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. Author manuscript; available in PMC: 2023 May 1.
Published in final edited form as: Hypertension. 2022 Feb 16;79(5):1045–1056. doi: 10.1161/HYPERTENSIONAHA.121.18776

Arterial stiffness and long-term risk of health outcomes: The Framingham Heart Study

Ramachandran S Vasan 1,2,3, Stephanie Pan 4, Vanessa Xanthakis 1,2,4, Alexa Beiser 2,4,5, Martin G Larson 2,4, Sudha Seshadri 2,5,6, Gary F Mitchell 7
PMCID: PMC9009137  NIHMSID: NIHMS1778540  PMID: 35168368

Abstract

Background.

Arterial stiffness increases with age and is associated with an increased risk of adverse outcomes on short-term follow-up (typically <10 years). Data regarding associations of arterial stiffness with health outcomes on longer-term follow-up are lacking.

Methods.

We evaluated 7283 Framingham Study participants (mean age 50 years, 53% women) who underwent assessment of carotid-femoral pulse wave velocity (CFPWV, a marker of arterial stiffness) via applanation tonometry at one or more routine examinations. We used time-dependent Cox proportional hazards regression models to relate CFPWV to the incidence of health outcomes (updating CFPWV and all covariates at serial examinations).

Results.

On long-term follow-up (median 15 years; minimum-maximum, 0–20), participants developed cardiometabolic disease (hypertension [1255 events]; diabetes [381 events]), chronic kidney disease (CKD, 529 events), dementia (235 events), cardiovascular disease (CVD, 684 events) and its components (coronary heart disease [CHD, 314 events], heart failure [191 events], transient ischemic attacks [TIA] or stroke [250 events]), and death (1086 events). In multivariable-adjusted models, each standard deviation (SD) increment in CFPWV was associated with increased risk of hypertension (hazards ratio [HR] 1.32, 95%CI 1.21–1.44), diabetes (HR 1.32, 95%CI 1.11–1.58), CKD (1.19, 95%CI 1.05–1.34), dementia (HR 1.27, 95%CI 1.06–1.53), CVD (HR 1.20, 95%CI 1.06–1.36) and its components (CHD, HR 1.37, 95%CI 1.13–1.65; TIA/stroke, HR 1.24, 95%CI 1.00–1.53), and death (HR 1.29, 95%CI 1.17–1.43). The association with heart failure was borderline non-significant (HR 1.21, 95%CI 0.98–1.51, p=0.08).

Conclusions.

Our prospective observations of a large community-based sample establish the long-term prognostic importance of arterial stiffness for multiple health outcomes.

Keywords: arterial stiffness, pulse wave velocity, epidemiology, cardiovascular disease, dementia, mortality, risk, cohort studies

Introduction

Increased arterial stiffness is a universal concomitant of aging in western societies.1 Arterial stiffening is associated with decrease in elasticity of the aorta2 and an increase in carotid-femoral pulse wave velocity (CFPWV).3 Greater arterial stiffness results in increased transmission of pulsatile pressure into the microcirculation, increasing disease risk.4 Thus, higher CFPWV has been associated with an increased risk cardiometabolic outcomes (hypertension5,6 and diabetes7), chronic kidney disease (CKD),8 cardiovascular disease (CVD) and its components (coronary heart disease [CHD], heart failure and stroke), and death.9–13

Previous studies5–13 reporting the associations of CFPWV with adverse outcomes were limited by short follow-up times (median 6–8 years in meta-analyses9–11), single occasion CFPWV measurements, and a focus on high-risk samples or older people. None evaluated the risk of multiple health outcomes simultaneously during extended follow-up of a young-to-middle-aged population. Accordingly, the present investigation assessed the long-term prognostic significance of arterial stiffness with regards to a range of health outcomes in a community-based sample of participants spanning a wide age range, who underwent serial measurements of CFPWV and were followed up for two decades.

We hypothesized that higher CFPWV is associated with an increased risk of multiple cardiometabolic and vascular outcomes and mortality in the community. We postulated that associations of CFPWV with health outcomes would be consistent in both sexes and across a wide age range and would remain robust on long-term follow-up. We tested our hypothesis prospectively in the Framingham Heart Study (FHS) cohorts, leveraging serial arterial stiffness measurements across two generations of participants followed for two decades.

Methods

All data and materials from the Framingham Heart Study (FHS) cohorts are publicly available at the National Heart, Lung, and Blood Institute data repository (Biologic Specimen and Data Repositories Information Coordinating Center) at https://biolincc.nhlbi.nih.gov/studies/fhs/.

Study Samples

The design and inclusion criteria of the Framingham Offspring Study (FOS) and Third Generation (Gen 3) cohorts have been described previously.14,15 The present investigation evaluated FOS participants who attended their seventh (1998–2001) or eighth (2005–2008) examination, and Gen 3 participants who attended their first (2002–2005) or second (2008–2011) examination. Attendees at these examinations underwent arterial tonometry. The first examination at which a participant underwent tonometry served as the baseline (index examination) for that participant.

Of the 7786 eligible participants, 503 (n=424 FOS, n=79 Gen 3) without arterial tonometry data were excluded. Thus, our study sample comprises 7283 unique participants (3267 FOS and 4016 Gen 3), who contributed 12261 person-observations (sample 1; Figure S1). Additional subsamples (samples 2–5) were outcome-specific; participants with a prevalent outcome were excluded for analyses of the incidence of that outcome (Figure S1). We used two alternative definitions for incident CKD, resulting in two subsamples (samples 6 and 7) for this outcome. The Institutional Review Board at the Boston University Medical Center approved the study protocol. All FHS participants provided written informed consent.

Covariate Assessment

Participants underwent phlebotomy (after an overnight fast) to assay CVD risk factors, and standardized blood pressure measurements. Hypertension was defined as systolic blood pressure ≥140 mmHg, or diastolic blood pressure ≥90 mmHg, or the use of hypertensive medications.16 Diabetes mellitus was defined as fasting blood glucose ≥126 mg/dL or non-fasting blood glucose ≥200 mg/dL or the use of hypoglycemic medications.17 CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 or a urine albumin-to-creatinine ratio (UACR) ≥30 mg/g (see alternative definition below).18

Arterial stiffness assessment

Trained sonographers performed applanation tonometry on the right brachial, femoral, and carotid arteries of supine participants using a standardized protocol with excellent reproducibility (intraclass correlation coefficients of 0.93 to 0.95 for repeated measures and inter-observer correlations of 0.97 or higher).19–21 Arterial waveforms were signal-averaged using the electrocardiographic R wave as the fiducial point. The brachial arterial waveform was integrated and calibrated with the systolic and diastolic auscultatory blood pressure obtained during tonometry to derive mean arterial pressure (MAP).

CFPWV was calculated by dividing the carotid-femoral transit distance (calculated using the difference in body surface measurements from the suprasternal notch to the femoral and carotid sites) by the carotid-femoral transit time delay (measured using the foot of the carotid and femoral waveforms).19

Criteria for and Ascertainment of Outcomes

We evaluated incidence of the following outcomes: hypertension, diabetes, CKD; dementia; CVD (including its components: CHD, heart failure, and transient ischemic attacks [TIA] or stroke); and all-cause mortality. FOS and Gen 3 cohorts are under surveillance for the occurrence of these outcomes.22,23 Details regarding ascertainment of these events are under Supplementary Methods. Ascertainment of new-onset hypertension, diabetes, and CKD was made at FHS visits after the index examinations.16–18 Urine albumin and creatinine measurements were not available in the Gen 3 cohort. Therefore, analyses of incident CKD defined using eGFR and UACR were limited to FOS. We evaluated an alternative definition of CKD as an eGFR <60 mL/min/1.73 m2 without the UACR criterion, which permitted combined analyses of FOS and Gen 3. Separate physician review panels adjudicated the outcomes of dementia, CVD and stroke using standardized criteria.22,23

Statistical Analyses

Details of the statistical methods are in the Supplemental Methods section and summarized below. We inverse transformed CFPWV (to 1/CFPWV) to reduce heteroscedasticity, multiplied the value by −1000 to restore the directionality of associations, and then standardized it (mean=0, SD=1). The use of 1/CFPWV for modeling indicates vascular distensibility is modeled (not stiffness). The term arterial stiffness is used, however, given its more frequent use in the literature.

In primary analyses, standardized CFPWV (continuous variable) was related to the incidence of each outcome using time-dependent multivariable-adjusted Cox proportional hazards regression models (follow-up through 2018) stratified by cohort status.24 Models evaluating all-cause mortality were stratified by prevalent CVD status. Cox regression with discrete-time intervals was used to analyze the incidence of hypertension, diabetes, and CKD. CFPWV was updated for participants who underwent tonometry at a subsequent examination. Except for sex, all covariates were updated at each follow-up examination.

For each outcome, sequential models adjusted for the following: age and sex (Model 1); age, sex, current smoking, the ratio of total to high-density lipoprotein cholesterol (Tc/HDL), and diabetes (Model 2); variables in Model 2 plus systolic blood pressure and hypertensive treatment (Model 3). We chose this modeling strategy because of the bidirectional relations between blood pressure and CFPWV.25 We assessed effect modification by age and sex in Model 3. In exploratory analyses for incident hypertension, CKD, and dementia, Model 3 additionally adjusted for the following covariates: diastolic blood pressure (for hypertension), eGFR (for CKD), and education and ApoƐ4 status (for dementia).

Additional analyses

For each outcome, we evaluated the predictive utility of CFPWV by assessing the increment in Harrell’s C-statistic when CFPWV was added to a model that included clinical covariates in Model 3. Potential non-linearity of associations were assessed using restricted cubic splines. Additionally, we evaluated the quartiles of CFPWV (defined in sample 1). For outcomes with continuous surveillance (i.e., dementia, CVD, CVD subtypes, and all-cause mortality), we plotted the cumulative incidence by CFPWV quartiles (tertiles for heart failure) using the Kaplan-Meier method and estimated the age- and sex-adjusted cumulative probabilities from Cox models.

Multivariable Cox regression models related CFPWV quartiles to the incidence of each outcome event (the first quartile as the referent) adjusting for Model 3 covariates. Tertiles were used (instead of quartiles) for incident heart failure, given very few incident events in the first quartile. In sensitivity analyses, CFPWV quartiles were defined at each serial examination and the foregoing analyses repeated. We calculated the population attributable risk (PAR) for each outcome that is associated with the top quartile of CFPWV (top tertile, in the case of heart failure).26

CFPWV varies with age, sex and BP.27 Therefore, we tested the premise whether CFPWV predicted risk of outcomes, accounting for these key determinants. We regressed CFPWV (dependent variable) on age, age2, sex, systolic BP and systolic BP2 in sample 1. CFPWV residuals modeled as continuous and binary variables (dichotomized at the median, 75th and 90th percentile) were related to the risk of each outcome, adjusting for smoking, TC/HDL ratio, diabetes, and antihypertensive treatment.

Statistical significance was evaluated using a two-sided P<0.05 unless otherwise stated.

Results

Baseline characteristics

The characteristics of our study sample, overall and by sex, are shown in Table 1. Participants were middle-aged, over half were women, and 55 percent were from the Gen 3 cohort. Table S1 shows the baseline characteristics by FHS cohort (Offspring vs. Gen 3).

Table 1.

Characteristics of the Study Sample at the Index Exam,* Overall and Stratified by Sex

Characteristics Men (n= 3392) Women (n= 3891) Overall (n= 7283)
Age, years 50.4±14.5 50.3±14.4 50.3±14.5
Body mass index, kg/m2 28.2±4.5 26.4±5.6 27.2±5.2
Offspring Cohort (%) 1763 (45.3) 1504 (44.3) 3267 (44.9)
Gen 3 Cohort (%) 2128 (54.7) 1888 (55.7) 4016 (55.1)
Current smokers (%) 478 (14.1) 523 (13.4) 1001 (13.8)
Systolic blood pressure, mmHg 124±15 119±18 121±17
Diastolic blood pressure, mmHg 77±10 72±9 75±10
Mean arterial pressure, mmHg 94±11 90±12 92±12
Hypertensive (%) 1212 (35.7) 1052 (27.1) 2264 (31.1)
Antihypertensive medication (%) 828 (24.4) 754 (19.4) 1582 (21.8)
Total cholesterol, mg/dL 190±37 194±37 192±37
Total/HDL cholesterol ratio 4.32 ± 1.45 3.34 ± 1.07 3.8±1.4
High density lipoprotein cholesterol, mg/dL 47±13 62±17 55±17
Estimated glomerular filtration rate (eGFR), mL/min/1.73 m2 92±18 93±19 93±18
Urine albumin-to-creatinine ratio, mg/g 3.55 (2.35, 7.09) 5.56 (3.33, 10.70) 4.6 (2.8, 9.1)
Lipid lowering medication (%) 673 (19.9) 476 (12.2) 1149 (15.8)
Fasting blood glucose, mg/dL 103±22 96±21 99±22
Diabetes (%) 294 (8.7) 212 (5.5) 506 (7)
Diabetes medication (%) 180 (5.4) 137 (3.5) 317 (4.4)
Prevalent CVD (%) 319 (9.4) 200 (5.1) 519 (7.1)
 CHD 246 (7.3) 110 (2.8) 356 (4.9)
 CHF 42 (1.2) 24 (0.6) 66 (0.9)
 Stroke/TIA 61 (1.8) 56 (1.4) 117 (1.6)
Prevalent CKD1 287 (9) 312 (8.6) 599 (8.8)
CFPWV, m/sec 7.98 (6.91, 9.64) 7.22 (6.23, 8.98) 7.6 (6.5, 9.3)
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CVD=cardiovascular disease; CHD=coronary heart disease; CHF=congestive heart failure; TIA=transient ischemic attack; CKD=chronic kidney disease.

Data are shown as mean±SD or median (quartile 1, quartile 3) for continuous measures and frequency (%) for categorical measures.

*

The index examination refers to the first examination at which arterial stiffness was assessed.

1

CKD defined as estimated glomerular filtration rate <60 mL/min/1.73 m2 or urine albumin-to-creatinine ratio ≥30 mg/g.

Relations of CFPWV with the incidence of outcome events

During follow-up (median 15 years, [min-max] 0–20 years), the following new-onset events developed: hypertension, 1255 events; diabetes, 381 events; CKD, 529 events (using eGFR and UACR criteria), and 518 events (using the eGFR criterion alone); dementia, 235 events; CVD, 684 events; CHD, 314 events; heart failure, 191 events; stroke/TIA, 250 events; and death, 1086 events. The number of incident events by cohort (FOS vs. Gen 3) and by sex is shown in Table S2.

Table 2 shows the associations of CFPWV with the incidence of each outcome. CFPWV was associated with increased risk of each outcome in Models 1 and 2, with effect sizes being of a slightly greater magnitude for hypertension, diabetes, CHD (hazards ratios [HR] per SD exceeded 1.40). Associations were modestly attenuated in Model 3, although statistical significance was maintained for all outcomes except for heart failure that became borderline non-significant.

Table 2.

Association of Carotid-femoral pulse wave velocity with the incidence of outcome events.

Outcome Model 1
Age- and Sex-adjusted		 Model 2
Adjusting for standard risk factors* except for systolic BP and HTN treatment		 Model 3
Adjusting for standard risk factors* including systolic BP and HTN treatment
No. events/ No. person-observations HR (95% CI) P-value No. events/ No. person-observations HR (95% CI) P-value No. events/ No. person-observations HR (95% CI) P-value
Cardiometabolic Disease
Hypertension 1255/8145 1.88 (1.73, 2.04) <.0001 1212/7926 1.78 (1.63, 1.94) <.0001 1212/7922 1.32 (1.21, 1.44) <.0001
Diabetes 381/11377 2.13 (1.81, 2.51) <.0001 370/11178 1.43 (1.22, 1.67) <.0001 370/11152 1.32 (1.11, 1.58) 0.002
Chronic Kidney Disease (CKD)
CKDa† 529/4159 1.31 (1.17, 1.46) <.0001 505/3949 1.26 (1.12, 1.41) <.0001 505/3946 1.19 (1.05, 1.34) 0.005
CKDb 518/11585 1.34 (1.17, 1.53) <.0001 499/11268 1.28 (1.11, 1.47) 0.0006 497/11240 1.17 (1.01, 1.35) 0.03
Neurocognitive Outcomes
Dementia† 235/5035 1.28 (1.07, 1.52) 0.006 228/4791 1.29 (1.08, 1.54) 0.004 227/4787 1.27 (1.06, 1.53) 0.01
Cardiovascular Disease and Subtypes
CVD (composite) 684/11405 1.42 (1.26, 1.59) <.0001 661/11095 1.32 (1.17, 1.48) <.0001 657/11069 1.20 (1.06, 1.36) 0.005
CHD 314/11405 1.65 (1.40, 1.95) <.0001 301/11095 1.56 (1.31, 1.85) <.0001 299/11069 1.37 (1.13, 1.65) 0.001
CHF 191/11405 1.47 (1.18, 1.83) 0.0005 187/11095 1.37 (1.10, 1.70) 0.005 187/11069 1.21 (0.98, 1.51) 0.08
Stroke/TIA 250/11405 1.42 (1.17, 1.72) 0.0003 241/11095 1.30 (1.07, 1.59) 0.01 240/11069 1.24 (1.00, 1.53) 0.047
Death
All-Cause Mortality 1086/12261 1.35 (1.24, 1.48) <.0001 1028/11921 1.31 (1.19, 1.44) <.0001 1026/11893 1.29 (1.17, 1.43) <.0001
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HR = hazards ratio per SD increment in CFPWV. P-values <0.05 are bolded.

*

Model 2 adjusted for age, sex, current smoking status, TC/HDL cholesterol, and diabetes (or fasting blood glucose). Model 3 adjusted for systolic BP, HTN Rx, and all the variables in Model 2. The number at risk varies slightly by Model due to a few participants missing select covariates.

All models are stratified by cohort (FOS versus Gen 3). Models for death were stratified additionally by prevalent CVD status.

†

at-risk samples limited to Offspring cohort.

CKDa was defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2 or a urine albumin-to-creatinine ratio ≥30 mg/g.

CKDb was defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2.

In analyses adjusting for additional outcome-specific covariates in Model 3, the associations of CFPWV with incident hypertension, CKD (combined eGFR and UACR definition), and dementia remained robust (HR per SD increment: hypertension, 1.30, 95%CI 1.19–1.42 [adjusted for diastolic blood pressure]; CKD, 1.16, 95%CI 1.02–1.31 [adjusted for eGFR]; dementia, 1.24, 95% CI 1.02–1.50 [adjusted for education and Apo E4 allele status]). The association of CFPWV with CKD defined using reduced eGFR alone was attenuated (HR per SD 1.14, 95%CI 0.98–1.31, p=0.08).

We observed statistically significant interactions of CFPWV with age in relation to the incidence of hypertension, diabetes, CKD (defined using the reduced eGFR criterion), and stroke/TIA (Table S3). Larger effect sizes were observed for participants below age 50 for incident hypertension, diabetes, and CKD. In contrast, a stronger association with stroke/TIA was observed in those above age 50 (Figure 1).

Figure 1.

Figure 1.

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Relations of CFPWV and incidence of outcome events dichotomized by median age (50 years for analyses combining FOS and Gen3 [incidence of hypertension, diabetes, CKDb, CVD, CVD subtypes, and death]; 60 years for analyses limited to FOS [incidence of CKDa and dementia]). Hazards ratios are per SD increment in CFPWV from age-stratified models adjusting for Model 3 covariates (age, sex, current smoking status, TC/HDL cholesterol, diabetes [or fasting blood glucose, for incident diabetes], systolic blood pressure, and antihypertensive treatment). Interaction P values are from models pooling age groups. CKDa and CKDb refer to definitions of incident disease based on reduced eGFR and increased UACR versus reduced eGFR alone, respectively.

We observed a statistically significant multiplicative interaction of CFPWV with sex for the incidence of hypertension, CKD (defined using the combined reduced eGFR and increased UACR criteria), CVD, and stroke/TIA (Table S3). Sex-stratified analyses demonstrated a higher magnitude of the associations of CFPWV with stroke/TIA in women, and with hypertension, CKD, and CVD in men (Figure 2).

Figure 2.

Figure 2.

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Sex-specific relations of CFPWV and incidence of outcome events. Hazards ratios are per SD increment in CFPWV from sex-stratified models adjusting for Model 3 covariates (age, sex, current smoking status, TC/HDL cholesterol, diabetes [or fasting blood glucose, for incident diabetes], systolic blood pressure, and antihypertensive treatment). Interaction P values are from pooled sex models. CKDa and CKDb refer to definitions of incident disease based on reduced eGFR and increased UACR versus reduced eGFR alone.

Additional analyses

Table S4 provides the increment in C-statistic with the addition of CFPWV to a multivariable model, including the clinical covariates (including systolic BP) for each outcome evaluated. The incremental predictive utility of CFPWV was minimal (Table S4).

Analysis of restricted cubic splines confirmed the linearity of the associations of CFPWV with each outcome (Figure S2, Panels A–J). Figure 3 displays the rising unadjusted cumulative incidence and the age- and sex-adjusted probability of dementia (Panels A-B), CVD (Panels C-D), and all-cause mortality (Panels E-F) according to CFPWV quartiles. Figure 4 (panels A-F) displays the increasing unadjusted cumulative incidence and the age- and sex-adjusted probability of CVD subtypes, according to CFPWV quantiles. Figures 3 and 4 illustrate that the cumulative incidence (and adjusted probabilities) of outcomes was very low in the lowest quantile, but substantially higher in the top quantile.

Figure 3.

Figure 3.

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Unadjusted cumulative incidence and the age- and sex-adjusted probability of outcomes according to quartiles of CFPWV. Outcomes include dementia (Panels A, B), cardiovascular disease (CVD, Panels C, D), and death (Panels E, F).

Figure 4.

Figure 4.

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Panel A. Unadjusted cumulative incidence and age- and sex-adjusted probability of CVD subtypes according to quartiles of CFPWV. Outcomes include coronary heart disease (CHD, Panels A, B), heart failure (Panels C, D), and stroke or transient ischemic attack (Panels E, F).

Figure S3 illustrates the results of the multivariable Cox models with CFPWV quartile (or tertile) groups defined at the index examination, adjusting for Model 3 covariates. There was a consistent pattern of an elevated risk of each of the outcomes with increasing quantiles of CFPWV. We observed a linear trend of increasing risk of each outcome across CFPWV quantiles (p≤0.005 for trend for all outcome events, except for heart failure, for which the trend was borderline non-significant [p=0.08]). Table S5 shows the PAR, which ranged from 10 to 18%, for different outcome events associated with the highest quantile of CFPWV. Associations were maintained in sensitivity analysis defining CFPWV quartiles within each exam and cohort (Figure S4).

Table S6 shows results relating CFPWV residuals (adjusted for age, sex and systolic BP) to each outcome. Modeled as a continuous variable, CFPWV residuals were associated linearly with increased risk of hypertension, diabetes, CKD (defined using eGFR and UACR), CHD and all-cause mortality. Values above the median and the 75th percentile values were associated with risk of hypertension, diabetes, dementia, and all-cause mortality. CKD (defined using only eGFR), heart failure, stroke and the composite outcomes of all CVD were not associated with CFPWV residuals.

Discussion

Principal Findings

First, we observed robust and linear associations of CFPWV with several outcomes on long-term follow-up. Second, rates of incident outcome events and their age- and sex-adjusted probabilities were strikingly low in the lowest CFPWV quantile. Third, adjustment for hypertension treatment and systolic BP (Model 3) modestly attenuated several associations. However, statistical significance was maintained for all outcomes, except for heart failure (which became borderline non-significant). The incremental predictive utility of CFPWV over clinical covariates was minimal. Fourth, we observed effect modification by age (for incident hypertension, diabetes, CKD, and stroke/TIA) and sex (for incident hypertension, CKD, CVD, and stroke/TIA). The strength of CFPWV relations was directionally concordant but greater for the associations with incident hypertension, diabetes, and CKD in those below age 50. In contrast, a stronger association with stroke/TIA was observed in those above age 50; analyses of the group below age 50 were constrained by a paucity of incident stroke/TIA events. We observed stronger relations of CFPWV with stroke in women; and with hypertension, CKD, and CVD in men. Fifth, the population attributable risks associated with the top quantile of CFPWV ranged from 10 to 18% for different outcomes. Sixth, when CFPWV residuals were modeled (adjusted for age, age2, sex, systolic BP and systolic BP2) as a continuous variable, associations with hypertension, diabetes, CKD, CHD and all-cause mortality were maintained, whereas associations with CVD, heart failure and stroke were not statistically significant. Caution must be exercised in interpreting these results given bidirectional associations of CFPWV with systolic BP, and the possibility that increases of CFPWV with age may not be physiological.

In the context of the published literature

Three different meta-analyses9–11 reported robust associations of CFPWV with CVD (and its subtypes) and mortality over a median follow-up period of 6–8 years. We extend these observations over a follow-up period of twenty years, and demonstrate robust associations with additional health outcomes, including cardiometabolic disease, CKD, and dementia. Effect sizes observed for associations with CVD and mortality (HRs per SD CFPWV of 1.20 and 1.29, respectively) were consistent with two prior meta-analyses9,10 but of a lesser magnitude than that reported by a third meta-analysis11 over a much shorter duration of follow-up. Consistent with a previous meta-analysis,10 we did not observe incremental predictive utility of CFPWV for any outcome event. Notably, we observed a stronger association of CFPWV with incident CKD than previously reported.8 Multiple investigations link higher arterial stiffness indices to the development of high BP5,6,28–30 and diabetes7,31–33 on short-term follow-up (typically 5 years). Our investigation extends these observations over a longer time frame. Adjustment for systolic BP and antihypertensive medication use rendered the association with heart failure risk non-significant; these analyses were constrained by a modest number of incident heart failure events (reducing statistical power). Additionally, it can be argued that such adjustment might represent an over-adjustment, given the bidirectional relations of CFPWV with BP.

Two previous meta-analyses confirmed the longitudinal association of aortic stiffness with cognitive function and decline.34,35 However, relations of CFPWV to incident dementia have yielded inconsistent results. Some studies reported no association during short-term follow-up (5–10 years),36–38 whereas a recent investigation documented a positive association of CFPWV with long-term follow-up (15 years).39 Our findings are more consistent with the latter investigation, perhaps reflecting the need for long-term surveillance to discern the effects of arterial stiffness on dementia.

We observed effect modification by age, with a greater magnitude of association with CVD observed in people below age 50 years, consistent with two prior meta-analyses.9,10 It has been postulated10 that a ‘healthy survivor effect’, and an increasing impact of other risk factors with aging, especially systolic BP, might explain our findings.

Effect modification by sex has been less consistently observed in the literature; a stronger association of CFPWV with CVD in men was reported by the most recent meta-analysis9 but not in earlier meta-analyses.10,11 We observed stronger associations of CFPWV with hypertension, CKD, and CVD in men. Investigators have postulated that arterial stiffness measures are more correlated with standard risk factors in women (compared to men.40,41 Sex differences in aortic stiffness measures (due to dissimilarities in gene expression, extracellular matrix remodeling, and hormonal factors) may be contributory.42,43

Mechanisms underlying the observed associations

A normal aorta buffers the intermittent systemic blood flow resulting from left ventricular systolic ejection such that mean arterial pressure is well maintained throughout the arterial tree, and non-pulsatile continuous perfusion of end organs ensues. The microcirculation in nominally high-resistance vascular beds is protected against pulsatile energy by vasoconstriction of precapillary resistance arterioles. Important exceptions are low-resistance, high-flow organs (e.g., brain and kidneys), which pulsate with cardiac contraction due to the transmission of pulsatile flow and pressure into their microcirculation.44

The aorta loses its buffering action with aging because of elastin loss with cyclical stress. There is a reduced impedance mismatch between the aorta and large first-generation conduit arteries.45,46 Wave reflection sites move proximate to the microcirculation, increasing the amount of forward pressure wave and pulsatile flow that can penetrate end organ capillaries (e.g., brain) and cause tissue damage.47–49 In the kidneys, dynamic constriction of precapillary resistance vessels in response to excessive pressure pulsatility can interfere with blood flow autoregulation. Compensatory post-capillary arteriolar constriction accentuates intraglomerular hypertension and pulsatility, leading to glomerular sclerosis and renal function decline.50,51 Relatively high blood flows are also seen in the liver and the endocrine pancreas.52 Arterial stiffness, therefore, can accentuate hepatic and systemic insulin resistance via microvascular end-organ damage, a phenomenon worsened by the interaction of elastin degradation peptides and the insulin receptor.52

Increased CFPWV may be a time-integrated marker of exposure to high blood pressure.5,53 Thus, higher CFPWV could elevate CVD risk through the harmful effects of arterial pressure and flow pulsatility on the atherosclerotic process. Additionally, arterial stiffness harms the microcirculation of end-organs, translating into adverse clinical outcomes.54

Strengths and limitations

The long-term follow-up of a large ambulatory community-based sample, modeling of CFPWV and risk factors as time-varying covariates, and evaluation of several outcomes across a wide age range strengthen our investigation. However, there are several limitations. Not all participants had two CFPWV measurements. Analysis of CKD was constrained by the availability of UACR in only the FOS; we addressed this limitation by evaluating CKD defined in two different ways. We assessed multiple outcomes but did not correct for multiple statistical testing. We did not assess the incremental predictive utility of CFPWV using a range of metrics (as recommended55) or at several time points during follow-up56; additional studies are warranted to comprehensively assess the prognostic utility of CFPWV. Further, our observational findings preclude any causal inferences. Last, our sample was predominantly White, limiting generalizability of findings to other races/ethnicities. Additional studies of large multi-ethnic samples with long-term follow-up are critical to understand the extent to which our findings (based on a white cohort in Northeast US) might be valid in populations in different regions of the US and the world.

Perspectives

Increased arterial stiffness can impact function of high-flow, low-resistance organs (e.g., heart, brain, kidneys, and pancreas), which can manifest initially as subtle alterations in function. With increasing microcirculatory damage, overt cardiometabolic, cognitive, and vascular outcomes ensue. Notably optimal CFPWV over the adult lifecourse is associated with a very low risk of adverse outcomes. We have reported previously that a healthy lifestyle characterized by a healthy diet, regular exercise, the absence of smoking and excess weight, and optimal levels of BP, blood glucose, and lipids is a powerful correlate of healthy arterial aging.1 Accordingly, such healthy vascular aging during young adulthood will prevent multiple comorbidities with aging,1,48 and mitigate risk of premature death.

Supplementary Material

Supplemental Publication Material

Pathophysiological Novelty and Relevance.

What is new?

  • The robust association of CFPWV with a range of health outcomes on long-term follow-up (median 15 years, maximum 20 years) of a large community-based sample.

  • We used CFPWV and covariates as time-varying exposures, updating them at serial examinations.

What is relevant?

  • Consistency of associations of CFPWV with multiple outcomes in both sexes.

  • Associations were linear without a threshold.

Clinical and Pathophysiological Implications

  • CFPWV was associated with multiple outcomes on long-term follow-up. Individuals in the lowest quartile of CFPWV had a very low cumulative incidence of outcome events.

  • Targeting arterial stiffness (beyond lowering blood pressure) may mitigate risk of several health outcomes that may have a vascular basis.

Sources of Funding

This work was supported by contracts N01-HC-25195, HHSN268201500001I and 75N92019D00031 from the National Heart, Lung and Blood Institute (NHLBI); NHLBI grants HL080124, HL071039, HL077447, HL107385, HL126136, HL107385, HL60040, HL70100, HL131532, and R01HL134168; grants from the National Institute on Aging (R01 AG054076, R01 AG049607, R01 AG033040, R01 AG063507, RF1 AG052409, RF1 AG061872, U01 AG049505, AG058589); grant from the National Institute of Neurological Disorders and Stroke (NS017950).

Dr. Vasan is supported by the Evans Medical Foundation and the Jay and Louis Coffman Endowment from the Department of Medicine, Boston University School of Medicine.

Non-standard abbreviations

ApoƐ

Apolipoprotein E

CFPWV

Carotid-femoral pulse wave velocity

eGFR

estimated glomerular filtration rate

FHS

Framingham Heart Study

FOS

Framingham Offspring Study

Gen 3

Third Generation cohort

MAP

Mean arterial pressure

PAR

Population attributable risk

Tc

Total cholesterol concentration in blood

UACR

urine albumin to creatinine ratio

Footnotes

Disclosures

Gary F. Mitchell is the owner of Cardiovascular Engineering, Inc., a company that designs and manufactures devices that measure vascular stiffness. The company uses these devices in clinical trials that evaluate the effects of diseases and interventions on vascular stiffness. He also reports receiving grants from the National Institutes of Health and Novartis and consulting fees from Novartis, Bayer, Merck, and Servier.

The remaining authors report no conflicts.

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