O R I G I N A L P A P E R

Sleep and Health-Related Quality of Life in Heart Failure

Q uality of life is often poor inpatients with heart failure (HF)

and is attributable to worse functionalstatus and symptom burden1–3 but alsoto depression and fatigue, which arecommon in HF.4,5 In addition, femalesex and ethnicity are associated withpoorer quality of life in HF.1–3

Sleep-disordered breathing (SDB) iscommon in individuals with HF.6

Reported incidence rates of obstructivesleep apnea (OSA) and central sleepapnea (CSA) vary depending on NewYork Heart Association (NYHA) func-tional class; rates typically increasingwith greater severity. While OSA is con-sidered a risk factor for HF,7 HF is themost common cause of CSA.8,9 Anapnea-hypopnea index (AHI) cutpointof �10 events ⁄h is a commonlyaccepted and clinically relevant defini-tion of sleep apnea.10–12 In mild to mod-erate HF, AHI scores of �10 events ⁄hyield OSA prevalence rates of 15% to53% and CSA prevalence rates of 15%to 57%,13,14 depending upon sample age.SDB in HF is associated with increasedrisk of death and hospitalization.15,16

In non-HF populations, SDB is associ-atedwithpoorqualityof life.Forexample,individualswithOSAhaveoverallpoorerquality of life than age- and sex-matchedpopulations.17 The poor quality of life isindependently associated with fatigueand with severity of SDB, specifically,with the degree of respiratory disturbanceandnumberofarousals fromsleep.18,19

Studies have begun to assess the con-tribution of poor sleep to quality of life inHF. Brostrom and colleagues20 showedthat self-reported difficulties with sleep,including difficulties initiating and ⁄orfalling asleep, are associated with worsequality of life in HF. Other studies sug-gest that HF patients with SDB havepoorer quality of life as compared withHF patients without SDB,21,22 although

such studies have not examined possibleconfounding factors such as fatigue anddepression, both of which also influencequality of life and are tightly linked withsleep quality.1–4 It could be, for example,that the negative influence of SDB onquality of life in HF is an indirect conse-quence of the fatigue associated withSDB and not with SDB per se.23

The purpose of this study thereforewas to characterize sleep and SDB inpatients with HF and to determinepotential independent contributions offatigue and depression, as well as func-tional capacity, to quality of life.

MethodsParticipants. Stable HF patients withleft ventricular ejection fraction (LVEF)�45% were recruited from the UCSDHeart Failure Program and the VA Medi-

cal Center Coronary Care Program. Of74 HF patients eligible to participate inthe study, 40 men and women (33NYHA class II and 7 NYHA class III)between the ages of 31 and 80 yearsagreed to participate and completed thestudy. Healthy non-HF volunteers wererecruited from the local community viaadvertisement and referrals. Of 61 non-HF volunteers eligible to participate inthe study, 34 men and women betweenthe ages of 35 and 81 years agreed to par-ticipate and completed the study. Indi-viduals who did not agree to participatecited lack of interest or time as reasons.

Inclusion criteria specific to HFincluded NYHA functional classes IIthrough IV; symptoms of HF for at least3 months that have been optimally trea-ted with diuretics, angiotensin-convert-ing enzyme inhibitors, and b-blockers

This study characterized sleep in heart failure (HF) and determined associations with qual-ity of life. Forty stable HF patients and 34 healthy volunteers were studied in a clinicalresearch unit. HF patients had more central apneas per hour (17.6 vs 5.4; P�.01) andobstructive apneas per hour (21.7 vs 8.5; P�.05), spent more time in stage 1 sleep (54vs 35 min; P�.05), and had more respiratory awakenings following apneic events (27.2vs 4.2; P�.01). More HF patients were depressed (55% vs 27.2%; P�.01) and hadworse fatigue (P�.05). In multiple regression analysis, physical functioning quality of lifewas predicted by reduced left ventricular ejection fraction (P�.05), shorter distance on a6-minute walk test (P�.05), greater fatigue (P�.01), and more apneas (P�.05) (modelR2=.672; P�.001). Emotional functioning quality of life was predicted by greater fatigue(P�.01) (model adjusted R2=.732; P<.001). Findings provide evidence that in additionto functional status and ongoing fatigue, poorer quality of life in HF is independentlyrelated to the severity of sleep-disordered breathing. Congest Heart Fail. 2009;15:228–233. �2009 Wiley Periodicals, Inc.

Paul J. Mills, PhD;1 Joel E. Dimsdale, MD;1 Loki Natarajan, PhD;2

Michael G. Ziegler, MD;3 Alan Maisel, MD;3 Barry H. Greenberg, MD3

Departments of Psychiatry;1 Family and Preventive Medicine;2 and Medicine,University of California San Diego, La Jolla, CA3

Address for correspondence:Paul J. Mills, UCSD Medical Center, Psychiatry and Behavioral Medicine,200 West Arbor Drive, San Diego, CA 92103-0804E-mail: pmills@ucsd.eduManuscript received October 21, 2008; revised March 10, 2009; accepted May29, 2009

doi: 10.1111/j.1751-7133.2009.00106.x

quality of life in heart failure september • october 2009228

where appropriate (approximately 95%of the patients were receiving b-block-ers); and an ejection fraction �45%.Other study inclusion criteria includedage between 30 and 85 years, blood pres-sure <180 ⁄110 mm Hg, and men andwomen of all ethnicities and races. Exclu-sion criteria included recent myocardialinfarction (within 1 month), recentstroke or significant cerebral neurologicalimpairment, severe chronic obstructivepulmonary disease, and psychiatric illnessother than depression. Inclusion criteriaspecific to the non-HF controls includedbeing in the same age range as the HFpatients and being physically healthy.The control participants were recruitedspecifically to participate in this study onsleep in HF and did not undergo echocar-diography or the 6-minute walk test (asdescribed below for the HF patients).

The investigation conformed to theprinciples outlined in the Declaration ofHelsinki. The study was approved bythe University of California, San Diegoinstitutional review board. All partici-pants gave informed written consent.

ProceduresQuality of Life, Fatigue, and Depres-sion. All HF patients completed the21-item Minnesota Living With HeartFailure Questionnaire (MLHFQ). TheMLHFQ was designed to assess perceivedquality of life due to the effects of HF andits treatment. This psychometricallysound instrument questions signs andsymptoms of HF, work and emotions,social relationships, and physical andsexual activity.24 All participants com-pleted the 30-item MultidimensionalFatigue Symptom Inventory–Short Form(MFSI-SF)25 and the 21-item BeckDepression Inventory (BDI).26 TheMFSI-SF assesses the principal manifes-tations of fatigue, yielding a total fatiguescore. The 21-item BDI assesses symp-toms related to sadness, feelings of guilt,perceptions of self-worth, suicidal idea-tion, and changes in appetite and bodyweight, among other characteristics.26

Scores�10 indicate possible depression.

Disease Severity and Functional Capa-city. Echocardiography and 6-minutewalk studies were performed, as previ-

ously described.27 The 6-minute walktest has been shown to be independentlyrelated to self-reported ratings of physi-cal capacity, including MLHFQ physicalfunctioning.28,29

Sleep Monitoring. Participants werescheduled for one night of sleepmonitoring at the Gillin Laboratory ofSleep and Chronobiology at the UCSDGeneral Clinic Research Center. Partic-ipants arrived at 6 PMPM. Sleep setupbegan at 8 PMPM and took approximately1 hour. Lights were turned off at 10 PMPM.

Sleep data was recorded using standardpolysomnography.30 Electroencephalo-graphy (EEG), electrooculography, chinelectromyography (EMG), and thoracicand abdominal respiration were recordedon a Grass model PSG36-2 (Grass Tech-nologies, West Warwick, RI) or Emblamodel A10 polysomnograph (Broom-field, CO). Oxyhemoglobin saturationwas monitored using a pulse oximeter(Biox 3740; Ohmeda, Louisville, CO)and analyzed by software from PROFOX(Escondido, CA). Anterior tibialis EMGwas used to rule out periodic limb move-ments during sleep. Records were scoredwith the Rechtshaffen and Kales31

criteria by technicians with interraterreliabilities>90%.

Based on the existing literature,9,32 wechose a panel of 9 sleep parameters toexamine: Time spent in sleep stage 1,stage 2, slow-wave sleep (stage 3 andstage 4 combined), and REM sleep wereused as descriptors of sleep architecture.Percentage sleep efficiency and sleeponset latency were chosen as objectiveindices of sleep efficiency. (Percentagesleep efficiency was computed as theratio of total sleep time to time spent inbed multiplied by 100.) Total number ofarousals, number of respiratory awaken-ings, and wake after sleep onset werechosen to represent sleep fragmentation.An arousal was defined as a shift in EEGfrequency to alpha or theta for �3 sec-onds but <15 seconds as scored fromcentral, occipital, or both EEG leads.

The total number of apneas and hyp-opneas per hour of sleep were deter-mined, as well as the total number ofcentral and obstructive apneas per hour.An apnea was defined as a decrement in

airflow �90% from baseline for�10 seconds. A hypopnea was definedas a decrement in airflow �50% but<90% from baseline for �10 seconds.AHI was defined as the total number ofapneas plus hypopneas per hour of sleep.Central AHI (C-AHI) was defined asthe total number of central apneas plushypopneas per hour of sleep. ObstructiveAHI (O-AHI) was defined as the totalnumber of obstructive apneas plus hyp-opneas per hour of sleep.

Data Analysis. Data were analyzedusing one-way ANOVA, multivariateanalysis of variance (MANOVA), Pear-son correlations, and multiple linearregression (SPSS 15.0 for Windows(SPSS Inc., Chicago, IL). Data are pre-sented as means � SD. The level of sta-tistical significance was set at P�.05(two-tailed). Borderline significance(P�.10) is also presented to show trendsthat may help to better illustrate effectsand relationships.

ResultsDemographic Characteristics. Demo-graphic characteristics are presented inTable I. Participants with HF and thosewithout were similar in age, body massindex, race, and incidence of hyperten-sion. There were fewer women in theHF group than in the non-HF group(V2=8.75; P=.003).

Fatigue, Depression, and Quality ofLife Characteristics. MFSI-SF scores(F=4.23; P=.043) and BDI scores(F=6.62; P=.012) were higher in HFpatients than in controls. Fifty-five per-cent of HF patients were depressed (ie,BDI score�10) as compared to 27.2% ofcontrols (V2=5.69; P=.015). HF patients’MLHFQ physical functioning score was20.35 (SD, 11.2; range, 0–40) andemotional functioning score was 8.85(SD, 7.1; range, 0–25). These values arecomparable to those found in the litera-ture for our NYHA class II and IIIpatients20 (Table I).

Sleep Characteristics. Sleep character-istics are presented in Table II. AMANOVA controlling for sex was

quality of life in heart failure september • october 2009 229

significant for the HF group (F=2.42;Wilk’s lambda P=.015). Regarding sleeparchitecture, HF patients spent moretime in stage 1 sleep (F=4.80; P=.032)and marginally less time in REM sleep(F=3.71; P=.058). Regarding sleep frag-mentation, HF patients had a greaternumber of respiratory awakenings(F=6.22; P=.015). HF patients tendedtoward a greater number of total arousals(F=3.01; P=.084) and showed no differ-ence in how much time was spentawake after sleep onset. There were nogroup differences in sleep efficiency. HF

patients had a lower average nocturnalO2 saturation (F=7.19; P=.009) andspent more time below 90% saturation(F=5.97; P=.017).

HF patients had a greater total numberof apneas per hour compared with con-trols (AHI, 78.0 [SD, 62] vs 65.4 [SD,48]; F=6.51; P=.021). HF patients had agreater number of central (F=8.95;P=.004) and obstructive apneas per hour(F=5.42; P=.022) (Table II; Figure). Thepresence of sleep apnea was defined asAHI, C-AHI, and O-AHI �10.14

According to this definition, compared

with controls, more HF patients wereclassified as apneic: AHI, 23.4% vs72.5% (V2=17.6; P<.001); C-AHI,11.7% vs 57.5% (V2=16.6; P<.001); O-AHI, 20.5% vs 50.0% (V2=6.8; P<.01).

Sleep and Quality of Life. Separatemultiple linear regression models wereconstructed for the dependent variablesMLHFQ physical and emotionalfunctioning subscales. The independentvariables body mass index, sex, and racewere entered into the first block of vari-ables. LVEF and 6-minute walk testresults were entered in the second block.BDI scores were entered into the thirdblock. MFSI-SF scores were entered intothe fourth block, and the sleep variablesfrom the MANOVA were entered intothe fifth block of variables.

MLHFQ physical functioning waspredicted (model adjusted R2=.610;F=8.74; P<.001) by a combination ofvariables including reduced LVEF(P=.005), shorter distance on the 6-min-ute walk test (P=.055), higher MFSI-SFscores (P=.031), greater number ofobstructive apneas (P=.027), and greaternumber of central apneas (P=.038)(Table III). MLHFQ emotional func-tioning was predicted (model adjustedR2=.732; F=13.7; P<.001) by higherMFSI-SF scores (P<.001) and margin-ally by the number of central apneas(P=.070) (Table IV).

DiscussionUnderstanding factors that determinequality of life in HF is vital because inaddition to the importance of day-to-day satisfaction with life, quality of lifepredicts morbidity and mortality inHF.33 Much is already known aboutdeterminants of quality of life in HF. HFseverity, as determined by functional sta-tus and symptom burden,1–3 influencesquality of life. Depression and fatiguetoo are predictors of poorer quality of lifein HF,4,5 as are female sex and ethnicity(quality of life is poorer in AfricanAmericans and Caucasians comparedwith Hispanic persons).1–3 Increasedincidence of both depression and fatigueare linked to severity of HF and nega-tively affect quality of life.5,34

Table I. Study Participant Characteristics (Mean � SD)

WITH HEART

FAILURE

WITHOUT HEART

FAILURE

SIGNIFICANT

P VALUES

No. 40 34Age, y 56.4 (14.3) 54.2 (11.6)Body mass index, kg ⁄ m2 31.9 (8.2) 28.8 (6.4)Female ⁄ male, No. 8 ⁄ 2 18 ⁄ 16 �.01Hypertensive ⁄normotensive, No.

5 ⁄ 35 6 ⁄ 28

Race 11 African American26 Caucasian

1 Native American2 Asian

14 African American20 Caucasian

0 Native American0 Asian

BDI 11.38 (7.2) 7.12 (6.8) �.01MFSI-SF total fatigue 17.18 (23) 6.29 (21) �.05LVEF 29.10 (8.6) NA6-minute walk test, m 425 (147) NAMLHFQ physical function 20.2 (11.2) NAMLHFQ emotional function 8.85 (7.1) NA

Abbreviations: BDI, Beck Depression Inventory; LVEF, left ventricular ejection fraction; MFSI-SF, Multidimensional Fatigue Symptom Inventory–Short Form; MLHFQ, Minnesota LivingWith Heart Failure Questionnaire; NA, not assessed.

Table II. Study Participant Sleep Characteristics (Mean � SD)

WITH HEART

FAILURE

WITHOUT HEART

FAILURE

SIGNIFICANT

P VALUES

Sleep architectureStage 1 sleep, min 56.2 (37) 34.5 (20) �.05Stage 2 sleep, min 177 (57) 195 (46)Slow-wave sleep, minutes 39.1 (35) 52.6 (36)REM sleep, min 57.7 (30) 69.5 (35) �.05

Sleep efficiencySleep efficiency, % 77.1 (17) 82.3 (14)Sleep onset latency, min 20.4 (30) 11.9 (22)

Sleep fragmentationNo. of arousals 84.7 (87) 54.4 (34)No. of respiratory awakenings 28.3 (44) 3.9 (5.2) �.01Wake after sleep onset 78.0 (62) 65.4 (48)

Oxyhemoglobin saturationAverage O2 saturation, % 92.9 (3.4) 95.1 (2.8) �.01Time SpO2 <90%, min 297.8 (181) 184.6 (194) �.01

ApneasNo. of central apneas ⁄ h 17.6 (18) 5.4 (7.2) �.01No. of obstructive apneas ⁄ h 21.7 (31) 8.5 (12) �.05

Abbreviation: SpO2, oxyhemoglobin saturation.

quality of life in heart failure september • october 2009230

The purpose of this study was todetermine possible independent contri-butions of SDB to quality of life in indi-viduals with HF. As a first step,compared with individuals without HF,we sought to confirm prior studies’ find-ings showing that sleep is poor in HF,particularly showing high rates of CSAand OSA.6 Studies indicate that theseverity of SBD in HF reflects the sever-ity of HF, as indicated by pulmonaryartery pressure and pulmonary capillarywedge pressure.35 Also consistent withthe literature, fairly high rates of sleepapnea were observed in our otherwisehealthy group of comparison partici-pants.36 Regarding quality of life in HF,our findings extend the few existingstudies in this area by showing that SDBis independently associated with poorerquality of life in HF. We found thatindependent of demographic factors,functional status, fatigue, and depres-sion, the severity of apnea is associatedwith poorer quality of life in terms ofphysical functioning, but less so withemotional functioning.

Although there are no currentlyendorsed strategies for the treatment ofSDB in HF,37,38 there are several differ-ent treatment approaches that are prom-ising. Studies examining the effects ofcontinuous positive airway pressure(CPAP) for OSA are generally posit-ive. For example, studies examining3 months of CPAP for OSA report nor-malized AHI and improved LVEF inNYHA classes II or higher.14,39 Studiesusing CPAP or autotitrating CPAP forOSA and ⁄or CSA report improvementsin apnea severity as well as severaldomains of quality of life including phys-ical functioning, emotional well-being,and fatigue.39–41 In addition to improv-ing SDB and quality of life, CPAPmight also significantly reduce riskof death and hospitalization amongpatients with HF.15 Since CSA appearsto be a consequence of HF, some stan-dard therapies for HF such as b-blockersand diuretics may attenuate CSAseverity.38

In addition to CPAP, physical train-ing can improve SDB and associatedindices of quality of life. Six months ofexercise training in HF patients with

both systolic dysfunction (LVEF <45%)and SDB (AHI>10) led to a significantreduction in AHI (from 24.9 to 8.8) aswell as a reduction in the number ofCSA events per night (from 152 to50).42 Other studies show that exercisetraining improves quality of life in HF.43

Twelve weeks of nocturnal oxygen ther-apy for SDB leads to an improvement inAHI (from 21.0 to 10.0) in NYHA clas-ses II and III HF patients and an associ-ated improvement in quality of life.44

We found that the association of qual-ity of life with SDB was independent of

A

BNo

. of

Ob

stru

ctiv

e A

pn

eas/

hN

o. o

f C

entr

al A

pn

eas/

h

Figure. Number of central apneas per hour of sleep (A) and obstructive apneas per hour ofsleep (B) in 40 patients with heart failure (HF) and in 34 individuals without heart failure(non-HF) (means � SEM). HF patients had more central (P�.01) as well as obstructive(P�.05) apneas per hour.

Table III. Physical Functioning Quality of Life Regression Outcomes

REGRESSION BLOCKSa ⁄

SIGNIFICANT PREDICTORS

MODEL

ADJUSTED R2STANDARDIZED

ß COEFFICIENT P VALUE

1. — — — —2. 6-minute walk test .122 ).433 .0193. 6-minute walk test .416 ).324 .034

LVEF ).304 .035Depression .584 .000

4. 6-minute walk test .545 ).248 .068LVEF ).312 .015

Fatigue .632 .0045. 6-minute walk test .610 ).244 .055

LVEF ).346 .005Fatigue .468 .031

No. of obstructive apneas ⁄ h .343 .027No. of central apneas ⁄ h .301 .038

aBlock 1 included body mass index, sex, and ethnicity; block 2 included prior blockvariables plus 6-minute walk test results and left ventricular ejection fraction (LVEF); block 3included prior block variables plus depression (Beck Depression Inventory score); block 4included prior block variables plus fatigue (Multidimensional Fatigue Symptom Inventory–Short Form); and block 5 included prior block variables plus sleep variables from theMANOVA. Abbreviations: —, no significant predictor variables at that step of theregression model.

quality of life in heart failure september • october 2009 231

fatigue or depression. Fatigue is commonin OSA and can be associated withseverity of apnea.45 Depression too iscommon in HF and has been found tobe predictive of quality of life indepen-dent of LVEF.5 While the purpose ofthis study was not to identify predictorsof depression in HF, other studies reportthat severity of depression amongpatients with HF is associated with fati-gue and excessive daytime sleepiness,independent of physical functioning. Inour study, depression was initially a pre-dictor of physical functioning–relatedquality of life but then fell out of theregression model once fatigue wasentered. Fatigue remained a significantpredictor above and beyond the inde-

pendent contributions of SDB to physi-cal functioning. In contrast to physicalfunctioning, only fatigue was found tobe significantly associated with emo-tional functioning. The ongoing fatigueresulting from repeated sleep disruptionin individuals with OSA may be a medi-ator of poor quality of life observed inOSA.46 In pursuit of this possibility inHF, we ran mediator analyses47 andfound that fatigue was not a mediator ofthe relationship between SDB andpoorer physical functioning in our sam-ple of HF patients. If not fatigue anddepression, what might be mechanismslinking SDB to poorer quality of life inHF? More severe sleep apnea, likely as aresult of its associated daytime hypox-

emia, is associated with neurocognitivedeficits.11,48 Perhaps the more severeSDB seen in HF adversely affects qualityof life through its effects on cognition,although little attention has been paidto this area in HF49 that merits furtherstudy.

There are several limitations of thisstudy that should be addressed. Wehad relatively modest sample sizes foreach study group. In addition, ourcomparison group was not matchedfor sex. Finally, the vast majority ofour HF patients had more ‘‘mild’’ HF(ie, NYHA class II), and thus thefindings might not generalize to moresevere HF.

In summary, independent of HFseverity and independent of associatedfatigue and depression, SDB adverselyaffects health-related quality of life inpatients with HF, particularly physicalfunctioning quality of life. In addition tohelping delineate associations betweensleep and quality of life, the findings pro-vide more support for the sometimescontroversial position of more aggres-sively identifying and treating SDB inHF patients.

Acknowledgments: This work wassupported by grants HL-073355 and HL-57265 from the National Institutes of Healthand the UCSD General Clinical ResearchCenter (MO1RR-00827).

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Table IV. Emotional Functioning Quality of Life Regression Outcomes

REGRESSION BLOCKSa ⁄

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MODEL ADJUSTED

R SQUARE

STANDARIZED

ß-COEFFICIENT P-VALUE

1. — — — —2. — — — —3. Depression 0.553 0.772 .0004. Depression 0.717 0.261 .099

Fatigue 0.687 .0005. Fatigue 0.732 0.677 .000

Number of central apneas ⁄ hour 0.213 .070aBlock 1 included BMI, gender, ethnicity; Block 2 included prior block variables plus six-minute walk test and LVEF (left ventricular ejection fraction), Block 3 included prior blockvariables plus depression (Beck Depression Inventory), Block 4 included prior blockvariables plus fatigue (Multidimensional Fatigue Symptom Inventory-Short Form), Block 5included prior block variables plus sleep variables from the multivariate analysis of variance.Abbreviation: —, no significant predictor variables at that step of the regression model.

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