C 2 R at baseline and follow-up were calculated, adjusted for duration of follow-up (years). The crosslagged path coefficients (ρ 1 and ρ 2 ) in the path diagrams were estimated simultaneously based on the correlation matrix using the maximum likelihood method with the software program LISREL, version 8.52 (15, 16). The validity of model fitting was evaluated by means of a goodness-of-fit χ 2 test and the comparative fitness index. The temporal relationships of SBP and DBP with afpwv, C 1 R, and C 2 R were examined in separate models. The difference between ρ 1 and ρ 2 derived from the standardized variables (z scores) was tested using Fisher s z test as described in a previous article (17). Although the significance of an individual ρ 1 or ρ 2 Table 1. Characteristics of Study Participants at Baseline and Follow-up, by Race/Ethnicity, Bogalusa Heart Study, 2000 2010 Mean (SD) % Mean (SD) % Mean (SD) % Characteristic a Whites (n = 342) Blacks (n = 104) P Value b Total (n = 446) Baseline Age, years 36.8 (4.2) 35.6 (4.4) 0.109 36.5 (4.3) BMI c 27.7 (5.8) 28.7 (6.9) 0.170 27.9 (6.1) HR, beats/minute 68.0 (8.4) 69.5 (9.6) 0.150 68.3 (8.7) Smoking 24.6 31.7 0.146 26.2 Diabetes 3.7 6.3 0.042 4.5 SBP, mm Hg 111.5 (10.2) 116.9 (12.6) <0.001 112.7 (11.0) DBP, mm Hg 75.8 (7.7) 78.5 (9.1) <0.001 76.5 (8.2) afpwv, m/second 5.1 (0.8) 5.3 (1.0) 0.008 5.1 (0.8) C 1, d ml/mm Hg 10 e 15.6 (4.2) 14.4 (4.3) 0.012 15.3 (4.3) C 2, d ml/mm Hg 100 e 6.7 (2.6) 5.5 (2.5) <0.001 6.3 (2.6) SVR, dynessecondcm 5e 1,297 (235) 1,403 (284) <0.001 1,326 (253) Follow-up Age, years 43.6 (4.4) 42.4 (4.5) 0.024 43.3 (4.4) BMI 28.9 (6.1) 30.1 (7.4) 0.108 29.2 (6.4) HR, beats/minute 69.7 (8.9) 71.4 (9.6) 0.126 70.1 (9.1) Smoking 24.9 31.7 0.164 26.5 Diabetes 7.2 12.5 0.026 8.4 SBP, mm Hg 113.5 (11.7) 120.5 (15.2) <0.001 115.2 (13.0) DBP, mm Hg 79.3 (7.9) 82.9 (11.0) <0.001 80.1 (8.9) afpwv, m/second 6.9 (2.1) 7.0 (1.9) 0.328 6.9 (2.0) C 1, ml/mm Hg 10 e 15.2 (4.4) 13.2 (4.4) <0.001 14.7 (4.5) C 2, ml/mm Hg 100 e 6.2 (2.8) 4.8 (2.1) <0.001 5.8 (2.7) SVR, dynessecondcm 5e 1,358 (249) 1,530 (339) <0.001 1,405 (287) Abbreviations: afpwv, aortic-femoral pulse wave velocity; BMI, body mass index; DBP, diastolic blood pressure; HR, heart rate; SBP, systolic blood pressure; SVR, systemic vascular resistance. a Unless otherwise noted, the total number of subjects was 446 (342 whites and 104 blacks), with 148 males and 194 females among whites and 39 males and 65 females among blacks. b P values for racial/ethnic differences in continuous variables were adjusted for sex and age (except age itself). c Weight (kg)/height (m) 2. d C 1, large-artery (capacitive) compliance; C 2, small-artery (oscillatory) compliance. e The total number of subjects was 381 (277 whites and 104 blacks), with 116 males and 161 females among whites and 38 males and 66 females among blacks.

602 Chen et al. value suggests a directional relationship, a significant difference between ρ 1 and ρ 2 provides stronger evidence for a temporal relationship between BP and arterial function measures. RESULTS Table 1 shows mean levels of study variables at baseline and follow-up, by race/ethnicity. The mean levels of continuous variables were compared between racial/ethnic groups, adjusting for sex and age (except age itself). BMI, heart rate, and prevalence of smoking did not differ significantly between racial/ethnic groups; however, blacks had a significantly higher prevalence of type 2 diabetes than whites. Baseline and follow-up values of SBP, DBP (blacks > whites), C 1, C 2 (blacks < whites), and SVR (blacks > whites) showed significant racial differences; afpwv differed significantly by race/ethnicity (blacks > whites) at baseline only. Analyses of the temporal relationship of SBP and DBP with afpwv, C 1 R, and C 2 R were performed in separate models by race/ethnicity, with adjustment for age, sex, BMI, heart rate, smoking, diabetes, and duration of follow-up. Crosslaggedpathcoefficients from the 6 models did not differ significantly between blacks and whites, as presented in Appendix Table 1. Cross-lagged path coefficients for the total sample are given in Table 2. After adjustment for age, sex, race/ethnicity, BMI, heart rate, smoking, diabetes, and duration of follow-up, the path coefficients (ρ 2 ) from baseline to follow-up afpwv were significantly greater than the path coefficients Table 2. Cross-Lagged Path Coefficients for the Association of Blood Pressure With Aortic-Femoral Pulse Wave Velocity (n = 446) and Artery Elasticity (n = 381) in the Total Sample, With Adjustment for Covariates, a Bogalusa Heart Study, 2000 2010 Model ρ 1 b Path Coefficient ρ 2 c Model Goodness of Fit P Value d P Value e CFI SBP-afPWV 0.07 0.20 f 0.048 <0.001 0.94 DBP-afPWV 0.05 0.19 f 0.034 <0.001 0.92 SBP-C 1 R g 0.02 0.11 0.214 <0.001 0.88 DBP-C 1 R 0.07 0.10 0.019 <0.001 0.91 SBP-C 2 R g 0.08 0.06 0.782 <0.001 0.89 DBP-C 2 R 0.05 0.09 0.580 0.002 0.96 Abbreviations: afpwv, aortic-femoral pulse wave velocity; CFI, comparative fitness index; DBP, diastolic blood pressure; SBP, systolic blood pressure. a Covariates included age, sex, body mass index, heart rate, smoking, diabetes, and duration of follow-up. b ρ 1 describes the path from baseline measures of arterial function (afpwv, C 1 R, and C 2 R) to follow-up BP. c ρ 2 describes the path from baseline BP to follow-up measures of arterial function (afpwv, C 1 R, and C 2 R). d P value for difference between ρ 1 and ρ 2. e P value for χ 2 test of model fitting. f For ρ 1 and ρ 2 being different from 0, P < 0.01. g C 1 R, large-artery (capacitive) compliance systemic vascular resistance; C 2 R, small-artery (oscillatory) compliance systemic vascular resistance. 2000 2002 Survey 2008 2010 Survey Baseline r 1 = 0.19 (SBP) r 1 = 0.21 (DBP) Baseline afpwv (ρ 1 ) from baseline afpwv to follow-up. In BP-C 1 R analysis models, the paths of SBP C 1 R (ρ 2 = 0.11, P = 0.056) and DBP C 1 R (ρ 2 = 0.10, P = 0.068) were marginally significant; the difference between ρ 1 and ρ 2 in the DBP-C 1 R model was significant (P = 0.019). In 2000 2002 Survey 2008 2010 Survey r 2 = 0.59 (SBP) Baseline Follow-up r 2 = 0.55 (DBP) r 1 = 0.05 (SBP) r 1 = 0.04 (DBP) Baseline C 1 R r 2 = 0.59 (SBP) r 2 = 0.50 (DBP) r 3 = 0.13 (SBP included) r 3 = 0.13 (DBP included) r 3 = 0.22 (SBP included) r 3 = 0.23 (DBP included) Follow-up 1 = 0.07 (SBP); 1 = 0.05 (DBP) 2 = 0.20 (SBP); 2 = 0.19 (DBP) Follow-up afpwv Figure 1. Cross-lagged path analysis models for the association of systolic blood pressure (SBP) and diastolic blood pressure (DBP) with aortic-femoral pulse wave velocity (afpwv) in the total sample (n = 446), Bogalusa Heart Study, 2000 2010. Results were adjusted for race/ethnicity, age, sex, body mass index, heart rate, smoking, diabetes, and duration of follow-up. ρ 1, cross-lagged path coefficient from baseline afpwv to follow-up blood pressure (BP); ρ 2, cross-lagged path coefficient from baseline BP to follow-up afpwv. r 1 represents synchronous correlations; r 2 and r 3 represent tracking correlations. Variance of follow-up BP explained: R 2 =0.36(SBP)andR 2 =0.25 (DBP). Variance of follow-up afpwv explained: R 2 = 0.08 (SBP included) and R 2 = 0.08 (DBP included). For r 1, r 2, ρ 1, and ρ 2 being different from 0 for SBP and DBP, P < 0.01; for r 3 being different from 0 for SBP and DBP, P < 0.05; for difference in SBP between ρ 1 and ρ 2, P = 0.048; and for difference in DBP between ρ 1 and ρ 2, P = 0.034. 1 = 0.02 (SBP); 1 = 0.07 (DBP) 2 = 0.11 (SBP); 2 = 0.10 (DBP) Follow-up C 1 R Figure 2. Cross-lagged path analysis models for the association of systolic blood pressure (SBP) and diastolic blood pressure (DBP) with large-artery elasticity (C 1 R) in the total sample (n = 381), Bogalusa Heart Study, 2000 2010. Results were adjusted for race/ethnicity, age, sex, body mass index, heart rate, smoking, diabetes, and duration of follow-up. ρ 1, cross-lagged path coefficient from baseline C 1 R to follow-up blood pressure (BP); ρ 2, cross-lagged path coefficient from baseline BP to follow-up C 1 R. r 1 represents synchronous correlations; r 2 and r 3 represent tracking correlations. Variance of follow-up BP explained: R 2 = 0.36 (SBP) and R 2 = 0.31 (DBP); variance of follow-up C 1 R explained: R 2 = 0.16 (SBP included) and R 2 =0.12 (DBP included). For r 2 and r 3 being different from 0 for SBP and DBP, P < 0.01; for difference in SBP between ρ 1 and ρ 2, P = 0.214; and for difference in DBP between ρ 1 and ρ 2, P = 0.019.

Blood Pressure and Arterial Stiffness 603 2000 2002 Survey 2008 2010 Survey r 2 = 0.59 (SBP) Baseline Follow-up r 2 = 0.55 (DBP) r 1 = 0.21 (SBP) r 1 = 0.20 (DBP) Baseline C 2 R BP-C 2 R analysis models, the paths of C 2 R SBP (ρ 1 = 0.08, P = 0.057) and DBP C 2 R (ρ 2 = 0.09, P = 0.053) were marginally significant; the paths of SBP C 2 R and C 2 R DBP were not significant. The difference between ρ 1 and ρ 2 was not significant in the BP-C 2 R models. Based on the model-fitting parameters, P values were less than 0.001 in χ 2 goodness-of-fit tests for all models, indicating a difference between the hypothesized models and the observed data. However, this was probably due to the high sensitivity of the A) B) 0.5 Δ afpwv, m/second/year 0.4 0.3 0.2 0.1 r 3 = 0.40 (SBP included) r 3 = 0.42 (DBP included) 1 = 0.08 (SBP); 1 = 0.05 (DBP) 2 = 0.06 (SBP); 2 = 0.09 (DBP) Follow-up C 2 R Figure 3. Cross-lagged path analysis models for the association of systolic blood pressure (SBP) and diastolic blood pressure (DBP) with small-artery elasticity (C 2 R)inthetotalsample(n = 381), Bogalusa Heart Study, 2000 2010. Results were adjusted for race/ethnicity, age, sex, body mass index, heart rate, smoking, diabetes, and duration of follow-up. ρ 1, cross-lagged path coefficient from baseline C 2 R to follow-up blood pressure (BP); ρ 2, cross-lagged path coefficient from baseline BP to follow-up C 2 R. r 1 represents synchronous correlations; r 2 and r 3 represent tracking correlations. Variance of follow-up BP explained: R 2 = 0.36 (SBP) and R 2 = 0.33 (DBP); variance of follow-up C 2 R explained: R 2 = 0.17 (SBP included) and R 2 =0.19 (DBP included). For r 1, r 2,andr 3 being different from 0 for SBP and DBP, P < 0.01. χ 2 test to a large sample size. Comparative fit index values ranged from 0.88 to 0.96, indicating a good fit to the observed data in 4 of the 6 models according to the standard criterion of a comparative fit index of 0.90. Figure 1 provides detailed parameter information on crosslagged path analysis models of the association of SBP and DBP with afpwv in the total sample, with adjustment for age, sex, race/ethnicity, BMI, heart rate, smoking, diabetes, and duration of follow-up. The variance of follow-up BP explained by baseline predictors was greater than that of follow-up afpwv. Tracking correlation over time was much lower for afpwv than for BP. There was no change in device, protocol, or method of measuring BP, afpwv, or arterial elasticity between baseline and follow-up. The only possible explanation for the lower tracking correlation (r = 0.13) is that afpwv increased more over the years and had a relatively greater measurement error. Figure 2 provides detailed parameter information on crosslagged path analysis models of the association of SBP and DBP with C 1 R in the total sample, with adjustment for age, sex, race/ethnicity, BMI, heart rate, smoking, diabetes, and duration of follow-up. The variance of follow-up BP explained by baseline predictors was greater than that of follow-up C 1 R. Tracking correlation over time was stronger for BP than for C 1 R. Figure 3 provides detailed parameter information on crosslagged path analysis models of the association of SBP and DBP with C 2 R in the total sample, with adjustment for age, sex, race/ethnicity, BMI, heart rate, smoking, diabetes, and duration of follow-up. The variance of follow-up BP explained by baseline predictors was greater than that of follow-up C 2 R. Tracking correlation over time was stronger for BP than for C 2 R. Figure 4 illustrates yearly rates of change (adjusted for race/ethnicity, sex, age, BMI, heart rate, smoking, and diabetes) in afpwv and SBP according to quartiles of their Δ SBP, mm Hg/year 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Quartile of Baseline SBP 0.0 Quartile of Baseline afpwv Figure 4. Yearly rates of change (Δ) in aortic-femoral pulse wave velocity (afpwv) (A) and systolic blood pressure (SBP) (B) according to quartiles of their baseline values in the total sample (n = 446), Bogalusa Heart Study, 2000 2010. Results were adjusted for race/ethnicity, sex, age, body mass index, heart rate, smoking, and diabetes. P-trend = 0.017 for ΔafPWV; P-trend = 0.340 for ΔSBP.

604 Chen et al. A) B) 200 0.8 Δ C 1 R per Year 150 100 50 0 50 100 Quartile of Baseline SBP baseline values in the total sample. The rate of change in afpwv during the follow-up period significantly increased across increasing quartiles of baseline SBP (P = 0.017) (Figure 4A). However, the covariate-adjusted rate of change in SBP did not show a significantly increasing trend across quartiles of baseline afpwv (Figure 4B). The rates of change in DBP and afpwv (data not shown) had trend patterns similar to those noted for SBP and afpwv. The results for rates of change shown in Figure 4 were consistent with the BP Δ SBP, mm Hg/year 0.6 0.4 0.2 0.0 Quartile of Baseline C 1 R Figure 5. Yearly rates of change (Δ) in large-artery elasticity (C 1 R) (A) and systolic blood pressure (SBP) (B) according to quartiles of their baseline values in the total sample (n = 381), Bogalusa Heart Study, 2000 2010. Results were adjusted for race/ethnicity, sex, age, body mass index, heart rate, smoking, and diabetes. P-trend = 0.052 for ΔC 1 R; P-trend = 0.746 for ΔSBP. A) B) 200 Δ C 2 R per Year 150 100 50 0 50 afpwv 1-directional relationship in the cross-lagged path analyses shown in Table 2 and Figure 1. Figure 5 illustrates yearly rates of change (adjusted for race/ethnicity, sex, age, BMI, heart rate, smoking, and diabetes) in C 1 R and SBP according to quartiles of their baseline values. As can be seen in Figure 5A, the trend in the rate of decrease in C 1 R during the follow-up period was borderline significant (P = 0.052) across increasing quartiles of baseline SBP. On the other hand, the decreasing trend was not Δ SBP, mm Hg/year 0.8 0.6 0.4 0.2 100 Quartile of Baseline SBP 0.0 Quartile of Baseline C 2 R Figure 6. Yearly rates of change (Δ) in small-artery elasticity (C 2 R) (A) and systolic blood pressure (SBP) (B) according to quartiles of their baseline values in the total sample (n = 381), Bogalusa Heart Study, 2000 2010. Results were adjusted for race/ethnicity, sex, age, body mass index, heart rate, smoking, and diabetes. P-trend = 0.875 for ΔC 2 R; P-trend = 0.331 for ΔSBP.

Blood Pressure and Arterial Stiffness 605 significant for the rate of change in SBP by increasing quartile of baseline C 1 R (Figure 5B). The rates of change in DBP and C 1 R (data not shown) had similar trend patterns as those noted for SBP and C 1 R. The results for yearly rates of change in SBP and C 1 R by their baseline quartiles shown in Figure 5 were consistent with the parameters of the cross-lagged path analyses shown in Table 2 and Figure 2. Note that C 1 R is a measure related to large-artery elasticity; the annual ΔC 1 R was calculated as the follow-up value minus the baseline value, divided by the duration of follow-up. Therefore, the greater absolute value of the negative ΔC 1 R is worse with respect to vascular function. Figure 6 illustrates yearly rates of change (adjusted for race/ethnicity, sex, age, BMI, heart rate, smoking, and diabetes) in C 2 R and SBP according to quartiles of their baseline values. As can be seen in Figure 6A, the trend in the rate of decrease in C 2 R during the follow-up period was not significant (P = 0.875) across increasing quartiles of baseline SBP; the trend was also not significant for the rate of change in SBP by increasing quartile of baseline C 2 R (P =0.331) (Figure 6B). The rates of change in DBP and C 2 R (data not shown) had trend patterns similar to those noted for SBP and C 2 R. The results for yearly rates of change in SBP and C 2 R by their baseline quartiles shown in Figure 6 were consistent with the parameters of the cross-lagged path analyses shown in Table 2 and Figure 3. C 2 R is a measure related to small-artery elasticity; as for ΔC 1 R, the greater absolute value of the negative ΔC 2 R is worse with respect to vascular function. DISCUSSION Although the role of arterial stiffness in isolated systolic hypertension and pulse pressure amplitude has been well documented in elderly populations (1, 2, 18 21), the temporal relationship between arterial stiffening and BP elevation during childhood and early adulthood has been incompletely elucidated. In the present study, we examined the temporal relationship between BP and arterial function measures in a longitudinal cohort of black and white middle-aged adults using a cross-lagged path analysis model, a powerful statistical approach in dissecting a causal relationship between intercorrelated variables. The results indicated that elevated BP preceded increased large-artery stiffness during young adulthood, with blacks and whites showing similar patterns of this 1-directional relationship. These findings on the BP arterial stiffness pathway were partly confirmed using large- (C 1 R)and small- (C 2 R) artery elasticity, as measured by the HDI device, in this longitudinal study cohort. The observations from the current study suggest that the mechanisms underlying the development of hypertension might be different during younger and older age periods. BP levels and arterial vascular alterations are both influenced by aging processes and cardiovascular risk factors (3 6). In a systematic review of 77 cross-sectional studies in adults, age and BP were found to be consistently, independently associated with aortic pulse wave velocity in 91% and 90% of studies, respectively (3). The Bogalusa Heart Study has shown that BP is one of the important risk factors for arterial stiffness in children and young adults (5, 6). An important question raised by these cross-sectional studies is whether an increase in arterial stiffness precedes increases in BP or vice versa, or whether the relationship is bidirectional. The observations from cross-sectional studies limit inference regarding the temporal relationship between BP and arterial function changes. Although BP has been used as a predictor variable in previous cross-sectional studies (3, 4), it is largely unknown whether changes in mechanical properties of the arterial wall or increased BP occurs first or whether the causal relationship varies in different age periods. Several longitudinal studies have analyzed the temporal relationship between BP and arterial stiffness and elasticity; however, their results have not been consistent. In the Framingham Study, Kaess et al. (18) found that higher aortic stiffness, forward pressure-wave amplitude, and augmentation index were associated with higher risk of future incident hypertension. However, initial BP was not independently associated with risk of progressive aortic stiffening in a cohort of participants with a mean age of 60 years followed over a 7-year period (18). In another large epidemiologic study, the Atherosclerosis Risk in Communities (ARIC) Study, Liao et al. (19) reported that higher carotid artery stiffness was associated with future incident hypertension in the elderly. The Multi-Ethnic Study of Atherosclerosis (MESA) showed that lower large- and small-artery elasticity (C 1 and C 2 ) was associated with incident hypertension in a cohort aged 45 84 years (mean age = 58.1 years) with a mean follow-up time of 4.3 years (20). Other investigators have also reported similar results regarding the relationship between arterial vascular alteration and BP (21 23). In contrast, some studies have shown a relationship between BP and arterial stiffness in an opposite direction; that is, elevated BP resulted in increased arterial stiffening (24 27). Annual rates of progression in pulse wave velocity over a 6-year follow-up period among persons with treated hypertension were significantly higher than in normotensive persons (27). By comparing the ages of participants in the 2 groups of studies mentioned above, one can see that the cohorts for which an arterial vascular alteration BP relationship was reported were relatively older (18 20, 23) than those in studies reporting a BP pulse wave velocity relationship (24 27). Interestingly, a few studies, including ours, found that childhood BP levels predicted adult arterial stiffness (28 30). In our previous longitudinal analysis, childhood systolic BP showed the highest correlation (r = 0.111, P < 0.01) with adult brachial-ankle pulse wave velocity among cardiovascular risk factors (28). The controversy surrounding the temporal relationship between BP and arterial stiffness is mainly explained by the different age groups under study (27, 31). Further, in longitudinal studies, exclusion of hypertension patients receiving pharmacological treatment at baseline favors arterial vascular alteration-to-bp directionality but limits BP-to-arterial vascular alteration directionality, which makes it difficult to detect the temporal relationship consistently. BP levels and the structure-function properties of the largearterial wall are highly interrelated during the development of hypertension. The strong association suggests that their temporal relationship is bidirectional, like a 2-way street, based on vascular wall biology and hemodynamics; that is, they are mutually influenced during the aging process (7, 8). It is

606 Chen et al. generally thought that elevated BP from childhood to young adulthood accelerates arterial stiffness due to increased wear and tear on the artery walls, subsequently leading to muscle cell hypertrophy, collagen synthesis in the vascular wall, and fatigue fracture of the elastic elements within the media. In turn, arterial stiffness increases systolic BP, leading to widening of pulse pressure due to alterations in the buffering function of the conduit artery walls among older individuals (1, 2, 7, 8). A 1-way direction from elevated BP to increased arterial stiffness was found in the current study cohort of adults aged 32 51 years. Furthermore, a subset of 381 adults had large- and small-arterial compliance measurements available at baseline and follow-up in this study cohort. The decreased arterial elasticity (C 1 and C 2 ) measured by the HDI device has been demonstrated to be associated with incident hypertension, cardiovascular disease, stroke, heart failure events, and kidney function decline in MESA (20, 32, 33). In the current study, the 1-way direction of BP to afpwv was partly confirmed using C 1 R and C 2 R, measures related to large- and small-artery elasticity, respectively. The observation in this and our previous study (28) supports the notion that elevated BP levels result in an accelerated arterial stiffening process that begins in early life. However, the data do not preclude arterial stiffening resulting in isolated systolic hypertension in older adults. Blacks outpace other racial/ethnic groups in the United States in terms of prevalence, early onset, and severity of hypertension (34). The black-white difference in BP is seen even in childhood, with blacks showing higher levels and a faster rate of change than whites (35, 36). Furthermore, a greater BP-dependent increase in aortic stiffness in blacks than in whites was observed in a cohort of young adults aged 19 50 years, pointing towards differences in mechanical properties of large arteries between these racial/ethnic groups (37). In the present study cohort of middle-aged adults, blacks showed higher levels of BP, afpwv, and systemic vascular resistance but lower levels of C 1 and C 2 than whites (Table 1). The black-white difference in C 1 and C 2 in this study cohort was consistent with the racial/ethnic difference in C 1 and C 2 observed in the MESA cohort (38). With respect to the temporal parameters, however, the cross-lagged path coefficients (ρ 1 and ρ 2 ), as shown in Appendix Table 1, did not differ significantly between blacks and whites, except for ρ 2 in the DBP-C 1 R model. Further studies are needed to understand the temporal relationships between BP and arterial stiffness and elasticity in black and white populations. This community-based longitudinal cohort study provided a unique opportunity to examine temporal relationships; however, it also had certain limitations. First, exclusion of hypertensive persons receiving pharmacological treatment might have resulted in a loss of information, because these individuals represent a subgroup who, without treatment, would be expected to have the highest BP levels; thus, this may have led to underestimation of the BP arterial stiffness relationship. Second, the relatively small sample size, especially for blacks, meant that we had limited statistical power to detect the weak-to-moderate associations. Third, data on physical activity, serum lipid concentrations, and diet were either not available or only partly available in the present study cohort, which might have led to bias in the association analyses. In summary, in a longitudinal assessment of the temporal relationship between BP and vascular stiffness using a crosslagged path analysis model, we demonstrated that elevated SBP and DBP levels precede increased large-arterial stiffness in middle-aged adults. This 1-directional relationship was supported in part by analyses of the associations between BP and large- and small-artery elasticity. The results suggest that the hemodynamic and vascular functional changes underlying hypertension differ between younger and older age periods in that the arterial wall may not be stiff enough in youth to alter BP levels during young adulthood. These findings underscore the influence of BP elevation on the arterial stiffening process during young adulthood, which improves our understanding of the mechanisms involved and has implications for treating and preventing hypertension by targeting causal factors to delay subsequent arterial stiffening, especially early in life. ACKNOWLEDGMENTS Author affiliations: Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana (Wei Chen, Shengxu Li, Camilo Fernandez, Dianjianyi Sun, Chin-Chih Lai, Tao Zhang, Lydia Bazzano); Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (Dianjianyi Sun); Department of Cardiology, Peking Union Medical College Hospital, Beijing, China (Chin-Chih Lai); Department of Biostatistics, School of Public Health, Shandong University, Jinan, China (Tao Zhang); Preventive Cardiology Program, Cincinnati Children s Hospital Medical Center, Cincinnati, Ohio (Elaine M. Urbina); and Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana (Hong-Wen Deng). This study was supported by grant 5R01ES021724 from the National Institute of Environmental Health Sciences, grant 2R01AG016592 from the National Institute on Aging, and grant 13SDG14650068 from the American Heart Association. S.L. is a scholar of the Building Interdisciplinary Research in Women s Health program, supported by grant K12HD043451 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development. L.B. was supported by grant R01AG041200 from the National Institute on Aging. Conflict of interest: none declared. REFERENCES 1. Arnett DK, Evans GW, Riley WA. Arterial stiffness: a new cardiovascular risk factor? Am J Epidemiol. 1994;140(8): 669 682. 2. O Rourke MF, Mancia G. Arterial stiffness. J Hypertens. 1999; 17(1):1 4. 3. Cecelja M, Chowienczyk P. Dissociation of aortic pulse wave velocity with risk factors for cardiovascular disease other than

Blood Pressure and Arterial Stiffness 607 hypertension: a systematic review. Hypertension. 2009;54(6): 1328 1336. 4. Mitchell GF, Guo CY, Benjamin EJ, et al. Cross-sectional correlates of increased aortic stiffness in the community: the Framingham Heart Study. Circulation. 2007;115(20):2628 2636. 5. Urbina EM, Srinivasan SR, Kieltyka RL, et al. Correlates of carotid artery stiffness in young adults: the Bogalusa Heart Study. Atherosclerosis. 2004;176(1):157 164. 6. Li S, Chen W, Srinivasan SR, et al. Influence of metabolic syndrome on arterial stiffness and its age-related change in young adults: the Bogalusa Heart Study. Atherosclerosis. 2005; 180(2):349 354. 7. Mitchell GF. Arterial stiffness and hypertension: chicken or egg? Hypertension. 2014;64(2):210 214. 8. Franklin SS. Arterial stiffness and hypertension: a two-way street? Hypertension. 2005;45(3):349 351. 9. Berenson GS, McMahan CA, Voors AW, et al. Cardiovascular Risk Factors in Children: The Early Natural History of Atherosclerosis and Essential Hypertension. New York, NY: Oxford University Press; 1980:47 123. 10. Jo CO, Lande MB, Meagher CC, et al. A simple method of measuring thoracic aortic pulse wave velocity in children: methods and normal values. J Am Soc Echocardiogr. 2010; 23(7):735 740. 11. Hypertension Diagnostics, Inc. HD/PulseWave CR-2000 Research CardioVascular Profiling System Operator s Manual. Eagan, MN: Hypertension Diagnostics, Inc.; 1999. 12. Kenny DA. Cross-lagged panel correlation: a test for spuriousness. Psychol Bull. 1975;82(6):887 903. 13. Kivimäki M, Feldt T, Vahtera J, et al. Sense of coherence and health: evidence from two cross-lagged longitudinal samples. Soc Sci Med. 2000;50(4):583 597. 14. Li CC. Path Analysis A Primer. Pacific Grove, CA: Boxwood Press; 1975. 15. Joreskog K, Sorbom D. LISREL 8.52: Structural Equation Modeling with the SIMPLIS Command Language. Chicago, IL: Scientific Software International; 1993. 16. Joreskog K, Sorbom D. LISREL 8.52: User s Reference Guide. Chicago, IL: Scientific Software International; 2001. 17. Chen W, Srinivasan SR, Berenson GS. Path analysis of metabolic syndrome components in black versus white children, adolescents, and adults: the Bogalusa Heart Study. Ann Epidemiol. 2008;18(2):85 91. 18. Kaess BM, Rong J, Larson MG, et al. Aortic stiffness, blood pressure progression, and incident hypertension. JAMA. 2012; 308(9):875 881. 19. Liao D, Arnett DK, Tyroler HA, et al. Arterial stiffness and the development of hypertension. The ARIC Study. Hypertension. 1999;34(2):201 206. 20. Peralta CA, Adeney KL, Shlipak MG, et al. Structural and functional vascular alterations and incident hypertension in normotensive adults: the Multi-Ethnic Study of Atherosclerosis. Am J Epidemiol. 2010;171(1):63 71. 21. Takase H, Dohi Y, Toriyama T, et al. Brachial-ankle pulse wave velocity predicts increase in blood pressure and onset of hypertension. Am J Hypertens. 2011;24(6):667 673. 22. Dernellis J, Panaretou M. Aortic stiffness is an independent predictor of progression to hypertension in nonhypertensive subjects. Hypertension. 2005;45(3):426 431. 23. Najjar SS, Scuteri A, Shetty V, et al. Pulse wave velocity is an independent predictor of the longitudinal increase in systolic blood pressure and of incident hypertension in the Baltimore Longitudinal Study of Aging. J Am Coll Cardiol. 2008;51(14): 1377 1383. 24. Nürnberger J, Dammer S, Opazo Saez A, et al. Diastolic blood pressure is an important determinant of augmentation index and pulse wave velocity in young, healthy males. J Hum Hypertens. 2003;17(3):153 158. 25. Tomiyama H, Yoshida M, Yamada J, et al. Arterial-cardiac destiffening following long-term antihypertensive treatment. Am J Hypertens. 2011;24(10):1080 1086. 26. Tomiyama H, Hashimoto H, Hirayama Y, et al. Synergistic acceleration of arterial stiffening in the presence of raised blood pressure and raised plasma glucose. Hypertension. 2006;47(2): 180 188. 27. Benetos A, Adamopoulos C, Bureau JM, et al. Determinants of accelerated progression of arterial stiffness in normotensive subjects and in treated hypertensive subjects over a 6-year period. Circulation. 2002;105(10):1202 1207. 28. Li S, Chen W, Srinivasan SR, et al. Childhood blood pressure as a predictor of arterial stiffness in young adults: the Bogalusa Heart Study. Hypertension. 2004;43(3):541 546. 29. Aatola H, Hutri-Kähönen N, Juonala M, et al. Lifetime risk factors and arterial pulse wave velocity in adulthood: the Cardiovascular Risk in Young Finns Study. Hypertension. 2010;55(3):806 811. 30. Koivistoinen T, Hutri-Kähönen N, Juonala M, et al. Metabolic syndrome in childhood and increased arterial stiffness in adulthood: the Cardiovascular Risk in Young Finns Study. Ann Med. 2011;43(4):312 319. 31. Mitchell GF, Wang N, Palmisano JN, et al. Hemodynamic correlates of blood pressure across the adult age spectrum: noninvasive evaluation in the Framingham Heart Study. Circulation. 2010;122(14):1379 1386. 32. Duprez DA, Jacobs DR Jr, Lutsey PL, et al. Association of small artery elasticity with incident cardiovascular disease in older adults: the Multi-Ethnic Study of Atherosclerosis. Am J Epidemiol. 2011;174(5):528 536. 33. Peralta CA, Jacobs DR Jr, Katz R, et al. Association of pulse pressure, arterial elasticity, and endothelial function with kidney function decline among adults with estimated GFR >60 ml/min/1.73 m 2 : the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Kidney Dis. 2012;59(1):41 49. 34. Pickering TG. Hypertension in blacks. Curr Opin Nephrol Hypertens. 1994;3(2):207 212. 35. Voors AW, Berenson GS, Dalferes ER, et al. Racial differences in blood pressure control. Science. 1979;204(4397): 1091 1094. 36. Manatunga AK, Jones JJ, Pratt JH. Longitudinal assessment of blood pressures in black and white children. Hypertension. 1993;22(1):84 89. 37. Ferreira AV, Viana MC, Mill JG, et al. Racial differences in aortic stiffness in normotensive and hypertensive adults. J Hypertens. 1999;17(5):631 637. 38. Duprez DA, Jacobs DR Jr, Lutsey PL, et al. Race/ethnic and sex differences in large and small artery elasticity results of the Multi-Ethnic Study of Atherosclerosis (MESA). Ethn Dis. 2009;19(3):243 250. (Appendix follows)

608 Chen et al. Appendix Table 1. Cross-Lagged Path Coefficients for the Association of Blood Pressure With Aortic-Femoral Pulse Wave Velocity (n = 446) and Arterial Elasticity (n = 381), by Race/Ethnicity, With Adjustment for Covariates, a Bogalusa Heart Study, 2000 2010 Model ρ 1 b Whites (n = 277) Blacks (n = 104) ρ 2 c P Value d ρ 1 b ρ 2 c Racial/Ethnic Difference P Value d P for ρ 1 P for ρ 2 SBP-afPWV 0.12 e 0.22 e 0.180 0.08 0.13 0.134 NS f NS DBP-afPWV 0.10 g 0.19 e 0.231 0.09 0.14 0.100 NS NS SBP-C 1 R h 0.06 0.07 0.906 0.10 0.15 0.074 NS NS DBP-C 1 R 0.05 0.04 0.292 0.11 0.21 g 0.021 NS NS SBP-C 2 R h 0.08 0.02 0.481 0.10 0.18 g 0.562 NS NS DBP-C 2 R 0.08 0.08 0.986 0.03 0.16 0.174 NS NS Abbreviations: afpwv, aortic-femoral pulse wave velocity; DBP, diastolic blood pressure; NS, not significant; SBP, systolic blood pressure. a Covariates included age, sex, body mass index, heart rate, smoking, diabetes, and duration of follow-up. b ρ 1 represents the path from afpwv, C 1 R,orC 2 R to BP. c ρ 2 represents the path from BP to afpwv, C 1 R,orC 2 R. d P value for difference between ρ 1 and ρ 2 within racial/ethnic groups. e For ρ 1 and ρ 2 being different from 0, P < 0.01. f P > 0.05. g For ρ 1 and ρ 2 being different from 0, P < 0.05. h C 1 R, large-artery (capacitive) compliance systemic vascular resistance; C 2 R, small-artery (oscillatory) compliance systemic vascular resistance.