2024 年 31 巻 5 号 p. 626-640
Aim: The concept of risk age may help overcome an excessive weight of age in cardiovascular risk functions. This study aimed to evaluate the equivalence of risk age with arterial stiffness by comparing people with increased risk age and individuals with the same chronological and risk age. In order to materialize this aim, we categorized individuals based on cardiovascular risk and compared groups with increased risk factors (other than age) and groups with normal levels.
Methods: This is a cross-sectional population-level study carried out in Girona province within the context of the REGICOR study (Girona Heart Registry). In this study, individuals aged 35–90 years who had a brachial–ankle pulse wave velocity measurement and with no previous cardiovascular disease or peripheral arterial disease were included. Cardiovascular risk was estimated with the FRESCO (in 35–79 year-olds), SCORE2 (in 35–69 year-olds), and SCORE2-OP (in 70–90 year-olds) functions and categorized to calculate and compare (in each category) the median chronological age in the group with increased risk factors and the reference. Arterial stiffness was assessed with the brachial–ankle pulse wave velocity (baPWV). The analyses were carried out separately by sex.
Results: In this study, 2499 individuals were included, with a mean age of 59.7 and 46.9% of men. Men presented worse health condition, including a higher mean cardiovascular disease risk score. Both men and women with increased levels of risk factors showed worse health condition than the respective men and women with optimal levels. In each risk category, the groups with higher risk age than chronological age (increased risk factors) were similar in baPWV values to the groups with the same chronological and risk ages (reference), who were consistently older.
Conclusions: In categories with the same cardiovascular risk, the arterial stiffness of participants with a higher risk factor burden (increased risk age) matched that of older participants with the rest of the risk factors at optimal levels (same chronological and risk age). These results support the guidelines on the utilization of risk age to explain heightened cardiovascular risk, particularly among individuals in middle age.
Lia Alves-Cabratosa and Marc Elosua-Bayés contributed equally to this work.
Rafel Ramos and Jaume Marrugat are joint senior authors.
Despite improvements in management and preventive efforts, cardiovascular (CV) diseases are still a major cause of morbidity and mortality globally1). CV disease prevention involves risk factor assessment, which can be integrated via risk prediction functions to calculate an individual score. Nevertheless, the estimation of overall cardiovascular risk with risk functions has certain limitations, such as the contribution of age. The weight of age could be sufficient to yield a high score in elderly people without any other CV risk factor (CVRF). The opposite could apply to young people and lead to risk underestimation. They could have increased levels of risk factors and be at low absolute risk2). Accordingly, preventive measures and treatments may be omitted in this population while they accumulate a masked excess of risk.
The concept of risk age aims to address this limitation. In individuals with the same CV risk score, the risk age of a person with CVRFs corresponds to the age of an older person with optimal risk factors2). Based on this definition, people with adequate levels of CVRFs would have the same chronological and risk age; however, those with increased levels would have a higher risk age than their chronological age. Risk age is one of the indicators suggested by the European CV prevention guidelines to represent 10-year CV risk to the general population2). This communication strategy has proven fruitful in raising patient self-awareness and inducing behavioral changes toward better CV health3).
The pathological bases upon which CVRFs play their role involve arterial damage, which includes arteriosclerosis and atherosclerosis components4, 5). This process starts early in life and has a long asymptomatic phase. The CV risk should, therefore, reflect the state of the arterial tree, which can be studied using simple and noninvasive techniques that measure arterial stiffness, such as pulse wave velocity6, 7). The arteries in people with higher CV risk scores would presumably be more damaged than those in individuals with lower scores. However, this may not always be the case, especially for the younger population, in whom risk age could help explain their arterial state8). Still, when individuals with CV risk factors and a certain risk score have a particular risk age, it is assumed that the state of their arteries is similar to that of older people with no CVRFs (other than age) and the same risk score. In other words, we presume that because of their risk factors, the state of their arteries resembles that of older people. However, whether the risk age construct accurately represents arterial condition, arterial stiffness, in particular, is still yet to be confirmed.
This study aimed to evaluate the equivalence between cardiovascular risk age and arterial stiffness as a measure of subclinical damage. To this end, we aimed to determine whether the arterial stiffness of people with increased risk factors corresponded to that of older people with the rest of the risk factors at optimal levels, in individuals with the same CV risk score.
We conducted a cross-sectional analysis in the context of the REGICOR (REgistre GIroní del COR; which stands for Girona Heart Registry) study. In the REGICOR study, those living in the city of Girona and three surrounding rural villages were randomly selected from the nearest census, invited to participate, and examined from 2003 to 2006, with a second follow-up visit between 2007 and 2013 9). In this study, recruited participants had lived in the referral area for at least 6 months before the first visit. Those with terminal diseases or institutionalized at the time of the appointment were ineligible for the study. Eligible individuals were those who had attended both visits, ranging from 35 to 90 years old, a brachial–ankle pulse wave velocity (baPWV) assessment on record, and no previous self-reported CV disease (myocardial infarction, angina pectoris, and stroke) or presence of peripheral arterial disease (PAD) defined as an ankle–brachial index ≤ 0.9 because stenosis in the lower limb arteries would be suspected. Stenotic lesions affect the arterial diameter and the PWV depends on arterial stiffness and also on arterial diameter10); thus, the PWV measurement in patients with PAD could be inaccurate and confuse the interpretation of the results11, 12).
VariablesUsing standardized methods, homologated devices, and validated questionnaires as previously described, trained nurses performed the examinations and interviews13). Arterial stiffness was assessed with the baPWV, using the following equation, where tba is the time interval between the arm and ankle waves obtained with a VaSera device14):
baPWV=(0.5934 * height (cm)＋14.4724)/tba15).
We estimated the 10-year CV risk by sex applying various risk functions, as a consistency analysis. We utilized the FRESCO risk function, which has been specifically validated in the Spanish population and also the SCORE2 and SCORE2-OP risk functions, recently validated in the European population. The FRESCO function considers the following variables: age, smoking habit, diabetes mellitus, systolic blood pressure (BP), total cholesterol, high-density lipoprotein cholesterol (HDL-C), and systolic BP values while receiving hypertension treatment; it assesses the risk of developing coronary and cerebrovascular disease in individuals aged 35–79 years16). Both the SCORE2 and the SCORE2-OP consider age, smoking habits, diabetes mellitus, SBP, and total and HDL-C and assess the risk of developing CV disease (defined as a composite of cardiovascular mortality, non-fatal myocardial infarction, and non-fatal stroke)17, 18). The SCORE2 applies to people aged 35–69 years18), and the SCORE2-OP to people aged over 70 years17).
Sociodemographic variables, smoking (current smokers, former smokers [quit smoking ＞1 year], or never smokers), and history of high BP, diabetes, hypercholesterolemia, and corresponding treatments were recorded and blood samples were obtained. Using a calibrated oscillometric sphygmomanometer (OMRON M6, HEM-7001-E), BP was assessed twice; when the measurements differed by more than 5 mmHg, a third was taken and the mean of the last two assessments was recorded. Brachial pulse pressure was the difference between the mean systolic and diastolic BP. We also measured weight, height, body mass index (BMI), and waist circumference. Blood samples were obtained after 10–14 h of fasting. Total cholesterol, HDL-C, triglycerides, and glucose levels were determined via direct methodology (Roche Diagnostics, Basel, Switzerland). Using the Friedewald equation, low-density lipoprotein cholesterol was determined when triglycerides were lower than 400 mg/dL (＜3.4 mmol/L)19).
Hypertension was considered when BP measurements presented systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg, the participant was receiving antihypertensive treatment, or the participant had been previously diagnosed with the condition. Diabetes was considered when participants reported a previous diabetes diagnosis, received treatment for it, or when fasting glucose concentration was ≥ 126 mg/dL.
Statistical AnalysesFor analysis, we divided the population into two groups. The group with increased risk factors comprised individuals with altered levels of the risk factors included in the CV risk functions; the reference group included those with all the considered risk factors (except age) at optimal levels; both groups were categorized by risk—using the CV risk functions—and sex. The optimal values for the CV risk functions that determined the allocation of participants in the reference group were the same for all the analyzed risk functions: no smoking habit, no diabetes mellitus, SBP ＜120 mmHg20), total cholesterol ＜155 mmHg21), HDL-C ＜55 mg/dL in women, and HDL-C ＜45 mg/dL in men22, 23).
We described the characteristics of the participating men and women for each group (increased risk factors and reference). Continuous variables were presented as mean (standard deviation) or median [first quartile to third quartile] and categorical variables as counts (percentages). Student’s t (or Wilcoxon rank-sum test where appropriate) and Chi-square tests were employed to analyze the differences between continuous and categorical variables, respectively. An alpha (α) level of 0.05 was considered.
We defined CV risk categories using the risk functions, setting 5-year age intervals, and estimating the theoretical risk for the ages at the limits of each interval when considering all the rest of the risk factors at reference levels. Within each category of CV risk, the median chronological age (first to third quartile) for each group (increased risk factors or reference) was calculated and then compared. Thus, the median chronological age obtained in the reference groups corresponded to the risk age of people in the groups with increased risk factors. Then, we examined the median baPWV values of each group—increased risk factors and reference—in each category of CV risk. Using the Wilcoxon rank-sum test, the differences in baPWV values for each risk category were examined. Finally, we performed an analysis stratifying by hypertension status because of the association of high BP with high baPWV levels. Using the R-studio software (R Foundation for Statistical Computing, Vienna, Austria; Version 3.3.2), statistical analyses were performed24). Using the ggplot package, figures were constructed.
Ethical ConsiderationsAll participants signed an informed consent for the study, and this work was approved by the IDIAPJGol Research Ethics Committee (2002/1402/1).
Initially, 4280 participants were recruited in the context of the REGICOR study. After applying inclusion and exclusion criteria (1430 individuals had no baPWV assessment on record, 223 of the remaining participants had previous cardiovascular disease, and 128 had ABI ＜0.9); a final sample of 2499 participants was obtained, with a mean age of 59.7 (11.0) years and 46.9% of men. We estimated that most participants were White (88.1%)25-27). Table 1 shows the description of the participants’ characteristics by sex. In general, men showed worse health condition. BP measurements, percentage of persons with hypertension, diabetes mellitus, and current and former smokers were higher in men. Women had a slightly better lipid profile, with higher HDL and lower triglyceride values. The mean CV disease risk was higher in men. Supplementary Table 1 shows the missing value counts and percentages of the study variables. The maximum percentage in the overall population was 2.7%, for LDL-C, and thus, we considered that such low counts of missing values would not affect the interpretation of the study results.
| name | All | Men | Women | p-value |
|---|---|---|---|---|
| Number of Subjects | 2499 | 1172 | 1327 | |
| Age(years; mean (SD)) | 59.7 (11.0) | 59.5 (10.6) | 59.8 (11.3) | 0.619 |
| Age (years; median [1st-3rd quartile]) | 59.0 [51.0-67.0] | 59.0 [51.0-67.0] | 59.0 [50.0-68.0] | 0.839 |
| Systolic BP(mmHg) | 130.5 (19.6) | 135.2 (18.2) | 126.4 (19.8) | ＜0.001 |
| Diastolic BP(mmHg) | 77.6 (10.1) | 80.5 (9.8) | 75.0 (9.6) | ＜0.001 |
| Pulse pressure(mmHg) | 52.9 (15.6) | 54.7 (15.1) | 51.4 (15.9) | ＜0.001 |
| Hypertension | 1183 (47.3%) | 638 (54.4%) | 545 (41.1%) | ＜0.001 |
| Hypertension treatment | 599 (24.0%) | 303 (25.9%) | 296 (22.3%) | 0.043 |
| Total cholesterol(mg/dL) | 202.0 (34.7) | 198.9 (34.3) | 204.9 (34.8) | ＜0.001 |
| LDL-c(mg/dL) | 131.0 (29.9) | 130.4 (29.6) | 131.6 (30.1) | 0.347 |
| HDL_c(mg/dL) | 51.4 (11.5) | 47.2 (10.4) | 55.3 (11.1) | ＜0.001 |
| Hypercholesterolemia treatment | 644 (25.8%) | 301 (25.7%) | 343 (25.8%) | 0.763 |
| Glucose(mg/dL) | 96.0 (21.7) | 100.6 (24.7) | 91.8 (17.5) | ＜0.001 |
| Diabetes mellitus | 320 (12.8%) | 196 (16.7%) | 124 (9.3%) | ＜0.001 |
| Diabetes mellitus treatment | 195 (7.8%) | 116 (9.9%) | 79 (6.0%) | ＜0.001 |
| Triglycerides(mg/dL; median [1st-3rd quartile]) | 85.0 [62.0-118.0] | 92.0 [68.0-128.0] | 80.0 [58.0-109.0] | ＜0.001 |
| BMI(m/Kg2) | 27.4 (4.6) | 27.9 (4.0) | 26.9 (5.1) | ＜0.001 |
| Smoking habit | ||||
| Current | 431 (17.2%) | 250 (21.3%) | 181 (13.6%) | ＜0.001 |
| Former | 747 (29.9%) | 517 (44.1%) | 230 (17.3%) | ＜0.001 |
| Never | 1311 (52.5%) | 398 (34.0%) | 913 (68.8%) | ＜0.001 |
| FRESCO risk a | 5.2 (4.8) | 7.2 (5.5) | 3.3 (3.0) | ＜0.001 |
| SCORE2 risk b | 4.7 (3.3) | 6.1 (3.5) | 3.3 (2.3) | ＜0.001 |
| SCORE2-OP risk c | 14.6 (6.2) | 16.7 (5.9) | 12.8 (5.9) | ＜0.001 |
| baPWV(cm/s) | 1443.2 (313.6) | 1467.5 (301.0) | 1421.8 (323.0) | ＜0.001 |
Values are mean (SD) for continuous variables and counts (%) for categorical variables unless otherwise indicated.
a Spanish cardiovascular risk function, for 35 to 79 year-olds16).
b Systematic COronary Risk Evaluation model 2, for 35 to 69 year-olds18).
c Systematic COronary Risk Evaluation-Older Persons, for 70 year-olds or over17).
baPWV indicates brachial-ankle pulse wave velocity; BMI, body mass index; BP, blood pressure; HDL, high density lipoprotein; LDL, low density lipoprotein.
| Variable | All | Men | Women |
|---|---|---|---|
| Total cholesterol (mg/dL) | 34 (1.4) | 4 (0.3) | 30 (2.3) |
| LDL-c (mg/dL) | 68 (2.7) | 30 (2.6) | 38 (2.9) |
| HDL_c (mg/dL) | 34 (1.4) | 4 (0.3) | 30 (2.3) |
| Hypercholesterolemia treatment | 31 (1.2) | 4 (0.3) | 27 (2.0) |
| Glucose (mg/dL) | 34 (1.4) | 4 (0.3) | 30 (2.3) |
| Diabetes mellitus | 39 (1.6) | 7 (0.6) | 32 (2.4) |
| Triglycerides (mg/dL) | 34 (1.4) | 4 (0.3) | 30 (2.3) |
| Smoking habit | 10 (0.4) | 7 (0.6) | 3 (0.2) |
| FRESCO risk＊ | 174 (7.0) | 64 (5.5) | 110 (8.3) |
| SCORE2 risk | 548 (21.9) | 238 (20.3) | 310 (23.4) |
| SCORE2-OP risk | 2001 (80.1) | 948 (80.9) | 1053 (79.4) |
a Spanish cardiovascular risk function, for 35 to 79 year-olds1).
b Systematic COronary Risk Evaluation model 2, for 35 to 69 year-olds2).
c Systematic COronary Risk Evaluation-Older Persons, for 70 year-olds or over3).
Tables 2 and 3 describe women and men, respectively, comparing the group with increased risk factor levels and the group with optimal levels. The analysis with the FRESCO and SCORE2 functions included individuals aged 40 years (and up to 79 and 69 years, respectively) since there were no participants with increased risk factors younger than this age. The analysis with the SCORE2-OP function included those aged from 70 to 85 years, considering that there were no participants with reference levels of risk factors older than 85 years. Participants, both women and men, with increased levels of risk factors presented worse health condition in terms of the considered variables than the respective women and men with optimal levels (Tables 2 and 3, respectively). This was observed in both analyses, with the FRESCO, and with the SCORE2/SCORE2-OP risk functions.
| Women | Men | |||||
|---|---|---|---|---|---|---|
| Variable | Increased risk | Reference | p-value | Increased risk | Reference | p-value |
| Number of Subjects | 920 | 179 | 888 | 101 | ||
| Age (years; mean (SD)) | 57.6 (9.0) | 53.1 (8.4) | ＜0.001 | 57.3 (8.7) | 56.8 (11.6) | 0.681 |
| Age (years; median[1st-3rd quartile]) | 57.0 [50.0-64.0] | 51.0 [46.5-59.0] | 57.0 [50.0-64.0] | 53.0 [47.0-65.0] | 0.145 | |
| Systolic BP (mmHg) | 125.7 (18.5) | 113.0 (15.0) | ＜0.001 | 134.8 (15.7) | 120.1 (19.0) | ＜0.001 |
| Diastolic BP (mmHg) | 76.1 (9.6) | 70.9 (8.6) | ＜0.001 | 82.0 (9.0) | 72.2 (8.2) | ＜0.001 |
| Pulse pressure (mmHg) | 49.7 (13.7) | 42.0 (10.5) | ＜0.001 | 52.8 (12.9) | 48.0 (15.3) | 0.003 |
| Hypertension | 355 (38.6%) | 19 (10.6%) | ＜0.001 | 466 (52.5%) | 22 (21.8%) | ＜0.001 |
| Hypertension treatment | 177 (19.2%) | 5 (2.8%) | ＜0.001 | 192 (21.6%) | 7 (6.9%) | 0.001 |
| Total cholesterol (mg/dL) | 207.4 (34.2) | 193.9 (35.1) | ＜0.001 | 201.7 (33.5) | 184.8 (31.4) | ＜0.001 |
| LDL-c (mg/dL) | 135.6 (28.9) | 113.9 (27.5) | ＜0.001 | 133.5 (29.0) | 116.2 (24.9) | ＜0.001 |
| HDL_c (mg/dL) | 53.3 (9.3) | 68.9 (10.4) | ＜0.001 | 46.5 (9.5) | 55.4 (14.6) | ＜0.001 |
| Hypercholesterolemia treatment | 243 (26.4%) | 21 (11.7%) | ＜0.001 | 222 (25.0%) | 12 (11.9%) | 0.005 |
| Glucose (mg/dL) | 91.1 (15.6) | 84.5 (7.6) | ＜0.001 | 98.2 (18.4) | 89.1 (7.6) | ＜0.001 |
| Diabetes mellitus | 59 (6.4%) | 0 (0.0%) | 0.001 | 109 (12.3%) | 0 (0.0%) | ＜0.001 |
| Diabetes mellitus treatment | 35 (3.8%) | 0 (0.0%) | 0.016 | 57 (6.4%) | 0 (0.0%) | 0.017 |
| Triglycerides (mg/dL) | 82.0 [61.0-113.0] | 53.0 [43.5-64.0] | ＜0.001 | 94.5 [71.0-131.2] | 58.0 [49.0-77.0] | ＜0.001 |
| BMI (m/Kg2) | 27.2 (5.0) | 23.7 (3.4) | ＜0.001 | 28.0 (3.9) | 25.7 (3.6) | ＜0.001 |
| Smoking habit | ||||||
| Current | 164 (17.8%) | 0 (0.0%) | ＜0.001 | 220 (24.8%) | 3 (3.0%) | ＜0.001 |
| Former | 165 (17.9%) | 50 (27.9%) | 0.003 | 392 (44.1%) | 42 (41.6%) | 0.700 |
| Never | 591 (64.2%) | 129 (72.1%) | 0.054 | 276 (31.1%) | 56 (55.4%) | ＜0.001 |
| FRESCO risk＊ | 2.8 (1.8) | 1.1 (1.0) | ＜0.001 | 6.2 (3.6) | 3.4 (3.6) | ＜0.001 |
| SCORE2 risk | 3.5 (2.0) | 1.6 (1.1) | ＜0.001 | 6.0 (2.9) | 2.7 (1.5) | ＜0.001 |
| SCORE2-OP risk | 7.8 (1.7) | 6.7 (2.4) | 0.156 | 12.6 (3.2) | 13.9 (4.6) | 0.250 |
| Risk Age | 62.8 (9.5) | 50.8 (8.6) | ＜0.001 | 65.2 (9.0) | 54.3 (12.1) | ＜0.001 |
| baPWV (cm/s) | 1383.2 (279.7) | 1243.3 (250.4) | ＜0.001 | 1425.8 (256.7) | 1335.6 (331.9) | 0.009 |
Values are mean (SD) for continuous variables and counts (%) for categorical variablesunless otherwise indicated.
a Spanish cardiovascular risk function, for 35 to 79 year-olds16).
b Systematic COronary Risk Evaluation model 2, for 35 to 69 year-olds18).
c Systematic COronary Risk Evaluation-Older Persons, for 70 year-olds or over17).
baPWV indicates brachial-ankle pulse wave velocity; BMI, body mass index; BP, blood pressure; HDL, high density lipoprotein; LDL, low density lipoprotein.
| Women | Men | |||||
|---|---|---|---|---|---|---|
| Variable | Increased risk | Reference | p-value | Increased risk | Reference | p-value |
| Number of Subjects | 705 | 350 | 740 | 91 | ||
| Age (years; mean (SD)) | 61.1 (10.9) | 55.1 (8.5) | ＜0.001 | 57.7 (10.6) | 54.6 (9.5) | 0.005 |
| Age (years;median [1st-3rd quartile]) | 61.0 [53.0-70.0] | 54.0 [48.2-60.0] | 56.0 [49.0-64.2] | 52.0 [47.0-60.5] | 0.007 | |
| Systolic BP (mmHg) | 131.1 (17.2) | 111.3 (10.1) | ＜0.001 | 132.5 (14.8) | 114.2 (9.2) | ＜0.001 |
| Diastolic BP (mmHg) | 76.7 (9.4) | 70.7 (7.4) | ＜0.001 | 80.7 (9.1) | 72.1 (8.2) | ＜0.001 |
| Pulse pressure (mmHg) | 54.3 (14.7) | 40.6 (7.5) | ＜0.001 | 51.8 (12.5) | 42.1 (8.7) | ＜0.001 |
| Hypertension | 362 (51.3%) | 38 (10.9%) | ＜0.001 | 356 (48.1%) | 16 (17.6%) | ＜0.001 |
| Hypertension treatment | 196 (27.8%) | 25 (7.1%) | ＜0.001 | 156 (21.1%) | 14 (15.4%) | 0.257 |
| Total cholesterol (mg/dL) | 208.1 (35.1) | 200.2 (31.0) | ＜0.001 | 200.3 (32.9) | 184.1 (30.5) | ＜0.001 |
| LDL-c (mg/dL) | 135.5 (30.1) | 126.0 (25.1) | ＜0.001 | 132.8 (28.6) | 114.3 (24.3) | ＜0.001 |
| HDL_c (mg/dL) | 53.2 (10.2) | 60.4 (11.4) | ＜0.001 | 46.8 (9.5) | 56.6 (14.2) | ＜0.001 |
| Hypercholesterolemia treatment | 211 (29.9%) | 49 (14.0%) | ＜0.001 | 165 (22.3%) | 9 (9.9%) | 0.009 |
| Glucose (mg/dL) | 92.0 (15.6) | 85.7 (8.3) | ＜0.001 | 95.5 (14.5) | 89.0 (7.6) | ＜0.001 |
| Diabetes mellitus | 55 (7.8%) | 0 (0.0%) | ＜0.001 | 48 (6.5%) | 0 (0.0%) | 0.024 |
| Diabetes mellitus treatment | 34 (4.8%) | 0 (0.0%) | ＜0.001 | 28 (3.8%) | 0 (0.0%) | 0.114 |
| Triglycerides (mg/dL) | 88.0 [65.0-117.0] | 61.0 [51.0-81.0] | ＜0.001 | 89.0 [68.0-124.0] | 57.0 [46.5-75.5] | ＜0.001 |
| BMI (m/Kg2) | 27.7 (5.0) | 24.9 (4.0) | ＜0.001 | 27.6 (3.7) | 26.1 (3.7) | ＜0.001 |
| Smoking habit | ||||||
| Current | 145 (20.6%) | 0 (0.0%) | ＜0.001 | 137 (18.5%) | 0 (0.0%) | ＜0.001 |
| Former | 92 (13.0%) | 98 (28.0%) | ＜0.001 | 341 (46.1%) | 39 (42.9%) | 0.638 |
| Never | 468 (66.4%) | 252 (72.0%) | 0.076 | 262 (35.4%) | 52 (57.1%) | ＜0.001 |
| FRESCO risk＊ | 3.8 (3.0) | 1.5 (1.3) | ＜0.001 | 5.8 (4.5) | 2.3 (2.2) | ＜0.001 |
| SCORE2 risk | 3.4 (1.4) | 1.8 (1.0) | ＜0.001 | 4.6 (1.7) | 2.8 (1.4) | ＜0.001 |
| SCORE2-OP risk | 11.3 (3.7) | 8.4 (2.7) | ＜0.001 | 13.9 (3.2) | 12.0 (3.6) | 0.265 |
| Risk Age | 65.0 (10.2) | 52.0 (9.4) | ＜0.001 | 63.6 (10.1) | 52.5 (9.8) | ＜0.001 |
| baPWV (cm/s) | 1472.0 (311.7) | 1249.0 (211.3) | ＜0.001 | 1422.6 (280.5) | 1272.0 (220.9) | ＜0.001 |
Values are mean (SD) for continuous variables and counts (%) for categorical variablesunless otherwise indicated.
a Spanish cardiovascular risk function, for 35 to 79 year-olds16).
b Systematic COronary Risk Evaluation model 2, for 35 to 69 year-olds18).
c Systematic COronary Risk Evaluation-Older Persons, for 70 year-olds or over17).
baPWV indicates brachial-ankle pulse wave velocity; BMI, body mass index; BP, blood pressure; HDL, high density lipoprotein; LDL, low density lipoprotein.
Figs.1 and 2 compare, for each category of CV risk, the arterial stiffness of participants with increased levels of risk factors and participants with optimal levels (reference). Supplementary Table 2 shows the ages at the limits of the risk categories and counts of participants in each risk category. For each category of CV risk, participants in the groups with increased levels of risk factors had the same median risk age (and younger chronological age) as those in the reference groups, who were older and, importantly, had similar baPWV values, up to around 60 years of age. This occurred in women and men and with all the risk functions applied. The analysis stratified by hypertension status included too low numbers of participants in the reference groups and thus were inconclusive (data not shown).
The limits of the CV risk categories were assessed with the FRESCO (in 40–79 year-olds) risk function. Median ages of participants with increased levels of risk factors and in the Reference group are shown for each category of CV risk.
The limits of the CV risk categories were assessed with the SCORE2 (in 40–69 year-olds) and SCORE2-OP (in 70–85 year-olds) CV disease risk functions. Median ages of participants with increased levels of risk factors and in the Reference group are shown for each category of CV risk.
| Women | ||||||
|---|---|---|---|---|---|---|
| Limits of the cardiovascular risk categories | Counts of participants in each risk category | |||||
| Age | FRESCO a risk |
SCORE2/ SCORE2-OP risk |
Reference FRESCO | Increased risk FRESCO | Reference SCORE2 b/ SCORE2-OP c | Increased risk SCORE2/ SCORE2-OP |
| 40-45 | [0.368, 0.54) | [0.764, 1.08) | 51 | 24 | 90 | 8 |
| 45-50 | [0.54, 0.793) | [1.08, 1.52) | 49 | 70 | 73 | 32 |
| 50-55 | [0.793, 1.16) | [1.52, 2.14) | 24 | 108 | 71 | 78 |
| 55-60 | [1.16, 1.7) | [2.14, 3.01) | 24 | 136 | 47 | 101 |
| 60-65 | [1.7, 2.5) | [3.01, 4.23) | 14 | 150 | 32 | 131 |
| 65-70 | [2.5, 3.65) | [4.23, 5.93) | 10 | 180 | 13 | 154 |
| 70-75 | [3.65, 5.31) | [5.14, 7.94) | 5 | 136 | 11 | 47 |
| 75-80 | [5.31, 7.71) | [7.94, 12.2) | 2 | 116 | 11 | 73 |
| 80-85 | [12.2, 18.4) | 2 | 81 | |||
| Men | ||||||
| Limits of the cardiovascular risk categories | Counts of participants in each risk category | |||||
| Age | FRESCO a risk |
SCORE2/ SCORE2-OP risk |
Reference FRESCO | Increased risk FRESCO | Reference SCORE2 b/ SCORE2-OP c | Increased risk SCORE2/ SCORE2-OP |
| 40-45 | [0.695, 1.03) | [1.24, 1.69) | 28 | 11 | 21 | 10 |
| 45-50 | [1.03, 1.51) | [1.69, 2.3) | 20 | 40 | 22 | 42 |
| 50-55 | [1.51, 2.22) | [2.3, 3.14) | 10 | 80 | 15 | 98 |
| 55-60 | [2.22, 3.27) | [3.14, 4.27) | 10 | 114 | 12 | 119 |
| 60-65 | [3.27, 4.79) | [4.27, 5.79) | 9 | 149 | 10 | 148 |
| 65-70 | [4.79, 6.99) | [5.79, 7.83) | 6 | 151 | 5 | 170 |
| 70-75 | [6.99, 10.1) | [6.94, 9.86) | 8 | 191 | 2 | 22 |
| 75-80 | [10.1, 14.6) | [9.86, 13.9) | 10 | 152 | 2 | 52 |
| 80-85 | [13.9, 19.4) | 2 | 79 | |||
a Spanish cardiovascular risk function, for 35 to 79 year-olds1).
b Systematic COronary Risk Evaluation model 2, for 35 to 69 year-olds2).
c Systematic COronary Risk Evaluation-Older Persons, for 70 year-olds or over3).
We observed that in participants with the same CV risk, middle-aged individuals with increased risk factors presented similar arterial stiffness to older participants with optimal risk factor levels (reference), especially up to the risk category that corresponds to around 60 years of age. These results confirm an assumption in the concept of risk age, that is, the arterial state in individuals with the same risk age is similar, and this occurred in both women and men. When explaining the risk age to a person to communicate cardiovascular risk, we assume that the state of their arteries is similar to that of an older person with no risk factors (other than age) and the same cardiovascular risk score. We examined and confirmed such an assumption. In Figs.1 and 2 of our study, the median age of the groups in the row labeled as “Reference” (optimal levels of risk factors) represents the risk age of participants in the row labeled as “Increased risk” (increased levels of risk factors), and both groups had similar arterial condition. For example, the women in Fig.2 who had increased risk factors in the group with a median chronological age of 49 years had a median risk age of 55 years, and importantly, their arterial condition was similar to that in 55-year-old people with optimal risk factor levels. This is a novelty in our study: To show similar arterial condition when comparing people with the same risk age but different chronological ages.
Our findings are coherent with a study that showed a correlation between coronary artery calcium and a Framingham risk score that used test-derived vascular age instead of chronological age and differ from another analysis that showed a lack of agreement of carotid intima-media thickness values with the risk age estimated using the Framingham risk score28). Differences in the studied populations might partly explain the discrepant results. We analyzed CV risk categories as assessed with the FRESCO function, which is specific for the Spanish population, and the SCORE2 and SCORE2-OP, which consider various risk regions of CV risk17, 18). Interestingly, all these different functions provided similar results.
Our results are also aligned with an analysis that found a correlation between PWV levels and CV SCORE risk in participants with low score values (＜5%); another report that included cohorts from various continents also found a correlation between vascular age and risk age, but the study was restricted to patients with rheumatoid arthritis22). Finally, an analysis in a young population found a moderate correlation between carotid-femoral PWV and risk of fatal CV disease assessed with SCORE, and a strong correlation between risk age—calculated with the high-risk countries’ SCORE risk scale—and 10-year risk of fatal CV. The studied population involved individuals who were 18–50 years old, and the researchers were required to calculate risk age assuming 40 years of age for patients younger than that, as the SCORE does not cover this group. Furthermore, despite describing the population separately for women and men, they did not analyze the correlation between risk age and CV risk by sex. They also stated the lack of studies with participants at low-moderate fatal CV risk and high levels of risk factors and reported limited evidence to show increased levels of atherosclerosis in these patients29). Importantly, there were no studies that compared the arterial status of individuals with and without increased levels of risk factors (other than age)—by categories of the same cardiovascular risk score.
The concordance we observed is especially important for younger and middle-aged individuals since communication of CV risk using risk age is an approach particularly useful in this population. In young and middle-aged people, the score obtained with the risk functions may be misleading, because age represents a major risk driver. Middle-aged individuals with risk factors including smoking, diabetes, increased cholesterol levels, and BP measurements could have a low absolute risk when using the risk functions to calculate it. Because of their low absolute score, realizing and accepting that their risk is increased and the state of their arteries damaged and aged may be difficult for them. The use of communication tools such as risk age should be encouraged to help and motivate people with high risk age but low absolute risk to adopt healthier lifestyles8). The latest guidelines on cardiovascular prevention mention the automatic calculation of risk age in clinical practice; however, its use does not seem too widespread in the clinical setting. This is especially relevant in the current context of the worrisome prevalence of young people who smoke30) or suffer from hypertension20) or obesity31). Being able to effectively convey this message promptly can have great benefits because lifestyle changes at young ages could completely revert some of their adverse effects over time32).
The relation of arterial stiffness with CV risk across risk categories was similar for women and men and so was the comparison of median ages for each risk category, but the risk estimation that defined risk categories was slightly lower in women. This can be explained partially by the lower weight of the risk factors included in the analyzed risk equations when determining CV risk in women. Previous reports have described differences in arterial stiffness with aging by sex33)—which justified the separation by sex in our analysis. Plausible mechanisms to explain them include hormonal, genetic, and lifestyle variations33). The study of additional processes that could modulate this divergence is still an area of high interest to address in further studies.
Our results propose that the risk age reflects the vascular tree condition in the middle-aged population. The findings were consistent in all the risk functions analyzed, and thus, extrapolation of the results would apply not only to Spain but also to other European populations2). We also acknowledge some limitations. First, the number of participants decreased from the initial 4280 recruited in the context of the REGICOR study to 2499 partly because we analyzed individuals who had a baPWV measurement, and this measurement was only performed from a certain date, during recruitment. However, this implies that the random selection of participants was not violated. Second, the number of participants in the reference groups aged ＞65 years was very small, which calls for caution in interpreting the results in these age groups. As mentioned above, our findings would mainly apply to individuals aged up to around 60 years. Finally, the cross-sectional design of the study precludes the confirmation of causality, but the large total sample size and the specific training of the nurses provide robustness to the results. Follow-up studies to confirm the increase of arterial stiffness according to risk age over time would be of interest.
In this analysis, some evidence that supports current European Guidelines on CV prevention in clinical practice is provided. The guidelines recommend the use of risk age as an effective informative tool to promote CV health in patients younger than 50 years, the targeted age group for early and timely prevention, especially in the presence of CV disease risk factors2). These findings also support previous analyses that used risk age in the CV risk functions instead of chronological age to enhance risk classification in younger and middle-aged individuals34, 35). Further studies could investigate the effectiveness of primary prevention strategies that categorize the risk using risk age to ameliorate arterial stiffness.
To conclude, we observed that younger people with a higher risk age than chronological age (increased risk factors) had the same arterial condition as older participants with the same chronological and risk age (reference). Our findings are especially important when targeting the middle-aged population with risk factors, to help them notice the burden of such risk factors, such as the damage in their arteries.
The authors thank all the participants and staff (Medical doctors, nurses, technicians and researchers) from the REGICOR study. The authors also acknowledge Susanna Tello, Marta Cabañero and Leny Franco for the data management.
This work with the REGICOR cohorts was supported by the HERACLES program (Essential Hypertension: Network for the Analysis of ionic channels from the arterial smooth muscle) within the RIC: Network for Cardiovascular Research [grant number RD12/0042]; RedIAPP: Primary Care Prevention and Health Promotion Research Network [grant number RD12/0007]; an award on the call for the creation of the RICORS: Health Outcomes-Oriented Cooperative Research Networks [reference RD21/0016/0001], co-funded with European Union – Next Generation EU funds; European Regional Development Funds (ERDF-FEDER), Centro de Investigación Biomédica en Red Enfermedades Cardiovasculares (CIBERCV) , Health Research Fund [grant numbers FIS90/0672, FIS93/0568, FIS96/0026-01, FIS99/0655, FIS99/0013-01, FIS 99/9342, FIS02/0589, FIS2003/HERMES PI20471, FIS14/00449, INTRASALUD PI11/01801]; the Government of Catalonia through Agency for Management of University and Research Grants [grant numbers 2014 SGR 240, 2014 SGR 902]. M.G. is funded by an ERDF contract from Carlos III Health institute [grant number FIS CP12/03287].
The authors declare no conflicts of interest.
1)Marrugat J, Subirana I, Ramos R et al. Derivation and validation of a set of 10-year cardiovascular risk predictive functions in Spain: The FRESCO Study. Prev Med (Baltim), 2014; 61: 66-74
2)SCORE2 working group and ESC Cardiovascular risk collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J, 2021; 42: 2439-2454
3)SCORE2-OP working group and ESC Cardiovascular risk collaboration. SCORE2-OP risk prediction algorithms: estimating incident cardiovascular event risk in older persons in four geographical risk regions. Eur Heart J, 2021; 42: 2455-2467
