Abstract
Objectives
The prevalence of and risk factors for IAD among different ethnicity groups was unknown. Our aim was to investigate the prevalence of and risk factors for IAD among Han, Uygur and Kazakh ethnicities in Xinjiang. China.
Methods
In total, 14,618 adult participants (7,799 males and 6,819 females) were recruited from the Cardiovascular Risk Survey. A 4-stage stratified cluster random sampling method was used. The participants’ personal information and medical history were assessed by questionnaire. IAD was diagnosed by a noninvasive arteriosclerosis analyzer.
Results
The prevalence of abnormal IAD among the general population was 14.3%, with 12.5% in the Han, 14.9% in the Uygur, and 16.4% in the Kazakh populations. The prevalence of abnormal IAD among the hypertensive population was 19.4%, with 17.0% in the Han, 18.1% in the Uygur, and 22.7% in the Kazakh populations. The prevalence of abnormal IAD increased with age (all P < 0.01) but was not significantly different between the genders (all P> 0.05). Multivariate logistic regression analysis showed that age more than 45 years, obesity and hypertriglyceridemia were significantly associated with a higher prevalence of IAD. There were different risk factors for abnormal IAD in different ethnicities. Middle or old age, obesity, ABI and diabetes mellitus were risk factors for the Han population, smoking was a risk factor in the Uygur population, and obesity and PAD were risk factors in the Kazakh population.
Conclusion
The prevalence of abnormal IAD in the Kazakh participants was higher than that in the Han and Uygur populations among both the general population and the hypertensive population in Xinjiang, China. The main risk factors of IAD were age, obesity, and triglyceride levels. Different ethnicities had different kinds of risk factors for IAD.
Introduction
Recent studies have shown that the inter-arm blood pressure difference (IAD) is associated with not only peripheral artery disease but also subclavian artery stenosis, cardiovascular morbidity and mortality, and all-cause mortality [1–3].
IAD is defined as the absolute difference in averaged BPs between the left and right arms, and an IAD≥10 mm Hg is considered to be significant [4,5]. Significantly increased IAD increases the risk for cardiovascular disease (CVD) [6,7]. Importantly, IAD is a more easily obtained, economical and non-invasive parameter than traditional risk factors [4,8].
The Hypertension Genetic Epidemiology Network study also found [9] that compared with the general population (9.2%), people with hypertension have a higher prevalence of IAD (14.2%). The Kimura A’ study noted that IAD is associated with risk factors for arteriosclerosis such as hypertension, hypercholesterolemia, obesity and metabolic abnormalities [10]. However, there is a lack of epidemiological data assessing the prevalence of IAD in populations with different ethnic backgrounds. Therefore, the purpose of this study was to estimate the abnormal prevalence of IAD and to analyze its risk factors among the Han, Uygur, and Kazakh populations in Xinjiang, China.
Methods
Ethics statement
This study was approved by the Ethical Committee of the First Affiliated Hospital of Xinjiang Medical University and was carried out according to the Declaration of Helsinki. Each participant signed a written informed consent form.
Participants
All the participants were selected from the Cardiovascular Risk Survey (CRS) conducted during October 2007 and March 2010. The study population and methods have been described in detail in a previous study [11–13]. Briefly, the CRS was a multiple ethnicity, community-based, cross-sectional study. We use 4-stage stratified cluster random sampling to select a representative sample of the general population of Chinese Hans, Uygurs, and Kazakhs of this area. Seven cities (Urumqi, Kelamayi, Hetian, Zhaosu, Fukang, Tulufan, and Fuhai) were chosen and, based on the government record of registered residence, one participant was randomly selected from each household. In this investigation, out of the total, 14618 participants (5757 Han, 4767 Uygur, and 4094 Kazakh Chinese), were randomly selected from 26 villages of those seven cities and invited to participate. Those whose data were incomplete were excluded. Finally, 11,239 subjects (5145 Hans, 2456 Uygurs, and 3638 Kazakhs) completed the survey and examination.
Survey contents
The investigations were carried out with the same survey program after the same training. The survey included two parts, the completion of the questionnaire form and a physical examination, which were conducted by standardized cardiovascular specialists. The questionnaire mainly included questions about the subject’s general condition, occupation, labor intensity, personal history of hypertension, family history and so on. The physical examination section included measurements of blood pressure, heart rate, electrocardiogram, height, weight, waist circumference, abdominal circumference, and hip circumference.
Measurement methods
Height was measured using a centimeter ruler. The ruler was placed perpendicular to the ground and affixed to the wall. The subjects were instructed to keep their line of sight forward. The examiner measured and recorded the number level with the top of the subject’s head using the right-angle side of a triangular ruler. For the weight measurement, the scale was zeroed before each use. Subjects fasted and urinated before the measurement. For the blood pressure (BP) measurement, the subjects stopped smoking 15 min before the test and spent at least 5 minutes resting in the sitting position. The BP measurement was performed three times using the right arm, and the mean BP value of the three readings was used for statistical analysis. For the measurements of IAD and the ankle-brachial index (ABI), the subjects were supine, their limbs were wrapped with a special double-cuff. Then, the blood pressure in the limbs was measured in a synchronized way by a Japanese Omron-Colin noninvasive arteriosclerosis analyzer VP-1000 (BP-20w3RPE II), and the IAD was calculated by the subtracting the blood pressure value of the left upper limb from that of the right upper limb. The ABI value was automatically derived by dividing the ankle blood pressure by the higher value of blood pressure in the right or left upper arm.
Personnel training and quality control
All survey forms were reviewed daily and maintained by a specially assigned person. Data were input by various researchers after a unified standardized training. The database was established, and the statistical analysis was conducted. Investigators were supervised during the investigation. The data was recorded twice with the unified database software. Each 100 questionnaire forms were used as a batch of materials for comparison. Modification was performed according to the original table in the case of any inconsistency. The process was repeated until the data were correct.
Laboratory testing
Study subjects fasted for 12 h, and 5 mL of venous blood was collected the morning of the day of the physical examination. Blood tests included total cholesterol (TC), triglyceride (TG), fasting blood glucose (FBG), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), blood urea nitrogen (BUN), creatinine (Cr), and uric acid (UA). The mentioned inspection and testing were performed by well-trained professionals.
Definition of IAD
IAD was defined as the absolute difference in averaged BPs between the left and right arm, and an IAD ≥ 10 mm Hg was significant [5].
Definition of hypertension
According to the criteria in the China hypertension guidelines (2010) [14], the definition of hypertension was as follows: systolic blood pressure (SBP) ≥ 140 mm Hg (1 mm Hg = 0.133 kPa) and (or) diastolic blood pressure (DBP) ≥ 90 mm Hg. Alternatively, patients were measured and had normal blood pressure after nearly 2 weeks of taking antihypertensive drugs, excluding secondary hypertension.
Definition of ankle brachial index
The ankle-brachial index (ABI) was defined the ankle blood pressure divided by the higher value of blood pressure in the right or left upper arm. The ABI was classified as ABI ≤ 0.90 or ≥ 1.40, with a lower ABI as the patient's ABI [15,16].
Definition of diabetes mellitus
According to the World Health Organization (WHO) Diabetes Classification and Guidelines [17], diabetes was defined as FBG ≥ 7.0 mmol/L or a history of diagnosed diabetes.
Definition of dyslipidemia
Dyslipidemia was determined by a self-report of using anti-hyperlipidemic medications or by having one of the following four lipid abnormalities: TC > 6.22 mmol/L (240 mg/dL) was defined as hypercholesterolemia, TG > 2.26 mmol/L (200 mg/dL) was defined as hypertriglyceridemia, LDL-c > 4.14 mmol/L (160 mg/dL) was defined as a high concentration of LDL-c, and HDL-c < 1.04 mmol/L (40 mg/dL) was defined as a low concentration of HDL-c [18].
Definition of obesity
The body mass index is calculated as body weight (kg)/height2 (m2). Patients with 18.5 kg/m2 ≤ BMI < 24 kg/m2 were normal weight, patients with 24 kg/m2 ≤ BMI < 28 kg/m2 were overweight, and patients with BMI ≥ 28 kg/m2 were obese [19].
Definition of smoking and drinking
Participants who reported regular smoking in the previous 6 months were considered current smokers, and those who reported regular drinking in the last 6 months were considered alcohol users [20].
Statistical analysis
The data were verified and corrected by two staff members using EpiData 3.02 software (EpiData Association, Odense, Denmark). The statistical analysis was conducted using Social Sciences SPSS for Windows version 22. (SPSS, Inc., IL, USA). Continuous variables were expressed as the means ± standard deviation, numerical data were expressed as rates, and a chi-square test (χ2) was used to evaluate differences between groups. Age standardization was performed according to the census of the Xinjiang Uygur autonomous region in 2010. The risk factors for IAD were analyzed using a multivariate unconditional logistic regression, and the significance level alpha value was set to 0.05.
Results
General characteristics of the included population
The survey included a total of 11,239 people [5294 (47.7%) males and 5945 (52.9%) females]. The average age of all subjects was 50.60 ± 12.50 years. A total of 5145 cases (45.8%), 2495 cases (21.9%) and 3638 cases (32.4%) were from Han, Uygur, and Kazakh populations, respectively. The cases were divided into five groups according to the age composition of the total population. Patients with complete information were included in the final analysis, and their general information is presented in Table 1. Gender, blood pressure, BMI, TGs, TC and other indicators were significantly different among different ethnic groups. The distribution of epidemiological data of the IAD normal and abnormal groups is shown in Table 2.
Table 1. General characteristics of study participants.
| Group | Han (n = 5145) | Uygur (n = 2456) | Kazakh (n = 3638) |
|---|---|---|---|
| Age, years | 52.29±12.62 | 52.26±12.18* | 48.56±11.81*☨ |
| Height, cm2 | 163.14±8.54 | 161.65±8.27 | 162.57±8.74* |
| BMI, kg/m2 | 25.14±3.51 | 26.29±4.31* | 26.49±4.76*☨ |
| SBP, mm Hg | 132±20 | 136±21* | 140±25* |
| DBP, mm Hg | 85±16 | 84±16* | 88±20☨ |
| ABI | 1.07±0.09 | 1.03±0.11* | 1.05±0.10*☨ |
| PWV | 1521.82±400.68 | 1518.29±376.35 | 1553.26±397.74*☨ |
| FBG, mmol/L | 5.33±1.78 | 5.12±1.51* | 5.17±1.71*☨ |
| Smoking | 1611(31.3%) | 652(26.6%) | 1302(35.9%) |
| Drinking | 986(19.2%) | 388(15.8%) | 517(14.2%) |
| TG, mmol/L | 1.72±1.45 | 1.68±1.18 | 1.21±0.89*☨ |
| HDL-c, mmol/L | 1.25±0.46 | 1.26±0.49 | 1.29±0.42* |
| LDL-c, mmol/L | 2.86±0.90 | 2.90±0.94 | 2.90±0.93 |
| TC, mmol/L | 4.68±1.08 | 4.60±1.24 | 4.76±1.16 |
| UA, μmol/L | 306.45±87.52 | 258.49±79.71* | 260.71±79.40*☨ |
| Cr, μmol/L | 75.79±26.91 | 73.93±34.01* | 70.68±19.29*☨ |
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; ABI, ankle-brachial index; PWV, pulse wave velocity; FBG, fasting blood glucose; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides; Cr, creatinine; UA, uric acid.
*p<0.05 versus the Han participants
☨p<0.05 versus the Uygur participants.
Table 2. Distribution of epidemiological data of IAD normal and abnormal groups.
| Groups | IAD < 10 mm Hg | IAD ≥ 10 mm Hg | t / χ2 | P |
|---|---|---|---|---|
| Age, years | 50.67±12.34 | 53.52±12.37 | -8.56 | 0.79 |
| Height, cm2 | 162.71±8.53 | 162.18±8.78 | 2.27 | 0.15 |
| Weight, kg | 68.17±13.19 | 70.70±14.10 | -6.68 | <0.01 |
| BMI, kg/m2 | 25.66±4.11 | 26.79±4.43 | -9.45 | <0.01 |
| SBP, mm Hg | 134±21 | 148±27 | -19.68 | <0.01 |
| DBP, mm Hg | 85±17 | 92±19 | -13.78 | <0.01 |
| ABI | 1.05±0.10 | 1.05±0.11 | 2.37 | <0.01 |
| PWV | 1746.31±429.94 | 1851.47±437.37 | 4.21 | 0.01 |
| FBG, mmol/L | 5.14±1.59 | 5.33±2.30 | -3.13 | <0.01 |
| Smoking | 3077(32.0%) | 488(30.5%) | 1.40 | 0.24 |
| Drinking | 1627(16.9%) | 264(16.5%) | 0.17 | 0.68 |
| TG, mmol/L | 1.53±1.25 | 1.63±1.30 | -2.78 | 0.07 |
| TC, mmol/L | 4.68±1.13 | 4.74±1.20 | -1.95 | 0.03 |
| HDL-c, mmol/L | 1.27±0.45 | 1.25±0.48 | 0.21 | 0.82 |
| LDL-c, mmol/L | 2.88±0.92 | 2.88±0.93 | -0.18 | 0.32 |
| Cr, μmol/L | 73.83±27.05 | 73.21±25.21 | 0.84 | 0.78 |
| UA, μmol/L | 280.87±86.46 | 283.44±86.57 | -1.08 | 0.53 |
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; ABI, ankle-brachial index; PWV, pulse wave velocity; FBG, fasting blood glucose; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides; Cr, creatinine; UA, uric acid.
Analysis of the prevalence of IAD in different sex and age groups
The total detection rate of interarm pressure differences was 14.3%. The detection rate of IAD was 14.5% in males and 14.0% in females. The prevalence of IAD was not significantly different between males and females (χ2 = 0.57, P = 0.45). A significant difference was observed in the prevalence of IAD among different age groups (χ2 = 75.45, P < 0.01). The prevalence of IAD in the age groups of 35–44, 45–54, 55–64, 65–74, and over 75 years was 10.8%, 14.9%, 16.3%, 18% and 18.5%, respectively (Table 3).
Table 3. Comparison of abnormal IAD prevalence rates of the general population among three ethnic groups (n, %).
| Age/years | Han (n = 642) | Total | Uygur (n = 366) | Total | Kazakh (n = 595) | Total | |||
|---|---|---|---|---|---|---|---|---|---|
| Male | Female | Male | Female | Male | Female | ||||
| 35–44 y | 94 | 72 | 166 | 34 | 50 | 84 | 94 | 95 | 189 |
| (10.3%) | (8.0%) | (9.2%) | (13.0%) | (11.7%) | (12.2%) | (13.0%) | (11.3%) | (12.1%) | |
| 45–54 y | 73 | 83 | 156 | 59 | 59 | 118 | 82 | 91 | 173 |
| (12.1%) | (12.6%) | (12.4%) | (18.0%) | (13.9%) | (15.7%) | (17.8%) | (17.4%) | 17.6% | |
| 55–64 y | 47 | 88 | 135 | 36 | 54 | 90 | 63 | 73 | 136 |
| (11.9%) | (15.4%) | (13.9%) | (12.9%) | (8.1%) | (15.5%) | (20.5%) | (20.6%) | (16.3%) | |
| 65–74 y | 76 | 72 | 148 | 32 | 28 | 60 | 43 | 34 | 77 |
| (18.8%) | (13.0%) | (16.7%) | (16.8%) | (17.8%) | (17.3%) | (22.1%) | (21.5%) | (21.8%) | |
| more than 75y | 19 | 18 | 37 | 6 | 8 | 14 | 11 | 9 | 20 |
| (14.4%) | (20.7%) | (16.9%) | (11.1%) | (22.9%) | (15.7%) | (23.9%) | (31.0%) | (26.7%) | |
| Total | 309 | 333 | 642 | 167 | 199 | 366 | 293 | 302 | 595 |
| (12.6%) | (12.3%) | (12.5%) | (15.0%) | (14.8%) | (14.9%) | (16.9%) | (15.9%) | (16.4%) | |
| Standard prevalence | 309 | 333 | 642 | 167 | 199 | 366 | 293 | 302 | 595 |
| (11.9%) | (11.6%) | (11.8%) | (14.6%) | (14.3%) | (14.3%) | (16.7%) | (16.2%) | (15.7%) | |
The incidence of abnormal IAD was higher for the Kazakh ethnic group than for the Uygur and Han ethnic groups; there were differences between the three groups (χ2 = 70.35, P < 0.01). A significant difference was observed in the prevalence of IAD among different age groups (χ2 = 72.45, P < 0.01).
Analysis of the prevalence of IAD among different ethnicities
The prevalence of IAD was 12.5% in the Han subjects, 14.9% in the Uygur subjects, and 16.4% in the Kazakh subjects, respectively. After age standardization, the prevalence of IAD abnormality was 11.8%, 14.3%, and 16.4%, respectively, in the three populations (Table 3). The prevalence of IAD abnormalities among the three ethnic groups was significantly different (χ2 = 70.35, P < 0.01).
Analysis of the prevalence of IAD in the hypertensive population of different ethnicities
The total prevalence of IAD was 19.4% in patients with hypertension. The prevalence of IAD in hypertensive Han, Uygur and Kazakh populations were 17.0%, 18.1% and 22.7%, respectively. After age standardization, the prevalence of IAD abnormality was 15.5%, 18.6%, and 21.4%, respectively, in the three groups. The prevalence of IAD was significantly different among those three ethnic groups (χ2 = 70.35, P < 0.01). The prevalence of IAD in hypertensive males was 19.0%, while it was 19.7% in hypertensive females, and there was no significant difference between the prevalence according to gender (χ2 = 0.34, P = 0.56). The prevalence of IAD among different age groups in the hypertensive population was significantly different (χ2 = 10.76, P = 0.03) (Table 4). The prevalence of IAD was 15.7%, 19.8%, 20.3%, 20.6%, and 21.6% in the 35–44, 45–54, 55–64, 65–74, and over 75 years age groups, respectively.
Table 4. Comparison of the prevalence of abnormal IAD in the hypertensive population among the three ethnic groups (n, %).
| Age/years | Han (n = 328) | Total | Uygur (n = 188) | Total | Kazakh (n = 394) | Total | |||
|---|---|---|---|---|---|---|---|---|---|
| Male | Female | Male | Female | Male | Female | ||||
| 35–44 y | 32 | 19 | 51 | 8 | 16 | 24 | 48 | 28 | 76 |
| (12.7%) | (15.0%) | (13.5%) | (13.6%) | (18.2%) | (16.3%) | (18.9%) | (15.6%) | (17.6%) | |
| 45–54 y | 35 | 27 | 62 | 24 | 36 | 60 | 59 | 62 | 121 |
| (15.4%) | (16.1%) | (15.7%) | (21.1%) | (18.5%) | (19.4%) | (23.0%) | (22.4%) | (23.0%) | |
| 55–64 y | 26 | 59 | 85 | 22 | 29 | 51 | 50 | 63 | 66 |
| (15.2%) | (19.6) | (18.0%) | (15.8%) | (17.5%) | (16.7%) | (23.80%) | (26.4%) | (24.9%) | |
| 65–74 y | 48 | 55 | 103 | 20 | 22 | 42 | 38 | 28 | 26 |
| (1.7%) | (17.0%) | (18.9%) | (18.2%) | (21.40%) | (19.7%) | (26.4%) | (23.0%) | (24.8%) | |
| more than 75y | 13 | 14 | 27 | 5 | 6 | 11 | 10 | 8 | 18 |
| (16.7%) | (23.7) | (19.7%) | (13.2%) | (25.0%) | (17.7%) | (27.0%) | (34.8%) | (30.0%) | |
| Total | 154 | 174 | 328 | 79 | 109 | 188 | 205 | 189 | 394 |
| (16.2%) | (17.8%) | (17.0%) | (17.2%) | (18.9%) | (18.1%) | (23.0%) | (22.50%) | (22.7%) | |
| Standard prevalence |
154 | 174 | 328 | 79 | 109 | 188 | 205 | 189 | 394 |
| (14.4%) | (16.5%) | (15.5%) | (16.4%) | (18.7%) | (18.6%) | (22.0%) | (20.7%) | (21.4%) | |
Differences were observed among the three groups in the hypertensive population (χ2 = 70.35, P < 0.01). A significant difference was observed in the prevalence of IAD among different age groups (χ2 = 10.76, P = 0.03).
Analysis of the relevant risk factors for IAD
Multivariate unconditional logistic regression analysis was used to analyze the data. The valuable and empirical variables were included in the multivariate unconditional logistic regression analysis (Table 5), and the variables were introduced in the equation. Age, ethnicity, obesity, and ABI were the risk factors for IAD after adjusting for factors such as investigation site, sex, marital status, and diet. Compared with the group of subjects aged 35–44 years (OR = 1), the risk of developing IAD increased by 1.71-fold in the groups of subjects with ages greater than 75 years (OR = 1.71, 95% CI: 1.25–2.33). In the obese group, the risk of IAD was 1.41-fold higher (OR = 1.41, 95% CI: 1.21–1.65) than that of the normal population. Risk factors for IAD in the hypertensive population were consistent with those in the general population (Table 6). A multiple regression analysis was also performed for differences in the prevalence of IAD abnormalities among the three ethnic groups. No significant differences were observed in the risk factors for IAD among the different ethnic groups. Age, ethnicity, obesity, and ABI were the common risk factors for IAD among the three ethnicities.
Table 5. Multivariate unconditional logistic regression analysis of risk factors for abnormal IAD in the general population.
| Factor | B | S.E. | wald | df | P | OR | 95% CI |
|---|---|---|---|---|---|---|---|
| Sex | 0.00 | 0.08 | 0.00 | 1 | 0.10 | 1.00 | 0.86–1.16 |
| Age | 22.70 | 4 | 0.00 | ||||
| 35–44 y | 1 | ||||||
| 45–54 y | 0.23 | 0.08 | 8.60 | 1 | 0.03 | 1.26 | 1.08–1.48 |
| 55–64 y | 0.30 | 0.09 | 11.50 | 1 | 0.01 | 1.91 | 1.14–1.61 |
| 65–74 y | 0.42 | 0.10 | 16.90 | 1 | 0.00 | 2.03 | 1.24–1.85 |
| More than 75y | 0.53 | 0.16 | 11.30 | 1 | 0.01 | 2.88 | 1.25–2.33 |
| Ethnicity | 12.20 | 2 | 0.01 | ||||
| Han | 1 | ||||||
| Uygur | 0.07 | 0.09 | 0.58 | 1 | 0.45 | 0.67 | 0.90–1.28 |
| Kazakh | 0.26 | 0.08 | 11.12 | 1 | 0.01 | 1.00 | 1.12–1.51 |
| Smoking | -0.08 | 0.08 | 0.91 | 1 | 0.34 | 0.89 | 0.80–1.08 |
| Drinking | 0.03 | 0.09 | 0.09 | 1 | 0.77 | 1.17 | 0.86–1.23 |
| BMI | 19.70 | 2 | 0.00 | ||||
| Normal | 1 | ||||||
| Overweight | 0.15 | 0.07 | 3.93 | 1 | 0.47 | 1.16 | 1.00–1.34 |
| Obesity | 0.35 | 0.08 | 19.30 | 1 | 0.00 | 1.41 | 1.21–1.65 |
| Diabetes | 0.14 | 0.11 | 1.47 | 1 | 0.23 | 1.15 | 0.92–1.43 |
| TG | 0.14 | 0.07 | 4.27 | 1 | 0.04 | 1.15 | 1.01–1.32 |
| TC | -0.06 | 0.07 | 0.79 | 1 | 0.37 | 0.94 | 0.83–1.07 |
| HDL-c | -0.02 | 0.06 | 0.13 | 1 | 0.72 | 0.98 | 0.87–1.11 |
| LDL-c | 0.03 | 0.64 | 0.22 | 1 | 0.64 | 1.03 | 0.91–1.17 |
| ABI | -0.83 | 0.36 | 5.35 | 1 | 0.02 | 0.04 | 0.22–0.88 |
| Constant | -1.28 | 0.46 | 7.86 | 1 | 0.05 | 0.28 |
BMI, body mass index; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides.
Table 6. Multivariate unconditional logistic regression analysis of risk factors for IAD in the hypertensive population.
| Factor | B | S.E. | wald | df | P | OR | 95% CI |
|---|---|---|---|---|---|---|---|
| Sex | 0.00 | 0.10 | 0.00 | 1 | 1.00 | 1.00 | 0.83–1.21 |
| Age | 5.54 | 4 | 0.24 | ||||
| 35–44 y | 1 | ||||||
| 45–54 y | 0.14 | 0.12 | 1.27 | 1 | 0.26 | 1.15 | 0.90–1.46 |
| 55–64 y | 0.20 | 0.13 | 2.49 | 1 | 0.12 | 1.22 | 0.95–1.56 |
| 65–74 y | 0.27 | 0.13 | 4.15 | 1 | 0.04 | 1.31 | 1.01–1.70 |
| More than 75y | 0.35 | 0.19 | 3.49 | 1 | 0.06 | 1.43 | 0.98–2.07 |
| Ethnicity | 12.2 | 2 | 0.01 | ||||
| Han | 1 | ||||||
| Uygur | -0.05 | 0.11 | 0.11 | 1 | 0.68 | 0.96 | 0.77–1.19 |
| Kazakh | 0.26 | 0.08 | 0.10 | 1 | 0.01 | 1.33 | 1.11–1.61 |
| Smoking | -0.08 | 0.08 | 0.11 | 1 | 0.49 | 0.93 | 0.76–1.14 |
| Drinking | 0.03 | 0.13 | 0.04 | 1 | 0.84 | 1.03 | 0.81–1.31 |
| BMI | 7.69 | 2 | 0.02 | ||||
| Normal | 1 | ||||||
| Overweight | -0.03 | 0.11 | 0.06 | 1 | 0.81 | 0.98 | 0.79–1.20 |
| Obesity | 0.21 | 0.11 | 3.91 | 1 | 0.048 | 1.23 | 1.00–1.52 |
| Diabetes | 0.06 | 0.14 | 0.20 | 1 | 0.66 | 1.06 | 0.81–1.40 |
| TG | 0.11 | 0.09 | 1.52 | 1 | 0.22 | 1.03 | 0.79–1.35 |
| TC | -0.02 | 0.08 | 0.08 | 1 | 0.78 | 0.98 | 0.83–1.15 |
| HDL-c | 0.01 | 0.09 | 0.01 | 1 | 0.95 | 1.01 | 0.85–1.19 |
| LDL-c | -0.03 | 0.08 | 0.08 | 1 | 0.77 | 0.98 | 0.83–1.15 |
| ABI | -1.41 | 0.47 | 8.89 | 1 | 0.01 | 0.24 | 0.09–0.62 |
| Constant | -0.52 | 0.55 | 0.89 | 1 | 0.35 | 0.60 |
ABI, ankle-brachial index; BMI, body mass index; HDL-c, high-density lipoprotein cholesterol; LDL-c low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides.
Comparison of IAD risk factors in the three ethnicity groups
Multivariate unconditional logistic regression analysis was used on all related risk factors to recognize any existing differences in those risk factors that might explain the difference in IAD prevalence among the three ethnicities. The comparison was made between participants with abnormal IAD values in the Han (n = 595), Uygur (n = 320) and Kazakh (n = 541) populations and their corresponding IAD-normal participants, and the results are shown in S1 Table (S1 Table). In the Han population, middle and old age (65–74 years old, OR = 1.640, 95% CI: 1.243–2.164), obesity (OR = 1.469, 95% CI: 1.146–1.884), ABI (OR = 0.229, 95% CI: 0.076–0.695) and diabetes mellitus (OR = 1.340, 95% CI: 1.007–1.783) remained risk factors. In the Uygur population, smoking (OR = 3.626, 95% CI: 2.295–5.729) remained a risk factor, and in the Kazakh population, obesity (OR = 1.490, 95% CI: 1.154–1.295) and PAD (OR = 1.603, 95% CI: 1.014–2.533) remained risk factors for IAD.
Discussion
In the present study, we found that the abnormal prevalence of IAD was 14.3%, which was higher than the prevalence reported in previous studies (10.7% [21] and 3.7% [22]). Meanwhile, our data also illustrated that the prevalence of abnormal IAD in the hypertensive population was 19.4%, which was higher than the prevalence reported in studies by Kim SA et al. (7.7%) [5] and Clark CE et a1. (11.2%) [23]. This might be due to differences in study populations and the methods used for BP measurement.
Our study showed differences in the prevalence of abnormal IAD according to ethnicity. The prevalence of abnormal IAD in the Han, Uygur and Kazakh populations was 12.5%, 14.9% and 16.4%, respectively. The prevalence of abnormal IAD in the Kazakh population was significantly higher than that in the Han and Uygur populations. The present data also showed that the prevalence of abnormal IAD has differences in the hypertensive population according to ethnicity. Of the three ethnicities, the highest rate of abnormal IAD was 22.7% in the Kazakh ethnic group. This difference may be due to a higher prevalence of hypertension among the Kazakh population in Xinjiang [24].
Many studies have demonstrated that arterial elasticity decreases and peripheral vascular resistance increases with age, which are associated with atherosclerosis. This could account for the prevalence of abnormal IAD in the elderly population [25,26]. In the present study, we found significant differences in the prevalence of abnormal IAD according to age, with higher prevalence in older age groups. The rates of abnormal IAD in different age groups (35–44 years, 45–54 years, 55–64 years, 65–74 years and > 75 years) were 10.8%, 14.9%, 16.3%, 18% and 18.5%, respectively., People over the age of 45 are at especially high risk for abnormal IAD and particular attention should be paid to measurements of inter-arm differences in BP in these people. Furthermore, our study showed that gender was not a significant factor associated with a large IAD, which is consistent with the results of other reports [27]. It is unclear whether this was influenced by changes associated with female hormones and menopause [28,29].
In the present study, obesity and hyperlipidemia were associated with a higher risk of abnormal IAD. Obesity is an increasing epidemic in both adults and children, and these obese individuals often have concomitant hypertension. Obesity is associated with increased blood viscosity, which increases the rheological component of peripheral resistance and contributes to obesity-associated changes in arterial blood pressure [30]. In our study, obesity was associated with a higher risk of abnormal IAD, which is similar to the results of the Kimura A study [10]. Hyperlipidemia was also a risk factor for IAD, but other lipid profiles were not. The multivariate unconditional logistic regression analysis of the hypertensive population showed that their risk factors for abnormal IAD were consistent with those of the general population. Interestingly, smoking and dyslipidemia did not enter into the regression equation, which may be due to the long-term interaction of genetic and environmental factors with hypertension.
In addition, we observed that the risk factors for abnormal IAD were different among the three ethnicities, which may explain the difference in IAD incidence among these ethnicities. In the Han participants, age greater than 45 years, obesity, ABI and diabetes were risk factors. In Uygur participants, smoking was the predominant risk factor, and in the Kazakh participants, obesity and PAD were risk factors. These differences might due to lifestyle, life conditions and genetic factors. A further study is required to better define the risk factors responsible for a higher prevalence of abnormal IAD. Early detection of abnormal IAD may be useful for preventing the progression of atherosclerosis and reducing cardiovascular mortality in Xinjiang, China.
Some limitations of the current study were as follows: First, this was a retrospective, cross-sectional study. Second, the information about diet patterns, physical activity, and socioeconomic conditions were not analyzed in the study population. This could lead to deviations in the results. Systematic, large-scale, prospective studies need to be conducted to further elucidate the epidemiological pattern of abnormal IAD and its associated risk factors.
Conclusion
There were differences according to ethnicity in the prevalence of IAD in Xinjiang, China. Of the three groups, the Kazakh participants had the highest IAD prevalence and the Han participants had the lowest. Age, obesity and high triglyceride levels were relevant risk factors for IAD. Participants with different ethnicity backgrounds had different patterns of risk factors for IAD.
Supporting information
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(DOCX)
(DOC)
Acknowledgments
The authors wish to thank all the study participants for the knowledge and insights provided by them. Helpful comments and suggestions from the reviewers to improve this paper are met with heartfelt appreciation.
Data Availability
All of the data were collected from the Cardiovascular Risk Survey in Xinjiang, and are present in the Supporting Information files.
Funding Statement
The authors received no specific funding for this work.
References
- 1.Clark CE, Taylor RS, Shore AC, Ukoumunne OC, Campbell JL. Association of a difference in systolic blood pressure between arms with vascular disease and mortality: a systematic review and meta-analysis. Lancet 2012; 10; 379(9819): 905–914. doi: 10.1016/S0140-6736(11)61710-8 [DOI] [PubMed] [Google Scholar]
- 2.Clark CE1, Taylor RS, Shore AC, Campbell JL. The difference in blood pressure readings between arms and survival: primary care cohort study, BMJ 2012; 20; 344:e1327 doi: 10.1136/bmj.e1327 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Clark CE. Difference in blood pressure measurements between arms: methodological and clinical implications. Curr Pharm Des 2015; 21:737–743. [DOI] [PubMed] [Google Scholar]
- 4.National Institue for Health and Clinical Excellence, Hypertension: the clinical management of primary hypertension in adults CG127, NICE; 2011; 905–914. [Google Scholar]
- 5.Kim SA, Kim JY, park JB. Significant interarm blood pressure difference predicts cardiovascular risk in hypertentive patients: CoCoNet study. Medicine (Baltimore).2016; 95(24): e3888. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Mancia G, Fagard R, Narkiewicz K, Redon J, Zanchetti A, Böhm M, et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur Heart J 2013; 34:2159–219. doi: 10.1093/eurheartj/eht151 [DOI] [PubMed] [Google Scholar]
- 7.Orme S, Ralph SG, Birchall A, Lawson-Matthew P, McLean K, Channer KS. The normal range for inter-arm differences in blood pressure. Age Ageing 1999; 28 (6):537–42. [DOI] [PubMed] [Google Scholar]
- 8.Singh S, Sethi A, Singh M, Khosla S. Prevalence of simultaneously measured interarm systolic blood pressure difference and its clinical and demographic predictors: a systemic review and meta-analysis, Blood Press Monit 2015; 20(4):178–185. doi: 10.1097/MBP.0000000000000115 [DOI] [PubMed] [Google Scholar]
- 9.Arnett DK, Tang W, Province MA, Oberman A, Ellison RC, Morgan D, et al. Interarm differences in seated systolic and diastolic blood pressure: the Hypertension Genetic Epidemiology Network study. J Hypertens 2005; 23 (6):1141–1147. [DOI] [PubMed] [Google Scholar]
- 10.Kimura A, Hashimoto J, Watabe D, Takahashi H, Ohkubo T, Kikuya M, et al. Patient characteristics and factors associated with inter-arm difference of blood pressure measurements in a general population in ohasama, japan. J Hypertens, 2004; 22(12): 2277–2283. [DOI] [PubMed] [Google Scholar]
- 11.Pan S, Yu Z-X, Ma Y-T, Liu F, Yang YN, Ma X, et al. Appropriate body mass index and waist circumference cutoffs for categorization of overweight and central adiposity among uighur adults in Xinjiang. PLoS One 2013; 8 (11): e80185 doi: 10.1371/journal.pone.0080185 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Xie X, Ma YT, Yang YN, Li XM, Liu F, Huang D, et al. Alcohol consumption and ankle-to-brachial index: results from the cardiovascular risk survey. PLoS One 2010; 5: e15181 doi: 10.1371/journal.pone.0015181 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Xie X, Ma YT, Yang YN, Fu ZY, Li XM, Huang D, et al. Polymorphisms in the SAA1/2 gene are associated with carotid intima media thickness in healthy Han Chinese subjects: the cardiovascular risk survey. PLoS One 2010; 5: e13997 doi: 10.1371/journal.pone.0013997 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.McManus RJ, Caulfield M, Williams B. National Institute for Health and Clinical Excellence. NICE hypertension guideline 2011: Evidence based evolution. BMJ 2012; 344: e181 doi: 10.1136/bmj.e181 [DOI] [PubMed] [Google Scholar]
- 15.Gao X, Ma YT, Yang YN, Xie X, Liu F, Li XM, et al. Prevalence of abnormal ankle brachial index in Xinjiang adult population. Zhonghua xin xue guan Bing Za Zhi 2011; 39 (9): 857–60. [PubMed] [Google Scholar]
- 16.Arroyo D, Betriu A, Valls J, Gorriz JL, Pallares V, Abajo M, et al. Factors influencing pathological ankle-brachial index values along the chronic kidney disease spectrum: the NEFRONA study. Nephrol Dial Transplant 2017; 32 (3): 513–520. doi: 10.1093/ndt/gfw039 [DOI] [PubMed] [Google Scholar]
- 17.World Health Organization Study Group, Diabetes mellitus. WHO Tech Rep Ser 1985; 727: 1–104. [PubMed] [Google Scholar]
- 18.Joint Committee for Developing Chinese guidelines on Prevention and Treatment of Dyslipidemia in Adults. Chinese Guidelines on prevention and treatment of dyslipidemia in adults. Zhonghua Xin Xue Guan Bing Za Zhi 2007; 35: 390–419. [PubMed] [Google Scholar]
- 19.Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000; 894: i–xii, 1–253 [PubMed] [Google Scholar]
- 20.Liu F, Adi D, Xie X, Li XM, Fu ZY, Shan CF, et al. Prevalence of Isolated Diastolic Hypertension and Associated Risk Factors among Different Ethnicity Groups in Xinjiang, China. PLoS ONE 2015; 10 (12): e0145325 doi: 10.1371/journal.pone.0145325 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Weinberg I, Gona P, O’Donnell CJ, Jaff MR, Murabito JM. The systolic blood pressure difference between arms and cardiovascular disease in the Framingham Heart Study. Am J Med 2014; 127:209–215. doi: 10.1016/j.amjmed.2013.10.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Song BM, Kim HC, Shim JS, Lee MH, Choi DP. Inter-Arm Difference in Brachial Blood Pressure in the General Population of Koreans. Korean Circ J 2016; 46 (3):374–83. doi: 10.4070/kcj.2016.46.3.374 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Clark CE, Taylor RS, Shore AC, Campbell JL. Prevalence of systolic inter-arm differences in blood pressure for different primary care populations: systematic review and meta-analysis. Br J Gen Pract 2016; 66 (652): e838–e847. doi: 10.3399/bjgp16X687553 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Liu F, Ma YT, Yang YN, Xie X, Li XM, Huang Y, et a1. Current status of primary hypertension in Xinjlang: an epidemiological study of Han. Uygur and Hazakh populations.J. Natl Med J China 2010; 90 (64):3259–3263. [PubMed] [Google Scholar]
- 25.Fotherby MD, Panayiotou B, Potter JF. Age-related differences in simultaneous interarm blood pressure measurements. Postgrad Med J 1993; 69:194–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Grossman A, Weiss A, Beloosesky Y, Morag-Koren N, Green H, Grossman E. Inter-arm blood pressure difference in hospitalized elderly patients–is it consistent? J Clin Hypertens 2014; 16:518–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Lane D, Beevers M, Barnes N, Bourne J, John A, Malins S, et al. ter-arm differences in blood pressure: When are they clinically significant? J Hypertens 2002; 20 (6):1089–95 [DOI] [PubMed] [Google Scholar]
- 28.Su H-M, Lin T-H, Hsu PC, Chu CY, Lee WH, Chen SC, et al. Association of Interarm Systolic Blood Pressure Difference with Atherosclerosis and Left Ventricular Hypertrophy. PLOS ONE 2012; 7 (8): e41173 doi: 10.1371/journal.pone.0041173 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Mumford SL, Dasharathy S, Pollack AZ, Schisterman EF. Variations in lipid levels according to menstrual cycle phase: Clinical implications. Clin Lipidol 2011, 6:225–234. doi: 10.2217/clp.11.9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Zhang R, Reisin E. Obesity-hypertension: the effects on cardiovascular and renal systems. Am J Hypertens 2000; 13:1308–1314. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
(DOC)
(DOCX)
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Data Availability Statement
All of the data were collected from the Cardiovascular Risk Survey in Xinjiang, and are present in the Supporting Information files.