The Effects of Cardiovascular Health Behaviors and Risk Factors on Brachial-Ankle Pulse Wave Velocity in Middle-Aged Men： in Southeastern China

The Effects of Cardiovascular Health Behaviors and Risk Factors on Brachial-Ankle Pulse Wave Velocity in Middle-Aged Men： in Southeastern China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Effects of Cardiovascular Health Behaviors and Risk Factors on Brachial-Ankle Pulse Wave Velocity in Middle-Aged Men： in Southeastern China Yun Lu, Zhenhai Shen, Fangcen Yuan, Yupeng Fan, Zaibo Ni, Liuyu Wang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6739204/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cardiovascular diseases (CVD) were the leading cause of global mortality. We conducted a across sectional study and to investigate the association between cardiovascular health behaviors and risk factors with brachial-ankle pulse wave velocity (baPWV) in middle-aged men. A total of 6124 men of health examination were enrolled. According to the scores of cardiovascular health behaviors and risk factors, all subjects were divided into poor group (0-6 points), medium group (7-10 points) and good group (11-14 points). Levels of BMI, FBG, SBP, DBP, TC, and baPWV demonstrated a significant downward trend across three groups (from poor to good) with improving scores of cardiovascular health behavior and factor (P<0.05). The incidence of high arterial stiffness in the poor, medium and good groups were 70.2%, 45.2% and 24.1% respectively which showed a gradual decrease (P<0.05). BMI, TC, elevated BP, FBG, Smoking, and age were identified as independent risk factors for increased baPWV, while physical exercise served as a protective factor (all P<0.05). After age adjustment, the odds ratios (ORs) for high arterial stiffness were significantly lower in the medium (OR=0.34) and good (OR=0.13) groups compared to the poor group (both P<0.05). Cardiovascular health behaviors and risk factors were significantly associated with brachial-ankle pulse wave velocity (baPWV) in middle-aged men. Targeted modification of these modifiable factors may contribute to the prevention and management of arterial stiffness in this population. Health sciences/Risk factors Biological sciences/Physiology/Cardiovascular biology/Cardiovascular diseases/Vascular diseases/Atherosclerosis Cardiovascular health Arteriosclerosis Middle-aged men novel anthropometric parameters hyperuricemia obesity SUMMARY What is known about topic: The American Heart Association (AHA) established criteria for ideal cardiovascular health behaviors and risk factors that risk factor control contributed to a 50% reduction in coronary heart disease mortality in the United States between 1980-2000. The Cardiovascular Health Score, developed in 2012, quantitatively integrates these behavioral and physiological metrics, with studies demonstrating its association with improved cardiovascular structure and function in aging populations. What this study adds: This study included 6,124 middle-aged men from southeastern China, representing this demographic population. We evaluated cardiovascular risk factors and behavioral traits in relation to brachial-ankle pulse wave velocity (baPWV), a marker of early vascular dysfunction that reflects both central and peripheral arterial health. These findings suggest controlling these modifiable factors may contribute to the prevention and early intervention of arteriosclerosis. BACKGROUND Cardiovascular diseases (CVD) remain the leading cause of global mortality, affecting approximately 290 million individuals [ 1 ]. Recognizing this burden, the American Heart Association (AHA) established criteria for ideal cardiovascular health behaviors and risk factors in 2010 [ 2 ], building on evidence that risk factor control contributed to a 50% reduction in coronary heart disease mortality in the United States between 1980–2000 [ 3 ]. The Cardiovascular Health Score, developed by Huffman et al. [ 4 ] in 2012, quantitatively integrates these behavioral and physiological metrics, with studies demonstrating its association with improved cardiovascular structure and function in aging populations [ 5 ]. Arterial stiffness, a hallmark of early vascular dysfunction, is most accurately assessed via pulse wave velocity [ 3 ]. As brachial-ankle PWV (baPWV) reflects both central and peripheral arterial health, it serves as a critical indicator of cardiovascular risk. Our prior research in southern Jiangsu Province of China revealed alarmingly low rates of ideal cardiovascular health metrics among young and middle-aged adults [ 6 ], underscoring the urgency for targeted interventions. This study specifically examines the impact of cardiovascular health behaviors and risk factors on baPWV in middle-aged men, aiming to elucidate modifiable targets for arterial stiffness prevention. Therefore, it is particularly important to strengthen the modulation of cardiovascular health behaviors and risk factors. The aim of this study was to investigate the effects of cardiovascular health behaviors and risk factors on baPWV in middle-aged men. METHODS STUDY PARTICIPANTS We conducted a cross-sectional study of 6124 middle-aged men (aged 40–64 years) who underwent routine health examinations at The Taihu Rehabilitation Hospital of Jiangsu Province between June 2020 and April 2021. Eligible participants were required to have been residents of southeastern china for at least five years. We excluded individuals with: a history of myocardial infarction or stroke; secondary hypertension; severe hepatic or renal insufficiency; peripheral vascular disease; or incomplete study data. The study protocol was approved by the Ethics Committee of Taihu Rehabilitation Hospital of Jiangsu Province (SGLL-2020006) and the subjects signed the informed consent. All methods were carried out in accordance with relevant guidelines and regulations (e.g. Helsinki guidelines). DATA ACQUISITION Our questionnaire collected data on age, smoking status, alcohol consumption, physical exercise, and medical history (including hypertension, diabetes, coronary heart disease, and other chronic conditions, as well as medication use). Height and weight were measured to calculate body mass index (BMI) using the formula: BMI = weight (kg)/height (m)². Blood pressure (BP) was measured using a mercury sphygmomanometer. All participants fasted for 8–12 hours prior to blood collection. Fasting blood glucose (FBG) and total cholesterol (TC) levels were analyzed using a HITACHI 008α automated biochemical analyzer. DETECTION OF BAPWV PWV was measured using a standard device by use of applanation tonometry (Corin BP-203RPE II VP-100, Japanese). Before the test, the subjects rested for 5–10 minutes in a supine position without a pillow. The unified procedure was carried out, and the average value of baPWV on the left and right sides was taken for statistical analysis and baPWV levels above 1400cm/s indicate high arterial stiffness. CARDIOVASCULAR HEALTH BEHAVIORS AND RISK FACTORS Since this study’s questionnaire did not assess specific vegetable intake, vegetable intake was replaced with salt intake for adjustment, based on the American Heart Association (AHA) definition of cardiovascular health. As defined by the AHA and consistent with our previous studies, cardiovascular health behaviors include smoking, BMI, exercise, and salt intake, while cardiovascular health factors include BP, FBG, and TC [ 2 , 6 ]. (See Table 1 ). Table 1 Classification and scores of cardiovascular health behaviors and risk factors in relation to baPWV Factors Classification Scoring Standard value Smoking Ideal No smoking or quit smoking > 1 year 2 Average Smoking cessation ≤ 1 year or occasional/small amount of smoking 1 Low Currently smoking 0 BMI Ideal BMI< 25 kg/m2 2 Average BMI 25.0-29.9 kg/m2 1 Low BMI ≥ 30 kg/m2 0 Salt intake Ideal low-salt diet( 12 g/d) 0 Exercise Ideal Regular exercise ≥ 3 times per week or ≥ 90 min per week 2 Average Occasional exercise < 3 times per week, or ≤ 89 min cumulative time spent exercising per week 1 Low Physical inactivity, no additional physical activity beyond daily living and work activities 0 BP Ideal SBP < 120 mmHg and DBP < 80 mmHg without medication 2 Average Systolic blood pressure of 120–139 mmHg or diastolic blood pressure of 80–89 mmHg or blood pressure < 140/90 mmHg with antihypertensive medication. 1 Low Systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg 0 FBG Ideal Non-pharmacological FBG < 5.6 mmol/L 2 Average FBG between 5.6 and 7.0 mmol/L or with hypoglycemic drugs FBG 7.0 mmol/L 0 TC Ideal Non-pharmacological TC < 5.2 mmol/L 2 Average TC 5.2–6.2 mmol/L or in the case of lipid-modulating drugs TC 6.2 mmol/L 0 baPWV Normal <1400cm/s Abnormal ≥ 1400cm/s Note: baPWV, brachial-ankle pulse wave conduction velocity; BMI, body mass index; BP, blood pressure; FBG, fasting blood glucose; TC, total cholesterol GROUPING According to the Huffman score [ 4 ], cardiovascular health behaviors and risk factors were categorized into three levels: ideal (2 points), average (1 point), and low (0 points), yielding a maximum total score of 14 points. According to the sum of the scores, all subjects were divided into poor group (0–6 points), medium group (7–10 points), and good group (11–14 points). STATISTICAL PROCESSING SPSS14.0 statistical software was used to test the normal distribution and homogeneity of variance of the measurement data. The measurement data conforming to the normal distribution was represented by mean ± standard deviation (± s). Independent sample t test was used for comparison between two groups, and one-way analysis of variance was used for comparison among multiple groups. LSD method was used for pound-pair comparison, and Tamhane's method was used when variance was uneven. The measurement data of non-normal distribution were expressed as the median (P25, P75), and Kruskal Wallis H test was used for comparison between groups. Measurement data were tested by the chi-square test for trend. logistic regression analysis (Input method) was used to analyze the relationship between each factor and baPWV. logistic regression analysis (Stepwise method) was used to analyze the relationship between cardiovascular health behavior and factor rating and baPWV. A p-value of < 0.05 was considered as significant correlation. RESULTS Effects of Cardiovascular Health Behaviors and Risk Factors on baPWV in Middle-Aged Men: This study included 6142 baseline subjects. Participants were categorized into three groups based on their cardiovascular health behavior and factor scores: poor (0–6 points), medium (7–10 points), and good (11–14 points). The poor group comprised 836 subjects (mean age 51.88 ± 6.31 years), the medium group 3847 subjects (51.45 ± 6.57 years), and the good group 1441 subjects (50.81 ± 6.51 years). Age differences among the three groups were statistically significant (P < 0.05). We observed decreasing trends across the poor, medium, and good groups for BMI, FBG, SBP, DBP, TC, and baPWV levels, while the proportions of smokers, individuals with normal salt intake, and those who exercised regularly showed gradual increases. The incidence of high arterial stiffness demonstrated a significant decreasing trend across the groups: 70.2% in the poor group, 45.2% in the medium group, and 24.1% in the good group (P < 0.05). (See Table 2 ). Table 2 Baseline Characteristics of Cardiovascular Health Behaviors and Risk Factors in Middle-Aged Men Across Different Risk Groups Parameters Poor Group(n = 836) Medium Group(n = 3847) Good Group(n = 1441) F/χ2 P Age(Years) 51.88 ± 6.31 51.45 ± 6.57 50.81 ± 6.51a 8.03 0.00 BMI(kg/m2) 25.92 ± 2.98 24.88 ± 2.79a 24.17 ± 2.45ab 108.31 0.00 Smoking Idea [n(%)] 60(7.2) 1227(31.9) 1225(85.0) 1744.89 0.00 average [n(%)] 39(4.7) 283(7.4) 66(4.6) Poor[n(%)] 737(88.2) 2337(60.7) 150(10.4) Salt intake Idea [n(%)] 31(3.7) 435(11.3) 484(33.6) 810.04 0.00 Average [n(%)] 474(56.7) 2729(70.9) 886(61.5) Poor[n(%)] 331(39.6) 683(17.8) 71(4.9) Exercise Idea [n(%)] 110(13.1) 1540(40.0) 1019(70.7) 1015.99 0.00 Average [n(%)] 533(63.8) 2088(54.3) 411(28.5) Poor[n(%)] 193(23.1) 219(5.7) 11(0.8) SBP(mmHg) 136.99 ± 14.11 127.27 ± 13.25a 119.63 ± 10.09ab 501.24 0.00 DBP(mmHg) 85.69 ± 9.30 79.44 ± 9.23a 74.23 ± 7.83ab 444.58 0.00 FBG(mmol/L) 6.92 ± 2.07 5.58 ± 1.07a 5.20 ± 0.52ab 605.14 0.00 TC(mmol/L) 5.45 ± 1.03 4.80 ± 0.82a 4.53 ± 0.68ab 337.14 0.00 baPWV Level(cm/s) 1532.84 ± 226.60 1408.43 ± 206.55a 1312.27 ± 163.78ab 324.87 0.00 baPWV Abnormal[n(%)] 587(70.2) 1740(45.2) 348(24.1) 466.46 0.00 Note: Measurements are expressed as mean ± standard deviation, and counts are expressed as number of cases. baPWV, brachial-ankle pulse wave conduction velocity. Compared with the poor group, aP < 0.01; compared with the medium group, bP < 0.01. baPWV, brachial-ankle pulse wave conduction velocity; BMI, body mass index; BP, blood pressure; FBG, fasting blood glucose; TC, total cholesterol. baPWV Levels and Incidence of High Arter Stiffness by Number of Ideal Cardiovascular Health Metrics: As the number of ideal cardiovascular health behaviors and risk factors increased incrementally from 0 to 7, we observed: a progressive decline in the incidence of high arterial stiffness across groups (69.4%, 60.0%, 53.9%, 43.2%, 36.2%, 34.8%, 21.2%, and 10.9%, respectively). Corresponding decreases in both baPWV levels and prevalence of high arterial stiffness (P < 0.05 for all trends). (See Table 3 ). Table 3 baPWV Levels and Prevalence of High Arterial Stiffness Across Different Categories of Ideal Cardiovascular Health Behaviors and Risk Factors Number of ideal cardiovascular health behaviors and risk factors baPWV(cm/s) High arterial stiffness [n(%)] 0(n = 160) 1503.95 ± 204.17 111(69.4) 1(n = 633) 1473.18 ± 215.00 380(60.0) 2(n = 1235) 1448.84 ± 205.81 666(53.9) 3(n = 1517) 1407.09 ± 213.98 655(43.2) 4(n = 1389) 1376.64 ± 204.80 503(36.2) 5(n = 824) 1347.55 ± 193.77 287(34.8) 6(n = 320) 1292.10 ± 161.69 68(21.2) 7(n = 46) 1252.61 ± 134.91 5(10.9) F 54.11 295.385 P 0.00 0.00 Note: baPWV, brachial-ankle pulse wave conduction velocity. Logistic Regression Analysis of Cardiovascular Health Behaviors and Risk Factors, and High Arterial Stiffness: Smoking, BMI, TC, BP, FBG and age were independent risk factors for high arterial stiffness (P < 0.05). Exercise was a protective factor for high arterial stiffness (P < 0.05). Subjects with average BP, exercise, BMI and FBG were more likely to develop arterial stiffness compared with ideal level of these factors and the OR values were 3.75, 1.99, 1.24, 1.18, respectively (P < 0.05). The OR values of arterial stiffness in subjects with worse BP, exercise, FBG, BMI, TC and smoking were 15.89、1.91、1.80、1.35、1.34、1.25, respectively(P 0.05). However, each additional year of age was associated with a 10% increased risk of high arterial stiffness (OR = 1.10, P < 0.05). (See Table 4 ). Table 4 Logistic regression analysis of various cardiovascular health hehaviors and factors with high arterial stiffness Factors Classification β Wald P OR(95%CI) Smoking Ideal 11.64 0.00 Average 0.11 0.78 0.38 1.12(0.87–1.44) Low 0.22 11.63 0.00 1.25(1.10–1.42) Salt intake Ideal 0.29 0.86 Average 0.04 0.22 0.64 1.04(0.88–1.23) Low 0.01 0.01 0.91 1.01(0.82–1.25) Exercise Ideal 119.07 0.00 Average 0.69 113.93 0.00 1.99(1.76–2.26) Low 0.65 27.45 0.00 1.91(1.50–2.43) BMI Ideal 14.47 0.00 Average 0.21 11.17 0.00 1.24(1.09–1.40) Low 0.30 7.43 0.01 1.35(1.09–1.67) TC Ideal 5.60 0.06 Average 0.01 0.03 0.87 1.01(0.88–1.16) Low 0.30 5.56 0.02 1.34(1.05–1.72) BP Ideal 807.13 0.00 Average 1.32 300.52 0.00 3.75(3.23–4.36) Low 2.77 806.83 0.00 15.89(13.13–19.24) FBG Ideal 32.03 0.00 Average 0.17 5.93 0.01 1.18(1.03–1.36) Low 0.59 30.35 0.00 1.80(1.46–2.21) Alcohol Consumption -0.05 1.54 0.21 0.95(0.88–1.03) Age 11.64 0.00 1.10(1.09–1.10) constant 0.11 0.78 0.38 Note: BMI, body mass index; BP, blood pressure; FBG, fasting blood glucose; TC, total cholesterol. Logistic Regression Analysis of Cardiovascular Health Behavior and Factor Scores in Relation to High Arterial Stiffness: Compared with the poor group, the unadjusted OR for abnormal baPWV were 0.35 (medium group) and 0.14 (good group) (both p < 0.05). After age adjustment, the corresponding OR were 0.34 and 0.13, respectively (both p < 0.05). (see Table 5 ). Table 5 Logistic analysis of cardiovascular health behavior and factor score subgroups and high arterial stiffness Model 1 Model 2 β Wald P OR(95%CI) β Wald P OR(95%CI) Poor group 428.81 0.00 1 418.05 0.00 1 Medium group -1.05 162.55 0.00 0.35(0.30–0.41) -1.08 162.12 0.00 0.34(0.29–0.40) Good group -2.00 421.56 0.00 0.14(0.11–0.16) -2.04 411.88 0.00 0.13(0.11–0.16) Age 0.08 360.49 0.00 1.09(1.08–1.10) Note: Model 1 indicates unadjusted; model 2 indicates adjusted for age. DISCUSSION Mounting evidence supports the protective role of ideal cardiovascular health metrics against vascular disease. The 2010 AHA studies demonstrated that optimal cardiovascular health status not only reduces cerebrovascular risk but also lowers all-cause mortality among CVD patients [ 7 ]. Subsequent research has confirmed a dose-response relationship, showing progressive reductions in hypertension and diabetes risk with increasing numbers of ideal cardiovascular health components [ 8 ]. Our findings extend this evidence to arterial stiffness, a validated predictor of early cardiovascular dysfunction, in middle-aged men. The developmental trajectory of arterial stiffness may begin earlier than traditionally assumed. An Italian cohort study revealed that aortic stiffening originates in adolescence, where favorable cardiovascular health behaviors and risk factors confer vascular protection [ 9 ]. This phenomenon persists across the lifespan, as evidenced by a 4-5year longitudinal study of older adults (mean age ~ 60 years), where participants maintaining ≥ 5 ideal cardiovascular health indicators exhibited significantly lower arterial stiffness than those with ≤ 2 indicators [ 10 ]. Our cross-sectional data align with these observations, demonstrating: an inverse relationship between ideal cardiovascular health metrics and baPWV (a robust measure of arterial stiffness), and elevated arterial stiffness risk among middle-aged men with suboptimal cardiovascular health profiles after age adjustment. Notably, we identified salt intake, smoking, elevated BMI, TC, BP, FBG, and advancing age as independent baPWV determinants. These findings carry important clinical implications: targeted modification of these modifiable factors-particularly through smoking cessation, dietary sodium reduction, and metabolic parameter optimization-may attenuate arterial stiffening. Given that arterial stiffness precedes overt atherosclerotic changes, our results suggest cardiovascular health interventions could serve as a primary prevention strategy for arteriosclerosis in this population. Smoking remains one of the most significant modifiable risk factors for CVD, accounting for approximately 20% of CVD-related mortality globally [ 11 ]. The pathophysiological mechanisms underlying this association are multifactorial, involving: impairment of vascular endothelial function, chronic low-grade inflammation, platelet activation and hypercoagulability, sympathetic nervous system overactivation with consequent coronary vasoconstriction, and structural degradation of arterial elastic fibers [ 12 ]. These smoking-induced alterations collectively accelerate arterial stiffening, even at low exposure levels-with emerging evidence suggesting secondhand smoke exposure similarly compromises vascular integrity. Our findings corroborate these established biological pathways, demonstrating that current smokers exhibited 1.25-fold higher odds of elevated baPWV compared to their non-smoking counterparts after multivariable adjustment. This dose-independent effect (observed across all smoking intensities) positions tobacco cessation as a critical intervention target for arterial stiffness mitigation in middle-aged men. The magnitude of this association aligns with previous cohort studies reporting 1.2–1.3 fold increased arterial stiffness risk among smokers. Previous studies have shown that exercise improves both cardiovascular risk factors and arterial stiffness [ 14 ]. The effects of different exercise programs are different, especially for the middle-aged and old people, because of the decline of muscle strength, especially high-intensity exercise is easy to cause some sports injuries, and the reasonable exercise program is also controversial. Exercise training, although reducing cardiovascular risk factors in subjects, did not improve arterial stiffness in older adults [ 15 ]. Miyachi etal [ 16 ] found that 4 months of resistance movement increased the human muscle strength but appeared to exacerbate the degree of arterial elastic sclerosis. Exercise could reverse the arterial stiffness and abnormal BP in patients with metabolic syndrome and the effect of high intensity exercise is better in subjects with metabolic syndrome underwent 8-week supervised aerobic exercise at target heart rate [ 17 ]. Recent studies have also found that moderate-intensity or low-intensity long-term resistance exercise can improve arterial stiffness and prevent cardiovascular disease [ 18 ]. The results of our study suggest that exercise is a protective factor for baPWV levels in middle-aged men, and even occasional exercise can significantly improve arterial stiffness in this population. Previous studies on the correlation between BMI and baPWV mostly focused on hypertensive populations and the results have been reported in controversial. A cross-sectional study of 14,866 hypertensive men in northern China found a negative association between BMI and baPWV, high BMI may be a protective factor for arteriosclerosis,in the age range of 35–55 years is more obvious [ 19 ]. Mallat etal [ 20 ] found a positive correlation between pulse wave velocity and body mass index in elderly hypertensive patients. A study of 202 essential hypertension patients found no association between BMI and arterial stiffness [ 21 ]. BMI was found to be an independent risk factor for baPWV in middle-aged men from southern Jiangsu province, China. Research on the effect of TC on baPWV levels is generally consistent. A recent large-scale community-based study of 45,092 people in our northern population found a significant association between TC and baPWV, with each unit increase in TC after adjustment for related variables, baPWV increases by 5.34 cm/s [ 22 ]. The possible mechanism is that TC can cause direct damage to vascular endothelial function, which leads to arterial stiffness and inflammatory responses to lipid formation lead to the degradation of collagen, elastic fibers, and proliferation of smooth muscle cells, which also contribute to the development of arterial stiffness [ 23 ]. Our study identified elevated TC as an independent risk factor for higher baPWV levels in middle-aged men. Specifically, individuals with suboptimal TC levels had a 1.34-fold increase in arterial stiffness compared to those with ideal TC levels. These findings suggest that active management of TC through lifestyle modifications and/or pharmacological interventions may help reduce arterial stiffness. Our study found that blood pressure had the greatest effect on baPWV levels among all cardiovascular health behaviors and risk factors, middle-aged men with average and poor blood pressure were 3.75 to15.89 times arteriosclerosis than those with ideal blood pressure. Blood pressure is an important factor in arterial stiffness [ 24 ] and the possibly mechanism of its effect were increased blood pressure levels cause changes in the structure and function of the vascular elastic arterial wall which leads to arteriosclerosis [ 25 ]. The effect of blood pressure on arterial stiffness should also be taken into account by age. A large cross-sectional study in northern China found a positive correlation between systolic blood pressure and arterial stiffness in different age groups, with the strongest correlation in the youth group, followed by the middle-aged group, and the weakest in the elderly group [ 26 ]. Cecelja et al [ 27 ] found positive correlations between systolic and diastolic blood pressure levels and arteriosclerosis in young and middle-aged people. We also found the age was an independent risk factor for abnormal arterial stiffness in the middle-aged male population, with a 1.1-fold increase in the risk of arterial stiffness for each 1-year increase in age. It is suggested that the vascular structure changes with aging. It has also been reported that blood pressure and arterial stiffness may be mutually causal [ 28 ]. In conclusion, it is recommended that middle-aged men should actively monitor and control their blood pressure in order to reduce the occurrence and development of arteriosclerosis. Diabetes is an independent risk factor for cardiovascular disease, and patients with diabetes are arteriosclerosis at an early age and are prone to cardiovascular events [ 29 ]. The American diabetes society notes impaired FBG regulation and increased carotid intima-media thickness in patients with type 2 diabetes, independent of other risk factors [ 30 ]. Accumulation of metabolic syndrome components, including blood glucose levels, was strongly associated with baPWV change rates, with blood pressure and FBG levels having the greatest effect on baPWV change rates in more than 2 components [ 31 ]. The present study found that FBG was an independent risk factor for baPWV in a middle-aged male population, consistent with previous studies [ 31 ]. Previous studies have debated the effects of alcohol consumption on cardiovascular health and arterial stiffness. Moderate alcohol consumption appears to have short-term cardiovascular protective effects, whereas heavy alcohol consumption can be harmful to the vascular system [ 32 ]. Studies have shown that long-term alcohol consumption in men increases arterial stiffness after 4–5 years suggesting that even moderate alcohol consumption may confer long-term cardiovascular risk, especially in middle-aged and older men [ 33 ]. A Spanish multicenter study showed that heavy alcohol consumption (> 70 g/week) increased carotid intima-media thickness, but did not find an effect on baPWV [ 34 ]. This study found no effect of alcohol consumption on arterial stiffness in middle-aged men, and further prospective studies are needed to confirm this. In addition, there are few studies on the relationship between dietary salt intake and arterial stiffness, and our study did not find any effect of salt intake on baPWV levels. A recent study suggested that dietary salt restriction had no effect on baPWV levels [ 34 ], which is consistent with the present study. 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[PubMed:15699456] Huang J, Chen Z, Yuan J, et al. Association Between Body Mass Index (BMI) and Brachial-Ankle Pulse Wave Velocity (baPWV) in Males with Hypertension: A Community-Based Cross-Section Study in North China. Med Sci Monit, 2019;25:5241-5257. [PubMed:31303640] Cecelja M, Chowienczyk P. Dissociation of aortic pulse wave velocity with risk factors for cardiovascular disease other than hypertension: a systematic review[J]. Hypertension, 2009, 54(6):1328-36. [PubMed: 19884567] Niiranen TJ, Kalesan B, Hamburg NM, et al. Relative contributions of arterial stiffness and hypertension to cardiovascular disease: the Framingham heart study[J]. J Am Heart Assoc, 2016, 5(11): e004271. [PubMed:27912210] Moh MC, Sum CF,Tavintharan S, etal. Association of the anti-angiogenic factor secreted protein and rich incysteine (SPARC)with vascular complications among Chinese type 2 diabetic patients in Singapore [J]. J Diabetes Complication, 2016, 31(7):121-132. [PubMed:28479157] Greenlee RT, Naleway AL, Vidaillet H. Incidence of myocardial in farction in a general population: the Marshfield Epidemiologic Study Area[J]. WMJ, 2002, 101(7):46-52. [PubMed:12426920] Sang Y, Wu X, Miao J, etal. Determinants of Brachial-Ankle Pulse Wave Velocity and Vascular Aging in Healthy Older Subjects. Med Sci Monit, 2020;26:e923112.[ PubMed: 32445331] Laguzzi F, Baldassarre D, Veglia F, etal. Alcohol consumption in relation to carotid subclinical atherosclerosis and its progression: results from a European longitudinal multicentre study[J]. Eur J Nutr. 2021, 60(1):123-134. [PubMed:32206896] O'Neill D, Britton A, Brunner EJ, etal. Twenty-Five-Year Alcohol Consumption Trajectories and Their Association With Arterial Aging: A Prospective Cohort Study[J]. J Am Heart Assoc, 2017, 6(2):e005288. [PubMed:28219925] Gonzalez-Sanchez J, Garcia-Ortiz L, Rodriguez-Sanchez E, et a1. The Relationship Between Alcohol Consumption with Vascular Structure and Arterial Stiffness in the Spanish Population: EVA Study[J]. Alcohol Clin Exp Res, 2020, 44(9):1816-1824. [PubMed: 32623750] Additional Declarations There is NO conflict of interest to disclose. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6739204","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":463670578,"identity":"68954f99-b1ba-447e-906e-11fecd76a64b","order_by":0,"name":"Yun 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Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACfvnDxz8k/mPj4WdvIFKL5Ay2NIYHbHxykj0HiNRiMIPHjPEBm5yxwY0EYrVIN5g9SOAxS5w58/HGGww1NtEEtZjLHEg3SJBIS+yXTiu2YDiWlttASItlQ8IBiQSDY4kzZ+eYSTA2HCasxeBAYoNEQsL/xA03zxCr5UYym0TCATag93mI1CLZc4zZILGBDRjIQL8kEOMXfvb+jw9/NoCi8vDGGx9qbAhrQXGkRAIpyiFaSNUxCkbBKBgFIwMAABleQhStnZXdAAAAAElFTkSuQmCC","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Shaolei","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-05-24 13:05:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6739204/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6739204/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84558147,"identity":"4b74953f-6aac-4dac-af84-7277a7af1e51","added_by":"auto","created_at":"2025-06-13 12:14:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":787244,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6739204/v1/9260a3df-b59a-4249-900c-46057c3aa893.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"The Effects of Cardiovascular Health Behaviors and Risk Factors on Brachial-Ankle Pulse Wave Velocity in Middle-Aged Men： in Southeastern China","fulltext":[{"header":"SUMMARY","content":"\u003cp\u003e\u003cstrong\u003eWhat is known about topic:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe American Heart Association (AHA) established criteria for ideal cardiovascular health behaviors and risk factors that risk factor control contributed to a 50% reduction in coronary heart disease mortality in the United States between 1980-2000.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Cardiovascular Health Score, developed in 2012, quantitatively integrates these behavioral and physiological metrics, with studies demonstrating its association with improved cardiovascular structure and function in aging populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 6,124 middle-aged men from southeastern China, representing this demographic population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe evaluated cardiovascular risk factors and behavioral traits in relation to brachial-ankle pulse wave velocity (baPWV), a marker of early vascular dysfunction that reflects both central and peripheral arterial health.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese findings suggest controlling these modifiable factors may contribute to the prevention and early intervention of arteriosclerosis.\u003c/p\u003e"},{"header":"BACKGROUND","content":"\u003cp\u003eCardiovascular diseases (CVD) remain the leading cause of global mortality, affecting approximately 290\u0026nbsp;million individuals [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Recognizing this burden, the American Heart Association (AHA) established criteria for ideal cardiovascular health behaviors and risk factors in 2010 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], building on evidence that risk factor control contributed to a 50% reduction in coronary heart disease mortality in the United States between 1980\u0026ndash;2000 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The Cardiovascular Health Score, developed by Huffman et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] in 2012, quantitatively integrates these behavioral and physiological metrics, with studies demonstrating its association with improved cardiovascular structure and function in aging populations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Arterial stiffness, a hallmark of early vascular dysfunction, is most accurately assessed via pulse wave velocity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. As brachial-ankle PWV (baPWV) reflects both central and peripheral arterial health, it serves as a critical indicator of cardiovascular risk. Our prior research in southern Jiangsu Province of China revealed alarmingly low rates of ideal cardiovascular health metrics among young and middle-aged adults [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], underscoring the urgency for targeted interventions. This study specifically examines the impact of cardiovascular health behaviors and risk factors on baPWV in middle-aged men, aiming to elucidate modifiable targets for arterial stiffness prevention. Therefore, it is particularly important to strengthen the modulation of cardiovascular health behaviors and risk factors. The aim of this study was to investigate the effects of cardiovascular health behaviors and risk factors on baPWV in middle-aged men.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSTUDY PARTICIPANTS\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional study of 6124 middle-aged men (aged 40\u0026ndash;64 years) who underwent routine health examinations at The Taihu Rehabilitation Hospital of Jiangsu Province between June 2020 and April 2021. Eligible participants were required to have been residents of southeastern china for at least five years. We excluded individuals with: a history of myocardial infarction or stroke; secondary hypertension; severe hepatic or renal insufficiency; peripheral vascular disease; or incomplete study data. The study protocol was approved by the Ethics Committee of Taihu Rehabilitation Hospital of Jiangsu Province (SGLL-2020006) and the subjects signed the informed consent. All methods were carried out in accordance with relevant guidelines and regulations (e.g. Helsinki guidelines).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDATA ACQUISITION\u003c/h3\u003e\n\u003cp\u003eOur questionnaire collected data on age, smoking status, alcohol consumption, physical exercise, and medical history (including hypertension, diabetes, coronary heart disease, and other chronic conditions, as well as medication use). Height and weight were measured to calculate body mass index (BMI) using the formula: BMI\u0026thinsp;=\u0026thinsp;weight (kg)/height (m)\u0026sup2;. Blood pressure (BP) was measured using a mercury sphygmomanometer. All participants fasted for 8\u0026ndash;12 hours prior to blood collection. Fasting blood glucose (FBG) and total cholesterol (TC) levels were analyzed using a HITACHI 008α automated biochemical analyzer.\u003c/p\u003e\n\u003ch3\u003eDETECTION OF BAPWV\u003c/h3\u003e\n\u003cp\u003ePWV was measured using a standard device by use of applanation tonometry (Corin BP-203RPE II VP-100, Japanese). Before the test, the subjects rested for 5\u0026ndash;10 minutes in a supine position without a pillow. The unified procedure was carried out, and the average value of baPWV on the left and right sides was taken for statistical analysis and baPWV levels above 1400cm/s indicate high arterial stiffness.\u003c/p\u003e\n\u003ch3\u003eCARDIOVASCULAR HEALTH BEHAVIORS AND RISK FACTORS\u003c/h3\u003e\n\u003cp\u003eSince this study\u0026rsquo;s questionnaire did not assess specific vegetable intake, vegetable intake was replaced with salt intake for adjustment, based on the American Heart Association (AHA) definition of cardiovascular health. As defined by the AHA and consistent with our previous studies, cardiovascular health behaviors include smoking, BMI, exercise, and salt intake, while cardiovascular health factors include BP, FBG, and TC [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. (See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification and scores of cardiovascular health behaviors and risk factors in relation to baPWV\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eScoring Standard\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo smoking or quit smoking\u0026thinsp;\u0026gt;\u0026thinsp;1 year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSmoking cessation\u0026thinsp;\u0026le;\u0026thinsp;1 year or occasional/small amount of smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCurrently smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBMI\u0026lt; 25 kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBMI 25.0-29.9 kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elow-salt diet(\u0026lt; 6 g/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emoderate in salt(6\u0026ndash;12 g/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ehigh salt diet(\u0026gt; 12 g/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegular exercise\u0026thinsp;\u0026ge;\u0026thinsp;3 times per week or \u0026ge;\u0026thinsp;90 min per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOccasional exercise\u0026thinsp;\u0026lt;\u0026thinsp;3 times per week, or \u0026le;\u0026thinsp;89 min cumulative time spent exercising per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePhysical inactivity, no additional physical activity beyond daily living and work activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSBP\u0026thinsp;\u0026lt;\u0026thinsp;120 mmHg and DBP\u0026thinsp;\u0026lt;\u0026thinsp;80 mmHg without medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSystolic blood pressure of 120\u0026ndash;139 mmHg or diastolic blood pressure of 80\u0026ndash;89 mmHg or blood pressure\u0026thinsp;\u0026lt;\u0026thinsp;140/90 mmHg with antihypertensive medication.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSystolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg or diastolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-pharmacological FBG \u0026lt; 5.6 mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFBG between 5.6 and 7.0 mmol/L or with hypoglycemic drugs FBG \u0026lt; 5.6 mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFBG\u0026thinsp;\u0026gt;\u0026thinsp;7.0 mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-pharmacological TC \u0026lt; 5.2 mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTC 5.2\u0026ndash;6.2 mmol/L or in the case of lipid-modulating drugs TC \u0026lt; 5.2 mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTC\u0026thinsp;\u0026gt;\u0026thinsp;6.2 mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebaPWV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;1400cm/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1400cm/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: baPWV, brachial-ankle pulse wave conduction velocity; BMI, body mass index; BP, blood pressure; FBG, fasting blood glucose; TC, total cholesterol\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eGROUPING\u003c/h3\u003e\n\u003cp\u003eAccording to the Huffman score [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], cardiovascular health behaviors and risk factors were categorized into three levels: ideal (2 points), average (1 point), and low (0 points), yielding a maximum total score of 14 points. According to the sum of the scores, all subjects were divided into poor group (0\u0026ndash;6 points), medium group (7\u0026ndash;10 points), and good group (11\u0026ndash;14 points).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSTATISTICAL PROCESSING\u003c/h2\u003e \u003cp\u003eSPSS14.0 statistical software was used to test the normal distribution and homogeneity of variance of the measurement data. The measurement data conforming to the normal distribution was represented by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (\u0026plusmn;\u0026thinsp;s). Independent sample t test was used for comparison between two groups, and one-way analysis of variance was used for comparison among multiple groups. LSD method was used for pound-pair comparison, and Tamhane's method was used when variance was uneven. The measurement data of non-normal distribution were expressed as the median (P25, P75), and Kruskal Wallis H test was used for comparison between groups. Measurement data were tested by the chi-square test for trend. logistic regression analysis (Input method) was used to analyze the relationship between each factor and baPWV. logistic regression analysis (Stepwise method) was used to analyze the relationship between cardiovascular health behavior and factor rating and baPWV. A p-value of \u0026lt;\u0026thinsp;0.05 was considered as significant correlation.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eEffects of Cardiovascular Health Behaviors and Risk Factors on baPWV in Middle-Aged Men: This study included 6142 baseline subjects. Participants were categorized into three groups based on their cardiovascular health behavior and factor scores: poor (0\u0026ndash;6 points), medium (7\u0026ndash;10 points), and good (11\u0026ndash;14 points). The poor group comprised 836 subjects (mean age 51.88\u0026thinsp;\u0026plusmn;\u0026thinsp;6.31 years), the medium group 3847 subjects (51.45\u0026thinsp;\u0026plusmn;\u0026thinsp;6.57 years), and the good group 1441 subjects (50.81\u0026thinsp;\u0026plusmn;\u0026thinsp;6.51 years). Age differences among the three groups were statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). We observed decreasing trends across the poor, medium, and good groups for BMI, FBG, SBP, DBP, TC, and baPWV levels, while the proportions of smokers, individuals with normal salt intake, and those who exercised regularly showed gradual increases. The incidence of high arterial stiffness demonstrated a significant decreasing trend across the groups: 70.2% in the poor group, 45.2% in the medium group, and 24.1% in the good group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of Cardiovascular Health Behaviors and Risk Factors in Middle-Aged Men Across Different Risk Groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor Group(n\u0026thinsp;=\u0026thinsp;836)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium Group(n\u0026thinsp;=\u0026thinsp;3847)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGood Group(n\u0026thinsp;=\u0026thinsp;1441)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF/χ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.88\u0026thinsp;\u0026plusmn;\u0026thinsp;6.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.45\u0026thinsp;\u0026plusmn;\u0026thinsp;6.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.81\u0026thinsp;\u0026plusmn;\u0026thinsp;6.51a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI(kg/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.92\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.88\u0026thinsp;\u0026plusmn;\u0026thinsp;2.79a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e108.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking Idea [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60(7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1227(31.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1225(85.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1744.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eaverage [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39(4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e283(7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66(4.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor[n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e737(88.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2337(60.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150(10.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt intake Idea [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e435(11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e484(33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e810.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e474(56.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2729(70.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e886(61.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor[n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e331(39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e683(17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71(4.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise Idea [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110(13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1540(40.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1019(70.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1015.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e533(63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2088(54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e411(28.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor[n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e193(23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e219(5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136.99\u0026thinsp;\u0026plusmn;\u0026thinsp;14.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.27\u0026thinsp;\u0026plusmn;\u0026thinsp;13.25a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119.63\u0026thinsp;\u0026plusmn;\u0026thinsp;10.09ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e501.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85.69\u0026thinsp;\u0026plusmn;\u0026thinsp;9.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.44\u0026thinsp;\u0026plusmn;\u0026thinsp;9.23a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.23\u0026thinsp;\u0026plusmn;\u0026thinsp;7.83ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e444.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.92\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e605.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e337.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebaPWV Level(cm/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1532.84\u0026thinsp;\u0026plusmn;\u0026thinsp;226.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1408.43\u0026thinsp;\u0026plusmn;\u0026thinsp;206.55a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1312.27\u0026thinsp;\u0026plusmn;\u0026thinsp;163.78ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e324.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebaPWV Abnormal[n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e587(70.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1740(45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e348(24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e466.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Measurements are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and counts are expressed as number of cases. baPWV, brachial-ankle pulse wave conduction velocity. Compared with the poor group, aP\u0026thinsp;\u0026lt;\u0026thinsp;0.01; compared with the medium group, bP\u0026thinsp;\u0026lt;\u0026thinsp;0.01. baPWV, brachial-ankle pulse wave conduction velocity; BMI, body mass index; BP, blood pressure; FBG, fasting blood glucose; TC, total cholesterol.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ebaPWV Levels and Incidence of High Arter Stiffness by Number of Ideal Cardiovascular Health Metrics: As the number of ideal cardiovascular health behaviors and risk factors increased incrementally from 0 to 7, we observed: a progressive decline in the incidence of high arterial stiffness across groups (69.4%, 60.0%, 53.9%, 43.2%, 36.2%, 34.8%, 21.2%, and 10.9%, respectively). Corresponding decreases in both baPWV levels and prevalence of high arterial stiffness (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all trends). (See Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ebaPWV Levels and Prevalence of High Arterial Stiffness Across Different Categories of Ideal Cardiovascular Health Behaviors and Risk Factors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of ideal cardiovascular health behaviors and risk factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebaPWV(cm/s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh arterial stiffness [n(%)]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0(n\u0026thinsp;=\u0026thinsp;160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1503.95\u0026thinsp;\u0026plusmn;\u0026thinsp;204.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e111(69.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1(n\u0026thinsp;=\u0026thinsp;633)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1473.18\u0026thinsp;\u0026plusmn;\u0026thinsp;215.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e380(60.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2(n\u0026thinsp;=\u0026thinsp;1235)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1448.84\u0026thinsp;\u0026plusmn;\u0026thinsp;205.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e666(53.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3(n\u0026thinsp;=\u0026thinsp;1517)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1407.09\u0026thinsp;\u0026plusmn;\u0026thinsp;213.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e655(43.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4(n\u0026thinsp;=\u0026thinsp;1389)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1376.64\u0026thinsp;\u0026plusmn;\u0026thinsp;204.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e503(36.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5(n\u0026thinsp;=\u0026thinsp;824)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1347.55\u0026thinsp;\u0026plusmn;\u0026thinsp;193.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e287(34.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6(n\u0026thinsp;=\u0026thinsp;320)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1292.10\u0026thinsp;\u0026plusmn;\u0026thinsp;161.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68(21.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7(n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1252.61\u0026thinsp;\u0026plusmn;\u0026thinsp;134.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5(10.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e295.385\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: baPWV, brachial-ankle pulse wave conduction velocity.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLogistic Regression Analysis of Cardiovascular Health Behaviors and Risk Factors, and High Arterial Stiffness: Smoking, BMI, TC, BP, FBG and age were independent risk factors for high arterial stiffness (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Exercise was a protective factor for high arterial stiffness (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Subjects with average BP, exercise, BMI and FBG were more likely to develop arterial stiffness compared with ideal level of these factors and the OR values were 3.75, 1.99, 1.24, 1.18, respectively (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The OR values of arterial stiffness in subjects with worse BP, exercise, FBG, BMI, TC and smoking were 15.89、1.91、1.80、1.35、1.34、1.25, respectively(P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Salt intake showed no significant association with baPWV levels in middle-aged men (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, each additional year of age was associated with a 10% increased risk of high arterial stiffness (OR\u0026thinsp;=\u0026thinsp;1.10, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (See Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis of various cardiovascular health hehaviors and factors with high arterial stiffness\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.12(0.87\u0026ndash;1.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.25(1.10\u0026ndash;1.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.04(0.88\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.01(0.82\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e119.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e113.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.99(1.76\u0026ndash;2.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.91(1.50\u0026ndash;2.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.24(1.09\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.35(1.09\u0026ndash;1.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.01(0.88\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.34(1.05\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e807.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e300.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.75(3.23\u0026ndash;4.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e806.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.89(13.13\u0026ndash;19.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.18(1.03\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.80(1.46\u0026ndash;2.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol Consumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.95(0.88\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.10(1.09\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003econstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: BMI, body mass index; BP, blood pressure; FBG, fasting blood glucose; TC, total cholesterol.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLogistic Regression Analysis of Cardiovascular Health Behavior and Factor Scores in Relation to High Arterial Stiffness: Compared with the poor group, the unadjusted OR for abnormal baPWV were 0.35 (medium group) and 0.14 (good group) (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). After age adjustment, the corresponding OR were 0.34 and 0.13, respectively (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic analysis of cardiovascular health behavior and factor score subgroups and high arterial stiffness\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e428.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e418.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35(0.30\u0026ndash;0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e162.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.34(0.29\u0026ndash;0.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e421.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14(0.11\u0026ndash;0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e411.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.13(0.11\u0026ndash;0.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e360.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.09(1.08\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eNote: Model 1 indicates unadjusted; model 2 indicates adjusted for age.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eMounting evidence supports the protective role of ideal cardiovascular health metrics against vascular disease. The 2010 AHA studies demonstrated that optimal cardiovascular health status not only reduces cerebrovascular risk but also lowers all-cause mortality among CVD patients [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Subsequent research has confirmed a dose-response relationship, showing progressive reductions in hypertension and diabetes risk with increasing numbers of ideal cardiovascular health components [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Our findings extend this evidence to arterial stiffness, a validated predictor of early cardiovascular dysfunction, in middle-aged men. The developmental trajectory of arterial stiffness may begin earlier than traditionally assumed. An Italian cohort study revealed that aortic stiffening originates in adolescence, where favorable cardiovascular health behaviors and risk factors confer vascular protection [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This phenomenon persists across the lifespan, as evidenced by a 4-5year longitudinal study of older adults (mean age ~ 60 years), where participants maintaining ≥ 5 ideal cardiovascular health indicators exhibited significantly lower arterial stiffness than those with ≤ 2 indicators [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Our cross-sectional data align with these observations, demonstrating: an inverse relationship between ideal cardiovascular health metrics and baPWV (a robust measure of arterial stiffness), and elevated arterial stiffness risk among middle-aged men with suboptimal cardiovascular health profiles after age adjustment. Notably, we identified salt intake, smoking, elevated BMI, TC, BP, FBG, and advancing age as independent baPWV determinants. These findings carry important clinical implications: targeted modification of these modifiable factors-particularly through smoking cessation, dietary sodium reduction, and metabolic parameter optimization-may attenuate arterial stiffening. Given that arterial stiffness precedes overt atherosclerotic changes, our results suggest cardiovascular health interventions could serve as a primary prevention strategy for arteriosclerosis in this population.\u003c/p\u003e \u003cp\u003eSmoking remains one of the most significant modifiable risk factors for CVD, accounting for approximately 20% of CVD-related mortality globally [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The pathophysiological mechanisms underlying this association are multifactorial, involving: impairment of vascular endothelial function, chronic low-grade inflammation, platelet activation and hypercoagulability, sympathetic nervous system overactivation with consequent coronary vasoconstriction, and structural degradation of arterial elastic fibers [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These smoking-induced alterations collectively accelerate arterial stiffening, even at low exposure levels-with emerging evidence suggesting secondhand smoke exposure similarly compromises vascular integrity. Our findings corroborate these established biological pathways, demonstrating that current smokers exhibited 1.25-fold higher odds of elevated baPWV compared to their non-smoking counterparts after multivariable adjustment. This dose-independent effect (observed across all smoking intensities) positions tobacco cessation as a critical intervention target for arterial stiffness mitigation in middle-aged men. The magnitude of this association aligns with previous cohort studies reporting 1.2–1.3 fold increased arterial stiffness risk among smokers.\u003c/p\u003e \u003cp\u003ePrevious studies have shown that exercise improves both cardiovascular risk factors and arterial stiffness [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The effects of different exercise programs are different, especially for the middle-aged and old people, because of the decline of muscle strength, especially high-intensity exercise is easy to cause some sports injuries, and the reasonable exercise program is also controversial. Exercise training, although reducing cardiovascular risk factors in subjects, did not improve arterial stiffness in older adults [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Miyachi etal [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] found that 4 months of resistance movement increased the human muscle strength but appeared to exacerbate the degree of arterial elastic sclerosis. Exercise could reverse the arterial stiffness and abnormal BP in patients with metabolic syndrome and the effect of high intensity exercise is better in subjects with metabolic syndrome underwent 8-week supervised aerobic exercise at target heart rate [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Recent studies have also found that moderate-intensity or low-intensity long-term resistance exercise can improve arterial stiffness and prevent cardiovascular disease [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The results of our study suggest that exercise is a protective factor for baPWV levels in middle-aged men, and even occasional exercise can significantly improve arterial stiffness in this population.\u003c/p\u003e \u003cp\u003ePrevious studies on the correlation between BMI and baPWV mostly focused on hypertensive populations and the results have been reported in controversial. A cross-sectional study of 14,866 hypertensive men in northern China found a negative association between BMI and baPWV, high BMI may be a protective factor for arteriosclerosis,in the age range of 35–55 years is more obvious [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Mallat etal [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found a positive correlation between pulse wave velocity and body mass index in elderly hypertensive patients. A study of 202 essential hypertension patients found no association between BMI and arterial stiffness [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. BMI was found to be an independent risk factor for baPWV in middle-aged men from southern Jiangsu province, China. Research on the effect of TC on baPWV levels is generally consistent. A recent large-scale community-based study of 45,092 people in our northern population found a significant association between TC and baPWV, with each unit increase in TC after adjustment for related variables, baPWV increases by 5.34 cm/s [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The possible mechanism is that TC can cause direct damage to vascular endothelial function, which leads to arterial stiffness and inflammatory responses to lipid formation lead to the degradation of collagen, elastic fibers, and proliferation of smooth muscle cells, which also contribute to the development of arterial stiffness [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Our study identified elevated TC as an independent risk factor for higher baPWV levels in middle-aged men. Specifically, individuals with suboptimal TC levels had a 1.34-fold increase in arterial stiffness compared to those with ideal TC levels. These findings suggest that active management of TC through lifestyle modifications and/or pharmacological interventions may help reduce arterial stiffness.\u003c/p\u003e \u003cp\u003eOur study found that blood pressure had the greatest effect on baPWV levels among all cardiovascular health behaviors and risk factors, middle-aged men with average and poor blood pressure were 3.75 to15.89 times arteriosclerosis than those with ideal blood pressure. Blood pressure is an important factor in arterial stiffness [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and the possibly mechanism of its effect were increased blood pressure levels cause changes in the structure and function of the vascular elastic arterial wall which leads to arteriosclerosis [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The effect of blood pressure on arterial stiffness should also be taken into account by age. A large cross-sectional study in northern China found a positive correlation between systolic blood pressure and arterial stiffness in different age groups, with the strongest correlation in the youth group, followed by the middle-aged group, and the weakest in the elderly group [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Cecelja et al [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] found positive correlations between systolic and diastolic blood pressure levels and arteriosclerosis in young and middle-aged people. We also found the age was an independent risk factor for abnormal arterial stiffness in the middle-aged male population, with a 1.1-fold increase in the risk of arterial stiffness for each 1-year increase in age.\u003c/p\u003e \u003cp\u003eIt is suggested that the vascular structure changes with aging. It has also been reported that blood pressure and arterial stiffness may be mutually causal [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In conclusion, it is recommended that middle-aged men should actively monitor and control their blood pressure in order to reduce the occurrence and development of arteriosclerosis. Diabetes is an independent risk factor for cardiovascular disease, and patients with diabetes are arteriosclerosis at an early age and are prone to cardiovascular events [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The American diabetes society notes impaired FBG regulation and increased carotid intima-media thickness in patients with type 2 diabetes, independent of other risk factors [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Accumulation of metabolic syndrome components, including blood glucose levels, was strongly associated with baPWV change rates, with blood pressure and FBG levels having the greatest effect on baPWV change rates in more than 2 components [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The present study found that FBG was an independent risk factor for baPWV in a middle-aged male population, consistent with previous studies [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies have debated the effects of alcohol consumption on cardiovascular health and arterial stiffness. Moderate alcohol consumption appears to have short-term cardiovascular protective effects, whereas heavy alcohol consumption can be harmful to the vascular system [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Studies have shown that long-term alcohol consumption in men increases arterial stiffness after 4–5 years suggesting that even moderate alcohol consumption may confer long-term cardiovascular risk, especially in middle-aged and older men [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. A Spanish multicenter study showed that heavy alcohol consumption (\u0026gt; 70 g/week) increased carotid intima-media thickness, but did not find an effect on baPWV [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This study found no effect of alcohol consumption on arterial stiffness in middle-aged men, and further prospective studies are needed to confirm this. In addition, there are few studies on the relationship between dietary salt intake and arterial stiffness, and our study did not find any effect of salt intake on baPWV levels. A recent study suggested that dietary salt restriction had no effect on baPWV levels [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], which is consistent with the present study.\u003c/p\u003e \u003cp\u003eLimitations: This study is a cross-sectional study, and is not based on a population-wide or community-based sample, it cannot be shown that ideal cardiovascular health and behavioral factors are causally associated with baPWV in a middle-aged male population, and further prospective intervention studies are needed to clarify this.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors have declared that no conflicts of interest exist.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFund program\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eKey Medical Disciplines Project （Joint construction） of Jiangsu Province（IDXKC2016011）；Wuxi Science and Technology Research and Development Projects（CMB41S1701）\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWeiwei C, Runlin G, Lisheng L, et a1. 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[PubMed:27912210]\u003c/li\u003e\n\u003cli\u003eMoh MC, Sum CF,Tavintharan S, etal. Association of the anti-angiogenic factor secreted protein and rich incysteine (SPARC)with vascular complications among Chinese type 2 diabetic patients in Singapore [J]. J Diabetes Complication, 2016, 31(7):121-132. [PubMed:28479157]\u003c/li\u003e\n\u003cli\u003eGreenlee RT, Naleway AL, Vidaillet H. Incidence of myocardial in farction in a general population: the Marshfield Epidemiologic Study Area[J]. WMJ, 2002, 101(7):46-52. [PubMed:12426920]\u003c/li\u003e\n\u003cli\u003eSang Y, Wu X, Miao J, etal. Determinants of Brachial-Ankle Pulse Wave Velocity and Vascular Aging in Healthy Older Subjects. Med Sci Monit, 2020;26:e923112.[ PubMed: 32445331]\u003c/li\u003e\n\u003cli\u003eLaguzzi F, Baldassarre D, Veglia F, etal. Alcohol consumption in relation to carotid subclinical atherosclerosis and its progression: results from a European longitudinal multicentre study[J]. Eur J Nutr. 2021, 60(1):123-134. [PubMed:32206896]\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Neill D, Britton A, Brunner EJ, etal. Twenty-Five-Year Alcohol Consumption Trajectories and Their Association With Arterial Aging: A Prospective Cohort Study[J]. J Am Heart Assoc, 2017, 6(2):e005288. [PubMed:28219925]\u003c/li\u003e\n\u003cli\u003eGonzalez-Sanchez J, Garcia-Ortiz L, Rodriguez-Sanchez E, et a1. The Relationship Between Alcohol Consumption with Vascular Structure and Arterial Stiffness in the Spanish Population: EVA Study[J]. Alcohol Clin Exp Res, 2020, 44(9):1816-1824. [PubMed: 32623750]\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cardiovascular health, Arteriosclerosis, Middle-aged men, novel anthropometric parameters, hyperuricemia, obesity","lastPublishedDoi":"10.21203/rs.3.rs-6739204/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6739204/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCardiovascular diseases (CVD) were the leading cause of global mortality. We conducted a across sectional study and to investigate the association between cardiovascular health behaviors and risk factors with brachial-ankle pulse wave velocity (baPWV) in middle-aged men. A total of 6124 men of health examination were enrolled. According to the scores of cardiovascular health behaviors and risk factors, all subjects were divided into poor group (0-6 points), medium group (7-10 points) and good group (11-14 points). Levels of BMI, FBG, SBP, DBP, TC, and baPWV demonstrated a significant downward trend across three groups (from poor to good) with improving scores of cardiovascular health behavior and factor (P\u0026lt;0.05). \u0026nbsp;The incidence of high arterial stiffness in the poor, medium and good groups were 70.2%, 45.2% and 24.1% respectively which showed a gradual decrease (P\u0026lt;0.05). BMI, TC, elevated BP, FBG, Smoking, and age were identified as independent risk factors for increased baPWV, while physical exercise served as a protective factor (all P\u0026lt;0.05). After age adjustment, the odds ratios (ORs) for high arterial stiffness were significantly lower in the medium (OR=0.34) and good (OR=0.13) groups compared to the poor group (both P\u0026lt;0.05). Cardiovascular health behaviors and risk factors were significantly associated with brachial-ankle pulse wave velocity (baPWV) in middle-aged men. Targeted modification of these modifiable factors may contribute to the prevention and management of arterial stiffness in this population.\u003c/p\u003e","manuscriptTitle":"The Effects of Cardiovascular Health Behaviors and Risk Factors on Brachial-Ankle Pulse Wave Velocity in Middle-Aged Men： in Southeastern China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-30 09:23:30","doi":"10.21203/rs.3.rs-6739204/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"30113b39-2a49-48bf-a8c2-d0fbf9e8f5f6","owner":[],"postedDate":"May 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49234542,"name":"Health sciences/Risk factors"},{"id":49234543,"name":"Biological sciences/Physiology/Cardiovascular biology/Cardiovascular diseases/Vascular diseases/Atherosclerosis"}],"tags":[],"updatedAt":"2025-06-13T12:06:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-30 09:23:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6739204","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6739204","identity":"rs-6739204","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}