The prevalence of depressive symptoms among persons living with HIV is more than double than that found in the general population, with studies reporting on prevalence levels as high as 34% [1–3]. Several studies indicate that depressive symptoms are associated with disease progression and death in individuals with HIV prior to the development of effective HIV antiretroviral therapies (e.g. HAART), and since the introduction of these more effective therapies these associations have been magnified [4–11]. The mechanism of how depressive symptoms impact HIV disease progression is unclear [12,13]. Depressive symptoms may impact survival and disease progression through biologic factors mediated through CD4+ T and CD8+ T cells [4,6,8], CD56+ and CD16+ natural killer (NK) cells [14,15] or through health-related behaviors, since it has been shown that patients presenting depressive symptoms are more likely to have an early discontinuation or delayed initiation of HIV antiretroviral therapy [7,8,16–18] Depression has also been shown to be closely associated with non-adherence to therapy, which in turn, is associated with both disease progression and survival [16,17,19,20].
No study to date has specifically evaluated whether depressive symptoms impact survival exclusively among antiretroviral-naive individuals, nor the extent to which the association between depression symptoms and survival in individuals with HIV is modified by adherence to therapy. We set out to examine the association between depressive symptoms and mortality among patients first initiating HAART and the potential role of patient adherence as a confounder and effect modifier of this association.
HIV/AIDS drug treatment program
The British Columbia Centre for Excellence in HIV/AIDS (the Centre) distributes antiretroviral agents at no cost to all eligible individuals infected with HIV through its drug distribution program. This program has been described in detail elsewhere . Antiretroviral therapy is distributed according to the specific guidelines generated by the Therapeutic Guidelines Committee. The Centre's guidelines have been regularly updated and remain consistent with those from the International AIDS Society-USA [21–23].
Physicians enrolling an individual with HIV in the Drug Treatment Program must complete a drug request enrolment form. This form acts as a legal prescription and compiles information on the patient's address, enrolling physician, past HIV-specific history, CD4 cell count, HIV viral load and current drug requests. A qualified practitioner reviews all requests to verify that they follow the therapeutic guidelines outlined by the Centre. Approved prescriptions are renewed every 1 to 3 months. At the time of first refill, each patient is asked to complete an enrolment survey that elicits self-reported sociodemographic, clinical and behavioral information. The Providence Health Care Research Ethics Board has approved the use of the data generated from the program for research purposes.
All study participants were ≥ 18 years old, naive to antiretroviral therapy when they started HAART, which consisted of two nucleoside reverse transcriptase inhibitors, plus one protease inhibitor or one non-nucleoside reverse transcriptase inhibitor. Data were collected between 1 August 1996 and 30 June 2002. All participants completed a participant survey in their first year of therapy.
Outcome measures and independent variables
The Centre's enrolment survey incorporates the Center for Epidemiologic Studies Depression Scale (CES-D Scale). CES-D is a short scale designed to measure current levels of depressive symptoms. The scale scoring has been explained elsewhere [2,24]. As for comparable studies, a cut-off of 16 points in the CES-D scale (range, 0–60) was used to indicate the presence of depressive symptoms [2,6,8]. The presence of depressive symptoms was evaluated using a dichotomous variable based on this cut-off (CES-D ≥ 16 (yes) versus CES-D < 16 (no)). We also conducted a sensitivity analysis to evaluate the effect of data incompleteness using instead the Center for Epidemiologic Studies Short Depression Scale (10 item CES-D Scale) . A cut-off of 10 points in the CES-D scale (range, 0–30) was used to indicate the presence of depressive symptoms.
The primary endpoint in this study was time to all-cause mortality. It was not possible to run the analysis in this study for only HIV-related deaths due to the lack of power in this latter analysis. Deaths were identified on a continuous basis from physician reports and by record linkages with the British Columbia Division of Vital Statistics Agency. Event-free subjects were censored as of 30 June 2003. Independent baseline variables included in our study were CD4 cell count, plasma HIV RNA levels, physician's experience with HIV patients, gender, age, aboriginal status, an AIDS diagnosis, depressive symptoms, income, education, history of injection drug use and adherence. Physician experience was based on the experience of first follow-up physician of each patient. This variable represented the cumulative number of patients with HIV receiving antiretroviral therapy within the physician practice accounting for the date of subject's first known eligibility . Income was defined as a total yearly income of ≥ $10 000 or < $10 000 (in Canadian dollars), which approximates the low income cutoff for Canada [26–28]. Education was defined as having a high-school diploma or not. History of injection drug use was defined as ‘ever-injected drugs’ (yes versus no), which was physician or self-reported. Adherence was estimated using follow-up pharmacy refill compliance during the first year of therapy. In brief, we estimated adherence level by dividing the number of months of medications dispensed by the number of months of follow-up. This measure of adherence has been shown to be independently associated with survival among persons with HIV enrolled in the HIV/AIDS drug treatment program . Patients were defined a priori as non-adherent if they received antiretroviral medications for less than 95% of the follow-up period during the first year of therapy, as in previously published work [30,31].
Epidemiological and statistical analyses
We conducted a series of analyses as described in Gordis  and Rothman and Greenland  to determine the role of adherence as a potential confounder and effect modifier factor in the relationship between depressive symptoms and mortality. Confounding is a bias commonly found in observational epidemiological studies. For adherence to be considered a confounder in the relationship between depressive symptoms and mortality, it should be a risk factor for mortality, and it should be associated with depressive symptoms. When testing adherence for effect modification, we should determine whether the association between depressive symptoms and mortality is equally strong in each strata defined by adherence level. Effect modification is also known as interaction. If the association of main interest is proven to be equally strong across the different levels of adherence, we say that there is no interaction, or that adherence is not an effect modifier in this association. For this latter analysis, we created a new four-level categorical variable combining the levels of adherence (< 95% and ≥ 95%) and depressive symptoms (CES-D < 16 and CES-D ≥ 16). Adherence, if determined to be an effect modifier, was included in all analyses as this 4-level categorical variable. More details about confounding and effect modification are given in the section entitled ‘Confounding and effect modification by adherence on the relationship between depressive symptoms and mortality’, which follows the Discussion section.
Baseline information on CD4 cell count, plasma HIV viral load, physician's experience with patients with HIV, gender, age, aboriginal status, history of injection drug use, income, education, and AIDS diagnosis (to control for opportunistic infection prophylaxis as well as disease stage) were also included in the model as potential confounders. Since we are now dealing with several factors that, simultaneously, can potentially be considered as confounders, we cannot any longer apply the technique described in the section entitled ‘Confounding and effect modification by adherence on the relationship between depressive symptoms and mortality’. In order to cope with this level of complexity, several authors have suggested a backward stepwise approach to select potential confounders for evaluation, based on the magnitude of change in the coefficient of the explanatory variable of main interest . Starting with the full model, variables were dropped one at a time, using the relative change in the coefficient for the variable related to depressive symptoms as a criterion, until the maximum change from the full model exceeded 5%, which is a more conservative approach than the one suggested by Maldonado and Greenland .
Analyses were performed using SAS software version 9.1.3 Service Pack 3 (SAS Institute Inc., Cary, North Carolina, USA). Categorical variables were analyzed using the Pearson chi-squared statistic, and continuous variables were analyzed using the Wilcoxon rank sum test. Cox-proportional hazard regression was used to model the effect of depressive symptoms and other potential confounders on survival time . The assumptions of proportional hazards were examined graphically.
Between 1 August 1996 and 30 June 2002, a total of 1011 antiretroviral-naive participants aged 18 years and over initiated triple combination therapy consisting of two nucleoside reverse transcriptase inhibitors plus a protease inhibitor or a non-nucleoside reverse transcriptase inhibitor. Among them, 448 (44%) were excluded from the analyses because they did not complete all 20 questions on the CES-D scale during the baseline survey. A total of 563 individuals (91% males) were involved in the study and followed by a median of 4 years [interquartile range (IQR), 3–6 years]. At baseline, the median age was 38 years (IQR, 34–46 years), CD4 cell count was 230 cells/μl (IQR, 80–390 cells/μl), HIV RNA plasma viral load was 120 000 copies/ml (IQR, 43 800–280 000), and physician experience was 77 patients per physician (IQR, 9–199 patients per physician). Of these subjects, 35% had an average annual income of less than $10 000, 29% did not complete high school, 28% had a history of injection drug use, 13.7% reported being aboriginal, 20% had an AIDS diagnosis, and 23% of participants were less than 95% adherent in the first year of follow-up. The overall all-cause mortality rate was 10% during follow-up. When participants who did not complete the enrollment survey were compared with those who completed it, they tended to be female, have no high school completion, lower income, higher baseline CD4 cell count, lower baseline HIV RNA plasma viral load, less experienced physicians, lower adherence and longer survival (P < 0.05).
At baseline, 289 individuals (51%) were classified as having depressive symptoms (CES-D ≥ 16). As noted in Table 1, depressive symptoms was associated with high school completion, annual income, history of injection drug use, physician experience, gender, and adherence (P < 0.05). When we compared each level of these variables across the depressive symptoms strata (CES-D ≥ 16 versus CES-D < 16), females were more likely to present depressive symptoms than males, and non-adherent patients, those with a history of injection drug use, those with no high school completion and those with income < $10 000 were also more likely to have depressive symptoms. Age, AIDS diagnosis, aboriginal status, CD4 cell count, and plasma HIV viral load were not significantly associated with depressive symptoms.
Our analyses (see section entitled ‘Confounding and effect modification by adherence on the relationship between depressive symptoms and mortality’ below) found that adherence is a confounder and effect modifier in the relationship between depressive symptoms and mortality. In this study population it is also important to control for the effects of age, gender, aboriginal status and history of injection drug use as potential confounders in this relationship. However, we observed that in Table 1 there is no apparent association between age, aboriginal status and depressive symptoms, which by definition would disqualify these variables as confounders in our analyses. Nevertheless, as few aboriginal people were included in the study, aboriginal status could arguably be regarded as a confounder. This same conclusion was applied to age.
In all subsequent analyses we used the four-level categorical variable combining the levels of adherence (< 95% and ≥ 95%) and depressive symptoms (CES-D < 16 and CES-D ≥ 16). The univariate analysis of baseline factors associated with all cause mortality is presented in Table 2 (Model 1). The univariate analysis for baseline characteristics showed that only age, CD4 cell count (per 100 decrease), education, income, history of injection drug use, aboriginal status, adherence and depressive symptoms were associated with mortality. Table 2 also presents the multivariate analysis results for the association between depressive symptoms, adherence and mortality, after controlling for several confounder variables flagged applying the change-in-coefficient method for confounder selection. When only age and gender were forced into the model (Model 2) those with no depressive symptoms and with adherence < 95% were 4.79 times [95% confidence interval (CI), 1.91–12.02] more likely to die than those with no depressive symptoms and with adherence ≥ 95%. As also shown by this model, those with depressive symptoms and with adherence < 95% were 5.90 times (95% CI, 2.55–13.68) more likely to die than those with no depressive symptoms and with adherence ≥ 95%. When aboriginal status and history of injection drug use, in addition to gender and age, were also forced into the multivariate model (Model 3) we observed that the association between depressive symptoms and adherence with mortality remained very strong, with poorly adherent individuals with depressive symptoms being more likely to die.
A similar gradient in all cause mortality is shown in Figs 1 and 2, where, respectively, we provide the crude Kaplan–Meier estimates and the estimated model-based survival probabilities of mortality by the levels of adherence and depressive symptoms. As shown in Fig. 1, the mortality rate was very distinct among the different depressive symptoms and adherence groups, with non-adherent individuals with depressive symptoms having higher mortality rates (log-rank test P-value: < 0.0001). When only adherent patients were considered, the mortality rate was similar for those with and without depressive symptoms (log-rank test P-value, 0.2176). When only non-adherent patients were considered, the mortality rate was elevated among patients with depressive symptoms (log-rank test P-value: < 0.0001). The estimated median model-based survival probabilities for the four adherence × depressive symptoms groups are shown in Fig. 2; these were, respectively: 97% (IQR, 94–98%) for no depressive symptoms and adherence ≥ 95%; 94% (IQR, 91–97%) for depressive symptoms and adherence ≥ 95%; 87% (IQR, 78–93%) for no depressive symptoms and adherence < 95%; and 81% (IQR, 72–89%) for depressive symptoms and adherence < 95%.
Depressive symptoms can impact HIV disease outcomes through multiple mechanisms. To our knowledge this is the first study to demonstrate that both depressive symptoms and adherence were associated with mortality, when included in the same analyses, after controlling for known baseline confounders. In our analyses, combining both depressive symptoms and adherence, we found that presence of depressive symptoms (i.e., CES-D ≥ 16) among non-adherent patients was associated with mortality in patients initiating HAART [hazard ratio (HR) = 5.90; 95% CI, 2.55–13.68] after controlling for several baseline confounder variables. Conversely, the same association was not seen among adherent patients (HR = 1.39; 95% CI, 0.62–3.12).
This was the first study that we are aware of to evaluate a graded impact of depressive symptoms and adherence on the mortality risk in a cohort of patients exclusively on HAART. Studies report conflicting evidence about the association between depressive symptoms (using CES-D) and mortality among HIV-infected individuals [5,6,8,37–41]. Among the studies showing an association between depressive symptoms (using CES-D) and mortality, these studies did not address the potential confounding and effect modification of adherence to therapy on this relationship [6,8,37]. There are several other features of our study that should be highlighted. First, our study was carried out within a province-wide treatment program where all individuals with HIV have access to medical attention, combination antiretroviral therapy, and laboratory monitoring free of charge. We believe, therefore, that our results are not influenced by access to therapy-related issues that have often compromised the interpretation of similar cohort-based studies. Second, this study was based on treatment-naive individuals, thus our results are not confounded by previous therapy use. Third, by measuring depressive symptoms at baseline and adherence at the end of the first year of therapy we avoided and minimized, respectively, the effect of downward drifts as HIV disease progresses.
Our study has a number of limitations. First, the CES-D scale is not a diagnostic tool. It commonly overestimates the number of individuals who actually have clinical depression . However, the majority of our sample did not score in the severe range of depressive symptoms, and our analysis suggests that the observed relationship was not driven by the more severe group. An advantage of the CES-D scale over some measures of depression like the Hamilton Depression scale , is that the CES-D focuses on mood and excludes physical symptoms associated with HIV that might confound the present analyses. While we recommend that future studies should seek to examine these relationships in more detail, resources required for clinical detection of depressive symptoms in such a large cohort are substantial, and the use of CES-D has been shown to have a well-established precedent of use and utility in epidemiological studies [2,37,38]. Second, some studies have suggested that some depression scales that include somatic symptoms may inflate depression scores for people living with HIV infection, due to the overlapping of depression and HIV symptoms . Kalichman et al.  examined the degree in which items, reflecting somatic depression symptoms, in the Beck Depression Inventory (BDI) and in the CES-D scales overlap with symptoms of HIV disease. The authors found that the BDI items reflecting somatic symptoms showed very high associations with HIV disease symptoms. However, when the authors examined the CES-D somatic items associated with HIV disease symptoms, they observed that the highest associations were for items that did not reflect somatic concerns, and they attributed this finding to the possibility that the CES-D scale is more of a mood symptoms scale (reflecting illness experiences), rather than a physical symptoms scale. Thus, if somatic symptoms influenced our associations, the prevalence rate reported here might be overestimated, and it could be argued that the relationship seen between mortality and depressive symptoms could be due to the CES-D scale interpreting HIV symptoms as depression. However, based on the findings by Kalichman et al. , and since baseline disease markers were controlled for in all analyses, we possibly might have corrected for this potential source of bias. Third, given the multitude of possible prognostic variables, we did not have adequate statistical power to investigate and control for effect modification by all these prognostic variables, and in particular the effect modification of aboriginal status and history of injection drug use. However, investigating these relationships should be pursued in future research. Lastly, our study might be limited by a certain degree of response bias. In this study, the overall CES-D score was only calculated for those respondents that completed all 20 questions on the CES-D scale during the baseline survey (56% of individuals from our initial cohort). It is possible that people with severe depressive symptoms were not motivated enough to complete the baseline survey. If this is true, our results would have been biased toward a less depressed sample. However, based on the results shown in this study we believe that this bias, if present, did not play a significant role in biasing our results downward, since we were able to prove a strong association between depressive symptoms with mortality.
In conclusion, we found that depressive symptoms were strongly associated with higher mortality among naive individuals initiating HAART. This relationship was the strongest among non-adherent individuals with depressive symptoms. Efforts to diagnose and treat depression, especially in individuals with sub-optimal adherence may be an important strategy for reducing psychiatric morbidity, as well as improving adherence and potentially disease outcomes.
Confounding and effect modification by adherence on the relationship between depressive symptoms and mortality
1. The crude association between depressive symptoms and adherence is given by a crude mortality hazard ratio (HR) for depressive symptoms (CES-D ≥ 16) of 1.75 (95%CI, 1.00–3.06). Is this association confounded by adherence?
2. We investigated the potential confounding of adherence by stratifying the data by adherence levels and examining the stratum-specific HRs.
a. Adherence ≥ 95%: The crude HR for depressive symptoms (CES-D ≥ 16) is 1.64 (95% CI, 0.74–3.61).
b. Adherence < 95%: The crude HR for depressive symptoms (CES-D ≥ 16) is 1.52 (95% CI, 0.69–3.37).
3. Conclusion: the HRs in both adherence strata are no longer statistically significant, and the effects are similar in magnitude and smaller than those found in item (1). Therefore adherence is a confounder factor that needs to be controlled for in the analysis.
1. Now the question we should ask is whether the observed association between depressive symptoms and mortality risk is modified by adherence. For this we need to assess two types of effect modification: additive and multiplicative effects.
a. Additive model
b. Multiplicative model
2. Conclusion. We observed that under the multiplicative model there is a much closer agreement between the observed and expected hazard ratios, thus suggesting that the relationship among adherence, depressive symptoms and mortality is multiplicative.
We thank Benita Yip, Elizabeth Ferris, Marnie Gidman, Nada Gataric, Kelly Hsu, Patricia Krentz, Myrna Reginaldo, Peter Vann for their research and administrative assistance.
Author contributions: study concept and design: V.D.L., J.G., D.R.B., T.L.P., M.D., T.K., J.S.G.M., R.S.H.; acquisition of data: R.S.H., J.S.G.M.; analysis and interpretation of data: V.D.L.; drafting of the manuscript: V.D.L.; critical revision of the manuscript for important intellectual content: V.D.L., J.G., D.R.B., T.L.P., M.D., T.K, J.S.G.M, R.S.H.; statistical analysis: V.D.L.; obtained funding: R.S.H.; administrative, technical, or material support: R.S.H.; study supervision: R.S.H.
Sponsorship: This work was supported by the Michael Smith Foundation for Health Research through a Senior Scholar Award to R.S.H.
1. Barnes GE, Currie RF, Segall A. Symptoms of depression in a Canadian urban sample. Can J Psychiatry 1988; 33:386–393.
2. Low-Beer S, Chan K, Yip B, Wood E, Montaner JS, O'Shaughnessy MV, et al
. Depressive symptoms decline among persons on HIV protease inhibitors. J Acquir Immune Defic Syndr 2000; 23:295–301.
3. Turner BJ, Laine C, Cosler L, Hauck WW. Relationship of gender, depression, and health care delivery with antiretroviral adherence in HIV-infected drug users. J Gen Intern Med 2003; 18:248–257.
4. Burack JH, Barrett DC, Stall RD, Chesney MA, Ekstrand ML, Coates TJ. Depressive symptoms and CD4 lymphocyte decline among HIV-infected men. JAMA 1993; 270:2568–2573.
5. Farinpour R, Miller EN, Satz P, Selnes OA, Cohen BA, Becker JT, et al
. Psychosocial risk factors of HIV morbidity and mortality: findings from the Multicenter AIDS Cohort Study (MACS). J Clin Exp Neuropsychol 2003; 25:654–670.
6. Ickovics JR, Hamburger ME, Vlahov D, Schoenbaum EE, Schuman P, Boland RJ, et al
. Mortality, CD4 cell count decline, and depressive symptoms among HIV-seropositive women: longitudinal analysis from the HIV Epidemiology Research Study. JAMA 2001; 285:1466–1474.
7. Leserman J, Petitto JM, Gu H, Gaynes BN, Barroso J, Golden RN, et al
. Progression to AIDS, a clinical AIDS condition and mortality: psychosocial and physiological predictors. Psychol Med 2002; 32:1059–1073.
8. Mayne TJ, Vittinghoff E, Chesney MA, Barrett DC, Coates TJ. Depressive affect and survival among gay and bisexual men infected with HIV. Arch Intern Med 1996; 156:2233–2238.
9. Leserman J, Jackson ED, Petitto JM, Golden RN, Silva SG, Perkins DO, et al
. Progression to AIDS: the effects of stress, depressive symptoms, and social support. Psychosom Med 1999; 61:397–406.
10. Leserman J, Petitto JM, Golden RN, Gaynes BN, Gu H, Perkins DO, et al
. Impact of stressful life events, depression, social support, coping, and cortisol on progression to AIDS. Am J Psychiatry 2000; 157:1221–1228.
11. Page-Shafer K, Delorenze GN, Satariano WA, Winkelstein W Jr. Comorbidity and survival in HIV-infected men in the San Francisco Men's Health Survey. Ann Epidemiol 1996; 6:420–430.
12. Kopnisky KL, Stoff DM, Rausch DM. Workshop report: The effects of psychological variables on the progression of HIV-1 disease. Brain Behav Immun 2004; 18:246–261.
13. Leserman J. HIV disease progression: depression, stress, and possible mechanisms. Biol Psychiatry 2003; 54:295–306.
14. Evans DL, Ten Have TR, Douglas SD, Gettes DR, Morrison M, Chiappini MS, et al
. Association of depression with viral load, CD8 T lymphocytes, and natural killer cells in women with HIV infection. Am J Psychiatry 2002; 159:1752–1759.
15. Leserman J, Petitto JM, Perkins DO, Folds JD, Golden RN, Evans DL. Severe stress, depressive symptoms, and changes in lymphocyte subsets in human immunodeficiency virus-infected men. A 2-year follow-up study. Arch Gen Psychiatry 1997; 54:279–285.
16. DiMatteo MR, Lepper HS, Croghan TW. Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. Arch Intern Med 2000; 160:2101–2107.
17. Gordillo V, del AJ, Soriano V, Gonzalez-Lahoz J. Sociodemographic and psychological variables influencing adherence to antiretroviral therapy. AIDS 1999; 13:1763–1769.
18. Kalichman SC, Ramachandran B, Catz S. Adherence to combination antiretroviral therapies in HIV patients of low health literacy. J Gen Intern Med 1999; 14:267–273.
19. Simpson SH, Eurich DT, Majumdar SR, Padwal RS, Tsuyuki RT, Varney J, et al
. A meta-analysis of the association between adherence to drug therapy and mortality. BMJ 2006; 333:15.
20. Paterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C, et al
. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med 2000; 133:21–30.
21. Carpenter CC, Fischl MA, Hammer SM, Hirsch MS, Jacobsen DM, Katzenstein DA, et al
. Antiretroviral therapy for HIV infection in 1996. Recommendations of an international panel. International AIDS Society-USA. JAMA 1996; 276:146–154.
22. Carpenter CC, Fischl MA, Hammer SM, Hirsch MS, Jacobsen DM, Katzenstein DA, et al
. Antiretroviral therapy for HIV infection in 1997. Updated recommendations of the International AIDS Society–USA panel. JAMA 1997; 277:1962–1969.
23. Carpenter CC, Cooper DA, Fischl MA, Gatell JM, Gazzard BG, Hammer SM, et al
. Antiretroviral therapy in adults: updated recommendations of the International AIDS Society-USA Panel. JAMA 2000; 283:381–390.
24. Radloff LS. The CES-D Scale: a self-report depression scale for research in the general population. Appl Psychol Meas 1977; 1:385–401.
25. Andresen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well older adults: evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale). Am J Prev Med 1994; 10:77–84.
26. Wood E, Montaner JS, Chan K, Tyndall MW, Schechter MT, Bangsberg D, et al
. Socioeconomic status, access to triple therapy, and survival from HIV-disease since 1996. AIDS 2002; 16:2065–2072.
27. Hogg RS, Strathdee SA, Craib KJ, O'Shaughnessy MV, Montaner JS, Schechter MT. Lower socioeconomic status and shorter survival following HIV infection. Lancet 1994; 344:1120–1124.
28. Schechter MT, Hogg RS, Aylward B, Craib KJ, Le TN, Montaner JS. Higher socioeconomic status is associated with slower progression of HIV infection independent of access to health care. J Clin Epidemiol 1994; 47:59–67.
29. Hogg RS, Heath K, Bangsberg D, Yip B, Press N, O'Shaughnessy MV, et al
. Intermittent use of triple-combination therapy is predictive of mortality at baseline and after 1 year of follow-up. AIDS 2002; 16:1051–1058.
30. Wood E, Montaner JS, Yip B, Tyndall MW, Schechter MT, O'Shaughnessy MV, et al
. Adherence and plasma HIV RNA responses to highly active antiretroviral therapy among HIV-1 infected injection drug users. CMAJ 2003; 169:656–661.
31. Low-Beer S, Yip B, O'Shaughnessy MV, Hogg RS, Montaner JS. Adherence to triple therapy and viral load response. J Acquir Immune Defic Syndr 2000; 23:360–361.
32. Gordis L. Epidemiology. Philadelphia: W.B. Saunders; 2000.
33. Rothman KJ, Greenland S. Modern epidemiology. Philadelphia: Lippincott-Raven; 1998.
34. Lima VD, Kopec JA. Quantifying the effect of health status on health care utilization using a preference-based health measure. Soc Sci Med 2005; 60:515–524.
35. Maldonado G, Greenland S. Simulation study of confounder-selection strategies. Am J Epidemiol 1993; 138:923–936.
36. Hosmer DW, Lemeshow S. Applied survival analysis: regression modeling of time to event data. New York: Wiley; 1999.
37. Kilbourne AM, Justice AC, Rollman BL, McGinnis KA, Rabeneck L, Weissman S, et al
. Clinical importance of HIV and depressive symptoms among veterans with HIV infection. J Gen Intern Med 2002; 17:512–520.
38. Moskowitz JT. Positive affect predicts lower risk of AIDS mortality. Psychosom Med 2003; 65:620–626.
39. Kalichman SC, Rompa D, Cage M. Distinguishing between overlapping somatic symptoms of depression and HIV disease in people living with HIV-AIDS. J Nerv Ment Dis 2000; 188:662–670.
40. Lyketsos CG, Hoover DR, Guccione M, Dew MA, Wesch J, Bing EG, et al
. Depressive symptoms over the course of HIV infection before AIDS. Soc Psychiatry Psychiatr Epidemiol 1996; 31:212–219.
41. Patterson TL, Shaw WS, Semple SJ, Cherner M, McCutchan JA, Atkinson JH, et al
. Relationship of psychosocial factors to HIV disease progression. Annals of Behavioral Medicine 1996; 18:30–39.
42. Mulrow CD, Williams JW Jr, Gerety MB, Ramirez G, Montiel OM, Kerber C. Case-finding instruments for depression in primary care settings. Ann Intern Med 1995; 122:913–921.
43. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960; 23:56–62.
Keywords:© 2007 Lippincott Williams & Wilkins, Inc.
HIV/AIDS; depressive symptoms; HAART; mortality; adherence