OBJECTIVE—Although tight blood pressure (BP) control is proven to reduce diabetes-related cardiovascular risk, it has been difficult to achieve in practice, perhaps in part because of low-quality monitoring data. We hypothesized that low-quality BP data, reflected in end-digit preference (EDP), remains common in primary care of diabetic adults.
RESEARCH DESIGN AND METHODS—Data were abstracted from the charts of 404 adults with type 2 diabetes seen at 16 academically affiliated clinics from 1999 to 2001. End-digits of systolic and diastolic BPs taken with nonautomated sphygmomanometers were extracted, and prevalence of EDP for zero was calculated. Associations between EDP and selected patient characteristics were determined using multiple logistic regressions.
RESULTS—EDP was highly prevalent in the BP measurements taken by nonphysicians (4,333 BPs; 50% of systolic, 50% of diastolic readings ended in zero; P < 0.001) and physicians (1,347 BPs; 69% of systolic, 64% of diastolic readings ended in zero; P < 0.001). In multivariate analysis, nonphysicians showed greater EDP for systolic BP in older patients (odds ratio [OR] 1.07 per 5 years) and women (OR 1.36 vs. men) and for diastolic BP in African-Americans (OR 1.25 vs. whites; all P < 0.05); physicians showed greater EDP for diastolic BP in less obese patients (OR 0.97 per 5 kg/m2 increment in BMI; P = 0.02).
CONCLUSIONS—Low-quality BP measurement is common in primary care of diabetic adults. Procedural and technological improvements to BP measurement deserve attention as part of an overall strategy to tighten BP control and reduce cardiovascular risk.
Although tight blood pressure (BP) control is proven to reduce diabetes-related cardiovascular risk in controlled trials (1–3), it has been difficult to achieve in general practice (4,5). One reason might be low-quality monitoring data: compared with A1C and lipids, which are stable day to day and are measured in laboratories with strict quality control standards, BP is quite variable and is measured by busy clinicians with little attention to standardization. A widely accepted indicator of low-quality BP measurement made with nonautomated sphygmomanometers is end-digit preference (EDP)—the occurrence of zeros as end digits more frequently than would be expected by chance alone. Earlier studies have found high prevalence of EDP in primary care (6,7) and specialty hypertension clinics (8). These studies have suggested that EDP might affect antihypertensive medication prescribing patterns (7) and that, in turn, the likelihood of EDP might be influenced by patient demographic characteristics (8).
We therefore conducted a study to identify EDP and its correlates in a cohort of adults with type 2 diabetes in primary care. We hypothesized that EDP remains common, even in contemporary practice, and that EDP would be influenced by patient characteristics, including age, sex, race, and BMI.
RESEARCH DESIGN AND METHODS—
We conducted a non-concurrent prospective cohort study of 404 adults with type 2 diabetes seen at 16 academically affiliated clinics during the years 1999–2001. The cohort was comprised of federal employees and their dependents enrolled in a managed care program. Patients were eligible for inclusion if their charts were coded with ICD-9 codes 250.xx, 357.2, 362.0, or 366.41, or if they had been prescribed insulin or oral hypoglycemic agents and if they had been seen for two or more primary care encounters or one emergency room or hospital stay during 1 January 1999 to 31 December 2001. Chart abstraction was performed by two trained registered nurses and reviewed by two physicians. Abstracted data included BP readings by the medical assistant and/or by the physician, age, sex, race, height, weight, and presence of other comorbidities.
STATA software (9) was used to perform all statistical analyses. Distributions of end digits of systolic and diastolic BPs were plotted and a single sample test of proportion was used to test for significant differences. Student's t test and χ2 analyses were used to compare demographic variables in BPs ending in zero and BPs ending in nonzero. Finally, multivariate analysis was performed using generalized estimating equations to fit logistic regression models to account for longitudinal correlation between multiple measurements in the same patients and to simultaneously adjust for confounding factors.
RESULTS—
The majority of study subjects were male (58%), white (59%), older (63 ± 8 years), seen in urban clinic locations (83%), overweight (mean BMI 32 ± 5.8 kg/m2), and hypertensive (70%) (Table 1). There was 5,677 BPs taken with nonautomated sphygmomanometers (4,330 by nonphysicians; 1,347 by physicians). BP taken by nonphysicians was 139 ± 19/78 ± 11 (mean ± SD) (n = 4,330) and 142 ± 19/80 ± 10 taken by physicians (n = 1,347). Compared with the expected frequency of end-digit zeros of 20% (since zero is one of five even gradations on scales of manual sphygmomanometers), there was strong evidence of EDP among nonphysicians (50% of systolic and 50% of diastolic readings ended in zero; Fig. 1) and even stronger evidence among physicians (69% of systolic and 64% of diastolic readings ended in zero; Fig. 2).
Characteristics of the study population by BP end digit are presented in Table 2. In multivariate logistic regression, nonphysicians showed greater EDP for systolic blood pressure with older patients (odds ratio [OR] 1.07 per 5 years) and women (OR 1.36 vs. men) and for diastolic blood pressure with African-Americans (OR 1.25 vs. whites; all adjusted ORs, P < 0.05). In contrast, physicians were less influenced by age, sex, or race, but did show greater EDP in patients with lower BMI (OR 0.97 per 5 kg/m2, P = 0.02; Table 3).
These analyses were repeated after pooling EDP data across systolic and diastolic readings among physicians and among nonphysicians. In these pooled analyses (Table 4), nonphysicians showed greater EDP for female patients (OR 1.26 vs. men; P = 0.006), and physicians showed greater EDP for African-American patients (OR 1.35 vs. whites; P = 0.03) and for patients with lower BMI (OR 0.97 per 5 kg/m2; P = 0.02).
CONCLUSIONS—
Our data indicate that low-quality BP measurement remains common in the primary care of adults with type 2 diabetes and also suggest that it may be more common in women and African-Americans. Widely accepted practice guidelines recommend a target BP of <130/80 mmHg in adults with diabetes (10). Such guidelines heighten the need for accurate BP assessment in this population. However, the high observed frequency of EDP indicates that medical staff are rounding BPs to the nearest zero. Insofar as they round down (e.g., from 134 mmHg systolic to 130 mmHg), this practice may lead to underdiagnosis and undertreatment. Improving BP measurement may therefore represent a potential strategy for reducing health care disparities.
Practitioners might justify their behavior on the basis of the underlying variability of BP itself and the imprecision inherent in sphygomanometry: why record BPs that imply greater precision than is actually achievable? BP is more variable than other diabetes-related risk factors such as A1C and fasting lipids. Nonetheless, guidelines incorporate variability into their conceptual framework by suggesting that treatment be based on several BP measurements at successive visits (10). Within this framework, measures to reduce variability related to technique and equipment should increase underlying precision, inspire greater confidence, and enhance decision-making.
To our knowledge, our study is the first to quantify EDP in diabetic adults in a primary care setting. Limitations to this study include the inability to compare the level of EDP in diabetic patients compared with nondiabetic patients in the same practice (could the level of EDP actually be worse in nondiabetic patients?) and the inability to assess the impact of BP inaccuracy over time in terms of provider prescribing patterns or cardiovascular outcomes. The results of this study, however, raise some interesting questions regarding measurement bias in BP based on a patient's sex, race, and weight. Our findings of increased EDP in older patients and patients with lower BMI support previous findings (8). These results could indeed be explained by concern of missing a diagnosis of hypertension in young or obese patients, but additionally, lower EDP in heavier patients could also be due to the use of better fitting cuffs and less confidence in taking BPs in patients with larger arm circumferences, leading to more careful BP measurements. Additionally, the finding that there is more EDP in BPs taken in women and African-American patients is particularly worrisome, since women comprise 51% of all heart disease deaths (11) and African-Americans have the highest rate of hypertension among all racial groups (12), with substantially higher rates of cardiovascular mortality (13). Design of further studies on the topic of BP measurement accuracy should take into account these findings in an effort to decrease cardiovascular morbidity and mortality overall, but also to better discern causes of cardiovascular health disparity between sexes and among races in an effort to eliminate them altogether.
EDP in BP measurements taken in a diabetic population is common. The main implication is that better quality standards and/or alternative methods for BP measurement deserve attention as part of an overall strategy to tighten BP control in diabetic adults. While some sources of error, such as pervasive hearing loss, are not immediately amenable to systematic remediation, faulty measurement technique (14,15) and faulty equipment (16,17) can be addressed by retraining or better equipment. Automated sphygmomanometers have emerged as an alterative to reduce imprecision related to technique (18–20), although they may introduce new sources of inaccuracy (21,22). At the very least, manual sphygmomanometers, which are still in use in many physician offices, should be well maintained and calibrated to obtain the most accurate readings. Additionally, effort should be made to reduce observer and technical error (23,24) by improving training and standardization of BPs measured by physicians and clinic staff.
Distributions of systolic (A) and diastolic (B) BPs taken by staff. C: Distribution of end digits of systolic blood pressure (SBP) and diastolic blood pressure (DBP) taken by staff. A total of 50% of systolic and 50% of diastolic blood pressure readings ended in zero. The difference between the prevalence of zero and other end digits is statistically significant (P < 0.001).
Distributions of systolic (A) and diastolic (B) BPs taken by staff. C: Distribution of end digits of systolic blood pressure (SBP) and diastolic blood pressure (DBP) taken by staff. A total of 50% of systolic and 50% of diastolic blood pressure readings ended in zero. The difference between the prevalence of zero and other end digits is statistically significant (P < 0.001).
Distribution of systolic (A) and diastolic (B) BP by physicians. C: Distribution of end digits of systolic blood pressure (SBP) and diastolic blood pressure (DBP) taken by physicians. A total of 69% of systolic and 64% of diastolic blood pressure readings ended in zero. The difference between the prevalence of zero and other end digits is statistically significant (P < 0.001).
Distribution of systolic (A) and diastolic (B) BP by physicians. C: Distribution of end digits of systolic blood pressure (SBP) and diastolic blood pressure (DBP) taken by physicians. A total of 69% of systolic and 64% of diastolic blood pressure readings ended in zero. The difference between the prevalence of zero and other end digits is statistically significant (P < 0.001).
Selected characteristics of 404 diabetic adults in primary care
Mean age (years) | 63 ± 8 |
Race | |
White | 59 |
Black | 32 |
Other | 9 |
Female | 42 |
Mean BMI (kg/m2) | 32 ± 5.8 |
Clinic location | |
Urban/suburban | 83 |
Rural | 17 |
History of transient ischemic attack/stroke | 4 |
History of hypertension | 70 |
History of coronary artery disease | 23 |
History of renal disease | 13 |
Mean age (years) | 63 ± 8 |
Race | |
White | 59 |
Black | 32 |
Other | 9 |
Female | 42 |
Mean BMI (kg/m2) | 32 ± 5.8 |
Clinic location | |
Urban/suburban | 83 |
Rural | 17 |
History of transient ischemic attack/stroke | 4 |
History of hypertension | 70 |
History of coronary artery disease | 23 |
History of renal disease | 13 |
Data are percent or means ± SD.
Characteristics of patients seen at 4,424 visits by end digits of BPs
. | BP measured by staff . | . | BP measured by physicians . | . | ||
---|---|---|---|---|---|---|
. | End digit = 0 . | End digit = other integers . | End digit = 0 . | End digit = other integers . | ||
Systolic BP | ||||||
n | 2,158 | 2,172 | 929 | 418 | ||
Mean age*† (years) | 63.7 | 62.9 | 64.8 | 63.9 | ||
% Black*† | 52 | 48 | 73 | 64 | ||
% Female* | 54 | 46 | 71 | 67 | ||
Mean weight*† (lb) | 203 | 208 | 204 | 214 | ||
Mean BMI*† (kg/m2) | 31.9 | 32.3 | 32.1 | 33.1 | ||
Diastolic BP | ||||||
n | 2,174 | 2,155 | 854 | 492 | ||
Mean age† (years) | 63.5 | 63.1 | 64.9 | 63.8 | ||
% Black*† | 55 | 47 | 67 | 61 | ||
% Female* | 52 | 48 | 65 | 62 | ||
Mean weight*† (lb) | 204 | 207 | 204 | 212 | ||
Mean BMI† (kg/m2) | 32.1 | 32.2 | 32.0 | 33.1 |
. | BP measured by staff . | . | BP measured by physicians . | . | ||
---|---|---|---|---|---|---|
. | End digit = 0 . | End digit = other integers . | End digit = 0 . | End digit = other integers . | ||
Systolic BP | ||||||
n | 2,158 | 2,172 | 929 | 418 | ||
Mean age*† (years) | 63.7 | 62.9 | 64.8 | 63.9 | ||
% Black*† | 52 | 48 | 73 | 64 | ||
% Female* | 54 | 46 | 71 | 67 | ||
Mean weight*† (lb) | 203 | 208 | 204 | 214 | ||
Mean BMI*† (kg/m2) | 31.9 | 32.3 | 32.1 | 33.1 | ||
Diastolic BP | ||||||
n | 2,174 | 2,155 | 854 | 492 | ||
Mean age† (years) | 63.5 | 63.1 | 64.9 | 63.8 | ||
% Black*† | 55 | 47 | 67 | 61 | ||
% Female* | 52 | 48 | 65 | 62 | ||
Mean weight*† (lb) | 204 | 207 | 204 | 212 | ||
Mean BMI† (kg/m2) | 32.1 | 32.2 | 32.0 | 33.1 |
P < 0.05 for difference between end-digit groups in BPs taken by staff.
P < 0.05 for difference between end-digit groups in BPs taken by physicians.
Crude and adjusted odds ratios of zero as end digit in systolic and diastolic BPs measured by medical staff and physicians in 404 diabetic patients
. | Unadjusted OR (95% CI) . | Adjusted* OR (95% CI) . | Adjusted* P value . |
---|---|---|---|
Measured by staff | |||
Systolic BP | |||
Age (per 5 years) | 1.06 (1.01–1.12) | 1.07 (1.00–1.13) | 0.03 |
Black (vs. white) | 1.14 (0.97–1.35) | 1.06 (0.89–1.27) | 0.51 |
Female (vs. male) | 1.36 (1.16–1.59) | 1.36 (1.13–1.63) | 0.001 |
BMI (per 5 kg/m2) | 0.99 (0.98–1.01) | 0.99 (0.97–1.01) | 0.10 |
Diastolic BP | |||
Age (per 5 years) | 1.03 (0.97–1.08) | 1.04 (0.98–1.10) | 0.23 |
Black (vs. white) | 1.33 (1.13–1.57) | 1.25 (1.04–1.50) | 0.02 |
Female (vs. male) | 1.17 (1.00–1.38) | 1.15 (0.95–1.40) | 0.14 |
BMI (per 5 kg/m2) | 1.00 (0.98–1.01) | 1.00 (0.98–1.02) | 0.87 |
Measured by physicians | |||
Systolic BP | |||
Age (per 5 years) | 1.10 (0.99–1.22) | 1.07 (0.94–1.21) | 0.33 |
Black (vs. white) | 1.51 (1.11–2.05) | 1.36 (0.98–1.89) | 0.07 |
Female (vs. male) | 1.29 (0.96–1.73) | 1.20 (0.86–1.69) | 0.27 |
BMI (per 5 kg/m2) | 0.98 (0.95–1.00) | 0.98 (0.95–1.00) | 0.08 |
Diastolic BP | |||
Age (per 5 years) | 1.13 (1.02–1.25) | 1.05 (0.94–1.18) | 0.40 |
Black (vs. white) | 1.31 (0.98–1.76) | 1.30 (0.95–1.78) | 0.10 |
Female (vs. male) | 1.26 (0.95–1.68) | 1.27 (0.93–1.73) | 0.14 |
BMI (per 5 kg/m2) | 0.97 (0.95–0.99) | 0.97 (0.94–0.99) | 0.02 |
. | Unadjusted OR (95% CI) . | Adjusted* OR (95% CI) . | Adjusted* P value . |
---|---|---|---|
Measured by staff | |||
Systolic BP | |||
Age (per 5 years) | 1.06 (1.01–1.12) | 1.07 (1.00–1.13) | 0.03 |
Black (vs. white) | 1.14 (0.97–1.35) | 1.06 (0.89–1.27) | 0.51 |
Female (vs. male) | 1.36 (1.16–1.59) | 1.36 (1.13–1.63) | 0.001 |
BMI (per 5 kg/m2) | 0.99 (0.98–1.01) | 0.99 (0.97–1.01) | 0.10 |
Diastolic BP | |||
Age (per 5 years) | 1.03 (0.97–1.08) | 1.04 (0.98–1.10) | 0.23 |
Black (vs. white) | 1.33 (1.13–1.57) | 1.25 (1.04–1.50) | 0.02 |
Female (vs. male) | 1.17 (1.00–1.38) | 1.15 (0.95–1.40) | 0.14 |
BMI (per 5 kg/m2) | 1.00 (0.98–1.01) | 1.00 (0.98–1.02) | 0.87 |
Measured by physicians | |||
Systolic BP | |||
Age (per 5 years) | 1.10 (0.99–1.22) | 1.07 (0.94–1.21) | 0.33 |
Black (vs. white) | 1.51 (1.11–2.05) | 1.36 (0.98–1.89) | 0.07 |
Female (vs. male) | 1.29 (0.96–1.73) | 1.20 (0.86–1.69) | 0.27 |
BMI (per 5 kg/m2) | 0.98 (0.95–1.00) | 0.98 (0.95–1.00) | 0.08 |
Diastolic BP | |||
Age (per 5 years) | 1.13 (1.02–1.25) | 1.05 (0.94–1.18) | 0.40 |
Black (vs. white) | 1.31 (0.98–1.76) | 1.30 (0.95–1.78) | 0.10 |
Female (vs. male) | 1.26 (0.95–1.68) | 1.27 (0.93–1.73) | 0.14 |
BMI (per 5 kg/m2) | 0.97 (0.95–0.99) | 0.97 (0.94–0.99) | 0.02 |
Adjusted for age (per 5 years), race, sex, and BMI.
Crude and adjusted odds ratio of zero as end digit for either systolic or diastolic BP in 404 diabetic patients at 4,424 primary care visits
. | Unadjusted OR (95% CI) . | Adjusted* OR (95% CI) . | Adjusted* P value . |
---|---|---|---|
Measured by staff | |||
Age (per 5 years) | 1.04 (1.00–1.09) | 1.05 (1.00–1.11) | 0.06 |
Black (vs. white) | 1.23 (1.07–1.41) | 1.15 (0.98–1.34) | 0.09 |
Female (vs. male) | 1.27 (1.11–1.45) | 1.26 (1.06–1.48) | 0.006 |
BMI (per 5 kg/m2) | 0.99 (0.98–1.01) | 0.99 (0.98–1.01) | 0.34 |
Measured by physicians | |||
Age (per 5 years) | 1.11 (1.01–1.22) | 1.06 (0.96–1.17) | 0.27 |
Black (vs. white) | 1.42 (1.10–1.84) | 1.35 (1.03–1.77) | 0.03 |
Female (vs. male) | 1.29 (1.00–1.66) | 1.26 (0.95–1.67) | 0.11 |
BMI (per 5 kg/m2) | 0.98 (0.96–1.00) | 0.97 (0.95–0.99) | 0.02 |
. | Unadjusted OR (95% CI) . | Adjusted* OR (95% CI) . | Adjusted* P value . |
---|---|---|---|
Measured by staff | |||
Age (per 5 years) | 1.04 (1.00–1.09) | 1.05 (1.00–1.11) | 0.06 |
Black (vs. white) | 1.23 (1.07–1.41) | 1.15 (0.98–1.34) | 0.09 |
Female (vs. male) | 1.27 (1.11–1.45) | 1.26 (1.06–1.48) | 0.006 |
BMI (per 5 kg/m2) | 0.99 (0.98–1.01) | 0.99 (0.98–1.01) | 0.34 |
Measured by physicians | |||
Age (per 5 years) | 1.11 (1.01–1.22) | 1.06 (0.96–1.17) | 0.27 |
Black (vs. white) | 1.42 (1.10–1.84) | 1.35 (1.03–1.77) | 0.03 |
Female (vs. male) | 1.29 (1.00–1.66) | 1.26 (0.95–1.67) | 0.11 |
BMI (per 5 kg/m2) | 0.98 (0.96–1.00) | 0.97 (0.95–0.99) | 0.02 |
Adjusted for age (per 5 years), race, sex, and BMI.
Article Information
This study was funded by National Institutes of Health Grants K24-DK62222 and R01-DK48117 (F.L.B. was the principle investigator for both grants).
E.S.H.K. initiated/conducted/completed this work while a medical resident at the Johns Hopkins Hospital and was supported by the Osler Fund for Scholarship, Department of Medicine, Johns Hopkins University.
References
Published ahead of print at http://care.diabetesjournals.org on 7 May 2007. DOI: 10.2337/dc07-0020.
E.S.H.K. is currently affiliated with the Department of Cardiology, Cleveland Clinic, Cleveland, Ohio.
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.
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