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Article

Comparison of Oscillometric Blood Pressure Measurements on the Arm and Forearm in Patients with Obesity, Prediabetes, and Hypertension

by
Tatiana Palotta Minari
1,2,*,
Luciana Pellegrini Pisani
2,
Tatiane de Azevedo Rubio
3,
Louise Buonalumi Tácito Yugar
3,
Luis Gustavo Sedenho-Prado
3,
Luciana Neves Cosenso-Martin
1,
Lúcia Helena Bonalume Tácito
1,
Heitor Moreno
3,
José Fernando Vilela-Martin
1 and
Juan Carlos Yugar-Toledo
1
1
Hypertension Clinic, Department of Internal Medicine, State Medical School of São José do Rio Preto (FAMERP), São José do Rio Preto 15090-000, SP, Brazil
2
Department of Bioscience, Federal University of São Paulo (UNIFESP), Santos 11015-020, SP, Brazil
3
Faculty of Medical Sciences, State University of Campinas (UNICAMP), Campinas 13083-876, SP, Brazil
*
Author to whom correspondence should be addressed.
Diabetology 2025, 6(9), 94; https://doi.org/10.3390/diabetology6090094
Submission received: 5 August 2025 / Revised: 26 August 2025 / Accepted: 29 August 2025 / Published: 3 September 2025
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Abstract

Background: The global surge in obesity has reignited the need for larger cuff sizes to avoid inaccurate blood pressure (BP) readings and inappropriate antihypertensive treatment. More precise methods are essential. Forearm BP measurement has emerged as a promising alternative, showing strong correlation with noninvasive beat-to-beat monitoring. This study aimed to validate the digital oscillometric method on the forearm, comparing results to brachial artery readings in hypertensive patients with prediabetes and obesity. Methods: A non-randomized, open, cross-sectional observational study was conducted with 72 hypertensive individuals presenting with obesity and prediabetes. BP was measured using oscillometric devices on both the arm and forearm, following standardized protocols. Data were analyzed using Pearson correlation and Bland–Altman agreement tests. Results: Arm and forearm BP readings showed high agreement: r = 0.86 for systolic BP (SBP), r = 0.93 for diastolic BP (DBP), and r = 0.90 for mean arterial pressure (MAP). Bland–Altman analysis confirmed equivalence (SBP: p = 0.8, DBP: p = 0.3, MAP: p = 0.2). Conclusions: Forearm BP measurement is a reliable and effective alternative, particularly for hypertensive patients with prediabetes and obesity. It offers accurate readings, reduces treatment risks, and supports better clinical decisions. Broader studies are needed for generalization.

1. Introduction

The advent of devices utilizing oscillometric techniques has revolutionized blood pressure (BP) measurements, enabling the accurate determination of mean arterial pressure (MAP), systolic blood pressure (SBP), and diastolic blood pressure (DBP) [1,2]. These devices measure the arterial pulsations transmitted to an air-inflated brachial cuff, which are detected by transducers and processed by microprocessors using algorithms to minimize interference and ensure accuracy [3,4].
Oscillometric devices measure the amplitude of pressure oscillations during gradual cuff deflation over a period of 30–40 s. This process begins with the cessation of systolic blood pressure (collapse of the brachial artery) and continues as the pressure decreases. As the cuff deflates, blood flows through the reopening brachial artery, causing arterial wall oscillations that increase until the counterpressure exerted by the cuff permits minimal arterial wall tension and maximal arterial volume change. The cuff pressure at the point of maximum oscillation represents mean arterial pressure (MAP), whereas systolic blood pressure (SBP) and diastolic blood pressure (DBP) are derived using proprietary algorithms developed by device manufacturers. While older oscillometric methods relied on fixed ratios to determine SBP and DBP, modern devices employ more advanced computational techniques that incorporate individual physiological characteristics to improve measurement accuracy [5]. Technological advancements have led to the development of 24 h ambulatory and home monitors, prompting discussions about the accuracy of traditional Riva-Rocci blood pressure measurement methods [6,7,8]. Despite these considerations, the Riva-Rocci method remains a cornerstone of medical practice and continues to be widely used in both clinical and emergency settings [2,6,7,8,9].
Recently, significant advancements have been made in the diagnosis, treatment, and understanding of the epidemiology and pathophysiology of hypertension [10,11]. However, achieving optimal treatment outcomes requires accurate blood pressure (BP) measurement, as errors can arise due to patient-specific characteristics, improper cuff sizing (e.g., in individuals with obesity), or external factors that may lead to inaccurate BP readings [12,13,14]. Precise BP measurement is essential for both the diagnosis and monitoring of hypertensive patients. Nonetheless, anatomical variations, such as differences in arm musculature or obesity, can affect measurement accuracy in certain individuals [4,6,14,15,16,17].
Given these challenges, several studies have evaluated the comparability of blood pressure (BP) measurements obtained from alternative sites, such as the forearm and wrist, in relation to traditional arm measurements [7,17,18,19]. Tachovsky (1985) was among the first researchers to investigate forearm BP measurements, reporting significant differences between values recorded at the arm and forearm [18]. Subsequent studies conducted in 1996 and 1997 compared automatic wrist cuffs (Cardio Analysis Systems) with standard sphygmomanometers, concluding that wrist measurements were generally reliable but cautioning against their use in hypertensive patients due to variability [10,19,20,21,22,23,24].
Studies have observed substantial differences between wrist and arm BP readings in hospitalized patients, underscoring the importance of specifying the measurement site in clinical assessments [21,25]. Similarly, in 2004, Palatini identified a consistent difference in BP values obtained from wrist measurements compared with arm readings, suggesting that physiological factors such as pulse amplification may contribute to these variations, rather than simple measurement error [18,21]. Additional research has highlighted anatomical factors as contributors to the differences observed between BP measurement sites [21,22,23,24,25,26,27,28,29]. Notably, studies have revealed that forearm measurements overestimate DBP, although these discrepancies diminish when cuff sizes are appropriately adjusted to fit the patient’s anatomy [10,30]. Accurate BP measurement relies on careful patient preparation, standardized techniques, and thorough interpretation of results [7,12,31,32,33,34].
Obesity and arm deformities introduce additional complexities, often resulting in measurement errors that compromise the diagnosis and follow-up of patients [35]. Developing and validating alternative measurement techniques in such cases can enhance accuracy and improve patient care for this population, fostering greater inclusivity and equity, particularly within the realm of public health [19]. In addition, the global increase in obesity prevalence has reignited discussions on using larger-than-standard cuffs to minimize inaccuracies and reduce inappropriate antihypertensive treatments and their associated side effects [7,8,19,36]. As an alternative, forearm BP measurement has demonstrated a promising correlation with non-invasive beat-to-beat monitoring systems, offering a viable option for patients with anatomical constraints [35,37,38,39,40,41].
Considering the positive aspects, controversies, and gaps in the literature, some questions remain unaddressed. Are BP measurements obtained on the arm equivalent to those obtained on the forearm? To address these questions, this study aimed to measure and compare BP values from the arm (brachial artery) and forearm using the oscillometric method, focusing on hypertensive patients with obesity and prediabetes. The ultimate goal is to validate forearm measurements as a precise and reliable alternative for use in clinical settings.

2. Materials and Methods

2.1. Institutional Review Board Statement

This study was conducted in strict accordance with the principles of the Declaration of Helsinki. It received approval from the Institutional Ethics Committee of the State Faculty of Medicine in São José do Rio Preto (FAMERP), specifically the Human Research Ethics Committee (CAAE: 16076719.2.0000.5415). This study was approved on 18 June 2016.

2.2. Informed Consent Statement

All participants provided written informed consent, ensuring that they fully understood the objectives, procedures, potential risks, and benefits of the study before agreeing to participate. Strict measures were implemented to safeguard confidentiality and anonymity, including the secure storage of data and the use of anonymized identifiers to prevent the disclosure of personal information. These protocols were rigorously adhered to throughout the research process, maintaining the ethical integrity of the study and protecting the identities of all individuals involved.

2.3. Study Design and Participants

This was a non-randomized, open, cross-sectional observational study that employed a quantitative approach. This study was conducted at the Resistant Hypertension Clinic of the Faculty of Medicine of São José do Rio Preto (FAMERP).
The research included men and women aged 30–85 years who were diagnosed with hypertension (SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg) and obesity (body mass index [BMI] > 30 kg/m2). Participants who had fasting blood glucose levels between 100 and 125 mg/dL or HbA1c values between 5.7% and 6.4%, consistent with prediabetes, were also eligible for inclusion. All participants were under regular antihypertensive treatment, with stable medication regimens maintained for at least 3 months before BP measurements. No recent changes in dosage or drug class were reported, as confirmed through clinical interviews and medical record review. These criteria ensured the inclusion of individuals who best represented the population affected by both conditions, allowing for focused investigation of their combined effects on cardiovascular outcomes.
Patients with one or both upper limbs missing were excluded because the absence of an arm would prevent standard BP measurement procedures. Additionally, individuals who did not meet the obesity and prediabetes criteria, those without a diagnosis of hypertension, those with insulin-dependent diabetes, or those diagnosed with chronic kidney disease (CKD) with an estimated glomerular filtration rate (eGFR) below 60 mL/min/1.73 m2 were excluded. Patients with cardiac arrhythmias, atrial fibrillation, or post-catheterization sequelae were excluded. Although peripheral artery disease (PAD) was not explicitly listed as an exclusion criterion, patients with clinical signs of advanced vascular disease—including those with post-catheterization sequelae, insulin-dependent diabetes, or chronic kidney disease—were excluded. These conditions often overlap with PAD, and patients with suspected peripheral vascular compromise were not included in the study. Finally, patients who declined to sign the Informed Consent Form or who expressed unwillingness to participate in the study were excluded.

2.4. Blood Pressure Measurement Process

Blood pressure (BP) was measured in accordance with the Brazilian Guidelines for the Treatment of Hypertension [34], using the oscillometric method with two digital devices (Microlife, Clearwater, FL, USA, model BP3AC1-1 PC), which feature automatic inflation and deflation and a pressure range of 0–280 mmHg. Each participant underwent three consecutive readings, with two-minute intervals between measurements to ensure consistency and reduce variability.
Cuff selection was based on direct measurement of mid-arm circumference, following international guidelines [10,11,14,33,34]. Standard anatomical landmarks were used: 10 cm above the olecranon for the upper arm and 5 cm below the cubital fossa for the forearm. All cuffs were cylindrical in shape and selected to ensure proper fit, with the bladder width covering approximately 40% of the limb circumference and the bladder length encompassing at least 80%. The available cuff sizes included medium (22–32 cm; 12 × 23 cm) and large (33–42 cm; 15 × 33 cm). No participants required small cuffs (17–22 cm), as none had arm circumferences within that range.
To identify any significant inter-arm differences, BP was initially measured on both arms. If a discrepancy greater than 10 mmHg in systolic or diastolic pressure was observed, the arm with the higher readings was selected for comparison with forearm measurements, in line with established guidelines [7,19,31,33,34]. The corresponding forearm was then used to maintain consistency. All measurements were performed sequentially—not simultaneously—due to equipment limitations and the need for standardized cuff placement. A two-minute interval was maintained between transitions to minimize physiological fluctuations.
Participants were placed in a controlled environment to reduce external influences. Before measurements began, they rested for five minutes, seated with legs parallel, backs supported by a chair, and arms resting on a table at mid-sternum level, corresponding to heart level, with palms facing upward [31,33,34]. During transitions between arm and forearm measurements, participants were instructed to remain relaxed, avoiding speech or movement [32]. BP readings were carefully recorded and tabulated by trained evaluators for subsequent analysis.

2.5. Anthropometric Data

Weight and height were measured using the Welmy W200 Scale® (São Paulo, SP, Brazil), and body mass index (BMI) was calculated using the standard formula: weight (kg) divided by height squared (m2). BMI classification was defined as follows: eutrophic (22–24.9 kg/m2), overweight (25.0–29.9 kg/m2), and obesity, which was further categorized into three grades: grade I obesity (30.0–34.9 kg/m2), grade II obesity (35.0–39.9 kg/m2), and grade III obesity (≥40.0 kg/m2) [31].

2.6. Laboratory Analysis

Blood samples were obtained by venipuncture from the antecubital vein using sterile vacuum collection tubes. All participants underwent an overnight fast of at least 8 h before sample collection. Fasting plasma glucose levels were determined using an enzymatic colorimetric assay, while glycated hemoglobin (HbA1c) was measured using high-performance liquid chromatography (HPLC), a standardized and widely accepted method for HbA1c quantification. All laboratory analyses were conducted in a certified facility, following strict quality control protocols [31].

2.7. Medications

The most commonly prescribed drug classes included angiotensin II receptor blockers (ARBs), angiotensin-converting enzyme (ACE) inhibitors, calcium channel blockers, and thiazide diuretics. The selection of these agents followed clinical guidelines for patients with obesity, prioritizing medications with neutral or favorable metabolic profiles and minimal impact on insulin resistance, glycemic control, and body weight [31,32,33]. Treatment stability was confirmed through clinical interviews conducted by qualified professionals and a thorough review of medical records, ensuring consistency in blood pressure data throughout the study. All individuals were under regular antihypertensive treatment, with stable pharmacological regimens maintained for at least three months before the initiation of data collection. No changes in medication dosage or drug class were made during the study period.

2.8. Sample Size

The sample size calculation was conducted using MedCalc Statistical Software version 19.2.6® (MedCalc Software bv, Ostend, Belgium; https://www.medcalc.org; 2020, accessed on 14 January 2024). The calculation accounted for a Type I error (alpha) of 0.05, indicating a 5% chance of rejecting the null hypothesis when it was true, and a Type II error (beta) of 0.20, indicating an 80% statistical power to detect a true effect or difference. An effect size of 10% was used to estimate the required sample size, resulting in the determination that a minimum of 72 patients was necessary to ensure the validity and reliability of the study. Additionally, the calculation incorporated insights from the sample sizes reported in previous studies using similar protocols and sampling methods [42,43,44]. This integration of prior research results helped refine the estimation, ensuring that the sample size was adequate for capturing clinically meaningful differences and reducing the risk of underpowered analyses.

2.9. Statistical Analysis

Quantitative variables are described as mean ± standard deviation in the presence of a normal distribution or as median ± interquartile range for non-Gaussian distributions. Normality of data distribution was assessed using the Shapiro–Wilk test. For comparisons between independent subgroups (sex, obesity grade, cuff size, and inter-arm difference), Student’s t-test or one-way ANOVA was used for normally distributed variables, while the Mann–Whitney U test or Kruskal–Wallis test was applied for non-parametric data.
To evaluate the relationship and agreement between BP measurements obtained from the arm and forearm, both continuous and categorical statistical methods were applied. Pearson’s correlation coefficient was used to assess the linear association between paired systolic and diastolic BP values. Correlation strength was interpreted as strong (r ≥ 0.70), moderate (0.40 ≤ r < 0.70), or weak (r < 0.40), with statistical significance defined as p < 0.05.
Bland–Altman analysis was conducted to assess the level of agreement between the two measurement sites and to identify any systematic bias. Limits of agreement were calculated as the mean difference ± 1.96 standard deviations, providing insight into the clinical interchangeability of arm and forearm readings.
For categorical analysis, patients were classified as hypertensive or non-hypertensive using the 140/90 mmHg threshold. Cross-tabulation and Cohen’s kappa coefficient were used to evaluate diagnostic agreement between sites. Kappa values were interpreted according to the Landis and Koch scale, with κ ≥ 0.60 considered substantial agreement.
The level of statistical significance was p < 0.05 and α < 0.05. All statistical analysis was performed with MedCalc Statistical Software version 19.2.6 ® (MedCalc Software bv, Ostend, Belgium; https://www.medcalc.org; 2020).

2.10. Clinical Error Thresholds

To enhance the clinical relevance of the agreement analysis, predefined thresholds for acceptable error margins were established before data analysis. Based on recommendations from previous validation studies and clinical guidelines, differences of ±5 mmHg, ±10 mmHg, and ±15 mmHg between arm and forearm measurements were considered acceptable for systolic and diastolic blood pressure. These thresholds were used to calculate the proportion of paired measurements falling within each range, allowing for a more practical assessment of the interchangeability between measurement sites [31,33].

2.11. Data Availability Statement

Data were collected and managed using REDCap 14.0.9 ® electronic data capture tools hosted by REDCap—FUNFARME/FAMERP (State Faculty of Medicine, São José do Rio Preto, https://redcap.hospitaldebase.com.br/, accessed on 14 January 2024). These data are available upon request from the corresponding author but are not publicly accessible due to privacy considerations.

3. Results

The protocols for preparing patients for BP measurements, anthropometric data, clinical characteristics, and participant classification by sex, obesity grade, cuff size, or inter-arm difference (IAD) of the 72 patients are presented in Table 1, Table 2 and Table 3, respectively.
Statistical analysis of the measured BP values showed that the values were similar, as the Pearson analysis demonstrated an excellent correlation between arm and forearm BP measurements for SBP, DBP, MAP, PP, and HR (Figure 1) and Bland–Altman agreement tests (Figure 2).
In addition to correlation and agreement analyses, the proportion of paired measurements falling within predefined clinical error margins was evaluated. For systolic BP, 18% of pairs were within ±5 mmHg, with 52% within ±10 mmHg and 78% within ±15 mmHg. For diastolic BP, 25% of pairs were within ±5 mmHg, with 61% within ±10 mmHg and 85% within ±15 mmHg. These results suggest that although the average bias was minimal, the wide limits of agreement observed in Bland–Altman plots may have clinical implications, particularly in borderline cases of hypertension diagnosis or treatment adjustment. Screening for IAD revealed that 26.4% of participants (n = 19) presented a systolic IAD ≥ 10 mmHg, while 16.7% (n = 12) exhibited a diastolic IAD ≥ 10 mmHg. In accordance with current guidelines, the arm with the higher BP reading was selected for comparison with the forearm.
To assess the clinical agreement between arm and forearm BP measurements, patients were classified as hypertensive or non-hypertensive using the 140/90 mmHg threshold. Cross-tabulation showed that 65 out of 72 patients (90.3%) were consistently classified across both sites. Cohen’s kappa coefficient was κ = 0.66, indicating substantial agreement. Reclassification occurred in seven patients (9.7%), with four cases of underdiagnosis (arm ≥ 140/90 mmHg, forearm < 140/90 mmHg) and three cases of overdiagnosis (arm < 140/90 mmHg, forearm ≥ 140/90 mmHg). These findings provide a clear quantification of misclassification risk when using forearm measurements and support the use of categorical agreement metrics in clinical validation studies.

4. Discussion

The population sample of this study demonstrated a predominance of females, with a BMI compatible with class I obesity and prediabetes. In this study, the BP values recorded in the arm and forearm showed an excellent correlation. The Pearson’s correlation coefficients were 0.86 for SBP, 0.93 for DBP, and 0.90 for MAP. All of them are also presented (p < 0.0001), which suggests that this correlation was highly statistically significant. These indices are higher than those reported in previous studies [41,42]. This finding may be because the study population is known to have an established vascular disease (hypertension) [1,2,3,4,5,33].
The Bland–Altman analyses for SBP, DBP, and MAP demonstrated no bias between the respective measurement methods, as confirmed by the 95% confidence intervals and statistical results (p > 0.05). These limits of agreement fall within clinically acceptable thresholds for noninvasive BP monitoring, indicating that forearm measurements are unlikely to result in misclassification of hypertension or inappropriate treatment decisions. This reinforces the forearm as a viable alternative site for BP assessment, particularly in patients with obesity and prediabetes or anatomical constraints. These findings are consistent with reports in the literature that emphasize that when methods are applied appropriately, no systematic differences are observed [42,43,44]. The limits of agreement, while showing some variability across individual measurements, remained consistent within acceptable ranges and were comparable to those reported in prior studies validating BP measurement techniques in patients with hypertension, prediabetes, and obesity [33]. For instance, the SBP limits of −31.335 to 32.068, DBP limits of −23.02 to 26.33, and MAP limits of −15.94 to 18.45 reflect variability that does not detract from the overall agreement between the methods [41,42,43,44]. The results of this alternative BP measurement method are particularly valuable for patients with obesity or arm deformities, for example. Within the public health context, this approach fosters inclusivity and ensures adequate monitoring of all patients, thereby addressing their unique conditions and healthcare needs [1,2,3,4].
Beyond statistical agreement, clinical classification consistency plays a pivotal role in guiding therapeutic decisions. Using the 140/90 mmHg threshold, our analysis demonstrated substantial categorical agreement between arm and forearm measurements (Cohen’s κ = 0.66). Although 90.3% of patients were consistently classified, 9.7% experienced reclassification, comprising four cases of underdiagnosis and three of overdiagnosis. While these discrepancies were limited in number, they underscore the need for contextual interpretation when relying on forearm BP readings, particularly in borderline cases where small deviations may alter clinical management. The inclusion of categorical agreement metrics enhances the clinical relevance of our findings and reinforces the importance of site-specific considerations in hypertension assessment.
Although Bland–Altman analyses revealed minimal mean bias between arm and forearm measurements, the limits of agreement were notably wide (e.g., –31 to +32 mmHg for SBP and –23 to +26 mmHg for DBP). These intervals, while statistically acceptable, may fall short of clinical precision requirements in certain scenarios [31,32,33]. To address this, we incorporated predefined clinical error thresholds (±5, ±10, ±15 mmHg) to evaluate the practical interchangeability of measurements. The proportion of readings within these margins indicated that forearm measurements are generally reliable; however, they may not be appropriate for all patients—especially when minor differences could influence diagnosis or treatment decisions. These findings reinforce the need for cautious interpretation and highlight the importance of individualized assessment when considering alternative measurement sites.
New research examines the differences between the two measurement sites, the arm and forearm, and correlation indices of 0.75 for SBP and 0.72 for DPB were obtained [34]. This allowed us to conclude that forearm measurement is a good indicator for most patients and should be used when arm measurement is not possible [33]. Similar indices were observed in another study [42]. However, measurements recorded resulted in significantly lower values in the arms, leading the authors to advise against forearm measurements because they could increase the prevalence of hypertension in patients with obesity and prediabetes [41,43,44]. The American Heart Association’s BP measurement committee considers forearm measurements possible but notes that they are not widely used because of the potential for obtaining falsely elevated diastolic values [11].
BP measurement on the forearm is considered a valid alternative for most patients, especially when arm measurements are not possible [30,31]. The adoption of standardized measurement methods and the use of appropriate cuff sizes are essential for ensuring measurement accuracy [30,31,32,33]. These results have significant clinical implications and underscore the need for further research to validate forearm measurements in different populations [40]. It is important to remember that appropriate cuff sizes were used according to the circumferences of the arm and forearm [31]. In recent studies, differences in DBP were observed, which were attributed to the profile of the patients [42,43,44]. Accurate BP measurement is crucial for effective hypertension treatment. However, a caveat regarding the cited studies is the lack of cuffs covering 40% of the arm or forearm circumference [14,30].
Several researchers have attempted to validate forearm measurements using the auscultatory method and conventional cuffs (13 × 23 cm) at both sites, which might have introduced significant methodological bias [20,30,37]. In cases where Korotkoff sounds are inaudible in some individuals, the oscillometric method allows better BP measurement [23,27,28]. For patients with post-catheterization sequelae or obstructive lesions in the upper limbs, using the brachial artery for BP measurement is impractical. The radial artery is easily accessible, but studies have identified a lack of preparation and confidence in conducting measurements at alternative sites [17], leading to increased time consumption and compromised evaluator competence [34,40,41,42,43,44].
It is important to recognize that this study presents just one potential approach to forearm BP measurement within office-based blood pressure monitoring (OBPM). Cuff-based ambulatory blood pressure monitoring (ABPM), which is considered the gold standard for out-of-office measurements [33], was not utilized in this study and, therefore, could not be evaluated for comparison. Additionally, the hydrostatic pressure difference between cuff placement and heart level is a significant source of potential measurement errors in the forearm BP. If the forearm is positioned below or above the heart level during measurement, this could result in over- or underestimation of BP values, respectively. This variable must be carefully controlled in both clinical practice and research settings to ensure the accuracy of forearm measurements [31].
The oscillometric method used in this study is considered reliable. However, prior research has noted potential inaccuracies in forearm BP measurements, especially in individuals with obesity and prediabetes, where diastolic values may be falsely elevated [42,43,44]. Simultaneous measurements on the arm and forearm were not feasible due to methodological and logistical constraints, including the need for specialized equipment, precise calibration, and synchronized positioning—requirements beyond the scope of this study. A sequential protocol was therefore adopted, enabling careful cuff placement and adherence to standardized procedures. While this approach ensured consistency, it may have introduced temporal variability from physiological changes between readings. Despite efforts to reduce such effects through rest intervals and standardized positioning, the absence of simultaneous measurements remains a limitation. Additionally, the study did not include a reference standard such as ambulatory or invasive monitoring. Sequential readings are vulnerable to short-term fluctuations and hydrostatic pressure differences caused by arm height variation, which may affect comparability between sites. Future research should consider randomizing measurement order, performing near-simultaneous paired readings, and incorporating validated reference methods to enhance the reliability and clinical relevance of forearm BP assessment [31,33].
While forearm BP measurement has been validated as an alternative when arm measurement is not feasible, challenges such as cardiac arrhythmias, atrial fibrillation, or post-catheterization sequelae in the upper limbs could compromise its accuracy and warrant further investigation [33]. Patients with these conditions were excluded from this study. However, it is important to consider these challenges in other scenarios as well. Moreover, as highlighted in previous studies, the reduced expertise and confidence of evaluators conducting measurements at alternative sites may also impact the broader applicability of the results in real-world clinical settings [33,42,43,44].
The sample size calculation for this study incorporated insights from previous studies that used similar protocols and sampling methods [42,43,44]. However, it is important to note that the sample was relatively small. This restricts the generalizability of the findings to broader populations and reduces their ability to explore potential variations in BP measurements across specific patient subgroups. Future studies should aim to recruit larger and more heterogeneous cohorts, enabling stratified analyses that can better elucidate the reliability and clinical applicability of forearm BP measurements across diverse patient profiles.
Additionally, the presence of established hypertension and increased arterial stiffness in elderly individuals (>60 years) within the sample could have contributed to the high correlation coefficients between arm and forearm measurements. While the Pearson correlation and Bland–Altman results were excellent and exceeded those reported in previous studies, these findings should not be extrapolated to younger or metabolically healthier populations without further validation.
Building upon the findings and limitations of this study, future research should focus on expanding the sample size to include a more diverse population, encompassing varying demographics, such as age, sex, BMI classifications, and comorbidities. This would enable subgroup analyses and provide deeper insights into the accuracy and reliability of forearm BP measurements across different patient profiles. Additionally, studies comparing forearm and arm measurements in populations with specific vascular conditions, such as advanced arterial stiffness or obesity-related hypertension and prediabetes, could help refine protocols for alternative BP measurement sites.
Standardization of measurement techniques, emphasizing patient positioning during assessments, and validation of equipment are crucial areas for future research [31,33]. Efforts should be directed toward developing consistent methodologies for forearm measurements, including the use of optimized cuff sizes and ensuring proper training for evaluators. Although effective, the oscillometric method requires further investigation to address its potential limitations, particularly in patients with arrhythmias or atypical cardiovascular conditions. Future research could also explore simultaneous measurement techniques to reduce temporal discrepancies and enhance the precision of comparative analyses between arm and forearm blood pressure readings.
Building upon the findings of this study, future research should focus on improving the assessment of BP measurement accuracy on the forearm, particularly in patients with diverse anatomical and clinical profiles. Additionally, validation studies examining the effectiveness of truncoconical cuffs could enhance the adaptability and precision of BP measurements on the forearm. Another promising approach involves developing automated devices capable of simultaneous BP measurements at different anatomical sites, reducing potential biases associated with sequential readings. Implementing these advancements could significantly contribute to the standardization of BP measurement techniques, ensuring greater reliability and clinical applicability of forearm BP measurements.
Finally, long-term studies examining the clinical implications of forearm BP measurement, such as its impact on hypertension diagnosis, treatment outcomes, and cardiovascular risk stratification, are essential. Incorporating technological advancements such as wearable devices, ABPM, and digital monitoring systems into BP measurement strategies may offer promising solutions for overcoming the challenges posed by traditional methods. By addressing these gaps, future research can enhance the accuracy, reliability, and applicability of BP measurement in diverse patient populations.

5. Conclusions

SBP, DBP, and MAP demonstrated equivalence in the arm and forearm, suggesting that BP measurements in patients with hypertension, prediabetes, and obesity can be effective at both locations. This method is particularly useful for patients with obesity and prediabetes or arm deformities, especially within the context of public health and clinical practice, as it promotes inclusion and ensures the proper monitoring of all patients and their respective conditions. Furthermore, this study highlights that accurate BP measurement is crucial for effective treatment of hypertension. Despite the strong correlation and minimal bias observed, the wide limits of agreement and potential for reclassification in borderline cases underscore the need for contextual interpretation, particularly in individuals with obesity and prediabetes. Ensuring accuracy requires the use of standardized measurement protocols, appropriately sized cuffs, and proper positioning to reduce hydrostatic pressure differences. Further research is needed to validate forearm measurement techniques in diverse populations and to evaluate their consistency with the gold standard ABPM, enhancing their clinical reliability and applicability.

Author Contributions

All authors (T.P.M., L.P.P., T.d.A.R., L.B.T.Y., L.G.S.-P., L.N.C.-M., L.H.B.T., H.M., J.F.V.-M. and J.C.Y.-T.) of this study made substantial contributions to the conception, design, data collection, analysis, drafting, and editing of the work. They were involved sufficiently in the writing of this article to claim ownership of its intellectual content. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in strict accordance with the principles of the Declaration of Helsinki. It was approved by the Institutional Ethics Committee of the State Faculty of Medicine in São José do Rio Preto (FAMERP), specifically by the Human Research Ethics Committee (CAAE: 16076719.2.0000.5415). Approval was granted on 18 June 2016.

Informed Consent Statement

All study participants provided written informed consent, and measures were taken to ensure their confidentiality and anonymity, protecting their identities throughout the research process.

Data Availability Statement

Data were collected and managed using REDCap 14.0.9 electronic data capture tools, hosted by REDCap—FUNFARME/FAMERP (State Faculty of Medicine, São José do Rio Preto). These data are available upon request from the corresponding author but are not publicly accessible due to privacy considerations.

Acknowledgments

We express our gratitude to the State Faculty of Medicine of São José do Rio Preto (FAMERP), Federal University of São Paulo (UNIFESP), and the State University of Campinas (UNICAMP) for their support in making this work possible.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. The brands of the devices used to collect the variables in this study have no association with the authors or this manuscript.

Abbreviations

The following abbreviations are used in this manuscript:
ABPMambulatory blood pressure monitoring
ARBangiotensin II receptor blockers
ACEangiotensin-converting enzyme
BMIbody mass index
BPblood pressure
DBPdiastolic blood pressure
DBP ADiastolic Blood Pressure measured on the arm
DBP FADiastolic Blood Pressure measured on the forearm
FAMERPState Faculty of Medicine in São José do Rio Preto
HRheart rate
IADinter-arm difference
MAPmean arterial pressure
MAP AMean Arterial Pressure measured on the arm
MAP FAMean Arterial Pressure measured on the forearm
OBPMoffice-based blood pressure monitoring
PADperipheral artery disease
PPpulse pressure
SBPsystolic blood pressure
SBP ASystolic Blood Pressure measured on the arm
SBP FASystolic Blood Pressure measured on the forearm
UNICAMPState University of Campinas
UNIFESPFederal University of São Paulo

References

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Diabetology 06 00094 g001aDiabetology 06 00094 g001b
Figure 1. Pearson correlation analyses and a box plot to illustrate the relationship and distribution of BP measurements from the arm and forearm. Strong positive correlations were observed across all parameters: (A) SBP (r = 0.86), (B) DBP (r = 0.93), (C) MAP (r = 0.90), (D) HR (r = 0.96), and (E) PP (r = 0.82), with high statistical significance (p < 0.0001). The box plot (F) visually highlights the distribution, median values, interquartile ranges, and potential outliers for SBP, DBP, and MAP, demonstrating excellent agreement between measurements from the arm and forearm, with no significant differences (p > 0.05). These findings reflect the reliability of the BP measurements at both locations. N = 72. DBP FA: Diastolic Blood Pressure measured on the forearm; DBP A: Diastolic Blood Pressure measured on the arm; SBP FA: Systolic Blood Pressure measured on the forearm; SBP A: Systolic Blood Pressure measured on the arm; MAP FA: Mean Arterial Pressure measured on the forearm; MAP A: Mean Arterial Pressure measured on the arm.
Figure 1. Pearson correlation analyses and a box plot to illustrate the relationship and distribution of BP measurements from the arm and forearm. Strong positive correlations were observed across all parameters: (A) SBP (r = 0.86), (B) DBP (r = 0.93), (C) MAP (r = 0.90), (D) HR (r = 0.96), and (E) PP (r = 0.82), with high statistical significance (p < 0.0001). The box plot (F) visually highlights the distribution, median values, interquartile ranges, and potential outliers for SBP, DBP, and MAP, demonstrating excellent agreement between measurements from the arm and forearm, with no significant differences (p > 0.05). These findings reflect the reliability of the BP measurements at both locations. N = 72. DBP FA: Diastolic Blood Pressure measured on the forearm; DBP A: Diastolic Blood Pressure measured on the arm; SBP FA: Systolic Blood Pressure measured on the forearm; SBP A: Systolic Blood Pressure measured on the arm; MAP FA: Mean Arterial Pressure measured on the forearm; MAP A: Mean Arterial Pressure measured on the arm.
Diabetology 06 00094 g001aDiabetology 06 00094 g001b
Diabetology 06 00094 g002
Figure 2. Bland–Altman plots assessing the agreement between the arm and forearm measurement methods across different parameters. Panels (A–C) show Bland–Altman plots comparing two blood pressure measurement methods. The green and pink shaded areas represent the upper and lower limits of agreement, respectively. The gray band indicates the confidence interval around the mean difference, while the blue band reflects the confidence interval around the regression line, illustrating how the difference between methods varies across the measurement range. For SBP (A), the bias was minimal (0.366), with limits of agreement ranging from −31.335 to 32.068, confirming reliability (t = 0.19, p = 0.8). For DBP (B), the bias was 1.65, with limits of agreement ranging from −23.02 to 26.33, indicating consistency (t = 1.1, p = 0.3). For MAP (C), the bias was 1.25, with limits of agreement ranging from −15.94 to 18.45, showing reliability (t = 1.2, p = 0.2). The 95% confidence intervals validated the reliability across all the parameters, p > 0.05. N = 72.
Figure 2. Bland–Altman plots assessing the agreement between the arm and forearm measurement methods across different parameters. Panels (A–C) show Bland–Altman plots comparing two blood pressure measurement methods. The green and pink shaded areas represent the upper and lower limits of agreement, respectively. The gray band indicates the confidence interval around the mean difference, while the blue band reflects the confidence interval around the regression line, illustrating how the difference between methods varies across the measurement range. For SBP (A), the bias was minimal (0.366), with limits of agreement ranging from −31.335 to 32.068, confirming reliability (t = 0.19, p = 0.8). For DBP (B), the bias was 1.65, with limits of agreement ranging from −23.02 to 26.33, indicating consistency (t = 1.1, p = 0.3). For MAP (C), the bias was 1.25, with limits of agreement ranging from −15.94 to 18.45, showing reliability (t = 1.2, p = 0.2). The 95% confidence intervals validated the reliability across all the parameters, p > 0.05. N = 72.
Diabetology 06 00094 g002
Table 1. Recommendations for preparing patients for BP measurements [33].
Table 1. Recommendations for preparing patients for BP measurements [33].
1. Explain the procedure to the patients.
2. Ensure at least 5 min of rest in a calm environment.
3. Avoid a full bladder.
4. Refrain from physical exercise 60–90 min before measurement.
5. Do not consume alcoholic beverages, coffee, or food or smoke 30 min before the measurement.
7. Keep legs uncrossed, feet flat on the floor, back supported by the chair, and body relaxed.
6. Clothing is removed from the arm where the cuff is placed.
8. Position the arm at heart level (mid-sternum or 4th intercostal space). Supported, with the palm facing upward and the elbow slightly bent.
9. The patient was asked to remain silent during measurements.
Table 2. Anthropometric data and clinical characteristics of the patients.
Table 2. Anthropometric data and clinical characteristics of the patients.
VariableMeanStandard
Deviation (SD)		Confidence
Interval		SD of
Differences		Obesity
Classification (%)
Age (years)65.510.862.9–68.1--
Gender (M/F)21/51----
Height (m)1.620.0861.59–1.73--
Weight (kg)89.912.986.9–92.9--
BMI (kg/m2)32.64.9630.4–34.6--
Obesity Grade I
(30.0–34.9 kg/m2)		 45%
Obesity Grade II
(35.0–39.9 kg/m2)		 38%
Obesity Grade III
(≥40.0 kg/m2)		 17%
Fasting Glucose (mg/dL)108.49.6106.2–110.68.3
HbA1c (%)5.90.45.8–6.00.3
SBP (mmHg)147.925.3131.2–163.77.4-
DBP (mmHg)86.814.271.1–96.25.2-
MAP (mmHg)107.216.393.7–115.26.1-
HR (bpm)78.714.768.1–86.3--
PP (mmHg)61.618.3356.53–64.5--
Age (years), gender (male/female), height (m), weight (kg), BMI: body mass index (kg/m2), SBP: systolic blood pressure (mmHg), DBP: diastolic blood pressure (mmHg), MAP: mean arterial pressure (mmHg), HR: heart rate (bpm), PP: pulse pressure (mmHg). N = 72.
Table 3. Comparative analysis of anthropometric and hemodynamic variables across subgroups.
Table 3. Comparative analysis of anthropometric and hemodynamic variables across subgroups.
SubgroupNAge (Years)BMI (kg/m2)SBP (mmHg)DBP (mmHg)MAP (mmHg)HR (bpm)PP (mmHg)p-Value
Male2166.2 ± 9.833.1 ± 5.2151.3 ± 24.188.4 ± 13.6109.4 ± 15.776.5 ± 13.262.9 ± 17.50.95
Female5165.2 ± 11.232.4 ± 4.8146.5 ± 26.186.2 ± 14.7106.3 ± 16.879.4 ± 15.161.2 ± 18.7
Obesity Grade I (30–34.9)3264.8 ± 10.532.1 ± 1.3145.2 ± 22.685.1 ± 13.9105.1 ± 15.477.3 ± 14.160.1 ± 17.20.99
Obesity Grade II (35–39.9)2766.1 ± 11.036.7 ± 1.4149.8 ± 26.387.9 ± 14.5108.5 ± 17.279.9 ± 15.361.9 ± 19.1
Obesity Grade III (≥40)1365.9 ± 10.242.3 ± 2.1153.4 ± 28.789.6 ± 15.1110.9 ± 18.480.2 ± 16.063.8 ± 20.3
Standard Cuff
(22–32 cm)		4265.1 ± 10.931.8 ± 4.2144.7 ± 23.585.6 ± 13.8105.3 ± 15.977.8 ± 14.459.1 ± 17.90.89
Large Cuff
(33–42 cm)		3066.0 ± 10.734.1 ± 5.3151.2 ± 26.888.1 ± 14.6108.5 ± 17.179.6 ± 15.063.1 ± 18.6
IAD ≥ 10 mmHg1966.7 ± 10.333.5 ± 5.0155.6 ± 27.489.2 ± 15.3111.3 ± 18.280.1 ± 15.666.4 ± 19.70.99
IAD < 10 mmHg5365.2 ± 10.932.3 ± 4.9146.1 ± 24.686.1 ± 14.1106.1 ± 16.378.4 ± 14.660.0 ± 18.1
N: number of individuals in each subgroup; age (years): mean age in years; BMI (kg/m2): body mass index; SBP (mmHg): systolic blood pressure; DBP (mmHg): diastolic blood pressure; IAD (mmHg): inter-arm difference; MAP (mmHg): mean arterial pressure; HR (bpm): heart rate in beats per minute; PP (mmHg): pulse pressure, calculated as the difference between SBP and DBP; p-value: statistical significance for comparisons between subgroups (t-test or ANOVA); values greater than 0.05 indicate no significant difference.
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Minari, T.P.; Pisani, L.P.; Rubio, T.d.A.; Yugar, L.B.T.; Sedenho-Prado, L.G.; Cosenso-Martin, L.N.; Tácito, L.H.B.; Moreno, H.; Vilela-Martin, J.F.; Yugar-Toledo, J.C. Comparison of Oscillometric Blood Pressure Measurements on the Arm and Forearm in Patients with Obesity, Prediabetes, and Hypertension. Diabetology 2025, 6, 94. https://doi.org/10.3390/diabetology6090094

AMA Style

Minari TP, Pisani LP, Rubio TdA, Yugar LBT, Sedenho-Prado LG, Cosenso-Martin LN, Tácito LHB, Moreno H, Vilela-Martin JF, Yugar-Toledo JC. Comparison of Oscillometric Blood Pressure Measurements on the Arm and Forearm in Patients with Obesity, Prediabetes, and Hypertension. Diabetology. 2025; 6(9):94. https://doi.org/10.3390/diabetology6090094

Chicago/Turabian Style

Minari, Tatiana Palotta, Luciana Pellegrini Pisani, Tatiane de Azevedo Rubio, Louise Buonalumi Tácito Yugar, Luis Gustavo Sedenho-Prado, Luciana Neves Cosenso-Martin, Lúcia Helena Bonalume Tácito, Heitor Moreno, José Fernando Vilela-Martin, and Juan Carlos Yugar-Toledo. 2025. "Comparison of Oscillometric Blood Pressure Measurements on the Arm and Forearm in Patients with Obesity, Prediabetes, and Hypertension" Diabetology 6, no. 9: 94. https://doi.org/10.3390/diabetology6090094

APA Style

Minari, T. P., Pisani, L. P., Rubio, T. d. A., Yugar, L. B. T., Sedenho-Prado, L. G., Cosenso-Martin, L. N., Tácito, L. H. B., Moreno, H., Vilela-Martin, J. F., & Yugar-Toledo, J. C. (2025). Comparison of Oscillometric Blood Pressure Measurements on the Arm and Forearm in Patients with Obesity, Prediabetes, and Hypertension. Diabetology, 6(9), 94. https://doi.org/10.3390/diabetology6090094

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