Published online before print May 2, 2005, doi: 10.1161/01.HYP.0000165672.69176.ed
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Hypertension. 2005;45:1072.)
© 2005 American Heart Association, Inc.
Original Articles |
Relationship of Office, Home, and Ambulatory Blood Pressure to Blood Glucose and Lipid Variables in the PAMELA Population
From the Istituto di Clinica Medica (G.M., R.F., M.B., H.P.F., G.G., C.G., R.S.), Dipartimento di Medicina Clinica, Prevenzione e Biotecnologie Sanitarie, Università Milano-Bicocca, Ospedale S Gerardo, Monza, Milan, Italy; Istituto Auxologico Italiano (G.M., G.G., C.G.), Milan, Italy; and Centro di Fisiologia Clinica e Ipertensione (G.M., G.G., C.G.), IRCCS, Ospedale Maggiore, Milan, Italy.
Correspondence to Professor Giuseppe Mancia, Clinica Medica, Ospedale S Gerardo, Via Donizetti 106, 20052 Monza, Milano, Italy. E-mail giuseppe.mancia{at}unimib.it
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
Alterations in blood glucose and cholesterol are more frequently detectable in hypertensive than in normotensive conditions. However, no information exists as to whether this phenomenon involves only office or also home and 24-hour ambulatory blood pressure (ie, when values are representative of daily life). In 2045 subjects enrolled in the Pressioni Arteriose Monitorate E Loro Associazioni (PAMELA) study, we measured home, 24-hour, and office blood pressure. Measurements also included fasting blood glucose and serum total and HDL cholesterol values. Prevalence of diabetes (
126 mg/dL or use of antidiabetic drugs), impaired fasting blood glucose (110 to <126 mg/dL), and hypercholesterolemia (serum total cholesterol 240 mg/dL or 200 mg/dL) increased progressively from "optimal" to "normal," "high-normal," and "elevated" office systolic or diastolic blood pressure. Fasting blood glucose and total serum cholesterol also increased progressively from the first to the fourth group, with HDL cholesterol values showing a concomitant progressive decrease. This was also the case for quartiles of office, home, and 24-hour blood pressure. In the whole population, there was a positive correlation between serum cholesterol or blood glucose and all blood pressure values (P always <0.0001), with a much smaller and less consistent relationship with heart rate. In a multivariate analysis that included gender, body mass index, age, and antihypertensive treatment, all blood pressure values remained highly significantly related to values of either metabolic variables. Thus, in the PAMELA population, glucose and lipid values are independently related to blood pressure. This is also the case when daily life blood pressure values are considered.
Key Words: blood pressure monitoring, ambulatory • cholesterol • glucose • lipids
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Several studies have shown that hypertensive individuals more frequently display alterations in glucose and lipid metabolism than normotensive ones.1–11 Evidence has also been obtained that alterations in lipid and glucose metabolism are more frequent in individuals with blood pressure values in the high-normal range (ie, between 130 and 139 mm Hg systolic or 85 and 89 mm Hg diastolic) than in those with lower values,1,5,7,12 suggesting that the relationship between blood pressure and metabolic alterations may have a continuous rather than a threshold-related nature.
We thought that the Pressioni Arteriose Monitorate E Loro Associazioni (PAMELA) study13 could provide relevant information on this issue because: (1) blood pressure, total serum cholesterol, and blood glucose were assessed in a sample representative of the general population; and (2) blood pressure measurements were obtained not only in the office but at home and during the 24 hours (ie, under conditions devoid of biological artifacts such as the white coat effect and representative of daily life values).14–15
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
The methodology used in the PAMELA study has been reported in detail previously.13 Briefly, 3200 individuals were selected randomly from the residents of Monza (a town in the northeast part of the Milan province) to be representative of the town population for gender, age decades (25 to 74 years), and socioeconomic characteristics, according to the criteria used in the World Health Organization Monitoring Diseases (WHO-MONICA) project conducted in the same geographic area.16–17 The overall participation rate was 64% consistently in each age–gender stratum. The demographic characteristics of nonparticipants were similar to those of participants. This was also the case for cardiovascular risk factors on the basis of information collected via telephone interviews.
Entry Data
Participants were invited to come to the outpatient clinic of the local hospital (San Gerardo) in the morning of a working day (Monday through Friday) where several data were collected. Relevant to the present study are: (1) 3 sphygmomanometric blood pressure measurements with the subject in the sitting position, starting 10 minutes after the beginning of the medical visit and including heart rate measurement (palpatory method) after each blood pressure measurement; (2) a 24-hour ambulatory blood pressure monitoring through an oscillometric device (Spacelabs 90207; Spacelabs) with the blood pressure readings set at 20-minute intervals (subjects were sent home after checking for the device accuracy with the instruction to continue their usual activities and to come back the next morning for the device removal); (3) 2 home blood pressure measurements (at 
7:00 AM and 7:00 PM) through a semiautomatic device (Model HP 5331; Philips), using the arm contralateral to that used for ambulatory monitoring; (4) 3 additional sphygmomanometric sitting blood pressure and heart rate measurements after removal of the ambulatory blood pressure measuring device; and (5) information on cardiovascular risk factors derived from history, physical, and laboratory examinations. Laboratory examinations included blood glucose and serum total cholesterol, which were measured by a standard glucose oxidase and an enzymatic method, respectively, from a venous blood sample collected in the morning after a fasting overnight period. The same blood sample was used to measure HDL cholesterol via the enzymatic method.
Data Analysis
The 6 office (3 before and 3 after ambulatory blood pressure monitoring) and 2 home blood pressure measurements were separately averaged. Ambulatory blood pressure values were edited for artifacts according to preselected criteria18 and averaged for the 24 hours. Averages were also calculated for the corresponding office, home, and 24-hour heart rate values. Subjects were divided into 4 groups according to the office blood pressure criteria of the guidelines of the European Societies of Hypertension and Cardiology19 (ie, "hypertension" [systolic blood pressure 140 mm Hg or diastolic blood pressure 90 mm Hg], high-normal blood pressure [systolic 130 to 139 mm Hg or diastolic 85 to 89 mm Hg], normal blood pressure [systolic 120 to 129 mm Hg or diastolic 80 to 84 mm Hg], and optimal blood pressure [systolic <120 mm Hg and diastolic <80mm Hg]). Because the above office blood pressure classification does not have a counterpart for home and ambulatory blood pressure, subjects were also divided in quartiles based on office, 24-hour and home systolic values. For each office blood pressure category and each office, home, or 24-hour blood pressure quartile, calculations were made of: (1) the demographic characteristics; (2) the average body mass index, serum total cholesterol, and blood glucose; and (3) the number of patients with hypercholesterolemia (serum total cholesterol 240 mg/dL or 200 mg/dL), impaired fasting blood glucose (110 to <126 mg/dL), or diabetes (126 mg/dL or use of antidiabetic drugs).
Comparisons between groups or quartiles were made by ANOVA, using the t test for unpaired observations to determine between-group differences, with the Bonferroni correction for multiple comparisons. Pearson correlation coefficients were used to determine the relationship between blood pressure or heart rate and metabolic variables. A multivariate analysis was also performed with office, home, 24-hour systolic and diastolic blood pressure, age, gender, antihypertensive treatment, and blood glucose as the independent variables and serum total cholesterol as the dependent variable to determine the blood pressure involvement in the abnormality of the lipid profile after considering other potentially involved factors. A similar analysis was performed by replacing total serum cholesterol with blood glucose as the dependent variable and blood glucose with serum cholesterol as an independent variable. A P<0.05 was the value at the level of statistical significance. Throughout the tables, the symbol ± refers to SD of the mean, except for the ß-coefficient in the multivariate analysis, in which it refers to the SEM.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Table 1 shows that, except for smoking, male prevalence, age, body mass index, serum total cholesterol, and blood glucose showed a progressive increase from the group with an optimal office blood pressure to the group with normal, high-normal, and elevated office blood pressure values, whereas serum HDL cholesterol showed a progressive decrease. This was also the case for the number of patients with hypercholesterolemia (serum total cholesterol
240 mg/dL or 200 mg/dL), impaired fasting blood glucose, and diabetes. Similar findings were observed when the PAMELA population was divided into quartiles based on office, home or 24-hour blood pressure (Tables 2, 3, and 4 
).
|
|
|
|
As shown in Table 5, office, home, and 24-hour systolic and diastolic blood pressure all showed a positive correlation with body mass index. They also correlated positively with serum total cholesterol and blood glucose values, which showed a weak positive correlation to each other (r=0.10; P<0.001) and, except in one instance, no substantial correlation with office, home, and 24-hour heart rate values. Similar findings were observed in men and women analyzed separately (data not shown). In the multivariate analysis (Table 6), blood glucose was positively related to gender (greater values in females), body mass index, and age, while showing no relationship with the presence or absence of antihypertensive treatment and serum total cholesterol. Serum total cholesterol was related inversely to gender (greater values in males), positively related to age and body mass index, and not related to antihypertensive treatment and blood glucose (Table 7). Blood glucose and total serum cholesterol showed a highly significant positive relationship with either systolic or diastolic blood pressure, regardless whether office, home, and 24-hour values were considered (Tables 6 and 7).
|
|
|
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
In the PAMELA study population, the prevalence of diabetes, impaired fasting glucose, and hypercholesterolemia was greater in subjects with hypertension than in those with normotension on the basis of office blood pressure values. Furthermore, all 3 conditions became progressively more frequent from subjects with optimal to those with normal, high-normal, and elevated office blood pressure, with a concomitant progressive increase in average blood glucose and total serum cholesterol and a reduction in HDL cholesterol values.
Finally, all the above findings were replicated when subdivision into blood pressure subgroups was based on home or ambulatory rather than on office blood pressures, and all 3 pressures showed an independent and positive relationship with blood glucose and total serum cholesterol values even in a multivariate analysis that considered the contribution of other factors (ie, age, gender, body mass index, and antihypertensive treatment, as well as serum total cholesterol for blood glucose and blood glucose for total serum cholesterol). This confirms previous findings that alterations in glucose and lipid metabolism cluster with blood pressure alterations,1–12 making diabetes, prediabetes, and hypercholesterolemia more frequent in the presence than in the absence of a blood pressure elevation. It also provides clear-cut evidence that in the population, glucose and lipid variables are related to blood pressure in a continuous fashion, which means that their abnormalities have a different prevalence even within the normal blood pressure range, that is, diabetes, prediabetes, and hypercholesterolemia are considerably more frequent in the group with high-normal than in those with normal or optimal office blood pressures. Finally, it shows for the first time that what is observed when subjects are classified by their office blood pressure occurs also when classification is based on home and ambulatory values (ie, on values that are not just occasional but typical of daily life).
Several other findings of our study deserve to be mentioned. One, the observation that alterations in glucose and lipid metabolism are related not only to office but also to home and ambulatory blood pressure is important because in normotensive and hypertensive subjects, office blood pressure is frequently affected by the white coat effect (ie, by the pressor response induced by stimulation of the sympathetic nervous system triggered by an alerting reaction).14,20–21 Although relatively ineffective on serum cholesterol values, this stimulation may raise blood glucose in a way that favors its relationship with a blood pressure elevation.22–25 This is not the case for home and 24-hour blood pressures, which are virtually devoid of any pressor effect.26 Two, in the PAMELA study, home blood pressure was measured only twice within the same day, thereby not exploiting the full potential of these measurements, which can be spread over days and weeks. The finding that home blood pressure correlated with blood glucose and cholesterol fraction as well as ambulatory blood pressure points toward the clinical relevance of the approach. Three, in the subjects of the PAMELA population, blood glucose and total serum cholesterol values showed a positive correlation that was weaker than that for either variable displayed with office, home, or ambulatory blood pressure. Furthermore, and more important, the correlation between these 2 metabolic variables disappeared in the multivariate analysis, at variance with the correlation either of them showed with in-office and out-of-office blood pressure values, which was preserved. Four, at variance from blood pressure, blood glucose and total serum cholesterol show an inconsistent correlation with heart rate values, regardless of whether they were measured in the doctor’s office, at home, or during the 24 hours. Because heart rate is a marker of sympathetic tone,27 this may appear to score against a sympathetic hyperactivity as an important common mechanism for the blood pressure and the metabolic alterations. However, it should be considered that cardiac and peripheral sympathetic activities do not always proceed "pari passu," which makes heart rate a "sympathetic" marker of limited sensitivity.28
Perspectives
Our findings indicate that a blood pressure elevation is separately related to alterations in glucose and lipid abnormalities, possibly playing a causal role for both. We can speculate that this role is exerted trough the vasoconstriction that characterizes a chronic hypertensive state29 because this hemodynamic phenomenon may adversely affect glucose and lipid metabolism. In the skeletal muscle, vasoconstriction increases the distance insulin has to travel to facilitate glucose disposal across the cell membrane.30 In adipose and hepatic tissue, it may slow down the disposal of the various components of the lipid profile.31–33
Received January 10, 2005; first decision January 19, 2005; accepted February 17, 2005.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. Haffner SM, Miettienen H, Gaskill SP, Stern MP. Metabolic precursors of hypertension. The San Antonio Heart Study. Arch Intern Med. 1996; 156: 1994–2001.
2. Simon JA, Fong J, Bernert JT. Serum fatty acids and blood pressure. Hypertension. 1996; 27: 303–307.
3. Palatini P, Casiglia E, Pauletto P, Staessen J, Kaciroti N, Julius S. Relationship of tachycardia with high blood pressure and metabolic abnormalities: a study with mixture analysis in three populations. Hypertension. 1997; 30: 1267–1273.
4. Mann JL, Lewis B, Shepherd AF, Fenster S, Rose L, Morgan B. Blood lipid concentrations and other cardiovascular risk factors: distribution, prevalence, and detection in Britain. BMJ. 1998; 18: 1702–1706.
5. Blood pressure, cholesterol and stroke in eastern Asia. Eastern Stroke and Coronary Heart Disease Collaborative Research Group. Lancet. 1998; 532: 1801–1807.
6. He J, Klang MJ, Caballero B, Appel LJ, Charleston J, Whelton PK. Plasma insulin levels and incidence of hypertension in African Americans and whites. Arch Intern Med. 1999; 159: 498–503.
7. Lewington S, MacMahon S. Blood pressure, cholesterol and common causes of death: a review. Prospective studies collaboration. Am J Hypertens. 1999; 12: 96S–98S.[Medline] [Order article via Infotrieve]
8. Grimsgaard S, Bonaa KH, Jacobsen BK, Bjerve KS. Plasma saturated and linoleic fatty acids are independently associated with blood pressure. Hypertension. 1999; 34: 478–483.
9. Stamler J, Daviglus ML, Garside DB, Dyer AR, Greenland P, Neaton JD. Relationship of baseline serum cholesterol levels in 3 large cohorts of younger men to long-term coronary, cardiovascular and all-cause mortality and longevity. J Am Med Assoc. 2000; 284: 311–318.
10. Facchini FS, Hua N, Abbasi F, Reaven GM. Insulin resistance as a predictor of age-related diseases. J Clin Endocrinol Metab. 2001; 86: 3574–3578.
11. Goff DC, Zaccaro DJ, Haffner SM, Saad MF. Insulin Resistance Atherosclerosis Study. Insulin sensitivity and the risk of incident hypertension: insights from the Insulin Resistance Atherosclerosis Study. Diabetes Care. 2003; 26: 805–809.
12. Meigs JB, Nathan DM, D’Agostino RB, Wilson PW. Framingham Offspring Study. Fasting and postchallenge glycemia and cardiovascular disease risk: the Framingham Offspring Study. Diabetes Care. 2002; 25: 1845–1850.
13. Mancia G, Sega R, Bravi C, De Vito G, Valagussa F, Cesana G, Zanchetti A. Ambulatory blood pressure normality: results from the PAMELA study. J Hypertens. 1995; 13: 1377–1390.[Medline] [Order article via Infotrieve]
14. Mancia G, Bertinieri G, Grassi G, Parati G, Pomidossi G, Ferrari A, Gregorini C, Zanchetti A. Effects of blood pressure measurement by the doctor on patient’s blood pressure and heart rate. Lancet. 1983; 24: 695–698.
15. Mancia G, Parati G, Omboni S, Ulian L, Zanchetti A. Ambulatory blood pressure monitoring. Clin Exp Hypertens. 1999; 21: 703–715.[Medline] [Order article via Infotrieve]
16. WHO-MONICA Project Principal Investigators. The World Health Organization Monica Project: a major international collaboration. J Clin Epidemiol. 1988; 41: 105–114.[CrossRef][Medline] [Order article via Infotrieve]
17. Gruppo di Ricerca Area Brianza Progetto Monica "Area Brianza." Distribuzione dei fattori di rischio coronarico. G Ital Cardiol. 1998; 18: 1034–1044.
18. Groppelli A, Omboni S, Parati G, Mancia G. Evaluation of non-invasive monitoring devices Spacelabs 90202 and 90207 versus resting and ambulatory 24 hour intraarterial blood pressure. Hypertension. 1992; 20: 227–232.
19. Guidelines Committee. 2003 European Society of Hypertension-European Society guidelines for the management of arterial hypertension. J Hypertens. 2003; 21: 1011–1053.[CrossRef][Medline] [Order article via Infotrieve]
20. Mancia G, Parati G, Pomidossi G, Grassi G, Casadei R, Zanchetti A. Alerting reaction and rise in blood pressure during measurement by physician and nurse. Hypertension. 1987; 9: 209–215.
21. Grassi G, Turri C, Vailati S, Dell’Oro R, Mancia G. Muscle and skin sympathetic nerve traffic during the "white-coat" effect. Circulation. 1999; 100: 222–225.
22. Jamerson KA, Julius S, Gudbrandsson T, Andersson O, Brant DO. Reflex sympathetic activation induces acute insulin resistance in the human forearm. Hypertension. 1993; 21: 618–623.
23. Gerich JE. Control of glycaemia. Baillieres Clin Endocrinol Metab. 1993; 7: 551–586.[CrossRef][Medline] [Order article via Infotrieve]
24. Brook RD, Julius S. Autonomic imbalance, hypertension and cardiovascular risk. Am J Hypertens. 2000; 13: 112S–122S[Medline] [Order article via Infotrieve]
25. Hoieggen A, Fossum E, Moan A, Rostrup M, Eide IK, Kjeldsen SE. Biphasic effect of epinephrine on blood glucose during hyperinsulinemia in borderline hypertensive young men. Am J Hypertens. 2001; 14: 539–545.[Medline] [Order article via Infotrieve]
26. Parati G, Pomidossi G, Casadei R, Malaspina D, Colombo A, Ravogli A, Mancia G. Lack of alerting reaction to intermittent cuff inflations during non-invasive blood pressure monitoring. Hypertension. 1985; 7: 597–601.
27. Palatini P, Julius S. Heart rate and the cardiovascular risk. J Hypertens. 1997; 15: 3–17.[CrossRef][Medline] [Order article via Infotrieve]
28. Grassi G, Vailati S, Bertinieri G, Seravalle G, Stella ML, Dell’Oro R, Mancia G. Heart rate as marker of sympathetic activity. J Hypertens. 1998; 16: 1635–1639.[CrossRef][Medline] [Order article via Infotrieve]
29. Lund-Johansen P. Newer thinking on the hemodynamics of hypertension. Curr Opin Cardiol. 1994; 9: 505–511.[Medline] [Order article via Infotrieve]
30. Baron AD, Brechtel-Hook G, Johnson A. Effect of perfusion rate on the time course of insulin-mediated skeletal muscle glucose uptake. Am J Physiol. 1996; 271: E1067–E1072.[Medline] [Order article via Infotrieve]
31. Noogaki K. New insight into sympathetic regulation of glucose and fat metabolism. Diabetologia. 2000; 43: 533–549.[CrossRef][Medline] [Order article via Infotrieve]
32. Hall JE, Brands MW, Zappe DH, Alonso-Galicia M. Cardiovascular actions of insulin: are they important in long-term blood pressure regulation? Clin Exp Pharmacol Physiol. 1995; 22: 689–700.[Medline] [Order article via Infotrieve]
33. Reaven GM, Lithell H, Landsberg L. Hypertension and associated metabolic abnormalities: the role of insulin resistance and the sympathoadrenal system. N Engl J Med. 1996; 334: 374–381.
This article has been cited by other articles:
 |
|
 |
|
  A. Leibowitz and E. Grossman How to Define Prehypertension in Diabetes/Metabolic Syndrome Diabetes Care, November 1, 2009; 32(suppl_2): S275 - S279. [Full Text] [PDF]
|
|
|
|
|
|
M. Bursztyn and I. Z. Ben-Dov White-Coat Hypertension Should Not Be Treated in Subjects With Diabetes Diabetes Care, November 1, 2009; 32(suppl_2): S310 - S313. [Full Text] [PDF]
|
|
|
|
 |
|
 T. W. Hansen, L. Thijs, J. Boggia, Y. Li, M. Kikuya, K. Bjorklund-Bodegard, T. Richart, T. Ohkubo, J. Jeppesen, C. Torp-Pedersen, et al. Prognostic Value of Ambulatory Heart Rate Revisited in 6928 Subjects From 6 Populations Hypertension, August 1, 2008; 52(2): 229 - 235. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Authors/Task Force Members:, G. Mancia, G. De Backer, A. Dominiczak, R. Cifkova, R. Fagard, G. Germano, G. Grassi, A. M. Heagerty, S. E. Kjeldsen, et al. 2007 Guidelines for the Management of Arterial Hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC) Eur. Heart J., June 11, 2007; (2007) ehm236v1. [Full Text] [PDF]
|
|
|
|
|
|
G. Mancia, R. Facchetti, M. Bombelli, G. Grassi, and R. Sega Long-Term Risk of Mortality Associated With Selective and Combined Elevation in Office, Home, and Ambulatory Blood Pressure Hypertension, May 1, 2006; 47(5): 846 - 853. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Bursztyn Out-of-Office Blood Pressure Measurement: A New Era Hypertension, June 1, 2005; 45(6): 1070 - 1071. [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||