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Healthy Lifestyles and Health-Related Quality of Life Among Men Living With HIV Infection
Healthy Lifestyles and Health-Related Quality of Life Among Men Living With HIV Infection Constance R. Uphold, PhD, ARNP, FAAN Wanda Holmes, PhD, RN Kimberly Reid, MS Kimberly Findley, RN Jorge P. Parada, MD, MPH Although healthy lifestyles are related to improved quality of life in the general population, little is known about the role of healthy lifestyles during HIV infection. The authors examined the relationships between health-promoting behaviors, risk behaviors, stress, and health-related quality of life (HRQOL) among 226 men with HIV infection who were attending three infectious disease clinics. As hypothesized, healthpromoting behaviors were positively related and stress was negatively related with most of the HRQOL dimensions. Contrary to the hypothesis, tobacco use, recreational drug use, and unsafe sexual behaviors were not related to the HRQOL dimensions. Hazardous alcohol use was negatively associated with one HRQOL dimension—social functioning. The association of modifiable factors, such as health-promoting behaviors and stress, with HQROL offers opportunities for improving HIV-related health care. Relatively simple, straightforward changes in lifestyles such as eating well, remaining active, and avoiding stressful life events may result in improvements in HRQOL. Key words: health-related quality of life, healthy lifestyles, health-promoting behaviors, risk behaviors, stress, HIV infection
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edical advances have afforded individuals longer, healthier, and more productive lives, resulting in a paradigm shift from HIV infection as a rapidly fatal illness to that of a long-term, chronic disease
(Vosvick et al., 2003). Consequently, health-related quality of life (HRQOL) among individuals with HIV infection has become an important focus of clinical practice and research. Researchers have identified a breadth of sociodemographic and clinical factors that affect HRQOL including age, ethnicity, socioeconomic status, lack of health care coverage, symptoms, and CD41 lymphocytes (Bing et al., 2000; Campsmith, Nakashima, & Davidson, 2003). Less is known about the role that healthy lifestyles play in improving HQROL during HIV infection. Healthy lifestyles encompass actions aimed at promoting wellness (e.g., physical activity, stress management) as well as those behaviors undertaken to prevent disease (e.g., avoidance of bad health habits Constance R. Uphold, PhD, ARNP, FAAN, is at the Rehabilitation Outcomes Research Center (RORC)/Geriatrics Research Education and Clinical Center (GRECC), North Florida/South Georgia Veterans Health System, Gainesville, Florida, and the Colleges of Nursing and Medicine, University of Florida, Gainesville. Wanda Holmes, PhD, RN, is at the North Florida/South Georgia Veterans Health System. Kimberly Reid, MS, is at the Mid American Heart Institute, Saint Luke’s Health System, Kansas City, Missouri. Kimberly Findley, RN, is at the RORC, North Florida/South Georgia Veterans Health System. Jorge P. Parada, MD, MPH, is at the Midwest Center for Health Services Research and Policy at the Hines Veterans Administration Hospital, Hines, Illinois, and the Stritch School of Medicine, Loyola University, Maywood, Illinois.
JOURNAL OF THE ASSOCIATION OF NURSES IN AIDS CARE, Vol. 18, No. 6, November/December 2007, 54-66 doi:10.1016/j.jana.2007.03.010 Copyright Ó 2007 Association of Nurses in AIDS Care
Uphold et al. / Healthy Lifestyles and Quality of Life
and stress) (Abel, 1991). A growing body of literature highlights the importance of healthy lifestyles in preventing morbidity and premature mortality (Mokdad, Marks, Stroup, & Gerberding, 2004) and in enhancing HRQOL among patients living with chronic illnesses such as multiple sclerosis (Stuifbergen, Seraphine, & Roberts, 2000), cardiovascular disease (Salyer, Flattery, Joyner, & Elswick, 2003), and neuromuscular disorders (Hofoss, 2004). Until recently, a healthy lifestyle among patients with HIV infection was a neglected topic of research (Clingerman, 2004). In particular, there are limited data on the effects of healthy lifestyles on HRQOL and other outcomes. According to a recent literature review (Chou & Holzemer, 2004), only one research team (Gielen, McDonnell, Wu, O’Campo, & Faden, 2001) has investigated the full impact of overall healthy lifestyles on HRQOL during HIV infection. In this study that excluded men, Gielen et al. (2001) reported that women who practiced more self-care behaviors (i.e., healthy eating, use of vitamin therapy, adequate sleep and physical activity, and stress management) had better HRQOL. On the other hand, several studies have examined relationships between specific domains of healthpromoting behaviors and HIV-related outcomes. Health-promoting behaviors are actions directed toward increasing well-being, self-actualization, and personal fulfillment and include the dimensions of health responsibility, physical activity, nutrition, spiritual growth, interpersonal relations, and stress management (Walker, Sechrist, & Pender, 1987). Using diverse theoretical and operational definitions, researchers reported that exercise and physical activity improved physiological outcomes as well as HRQOL among adults living with HIV (Clingerman, 2004). Although no known investigative team has specifically examined the effects of healthy eating on HRQOL during HIV infection, adequate nutrition is known to enhance the immune system, build reserves, and reduce vulnerability to wasting, thereby improving physical health (Wheeler et al., 1998) and most likely also improving HRQOL. Evidence is accumulating that behaviors related to spiritual growth (Flannelly & Inouye, 2001; Tuck, McCain, & Elswick, 2001) and actions aimed at reducing stress through the development of interpersonal relationships and coping strategies are associated with improved HRQOL during HIV infection
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(Chesney, Chambers, Taylor, & Johnson, 2003; Vosvick et al., 2003). Previous HIV-related literature also showed that risk factors (Samet, Horton, Traphagen, Lyon, & Freedberg, 2003) such as tobacco use, alcohol consumption, recreational drug use, and unsafe sexual practices increase medical complications and enhance the spread of HIV transmission. However, the link between risk behaviors and HRQOL is less understood. Tobacco use was associated with decrements in various dimensions of HRQOL among persons who were not infected (Martinez, Moto, Vianna, & Rodrigues, 2004), as well as those who were infected with HIV (Chesney, 2001; Turner et al., 2001). Previous research on alcohol consumption and HRQOL among the general population has shown that excessive alcohol consumption increased mortality (Thun et al., 1997) and that alcohol dependence and binge drinking were negatively associated with HRQOL (Okoro et al., 2004). During HIV infection, there is limited information on the direct effects of alcohol consumption on HRQOL. However, excessive alcohol use was reported to increase the rate of progression to AIDS (Lucas, Gebo, Chaisson, & Moore, 2002; Samet et al., 2003). Most of the studies on recreational drug use have focused on injection drug abusers and report that drug use was associated with depression (Knowlton et al., 2000) and poorer HRQOL during HIV infection (Riley et al., 2003). Whereas there are numerous studies investigating the practice of unsafe sexual behaviors (Kalichman & Rompa, 2003), little is known about the relationship of unsafe sexual practices and HRQOL. In a study on risk perceptions, Demmer (2001) reported that adults with lower HRQOL compared with those with higher HRQOL were less likely to believe that the practice of safe sexual behaviors was important. Adults with HIV infection face a multitude of stressful life events including deterioration in health status, alienation from others, and prospects of losing employment, financial security, and social roles. Evidence of a negative impact of stress on disease progression during HIV infection is growing (Leserman et al., 1997). Similarly, researchers have increasingly noted that stressful life events are inversely related to various components of HRQOL (Au et al., 2004; Jones, Beach, Forehand, & Foster, 2003).
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Because most previous researchers have limited their investigations to examining selected behavioral variables that may affect one or more components of HRQOL, the purpose of this study was to examine the interplay of multiple components of healthy lifestyles and HRQOL dimensions among men living with HIV infection. Rather than focusing on one or two health behaviors such as exercise or diet, the authors included a full array of health-promoting behaviors, risk behaviors, and stress as independent variables in their models. This approach allowed them to determine relationships between various health behaviors and HRQOL when all other variables were controlled. The authors hypothesized that health-promoting behaviors would be positively related, whereas risk behaviors (i.e., tobacco use, hazardous alcohol use, recreational drug use, practice of unsafe sexual behaviors) and stress would be negatively related to HRQOL among men with HIV infection.
Method Sample The authors collected data from 226 HIV-infected men who were enrolled in a larger prospective cohort investigation designed to examine biopsychosocial determinants of disease progression during HIV infection. Participants were recruited from three infectious disease clinics in the southeastern United States: Veterans Affairs (VA) medical center (n 5 131), university hospital (n 5 40), and public health department (n 5 55). Inclusion criteria were male gender, 18 years of age and older, positive enzyme-linked immunosorbent assay screening and Western blot confirmatory tests, and English-speaking. Participants were excluded if they currently used corticosteroids or testosterone replacement therapy, had a current bacterial or viral infection, were diagnosed with HIV infection for less than 3 months, had a recent change (i.e., within 30 days) in their antiretroviral medication regimens, or were moribund or cognitively impaired. Clinicians at the clinics referred patients to the principal investigator. After scheduled clinic appointments, men were given information about the study and invited to participate. Participants were enrolled
sequentially at each site until recruitment targets were attained. The authors enrolled all male patients who regularly attended the three clinics between January 2001 and November 2002 and who met the study criteria, except for 43 patients who declined to participate. The main reasons for not participating were time constraints or feeling too ill to answer questions. Procedure Trained data collectors obtained informed consent, conducted structured face-to-face interviews, and helped subjects complete standardized questionnaires. Venipunctures to obtain blood samples were performed, and specimens were analyzed in the VA medical center laboratory. Typical research visits lasted 2 to 3 hours. Members of the research team reviewed the participants’ medical records to validate demographic and clinical data obtained during the interviews. Participants received a $30 stipend for completing the baseline interviews. The university institutional review board and the human protection committees of the related sites approved the study procedures. Measures Sociodemographic and clinical characteristics. Sociodemographic information included age, race/ ethnicity, and highest completed grade of education. Clinical measures included CD41 cell count and comorbidity. The authors obtained the CD41 cell count (cells per microliter of blood) from blood specimens that were drawn and analyzed at the VA clinical laboratory. The Charlson Comorbidity Questionnaire (Katz, Chang, Sangha, Fossel, & Bates, 1996) was used to assess the patients’ comorbid conditions, with the higher the summary score, the more severe the burden of comorbidity. The score for AIDS diagnosis was excluded from the summary score. Health-promoting behaviors. The Health-Promoting Lifestyle Profile II (HPLP-II) measured health-promoting behaviors. Health-promoting behaviors are actions directed at increasing well-being,
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self-actualization, and personal fulfillment (Walker et al., 1987). The HPLP-II is a 52-item instrument that consists of six subscales that measure major components of a healthy lifestyle: health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Health responsibility included seeking educational and professional assistance to improve health and paying attention to one’s health. Physical activity involved participating in regular exercise. The nutritional category included items related to healthy meal patterns and food choices. Interpersonal relations involved intimacy and closeness with others. Spiritual growth included items related to self-actualization and being connected with a force greater than oneself. Stress management involved using behaviors to control stress and improve coping abilities. Response choices ranged from 1 (never) to 4 (routinely). A score for overall health-promoting behaviors was determined by calculating the mean of each participant’s responses to all 52 items. Scores for the six subscales were obtained similarly by calculating a mean of the responses to the subscale items. The scale has established reliability and validity (Walker et al., 1987). In this study, Cronbach’s alpha for the total score was .91. Cronbach’s alphas for the subscales ranged from .80 to .90. Risk behaviors. Participants were considered tobacco users if they indicated that they currently smoked cigarettes/cigars or chewed tobacco. Alcohol use was measured by the Quantity/Frequency of Alcohol Consumption Tool developed by the National Institute of Alcohol Abuse and Alcoholism (National Institute of Alcohol Abuse and Alcoholism, 1995). It consists of three items, which ask participants how many days per week they drink, how many drinks they have on a typical day, and the maximum number of drinks on a given occasion. The authors determined whether participants were hazardous drinkers. Hazardous drinking was defined as having more than 14 drinks per week or having more than 4 drinks on a given occasion (Agency for Healthcare Research and Quality, 2004). Participants indicated the drugs they used in the past and the drugs they were using currently from a list of 54 items that included both ‘‘street’’ names and generic names. Participants were considered recreational drug users
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if they identified current drug use from any of the following categories: cannabis, stimulants, cocaine, hallucinogens, other. The authors also categorized participants as heavy recreational drug users if they used recreational drugs more than 3 days per week. Unsafe sexual practices were measured by two items that asked participants to indicate on scales from 1 (never) to 5 (all the time) whether they used recommended ‘‘safer sex’’ practices (i.e., condoms, rubber dams) with those people who were HIV-negative/ HIV status unknown and those people who were HIV-positive in the last 3 months. Participants were considered to be practicing unsafe sex if they indicated they failed to use recommended practices all of the time. The authors also reviewed the participants’ medical records to determine if they had ever been treated for drug or alcohol abuse problems and if their drug and alcohol problems were resolved or ongoing. Life event stress. Life event stress was measured with a semistructured interview, the Psychiatric Epidemiology Research Interview (Dohrenwend, Krasnoff, Askenasy, & Dohrenwend, 1978), which was modified to include stressors relevant to the HIV population (Leserman et al., 1997). Participants indicated which of the 113 stressors and difficulties they had experienced over the preceding 12 months. Participants were asked how stressful the event was and whether the event had a positive or negative impact. Interviewers then asked participants openended questions, followed as needed by probing questions to obtain detailed descriptions of each stressful event and its effect on the participant’s life. After the interviews were completed, the authors used a methodology similar to Leserman et al. (1997) to rate the long-term impact of the stressor by taking into account the contextual aspects of each event. Two trained researchers used a manual, which provided guidelines and criteria for making rating decisions and assigned a score from 0 (no threat) to 4 (severe threat) to each stressful event. Then, a composite stress score was obtained by summing the rating scores. There was a 90% interrater agreement between three raters on 15 randomly selected interview forms. The instrument is comprehensive, objectively measures chronic difficulties, and estimates the impact of a stressful event in a specific context for the
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average individual, thereby avoiding individual subjective reactions that invalidate other life event stress measures. Health-related quality of life (HRQOL). Scales from the HIV Cost and Services Utilization Study (Hays et al., 2000) were used to assess dimensions of HRQOL. This disease-specific measure assesses how well an individual functions and the individual’s perceptions of well-being in the physical, mental, and social domains of life. This 31-item measure includes the following scales: physical functioning (9 items), role functioning (2 items), pain (2 items), general health perceptions (3 items), social functioning (2 items), energy (2 items), emotional well-being (7 items), disability days (1 item), overall health (1 item), and overall quality of life (1 item). The physical functioning items denote a range of functioning from feeding oneself to vigorous exercise. Role functioning represents one’s ability to perform certain roles at work and at home. Items in the pain dimension involve amount of pain and the interference of pain with work. The general health items ask participants to rate their level of health and their perceptions of whether they tend to get sicker easier than others. The items on the social functioning subscale ask participants to rate the extent and amount their health interferes with social activities. The energy item represents the participant’s degree of tiredness and whether he has enough energy to perform tasks. Emotional well-being represents the participants’ positive/negative affect, anxiety, and depression. The one-item scales (i.e., disability days, overall health, overall quality of life) ask participants to list the number of days their health caused them to remain in bed and to rate their overall health and quality of life on a scale from 1 to 100. The authors excluded the one-item scales from their analyses. For the remaining scales, the items were averaged to get a score. In accordance with standard reporting procedures, all of the measures were then linearly transformed with a range of 0 to 100, with 100 representing the best health. The scales within the instrument were also summarized into three composite scales, a physical health summary, a mental health summary, and an overall HRQOL summary. This instrument has been used extensively in previous HIV-related research and has established validity
and reliability (Revicki, Sorensen, & Wu, 1998). In the present study, all of the scales and composite measures had acceptable internal reliabilities with Cronbach’s alphas ranging from .76 to .94. Data Analysis For the present study, only baseline data were analyzed. Descriptive statistics were used to delineate characteristics of the sample. Pearson productmoment correlations were used to test for associations between health promoting behaviors, stress, and HRQOL scores. Two sample t-tests were used to compare HRQOL scores between men who currently engaged in risk behaviors or had a history of risk behaviors (i.e., tobacco use, hazardous alcohol use, illicit drug use, heavy illicit drug use, unsafe sexual practices, previous/current drug and alcohol abuse treatments) and men who were not involved in risk behaviors. To investigate the interplay of multiple components of healthy lifestyles and HQROL dimensions, the authors included health-promoting behaviors, risk behaviors, and stress as independent variables in the models. Multivariable linear regression analyses were used to determine the relationships between health-promoting behaviors, risk behaviors, and stress and HRQOL dimensions, after controlling for covariates. Demographic variables and clinical factors reported to be consistently correlated with HRQOL and health behaviors in previous research were included as covariates: age (continuous), race/ethnicity (White, non-White), years of education (continuous), comorbidity (continuous), and number of CD41 cells (continuous). In each model, the dependent variable was the HRQOL score, and the independent variables were as follows: health-promoting behaviors (continuous), tobacco use (yes, no), hazardous alcohol use (yes, no), recreational drug use (yes, no), and unsafe sexual practices (yes, no). Because of high correlations among the HPLP-II subscales, the authors included only the total score in their multivariable linear regression analyses. Collinearity, model assumptions, and model fit of the final multivariable models were assessed and were not reported to be problems. Dichotomous results are reported as yes versus no as the reference level. White results are compared to reference level of non-White. All statistical tests
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were two-sided, and statistical significance was determined at the 5% level. All analyses were conducted by using SAS version 8.2 (SAS Institute, Inc., Cary, NC) statistical software package.
Results Descriptive Characteristics A total of 226 men participated in this study. The average age of the participants was 45.7 (SD 5 8.7) with a range of 20 to 70 years. The majority of participants were White (n 5 124, 55%), had more than 12 years of education (n 5 120, 53%), and had total family incomes of , $35,000 (n 5184, 81%). Homosexual contact was listed as the most frequent mode of transmission (n 5 72, 32%). A total of 52 (22%) men were infected through heterosexual contact, 19 (8%) listed intravenous drug use as their risk factor, 6 (3%) were infected through blood transfusions, and 79 (35%) were unsure of how they were infected or had multiple risk factors. The average score on the comorbidity index was 1.1. Liver disease, chronic obstructive pulmonary disease, and peptic ulcer disease were the most common comorbid conditions. The mean CD41 cell count was 415/mm3. Participants had lived an average of 8.3 years after testing positive for HIV. Most of the participants (n 5 198, 87.6%) were taking highly active antiretroviral therapy (HAART) medication regimens. The average score on the HPLP-II was 2.6 (SD 5 .48), with a range of 1.4 to 4.0. A total of 120 men (53%) used tobacco products. Almost half of the men (n 5112) smoked cigarettes, only 12 men smoked cigars, and 4 men chewed tobacco. The men drank alcohol on an average of 1.1 days per week. The average maximum number of drinks on one occasion was 2.4, with a range of 0 to 24. More than half of the men (n 5138, 61%) did not drink any alcohol, whereas 63 of the men (28%) were hazardous alcohol drinkers. On medical record review, the authors reported that 30 men (13%) were reported as having been previously treated for alcohol abuse problems. Of these men, 25 (83%) had unresolved alcohol abuse problems. The majority of the men (n 5 160, 71%) did not use recreational drugs, and only 24 were heavy recreational drug users. Marijuana was currently
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used by 52 men (23.0%), whereas none of the men were using hallucinogens, and only a small number were using cocaine (n 5 8, 4%) and stimulants (n 5 3, 1%). The majority of the men (n 5 180, 80%) stated that they had used recreational drugs in the past. From the medical records, the authors reported that 35 men (15%) had previously been treated for drug abuse problems and 28 (80%) of these men had unresolved drug abuse problems. Of the 110 men who had engaged in sexual activity in the past 3 months, 11 had failed to always practice safe sex with men who had unknown or negative HIV status, and 10 failed to always practice safe sex with men known to be HIV-positive. The average stress rating was 9.7, with a range of 0 to 51. The most frequently identified severe stressors were hospitalizations for life-threatening conditions, receiving information that their condition was fatal, progression of HIV infection, chronic financial stress, and death of an immediate family member.
Correlations Between Health-Promoting Behaviors, Stress, and Health-Related Quality of Life The authors examined the correlations between health-promoting behavior domains and stress and HRQOL dimensions (Table 1). Health responsibility was unrelated to any HRQOL dimension, whereas physical activity was positively related to every HRQOL dimension, with correlations ranging from .16 to .34. The total health-promoting behavioral score as well as spiritual growth, interpersonal relations, and stress management subscales were related to improvement in pain and better general health, emotional well-being, social functioning, energy, physical health, mental health, and overall HRQOL but were not related to two HRQOL dimensions (i.e., physical functioning and role functioning). The nutrition subscale was positively related to all dimensions of HRQOL except physical functioning, role functioning, emotional well-being, and energy. Stress was related to all dimensions of HRQOL except physical functioning. More frequent participation in health-promoting behaviors and less life-event stress were associated with higher ratings on most of the HRQOL dimensions.
60 JANAC Vol. 18, No. 6, November/December 2007 Table 1.
Pearson Product-Moment Correlations Between Health-Related Quality of Life Dimensions and Health-Promoting Behavior Domains and Stress Health-Promoting Health Physical Spiritual Interpersonal Stress Lifestyle Responsibility Activity Nutrition Growth Relations Management Stress
Physical functioning Role functioning Pain General health Emotional well-being Social functioning Energy Physical health summary Mental health summary Overall HRQOL summary
.10 .13 .20c .29a .30a .33a .22b .26a .33a .33a
.04 .05 .10 .06 .01 .09 2.01 .07 .03 .05
.26a .23b .21c .29a .16d .28a .25a .34a .21c .30a
.01 .06 .19c .23b .12 .16d .11 .16d .15d .17c
.04 .09 .11 .31a .45a .37a .28a .25b .46a .40a
.01 .06 .15d .18c .29a .27a .17d .16d .30a .26a
.06 .07 .20c .24b .37a .32a .19c .22b .35a .32a
2.03 2.25b 2.23b 2.31a 2.31a 2.33a 2.19c 2.29a 2.34a 2.35a
NOTE: HRQOL 5 health-related quality of life. a. p , .0001 b. p , .001 c. p , .01 d. p , .05
Comparisons Between Participants Who Did and Did Not Engage in Risk Behaviors The authors compared participants who engaged in risk behaviors with those who stated they did not engage in risk behaviors (Table 2). Although there were no statistically significant differences, men who used tobacco consistently had lower mean ratings on all the HRQOL dimensions than nonusers. Hazardous alcohol use was associated with one dimension of HRQOL—social functioning. Hazardous alcohol users had on average almost 10 points lower social functioning than other men (p , .05). Hazardous alcohol users also had lower scores on the other dimensions of HRQOL, but these differences were not statistically significant. There were no statistically significant differences in HRQOL between men who had been previously treated for alcohol abuse and whose current alcohol abuse problems were currently unresolved according to their medical records (data not shown). Men who used recreational drugs scored lower in all dimensions of HRQOL than nonusers, but these differences were not statistically significant. There were no statistically significant differences in HRQOL scores between men who were heavy and light recreational drug users. Men who had been previously treated for drug abuse problems and whose current drug abuse problems were currently unresolved had 11 points lower physical
functioning (t value 5 2.35, p 5 .02) and 14 points lower pain improvement (t value 5 2.64, p 5 .01) than men with a history of drug abuse treatment who were free of current drug abuse problems according to their medical records. Men who engaged in unsafe sexual practices had lower mean ratings on all HRQOL dimensions except the general health dimension than men who practiced safe sex, but these differences were not statistically significant. Multivariable Linear Regression Models The authors tested their hypothesis and examined the relationships of health-promoting behaviors, risk behaviors, stress, and HRQOL, controlling for age, race, education, comorbidity, and CD41 cell counts (Table 3). The variance explained by the independent variables and covariates in every model was statistically significant and ranged from 11% to 26%. Health-promoting behaviors were significantly related to all dimensions of HRQOL except physical functioning and role functioning. Higher scores on the health-promoting behaviors questionnaire were highly related to better general health, emotional well-being, social functioning, energy, physical health, mental health, overall quality of life, and lower levels of pain, with a one-unit improvement in health behaviors coinciding with 3- to 16-point improvements in HRQOL dimensions. Self-reported
82.9 (22.5) 75.2 (32.0) 60.9 (26.3) 59.4 (27.2) 69.7 (20.5) 73.8 (28.5) 60.9 (27.1) 52.0 (8.3) 52.5 (9.0) 52.4 (8.5) 76.0 (26.7) 65.8 (36.5) 49.5 (30.8) 62.3 (30.0) 61.1 (20.5) 65.1 (30.0) 57.9 (27.6) 49.2 (10.7) 49.4 (9.2) 49.2 (9.9) 76.4 (27.4) 68.3 (34.9) 57.1 (25.8) 58.1 (26.1) 66.3 (18.8) 70.7 (25.4) 59.0 (24.2) 50.4 (7.5) 51.2 (8.5) 50.9 (7.6) 85.9 (23.4) 78.1 (33.2) 55.4 (26.5) 52.8 (26.7) 69.5 (17.4) 68.8 (31.3) 60.0 (25.2) 51.1 (9.2) 51.8 (8.2) 51.6 (8.6) 84.2 (22.2) 74.8 (33.4) 61.5 (27.1) 62.4 (27.5) 70.8 (19.1) 74.8 (27.5) 62.5 (27.7) 52.5 (8.5) 53.0 (8.6) 53.0 (8.5)
77.7 (26.3) 68.3 (33.7) 56.3 (28.9) 60.4 (28.9) 64.9 (22.2) 65.7 (32.5)a 60.6 (27.5) 50.3 (9.0) 50.7 (10.1) 50.5 (9.5)
84.4 (21.2) 77.1 (31.6) 61.3 (26.0) 59.0 (26.9) 70.2 (20.0) 75.5 (26.7)a 60.4 (27.0) 52.3 (8.2) 52.7 (8.7) 52.7 (8.3)
80.2 (26.1) 72.3 (34.3) 56.1 (25.9) 56.6 (25.1) 67.4 (18.1) 70.1 (27.3) 59.2 (24.2) 50.7 (8.1) 51.4 (8.3) 51.1 (7.9)
83.4 (21.4) 75.6 (3.6) 61.5 (27.2) 60.6 (28.2) 69.3 (21.7) 73.9 (29.3) 60.9 (28.2) 52.1 (8.7) 53.9 (9.4) 52.5 (8.9)
Discussion
81.0 (23.4) 74.6 (31.6) 58.5 (26.6) 56.7 (27.1) 67.0 (21.9) 71.0 (29.7) 58.6 (26.5) 51.1 (8.5) 51.3 (9.5) 51.3 (8.8) a. p , .05
Hazardous Recreational Heavy Recreational Unsafe Sexual Tobacco Use Alcohol Use Drug Use Drug Use Practices Yes No Yes No Yes No Yes No Yes No (n 5 226) (n 5 120) (n 5 106) (n 5 63) (n 5 163) (n 5 66) (n 5 160) (n 5 24) (n 5 41) (n 5 19) (n 5 205) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Total Sample
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use of tobacco and recreational drugs and practice of unsafe sexual behaviors were not related to any of the HRQOL dimensions. Hazardous alcohol use was associated with one dimension of HRQOL—social functioning. Self-reported hazardous alcohol users had over 8 points lower social functioning than nonusers, after adjusting for covariates. Life-event stress was related to all dimensions of HRQOL except physical functioning. Greater life-event stress was associated with lower levels of HRQOL, with a one-unit increment in life-event stress coinciding with .26- to .98point decreases in HRQOL dimensions.
82.5 (22.9) 74.7 (32.4) 59.9 (26.8) 59.4 (27.4) 68.8 (20.7) 72.8 (28.7) 60.4 (27.1) 51.7 (8.5) 52.1 (9.1) 52.1 (8.7) Physical functioning Role functioning Pain General health Emotional well-being Social functioning Energy Physical health summary Mental health summary Overall quality of life summary
Table 2.
Means and Standard Deviations of Health-Related Quality of Life Dimension Scores for the Total Sample (N 5 226) and HIV-Infected Men Who Did and Did Not Engage in Risky Behaviors
Uphold et al. / Healthy Lifestyles and Quality of Life
Now that people are living longer with HIV infection, improving HRQOL is an important clinical issue. Although previous researchers have reported that healthy lifestyles positively influence HRQOL among patients suffering from various chronic diseases, there is limited research on the role of healthy lifestyles during HIV infection. Results in this study highlight the association of modifiable factors, such as health-promoting behaviors and stress, with HRQOL among men living with HIV infection. Interventions aimed at promoting positive lifestyle changes have the potential to improve HRQOL. Instead of solely focusing on monitoring CD41 T cells and viral loads results to improve outcomes, clinicians need to include individualized counseling, patient education, and cognitive therapies to improve lifestyle choices in their management or care plans. As hypothesized, health-promoting behaviors had positive relationships with most of the HRQOL dimensions. This result is consistent with the results of Gielen et al. (2001) who reported that women who engaged in more health-promoting behaviors had better HRQOL. The authors also examined the correlations between specific domains within the overall health-promoting behavioral measure and the HRQOL dimensions. Physical activity was positively associated with all of the HRQOL dimensions, and the other health-promoting domains were positively related to most of the HRQOL dimensions. These results support those of others that exercise is a strong factor in enhancing well-being (Clingerman, 2004) and that spirituality (Flannelly & Inouye, 2001;
Multivariable Linear Regression Models of Factors Potentially Associated With Health-Related Quality of Life Scores (N 5 226)
Predictors
Physical Role Functioning Functioning Parameter Parameter Estimate Estimate (SE) (SE)
Pain Parameter Estimate (SE)
General Health Parameter Estimate (SE)
Emotional Social Well-Being Functioning Parameter Parameter Estimate Estimate (SE) (SE)
Energy Parameter Estimate (SE)
Physical Health Parameter Estimate (SE)
Overall Quality Mental of Life Health Parameter Parameter Estimate Estimate (SE) (SE)
Health behaviors 3.87 (3.16) 6.64 (4.37) 10.23c (3.62) 13.02c (3.58) 9.78b (2.67) 15.80a (3.71) 9.58c (3.64) 3.81b (1.11) 4.85a (1.15) 4.70a (1.09) Risk Behaviors Tobacco use 2.57 (3.10) 3.13 (4.28) 2.79 (3.55) 23.10 (3.51) 21.84 (2.62) 2.29 (3.64) 21.32 (3.57) 2.23 (1.09) 2.82 (1.13) 2.57 (1.07) Hazardous alcohol use 26.02 (3.56) 28.25 (4.91) 23.75 (4.07) 1.78 (4.03) 23.99 (3.00) 28.62d (4.17) 2.88 (4.09) 21.71 (1.25) 21.54 (1.30) 21.76 (1.22) Recreational drug use 21.07 (3.48) 2.98 (4.80) 22.06 (3.99) 22.91 (3.94) 1.71 (2.94) .45 (4.08) 1.13 (4.00) 2.37 (1.22) .53 (1.27) .08 (1.20) Unsafe sexual practices 2.60 (5.87) 2.38 (8.12) 25.17 (6.73) 9.00 (6.65) 21.89 (4.96) 1.94 (6.90) 3.02 (6.76) .43 (2.06) 2.06 (2.14) .20 (2.02) Stress 2.06 (.20) 2.87c (.27) 2.58d (.23) 2.90a (.22) 2.71a (.17) 2.98a (.23) 2.59c (.23) 2.26b (.07) 2.34a (.07) 2.32a (.07) Covariates Age 2.49c (.18) 2.49d (.24) 2.17 (.20) .42d (.20) .25 (.15) .15 (.21) .23 (.20) 2.03 (.06) .13 (.06) .05 (.06) White race 21.13 (3.09) 3.58 (4.27) 1.93 (3.54) 21.82 (3.50) 24.60 (2.61) 2.59 (3.63) 211.42c (3.56) 2.67 (1.09) 21.99 (1.13) 2.44 (1.06) Education .46 (.77) .42 (1.06) .58 (.88) .81 (.87) .27 (.65) .01 (.90) .51 (.88) .21 (.27) .13 (.28) .18 (.26) Comorbidity 22.00a (.85) 23.28b (1.18) 23.36b (.98) 22.37d (.97) 2.63 (.72) 21.77 (1.00) 23.20c (.98) 21.09b (.30) 2.46 (.31) 2.84c (.23) CD41 T cells 2.01 (.01) 2.01 (.01) 2.01 (.01) 2.00 (.01) 2.01d (.01) 2.01 (.01) 2.01 (.01) 2.01 (.01) 2.01d (.01) 2.01 (.01) 2 2 2 2 2 2 2 R 5 .11 R 5 .15 R 5 .16 R 5 .22 R 5 .22 R 5 .23 R 5 .17 R2 5 .21 R2 5 .25 R2 5 .26 NOTE: SE 5 standard error. a. p , .0001 b. p , .001 c. p , .01 d. p , .05
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Table 3.
Uphold et al. / Healthy Lifestyles and Quality of Life
Tuck et al., 2001), coping through self-management skills, and development of interpersonal relationships are associated with improved HRQOL (Chesney et al., 2003). In addition, this study is one of the first investigations to show that healthy eating is related to improved HRQOL. Surprisingly, health responsibility was not associated with any HRQOL dimension. It is possible that health responsibility, which emphasizes reliance on others (i.e., health professionals and educational programs) to improve health, is conceptually different from the other health-promoting domains, which focus on self-initiative and self-management. Another explanation is that health responsibility has a different meaning and impact on HRQOL among persons with HIV infection than on those persons living with other chronic diseases. Unlike the experience of patients with other chronic diseases, adults with HIV infection have frequent contact with health care providers and thus have limited choices in scheduling their health care visits and assuming responsibility for when they seek care. Contrary to the hypothesis, risk behaviors were not related to most dimensions of the HRQOL. Unlike previous research in the general population (Martinez et al., 2004) and HIV/AIDS population (Chesney, 2001; Turner et al., 2001), tobacco use was not associated with HQROL. Tobacco use, as well as use of alcohol and drugs, can sometimes enhance HQROL, particularly on a short-term basis. For example, tobacco use can provide immediate gratification of needs, lead to pleasurable sensations, and act as a coping mechanism. In this study, the short-term benefits of tobacco use may have counterbalanced the negative long-term effects of tobacco use. Hazardous alcohol use was associated with poor social functioning, which supports theory and previous research that has consistently reported a relationship between increased alcohol consumption and difficulties with social activities with family, friends, and colleagues (Sindelar, 1998). However, hazardous alcohol use was not associated with any other HRQOL dimension. To the authors’ knowledge, no study has examined hazardous alcohol use and HRQOL during HIV infection. However, because previous research reported that hazardous alcohol use results in rapid progression to AIDS (Lucas et al., 2002; Samet et al., 2003), it is surprising that this hazardous alcohol was not related to HRQOL.
63
In this study, hazardous alcohol use was defined as more than 14 drinks per week or having more than 4 drinks on a given occasion in a week (Agency for Healthcare Research and Quality, April 2004). Other researchers have used different indicators of alcohol consumption and reported that alcohol dependence and binge drinking were associated with decreased HRQOL in the general population (Okoro et al., 2004). It is likely that alcohol consumption has a dose-response relationship to outcomes. In studies involving non-HIV-infected persons, light and moderate alcohol consumption was associated with improved outcomes (Berger et al., 1999), whereas excessive alcohol consumption increased mortality (Thun et al., 1997). Additional research is recommended to determine the impact of various frequencies and amounts of alcohol consumption on HQROL during HIV infection. Recreational drug use was not associated with any HRQOL dimension, which contrasts with previous research (Riley et al., 2003). However, in most previous studies, the samples included high proportions of adults who were injection drug users and/or were adults who were addicted to opioids. In this study, the majority of the men were using marijuana and none acknowledged injection drug use. As noted by Sullivan, Nakashima, Purcell, and Ward (1998), patterns of recreational drug use vary among different regions of the country. In this predominantly suburban and rural area in the southeastern United States, the association of recreational drug abuse with HQROL may be different than that reported in urban epicenters of the northeastern and western United States. These results emphasize the importance of considering local patterns of substance use when counseling patients and planning interventions and programs. Unsafe sexual behaviors were unrelated to HRQOL. To the authors’ knowledge, this was the first investigative team to examine this relationship. However, additional research is recommended because researchers have recently reported resurgence in the rate of unprotected sexuality activity (Dukers et al., 2001), which may have a significant impact on outcomes among adults with HIV infection in the future. Stress was negatively associated with all dimensions of HRQOL except for physical functioning. These results support previous research that has
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consistently reported that increased stressful life events are related to lower levels of HRQOL (Au et al., 2004; Leserman et al., 1997). Certain life events such as illness and death are outside the control of individuals. However, avoidance of other events such as demotion at work, conflict with partners, and jail terms for crimes is possible, and the efforts to sustain a stress-free life appear to be an important factor in maintaining a healthy lifestyle and improving HRQOL. The results of this study have important implications for clinical practice and health policy. As Gielen et al. (2001) note, the association of potentially modifiable factors such as health-promoting behaviors and stress offers new opportunities for enhancing HRQOL. Even in the complicated context of HIV infection, relatively simple, straightforward changes in lifestyles such as eating well, managing stress, and remaining active may result in significant improvements in HRQOL. Although there are challenges in altering one’s behavior, this study highlights the importance of counseling men with HIV infection about the benefits of engaging in health-promoting behaviors and avoiding stressful life events. In addition, as noted in the literature, educational programs that emphasize self-care (Gifford, Laurent, Gonzales, Chesney, & Lorig, 1998), coping improvement (Heckman et al., 1999), and cognitive behaviors strategies that reduce stress (McCain, Zeller, Cella, Urbanski, & Novak, 1996) are practical and cost-effective mechanisms for empowering patients with HIV infection to take personal responsibility for improving their health and quality of life. Although risk behaviors were not associated with HRQOL, the authors’ results support previous research, which reported that tobacco use and substance use are prevalent and difficult problems to resolve among patients with HIV infection (Galvan et al., 2002; Gritz, Vidrine, Lazev, Amick, & Arduino, 2004). The authors reported that 83% and 80% of the men treated for alcohol abuse and drug abuse, respectively, had unresolved substance use problems. Further, in this predominantly rural and suburban sample, there were sizeable numbers of men who were current tobacco users (n 5 120, 53%) and hazardous alcohol drinkers (n 5 63, 28%). In addition, 80% of the men stated that they had previously used recreational drugs. These figures of adults en-
gaging in risk behaviors are higher than those reported in the general population (U.S. Department of Health and Human Services, 2000) and highlight the importance of conducting additional studies that examine the long-term impact of risky behaviors on HRQOL. This study has several limitations. The sample was restricted to men living in the southeastern United States, which limits the generalizability of the results. Participants were recruited from health care clinics, and thus may have had healthier lifestyles and less stress than those persons who were not receiving regular health care. Behaviors and stress were measured by participant self-reports during face-to-face interviews. It is important to consider that participants may have provided socially desirable responses or inaccurate accounts because of poor retrospective recall. Because of the cross-sectional design of the study, causal inference is not possible. Nonetheless, unlike most behavioral studies that were conducted when HIV infection was considered an invariably fatal disease, this study was conducted after the advent of HAART, with patients now having renewed hopes of increasing the quantity and quality of their lives by engaging in health-promoting behaviors and avoiding risk behaviors and stress. In this era, the consequences of making healthy as well as risky lifestyle choices are different than in the pre-HAART era of HIV care. These results emphasize the importance of helping patients make healthy lifestyle choices and the need to integrate health promotion counseling and self-management programs into the health care plans of adults living with HIV infection.
Acknowledgements This work is based upon work supported by the Health Services Research and Development, Department of Veterans Affairs (NRI 98182, RCD 99011).
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HIV: The importance of violence, social support, and self care behaviors. Social Science and Medicine, 52, 315-322. Gifford, A. L., Laurent, D. D., Gonzales, V. M., Chesney, M. A., & Lorig, K. R. (1998). Pilot randomized trial of education to improve self-management skills of men with symptomatic HIV/AIDS. Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology, 18, 136-144. Gritz, E. R., Vidrine, D. J., Lazev, A. B., Amick, B. C., 3rd, & Arduino, R. C. (2004). Smoking behavior in a low-income multiethnic HIV/AIDS population. Nicotine and Tobacco Research, 6, 71-77. Hays, R. D., Cunningham, W. E., Sherbourne, C. D., Wilson, I. B., Wu, A. W., Cleary, P. D., et al. (2000). Health-related quality of life in patients with human immunodeficiency virus infection in the United States: Results from the HIV Cost and Services Utilization Study. The American Journal of Medicine, 108, 714-722. Heckman, T. G., Kalichman, S. C., Roffman, R. R., Sikkema, K. J., Heckman, B. D., Somlai, A. M., et al. (1999). A telephone-delivered coping improvement intervention for persons living with HIV/AIDS in rural areas. Social Work with Groups, 21, 49-61. Hofoss, D. (2004). Healthy living does not reduce life satisfaction among physically handicapped persons. Patient Education and Counseling, 52, 17-22. Jones, D. J., Beach, S. R., Forehand, R., & Foster, S. E. (2003). Self-reported health in HIV-positive African American women: The role of family stress and depressive symptoms. Journal of Behavioral Medicine, 26, 577-599. Kalichman, S., & Rompa, D. (2003). HIV treatment adherence and unprotected sex practices in people receiving antiretroviral therapy. Sex Transmitted Infections, 79, 59-61. Katz, J. F., Chang, L. C., Sangha, O., Fossel, A. H., & Bates, D. W. (1996). Can comorbidity be measured by questionnaire rather than medical record review? Medical Care, 34, 74-84. Knowlton, A., Latkin, C., Chung, S., Hoover, D., Ensinger, M., & Celento, D. (2000). HIV and depression among lowincome illicit drug users. AIDS and Behavior, 4, 353-360. Leserman, J., Petitto, J. M., Perkins, D. O., Folds, J. D., Golden, R. N., & Evans, D. L. (1997). Severe stress, depressive symptoms, and changes in lymphocyte subsets in human immunodeficiency virus-infected men: A 2-year follow-up study. Archives of General Psychiatry, 54, 279-285. Lucas, G. M., Gebo, K. A., Chaisson, R. E., & Moore, R. D. (2002). Longitudinal assessment of the effects of drug and alcohol abuse on HIV-1 treatment outcomes in an urban clinic. AIDS, 16, 767-774. Martinez, J., Moto, G., Vianna, G., & Rodrigues, A. (2004). Impaired quality of life of healthy young smokers. Chest, 125, 425-428. McCain, N. L., Zeller, J. M., Cella, D. F., Urbanski, P. A., & Novak, R. M. (1996). The influence of stress management training in HIV disease. Nursing Research, 45, 246-253. Mokdad, A. H., Marks, J. S., Stroup, D. F., & Gerberding, J. L. (2004). Actual causes of death in the United States, 2000.
66 JANAC Vol. 18, No. 6, November/December 2007 Journal of the American Medical Association, 291, 12381245. National Institute of Alcohol Abuse and Alcoholism. (1995). The Physicians’ Guide to Helping Patients with Alcohol Problems. (NIH Pub. No. 95-3769). Bethesda, MD: Author. Okoro, C. A., Brewer, R. D., Naimi, T. S., Moriarty, D. G., Giles, W. H., & Mokdad, A. H. (2004). Binge drinking and health-related quality of life: Do popular perceptions match reality? American Journal of Preventive Medicine, 25, 230233. Revicki, D. A., Sorensen, S., & Wu, A. W. (1998). Reliability and validity of physical and mental health summary scores from the medical outcomes study HIV health survey. Medical Care, 36, 126-137. Riley, E. D., Wu, A. W., Perry, S., Clark, R. A., Moss, A. R., Crane, J., & Bangsberg, D. R. (2003). Depression and drug use impact health status among marginally housed HIVinfected individuals. AIDS Patient Care and STDs, 17, 401-406. Salyer, J., Flattery, M. P., Joyner, P. L., & Elswick, R. K. (2003). Lifestyle and quality of life in long-term cardiac transplant recipients. Journal of Heart and Lung Transplantation, 22, 309-321. Samet, J. H., Horton, N. J., Traphagen, E. T., Lyon, S. M., & Freedberg, K. A. (2003). Alcohol consumption and HIV disease progression: Are they related? Alcoholism, Clinical, and Experimental Research, 27, 862-867. Sindelar, J. (1998). The social costs of alcohol. Journal of Drug Issues, 28, 763-780. Stuifbergen, A. K., Seraphine, A., & Roberts, G. (2000). An explanatory model of health promotion and quality of life in chronic disabling conditions. Nursing Research, 49, 122-129. Sullivan, P. S., Nakashima, A. K., Purcell, D. W., & Ward, J. W. (1998). Geographic differences in noninjection and injection substance use among HIV-seropositive men who have sex with men: Eastern United States versus other regions. Journal of Acquired Immune Deficiency Syndromes, 19, 266-274. Thun, M. J., Peto, R., Lopez, A. D., Monaco, J. H., Henley, S. J., Heath C. W., Jr., et al. (1997). Alcohol consumption and mortality among middle-aged and elderly U.S. adults. New England Journal of Medicine, 337, 1705-1714. Tuck, I., McCain, N. L., & Elswick, R. K. (2001). Spirituality and psychosocial factors in persons living with HIV. Journal of Advanced Nursing, 33, 776-783. Turner, J., Page-Shafer, K., Chin, D., Osmond, D., Mossar, M., Markstein, L., et al. (2001). Adverse impact of cigarette smoking on dimensions of health-related quality of life in persons with HIV infection. AIDS Patient Care and STDs, 15, 615-623. U.S. Department of Health and Human Services. (2000). Healthy People 2010. McLean, VA: International Medical Publishing. Vosvick, M. K., Koopman, C., Gore-Felton, C., Thoresen, C., Krumboltz, J., & Spiegel, D. (2003). Relationship of functional quality of life to strategies for coping with the stress of living with HIV/AIDS. Psychosomatics, 44, 51-58.
Walker, S. N., Sechrist, K. R., & Pender, N. J. (1987). The health-promoting lifestyle profile: Development and psychometric characteristics. Nursing Research, 36, 76-81. Wheeler, D. A., Gilbert, C. L., Launer, C. A., Muurahainen, N., Elion, R. A., Abrams, D. I., et al. (1998). Weight loss as a predictor of survival and disease progression in HIV infections. Journal of Acquired Immune Deficiency Syndromes and Retrovirology, 18, 80-85.
M
edical advances have afforded individuals longer, healthier, and more productive lives, resulting in a paradigm shift from HIV infection as a rapidly fatal illness to that of a long-term, chronic disease
(Vosvick et al., 2003). Consequently, health-related quality of life (HRQOL) among individuals with HIV infection has become an important focus of clinical practice and research. Researchers have identified a breadth of sociodemographic and clinical factors that affect HRQOL including age, ethnicity, socioeconomic status, lack of health care coverage, symptoms, and CD41 lymphocytes (Bing et al., 2000; Campsmith, Nakashima, & Davidson, 2003). Less is known about the role that healthy lifestyles play in improving HQROL during HIV infection. Healthy lifestyles encompass actions aimed at promoting wellness (e.g., physical activity, stress management) as well as those behaviors undertaken to prevent disease (e.g., avoidance of bad health habits Constance R. Uphold, PhD, ARNP, FAAN, is at the Rehabilitation Outcomes Research Center (RORC)/Geriatrics Research Education and Clinical Center (GRECC), North Florida/South Georgia Veterans Health System, Gainesville, Florida, and the Colleges of Nursing and Medicine, University of Florida, Gainesville. Wanda Holmes, PhD, RN, is at the North Florida/South Georgia Veterans Health System. Kimberly Reid, MS, is at the Mid American Heart Institute, Saint Luke’s Health System, Kansas City, Missouri. Kimberly Findley, RN, is at the RORC, North Florida/South Georgia Veterans Health System. Jorge P. Parada, MD, MPH, is at the Midwest Center for Health Services Research and Policy at the Hines Veterans Administration Hospital, Hines, Illinois, and the Stritch School of Medicine, Loyola University, Maywood, Illinois.
JOURNAL OF THE ASSOCIATION OF NURSES IN AIDS CARE, Vol. 18, No. 6, November/December 2007, 54-66 doi:10.1016/j.jana.2007.03.010 Copyright Ó 2007 Association of Nurses in AIDS Care
Uphold et al. / Healthy Lifestyles and Quality of Life
and stress) (Abel, 1991). A growing body of literature highlights the importance of healthy lifestyles in preventing morbidity and premature mortality (Mokdad, Marks, Stroup, & Gerberding, 2004) and in enhancing HRQOL among patients living with chronic illnesses such as multiple sclerosis (Stuifbergen, Seraphine, & Roberts, 2000), cardiovascular disease (Salyer, Flattery, Joyner, & Elswick, 2003), and neuromuscular disorders (Hofoss, 2004). Until recently, a healthy lifestyle among patients with HIV infection was a neglected topic of research (Clingerman, 2004). In particular, there are limited data on the effects of healthy lifestyles on HRQOL and other outcomes. According to a recent literature review (Chou & Holzemer, 2004), only one research team (Gielen, McDonnell, Wu, O’Campo, & Faden, 2001) has investigated the full impact of overall healthy lifestyles on HRQOL during HIV infection. In this study that excluded men, Gielen et al. (2001) reported that women who practiced more self-care behaviors (i.e., healthy eating, use of vitamin therapy, adequate sleep and physical activity, and stress management) had better HRQOL. On the other hand, several studies have examined relationships between specific domains of healthpromoting behaviors and HIV-related outcomes. Health-promoting behaviors are actions directed toward increasing well-being, self-actualization, and personal fulfillment and include the dimensions of health responsibility, physical activity, nutrition, spiritual growth, interpersonal relations, and stress management (Walker, Sechrist, & Pender, 1987). Using diverse theoretical and operational definitions, researchers reported that exercise and physical activity improved physiological outcomes as well as HRQOL among adults living with HIV (Clingerman, 2004). Although no known investigative team has specifically examined the effects of healthy eating on HRQOL during HIV infection, adequate nutrition is known to enhance the immune system, build reserves, and reduce vulnerability to wasting, thereby improving physical health (Wheeler et al., 1998) and most likely also improving HRQOL. Evidence is accumulating that behaviors related to spiritual growth (Flannelly & Inouye, 2001; Tuck, McCain, & Elswick, 2001) and actions aimed at reducing stress through the development of interpersonal relationships and coping strategies are associated with improved HRQOL during HIV infection
55
(Chesney, Chambers, Taylor, & Johnson, 2003; Vosvick et al., 2003). Previous HIV-related literature also showed that risk factors (Samet, Horton, Traphagen, Lyon, & Freedberg, 2003) such as tobacco use, alcohol consumption, recreational drug use, and unsafe sexual practices increase medical complications and enhance the spread of HIV transmission. However, the link between risk behaviors and HRQOL is less understood. Tobacco use was associated with decrements in various dimensions of HRQOL among persons who were not infected (Martinez, Moto, Vianna, & Rodrigues, 2004), as well as those who were infected with HIV (Chesney, 2001; Turner et al., 2001). Previous research on alcohol consumption and HRQOL among the general population has shown that excessive alcohol consumption increased mortality (Thun et al., 1997) and that alcohol dependence and binge drinking were negatively associated with HRQOL (Okoro et al., 2004). During HIV infection, there is limited information on the direct effects of alcohol consumption on HRQOL. However, excessive alcohol use was reported to increase the rate of progression to AIDS (Lucas, Gebo, Chaisson, & Moore, 2002; Samet et al., 2003). Most of the studies on recreational drug use have focused on injection drug abusers and report that drug use was associated with depression (Knowlton et al., 2000) and poorer HRQOL during HIV infection (Riley et al., 2003). Whereas there are numerous studies investigating the practice of unsafe sexual behaviors (Kalichman & Rompa, 2003), little is known about the relationship of unsafe sexual practices and HRQOL. In a study on risk perceptions, Demmer (2001) reported that adults with lower HRQOL compared with those with higher HRQOL were less likely to believe that the practice of safe sexual behaviors was important. Adults with HIV infection face a multitude of stressful life events including deterioration in health status, alienation from others, and prospects of losing employment, financial security, and social roles. Evidence of a negative impact of stress on disease progression during HIV infection is growing (Leserman et al., 1997). Similarly, researchers have increasingly noted that stressful life events are inversely related to various components of HRQOL (Au et al., 2004; Jones, Beach, Forehand, & Foster, 2003).
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Because most previous researchers have limited their investigations to examining selected behavioral variables that may affect one or more components of HRQOL, the purpose of this study was to examine the interplay of multiple components of healthy lifestyles and HRQOL dimensions among men living with HIV infection. Rather than focusing on one or two health behaviors such as exercise or diet, the authors included a full array of health-promoting behaviors, risk behaviors, and stress as independent variables in their models. This approach allowed them to determine relationships between various health behaviors and HRQOL when all other variables were controlled. The authors hypothesized that health-promoting behaviors would be positively related, whereas risk behaviors (i.e., tobacco use, hazardous alcohol use, recreational drug use, practice of unsafe sexual behaviors) and stress would be negatively related to HRQOL among men with HIV infection.
Method Sample The authors collected data from 226 HIV-infected men who were enrolled in a larger prospective cohort investigation designed to examine biopsychosocial determinants of disease progression during HIV infection. Participants were recruited from three infectious disease clinics in the southeastern United States: Veterans Affairs (VA) medical center (n 5 131), university hospital (n 5 40), and public health department (n 5 55). Inclusion criteria were male gender, 18 years of age and older, positive enzyme-linked immunosorbent assay screening and Western blot confirmatory tests, and English-speaking. Participants were excluded if they currently used corticosteroids or testosterone replacement therapy, had a current bacterial or viral infection, were diagnosed with HIV infection for less than 3 months, had a recent change (i.e., within 30 days) in their antiretroviral medication regimens, or were moribund or cognitively impaired. Clinicians at the clinics referred patients to the principal investigator. After scheduled clinic appointments, men were given information about the study and invited to participate. Participants were enrolled
sequentially at each site until recruitment targets were attained. The authors enrolled all male patients who regularly attended the three clinics between January 2001 and November 2002 and who met the study criteria, except for 43 patients who declined to participate. The main reasons for not participating were time constraints or feeling too ill to answer questions. Procedure Trained data collectors obtained informed consent, conducted structured face-to-face interviews, and helped subjects complete standardized questionnaires. Venipunctures to obtain blood samples were performed, and specimens were analyzed in the VA medical center laboratory. Typical research visits lasted 2 to 3 hours. Members of the research team reviewed the participants’ medical records to validate demographic and clinical data obtained during the interviews. Participants received a $30 stipend for completing the baseline interviews. The university institutional review board and the human protection committees of the related sites approved the study procedures. Measures Sociodemographic and clinical characteristics. Sociodemographic information included age, race/ ethnicity, and highest completed grade of education. Clinical measures included CD41 cell count and comorbidity. The authors obtained the CD41 cell count (cells per microliter of blood) from blood specimens that were drawn and analyzed at the VA clinical laboratory. The Charlson Comorbidity Questionnaire (Katz, Chang, Sangha, Fossel, & Bates, 1996) was used to assess the patients’ comorbid conditions, with the higher the summary score, the more severe the burden of comorbidity. The score for AIDS diagnosis was excluded from the summary score. Health-promoting behaviors. The Health-Promoting Lifestyle Profile II (HPLP-II) measured health-promoting behaviors. Health-promoting behaviors are actions directed at increasing well-being,
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self-actualization, and personal fulfillment (Walker et al., 1987). The HPLP-II is a 52-item instrument that consists of six subscales that measure major components of a healthy lifestyle: health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Health responsibility included seeking educational and professional assistance to improve health and paying attention to one’s health. Physical activity involved participating in regular exercise. The nutritional category included items related to healthy meal patterns and food choices. Interpersonal relations involved intimacy and closeness with others. Spiritual growth included items related to self-actualization and being connected with a force greater than oneself. Stress management involved using behaviors to control stress and improve coping abilities. Response choices ranged from 1 (never) to 4 (routinely). A score for overall health-promoting behaviors was determined by calculating the mean of each participant’s responses to all 52 items. Scores for the six subscales were obtained similarly by calculating a mean of the responses to the subscale items. The scale has established reliability and validity (Walker et al., 1987). In this study, Cronbach’s alpha for the total score was .91. Cronbach’s alphas for the subscales ranged from .80 to .90. Risk behaviors. Participants were considered tobacco users if they indicated that they currently smoked cigarettes/cigars or chewed tobacco. Alcohol use was measured by the Quantity/Frequency of Alcohol Consumption Tool developed by the National Institute of Alcohol Abuse and Alcoholism (National Institute of Alcohol Abuse and Alcoholism, 1995). It consists of three items, which ask participants how many days per week they drink, how many drinks they have on a typical day, and the maximum number of drinks on a given occasion. The authors determined whether participants were hazardous drinkers. Hazardous drinking was defined as having more than 14 drinks per week or having more than 4 drinks on a given occasion (Agency for Healthcare Research and Quality, 2004). Participants indicated the drugs they used in the past and the drugs they were using currently from a list of 54 items that included both ‘‘street’’ names and generic names. Participants were considered recreational drug users
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if they identified current drug use from any of the following categories: cannabis, stimulants, cocaine, hallucinogens, other. The authors also categorized participants as heavy recreational drug users if they used recreational drugs more than 3 days per week. Unsafe sexual practices were measured by two items that asked participants to indicate on scales from 1 (never) to 5 (all the time) whether they used recommended ‘‘safer sex’’ practices (i.e., condoms, rubber dams) with those people who were HIV-negative/ HIV status unknown and those people who were HIV-positive in the last 3 months. Participants were considered to be practicing unsafe sex if they indicated they failed to use recommended practices all of the time. The authors also reviewed the participants’ medical records to determine if they had ever been treated for drug or alcohol abuse problems and if their drug and alcohol problems were resolved or ongoing. Life event stress. Life event stress was measured with a semistructured interview, the Psychiatric Epidemiology Research Interview (Dohrenwend, Krasnoff, Askenasy, & Dohrenwend, 1978), which was modified to include stressors relevant to the HIV population (Leserman et al., 1997). Participants indicated which of the 113 stressors and difficulties they had experienced over the preceding 12 months. Participants were asked how stressful the event was and whether the event had a positive or negative impact. Interviewers then asked participants openended questions, followed as needed by probing questions to obtain detailed descriptions of each stressful event and its effect on the participant’s life. After the interviews were completed, the authors used a methodology similar to Leserman et al. (1997) to rate the long-term impact of the stressor by taking into account the contextual aspects of each event. Two trained researchers used a manual, which provided guidelines and criteria for making rating decisions and assigned a score from 0 (no threat) to 4 (severe threat) to each stressful event. Then, a composite stress score was obtained by summing the rating scores. There was a 90% interrater agreement between three raters on 15 randomly selected interview forms. The instrument is comprehensive, objectively measures chronic difficulties, and estimates the impact of a stressful event in a specific context for the
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average individual, thereby avoiding individual subjective reactions that invalidate other life event stress measures. Health-related quality of life (HRQOL). Scales from the HIV Cost and Services Utilization Study (Hays et al., 2000) were used to assess dimensions of HRQOL. This disease-specific measure assesses how well an individual functions and the individual’s perceptions of well-being in the physical, mental, and social domains of life. This 31-item measure includes the following scales: physical functioning (9 items), role functioning (2 items), pain (2 items), general health perceptions (3 items), social functioning (2 items), energy (2 items), emotional well-being (7 items), disability days (1 item), overall health (1 item), and overall quality of life (1 item). The physical functioning items denote a range of functioning from feeding oneself to vigorous exercise. Role functioning represents one’s ability to perform certain roles at work and at home. Items in the pain dimension involve amount of pain and the interference of pain with work. The general health items ask participants to rate their level of health and their perceptions of whether they tend to get sicker easier than others. The items on the social functioning subscale ask participants to rate the extent and amount their health interferes with social activities. The energy item represents the participant’s degree of tiredness and whether he has enough energy to perform tasks. Emotional well-being represents the participants’ positive/negative affect, anxiety, and depression. The one-item scales (i.e., disability days, overall health, overall quality of life) ask participants to list the number of days their health caused them to remain in bed and to rate their overall health and quality of life on a scale from 1 to 100. The authors excluded the one-item scales from their analyses. For the remaining scales, the items were averaged to get a score. In accordance with standard reporting procedures, all of the measures were then linearly transformed with a range of 0 to 100, with 100 representing the best health. The scales within the instrument were also summarized into three composite scales, a physical health summary, a mental health summary, and an overall HRQOL summary. This instrument has been used extensively in previous HIV-related research and has established validity
and reliability (Revicki, Sorensen, & Wu, 1998). In the present study, all of the scales and composite measures had acceptable internal reliabilities with Cronbach’s alphas ranging from .76 to .94. Data Analysis For the present study, only baseline data were analyzed. Descriptive statistics were used to delineate characteristics of the sample. Pearson productmoment correlations were used to test for associations between health promoting behaviors, stress, and HRQOL scores. Two sample t-tests were used to compare HRQOL scores between men who currently engaged in risk behaviors or had a history of risk behaviors (i.e., tobacco use, hazardous alcohol use, illicit drug use, heavy illicit drug use, unsafe sexual practices, previous/current drug and alcohol abuse treatments) and men who were not involved in risk behaviors. To investigate the interplay of multiple components of healthy lifestyles and HQROL dimensions, the authors included health-promoting behaviors, risk behaviors, and stress as independent variables in the models. Multivariable linear regression analyses were used to determine the relationships between health-promoting behaviors, risk behaviors, and stress and HRQOL dimensions, after controlling for covariates. Demographic variables and clinical factors reported to be consistently correlated with HRQOL and health behaviors in previous research were included as covariates: age (continuous), race/ethnicity (White, non-White), years of education (continuous), comorbidity (continuous), and number of CD41 cells (continuous). In each model, the dependent variable was the HRQOL score, and the independent variables were as follows: health-promoting behaviors (continuous), tobacco use (yes, no), hazardous alcohol use (yes, no), recreational drug use (yes, no), and unsafe sexual practices (yes, no). Because of high correlations among the HPLP-II subscales, the authors included only the total score in their multivariable linear regression analyses. Collinearity, model assumptions, and model fit of the final multivariable models were assessed and were not reported to be problems. Dichotomous results are reported as yes versus no as the reference level. White results are compared to reference level of non-White. All statistical tests
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were two-sided, and statistical significance was determined at the 5% level. All analyses were conducted by using SAS version 8.2 (SAS Institute, Inc., Cary, NC) statistical software package.
Results Descriptive Characteristics A total of 226 men participated in this study. The average age of the participants was 45.7 (SD 5 8.7) with a range of 20 to 70 years. The majority of participants were White (n 5 124, 55%), had more than 12 years of education (n 5 120, 53%), and had total family incomes of , $35,000 (n 5184, 81%). Homosexual contact was listed as the most frequent mode of transmission (n 5 72, 32%). A total of 52 (22%) men were infected through heterosexual contact, 19 (8%) listed intravenous drug use as their risk factor, 6 (3%) were infected through blood transfusions, and 79 (35%) were unsure of how they were infected or had multiple risk factors. The average score on the comorbidity index was 1.1. Liver disease, chronic obstructive pulmonary disease, and peptic ulcer disease were the most common comorbid conditions. The mean CD41 cell count was 415/mm3. Participants had lived an average of 8.3 years after testing positive for HIV. Most of the participants (n 5 198, 87.6%) were taking highly active antiretroviral therapy (HAART) medication regimens. The average score on the HPLP-II was 2.6 (SD 5 .48), with a range of 1.4 to 4.0. A total of 120 men (53%) used tobacco products. Almost half of the men (n 5112) smoked cigarettes, only 12 men smoked cigars, and 4 men chewed tobacco. The men drank alcohol on an average of 1.1 days per week. The average maximum number of drinks on one occasion was 2.4, with a range of 0 to 24. More than half of the men (n 5138, 61%) did not drink any alcohol, whereas 63 of the men (28%) were hazardous alcohol drinkers. On medical record review, the authors reported that 30 men (13%) were reported as having been previously treated for alcohol abuse problems. Of these men, 25 (83%) had unresolved alcohol abuse problems. The majority of the men (n 5 160, 71%) did not use recreational drugs, and only 24 were heavy recreational drug users. Marijuana was currently
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used by 52 men (23.0%), whereas none of the men were using hallucinogens, and only a small number were using cocaine (n 5 8, 4%) and stimulants (n 5 3, 1%). The majority of the men (n 5 180, 80%) stated that they had used recreational drugs in the past. From the medical records, the authors reported that 35 men (15%) had previously been treated for drug abuse problems and 28 (80%) of these men had unresolved drug abuse problems. Of the 110 men who had engaged in sexual activity in the past 3 months, 11 had failed to always practice safe sex with men who had unknown or negative HIV status, and 10 failed to always practice safe sex with men known to be HIV-positive. The average stress rating was 9.7, with a range of 0 to 51. The most frequently identified severe stressors were hospitalizations for life-threatening conditions, receiving information that their condition was fatal, progression of HIV infection, chronic financial stress, and death of an immediate family member.
Correlations Between Health-Promoting Behaviors, Stress, and Health-Related Quality of Life The authors examined the correlations between health-promoting behavior domains and stress and HRQOL dimensions (Table 1). Health responsibility was unrelated to any HRQOL dimension, whereas physical activity was positively related to every HRQOL dimension, with correlations ranging from .16 to .34. The total health-promoting behavioral score as well as spiritual growth, interpersonal relations, and stress management subscales were related to improvement in pain and better general health, emotional well-being, social functioning, energy, physical health, mental health, and overall HRQOL but were not related to two HRQOL dimensions (i.e., physical functioning and role functioning). The nutrition subscale was positively related to all dimensions of HRQOL except physical functioning, role functioning, emotional well-being, and energy. Stress was related to all dimensions of HRQOL except physical functioning. More frequent participation in health-promoting behaviors and less life-event stress were associated with higher ratings on most of the HRQOL dimensions.
60 JANAC Vol. 18, No. 6, November/December 2007 Table 1.
Pearson Product-Moment Correlations Between Health-Related Quality of Life Dimensions and Health-Promoting Behavior Domains and Stress Health-Promoting Health Physical Spiritual Interpersonal Stress Lifestyle Responsibility Activity Nutrition Growth Relations Management Stress
Physical functioning Role functioning Pain General health Emotional well-being Social functioning Energy Physical health summary Mental health summary Overall HRQOL summary
.10 .13 .20c .29a .30a .33a .22b .26a .33a .33a
.04 .05 .10 .06 .01 .09 2.01 .07 .03 .05
.26a .23b .21c .29a .16d .28a .25a .34a .21c .30a
.01 .06 .19c .23b .12 .16d .11 .16d .15d .17c
.04 .09 .11 .31a .45a .37a .28a .25b .46a .40a
.01 .06 .15d .18c .29a .27a .17d .16d .30a .26a
.06 .07 .20c .24b .37a .32a .19c .22b .35a .32a
2.03 2.25b 2.23b 2.31a 2.31a 2.33a 2.19c 2.29a 2.34a 2.35a
NOTE: HRQOL 5 health-related quality of life. a. p , .0001 b. p , .001 c. p , .01 d. p , .05
Comparisons Between Participants Who Did and Did Not Engage in Risk Behaviors The authors compared participants who engaged in risk behaviors with those who stated they did not engage in risk behaviors (Table 2). Although there were no statistically significant differences, men who used tobacco consistently had lower mean ratings on all the HRQOL dimensions than nonusers. Hazardous alcohol use was associated with one dimension of HRQOL—social functioning. Hazardous alcohol users had on average almost 10 points lower social functioning than other men (p , .05). Hazardous alcohol users also had lower scores on the other dimensions of HRQOL, but these differences were not statistically significant. There were no statistically significant differences in HRQOL between men who had been previously treated for alcohol abuse and whose current alcohol abuse problems were currently unresolved according to their medical records (data not shown). Men who used recreational drugs scored lower in all dimensions of HRQOL than nonusers, but these differences were not statistically significant. There were no statistically significant differences in HRQOL scores between men who were heavy and light recreational drug users. Men who had been previously treated for drug abuse problems and whose current drug abuse problems were currently unresolved had 11 points lower physical
functioning (t value 5 2.35, p 5 .02) and 14 points lower pain improvement (t value 5 2.64, p 5 .01) than men with a history of drug abuse treatment who were free of current drug abuse problems according to their medical records. Men who engaged in unsafe sexual practices had lower mean ratings on all HRQOL dimensions except the general health dimension than men who practiced safe sex, but these differences were not statistically significant. Multivariable Linear Regression Models The authors tested their hypothesis and examined the relationships of health-promoting behaviors, risk behaviors, stress, and HRQOL, controlling for age, race, education, comorbidity, and CD41 cell counts (Table 3). The variance explained by the independent variables and covariates in every model was statistically significant and ranged from 11% to 26%. Health-promoting behaviors were significantly related to all dimensions of HRQOL except physical functioning and role functioning. Higher scores on the health-promoting behaviors questionnaire were highly related to better general health, emotional well-being, social functioning, energy, physical health, mental health, overall quality of life, and lower levels of pain, with a one-unit improvement in health behaviors coinciding with 3- to 16-point improvements in HRQOL dimensions. Self-reported
82.9 (22.5) 75.2 (32.0) 60.9 (26.3) 59.4 (27.2) 69.7 (20.5) 73.8 (28.5) 60.9 (27.1) 52.0 (8.3) 52.5 (9.0) 52.4 (8.5) 76.0 (26.7) 65.8 (36.5) 49.5 (30.8) 62.3 (30.0) 61.1 (20.5) 65.1 (30.0) 57.9 (27.6) 49.2 (10.7) 49.4 (9.2) 49.2 (9.9) 76.4 (27.4) 68.3 (34.9) 57.1 (25.8) 58.1 (26.1) 66.3 (18.8) 70.7 (25.4) 59.0 (24.2) 50.4 (7.5) 51.2 (8.5) 50.9 (7.6) 85.9 (23.4) 78.1 (33.2) 55.4 (26.5) 52.8 (26.7) 69.5 (17.4) 68.8 (31.3) 60.0 (25.2) 51.1 (9.2) 51.8 (8.2) 51.6 (8.6) 84.2 (22.2) 74.8 (33.4) 61.5 (27.1) 62.4 (27.5) 70.8 (19.1) 74.8 (27.5) 62.5 (27.7) 52.5 (8.5) 53.0 (8.6) 53.0 (8.5)
77.7 (26.3) 68.3 (33.7) 56.3 (28.9) 60.4 (28.9) 64.9 (22.2) 65.7 (32.5)a 60.6 (27.5) 50.3 (9.0) 50.7 (10.1) 50.5 (9.5)
84.4 (21.2) 77.1 (31.6) 61.3 (26.0) 59.0 (26.9) 70.2 (20.0) 75.5 (26.7)a 60.4 (27.0) 52.3 (8.2) 52.7 (8.7) 52.7 (8.3)
80.2 (26.1) 72.3 (34.3) 56.1 (25.9) 56.6 (25.1) 67.4 (18.1) 70.1 (27.3) 59.2 (24.2) 50.7 (8.1) 51.4 (8.3) 51.1 (7.9)
83.4 (21.4) 75.6 (3.6) 61.5 (27.2) 60.6 (28.2) 69.3 (21.7) 73.9 (29.3) 60.9 (28.2) 52.1 (8.7) 53.9 (9.4) 52.5 (8.9)
Discussion
81.0 (23.4) 74.6 (31.6) 58.5 (26.6) 56.7 (27.1) 67.0 (21.9) 71.0 (29.7) 58.6 (26.5) 51.1 (8.5) 51.3 (9.5) 51.3 (8.8) a. p , .05
Hazardous Recreational Heavy Recreational Unsafe Sexual Tobacco Use Alcohol Use Drug Use Drug Use Practices Yes No Yes No Yes No Yes No Yes No (n 5 226) (n 5 120) (n 5 106) (n 5 63) (n 5 163) (n 5 66) (n 5 160) (n 5 24) (n 5 41) (n 5 19) (n 5 205) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Total Sample
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use of tobacco and recreational drugs and practice of unsafe sexual behaviors were not related to any of the HRQOL dimensions. Hazardous alcohol use was associated with one dimension of HRQOL—social functioning. Self-reported hazardous alcohol users had over 8 points lower social functioning than nonusers, after adjusting for covariates. Life-event stress was related to all dimensions of HRQOL except physical functioning. Greater life-event stress was associated with lower levels of HRQOL, with a one-unit increment in life-event stress coinciding with .26- to .98point decreases in HRQOL dimensions.
82.5 (22.9) 74.7 (32.4) 59.9 (26.8) 59.4 (27.4) 68.8 (20.7) 72.8 (28.7) 60.4 (27.1) 51.7 (8.5) 52.1 (9.1) 52.1 (8.7) Physical functioning Role functioning Pain General health Emotional well-being Social functioning Energy Physical health summary Mental health summary Overall quality of life summary
Table 2.
Means and Standard Deviations of Health-Related Quality of Life Dimension Scores for the Total Sample (N 5 226) and HIV-Infected Men Who Did and Did Not Engage in Risky Behaviors
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Now that people are living longer with HIV infection, improving HRQOL is an important clinical issue. Although previous researchers have reported that healthy lifestyles positively influence HRQOL among patients suffering from various chronic diseases, there is limited research on the role of healthy lifestyles during HIV infection. Results in this study highlight the association of modifiable factors, such as health-promoting behaviors and stress, with HRQOL among men living with HIV infection. Interventions aimed at promoting positive lifestyle changes have the potential to improve HRQOL. Instead of solely focusing on monitoring CD41 T cells and viral loads results to improve outcomes, clinicians need to include individualized counseling, patient education, and cognitive therapies to improve lifestyle choices in their management or care plans. As hypothesized, health-promoting behaviors had positive relationships with most of the HRQOL dimensions. This result is consistent with the results of Gielen et al. (2001) who reported that women who engaged in more health-promoting behaviors had better HRQOL. The authors also examined the correlations between specific domains within the overall health-promoting behavioral measure and the HRQOL dimensions. Physical activity was positively associated with all of the HRQOL dimensions, and the other health-promoting domains were positively related to most of the HRQOL dimensions. These results support those of others that exercise is a strong factor in enhancing well-being (Clingerman, 2004) and that spirituality (Flannelly & Inouye, 2001;
Multivariable Linear Regression Models of Factors Potentially Associated With Health-Related Quality of Life Scores (N 5 226)
Predictors
Physical Role Functioning Functioning Parameter Parameter Estimate Estimate (SE) (SE)
Pain Parameter Estimate (SE)
General Health Parameter Estimate (SE)
Emotional Social Well-Being Functioning Parameter Parameter Estimate Estimate (SE) (SE)
Energy Parameter Estimate (SE)
Physical Health Parameter Estimate (SE)
Overall Quality Mental of Life Health Parameter Parameter Estimate Estimate (SE) (SE)
Health behaviors 3.87 (3.16) 6.64 (4.37) 10.23c (3.62) 13.02c (3.58) 9.78b (2.67) 15.80a (3.71) 9.58c (3.64) 3.81b (1.11) 4.85a (1.15) 4.70a (1.09) Risk Behaviors Tobacco use 2.57 (3.10) 3.13 (4.28) 2.79 (3.55) 23.10 (3.51) 21.84 (2.62) 2.29 (3.64) 21.32 (3.57) 2.23 (1.09) 2.82 (1.13) 2.57 (1.07) Hazardous alcohol use 26.02 (3.56) 28.25 (4.91) 23.75 (4.07) 1.78 (4.03) 23.99 (3.00) 28.62d (4.17) 2.88 (4.09) 21.71 (1.25) 21.54 (1.30) 21.76 (1.22) Recreational drug use 21.07 (3.48) 2.98 (4.80) 22.06 (3.99) 22.91 (3.94) 1.71 (2.94) .45 (4.08) 1.13 (4.00) 2.37 (1.22) .53 (1.27) .08 (1.20) Unsafe sexual practices 2.60 (5.87) 2.38 (8.12) 25.17 (6.73) 9.00 (6.65) 21.89 (4.96) 1.94 (6.90) 3.02 (6.76) .43 (2.06) 2.06 (2.14) .20 (2.02) Stress 2.06 (.20) 2.87c (.27) 2.58d (.23) 2.90a (.22) 2.71a (.17) 2.98a (.23) 2.59c (.23) 2.26b (.07) 2.34a (.07) 2.32a (.07) Covariates Age 2.49c (.18) 2.49d (.24) 2.17 (.20) .42d (.20) .25 (.15) .15 (.21) .23 (.20) 2.03 (.06) .13 (.06) .05 (.06) White race 21.13 (3.09) 3.58 (4.27) 1.93 (3.54) 21.82 (3.50) 24.60 (2.61) 2.59 (3.63) 211.42c (3.56) 2.67 (1.09) 21.99 (1.13) 2.44 (1.06) Education .46 (.77) .42 (1.06) .58 (.88) .81 (.87) .27 (.65) .01 (.90) .51 (.88) .21 (.27) .13 (.28) .18 (.26) Comorbidity 22.00a (.85) 23.28b (1.18) 23.36b (.98) 22.37d (.97) 2.63 (.72) 21.77 (1.00) 23.20c (.98) 21.09b (.30) 2.46 (.31) 2.84c (.23) CD41 T cells 2.01 (.01) 2.01 (.01) 2.01 (.01) 2.00 (.01) 2.01d (.01) 2.01 (.01) 2.01 (.01) 2.01 (.01) 2.01d (.01) 2.01 (.01) 2 2 2 2 2 2 2 R 5 .11 R 5 .15 R 5 .16 R 5 .22 R 5 .22 R 5 .23 R 5 .17 R2 5 .21 R2 5 .25 R2 5 .26 NOTE: SE 5 standard error. a. p , .0001 b. p , .001 c. p , .01 d. p , .05
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Table 3.
Uphold et al. / Healthy Lifestyles and Quality of Life
Tuck et al., 2001), coping through self-management skills, and development of interpersonal relationships are associated with improved HRQOL (Chesney et al., 2003). In addition, this study is one of the first investigations to show that healthy eating is related to improved HRQOL. Surprisingly, health responsibility was not associated with any HRQOL dimension. It is possible that health responsibility, which emphasizes reliance on others (i.e., health professionals and educational programs) to improve health, is conceptually different from the other health-promoting domains, which focus on self-initiative and self-management. Another explanation is that health responsibility has a different meaning and impact on HRQOL among persons with HIV infection than on those persons living with other chronic diseases. Unlike the experience of patients with other chronic diseases, adults with HIV infection have frequent contact with health care providers and thus have limited choices in scheduling their health care visits and assuming responsibility for when they seek care. Contrary to the hypothesis, risk behaviors were not related to most dimensions of the HRQOL. Unlike previous research in the general population (Martinez et al., 2004) and HIV/AIDS population (Chesney, 2001; Turner et al., 2001), tobacco use was not associated with HQROL. Tobacco use, as well as use of alcohol and drugs, can sometimes enhance HQROL, particularly on a short-term basis. For example, tobacco use can provide immediate gratification of needs, lead to pleasurable sensations, and act as a coping mechanism. In this study, the short-term benefits of tobacco use may have counterbalanced the negative long-term effects of tobacco use. Hazardous alcohol use was associated with poor social functioning, which supports theory and previous research that has consistently reported a relationship between increased alcohol consumption and difficulties with social activities with family, friends, and colleagues (Sindelar, 1998). However, hazardous alcohol use was not associated with any other HRQOL dimension. To the authors’ knowledge, no study has examined hazardous alcohol use and HRQOL during HIV infection. However, because previous research reported that hazardous alcohol use results in rapid progression to AIDS (Lucas et al., 2002; Samet et al., 2003), it is surprising that this hazardous alcohol was not related to HRQOL.
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In this study, hazardous alcohol use was defined as more than 14 drinks per week or having more than 4 drinks on a given occasion in a week (Agency for Healthcare Research and Quality, April 2004). Other researchers have used different indicators of alcohol consumption and reported that alcohol dependence and binge drinking were associated with decreased HRQOL in the general population (Okoro et al., 2004). It is likely that alcohol consumption has a dose-response relationship to outcomes. In studies involving non-HIV-infected persons, light and moderate alcohol consumption was associated with improved outcomes (Berger et al., 1999), whereas excessive alcohol consumption increased mortality (Thun et al., 1997). Additional research is recommended to determine the impact of various frequencies and amounts of alcohol consumption on HQROL during HIV infection. Recreational drug use was not associated with any HRQOL dimension, which contrasts with previous research (Riley et al., 2003). However, in most previous studies, the samples included high proportions of adults who were injection drug users and/or were adults who were addicted to opioids. In this study, the majority of the men were using marijuana and none acknowledged injection drug use. As noted by Sullivan, Nakashima, Purcell, and Ward (1998), patterns of recreational drug use vary among different regions of the country. In this predominantly suburban and rural area in the southeastern United States, the association of recreational drug abuse with HQROL may be different than that reported in urban epicenters of the northeastern and western United States. These results emphasize the importance of considering local patterns of substance use when counseling patients and planning interventions and programs. Unsafe sexual behaviors were unrelated to HRQOL. To the authors’ knowledge, this was the first investigative team to examine this relationship. However, additional research is recommended because researchers have recently reported resurgence in the rate of unprotected sexuality activity (Dukers et al., 2001), which may have a significant impact on outcomes among adults with HIV infection in the future. Stress was negatively associated with all dimensions of HRQOL except for physical functioning. These results support previous research that has
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consistently reported that increased stressful life events are related to lower levels of HRQOL (Au et al., 2004; Leserman et al., 1997). Certain life events such as illness and death are outside the control of individuals. However, avoidance of other events such as demotion at work, conflict with partners, and jail terms for crimes is possible, and the efforts to sustain a stress-free life appear to be an important factor in maintaining a healthy lifestyle and improving HRQOL. The results of this study have important implications for clinical practice and health policy. As Gielen et al. (2001) note, the association of potentially modifiable factors such as health-promoting behaviors and stress offers new opportunities for enhancing HRQOL. Even in the complicated context of HIV infection, relatively simple, straightforward changes in lifestyles such as eating well, managing stress, and remaining active may result in significant improvements in HRQOL. Although there are challenges in altering one’s behavior, this study highlights the importance of counseling men with HIV infection about the benefits of engaging in health-promoting behaviors and avoiding stressful life events. In addition, as noted in the literature, educational programs that emphasize self-care (Gifford, Laurent, Gonzales, Chesney, & Lorig, 1998), coping improvement (Heckman et al., 1999), and cognitive behaviors strategies that reduce stress (McCain, Zeller, Cella, Urbanski, & Novak, 1996) are practical and cost-effective mechanisms for empowering patients with HIV infection to take personal responsibility for improving their health and quality of life. Although risk behaviors were not associated with HRQOL, the authors’ results support previous research, which reported that tobacco use and substance use are prevalent and difficult problems to resolve among patients with HIV infection (Galvan et al., 2002; Gritz, Vidrine, Lazev, Amick, & Arduino, 2004). The authors reported that 83% and 80% of the men treated for alcohol abuse and drug abuse, respectively, had unresolved substance use problems. Further, in this predominantly rural and suburban sample, there were sizeable numbers of men who were current tobacco users (n 5 120, 53%) and hazardous alcohol drinkers (n 5 63, 28%). In addition, 80% of the men stated that they had previously used recreational drugs. These figures of adults en-
gaging in risk behaviors are higher than those reported in the general population (U.S. Department of Health and Human Services, 2000) and highlight the importance of conducting additional studies that examine the long-term impact of risky behaviors on HRQOL. This study has several limitations. The sample was restricted to men living in the southeastern United States, which limits the generalizability of the results. Participants were recruited from health care clinics, and thus may have had healthier lifestyles and less stress than those persons who were not receiving regular health care. Behaviors and stress were measured by participant self-reports during face-to-face interviews. It is important to consider that participants may have provided socially desirable responses or inaccurate accounts because of poor retrospective recall. Because of the cross-sectional design of the study, causal inference is not possible. Nonetheless, unlike most behavioral studies that were conducted when HIV infection was considered an invariably fatal disease, this study was conducted after the advent of HAART, with patients now having renewed hopes of increasing the quantity and quality of their lives by engaging in health-promoting behaviors and avoiding risk behaviors and stress. In this era, the consequences of making healthy as well as risky lifestyle choices are different than in the pre-HAART era of HIV care. These results emphasize the importance of helping patients make healthy lifestyle choices and the need to integrate health promotion counseling and self-management programs into the health care plans of adults living with HIV infection.
Acknowledgements This work is based upon work supported by the Health Services Research and Development, Department of Veterans Affairs (NRI 98182, RCD 99011).
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