Abstract
Whether the combination of inter‐arm and inter‐leg systolic blood pressure differences (BPDs) and ankle‐brachial index is of clinical significance remains unclear. In this study, we aimed to investigate the association of the combination of inter‐limb systolic BPDs with cardiovascular risk factors and hypertension‐mediated organ damage (HMOD). A total of 2621 elderly subjects from the Northern Shanghai Study were divided into Group A, B, and C consisting of participants with 0, 1, and ≥2 abnormal inter‐limb systolic BPDs, respectively. Comparisons of cardiovascular risk factors and parameters of cardiac, vascular, and renal damage between groups and logistic regression models were conducted. The proportions of subjects presenting 0, 1, and ≥2 abnormal inter‐limb systolic BPDs were 60.9%, 25.1%, and 14.0%, respectively. Upward trends, from Group A, through Group B, to Group C, were observed for the level or prevalence of nearly all cardiovascular risk factors and HMOD (P for trend ≤0.007 for all). In multiple logistic regression, Group C showed significantly higher odds for carotid plaque (vs Group A: Odds ratio [OR] = 1.88, 95% confidence interval [CI] = 1.43‐2.48; vs Group B: OR = 1.46, 95% CI = 1.08‐1.97), arterial stiffness (vs Group A: OR = 1.26, 95% CI = 0.96‐1.65; vs Group B: OR = 1.36, 95% CI = 1.01‐1.83), and left ventricular hypertrophy (vs Group A: OR = 1.35, 95% CI = 1.04‐1.76; vs Group B: OR = 1.25, 95% CI = 0.93‐1.67), when compared with Group A and B. In conclusion, the combination of abnormal inter‐limb systolic BPDs significantly associates with greater burden of cardiovascular risk factors and higher likelihood for HMOD, especially carotid plaque, arterial stiffness, and left ventricular hypertrophy.
Keywords: ankle‐brachial index, hypertension‐mediated organ damage, inter‐arm blood pressure difference, inter‐leg blood pressure difference
1. INTRODUCTION
Differences in blood pressure (BP) between limbs are commonly observed in clinical practice. Small difference is a physiological manifestation, usually caused by the anatomical and hemodynamic asymmetries between extremities. However, when the difference exceeds certain extent, it may suggest that pathophysiological changes (mostly atherosclerotic lesions, rarely non‐atherosclerotic lesions such as arthritis) may occur in the artery of limb.1 From this perspective, BP differences (BPDs) between limbs may possess potentially important value in diagnosing upper and lower extremity arterial diseases and predicting atherosclerotic cardiovascular risk. Accordingly, extensive investigations have been carried out to demonstrate this speculation in the past decades. Ankle‐brachial index (ABI) has been developed as a first‐line tool for screening lower extremity arterial disease, also called peripheral artery disease (PAD), a marker for generalized atherosclerosis and a predictor for cardiovascular and all‐cause mortalities.2 Inter‐arm systolic BPDs (IASBPD) has been linked to increased cardiovascular and overall mortalities by many cohort studies based on unselected populations3, 4 and selected populations with diabetes,5 hypertension6 or established vascular diseases7, 8 and meta‐analysis,9, 10 although there is still controversy in the elderly.11, 12 IASBPD is also indicated to be associated with PAD9, 13 and various organ damage including coronary artery calcium score, carotid intima‐media thickness and plaque, arterial stiffness, albuminuria and left ventricular mass index/hypertrophy (LVMI/LVH).7, 14, 15, 16, 17, 18 Similar findings were also found for inter‐leg systolic BPD (ILSBPD).4, 19, 20, 21, 22 However, in clinical practice, we can observe that patients may have different exposures to abnormal inter‐limb systolic BPDs; some patients have only one of the abnormal inter‐limb systolic BPDs, but others may present abnormal IASBPD, ILSBPD, and ABI at the same time. This leads us to think whether the latter has higher cardiovascular risk than the former. However, few studies investigated the significance of the combination of IASBPD, ILSBPD, and ABI within one cohort so far. Accordingly, in the present study, we aimed to investigate whether the combination of abnormal inter‐limb systolic BPDs suggests higher burden of cardiovascular risk factors and higher level of hypertension‐mediated organ damage (HMOD), in a large community‐based cohort of elderly people from the Northern Shanghai Study.
2. METHODS
2.1. Study design and population
The present study is a cross‐sectional analysis based on the cohort of the Northern Shanghai Study, a registered (ClinicalTrials.gov Identifier: NCT02368938) and ongoing prospective study with purpose of establishing a cardiovascular risk evaluation score for the elderly Chinese. The detailed rationale and design of the Northern Shanghai Study has been described elsewhere.23 Briefly, it recruits the residents with age of ≥65 years from the urban communities in the northern area of Shanghai. Subjects with severe cardiac diseases (defined as New York Heart Association Classification IV), end‐stage renal disease, stroke within 3 months, and malignant tumor were excluded. This study was approved by the local institution's ethics committee, and written informed content was gained from each participant. Since August 2014, a total of 2830 subjects (response rate 91.5%) have been enrolled. In the present analysis, 209 subjects lacking four‐limb blood pressures and other important data were further excluded. Thus, a total of 2621 subjects were included in the final analysis.
2.2. Protocol
All participants completed a detailed lifestyle and medical history questionnaire. Height and weight were measured; body surface area and body mass index (BMI) were calculated. After 5 minutes of rest in a quiet room, blood pressure in sitting position was measured for three times at a 2‐minute interval, using a mercury sphygmomanometer. The average of blood pressures was used for further analysis. Then, the following measurements, including four‐limb blood pressures, carotid‐femoral pulse wave velocity (CF‐PWV), and cardiac and carotid ultrasonography, were performed sequentially. Blood sample was collected from the antecubital vein under fasting condition. Biochemical parameters, including fasting plasma glucose, serum creatinine, and lipid profiles, were assayed by standard methods in the Department of Laboratory Medicine of Shanghai Tenth People's Hospital. Estimated glomerular filtration rate (eGFR) was calculated by Asian‐modified CKD‐EPI formula.24 All measurements were performed by trained investigators.
2.3. Measurement of four‐limb blood pressures
Four‐limb blood pressures were measured with an ABI‐form device (Collin VP‐1000, Omron). After around 10 minutes of rest in supine position, four cuffs with appropriate size were placed on both arms and ankles of each subject, and then, four‐limb blood pressures were measured automatically and simultaneously by the device. IASBPD and ILSBPD were calculated as the absolute differences in systolic blood pressures between right and left arms and ankles, respectively. Left and right ABI were reported by the device automatically, and the minimum value of ABIs in both sides was used for analysis.
2.4. Measurement of CF‐PWV
A validated and commercially available applanation tonometry device (SphygmoCor, AtCor Medical) was applied to assess CF‐PWV. With participants in supine position, the superficial distances from the sternal notch to the right carotid artery and from the sternal notch to the right femoral artery were measured. The traveling distance of pulse wave was calculated as the difference between the two measured distances. Then pulse waves were recorded at the right common carotid and femoral arteries sequentially. Meanwhile, electrocardiogram signal was monitored, which provided information on travel time of pulse wave. Based on these data, CF‐PWV was automatically computed by the inbuilt software. The measurement would be repeated if the operator index, an indicator for the quality of measurement, was <60%. Only were the measurements fulfilling the quality requirements reserved.
2.5. Cardiac and carotid ultrasonography
Cardiac ultrasonography was performed using MyLab 30 CV machine (ESAOTE SPA), according to the American Society of Echocardiography recommendation. Left ventricular internal diameter (LVIDd) and septal (SWTd) and posterior wall thickness at the end diastole (PWTd) were measured in the parasternal long‐axis view in M‐mode. Left ventricular mass was calculated by the formula LVM (g) = 0.8 × {1.04 × [(LVIDd + PWTd + SWTd)3−(LVIDd)3]} + 0.6 and indexed for body surface area to get left ventricular mass index (LVMI). Left atrial parameters including left atrial dimension (SA1) in the parasternal short‐axis view and measurements of short (SA2) and long axes (LA) in the apical four‐chamber view at ventricular end systole were measured. Left atrial volume was calculated using the formula: left atrial volume = π × (SA1 × SA2 × LA)/6, and then indexed for the body surface area as left atrial volume index (LAVI). In the apical four‐chamber view, peak early diastolic transmitral flow velocity (E) and early diastolic lateral mitral annular velocity (E a) were measured with pulse wave and tissue Doppler imaging, respectively. E/E a ratio was then calculated.
After cardiac ultrasonography, carotid ultrasonography was performed using same machine but different transducer (7.5 MHz). Common, internal, and external carotid arteries of both right and left sides were all scanned longitudinally and transversely to detect the presence of plaques. Specifically, the plaque was defined as an intima‐media thickness >1.5 mm or a focal increase in thickness of 0.5 mm or 50% of the surrounding intima‐media thickness.25
2.6. Statistics
Continuous variables were presented as mean ± SD for those with normal distribution or median (interquartile range) for those with skewed distribution; categorical variables were presented as absolute numbers and percentage in parenthesis. According to the number of abnormal inter‐limb systolic BPDs (IASBPD ≥10 mm Hg, ILSBPD ≥15 mm Hg and ABI ≤0.9), the entire population was initially divided into four groups, namely Group A, B, C, and D, which presented 0, 1, 2, and 3 abnormal inter‐limb systolic BPDs, respectively. Since the small number of participants, Group D was incorporated into Group C; thus, three groups were obtained finally. One‐way ANOVA (Kruskal‐Wallis test used if the variable is not normally distributed) and chi‐square tests were used to explore the differences in continuous and categorical variables among groups, respectively. Bonferroni method was used for post hoc comparisons. Then, trend tests were performed to detect whether there are upward/downward trends in the level or prevalence of variables of interest, from Group A, through Group B, to Group C. To achieve this purpose, linear regression model treating group as continuous variable (Cuzick's test for trend used if the variable is not normally distributed) was used for continuous variables, and Cochran‐Armitage test was used for categorical variables. Finally, multiple logistic regression models with different adjustments were conducted to investigate the relative risk of HMOD between groups with different numbers of abnormal inter‐limb systolic BPDs. Abovementioned analyses were repeated in the subgroup of 1471 subjects without cardiovascular arterial disease (CAD) or stroke.
2.7. Definitions
Hypertension was defined as brachial systolic BP/diastolic BP ≥140/90 mm Hg or self‐reported antihypertensive medication25 and diabetes mellitus as fasting serum glucose ≥7.0 mmol/L or self‐reported antidiabetic medication.26 Abnormalities of inter‐limb systolic BPDs were defined as ABI ≤0.9, IASBPD ≥10 mm Hg, and ILSBPD ≥15 mm Hg,2, 4 respectively. LVH was defined as LVMI ≥115 g/m2 (men) or LVMI ≥95 g/m2 (women).27 Left ventricular diastolic dysfunction (LVDD) was diagnosed using the following criteria: E/E a ≥15; or 8 < E/E a < 15 and LAVI >40 mL/m2; or 8 < E/E a < 15 and LVMI >149 g/m2 for male (LVMI >122 g/m2 for female).28 Renal damage was defined as eGFR <60 mL/min/1.73 m2 and arterial stiffness as CF‐PWV >10 m/s.25 Carotid plaque was defined as the presence of plaque in at least one of both right and left sides.
3. RESULTS
3.1. Characteristics of the entire population
Characteristics of study participants are shown in Table 1. The median age of the population was 70 years. Hypertension and diabetes rates were 64.3% and 23.1%, respectively. There were 867 (33.2%) subjects with CAD and 537 (20.5%) subjects with stroke. The prevalences of LVH, LVDD, arterial stiffness, carotid plaque, and renal damage were 30.9%, 15.5%, 34.0%, 63.7%, and 10.4%, respectively.
Table 1.
Characteristics of the entire population
| Variables | Mean ± SD/Median (IQR) or n (%) |
|---|---|
| Demographic and medical history | |
| Age, y | 70 (67‐76) |
| Male, n (%) | 1166 (44.5) |
| Body mass index, kg/m2 | 24.0 ± 3.6 |
| Systolic blood pressure, mm Hga | 135 ± 17 |
| Smokers, n (%) | 385 (14.7) |
| Hypertension, n (%) | 1685 (64.3) |
| Diabetes, n (%) | 604 (23.1) |
| Coronary arterial disease, n (%) | 867 (33.2) |
| Stroke, n (%) | 537 (20.5) |
| Antihypertensive therapy, n (%) | 1319 (50.3) |
| Hypoglycemic therapy, n (%) | 459 (17.5) |
| Statin treatment, n (%) | 445 (17.0) |
| Biochemical parameters | |
| Total cholesterol, mmol/L | 5.11 ± 1.04 |
| LDL, mmol/L | 3.13 ± 0.88 |
| HDL, mmol/L | 1.40 ± 0.37 |
| Triglyceride, mmol/L | 1.38 (1.03‐1.89) |
| Glucose, mmol/L | 5.2 (4.8‐6.0) |
| Serum creatinine, µmol/L | 75.49 ± 21.15 |
| Hypertension‐mediated organ damage | |
| LVMI, g/m2 | 93.3 ± 29.5 |
| LVH, n (%) | 805 (30.9) |
| E/E a | 9.7 ± 3.9 |
| LVDD, n (%) | 397 (15.5) |
| CF‐PWV, m/s | 9.5 ± 2.3 |
| Arterial stiffness, n (%) | 871 (34.0) |
| Carotid plaque, n (%) | 1663 (63.7) |
| eGFR, mL/min/1.73 m2 | 81.90 ± 15.04 |
| Renal damage, n (%) | 273 (10.4) |
Values are represented as n (%) or mean ± SD/median (IQR).
Abbreviations: CF‐PWV, carotid‐femoral pulse wave velocity; E/E a, ratio of peak early diastolic transmitral flow velocity (E) and early diastolic lateral mitral annular velocity (E a); eGFR, estimated glomerular filtration rate; HDL, high density lipoprotein cholesterol; IQR, interquartile range; LDL, low density lipoprotein cholesterol; LVDD, left ventricular diastolic dysfunction; LVH, left ventricular hypertrophy; LVMI, left ventricular mass index.
Measured in sitting position using a mercury sphygmomanometer.
3.2. Four‐limb blood pressures and their differences
As shown in Table 2, the median IASBPD, ILSBPD, and mean ABI were 5, 7, and 1.0 mm Hg, respectively. Prevalences of IASBPD ≥10 mm Hg, ILSBPD ≥15 mm Hg, and ABI ≤0.9 were 24.2%, 18.4%, and 13.5%, respectively. The proportions of subjects presenting 0, 1, and ≥2 abnormal inter‐limb systolic BPDs were 60.9%, 25.1%, and 14.0%, respectively.
Table 2.
Four‐limb blood pressures and their differences
| Variables | Mean ± SD/Median (IQR) or n (%) |
|---|---|
| Right arm systolic BP, mm Hg | 145 ± 22 |
| Right arm diastolic BP, mm Hg | 80 ± 12 |
| Left arm systolic BP, mm Hg | 143 ± 21 |
| Left arm diastolic BP, mm Hg | 79 ± 11 |
| Right leg systolic BP, mm Hg | 156 ± 24 |
| Right leg diastolic BP, mm Hg | 75 ± 10 |
| Left leg systolic BP, mm Hg | 154 ± 24 |
| Left leg diastolic BP, mm Hg | 75 ± 10 |
| IASBPD, mm Hg | 5 (2‐10) |
| ILSBPD, mm Hg | 7 (3‐13) |
| ABI | 1.0 ± 0.1 |
| IASBPD ≥10 mm Hg, n (%) | 635 (24.2) |
| IASBPD ≥15 mm Hg, n (%) | 482 (18.4) |
| ABI ≤0.9, n (%) | 354 (13.5) |
Values are represented as n (%) or mean ± SD/median (IQR).
Abbreviations: ABI, ankle‐brachial index; BP, blood pressure; IASBPD, inter‐arm systolic blood pressure difference; ILSBPD, inter‐leg systolic blood pressure difference; IQR, interquartile range.
3.3. Comparisons of risk factors, biochemical parameters, and diseases between groups
Comparisons of risk factors, biochemical parameters, and cerebro‐cardiovascular diseases between groups are shown in Table 3. In terms of the level or prevalence, nearly all cardiovascular risk factors showed upward trends from Group A, through Group B, to Group C, with statistical significance reached in age, BMI, SBP, smoking, hypertension, diabetes, triglyceride, and glucose (P ≤ 0.007 for overall trend for each variable). HDL showed a significantly negative association with the accumulation of abnormal inter‐limb systolic BPDs (P < 0.0001 for overall trend). Prevalences of CAD and stroke also increased from Group A, through Group B, to Group C, but statistical significance only reached in stroke (P = 0.007 for overall trend). In post hoc comparisons, compared with Group A, Group B showed significantly higher levels of BMI, SBP, and triglyceride and higher prevalence of hypertension and diabetes, but lower HDL; Group C showed significantly higher age, BMI, SBP, triglyceride, glucose and higher prevalence of smoking, hypertension, diabetes, and stroke, indicating that participants with two or more abnormal inter‐lime systolic BPDs presented the highest burden of cardiovascular risk factors.
Table 3.
Comparisons of risk factors, biochemical parameters, and diseases between groups
| Variables |
Group A 1595 (60.9%) |
Group B 657 (25.1%) |
Group C 369 (14.0%) |
P | P for trend |
|---|---|---|---|---|---|
| Cardiovascular risk factors | |||||
| Age, y | 70 (67‐74) | 70 (67‐76) | 72 (68‐79)*, ** | <0.0001 | <0.0001 |
| Male, n (%) | 692 (43.4) | 293 (44.6) | 181 (49.2) | 0.18 | 0.06 |
| Body mass index, kg/m2 | 23.5 ± 3.5 | 24.7 ± 3.5* | 24.9 ± 3.6* | <0.0001 | <0.0001 |
| Systolic blood pressure, mm Hga | 133 ± 17 | 138 ± 18* | 139 ± 18* | <0.0001 | <0.0001 |
| Smokers, n (%) | 209 (13.1) | 106 (16.1) | 70 (19.0)* | 0.008 | 0.002 |
| Hypertension, n (%) | 970 (60.9) | 455 (69.3)* | 260 (70.5)* | <0.0001 | <0.0001 |
| Diabetes, n (%) | 327 (20.5) | 168 (25.6)* | 109 (29.5)* | 0.0002 | <0.0001 |
| Biochemical parameters | |||||
| TC, mmol/L | 5.11 ± 1.04 | 5.09 ± 1.00 | 5.14 ± 1.08 | 0.73 | 0.77 |
| LDL, mmol/L | 3.13 ± 0.90 | 3.11 ± 0.81 | 3.19 ± 0.92 | 0.40 | 0.53 |
| HDL, mmol/L | 1.44 ± 0.37 | 1.37 ± 0.37* | 1.30 ± 0.31*, ** | <0.0001 | <0.0001 |
| Triglyceride, mmol/L | 1.33 (1.00‐1.84) | 1.44 (1.05‐1.91)* | 1.47 (1.09‐2.09)* | 0.0004 | <0.0001 |
| Glucose, mmol/L | 5.2 (4.8‐5.9) | 5.2 (4.8‐6.1) | 5.3 (4.9‐6.4)* | 0.01 | 0.005 |
| Cerebro‐cardiovascular diseases | |||||
| CAD, n (%) | 519 (32.6) | 216 (32.9) | 132 (35.9) | 0.49 | 0.30 |
| Stroke, n (%) | 303 (19.0) | 141 (21.5) | 93 (25.2)* | 0.02 | 0.007 |
Abbreviations: CAD, cardiovascular arterial disease; HDL, high density lipoprotein cholesterol; LDL, low density lipoprotein cholesterol; TC, total cholesterol.
Measured in sitting position using a mercury sphygmomanometer.
P < 0.05, compared with Group A.
P < 0.05, compared with Group B.
3.4. The differences in HMOD between groups
The prevalence of most organ damage gradually increased from Group A, across Group B, to Group C (P ≤ 0.0003 for overall trend), as shown in Table 4. Post hoc comparisons indicated that Group C presented a clustering of HMOD including LVH, arterial stiffness, carotid plaque, and renal damage, compared with Group A and Group B. In univariable logistic regression analyses, similar findings were observed, as shown in Table 5. After adjustment for covariates including age, gender, BMI, smoking, hypertension, diabetes, low density lipoprotein cholesterol, high density lipoprotein cholesterol, and antihypertensive, hypoglycemic, and statin treatment, Group C still showed higher risk for LVH (Odds ratio [OR]: 1.35; 95% confidence interval [CI]: 1.04‐1.76) and carotid plaque (OR: 1.88; 95% CI: 1.43‐2.48) compared with Group A and higher risk for arterial stiffness (OR: 1.36; 95% CI: 1.01‐1.83) and carotid plaque (OR: 1.46; 95% CI: 1.08‐1.97) compared with Group B. However, adjustment for potential covariates attenuated the association for renal damage.
Table 4.
The differences in HMOD among groups
| Variables | Group A | Group B | Group C | P | P for trend |
|---|---|---|---|---|---|
| LVMI, g/m2 | 91.6 ± 27.9 | 95.2 ± 40.4* | 97.5 ± 33.7* | 0.0004 | <0.0001 |
| LVH, n (%) | 452 (28.5) | 214 (32.8) | 139 (37.7)* | 0.001 | 0.0003 |
| E/E a | 9.7 ± 3.8 | 9.8 ± 4.0 | 9.6 ± 4.3 | 0.70 | 0.81 |
| LVDD, n (%) | 232 (14.8) | 110 (17.1) | 55 (15.6) | 0.39 | 0.39 |
| CF‐PWV, m/s | 9.3 ± 2.2 | 9.6 ± 2.3* | 10.2 ± 2.6*, ** | <0.0001 | <0.0001 |
| Arterial stiffness, n (%) | 488 (31.3) | 223 (34.6) | 160 (45.2)*, ** | <0.0001 | <0.0001 |
| Carotid plaque, n (%) | 949 (59.72) | 431 (66.0)* | 283 (76.9)*, ** | <0.0001 | <0.0001 |
| GFR, mL/min/1.73 m2 | 83.1 ± 14.0 | 81.6 ± 15.9 | 77.1 ± 16.9*, ** | <0.0001 | <0.0001 |
| Renal damage, n (%) | 136 (8.5) | 75 (11.4) | 62 (16.8)*, ** | <0.0001 | <0.0001 |
Abbreviations: CF‐PWV, carotid‐femoral pulse wave velocity; E/E a, ratio of peak early diastolic transmitral flow velocity (E) and early diastolic lateral mitral annular velocity (E a); eGFR, estimated glomerular filtration rate; LVDD, left ventricular diastolic dysfunction; LVH, left ventricular hypertrophy; LVMI, left ventricular mass index.
P < 0.05, compared with Group A.
P < 0.05, compared with Group B.
Table 5.
Association of the number of abnormal inter‐limb systolic BPDs with HMOD by logistic regression models
| Models | Group A | Group B | Group C | Group Ca |
|---|---|---|---|---|
| Model 1 | ||||
| LVH | Ref. | 1.22 (1.01, 1.49) | 1.52 (1.20, 1.92) | 1.24 (0.95, 1.62) |
| LVDD | Ref. | 1.19 (0.93, 1.52) | 1.07 (0.77, 1.47) | 0.90 (0.63, 1.28) |
| Arterial stiffness | Ref. | 1.17 (0.96, 1.42) | 1.81 (1.43, 2.29) | 1.56 (1.20, 2.03) |
| Carotid plaque | Ref. | 1.31 (1.08, 1.58) | 2.25 (1.73, 2.92) | 1.72 (1.28, 2.30) |
| Renal damage | Ref. | 1.38 (1.03, 1.86) | 2.17 (1.57, 3.00) | 1.57 (1.09, 2.26) |
| Model 2 | ||||
| LVH | Ref. | 1.08 (0.88, 1.34) | 1.35 (1.03, 1.75) | 1.24 (0.93, 1.66) |
| LVDD | Ref. | 1.01 (0.78, 1.32) | 0.81 (0.57, 1.15) | 0.80 (0.55, 1.16) |
| Arterial stiffness | Ref. | 0.92 (0.74, 1.14) | 1.25 (0.96, 1.64) | 1.36 (1.01, 1.83) |
| Carotid plaque | Ref. | 1.26 (1.04, 1.54) | 1.85 (1.42, 2.43) | 1.46 (1.08, 1.98) |
| Renal damage | Ref. | 1.12 (0.80, 1.59) | 1.23 (0.83, 1.82) | 1.10 (0.72, 1.67) |
| Model 3 | ||||
| LVH | Ref. | 1.08 (0.88, 1.34) | 1.35 (1.04, 1.76) | 1.25 (0.93, 1.67) |
| LVDD | Ref. | 1.02 (0.79, 1.33) | 0.82 (0.58, 1.16) | 0.80 (0.55, 1.16) |
| Arterial stiffness | Ref. | 0.92 (0.74, 1.15) | 1.26 (0.96, 1.65) | 1.36 (1.01, 1.83) |
| Carotid plaque | Ref. | 1.29 (1.06, 1.58) | 1.88 (1.43, 2.48) | 1.46 (1.08, 1.97) |
| Renal damage | Ref. | 1.15 (0.81, 1.62) | 1.23 (0.83, 1.81) | 1.07 (0.70, 1.63) |
Bold text indicates statistical significance. Model 1, unadjusted; Model 2 adjusted for age, gender, BMI, smoking, hypertension, diabetes, low density lipoprotein cholesterol, and high density lipoprotein cholesterol; Model 3 adjusted for factors included in Model 2 and antihypertensive treatment, hypoglycemic treatment, and statin treatment.
Abbreviations: LVDD, left ventricular diastolic dysfunction; LVH, left ventricular hypertrophy.
Group B regarded as reference.
3.5. Results of subgroup analyses of subjects without CAD or stroke
Consistent results were obtained in subgroup analyses of the 1471 subjects without CAD or stroke, as seen in supplemental Table S1‐S5. Of note, after adjusting for covariates, Group C showed higher likelihoods of LVH (OR: 1.48; 95% CI: 1.02‐2.15) and carotid plaque (OR: 1.92; 95% CI: 1.32‐2.79) than those of Group A and higher likelihoods of arterial stiffness (OR: 1.55; 95% CI: 1.03‐2.34) and carotid plaque (OR: 1.53; 95% CI: 1.02‐2.31) than those of Group B; however, Group B showed no difference in the risk of HMOD, compared with Group A (Table S5).
4. DISCUSSION
In the present study, we revealed a significant relationship between the combination of abnormal inter‐limb systolic BPDs and the burden of cardiovascular risk factors and the severity of HMOD. We have indicated that participants with two or more abnormal inter‐limb systolic BPDs showed highest level or prevalence of cardiovascular risk factors and HMOD, especially carotid plaque, arterial stiffness, and LVH, compared with those with 0 or 1 one abnormal inter‐limb systolic BPDs. We also observed that there was a significantly higher prevalence of pre‐existing stroke in participants with higher accumulation of abnormal inter‐limb systolic BPDs. Together, these findings suggest that the combination of abnormal inter‐limb systolic BPDs may be of important value in predicting atherosclerosis‐related cardiovascular risk than each of ABI, IASBPD, and ILSBPD alone.
Previous studies have indicated that there are significant differences among the prevalences of abnormal ABI, IASBPD, and ILSBPD.2, 4, 29 In the present study, we obtained consistent results. In addition, we firstly reported the proportions of participants with 1 and ≥2 abnormal inter‐limb systolic BPDs in an elderly population (25.1% and 14.0%, respectively). These data indicate a discrepancy between the presences of upper and lower extremity artery diseases, which suggests that abnormal inter‐limb BPDs are not concomitant with each other all the time. This may explain why inter‐arm systolic BPD shows low accuracy in diagnosing lower extremity artery disease in previous studies.9, 30 Future investigation should further investigate the distribution of abnormalities of three inter‐limb systolic BPDs in other populations, especially in the selected populations such as patients with hypertension, diabetes, or CAD.
Much work has been poured into the investigation of inter‐limb BPDs, especially ABI. However, nearly all previous investigations focus on the significance of each IASBPD, ILSBPD, and ABI alone rather than the combination of them. Pathophysiologically, abnormal IASBPD directly indicates the anatomical and hemodynamic changes in vasculature of arms, while ILSBPD and ABI directly indicate the clinical changes in arteries of legs. It has been shown that the value of IASBPD is inversely related to ABI31, 32 and that increased IASBPD significantly associates with reduced ABI.33 Nevertheless, there can be some participants who have only one of the abnormalities of inter‐limb systolic BPDs, as shown in our present study. Therefore, various inter‐limb systolic BPDs are not interchangeable and the number of abnormal inter‐limb BPDs may provide additional information on multisite atherosclerotic lesion (for example, atherosclerotic lesion in both arm and leg) and suggest the severity of atherosclerosis of vasculature. In fact, a recent study has lent support to this speculation. Based on 3133 community‐dwelling elderly Chinese, Sheng and colleagues have demonstrated that the prognostic significances of ABI, IASBPD, and ILSBPD are additive and their combination can improve the prediction of mortality.4 However, the potentially underlying mechanisms for the better prediction of the combination of various inter‐limb systolic BPDs remains unclear. In our study, we found that high accumulation of abnormal inter‐limb systolic BPDs was significantly associated with greater burden of cardiovascular risk factors. Moreover, we found that participants presenting two or more abnormal inter‐limb systolic BPDs had higher odds for HMOD, especially carotid plaque, arterial stiffness, and LVH, than those with 0 or 1 abnormal inter‐limb systolic BPD. These data suggest that the greater burden of cardiovascular risk factors and higher likelihood for HMOD mediate the additively predictive value of the combination of inter‐limb systolic BPDs for mortality.
Compared to participants with 0 or 1 abnormal inter‐limb systolic BPDs, those participants with two or more abnormal inter‐limb systolic BPDs showed significantly higher likelihoods of carotid plaque and aortic stiffness, implying that the combination of abnormal inter‐limb BPDs is more closely associated with atherosclerotic lesion in carotid artery and arteriosclerotic change in aorta. Besides, we also found participants with two or more abnormal inter‐limb BPDs showed higher prevalences of previous CAD and stroke than those with 0 or 1 abnormal inter‐limb systolic BPDs, although statistical significance only reached in stroke. This suggests a closer association of the combination of abnormal inter‐limb BPDs with atherosclerotic lesions in coronary and intracranial arteries. Taken together, the combination of abnormal inter‐limb BPDs may be a better marker for multisite artery disease and can provide more information on generalized atherosclerosis and arteriosclerosis of vasculature, than each of ABI, IASBPD, and ILSBPD alone. Further investigations focusing on the association between inter‐limb BPDs and atherosclerosis of vascular system based on more accurate and comprehensive evaluation approaches such as invasive angiography could confirm our findings.
The associations of LVMI/LVH with each of ABI,34, 35 IASBPD,17, 18 and ILSBPD21 have been indicated in previous studies. In the present study, we reported the association between LVMI/LVH and the accumulation of abnormal inter‐limb BPDs, which lends further support for the association between both and suggests that LVH may be one of the mechanisms underlying the association between inter‐limb BPDs and mortality. Considering that LVH is generally correlated with LVDD, we may infer that LVDD should also associate with inter‐limb BPDs. Surprisingly, there is no association observed in either previous18 or our present study. One of the possible reasons could be that the mean E/E a of our study population was in the “gray zone” (E/E a is between 8 and 13) where the application of E/E a ratio to diagnose LVDD is limited.36 More investigations, especially using left atrium statin imaging to assess diastolic dysfunction, are required to further explore the association between LVDD and inter‐limb BPDs.
4.1. Limitations
Our study has several limitations. First, some non‐atherosclerotic diseases, such as arteritis and fibromuscular dysplasia, may also cause blood pressure differences between limbs,37 but we do not have enough information to exclude those participants in our analysis. This may have potential influence on our results, although low prevalences for these diseases. Second, in our study, CAD was diagnosed by self‐reported medical history; thus, some participants with undiagnosed latent CAD have not been counted. Besides, participants with stroke within 3 months were excluded in the Northern Shanghai Study. Therefore, the prevalences of CAD and stroke in our study are underestimated, which may produce bias for our results. Third, because of lacking detailed information on antihypertensive agents in our population, we cannot further adjust the classes of antihypertensive medications. Fourth, high ABI is associated with increased cardiovascular risk. Thus, ABI >1.4 is suggested to be also considered when stratifying the subjects in this study. However, the number of participants with ABI >1.4 in this cohort is tiny (only six subjects). But we will further investigate this topic when we obtain enough cases in the future, considering that the Northern Shanghai Study is an ongoing prospective study.
5. CLINICAL IMPLICATIONS
It has been well recognized that blood pressure should be measured for both the upper extremities at the first visit. However, whether the blood pressures in lower extremities should also be measured has not been answered. In the elderly, ABI measurement is recommended by guideline, which means four‐limb BPs should be measured in elderly individuals although the purpose is to calculate ABI. This points out that, to some extent, the four‐limb blood pressure measurement may be of potential value for elderly people. In a previous study based on an elderly cohort, the combination of ABI, IASBPD, and ILSBPD was indicated to improve the prediction of mortality.4 In our study, also based on an elderly population, we demonstrated that the combination of abnormal inter‐limb systolic BPDs was significantly associated with greater burden of cardiovascular risk factors, higher level of HMOD, especially carotid plaque, arterial stiffness and LVH, and higher prevalence of previous stroke. Additionally, in subgroup analyses of subjects without CAD or stroke, we obtained consistent findings. Collectively, these findings suggest the extra value of the combination of abnormal inter‐limb systolic BPDs, as least for the elderly. In other words, it may be of importance to expand the measurement of blood pressure in both arms to both arms and legs, namely four‐limb blood pressure measurement, in clinical practice.
CONFLICT OF INTEREST
The authors declare no conflicts of interest.
AUTHOR CONTRIBUTION
Shikai Yu performed literature search; conceived, designed, and performed the analysis; and wrote the paper. Hongwei Ji, Yuyan Lu, Jing Xiong, Chen Chi, Jiadela Teliewubai, Ximin Fan, Yi Zhang, and Shikai Yu collected the data. Shikai Yu, Shanquan Chen, Yawei Xu, and Yi Zhang interpreted the results. Shanquan Chen conceived and designed the analysis. Jacque Blacher, Jue Li, Yi Zhang, and Yawei Xu formulated the methods and designed the protocol of The Northern Shanghai Study. Yi Zhang and Yawei Xu reviewed and revised the manuscript.
Supporting information
ACKNOWLEDGMENT
The authors thank all the investigators and participants who participated in the Northern Shanghai Study. This work was authorized and financially supported by the National Key Research and Development Grant (2017YFC0111800) and the Shanghai Municipal Government Grant (2013ZYJB0902; 15GWZK1002). Yi Zhang was supported by the National Nature Science Foundation of China (81300239; 81670377). Shikai Yu was supported by the China Scholarship Council (Grant No. 201806260070).
APPENDIX 1.
The Northern Shanghai Study investigators: Yawei Xu, Yi Zhang, Jue Li, Jacque Blacher, Yuyan Lu, Jing Xiong, Shikai Yu, Chen Chi, Jiadela Teliewubai, Bin Bai, Hongwei Ji, Ximin Fan, Yiwu Zhou, Jun Zhang, Ziwen Zhu, Jiamin Tang, Song Zhao, Yuan Zhong, and Rusitanmujiang Maimaitiaili.
Yu S, Ji H, Lu Y, et al; On behalf of the Northern Shanghai Study investigators . Significance of the combination of inter‐limb blood pressure differences in the elderly: The Northern Shanghai Study. J Clin Hypertens. 2019;21:884–892. 10.1111/jch.13588
Contributor Information
Yi Zhang, Email: yizshcn@gmail.com.
Yawei Xu, Email: xuyawei@tongji.edu.cn.
On behalf of the Northern Shanghai Study investigators:
Bin Bai, Yiwu Zhou, Jun Zhang, Ziwen Zhu, Jiamin Tang, Song Zhao, Yuan Zhong, and Rusitanmujiang Maimaitiaili
REFERENCES
- 1. Aboyans V. Asymmetrical limbs arterial pressures: a new marker of atherosclerosis. Hypertens Res. 2013;36:394‐395. [DOI] [PubMed] [Google Scholar]
- 2. Aboyans V, Ricco J‐B, Bartelink M‐L, et al. 2017 ESC guidelines on the diagnosis and treatment of peripheral arterial diseases, in collaboration with the European Society for Vascular Surgery (ESVS): document covering atherosclerotic disease of extracranial carotid and vertebral, mesenteric, renal, upper and lower extremity arteries endorsed by: the European Stroke Organization (ESO)the task force for the diagnosis and treatment of peripheral arterial diseases of the European Society of Cardiology (ESC) and of the European Society for Vascular Surgery (ESVS). Eur Heart J. 2018;39:763‐816. [DOI] [PubMed] [Google Scholar]
- 3. 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] [PMC free article] [PubMed] [Google Scholar]
- 4. Sheng C‐S, Liu M, Zeng W‐F, Huang Q‐F, Li Y, Wang J‐G. Four‐limb blood pressure as predictors of mortality in elderly chinese. Hypertension. 2013;61:1155‐1160. [DOI] [PubMed] [Google Scholar]
- 5. Clark CE, Steele AM, Taylor RS, Shore AC, Ukoumunne OC, Campbell JL. Interarm blood pressure difference in people with diabetes: measurement and vascular and mortality implications: a cohort study. Diabetes Care. 2014;37:1613‐1620. [DOI] [PubMed] [Google Scholar]
- 6. Clark CE, Campbell JL, Powell RJ. The interarm blood pressure difference as predictor of cardiovascular events in patients with hypertension in primary care: cohort study. J Hum Hypertens. 2007;21:633‐638. [DOI] [PubMed] [Google Scholar]
- 7. Kranenburg G, Spiering W, de Jong PA, et al. Inter‐arm systolic blood pressure differences, relations with future vascular events and mortality in patients with and without manifest vascular disease. Int J Cardiol. 2017;244:271‐276. [DOI] [PubMed] [Google Scholar]
- 8. Kim J, Song T‐J, Song D, et al. Interarm blood pressure difference and mortality in patients with acute ischemic stroke. Neurology. 2013;80:1457‐1464. [DOI] [PubMed] [Google Scholar]
- 9. 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;379:905‐914. [DOI] [PubMed] [Google Scholar]
- 10. Aboyans V, Criqui MH, McDermott MM, et al. The vital prognosis of subclavian stenosis. J Am Coll Cardiol. 2007;49:1540‐1545. [DOI] [PubMed] [Google Scholar]
- 11. Weiss A, Grossman A, Beloosesky Y, Koren‐Morag N, Green H, Grossman E. Inter‐arm blood pressure difference in hospitalized elderly patients is not associated with excess mortality. J Clin Hypertens (Greenwich). 2015;17:786‐791. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Ozturk C, Balta S, Ozturk A, Aparci M, Sadir S, Celik T. Inter‐arm blood pressure differences may be important for predicting mortality. J Clin Hypertens (Greenwich). 2016;18:164. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Shadman R, Criqui MH, Bundens WP, et al. Subclavian artery stenosis: prevalence, risk factors, and association with cardiovascular diseases. J Am Coll Cardiol. 2004;44:618‐623. [DOI] [PubMed] [Google Scholar]
- 14. Aboyans V, Kamineni A, Allison MA, et al. The epidemiology of subclavian stenosis and its association with markers of subclinical atherosclerosis: the multi‐ethnic study of atherosclerosis (MESA). Atherosclerosis. 2010;211:266‐270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Canepa M, Milaneschi Y, Ameri P, et al. Relationship between inter‐arm difference in systolic blood pressure and arterial stiffness in community‐dwelling older adults. J Clin Hypertens (Greenwich). 2013;15:880‐887. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Tanaka Y, Fukui M, Tanaka M, et al. The inter‐arm difference in systolic blood pressure is a novel risk marker for subclinical atherosclerosis in patients with type 2 diabetes. Hypertens Res. 2014;37:548‐552. [DOI] [PubMed] [Google Scholar]
- 17. Spannella F, Giulietti F, Fedecostante M, et al. Interarm blood pressure differences predict target organ damage in type 2 diabetes. J Clin Hypertens (Greenwich). 2017;19:472‐478. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Su H‐M, Lin T‐H, Hsu P‐C, et al. Association of interarm systolic blood pressure difference with atherosclerosis and left ventricular hypertrophy. PLoS ONE. 2012;7:e41173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Chen S‐C, Chang J‐M, Tsai Y‐C, et al. Association of interleg bp difference with overall and cardiovascular mortality in hemodialysis. Clin J Am Soc Nephrol. 2012;7:1646‐1653. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Okada H, Fukui M, Tanaka M, et al. A difference in systolic blood pressure between arms and between lower limbs is a novel risk marker for diabetic nephropathy in patients with type 2 diabetes. Hypertens Res. 2013;36:403‐407. [DOI] [PubMed] [Google Scholar]
- 21. Su H‐M, Lin T‐H, Hsu P‐C, et al. Association of interankle systolic blood pressure difference with peripheral vascular disease and left ventricular mass index. Am J Hypertens. 2014;27:32‐37. [DOI] [PubMed] [Google Scholar]
- 22. Guo H, Sun F, Zhang H, Dong L, Gu X, Tian YE. Interankle systolic blood pressure difference is a marker of prevalent stroke in chinese adults: a cross‐sectional study. J Clin Hypertens (Greenwich). 2017;19:58‐66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Ji H, Xiong J, Yu S, et al. Northern shanghai study: cardiovascular risk and its associated factors in the Chinese elderly‐a study protocol of a prospective study design. BMJ Open. 2017;7:e013880. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Stevens LA, Claybon MA, Schmid CH, et al. Evaluation of the chronic kidney disease epidemiology collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kidney Int. 2011;79:555‐562. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Mancia G, Fagard R, Narkiewicz K, 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). J Hypertens. 2013;31:1281‐1357. [DOI] [PubMed] [Google Scholar]
- 26. World Health Organization . Definition, diagnosis and classification of diabetes mellitus and its complications: report of a who consultation. Part 1, diagnosis and classification of diabetes mellitus. Department of Noncommunicable Disease Surveillance, Geneva, 1999. Report No.: WHO/NCD/NCS/99.2.
- 27. Lang R, Bierig M, Devereux R, et al. Recommendations for chamber quantification. Eur J Echocardiogr. 2006;7:79‐108. [DOI] [PubMed] [Google Scholar]
- 28. Nagueh SF, Appleton CP, Gillebert TC, et al. Recommendations for the evaluation of left ventricular diastolic function by echocardiography. Eur J Echocardiogr. 2009;10:165‐193. [DOI] [PubMed] [Google Scholar]
- 29. Zhang Z, Ma J, Tao X, Zhou Y, Liu X, Su H. The prevalence and influence factors of inter‐ankle systolic blood pressure difference in community population. PLoS ONE. 2013;8:e70777. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Herráiz‐Adillo Á, Soriano‐Cano A, Martínez‐Hortelano JA, et al. Simultaneous inter‐arm and inter‐leg systolic blood pressure differences to diagnose peripheral artery disease: a diagnostic accuracy study. Blood Press. 2018;27:112‐119. [DOI] [PubMed] [Google Scholar]
- 31. Clark CE, Campbell JL, Powell RJ, Thompson JF. The inter‐arm blood pressure difference and peripheral vascular disease: cross‐sectional study. Fam Pract. 2007;24:420‐426. [DOI] [PubMed] [Google Scholar]
- 32. Igarashi Y, Chikamori T, Tomiyama H, et al. Clinical significance of inter‐arm pressure difference and ankle‐brachial pressure index in patients with suspected coronary artery disease. J Cardiol. 2007;50:281‐289. [PubMed] [Google Scholar]
- 33. Singh S, Sethi A, Singh M, et al. Simultaneously measured inter‐arm and inter‐leg systolic blood pressure differences and cardiovascular risk stratification: a systemic review and meta‐analysis. J Am Soc Hypertens. 2015;9:640‐650.e612. [DOI] [PubMed] [Google Scholar]
- 34. Ix JH, Katz R, Peralta CA, et al. A high ankle brachial index is associated with greater left ventricular mass mesa (Multi‐Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2010;55:342‐349. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Fu W, Ye C, Mei C, Rong S, Wang W. Reverse correlation between ankle‐brachial index and left ventricular hypertrophy in patients on maintenance haemodialysis. Nephrology. 2006;11:9‐14. [DOI] [PubMed] [Google Scholar]
- 36. Ommen SR, Nishimura RA, Appleton CP, et al. Clinical utility of doppler echocardiography and tissue doppler imaging in the estimation of left ventricular filling pressures: a comparative simultaneous doppler‐catheterization study. Circulation. 2000;102:1788‐1794. [DOI] [PubMed] [Google Scholar]
- 37. Sharma BK, Jain S, Suri S, Numano F. Diagnostic criteria for takayasu arteritis. Int J Cardiol. 1996;54(Suppl):S141‐S147. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials