javaheri

Sleep Quality and Elevated Blood Pressure in Adolescents

Sogol Javaheri, MA1, Amy Storfer-Isser, MS1,2,4, Carol L Rosen, MD1,2,3, and Susan Redline,MD MPH1,2,4

1Case School of Medicine, Case Western Reserve University School 2Center for ClinicalInvestigation, Case Western Reserve University School of Medicine 3Department of Pediatrics,Rainbow Babies & Children’s Hospital 4Case Center for Transdisciplinary Research on Energeticsand Cancer, Case Comprehensive Cancer Center and Department of Medicine, University Hospitalsof Cleveland

AbstractBackground—We assessed whether insufficient sleep is associated with pre-hypertension inhealthy adolescents.

Methods and Results—Cross-sectional analysis of 238 adolescents, all without sleep apnea orsevere co-morbidities. Participants underwent multiple day wrist actigraphy at home to provideobjective estimates of sleep patterns. In a clinical research facility, overnight polysomnography,anthropometry, and 9 blood pressure (BP) measurements over 2 days were made. Exposures wereactigraphy-defined low weekday sleep efficiency, an objective measure of sleep quality (low sleepefficiency ≤85%) and short sleep duration (≤6.5 hrs). The main outcome was pre-hypertension(≥90th%ile for age, sex, and height), with systolic and diastolic BP as continuous measures assecondary outcomes. Pre-hypertension, low sleep efficiency, and short sleep duration occurred in14%, 26%, and 11% of the sample, respectively. In unadjusted analyses, the odds of pre-hypertensionwas increased 4.5-fold (95% CI: 2.1, 9.7) in adolescents with low sleep efficiency and 2.8-fold (95%CI: 1.1,7.3) in those with short sleep. In analyses adjusted for gender, BMI percentile andsocioeconomic status, the odds of pre-hypertension was increased 3.5-fold (95% CI: 1.5. 8.0) for lowsleep efficiency and 2.5 fold (95% CI: 0.9, 6.9) for short sleep. Adjusted analyses showed thatadolescents with low sleep efficiency, on average, had a 4.0 ± 1.2 mm Hg higher systolic BP comparedto other children(p<0.01).

Correspondence: Susan Redline, Case Western Reserve University, Cleveland, OH 44106-6003; [email protected]; fax: 216-844-2580phone: 216-844 6262..Disclosures: Carol Rosen has received a Subcontract from Advanced Brain Monitoring, Inc to provide clinical research services fundedthrough a NIH SBIR. Susan Redline has received a Subcontract from Cleveland Medical Devices Inv to provide clinical research servicesas part of a NIH SBIR. S Javaheri and Amy Storfer Isser do not have any disclosures.Clinical Implications:Childhood hypertension is a risk factor for adult hypertension and for target-organ damage. Early recognition and intervention ofchildhood hypertension are believed to be important in reducing risk of cardiovascular morbidity in adulthood. Traditional approachesfor intervention focus on the role of overweight as a contributing cause of hypertension, and include weight reduction, increased physicalactivity and nutritional changes. The current report identifies a significant association between increased blood pressure and poor sleepquality (i.e., increased wake time during the sleep period), found in 26% of a community sample of adolescents. Independent of obesity,gender and socioeconomic status, and unrelated to sleep apnea, adolescents with poor sleep had a 3.5 fold increased risk of pre-hypertension or hypertension. This finding suggests that approaches for optimizing sleep quality and duration in children may complementother behavioral approaches for preventing or treating pediatric hypertension. Monitoring sleep quality and duration in children as partof their health supervision may help identify children who are at risk for both sleep problems and hypertension, and who would benefitfrom behavioral interventions aimed at improving sleep.

NIH Public AccessAuthor ManuscriptCirculation. Author manuscript; available in PMC 2009 December 28.

Published in final edited form as:Circulation. 2008 September 2; 118(10): 1034–1040. doi:10.1161/CIRCULATIONAHA.108.766410.

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Conclusions—Poor sleep quality is associated with pre-hypertension in healthy adolescents.Associations are not explained by socioeconomic status, obesity, sleep apnea or known co-morbidities, suggesting that inadequate sleep quality is associated with elevated blood pressure.

Keywordsblood pressure; epidemiology; pediatrics

INTRODUCTIONHypertension is an increasingly prevalent health problem in adults and adolescents alike.Between 1988 and 1999, pre-hypertension (i.e., a blood pressure {BP} ≥ the 90th percentilefor height, age, and gender) and hypertension were estimated to increase in children by 2.3%and 1%, respectively. 1 Childhood hypertension is associated with hypertension in adulthood,a risk factor for cardiovascular disease incidence and mortality. 2-5 It is also associated withend-organ damage in both children and adults, notably left ventricular hypertrophy. 6, 7

Several studies have implicated insufficient sleep as a risk factor for hypertension in adults8-12. Although the etiology is unclear, experimental studies indicate that shorter sleep resultsin metabolic and endocrine dysfunction that may contribute to cardiovascular disease. 13-17

Studies in both adult and pediatric populations also have reported associations of shorter sleepduration to obesity and impaired glucose tolerance. 14, 18, 19 These findings have a potentiallylarge public impact given the frequency of sleep curtailment. 20

Few studies have addressed the relationship between sleep and hypertension in children. Ahigher level of diastolic, but not systolic blood pressure (BP) was reported in children withobstructive sleep apnea compared to primary snorers. 21 The Tucson’s Children’s Assessmentof Sleep Apnea Study found that elevations in systolic and diastolic BP were independentlyassociated with sleep efficiency, respiratory disturbance index (a measure of sleep apnea), andobesity in 230 children aged 6 to 11 years.22 To our knowledge no studies have examined theassociation between insufficient sleep and BP in adolescents free of sleep apnea. In this report,we examine the relationship between pre-hypertension and systolic and diastolic BP levelswith objective measures of sleep quality and duration in a community-based cohort ofadolescents. First, we hypothesize that adolescents with poor sleep quality or short sleepduration will be at increased odds of pre-hypertension. Second, we posit that adolescents withshort sleep duration or poor sleep quality will have higher systolic and diastolic blood pressurereadings on average compared to adolescents with better quality sleep. We excludedadolescents with clinically significant levels of sleep apnea to minimize the influence of thisexposure on BP and sleep duration measurement.

METHODSStudy Population

The sample was derived from the Cleveland Children’s Sleep and Health Study (CCSHS), alongitudinal cohort study. Data for this analysis are from 238 adolescents free of severeillnesses who participated in an examination performed 2002-2006 aimed at participants aged13 to 16 years. Details of the study population have been reported elsewhere2523 and arereviewed in an On Line Supplement.

Study ProtocolAdolescents underwent 5 to 7 day wrist actigraphy and completed a daily sleep log at homeduring the week prior to a clinical research center exam and when free of acute illness. After

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this period of in-home monitoring, participants were studied in a dedicated clinical researchcenter where overnight polysomnography, physiological and anthropometric assessments wereperformed using a standardized protocol .23,24 Examinations at the research center began atapproximately 17:00 and ended the following day at 11:00. Informed consent was obtainedfrom the child’s legal guardian and written assent was obtained from the child. The study wasapproved by the governing institutional review board.

MeasurementsActigraphy—Sleep wake estimation was made using wrist actigraphy (Octagonal SleepWatch 2.01; AMI, Ambulatory Monitoring Inc., Ardsley, NY) analyzed using the Action-Wsoftware and the Time Above Threshold algorithm. 25 Using weekday data (minimal 3 days),mean sleep duration and mean sleep efficiency, an objective measure of sleep continuity andquality, defined as the percentage time in bed estimated to be asleep (i.e., total time estimatedto be asleep/total time in bed for the major sleep period) *100) were calculated. Adolescentswith a sleep efficiency ≤85% were considered to have low sleep efficiency. Given the lack ofdata on cutoffs for defining “short sleep duration” in this age, we used the lowest decile ofmean sleep duration on weekdays to define short sleep duration, which approximated 6.5 hours.

Blood Pressure—Three BP readings were obtained at each of three times (21:00 [supine]the night of the polysomnography, 08:00 [supine], and 9:30 [sitting] the following morning)following published guidelines. 23 After a 10 minute rest period, BP was obtained using acalibrated sphygmomanometer by trained nurses. The mean systolic BP and diastolic BP valuesused in primary analyses were based on the average of all nine measurements. Pre-hypertensionwas identified if the systolic and/or diastolic BP ≥90th percentile for age, gender, and height.4 Hypertension (HTN) was defined as systolic BP or diastolic BP ≥ 95th percentile. Oneadolescent using anti-hypertensive medication was classified as having HTN.

Other Measurements—A rigid stadiometer was used to measure height, and a calibrateddigital scale to measure weight. Body mass index was calculated by dividing the weight inkilograms by height in meters squared and converted into age and sex adjusted percentiles(http://www.cdc.gov/growthcharts/). Overweight was defined as a BMI ≥ 95th percentile.Adolescents who were reported to snore loudly at least 1-2 times per week during the pastmonth were categorized as snorers. The apnea hypopnea index was defined as all obstructiveapneas and l hypopneas with a ≥ 3% desaturation per sleep hour from the polysomnogram.Socioeconomic status (SES) measures included parent report of educational level and familyincome. Additionally, the census tract of the child’s residence when initially enrolled in thestudy was linked to the corresponding 2000 U.S. Census Bureau database, and median incomeof the census tract was ascertained (http://wagda.lib.washington.edu/data/type/census/). Acomposite SES z-score was created by averaging the sample z-scores for these three measures.Tanner staging was performed by a physician to determine pubertal status 26, 27 . Preterm statuswas ascertained from birth records and defined as a gestational age <37 weeks. AttentionDeficit Hyperactivity Disorder (ADHD) was defined as parent reported doctor’s diagnosis ofADHD and either condition currently present or medication/stimulant use for ADHD duringthe past year. Using a standardized questionnaire, adolescents reported the frequency withwhich they consumed caffeine after 6 PM in the evening during the past month; those reporting“frequently” or “always” consuming caffeine were coded as consuming caffeine in the evening.

Statistical AnalysisBetween-group differences for the binary outcome, pre-hypertension, were assessed using thePearson chi-square test for categorical variables, the two-sample t-test for normally distributedvariables, and the Wilcoxon Rank-Sum test for non-normally distributed measures. To assessconfounding, associations between the primary exposures, low sleep efficiency (≤85%) and



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http://www.cdc.gov/growthcharts/

http://wagda.lib.washington.edu/data/type/census/

short sleep duration (≤6.5 hrs), and sociodemographic characteristics were also examined.Spearman and Pearson correlations assessed the strength of the linear relationship betweensleep characteristics obtained from polysomnography and actigraphy. Logistic regressionanalyses were used examine whether adolescents with short sleep duration or low sleepefficiency were at increased odds of pre-hypertension. Given the relatively small number ofadolescents with pre-hypertension, covariate adjustment was limited to the SES z-score andthe 2 variables most strongly associated with pre-hypertension: gender and BMI percentile.Multiple linear regression, adjusting for age, gender, race, preterm status, BMI percentile, andSES z-score, was used to examine the linear associations between sleep duration or sleepefficiency with continuously measured systolic and diastolic blood pressure levels. Additionalanalyses included low sleep efficiency from the polysomnography as the exposure. Residualconfounding by snoring or the apnea hypopnea index also was assessed by including thesemeasures as covariates in the adjusted analyses.

Statement of ResponsibilityThe authors had full access to and take full responsibility for the integrity of the data. Allauthors have read and agree to the manuscript as written.

RESULTSCharacteristics of the analytic sample are shown in Table 1. The average participant was age13.7 ± 0.7 years. As designed, the sample had an approximately 50% representation of boys,African Americans and children born prematurely. One fifth of the sample was overweight.Approximately one-fourth reported their household income as less than $20,000 per year.Sixty-one adolescents (26%) had low sleep efficiency. Average weekday sleep duration was7.71 hours and 11% of the sample slept ≤ 6.5 hrs.

Sample characteristics stratified by pre-hypertension are also shown in Table 1. Overall, 33children (14%) met the criteria for pre-hypertension, including 19 who had pre-hypertensionand 14 who were hypertensive. Compared to normotensive adolescents, those with pre-hypertension tended to have a higher proportion of males, higher BMI and were morefrequently from neighborhoods with a low median income (p-values between 0.05 - 0.10). Bothlow sleep efficiency (p<.0001) and short sleep duration (p = 0.06) were more than two-foldmore prevalent in those with pre-hypertension compared to normotensive adolescents.

The distribution of various BP measures is further detailed in Table 2. Using the mean of nineBP readings, approximately 11% of the sample was classified with elevated systolic BP and5% with elevated diastolic BP. All measures of systolic BP were significantly higher amongthe adolescents with low sleep efficiency compared to those with higher sleep efficiency.Adolescents with low sleep efficiency also had a higher prevalence of elevated diastolic BPand had higher 08:00 diastolic BP values. Adolescents with short sleep duration did not differfrom those with longer sleep duration in regards to systolic BP, but had a higher averagediastolic BP and higher prevalence of elevated diastolic BP (24.0% vs 2.4%; p<0.001).

To assess confounding, associations among the sleep exposures and sociodemographiccharacteristics were examined (see on-line supplement). Adolescents with low sleep efficiencyhad a higher BMI, were more often male, and were from households with lower incomes andlower levels of caregiver education. These characteristics were not significantly associatedwith short sleep duration. Approximately two-thirds (68.0%) of adolescents with short sleepduration also had low sleep efficiency, while 27.9% of adolescents with low sleep efficiencyalso had short sleep duration. The correlation between mean weekday sleep efficiency andsleep efficiency from the night of the polysomnography was low (r= 0.13, p=0.04), as was thecorrelation between mean weekday sleep duration and sleep duration from the night of the



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polysomnography (r=-0.06, p=0.37). Approximately one-third (32.8%) of adolescents withlow sleep efficiency based on actigraphy also had low sleep efficiency from thepolysomnography.

The results of the logistic regression models of the association between each sleep measureand the odds of pre-hypertension are shown in Tables 3a and 3b. After adjusting for gender,BMI percentile and SES z-score, those with low sleep efficiency had 3.5 times the odds of pre-hypertension compared to those without low sleep efficiency (95% CI: 1.54, 7.96). Short sleepduration was associated with a 2.8-fold increased odds of pre-hypertension in unadjustedanalyses (95% CI: 1.07, 7.34), but this association was modestly attenuated after adjusting forgender, BMI percentile and SES z-score (OR: 2.54; 95% CI: 0.93, 6.90).

The unadjusted and adjusted associations between continuously measured systolic anddiastolic BP levels with sleep efficiency are shown in Table 4. After adjusting for age, gender,race, term status, BMI percentile and SES z-score, the model predicts that each 5 percentageincrease in sleep efficiency was associated with a 1.5 ± .40 mmHg decrease in systolic BP (p<.001). Weaker associations were observed between sleep efficiency and diastolic BP; i.e., each5 percentage increase in sleep efficiency was associated with a 0.65 ± .35 decrease in diastolicBP (p=.05). When modeling low sleep efficiency as a dichotomous exposure, the adjustedmodel estimates that adolescents with low sleep efficiency had a mean systolic BP that was onaverage, 3.99 ± 1.24 mm Hg higher compared to those with higher sleep efficiency (p=0.002).Including sleep duration as a continuously measured covariate did not alter the primaryassociations of sleep efficiency and BP (data not shown).

Similar to the models of pre-hypertension, sleep duration was more weakly associated withcontinuously measured systolic and diastolic blood pressure compared to sleep efficiency(Table 5).

Additional AnalysesThe primary analyses also were repeated with low sleep efficiency ascertained viapolysomnography as the exposure. Consistent with the results of the primary analysis, afteradjusting for gender, BMI-percentile and SES z-score, those with polysomnography sleepefficiency ≤85% had nearly 3 times the odds of pre-hypertension as those with better sleep(OR=2.83, 95% CI: 1.28, 6.24). Also consistent with the results of the actigraphy-defined sleepexposures, in adjusted analyses, each one percentage increase in sleep efficiency was associatedwith a 0.20 ± .06 decrease in systolic BP (p<.001). Similarly, those with low polysomnographysleep efficiency had systolic BP that was 3.26 ± 1.25 mm HG higher on average compared tothose with better sleep (p=0.01).

Although analyses were restricted to children without clinically significant sleep apnea,additional analyses assessed potential residual confounding by snoring or the apnea hypopneaindex (i.e., in an apnea hypopnea index range of 0 - 4.9). The results show that loud snoringwas not significantly associated with pre-hypertension, systolic BP or diastolic BP. In contrast,while the apnea hypopnea index does not confound the association between the outcomes andthe sleep exposures, it was associated with increased odds of pre-hypertension after adjustingfor low sleep efficiency, gender and BMI percentile; i.e., for each one-unit increase in the apneahypopnea index, the odds of pre-hypertension increased by 47% (OR=1.47, 95% CI: 1.00,2.17). Similarly, the apnea hypopnea index was significantly associated with systolic BP inadjusted models; after adjusting for subject characteristics and low sleep efficiency, for eachone-unit increase in apnea hypopnea index, mean systolic BP increases by 1.65 mm Hg onaverage (p=0.009).



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DISCUSSIONTo our knowledge, this is the first reported association between low sleep efficiency and shortsleep duration objectively measured in the child’s usual sleep environment with elevated BP(pre-hypertension or hypertension) in adolescents without clinically significant levels of sleepapnea. Specifically, adolescents with poor sleep quality, as measured by a sleep efficiency of≤ 85%, were at 3.5-fold increased odds of being pre-hypertensive or hypertensive. Similarfindings were observed when single night polysomnography was used to quantify sleepefficiency. The association between low sleep efficiency and pre-hypertension persisted evenafter adjusting for gender, SES and adiposity. The results did not appreciably change afteradjusting for snoring or the apnea hypopnea index. Short sleep duration was also associatedwith a 2.5-fold increase in odds of pre-hypertension or hypertension. However, it was not clearif this association was attributable to the low sleep efficiency found in a majority of theadolescents with short sleep duration.

In adults, poor sleep quality identified by questionnaires has been reported in association withan increased prevalence of hypertension 12 and an increased rate of “non-dipper hypertension.”28 However, poor sleep quality in adults often occurs in the presence of primary sleep disorders,such as sleep apnea or insomnia, or secondary to numerous co-morbidities. Therefore, adultstudies reporting associations with disturbed or reduced sleep and hypertension have beencautiously interpreted due to concerns over residual confounding. 10 One large prospectivestudy reported associations of short sleep duration in women but not men 8, while another studyshowed no association of hypertension and sleep duration in the elderly, a group with a highprevalence of morbidities. 29 Since adolescents with major co-morbidities, including those withclinically significant levels of sleep apnea, were excluded from our analyses (to minimizeconfounding and reduce measurement error), it is unlikely that major confounding due tomedical illnesses, medications, or sleep-related hypoxemia explains the strong associationbetween low sleep efficiency and elevated BP. Given that the association between BP and lowsleep efficiency persisted even after adjusting for average sleep duration, our findings alsosuggest that recurrent arousals or awakenings from sleep (which reduce sleep efficiency) areassociated with elevated blood pressure. Our findings are consistent with a report from a sampleof pre-adolescent children studied with single night polysomnography which demonstrated anassociation between low sleep efficiency and elevated BP after adjusting for the apnea hyponeaindex. 22

The 3.5-fold odds of pre-hypertension or hypertension in children with low sleep efficiency,if causal, suggests associations with a potential large public health impact. Although the overallprevalence of low sleep efficiency in general pediatric samples is unknown, our prevalence of26% is likely an under-estimate given the exclusion of children with sleep disorders andsignificant co-morbidities. Our finding of an increased prevalence of low sleep efficiencyamong vulnerable population subgroups, such as poorer children and those of minorityethnicity, may be of special concern since these groups are known to be at risk for hypertensionand other adverse health outcomes.

Low sleep efficiency was associated with an average adjusted increase in systolic BP of 4 mmHg. Although limited data are available in children to interpret the clinical significance of thisabsolute elevation, large cohort studies suggest a log-linear increase in morbidity in associationwith incremental changes in systolic blood pressure. 30

Short sleep duration was associated with a 2.5-fold increased odds of pre-hypertension, anassociation partly attributable to low sleep efficiency. Short sleep duration has been increasingin all ages31 and is also associated with an increased risk for obesity. 13, 16-18 Efforts to optimizesleep in childhood, thus, may improve the BP profile of children through obesity dependent



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and independent pathways. Further work is needed to dissect the relative influences of sleepcurtailment from sleep disruption on health outcomes, which will be important in directingwhether future interventions would be best directed at improving sleep time, sleepconsolidation, or both.

The etiology of low sleep efficiency in healthy adolescents is unclear. Sensitivity analyses didnot indicate an association between low sleep efficiency with common childhood disorderssuch as asthma or attention deficit hyperactivity disorder or with caffeine or tobacco use, norwere these variables confounders in the association between sleep efficiency and BP (data notshown). It is possible that unknown psychological disorders may have confounded our results,but this seems unlikely given the strong associations and community sampling design.

Although children with significant sleep apnea were excluded from our analyses, the apneahypopnea index (in a range of 0 to 4.9) was significantly associated with pre-hypertension andsystolic blood pressure after adjusting for sleep efficiency. The latter suggests that even mildsleep disordered breathing may contribute to abnormal blood pressure levels, a result consistentwith reports of more severely affected children from sleep clinic samples. 21

Strengths of this report are the inclusion of a community-based sample of children, minimizingreferral biases, and the use of objective measures of sleep duration and multiple measures ofBP, minimizing measurement error and reporting biases. By characterizing numerous riskfactors and co-morbidities, we were able to restrict the analytical sample to children withoutdisorders likely to confound associations with sleep quality. Although former pre-term childrenwere over-represented by design, there was no evidence of any differences in the exposures,responses, or associations between preterm and full term children, suggesting our results shouldbe generalizable to other pediatric samples.

There are no established cutoffs to define thresholds of sleep duration or sleep efficiency thatincrease morbidity in adolescents. In adults, sleep durations of < 6 hrs have been associatedwith a variety of adverse health outcomes 15, 19, 32, 33 and sleep efficiencies of < 85% areconsidered low. Our choice for defining short sleep duration as less than 6.5 hrs was toapproximate the cutoff associated with hypertension risk in adults, 10 which, in our sample,represented the lowest decile. However, examination of a larger sample may permit a morecomprehensive assessment of dose-response and threshold levels for each sleep exposure.

A limitation of this cross-sectional study is that BP status was determined from measurementsmade on two consecutive days. Since BP may vary from day to day, repeated measurementsover time are needed to identify children with persistent elevations in BP. Another limitationis that the reported associations do not provide proof of causality. We also cannot exclude thepossibility that elevated BP operates as a risk factor for poor sleep. It is important, however,to interpret our findings in light of the biological plausibility of the observed associations andexperimental data that show acute effects of sleep disruption on BP. Mechanisms linking poorsleep efficiency or sleep deprivation with hypertension may be through disruptions in cortisolsecretion 19, 34, 35 and stimulation of the renin-angiotensin system and sympathetic nervoussystem, as measured by increased secretion of catecholamines 36 and abnormalities insympathovagal balance, 37 and through abnormal secretion of vasoactive hormones, includingendothelin, vasopressin, and aldosterone. 38 Experimental sleep disruption has been associatedwith elevated BP in sleep in normal subjects. 39 While some experimental models suggest thatsustained elevations in BP require sleep fragmentation to occur in a background of intermittenthypoxemia 40 (as occurs with sleep apnea), sleep fragmentation may be associated withelevated BP even in adults with a low apnea hypopnea index 41 or with simple snoring 11.Prospective and interventional studies are needed to provide further evidence of causality and



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also to address whether improving sleep quality and duration reduce BP and risk ofhypertension.

In summary, extensive analyses using objective measures of sleep quality and duration andmultiple measures of BP provide evidence for a strong association of low sleep efficiency withincreased risk of pre-hypertension and hypertension in a healthy sample of adolescents. Ourdata suggest that low sleep efficiency may more consistently be associated with pre-hypertension than short sleep duration. Future research is needed to address whether preventionof hypertension in children should not only include weight management and exercise, but alsoinclude optimization of sleep. Our data underscore the need to monitor quantity and quality ofsleep as part of health supervision in children.

Supplementary MaterialRefer to Web version on PubMed Central for supplementary material.

AcknowledgmentsFunding: Supported by grants: NIH HL07567, HL60957, RO1 NR02707, M01 RR00080 and 1U54CA116867.

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34. Spiegel K, Leproult R, L’Hermite-Baleriaux M, Copinschi G, Penev PD, Van Cauter E. Leptin levelsare dependent on sleep duration: relationships with sympathovagal balance, carbohydrate regulation,cortisol, and thyrotropin. J Clin Endocrin Metabo 2004;89:5762–5771.

35. Spath-Schwalbe E, Gofferje M, Kern W, Born J, Fehm HL. Sleep disruption alters nocturnal ACTHand cortisol secretory patterns. Biologic Psychiatry 1991;29:575–584.

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Table 1

Sample Characteristics

All (n=238) Normotensive (n=205) Pre-hypertension (n=33) p-value

Child Characteristics

Age 13.7 ± 0.7 13.7 ± 0.7 13.7 ± 0.9 0.9782

Male Gender 123 (51.7%) 101 (49.3%) 22 (66.7%) 0.0634

Caucasian Race 107 (45.0%) 94 (45.9%) 13 (39.4%) 0.4887

Preterm Status 136 (57.1%) 115 (56.1%) 21 (63.6%) 0.4167

Loud Snoring 41 (17.8%) 36 (18.2%) 5 (15.6%) 0.7259

ADHD 17 (7.2%) 13 (6.4%) 4 (12.1%) 0.2683

Caffeine Consumption after 6pm 61 (25.9%) 53 (26.1%) 8 (24.2%) 0.8204

BMI Percentile 72.2(47.1, 93.8)

70.9(45.2, 92.8)

87.9(63.1, 96.8)

0.0536

Overweight (BMI %tile ≥ 95th) 50 (21.0%) 40 (19.5%) 10 (30.3%) 0.1579

Tanner Stage ≥ 4 172 (73.5%) 148 (73.6%) 24 (72.7%) 0.9131

Socioeconomic (SES) Measures

Household Income<$20,000$20,000 - $49,999≥$50,000

62 (27.9%)64 (28.8%)96 (43.2%)

53 (27.8%)51 (26.7%)87 (45.5%)

9 (29.0%)13 (41.9%)9 (29.0%) 0.2689

Neighborhood MedianIncome Census Tract ($1k)

38.6(23.6, 52.4)

41.0(24.1, 55.2)

30.9(23.2, 43.1)

0.0617

Caregiver Education< High SchoolHigh School or GED> High School

19 (8.2%)47 (20.4%)165 (71.4%)

15 (7.6%)41 (20.7%)142 (71.7%)

4 (12.1%)6 (18.2%)23 (69.7%) 0.5803

SES z-score 0.00 ± 0.80 0.03 ± 0.81 -0.17 ± 0.74 0.1763

Actigraphy Sleep Characteristics

Low Sleep Efficiency (≤85%) 61 (25.6%) 43 (21.0%) 18 (54.6%) <0.0001

Short sleep (≤6.5 hr) 25 (10.5%) 18 (8.8%) 7 (21.2%) 0.0585

Sleep duration 33≤ 6.56.51 - 7.497.50 - 8.49≥ 8.5

25 (10.5%)75 (31.5%)87 (36.6%)51 (21.4%)

18 (8.8%)65 (31.7%)78 (38.0%)44 (21.5%)

7 (21.2%)10 (30.3%)9 (27.3%)7 (21.2%)

0.1644

Sleep duration 7.71 ± 1.03 7.75 ± 0.99 7.46 ± 1.23 0.1367

Polysomnography Sleep Characteristics

Arousal Index 7.4(6.0, 9.4)

7.4(6.1, 9.4)

7.5(6.0, 10.4)

0.8343

% time stage 3-4 33.8 ± 11.6 34.1 ± 11.4 32.3 ± 13.0 0.4005

% time REM 17.9 ± 4.8 17.9 ± 4.8 17.5 ± 4.9 0.6563

Sleep Efficiency 90.4(85.5, 94.0)

91.1(86.5, 94.2)

85.9(80.3, 89.6)

0.0002

Sleep Efficiency (≤85%) 55 (23.1%) 40 (19.5%) 15 (45.5%) 0.0010

Mean (%) or median (Interquartile range)



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Tabl

e 2

Blo

od P

ress

ure

In S

ubgr

oups

Def

ined

by

Slee

p Q

ualit

y

Slee

p E

ffici

ency

>85

%(n

=177

)Sl

eep

Effi

cien

cy ≤

85%

(n=6

1)p-

valu

eM

ean

Slee

p D

urat

ion

>6.

5 hr

s (n=

213)

Mea

n Sl

eep

Dur

atio

n ≤

6.5

hrs (

n=25

)p-

valu

e

Syst

olic

BP

Syst

olic

BP

perc

entil

e61

.2(4

2.7,

77.

8)71

.2(5

3.1,

91.

1)0.

0012

63.2

(46.

7, 8

0.8)

66.4

(42.

2, 7

7.4)

0.91

09

Elev

ated

Sys

tolic

BP

(≥ 9

0th p

erce

ntile

)11

(6.2

%)

16 (2

6.2%

)<0

.000

123

(10.

8%)

4 (1

6.0%

)0.

5005

Mea

n Sy

stol

ic B

P (m

m H

g)**

112.

6 ±

7.5

118.

4 ±

9.9

<0.0

001

113.

8 ±

7.9

116.

5 ±

12.6

0.31

85

21

:00

114.

6 ±

8.8

121.

9 ±

11.7

<0.0

001

116.

0 ±

9.2

120.

8 ±

15.4

0.14

20

08

:00

111.

4 ±

8.7

116.

6 ±

9.4

0.00

0111

2.6

± 8.

911

4.0

± 10

.90.

4726

09

:30

111.

9 ±

8.2

116.

8 ±

11.5

0.00

2811

3.0

± 8.

711

4.6

± 13

.80.

5635

Dia

stol

ic B

P

Dia

stol

ic B

P pe

rcen

tile

54.8

(41.

6, 7

0.6)

58.1

(42.

6, 7

4.3)

0.16

9555

.2(4

1.6,

70.

6)58

.0(4

6.0,

70.

8)0.

3127

Elev

ated

Dia

stol

ic B

P (≥

90th

per

cent

ile)

5 (2

.8%

)6

(9.8

%)

0.03

505

(2.4

%)

6 (2

4.0%

)0.

0003

Mea

n D

iast

olic

BP

(mm

Hg)

**

65.7

± 6

.267

.4 ±

7.4

0.08

1665

.8 ±

6.3

68.6

± 8

.20.

0463

21

:00

64.1

± 9

.165

.2 ±

11.

00.

4719

64.1

± 9

.367

.2 ±

12.

00.

1224

08

0066

.3 ±

7.1

68.4

± 7

.10.

0416

66.6

± 7

.269

.1 ±

6.6

0.09

08

09

3066

.7 ±

7.1

68.5

± 9

.00.

1661

66.9

± 7

.269

.5 ±

10.

50.

2308

Pre-

Hyp

erte

nsio

n15

(8.5

%)

18 (2

9.5%

)<0

.000

126

(12.

2%)

7 (2

8.0%

)0.

0585

Hyp

erte

nsio

n5

(2.8

%)

9 (1

4.8%

)0.

0019

9 (4

.2%

)5

(20.

0%)

0.00

89

⋆ Mea

n ±

SD o

r med

ian

(inte

rqua

rtile

val

ues)

or a

s n (%

).**

Ave

rage

of a

ll 9

valu

es



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Table 3a

Association Between Low Sleep Efficiency And Odds of Pre-Hypertension

Unadjusted OR (95% CI) p-value Adjusted OR(95% CI)

p-value

Low SleepEfficiency(≤85%)

4.52 (2.11, 9.70) 0.0001 3.50 (1.54, 7.96) 0.0028

Male Gender 1.78 (0.78, 4.04) 0.1702

BMI %tile(per 10-unit↑)

1.08 (0.93, 1.26) 0.3098

SES z-score 0.85 (0.51, 1.42) 0.5339



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Table 3b

Association Between Short Sleep And Odds of Pre-Hypertension

Unadjusted OR (95% CI) p-value Adjusted OR(95% CI)

p-value

Short Sleep(≤6.5 hrs)

2.79 (1.07, 7.34) 0.0366 2.54 (0.93, 6.90) 0.0679

Male Gender 2.20 (0.99, 4.88) 0.0523

BMI %tile(per 10-unit↑)

1.13 (0.98, 1.31) 0.1042

SES z-score 0.75 (0.46, 1.23) 0.2526



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Table 4

Association Between Actigraphy Sleep Efficiency (per 1% increase) & ContinuouslyMeasured BP

Unadjusted Adjusted ⋆

Beta ± SE p-value Beta ± SE p-value

Systolic Blood Pressure -0.42 ± 0.07 <0.0001 -0.30 ± 0.08 0.0002

Diastolic Blood Pressure -0.13 ± 0.06 0.03 -0.13 ± 0.07 0.05

⋆Adjusted for age, gender, race, term status, BMI %tile, SES z-score



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Table 5

Association Between Actigraphy Sleep Duration (per 1 hour increase) & ContinuouslyMeasured BP

Unadjusted Adjusted ⋆

Beta ± SE p-value Beta ± SE p-value

Systolic Blood Pressure -1.74 ± 0.53 0.0012 -0.98 ± 0.52 0.06

Diastolic Blood Pressure -0.60 ± 0.41 0.15 -0.41 ± 0.44 0.34

⋆Adjusted for age, gender, race, term status, BMI %tile, SES z-score



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