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. Author manuscript; available in PMC: 2021 Jul 1.
Published in final edited form as: AIDS Care. 2019 Sep 23;32(7):818–828. doi: 10.1080/09540121.2019.1668536

Self-perception of aging among HIV-positive and HIV-negative participants in the Multicenter AIDS Cohort Study

Karen Nieves-Lugo 1, Deanna Ware 2, M Reuel Friedman 3, Sabina Haberlen 4, James Egan 5, Andre L Brown 5, Omar Dakwar 6, Michael Plankey 2
PMCID: PMC7085960  NIHMSID: NIHMS1540664  PMID: 31547674

Abstract

Self-perception of aging is an important predictor of quality of life. Therefore, we sought to examine self-perceptions of aging (age discrepancy and aging satisfaction) between HIV-positive and HIV-negative men in the Multicenter AIDS Cohort Study (MACS). We included 835 HIV-negative and 784 HIV-positive men aged 50 years and older who had completed a survey about age discrepancy and aging satisfaction from the “Attitude toward own aging” subscale of the Philadelphia Geriatric Center Morale scale. Multinomial generalized logit models were generated to assess self-perception of aging by HIV status. Most of the participants self-identified as white, former smokers, and had completed high school. HIV-positive individuals reported higher prevalence of comorbidities than HIV-negative individuals. After adjusting for covariates, positive age discrepancy (older subjective age) was positively associated with being HIV positive and having less than a high school education, depressive symptoms, diabetes, and medium and low aging satisfaction. Low aging satisfaction was associated with being a current and former smoker and having depressive symptoms, diabetes, and no age and positive age discrepancy. Being black had decreased odds of low aging satisfaction. These findings should inform health care professionals to promote positive views of aging in the assessment and management of HIV, depression, and diabetes.

Keywords: Subjective age, HIV, self-perceptions of aging, aging satisfaction, Multicenter AIDS Cohort Study

Introduction

There are estimates that 70% of people living with HIV will be older than 50 years of age by 2020 (Centers for Disease Control and Prevention, 2018). HIV infection is associated with systemic inflammation that contributes to the progression of age-related morbidities and geriatric issues (Althoff et al., 2014; Franceschi & Campisi, 2014; Guaraldi et al., 2011; Triant et al., 2007). In addition, there is evidence that the assessment of one’s own physical and mental health influences the aging process (Barrett, 2003; Boehmer, 2007; Fumaz et al., 2012; Hubley & Russell, 2009; Kleinspehn-Ammerlahn et al., 2008; Kotter-Grühn, Kleinspehn-Ammerlahn, Gerstorf, & Smith, 2009; Levy, Slade, Kunkel, & Kasl, 2002; Menkin et al., 2017; Mock & Eibach, 2011). These perceptions toward our own aging process have been associated with successful aging, well-being, life satisfaction, and longevity (Barrett, 2003; Boehmer, 2007; Fumaz et al., 2012; Hubley & Russell, 2009; Kleinspehn-Ammerlahn et al., 2008; Kotter-Grühn, Kleinspehn-Ammerlahn, Gerstorf, & Smith, 2009; Levy, Slade, Kunkel, & Kasl, 2002; Mock & Eibach, 2011).

Self-perceptions of aging are described by 2 components: age discrepancy and aging satisfaction (Barker, O’Hanlon, McGee, Hickey, & Conroy, 2007; Barrett, 2003; Bergland, Nicolaisen, & Thorsen, 2014; Farinpour et al., 2003; Levy et al., 2002). Age discrepancy refers to how old an individual perceives themselves to be in comparison with his or her chronological age (Boehmer, 2007; Kotter-Grühn et al., 2015; Montepare, 2009). Aging satisfaction refers to the self-assessment of the aging process that can be influenced by experiences over time (i.e., energy level, quality of life) (Kleinspehn-Ammerlahn et al., 2008; Kotter-Grühn et al., 2009).

Findings demonstrated that having a positive self-perception of aging is associated with the use of preventive services (e.g., flu shots, cholesterol tests, prostate examination) and the adoption of preventive health behaviors (e.g., healthy diet, quit smoking, medication compliance, regular physician visits) (Kim, Moored, Giasson, & Smith, 2014; Levy & Myers, 2005; Levy & Myers, 2004). On the contrary, negative self-perceptions of aging are associated with low incomes, living alone, and poor physical and mental health (i.e., having a higher number of illnesses, disability, depression) (Kleinspehn-Ammerlahn et al., 2008; Moser et al., 2011). For instance, people who feel older than their actual chronological age are more likely to report negative predictions for future health (Barrett, 2003), lower life satisfaction (Barak, & Rahtz, 1999), and more functional limitations and disability (Moser et al., 2011; Stephan, Chalabaev, Kotter-Grühn, & Jaconelli, 2013). Fumaz et al. (2012) found that 37% of HIV-positive men reported feeling older than their chronological age and 43% perceived they were aging prematurely than their HIV-negative counterparts.

Despite the growing evidence that a positive self-perception of aging can improve quality of life (Boehmer, 2007), the literature examining self-perceptions of aging among HIV-positive individuals is scarce. The aim of this analysis was to compare self-perceptions of aging (i.e., age discrepancy and aging satisfaction) between HIV-positive and HIV-negative men. We hypothesized that HIV-positive men would have higher age discrepancy and lower aging satisfaction compared with HIV-negative participants after controlling for race, education, smoking status, non–HIV-defining comorbidities (i.e., depression symptoms, diabetes, hepatitis C, cancer, dyslipidemia, and high blood pressure) and time. Further, we hypothesized that age discrepancy and aging satisfaction would be positively associated with HIV-specific factors (i.e., viral load detectability and history of clinical AIDS) within the HIV-positive subsample.

Materials and methods

Study design and participants

The Multicenter AIDS Cohort Study (MACS) is an ongoing study that follows a cohort of HIV-positive and -negative men who have sex with men in 4 US sites: Baltimore/Washington, DC; Chicago; Los Angeles; and Pittsburgh/Columbus. Since its inception in 1984, a total of 7,352 HIV-seropositive and HIV-seronegative men who have sex with men have been enrolled in the study over 4 time periods: 4,954 in 1984–1985; 668 in 1987–1991; 1350 in 2001–2003; 380 in 2010–2018. MACS participants attend semiannual clinic visits that involve an Audio Computer-Assisted Self-Interview and a standardized clinical examination in which medical history data and specimens are collected. The study design of the MACS has been described elsewhere (Farinpour et al., 2003; Kaslow et al., 1987). Questionnaires are available at www.aidscohortstudy.org. Institutional review boards at each study site approved the MACS protocol and informed consent was obtained from all study participants. We used data from Understanding Patterns of Healthy Aging among Men who have Sex with Men, a multi-wave sub-study of the MACS parent protocol. Selection criteria for the sub-study were as follows: 1) being aged 40 years or older as of April 2016; 2) two consecutive MACS visit proceeding April 2016; and 3) report at least one incidence of sexual intercourse with another male since enrolling in the MACS. The refusal rate ranged from 5.4% to 7.1% over the six waves of data collection. In this analysis, we included 1,619 (835 HIV-negative/784 HIV-positive) men aged 50 years or older (CDC, 2019) who had complete information about age discrepancy and aging satisfaction at visits 62 (October 2014-March 2015), 63 (April 2015-September 2015), and 66 (October 2016-April 2017) The 1,619 participants contributed 4,269 person-visits to this analysis.

Measures

The outcome measures of self-perceptions of age were (1) age discrepancy and (2) aging satisfaction. Age discrepancy was assessed from self-report question: “What age (years) do you feel most of the time?” and was calculated as the difference between subjective age (how old a participant felt) and chronological age (age discrepancy = subjective age – chronological age). Positive values indicated that the participant reported a subjective age older than their chronological age, while negative values indicated that the participants reported a subjective age younger than their chronological age. Age discrepancy was collapsed into 3 categories: positive age discrepancy (subjective age > chronological age); no age discrepancy (subjective age = chronological age); and negative age discrepancy (subjective age < chronological age) (Barrett, 2003; Bergland et al., 2014; Boehmer, 2007). Aging satisfaction was measured using the Attitudes Towards Aging subscale from the validated Philadelphia Geriatric Center Morale Scale (Lawton, 1975; McCulloch, 1991; Lawton, 2003). The subscale included 5 items: (1) “Things keep getting worse as I get older (Yes/No)”; (2) “I have as much pep as I had over the past 6 months (Yes/No)”; (3) “As I get older, I am less useful (Yes/No)”; (4) “I am as happy now as I was when I was younger (Yes/No)”; and (5) “As I get older, things are __ than I thought they would be (Better/Worse).” “Yes” and “better” responses were assigned a value of 2, while “no” and “worse” responses were assigned a value of 1. Items 1 and 3 were reverse coded. All 5 items were then summed to obtain the aging satisfaction score, which ranged from 5 to 10, with higher scores indicating higher aging satisfaction. The resulting values were then categorized into low aging satisfaction: 5–6; moderate aging satisfaction: 7; and high aging satisfaction: 8–10 (Lawton, 1975).

HIV status, age, race, education, smoking status, and comorbidities were included as covariates in the model. Participants’ chronological age at visit was derived from self-reported date of birth and date of visit and categorized into (1) 50–59 years; (2) 60–69 years; and (3) 70 years and older in the models. Race was categorized as black and white. Other racial and ethnic categories were removed from the analysis due to small sample sizes. Education was categorized as “less than a high school diploma” and “obtained a high school diploma.” Smoking status was categorized as current, former, or never smoker based on participants’ response to the question, “Have you ever smoked cigarettes?”

Comorbidities examined included high blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥ 90 mm Hg), diabetes (fasting glucose ≥ 126 mg/dL), liver disease (serum glutamic pyruvic transaminase or serum glutamic oxaloacetic transaminase > 150 U/L), kidney disease (estimated glomerular filtration rate < 60 mL/min/1.73 m2 or urine protein-to-creatinine ratio ≥ 200), and dyslipidemia (total cholesterol ≥ 200 mg/dL or low-density lipoprotein cholesterol ≥ 130 mg/dL or high-density lipoprotein cholesterol < 40 mg/dL or triglycerides ≥ 150 mg/dL) (Althoff et al., 2014). Depressive symptoms were defined by the Center for Epidemiologic Studies Depression scale, with scores greater than or equal to 16 indicating the presence of significant depressive symptoms (Radloff & Radloff, 1977). Participants were classified as having a hepatitis C infection at each visit if they seroconverted or had an acute infection or chronic infection. Cancer was defined as a diagnosis of any type of cancer within a year of study visits 62, 63, or 66. HIV status (HIV positive/HIV negative) was assessed using enzyme-linked immunosorbent assay with confirmatory Western blot on all MACS participants at their initial visit and at every visit for men who were HIV negative at the previous visit.

HIV-positive participants included all men who were identified as such at their initial visit and those who seroconverted during study observation. Among HIV-positive men, information about plasma HIV RNA levels (viral load, copies/mL) and history of clinical AIDS diagnosis (yes/no) were obtained. For modeling purposes, viral load was dichotomized into detectable (> 20 copies/mL) and undetectable (≤20 copies/mL).

Statistical methods

Descriptive statistics on the outcomes and covariates were summarized by HIV status. T tests and χ2 tests were calculated, where appropriate, to assess differences between HIV-positive and -negative participants. HIV status was the primary predictor for the age discrepancy and aging satisfaction models. The other covariates included age, race, education, smoking status, and the aforementioned comorbidities. In addition, to explore the relationship between age discrepancy and aging satisfaction in the framework of self-perceptions of aging, we added aging satisfaction as a covariate in the age discrepancy model, while age discrepancy was added as a covariate in the aging satisfaction model. Four multinomial generalized logit models were generated in the overall sample, adjusting for covariates: (1) age discrepancy without aging satisfaction as a covariate; (2) aging satisfaction without age discrepancy as a covariate; (3) age discrepancy with aging satisfaction as a covariate; and (4) aging satisfaction with age discrepancy as a covariate. Modeling was repeated among HIV-positive participants, adjusting for viral load detectability and history of clinical AIDS. In the aging discrepancy models, we examined the factors associated with the likelihood of positive age discrepancy and no age discrepancy compared with negative age discrepancy. In the aging satisfaction models, we examined the factors associated with the likelihood of low and medium aging satisfaction compared with high aging satisfaction. Collinearity was assessed between the independent covariates using the variance inflation factor. Variance inflation factor values greater than 10 indicated possible multicollinearity. Adjusted odds ratios (OR) and their corresponding 95% confidence intervals (CIs) were reported. Statistical significance was set at the P < .05 level. Statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, North Carolina, USA).

Results

Table 1 summarizes participant characteristics by HIV status at the index visit. Most participants self-identified as white, former smokers, and had completed high school. The mean (SD) age at the index visit for HIV-positive and HIV-negative participants was 58.8 (6.2) years and 62.4 (7.4) years, respectively. HIV-positive participants had higher prevalence of diabetes, depression, hepatitis C, dyslipidemia, liver disease, and kidney disease, while HIV-negative participants had higher prevalence of hypertension. Among HIV-positive participants, most maintained undetectable viral load (71.8%) and only 15.7% had received a clinical AIDS diagnosis. Although both groups reported feeling younger than their chronological age (Table 1), the difference was smaller for HIV-positive men, who felt on average 10.3 (SD, 12.4) years younger, while HIV-negative men felt on average 12.2 (SD, 11.5) years younger (P <.001). Aging satisfaction was relatively high among all participants and did not differ between HIV-positive (7.99; SD, 1.2) and HIV-negative (8.00;SD, 1.1) participants (P = .37).

Table 1.

Characteristics of study population by HIV at index visit.

HIV status P value
Positive (n=784) Negative (n=835)
Age, mean (SD) (years) 58.8 (6.2) 62.4 (7.4) <.001
Race, n (%)
 White 575 (73.3) 705 (84.4) <.001
 Black 209 (26.7) 130 (15.6)
Education, n (%)
 Less than a high school diploma 376 (48.0) 289 (34.6) <.001
 Obtained high school diploma 408 (52.0) 546 (65.4)
Smoking status, n (%)
 Never 198 (25.3) 222 (26.6) .0002
 Former 396 (50.5) 482 (57.7)
 Current 153 (19.5) 109 (13.1)
 Missing 37 (4.7) 22 (2.6)
Comorbidities, n (%)
 Diabetes 105 (13.4) 102 (12.2) <.001
 Depression 157 (20.0) 153 (18.3) .65
 Hepatitis C 74 (9.4) 36 (4.3) <.001
 Dyslipidemia 539 (68.8) 555 (66.5) .008
 Cancer 13 (1.7) 13 (1.6) .87
 Hypertension 171 (21.8) 244 (29.2) .0006
 Liver Disease 5 (0.6) 0 (0.0) .003
 Kidney Disease 215 (27.4) 64 (7.7) <.001
Clinical AIDS diagnosis
 Yes 123 (15.7) - -
 No 661 (84.3) - -
HIV viral load, n (%)
 Detectable 91 (11.6) - -
 Undetectable 563 (71.8) - -
 Missing 130 (16.6) - -
Aging discrepancy, Mean (SD) −10.3 (12.2) −12.2 (11.5) 0.004
Aging satisfaction, Mean (SD) 7.99 (1.2) 8.0 (1.1) 0.37
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Abbreviation: SD, standard deviation.

The adjusted variance inflation factor values for each covariate in the model ranged between 1.005 and 1.257, indicating that there was no evidence of collinearity. The age discrepancy model revealed that participants who were HIV positive (vs negative; OR,1.66 [95% CI, 1.14–2.43]), obtained less than a high school diploma (vs high school diploma; OR, 1.94 [95% CI, 1.32–2.86]), and had depressive symptoms (vs none; OR, 4.68 [95% CI, 3.25–6.75]) and diabetes (vs none; OR, 1.79 [95% CI, 1.08–2.97]) were more likely to report a subjective age older than their chronological age (Table 2). These associations were attenuated when controlling for aging satisfaction, particularly among participants who were HIV positive (OR, 1.17 [95% CI, 0.85–1.61]) and had depressive symptoms (OR, 1.83 [95% CI, 1.22–2.75]). Individuals who reported low (vs high; OR, 14.24 [95% CI, 8.13–24.91]) and medium (vs high; OR, 3.04 [95% CI, 1.64–5.64]) aging satisfaction had greater likelihood of reporting a subjective age older than their chronological age compared with those individuals who reported higher aging satisfaction. Details regarding factors associated with reporting a subjective age equal to the chronological age are reported in Table 2.

Table 2.

Adjusted odds ratios (95% CL) for positive age discrepancy.

Outcome: age discrepancy Without aging satisfaction, adjusted odds ratio (95% CI) With aging satisfaction, adjusted odds ratio (95% CI)
Positive age discrepancy vs negative age discrepancy No age discrepancy vs negative age discrepancy Positive age discrepancy vs negative age discrepancy No age discrepancy vs negative age discrepancy
Age
 50–59 years old 2.24 (0.94–5.34) 1.20 (0.71–2.02) 3.01 (1.26–7.21) 1.38 (0.81–2.33)
 60–69 years old 1.51 (0.63–3.62) 1.04 (0.63–1.71) 1.75 (0.74–4.17) 1.12(0.68–1.83)
 ≥70 years old Referent Referent Referent Referent
HIV status
 Positive 1.66 (1.14–2.43)a 1.17 (0.85–1.61) 1.56 (1.04–2.36) a 1.13 (0.82–1.56)
 Negative Referent Referent Referent Referent
Visits
  6 months from baseline 0.86 (0.65–1.14) 1.02 (0.84–1.23) 0.87 (0.64–1.18) 1.01 (0.83–1.23)
  24 months from baseline 0.64 (0.42–0.99) a 0.58 (0.41–0.83) a 0.91 (0.56–1.48) 0.76 (0.52–1.12)
  Baseline Referent Referent Referent Referent
Race
 Black 0.62 (0.38–1.01) 0.83 (0.57–1.19) 0.73 (0.45–1.20) 0.89 (0.61–1.28)
 White Referent Referent Referent Referent
Education
 Less than a high school diploma 1.94 (1.32–2.86) a 1.01 (0.73–1.39) 2.03 (1.35–3.05) a 1.01 (0.73–1.40)
 Obtained high school diploma Referent Referent Referent Referent
Smoking status
 Current smoker 0.96 (0.56–1.67) 1.61 (1.03–2.49) a 0.87 (0.50–1.53) 1.56 (1.01–2.43) a
 Former smoker 1.02 (0.65–1.58) 1.16 (0.82–1.65) 0.98 (0.62–1.54) 1.15 (0.81–1.65)
 Never smoker Referent Referent Referent Referent
Depressive symptoms
 Yes 4.68 (3.25–6.75) a 1.66 (1.24–2.23) a 1.83 (1.22–2.75) a 1.15 (0.81–1.65)
 No Referent Referent Referent Referent
Kidney disease
 Yes 1.14 (0.73–1.79) 1.24 (0.90–1.72) 1.06 (0.66–1.70) 1.21 (0.87–1.68)
 No Referent Referent Referent Referent
Liver disease
 Yes 1.89 (0.18–19.97) 0.65 (0.07–5.76) 1.67 (0.10–29.20) 0.62 (0.06–5.95)
 No Referent Referent Referent Referent
High blood pressure
 Yes 0.89 (0.61–1.29) 0.89 (0.66–1.18) 0.96 (0.65–1.42) 0.9 (0.67–1.21)
 No Referent Referent Referent Referent
Diabetes
 Yes 1.79 (1.08–2.97) a 1.01 (0.40–2.56) 1.50 (0.89–2.54) 1.57 (1.08–2.26)
 No Referent Referent Referent Referent
Dyslipidemia
 Yes 1.36 (0.86–2.14) 1.15 (0.80–1.65) 1.60 (1.00–20.56) 1.23 (0.86–1.78)
 No Referent Referent Referent Referent
Cancer
 Yes 1.08 (0.29–3.97) 1.65 (1.14–2.37) a 0.88 (0.21–3.69) 0.94 (0.36–2.44)
 No Referent Referent Referent Referent
Aging satisfaction
 Low - - 14.24 (8.13–24.91) a 2.67 (1.91–3.74) a
 Medium - - 3.04 (1.64–5.64) a 1.44 (1.04–1.98) a
 High Referent Referent Referent Referent
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Abbreviation: CI, confidence interval.

a

Statistically significant at P<.05.

In the aging satisfaction model, being 50 to 59 years old (vs ≥70; OR, 0.42 [95% CI, 0.27–0.67]) or 60 to 69 years old (vs ≥70; OR, 0.61 [95% CI, 0.40–0.94]) and being black (vs white; OR, 0.58 [95% CI, 0.40–0.84]) were associated with being less likely to report low aging satisfaction (Table 3). While those who were current smokers (vs never; OR, 1.91 [95% CI, 1.23–2.95]), had depressive symptoms (vs none; OR, 14.06 [95% Cl, 10.21–19.36]), and had diabetes (vs none; OR, 1.84 [95% CI, 1.26–2.70]) were more likely to report low aging satisfaction (Table 3). When age discrepancy was added to the model, the association with presence of depressive symptoms was slightly attenuated (OR, 12.65 [95% Cl, 9.07–17.64]), while the other associations remained similar. Details regarding factors associated with reporting medium aging satisfaction are reported in Table 3.

Table 3.

Adjusted odds ratios (95% CL) for lower aging satisfaction.

Outcome: aging satisfaction Without age discrepancy, adjusted odds ratio (95% CI) With age discrepancy, adjusted odds ratio (95% CI)
Medium vs high Low vs high Medium vs high Low vs high
Age
 50–59 years old 0.59 (0.39–0.89)a 0.42 (0.27–0.67) a 0.56 (0.37–0.86) a 0.34 (0.22–0.55) a
 60–69 years old 0.74 (0.50–1.10) 0.61 (0.40–0.94) a 0.73 (0.49–1.08) 0.56 (0.37–0.87) a
 ≥70 years old Referent Referent Referent Referent
HIV status
 Positive 0.97 (0.74–1.26) 1.26 (0.94–1.68) 0.95 (0.73–1.24) 1.15 (0.85–1.55)
 Negative Referent Referent Referent Referent
Visits
  6 months from baseline 0.90 (0.73–1.09) 0.99 (0.82–1.19) 0.89 (0.73–1.09) 1.01 (0.82–1.23)
  24 months from baseline 0.30 (0.21–0.44) a 0.39 (0.28–0.55) 0.3 (0.21–0.44) a 0.40 (0.28–0.57) a
  Baseline Referent Referent Referent Referent
Race
 Black 0.79 (0.57–1.10) 0.58 (0.40–0.84) a 0.78 (0.57–1.09) 0.60 (0.42–0.88) a
 White Referent Referent Referent Referent
Education
 Less than a high school diploma 0.89 (0.68–1.16) 1.00 (0.74–1.35) 0.87 (0.66–1.13) 0.88 (0.65–1.20)
 Obtained high school diploma Referent Referent Referent Referent
Smoking status
 Current smoker 1.54 (1.05–2.26) a 1.91 (1.23–2.95) a 1.51 (1.03–2.23) a 1.88 (1.21–2.93) a
 Former smoker 1.20 (0.91–1.59) 1.37 (1.00–1.86) 1.20 (0.90–1.58) 1.36 (0.99–1.87)
 Never smoker Referent Referent Referent Referent
Depressive symptoms
 Yes 3.49 (2.50–4.85) a 14.06 (10.21–19.36) a 3.44 (2.47–4.80) a 12.65 (9.07–17.64) a
 No Referent Referent Referent referent
Kidney disease
 Yes 1.25 (0.92–1.70) 1.29 (0.93–1.80) 1.23 (0.91–1.68) 1.24 (0.89–1.73)
 No Referent Referent Referent Referent
Liver disease
 Yes 1.25 (0.23–6.82) 1.64 (0.29–9.33) 1.04 (0.16–6.85) 1.16 (0.12–10.79)
 No Referent Referent Referent Referent
High blood pressure
 Yes 0.97 (0.76–1.24) 0.89 (0.68–1.17) 0.99 (0.77–1.27) 0.91 (0.69–1.19)
 No Referent Referent Referent Referent
Diabetes
 Yes 1.39 (0.99–1.96) 1.84 (1.26–2.70) a 1.34 (0.95–1.88) 1.64 (1.12–2.41) a
 No Referent Referent Referent Referent
Dyslipidemia
 Yes 0.86 (0.65–1.14) 0.80 (0.59–1.09) 0.85 (0.64–1.14) 0.74 (0.54–1.02)
 No Referent Referent Referent Referent
Cancer
 Yes 2.35 (0.81–6.79) 2.06 (0.77–5.49) 2.4 (0.81–7.09) 2.14 (0.78–5.85)
 No Referent Referent Referent Referent
Aging discrepancy
 Older - - 3.21 (1.70–6.06) a 15.18 (8.53–27.01) a
 Same - - 1.41 (1.03–1.95) a 2.65 (1.89–3.72) a
 Younger Referent Referent Referent Referent
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Abbreviation: CI, confidence interval.

a

Statistically significant at P < .05.

A clinical history of AIDS was associated with low aging satisfaction, but not with age discrepancy (Tables 4 and 5). HIV-positive participants who felt older (OR, 15.97 [95% CI, 7.42–34.38]) had increased odds of low aging satisfaction compared with HIV-positive men who felt younger (Table 5). HIV-positive men with a clinical history of AIDS had a 78% increased likelihood of low aging satisfaction (vs no AIDS history; OR, 2.09 [95% CI, 1.22–3.56]) and the magnitude of association decreased (vs no AIDS history; OR, 1.94 [95% CI, 1.12–3.37]) when age discrepancy was added to the model (Table 5). Viral load detectability was not associated with age discrepancy or aging satisfaction.

Table 4.

Adjusted odds ratios (95% CL) for older age discrepancy: HIV positive only.

Outcome: age discrepancy Without aging satisfaction, adjusted odds ratio (95% CI) With aging satisfaction, adjusted odds ratio (95% CI)
Positive age discrepancy vs negative age discrepancy No age discrepancy vs negative age discrepancy Positive age discrepancy vs negative age discrepancy No age discrepancy vs negative age discrepancy
Age
 50–59 years old 7.81 (1.07–57.19)a 1.66 (0.62–4.43) 9.15 (1.37–60.93) a 1.78 (0.68–4.66)
 60–69 years old 5.90 (0.78–44.29) 1.69 (0.63–4.49) 6.23 (0.93–41.87) 1.75 (0.67–4.57)
 ≥70 years old Referent Referent Referent Referent
Visits
  6 months from baseline 1.12 (0.76–1.63) 0.95 (0.72–1.25) 1.19 (0.77–1.82) 0.96 (0.73–1.27)
  24 months from baseline 0.89 (0.52–1.54) 0.51 (0.29–0.87) a 1.19 (0.62–2.31) 0.62 (0.35–1.12)
  Baseline Referent Referent Referent Referent
Race
 Black 0.72 (0.39–1.33) 1.01 (0.63–1.60) 0.89 (0.46–1.71) 1.09 (0.69–1.74)
 White Referent Referent Referent Referent
Education
 Less than a high school diploma 2.09 (1.24–3.55) a 0.73 (0.46–1.17) 2.18 (1.25–3.83) 0.73 (0.46–1.17)
 Obtained high school diploma Referent Referent Referent Referent
Smoking status
 Current smoker 0.82 (0.39–1.71) 1.89 (1.03–3.49) a 0.73 (0.34–1.59) 1.86 (1.02–3.38) a
 Former smoker 1.29 (0.73–2.29) 1.54 (0.92–2.56) 1.32 (0.71–2.44) 1.62 (0.97–2.71)
 Never smoker Referent Referent Referent Referent
Depressive symptoms
 Yes 3.56 (2.26–5.61) a 2.09 (1.38–3.16) a 1.5 (0.89–2.53) 1.47 (0.92–2.34)
 No Referent Referent Referent Referent
Kidney disease
 Yes 1.41 (0.84–2.39) 1.25 (0.83–1.88) 1.25 (0.71–2.22) 1.17 (0.77–1.77)
 No Referent Referent Referent Referent
Liver disease
 Yes 2.97 (0.29–30.69) 0.99 (0.12–8.53) 2.11 (0.10–45.31) 0.85 (0.08–8.85)
 No Referent Referent Referent Referent
High blood pressure
 Yes 0.78 (0.46–1.34) 0.75 (0.49–1.15) 0.93 (0.52–1.67) 0.77 (0.50–1.20)
 No Referent Referent Referent Referent
Diabetes
 Yes 1.79 (0.92–3.47) 1.45 (0.90–2.36) 1.49 (0.74–3.01) 1.43 (0.87–2.34)
 No Referent Referent Referent Referent
Dyslipidemia
 Yes 1 (0.54–1.86) 1.16 (0.65–2.06) 1.3 (0.66–2.57) 1.31 (0.72–2.36)
 No Referent Referent Referent Referent
Cancer
 Yes No Estimate 2.35 (0.77–7.24) No Estimate 2.13 (0.73–6.16)
 No Referent Referent Referent Referent
Viral load detection
 Yes 1.25 (0.69–2.28) 1.11 (0.66–1.86) 1.01 (0.50–2.02) 1.04 (0.61–1.78)
 No Referent Referent Referent Referent
Clinical history of AIDS
 Yes 1.68 (0.90–3.14) 1.10 (0.62–1.95) 1.35 (0.70–2.58) 1.00 (0.55–1.82)
 No Referent Referent Referent Referent
Aging satisfaction
 Low - - 15.4 (7.33–32.36) a 2.73 (1.70–4.39) a
 Medium - - 2.47 (1.05–5.79) a 1.40 (0.87–2.24)
 High Referent Referent Referent Referent
Open in a new tab

Abbreviation: CI, confidence interval.

a

Statistically significant at P < .05.

Table 5.

Adjusted odds ratios (95% CL) for lower aging satisfaction: HIV positive only

Outcome: aging satisfaction Without age discrepancy Adjusted Odds Ratio (95% CI) With age discrepancy Adjusted Odds Ratio (95% CI)
Medium vs high Low vs high Medium vs high Low vs high
Age
 50–59 years old 0.93 (0.38–2.25) 0.92 (0.35–2.41) 0.87 (0.36–2.11) 0.66 (0.25–1.76)
 60–69 years old 1.03 (0.43–2.45) 1.33 (0.52–3.39) 0.97 (0.41–2.32) 1.04 (0.41–2.66)
 ≥70 years old Referent Referent Referent Referent
Visits
  6 months from baseline 0.87 (0.64–1.20) 0.9 (0.68–1.18) 0.86 (0.62–1.18) 0.86 (0.63–1.16)
  24 months from baseline 0.37 (0.22–0.62) 0.45 (0.28–0.72)a 0.35 (0.21–0.60) a 0.44 (0.27–0.72)
  Baseline Referent Referent Referent Referent
Race
 Black 0.82 (0.52–1.28) 0.54 (0.34–0.88) a 0.8 (0.51–1.26) 0.55 (0.34–0.90) a
 White Referent Referent Referent Referent
Education
 Less than a high school diploma 0.63 (0.43–0.92) 0.95 (0.61–1.48) 0.62 (0.42–0.91) 0.83 (0.53–1.30) a
 Obtained high school diploma Referent Referent Referent Referent
Smoking status
 Current smoker 1.77 (0.99–3.15) 2.03 (1.14–3.60) a 1.71 (0.96–3.07) 2.00 (1.11–3.59) a
 Former smoker 1.64 (1.03–2.59) a 1.27 (0.80–2.02) 1.58 (0.99–2.50) 1.13 (0.70–1.82)
 Never smoker Referent Referent Referent Referent
Depressive symptoms
 Yes 2.97 (1.82–4.87) a 10.04 (6.45–15.62) a 2.91 (1.77–4.79) a 8.85 (5.47–14.32) a
 No Referent Referent Referent Referent
Kidney disease
 Yes 1.15 (0.78–1.68) 1.36 (0.92–2.01) 1.14 (0.78–1.67) 1.27 (0.85–1.91)
 No Referent Referent Referent Referent
Liver disease
 Yes 0.93 (0.07–11.76) 3.12 (0.52–18.76) 1.01 (0.06–17.14) 2.37 (0.13–41.88)
 No Referent Referent Referent Referent
High blood pressure
 Yes 0.83 (0.57–1.21) 0.73 (0.49–1.08) 0.84 (0.57–1.22) 0.75 (0.50–1.14)
 No Referent Referent Referent Referent
Diabetes
 Yes 1.27 (0.76–2.09) 2.03 (1.18–3.51) a 1.22 (0.74–2.03) 1.8 (1.03–3.14) a
 No Referent Referent Referent Referent
Dyslipidemia
 Yes 0.55 (0.35–0.86) 0.55 (0.34–0.87) a 0.54 (0.34–0.86) a 0.51 (0.31–0.83) a
 No Referent Referent Referent Referent
Cancer
 Yes 7.85 (2.08–29.65) a 2.04 (0.45–9.18) 8.47 (2.19–32.70) a 2.45 (0.57–10.59)
 No Referent Referent Referent Referent
Viral load detection
 Yes 1.56 (0.93–2.61) 1.46 (0.87–2.44) 1.56 (0.92–2.65) 1.39 (0.79–2.44)
 No Referent Referent Referent Referent
Clinical history of AIDS
 Yes 1.79 (1.01–3.15) a 2.09 (1.22–3.56) a 1.78 (1.01–3.15) a 1.94 (1.12–3.37) a
 No Referent Referent Referent Referent
Aging discrepancy
 Older - - 2.57 (1.07–6.18) a 15.97 (7.42–34.38) a
 Same - - 1.43 (0.89–2.30) 2.81 (1.74–4.55) a
 Younger Referent Referent Referent Referent
Open in a new tab

Abbreviation: CI, confidence interval.

a

Statistically significant at P < .05.

Discussion

To date, the understanding of what factors contribute to positive or negative self-perceptions of aging among HIV-positive men is limited. This study contributes to the area of self-perceptions of aging among people aging with HIV by examining multiple factors affecting this population. These results demonstrate that both HIV-positive and HIV-negative participants reported younger subjective age (negative age discrepancy) than their chronological age. This finding is similar to the outcomes reported by Kleinspehn-Ammerlahn et al. (2008), who found that subjective age could be influenced by satisfaction with aging and the perception of having good health. Most of the MACS participants are long-term survivors who have been living with HIV for decades, with 27% of the currently active HIV-positive participants having been enrolled in 1984–1987. It is possible that their attitudes toward aging have been influenced by the fact that they have lived much longer than some of their HIV-positive peers. However, our finding is different to the results reported by Fumaz et al. (2012), who found that HIV-positive individuals felt that they are prematurely aging. This difference may be explained by the fact that our participants are older and that dealing with clinical manifestations of aging is less complicated in comparison with the younger (≤ 50 years old) participants in the study by Fumaz et al.

Furthermore, aging satisfaction did not differ between HIV-positive and HIV-negative men. Studies conducted with HIV-negative participants indicate that older people are generally satisfied with their aging (Levy, Slade, Kunkel, & Kasl, 2002; Kleinspehn-Ammerlahn et al., 2008; Rubin & Berntsen, 2006) and this satisfaction is contingent on their attitude toward aging (Kleinspehn-Ammerlahn, Kotter-Grühn, & Smith, 2008; Kotter-Grühn et al., 2009; Mock & Eibach, 2011). Adults aging with HIV have high levels of resilience and personal strengths, which help them overcome the challenges of aging with comorbidities and emotional burdens (Emlet, Tozay, & Raveis, 2010). However, understanding the mechanism about how resilience may contribute to self-perceptions of aging is beyond the scope of this work. Future studies will benefit from the inclusion of sociobehavioral measures including cultural attitudes toward aging, resilience, and perceived age discrimination.

Consistent with other studies, our findings indicate that the presence of depressive symptoms and diabetes is associated with feeling older and lower aging satisfaction (Barker, O’Hanlon, McGee, Hickey, & Conroy, 2007; Fumaz et al., 2012; Westerhof, Barrett, & Steverink, 2003). HIV-positive individuals show greater risk of developing age-related comorbidities and having unhealthy lifestyle behaviors (e.g., sedentary, smoking, alcohol and drug use) (Althoff et al., 2014; Effros et al., 2008; Erlandson et al., 2012). The use of antiretroviral treatment for a long period and the presence of age-related comorbidities may impose a burden on older individuals living with HIV, influencing their self-perceptions of aging. Our results also highlight the negative impact of depressive symptoms in self-perceptions of aging. Older individuals, especially HIV-infected adults, show greater risk of developing depression (Goulet et al., 2007). This finding is important because previous studies have shown that negative self-perceptions of aging are associated with the onset of depressive symptoms (Freeman et al., 2016; Han & Richardson, 2015; Keyes & Westerhof, 2012).

We found racial differences in aging satisfaction, with black men significantly more likely to report higher categories of aging satisfaction relative to white men. Menkin et al. (2017) found that expectations towards older people vary across different racial groups. In addition, these men self-identified as sexual minorities, which also adds social, emotional, and physical challenges. A study conducted with a sample of men who have sex with men showed that social oppression (i.e., the fear of a negative evaluation by his peers due to their personal appearances, and the discrimination towards older people) negatively affect their self-perceptions of aging (Schope, 2005).

We recognize the level of viral load suppression in this sample is lower than one should expect from an HIV treated cohort. However, it is consistent with other analyses. Trajectory analysis of viral load suppression among a sample of MACS participants from the Baltimore site revealed that only 58.1% maintained undetectable viral load from 1996 to 2013, while 29.6% and 12.3% had intermittent and sustained detectable viral load in the same period, respectively. The U.S. Centers for Diseases Control and Prevention (CDC) estimates that in 2015 approximately 59.8% of people with diagnosed HIV-infection in United States were virally suppressed (Centers for Disease Control and Prevention, 2019). We found no statistically significant effect of viral load on age discrepancy and aging satisfaction in the HIV only models (Table 4 and 5). To our knowledge, there is no study relating HIV-specific factors to self-perception of aging (e.g. age discrepancy and aging satisfaction), which make difficult to explain our finding. However, in a study conducted by Fumaz et al. (2012), where participants were younger than 50 years and 80% of the participants had HIV-RNA viral load under 25 copies, found that 37% of the participants felt older than HIV-negative control-aged participants. Lazarus and colleagues (2016) found that the quality of life of people living with HIV, who have achieved viral suppression, is affected by a lot of challenges such as comorbidities, anxiety, depression, financial stress, and polypharmacy. Therefore, it is important that healthcare providers consider the emotional burden associated with the care of the HIV-infection.

Our study has limitations. Our analyses were restricted to HIV-positive and HIV-negative men enrolled in the MACS and the findings may not be generalizable to other populations living with HIV. Despite this limitation, using data from MACS is appropriate to perform this analysis. The study includes a large cohort of multiethnic participants and an appropriate comparison group of HIV-negative men, which makes it possible to study the impact of living with a chronic HIV infection.

Our results indicate that physical health (e.g., comorbidities) and lifestyle factors (e.g., smoking) influence self-perceptions of aging. Age discrepancy and aging satisfaction are components of overall successful aging (Kleinspehn-Ammerlahn et al., 2008); therefore, these results highlight the importance of including behavioral risk measures, as well as disease prevention and management programs, into primary care. Furthermore, primary care providers can increase the odds of positive outcomes and facilitate the engagement in health care, as well as design strategies to improve the quality of life by helping older individuals coping with his aging process.

Acknowledgments

Funding: This work was supported by the NIH via interagency agreement with the National Institute of Allergy and Infectious Diseases, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and other NIH Cooperative Agreements under Grant U01-HD-32632, National Institute on Minority Health and Health Disparities under Grant R01-MD010680 and National Institute of Mental Health under grant 5 F32 MH105293-03.

Footnotes

Declaration of Interest

There are no conflicts of interest to disclose among the authors.

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