sleep apnea and hypertension.doc.doc

BMI 546 Gangnon July 2, 2010

BMI 546 –PRACTICUM IN DATA ANALYSIS AND INTERPRETATION

EXERCISE: STUDY DESIGNS AND INTERPRETATION: SLEEP APNEA AND HYPERTENSION

Objectives

In this exercise, you will be introduced to a broad spectrum of study designs in clinical and epidemiologic investigation. In particular, you will evaluate the advantages and disadvantages of different study designs and the measures of risk and association used in such studies. You will also learn how to assess whether an observed association is likely to be causal and how to deal with the concept of confounding.

After completing this Exercise, students will be able to:

1. Understand design features, strengths and limitations of different study designs in clinical epidemiologic investigation.

2. Calculate the different measures of risk and association used in epidemiologic studies.

3. Understand sources of bias in observational and experimental studies.

4. Understand the concept of confounding and a way to address this.

The specific area of research that is used to illustrate these issues and concepts is the hypothesized association between sleep apnea and hypertension. This is an area of increasing concern because of the potentially large clinical and public health significance of such an association, should it be proven to be causal. It is important to note, however, that research in this area has evolved only recently (in the last 30 years or so) and that some of the implications of this research remain controversial still today.

The specific studies used to illustrate the different study designs options in this exercise were picked based on convenience (type of data fitting the specific concept that was to be illustrated) and also because they follow a chronological sequence more or less parallel to the evolution of the rationale supporting the hypothesis. These studies, however, do not necessarily represent the “best” or most representative studies in this area.

The following section provides a brief description of the pathophysiology of sleep apnea.

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PART 1 : Background

Sleep apnea (aka “Sleep Disorder Breathing” or “SDB”) is the common term for a spectrum of disorders characterized by repeated breathing pauses during sleep. The main clinical manifestations of this syndrome are snoring and excessive daytime sleepiness. The breathing pauses may be complete (no air flow, apnea) or partial (reduced airflow, hypopnea). The most common form of this syndrome, known as “obstructive sleep apnea” (or “OSA”) is caused by increased resistance and partial or total collapse of the upper airway due to loss of tone in the pharyngeal muscles. The vulnerability to collapse may be due to increased fat deposition in the neck, but the mechanism is not known. A less common form of the syndrome, “central sleep apnea,” results from lack of brain signal to respiratory muscles usually secondary to other disorders with neurological damage, such as stroke. This exercise will focus on obstructive sleep apnea, a disorder we now know to be quite prevalent (but often undiagnosed) in the general population, particularly among overweight persons (see below). Appendix 1 contains a recent review article (1) describing the epidemiology and pathophysiology of obstructive sleep apnea. A brief summary follows. Pathophysiology of obstructive sleep apnea

With the onset of sleep, there is a relaxation of the tone of the upper airway. This happens in everyone, but in some people, the upper airway develops more compliance (becomes "floppy"), and as air is drawn through the airway in trying to breathe, resistance increases. This makes the airway vulnerable to collapse. (Think of trying to drink water through a floppy straw-the harder you try, the more the straw collapses.) During an apnea, the respiratory muscles work harder and harder, to increase the force in trying to breathe against a closed airway, resulting in an even more tightly collapsed airway; the resulting sound of air going through a collapsing airway is heard as snoring.

Significant breathing pauses (apnea or hypopnea) are those lasting 10 seconds or more and result in a number of profound physiologic changes that can be assessed using polysomnography (PSG). PSG is a multiple channel recording of the patient’s sleep that includes measures of brain and muscle activity (to characterize sleep stage), electrocardiogram, breathing (air flow and respiratory movements), blood pressure, and blood oxygen levels (see figure 2 in Appendix 1). One immediate consequence of the breathing pause is a momentary drop in blood oxygen levels (hypoxemia or hypoxia). This drop in blood oxygen saturation may be just a few percentage points (e.g., 98% to 94%) or might go as low as 60%. This hypoxia is detected by physiological sensors (chemoreceptors and baroreceptors) that signal an alarm to the brain—here is a choice between sleeping and breathing: the result is a brief arousal from sleep, during which time the awake tone of the airway returns, and clears the apnea. Usually, the person is not even aware of the arousal, and goes back to sleep only to go on and have another apnea, arousal, apnea, and on and on. With each event, there is an increase in sympathetic nerve activity, and this too has consequences. There are fluctuations in heart rate and rhythm, and blood pressure drops and then spikes as much as 120 mm Hg.

One consequence of the sleep arousal is that it fragments the continuity of sleep. The arousals disturb the normal pattern of going from light to deeper sleep and rapid eye movement (REM)

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sleep, in a few orderly cycles, over the night. When these arousals occur frequently over the course of the night (i.e., in cases of severe OSA) the affected person is never able to go into deep sleep. This may cause extreme daytime sleepiness, and the inability to fight off drowsiness and unwanted sleep. In addition, when these events occur several times an hour, night after night, the continuous burst of sympathetic activity and resulting hemodynamic and cardiopulmonary consequences are likely to have adverse effects that may impair daytime or overall health.

Clinical diagnosis and basic epidemiology of OSA

A common metric of the severity of sleep apnea is the average number of pauses per hour of sleep (known as the apnea-hypopnea index, or AHI) and is clinically assessed using a PSG exam. The number of breathing pauses may range from zero to >100 per hour of sleep. The occurrence of occasional apneas/hypopneas is considered normal, but an average of >5 per hour is usually considered physiological evidence of sleep apnea. AHI>15 and AHI>30 are cut-points used to define the presence of moderate or severe sleep apnea, respectively.

OSA was considered a rare disorder until fairly recently. Since the breathing pauses occurred during sleep, struggles to breath were usually not noticed—and snoring or daytime sleepiness were not considered signs of a disorder, but rather something to joke about. Thus, only severe cases were seen, and treatment was tracheotomy (certainly an unpopular treatment!). This all changed in 1982 with the invention of nasal continuous positive air pressure (nCPAP)—a nasal mask that delivers pressurized room air and keeps the airway open during sleep. When an effective and acceptable treatment became available, clinicians were more likely to look for OSA in their patients, and the National Institutes of Health became more interested in finding out more about the burden of OSA in the population.

The first large population study was begun in 1987, the Wisconsin Sleep Cohort. The study was designed to take a random sample of the population, and bring them into a sleep laboratory for a PSG exam and repeat this every four years. In this way, the prevalence could be estimated at baseline, and over time, incidence could be determined. With the longitudinal data, people with and without OSA could be followed to compare the incidence of health consequences. One of the first findings, published in 1993 in the New England Journal of Medicine (2), was that contrary to belief, OSA was quite prevalent in adults, and there was a wide severity spectrum. Most importantly, only a small (<7%) of cases had ever been diagnosed—leaving 93% of the total burden undiagnosed. The study showed that 4% of women and 9% of men had an AHI of 15 or greater. The significant proportion of women with OSA was even more unexpected than the overall prevalence. In clinics, the ratio of men to women with OSA was 9:1, but in the population, the ratio was about 2:1, showing that there was selection bias for men to be diagnosed with OSA.

Studies over the past few decades have identified some risk factors, such as aging, male gender, overweight, abnormal facial structure, and nasal congestion. Importantly, clinical and epidemiologic studies have shown that OSA is likely to have significant health consequences such as behavioral morbidity associated with cognitive impairment and excessive sleepiness: depression, occupational injuries, automobile crashes, as well as cardio- and cerebro-vascular disorders. The latter includes hypertension, the subject of this exercise.

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PART 2 : Early clinical observations

Reports concerning breathing disorders during sleep are remarkably absent from the medical literature up to around the beginning of the 1970s. One of the cardinal, but non-specific, symptoms of the syndrome, snoring, was at the time not considered a medical problem but rather an annoyance to bed partners and other family members of the affected persons. The other main symptom, excessive daytime sleepiness, was often perceived as a sign of “laziness.” As a result, patients with this disorder were not only undiagnosed and untreated, but often laughed at and constantly embarrassed; the sleepiness tendency was often associated with mood disturbances that frequently resulted in a diagnosis of “depression” with patients sustaining anti-depressive treatments for the rest of their lives.

In the late 1960s and early 1970s, and thanks in part to the development of polysomography (PSG) techniques (see Appendix A), a few clinical observations were published that described some of the profound psychological and physiological disturbances associated with this yet unrecognized syndrome.

Guilleminault et al: Arch Intern Med 1977

Among these early publications, Christian Guilleminault and co-authors from Stanford University, published a paper in Archives of Internal Medicine in 1977 describing the clinical features of 25 patients with “sleep apnea syndrome” (3). These patients were referred to the Sleep Disorders Clinic for either excessive daytime sleepiness or combination of loud snoring with hypertension, headaches, or abnormal behavior during sleep. All patients were male with age ranging from 25 to 65 years (mean 44.3 years) and a PSG exam determined that they all suffered from “obstructive” sleep apnea.

Using the 1959 Metropolitan Life Insurance Company statistical tables to standardize by age and height, the weight distribution of these patients was as follows:

Table 1 – Distribution of relative weight categories of sleep apnea patients (n=25) according to 1959 Metropolitan Live Insurance Company standards; Guilleminault et al, 1977Weight category NumberNormal5% to 15% Overweight16% to 39% Overweight40% to 100% Overweight

5 (20%)4 (16%)8 (32%)8 (32%)

The following were among the symptoms and signs reported in the manuscript:

- Loud snoring (occasionally interrupted by silences of 20 seconds or longer)- Excessive daytime sleepiness (sudden, excessive drowsiness at inappropriate times of day)- Personality changes (including depression, anxiety, irritability, hostility, as reported by

family members)- Morning headaches (frontal and occasionally diffuse)

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- Hypertension (systolic blood pressure higher than 150 mm Hg or diastolic blood pressure higher than 95 mm Hg)

Table 2 presents the occurrence of each of these clinical characteristics (with ‘+’ indicating presence and ‘–’ indicating absence) in the 25 patients, as reported in the manuscript.

Table 2 – Symptoms in sleep apnea patients (n=25); Guilleminault et al, 1977

Patient SnoringExcessive sleepiness

Personality changes

Morning headaches Hypertension

12345678910111213141516171819202122232425

+++++++++++++++++++++++++

++++++++++++++++++--++--+

++++++++++++++-----+-+---

++---+-+--+++-++--++-----

+++++---++____+++++-+-+--

Question 1: Calculate the estimated prevalence of each of these five clinical characteristics in this patient population. Find a 95% confidence interval for the true population prevalence of each of these five clinical characteristics based on these data.

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Question 2: The prevalence of hypertension in the general adult (18-74) male U.S. population based on the 1976-1980 National Health and Nutrition Examination Study was 33%. How does the prevalence of hypertension in these patients with sleep apnea compare to the prevalence in the general population?

Question 3. Would you conclude from these data that an association exists between sleep apnea and hypertension? Why or why not?

In the “Comments” section of the manuscript, Guilleminault et al wrote “Our Sleep Disorders Clinic has an obvious bias because most patients are referred for a ‘sleep disorder’.”

Question 4: What do you think the authors are referring to with this statement? What other types of bias may have affected these data?

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Guilleminault et al conclude their manuscript describing the diverse therapeutic interventions in these 25 patients, including diet, medications, and surgery; 5 patients refused treatment. Surgical treatment included adenoidectomy, resection of part of the soft palate or, most frequently (8 cases), tracheostomy and positioning of a permanent tracheal valve. The latter was reported as the most effective treatment in this series.

Lavie et al: Am Heart J 1984

In a subsequent study conducted in Israel, Lavie et al examined the prevalence of sleep apnea among patients with hypertension (4). The series included 50 patients (10 women and 40 men) attending Ramban University Hospital outpatient hypertension clinic that were diagnosed with “essential hypertension” (blood pressure >160 mm Hg systolic and 95 mm Hg diastolic with no known cause of hypertension). According to the authors, “all patients approached agreed to be interviewed; this precludes the possibility that the sample of 50 patients included a disproportionate number of patients with more severe sleep disorders, who expected some benefits from the sleep recordings.”

Question 5: What kind of bias are the authors concerned about? Do you agree that the 100% participation eliminates such bias?

Among the 50 patients that were interviewed, 16 (12 men and 4 women) were selected for a PSG examination based on the presence of at least three of the following complaints: 1) excessive daytime sleepiness; 2) loud snoring; 3) excessive motility in sleep; 4) multiple awakenings from sleep; 5) frequent headaches; and 6) chronic fatigue. Sleep apnea was diagnosed based on the “apnea index (AI),”* the average number of apneas (lasting more than 10 seconds) per hour of sleep.

Among the 16 patients who underwent PSG examination, the mean AI was 21.6 (SD, 18.4). Thirteen of the 16 patients had AI>5, 11 patients had AI>10, and 8 patients had AI>30. In the Discussion section of the paper (page 375), the authors state that the estimated prevalence of

* In the early years of research on this subject, hypopneas were often not considered and thus the Apnea Index was commonly used instead of the previously described Apnea-Hypopnea Index.

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sleep apnea (defined as AI>5) “is 26% of the initial sample of 50 patients [which] is considerably higher than the estimate of 1.26% of sleep apnea syndrome in men older than 21.”

Question 6: How was the 26% estimate calculated? Do you think this represents an accurate estimate of the prevalence of sleep apnea among hypertensives? Why or why not?

Question 7: Find a 95% confidence interval for the prevalence of sleep apnea among hypertensives. How does the prevalence of sleep apnea among hypertensives compare to the prevalence in the general population?

Question 8: Do these results help you conclude that sleep apnea and hypertension are associated? Why or why not?

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PART 3 : Observational epidemiologic evidence

More rigorous observational studies on this topic were published between the mid 1980s and the 1990s. These studies varied widely in terms of study population and study design. This section describes some salient results emerging from a few of these studies.

Norton and Dunn: Br Med J 1985

In a study conducted in four family practices in Toronto, Canada (5), 2001 subjects visiting these practices (about 85% of those approached) agreed to respond to a questionnaire that included basic demographic data about themselves and questions on snoring and medical conditions in members of their households. The definition of snoring was “a general one of noise produced while sleeping, but it was left to the reporters to interpret this as they saw fit.” Medical records were not reviewed. The 2001 reporters (691 of whom were men) provided data on a total of 2,629 subjects (1,411 men, 1,211 women, and seven with no recorded gender); the prevalence of snoring in this group was 42%. Table 3 displays the reported prevalence of several medical conditions and characteristics according to snoring history.

Table 3 – Demographic characteristics and medical conditions according to snoring (values are percentages); Norton & Dunn, 1985

Condition All Non-snorersOccasional

snorers

Those who snore nearly every night

Those who snore every

night(n=2629) (n=1379) (n=638) (n=213) (n=254)

Male sexOverweightSmoking

DepressionAsthmaDiabetes

Heart diseaseHypertension

53.77.217.9

0.82.91.5

4.26.2

45.42.310.3

0.22.00.8

1.72.3

64.28.924.0

1.35.02.0

5.58.8

69.016.932.9

2.83.82.3

9.912.2

73.222.833.9

2.02.03.5

11.818.5

Question 7: Using ‘non-snorers’ as the reference category, calculate the prevalence odds ratio of hypertension and associated 95% confidence interval for each of the other snoring categories. Describe and interpret your findings. (Please, comment on how the prevalence varies according to increasing snoring frequency.)

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Question 8: Describe the main limitations of the preceding analysis.

Because the above conditions occur more frequently in older individuals, Norton & Dunn also conducted analyses restricted to individuals older than 40 years of age. The following table displays results from more detailed analysis of hypertension prevalence in this older group.

Table 4 – Prevalence of hypertension (in %) in study participants ≥40 years old according to snoring, stratified by gender, age and other characteristics; Norton & Dunn, 1985

Men WomenSnorers Non-snorers Snorers Non-snorers

Age 40-49 y 50-59 y 60-69 y 70-79 y 80-89 y

Non-smokers, non-obeseSmokers (non-obese)Obese (non-smokers)Smokers and obese

722282712

19152935

013141311

811120

1210154040

20103933

01272940

737220

Question 9: Why do you think the authors showed these stratified data?

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Question 10: Calculate the prevalence odds ratio for hypertension within each strata. Are the prevalence odds ratios consistent across strata? Is there any additional information that you would need to answer this question more definitively?

Question 11: Was this a representative sample of the population? Why or why not? Is it essential for the purpose of the study that the sample be a fully representative one? Why or why not?

Question 12: Compared to the studies described in the preceding section, what features of this study add to the evaluation of a possible association between sleep apnea and hypertension? What are the main limitations affecting the conclusions from this study?

Fletcher et al: Ann Intern Med 1985

In another study conducted at the Houston Veterans Administration Medical Center, Fletcher et al examined the prevalence of undiagnosed sleep apnea in patients with essential hypertension and controls (6). The study population consisted of 46 men with essential hypertension (systolic blood pressure >140 mm Hg, or diastolic >90 mm Hg if age <45 years and >95 mm Hg if age >45 years, with no identifiable renal or endocrine abnormalities) and 34 normotensive men as controls. Sleep apnea was defined as more than 10 apneas per hour of sleep measured by PSG.

Hypertensive men were recruited from the hypertension, medical, and dermatologic clinics and from hospital employees; normotensive controls consisted of outpatients with minor dermatologic problems or healthy hospital employees. According to the authors, “men were

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selected without bias to physical habitus, except that efforts were made to recruit control and hypertensive persons of equivalent age and weight.”

Question 13: What type of study design was this? Why were the investigators concerned about age and weight? Were these concerns properly addressed?

The following table presents a comparison of characteristics of hypertensive patients and controls.

Table 5 – Comparison of characteristics of hypertensive patients and controls; Fletcher et al, 1985*

Controls Hypertensives P-Value

Number

Age, yearsPercentage of ideal body weightApnea index

34

52.4±1.5111.9±3.03.3±0.7

46

53.9±1.2117.2±3.910.0±2.3

* Values are mean and standard error.

Question 14: Calculate p-values for the comparisons of age, percentage of ideal body weight and apnea index between controls and hypertensives. Interpret the results..

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Figure 1 represents the apnea index in the 46 hypertensive and 34 control patients as presented in the published paper.

Question 15: Based on the data shown in figure 1, calculate the odds ratio of sleep apnea comparing hypertensive patients and controls along with the associated confidence interval.

Figure 1 -- Number of apneas per hour of sleep for hypertensive subjects (n=46) and controls (n=34). Horizontal line at 10 indicates the level above which the person is considered to have sleep apnea. Different bullet shapes in the hypertension group indicates the type of antihypertensive regiment in each patient.

Based on these observations, Fletcher et al concluded that “undiagnosed sleep apnea syndrome may be associated with systemic hypertension in many middle- and older-aged men. In some, sleep apnea syndrome could be the cause of hypertension, and in others it may contribute to hypertension of another cause.”

Question 16: How does this study add to the evaluation of a possible association between sleep apnea and hypertension? Are you persuaded by the authors’ conclusions regarding “causality”? What are the limitations affecting the conclusions from this study?

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Nieto et al: JAMA 2000

The Sleep Heart Health Study (SHHS) conducted a PSG exam in participants in several ongoing federally-funded cohort studies of cardiovascular disease (7). Participants in these cohort studies had been recruited from the community in 10 field centers across the US and had been subject to extensive evaluation of cardiovascular risk factors, including repeat blood pressure measurements. A total of 6,123 members of these cohorts underwent a full unattended overnight PSG exam in their home using a portable PSG monitor. Based on theses recordings, sleep apnea was defined based on the average number of apneas or hypopneas (partial apnea) per hour of sleep (the Apnea-Hypopnea Index, AHI). Table 6 presents the number of SHHS participants in a cross-tabulation of AHI and hypertension categories (hypertension defined based as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or use of antihypertensive medication, at the cohort exam closest to the time when the PSG exam was done.

Question 17: What type of study design was this?

Table 6 – Hypertension according to apnea-hypopnea index (AHI) categories, the Sleep Heart Health Study; Nieto et al, 2000

AHI*Hypertension*

Odds ratioYes No

<1.5 738 953 1.0 (Reference)

1.5-4.9 835 763 _________

5.0-14.9 1051 700 _________

15-29.9 451 268 _________

≥30 254 119 _________

*See text for definitions.

Question 18: Using the lowest AHI category (<1.5) as reference for comparison, calculate the odds ratio of hypertension for all the other categories along with the corresponding 95% confidence intervals.

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There are several different definitions for “confounding.” Generally it occurs when a variable, related to the exposures and outcome of interest in an observational study, is not properly accounted for (by statistical adjustment, stratification or matching), thus leading to an incorrect association to be measured between exposure and outcome. Empirically, confounding is detected when, after adjusting for a potentially confounding variable, the association (odds ratio, relative risk, correlation, etc.) between exposure and outcome substantially changes (e.g. the association is attenuated). Table 7 shows the odds ratio of hypertension adjusting for demographic characteristics (age, sex, and race) as well as body mass index (BMI)† as reported in the original manuscript (7).

Table 7 – Crude and adjusted odds ratio of hypertension according to apnea-hypopnea index (AHI) categories, the Sleep Heart Health Study; Nieto et al, 2000

*See text for definitions.

Question 19: Place the odds ratios you calculated in the previous question in the first column of Table 7. Compare these odds ratios with the adjusted odds ratios in the other two columns. Interpret the differences you observe.

† Body mass index (BMI): a measure of body weight relative to height, calculated as the ratio of weight (in kilograms) divided by the square of height (in meters). BMI≥25 is usually considered to indicate “overweight;” a BMI≥30 is used to define “obesity.”

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AHI*Odds ratio of Hypertension*

Unadjusted (from previous table)

Adjusted for age, sex, and race

Adjusted for age, sex, race, and BMI*

<1.5 1.0 (Reference) 1.0 (Reference) 1.0 (Reference)

1.5-4.9 _________ 1.25 1.12

5.0-14.9 _________ 1.57 1.28

15-29.9 _________ 1.73 1.32

≥30 _________ 2.27 1.60


Question 20: What are the potential strengths of this study as compared with the previous ones? What are its main limitations?

Peppard et al: N Engl J Med 2000

The Wisconsin Sleep Cohort Study is an ongoing prospective study of the occurrence, causes and consequences of sleep disorders (particularly sleep apnea) run by Professor Terry Young of the UW School of Medicine and Public Health. The study follows >1000 men and women selected from a working population in the late 1980s when participants were between 30 and 60 years old. Measures of PSG (attended, in-laboratory), blood pressure (average of three seated blood pressure readings), body habitus, and a variety of health history and behavior data are assessed at 4-year intervals. Peppard et al (8), described the results of analyses that examined the association of sleep apnea at baseline studies and the subsequent risk of developing hypertension 4 years later. Table 8 summarizes the findings:

Table 8 – Hypertension status at 4-year follow-up by baseline sleep apnea category among 515 baseline normotensives; the Wisconsin Sleep Cohort Study, Peppard et al, 2000Baseline sleep apnea category

Normotensive at 4-year follow-up

Hypertensive at 4-year follow-up

Risk of hypertension

at 4-year follow-up

AbsoluteRisk

Difference

RelativeRisk

Odds Ratio

AHI=0121 15

______ 0.0 (ref.) 1.0 (ref.) 1.0 (ref.)

0<AHI<5260 48

______ _______ ______ ______

5<AHI<1537 18

______ _______ ______ ______

AHI>15 11 6 ______ _______ ______ ______

Question 21: Calculate the risk of developing hypertension at 4-year follow-up for each baseline sleep apnea category. Then, calculate the absolute risk difference, the relative risk and the odds ratios of developing hypertension for each of the 3 higher sleep apnea categories relative to participants with baseline AHI=0. Write your results in Table 8.

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Because of the potential for confounding, analyses controlling for additional variables were conducted. The results are shown in table 9.

Table 9 – Relative risks for baseline sleep apnea category predicting hypertension at 4-year follow-up; potential confounding factors (“adjustment variables”) are progressively added to the model; the Wisconsin Sleep Cohort Study, Peppard et al, 2000

Adjustment variables (cumulative)

Age and sexAge, sex, and body

habitus (BMI, neck & waist girth)

Age, sex, body habitus, alcohol &

smoking habitsSleep apnea category Relative Risk Relative Risk Relative Risk

AHI=0 1.0 (ref.) 1.0 (ref.) 1.0 (ref.) 0<AHI<5 1.6 1.3 1.35≥AHI<15 2.5 1.7 1.7AHI≥15 3.9 2.3 2.3

P value for trend 0.001 0.03 0.03

Question 22: Examining the results in Table 8, after adjusting for age and sex, which additional adjustment variables (body habitus—BMI, waist & neck girth; or alcohol/cigarette use habits) most clearly confound the association between sleep apnea and hypertension? How do you know?

Question 23: How do the findings from Peppard et al (2000) affect your judgment of the association of sleep apnea and hypertension?

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References

1. Caples SM, Gami AS, Somers VK. Obstructive sleep apnea. Ann Intern Med 2005;142:187-97.

2. Young T., Palta M., Dempsey J., Skatrud J., Weber S., Badr S. The occurrence of sleep-disordered breathing among middle-aged adults [see comments]. N Engl J Med 1993;328:1230-5.

3. Guilleminault C, Eldridge FL, Tilkian A, Simmons FB, Dement WC. Sleep apnea syndrome due to upper airway obstruction: a review of 25 cases. Arch Intern Med 1977;137:296-300.

4. Lavie P, Ben-Yosef R, Rubin AE. Prevalence of sleep apnea syndrome among patients with essential hypertension. Am Heart J 1984;108:373-6.

5. Norton PG, Dunn EV. Snoring as a risk factor for disease: an epidemiological survey. Br Med J (Clin Res Ed) 1985;291:630-2.

6. Fletcher EC, DeBehnke RD, Lovoi MS, Gorin AB. Undiagnosed sleep apnea in patients with essential hypertension. Ann Intern Med 1985;103:190-5.

7. Nieto FJ, Young TB, Lind BK, et al. Association of sleep-disordered breathing, sleep apnea, and hypertension in a large community-based study. Sleep Heart Health Study. Jama 2000;283:1829-36.

8. Peppard PE, Young T, Palta M, Skatrud J. Prospective study of the association between sleep-disordered breathing and hypertension. N Engl J Med 2000;342:1378-84.

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