Abstract
Aim: This study aims to explore the association of cumulative exposure to cardiovascular health behaviors and factors with the onset and progression of arterial stiffness.
Methods: In this study, 24,110 participants were examined from the Kailuan cohort, of which 11,527 had undergone at least two brachial-ankle pulse wave velocity (baPWV) measurements. The cumulative exposure to cardiovascular health behaviors and factors (cumCVH) was calculated as the sum of the cumCVH scores between two consecutive physical examinations, multiplied by the time interval between the two. A logistic regression model was constructed to evaluate the association of cumCVH with arterial stiffness. Generalized linear regression models were used to analyze how cumCVH affects baPWV progression. Moreover, a Cox proportional hazards regression model was used to analyze the effect of cumCVH on the risk of arterial stiffness.
Results: In this study, participants were divided into four groups, according to quartiles of cumCVH exposure levels, namely, quartile 1 (Q1), quartile 2 (Q2), quartile 3 (Q3), and quartile 4 (Q4). Logistic regression analysis showed that compared with the Q1 group, the incidence of arterial stiffness in terms of cumCVH among Q2, Q3, and Q4 groups decreased by 16%, 30%, and 39%, respectively. The results of generalized linear regression showed that compared with the Q1 group, the incidence of arterial stiffness in the Q3 and Q4 groups increased by −25.54 and −29.83, respectively. The results of Cox proportional hazards regression showed that compared with the Q1 group, the incidence of arterial stiffness in cumCVH among Q2, Q3, and Q4 groups decreased by 11%, 19%, and 22%, respectively. Sensitivity analyses showed consistency with the main results.
Conclusions: High cumCVH can delay the progression of arterial stiffness and reduce the risk of developing arterial stiffness.
See editorial vol. 31: 347-348
1.Introduction
Arterial stiffness is known to be a manifestation of large vessel aging, and the weakened buffering effect on cardiac ejection pressure after large artery hardening may cause damage to low-resistance and high-flow target organs, such as the heart, brain, and kidneys1-3), which can be a possible risk factor for cardiovascular events. Previous studies have demonstrated that aging4), hypertension5), disorders in glucose6) and lipid metabolism7), smoking8), sedentary lifestyle9), and unhealthy diet10) are risk factors for arterial stiffness. However, these studies have mainly focused on the association of a single risk factor with arterial stiffness, most of which were cross-sectional studies. Only a few studies have observed the association of the Life’s Simple 7 (LS7) score with arterial stiffness11, 12), but these studies were limited to African-Americans and Caucasians with small sample sizes.
Maintaining a healthy lifestyle is the cornerstone of preventing cardiovascular disease13, 14). Therefore, the American Heart Association (AHA) proposed seven healthy behaviors and factors in 2010 15) and the Life’s Essential 8 (LE8) in 2022 16). Related studies have revealed that ideal cardiovascular health behaviors and factors (LS7) are negatively associated with adverse cardiovascular events, including arterial stiffness11). However, there are currently no studies examining the association of LE8 with arterial stiffness. Therefore, in this study, we aim to analyze the association of the cumulative exposure score of LE8 with arterial stiffness and its progression among participants from the Kailuan study (registration no.: ChiCTR-TNRC-11001489).
2.Objects and Methods
2.1 Objects
From 2006 to 2007, Kailuan General Hospital and its 11 affiliated hospitals, which belong to the Kailuan Group, conducted the first health examination among Kailuan Group’s active and retired employees and collected relevant data. Subsequently, the participants were followed up every 2 years. In the third health examination from 2010 to 2011, some employees underwent brachial-ankle pulse wave velocity (baPWV) measurements. In this study, we examined the individuals who participated in the Kailuan Health Examination from 2006 to 2012. Inclusion criteria were as follows: (1) individuals who participated in the Kailuan Health Examination for 3 consecutive years from 2006 to 2012; (2) individuals who underwent baPWV measurement at least once after three consecutive health examinations; and (3) individuals who agreed to participate in this study and signed an informed consent form. Meanwhile, exclusion criteria were as follows: (1) subjects with missing baseline data on ideal cardiovascular health behaviors and factors; (2) eliminate atrial fibrillation occurred at baseline; and (3) subjects with low baseline ABI. This study was approved by the Kailuan General Hospital Ethics Committee and was done in accordance to the Declaration of Helsinki.
2.2 Methods
2.2.1 General Information Collection:
Questionnaire survey design and anthropometric measurement methods are detailed in the papers previously published by our research group. The general information was collected through a questionnaire survey conducted by trained professionals17). The collected information included age, gender, smoking status (“never,” “former,” and “current”), alcohol consumption, sleep duration (hours of sleep per night), physical exercise (≥ 80 minutes/week, 20–80 minutes/week, and ≤ 20 minutes/week), salt intake [light preference (＜6 g/day), moderate preference (6–12 g/day), and heavy preference (＞12 g/day)], high-fat diet (＜1 time/week, 1–3 times/week, and ＞3 times/week), tea drinking (≥ 4 times/week, 1–3 times/week, 1–3 times/month, ＜ 1/month, and never), educational level, and medication use (such as antihypertensive, antidiabetic, and lipid-lowering medications)18). During the survey, trained nurses measured the participant’s height, weight, heart rate, and blood pressure; body mass index (BMI) was also calculated as weight (kg) divided by the square of height (m2).
2.2.2 Laboratory Testing Indices:
In total, 5 ml of fasting venous blood was drawn from the elbow on the day of the physical examination to measure low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fasting blood glucose, triglycerides, uric acid, high-sensitive C-reactive protein (hs-CRP), and creatinine. Based on the observed subject’s creatinine level, the estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI formula18). All the aforementioned analyses were performed using a Hitachi automated analyzer.
2.2.3 Blood Pressure Measurement:
A standard mercury sphygmomanometer was used to measure the participants’ blood pressure at 7:00–9:00 a.m. on the day of the physical examination. The subjects were asked to sit quietly and rest for at least 5 minutes before the measurement. The systolic blood pressure and diastolic blood pressure of the right upper arm were measured using the Korotkoff’s first and fifth sounds, respectively. Three measurements were conducted with a time interval of 1–2 minutes, and the average value was thereafter calculated.
2.2.4 Measurement Method of baPWV:
The BP-203RPE III networked arterial stiffness detection device (Omron Healthcare (China) Co., Ltd.) was used to collect baPWV values. The temperature of the examination room was maintained at 22℃ to 25℃. Before measurement, the subject was instructed not to smoke and to rest for more than 5 minutes. During the measurement, the subject remained quietly lying down, with the cuff of the upper arm airbag positioned over the brachial artery and the cuff of the lower limb airbag positioned on the inside of the lower limb. Each subject was measured twice, and the data from the second measurement was taken as the final result. The larger value of baPWV from the left and right sides was analyzed in this study. Judgment criteria are as follows: baPWV ＜1,800 cm/s indicated normal arterial stiffness, while baPWV ≥ 1,800 cm/s indicated arterial sclerosis19).
2.3 Relevant Definitions
2.3.1 Definition of CVH
The LE8 score is composed of four healthy behaviors (diet, physical exercise, smoking exposure, and sleep duration) and four health factors (BMI, blood lipids, blood glucose, and blood pressure) (Supplemental Table 1). For the dietary index, since there were no corresponding items in the questionnaire, we selected those items closely related to the cardiovascular health of Chinese people including salt, tea, and high-fat diets as a substitute index for the (Dietary Approaches to Stop Hypertension) DASH-style diet7, 20-22).
Supplementary Table 1.Definition of the Life’s Essential 8 score by AHA and the criteria used in this study
| Components |
Metric |
Method of measurement |
Quantification of CVH metric |
| Health behaviors |
Diet health |
Measurement: Self-reported intake of salt, fatty foods, and tea |
Metric: |
| Examples of salt intake measurement: “What flavor do you prefer.” |
The unweighted average of salt, fatty food, and tea scoring. |
| Examples of fatty food intake measurement: “How often do you eat fatty foods?” |
Salt scoring: |
| Example of tea intake measurement: “How often do you drink tea?” |
Points Level |
|
100 ＜6 g/day |
|
50 6-12 g/day |
|
0 ＞12 g/day |
|
Fatty food scoring: |
|
Points Level |
|
100 ＜1 time/week |
|
50 1-3 times/week |
|
0 ＞3 times/week |
|
Tea scoring: |
|
Points Level |
|
100 ≥ 4 times/week |
|
75 1-3 times/week |
|
50 1-3 times/month |
|
25 ＜ 1 time/month |
|
0 Never |
| Physical activity |
Measurement: Self-reported times of physical activity per week. |
Metric: Minutes of physical activity per week. |
| Example tools for measurement: |
Scoring: |
| “How many times did you usually spend on physical activity |
Points Level |
| (note: It took at least 20 minutes each time)? ” |
100 ≥ 60 |
|
50 20-60 |
|
0 ＜20 |
| Nicotine exposure |
Measurement: Self-reported use of cigarettes |
Metric: Smoking status |
| Example tools for measurement: Do you now smoke cigarettes? |
Scoring: |
| (Never smoker, former smoker, some days, every day) |
Points Status |
|
100 Never smoker |
|
50 Former smokers quit ≥ 1 y |
|
25 Current smokers,＜ 1cigarette/d |
|
0 Current smoker, ≥ 1cigarette/d |
| Sleep health |
Measurement: Self-reported average hours of sleep per night |
Metric: Average hours of sleep per night |
| Example tools for measurement: |
Scoring: |
| “On average, how many hours of sleep do you get per night?” |
Points Level |
|
100 7 -＜9 h |
|
90 9 - ＜ 10 h |
|
70 6 - ＜ 7 h |
|
40 5 - ＜6 or ≥ 10 h |
|
20 4 - ＜5 h |
|
0 ＜4h |
| Health factors |
Body mass index |
Measurement: Body weight (kg) divided by height squared(m²) |
Metric: Body mass index (kg/m2) |
| Example tools for measurement: Objective measurement of height and weight |
Scoring: |
|
Points Level |
|
100 ＜23 |
|
75 23.0-24.9 |
|
50 25.0-29.9 |
|
25 30.0-34.9 |
|
0 ≥ 35.0 |
| Blood lipids |
Measurement: |
Metric: Non-HDL cholesterol (mmol/L) |
| Plasma total and HDL cholesterol with the calculation of non-HDL cholesterol. |
Scoring: |
| Example tools for measurement: Fasting blood sample. |
Points Level |
| non-HDL-cholesterol unit conversion: |
100 ＜3.36 |
| 1mmol/L = 38.67mg/L |
60 3.36-4.13 |
| 1mg/L = 0.02586mmol/L |
40 4.14-4.90 |
|
20 4.91-5.68 |
|
0 ≥ 5.69 |
|
If drug treated, subtract 20 points |
| Blood glucose |
Measurement: Fasting blood glucose (FBG) |
Metric: FBG (mmol/L) |
| Example tools for measurement: Fasting blood glucose sample. |
Scoring: |
| HBA1C to FBG (mg/L) to conversion: |
Points Level |
| 28.7 * A1C - 46.7 = FBG |
100 No history of diabetes with FBG ＜5.6 |
| FBG unit conversion: |
60 No diabetes with FBG 5.6-6.9 |
| 1mg = 0.056mmol/L |
40 Diabetes with FBG ＜8.6 |
| 1mmol/L = 18.02 mg/dL |
30 Diabetes with FBG 8.6-10.1 |
|
20 Diabetes with FBG 10.2-11.6 |
|
10 Diabetes with FBG 11.7-13.2 |
|
0 Diabetes with FBG ≥ 13.3 |
| Blood pressure |
Measurement: Appropriately measured systolic and diastolic blood pressure |
Metric: Systolic and diastolic blood pressure (mm Hg) |
| Example tools for measurement: Corrected Mercury sphygmomanometer |
Scoring: |
|
Points Level |
|
100 ＜120 / ＜ 80 |
|
75 120-129 / ＜ 80 |
|
50 130-139 or 80-89 |
|
25 140-159 or 90-99 |
|
0 ≥ 160 or ≥ 100 |
|
If drug treated, subtract 20 points. |
The CVH score was noted to range from 0 to 100, and the average score was calculated for each participant. To calculate the cumulative exposure score of CVH, the cumulative score (cumCVH) was defined as the product of the average of the total CVH score from two tests and the duration of consecutive follow-up years: (cumCVH)=(CVH1＋CVH2)/2×time1-2＋(CVH2＋CVH3)/2×time2-3, where, CVH1, CVH2, and CVH3 refer to the CVH scores of the study participants who attended the first, second, and third health examinations, respectively. Time1-2 and time2-3 refer to the time intervals from the first to second and second to third health examinations, respectively.
2.3.3 Definition of Outcome Events:
Arterial stiffness is defined as an initial baPWV measurement of ≥ 1,800 cm/s, whereas progression of arterial stiffness is the difference between the last follow-up baPWV measurement and the initial baPWV measurement. New-onset arterial stiffness is defined as an initial baPWV measurement of ＜1,800 cm/s and a last baPWV measurement of ≥ 1,800 cm/s23).
2.4 Statistical Analysis
Data analysis was conducted using SAS 9.4 software (SAS Institute, Cary, North Carolina). Normally distributed continuous data were presented as means±standard deviations (X±S) and were compared using analysis of variance. Nonnormally distributed continuous data were presented as medians (P25-P75) and compared using the nonparametric Kruskal–Wallis test. Categorical data were presented as frequencies and percentages, and these were compared using the χ2 test. The CVH cumulative exposure score was divided into quartiles, and a logistic regression model was constructed to examine the relationship between CVH cumulative exposure and the detection rate of arterial sclerosis. A generalized linear regression model was used to analyze the effect of CVH cumulative exposure on baPWV progression, with adjustment for age, gender, educational level, income level, alcohol consumption, heart rate, hs-CRP, eGFR, follow-up time, and the initial baPWV level. A Cox proportional hazards regression model was used to analyze the effect of different CVH cumulative exposure score groups on the risk of developing arterial sclerosis. Model 1 was adjusted for age and gender. Model 2 was adjusted for educational level, income level, alcohol consumption, heart rate, hs-CRP, eGFR, and systolic blood pressure on the basis of Model 1. Model 3 was adjusted for baseline scores in addition to Model 2. Sensitivity analysis was thereafter performed by removing each individual CVH index from the logistic regression model to observe the degree of its effect on arterial sclerosis and progression. Differences with a P-value ＜0.05 (two-tailed test) were considered to be statistically significant.
3.Results
3.1 General Characteristics of the Study Population by cumCVH Quartiles:
In total, 32,717 individuals participated in the Kailuan Health Examination for three consecutive years from 2006 to 2012 and underwent at least one baPWV measurement after the third examination was included in this study. After excluding 7,275 individuals with missing data on baseline ideal cardiovascular health behaviors and factors and 1,332 individuals with atrial fibrillation and low ABI at baseline, a total of 24,110 individuals were included in this statistical analysis. Among these 24,110 participants, 17,292 (70.80%) were male, and the baseline age was (48.54±10.96) years old. Participants were categorized into four quartile groups according to their LE8 (cumCVH) values: the first quartile group with a cumCVH score of ＜219.71 (Q1), the second quartile group with a cumCVH score between 219.71 and 252.35 (Q2), the third quartile group with a cumCVH score between 252.35 and 287.87 (Q3), and the fourth quartile group with a cumCVH score of ≥ 287.87 (Q4). As cumCVH increased, the proportion of individuals with a high school education or higher and those who never drank alcohol increased. The detection rates of arterial stiffness (baPWV ≥ 1,800 cm/s) showed a decreasing trend, which were 28.81%, 23.61%, 20.14%, and 16.24%, respectively (Table 1). At baseline, the proportion of LE8 components was low, medium, and high (Fig.1).
Table 1.Characteristic of the participants according to the cumulative exposure of CVH (
n = 24110)
|
Group of cumulative exposure of CVH |
P value
|
| Total |
Q1 |
Q2 |
Q3 |
Q4 |
| No. Of participants |
24110 |
6102 |
6103 |
6103 |
6102 |
|
| Cumulative CVH exposure score |
|
＜219.71 |
219.71-252.35 |
252.35-287.87 |
＞287.87 |
＜0.001 |
| Age, year |
48.54±10.96 |
48.35±8.75 |
48.45±10.24 |
48.82±11.45 |
48.54±12.97 |
0.014 |
| Male, N (%) |
17292 (70.8) |
5686 (93.2) |
5069 (83.1) |
4021 (65.9) |
2516 (41.2) |
＜0.001 |
| Female, N (%) |
7118 (29.2) |
416 (6.82) |
1034 (16.9) |
2082 (34.1) |
3586 (58.8) |
＜0.001 |
| Education level, N (%) |
|
|
|
|
|
＜0.001 |
| ≤ primary school |
1152 (4.72) |
310 (5.08) |
298 (4.88) |
296 (4.85) |
248 (4.05) |
|
| junior high school |
13733 (56.3) |
4032 (65.1) |
3674 (60.2) |
3325 (54.5) |
2702 (44.3) |
|
| ≥ senior high school |
9525 (39.0) |
1760 (28.8) |
2131 (34.9) |
2482 (40.7) |
3152 (51.7) |
|
| Income level, ¥/ month, N (%) |
|
|
|
|
|
＜0.001 |
| ≤ 1000 |
9989 (40.9) |
2761 (45.2) |
2591. (44.1) |
2535 (41.5) |
2002 (32.8) |
|
| 1000-5000 |
12330 (50.5) |
2899 (47.5) |
2820 (45.2) |
2950 (48.3) |
3661 (50.0) |
|
| ≥ 5000 |
2091 (8.57) |
442 (7.24) |
592 (9.70) |
518 (10.1) |
439 (7.19) |
|
| Alcohol drinking, N (%) |
|
|
|
|
|
＜0.001 |
| Never |
15044 (61.6) |
2545 (41.7) |
3391 (55.6) |
4228 (69.3) |
4880 (80.0) |
|
| Current drinker |
9234 (37.8) |
3511 (57.5) |
2667 (43.7) |
1855 (30.4) |
1201 (19.7) |
|
| temperance |
132 (0.54) |
46 (0.75) |
45 (0.74) |
20 (0.33) |
21 (0.34) |
|
| Heat rate, bpm |
72.80±9.82 |
74.74±10.40 |
72.99±9.88 |
72.20±9.43 |
71.25±9.17 |
＜0.001 |
| eGFR, mL/min |
88.04±23.55 |
82.50±20.33 |
83.52±21.88 |
88.28±23.95 |
97.84±24.60 |
＜0.001 |
| hs-CRP, mg/L |
1.00 (0.50-2.30) |
1.30 (0.60-2.90) |
1.12 (0.50-2.51) |
1.00 (0.45-2.16) |
0.82 (0.40-1.76) |
＜0.001 |
| Antidiabetic treatment, N (%) |
2554 (10.46) |
1285 (21.06) |
654 (10.72) |
399 (6.54) |
216 (3.54) |
＜0.001 |
| Antihypertensive treatment, N (%) |
3617 (14.82) |
1560 (25.57) |
928 (15.21) |
711 (11.65) |
418 (6.85) |
＜0.001 |
| Lipid-lowering treatment, N (%) |
213 (0.87) |
112 (1.84) |
42 (0.69) |
32 (0.52) |
27 (0.44) |
＜0.001 |
| BaPWV ＜1800cm/s |
19881 (77.80) |
44344 (71.19) |
4662 (76.39) |
4874 (79.86) |
5111 (83.76) |
＜0.001 |
| BaPWV ≥ 1800cm/s |
5419 (22.20) |
1758 (28.81) |
1441 (23.61) |
1229 (20.14) |
991 (16.24) |
＜0.001 |
eGFR, estimated glomerular filtration rate;BaPWV,Brachial ankle pulse wave velocity.
Model 1 was adjusted for age and gender, while Model 2 was further adjusted for educational level, income level, alcohol consumption, heart rate, hs-CRP, and eGFR. The results showed that compared with the first quartile group, the odds ratios (ORs) [95% confidence interval (CI)] of cumCVH among Q2, Q3, and Q4 groups were 0.84 (0.76,0.92), 0.70 (0.63,0.78), and 0.61 (0.54,0.69), respectively. Moreover, for every one Standard deviation(SD) increase in cumCVH exposure level, the OR (95% CI) was 0.83 (0.79,0.86). The results of Model 3 showed that compared with the first quartile group, the OR values (95% CI) of cumCVH among Q2, Q3, and Q4 groups were 0.86 (0.78,0.95), 0.73 (0.65,0.82), and 0.65 (0.57,0.75), respectively (Table 2). Arterial sclerosis events were defined by baPWV ≥ 1,400 cm/s and baPWV ≥ 1,600 cm/s (Supplemental Tables 3–4).
Table 2.Odds ratios and 95% confident intervals of bapwv in relation to quartile of cumulative exposure of CVH (N = 24110)
|
Group of cumulative exposure of CVH |
Increase the SD |
P for trend value
|
| Q1 |
Q2 |
Q3 |
Q4 |
| Packet, N (%) |
6102 |
6103 |
6103 |
6102 |
|
|
| BaPWV ≥ 1800cm/s |
1758 (28.81) |
1441 (23.61) |
1299 (20.14) |
991 (16.24) |
|
|
| Model 1 |
Ref. |
0.69 (0.63, 0.77) |
0.50 (0.45, 0.55) |
0.33 (0.30, 0.37) |
0.65 (0.62, 0.67) |
＜0.001 |
| Model 2 |
Ref. |
0.84 (0.76, 0.92) |
0.70 (0.63, 0.78) |
0.61 (0.54, 0.69) |
0.83 (0.79, 0.86) |
＜0.001 |
| Model 3 |
Ref. |
0.86 (0.78, 0.95) |
0.73 (0.65, 0.82) |
0.65 (0.57, 0.75) |
0.84 (0.80, 0.89) |
＜0.001 |
CVH: Ideal cardiovascular health; Q1: quartile 1; Q2: quartile 2; Question 3: quartile 3; Q4: quartile 4.
Model 1: adjusted for age, gender;
Model 2: adjusted for all the variables in model 1 and education level, income level, alcohol consumption, Hear rate, hs-CRP, eGFR, Systolic blood pressure;
Model 3: adjusted for all the variables in model 2 and baseline score.
Supplemental Table 3.Odds ratios and 95% confident intervals of bapwv in relation to quartile of cumulative exposure of CVH (24110)
|
Group of cumulative exposure of CVH |
Increase the SD |
P for trend value
|
| Q1 |
Q2 |
Q3 |
Q4 |
| Packet, N (%) |
6102 |
6103 |
6103 |
6102 |
|
|
| BaPWV ≥ 1400cm/s |
4756 (30.38) |
4293 (27.59) |
3726 (23.80) |
2878 (18.39) |
|
|
| Model 1 |
Ref. |
0.72 (0.66, 0.78) |
0.50 (0.46, 0.55) |
0.30 (0.28, 0.33) |
0.62 (0.60, 0.64) |
＜0.001 |
| Model 2 |
Ref. |
0.89 (0.81, 0.97) |
0.72 (0.65, 0.79) |
0.54 (0.48, 0.60) |
0.78 (0.75, 0.81) |
＜0.001 |
| Model 3 |
Ref. |
0.95 (0.86, 1.04) |
0.80 (0.72, 0.89) |
0.62 (0.55, 0.70) |
0.82 (0.78, 0.86) |
＜0.001 |
CVH: Ideal cardiovascular health; Q1: quartile 1; Q2: quartile 2; Question 3: quartile 3; Q4: quartile 4.
Model 1: adjusted for age, gender;
Model 2: adjusted for all the variables in model 1 and education level, income level, alcohol consumption, Hear rate, hs-CRP, eGFR, Systolic blood pressure;
Model 3: adjusted for all the variables in model 2 and baseline score.
Supplemental Table 4.Odds ratios and 95% confident intervals of bapwv in relation to quartile of cumulative exposure of CVH (24110)
|
Group of cumulative exposure of CVH |
Increase the SD |
P for trend value
|
| Q1 |
Q2 |
Q3 |
Q4 |
| Packet, N (%) |
6102 |
6103 |
6103 |
6102 |
|
|
| BaPWV ≥ 1600cm/s |
3066 (32.09) |
2603 (27.24) |
2206 (23.09) |
1680 (17.58) |
|
|
| Model 1 |
Ref. |
0.72 (0.66, 0.77) |
0.51 (0.47, 0.56) |
0.32 (0.29, 0.35) |
0.63 (0.61, 0.66) |
＜0.001 |
| Model 2 |
Ref. |
0.87 (0.80, 0.95) |
0.72 (0.66, 0.79) |
0.56 (0.51, 0.62) |
0.80 (0.77, 0.83) |
＜0.001 |
| Model 3 |
Ref. |
0.90 (0.83, 0.99) |
0.77 (0.69, 0.85) |
0.61 (0.54, 0.69) |
0.82 (0.78, 0.86) |
＜0.001 |
CVH: Ideal cardiovascular health; Q1: quartile 1; Q2: quartile 2; Question 3: quartile 3; Q4: quartile 4.
Model 1: adjusted for age, gender;
Model 2: adjusted for all the variables in model 1 and education level, income level, alcohol consumption, Hear rate, hs-CRP, eGFR, Systolic blood pressure;
Model 3: adjusted for all the variables in model 2 and baseline score.
The results stratified by gender and age were consistent with those of the whole population, but the reduction in the risk of arterial stiffness associated with cumCVH was more significant in females and those aged ＜60 years (Supplemental Tables 5–6).
Supplemental Table 5.Odds ratios and 95% confident intervals of bapwv in relation to quartile of cumulative exposure of CVH (N = 24110)
|
Group of cumulative exposure of CVH |
Increase the SD |
P for trend value
|
| Q1 |
Q2 |
Q3 |
Q4 |
| Female, N (%) |
416 (5.84) |
1034 (14.53) |
2082 (29.25) |
3586 (50.38) |
|
|
| BaPWV ≥ 1800 cm/s |
152 (36.54) |
257 (24.85) |
383 (18.40) |
415 (11.57) |
|
|
| Model 1 |
Ref. |
0.61 (0.46, 0.82) |
0.49 (0.37, 0.64) |
0.29 (0.22, 0.37) |
0.64 (0.59, 0.69) |
＜0.001 |
| Model 2 |
Ref. |
0.70 (0.52, 0.95) |
0.68 (0.51, 0.91) |
0.59 (0.43, 0.77) |
0.84 (0.77, 0.91) |
＜0.001 |
| Model 3 |
Ref. |
0.77 (0.56, 1.04) |
0.79 (0.59, 1.07) |
0.73 (0.53, 1.01) |
0.90 (0.82, 0.99) |
0.146 |
| Male, N (%) |
5686 (32.88) |
5069 (29.31) |
4021 (23.25) |
2516 (14.55) |
|
|
| BaPWV ≥ 1800 cm/s |
1606 (28.24) |
1184 (23.36) |
846 (21.04) |
576 (22.89) |
|
|
| Model 1 |
Ref. |
0.71 (0.65, 0.78) |
0.51 (0.46, 0.57) |
0.39 (0.34, 0.44) |
0.70 (0.68, 0.73) |
＜0.001 |
| Model 2 |
Ref. |
0.88 (0.79, 0.97) |
0.72 (0.65, 0.81) |
0.66 (0.576, 0.76) |
0.86 (0.83, 0.90) |
＜0.001 |
| Model 3 |
Ref. |
0.87 (0.78, 0.97) |
0.72 (0.63, 0.81) |
0.65 (0.56, 0.77) |
0.85 (0.81, 0.90) |
＜0.001 |
CVH: Ideal cardiovascular health; Q1: quartile 1; Q2: quartile 2; Question 3: quartile 3; Q4: quartile 4.
Model 1: adjusted for age, gender;
Model 2: adjusted for all the variables in model 1 and education level, income level, alcohol consumption, Hear rate, hs-CRP, eGFR, Systolic blood pressure;
Model 3: adjusted for all the variables in model 2 and baseline score.
Supplemental Table 6.Odds ratios and 95% confident intervals of bapwv in relation to quartile of cumulative exposure of CVH (N = 24110)
|
Group of cumulative exposure of CVH |
Increase the SD |
P for trend value
|
| Q1 |
Q2 |
Q3 |
Q4 |
| age ＜60, N (%) |
5618 (26.99) |
5314 (25.53) |
5079 (24.40) |
4806 (23.09) |
|
|
| BaPWV ≥ 1800 cm/s |
1453 (25.86) |
981 (18.46) |
649 (12.78) |
302 (6.28) |
|
|
| Model 1 |
Ref. |
0.66 (0.61, 0.73) |
0.45 (0.40, 0.50) |
0.22 (0.19, 0.25) |
0.57 (0.54, 0.59) |
＜0.001 |
| Model 2 |
Ref. |
0.87 (0.79, 0.96) |
0.74 (0.66, 0.83) |
0.52 (0.44, 0.60) |
0.79 (0.75, 0.84) |
＜0.001 |
| Model 3 |
Ref. |
0.93 (0.83, 1.03) |
0.82 (0.72, 0.93) |
0.59 (0.50, 0.71) |
0.83 (0.78, 0.89) |
＜0.001 |
| age ≥ 60, N (%) |
484 (13.47) |
789 (21.96) |
1024 (28.50) |
1296 (36.07) |
|
|
| BaPWV ≥ 1800cm/s |
305 (63.02) |
460 (58.30) |
580 (56.64) |
689 (53.16) |
|
|
| Model 1 |
Ref. |
0.82 (0.65, 1.03) |
0.76 (0.61, 0.95) |
0.66 (0.53, 0.82) |
0.84 (0.78, 0.90) |
＜0.001 |
| Model 2 |
Ref. |
0.87 (0.68, 1.11) |
0.89 (0.71, 1.13) |
0.99 (0.79, 1.26) |
1.00 (0.93, 1.08) |
0.600 |
| Model 3 |
Ref. |
0.89 (0.70, 1.15) |
0.94 (0.73, 1.21) |
1.10 (0.82, 1.43) |
1.03 (0.94, 1.13) |
0.288 |
CVH: Ideal cardiovascular health; Q1: quartile 1; Q2: quartile 2; Question 3: quartile 3; Q4: quartile 4.
Model 1: adjusted for age, gender;
Model 2: adjusted for all the variables in model 1 and education level, income level, alcohol consumption, Hear rate, hs-CRP, eGFR, Systolic blood pressure;
Model 3: adjusted for all the variables in model 2 and baseline score.
Among the 24,110 participants included in this study, 11,527 individuals underwent at least two baPWV measurements, with an average time interval of 4.28 years between the first and last measurements. The average progression of baPWV was 77.48 cm/s. After adjusting for age, gender, educational level, income level, alcohol consumption, heart rate, hs-CRP, eGFR, follow-up time, and the initial baPWV level, the results showed that the Q3 and Q4 groups increased by −25.54 (−39.42, −11.66) and −29.83(−44.54, −15.12), respectively, as compared to the Q1 group. Additionally, for each SD increase in cumCVH, the baPWV progression decreased by −15.24 (−20.72, −9.76) (Table 3). The generalized linear regression model was used to analyze the impact of cumCVH on the baPWV (Supplemental Table 2).
Table 3.Longitudinal Associations of according to quartile of cumulative exposure of CVH With Progression of Arterial Stiffness (N = 11527)
|
Packet, N (%) |
Arterial stiffness progression, cm/s per year |
| β (95% CI) |
P value
|
| Q1 |
2765 (23.99) |
Ref. |
|
| Q2 |
2630 (22.82) |
-4.54 (-18.02, 8.95) |
0.509 |
| Q3 |
2791 (24.21) |
-25.54 (-39.42, -11.66) |
＜0.01 |
| Q4 |
3341 (28.98) |
-29.83 (-44.54, -15.12) |
＜0.01 |
| Increase the SD |
11527 |
-15.24 (-20.72, -9.76) |
＜0.01 |
The model was adjusted for age, gender,education level, income level, alcohol consumption, Hear rate, hs-CRP,e GFR, first baPWV and time. β indicates regression coefficient;
Supplemental Table 2.Associations of according to quartile of cumulative exposure of CVH With Brachial ankle pulse wave velocity (24110)
|
Packet, N (%) |
Arterial stiffness progression, cm/s per year |
| β (95% CI) |
P value
|
| Q1 |
6102 (25.00) |
Ref. |
|
| Q2 |
6103 (25.00) |
-39.46 (-50.33, -28.58) |
＜0.001 |
| Q3 |
6103 (25.00) |
-87.46 (-98.72, -76.19) |
＜0.001 |
| Q4 |
6102 (25.00) |
-136.00 (-148.18, -123.82) |
＜0.001 |
| Increase the SD |
24110 |
-53.33 (-57.73, -48.93) |
＜0.001 |
The model was adjusted for age, gender, education level, income level, alcohol consumption, Hear rate, hs-CRP, eGFR. β indicates regression coefficient;
Among the 11,527 individuals who underwent at least two baPWV measurements, 7,240 had an initial baPWV measurement of ＜1,800 cm/s. Among these 7,240 participants, 1,531 (21.14%) progressed to arterial stiffness at the last measurement. Using cumCVH exposure level as the independent variable and new-onset arterial stiffness event as the dependent variable, the Cox proportional hazards regression model was employed. Model 1 was adjusted for age and gender, while Model 2 was further adjusted for educational level, income level, alcohol consumption, heart rate, hs-CRP, and eGFR. The results revealed that, compared with the first quartile group of cumCVH exposure level, the HRs (95% CIs) of cumCVH among Q2, Q3, and Q4 groups were 0.89 (0.78,1.02), 0.81 (0.70,0.94), and 0.77 (0.65,0.91), respectively. Moreover, for each SD increase in cumCVH exposure level, the HR (95% CI) was 0.97 (0.90,1.05). The results of Model 3 showed that compared with the first quartile group of cumCVH exposure level, the HRs (95% CI) of cumCVH among Q2, Q3, and Q4 groups were 1.03 (0.89,1.20), 0.96 (0.81,1.15), and 1.06 (0.86,1.31), respectively (Table 4).
Table 4.The hazard ratios of arteriosclerosis was adjusted according to cumulative CVH exposure (7240)
|
Group of cumulative exposure of CVH |
Increase the SD |
P for trend value
|
| Q1 |
Q2 |
Q3 |
Q4 |
| Packet, N (%) |
1535 |
1589 |
1776 |
2340 |
|
|
| BaPWV ≥ 1800 m/s |
482 (31.40) |
391 (24.61) |
327 (18.41) |
331 (21.62) |
|
|
| Model 1 |
Ref. |
0.74 (0.65, 0.85) |
0.59 (0.51, 0.68) |
0.45 (0.38, 0.52) |
0.84 (0.78, 0.90) |
＜0.001 |
| Model 2 |
Ref. |
0.89 (0.78, 1.02) |
0.81 (0.70, 0.94) |
0.77 (0.65, 0.91) |
0.97 (0.90, 1.05) |
＜0.001 |
| Model 3 |
Ref. |
1.03 (0.89, 1.20) |
0.96 (0.81, 1.15) |
1.06 (0.86, 1.31) |
0.77 (0.70, 0.86) |
0.823 |
CVH: Ideal cardiovascular health; Q1: quartile 1; Q2: quartile 2; Question 3: quartile 3; Q4: quartile 4.
Model 1: adjusted for age, gender;
Model 2: adjusted for all the variables in model 1 and education level, income level, alcohol consumption, Hear rate, hs-CRP, eGFR, Systolic blood pressure;
Model 3: adjusted for all the variables in model 2 and baseline score.
Sensitivity analysis was performed by sequentially excluding one risk factor from the eight indicators of the cumCVH score. The results revealed that the protective trend against arterial stiffness remained, but it could be seen that blood pressure had the greatest impact among the eight factors (Table 5).
Table 5. Odds ratios (ORs) and 95% confident intervals (95%CI) of bapwv according to the cumulative exposure of CVH after one individual cardiovascular health is removed from the total score
| Removed component |
Group of cumulative exposure of CVH |
Increase the SD |
P for trend value
|
| Q1 |
Q2 |
Q3 |
Q4 |
| Diet health |
Ref. |
0.74 (0.58, 0.96) |
0.67 (0.50, 0.88) |
0.56 (0.40, 0.77) |
0.80 (0.71, 0.90) |
＜0.001 |
| Blood pressure |
Ref. |
0.82 (0.63, 1.07) |
1.06 (0.81, 1.40) |
0.74 (0.55, 1.01) |
0.92 (0.83, 1.00) |
0.241 |
| Blood glucose |
Ref. |
0.93 (0.72, 1.21) |
0.95 (0.72, 1.25) |
0.70 (0.50, 0.98) |
0.88 (0.78, 0.99) |
＜0.001 |
| Blood lipids |
Ref. |
0.78 (0.60, 1.01) |
0.79 (0.60, 1.05) |
0.57 (0.40, 0.80) |
0.83 (0.74, 0.94) |
＜0.001 |
| Body mass index |
Ref. |
0.83 (0.64, 1.07) |
0.66 (0.50, 0.88) |
0.60 (0.43, 0.84) |
0.79 (0.70, 0.89) |
＜0.001 |
| Sleep health |
Ref. |
0.94 (0.73, 1.22) |
0.76 (0.58, 1.01) |
0.62 (0.44, 0.87) |
0.81 (0.72, 0.91) |
＜0.001 |
| Nicotine exposure |
Ref. |
1.04 (0.81, 1.34) |
0.76 (0.58, 1.00) |
0.68 (0.49, 0.94) |
0.83 (0.74, 0.93) |
＜0.001 |
| Physical activity |
Ref. |
0.92 (0.72, 1.19) |
0.80 (0.61, 1.06) |
0.56 (0.40, 0.80) |
0.82 (0.72, 0.92) |
＜0.001 |
CVH: Ideal cardiovascular health; Q1: quartile 1; Q2: quartile 2; Question 3: quartile 3; Q4: quartile 4.
Model：adjusted for age, gender, education level, income level, alcohol consumption, Hear rate, hs-CRP, eGFR, Systolic blood pressure;
4.Discussion
Our main finding is that high cumCVH exposure can delay the progression of arterial stiffness and reduce the risk of developing arterial sclerosis. This protective effect shows a dose-response relationship and is more significant in female and middle-aged to elderly populations. Among the eight factors of cumCVH, blood pressure was determined to have the greatest impact on arterial sclerosis.
In this study, we highlight how high cumCVH exposure can delay the progression of arterial stiffness. Compared with the low exposure group (Q1), the high exposure groups (Q3 and Q4) had a reduction in the progression of baPWV by 25.54 cm/s and 29.83 cm/s, respectively. Moreover, for every one SD increase (51.50) in cumCVH, baPWV progression decreased by 15.24 cm/s. Although there was no previous report of cumCVH on the progression of arterial stiffness, a 4-year follow-up study of Chinese southern populations revealed that for every 1-point increase in the ideal cardiovascular health score (LS7), baPWV progression decreased by 3.29 cm/s24). In addition, Crichton et al. found that after a 4-year follow-up, the ideal cardiovascular health (LS7) score was negatively associated with carotid-femoral pulse wave velocity (cfPWV), and the ideal score group had a cfPWV of 9.8 m/s, which was significantly lower than the poor group’s 11.7 m/s25). In healthy adults, baPWV increases by an average of 15.3–23.7 cm/s per year26-28), while in this study, as cumCVH increased by one SD, baPWV progression decreased by 15.24 cm/s. Therefore, the effect of every 50-point increase in the score is equivalent to reducing the biological age of the blood vessels by 1 year compared with the chronological age.
We not only demonstrated that high cumCVH can delay the progression of arterial stiffness but also found that high cumCVH can reduce the incidence and risk of developing arterial stiffness. Compared with the Q1 group, the Q2, Q3, and Q4 groups had a 16%, 30%, and 39% reduction in terms of the risk of developing new-onset arterial stiffness, respectively, and 11%, 19%, and 22% reduction in its incidence. A study from the United States revealed that the risk of morbidity due to arterial sclerosis increased by 30% and 68% for those with general or poor CVH scores, respectively, compared with the ideal CVH score group11). This study also validates our findings from another perspective. Another study has also showed that compared with the 0–1 CVH group, the risk of morbidity due to arterial sclerosis in the 6–7 CVH score group decreased by 83%29). Our study is different from previous studies on delaying the progression and morbidity risk of arterial sclerosis with a single health factor30-33). We not only confirmed the protective effect of cumCVH on great vessels, suggesting the important role of long-term maintenance of multiple health factors in vascular health, but also increased the risk after adjustment for baseline CVH score. We have also suggested that multiple measurements of cumCVH reduced the incidence and risk of arterial stiffness as compared to the single measurement of CVH.
In addition, we found that the protective effect of high cumCVH on arterial stiffness is gender- and age-dependent. Compared with the Q1 group, the risk of arterial stiffness in the Q4 group decreased by 41% in females and 34% in males. For each SD increase in cumCVH, the risk of arterial stiffness decreased by 16% in females and 14% in males. We also noted that the protective effect of cumCVH in terms of reducing the risk of arterial stiffness is stronger in individuals below 60 years old compared with those above 60 years old. Previous studies have also revealed that the effect of ideal CVH in reducing CVD risk is more significant in females34). We have also previously reported that the later the exposure to risk factors such as hypertension and diabetes, the lower the risk of developing CVD. Similarly, the later the exposure to high cumCVH, the smaller its protective effect on arterial stiffness. Our study suggests that ideal CVH in early life, especially in male populations, is essential to protect large blood vessels.
In addition to analyzing the effect of cumCVH on arterial stiffness, we have also conducted separate analyses and removed individual factors to assess their contribution to cumCVH’s ability to reduce the risk of arterial stiffness. The results showed that the eight factors had different contributions in terms of reducing the risk of arterial stiffness with cumCVH. Blood pressure had the most significant contribution, followed by blood glucose, while diet, sleep, and BMI had relatively small contributions. This finding is similar to the results of previous studies that examined individual factors. Compared with individuals with normal blood pressure (＜120/80 mmHg), those with stage 1 hypertension (＞130–139/80–89 mmHg) have a 148% increased risk of arterial stiffness35). Compared with individuals with normal blood glucose levels, those with elevated blood glucose levels have a 68% increased risk of arterial stiffness36). These studies suggest that we need to maintain high levels of cumCVH comprehensively and with focus to reduce the risk of arterial stiffness.
Arterial stiffness is known to be a complex pathological process, with main pathological changes including loss, rupture, denaturation, and reconstruction of elastic proteins, as well as an increase in collagen. Factors that contribute to arterial stiffness include genetics, increased activity of the local and systemic renin-angiotensin system, endothelial dysfunction, impaired endothelial NO release, inflammation, oxidative stress, etc.37-39). High cumCVH exposure can block or delay arterial stiffness through multiple pathological and physiological pathways. Previous studies have also revealed4, 5, 40-42) that exercise, Mediterranean diet, weight loss, and ideal blood pressure, blood glucose, blood lipids, and sleep duration can lower sympathetic nerve activity, improve endothelial function, decrease inflammation, and reduce oxidative stress. As per the baseline data on the population exposed to the Q4 of cumCVH, it can be determined that heart rate, which is a marker of sympathetic nervous system activity, and the inflammatory marker hs-CRP are indeed lower than those in the Q1–Q3 groups, demonstrating that high cumCVH exposure may protect large arterial vessels through these multiple pathways.
This study is based on a large-scale, long-term follow-up study of the Kailuan community in China; it aims to evaluate the association of cumCVH exposure with baPWV progression and the risk of arterial stiffness. However, this study also has some limitations. First, we calculated the progression of baPWV based on the first and last baPWV measurements of each subject. The time interval between the first and last baPWV measurements of each subject was different, which may have some impact on the results. Therefore, we corrected the time interval to reduce the impact on the results. Second, since there were no data on the amount and types of food intake in the questionnaire, salt, high-fat foods, and tea consumption obtained from the questionnaire were used as surrogate indicators of diet quality21, 22, 43). Third, the number of males was larger than that of females in the Kailuan study population. But in this study, we stratified the analysis by gender. Accordingly, the impact on the study results was deemed slight. Fourth, our study population only included individuals from the Kailuan community in northern China. In this regard, further studies are still needed to determine whether our study results are applicable to other ethnic groups and races. Last, medications for hypertension, dyslipidemia, and glucose abnormality may have been started during the observation period, which weakened the association between the cumulative exposure to cardiovascular health behaviors and factors with arterial stiffness.
In conclusion, we found that cumulative exposure to high levels of LE8 was associated with a protective effect on the progression of arterial stiffness and arterial sclerosis, and this protective effect was independent of age and gender and exhibited a dose-response relationship. Our study findings suggest that maintaining a healthy lifestyle over the long-term plays an important role in reducing baPWV progression and preventing the onset of arterial stiffness.
Conflicts of Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
References
- 1) Kong X, Ma X, Tang L, Wang Z, Li W, Cui M and Xu D: Arterial stiffness evaluated by carotid-femoral pulse wave velocity increases the risk of chronic kidney disease in a Chinese population-based cohort. Nephrology (Carlton), 2017; 22: 205-212
- 2) Boutouyrie P, Chowienczyk P, Humphrey JD and Mitchell GF: Arterial stiffness and cardiovascular risk in hypertension. Circ Res, 2021; 128: 864-886
- 3) O’Rourke MF and Nichols WW: Aortic diameter, aortic stiffness, and wave reflection increase with age and isolated systolic hypertension. Hypertension, 2005; 45: 652-658
- 4) Cecelja M and Chowienczyk P: Dissociation of aortic pulse wave velocity with risk factors for cardiovascular disease other than hypertension: A systematic review. Hypertension, 2009; 54: 1328-1336
- 5) Tedla YG, Yano Y, Carnethon M and Greenland P: Association between long-term blood pressure variability and 10-year progression in arterial stiffness: The multiethnic study of atherosclerosis. Hypertension, 2017; 69: 118-127
- 6) Pavlovska I, Kunzova S, Jakubik J, Hruskova J, Skladana M, Rivas-Serna IM, Medina-Inojosa JR, Lopez-Jimenez F, Vysoky R, Geda YE, Stokin GB and González-Rivas JP: Associations between high triglycerides and arterial stiffness in a population-based sample: Kardiovize Brno 2030 study. Lipids Health Dis, 2020; 19: 170
- 7) Liu X, Cui L, Wang A, Wang X, Song Q, Li S, Shi J, Zhao X, Chen S, Du X, Ji C, Huxley R, Guo Y and Wu S: Cumulative exposure to ideal cardiovascular health and incident diabetes in a Chinese population: The Kailuan study. J Am Heart Assoc, 2016; 5
- 8) Saz-Lara A, Martínez-Vizcaíno V, Sequí-Domínguez I, Álvarez-Bueno C, Notario-Pacheco B and Cavero-Redondo I: The effect of smoking and smoking cessation on arterial stiffness: A systematic review and meta-analysis. Eur J Cardiovasc Nurs, 2022; 21: 297-306
- 9) Endes S, Schaffner E, Caviezel S, Dratva J, Autenrieth CS, Wanner M, Martin B, Stolz D, Pons M, Turk A, Bettschart R, Schindler C, Künzli N, Probst-Hensch N and Schmidt-Trucksäss A: Long-term physical activity is associated with reduced arterial stiffness in older adults: Longitudinal results of the SAPALDIA cohort study. Age Ageing, 2016; 45: 110-115
- 10) Pase MP, Grima NA and Sarris J: The effects of dietary and nutrient interventions on arterial stiffness: A systematic review. Am J Clin Nutr, 2011; 93: 446-454
- 11) Oyenuga AO, Folsom AR, Cheng S, Tanaka H and Meyer ML: Greater adherence to Life’s simple 7 is associated with less arterial stiffness: The atherosclerosis risk in communities (ARIC) study. Am J Hypertens, 2019; 32: 769-776
- 12) Unkart JT, Allison MA, Criqui MH, McDermott MM, Wood AC, Folsom AR, Lloyd-Jones D, Rasmussen-Torvik LJ, Allen N, Burke G, Szklo M, Cushman M, McClelland RL and Wassel CL: Life’s simple 7 and peripheral artery disease: The multi-ethnic study of atherosclerosis. Am J Prev Med, 2019; 56: 262-270
- 13) Han C, Liu F, Yang X, Chen J, Li J, Cao J, Li Y, Shen C, Yu L, Liu Z, Wu X, Zhao L, Hu D, Lu X, Wu X and Gu D: Ideal cardiovascular health and incidence of atherosclerotic cardiovascular disease among Chinese adults: The China-PAR project. Sci China Life Sci, 2018; 61: 504-514
- 14) Said MA, Verweij N and van der Harst P: Associations of combined genetic and lifestyle risks with incident cardiovascular disease and diabetes in the UK Biobank study. JAMA Cardiol, 2018; 3: 693-702
- 15) Hasbani NR, Ligthart S, Brown MR, Heath AS, Bebo A, Ashley KE, Boerwinkle E, Morrison AC, Folsom AR, Aguilar D and de Vries PS: American Heart Association’s Life’s simple 7: Lifestyle recommendations, polygenic risk, and lifetime risk of coronary heart disease. Circulation, 2022; 145: 808-818
- 16) Lloyd-Jones DM, Allen NB, Anderson CAM, Black T, Brewer LC, Foraker RE, Grandner MA, Lavretsky H, Perak AM, Sharma G, Rosamond W and American Heart Association: Life’s Essential 8: Updating and enhancing the American Heart Association’s construct of cardiovascular health: A presidential advisory from the American Heart Association. Circulation, 2022; 146: e18-e43
- 17) Wu S, Huang Z, Yang X, Zhou Y, Wang A, Chen L, Zhao H, Ruan C, Wu Y, Xin A, Li K, Jin C and Cai J: Prevalence of ideal cardiovascular health and its relationship with the 4-year cardiovascular events in a northern Chinese industrial city. Circ Cardiovasc Qual Outcomes, 2012; 5: 487-493
- 18) Zheng X, Zhang R, Liu X, Zhao H, Liu H, Gao J, Wu Y and Wu S: Association between cumulative exposure to ideal cardiovascular health and arterial stiffness. Atherosclerosis, 2017; 260: 56-62
- 19) Zheng M, Zhang X, Chen S, Song Y, Zhao Q, Gao X and Wu S: Arterial stiffness preceding diabetes: A longitudinal study. Circ Res, 2020; 127: 1491-1498
- 20) Dembo R, Dertke M, La Voie L, Borders S, Washburn M and Schmeidler J: Physical abuse, sexual victimization and illicit drug use: A structural analysis among high risk adolescents. J Adolesc, 1987; 10: 13-34
- 21) Di Daniele N, Marrone G, Di Lauro M, Di Daniele F, Palazzetti D, Guerriero C and Noce A: Effects of caloric restriction diet on arterial hypertension and endothelial dysfunction. Nutrients, 2021; 13
- 22) Li CH, Yang YC, Wu JS, Huang YH, Lee CT, Lu FH and Chang CJ: Increased tea consumption is associated with decreased arterial stiffness in a Chinese population. PLOS ONE, 2014; 9: e86022
- 23) Wu S, Xu L, Wu M, Chen S, Wang Y and Tian Y: Association between triglyceride-glucose index and risk of arterial stiffness: A cohort study. Cardiovasc Diabetol, 2021; 20: 146
- 24) Sang Y, Mao K, Cao M, Wu X, Ruan L and Zhang C: Longitudinal association between cardiovascular health and arterial stiffness in the Chinese adult population. J Int Med Res, 2021; 49: 300060521998889
- 25) Crichton GE, Elias MF and Robbins MA: Cardiovascular health and arterial stiffness: The Maine-Syracuse longitudinal study. J Hum Hypertens, 2014; 28: 444-449
- 26) Kim YS, Kim DH, Choi BH, Sohn EH and Lee AY: Relationship between brachial-ankle pulse wave velocity and cognitive function in an elderly community-dwelling population with metabolic syndrome. Arch Gerontol Geriatr, 2009; 49: 176-179
- 27) Fukuhara M, Matsumura K, Ansai T, Takata Y, Sonoki K, Akifusa S, Wakisaka M, Hamasaki T, Fujisawa K, Yoshida A, Fujii K, Iida M and Takehara T: Prediction of cognitive function by arterial stiffness in the very elderly. Circ J, 2006; 70: 756-761
- 28) Alvarez-Bueno C, Cunha PG, Martinez-Vizcaino V, Pozuelo-Carrascosa DP, Visier-Alfonso ME, Jimenez-Lopez E and Cavero-Redondo I: Arterial stiffness and cognition among adults: A systematic review and meta-analysis of observational and longitudinal studies. J Am Heart Assoc, 2020; 9: e014621
- 29) Yan N, Zhou Y, Wang Y, Wang A, Yang X, Russell A, Wu S, Zhao X and Wang W: Association of ideal cardiovascular health and brachial-ankle pulse wave velocity: A cross-sectional study in Northern China. J Stroke Cerebrovasc Dis, 2016; 25: 41-48
- 30) Aatola H, Koivistoinen T, Tuominen H, Juonala M, Lehtimäki T, Viikari JSA, Raitakari OT, Kähönen M and Hutri-Kähönen N: Influence of child and adult elevated blood pressure on adult arterial stiffness: The cardiovascular risk in Young Finns Study. Hypertension, 2017; 70: 531-536
- 31) Chami HA, Isma’eel H, Mitchel GF, Tamim H, Makki M, Berbari A and Al Mulla A: The association of waterpipe smoking with arterial stiffness and wave reflection in a community-based sample. Blood Press, 2021; 30: 300-309
- 32) Lee SB, Ahn CW, Lee BK, Kang S, Nam JS, You JH, Kim MJ, Kim MK and Park JS: Association between triglyceride glucose index and arterial stiffness in Korean adults. Cardiovasc Diabetol, 2018; 17: 41
- 33) Si XB and Liu W: Relationship between blood lipid and arterial stiffness in hypertension. Clin Invest Med, 2019; 42: E47-E55
- 34) Ommerborn MJ, Blackshear CT, Hickson DA, Griswold ME, Kwatra J, Djoussé L and Clark CR: Ideal cardiovascular health and incident cardiovascular events: The Jackson Heart study. Am J Prev Med, 2016; 51: 502-506
- 35) Liu S, Wu S, Niu J, Zheng R, Bie L, Xin Z, Wang S, Lin H, Zhao Z, Li M, Wang T, Xu M, Lu J, Chen Y, Xu Y, Bi Y, Wang W, Ning G and Xu Y: The 2017 ACC/AHA stage 1 hypertension is associated with arterial stiffness: A prospective analysis. Aging (Albany, NY), 2021; 13: 10075-10086
- 36) Liu F, Yang X, Li J, Cao J, Chen J, Li Y, Liu X, Zhao L, Shen C, Yu L, Huang J and Gu D: Association of fasting glucose levels with incident atherosclerotic cardiovascular disease: An 8-year follow-up study in a Chinese population. J Diabetes, 2017; 9: 14-23
- 37) Thijssen DH, Carter SE and Green DJ: Arterial structure and function in vascular ageing: Are you as old as your arteries? J Physiol, 2016; 594: 2275-2284
- 38) Greenwald SE: Ageing of the conduit arteries. J Pathol, 2007; 211: 157-172
- 39) Zieman SJ, Melenovsky V and Kass DA: Mechanisms, pathophysiology, and therapy of arterial stiffness. Arterioscler Thromb Vasc Biol, 2005; 25: 932-943
- 40) Saz-Lara A, Lucerón-Lucas-Torres M, Mesas AE, Notario-Pacheco B, López-Gil JF and Cavero-Redondo I: Association between sleep duration and sleep quality with arterial stiffness: A systematic review and meta-analysis. Sleep Health, 2022; 8: 663-670
- 41) Higgins S, Zemel BS, Khoury PR, Urbina EM and Kindler JM: Visceral fat and arterial stiffness in youth with healthy weight, obesity, and type 2 diabetes. Pediatr Obes, 2022; 17: e12865
- 42) Jennings A, Berendsen AM, de Groot LCPGM, Feskens EJM, Brzozowska A, Sicinska E, Pietruszka B, Meunier N, Caumon E, Malpuech-Brugère C, Santoro A, Ostan R, Franceschi C, Gillings R, O’ Neill CM, Fairweather-Tait SJ, Minihane AM and Cassidy A: Mediterranean-style diet improves systolic blood pressure and arterial stiffness in older adults : Results of a 1-year European multi-center trial. Hypertension, 2019; 73: 578-586
- 43) Jin M, Miao C, An L, Guo L, Yang X, Zheng M, Hong J, Wu S and Su Q: Association between perceived salt intake and arterial stiffness. BioMed Res Int, 2022; 2022: 9072082
