Study Oversight

This study was supported by the Spanish Society of Hypertension, Lacer Laboratories, and European government agencies. The funding sources had no role in the design of the study, the collection and analysis of the data, the interpretation of results, the writing of the report, or the decision to submit the report for publication.

The study protocol and analyses were approved by the institutional review board for all participating centers. The authors vouch for the accuracy and completeness of the data. The full list of investigators is provided in the Supplementary Appendix, available with the full text of this article at NEJM.org.

Patient Population

Data for this study were obtained from the ongoing Spanish Ambulatory Blood Pressure Registry, a national study of patients selected by their physicians at 223 primary care centers within the Spanish National Health System in all the 17 regions of Spain.24,25 Patients were required to be 18 years of age or older and to meet guideline-recommended indications for ambulatory blood-pressure monitoring,24-28 which included suspected white-coat hypertension, refractory or resistant hypertension, high-risk hypertension, and labile or borderline hypertension, as well as assessment of drug-treatment efficacy and study of the circadian blood-pressure pattern (details are provided in the Supplementary Appendix). All patients included in the registry provided written informed consent.

The current study is an analysis of mortality among 66,636 persons 18 years of age or older who were enrolled in the registry between March 1, 2004, and December 31, 2014. Of these, 2726 were excluded because of incomplete information on demographic or clinical characteristics; thus, 63,910 patients were included in the analysis.

Blood Pressure and Other Study Variables

Blood pressure was measured in the clinic according to standardized procedures, with the use of validated oscillometric devices (in 85% of patients) or calibrated mercury sphygmomanometers (in 15%), after the patient had been resting in a seated position for 5 minutes.26-28 We used the mean of two clinic blood-pressure readings. Thereafter, ambulatory blood-pressure monitoring was performed with validated, automated, oscillometric devices (Spacelabs model 90207, Spacelabs Healthcare) that were programmed to record blood pressure at 20-minute intervals during the day and at 30-minute intervals during the night. An appropriate cuff size (one of two sizes) was used for each patient. We used the mean of all valid readings for the analysis. Valid measurements had to fulfill prespecified quality criteria, including the successful recording of at least 70% of systolic and diastolic blood-pressure readings during the 24-hour recording period. Day and night periods were defined according to sleeping and waking times reported by the patient.

Patient data were obtained from interviews and physical examinations during the visits and from clinical records. The clinical characteristics of the patients were assessed in accordance with international guidelines.26-28 Additional details are provided in the Supplementary Appendix.

Mortality Data

The date and cause of death were ascertained from a computerized search of the vital registry of the Spanish National Institute of Statistics; evidence of the completeness, accuracy, and reliability of this vital-status information has been made available by the Institute.29 Persons were designated as having died if the deaths were recorded in the vital registry. The cause of death was determined from the death certificate by a nosologist and was coded according to the International Statistical Classification of Diseases, 10th Revision. We included all deaths that were classified as being of cardiovascular origin (codes I00 to I99) and further subcategorized cardiovascular-related deaths as having been caused by ischemic heart disease (codes I21–I25), stroke (codes I60–I69), or heart failure (code I50). For each study participant, follow-up was from the date of the recruitment visit for the blood-pressure registry to the date of death or December 31, 2014, whichever occurred first.

Statistical Analysis

Hypertension phenotypes in untreated patients were defined as white-coat hypertension (clinic systolic blood pressure ≥140 mm Hg or diastolic ≥90 mm Hg and 24-hour systolic pressure <130 mm Hg and diastolic <80 mm Hg), masked hypertension (clinic systolic pressure <140 mm Hg and diastolic <90 mm Hg and 24-hour systolic pressure ≥130 mm Hg or diastolic ≥80 mm Hg), sustained hypertension (clinic systolic pressure ≥140 mm Hg or diastolic ≥90 mm Hg and ambulatory 24-hour systolic pressure ≥130 mm Hg or diastolic ≥80 mm Hg), or normotension (clinic systolic pressure <140 mm Hg and diastolic <90 mm Hg and 24-hour systolic pressure <130 mm Hg and diastolic <80 mm Hg).26-28 An explanation of the blood-pressure thresholds we used is provided in the Supplementary Appendix. In treated patients, the corresponding terms were white-coat uncontrolled hypertension, masked uncontrolled hypertension, sustained uncontrolled hypertension, and controlled hypertension, respectively.

Associations between blood pressure and mortality were summarized with hazard ratios and 95% confidence intervals, estimated with Cox models. Hazard ratios were calculated per 1-SD increment in blood pressure, and for hypertension phenotypes the reference group was untreated normotension. Two Cox models were constructed. Model 1 was adjusted for age, sex, smoking status, body-mass index (the weight in kilograms divided by the square of the height in meters), and status with respect to diabetes, dyslipidemia, previous cardiovascular disease, and number of antihypertensive medications used. To assess whether the associations were independent of other blood-pressure measurements, additional adjustments were performed (model 2): the hazard ratio for clinic blood pressure was adjusted for 24-hour blood pressure; 24-hour pressure was adjusted for clinic pressure; daytime pressure was adjusted for clinic and nighttime pressure; nighttime pressure was adjusted for clinic and daytime pressure; and the hazard ratios for each hypertension phenotype were adjusted for clinic pressure.

We assessed consistency in the results according to age (<60 vs. ≥60 years), sex, body-mass index (<30 vs. ≥30), presence of diabetes (yes vs. no), previous cardiovascular disease (yes vs. no), and antihypertensive medication use (yes vs. no). We also calculated the discriminative performance (expressed as the C statistic [area under the receiver-operating-characteristic curve]) and predictive performance (Akaike and Bayesian information criteria) of models containing blood-pressure components.30

In addition, we calculated rate advancement periods31 to estimate the number of additional years of chronologic age that would be required to yield the equivalent mortality rate per 1-SD increase in blood pressure or for each hypertension phenotype as compared with normotension. Population attributable fractions32 were calculated to estimate the fraction of mortality in the population that could be attributed to each hypertension phenotype (formulas are provided in the Supplementary Appendix).

Sensitivity analyses were performed in which persons who died in the first 2 years of follow-up were excluded, to minimize the influence of reverse causation. We also checked the robustness of results by defining hypertension phenotypes on the basis of all ambulatory periods (24-hour, daytime, and nighttime) (see the Supplementary Appendix).26-28,33,34 Finally, we tested the reproducibility of the main results among the 2811 participants who had two ambulatory blood-pressure measurement sessions, separated by a median time of 6.5 months.

We used SPSS software, version 19.0 (IBM), and R software, version 3.0.2 (R Foundation for Statistical Computing), for statistical analysis. Two-tailed P values of less than 0.05 were considered to indicate statistical significance; no correction for multiple testing was performed.