Abstract
Aim: Pulse wave velocity (PWV) is thought to have different relationships with metabolic syndrome (MS) components, inflammatory markers, and oxidative stress, according to age. However, age-specific determinants of PWV have not yet been studied. We investigated age-dependent relationships among PWV and MS components, inflammatory markers, and oxidative stress.
Methods: A total of 4,318 subjects were divided into 4 groups: 19–34 y (n = 687), 35–44 y (n = 1,413), 45–54 y (n = 1,384), and 55–79 y (n = 834). MS components, brachial-ankle PWV (baPWV), high-sensitivity C-reactive protein (hs-CRP), and oxidative stress markers were measured.
Results: There were age-related increases in MS, body mass index (BMI), waist circumference, systolic blood pressure (SBP), diastolic BP (DBP), triglycerides, glucose, hs-CRP, oxidized low-density lipoprotein (LDL), 8-epi-prostaglandin F2α (8-epi-PGF2α), and baPWV. BaPWV was significantly associated with sex and elevated BP in the 19–34 y group; with age, sex, BMI, elevated BP and triglycerides in the 35–44 y group; with age, sex, elevated BP, fasting glucose, hs-CRP and oxidized LDL in the 45–54 y group; and with age, BMI, elevated BP, fasting glucose and oxidized LDL in the 55–79 y group.
Conclusions: Our results show that age-related increases in baPWV are associated with age-related changes in MS components, inflammatory markers, and oxidative stress. However, each of these factors has an age-specific, different impact on arterial stiffness. In particular, oxidative stress may be independently associated with arterial stiffness in individuals older than 45 y.
Keywords: Arterial stiffness, baPWV, Metabolic syndrome, Oxidative stress
Introduction
Metabolic syndrome (MS) is a phrase that refers to a cluster of several cardiovascular risk factors, including abdominal obesity, impaired glucose tolerance, dyslipidemia, and hypertension1, 2). MS is associated with a marked increase in the risk of atherosclerotic cardiovascular disease. MS affects 24% of adults in the US and 18.8% of adults in Korea3, 4). MS and age are major risk factors for arterial stiffness, a marker of arterial damage. Moreover, oxidative stress was recently reported to be a marker of metabolic risk in the general population, and it has been suggested that it is associated with the pathogenesis underlying arterial stiffness5, 6). Increases in arterial stiffness have been associated with an increased risk of experiencing a cardiovascular event7).
Brachial ankle pulse wave velocity (baPWV) is an effective index of the arterial stiffness of large arteries that is widely used for noninvasive assessments of vascular function8). In a community-based population, baPWV has been shown to be significantly higher in asymptomatic individuals with composite coronary and carotid atherosclerotic changes, as determined by coronary CT and carotid ultrasonography, demonstrating its good diagnostic potential for atherosclerosis9). In addition, many previous studies have shown that ba-PWV is a useful marker for the management of atherosclerotic cardiovascular disease and/or its risk factors, including screening, diagnosis, prognostication, and treatment10).
It is thought that PWV may have different relationships with different MS components, inflammatory markers, and oxidative stress that may vary according to age. However, age-specific determinants of PWV have not yet been studied. Therefore, in the present study, we investigate the age-dependent relationships between pulse wave velocity and MS components, inflammatory markers, and oxidative stress.
Materials and Methods
Study Population
Study participants were recruited from a cohort of 4,336 individuals (2,174 males and 2,162 females; age range 19–79 years old) who underwent a health examination at the National Health Insurance Corporation, Ilsan Hospital, in Goyang, Korea from January 2011 to December 2015. Among these participants, 4,318 (2,165 men and 2,153 women; age range 19–79 years old) met the study criteria and were included in the final analysis. The exclusion criteria were as follows: cardiovascular disease, cancer, liver disease, renal disease, pancreatitis, or psychiatric problems; pregnancy or lactation; and drug or alcohol abuse. The aim of this study was carefully explained to all participants, and each participant provided written informed consent. The Institutional Review Board of Yonsei University and Ilsan Hospital approved the study protocol, which complied with the Declaration of Helsinki.
Definition of Metabolic Syndrome
The definition of MS was based on A Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; the National Heart, Lung, and Blood Institute; the American Heart Association; the World Heart Federation; the International Atherosclerosis Society; and the International Association for the Study of Obesity11). MS was defined as the presence of three or more of the following five criteria: waist circumference ≥ 90 cm in males and ≥ 80 cm in females (defined by the WHO Asian Region guidelines12)); triglycerides (TG) ≥ 150 mg/dL (drug treatment for elevated TGs was used as an alternate indicator); high-density lipoprotein (HDL) cholesterol < 40 mg/dL in males and < 50 mg/dL in females (drug treatment for reduced HDL cholesterol was used as an alternate indicator); systolic blood pressure (SBP) ≥ 130 mmHg or diastolic BP (DBP) ≥ 85 mmHg (antihypertensive drug treatment was used an alternate indicator); and fasting glucose ≥ 100 mg/dL (drug treatment for elevated glucose was used as an alternate indicator).
Grouping Subjects According to Age and the Presence of Metabolic Syndrome
To determine the effects of age and MS on high-sensitivity C-reactive protein (hs-CRP), oxidative stress, and baPWV, the 4,318 healthy included subjects were divided into eight subgroups based on age and the presence of MS: 19–34 years old with no MS (n = 635) and with MS (n = 52), 35–44 years old with no MS (n = 1,241) and with MS (n = 172), 45–54 years old with no MS (n = 1,087) and with MS (n = 297), and 55–79 years old with no MS (n = 548) and with MS (n = 286).
Blood Pressure and baPWV
BP was measured using a random-zero sphygmomanometer (HM-1101, Hico Medical Co., Ltd., Chiba, Japan) with an appropriately sized cuff after a rest period during which the participant was seated for at least 20 minutes. BP was measured in both arms, and the higher of the two measurements was recorded. Three BP measurements were obtained at each visit, and the difference between the three systolic BP measurements was always < 2 mmHg. The average values of the systolic and diastolic BP measurements were used. The participants were instructed not to smoke or drink alcohol for at least 30 minutes before each BP measurement. baPWV was measured using an automatic waveform analyzer (model VP-1000; Nippon Colin Ltd., Komaki, Japan) as previously described13).
Clinical and Biochemical Assessments
Detailed information regarding the clinical and biochemical assessments performed in this study are provided elsewhere14). Body weight and height were measured, and body mass index (BMI) was calculated in units of kilograms per square meter (kg/m2). Waist circumference (measured directly on the skin) was measured at the umbilical level after normal expiration using a plastic measuring tape with measurements to the nearest 0.1 cm while the subject was in an upright standing position. Blood samples were collected following an overnight fast of at least 12 hours. Fasting TGs; total, HDL, and low-density lipoprotein (LDL) cholesterol; glucose; serum hs-CRP; oxidized LDL; and LDL particle size were measured as previously described14). Plasma malondialdehyde (MDA) levels were measured from thiobarbituric acid-reactive substance (TBARS) levels using a TBARS assay kit (ZeptoMetrix Co., Buffalo, NY). The level of 8-epi-prostaglandin F2α (8-epi-PGF2α) was measured using a Urinary Isoprostane ELISA kit (Oxford Biomedical Research Inc., Rochester Hills, MI).
Statistical Analysis
All statistical analyses were performed using SPSS version 21.0 (IBM/SPSS, Chicago, IL, USA). Analysis of covariance (ANCOVA) with a Bonferroni post hoc test was used to compare differences according to age. Independent t-tests were used to compare parameters between groups with and without MS in each age group. Pearson's chi-squared tests were performed to compare MS status according to age. Linear-by-linear association tests were used to determine whether there was a linear trend between the proportion of MS and age. Pearson's correlation coefficient was used to analyze the relationships between variables. A multiple linear regression analysis was performed to identify independent predictors of baPWV across all subjects, within each age group, and among the male and female groups. In the multiple linear regression model, MS components were included as binary variables according to the absence or presence of each MS component. A logarithmic transformation was performed on skewed variables. For descriptive purposes, the mean values are presented as untransformed values. The results are expressed as the means ± standard error. A two-tailed p-value < 0.05 was considered to indicate statistical significance.
Results
MS Components, hs-CRP, Oxidative Stress, and baPWV According to Age
Table 1 shows the MS components, hs-CRP, oxidative stress, and baPWV according to the age groups after adjusting for gender distribution, smoking, and drinking. The MS proportion, waist circumference, serum TGs, serum glucose, plasma oxidized LDL, and baPWV progressively and significantly increased with age. The mean value for BMI was the lowest in the youngest group (19–34 y). SBP and DBP increased with age, although there was no significant difference between the 19–34 y group and the 35–44 y group. The mean value for HDL cholesterol was lowest in the oldest group (55–79 y). The hs-CRP level was highest in the oldest group, and the mean value in the 45–54 y group was higher than the value in the 19–34 y group. LDL particle size decreased with age, although there was no significant difference between the 19–34 y group and the 35–44 y group. The mean values for oxidative stress (urinary 8-epi-PGF2α and MDA) were higher in the 45–54 y and 55–79 y groups than in the 19–34 y and 35–44 y groups (Table 1).
Table 1. MS components, hs-CRP, oxidative stress and baPWV according to age group.
| Total (n = 4,318) |
Comparisons |
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 19–34 | 35–44 | 45–54 | 55–79 | 1–2 | 1–3 | 1–4 | 2–3 | 2–4 | 3–4 | |
| (n = 687) | (n = 1,413) | (n = 1,384) | (n = 834) | |||||||
| Age (year) | 30.0 ± 0.14 | 39.3 ± 0.08 | 49.6 ± 0.08 | 60.5 ± 0.17 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| Metabolic syndrome n (%)†, ‡ | 52 (7.6) | 172 (12.2) | 297 (21.5) | 286 (34.3) | 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| BMI (kg/m2) | 23.0 ± 0.19 | 24.1 ± 0.17 | 24.5 ± 0.15 | 24.5 ± 0.14 | < 0.001 | < 0.001 | < 0.001 | 0.438 | 0.441 | 1.000 |
| Waist (cm) | 80.7 ± 0.34 | 82.0 ± 0.22 | 83.2 ± 0.20 | 86.0 ± 0.26 | 0.002 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| Systolic BP (mmHg) | 115.7 ± 0.50 | 116.2 ± 0.36 | 119.9 ± 0.39 | 124.4 ± 0.54 | 1.000 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| Diastolic BP (mmHg) | 69.5 ± 0.39 | 70.8 ± 0.29 | 74.9 ± 0.30 | 76.8 ± 0.38 | 0.052 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.001 |
| Triglyceride (mg/dL)∮ | 92.5 ± 2.43 | 105.8 ± 1.72 | 117.8 ± 2.03 | 126.4 ± 2.58 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.001 |
| HDL cholesterol (mg/dL)∮ | 54.0 ± 0.55 | 53.7 ± 0.38 | 53.2 ± 0.39 | 51.1 ± 0.49 | 1.000 | 1.000 | < 0.001 | 1.000 | < 0.001 | 0.002 |
| Glucose (mg/dL)∮ | 88.1 ± 0.45 | 91.6 ± 0.33 | 93.7 ± 0.44 | 96.0 ± 0.59 | < 0.001 | < 0.001 | < 0.001 | 0.002 | < 0.001 | 0.001 |
| hs-CRP (mg/L)∮ | 0.89 ± 0.06 | 0.95 ± 0.05 | 1.09 ± 0.06 | 1.35 ± 0.08 | 0.489 | 0.011 | < 0.001 | 0.538 | < 0.001 | < 0.001 |
| LDL particle size (nm)∮ | 24.0 ± 0.03 | 24.0 ± 0.02 | 23.8 ± 0.02 | 23.7 ± 0.03 | 0.522 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| Oxidized LDL (U/L)∮ | 42.0 ± 1.09 | 46.3 ± 0.90 | 50.2 ± 0.85 | 53.2 ± 0.97 | 0.039 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.005 |
| 8-epi-PGF2α (pg/mg creatinine)∮ | 1489.4 ± 28.1 | 1527 ± 17.7 | 1601.4 ± 21.2 | 1669.9 ± 25.9 | 0.525 | < 0.001 | < 0.001 | 0.025 | < 0.001 | 0.055 |
| Malondialdehyde (nmol/mL)∮ | 8.05 ± 0.12 | 8.5 ± 0.09 | 9.26 ± 0.10 | 9.53 ± 0.13 | 0.143 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.384 |
| baPWV (cm/s)∮ | 1182.3 ± 5.67 | 1230.5 ± 4.07 | 1337.6 ± 5.06 | 1512.9 ± 9.44 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
Mean ± SE.
tested by logarithmic transformation. ANCOVA was used to calculate the p-values. p-values were adjusted for sex, smoking, and drinking. All alphabetical p < 0.05 were derived from Bonferroni post hoc tests; a lack of a significant differences is marked with the same letter, and significant differences are marked with a different letter.
p < 0.001, derived from Pearson's chi-squared test.
p < 0.001, derived from linear-by-linear association test.
BaPWV, hs-CRP, LDL Particle Size and Oxidative Stress According to Age, and Ms
We examined samples from obtained subjects who were aged 19 to 79 years old to determine the impact of age and MS on baPWV, hs-CRP, LDL particle size, and oxidative stress (Table 2). The baPWV values were higher in MS subjects than in non-MS subjects in all of the age groups. In the non-MS subjects, baPWV progressively and significantly increased with age. Similarly, the highest baPWV values in the MS subjects were in the oldest group (55–79 y), and the mean value for the 45–54 y group was higher than the mean values for the 19–34 y and 35–44 y groups. MS subjects had higher hs-CRP than non-MS subjects except for the 55–79 y group. In non-MS subjects, the level of hs-CRP was highest in the oldest group, and the mean value for the 45–54 y group was higher than the mean value in the 19–34 y group. However, in the MS group, there was no significant difference in hs-CRP across age groups.
Table 2. BaPWV, hs-CRP, and oxidative stress in non-MS and MS subjects according to age group.
| Non-MS (n = 3,511) | Comparisons | MS (n = 807) | Comparisons | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 19–34 | 35–44 | 45–54 | 55–79 | 1–2 | 1–3 | 1–4 | 2–3 | 2–4 | 3–4 | 19–34 | 35–44 | 45–54 | 55–79 | 1–2 | 1–3 | 1–4 | 2–3 | 2–4 | 3–4 | |
| (n = 635) | (n = 1,241) | (n = 1,087) | (n = 548) | (n = 52) | (n = 172) | (n = 297) | (n = 286) | |||||||||||||
| baPWV (cm/s)∮ | 1177.0 ± 5.81 | 1219.0 ± 4.23 | 1313.5 ± 5.29 | 1471.0 ± 11.1 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 1248.7 ± 22.1 | 1313.8 ± 11.7 | 1425.7 ± 12.2 | 1591.8 ± 16.4 | 0.204 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| hs-CRP (mg/L)∮ | 0.86 ± 0.06 | 0.88 ± 0.05 | 1.00 ± 0.07 | 1.37 ± 0.10 | 0.763 | 0.044 | < 0.001 | 0.891 | < 0.001 | < 0.001 | 1.23 ± 0.16 | 1.49 ± 0.14 | 1.40 ± 0.11 | 1.33 ± 0.09 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
| LDL particle size (nm)∮ | 24.1 ± 0.03 | 24.0 ± 0.02 | 23.9 ± 0.03 | 23.8 ± 0.03 | 1.000 | 0.002 | < 0.001 | 0.042 | < 0.001 | 0.294 | 23.3 ± 0.11 | 23.4 ± 0.06 | 23.4 ± 0.05 | 23.2 ± 0.06 | 1.000 | 1.000 | 1.000 | 1.000 | 0.193 | 0.053 |
| Oxidized LDL (U/L)∮ | 41.1 ± 1.10 | 44.8 ± 0.95 | 49.5 ± 0.95 | 51.7 ± 1.11 | 0.212 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 0.110 | 52.1 ± 4.72 | 56.0 ± 2.47 | 53.4 ± 1.91 | 57.8 ± 1.92 | 1.000 | 1.000 | 0.082 | 1.000 | 0.473 | 0.093 |
| 8-epi-PGF2∮ (pg/mg creatinine)∮ | 1487.9 ± 26.4 | 1508.1 ± 19.4 | 1569.1 ± 19.0 | 1609.8 ± 27.9 | 1.000 | 0.004 | < 0.001 | 0.027 | 0.001 | 0.838 | 1507.8 ± 179.0 | 1664.7 ± 36.9 | 1722.0 ± 70.4 | 1793.2 ± 53.6 | 0.002 | < 0.001 | < 0.001 | 1.000 | 0.197 | 0.676 |
| Malondialdehyde (nmol/mL)∮ | 8.03 ± 0.12 | 8.32 ± 0.09 | 9.03 ± 0.10 | 9.18 ± 0.14 | 0.148 | < 0.001 | < 0.001 | < 0.001 | < 0.001 | 1.000 | 8.29 ± 0.49 | 9.83 ± 0.36 | 10.2 ± 0.28 | 10.5 ± 0.26 | 0.250 | 0.028 | 0.003 | 0.812 | 0.039 | 0.675 |
Mean ± SE.
tested by logarithmic transformation. ANCOVA was used to calculate the p-values. p-values were adjusted for sex, smoking, and drinking. All alphabetical p < 0.05 were derived from Bonferroni post hoc tests; a lack of a significant differences is marked with the same letter, and significant differences are marked with a different letter.
MS subjects had smaller LDL particle sizes than non-MS subjects in all age groups. In the non-MS subjects, the 45–79 y group had smaller LDL particle sizes than were observed in the 19–44 y group. Plasma oxidized LDL, urinary 8-epi-PGF2α, and plasma MDA levels were higher in the MS subjects than in the non-MS subjects in all age groups. In the non-MS subjects, plasma oxidized LDL, urinary 8-epi-PGF2α, and plasma MDA levels were higher in the 45–79 y group than in the 19–44 y group. However, there was no significant difference in LDL particle size or plasma oxidized LDL levels among the MS groups according to age. In the MS subjects, urinary 8-epi-PGF2α levels were higher in the 35–79 y group than in the 19–34 y group, MDA levels were the highest in the oldest group, and the mean MDA level was higher in the 45–79 y group than in the 19–34 y group.
Age-specific Multiple Regression Analysis of baPWV
The Pearson's correlation analysis across all subjects showed that baPWV was positively correlated with age, MS components (waist, SBP, DBP, TGs, and glucose), inflammatory markers (hs-CRP), and oxidative stress (oxidized LDL, 8-epi-PGF2α, and MDA) and negatively correlated with LDL particle size (data not shown).
A multiple regression analysis showed that among all the included subjects, baPWV was significantly associated with age, sex, BMI, elevated BP, elevated TGs, elevated fasting glucose, hs-CRP, and oxidized LDL but was not associated with smoking, drinking, elevated waist circumference, reduced HDL cholesterol, LDL particle size, 8-epi-PGF2α, or MDA (the far-right column in Table 3).
Table 3. Age-specific multiple regression analysis of baPWV.
| Variables | 19–34 (n = 687) |
35–44 (n = 1,413) |
45–54 (n = 1,384) |
55–79 (n = 834) |
Total (n = 4,318) |
|||||
|---|---|---|---|---|---|---|---|---|---|---|
| β | p-value | β | p-value | β | p-value | β | p-value | β | p-value | |
| Age (year) | 0.007 | 0.930 | 0.155 | < 0.001 | 0.156 | < 0.001 | 0.359 | < 0.001 | 0.409 | < 0.001 |
| Sex | −0.346 | 0.001 | −0.23 | < 0.001 | −0.105 | 0.041 | −0.004 | 0.945 | −0.131 | < 0.001 |
| Smoking | −0.018 | 0.819 | 0.043 | 0.336 | −0.002 | 0.962 | −0.075 | 0.144 | 0.001 | 0.979 |
| Drinking | −0.085 | 0.277 | 0.005 | 0.899 | 0.005 | 0.896 | 0.083 | 0.118 | 0.011 | 0.626 |
| BMI (kg/m2) | 0.133 | 0.207 | 0.162 | 0.003 | 0.052 | 0.255 | 0.212 | 0.001 | 0.116 | < 0.001 |
| Elevated waist circumference | −0.003 | 0.975 | 0.008 | 0.871 | 0.062 | 0.171 | 0.010 | 0.882 | 0.036 | 0.158 |
| Elevated blood pressure | 0.179 | 0.018 | 0.309 | < 0.001 | 0.382 | < 0.001 | 0.300 | < 0.001 | 0.293 | < 0.001 |
| Elevated triglycerides | 0.092 | 0.272 | 0.111 | 0.019 | 0.018 | 0.662 | 0.029 | 0.607 | 0.051 | 0.027 |
| Reduced HDL cholesterol | −0.117 | 0.122 | −0.048 | 0.240 | 0.032 | 0.390 | 0.112 | 0.035 | 0.015 | 0.483 |
| Elevated fasting glucose | −0.001 | 0.991 | −0.006 | 0.889 | 0.132 | 0.001 | 0.160 | 0.003 | 0.077 | < 0.001 |
| hs-CRP (mg/L)∮ | 0.143 | 0.063 | 0.061 | 0.156 | 0.091 | 0.017 | 0.075 | 0.132 | 0.072 | 0.001 |
| LDL particle size (nm)∮ | −0.122 | 0.157 | −0.035 | 0.457 | −0.039 | 0.358 | −0.036 | 0.506 | −0.040 | 0.090 |
| Oxidized LDL (U/L)∮ | 0.143 | 0.065 | 0.058 | 0.153 | 0.076 | 0.039 | 0.117 | 0.018 | 0.077 | < 0.001 |
| 8-epi-PGF2α (pg/mg creatinine)∮ | −0.015 | 0.836 | −0.010 | 0.796 | 0.052 | 0.166 | −0.083 | 0.091 | −0.005 | 0.795 |
| Malondialdehyde (nmol/mL)∮ | −0.007 | 0.928 | 0.014 | 0.739 | 0.061 | 0.116 | −0.015 | 0.766 | 0.019 | 0.368 |
tested by logarithmic transformation.
β; standardized regression coefficient.
The age-specific multiple regression analysis of baPWV showed that baPWV had a significantly different relationship with each of these parameters across the age groups. For example, in the 19–34 y group, baPWV was significantly associated with sex and elevated BP, whereas in the 35–44 y group, baPWV was significantly associated with age, sex, BMI, elevated BP, and elevated TGs. Additionally, the multiple regression analysis revealed that in the 45–54 y group, baPWV was independently associated with age, sex, elevated BP, elevated fasting glucose, hs-CRP, and oxidized LDL, and in the 55–79 y group, baPWV was independently associated with age, BMI, elevated BP, reduced HDL cholesterol, elevated fasting glucose, and oxidized LDL (Table 3).
Sex-specific Multiple Regression Analysis of baPWV
When we separated the male and female subjects, the multiple regression analysis of baPWV indicated that baPWV was associated with age, BMI, elevated BP, elevated fasting glucose, hs-CRP, and oxidized LDL in both males and females (Table 4). In the female group, menopause status was significantly associated with baPWV. Among the post-menopausal female subjects (n = 686), 17 subjects were in 35–44 y group, 289 subjects were in 45–54 y group, and 380 subjects were in 55–79 y group. The mean age at menopause was 49 years old.
Table 4. Sex-specific multiple regression analysis of baPWV.
| Variables | Male (n = 2,165) |
Female (n = 2,153) |
||
|---|---|---|---|---|
| β | p-value | β | p-value | |
| Age (year) | 0.395 | < 0.001 | 0.508 | < 0.001 |
| Menopause status | - | - | 0.100 | 0.023 |
| Smoking | 0.004 | 0.878 | −0.044 | 0.147 |
| Drinking | 0.041 | 0.140 | 0.003 | 0.922 |
| BMI (kg/m2) | 0.152 | < 0.001 | 0.107 | 0.008 |
| Elevated waist circumference | 0.014 | 0.674 | 0.058 | 0.121 |
| Elevated blood pressure | 0.290 | < 0.001 | 0.316 | < 0.001 |
| Elevated triglycerides | 0.058 | 0.060 | 0.053 | 0.128 |
| Reduced HDL cholesterol | 0.017 | 0.546 | 0.006 | 0.861 |
| Elevated fasting glucose | 0.089 | 0.002 | 0.070 | 0.030 |
| hs-CRP (mg/L)∮ | 0.072 | 0.011 | 0.075 | 0.021 |
| LDL particle size (nm)∮ | −0.032 | 0.296 | −0.027 | 0.437 |
| Oxidized LDL (U/L)∮ | 0.073 | 0.009 | 0.087 | 0.007 |
| 8-epi-PGF2α (pg/mg creatinine)∮ | −0.020 | 0.465 | 0.017 | 0.560 |
| Malondialdehyde (nmol/mL)∮ | −0.009 | 0.741 | 0.060 | 0.060 |
tested by logarithmic transformation.
β; standardized regression coefficient.
Discussion
In the present study, we investigated how aging and MS influence inflammatory markers (hs-CRP), oxidative stress markers (oxidized LDL, 8-epi-PGF2α and MDA) and arterial stiffness (baPWV). Our results demonstrate that age-related increases in baPWV are associated with age-related changes in MS components, inflammatory markers, and oxidative stress. However, each of these factors had an age-specific and different impact on arterial stiffness. For example, the multiple regression analysis revealed that in the 45–54 y and 55–79 y groups, baPWV was independently and positively associated with elevated fasting glucose and oxidized LDL, whereas in the 19–34 y and 35–44 y groups, these associations were not observed.
The present results indicate an independent association between baPWV and oxidized LDL, which is consistent with the previous findings of Brinkley et al.6), who showed that elevated levels of plasma oxidized LDL, a key player in the pathogenesis of atherosclerosis, was associated with increased arterial stiffness, independent of demographics, and traditional cardiovascular disease risk factors. Oxidized LDL is recognized as a key step during the initiation and progression of atherosclerosis15), which is also associated with elevated levels of known cardiovascular disease risk factors, including BP and fasting glucose16). In the 44–54 y and 55–79 y groups in this study, elevated fasting glucose and elevated BP were also independently associated with baPWV. A limited amount of evidence suggests that oxidized LDL is associated with the development of arterial stiffness. Oxidized LDL stimulates collagen synthesis in arterial smooth muscle cells17) and promotes intimal thickening18). Additionally, oxidized LDL also induces endothelial dysfunction by impairing endothelium-dependent vasodilation, inhibiting nitric oxide bioavailability, and reducing the expression and activity of endothelial nitric oxide synthase19). All of these roles of oxidized LDL may contribute to the observed increase in arterial stiffness. Furthermore, arterial stiffness may be either directly or indirectly explained by oxidative stress-mediated cellular injury20).
The differences that were observed in arterial stiffness according to age could be partly explained by the involvement of estradiol in nitric oxide stimulation21, 22). In the present study, menopause status was independently associated with baPWV in the female group. Considering that the mean age at menopause was 49 years old in this study, the different modality in multiple regression analysis between the age groups under 45 y and over 45 y could be convincible. Indeed, there was no significant association of sex with baPWV in the subjects aged ≥ 55 years old in this study, suggesting that the differences that were observed in baPWV between males and females disappeared after menopause.
Age and BP have long been considered to be two important factors that affect baPWV8). In this study, elevated BP was a positive independent factor for baPWV in all of the age groups. The effect of elevated BP on progressive baPWV may be the result of a direct effect on arterial walls. Elevated BP may accelerate arterial stiffening, because it forces endothelial cells and arterial smooth muscle cells to be chronically exposed to the increased arterial wall dispensability, which reflects arterial stiffening8). Additionally, arterial stiffness can increase SBP, and because of the rapid PWV, the reflected wave returns during systole rather than diastole, thereby amplifying SBP even further and imposing an additional workload on the heart23, 24).
Hyperglycemia induces a large number of alterations at the cellular level in vascular tissues that can potentially accelerate the atherosclerotic process. Animal and human studies have revealed several major mechanisms that underlie most of the pathological alterations that have been observed in diabetic vasculature25). These include a hyperglycemia-mediated increase in oxidative stress that involves several pathways, the major mechanism of which appears to include the overproduction of the superoxide anion by the mitochondrial electron transport chain and the promotion of inflammation by hyperglycemia. In this study, elevated fasting glucose and oxidized LDL were positively and independently associated with baPWV in the 45–54 y and 55–79 y groups.
Several limitations of the present study should be considered. First, because this study was cross-sectional in design, we could not determine whether arterial stiffening was caused by an increase in oxidative stress or was simply a by-product of other disease processes. Second, although there is strong in vitro evidence supporting a role for oxidative stress in the development of the vascular changes that promote arterial stiffness, we could not determine how or where the oxidation occurred, nor could we identify the mechanisms by which plasma oxidative stress markers might have been related to arterial stiffness.
Despite these limitations, our results show that age-related increases in baPWV are associated with age-related changes in MS components, inflammatory markers, and oxidative stress. However, each of these factors has an age-specific and different impact on arterial stiffness. In particular, our data suggest that oxidative stress may be independently associated with arterial stiffness in subjects older than 45 y old. Hence, reducing oxidative stress is an attractive therapeutic target for preventing age-related changes in arterial structure and function and subsequent disease.
Acknowledgments
This study was funded by the Bio-Synergy Research Project (NRF-2012 M3A9C4048762) and the Mid-career Researcher Program (NRF-2016R1A2B4011662) of the Ministry of Science, ICT and Future Planning through the National Research Foundation of the Republic of Korea.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
References
- 1). Expert Panel on Detection: Executive summary of the Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA, 2001; 285: 2486-2497 [DOI] [PubMed] [Google Scholar]
- 2). Alberti KG, Zimmet P, Shaw J, IDF Epidemiology Task Force Consensus Group : The metabolic syndrome--a new worldwide definition. Lancet, 2005; 366: 1059-1062 [DOI] [PubMed] [Google Scholar]
- 3). Aguilar D, Fisher MR, O'Connor CM, Dunne MW, Muhlestein JB, Yao L, Gupta S, Benner RJ, Cook TD, Edwards D, Pfeffer MA, Investigators in the Weekly Intervention with Zithromax for Atherosclerosis and its Related Disorder study : metabolic syndrome, C-reactive protein, and prognosis in patients with established coronary artery disease. Am Heart J, 2006; 152: 298-304 [DOI] [PubMed] [Google Scholar]
- 4). Kim S-H, Ji S-H, Park Y-M, Cho K-H: The relationship of the prevalence metabolic syndrome and the difference of life style in Korean adult. Korean J Fam Pract, 2015; 5: 500-509 [Google Scholar]
- 5). Mure K, Yoshimura N, Hashimoto M, Muraki S, Oka H, Tanaka S, Kawaguchi H, Nakamura K, Akune T, Takeshita T: Urinary 8-iso-prostaglandin F2α as a marker of metabolic risks in the general Japanese population: the ROAD study. Obesity (Silver Spring), 2015; 23: 1517-1524 [DOI] [PubMed] [Google Scholar]
- 6). Brinkley TE, Nicklas BJ, Kanaya AM, Satterfield S, Lakatta EG, Simonsick EM, Sutton-Tyrrell K, Kritchevsky SB: Plasma oxidized low-density lipoprotein levels and arterial stiffness in older adults: the health, aging, and body composition study. Hypertension, 2009; 53: 846-852 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7). Vlachopoulos C, Aznaouridis K, Stefanadis C: Prediction of cardiovascular events and all-cause mortality with arterial stiffness: a systematic review and meta-analysis. J Am Coll Cardiol, 2010; 55: 1318-1327 [DOI] [PubMed] [Google Scholar]
- 8). Chen L, Zhu W, Mai L, Fang L, Ying K: The association of metabolic syndrome and its components with brachial-ankle pulse wave velocity in south China. Atherosclerosis, 2015; 240: 345-350 [DOI] [PubMed] [Google Scholar]
- 9). Joo HJ, Cho SA, Cho JY, Lee S, Park JH, Hwang SH, Hong SJ, Yu CW, Lim DS: Brachial-ankle pulse wave velocity is associated with composite carotid and coronary atherosclerosis in a middle-aged asymptomatic population. J Atheroscler Thromb, 2016; 23: 1033-1046 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10). Tomiyama H, Matsumoto C, Shiina K, Yamashina A: Brachial-ankle PWV: current status and future directions as a useful marker in the management of cardiovascular disease and/or cardiovascular risk factors. J Atheroscler Thromb, 2016; 23: 128-146 [DOI] [PubMed] [Google Scholar]
- 11). Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC, Jr, International Diabetes Federation Task Force on Epidemiology and Prevention, Hational Heart, Lung, and Blood Institute, American Heart Association, World Heart Federation, International Atherosclerosis Society, and International Association for the Study of Obesity : Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation, 2009; 120: 1640-1645 [DOI] [PubMed] [Google Scholar]
- 12). WHO Expert Consultation: Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet, 2004; 363: 157-163 [DOI] [PubMed] [Google Scholar]
- 13). Yeo HY, Kim OY, Lim HH, Kim JY, Lee JH: Association of serum lycopene and brachial-ankle pulse wave velocity with metabolic syndrome. Metabolism, 2011; 60: 537-543 [DOI] [PubMed] [Google Scholar]
- 14). Ahn HY, Kim M, Chae JS, Ahn YT, Sim JH, Choi ID, Lee SH, Lee JH: Supplementation with two probiotic strains, Lactobacillus curvatus HY7601 and Lactobacillus plantarum KY1032, reduces fasting triglycerides and enhances apolipoprotein A-V levels in non-diabetic subjects with hypertriglyceridemia. Atherosclerosis, 2015; 241: 649-656 [DOI] [PubMed] [Google Scholar]
- 15). Stocker R, Keaney JF, Jr: Role of oxidative modifications in atherosclerosis. Physiol Rev, 2004; 84: 1381-1478 [DOI] [PubMed] [Google Scholar]
- 16). Holvoet P, Stassen JM, Van Cleemput J, Collen D, Vanhaecke J: Oxidized low density lipoproteins in patients with transplant-associated coronary artery disease. Arterioscler Thromb Vasc Biol, 1998; 18: 100-107 [DOI] [PubMed] [Google Scholar]
- 17). Jimi S, Saku K, Uesugi N, Sakata N, Takebayashi S: Oxidized low density lipoprotein stimulates collagen production in cultured arterial smooth muscle cells. Atherosclerosis, 1995; 116: 15-26 [DOI] [PubMed] [Google Scholar]
- 18). Matthys KE, Van Hove CE, Kockx MM, Andries LJ, Van Osselaer N, Herman AG, Bult H: Local application of LDL promotes intimal thickening in the collared carotid artery of the rabbit. Arterioscler Thromb Vasc Biol, 1997; 17: 2423-2429 [DOI] [PubMed] [Google Scholar]
- 19). Michell BJ, Chen ZP, Tiganis T, Stapleton D, Katsis F, Power DA, Sim AT, Kemp BE: Coordinated control of endothelial nitric-oxide synthase phosphorylation by protein kinase C and the cAMP-dependent protein kinase. J Biol Chem, 2001; 276: 17625-17628 [DOI] [PubMed] [Google Scholar]
- 20). de Faria AP, Fontana V, Modolo R, Barbaro NR, Sabbatini AR, Pansani IF, Ferreira-Melo SE, Moreno H: Plasma 8-isoprostane levels are associated with endothelial dysfunction in resistant hypertension. Clin Chim Acta, 2014; 433: 179-183 [DOI] [PubMed] [Google Scholar]
- 21). Landmesser U, Drexler H: Endothelial function and hypertension. Curr Opin Cardiol, 2007; 22: 316-320 [DOI] [PubMed] [Google Scholar]
- 22). Michel T, Vanhoutte PM: Cellular signaling and NO production. Pflugers Arch, 2010; 459: 807-816 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23). Dao HH, Essalihi R, Bouvet C, Moreau P: Evolution and modulation of age-related medial elastocalcinosis: impact on large artery stiffness and isolated systolic hypertension. Cardiovasc Res, 2005; 66: 307-317 [DOI] [PubMed] [Google Scholar]
- 24). O'Rourke MF, Hashimoto J: Mechanical factors in arterial aging: a clinical perspective. J Am Coll Cardiol, 2007; 50: 1-13 [DOI] [PubMed] [Google Scholar]
- 25). Aronson D: Hyperglycemia and the pathobiology of diabetic complications. Adv Cardiol, 2008; 45: 1-16 [DOI] [PubMed] [Google Scholar]