Temporal Relationship Between Elevated Blood Pressure and Arterial Stiffening Among Middle-Aged Black and White Adults: The Bogalusa Heart Study - PubMed (original) (raw)

Temporal Relationship Between Elevated Blood Pressure and Arterial Stiffening Among Middle-Aged Black and White Adults: The Bogalusa Heart Study

Wei Chen et al. Am J Epidemiol. 2016.

Abstract

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 (ρ2) from baseline BP to follow-up afPWV was significantly greater than the path coefficient (ρ1) from baseline afPWV to follow-up BP (ρ2 = 0.20 vs. ρ1 = 0.07 (P = 0.048) for systolic BP; ρ2 = 0.19 vs. ρ1 = 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.

Keywords: arterial elasticity; arterial stiffness; blood pressure; longitudinal analysis; temporal relationships.

© 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.

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Figures

Figure 1.

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. ρ1, cross-lagged path coefficient from baseline afPWV to follow-up blood pressure (BP); ρ2, 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) and _R_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, ρ1, and ρ2 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 ρ1 and ρ2, P = 0.048; and for difference in DBP between ρ1 and ρ2, P = 0.034.

Figure 2.

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. ρ1, cross-lagged path coefficient from baseline C_1_R to follow-up blood pressure (BP); ρ2, 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 ρ1 and ρ2, P = 0.214; and for difference in DBP between ρ1 and ρ2, P = 0.019.

Figure 3.

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) 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. ρ1, cross-lagged path coefficient from baseline C_2_R to follow-up blood pressure (BP); ρ2, 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, and _r_3 being different from 0 for SBP and DBP, P < 0.01.

Figure 4.

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.

Figure 5.

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 Δ_C_1_R; _P-_trend = 0.746 for ΔSBP.

Figure 6.

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 Δ_C_2_R; _P-_trend = 0.331 for ΔSBP.

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