S. Majahalme et al., BLOOD-PRESSURE LEVELS AND VARIABILITY, SMOKING, AND LEFT-VENTRICULAR STRUCTURE IN NORMOTENSION AND IN BORDERLINE AND MILD HYPERTENSION, American journal of hypertension, 9(11), 1996, pp. 1110-1118
The aims of this study were to determine the importance of ambulatory
blood pressure measurement, diurnal blood pressure (BP) profile, and v
ariability in the evaluation of left ventricular (LV) parameters, and
the impact of smoking on these factors. We performed intraarterial amb
ulatory BP (IAMB) recording and echocardiography in 80 healthy, unmedi
cated men aged 35 to 45 years. Based on repeated casual (GAS) readings
before the study, the subjects were classified as normotensive (NT, n
= 32), borderline hypertensive (BHT, n = 21), or mildly hypertensive
(HT, n = 27) according to WHO criteria. There were 19 (8 NT/5 BHT/6 HT
) smokers and 48 (18 NT/13 BHT/17 HT) nonsmokers. Both BHT and HT had
significantly greater LV mass index (LVMI) than NT, but LVMI did not d
iffer between nonsmokers and smokers. For the whole group, 24-h BP cor
related somewhat better with LVMI than CAS BP (24-h IAMB SEP r = 0.44,
P < .001, DBP r = 0.36, P < .001, and CAS SEP r = 0.35, P < .01, DBP
r = 0.37, P < .001). Casual SEP alone explained 12% of LVMI variance (
F = 10.7, P < .01), whereas 24-h IAMB SEP alone explained 19% of LVMI
variance (F = 18.4, P < .001). When comparing day and night SEP and DB
P levels, night SEP showed the closest correlation with LVMI (r = 0.43
, P < .001), and this alone explained 18% of LVMI variance (F = 18.1,
P < .001). Smokers had higher correlations between night BP and LVMI (
SBP and DBP r = 0.56, P < .05) than nonsmokers (SEP r = 0.37, P < .01
and DBP r = 0.30, P < .05). In a multiple linear regression including
all BP variables, for smokers, night DBP (although only marginally bet
ter than night SEP) was the best predictor, explaining 32% of LVMI var
iance (F = 10.6, P < .01) and additionally night DBP standard deviatio
n (SD) added 18% to the prediction of LVMI (F = 5.8, P < .05). For non
smokers, day SEP had closest correlation with LVMI (r = .43, P < .01),
but explained only 19% of LVMI variance (F = 10.5, P < .01), and othe
r measures did not increase the explanation. We conclude that ambulato
ry BP was slightly better than CAS BP in predicting LVMI, but BP level
, also when measured with the best method available, explained only a
moderate fraction of LVMI variance in mild hypertension. However, amon
g smokers, BP, especially nighttime and BP variability, explained LV c
hanges better than among nonsmokers. Thus smoking may have an impact o
n the interaction of ambulatory BP and LVMI, and in future studies mor
e attention should be paid to this toxic factor.