Association Between Healthy and Non-Healthy Vascular Aging with Hypertensive Target Organ Damage

doi:10.21203/rs.3.rs-6259968/v1

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Association Between Healthy and Non-Healthy Vascular Aging with Hypertensive Target Organ Damage

https://doi.org/10.21203/rs.3.rs-6259968/v1

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Objective: To investigate the correlation between healthy vascular aging (HVA) and non-healthy vascular aging (NHVA) with hypertensive target organ damage (TOD).

Methods: This study included individuals from the Geriatrics Department of Ruijin Hospital in Shanghai since January 2023. Participants were divided into HVA and NHVA groups based on blood pressure and carotid-femoral pulse wave velocity (cf-PWV). HVA was defined as no history of hypertension and cf-PWV < 7.6 m/s; NHVA was defined as a history of hypertension or cf-PWV ≥ 7.6 m/s. Hypertensive TOD indicators included carotid intima-media thickness (cIMT), chronic kidney disease, albumin-to-creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), and left ventricular mass index (LVMI).

Results: A total of 1,257 participants was included in the study. After grouping by cf-PWV and blood pressure, 31.8% met the HVA criteria. Compared to the HVA group, the NHVA group was older, had more smokers, and exhibited higher levels body mass index, blood glucose, lipids, and blood pressure. The NHVA group also showed lower creatinine clearance (88.72±17.27 mL/min/1.73 m² vs. 93.41 ± 15.79 mL/min/1.73 m², p<0.001), higher LVMI (108.00 ± 26.44 g/m² vs. 92.25 ± 22.29 g/m², p < 0.001), greater cIMT (0.75 ± 0.14 mm vs. 0.70 ± 0.12 mm, p < 0.001), and higher cf-PWV (9.06 ± 1.91 m/s vs. 6.5 ± 0.74 m/s, p < 0.001). Multivariate linear regression analysis revealed significant associations between vascular aging groups and LVMI (p = 0.003) and lgACR (p=0.022). Binary stepwise logistic regression results demonstrated a significant correlation between vascular aging and LVMI (OR = 2.201, 95% CI: 1.299–3.73, p = 0.003).

Conclusion: Accelerated vascular aging is associated with cardiac and renal TOD, providing a potential target for intervention. Vascular aging shows a significant correlation with LVMI.

Healthy vascular aging

Carotid-femoral pulse wave velocity

Hypertensive target organ damage

With the exacerbation of population aging, the prevalence of cardiovascular disease has also exhibited an upward trend. Vascular aging, serving as the initial stage of cardiovascular disease, is significantly associated with adverse cardiovascular events, cardiovascular mortality, and disability[1]. As individuals age, vascular structure and function undergo degenerative alterations, culminating in vascular stiffening—a phenomenon referred to as vascular aging[2]. These modifications in vascular structure and function constitute significant independent risk factors for the onset and progression of cardiovascular events and serve as optimal indicators or surrogate endpoints for forecasting cardiovascular risk. The extent of vascular aging can be quantified through the analysis of arterial stiffness.

Pulse wave velocity (PWV) is one of the most extensively recognized and utilized assessment methodologies. Notably, carotid-femoral artery pulse wave velocity (cf-PWV) is considered the gold standard for PWV measurement and is acknowledged as a predictive and prognostic marker of cardiovascular risk[3]. An increment of one standard deviation in cf-PWV corresponds to an elevated risk of mortality and cardiovascular events, equating to a risk augmentation greater than 1.5 times that associated with a 10-year increase in age or a 10 mm Hg rise in systolic blood pressure (SBP)[4]. Vascular health in the elderly is characterized by a cf-PWV of less than 7.6 m/s, which aligns with the mean ± standard deviation of the reference population aged 30 years [5].

Healthy vascular aging (HVA) denotes the absence of hypertension and a lack of substantial increases in arterial stiffness as indicated by PWV. Research has demonstrated that HVA is correlated with a diminished incidence of cardiovascular disease in Western populations[5]. In a chinese cohort study included 11,474 participants aged ≥ 50 years concludes that HVA significantly reduces the risk of first stroke in a community-based Chinese population, suggesting that assessing vascular aging could be useful for stroke risk assessment and prevention[6]. However, the majority of studies have utilized brachial-ankle pulse wave velocity (ba-PWV) as an indicator of arterial stiffness, rather than the gold standard cf-PWV. This study categorized participants based on peripheral blood pressure and cf-PWV into two groups: HVA and non-healthy vascular aging (NHVA), to examine the impact of these conditions on target organ damage (TOD) in hypertension. HVA was defined as no history of hypertension and cf-PWV < 7.6m/s; NHVA was defined as a history of hypertension or cf-PWV ≥ 7.6 m/s.

2.1 Study population

A total of 1,257 elderly patients who underwent physical examinations and were hospitalized at the northern branch of Shanghai Ruijin Hospital between December 2017 and September 2021 was included in this study. Exclusion criteria were: (1) severe cardiovascular conditions, including acute coronary syndrome, heart failure (both acute and chronic), severe arrhythmia, myocarditis, and Marfan syndrome; (2) severe neurological disorders, such as acute stroke, traumatic brain injury, and epilepsy; (3) severe renal disease, including acute glomerulonephritis, acute renal insufficiency, and renal tumors; (4) pulmonary conditions, such as severe pulmonary hypertension, acute and chronic pulmonary embolism, pulmonary heart disease, and acute asthma attacks; (5) patients with lower extremity arterial stenosis; (6) other significant medical conditions, including severe hepatic insufficiency, pregnancy, severe anemia, thyroid disorders, and malignant tumors. This study was approved by the Ethics Committee of Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine (Approval No. 2023 − 127).

2.2 General Data Collection

The general data of all participants were systematically gathered, encompassing personal identifiers such as name, gender, and age, alongside physiological metrics such as weight, height, duration of hypertension, history of diabetes mellitus, smoking status, presence of specific diseases, medication history, and Body Mass Index (BMI). For the purpose of this study, current smokers were defined as individuals consuming more than one cigarette daily, while former smokers referred to those who had ceased smoking within the past six months.

2.3 Brachial Blood Pressure Measurement

Following a five-minute rest period in a seated position, the brachial artery blood pressure of each participant was measured three times using an electronic sphygmomanometer (model HEM907, Omron, Japan). The measurements included brachiall systolic blood pressure (SBP), brachial diastolic blood pressure (DBP), and brachial pulse pressure (bPP). The average values from these readings were then calculated for further analysis.

2.4 Laboratory Tests

Fasting blood samples were collected in the morning to measure total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), serum creatinine (Scr), and fasting blood glucose (FBG). The estimated glomerular filtration rate (eGFR) was calculated using the Chinese Simplified MDRD formula: eGFR (ml/min/1.73 m²) = 175 × Cr (mg/dl)^−1.234 × age (years old)^−0.179 × 0.79 (if female patient).This formula has been validated for use in Chinese patients with chronic kidney disease (National EGFR Project Collaboration Group, 2006). Additionally, mid-morning urine was collected on the second day of hospitalization to determine the urinary albumin-to-creatinine ratio (ACR).

2.5 Measurement of pulse wave velocity

Cf-PWV was measured using the SphygmoCor device (SphygmoCor-Px V8.0, AtCor Medical, Australia). The instrument's applanation tonometer probe was placed at the strongest pulsation of the right radial artery and femoral artery. The device automatically obtained 20 pulse waveforms for analysis, and cf-PWV value was calculated using to the distance between the sites of two pulse waves, after subtraction of the distance between the supra-sternal notch and the carotid site, and the pulse wave transit time. The measurements were repeated twice.

2.5 Measurement of left ventricular mass

Cardiac two-dimensional, M-mode, color Doppler and tissue Doppler ultrasound examination were performed by a color ultrasound diagnostic instrument. Left atrial diameter (LAD), left ventricular end-diastolic diameter (LVEDD) and left ventricular end-systolic diameter (LVEDD) were measured in the parasternal long axis view, including left ventricular end-systolic diameter (LVESD), interventricular septal thickness (IVST), and left ventricular posterior wall thickness (LVPW). Simpson method was used to calculate left atrial volume (LAV) and left ventricular ejection fraction (LVEF). Left ventricular mass (LVM) was calculated according to the following formula from which was determined left ventricular mass index (LVMI) After 3 consecutive cardiac cycles, the average value was calculated, and the left ventricular mass (LVM) was corrected according to Devereux's formula: LVM (g) = 0.8×1.04×[(IVST + LVDD + LVPWT) ³-LVDD ³] + 0.6, LVMI = LVM (g)/ body surface area, where body surface area = 0.0061× height (cm) + 0.0128× weight (kg) -0.1529.

2.6 Measurement of carotid intima-media thickness

The subjects were placed in the supine position with the neck fully exposed. Color doppler ultrasound was used to assess the presence of plaque, plaque location and number, and echo in the intima of the bilateral common carotid artery and bifurcation, internal carotid artery, external carotid artery and each main trunk and branch. Carotid intima-media thickness (cIMT) was measured on both left and right common carotid artery starting ~ 1.5 cm proximal to the carotid artery bulb. Three recordings were taken, and the mean value was calculated for each side. “Plaque = 0” referred to the absence of plaque, while “plaque = 1” referred to the presence of plaque.

2.7 Relevant Diagnostic Criteria and Grouping

2.7.1 Hypertension. Hypertension was defined as SBP ≥ 140 mmHg, and/or a diastolic blood pressure ≥ 90 mmHg, or the current use of antihypertensive medication. Diabetes was diagnosed based on a fasting plasma glucose level exceeding 7.0 mmol/L, and/or a 2-hour plasma glucose level exceeding 11.1 mmol/L during an oral glucose tolerance test, or the current use of antidiabetic medications.

2.7.2 Target Organ Damage (TOD). Indicators of TOD were: (1) LVMI: ≥115 g/m² for males and ≥ 95 g/m² for females; (2) Chronic Kidney Disease: estimated Glomerular Filtration Rate (eGFR) < 60 mL/min/1.73m² and/or Urinary Albumin-to-Creatinine Ratio(ACR) > 30mg/g;(3)cIMT ≥ 900µm(including intimal thickening and plaque). In this study, the presence of TOD was defined as the presence of any of the aforementioned indicators.

2.7.3 Population stratification. The population was stratified into two groups based on blood pressure cf-PWV: HVA and NHVA. HVA was defined as individuals with no history of hypertension and a cf-PWV < 7.6 m/s; NHVA was defined as individuals with a history of hypertension and/or a cfPWV ≥ 7.6 m/s.

3. Statistical analysis

SPSS 26.0 software package (SPSS, Chicago, IL) and Excel were used for statistical analysis. Continuous variables are expressed as mean ± SD, and frequencies (percentage) are reported for categorical variables after testing for normality Continuous and categorical variables were compared using t-test and Chi-square test respectively for males and females. To compare continuous and categorical variables between HVA and NHVA, t-test and Chi-square test respectively were used. Multivariate linear regression was conducted to compare the TOD between the HVA and NVHA groups. Multivariate binary logistic regression analysis was used on TOD of HVA and NHVA groups. A two-sided p < 0.05 was considered statistically significant.

4.1 Population characteristics

A total of 1257 patients was included in this study, with an average age of 53.13 ± 12.65 years, 807(64.2%) males, 382(30.4%) hypertensive patients taking antihypertensive treatment, 176(13.7%) diabetic patients. Table 1 shows the general basic data between male and female groups, including cardiovascular risk factors, combined clinical diseases, and indicators of TOD in hypertension. Compared with the female group, the male group was younger (52.09 ± 12.55 VS 54.99 ± 12.63 years, p < 0.001), more patients were older than 65 years (148 (18.3%), p = 0.003), and more smokers (24.7% VS 3.6%, p < 0.001). BMI (25.93 ± 3.75kg/m² VS 24.23 ± 3.93 kg/m², p < 0.001) and fasting blood glucose (5.90 ± 1.78 mmol/l VS 5.68 ± 1.87mmol/l, p = 0.064) were higher. Triglyceride was higher (2.07 ± 1.76mmol/l VS 1.62 ± 1.05mmol/l, p < 0.001), cholesterol was lower (4.69 ± 1.09mmol/l VS 4.97 ± 1.02 mmol/l, p < 0.001). Lower high density lipoprotein (1.08 ± 0.35 mmol/l VS 1.26 ± 0.29mmol/l, p < 0.001), higher low density lipoprotein (3.06 ± 0.81 mmol/l VS 3.21 ± 0.79 mmol/l, p = 0.005); Brachial diastolic blood pressure was higher (78.12 ± 11.50 mmHg VS 74.13 ± 12.35mmHg, p < 0.001), and the brachial pulse pressure was lower (53.31 ± 12.52 mmHg VS 55.12 ± 14.61mmHg, p < 0.001). Compared with asymptomatic TOD, the creatinine clearance rate of male and female patients with hypertension was higher (92.17 ± 17.55 mL/min 1.73 m² VS 86.27 ± 15.19 mL/min 1.73 m², p < 0.001). LVMI was higher (107.67 ± 26.52 g/m² VS 96.08 ± 24.60 g/m², p < 0.001). cf-PWV was higher in males (8.35 ± 1.96 m/s VS 8.06 ± 2.11 m/s, p = 0.018), and cf-PWV ≥ 7.6m/s was more common in males (492, 61.0%, p = 0.016).

Table 1

Clinical Characteristics of participants by Sex
	Overall N = 1257	Men N = 807	Women N = 450	P-Value
Age, years	53.13±12.65	52.09 ± 12.55	54.99 ± 12.63	<0.001
Smoking history,n(%)	215(17.1)	199(24.7)	16(3.6)	<0.001
Body mass index, kg/m²	25.32±3.90	25.93 ± 3.75	24.23 ± 3.93	<0.001
Hypertension, n (%)	398(31.7)	293(36.3)	105(23.3)	<0.001
Antihypertensive treatment, n (%)	382(30.4)	282(34.9)	100(22.2)	<0.001
Diabetes treatment, n (%)	176(13.7)	120(14.6)	56(12.1)	0.218
Total triglycerides, mmol/L	1.91±1.56	2.07 ± 1.76	1.62 ± 1.05	<0.001
Total cholesterol, mmol/l	4.79±1.07	4.69 ± 1.09	4.97 ± 1.02	<0.001
High-density lipoprotein, mmol/l	1.15±0.34	1.08 ± 0.35	1.26 ± 0.29	<0.001
Low density lipoprotein, mmol/l	3.12±0.81	3.06 ± 0.81	3.21 ± 0.79	0.005
Fasting plasmaglucose, mmol/l	5.82±1.81	5.90 ± 1.78	5.68 ± 1.87	0.064
Brachial SBP, mmHg	130.65±18.56	131.43 ± 17.38	129.25 ± 20.45	0.056
Brachial DBP, mmHg	76.69±11.96	78.12 ± 11.50	74.13 ± 12.35	<0.001
Heart rate ,bpm	69.25±10.39	69.20 ± 10.23	69.34 ± 10.67	0.819
Brachial pulse pressure,mmHg	53.96±13.33	53.31 ± 12.52	55.12 ± 14.61	0.027
eGFR, mL/min 1.73 m²	90.07±16.98	92.17 ± 17.55	86.27 ± 15.19	<0.001
Urinary ACR, mg/mmol	6.43±28.72	7.78 ± 34.29	3.38 ± 4.54	0.007
LVMI, g/m²	104.05±26.35	107.67 ± 26.52	96.08 ± 24.60	<0.001
cIMT, mm	0.74±0.14	0.74 ± 0.14	0.73 ± 0.12	0.095
cf-PWV m/s	8.24±2.02	8.35 ± 1.96	8.06 ± 2.11	0.018
cf-PWV ≥ 7.6 m/s	735(58.5)	492(61.0)	243(54.0)	0.016
Age>65year	262(20.8)	148(18.3)	114(25.3)	0.003
Data are means standard deviation or numbers with percentages in parentheses. Student t test and chi-squared test were conducted to compare the differences between men and women for quantitative and qualitative variables, respectively; cf-PWV, carotid femoral pulse wave velocity; eGFR, estimated glomerular filtration rate; cIMT, carotid intima-media thickness; LVMI, left ventricular mass index; ACR, urine albumin-creatinine ratio.

4.12 Healthy and Non-Healthy Vascular Aging

Table 2 shows that the total population was further divided into HVA and NHVA groups. There were 857 patients (68.2%) in NHVA group, and the average Age was older than that in HVA group (55.62 ± 12.40 years). There were 234 patients (27.3%) older than 65 years, and 583 patients (68.0%) were male. Compared with the HVA group, there were more smokers (8.8% VS 21.0%, p < 0.001) and higher BMI (25.87 ± 3.80kg/m² VS 24.13 ± 3.82 kg/m², p < 0.001). Fasting blood glucose (6.00 ± 1.94mmol/l VS 5.40 ± 1.38mmol/l, p = 0.064) and triglyceride (2.05 ± 1.75mmol/l VS1.55 ± 0.87mmol/l, p < 0.001) were higher. Cholesterol (4.76 ± 1.12mmol/l VS 4.85 ± 0.95mmol/l, p < 0.001) and high density lipoprotein (1.11 ± 0.32 mmol/l vs 1.23 ± 0.37mmol/l, p < 0.001) were lower. Lower density lipoprotein (3.10 ± 0.83mmol/l VS 3.17 ± 0.76 mmol/l, p = 0.005) and higher brachial SBP systolic (136.12 ± 17.34mmHg VS 118.93 ± 15.40mmHg, p < 0.001). Brachial DBP (79.39 ± 11.61 mmHg VS 70.92 ± 10.61mmHg, p < 0.001) and barchial pulse pressure (56.74 ± 13.56 mmHg VS 48.01 ± 10.61mmHg, p < 0.001) were higher. Compared with asymptomatic TOD, the creatinine clearance rate was lower in the two groups (88.72 ± 17.27 mL/min 1.73 m² VS 93.41 ± 15.79 mL/min 1.73 m², p < 0.001). Left ventricular hypertrophy index (108.00 ± 26.44 g/m²VS92.25 ± 22.29g/m², p < 0.001) and cIMT(0.75 ± 0.14 mmVS0.70 ± 0.12mm, p < 0.001) were higher. cf-PWV was higher (9.06 ± 1.91 m/s VS 6.5 ± 0.74 m/s, p < 0.001).

Table 2

Clinical Characteristics of participants by HVA and NHV
	Overall N = 1257	HVA N = 400	NHVA N = 857	p-Value
Age, years	53.13±12.65	47.8 ± 11.51	55.62 ± 12.40	<0.001
Age>65year	262(20.8)	28(7.0)	234(27.3)	<0.001
Sex	807(64.2)	224(56.0)	583(68.0)	<0.001
Smoking history,n(%)	215(17.1)	35(8.8)	180(21.0)	<0.001
Body mass index, kg/m²	25.32±3.90	24.13 ± 3.82	25.87 ± 3.80	<0.001
Total triglycerides, mmol/L	1.91±1.56	1.55 ± 0.87	2.05 ± 1.75	<0.001
Total cholesterol, mmol/l	4.79±1.07	4.85 ± 0.95	4.76 ± 1.12	<0.001
High-density lipoprotein, mmol/l	1.15±0.34	1.23 ± 0.37	1.11 ± 0.32	<0.001
Low density lipoprotein, mmol/l	3.12±0.81	3.17 ± 0.76	3.10 ± 0.83	0.207
Fasting plasmaglucose, mmol/l	5.82±1.81	5.40 ± 1.38	6.00 ± 1.94	<0.001
Peripheral systolic blood pressure, mmHg	130.65±18.56	118.93 ± 15.40	136.12 ± 17.34	<0.001
Peripheral diastolic pressure, mmHg	76.69±11.96	70.92 ± 10.61	79.39 ± 11.61	<0.001
Heart rate bpm	69.25±10.39	68.33 ± 10.43	69.68 ± 10.35	0.031
Peripheral pulse pressure, mmHg	53.96±13.33	48.01 ± 10.61	56.74 ± 13.56	<0.001
Creatinine clearance rate, mL/min 1.73 m²	90.07±16.98	93.41 ± 15.79	88.72 ± 17.27	<0.001
Urinary creatinine ratio rate, mg/mmol	6.43±28.72	2.83 ± 2.25	7.67 ± 33.17	<0.001
Left ventricular mass index, g/m²	104.05±26.35	92.25 ± 22.29	108.00 ± 26.44	<0.001
Carotid intima-media thickness, mm	0.74±0.14	0.70 ± 0.12	0.75 ± 0.14	<0.001
cf-PWV m/s	8.24±2.02	6.5 ± 0.74	9.06 ± 1.91	<0.001
Data are means standard deviation or numbers with percentages in parentheses. Student t test and chi-squared test were conducted to compare the differences between men and women for quantitative and qualitative variables, respectively; cf-PWV, carotid femoral pulse wave velocity. HVA, healthy vascular aging. NHVA, non-healthy vascular aging. cf-PWV, carotid femoral pulse wave velocity.

4.1.3 Target Organ Damage

Taking TOD indicators as dependent variables, both general cardiovascular risk factors and the groups of HVA versus NHVA were incorporated into a multiple linear regression model. The analysis revealed a statistically significant correlation between the two vascular aging groups and both LMVI (p = 0.003) and eGFR (p = 0.022). (Table 3)

Table 3

Multiple linear regression was used to compare the target organ damage between the healthy vascular aging group and the non-healthy vascular aging group
TOD	Factors	B	Std. Error	Beta	P-value	R²
LVMI						0.124
	Hypertension	0.662	2.315	0.013	0.775
	Smoking history	2.715	2.209	0.046	0.219
	Body mass index	0.827	0.261	0.125	0.002
	Age	0.481	0.081	0.237	<0.001
	Total triglycerides	0.412	0.724	0.022	0.569
	Low density lipoprotein	-1.984	1.158	-0.064	0.087
	Fasting plasmaglucose	0.002	0.57	0	0.997
	HVA/NHVA	8.421	2.803	0.141	0.003
cIMT						0.166
	Hypertension	0.003	0.012	0.012	0.786
	Smoking history	0.028	0.011	0.093	0.015
	Body mass index	0.003	0.001	0.081	0.041
	Age	0.004	0	0.4	<0.001
	Total triglycerides	-0.005	0.004	-0.052	0.183
	Low density lipoprotein	-0.001	0.006	-0.004	0.914
	Fasting plasmaglucose	0.004	0.003	0.053	0.166
	HVA/NHVA	0.001	0.015	0.004	0.928
lgACR						0.05
	Hypertension	-0.006	0.028	-0.011	0.835
	Smoking history	0.031	0.025	0.051	0.204
	Body mass index	-0.002	0.003	-0.026	0.535
	Age	-0.001	0.001	-0.045	0.295
	Total triglycerides	0.015	0.007	0.088	0.034
	Low density lipoprotein	0.027	0.013	0.08	0.043
	Fasting plasmaglucose	0.013	0.006	0.091	0.029
	HVA/NHVA	0.079	0.034	0.124	0.022
eGFR						0.145
	Hypertension	0.227	1.189	0.007	0.849
	Smoking history	0.466	1.276	0.011	0.715
	Body mass index	-0.067	0.132	-0.016	0.611
	Age	-0.493	0.042	-0.377	<0.001
	Total triglycerides	-0.211	0.324	-0.02	0.515
	Low density lipoprotein	-2.377	0.609	-0.117	<0.001
	Fasting plasmaglucose	0.716	0.282	0.078	0.011
	HVA/NHVA	-0.532	1.31	-0.015	0.685
HVA, healthy vascular aging. NHVA, non-healthy vascular aging. eGFR, estimated glomerular filtration rate; CIMT, carotid intima-media thickness; LVMI, left ventricular mass index; ACR, urine albumin-creatinine ratio.

In this study, binary stepwise logistic regression was used to evaluate the influence of age, gender, BMI, hypertension, fasting blood glucose, triglyceride, low-density lipoprotein, and vascular aging on TOD of patients. Logistic regression analysis showed that vascular aging was significantly associated with LVMI (OR = 2.201 [1.299–3.73], p = 0.003). (Table 4)

Table 4

Multivariate binary logistic regression analysis of healthy vascular aging group and non-healthy vascular aging group target organ damage
	Factors	p-value	OR	95% CI
eGFR
	Smoking history	0.098	2.396	0.852–6.739
	Body mass index	0.537	0.965	0.863–1.08
	Age	<0.001	1.072	1.033–1.113
	Sex	0.325	1.543	0.650–3.663
	Hypertension	0.909	0.95	0.392–2.299
	Total cholesterol	0.845	0.897	0.301–2.674
	Low density lipoprotein	0.489	1.637	0.406–6.602
	Fasting plasmaglucose	0.857	1.017	0.844–1.226
	HVA/NHVA	0.53	1.475	0.438–4.964
ACR
	Smoking history	0.684	1.103	0.688–1.77
	Body mass index	0.859	1.005	0.950–1.064
	Age	0.889	0.999	0.980–1.018
	Sex	0.546	0.852	0.506–1.434
	Hypertension	0.065	1.684	0.967–2.93
	Total cholesterol	0.512	1.124	0.793–1.595
	Low density lipoprotein	0.978	0.993	0.623–1.585
	Fasting plasmaglucose	0.008	1.14	1.035–1.256
	HVA/NHVA	0.092	1.978	0.895–4.373
LVMI
	Smoking history	0.668	0.914	0.604–1.382
	Body mass index	0.075	1.045	0.995–1.097
	Age	<0.001	1.046	1.031–1.062
	Sex	<0.001	2.158	1.460–3.191
	Hypertension	0.883	1.03	0.691–1.536
	Total cholesterol	0.524	0.847	0.509–1.411
	Low density lipoprotein	0.66	1.158	0.602–2.227
	Fasting plasmaglucose	0.874	0.992	0.901–1.093
	HVA/NHVA	0.003	2.201	1.299–3.73
HVA, healthy vascular aging. NHVA, non-healthy vascular aging. eGFR, estimated glomerular filtration rate; CIMT, carotid intima-media thickness; LVMI, left ventricular mass index; ACR, urine albumin-creatinine ratio; OR, Odds Ratio.

After grouping by cf-PWV and blood pressure, we found that 31.8% of participants met the HVA criteria. Compared with the HVA group, the NHVA group was older, with more smokers, and higher levels of BMI, blood glucose, lipids, and blood pressure. It also had elevated TOD indicators such as creatinine clearance rate, left ventricular hypertrophy, and cIMT. Multiple linear regression showed the NHVA was more correlated with the increase of LMVI and the decrease of eGFR. Binary logistic regression indicated NHVA had a higher risk of LMVI elevation (OR = 2.201 [1.299–3.73], p = 0.003).

Age, as a major risk factor for cardiovascular disease, leads to the dilation of elastic arteries, thickening and stiffening of artery walls, and decline of endothelial function even in seemingly healthy people, with differences between individuals[7]. Blood pressure is another important factor in vascular aging and a key indicator for HVA assessment. Hypertension is closely related to the increase in arterial stiffness, and the two often interact[8].Metabolic syndrome, including components such as obesity, dyslipidemia, and hyperglycemia, is closely related to vascular aging[3, 7]. The strong association between smoking and early vascular aging is well known[9, 10].Consistent with previous studies, we found that the NHVA group was higher than the HVA group in terms of age, percentage of smokers, BMI, blood glucose, lipids, and blood pressure. Management of these conventional cardiovascular risk factors may contribute to achieving HVA. It has been shown that reducing body mass, maintaining a healthy dietary pattern, and using medications to lower blood pressure and lipids can significantly reduce the increase in arterial stiffness and thus maintain HVA[11].

Although the relationship between TOD and vascular aging is not fully understood, previous studies have suggested that arterial stiffness or early vascular aging increases cardiac load, aggravates cardiac ischemia and hypoxia, increases blood pulsation transmission, and causes kidney and brain microvascular damage[12–14]. In studies based on Chinese community - dwelling populations, HVA is found to be associated with a reduced risk of first stroke[6], and on the contrary, accelerated vascular aging was associated with left ventricular diastolic dysfunction (LVDD), left ventricular hypertrophy (LVH), and micro - albuminuria (MAU) [15]. In our study, NHVA seemed to have higher risks of LMVI elevation and eGFR decline. Therefore, enhanced TOD screening and early intervention in the NHVA population may help reverse or terminate the occurrence of cardiac and renal endpoint events.

Our study attempted to use the gold standard cf-PWV as a grouping criterion to verify the association between HVA and cardiovascular disease risk. However, results from cIMT and lgACR were of little statistical significance. This may be due to the fact that there was no strict age restriction or age stratification in this study, the overall age of participants was younger than in previous studies, and the participants were mostly outpatient or inpatient patients who received more drug interventions, resulting in fewer abnormal TOD-related indicators and thus fewer positive results.

There are other limitations. First, this study is a cross-sectional correlation study, which can only confirm the correlation between HVA and cardiovascular disease risk, but cannot confirm the causal relationship between the two, and cannot avoid reverse causality. Therefore, prospective follow-up studies are needed to further verify the findings of this study. Second, results of this study referred only to Chinese population and perhaps could not be applied to other populations. Third, exercise has long been thought to be a protective factor against vascular aging. Exercise may reduce blood flow resistance in the central and peripheral vascular beds, thereby significantly reducing hypertension and reducing arterial stiffness in the clinic [16–18]. Family history of early cardiovascular disease has been significantly associated with the risk of early cardiovascular disease[19]. The above two points were not considered in this study.

In conclusion, accelerated vascular aging is related to cardiac and renal TOD, providing a potential target for intervention. A healthy lifestyle with better control of BP, body weight and metabolic profile may help to alleviate vascular aging.

Funding sources

Shanghai Municipal Health Commission 20234Y2139, Shanghai Municipal Commission of Science and Technology 23015820100.

Conflict of interest disclosure

The authors declare that they have no competing interests.

Ethics of approval statement

The study protocol was reviewed and approved by the Ethics Committee of Ruijin Hospital, Shanghai Jiaotong University School of Medicine (2023 − 127).

Author Contribution

Huijuan Chao, Qian Wang, and Yanqing Bao contributed equally to this work. Huijuan Chao and Qian Wang were involved in the conception and design of the study, data collection, and drafting of the manuscript. Yanqing Bao contributed to the data analysis and interpretation and critically revised the manuscript for important intellectual content. Yaya Bai assisted with data collection and management. Mark Butlin and Alberto Avolio provided expertise in the measurement of pulse wave velocity and critically reviewed the manuscript. Junli Zuo supervised the overall study, provided guidance on study design and interpretation of results, and approved the final version of the manuscript for submission. All authors read and approved the final manuscript.

Data availability statement

The data that support the findings of this study are available from the corresponding author, [JL Z], upon reasonable request.

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No competing interests reported.

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Association Between Healthy and Non-Healthy Vascular Aging with Hypertensive Target Organ Damage

Status:

Version 1

Abstract

Introduction

Materials and Methods

2.1 Study population

2.2 General Data Collection

2.3 Brachial Blood Pressure Measurement

2.4 Laboratory Tests

2.5 Measurement of pulse wave velocity

2.5 Measurement of left ventricular mass

2.6 Measurement of carotid intima-media thickness

2.7 Relevant Diagnostic Criteria and Grouping

3. Statistical analysis

Results

4.1 Population characteristics

4.12 Healthy and Non-Healthy Vascular Aging

4.1.3 Target Organ Damage

DISCUSSION

Declarations

Conflict of interest disclosure

Ethics of approval statement

Author Contribution

Data availability statement

References

Additional Declarations

Status:

Version 1