Inter-arm blood pressure difference detected with computer-programmed blood pressure measurement:difference on the first reading and the average value of 2-3 readings

Inter-arm blood pressure difference detected with computer-programmed blood pressure measurement:difference on the first reading and the average value of 2-3 readings | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Inter-arm blood pressure difference detected with computer-programmed blood pressure measurement:difference on the first reading and the average value of 2-3 readings Hai Su, linglin XIA, Huihui Bao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6143519/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: To compare the inter-arm blood pressure (BP) difference (IAD) detected from the first BP reading with that detected from the average value of 2-3 BP readings when using computer program-controlled BP measurement (CCBPM). Methods: The CCBPM was used for BP measurement during a health examination of 3，067 rural community residents. The IAD was evaluated based on the first BP reading and the average value of 2-3 BP readings, respectively. A systolic- and diastolic-IAD (sIAD or dIAD) ≥10 mm Hg was considered abnormal. Results: In the reference arm, the SBP/DBP was 136.42±19.81/81.23 ± 10.51 mm Hg in the first BP reading; while in the average reading, they were significantly lower (134.64±18.39/80.28±9.78 mm Hg, both P = 0.011). The detection rate of abnormal sIAD was 9.08% and that of abnormal dIAD was 4.74% in the first BP reading, while in the average reading, the sIAD was 5.47% and the dIAD was 2.47%. There was a difference of about 40% for sIAD. Conclusion: Even when using CCBPM, the detection rate of IAD in the first BP reading was significantly higher than that in the average value of 2-3 BP readings. Health sciences/Health care/Disease prevention Biological sciences/Physiology/Circulation old age BP prevalence hypertension bilateral Summary Table What is known about the topic: To evaluate the inter-arm blood pressure (BP) difference (IAD) bilateral-arm blood pressure (BP) method should be used. The CCBPM is a compute controlled bilateral-arm BP device with 3 rest times before BP measurement and standard BP measurement program. What this study adds: The detection rate of abnormal sIAD based on the first BP reading was higher than that on the average BP reading . Even using CCBPM, for evaluating IAD the average value of 2-3 BP readings should be used. Introduction The hypertension guidelines published by many countries recommend simultaneous bilateral-arm blood pressure (BP) measurement [1-4]. The first purpose is to determine the reference arm and the second is to assess the inter-arm difference (IAD). The reference arm is the one with a higher BP reading, and it should be used for subsequent BP measurements. Many studies have demonstrated that using the reference arm for BP measurement can reduce the misdiagnosis of hypertension compared to using only the right or left arm. The second purpose of bilateral-arm BP measurement is to evaluate the IAD. Normally, the BP levels between the two arms are basically similar or their difference is less than 10 mm Hg. When using a mercury-column sphygmomanometer, the sequential BP method was commonly used to evaluate IAD, but the results were often overestimated by about three times compared to the synchronous method [5]. A large number of studies have demonstrated the value of IAD in diagnosing peripheral vascular diseases and predicting poor outcomes of cardiovascular diseases [5-8]. In fact, IAD is rarely involved in epidemiological studies. Even when it is involved, the common method currently is to use two electronic BP devices of the same model to measure the BP of both arms. However, this method may have some shortcomings. For example, the rest time of participants may be insufficient, and the interval between two BP measurements may not be 1-2 minutes. According to the requirements for a standard BP measurement, at least 8 minutes are needed. But this may be difficult to achieve in clinical practice. Currently, a new type of BP device, a computer-controlled, fully automated bilateral-arm BP measurement instrument (CCBPM, Jiangxi Changgang Medical Technology Co., LTD) with two built-in Omron devices (Omron-U30), has been developed. When using the CCBPM, the operator just needs to place two cuffs on both upper arms; after a 3-minute waiting time, the BP is measured twice with a 1-minute interval; based on the difference between the first two BP readings, the instrument automatically decides whether a third BP measurement is necessary; finally, the average value of 2 or 3 BP readings is reported [9, 10]. It is well-known that evaluating IAD is important, but the measurement methodology has a major influence on the results. It is unclear what influence a single BP measurement has on IAD evaluation [6]. This study aimed to investigate whether there is a difference in the detection rate of abnormal IAD (≥10 mm Hg) based on the first BP reading and the average value of 2-3 BP readings when using CCBPM in 3,067 rural residents. Study Population and Methods The study was approved by the ethics committee of the Second Affiliated Hospital of Nanchang University (The IBR EC opinion letter 2024-02) and was in line with the Helsinki principles, causing no harm to the interests of patients. All patients provided their oral informed consent. Survey Population From April to June 2024, 3,067 residents (68.09 ± 9.34 years old, age range 45-94 years old) were included. Among them, 1705 were women and 1362 were men. Specifically, 605 were in the middle-aged group of 45-59 y, (54.27 ± 3.5 y, 57.4% women), 1,650 were in the 60-74 age group (67.65 ± 4.34 y, 56.5% women), and 812 were in the very-old group (≥75 years old, 79.27 ± 3.76 y, 52.3% women). Methods All participants completed BP measurements in the morning fasting state (7 to 11 am) according to the Chinese Hypertension Guideline (2018). The CCBPM is designed strictly according to the existing BP measurement requirements. There is a 3-minute rest time before BP measurement. After the 3-minute countdown, the instrument automatically starts to measure the BP with an interval of one minute. If the difference between the first two BP levels is greater than 5 mmHg, the CCBPM will automatically measure the third BP. At the end of the BP measurement, the instrument will calculate the average BP value of the two arms and the systolic IAD (sIAD) and diastolic IAD (dIAD) based on the average value of 2-3 BP readings (average). In this study, the IAD of the first BP reading was calculated to compare the difference in the detection rate of abnormal IAD (≥ 10 mmHg). Standards for Different Subgroups (1) Different HT Subgroups Hypertension Classification: Based on the BP values of the reference arm. Normal: SBP/DBP < 140/90 mm Hg (1891 cases) Grade 1 hypertension: SBP/DBP between 140-159/90-99 mm Hg (889 cases) Grade 2 hypertension: SBP/DBP between 160-179/100-109 mm Hg (237 cases) 2. Different Age Subgroups Three subgroups were created: Middle-aged subgroup: 45-59 years old, 605 participants Elderly subgroup: 60-74 years old, 1650 participants Very-old subgroup: > 75 years old, 812 participants 3. Different Sex Subgroups : Two subgroups were created, namely male and female. Statistical Methods Data were processed and analyzed using Excel 2019 and SPSS 26.0 statistical software. Data with a normal distribution are presented as mean ± standard deviation, and the paired t-test was used for testing. Data without a normal distribution were described by the median and interquartile range, and the Wilcoxon signed-rank test was used for analysis. Classification data are presented as percentages (%) and were tested with the chi-square test. The criteria for determining statistical significance are as follows: P < 0.05 indicates a statistical difference, P < 0.01 indicates a significant statistical difference, and P < 0.001 indicates an extremely significant statistical difference. Results 2.1 BP Values and IAD on the First and Average BP Readings Based on the reference arm, in the 3067 participants, the systolic blood pressure (SBP) and diastolic blood pressure (DBP) on the first BP reading were significantly higher than those on the average BP readings (134.90±19.63/81.57±10.52 mm Hg vs 133.29±18.31/80.79±9.92 mm Hg, P < 0.001). At the same time, the values of systolic inter-arm difference (sIAD) and diastolic inter-arm difference (dIAD) on the first BP reading were also higher than those on the average BP reading. On the first BP reading, the detection rate of abnormal sIAD was 9.1% and that of abnormal dIAD was 4.3%; these were significantly higher than those of 5.6% and 2.2% on the average value. However, there was no significant difference in the pulse rate between the first BP reading and the average BP reading (P = 0.687) (Table 1). Table 1. The SBP and DBP on the first BP reading were higher than those on the average BP reading. This finding was observed among the three age subgroups and hypertension subgroups. Meanwhile, the absolute sIAD and dIAD levels on the first reading were also higher than those on the average reading. Similarly, this finding was also observed in different age and hypertension subgroups (Table 2). Table 2. The detection rate of abnormal sIAD was higher on the first BP reading than that on the average BP reading in different sex, age, and hypertension grade subgroups. The detection rate of abnormal dIAD on the first BP reading was higher than that on the average BP reading in different age and hypertension grade subgroups, but it was lower on the first reading in some cases. The detection rate of abnormal sIAD in hypertensive patients increased with the increase in hypertensive degree. However, this trend was not observed on the average BP reading. Table 3. Discussion In this study, the computer-controlled, fully automated bilateral-arm blood pressure (BP) measurement instrument (CCBPM) was used for the first time to evaluate the inter-arm difference (IAD) in a community health examination. The CCBPM used in this study has two built-in validated BP devices (OMRON, 3U). With the help of a computer, the whole BP measurement process is controlled according to the regulations of BP measurement, so the BP values are more accurate. Regarding the BP of the reference arm, the systolic blood pressure (SBP) and diastolic blood pressure (DBP) on the first BP reading in the 3,067 participants were significantly higher than those on the average BP reading. The detection rate of abnormal systolic inter-arm difference (sIAD) on the average reading was 5.6%, and that of diastolic inter-arm difference (dIAD) was 2.2%, which were lower than the 9.1% and 4.3% on the first BP reading, with a difference of about 40%. Why were the sIAD and dIAD on the average reading lower? The first reason is that the difference between electronic BP devices may be up to 5 mmHg. Using average readings may attenuate this difference. The second reason is that participants who had 2–3 BP measurements may have had a longer rest time (estimated to be 2–3 minutes more). It is well-known that for every 10 mmHg increase in SBP, the detection rate of sIAD over 10 mmHg increases by 4% [ 11 ]. Therefore, the prevalence of sIAD was higher in the group with elevated BP levels [ 12 ]. As the prevalence of IADs is overestimated threefold when sequential measurement is used [ 5 ], synchronous bilateral-arm BP measurement is suggested. This study shows that even when using synchronous bilateral-arm BP measurement, a single BP measurement can still lead to an overestimation of abnormal sIAD by 40% and that of dIAD by 50% compared with the average reading. Our findings demonstrate that the BP measurement methodology has a major influence on IAD results. To prevent overestimation and observer bias, IAD should be assessed simultaneously at both arms, and multiple readings should be taken [ 6 ]. Even though approximately 40% of this population may have hypertension based on the BP measurement, the detection rates of abnormal sIAD (5.5%) and dIAD (2.5%) on the average values are lower than the existing values. A meta-analysis showed that the pooled prevalence of abnormal sIAD from four studies was 19.6%, and that for abnormal dIAD was 8.1% [ 8 ]. In 414 hypertensives, the detection rate of sIAD was as high as 18.4% [ 13 ]. In a Chinese community survey with 10,657 healthy subjects, 15.0% had an sIAD of 10–15 mmHg, 8.3% had an sIAD of 15–20 mmHg, and 7.7% of participants had an sIAD > 20 mmHg [ 14 ]. Using CCBPM not only provides accurate BP readings but also greatly reduces the labor intensity of investigators in large-scale epidemiological investigations. According to our experience, one professional can manage 5 instruments [ 15 ]. Limitation The studied population was from a rural community in southern China, and the sample size was not very large. It is necessary to further accumulate data in a larger population and in different areas. Conclusions Even when using bilateral-arm BP measurement in participants who had enough rest time before BP measurement, the detection rate of IAD detected by a single BP measurement is significantly higher than that detected by the average value of 2–3 BP measurements. Declarations Conflict of interest： no References Chinese Guidelines for the Prevention and Treatment of Hypertension (revised in 2024). Chinese Journal of Hypertension (Chinese and English), 2024,32(7): 603–700. Whelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High blood pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 2017; 71(6):e13–e115. McEvoy JW, McCarthy CP, Bruno RM, Brouwers S, Canavan MD, Ceconi C, et al. 2024 ESC Guidelines for the management of elevated blood pressure and hypertension. Eur Heart J. 2024 ;45(38):3912-4018. doi: 10.1093/eurheartj/ehae178. PMID: 39210715. Umemura S, Arima H, Arima S, Asayama K, Dohi Y, Hirooka Y, et al. The Japanese Society of Hypertension Guidelines for the Management of Hypertension (JSH 2019). Hypertens Res. 2019;42(9):1235-1481. 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. Epub 2016 Oct 10. PMID: 27789511; PMCID: PMC5072922. 6 Verberk WJ, Kessels AG, Thien T. Blood pressure measurement method and inter-arm differences: a meta-analysis. Am J Hypertens. 2011;24(11):1201-8. doi: 10.1038/ajh.2011.125. Epub 2011 Jul 21. PMID: 21776035. 7 Clark CE, Campbell JL, Evans PH, Millward A. Prevalence and clinical implications of the inter-arm blood pressure difference: A systematic review. J Hum Hypertens. 2006;20(12):923-31. doi: 10.1038/sj.jhh.1002093. Epub 2006 Oct 12. PMID: 17036043. 8 Clark CE, Campbell JL, Evans PH, Millward A. Prevalence and clinical implications of the inter-arm blood pressure difference: A systematic review. J Hum Hypertens. 2006;20(12):923-31. doi: 10.1038/sj.jhh.1002093. Epub 2006 Oct 12. PMID: 17036043. Xia Linglin, Su Hai. Computerized-controlled, standardized office blood pressure measurement. Chinese Journal of Hypertension, 2022,30 (9): 886-887. Su Hai, Guo Zixing. The way out for accurate blood pressure measurement: automatic blood pressure measurement with standard and whole process control. Chinese Journal of Hypertension 2024,32 (04): 300-303. 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[J]. The British journal of general practice: the Journal of the Royal College of General Practitioners, 2016, 66(652): e838-e847. Watts RA, Hatemi G, Burns JC, Mohammad AJ. Global epidemiology of vasculitis. Nat Rev Rheumatol. 2022 ;18(1):22-3 Sun H, Li P, Su H, Wang J, Hu W, Li J, et al. The detection rates of inter-arm systolic blood pressure difference vary with blood pressure levels in hypertensive patients under antihypertensive therapy. International Journal of Cardiology. Int J Cardiol. 2014;172 (3):e419-20. English JA, Carell ES, Guidera SA, Tripp HF. Angiographic prevalence and clinical predictors of left subclavian stenosis in patients undergoing diagnostic cardiac catheterization . Catheterization and cardiovascular interventions. 2001; 54(1):8-11. doi: 10.1002/ccd.1230. PMID: 11553941. Yuan Zhao, Xia Linglin, Wang Tao, Bao Huihui, Su Hai. Comparative study of computer-programmed blood pressure measurement with measurement of blood pressure using an artificial right arm on the prevalence of hypertension in the elderly population. Chinese Journal of Cardiovascular Diseases；2025; 53 (1): 37-41. Tables Table 1 Compaction of the BP, IAD parameters on the first and average reading in 3067 participants item The first Average P SBP（mmHg） 134.90±19.63 133.29±18.31 ＜0.001 DBP（mmHg） 81.57±10.52 80.79±9.92 ＜0.001 Pulse rate （beats/min） 73.26±11.30 73.24±10.79 0.687 sIAD（mmHg） 4.31±4.71 3.68±3.64 ＜0.001 dIAD（mmHg） 3.27±3.30 2.77±2.48 ＜0.001 sIAD≥10 mm Hg n (%) 280（9.1） 172（5.6） ＜0.001 dIAD≥10 mm Hg n (%) 132（4.3） 67（2.2） ＜0.001 Table 2 the BP levels and IAD in different subgroups SBP DBP sIAD value dIAD value The first Average The first Average The first Average The first Average Females (1705) 135.29±20.62 133.62±19.29 * 80.98±10.62 80.08±9.95 * 4.26±4.93 3.56±3.69 * 3.37±3.57 2.80±2.52 * Males (1362) 134.42±18.32 132.88±17.01 * 82.30±10.35 81.69±9.81 *** 4.37±4.41 3.84±3.57 *** 3.14±2.93 2.72±2.42 *** P 0.226 0.268 0.001 ＜0.001 0.514 0.037 0.061 0.365 Middle (605) 128.24±18.60 126.94±17.38 * 83.00±11.00 82.88±10.38 4.35±5.70 3.56±3.32 *** 3.00±3.19 2.70±2.44 * Elderly (1650) 134.90±19.05 133.28±17.71 * 81.74±10.23 80.96±9.60 * 4.27±4.09 3.70±3.60 * 3.19±3.19 2.73±2.42 * Very old （812） 139.87±20.10 138.04±18.79 * 80.15±10.56 78.89±9.85 * 4.38±5.06 3.73±3.93 * 3.62±3.57 2.89±2.61 * P 0.001 0.001 0.002 0.001 0.082 0.726 0.251 0.103 Normal (1891) 123.85±12.68 122.22±10.98 * 77.02±7.88 76.25±7.21 * 3.88±4.00 3.27±3.04 * 3.03±3.09 2.59±2.41 * HT 1 grade (889) 146.94±10.74 145.66±7.40 * 86.83±8.59 86.15±7.55 * 4.87±5.44 4.16±3.97 * 3.49±3.64 2.91±2.47 * HT 2 grade (237) 166.48±10.17 164.17±8.02 * 93.46±10.37 92.35±9.96 * 5.20±5.38 4.85±5.30 4.09±3.37 3.49±2.86 * HT 3 grade (50) 189.18±12.80 185.46±11.96 * 103.6±13.78 102.76±13.27 6.44±8.55 5.08±5.70 4.24±3.50 3.44±2.30 P ＜0.001 ＜0.001 ＜0.001 ＜0.001 ＜0.001 ＜0.001 ＜0.001 0.004 Comparing with the first * P < 0.05, ** P < 0.01 , ***P < 0.001 . Table 3. the detection rate of abnormal IAD in different subgroups Grouping sIAD N（%） dIAD N（%） The first Average P The first Average P Females (1705) 152（8.9） 83（4.9） ＜0.001 83（4.9） 44（2.6） ＜0.001 Males (1362) 128（9.4） 89（6.5） ＜0.001 49（3.6） 23（1.7） ＜0.001 P 0.644 0.046 / 0.085 0.093 / Middle (605) 55（9.1） 30（5.0） ＜0.001 18（3.0） 10（1.7） ＜0.001 Elderly (1650) 153（9.3） 90（5.5） ＜0.001 65（3.9） 36（2.2） ＜0.001 Very old 72（8.9） 52（6.4） ＜0.001 49（6.0） 21（2.6） ＜0.001 P 0.947 0.466 / 0.011 0.493 / Normal (1634) 133（8.1） 64（3.9） ＜0.001 63（3.9） 37（2.3） ＜0.001 HT 1grade (780) 109（14.0） 76（9.7） ＜0.001 50（6.4） 20（2.6） ＜0.001 HT 2 grade (210) 31（14.8） 26（12.4） ＜0.001 15（7.1） 9（4.3） ＜0.001 HT 3 grade (46) 7（15.2） 6（13.0） ＜0.001 4（8.7） 1（2.2） ＜0.001 P ＜0.001 ＜0.001 / 0.007 0.338 / Additional Declarations There is NO conflict of interest to disclose. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6143519","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":430796079,"identity":"bea5fd32-1793-4d87-9f9e-303e9f435539","order_by":0,"name":"Hai Su","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYJCCw2CSvYGBmUQtPAdI0AJRKZFApBb5GTmGhwtq7uQZ3Hz+8HFhG4M8v9gB/FoMbuQYHJ5x7Fmxwe0cY+OZbQyGM2cnENAiAdTCw3Y4ccPtHDZp3jaGBIPbBLQAHQbU8g+o5ebxZ8RpYQA5jLcNqOUGgxlxWgzOPCs4zNv3rFjyDNAvPOckCPtFvj1582eeb3fy+I4ff/iYp8xGnl+akMMYOAyAxIEEhQNgngQh5SDA/gCsRb6BGMWjYBSMglEwIgEA1RJI0wWm4sEAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-3309-9636","institution":"the Second Affiliated Hospital of Nanchang University","correspondingAuthor":true,"prefix":"","firstName":"Hai","middleName":"","lastName":"Su","suffix":""},{"id":430796080,"identity":"8562e7f1-ad68-4670-86b6-085f4495d6d1","order_by":1,"name":"linglin XIA","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"linglin","middleName":"","lastName":"XIA","suffix":""},{"id":430796081,"identity":"28052802-37af-4199-b75d-eb00983afee3","order_by":2,"name":"Huihui Bao","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Huihui","middleName":"","lastName":"Bao","suffix":""}],"badges":[],"createdAt":"2025-03-03 07:15:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6143519/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6143519/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87483797,"identity":"85687f58-537a-46c1-9b8b-5cc1536d2d83","added_by":"auto","created_at":"2025-07-24 10:37:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":565923,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6143519/v1/75c81582-35d8-45f2-9264-f82d5791531c.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"\u003cp\u003eInter-arm blood pressure difference detected with computer-programmed blood pressure measurement:difference on the first reading and the average value of 2-3 readings\u003c/p\u003e","fulltext":[{"header":"Summary Table","content":"\u003cp\u003eWhat is known about the topic:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eTo evaluate the inter-arm blood pressure (BP) difference (IAD) bilateral-arm blood pressure (BP) method should be used.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe CCBPM is a compute controlled bilateral-arm BP device with 3 rest times before BP measurement and standard BP measurement program.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWhat this study adds:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eThe detection rate of abnormal sIAD based on the first BP reading was higher than that on the average BP reading .\u003c/li\u003e\n \u003cli\u003eEven using CCBPM, for evaluating IAD the average value of 2-3 BP readings should be used. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe hypertension guidelines published by many countries recommend simultaneous bilateral-arm blood pressure (BP) measurement [1-4]. The first purpose is to determine the reference arm and the second is to assess the inter-arm difference (IAD). The reference arm is the one with a higher BP reading, and it should be used for subsequent BP measurements. Many studies have demonstrated that using the reference arm for BP measurement can reduce the misdiagnosis of hypertension compared to using only the right or left arm.\u003c/p\u003e\n\u003cp\u003eThe second purpose of bilateral-arm BP measurement is to evaluate the IAD. Normally, the BP levels between the two arms are basically similar or their difference is less than 10 mm Hg. When using a mercury-column sphygmomanometer, the sequential BP method was commonly used to evaluate IAD, but the results were often overestimated by about three times compared to the synchronous method [5]. A large number of studies have demonstrated the value of IAD in diagnosing peripheral vascular diseases and predicting poor outcomes of cardiovascular diseases\u0026nbsp;[5-8].\u003c/p\u003e\n\u003cp\u003eIn fact, IAD is rarely involved in epidemiological studies. Even when it is involved, the common method currently is to use two electronic BP devices of the same model to measure the BP of both arms. However, this method may have some shortcomings. For example, the rest time of participants may be insufficient, and the interval between two BP measurements may not be 1-2 minutes.\u003c/p\u003e\n\u003cp\u003eAccording to the requirements for a standard BP measurement, at least 8 minutes are needed. But this may be difficult to achieve in clinical practice. Currently, a new type of BP device, a computer-controlled, fully automated bilateral-arm BP measurement instrument (CCBPM, Jiangxi Changgang Medical Technology Co., LTD) with two built-in Omron devices (Omron-U30), has been developed. When using the CCBPM, the operator just needs to place two cuffs on both upper arms; after a 3-minute waiting time, the BP is measured twice with a 1-minute interval; based on the difference between the first two BP readings, the instrument automatically decides whether a third BP measurement is necessary; finally, the average value of 2 or 3 BP readings is reported [9, 10].\u003c/p\u003e\n\u003cp\u003eIt is well-known that evaluating IAD is important, but the measurement methodology has a major influence on the results. It is unclear what influence a single BP measurement has on IAD evaluation [6]. This study aimed to investigate whether there is a difference in the detection rate of abnormal IAD (\u0026ge;10 mm Hg) based on the first BP reading and the average value of 2-3 BP readings when using CCBPM in 3,067 rural residents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Population and Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the ethics committee of the Second Affiliated Hospital of Nanchang University (The IBR EC opinion letter 2024-02) and was in line with the Helsinki principles, causing no harm to the interests of patients. All patients provided their oral informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurvey Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom April to June 2024, 3,067 residents (68.09 \u0026plusmn; 9.34 years old, age range 45-94 years old) were included. Among them, 1705 were women and 1362 were men. Specifically, 605 were in the middle-aged group of 45-59 y, (54.27 \u0026plusmn; 3.5 y, 57.4% women), 1,650 were in the 60-74 age group (67.65 \u0026plusmn; 4.34 y, 56.5% women), and 812 were in the very-old group (\u0026ge;75 years old, 79.27 \u0026plusmn; 3.76 y, 52.3% women).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eAll participants completed BP measurements in the morning fasting state (7 to 11 am) according to the Chinese Hypertension Guideline (2018).\u003c/p\u003e\n\u003cp\u003eThe CCBPM is designed strictly according to the existing BP measurement requirements. There is a 3-minute rest time before BP measurement. After the 3-minute countdown, the instrument automatically starts to measure the BP with an interval of one minute. If the difference between the first two BP levels is greater than 5 mmHg, the CCBPM will automatically measure the third BP. At the end of the BP measurement, the instrument will calculate the average BP value of the two arms and the systolic IAD (sIAD) and diastolic IAD (dIAD) based on the average value of 2-3 BP readings (average). In this study, the IAD of the first BP reading was calculated to compare the difference in the detection rate of abnormal IAD (\u0026ge; 10 mmHg).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStandards for Different Subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(1) Different HT Subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHypertension Classification:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the BP values of the reference arm.\u003c/p\u003e\n\u003cp\u003eNormal: SBP/DBP \u0026lt; 140/90 mm Hg (1891 cases)\u003c/p\u003e\n\u003cp\u003eGrade 1 hypertension: SBP/DBP between 140-159/90-99 mm Hg (889 cases)\u003c/p\u003e\n\u003cp\u003eGrade 2 hypertension: SBP/DBP between 160-179/100-109 mm Hg (237 cases)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Different Age Subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree subgroups were created:\u003c/p\u003e\n\u003cp\u003eMiddle-aged subgroup: 45-59 years old, 605 participants\u003c/p\u003e\n\u003cp\u003eElderly subgroup: 60-74 years old, 1650 participants\u003c/p\u003e\n\u003cp\u003eVery-old subgroup: \u0026gt; 75 years old, 812 participants\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Different Sex Subgroups\u003c/strong\u003e: Two subgroups were created, namely male and female.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Statistical Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were processed and analyzed using Excel 2019 and SPSS 26.0 statistical software. Data with a normal distribution are presented as mean \u0026plusmn; standard deviation, and the paired t-test was used for testing. Data without a normal distribution were described by the median and interquartile range, and the Wilcoxon signed-rank test was used for analysis. Classification data are presented as percentages (%) and were tested with the chi-square test. The criteria for determining statistical significance are as follows: P \u0026lt; 0.05 indicates a statistical difference, P \u0026lt; 0.01 indicates a significant statistical difference, and P \u0026lt; 0.001 indicates an extremely significant statistical difference.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e2.1 BP Values and IAD on the First and Average BP Readings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the reference arm, in the 3067 participants, the systolic blood pressure (SBP) and diastolic blood pressure (DBP) on the first BP reading were significantly higher than those on the average BP readings (134.90\u0026plusmn;19.63/81.57\u0026plusmn;10.52 mm Hg vs 133.29\u0026plusmn;18.31/80.79\u0026plusmn;9.92 mm Hg, P \u0026lt; 0.001). At the same time, the values of systolic inter-arm difference (sIAD) and diastolic inter-arm difference (dIAD) on the first BP reading were also higher than those on the average BP reading.\u003c/p\u003e\n\u003cp\u003eOn the first BP reading, the detection rate of abnormal sIAD was 9.1% and that of abnormal dIAD was 4.3%; these were significantly higher than those of 5.6% and 2.2% on the average value.\u003c/p\u003e\n\u003cp\u003eHowever, there was no significant difference in the pulse rate between the first BP reading and the average BP reading (P = 0.687) (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe SBP and DBP on the first BP reading were higher than those on the average BP reading. This finding was observed among the three age subgroups and hypertension subgroups. Meanwhile, the absolute sIAD and dIAD levels on the first reading were also higher than those on the average reading. Similarly, this finding was also observed in different age and hypertension subgroups (Table 2).\u003c/p\u003e\n\u003cp\u003eTable 2. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe detection rate of abnormal sIAD was higher on the first BP reading than that on the average BP reading in different sex, age, and hypertension grade subgroups. The detection rate of abnormal dIAD on the first BP reading was higher than that on the average BP reading in different age and hypertension grade subgroups, but it was lower on the first reading in some cases.\u003c/p\u003e\n\u003cp\u003eThe detection rate of abnormal sIAD in hypertensive patients increased with the increase in hypertensive degree. However, this trend was not observed on the average BP reading.\u003c/p\u003e\n\u003cp\u003eTable 3. \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the computer-controlled, fully automated bilateral-arm blood pressure (BP) measurement instrument (CCBPM) was used for the first time to evaluate the inter-arm difference (IAD) in a community health examination. The CCBPM used in this study has two built-in validated BP devices (OMRON, 3U). With the help of a computer, the whole BP measurement process is controlled according to the regulations of BP measurement, so the BP values are more accurate.\u003c/p\u003e \u003cp\u003eRegarding the BP of the reference arm, the systolic blood pressure (SBP) and diastolic blood pressure (DBP) on the first BP reading in the 3,067 participants were significantly higher than those on the average BP reading. The detection rate of abnormal systolic inter-arm difference (sIAD) on the average reading was 5.6%, and that of diastolic inter-arm difference (dIAD) was 2.2%, which were lower than the 9.1% and 4.3% on the first BP reading, with a difference of about 40%. Why were the sIAD and dIAD on the average reading lower? The first reason is that the difference between electronic BP devices may be up to 5 mmHg. Using average readings may attenuate this difference. The second reason is that participants who had 2\u0026ndash;3 BP measurements may have had a longer rest time (estimated to be 2\u0026ndash;3 minutes more). It is well-known that for every 10 mmHg increase in SBP, the detection rate of sIAD over 10 mmHg increases by 4% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, the prevalence of sIAD was higher in the group with elevated BP levels [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs the prevalence of IADs is overestimated threefold when sequential measurement is used [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], synchronous bilateral-arm BP measurement is suggested. This study shows that even when using synchronous bilateral-arm BP measurement, a single BP measurement can still lead to an overestimation of abnormal sIAD by 40% and that of dIAD by 50% compared with the average reading. Our findings demonstrate that the BP measurement methodology has a major influence on IAD results. To prevent overestimation and observer bias, IAD should be assessed simultaneously at both arms, and multiple readings should be taken [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEven though approximately 40% of this population may have hypertension based on the BP measurement, the detection rates of abnormal sIAD (5.5%) and dIAD (2.5%) on the average values are lower than the existing values. A meta-analysis showed that the pooled prevalence of abnormal sIAD from four studies was 19.6%, and that for abnormal dIAD was 8.1% [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In 414 hypertensives, the detection rate of sIAD was as high as 18.4% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In a Chinese community survey with 10,657 healthy subjects, 15.0% had an sIAD of 10\u0026ndash;15 mmHg, 8.3% had an sIAD of 15\u0026ndash;20 mmHg, and 7.7% of participants had an sIAD\u0026thinsp;\u0026gt;\u0026thinsp;20 mmHg [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUsing CCBPM not only provides accurate BP readings but also greatly reduces the labor intensity of investigators in large-scale epidemiological investigations. According to our experience, one professional can manage 5 instruments [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e"},{"header":"Limitation","content":"\u003cp\u003eThe studied population was from a rural community in southern China, and the sample size was not very large. It is necessary to further accumulate data in a larger population and in different areas.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eEven when using bilateral-arm BP measurement in participants who had enough rest time before BP measurement, the detection rate of IAD detected by a single BP measurement is significantly higher than that detected by the average value of 2\u0026ndash;3 BP measurements.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eConflict of interest： no\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChinese Guidelines for the Prevention and Treatment of Hypertension (revised in 2024). Chinese Journal of Hypertension (Chinese and English), 2024,32(7): 603\u0026ndash;700.\u003c/li\u003e\n\u003cli\u003eWhelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High blood pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 2017; 71(6):e13\u0026ndash;e115.\u003c/li\u003e\n\u003cli\u003eMcEvoy JW, McCarthy CP, Bruno RM, Brouwers S, Canavan MD, Ceconi C, et al. 2024 ESC Guidelines for the management of elevated blood pressure and hypertension. Eur Heart J. 2024 ;45(38):3912-4018. doi: 10.1093/eurheartj/ehae178. PMID: 39210715. \u003c/li\u003e\n\u003cli\u003eUmemura S, Arima H, Arima S, Asayama K, Dohi Y, Hirooka Y, et al. The Japanese Society of Hypertension Guidelines for the Management of Hypertension (JSH 2019). Hypertens Res. 2019;42(9):1235-1481.\u003c/li\u003e\n\u003cli\u003eClark 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. Epub 2016 Oct 10. PMID: 27789511; PMCID: PMC5072922.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e6 \u003c/strong\u003eVerberk WJ, Kessels AG, Thien T. Blood pressure measurement method and inter-arm differences: a meta-analysis. Am J Hypertens. 2011;24(11):1201-8. doi: 10.1038/ajh.2011.125. Epub 2011 Jul 21. PMID: 21776035. \u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e7 \u003c/strong\u003eClark CE, Campbell JL, Evans PH, Millward A. Prevalence and clinical implications of the inter-arm blood pressure difference: A systematic review. J Hum Hypertens. 2006;20(12):923-31. doi: 10.1038/sj.jhh.1002093. Epub 2006 Oct 12. PMID: 17036043.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e8 \u003c/strong\u003eClark CE, Campbell JL, Evans PH, Millward A. Prevalence and clinical implications of the inter-arm blood pressure difference: A systematic review. J Hum Hypertens. 2006;20(12):923-31. doi: 10.1038/sj.jhh.1002093. Epub 2006 Oct 12. PMID: 17036043. \u003c/li\u003e\n\u003cli\u003eXia Linglin, Su Hai. Computerized-controlled, standardized office blood pressure measurement. Chinese Journal of Hypertension, 2022,30 (9): 886-887. \u003c/li\u003e\n\u003cli\u003eSu Hai, Guo Zixing. The way out for accurate blood pressure measurement: automatic blood pressure measurement with standard and whole process control. Chinese Journal of Hypertension 2024,32 (04): 300-303.\u003c/li\u003e\n\u003cli\u003eClark 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[J]. The British journal of general practice: the Journal of the Royal College of General Practitioners, 2016, 66(652): e838-e847. \u003c/li\u003e\n\u003cli\u003eWatts RA, Hatemi G, Burns JC, Mohammad AJ. Global epidemiology of vasculitis. Nat Rev Rheumatol. 2022 ;18(1):22-3\u003c/li\u003e\n\u003cli\u003eSun H, Li P, Su H, Wang J, Hu W, Li J, et al. The detection rates of inter-arm systolic blood pressure difference vary with blood pressure levels in hypertensive patients under antihypertensive therapy. International Journal of Cardiology. Int J Cardiol. 2014;172 (3):e419-20. \u003cu\u003e \u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eEnglish JA, Carell ES, Guidera SA, Tripp HF. Angiographic prevalence and clinical predictors of left subclavian stenosis in patients undergoing diagnostic cardiac catheterization . Catheterization and cardiovascular interventions. 2001; 54(1):8-11. doi: 10.1002/ccd.1230. PMID: 11553941.\u003c/li\u003e\n\u003cli\u003eYuan Zhao, Xia Linglin, Wang Tao, Bao Huihui, Su Hai. Comparative study of computer-programmed blood pressure measurement with measurement of blood pressure using an artificial right arm on the prevalence of hypertension in the elderly population. Chinese Journal of Cardiovascular Diseases；2025; 53 (1): 37-41.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 \u0026nbsp;Compaction of the BP, IAD parameters on the first and average reading in 3067 participants\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"490\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2342%;\"\u003e\n \u003cp\u003eitem\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.4033%;\"\u003e\n \u003cp\u003eThe first\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.8289%;\"\u003e\n \u003cp\u003eAverage\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5336%;\"\u003e\n \u003cp\u003eP\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2342%;\"\u003e\n \u003cp\u003eSBP（mmHg）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.4033%;\"\u003e\n \u003cp\u003e134.90\u0026plusmn;19.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.8289%;\"\u003e\n \u003cp\u003e133.29\u0026plusmn;18.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5336%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2342%;\"\u003e\n \u003cp\u003eDBP（mmHg）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.4033%;\"\u003e\n \u003cp\u003e81.57\u0026plusmn;10.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.8289%;\"\u003e\n \u003cp\u003e80.79\u0026plusmn;9.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5336%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2342%;\"\u003e\n \u003cp\u003ePulse rate （beats/min）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.4033%;\"\u003e\n \u003cp\u003e73.26\u0026plusmn;11.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.8289%;\"\u003e\n \u003cp\u003e73.24\u0026plusmn;10.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5336%;\"\u003e\n \u003cp\u003e0.687\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2342%;\"\u003e\n \u003cp\u003esIAD（mmHg）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.4033%;\"\u003e\n \u003cp\u003e4.31\u0026plusmn;4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.8289%;\"\u003e\n \u003cp\u003e3.68\u0026plusmn;3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5336%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2342%;\"\u003e\n \u003cp\u003edIAD（mmHg）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.4033%;\"\u003e\n \u003cp\u003e3.27\u0026plusmn;3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.8289%;\"\u003e\n \u003cp\u003e2.77\u0026plusmn;2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5336%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2342%;\"\u003e\n \u003cp\u003esIAD\u0026ge;10 mm Hg \u0026nbsp; \u0026nbsp; n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.4033%;\"\u003e\n \u003cp\u003e280（9.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.8289%;\"\u003e\n \u003cp\u003e172（5.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5336%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2342%;\"\u003e\n \u003cp\u003edIAD\u0026ge;10 mm Hg \u0026nbsp; \u0026nbsp; n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.4033%;\"\u003e\n \u003cp\u003e132（4.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.8289%;\"\u003e\n \u003cp\u003e67（2.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5336%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 2 \u0026nbsp; the BP levels and IAD in different subgroups \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"680\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 178px;\"\u003e\n \u003cp\u003eSBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 159px;\"\u003e\n \u003cp\u003eDBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 142px;\"\u003e\n \u003cp\u003esIAD value \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 142px;\"\u003e\n \u003cp\u003edIAD value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eThe first\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eAverage\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eThe first\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eAverage\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eThe first\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eAverage\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eThe first\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eAverage\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eFemales (1705)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e135.29\u0026plusmn;20.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e133.62\u0026plusmn;19.29\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e80.98\u0026plusmn;10.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e80.08\u0026plusmn;9.95\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.26\u0026plusmn;4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.56\u0026plusmn;3.69\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.37\u0026plusmn;3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.80\u0026plusmn;2.52\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eMales (1362)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e134.42\u0026plusmn;18.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e132.88\u0026plusmn;17.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e82.30\u0026plusmn;10.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e81.69\u0026plusmn;9.81\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.37\u0026plusmn;4.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.84\u0026plusmn;3.57\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.14\u0026plusmn;2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.72\u0026plusmn;2.42\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eMiddle (605)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e128.24\u0026plusmn;18.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e126.94\u0026plusmn;17.38\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e83.00\u0026plusmn;11.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e82.88\u0026plusmn;10.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.35\u0026plusmn;5.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.56\u0026plusmn;3.32\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.00\u0026plusmn;3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.70\u0026plusmn;2.44\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eElderly (1650)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e134.90\u0026plusmn;19.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e133.28\u0026plusmn;17.71\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e81.74\u0026plusmn;10.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e80.96\u0026plusmn;9.60\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.27\u0026plusmn;4.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.70\u0026plusmn;3.60\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.19\u0026plusmn;3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.73\u0026plusmn;2.42\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eVery old\u003c/p\u003e\n \u003cp\u003e（812）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e139.87\u0026plusmn;20.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e138.04\u0026plusmn;18.79\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e80.15\u0026plusmn;10.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e78.89\u0026plusmn;9.85\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.38\u0026plusmn;5.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.73\u0026plusmn;3.93\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.62\u0026plusmn;3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.89\u0026plusmn;2.61\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eNormal (1891)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e123.85\u0026plusmn;12.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e122.22\u0026plusmn;10.98\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e77.02\u0026plusmn;7.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e76.25\u0026plusmn;7.21\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.88\u0026plusmn;4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.27\u0026plusmn;3.04\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.03\u0026plusmn;3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.59\u0026plusmn;2.41\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eHT 1 grade (889)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e146.94\u0026plusmn;10.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e145.66\u0026plusmn;7.40\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e86.83\u0026plusmn;8.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e86.15\u0026plusmn;7.55\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.87\u0026plusmn;5.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.16\u0026plusmn;3.97\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.49\u0026plusmn;3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.91\u0026plusmn;2.47\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eHT 2 grade \u0026nbsp;(237)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e166.48\u0026plusmn;10.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e164.17\u0026plusmn;8.02\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e93.46\u0026plusmn;10.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e92.35\u0026plusmn;9.96\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e5.20\u0026plusmn;5.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.85\u0026plusmn;5.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.09\u0026plusmn;3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.49\u0026plusmn;2.86\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eHT 3 grade (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e189.18\u0026plusmn;12.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e185.46\u0026plusmn;11.96\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e103.6\u0026plusmn;13.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e102.76\u0026plusmn;13.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e6.44\u0026plusmn;8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e5.08\u0026plusmn;5.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.24\u0026plusmn;3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.44\u0026plusmn;2.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eComparing with the first * P \u0026lt; 0.05, ** P \u0026lt; 0.01 , \u0026nbsp;***P \u0026lt; 0.001 .\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 3. \u0026nbsp;the detection rate of abnormal IAD in different subgroups\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"608\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrouping\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 178px;\"\u003e\n \u003cp\u003esIAD \u0026nbsp; \u0026nbsp;N（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 179px;\"\u003e\n \u003cp\u003edIAD \u0026nbsp; N（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eThe first\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eThe first\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFemales (1705)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e152（8.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e83（4.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e83（4.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e44（2.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eMales (1362)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e128（9.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e89（6.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e49（3.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e23（1.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eMiddle (605)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e55（9.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e30（5.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e18（3.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e10（1.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eElderly (1650)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e153（9.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e90（5.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e65（3.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e36（2.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eVery old \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e72（8.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e52（6.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e49（6.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e21（2.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eNormal (1634)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e133（8.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e64（3.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e63（3.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e37（2.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eHT 1grade (780)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e109（14.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e76（9.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e50（6.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e20（2.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eHT 2 grade (210)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e31（14.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e26（12.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e15（7.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e9（4.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eHT 3 grade (46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e7（15.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e6（13.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e4（8.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1（2.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"old age, BP, prevalence, hypertension, bilateral","lastPublishedDoi":"10.21203/rs.3.rs-6143519/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6143519/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To compare the inter-arm blood pressure (BP) difference (IAD) detected from the first BP reading with that detected from the average value of 2-3 BP readings when using computer program-controlled BP measurement (CCBPM).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The CCBPM was used for BP measurement during a health examination of 3，067 rural community residents. The IAD was evaluated based on the first BP reading and the average value of 2-3 BP readings, respectively. A systolic- and diastolic-IAD (sIAD or dIAD) ≥10 mm Hg was considered abnormal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In the reference arm, the SBP/DBP was 136.42±19.81/81.23 ± 10.51 mm Hg in the first BP reading; while in the average reading, they were significantly lower (134.64±18.39/80.28±9.78 mm Hg, both P = 0.011). The detection rate of abnormal sIAD was 9.08% and that of abnormal dIAD was 4.74% in the first BP reading, while in the average reading, the sIAD was 5.47% and the dIAD was 2.47%. There was a difference of about 40% for sIAD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Even when using CCBPM, the detection rate of IAD in the first BP reading was significantly higher than that in the average value of 2-3 BP readings.\u003c/p\u003e","manuscriptTitle":"Inter-arm blood pressure difference detected with computer-programmed blood pressure measurement:difference on the first reading and the average value of 2-3 readings","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-21 11:51:40","doi":"10.21203/rs.3.rs-6143519/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"95e64f65-76bc-47a0-957f-83c1ca5888e8","owner":[],"postedDate":"March 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":46012277,"name":"Health sciences/Health care/Disease prevention"},{"id":46012278,"name":"Biological sciences/Physiology/Circulation"}],"tags":[],"updatedAt":"2025-07-24T10:21:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-21 11:51:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6143519","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6143519","identity":"rs-6143519","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}