Table Table11 summarises the characteristics of the patient population of 1949 men and 728 women. Our patients were obese, middle aged males with mild to moderate sleep apnoea, and there was wide
scatter in all variables.
Anthropometric, sleep, and blood pressure data in 2677 adults attending sleep clinic
To show how blood pressure levels vary with apnoea we divided our population into four groups: non-apnoeic controls (apnoea-hypopnoea index 10 or less), mild apnoea (greater than 10 and less than 31), moderate apnoea (greater than 30 and less than 51), and severe apnoea (greater than 50). Table Table22 shows that unadjusted systolic and diastolic blood pressures increased with the apnoea-hypopnoea index. Trend analysis, however, showed that the important confounding factors, such as
percentage of males, age, obesity (as reflected by body mass index, neck circumference, and waist to hip ratio), and smoking history also significantly increased with the apnoea-hypopnoea index (all P<0.0001).
Changes in blood pressure and other confounding factors with severity of apnoea. Values are mean (SD) unless stated otherwise
We used the Cochran-Armitage trend test8
to test for linearity in percentage of males, hypertension, and antihypertensive use.
Multiple regression analysis—We performed multiple linear regression in 1865 patients not taking antihypertensives (table (table3).3). This showed that the apnoea-hypopnoea index was significantly related to diastolic and systolic blood pressure after adjustment for age and sex. Age and sex were significant covariates, but there was no interaction between the apnoea-hypopnoea index and age or sex. Smoking was only borderline statistically significant for the diastolic blood pressure, and therefore it was not included in further analysis. Stepwise linear regression, with the apnoea-hypopnoea index, age, and sex forced in the model, indicated that neck circumference (over body mass index, waist or hip circumference, and waist to hip ratio) was the most influential body habitus variable. When neck circumference was added to age and sex, the apnoea-hypopnoea index was still significantly related to diastolic and systolic blood pressures (adjusted R2 21.9% and 19.6% respectively). No interaction occurred between neck circumference and the apnoea-hypopnoea index. Under the conditions of the model, the β coefficient for the apnoea-hypopnoea index indicates an increase of 0.10 and 0.04 mm Hg
in systolic and diastolic blood pressures respectively for each additional apnoeic event per hour of sleep. The model predicts, for example, that the mean (SD) morning blood pressure readings will be 6 (1.2) mm Hg (systolic) and 4.7 (1.0) mm Hg (diastolic) higher for severe sleep related breathing disorders (apnoea-hypopnoea index 60) versus no sleep related breathing disorders. The same results were found when the analysis was repeated with the lowest nocturnal oxygen saturation.
Multiple linear regression models for blood pressure measurements only in patients not taking antihypertensive drugs (n=1865)
Multiple logistic regression—To evaluate the effect of the apnoea-hypopnoea index, we performed a
multiple logistic regression model of sleep related breathing disorders and hypertension with terms for the apnoea-hypopnoea index, sex, age, body mass index, and an interaction for body mass index and apnoea-hypopnoea index. This indicated that an increase in 10 apnoeic events per hour of sleep increased the risk of having hypertension by about 11.0% (β coefficient 0.011, table
fig1).1). A similar analysis replacing the apnoea-hypopnoea index with oxygen saturation nadir showed that each 10% decrease in saturation nadir increased the risk of having hypertension by about 13% (0.013; table table55 and fig fig2).2). Using percentage of time spent asleep below 90% oxygen saturation instead of nadir did not improve upon these results.
Odds ratios for apnoea-hypopnoea index, body mass index, sex, age, and hypertension
Odds ratios and Wald 95% confidence intervals for hypertension associated with apnoea-hypopnoea index level of 5, 15, 30, 40, 50, 60, and 70 predicted by best fitting multiple logistic model: T=e.012apnoea-hypopnoea index+.081age+.161male+.067body
Odds ratios for nadir in nocturnal oxygenation, body mass index, sex, age, and hypertension
Odds ratios and Wald 95% confidence intervals for hypertension associated with oxygen saturation nadir levels of 90%, 80%, 70%, 60%, 50%, and 40% predicted by model hypertension=e-.0133nadir+.081age+.265male+.072body