Abstract
Increased plasma homocysteine (Hcy) has been identified as one of the important risk factors for cardiovascular disease. However, the association between plasma Hcy and peripheral artery disease (PAD) is still controversial. This study aimed to investigate the association between plasma Hcy and PAD and the potential modifier factors in Chinese hypertensive adults. A total of 25 300 hypertensive patients aged 18 years or older were included in the analysis in this cross‐sectional study. The outcome was PAD, which defined as an ankle‐brachial index ≤0.90 in either limb. Multiple logistic regression was used to analyze the relationship between plasma Hcy and PAD. The median plasma Hcy was 14.00 (interquartile range: 11.60–17.80) μmol/L. There was a significant positive association between plasma Hcy and PAD (per SD increment; OR: 1.13; 95% CI: 1.06–1.19). Patients in the upper plasma Hcy tertile (≥16.16 μmol/L) were associated with a 53% increased risk of PAD compared with patients in the lower tertile (<12.33 μmol/L) after adjustment for multiple potential confounders. Subgroup analyses showed the association between Hcy and PAD was robust among various strata. Among Chinese adults with hypertension, plasma Hcy is an independent risk factor for PAD. This finding may improve the risk stratification of PAD.
Keywords: ankle‐brachial index, epidemiology, homocysteine, hypertension, peripheral arterial disease
1. INTRODUCTION
As a recognized fundamental pathophysiological mechanism of vascular disease, atherosclerosis is also a major pathological manifestation of peripheral artery disease (PAD). 1 Meanwhile, PAD has become a common atherosclerotic cardiovascular disease (ASCVD) after coronary heart disease (CHD) and stroke in the world, especially in low‐income countries. 2 Based on global data statistics, the number of cases of PAD is estimated to have increased to 236 million in 2015, 3 and will continue to increase, especially in low‐ and middle‐income countries. As a developing country, the prevalence of PAD in China is particularly severe. 4 The ankle‐brachial index (ABI) is the ratio of ankle pressure to brachial systolic pressure, and can be used as a first‐line non‐invasive test for screening and diagnosis of asymptomatic PAD. 5 Study have shown that men with low ABI (≤0.90) had a threefold increased risk of total death and fourfold increased risk of cardiovascular death compared with the reference group ABI (1.11–1.20), and women had a higher risk of total and cardiovascular death than men. 6 However, asymptomatic patients of PAD still constitute the majority and identifying early peripheral disease is a serious challenge in underdeveloped regions. 7
As a sulfur‐containing non‐protein amino acid, homocysteine (Hcy) can induce inflammatory response and oxidative stress in endothelial cells, and then promote the formation of atherosclerosis. 8 Studies have shown that plasma Hcy is an independent risk factor for hypertension, 9 , 10 stroke, 11 ischemic heart disease, 12 dementia, 13 even all‐cause mortality 14 and cardiovascular death 15 in the general population. The data showed that prevalence of hyperhomocysteinemia (Hcy ≥ 15.00 μmol/L) was 37.20% 16 in Chinese general population and reached 75% in patients with essential hypertension. 17 Furthermore, plasma Hcy and hypertension synergistically increase the risk of all‐cause mortality and cardiovascular mortality. 18 This may indicate that patients with high plasma Hcy may have a higher risk of PAD in hypertensive patients. However, it is still uncertainty regarding the association between plasma Hcy and PAD. Previous studies have shown that plasma Hcy is positively association with the risk of PAD, 19 , 20 but others have not found an obvious association between them. 21 , 22 In addition, up to now, there is no study on the association between plasma Hcy and the risk of PAD in patients with hypertension.
So, it is necessary to investigate the association between plasma Hcy and PAD in a Chinese hypertensive population, and analyze the possible effect modifiers.
2. METHODS
2.1. Study design and participants
In this study, all data used were obtained from the China H‐type Hypertension Registry Study (registration number: ChiCTR1800017274), which has been extensively reported previously. 23 In brief, this study was an ongoing multicenter prospective cohort study in a real‐world setting. Eligible participants were man and woman with age over 18 years and with hypertension, which was defined as seated resting systolic blood pressure (SBP) ≥140 mm Hg, or/and diastolic blood pressure (DBP) ≥90 mm Hg or/and the use of antihypertensive medications at baseline. Patients who are incapable to provide informed consent and unable to be followed up because of psychological or nervous system impairment were excluded. All participants have provided with informed consent. Exclusion criteria included the following: (1) Inability to provide informed consent due to psychological or neurological impairment; (2) Inability to follow up for a long time according to the study protocol or plan to relocate in the short term; and (3) Patients evaluated by physicians who were not suitable for enrollment or long‐term follow‐up. Finally, from March to August 2018, a total of 28 684 hypertensive patients were recruited from Wuyuan in Jiangxi province and Yuexi in Anhui province of China. After excluding those with missing ABI (n = 3330) and plasma Hcy data (n = 54), a total of 25 300 hypertensive patients were included in the final data analysis in Figure 1.
FIGURE 1.
Flow chart of the study.
This study complied with the Declaration of Helsinki and was approved by the Ethics Committee of the Institute of Biomedical Sciences, Anhui Medical University (Ethics NO. CH1059) and the Second Affiliated Hospital of Nanchang University (Ethics NO. 2018019). All patients signed informed consent before participating in this study.
2.2. Data collection
Health interviews were conducted by trained research staffs, and the demographic characteristics of the study population were collected in the form of face‐to‐face questionnaires. Demographic information included sex, age, lifestyle (smoking status, alcohol drinking status etc.), medical history, and medication information. Anthropometric measures included height, weight, and blood pressure. Blood pressure was measured as the average of three measurements with an electronic sphygmomanometer (OMRON) while the participant was seated and after 5 min of rest in the morning.
All patients were informed 1 day in advance that fasting venous blood samples would be collected the next morning. Venous blood samples from all study participants were collected after an overnight fast, frozen, and transported to the Shenzhen Biaojia Biotechnology Laboratory. Plasma Hcy, total cholesterol, triglyceride, albumin, low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C), uric acid (UA). Laboratory staffs were blind to the study content.
Body mass index (BMI) was calculated as weight (kg) divided by the square of height (m). Diabetes was defined as fasting blood glucose ≥7.0 mmol/L, history of diabetes, or use of glucose‐lowering drugs. Estimated glomerular filtration rate (eGFR) was estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI) equation, 24 and parameters of the equation were measured by Beckman Coulter automatic clinical analyzer.
2.3. PAD
The presence of PAD was defined as an ABI ≤ 0.9 in either leg. 5 The ABI, the ratio of systolic pressure at the ankle to that in the arm, is quick and easy to measure and has been used for many years in vascular practice to screen and assess the severity of PAD in the legs. 25 The ABI was measured using established methods. After participants rested supine for 5 min, the Omron Colin BP‐203RPE III device (Omron Health Care, Kyoto, Japan) was used to measure systolic pressures in the right and left brachial artery, right and left dorsalis pedis and posterior tibial arteries. The ABI was calculated as the highest systolic blood pressure at the ankle divided by the highest systolic blood pressure at the ipsilateral upper arm. The lowest leg ABI was used in analyses. In addition, the second measurement will be performed, if the deviation of ABI results measured by the patient is large from the normal value.
2.4. Covariates
The covariates included in all the analyses were age, sex, BMI, smoking status, alcohol drinking status, SBP, DBP, laboratory results [plasma Hcy, total cholesterol, triglycerides, albumin, HDL‐C, LDL‐C, UA, eGFR], history of disease (Diabetes, CHD, stroke) and medication use (antihypertensive drugs, glucose‐lowering drugs, lipid‐lowering drugs, antiplatelet drugs).
2.5. Statistical analysis
Continuous variables were expressed as mean ± standard deviation (mean ± SD), and categorical variables were expressed as percentage (%). T‐tests or χ2 test was used to compare the differences of variables between the patients with and without PAD. Multivariate logistic regression equation was used to analyze the odds ratio (OR) and 95% confidence interval (CI) of the association between plasma Hcy (continuous and categorical variable) and PAD after adjusting for known confounding factors. Tests for trend were performed by modeling the tertile classification of plasma Hcy as a continuous variable. At the same time, smooth curve fitting (penalized spline method) was used to visually display the changing trend of plasma Hcy and PAD.
To further evaluate the potential effect of different populations on plasma Hcy and PAD, the effects of sex, age (<60 vs. ≥60 years old), BMI (<24 vs. ≥24 kg/m2), SBP (<140 vs. ≥140 mm Hg), DBP (<90 vs. ≥90 mm Hg), smoking status, alcohol consumption status, LDL‐C (<2.6 vs. ≥2.6 mmol/L), UA (<420 vs. ≥420 mmol/L), eGFR (<60 vs. ≥60 mL/min/1.73 m−2) and stroke (yes vs. no) were compared and performed subgroup analyses. Potential effect modifiers were assessed in subgroup analyses and interaction tests, where plasma Hcy was used as a continuous variable.
The determination of statistical significance was grounded upon the criterion of a two‐sided p value < .05. All data analyses were executed through the utilization of R software, specifically version 4.2.2(http://www.r‐project.org).
3. RESULTS
3.1. Characteristics of study participants
A total of 25 300 hypertensive patients were included in the data analysis. The characteristics of participants stratified by presence of PAD for all patients were presented in Table 1, and the characteristics of the population stratified by plasma Hcy are shown in Table S1. Overall, the prevalence of PAD was 2.7% (680/25300), with a mean (SD) age of 60.7 (9.6) years and 47.0% in men. The median plasma Hcy levels was 14.0 (interquartile range 11.6–17.8) μmol/L. The range of plasma Hcy in tertiles were <12.33, 12.33–16.16, and ≥16.16 μmol/L, respectively. Compared with the non‐PAD group, the PAD group were older, had higher SBP, plasma Hcy, UA, and LDL‐C level, and had lower BMI, DBP, albumin, HDL‐C, and eGFR (all p < .05). There were no statistically significant differences in alcohol consumption status, total cholesterol, triglyceride, and use of glucose‐lowering and lipid‐lowering drugs between PAD and non‐PAD groups.
TABLE 1.
Characteristics of study participants by PAD.
| Variables | Total | PAD (ABI ≤ 0.9) | p value | |
|---|---|---|---|---|
| No | Yes | |||
| N | 25300 | 24620 | 680 | |
| Male, n (%) | 11899 (47.0) | 11521 (46.8) | 378 (55.6) | <.001 |
| Age (years) | 60.7 ± 9.6 | 60.6 ± 9.4 | 66.7 ± 11.7 | <.001 |
| BMI (kg/m2) | 24.1 ± 3.7 | 24.1 ± 3.7 | 23.6 ± 4.4 | <.001 |
| SBP (mm Hg) | 146.6 ± 18.1 | 146.5 ± 18.0 | 149.7 ± 22.6 | <.001 |
| DBP (mm Hg) | 91.0 ± 11.0 | 91.1 ± 10.9 | 86.8 ± 12.3 | <.001 |
| Smoking status, n (%) | <.001 | |||
| Never | 14274 (56.4) | 13982 (56.8) | 292 (42.9) | |
| Before | 4013 (15.9) | 3892 (15.8) | 121 (17.8) | |
| Current | 7013 (27.7) | 6746 (27.4) | 267 (39.3) | |
| Alcohol drinking status, n (%) | .117 | |||
| Never | 16741 (66.2) | 16298 (66.2) | 443 (65.1) | |
| Before | 3094 (12.2) | 2994 (12.2) | 100 (14.7) | |
| Current | 5465 (21.6) | 5328 (21.6) | 137 (20.1) | |
| Laboratory results | ||||
| Homocysteine (μmol/L) | 14.0 (11.6–17.8) | 13.9 (11.5–17.7) | 16.1 (12.8–20.7) | <.001 |
| Total cholesterol (mmol/L) | 5.2 ± 1.1 | 5.2 ± 1.1 | 5.3 ± 1.2 | .119 |
| Triglyceride (mmol/L) | 1.4 (0.9–2.0) | 1.4 (0.9–2.0) | 1.4 (1.0–2.1) | .454 |
| Albumin (g/L) | 46.5 ± 3.7 | 46.5 ± 3.7 | 45.7 ± 3.6 | <.001 |
| HDL‐C (mmol/L) | 1.6 ± 0.4 | 1.6 ± 0.4 | 1.5 ± 0.4 | <.001 |
| LDL‐C (mmol/L) | 3.1 ± 0.8 | 3.1 ± 0.8 | 3.2 ± 0.9 | <.001 |
| UA (mmol/L) | 403.1 ± 116.7 | 402.1 ± 116.5 | 439.1 ± 120.5 | <.001 |
| eGFR (mL/min/1.73m−2) | 91.0 ± 18.8 | 91.3 ± 18.6 | 80.9 ± 22.8 | <.001 |
| Complications, n (%) | ||||
| Diabetes | 4110 (16.2) | 3976 (16.1) | 134 (19.7) | .015 |
| Stroke | 3188 (12.6) | 3055 (12.4) | 133 (19.6) | <.001 |
| CHD | 2496 (9.9) | 2400 (9.7) | 96 (14.1) | <.001 |
| Medication use, n (%) | ||||
| Antihypertensive drugs | 16650 (65.8) | 16162 (65.6) | 488 (71.8) | <.001 |
| Glucose‐lowering drugs | 995 (3.9) | 966 (3.9) | 29 (4.3) | .725 |
| Lipid‐lowering drugs | 764 (3.0) | 740 (3.0) | 24 (3.5) | .501 |
| Antiplatelet drugs | 1130 (4.5) | 1083 (4.4) | 47 (6.9) | .002 |
Note: Data are expressed as mean ± SD, numbers (percentage) or quartile (IQR) as appropriate.
Abbreviations: 95% CI, 95% confidence interval; BMI, body mass index; CHD, coronary heart disease; DBP, diastolic blood pressure; eGFR, estimate glomerular filtration rate; HDL‐C, high‐density cholesterol; LDL‐C, low‐density lipoprotein cholesterol; OR, odd ratio; PAD, peripheral arterial disease; SBP, systolic blood pressure; UA, uric acid.
3.2. Association between plasma Hcy and PAD
The association between plasma Hcy and PAD is shown in Figure 2. In general, the risk of PAD significantly increased with the increase of plasma Hcy level. In addition, we also analyzed the association between plasma Hcy and ABI in Figures S1 and S2. Table 2 showed that there is a significant positive association between plasma Hcy levels and the risk of PAD (per SD increment; OR: 1.13; 95% CI: 1.06–1.19) after adjustment for possible confounding factors. Consistently, compared with the lowest tertile of plasma Hcy (T1), the highest tertile group (T3) had higher risk of PAD (OR: 1.53; 95% CI: 1.22–1.92) in the fully adjusted model. After combined the low and moderate plasma Hcy groups (T1‐T2) as a reference group, high plasma Hcy level (T3) is still significantly associated with the risk of PAD (OR: 1.43; 95% CI: 1.21–1.70). In addition, there may be a linear association between plasma Hcy and PAD (p for trend < .001).
FIGURE 2.
The association between plasma homocysteine with the risk of PAD. Model was adjusted for sex, age, BMI, SBP, DBP, smoking status, alcohol drinking status, albumin, triglyceride, HDL‐C, LDL‐C, UA, eGFR, diabetes, stroke, and CHD. 95% CI, 95% confidence interval; BMI, body mass index; CHD, coronary heart disease; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; Hcy, homocysteine; HDL‐C, high‐density cholesterol; LDL‐C, low‐density lipoprotein cholesterol; OR, odd ratio; PAD, peripheral arterial disease; SBP, systolic blood pressure; UA, uric acid.
TABLE 2.
Association of plasma homocysteine with the risk of PAD.
| Hcy (μmol/L) | N | Events, n (%) | PAD OR (95% CI), p value | ||
|---|---|---|---|---|---|
| Crude | Model I | Model II | |||
| Per SD increment | 25300 | 680 (2.67) | 1.22 (1.16–1.28), <.001 | 1.18 (1.12–1.24), <.001 | 1.13 (1.06–1.19), <.001 |
| Tertiles | |||||
| T1 (<12.33) | 8423 | 145 (1.72) | Ref. | Ref. | Ref. |
| T2 (≥12.33, <16.16) | 8437 | 196 (2.32) | 1.36 (1.09–1.69), .006 | 1.15 (0.92–1.43), .225 | 1.11 (0.89–1.39), .362 |
| T3 (≥16.16) | 8440 | 339 (4.02) | 2.39 (1.96–2.91), <.001 | 1.84 (1.49–2.27), <.001 | 1.53 (1.22–1.92), <.001 |
| p for trend | <.001 | <.001 | <.001 | ||
| Categories | |||||
| T1–T2 (<16.16) | 16860 | 341 (2.02) | Ref. | Ref. | Ref. |
| T3 (≥16.16) | 8440 | 339 (4.02) | 2.03 (1.74–2.36), <.001 | 1.69 (1.44–1.99), <.001 | 1.43 (1.21–1.70), <.001 |
Note: Model I was adjusted for sex, age, BMI, SBP, and DBP. Model II was adjusted for Model I plus smoking status, alcohol drinking status, albumin, triglyceride, HDL‐C, LDL‐C, UA, eGFR, diabetes, stroke, and CHD.
Abbreviations: 95% CI, 95% confidence interval; BMI, body mass index; CHD, coronary heart disease.; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; Hcy, homocysteine; HDL‐C, high‐density cholesterol; LDL‐C, low‐density lipoprotein cholesterol; OR, odd ratio; PAD, peripheral arterial disease; SBP, systolic blood pressure; UA, uric acid.
After conducting additional sensitivity analyses, which involved further adjusting for the use of medications (such as antihypertensive drugs, glucose‐lowering drugs, lipid‐lowering drugs, and antiplatelet drugs) and family history of diseases (such as family history of hypertension, family history of diabetes, family history of stroke and family history of coronary atherosclerotic heart disease) as shown in Table S2, and excluding patients with an ABI ≥ 1.4 (n = 25) as indicated in Table S3, the association between plasma Hcy and PAD did not show any significant changes. These findings suggest that the relationship between plasma Hcy and PAD remains consistent even after accounting for medication use and excluding certain patient groups. In response to reviewers' comments, we found no association between plasma Hcy and arterial calcification (AB ≥1.4) in Table S4. The results of propensity score showed that the P values of each variable in the control group and the case group were all > 0.05 (Table S5). At the same time, PAD was defined as the mean of left and right ABI ≤0.90, and multiple logistic regression was again used to explore the association between plasma Hcy levels and the risk of PAD (Table S6). The results showed that there was an independent association between plasma Hcy and the risk of PAD after adjusting for multiple confounding factors, which was consistent with the results of taking the smaller ABI for analysis.
3.3. Subgroup analyses
The stratified and interaction analyses of the association between plasma Hcy and PAD showed in Figure 3. Overall, no significant interactions that modified the association between plasma Hcy and PAD were found between stratification variables, including age, sex, BMI, SBP, DBP, stroke, smoking status, alcohol drinking status, LDL‐C, UA, and eGFR (all p‐interaction > .05).
FIGURE 3.
The association between plasma homocysteine with the risk of PAD in various subgroups. Model was adjusted, if not stratified, for sex, age, BMI, SBP, DBP, smoking status, alcohol drinking status, albumin, triglyceride, HDL‐C, LDL‐C, UA, eGFR, diabetes, stroke, and CHD. 95% CI, 95% confidence interval; BMI, body mass index; DBP, diastolic blood pressure; eGFR, estimate glomerular filtration rate; LDL‐C, low‐density lipoprotein cholesterol; OR, odd ratio; PAD, peripheral arterial disease; SBP, systolic blood pressure; UA, uric acid.
4. DISCUSSION
In the cross‐sectional study, we demonstrated that there was a significant positive association between plasma Hcy levels and the risk of PAD in Chinese adults with hypertension. In addition, the association between plasma Hcy and PAD was steady among various strata in subgroup analyses.
So far, the relationship between plasma Hcy and PAD is inconclusive. 26 In addition, most studies on plasma Hcy and PAD are based on the general population, and no findings have been found in hypertensive patients. A nested case‐control study of American population found a positive association between higher Hcy levels and PAD risk and an inverse association between higher folate intake and PAD risk in men. 27 Similarly, a case‐control study by Rong and coworkers also showed a higher risk of PAD with high plasma Hcy levels in Chinese adults. 19 Moreover, a multi‐population meta‐analysis of 11 687 patients showed higher plasma Hcy levels in patients with PAD compared with healthy individuals. 28 Consistent with the conclusions of our study, these studies all showed a significant association between plasma Hcy and PAD. However, Ridker and coworkers did not find a clear association between plasma Hcy and PAD in a nested case‐control study of 240 United States male physicians. 29 The same result was observed in a cohort study of US female health professionals, which found that the association between plasma Hcy and PAD disappeared after further adjustment for age, BMI, smoking status, diabetes, hypertension, and menopause status. 22 Furthermore, a cohort study did not find a significant association between plasma Hcy and progression of large‐vessel PAD or small‐vessel PAD in 403 non‐Hispanic whites over a period of 4.5 years. 30 However, It is important to note that these studies only focused on special sex and occupational and ethnic populations, which may cause a large selection bias, especially the medical staffs, and then the association between plasma Hcy and PAD was masked. Meanwhile, plasma Hcy levels of these studies were significantly lower (Hcy < 15.00 μmol/L) in both controls and case groups, which may not be sufficient to produce qualitative changes in the peripheral arteries. In addition, most of these studies did not further explore the possible moderating factors between plasma Hcy and PAD.
This study provides new insights into the association between plasma Hcy and PAD. First of all, to the best of my knowledge, this is the first study to investigate the association between plasma Hcy and PAD in a hypertensive population. As an important pathogenic factor of ASCVD, many studies have shown that Hcy can cause damage to vascular endothelial cells through a variety of pathways, including oxidative stress, 31 endoplasmic reticulum stress, 32 inhibition of S‐adenosylmethionine (SAM) transmethylation, 33 Hcy acidification and other pathways. 34 A population‐based study by Gori and coworkers showed significant associations of interleukin 6 and interleukin 1 receptor antagonist with plasma Hcy after adjustment for multiple factors, 35 and oxidative stress may be the main mechanism of Hcy‐induced atherosclerosis. These mechanisms further explain the intrinsic relationship between Hcy and PAD, and also provide the possibility of reducing plasma Hcy by supplementing folic acid or B vitamins to prevent PAD. However, whether plasma Hcy is a marker or a cause of PAD has not been determined. A randomized controlled trial showed that low‐dose folic acid or 5‐methyltetrahydrofolate supplementation significantly reduced plasma Hcy levels and slightly improved ankle‐brachial pressure index and brachial‐knee pulse wave velocity. 36 On the contrary, study conducted by Karsten Sydow and coworkers showed that supplementation with high doses of folic acid or B vitamins had no significant effect on the ankle‐brachial stress index compared with control. 37 These results seem to reconfirm that there is no significant association between plasma and vascular Hcy, and there were independent compartments between plasma and vascular Hcy metabolism. 38 Whether Hcy metabolism in peripheral arteries is tissue‐specific in plasma and blood vessels is not known, which requires further research.
Secondly, most previous studies have shown that there seems to be a sex difference in PAD, 27 in which males have a slightly higher prevalence of PAD than females due to risk factors such as smoking, drinking and obesity. 39 , 40 This is consistent with our results. In the stratified analysis, it was not female but male that was associated with the risk of PAD, but there was no a stark difference between them. This may be due to the fact that most of the population in this study was middle‐aged and elderly (average age was 63.9 years), and most of the women were postmenopausal, which led to the loss of the direct 41 or indirect 42 protective effect of estrogen on vascular endothelium, and accelerates the progression of PAD in women. In addition, with increasing age, the risk of developing PAD increases dramatically in the elderly population, especially between 60s and 70s, 7 which also can be seen in our results of the subgroup analysis. Finally, studies have shown that kidney injury may cause an increase in plasma Hcy levels. 43 However, in this study, the association between plasma Hcy and PAD remained after adjustment for renal function, and no significant interaction was found for renal function, which suggests that the effect of plasma Hcy on PAD may be independent of renal function. Guallar and coworkers suggested that renal injury may be an intermediate variable rather than a confounder. 44
Limitations of this study included: (1) as a cross‐sectional study, this study cannot explain the causal relationship between plasma Hcy and PAD, only show a strong association between them; (2) this study is only a study of Chinese adults with hypertension in rural areas, and whether it can be extended to other populations needs further research; (3) assessment of resting ABI may miss patients with PAD whose disease is identified only after exercise, but it is generally not feasible to include postexercise ABI in large epidemiological studies 45 ; and (4) although the known confounding factors were adjusted as much as possible, there are still some unknown residual confounding factors that were not adjusted, such as vitamin B12 and folic acid levels and eating habits.
5. CONCLUSIONS
In summary, our study suggested a significant positive association between plasma Hcy and PAD in Chinese adults with hypertension, which provides the possibility of primary prevention of PAD. However, more studies are needed to further verify whether plasma Hcy is a marker or a cause of PAD.
AUTHOR CONTRIBUTIONS
This article was a collaborative effort by many people, and the following is each person's contribution to this article: Chuanli Yu and Congcong Ding are the main contributors and co‐authors of the article. Yu Chuanli completed the literature search, data analysis, and data interpretation and the writing of the article, and with the help of Dr. Ding Congcong, he further improved the article before it was presented. Xiaoshu Cheng, Lihua Hu, Peixu Zhao, Yimeng Shi, Jin ‘e Liu, Liting Zhang, and Dan Sun conceived the study and participated in its design and coordination. Huihui Bao is the corresponding authors of this paper and participated in the study design and provided critical revision. All authors read and approved the final manuscript.
CONFLICT OF INTEREST STATEMENT
The authors declare that there is no conflict of interest that influences the publication of articles.
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ACKNOWLEDGMENTS
Thanks to all investigators and subjects who participated in the China Hypertension Registry Study. This work was supported by National Science and Technology Award reserve project (Grant number: 20223AEI91007), Science and Technology Innovation base plan of Jiangxi Province‐Jiangxi Clinical Medical Research Center (Grant number: 20223BCG74012), Jiangxi Science and Technology Innovation base construction project Center (Grant number: 20221ZDG02010), Jiangxi Innovation‐driven “5511” project (Grant number: 20165BCD41005), and Natural Science Foundation of Jiangxi Province (Grant number: 20212ACB206019, 20224BAB206090).
Yu C, Ding C, Hu L, et al. Association of plasma homocysteine with peripheral arterial disease in the hypertensive adults: A cross‐sectional study. J Clin Hypertens. 2024;26:286–294. 10.1111/jch.14766
Chuanli Yu and Congcong Ding contributed equally and should be considered as co‐first authors.
DATA AVAILABILITY STATEMENT
Because of the sensitivity of the questions asked in this study, we assured survey respondents that raw data would be confidential and would not be shared.
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Data Availability Statement
Because of the sensitivity of the questions asked in this study, we assured survey respondents that raw data would be confidential and would not be shared.