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Psychosomatic Medicine 61:496-507 (1999)
© 1999 American Psychosomatic Society

ORIGINAL ARTICLES

Association Between Subjective Sleep Quality and Depression on Immunocompetence in Low-Income Women at Risk for Cervical Cancer

Josée Savard, PhD, Suzanne M. Miller, PhD, Megan Mills, PhD, Ann O’Leary, PhD, Heather Harding, MS, Steven D. Douglas, MD, Charles E. Mangan, MD, Richard Belch, MD, PhD and Andrew Winokur, MD, PhD

From the Fox Chase Cancer Center, Philadelphia, PA (J.S., S.M.M., M.M., H.H.); Rutgers University, Piscataway, NJ (A.O.); Children’s Hospital of Philadelphia, Philadelphia, PA (S.D.D.); Pennsylvania Hospital, Philadelphia, PA (C.E.M.); Albert Einstein Medical Center, Philadelphia, PA (R.B.); and University of Connecticut, Storrs, CT (A.W.).

Address reprint requests to: Suzanne M. Miller, PhD, Division of Population Science, Fox Chase Cancer Center, 510 Township Line Road, Third Floor, Cheltenham, PA 19012. Email: sm_miller{at}fccc.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
OBJECTIVE: The purpose of this study was to investigate whether subjective sleep quality is more strongly associated with immunocompetence than depression among women at risk for cervical cancer.

METHODS: Participants were 91 women referred for colposcopy because of abnormal results on a Pap smear. On the day of the procedure, participants completed the Center for Epidemiological Studies Depression Scale, two indices of subjective sleep quality (ie, satisfaction with sleep obtained and degree of sleep restfulness), and a health behaviors assessment questionnaire. Levels of peripheral blood lymphocyte subpopulations (helper T, cytotoxic/suppressor T, NK, and B cells) were also assessed at this time. Approximately 10 days later, the presence of depressive disorder was assessed using the Structured Clinical Interview for DSM-III-R.

RESULTS: Hierarchical regression analyses revealed that satisfaction with the amount of sleep obtained was significantly associated with the circulating number and percentage of helper T cells (TH/CD4+) and the percentage of cytotoxic/suppressor T cells (TC/CD8+), after controlling for confounder variables (ie, age, smoking status, and drug use). Depression was significantly associated only with the percentage of TC cells. Sleep satisfaction remained significantly associated with the number and percentage of TH cells and percentage of TC cells after controlling for the variance explained by depression.

CONCLUSIONS: Results of this study suggest that subjective sleep quality shares a significant and independent portion of the variance with immunity that is not accounted for by depression. Although the long-term impact of these immune alterations on disease progression needs to be directly explored, it may be important to systematically screen for and manage sleep disturbance in women at high risk for cervical cancer.

Key Words: sleep • depression • immunity • psychoneuroimmunology • cervical cancer

Abbreviations: ASCUS = atypical squamous cells of uncertain significance; CD20+ = B cells; CES-D = Center forEpidemiological Studies Depression Scale; CIN = cervicalintraepithelial neoplasia; DSM-III-R = Diagnostic andStatistical Manual of Mental Disorders, third edition revised; DSM-IV = Diagnostic and Statistical Manual of MentalDisorders, fourth edition; EEG = electroencephalography; HDRS = Hamilton Depression Rating Scale; HPV = humanpapillomavirus; ICSD = International Classification of SleepDisorders; LGSIL = low-grade squamous intraepithelial lesion; MANOVA = multivariate analysis of variance; NK/CD3+/CD16+ = natural killer cells; PBS = phosphate-buffered saline; REM = rapid eye movement; SCID = Structured Clinical Interview for DSM-III-R; SD =standard deviation; TC/CD8+ =cytotoxic/suppressor T cells; TH/CD4+ =helper T cells.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
The relationship between depression and immune function has been a key focus of interest in studies of psychoneuroimmunology. In general, the findings suggest that medically healthy individuals who meet diagnostic criteria for a clinical depressive disorder demonstrate a number of immune alterations (1–4). These include reduced lymphocyte proliferation to mitogens and NK cell cytotoxic activity, as well as a reduction in the number and percentage of peripheral lymphocytes subpopulations, including NK, B, and T cells, as well as TH/CD4+ and TC/CD8+ cells. Despite these positive findings, some studies have failed to show an association between depression and immunity (5–7).

The inconsistencies in the literature may be reconciled by recent data showing that impaired sleep quality, a key concomitant of depression, is more strongly associated with immune downregulation than depression itself (8, 9). In a study comparing depressed and nondepressed individuals, objective indices of sleep quality, as assessed by EEG, including sleep efficiency (ie, the ratio of time slept by time spent in bed), total sleep time, and duration of non-REM sleep, were significantly associated with higher NK cell activity, independent of the presence of depression (9). In a follow-up study, insomnia, measured using the insomnia items of the HDRS (see Ref. 10), was significantly associated with decreased NK cell activity. Except for psychomotor retardation, other HDRS subscales and HDRS total score were not associated with alterations in immunity (8).

The purpose of the present investigation was to extend this line of research to women at risk for cervical cancer (11). Although overall mortality rates for cervical cancer have been reduced by 45% in the last 20 years in the United States (12), the incidence of cervical cancer among women younger than 45 years of age has been escalating (13–16). The rates of CIN, a precancerous condition of the cervix, have also been rising dramatically (17, 18). Unnecessary morbidity and mortality from these conditions can be substantially reduced through adherence to early detection regimens (19, 20). However, there appears to be a psychological cost associated with the feedback of an abnormal Pap smear result and with participation in diagnostic follow-up (11, 21–26).

These psychological sequelae, in turn, may have an effect on the promotion of cervical neoplasia (1, 11, 27, 28). For example, the results of prior research suggest that levels of depression and hopelessness (29, 30) and perceived impact of, and control over, life stressors are associated with the severity of cervical disease at diagnosis (31–33). Consistent with theory and findings in the field of psychoneuroimmunology, impairment in immune functioning may mediate the impact of psychological factors on the progression of cancer (1, 28, 34–38), including cervical disease (33). In a recent study (39), pessimism was significantly associated with immune downregulation among HIV-positive women at risk for cervical cancer.

There is also emerging evidence for the potential mediating role of sleep disturbance in the relationship between stress and immune downregulation. Hall et al. (40) observed that stress, defined by the report of increased intrusive and avoidant ideation, among bereaved individuals was associated with lower numbers of NK cells (see also Ref. 41). However, this relationship was no longer significant when the time spent awake during the initial period of non-REM sleep (assessed with EEG) was entered first into the model (see also Ref. 6). Another line of evidence supporting the immunosuppressive effect of sleep disturbance, although an indirect one, is provided by accumulating data showing that sleep deprivation in the laboratory produces a number of immune changes. Most relevant are studies of partial deprivation, in which participants are deprived of sleep for only a portion of the night to better approximate naturalistic sleep disturbance (42, 43). This paradigm has been found to lead to immunosuppressive effects, including a reduction in NK cells, NK cell activity, lymphokine activated killer cell activity, and the production of interleukin-2 (42, 43). Although the sleep deprivation laboratory paradigm may not be completely generalizable to the naturalistic effects of sleep disturbance, the data support the growing literature suggesting that poor sleep quality, rather than depression and related psychological states per se, accounts for the relation with immune alterations.

Sleep has been shown to be disturbed in 29% to 40% of women after receipt of a positive cytologic cervical screening result (22, 44). Therefore, these women may be at increased risk for immune downregulation and, in turn, for the progression of cervical disease. Indeed, immune function, particularly cell-mediated immunity, seems to play a key role in the development of virally related neoplasms, as is the case with cancer of the cervix (33, 45–49). It is now widely accepted that the presence of HPV, a DNA virus, is etiologically linked to precancerous and cancerous cervical disease (50–52). Among women with evidence of localized precancerous CIN, one recent study put HPV prevalence rates at 70% to 85% (53). Moreover, women with carcinoma in situ, or cervical cancer, have infection rates of 90% to 95% (20, 54–57). In contrast, infection rates for women without evidence of cervical disease are only at 15.4% (58). Despite the strong association between HPV and cervical disease, only 58% of HPV infections result in clinically apparent lesions (59). Thus, although the presence of HPV seems to be an important factor, it is not sufficient, by itself, to explain the development of oncogenic transformations in the cervix (49). It is increasingly believed that immunosuppression acts in conjunction with HPV to promote the progression of cervical lesions (49, 60). In summary, there is evidence that psychological factors are associated with the progression of cervical cancer. Furthermore, immunologic dysfunction appears to play a central role in the progression of cervical lesions. Immune alterations may act as a mediator between psychological factors and the promotion of cervical disease.

In the present study, we explored the relationships among depression, subjective sleep quality, and enumerative measures of immunity among women with mild cervical disease indicative of early HPV infection. Two dimensions of depression were assessed. The first dimension involved the presence of a clinically diagnosed depressive disorder, identified using a standardized, validated structured clinical interview format (61). The second dimension involved an assessment of the severity of depressive symptomatology based on a validated depression rating instrument (62). We thought it was important to assess both dimensions because an individual may exhibit high levels of depressive symptoms and yet may not be found to have a diagnosable depressive disorder. Furthermore, the severity of depressed mood has been found to be associated with immunosuppression, suggesting a linear relationship between depression and immunity (2, 4).

It was hypothesized that impaired subjective sleep quality, as well as indices of depression, would be associated with decrements in immunocompetence (as measured by the number and percentage of lymphocyte subsets present in samples of peripheral blood) (2, 63) after controlling for confounder variables. Furthermore, on the basis of data obtained by Cover and Irwin (8) and Irwin et al. (9), it was hypothesized that subjective sleep quality would be a more powerful predictor of immunocompetence than depression. The focus was on low-income, inner-city women, because this group is at highest risk for mortality due to cervical cancer (12). The sample was restricted to women with low grades of cervical dysplasia to explore the impact of psychological and behavioral variables at the initiation of the illness process (64). Consistent with current medical practice (65), patients were undergoing repeated screening but received no medical treatment. Therefore, the potential confounding effects of tumor processes and biological treatments were minimized (66).


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Participants
Participants were 91 women who had received an initial abnormal Pap smear test result and were referred for diagnostic follow-up (colposcopy and biopsy) to one of two colposcopy clinics in Philadelphia, Pennsylvania (Women and Children’s Health Services of Pennsylvania Hospital and Albert Einstein Colposcopy Clinic). Women were considered eligible for inclusion in the study if they (1) were between 18 and 45 years of age and (2) had received a Pap smear result of ASCUS, mild dysplasia consistent with HPV, or LGSIL/CIN I.

Participants were excluded if they (1) had undergone colposcopic examination in the past 2 years; (2) had a histologic diagnosis more severe than CIN I on colposcopy-directed biopsy; (3) had a history of life-threatening medical conditions (eg, cancer or HIV infection); (4) were using antihypertensive, antihistaminic, anti-inflammatory, or psychotropic medications; (5) were pregnant, had delivered a child in the past 12 months, or were breast-feeding; (6) had a CD4+ count lower than 500 (because this may indicate the presence of HIV infection or other immunosuppressive disease); (7) were unable to communicate readily in English; or (8) had less than an eighth-grade education.

A review of the medical charts revealed that 466 women met the initial inclusion criteria (ie, age and Pap test result). Of these, 40% (N = 186) could not be reached by telephone (ie, they had no phone or had moved) and failed to attend their colposcopy appointment as a result. Among patients contacted, 45 (9%) declined to participate. The major reason for declining was lack of time (42% of those who declined). Other reasons included a dislike of hospitals or doctors (7%), the personal nature of the questions (4%), a lack of interest in the study (4%), and fear of blood draws or needles (2%). Among the 235 remaining participants, 108 (23%) were found to be ineligible according to the exclusion criteria listed above, 16 (3%) did not undergo psychiatric diagnostic interview, and blood samples were unavailable for 16 (3%), leaving 95 potential participants. Four additional participants (1%) were subsequently excluded because of extreme data (outliers) on the immune measures.

The final sample of 91 participants (20% of the initial sample) consisted mainly of young, low-income, African American women. Mean age was 27.0 years (SD = 7.4; range, 18–44 years). Seventy-five percent of the sample was African American. Whites (13%) and Hispanic/Latinas (7%) accounted for the majority of the remaining sample, which also included women of Native American (2%), Asian/Indian/Pacific Islander (1%), or other (2%) descent. Forty-one percent of the sample were employed, 49% were receiving some form of public assistance, 2% received social security, and another 8% had no independent source of income. The majority of participants (70%) had completed either high school or trade school. Despite this, the monthly family income was only $711.37 (SD = $473.66). Sixty-seven percent of the sample were single, 22% were married or lived with their partner, and 11% were separated or widowed. Eighteen percent of participants were living alone with their children, 20% were living with their partner and children, 34% were living with their children and one or more other adults, and 28% had no children.

On biopsy, 33% of the sample received a diagnosis of LGSIL (including CIN I and mild dysplasia), and another 56% were diagnosed with a milder form of cervical disease (eg, ASCUS, cervicitis, or inflammation). Biopsy specimens were not obtained for 9% of participants, and the specimen was inadequate for diagnosis in 2% of participants. Viral typing was performed on exfoliated cervicovaginal cells using the polymerase chain reaction and hybrid capture. Results at the time of this writing are available on 50 patients (55% of the sample). Of those, 23 women (46%) were HPV positive, and 12 (24%) were infected with multiple HPV types from more than one risk category. This is consistent with current data on HPV infection in low-grade cervical disease (53). Among HPV-positive women, 39%, 65%, and 78% were infected with low-risk (types 6 and 11), moderate-risk (types 31, 33, and 35), and high-risk (types 16 and 18) types of HPV, respectively (67–70).

Procedure
Approximately 2 weeks before the colposcopy appointment, women determined to be potentially eligible on the basis of their referring Pap result and age were sent a letter that reminded them of their appointment, provided information on health insurance, briefly explained the study, and provided a phone number where they could obtain additional information about the study. Patients who did not call for more information were contacted by the research team by telephone 4 to 5 days before the scheduled appointment. In both cases, the research assistant reminded the patient of the colposcopy appointment and reassessed the participant’s study eligibility (ie, pregnancy, current and past medical illnesses, history of colposcopic examination, English fluency, and education level). Participants who still met the inclusion criteria were also provided with a brief explanation of the study.

For patients interested in participating, a precolposcopy assessment was scheduled at their home. During this visit, the study goals and procedures were fully described, and informed consent was obtained. Women who agreed to participate were asked to arrive approximately 30 minutes before their colposcopy appointment. At that time, they completed measures of depressive mood, subjective sleep quality, and health behaviors. All assessments were administered verbally to maximize comprehension.

During the colposcopic examination, the gynecologist took two cervical swabs (for HPV typing) and cervical biopsy samples as indicated. An average of 1.4 cervical biopsy samples (SD = 0.7), with a maximum of 3, were taken. Immediately after the procedure, peripheral blood samples (30 cc) were collected by a trained phlebotomist in heparinized tubes (for immune measures). All blood draws occurred between 1:30 PM and 3:30 PM to minimize the influence of diurnal variation on immune assessments. Approximately 10 days after the colposcopy visit, an appointment was scheduled at the study center office for a diagnostic interview to assess the presence of depressive disorder.

Measures
Background variables.
Demographic variables.

Age, marital and parental status, ethnic origin, education level, income, and source of financial support were assessed at baseline using a brief demographic questionnaire.

Health behaviors.
Specific health behaviors, particularly smoking, drug and alcohol use, physical activity, vitamin supplement use, and caffeine ingestion, have been shown to alter immunologic function (2, 63). In the present study, these behaviors were assessed at baseline with the following questions: (1) "Do you smoke?" (2) "Did you drink alcohol in the last week?" If yes, "How many drinks did you have in the last week?" (3) "How many cups of coffee, caffeinated tea, or cola have you had in the last 48 hours?" (4) "How many hours each day do you exercise or play sports?" (5) "Do you take daily vitamin supplements?" Drug use was assessed by asking the respondent to specify which of 16 drugs (eg, marijuana and cocaine) they had used in the past week. A dichotomous composite variable was created, indicating whether the respondent had used drugs.

Although there is some question about the validity of self-reported health behaviors, this represents the most practical assessment method and provides reasonably valid indices of a variety of health behaviors (71–73). Self-reported drug use, which is an illicit behavior, has been found to be a less valid measure (74–76). To address this issue, we used common or "street" drug names, emphasized the confidentiality of the data, and encouraged participants to refuse to answer a given question rather than to respond by giving a false answer. Participants were also asked about their menstrual status (ie, whether they were currently having their period, had it in the previous 2 weeks, or were expecting it in the next 2 weeks).

HPV typing.
During the colposcopic examination, two cervical swabs were taken for identification of HPV. Because many participants were infected with more than one HPV strain, women were categorized on the basis of the most severe strain detected, resulting in four categories: (1) high risk, (2) moderate risk, (3) low risk, or (4) no HPV.

Depression.
Depressive disorder.

The presence of a depressive disorder was assessed using the SCID (61), which was administered by a trained clinician. The SCID is a semistructured interview widely used in research, as well as in clinical practice, to determine the presence of psychiatric disorders, according to DSM-III-R diagnostic criteria. Participants were considered to have a current depressive disorder if they met the criteria for major depression, dysthymia, or adjustment disorder with depressed mood or mixed emotional features. The SCID can reliably assess the majority of axis I disorders, including depressive and adjustment disorders (61, 77–80).

Depressed mood.
Depressed mood was assessed with the CES-D (62), a widely used 20-item self-report scale. Respondents are asked to rate the frequency of occurrence of each symptom, in the past week, using a four-point Likert scale (eg, "I felt depressed" or "I thought my life had been a failure"). It has been specifically designed to be used with general, nonpsychiatric, populations and has been found to provide a reliable and valid measure of depressive symptomatology (81).

Subjective sleep quality.
Subjective sleep quality was assessed using two items. Specifically, participants were asked to rate (1) how often they obtained the amount of sleep they needed (on a seven-point Likert scale, where 1 = "never," 4 = "sometimes," and 7 = "always") and (2) their sleep restfulness at present (on a seven-point Likert scale, where 1 = "very restless," 4 = "about average," and 7 = "very restful").

Immunologic measures.
Four types of circulating lymphocytes were measured. These included TH/CD4+, TC/CD8+, NK/CD3+/CD16+, and CD20+ cells. The percentage of lymphocytes bearing each specific marker was determined using dual fluorescence-activated flow cytometry with whole-blood analysis on an Epics Elite flow cytometer equipped with two coherent Innova 300 series ion; 5-W ultraviolet-enhanced argon lasers operating at 300 mW; and a helium neon laser. Briefly, 0.01 ml of appropriately diluted monoclonal antibody was added to 0.1 ml of whole blood. After incubation for 30 minutes at 4°C, the samples were washed with PBS and 0.02 ml of appropriately diluted fluorescent isothiocyanate F(ab)12 goat anti-mouse immunoglobulin. Two milliliters of lysing-buffer ammonium chloride was then added to each sample to lyse erythrocytes, followed by a final wash with PBS and fixation in 10% paraformaldehyde. The absolute number per unit volume bearing each lymphocyte marker was determined by multiplying data obtained by flow cytometry with the absolute lymphocyte count derived from the complete blood count and differential. The number and percentage of NK cells and the percentage of TC cells were not normally distributed. Square root transformations successfully normalized these variables.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
First, we present descriptive data on the measures of depression and subjective sleep quality and their interrelations. Then, we present the results of correlational analyses (for continuous variables) and multivariate analyses of variance (for nominal variables) performed to determine confounder and study variables. Finally, the results of two sets of hierarchical regression analyses are presented. In the first set, potential confounders were entered on the first step, followed by subjective sleep quality scores (second step) and depression data (third step). Potential confounders were also entered on the first step in the second set of regressions, but depression and subjective sleep quality data were entered in the reverse order.

Interrelations of Depression and Sleep Variables
The mean CES-D score was 21.2 (SD = 12.9), which significantly exceeds the CES-D clinical cutoff score of 16. Indeed, 64% of participants had a score of 16 or higher. Hence, participants were generally highly depressed on the day of the colposcopic procedure. Using the SCID, 20 women (22% of the sample) met criteria for a depressive disorder, of which 15 had major depressive disorder (two had dysthymia superimposed), two had dysthymia, one had an adjustment disorder with depressed mood, and two had an adjustment disorder with mixed emotional features. With respect to satisfaction with sleep obtained, participants reported, on average, a sleep satisfaction of 4.4 (SD = 2.0), which corresponds to a little more than "sometimes." Only 24% of participants reported "always" getting the amount of sleep they needed, whereas 12% and 33% reported "never" or "sometimes" getting it, respectively. On average, women reported a sleep restfulness of 4.0 (SD = 2.0), which corresponds to a little less than "about average." Only 19% of women considered their sleep "very restful," and 30% and 17% considered it "about average" or "very restless," respectively.

Pearson’s (for normally distributed variables) and Spearman’s {rho} (for other variables) correlations were computed between the depression and subjective sleep quality measures. As shown in Table 1, these measures were significantly interrelated. Specifically, both the presence of a depressive disorder and more severe depressive mood were related to poorer subjective sleep quality. p < .05.


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  		Table 1. Correlational Analyses Between Depression and Subjective Sleep Quality Measures (N = 91)
 
Identification of Confounder and Study Variables
Relationship between background factors and enumerative measures of immunity.
To determine which variables would be included in the regression analyses, correlations were calculated between the background factors and immune variables. Among the background variables, age was the only factor to be associated with more than one immune variable. Age was significantly associated with a higher number (r(91) = 0.37, p < .0001) and percentage (r(91) = 0.44, p < .0001) of TH cells, with an increased number (r(91) = 0.31, p < .01) and percentage (r(91) = 0.24, p < .05) of B cells, as well as with a decreased percentage of TC cells (r(91) = -0.28, p < .01). MANOVAs revealed no significant differences in immunity for marital status (F(8,81) = 1.00; p = .46, with p values ranging from .06 to .61 for univariate analyses); for parental status (F(8,80) = 0.69; p = .86, with p values ranging from .28 to .90); or for ethnic origin (F(8,81) = 0.94; p = .53, with p values ranging from .11 to .34 for univariate analyses).

Because some participants (N = 52) were missing HPV typing data, it was not possible to control for the potential effect of HPV infection on immunity in the regression analyses. However, to investigate whether HPV infection influenced immunocompetence in the subsample, a MANOVA was conducted. No differences were found between the four HPV groups (ie, high, moderate, and low risk or no HPV) on immunity (F(8,40) = 1.07; p = .39, with p values ranging from .07 to .52 for univariate analyses).

Relationship between health behaviors and enumerative measures of immunity.
Correlational analyses and a MANOVA were also performed to investigate the relationship between health behaviors and immunity. Among the health behaviors, smoking status and drug use were the only variables to be significantly associated with more than one immune variable. More precisely, smokers were found to have a significantly higher number (rs(91) = 0.53, p < .0001) and percentage (rs(91) = 0.24, p < .05) of TH cells, as well as a decreased percentage of NK cells (rs(91) = -0.24, p < .05) and an increased number of B cells (rs(91) = 0.35, p < .001). Those who reported having used drugs in the past week had a significantly higher number (rs(91) = 0.23, p < .05) and percentage (rs(91) = 0.20, p < .05) of TH cells. A MANOVA was conducted on menstrual status to explore whether immunity varied as a function of follicular stage. No differences were found across stage on any of the immune variables (F(8,79) = 1.05; p = .40, with p values ranging from .12 to .42 for univariate analyses).

Relationship between sleep and enumerative measures of immunity.
Correlational analyses were conducted to determine which of the sleep variables was related to immunity. Immunity was significantly associated with how often women could obtain the amount of sleep they perceived they needed. Specifically, women who were better able to obtain the sleep they needed had a greater number (r(91) = 0.23, p < .05) and percentage (r(91) = 0.27, p < .01) of TH cells and a lower percentage of TC cells (r(91) = -0.24, p < .05). Sleep restfulness was not significantly related to any of the immune variables (p values ranging from .16 to .98). Consequently, it was not included in the follow-up regression analyses.

Relations of Subjective Sleep Quality and Depression to Enumerative Measures of Immunity
Two sets of hierarchical regression analyses were performed. In the first set of regression analyses, the confounder variables (ie, age, smoking status, and drug use) were entered first, followed by the subjective sleep quality variable (ie, satisfaction with sleep obtained) on the second step, and depression (SCID and CES-D) on the third step. In the second set of regression analyses, the confounder variables were entered on the first step, the depression data were entered on the second step, and the subjective sleep quality variable was entered on the third step.

As shown in Table 2, age, smoking status, and drug use together explained 23% of the variance in the percentage of TH cells. The addition of satisfaction with sleep obtained to the equation resulted in a significant increment in R2 (7%), but the addition of depression on the third step did not reliably improve the prediction of the percentage of TH cells. When depression was entered before the sleep satisfaction variable (on the second step), depression did not significantly increase the prediction of this immune variable. On the other hand, subsequent addition of satisfaction with sleep obtained (on the third step) still resulted in a significant increment in the R2. Indeed, the sleep satisfaction variable still explained 7% of the variance in the percentage of TH cells. A higher satisfaction with sleep obtained was associated with an increased percentage of TH cells.


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  		Table 2. Hierarchical Regression of Subjective Sleep Quality and Depression on Percentage of TH (CD4) Cells (N = 91)
 
A similar pattern of results was found for the absolute number of TH cells (see Table 3. Specifically, age, smoking status, and drug use together explained 33% of the variance, which was again significant. When entered on the second step, satisfaction with sleep obtained added significantly to the prediction of the TH cells number (5%), whereas depression did not when entered on the third step. Even when depression was entered into the regression model before the sleep satisfaction variable (on the second step), it did not reliably improve R2, whereas subsequent addition of satisfaction with sleep obtained (on the third step) significantly added to the prediction of the number of TH cells (5%). A higher level of sleep satisfaction was found to be associated with a greater number of TH cells.


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  		Table 3. Hierarchical Regression of Subjective Sleep Quality and Depression on Number of TH (CD4) Cells (N = 91)
 
Table 4 displays the pattern of results obtained for the percentage of TC cells. The confounding variables entered on the first step together explained 8% of the variance. The addition of satisfaction with sleep obtained on the second step resulted in a significant increment in R2 (6%), whereas subsequent addition of depression only marginally significantly contributed to the prediction of the TC cell percentage. Even though depression significantly improved R2 when entered on the second step (7%), addition of satisfaction with sleep obtained on the third step remained a significant predictor of this immune variable, which still explained 5% of the variance. In this case, increased sleep satisfaction was associated with a lower percentage of TC cells. Depression and subjective sleep quality did not significantly predict the number of TC cells or the number and percentage of NK or B cells.


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  		Table 4. Hierarchical Regression of Subjective Sleep Quality and Depression on Percentage of TC (CD8) Cells (N = 91)
 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
ACKNOWLEDGMENTS
 REFERENCES
 
The goal of this study was to investigate the effects of depression and subjective sleep quality on immunocompetence among low-income women undergoing follow-up screening for an abnormal Pap smear result. The mean level of depressed mood was found to fall within the clinically depressed range. Indeed, a large proportion of participants (22%) were found to suffer from a depressive disorder. These data are consistent with previous findings suggesting high levels of emotional distress after the receipt of an abnormal Pap smear result (11, 21–26). In addition to elevated rates of depression, a significant proportion of women (45%) estimated that their sleep was unsatisfying, with only 24% reporting that they always received the amount of sleep they needed. Finally, participants with either clinical depression or more severe depressive symptomatology reported poorer subjective sleep quality.

As predicted, subjective sleep quality was found to be a significant predictor of enumerative measures of immunity. Specifically, higher satisfaction with sleep obtained was related to an increased absolute number and percentage of TH cells and a decreased percentage of TC cells. Importantly, even after controlling for the effect of depression, including both the presence of depressive disorder and the severity of depressed mood, subjective sleep quality was still found to be significantly associated with immune alterations. These results suggest that subjective sleep quality shares a significant and independent portion of the variance with immunity that is not accounted for by coexistent depression.

The present findings are consistent with those of studies showing immunosuppression after laboratory sleep deprivation among healthy individuals (42, 43). The results are also consistent with results of clinical studies of depressed patients showing that sleep disturbance, not coexisting depression per se, alters immune function (8, 9). In our sample, poor sleep quality had a deleterious impact, regardless of depression status. These results build on and extend prior research with depressed patients to a cervical cancer model and suggest that the presence of sleep disturbance may be sufficient to alter immunocompetence, even in the absence of depression (see also Ref. 40). This process, in turn, may promote the progression of cervical disease (33, 39). Future research in this area should assess sleep impairment more extensively by systematically tapping its multidimensional aspects (ie, the nature, frequency, and severity of the problem). In particular, it will be important to assess the presence or absence of insomnia according to DSM-IV or ICSD classification systems. This assessment should ideally be objective, using sleep laboratory evaluation procedures (eg, polysomnography), as in Irwin et al. (9) and Hall et al. (40).

With respect to the clinical relevance of the immune alterations observed in this study, accumulating evidence supports the role of TH cells in the promotion of cervical cancer. For example, HIV-seropositive women are at significantly elevated risk for the development and recurrence of precancerous and cancerous cervical disease, especially those who have lower levels of TH cells and who are at more advanced stages of HIV disease (82–97). Higher prevalence rates of HPV have also been found in HIV-seropositive women, proportional to their level of immunosuppression (84, 96, 99, 100). Moreover, it has been shown that TH cells are involved in the defense against HPV-transformed cells (101). Hence, immunosuppression in general, and depletion of TH cells in particular, may interact with HPV infection to increase the risk of cervical cancer. The clinical relevance of alterations in TC cells for cervical cancer progression has received less attention. However, increased TC cells have been observed in women with cervical cancer and preinvasive neoplasia (102–107). Although poor subjective sleep quality was associated with increased, rather than decreased, TC cells, this relationship is probably not indicative of a favorable prognosis for cervical cancer progression.

In this study, sleep restfulness was not found to be associated with immunologic markers. This finding is consistent with recent data (108) suggesting that sleep satisfaction is a better indicator of an insomnia disorder, defined as meeting DSM-IV (109) and the ICSD (110) diagnostic criteria, than is sleep restfulness. As with previous research, certain background variables (ie, age, smoking, and drug use) were found to be associated with enumerative measures of immunity. Age has been found to be associated with increased TH cells and decreased TC cells (111–113). Furthermore, smoking has consistently been found to be associated with increased number and percentage of circulating T and TH cells (114–117). Marijuana usage, which represented the majority of drug users in this study, has also been found to result in higher levels of TH cells (118). These results underscore the need to control for the variance accounted for by these factors in psychoneuroimmunological studies (2, 63).

The two indices of depression, depressive disorder and depressed mood, were generally unrelated to immune function. The one exception was the association between severity of depressed mood and the percentage of TC cells. Although the literature tends to support an immunosuppressive effect of depression (1, 2, 4), the present findings are consistent with data obtained by Cover and Irwin (8) and other research teams who obtained null findings (eg, Refs. 5–7). In the present sample, the lack of an effect may be explained by the fact that participants were fairly young and ambulatory. The strongest relationships between depression and immunosuppression have been found in older, hospitalized depressed patients (2, 4, 7).

The absence of an association between depressed mood and immunity may be further explained by the specific depression measure used. Most studies showing a positive relationship between severity of depression and immune function have used the HDRS (eg, Refs. 119–121). Three HDRS items (ie, initial insomnia, middle insomnia, and early morning insomnia) are used to assess sleep impairment, out of a total of 17 items. These items account for 18% of the total depression scale. In comparison, the CES-D contains only one item assessing sleep, which represent only 5% of the total scale. If sleep is the major symptom accounting for the immunosuppressive effect of depression, then depression scales comprised of fewer sleep disturbance items should show a weaker association with immunity than those comprised of more sleep disturbance items. In addition, the only CES-D sleep item assesses sleep restfulness, and this construct was not found to be related to immune alterations in the present study.

The present research is characterized by a number of strengths. First, it focuses on a high-risk population for cervical cancer, namely young, low-income, inner-city women. Second, strict criteria (ie, pregnancy, history of severe medical illness, and use of particular medications) were used to exclude individuals with conditions that can influence immune functioning. Third, the contribution of relevant demographic and health behavior confounders on immune alterations was statistically controlled. This is important, because changes in health behaviors that are common in depression (especially increased smoking and drug and alcohol use) can constitute an indirect pathway through which depression may have an effect on immunity (63).

The primary limitation of the present study is its cross-sectional design. Findings from a larger, ongoing 2-year longitudinal study will allow us to (1) confirm the direction of causality of the relationships observed and (2) determine their long-term clinical significance for the development of cervical cancer. Additional limitations include the failure to control for the potential effect of HPV infection on immune functioning. Our preliminary analyses suggest that HPV typing does not have an impact on immunity with low-grade cervical lesions; however, the issue merits further investigation. In addition, as in other studies (122–125), health behaviors were assessed through retrospective self-reports. Although more sophisticated approaches (eg, urine or hair analysis) are often impractical, particularly with hard-to-access populations, the use of a daily diary or other more systematic forms of record keeping may help to reduce assessment bias (126). Finally, a subset of women who met broad inclusion criteria, according to the initial medical chart review, were not ultimately eligible for participation in the study. Hence, the findings may not be generalizable to the larger population of women at risk for cervical disease.

The results of this study may have implications for the clinical management of cervical cancer risk. If the relationship between impairment in sleep quality and immunocompetence is shown to be robust, and to affect cervical cancer progression, it may be useful to routinely assess patients for symptoms of sleep disturbance. It may also be important to target these symptoms in routine cervical risk management by implementing and evaluating the efficacy of cognitive–behavioral interventions that have been found to be effective for clinical insomnia. Potential intervention strategies that may be effective for this group include sleep restriction procedures, stimulus control instructions, and cognitive restructuring (127, 128). The psychoneuroimmunologic linkages and applications explored here may be relevant not only to the management of cervical risk but, ultimately, also to other cancer risk and chronic disease models (11).


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
REFERENCES
 
Preparation of this manuscript was supported in part by National Institutes of Health Grants CA58999, CA61280, CA06927, CA76446, and HG01766; Department of Defense (DOD) Grants BC971638 and OC970004; American Cancer Society Grant PB-89318; a research fellowship from the National Cancer Institute of Canada (supported with funds provided by the Terry Fox Run); and appropriations from the Commonwealth of Pennsylvania. The authors acknowledge the assistance of Lloyd Ohls, Rob Sipps, Leeann Speechley, Victoria Green, Kathy Keegan, Beth Mallon, Christine Plourde, Melissa Jenkins, Donald Campbell, Joann Cutilli, Nancy Tustin, Beth Cook, and Lisa Petrie.

Received for publication August 7, 1998.

Revision received March 29, 1999.


   REFERENCES
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 DISCUSSION
 ACKNOWLEDGMENTS
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