Health-related quality of life among women aging with and without HIV in Peru

Diego M Cabrera; Meibin Chen; Mijahil P Cornejo; Yvett Pinedo; Patricia J Garcia; Evelyn Hsieh

doi:10.1371/journal.pone.0269000

. 2022 Jun 9;17(6):e0269000. doi: 10.1371/journal.pone.0269000

Health-related quality of life among women aging with and without HIV in Peru

Diego M Cabrera ^1,², Meibin Chen ¹, Mijahil P Cornejo ³, Yvett Pinedo ⁴, Patricia J Garcia ², Evelyn Hsieh ^1,^*

Editor: Jerome T Galea⁵

PMCID: PMC9182248 PMID: 35679332

Abstract

Background

Studies have shown that women aging with HIV have significantly lower health-related quality of life (HRQoL) compared to women without HIV. However, no studies have examined this issue in Latin America and the Caribbean. We aimed to explore HRQoL measured by the 36-Item Short Form Health Survey (SF-36) among women aging with and without HIV in Peru.

Materials and methods

We conducted a cross-sectional study at a large HIV-clinic in Peru. Outcomes of the SF-36 were evaluated, exploring the relationship between physical activity (International Physical Activity Questionnaire), sociodemographic factors (ethnicity, alcohol/tobacco use, age, BMI) and clinical data (AIDS progression, treatment duration, CD4+ cell count and viral load, years since HIV diagnosis) with HRQoL using regression analysis. Statistical significance was set with a two-tailed p-value <0.05.

Results

We enrolled 427 women (175 HIV-infected) with mean age of 54±8 years. From the SF-36 individual domains: physical functioning, role limitations due to physical and emotional health, and emotional wellbeing were significantly lower for HIV-infected women. Summary component scores were lower for the HIV-subset for both physical (45.8 vs 47.3) and mental (45.1 vs 45.8) components, although they did not achieve statistical significance. Regression analysis of the HIV-infected women revealed that the physical component score was significantly associated with physical activity, ethnicity, and chronic comorbidities while the mental component was significantly associated with physical activity, employment, and CD4+ cell count.

Conclusion

In our study, HIV-infected women scored lower in both physical and mental component scores. Important determinants for each component included CD4+ cell count as an assessment of HIV severity for the mental component, and ethnicity, reflecting socio-cultural factors, for the physical component. These results reveal the importance of a holistic approach to addressing HRQoL in this population. Better understanding of these factors will help shape future policies and interventions to improve HRQoL of women aging with HIV.

Background

In the past two decades, the introduction of antiretroviral therapy (ART) has changed HIV from a fatal disease to a chronic condition that can be managed with long-standing medication. However, people living with HIV (PLWH) remain at increased risk for developing chronic conditions associated with aging, such as neurocognitive impairment, cardiovascular disease, as well as decreased physical functioning [1]. Reflecting this, PLWH continue to have significantly lower health-related quality of life (HRQoL) than the general population [2]. Data suggest that in addition to the burden of living with chronic infection, PLWH are more likely to be adversely affected by changes in their environment and in their social background [3].

Compared to general quality of life, HRQoL is more stringently defined as the way health is estimated to affect an individual’s quality of life, or the way an individual perceives their own well-being with regards to physical, mental and social domains of health [4]. Measures of HRQoL in individuals living with chronic conditions such as HIV allows for the evaluation of the efficacy of certain medications as well as for exploring the influence of HIV and associated comorbidities [2, 5]. The 36-Item Short Form Health Survey (SF-36) is a widely used, validated instrument for HRQoL evaluation [6]. This tool has proved to be useful in estimating the burden of different conditions on HRQoL among many populations [7]. The use of the SF-36, among other instruments, to evaluate HRQoL in HIV-infected populations has been reported in upper-income settings [8–10] and a few other Latin American countries [4, 6, 11], but not in Peru.

Women represent an estimated 31% of adults living with HIV in Latin America. Their vulnerability to HIV is related to many diverse influences, such as social, economic and policy-related factors [12]. Throughout the world, the unequal social status of women places them at higher risk for contracting HIV with reported barriers to access for prevention and treatment programs [13]. Furthermore, they may experience more HIV-related stigma compared with men due to their generally devalued status and the patriarchal power dynamics evidenced in certain cultures, which is highly prevalent in Latin America [14]. It is not uncommon in Peru for women to be expected to maintain culturally defined moral traditions and to adhere to conservative gender roles that are not conducive to open conversations related to sexuality. Valencia-Garcia et al. described that Peruvian women are often perceived to be the unfaithful partner when diagnosed with HIV, and thus experience stigma within society [15]. In Peru, as of 2018 there were at least 18,000 women living with HIV, representing 23% of all PLWH. Among them, 78% have received treatment [16] through the Peruvian National HIV Program since 2004 [17]. Most studies and interventions for women with HIV in Latin America have focused on reproductive and sexual health of pregnant women and sex workers [12] but have rarely focused on longer-term physical and mental health needs of middle-aged and older women living with HIV.

We therefore designed a study to examine health-related quality of life, as measured by the SF-36 among a group of middle-aged and older women with HIV compared with a group of women without HIV in Lima, Peru. We evaluated factors associated with HRQoL outcomes in both groups, including physical activity using the International Physical Activity Questionnaire (IPAQ), another well-validated tool, and hypothesized that HIV status may be an important predictor for physical and mental health of this population.

Materials and methods

Study design and participants

We conducted a hospital-based observational cross-sectional study. Participants were recruited at the HIV-clinic of Hospital Nacional Arzobispo Loayza (HNAL), a large public hospital in Lima, Peru for a study regarding musculoskeletal health between October 2019 and March 2020. We consecutively invited HIV-positive women aged ≥40 years who presented for routine care visits at HNAL during the study period, and concurrently recruited a control group of HIV-uninfected women aged ≥40 years. We used two strategies to recruit women in the control group, including inviting community-dwelling women from surrounding neighborhoods as well as advertising the study among hospital staff (nurses, office administrators assistants and technicians). Exclusion criteria for both groups included primary residency outside of Lima, pregnancy, history of or treatment for osteoporosis, and illiteracy.

Measures and data collection

At the time of enrollment, all participants completed a 15-minute self-administered questionnaire that included sociodemographic characteristics, the SF-36, and the IPAQ. Both tools were piloted among 10 patients and 10 clinic staff before recruitment began to confirm that questions were easily understandable and culturally appropriate. The questionnaire was administered to all patients by a single study staff member (D.M.C.) to avoid misinterpretation of the questions and to resolve any uncertainties. HIV-related data were obtained from clinical records, and viral suppression was defined as a current viral load count ≤50 copies.

Sociodemographic and clinical characteristics

Background information was obtained regarding: personal characteristics including age, self-reported ethnicity (White, Mestizo [mixed ethno-racial ancestry] and other [Black, Andean, Nikkei]), educational status (less than high school vs. high school and beyond), occupation (employed vs unemployed), marital status (single/divorced/separated/ widowed vs married/cohabitant), smoking history (ever vs never), current alcohol status (yes vs no); HIV-related factors such as nadir and current CD4+ cell count, nadir and current viral load, time since diagnosis, ART duration, history of AIDS diagnosis (yes vs no, with AIDS status defined by CD4+ cell count less than 200 cell/m³); and other clinical characteristics such as body mass index (BMI), hip and waist circumference, menopausal status, and other chronic comorbidities (hypertension, type 2 diabetes, cardiovascular disease, chronic renal disease, mental health illness, chronic respiratory disease, others).

Measure of physical activity (IPAQ)

The IPAQ was created as an instrument for cross-national assessment of physical activity and for standardization of measures of health-related physical activity behaviors across different sociocultural contexts [18]. We used the short (7-item) version that has been validated in multiple languages, including Spanish, in a study measuring the relation and differences between moderate-to-vigorous physical activity obtained by the IPAQ on two occasions, finding significantly correlated measures (r = 0.55, p<0.01) [19]. The IPAQ uses seven questions to explore the amount of time spent on vigorous-intensity activity, moderate-intense activity, walking and sitting during the past seven days. Answers collected for each category were weighted to calculate a total weekly metabolic equivalent of task (MET) score in minutes to obtain the total energy cost of the population’s activity on those seven days [20]. Categorical labels of low, moderate, and high levels of physical activity were assigned according to official scoring guidelines from the IPAQ [21]. We used the IPAQ as an additive to further explore physical activity assessment within the spectrum of the physical component of the SF-36.

SF-36

The SF-36 is a widely adopted tool used in clinical research to measure HRQoL that has been validated in many languages including Spanish, in a study within 2,144 subjects from Chile with a high internal consistency scale (Cronbach’s alpha 0.86–8.87), [22–24]. This questionnaire was developed as a product of the Medical Outcomes Study (MOS) [17] and yields eight domains of evaluation: physical functioning, role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, emotional well-being, social functioning, pain, and general health. Domain scores were calculated according to the RAND Corporation [25] “RAND 36-item Health Survey 1.0”, which transforms scores to a scale of 0–100 in which higher scores indicate a “better” HRQoL [10]. These domains were further aggregated into two summary measures: the Physical Component Summary score (physical component) and the Mental Component Summary score (mental component). To calculate summary scores, SF-36 domain scores were first standardized using a z-score transformation using population norms and metrics for Peruvian women. Each SF-36 domain score was multiplied by the appropriate orthogonal factor scoring coefficient from United States (US) normative data. Resulting scores underwent a t-score transformation to have a mean of 50 and a standard deviation of 10 as is the US norm for international comparison [24, 26]. Individual domain scores were not transformed.

Data analysis

Descriptive statistics, means, and standard deviations were used for reporting continuous variables, and frequencies and percentages for categorical variables. Parametric tests were used for normally distributed data and nonparametric tests were used for non-normally distributed data. Comparisons between HIV-infected and uninfected women were performed with independent two-tailed t-tests and Mann-Whitney tests for continuous variables as appropriate, and chi-square analysis for categorical variables. Further association between variables and physical activity and HRQoL was assessed using one-way analysis of variance, the Kruskal-Wallis Test, and regression analysis as appropriate. A p-value <0.05 was considered statistically significant.

Sociodemographic and clinical characteristics, along with physical activity scores, were used to fit a multivariable linear regression model with SF-36 component scores as the primary outcome of interest within HIV-infected and noninfected women, separately. Physical activity categorical variables were dichotomized into low activity level and moderate/high activity level. Variables with a p-value <0.25 in the univariate analysis were entered into the multivariable linear regression model and non-significant variables were removed one at a time beginning with the least significant. All variables with a p<0.1 were retained in the model. Age was retained regardless of significance. All statistical analysis was performed using R 3.6.3 and RStudio 1.3.959 with additional packages [27, 28].

Ethics

This study was reviewed and approved by the institutional review boards of Yale School of Medicine, Universidad Peruana Cayetano Heredia and HNAL. All willing participants provided written informed consent after a comprehensive explanation of the study procedures.

Results

Sociodemographic and clinical characteristics

A total of 427 Peruvian women were enrolled in this study, with 175 HIV-infected and 225 uninfected participants. The patients had a mean age of 54±8 (range 40–82) years with postmenopausal women representing 77% of the entire study population (Table 1). HIV-infected women tended to be single/divorced (p<0.001), with incomplete high school (p<0.001), unemployed (p<0.001), and with lower BMI (p<0.01), waist, and hip circumference (p<0.01). Only a minority of the women smoked or consumed alcohol in both groups and these behaviors were not significantly different between groups. IPAQ measurements, which include sedentary scores, total MET scores, and categorical scores, did not vary significantly depending on HIV status. Close to 60% of both groups, however, had a low physical activity categorical score (Table 2).

Table 1. Sociodemographic and clinical characteristics by HIV status.

Characteristics	HIV Status
Characteristics	HIV-infected (N = 175)	Uninfected (N = 252)
Sociodemographic and Behavioral Characteristics
Age Mean ± SD	51.32 ± 8.13	56.09 ± 8.861 ^***
Ethnicity N (%)
White	7 (4)	26 (10) ^**
Mestizo	162 (93)	222 (88)
Other	6 (3)	4 (2)
Marital Status N (%)
Single/divorced/separated/widowed	117 (67)	117 (46) ^***
Married/cohabitant	58 (33)	135 (54)
Education Level N (%)
Incomplete High School	54 (31)	38 (15) ^***
Completed High School	121 (69)	214 (85)
Occupation status N(%)
Employed	4 (2)	80 (32) ^***
Unemployed	171 (98)	172 (68)
Clinical Characteristics
Body mass index Mean ± SD	26.47 ± 5.10	27.55 ± 4.022 ^**
Height Mean ± SD	154.23 ± 6.08	154.07 ± 6.14
Weight Mean ± SD	62.98 ± 12.76	65.43 ± 10.542 ^**
Hip Circumference Mean ± SD	96.41 ± 11.28	100.29 ± 10.791 ^**
Waist Circumference Mean ± SD	88.78 ± 11.04	92.39 ± 10.631 ^**
Smoking, ever N(%)	49 (28)	50 (20)
Current alcohol use N (%)	45 (26)	66 (26)
Menopausal N (%)	123 (70)	206 (82) ^**
Diagnosis of other chronic comorbidity N (%)	47 (26)	118 (46)
HIV-Related Characteristics
Current CD4+ Cell Count Median (IQR)	592 (403–796)	–
Current Viral Load Median (IQR)	0 (0–40)	–
ART-Naive HIV viral load Median (IQR)	24081 (399–184000)	–
ART-Naive CD4+Cell Count Median (IQR)	240 (101–395)	–
Years since HIV diagnosis Median (IQR)	12 (7–15)	–
ART Duration in years Median (IRQ)	10 (6–14)	–
AIDS progression N (%)	14 (8)	–
Viral suppression N (%)	141 (80.6)
Physical Activity (IPAQ)
Sedentary Score Mean ± SD	180.77 ± 117.95	192.06 ± 151.01
Total MET Score Mean ± SD	795.51 ± 1379.60	844.69 ± 1207.54
Categorical Scores N (%)
Low	103 (59)	147 (58)
Moderate	61 (35)	83 (33)
High	11 (6)	22 (9)

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SD: standard deviation; ART: antiretroviral treatment; IPAQ: International Physical Activity Questionnaire; MET: Metabolic Equivalent of Task; IQR: Interquartile range; CD4+ cell count measured in cell/mm³; viral load measured in number of copies/mL; AIDS progression: CD4+ cell count <200 cell/mm³; Viral suppression: viral load ≤50 copies/mL

* p < 0.05

** p < 0.01

*** p < 0.001

Table 2. SF-36 outcomes by HIV status.

	HIV status
Characteristics	HIV-infected (N = 175)	Uninfected (N = 252)
	HIV-infected (N = 175)	Uninfected (N = 252)
SF-36 domains, Mean ± SD
Physical Functioning	82.37 ± 15.64	86.71 ± 11.92 ^*
Role Limit Physical	59.00 ± 35.37	66.47 ± 32.75 ^*
Bodily Pain	77.01 ± 12.95	75.90 ± 12.69
General Health	48.60 ± 11.33	50.50 ± 11.62
Energy/Fatigue	48.97 ± 10.70	50.46 ± 12.71
Social Functioning	74.64 ± 12.67	76.64 ± 14.08
Role Limit Emotional	86.29 ± 26.55	92.33 ± 22.33 ^**
Emotional Wellbeing	58.19 ± 10.36	59.54 ± 12.18 ^*
Physical Component Score	45.85 ± 8.000	47.29 ± 6.73
Mental Component Score	45.13 ± 6.14	45.81 ± 6.46

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SF-36: 36-Item Short Form Survey

SF-36 domains were scored from 0–100

PCS and MCS were scored from 0–100 and scaled to a mean of 50 and standard deviation of 10

* p < 0.05

** p < 0.01

*** p < 0.001

SF-36 domains and component scores

Average physical and mental components were lower than the US population norm [26] with transformed physical component average scores at 45.9±8, and mental component average scores at 45.1±6.1 for the HIV-infected women (Table 2). These aggregate scores did not vary significantly depending on HIV status, although the physical component had a p-value of 0.053. For individual SF-36 domains, participant scores were on average highest for “physical functioning,” “role limitation due to emotional health,” and “pain,” and on average lowest for “general health” and “energy/fatigue.” Four of the domains: “physical functioning,” “role limitations due to physical health,” “role limitations due to emotional health,” and “emotional wellbeing” were significantly higher for the uninfected compared to the HIV-infected subset.

SF-36 component summary scores in uninfected women

Unadjusted analysis for the physical component revealed that age, BMI, and postmenopausal status were associated with lower physical scores, and current alcohol use and higher education were independently associated with higher physical scores (Table 3). These factors were added to the multivariable regression model, where older age and higher BMI were found to be associated with lower physical scores. Current alcohol use was positively associated with the physical component. For the mental component, in unadjusted analysis, smoking trended toward significance (p = 0.059) for being negatively associated with the mental component. No other covariant were found to be significantly associated with mental scores in both unadjusted and adjusted analysis (Table 4).

Table 3. Unadjusted regression of factors related to SF-36 component scores.

Independent Variables	Physical Component Score				Mental Component Score
	Uninfected women		HIV-infected women		Uninfected women		HIV-Infected women
	β	95% CI	β	95% CI	β	95% CI	β	95% CI
Sociodemographic, Behavioral Characteristics
Ethnicity
white	Ref	-	Ref	-	Ref	-	Ref	-
mestizo	1.2027	-1.547 to 3.953	-8.4608	-14.459 to -2.463 ^**	0.5370	-2.101 to 3.175	2.0501	-2.611 to 6.712
other	3.8383	-3.287 to 10.964	-7.8581	-16.502 to 0.786	-3.8900	-10.725 to 2.944	-2.1098	-8.828 to 4.608
Marital Status
single/alone	Ref	-	Ref	-	Ref	-	Ref	-
couple	-0.0870	-1.764 to 1.590	-1.8393	-4.367 to 0.689	-0.0342	-1.645 to 1.576	0.9999	-0.946 to 2.946
Education
incomplete high school	Ref	-	Ref	-	Ref	-	Ref	-
complete high school	2.3810	0.062 to 4.699 ^*	1.8828	-0.694 to 4.459	0.6485	-1.594 to 2.891	0.7406	-1.246 to 2.727
Occupation
unemployed	Ref	-	Ref	-	Ref	-	Ref	-
employed	-0.9410	-2.734 to 0.852	-7.0368	-14.977 to 0.904	-0.6846	-2.408 to 1.039	6.4317	0.360 to 12.504 ^*
Current alcohol use
no	Ref	-	Ref	-	Ref	-	Ref	-
yes	2.6063	0.732 to 4.481 ^**	3.0271	0.326 to 5.728 ^*	-0.3254	-2.152 to 1.501	-1.0053	-3.102 to 1.092
Smoking, ever
no	Ref	-	Ref	-	Ref	-	Ref	-
yes	1.9562	-0.127 to 4.039	0.8200	-1.843 to 3.483	-1.9297	-3.929 to 0.070	-0.3759	-2.422 to 1.670
Clinical Characteristics
Age	-0.1956	-0.287 to -0.104 ^***	-0.1367	-0.283 to 0.010	0.0765	-0.014 to 0.167	0.0524	-0.061 to 0.166
BMI	-0.3158	-0.521 to -0.111 ^**	-0.0961	-0.331 to 0.139	0.0482	-0.152 to 0.248	0.0060	-0.175 to 0.187
Hip Circumference	-0.0547	-0.132 to 0.023	0.0190	-0.087 to 0.125	-0.0027	-0.077 to 0.072	-0.0167	-0.098 to 0.065
Waist Circumference	-0.0733	-0.152 to 0.005	0.0051	-0.104 to 0.114	0.0048	-0.071 to 0.081	-0.0231	-0.107 to 0.060
Menopausal
no	Ref	-	Ref	-	Ref	-	Ref	-
yes	-3.4560	-5.578 to -1.333 ^**	-1.5487	-4.158 to 1.061	1.4743	-0.597 to 3.545	1.1972	-0.805 to 3.200
Other Chronic Comorbidities
no	Ref	-	Ref	-	Ref	-	Ref	-
yes	-1.4257	-3.094 to 0.243	-4.0818	-6.732 to -1.432 ^**	-0.5536	-2.163 to 1.056	0.6850	-1.400 to 2.770
HIV Clinical Characteristics
AIDS progression
no	-	-	Ref	-	-	-	Ref	-
yes	-	-	-3.0460	-7.435 to 1.343	-	-	-2.1652	-5.537 to 1.206
Current CD4+ Cell Count	-	-	0.0019	-0.002 to 0.006	-	-	0.0034	0.0002 to 0.007 ^*
Naive HIV Viral load	-	-	3.23E-6	6.58E-6 to 1.08E-7	-	-	4.64E-7	3.06E-6 to 2.13E-6
Naive CD4+ Cell Count	-	-	0.0004	-0.006 to 0.007	-	-	-0.0043	-0.009 to 0.0003
Years since HIV diagnosis	-	-	0.1694	-0.033 to 0.372	-	-	-0.0390	-0.195 to 0.117
ART Duration (Years)	-	-	0.1076	-0.132 to 0.347	-	-	0.0795	-0.104 to 0.263
Physical Activity ^a
Sedentary Score	0.0036	-0.002 to 0.010	-0.0079	-0.018 to 0.002	-0.0027	-0.008 to 0.003	-0.0004	-0.008 to 0.007
Total MET Score	-8.76E-05	-0.00078 to 0.0006	0.0001	-0.001 to 0.001	-2.54E-05	-0.0007 to 0.0006	0.0002	-0.0004 to 0.001
Categorical Score
low	Ref	-	Ref	-	Ref	-	Ref	-
moderate or high	1.3777	-0.310 to 3.066	3.1382	0.752 to 5.525 ^**	-0.4193	-2.048 to 1.209	-2.1451	-3.984 to -0.306 ^*

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^aMeasured by the International Physical Activity Questionnaire (IPAQ); PCS, physical component score; MCS, mental component score; BMI, body mass index; ART, antiretroviral therapy; CI, confidence intervals

* p < 0.05

** p < 0.01

*** p < 0.001

Table 4. Adjusted multiple linear regression of factors related to SF-36 component scores.

Independent Variables	Physical Component Score				Mental Component Score
	Uninfected women		HIV-infected women		Uninfected women		HIV-Infected women
	β	95% CI	β	95% CI	β	95% CI	β	95% CI
Intercept	65.95	58.33 to 73.57^***	65.34	53.354 to 77.320^***	41.81	36.702 to 46.922^***	37.3028	2.905 to 45.558^***
Sociodemographic, Behavioral Characteristics
Ethnicity—White	-	-	Ref	-	-	-	Ref	-
Ethnicity—Mestizo	-	-	-8.8753	-14.598 to -3.153 ^**	-	-	-	-
Ethnicity—Other	-	-	-8.1751	-16.429 to 0.079	-	-	-	-
Employed	-	-	-6.6103	-14.149 to 0.928	-	-	6.8997	0.923 to 12.876 ^*
Smoking, ever	-	-			-1.9617	-3.954 to 0.030
Current Alcohol Use	2.4049	0.594 to 4.216 ^***	-	-	-	-	-	-
Clinical Characteristics
Age	-0.1864	-0.276 to -0.097 ^***	-0.0911	-0.235 to 0.053	0.0781	-0.012 to 0.170	0.0009	-0.113 to 0.115
BMI	-0.3522	-0.548 to -0.157 ^***	-	-	-	-	-	-
Presence of another comorbidity	-	-	-3.7413	-6.297 to -1.186 ^**	-	-	-	-
HIV Clinical Characteristics
Current CD4+ Count	-	-	-	-	-	-	0.0031	0.0001 to 0.006 ^*
Physical Activity ^a
Sedentary Score	0.0045	-0.001 to 0.010			-	-
Categorical Score—Low	-	-	Ref	-	-	-	Ref	-
Categorical Score—Moderate or High	-	-	2.7540	0.394 to 5.115 ^**	-	-	-2.0919	-3.959 to -0.225 ^*
R² value	0.124		0.124		0.018		0.057

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* p < 0.05

** p < 0.01

*** p < 0.001

SF-36 component summary scores in HIV-infected women

When we focused on the group of women with HIV, unadjusted analysis revealed that presence of other comorbidities, mestizo ethnicity, and current alcohol use, were independently associated with a lower physical component and moderate/high physical activity with a higher one (Table 3). These factors, as well as age, menopause status, marital status, education level, occupation, AIDS status, naïve HIV viral load, and years since HIV-diagnosis, were added into a multivariable linear regression analysis. In this model, moderate/high physical activity level was associated with a higher physical component while mestizo ethnicity and presence of chronic comorbidities were associated with a lower physical component. In the unadjusted analysis of the mental component: employment, current CD4+ cell count, and moderate/high physical activity were all independently associated with higher mental component scores. These factors, as well as AIDS status, menopause status, age, and height, were added into a multivariable regression model, which revealed that employment and CD4+ cell count was associated with a higher mental component, while moderate/high physical activity was associated with a lower one.

Discussion

Our study is the first to explore HRQoL among middle-aged and older women with and without HIV using the well-validated SF-36 questionnaire in Peru. While only four out of the eight SF-36 scores were significantly different between the HIV-infected population and the control group, these domains spanned both physical and mental components of HRQoL as defined by the SF-36. HIV-infected women scored lower for both physical and mental components. In addition, multivariable regression adjusting for various factors including age, BMI, and other sociodemographic factors of the HIV-infected subset illustrated that physical activity levels are also correlated with both physical and mental components.

In the overall sample, results for the SF-36 domains were generally consistent in terms of domain scoring with prior studies conducted using the SF-36 in other Latin American individuals, including a general population study among 4,344 participants in Peru, a validation study on 2,143 older (60–92 years) community-dwelling people in Chile, and a study among 118 HIV-infected individuals in Venezuela [22, 24, 29], all of which were cross-sectional, multicenter studies, but not limited to just women. Aside from two domains, the relationships identified between domains scores within our study were also observed in those Latin American studies. For example, domain scores like “physical functioning” and “social functioning” were all relatively high, while “general health” and “energy/fatigue” were relatively low compared to other scores, a pattern that was consistent across all studies. The two domains that differed in our study compared to the others were “role limitations due to physical health” and “role limitations due to emotional health.” Both included a total of seven items (three for the former and four from the latter) that explored functional limitation of work-related and daily activities because of physical and emotional problems, respectively. “Role limitations due to physical health” domain scores were lower and “role limitations due to emotional health” scores were higher than what was observed in the aforementioned reports. For physical health role limitations, these lower scores may be likely due to our specific focus on aging women, of which one-third were HIV-positive. For emotional health role limitations, the higher scores among women with HIV may reflect their engagement in longitudinal care at the HIV clinic and resultant regular access and communication with a healthcare team. It will be important however to clearly assess these potential relationships in future longitudinal studies among women with HIV from this region. Finally, compared to the population of a Brazilian monocentric study of 1,057 older woman (mean age 67.1 years) using the SF-36 among women with and without fractures and obesity [30], both HIV-infected and uninfected women from our sample scored lower in both the physical and mental component scores compared to the control group (non-obese without fracture) from that study. This population also followed the pattern of "physical functioning" and "social functioning" being relatively high and "general health" and "energy fatigue" being relatively low compared to the other scores.

Compared to other studies examining HRQoL between individuals with and without HIV using the SF-36, our results were similarly mixed. In our study, scores for four out of the eight domains (physical functioning, role limitations due to physical health, role limitations due to emotional health, emotional wellbeing) were significantly lower for the HIV-infected group than the control. While the general consensus is that PLWH have lower HRQoL scores across all domains [31–33], individual studies have found this to not be the case universally. For example, a study in Japan found “physical functioning” and “bodily pain” scores to be higher in PLWH [34], which represent a better HRQoL in those domains, and a study in the US found “emotional wellbeing” to be unaffected by HIV status [35]. As none of the aforementioned studies were conducted in Latin America nor specifically focused on women, possible variations in HIV treatment and socio-cultural nuances likely influenced the outcomes.

When controlling for other factors through regression analysis, age and BMI were independent predictors of a lower physical component among the uninfected women, which have been noted previously across many studies using the SF-36 [4, 34, 36]. However, for the HIV-infected subset, other factors such as mestizo ethnicity and presence of other comorbidities were independently associated with lower physical scores. These results suggest that despite progress made in the treatment for HIV, for aging Peruvian women, HIV continues to negatively impact the physical aspect of their quality of life and exacerbate other factors like ethnicity and illness. Ethnicity in particular is relevant because of the close association of socioeconomic stratification with racial hierarchies in Peru, of which the most disadvantaged are the indigenous, followed by mestizo ethnic groups [37].

For the mental component model, no factors measured were significant contributors for the uninfected women physical and mental outcomes. However, for the HIV-infected women, employment and higher CD4+ cell count were both significantly associated with a higher mental score. Other studies have reported depression, psychoactive drug usage, and social support as being among the variables correlated with the mental component [4, 34, 36]. As we did not measure these in our study, it is possible that these factors may also contribute to the mental component of aging Peruvian women, and we should not exclude them in future evaluations of HRQoL. It is well known that in general, PLWH can face stigma, prejudice, and discrimination [34, 38]. Thus, it is both expected and commonly observed that HIV diagnosis significantly influences this component. However, even though mental scores were slightly lower for the HIV-infected women compared to the uninfected, the difference was not statistically significant. Factors such as social support have been shown to be positively correlated with the mental component and factors such as stigma have been shown to be negatively correlated with this component [39]. For example, a Colombian cross-sectional study among 286 PLWH found a direct relationship between the emotional well-being dimension of the SF-36 and social support systems assessed by the Duke-UNC-11 questionnaire [39]. The fact that mental component scores were similar between the groups suggests that this sample of middle-aged and older Peruvian women with HIV may not encounter as much stigma or may have the support that they need to overcome the negative mental health consequences identified among other populations with HIV. However, as this was just one single-center, cross-sectional study, further investigations in this population are needed to confirm this finding.

Given our focus on women aging with HIV, we conducted additional regression models specifically for the HIV-infected subset to evaluate associations with HIV-related clinical characteristics. The presence of comorbidities contributing negatively to the physical component, and employment and current CD4 count contributing positively to the mental component is both expected and confirmed through other studies [35, 36, 40, 41]. Moderate-to-high physical activity contributed positively to the physical component, but also contributed negatively to the mental component, which reflects the mixed reports of other studies. While many reports describe the positive influence of physical activity on HRQoL [42–45], we also found studies that have observed the opposite [46]. A 2019 study in the US using a supervised exercise intervention on 32 PLWH and 37 controls recruited by invitation from an HIV-clinic and referrals from participants, respectively, failed to improve HRQoL measures and depressive symptoms in older PLWH, which suggested this could be related to assignment versus self-selection of the intervention, a greater burden of mental illness in their group, and a longer duration of study. It is important to note that these findings should be interpreted with caution due to the acknowledged limitations of a small sample size and large standard deviations [47]. Another study of 99 Canadian PWLH on psychological and behavioral variables in HRQoL also acknowledged the varied effectiveness of physical activity on HRQoL and attributed it to unequal matching between physical activity intensity and patient tolerance [36]. One possibility for our population is that physical activity levels are comprised of not only intentional exercise, but also unintentional physical activity such as manual labor. Physical health may be positively influenced by both types of physical activity, but mental health may be negatively affected by undesired physical activity.

Our study has some limitations. First, our findings cannot necessarily be extrapolated to represent HIV-infected women outside of the study sample, given it is a single-center study. However, we selected our study site because it is one of the largest public HIV clinics in the capital city of Peru, with a diverse patient population. However, as this study aimed to explore health-related perceptions, it required direct input from the population of interest. Second, we recruited both HIV-infected and uninfected women by convenience sampling because of feasibility reasons, this could potentially add some selection bias that should be taken into consideration. Finally, as this was a cross-sectional study, we were not able to infer causality within the relationships addressed. We hope, however, that it serves as a starting point for future longitudinal research on this subject, especially as it is the first study in Peru that used the SF-36 to measure HRQoL in women and HIV populations.

The SF-36 is a widely adopted tool that has been validated in different languages to measure HRQoL. With psychometric data supporting its usage in many disease areas, SF-36 has been the most frequently used generic HRQoL survey for PLWH, resulting in refined scoring protocols, numerous validation studies across different populations, and ample literature for clarification and comparison in this particular population [2, 9, 48, 49]. In low- and middle-income countries such as Peru, information regarding the performance of self-reported health surveys is important because these measures are comprehensive, practical and inexpensive, making them valuable for health intervention evaluations [19], particularly in the setting of HIV in Latin America, where there is an important pending agenda to address gaps in information regarding long-term care of PLWH [12]. More specifically, it is important to address aspects that are intrinsic to the patient-perspective, which HRQoL measures can help elucidate. Using findings from HRQoL studies can thus allow for better implementation on the individual and communitarian level.

As the number of HIV-infected women on ART continues to increase in Latin America, it is important to acknowledge that improvements in life expectancy because of ART have also led to new challenges in terms of the physical and mental burdens associated with life-long infection and HIV treatment. In summary, although overall physical and mental component scores were similar between the two groups, we found that HIV-infected women scored lower in specific domains within physical and mental health compared to uninfected women, consistent with our hypothesis that HIV status may be negatively associated with HRQoL among Peruvian women. In addition, while physical activity affected both physical and mental status in the HIV-infected subset, it did so in opposite ways. Directions for future studies could include how social support and HIV stigma affect HRQoL in women with HIV in Peru, and further elucidation of the relationship between physical activity and HRQoL in PLWH to determine how different types of physical activity, such as duration, frequency, and purpose, may affect SF-36 component scores. Moreover, our study also identified certain areas in which women with HIV in Peru appear to be thriving relative to reports from the literature, which illuminates opportunities for future research that examines resiliency factors that could ultimately benefit other patients with HIV. This study is the first that we know of to provide insights into HRQoL outcomes among HIV-infected and uninfected women in Peru. Better understanding of the influence of sociodemographic, behavioral, clinical, and activity characteristics of this population on HRQoL will help guide future interventions, policies, and practices that could improve HRQoL of women aging with HIV in Peru.

List of abbreviations

HRQoL: Health-related quality of Life
SF-36: 36-Item Short Form Health Survey
IPAQ: International Physical Activity Questionnaire
PLWH: People living with HIV
ART: Antiretroviral treatment
HNAL: Hospital Nacional Arzobispo Loayza
MET: Metabolic Equivalent of Task
MOS: Medical Outcomes Study

Data Availability

All datasets are available from the Open Science Framework public repository (https://osf.io/hfg64/).

Funding Statement

DMC serves as a Fogarty Global Health Trainee and is supported by the Fogarty International Center (FIC, URL: https://www.fic.nih.gov/) at the National Institutes of Health (NIH) and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) under grant number D43TW010540. EH is supported by FIC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Crane HM, Miller ME, Pierce J, Willig AL, Case ML, Wilkin AM, et al. Physical Functioning Among Patients Aging With Human Immunodeficiency Virus (HIV) Versus HIV Uninfected: Feasibility of Using the Short Physical Performance Battery in Clinical Care of People Living With HIV Aged 50 or Older. Open Forum Infect Dis. 2019;6. doi: 10.1093/ofid/ofz038 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Cooper V, Clatworthy J, Harding R, Whetham J, Emerge Consortium. Measuring quality of life among people living with HIV: a systematic review of reviews. Health Qual Life Outcomes. 2017;15: 220. doi: 10.1186/s12955-017-0778-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Drewes J, Gusy B, Rüden U von. More than 20 years of research into the quality of life of people with HIV and AIDS—a descriptive review of study characteristics and methodological approaches of published empirical studies. J Int Assoc Provid AIDS Care. 2013;12: 18–22. doi: 10.1177/1545109712456429 [DOI] [PubMed] [Google Scholar]
4.Dutra BS, Lédo AP, Lins-Kusterer L, Luz E, Prieto IR, Brites C. Changes health-related quality of life in HIV-infected patients following initiation of antiretroviral therapy: a longitudinal study. Braz J Infect Dis. 2019;23: 211–217. doi: 10.1016/j.bjid.2019.06.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Bozzette SA, Hays RD, Berry SH, Kanouse DE. A Perceived Health Index for use in persons with advanced HIV disease: derivation, reliability, and validity. Med Care. 1994;32: 716–731. doi: 10.1097/00005650-199407000-00005 [DOI] [PubMed] [Google Scholar]
6.Lins-Kusterer L, Valdelamar J, Aguiar CVN, Menezes MS, Netto EM, Brites C. Validity and reliability of the 36-Item Short Form Health Survey questionnaire version 2 among people living with HIV in Brazil. The Brazilian Journal of Infectious Diseases. 2019;23: 313–321. doi: 10.1016/j.bjid.2019.08.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Ware JE, Gandek B. Overview of the SF-36 Health Survey and the International Quality of Life Assessment (IQOLA) Project. Journal of Clinical Epidemiology. 1998;51: 903–912. doi: 10.1016/s0895-4356(98)00081-x [DOI] [PubMed] [Google Scholar]
8.Wu AW, Hanson KA, Harding G, Haider S, Tawadrous M, Khachatryan A, et al. Responsiveness of the MOS-HIV and EQ-5D in HIV-infected adults receiving antiretroviral therapies. Health Qual Life Outcomes. 2013;11: 42. doi: 10.1186/1477-7525-11-42 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Clayson DJ, Wild DJ, Quarterman P, Duprat-Lomon I, Kubin M, Coons SJ. A comparative review of health-related quality-of-life measures for use in HIV/AIDS clinical trials. Pharmacoeconomics. 2006;24: 751–765. doi: 10.2165/00019053-200624080-00003 [DOI] [PubMed] [Google Scholar]
10.Meng Y-J, Li N-X, Liu C-J, Chen J-H, Song Y-C, Qian Z-S. Quality of life and hostile mentality trend of patients with HIV/AIDS in China. Public Health. 2008;122: 404–411. doi: 10.1016/j.puhe.2007.06.007 [DOI] [PubMed] [Google Scholar]
11.Valdelamar-Jimenez J, Lins-Kusterer L, de Jesus STG, Netto EM, Brites C. Comparison of Three Health-Related Quality of Life Instruments to Evaluate Symptoms of Depression in HIV Patients in Brazil. Journal of Clinical Psychology in Medical Settings. 2019;27: 27. doi: 10.1007/s10880-019-09657-9 [DOI] [PubMed] [Google Scholar]
12.García PJ, Bayer A, Cárcamo CP. The Changing Face of HIV in Latin America and the Caribbean. Curr HIV/AIDS Rep. 2014;11: 146–157. doi: 10.1007/s11904-014-0204-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.UNAIDS. Peru. [cited 6 May 2020]. Available: https://www.unaids.org/en/regionscountries/countries/peru
14.Valencia-Garcia D, Rao D, Strick L, Simoni JM. Women’s experiences with HIV-related stigma from healthcare providers in Lima, Peru: “I would rather die than go back for care.” Health Care Women Int. 2017;38: 144–158. doi: 10.1080/07399332.2016.1217863 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Valencia-Garcia D, Starks H, Strick L, Simoni JM. After the fall from grace: negotiation of new identities among HIV-positive women in Peru. Cult Health Sex. 2008;10: 739–752. doi: 10.1080/13691050802213563 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Enríquez Canto Y, Díaz Gervasi GM, Menacho Alvirio LA. [Impact of the TARGA Program on the reduction of AIDS cases in the Peruvian health system, 1983-2018Impacto do Programa HAART na redução de casos de AIDS no sistema de saúde peruano, 1983–2018]. Rev Panam Salud Publica. 2020;44: e27. doi: 10.26633/RPSP.2020.27 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Laucis NC, Hays RD, Bhattacharyya T. Scoring the SF-36 in Orthopaedics: A Brief Guide. J Bone Joint Surg Am. 2015;97: 1628–1634. doi: 10.2106/JBJS.O.00030 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Oyeyemi AL, Oyeyemi AY, Adegoke BO, Oyetoke FO, Aliyu HN, Aliyu SU, et al. The short international physical activity questionnaire: cross-cultural adaptation, validation and reliability of the Hausa language version in Nigeria. BMC Med Res Methodol. 2011;11: 156. doi: 10.1186/1471-2288-11-156 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Medina C, Barquera S, Janssen I. Validity and reliability of the International Physical Activity Questionnaire among adults in Mexico. Rev Panam Salud Publica. 2013;34: 21–28. [PubMed] [Google Scholar]
20.Hsieh E, Fraenkel L, Bradley EH, Xia W, Insogna KL, Cui Q, et al. Osteoporosis Knowledge, Self-Efficacy, and Health Beliefs among Chinese Individuals with HIV. Arch Osteoporos. 2014;9: 201. doi: 10.1007/s11657-014-0201-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.International Physical Activity Questionnaire. [cited 7 May 2020]. Available: https://sites.google.com/site/theipaq/
22.Lera L, Fuentes-García A, Sánchez H, Albala C. Validity and reliability of the SF-36 in Chilean older adults: the ALEXANDROS study. Eur J Ageing. 2013;10: 127–134. doi: 10.1007/s10433-012-0256-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Alonso J, Prieto L, Antó JM. [The Spanish version of the SF-36 Health Survey (the SF-36 health questionnaire): an instrument for measuring clinical results]. Med Clin (Barc). 1995;104: 771–776. [PubMed] [Google Scholar]
24.Salazar FR, Bernabé E. The Spanish SF-36 in Peru: factor structure, construct validity, and internal consistency. Asia Pac J Public Health. 2015;27: NP2372–2380. doi: 10.1177/1010539511432879 [DOI] [PubMed] [Google Scholar]
25.RAND Corporation. 36-Item Short Form Survey (SF-36) Scoring Instructions. [cited 7 May 2020]. Available: https://www.rand.org/health-care/surveys_tools/mos/36-item-short-form/scoring.html
26.Ware J, Kosinki M, Keller S. SF-36 Physical and Mental Health Summary Scales—A User’s Manual. Boston, MA: New England Medical Center, The Health Institute; 1994. [Google Scholar]
27.R Core Team. R: The R Project for Statistical Computing. 2013. [cited 18 Jun 2020]. Available: https://www.r-project.org/ [Google Scholar]
28.Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, et al. Welcome to the Tidyverse. Journal of Open Source Software. 2019;4: 1686. doi: 10.21105/joss.01686 [DOI] [Google Scholar]
29.Bastardo YM, Kimberlin CL. Relationship between quality of life, social support and disease-related factors in HIV-infected persons in Venezuela. AIDS Care. 2000;12: 673–684. doi: 10.1080/095401200750003842 [DOI] [PubMed] [Google Scholar]
30.Copês RM, Dal Osto LC, Langer FW, de Vieira AR, Codevilla AA da S, Sartori GR, et al. Low health related quality of life associated with fractures in obese postmenopausal women in Santa Maria, Brazil. Bone Rep. 2017;6: 70–73. doi: 10.1016/j.bonr.2017.02.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Miners A, Phillips A, Kreif N, Rodger A, Speakman A, Fisher M, et al. Health-related quality-of-life of people with HIV in the era of combination antiretroviral treatment: a cross-sectional comparison with the general population. Lancet HIV. 2014;1: e32–40. doi: 10.1016/S2352-3018(14)70018-9 [DOI] [PubMed] [Google Scholar]
32.Robberstad B, Olsen JA. The health related quality of life of people living with HIV/AIDS in sub-Saharan Africa—a literature review and focus group study. Cost Effectiveness and Resource Allocation. 2010;8. doi: 10.1186/1478-7547-8-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Skevington SM, O’Connell KA. Measuring quality of life in HIV and AIDS: A review of the recent literature. Psychology and Health. Taylor & Francis Group; 2003. doi: 10.1080/0887044031000084030 [DOI] [Google Scholar]
34.Hikasa S, Shimabukuro S, Hideta K, Kuroda N, Higasa S, Sawada A, et al. Quality of life of people living with HIV compared with that of the general population in Japan. Journal of Infection and Chemotherapy. 2017;23: 698–702. doi: 10.1016/j.jiac.2017.07.012 [DOI] [PubMed] [Google Scholar]
35.Hays RD, Cunningham WE, Sherbourne CD, Wilson IB, Wu AW, Cleary PD, et al. 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. Am J Med. 2000;108: 714–722. doi: 10.1016/s0002-9343(00)00387-9 [DOI] [PubMed] [Google Scholar]
36.Kowal J, Overduin LY, Balfour L, Tasca GA, Corace K, Cameron DW. The Role of Psychological and Behavioral Variables in Quality of Life and the Experience of Bodily Pain Among Persons Living with HIV. Journal of Pain and Symptom Management. 2008;36: 247–258. doi: 10.1016/j.jpainsymman.2007.10.012 [DOI] [PubMed] [Google Scholar]
37.The Socioeconomic Advantages of Mestizos in Urban Peru Word. 2011 [cited 10 Oct 2021]. Available: https://www.semanticscholar.org/paper/The-Socioeconomic-Advantages-of-Mestizos-in-Urban/da3edc3e864f3bb309f03bf2e34ec625f5536c92
38.Rueda S, Mitra S, Chen S, Gogolishvili D, Globerman J, Chambers L, et al. Examining the associations between HIV-related stigma and health outcomes in people living with HIV/AIDS: a series of meta-analyses. BMJ open. 2016;6: e011453. doi: 10.1136/bmjopen-2016-011453 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Moreno-Montoya J, Barragán AM, Martínez M, Rodríguez A, González ÁC. Quality of life and perceived social support in people with HIV in Bogotá, Colombia. Biomedica. 2018;38: 577–585. doi: 10.7705/biomedica.v38i4.3819 [DOI] [PubMed] [Google Scholar]
40.De Francesco D, Underwood J, Bagkeris E, Anderson J, Williams I, Vera JH, et al. Risk factors and impact of patterns of co-occurring comorbidities in people living with HIV. Aids. 2019;33: 1871–1880. doi: 10.1097/QAD.0000000000002293 [DOI] [PubMed] [Google Scholar]
41.Blalock AC, McDaniel JS, Farber EW. Effect of employment on quality of life and psychological functioning in patients with HIV/AIDS. Psychosomatics. 2002;43: 400–404. doi: 10.1176/appi.psy.43.5.400 [DOI] [PubMed] [Google Scholar]
42.Erlandson KM, Allshouse AA, Jankowski CM, Mawhinney S, Kohrt WM, Campbell TB. Relationship of physical function and quality of life among persons aging with HIV infection. Aids. 2014;28: 1939–1943. doi: 10.1097/QAD.0000000000000384 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Nosrat S, Whitworth JW, Ciccolo JT. Exercise and mental health of people living with HIV: A systematic review. Chronic Illness. SAGE Publications Ltd; 2017. doi: 10.1177/1742395317694224 [DOI] [PubMed] [Google Scholar]
44.Wu XY, Han LH, Zhang JH, Luo S, Hu JW, Sun K. The influence of physical activity, sedentary behavior on health-related quality of life among the general population of children and adolescents: A systematic review. PLoS ONE. 2017;12. doi: 10.1371/journal.pone.0187668 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Musumari PM, Srithanaviboonchai K, Tangmunkongvorakul A, Dai Y, Sitthi W, Rerkasem K, et al. Predictors of health-related quality of life among older adults living with HIV in Thailand: results from the baseline and follow-up surveys. AIDS Care—Psychological and Socio-Medical Aspects of AIDS/HIV. 2019. doi: 10.1080/09540121.2019.1707472 [DOI] [PubMed] [Google Scholar]
46.Clingerman E. Physical activity, social support, and health-related quality of life among persons with HIV disease. J Community Health Nurs. 2004;21: 179–197. doi: 10.1207/s15327655jchn2103_5 [DOI] [PubMed] [Google Scholar]
47.Goulding DL, Wilson MP, MaWhinney S, Jankowski CM, Erlandson KM. A supervised exercise intervention fails to improve depressive symptoms and quality of life among sedentary older adults with HIV infection. AIDS Care—Psychological and Socio-Medical Aspects of AIDS/HIV. 2020;32: 714–721. doi: 10.1080/09540121.2019.1634788 [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Shahriar J, Delate T, Hays RD, Coons SJ. Commentary on using the SF-36 or MOS-HIV in studies of persons with HIV disease. Health Qual Life Outcomes. 2003;1: 25. doi: 10.1186/1477-7525-1-25 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Picavet H, Hoeymans N. Health related quality of life in multiple musculoskeletal diseases: SF-36 and EQ-5D in the DMC3 study. Ann Rheum Dis. 2004;63: 723–729. doi: 10.1136/ard.2003.010769 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0269000.r001

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PONE-D-21-11937Health-Related Quality of Life among Women Aging with and without HIV in Peru

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Reviewer #2: No

Reviewer #3: No

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5. Review Comments to the Author

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Reviewer #1: This is a very important paper on physical activity of women living with HIV.

SF-36 PCS and MCS scores transformation to have a mean of 50 and standard deviation of 10 should be better described for readers not familiarized with SF-36.

Alcohol and smoking status dichotomous assessment represents a limitation.

The authors should explore more the association of physical activity; it has affected both physical and mental status in the HIV-infected subset in opposite directions. What hypothesis could be formulated?

In the limitations paragraph the authors states that “findings cannot be extrapolated to represent HIV-infected women outside of Lima”. It should be rephrased. It lacks external validity even for HIV-infected women living in Lima , since it was not a probabilistic sample and was an hospital-based study.

Is there any plan to use SF-36 data in further health economic evaluations of technologies to improve physical activity for this population?

Reviewer #2: The manuscript “Health-Related Quality of Life among Women Aging with and without HIV in Peru” compares health related quality of life (measured by the SF-36) among aging women living with and without HIV and predictors of health related quality of life among these two samples. There are some interesting and surprising findings and I commend authors for exploring these issues among a population that is rarely studied. There were a few areas that, if addressed, would enhance the manuscript:

• Introduction

o It seems like the introduction could be improved by including directional hypotheses. Did authors predict that women living with HIV would have worse health related quality of life than those without HIV? Why did they predict this?

o Additionally, it seems like there are some important contextual factors missing from the examination of health-related quality of life. For example, what would the literature suggest about the impact of illness, stigma, etc. on health in this population? What are important contextual factors specific to Peru? Are there specific policies in Peru? Histories of stigma? Impact of religious stigma? Etc. Even a few sentences might “set up” why this is an important question in this location (other than that it has not been studied before). Authors point to the “unequal status of women” – how is that related to sexual health empowerment or lack thereof in Peru? How does that impact the context in which living with HIV is experienced?

• Methods

o Smoking history as “ever vs. never” seems less important to me than “current vs. not current.” Within the U.S. people living with HIV are much more likely to smoke cigarettes than the general population. Is this the same for Peru? It would have been nice to know whether individuals are current smokers, and this likely would be much more highly correlated with current health and health related quality of life than “ever” smoking status. This is particularly true because of the age of individuals – many may have smoked when they were younger and have since stopped. Without this information (or even years of smoking) the impact of this health behavior is less meaningful.

o Although the Spanish version of the SF-36 was used, I wonder if authors could comment on the cultural appropriateness of answering these questions within a medical setting in Peru. During pilot testing, did any patients comment on answering these questions? Did they seem comfortable giving a range of responses? I’m wondering if there is a chance that people may have answered in a socially desirable way because of cultural expectations or norms about health vs. illness. While outside the scope of this paper it might be worth commenting on the appropriateness of the use of this measure within the methods and/or acknowledging potential limitations in the discussion.

• Results

o Time since diagnosis and ART duration are presented as mean values with standard deviations. It would have also been nice to see the range of values for the sample and perhaps even the median value.

o HIV-related health values like CD4+ cell count and nadir and current viral load should also present median values. Mean values could be misrepresentative if there are extreme outliers.

o Current viral load mean seems extremely high for a population engaged in care. What could explain viral loads of 21,000+? This relates to my prior comment about presenting median values instead of means as this may be skewed by high outlier values. Typically, log viral load is what is presented in research – is that what these values are? Or have they not been converted to log values yet? Additionally, it would be beneficial to see how many were considered undetectable (different definitions by generally, <200 has been used internationally, <20 log viral load is used in most clinical settings in the U.S.) versus having a detectable viral load. It would make sense to look at the impact of viral load in this way as well.

• Discussion

o There is a statement made about “sociodemographics contributing to health” because mestizo-identified women had worse health than white identified women. However, I think this is better reframed as mestizo-identified women experienced worse self-reported health likely as a result of social forces and experiences. It might be worth describing how race and social status, health, etc. are related in general, within the global South, and/or within Peru.

o In general, there were some surprising findings that would benefit from additional post-hoc explanations and references to literature. For example, current alcohol use was associated with better health among women living with HIV and women without HIV. Why do authors think this is true? One potential explanation that came to mind is that it is possible individuals who drink alcohol are also socializing more, and that social support often promotes better health. Authors should explore this and other potential explanations for some of there findings rather than just leaving them.

o Another surprising finding was that women living with HIV reported fewer role limitations due to physical or emotional health. Why is this? Is it that they are employing perspective taking? Are happy about their health considering their HIV diagnoses? Could it be that they are more highly engaged in caring for their health because of HIV? That they seek medical care more often through an infectious disease clinic? Authors do not need to know the reasons for these surprising findings, but I do believe it would be beneficial to explore potential explanations in the context of plausible conclusions based on their knowledge of the sociocultural context, literature, etc.

o Within the limitations, authors state that their findings cannot be extrapolated or generalized outside of the specific city of Lima. Why is this? Is the sample in Lima not representative of Peru in general?

o In the final paragraph, authors acknowledge potential next steps in research, however, they are missing one somewhat obvious next step which is to understand how women living with HIV in Peru are thriving. This sample seems to report better health than those without HIV and maybe there are mental, social, or lifestyle behaviors that if identified could be leveraged to improve the health of women living with HIV. Rather than a deficit focus, this paper nicely lends itself to a resiliency focus of people living with HIV and this should be emphasized within the conclusion and carried throughout to strengthen the findings.

Reviewer #3: Review Report

Title: Health-Related Quality of Life among Women Aging with and without HIV in Peru

Reviewer: Prof. Sam Ibeneme

Institutional affiliations:

1. University of Nigeria, Enugu Campus, Department of Medical Rehabilitation, Faculty of Health Sciences, Enugu, Nigeria. sam.ibeneme@unn.edu.ng.

2. Department of Physiotherapy, Faculty of Health Sciences, School of Therapeutic Studies, University of the Witwatersrand, 7 York Road, Parktown, 2193 Johannesburg, South Africa

Reviewers Report

General comments

Many thanks for inviting me to review the suitability of the article Health-Related Quality of Life among Women Aging with and without HIV in Peru’ for publication. Essentially, this article sought to (1) determine whether the effects of aging on HRQOL vary in aging women with or without HIV infections, and (2) to explore the explanatory variables for the variance in HRQOL in aging women with or without HIV infections using predictive models. Therefore, they compared older adult women with and without HIV infection to know whether the impact of aging on HRQOL is similar in both groups or whether there are differences in both groups which could be accounted for by HIV-related factors. The authors also explored the predictive models that could explain differences in HRQOL between the older adult women with or without HIV infection. The findings seem to demonstrate that HRQOL is more negatively affected among older adult women with HIV than otherwise. The summary score for the physical component of HRQOL in the HIV subset was significantly associated with physical activity, ethnicity, and chronic comorbidities suggesting a role for physical activity, socio-cultural factors and HIV-related/age-related complications in the determination of the physical wellbeing of the aging HIV-infected women. Similarly, the mental component was significantly associated with physical activity, employment, and CD4+ cell count suggesting a role for a physical activity lifestyle, social functioning/economic factors and symptoms of the disease severity in the determination of the emotional wellbeing of the aging HIV-infected individuals. Overall, it was shown that HRQOL may have important clinical application in the early identification of the key drivers of physical and emotional welling in the aging HIV infected individuals. These drivers should be prioritised in the clinical management and policy interventions of HIV disease which may vary across socio-cultural boundaries considering the impact of ethnicity. Thus, I consider this study to be original, useful, timely and relevant.

Specific Comments

Following a preliminary review of this article, I find this paper quite interesting and an important scientific contribution towards understanding how the effects of aging on HRQOL vary in individuals with or without HIV infections, and likewise in identifying the explanatory variables that account for these differences. However, there are specific issues that need to be addressed to improve the quality of this paper.

Abstract

Background: The aim of this study is not stated in the background, rather a feeble attempt was made to provide the purpose of this study in the result section. Therefore, these sections of the abstract must be revisited. It was not indicated why the study focused on women and not both sexes.

Method: The sampling technique used should be indicated and likewise the level at which alpha was set. It must be indicated whether the p-value was one-tailed or two-tailed to give proper context when interpreting it. The explanatory variables that were explored in the regression analysis must be mentioned.

Conclusion: The authors reported that “the physical component was significantly associated with physical activity, ethnicity, and chronic comorbidities while the mental component was significantly associated with physical activity, employment, and CD4+ cell count.” However, they did not mention the implication of these relationships in the conclusion. For instance, CD4+ count enables the assessment of HIV symptom severity which should have an impact on emotional wellbeing when such symptoms become more severe. Similarly, ethnicity alludes to socio-cultural factors which influence people's lifestyle and way of life. Therefore, the implications of these findings should be given the proper context to appreciate the implications of the findings of this study. It was stated in the conclusion that “Of note, physical activity affected both 47 components in the HIV-infected group, but with opposite associations,” for this reason, the results should at least state the variables with the most significant negative and positive values, and likewise the proportion of variance that accounted for the relationship or the effect size.

Main study

Background:

The background to this study is well written and provides a good rationale for the present study.

Method:

1. The research design suggests that this is an observational cross-sectional study. It must be clearly stated so that there is a distinction bearing in mind that there are other types of cross-sectional study which fulfil other research purposes. Also, since this study was done among women with HIV and not AIDS, the defining cut-off point for the CD4+ cell count must be stated in the inclusion criteria.

2. It was not indicated how the sample size was determined to ensure that it has the power to detect the differences in the variables of interest between the study group and the comparison group.

Measures and data collection

In line 115, page 5, it was stated that a pilot study was conducted but the result of the pilot was not indicated as regards the validity and reliability of the test instrument. The validity and reliability of the test instruments - SF-36, IPAQ - must be indicated especially since it has been validated in Spanish.

Data Analysis

The type of t-test statistic that was applied in the study should be stated – whether it was independent or the dependent t-test. It is important to indicate whether the p is one-tailed or two-tailed. This is important because this study is driven by a non-directional hypothesis in which case a two-tailed p-value should be appropriate.

Results

1. The result section was well written.

2. However, the varied participants characteristics between the two groups show that they were not equivalent with respect to the variables that are likely to influence the HRQOL. First, the participants in the comparisons group were significantly older, more employed, of greater: BMI, adiposity, and white ethnic heritage. Given that some of these factors are also variate determinants of HRQOL, an explanatory model of the variance in the HQOL on the basis of other predictive variables may have errors except these covariates are appropriately controlled.

3. The results of the multivariate regression analysis should include the R-value to give a sense of the proportion of the population that accounted for the significant variance change in HQOL using the predictive model.

Discussion

1. The last sentence in paragraph one, page 19, reads as follows:

“As none of the aforementioned studies were conducted in Latin America nor specifically focused on women, a combination of changes in HIV treatment and socio-cultural nuances likely influenced the outcomes.”

2. I suggest that the sentence should be modified by replacing “a combination of changes” with “possible variations” since the authors are not certain of this claim.

3. I do not seem to agree with the interpretation of the findings highlighted in the last two sentences of the second paragraph on page 19 which stated as follows:

“However, for the HIV-infected subset, other factors such as mestizo ethnicity and presence of other comorbidities were independently associated with lower physical scores. These results suggest that despite progress made in the treatment for HIV, for aging Peruvian women, HIV continues to negatively impact the physical and sociodemographic aspects of their quality of life.”

In my view, the results indicated that those infected with HIV, and who were of mestizo ethnicity, were at a greater risk of poor physical functioning or physical health state than the rest. These hints of possible health disparity across ethnic boundaries that limit physical functioning in older women with HIV infection in Peru. However, given that such a relationship was not established among the control group, does not mean that it does not exist. Rather it could imply that HIV infection amplified some health disparities across socio-cultural boundaries in older women in Peru, in a manner that placed the mestizo ethnicity at a disadvantage. Since physical health in the HIV-infected population is also dependent on comorbidities, it implies that whatever factors that promote the onset of these comorbidities could be averse to physical health. Such factors may include limited access to healthcare, aging, prolonged usage of ART, socio-economic or employment (economic) inequality among others. Therefore, it could be investigated whether HIV-comorbidities are also common in the mestizo ethnicity than other ethnic groups and whether a similar trend was observed in studies done in other multi-ethnic countries in Latin America with similar access to health for all the ethnic groups as obtained in Peru.

4. The authors reported that physical activity has a mixed impact on the components of HRQOL since the emotional component was not improved in their study, and cited Goulding et al., 2019 (ref. 43). However, it would have been appropriate to also mention that the findings of Goulding et al., (2019) should be interpreted with caution because of the acknowledged limitations in the small sample size and large standard deviations recorded in the measured outcomes, which suggest that there was a wide margin of error or some degree of imprecision in the measurement. However, the authors had also mentioned that:

“In addition, multivariable regression adjusting for various factors including age, BMI, and other sociodemographic factors of the HIV-infected subset illustrated that physical activity levels are also correlated with both physical and mental components.”

Invariably, physical activity or exercise should be expected to influence physical and emotional HRQOL so far as the influence of age, BMI and socio-demographic factors are eliminated or controlled. Therefore, age, BMI and socio-demographic factors are confounding variables that may minimise the effects of an exercise intervention on HRQOL, and ought to be considered when interpreting the results of similar studies.

5. The authors in the introduction (see page 2, line 95), “hypothesized that HIV burden may be an important predictor for physical and mental health of this population.” However, it is not discussed whether this hypothesis was realised, and should be reflected in the discussion.

Conclusion

The conclusion section is meant to reflect on the outcome of the study concerning the set study objectives. Anything outside of this may distract from a primary need to project the key findings of the present study. I am wondering what the key objectives of this study are and whether they were met. I suggest that the specific objectives are clearly stated. Also, I do not find where a mention was made of whether the study hypothesis was accepted or rejected based on the findings.

Orthographic check

There is a need for minor orthographic check of the manuscript.

Other Comments

This is a novel study which provided scientific findings that may have useful application in the clinical management and policy interventions of HIV disease.

Missing sections

The following sections are missing at the back end of this manuscript and should be provided by the authors in line with the journal format and style, including:

- List of Abbreviations

- Ethics approval and consent to participate

- Consent to publish

- Availability of data and materials

- Competing interests

- Funding

- Authors' Contributions

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Prof Sam Chid Ibeneme

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PLoS One. 2022 Jun 9;17(6):e0269000. doi: 10.1371/journal.pone.0269000.r002

Author response to Decision Letter 0

22 Dec 2021

We have prepared a "Response to Reviewers" document addressing all the suggestions and comments made by the editor and the three reviewers. Please refer to that document for specific responses.

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PLoS One. doi: 10.1371/journal.pone.0269000.r003

Decision Letter 1

Jerome T Galea

13 May 2022

Health-Related Quality of Life among Women Aging with and without HIV in Peru

PONE-D-21-11937R1

Dear Dr. Hsieh,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Jerome T Galea, PhD, MSW

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Reviewer #1: I am happy with the response letter and the new version of the manuscript in which all comments were addressed. It will be a very important paper in its field.

Reviewer #2: The comments have been adequately addressed within the current version of the manuscript. In addition to improving this manuscript, I believe that some of the findings lend themselves nicely to future studies in the same population, which I hope authors will pursue!

Reviewer #3: Reviewers Report

General comments

Many thanks for inviting me to review the revised version of the article: ‘Health-Related Quality of Life among Women Aging with and without HIV in Peru’ - for publication.

Specific Comments

I have gone through the revised manuscript and feel satisfied that the authors reflected all the corrections as required. The quality of this manuscript has greatly improved and is fit for publication.

Recommendation

I recommend that this article is accepted for publication as it is.

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Reviewer #1: Yes: Rodolfo Castro

Reviewer #2: No

Reviewer #3: Yes: Prof. Sam Chidi Ibeneme

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PLoS One. doi: 10.1371/journal.pone.0269000.r004

Acceptance letter

Jerome T Galea

1 Jun 2022

PONE-D-21-11937R1

Health-Related Quality of Life among Women Aging with and without HIV in Peru

Dear Dr. Hsieh:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

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This section collects any data citations, data availability statements, or supplementary materials included in this article.

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Data Availability Statement

All datasets are available from the Open Science Framework public repository (https://osf.io/hfg64/).

[pone.0269000.ref001] 1.Crane HM, Miller ME, Pierce J, Willig AL, Case ML, Wilkin AM, et al. Physical Functioning Among Patients Aging With Human Immunodeficiency Virus (HIV) Versus HIV Uninfected: Feasibility of Using the Short Physical Performance Battery in Clinical Care of People Living With HIV Aged 50 or Older. Open Forum Infect Dis. 2019;6. doi: 10.1093/ofid/ofz038 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref002] 2.Cooper V, Clatworthy J, Harding R, Whetham J, Emerge Consortium. Measuring quality of life among people living with HIV: a systematic review of reviews. Health Qual Life Outcomes. 2017;15: 220. doi: 10.1186/s12955-017-0778-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref003] 3.Drewes J, Gusy B, Rüden U von. More than 20 years of research into the quality of life of people with HIV and AIDS—a descriptive review of study characteristics and methodological approaches of published empirical studies. J Int Assoc Provid AIDS Care. 2013;12: 18–22. doi: 10.1177/1545109712456429 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref004] 4.Dutra BS, Lédo AP, Lins-Kusterer L, Luz E, Prieto IR, Brites C. Changes health-related quality of life in HIV-infected patients following initiation of antiretroviral therapy: a longitudinal study. Braz J Infect Dis. 2019;23: 211–217. doi: 10.1016/j.bjid.2019.06.005 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref005] 5.Bozzette SA, Hays RD, Berry SH, Kanouse DE. A Perceived Health Index for use in persons with advanced HIV disease: derivation, reliability, and validity. Med Care. 1994;32: 716–731. doi: 10.1097/00005650-199407000-00005 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref006] 6.Lins-Kusterer L, Valdelamar J, Aguiar CVN, Menezes MS, Netto EM, Brites C. Validity and reliability of the 36-Item Short Form Health Survey questionnaire version 2 among people living with HIV in Brazil. The Brazilian Journal of Infectious Diseases. 2019;23: 313–321. doi: 10.1016/j.bjid.2019.08.001 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref007] 7.Ware JE, Gandek B. Overview of the SF-36 Health Survey and the International Quality of Life Assessment (IQOLA) Project. Journal of Clinical Epidemiology. 1998;51: 903–912. doi: 10.1016/s0895-4356(98)00081-x [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref008] 8.Wu AW, Hanson KA, Harding G, Haider S, Tawadrous M, Khachatryan A, et al. Responsiveness of the MOS-HIV and EQ-5D in HIV-infected adults receiving antiretroviral therapies. Health Qual Life Outcomes. 2013;11: 42. doi: 10.1186/1477-7525-11-42 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref009] 9.Clayson DJ, Wild DJ, Quarterman P, Duprat-Lomon I, Kubin M, Coons SJ. A comparative review of health-related quality-of-life measures for use in HIV/AIDS clinical trials. Pharmacoeconomics. 2006;24: 751–765. doi: 10.2165/00019053-200624080-00003 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref010] 10.Meng Y-J, Li N-X, Liu C-J, Chen J-H, Song Y-C, Qian Z-S. Quality of life and hostile mentality trend of patients with HIV/AIDS in China. Public Health. 2008;122: 404–411. doi: 10.1016/j.puhe.2007.06.007 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref011] 11.Valdelamar-Jimenez J, Lins-Kusterer L, de Jesus STG, Netto EM, Brites C. Comparison of Three Health-Related Quality of Life Instruments to Evaluate Symptoms of Depression in HIV Patients in Brazil. Journal of Clinical Psychology in Medical Settings. 2019;27: 27. doi: 10.1007/s10880-019-09657-9 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref012] 12.García PJ, Bayer A, Cárcamo CP. The Changing Face of HIV in Latin America and the Caribbean. Curr HIV/AIDS Rep. 2014;11: 146–157. doi: 10.1007/s11904-014-0204-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref013] 13.UNAIDS. Peru. [cited 6 May 2020]. Available: https://www.unaids.org/en/regionscountries/countries/peru

[pone.0269000.ref014] 14.Valencia-Garcia D, Rao D, Strick L, Simoni JM. Women’s experiences with HIV-related stigma from healthcare providers in Lima, Peru: “I would rather die than go back for care.” Health Care Women Int. 2017;38: 144–158. doi: 10.1080/07399332.2016.1217863 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref015] 15.Valencia-Garcia D, Starks H, Strick L, Simoni JM. After the fall from grace: negotiation of new identities among HIV-positive women in Peru. Cult Health Sex. 2008;10: 739–752. doi: 10.1080/13691050802213563 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref016] 16.Enríquez Canto Y, Díaz Gervasi GM, Menacho Alvirio LA. [Impact of the TARGA Program on the reduction of AIDS cases in the Peruvian health system, 1983-2018Impacto do Programa HAART na redução de casos de AIDS no sistema de saúde peruano, 1983–2018]. Rev Panam Salud Publica. 2020;44: e27. doi: 10.26633/RPSP.2020.27 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref017] 17.Laucis NC, Hays RD, Bhattacharyya T. Scoring the SF-36 in Orthopaedics: A Brief Guide. J Bone Joint Surg Am. 2015;97: 1628–1634. doi: 10.2106/JBJS.O.00030 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref018] 18.Oyeyemi AL, Oyeyemi AY, Adegoke BO, Oyetoke FO, Aliyu HN, Aliyu SU, et al. The short international physical activity questionnaire: cross-cultural adaptation, validation and reliability of the Hausa language version in Nigeria. BMC Med Res Methodol. 2011;11: 156. doi: 10.1186/1471-2288-11-156 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref019] 19.Medina C, Barquera S, Janssen I. Validity and reliability of the International Physical Activity Questionnaire among adults in Mexico. Rev Panam Salud Publica. 2013;34: 21–28. [PubMed] [Google Scholar]

[pone.0269000.ref020] 20.Hsieh E, Fraenkel L, Bradley EH, Xia W, Insogna KL, Cui Q, et al. Osteoporosis Knowledge, Self-Efficacy, and Health Beliefs among Chinese Individuals with HIV. Arch Osteoporos. 2014;9: 201. doi: 10.1007/s11657-014-0201-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref021] 21.International Physical Activity Questionnaire. [cited 7 May 2020]. Available: https://sites.google.com/site/theipaq/

[pone.0269000.ref022] 22.Lera L, Fuentes-García A, Sánchez H, Albala C. Validity and reliability of the SF-36 in Chilean older adults: the ALEXANDROS study. Eur J Ageing. 2013;10: 127–134. doi: 10.1007/s10433-012-0256-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref023] 23.Alonso J, Prieto L, Antó JM. [The Spanish version of the SF-36 Health Survey (the SF-36 health questionnaire): an instrument for measuring clinical results]. Med Clin (Barc). 1995;104: 771–776. [PubMed] [Google Scholar]

[pone.0269000.ref024] 24.Salazar FR, Bernabé E. The Spanish SF-36 in Peru: factor structure, construct validity, and internal consistency. Asia Pac J Public Health. 2015;27: NP2372–2380. doi: 10.1177/1010539511432879 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref025] 25.RAND Corporation. 36-Item Short Form Survey (SF-36) Scoring Instructions. [cited 7 May 2020]. Available: https://www.rand.org/health-care/surveys_tools/mos/36-item-short-form/scoring.html

[pone.0269000.ref026] 26.Ware J, Kosinki M, Keller S. SF-36 Physical and Mental Health Summary Scales—A User’s Manual. Boston, MA: New England Medical Center, The Health Institute; 1994. [Google Scholar]

[pone.0269000.ref027] 27.R Core Team. R: The R Project for Statistical Computing. 2013. [cited 18 Jun 2020]. Available: https://www.r-project.org/ [Google Scholar]

[pone.0269000.ref028] 28.Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, et al. Welcome to the Tidyverse. Journal of Open Source Software. 2019;4: 1686. doi: 10.21105/joss.01686 [DOI] [Google Scholar]

[pone.0269000.ref029] 29.Bastardo YM, Kimberlin CL. Relationship between quality of life, social support and disease-related factors in HIV-infected persons in Venezuela. AIDS Care. 2000;12: 673–684. doi: 10.1080/095401200750003842 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref030] 30.Copês RM, Dal Osto LC, Langer FW, de Vieira AR, Codevilla AA da S, Sartori GR, et al. Low health related quality of life associated with fractures in obese postmenopausal women in Santa Maria, Brazil. Bone Rep. 2017;6: 70–73. doi: 10.1016/j.bonr.2017.02.005 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref031] 31.Miners A, Phillips A, Kreif N, Rodger A, Speakman A, Fisher M, et al. Health-related quality-of-life of people with HIV in the era of combination antiretroviral treatment: a cross-sectional comparison with the general population. Lancet HIV. 2014;1: e32–40. doi: 10.1016/S2352-3018(14)70018-9 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref032] 32.Robberstad B, Olsen JA. The health related quality of life of people living with HIV/AIDS in sub-Saharan Africa—a literature review and focus group study. Cost Effectiveness and Resource Allocation. 2010;8. doi: 10.1186/1478-7547-8-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref033] 33.Skevington SM, O’Connell KA. Measuring quality of life in HIV and AIDS: A review of the recent literature. Psychology and Health. Taylor & Francis Group; 2003. doi: 10.1080/0887044031000084030 [DOI] [Google Scholar]

[pone.0269000.ref034] 34.Hikasa S, Shimabukuro S, Hideta K, Kuroda N, Higasa S, Sawada A, et al. Quality of life of people living with HIV compared with that of the general population in Japan. Journal of Infection and Chemotherapy. 2017;23: 698–702. doi: 10.1016/j.jiac.2017.07.012 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref035] 35.Hays RD, Cunningham WE, Sherbourne CD, Wilson IB, Wu AW, Cleary PD, et al. 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. Am J Med. 2000;108: 714–722. doi: 10.1016/s0002-9343(00)00387-9 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref036] 36.Kowal J, Overduin LY, Balfour L, Tasca GA, Corace K, Cameron DW. The Role of Psychological and Behavioral Variables in Quality of Life and the Experience of Bodily Pain Among Persons Living with HIV. Journal of Pain and Symptom Management. 2008;36: 247–258. doi: 10.1016/j.jpainsymman.2007.10.012 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref037] 37.The Socioeconomic Advantages of Mestizos in Urban Peru Word. 2011 [cited 10 Oct 2021]. Available: https://www.semanticscholar.org/paper/The-Socioeconomic-Advantages-of-Mestizos-in-Urban/da3edc3e864f3bb309f03bf2e34ec625f5536c92

[pone.0269000.ref038] 38.Rueda S, Mitra S, Chen S, Gogolishvili D, Globerman J, Chambers L, et al. Examining the associations between HIV-related stigma and health outcomes in people living with HIV/AIDS: a series of meta-analyses. BMJ open. 2016;6: e011453. doi: 10.1136/bmjopen-2016-011453 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref039] 39.Moreno-Montoya J, Barragán AM, Martínez M, Rodríguez A, González ÁC. Quality of life and perceived social support in people with HIV in Bogotá, Colombia. Biomedica. 2018;38: 577–585. doi: 10.7705/biomedica.v38i4.3819 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref040] 40.De Francesco D, Underwood J, Bagkeris E, Anderson J, Williams I, Vera JH, et al. Risk factors and impact of patterns of co-occurring comorbidities in people living with HIV. Aids. 2019;33: 1871–1880. doi: 10.1097/QAD.0000000000002293 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref041] 41.Blalock AC, McDaniel JS, Farber EW. Effect of employment on quality of life and psychological functioning in patients with HIV/AIDS. Psychosomatics. 2002;43: 400–404. doi: 10.1176/appi.psy.43.5.400 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref042] 42.Erlandson KM, Allshouse AA, Jankowski CM, Mawhinney S, Kohrt WM, Campbell TB. Relationship of physical function and quality of life among persons aging with HIV infection. Aids. 2014;28: 1939–1943. doi: 10.1097/QAD.0000000000000384 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref043] 43.Nosrat S, Whitworth JW, Ciccolo JT. Exercise and mental health of people living with HIV: A systematic review. Chronic Illness. SAGE Publications Ltd; 2017. doi: 10.1177/1742395317694224 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref044] 44.Wu XY, Han LH, Zhang JH, Luo S, Hu JW, Sun K. The influence of physical activity, sedentary behavior on health-related quality of life among the general population of children and adolescents: A systematic review. PLoS ONE. 2017;12. doi: 10.1371/journal.pone.0187668 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref045] 45.Musumari PM, Srithanaviboonchai K, Tangmunkongvorakul A, Dai Y, Sitthi W, Rerkasem K, et al. Predictors of health-related quality of life among older adults living with HIV in Thailand: results from the baseline and follow-up surveys. AIDS Care—Psychological and Socio-Medical Aspects of AIDS/HIV. 2019. doi: 10.1080/09540121.2019.1707472 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref046] 46.Clingerman E. Physical activity, social support, and health-related quality of life among persons with HIV disease. J Community Health Nurs. 2004;21: 179–197. doi: 10.1207/s15327655jchn2103_5 [DOI] [PubMed] [Google Scholar]

[pone.0269000.ref047] 47.Goulding DL, Wilson MP, MaWhinney S, Jankowski CM, Erlandson KM. A supervised exercise intervention fails to improve depressive symptoms and quality of life among sedentary older adults with HIV infection. AIDS Care—Psychological and Socio-Medical Aspects of AIDS/HIV. 2020;32: 714–721. doi: 10.1080/09540121.2019.1634788 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref048] 48.Shahriar J, Delate T, Hays RD, Coons SJ. Commentary on using the SF-36 or MOS-HIV in studies of persons with HIV disease. Health Qual Life Outcomes. 2003;1: 25. doi: 10.1186/1477-7525-1-25 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0269000.ref049] 49.Picavet H, Hoeymans N. Health related quality of life in multiple musculoskeletal diseases: SF-36 and EQ-5D in the DMC3 study. Ann Rheum Dis. 2004;63: 723–729. doi: 10.1136/ard.2003.010769 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Health-related quality of life among women aging with and without HIV in Peru

Diego M Cabrera

Meibin Chen

Mijahil P Cornejo

Yvett Pinedo

Patricia J Garcia

Evelyn Hsieh

Roles

Abstract

Background

Materials and methods

Results

Conclusion

Background

Materials and methods

Study design and participants

Measures and data collection

Sociodemographic and clinical characteristics

Measure of physical activity (IPAQ)

SF-36

Data analysis

Ethics

Results

Sociodemographic and clinical characteristics

Table 1. Sociodemographic and clinical characteristics by HIV status.

Table 2. SF-36 outcomes by HIV status.

SF-36 domains and component scores

SF-36 component summary scores in uninfected women

Table 3. Unadjusted regression of factors related to SF-36 component scores.

Table 4. Adjusted multiple linear regression of factors related to SF-36 component scores.

SF-36 component summary scores in HIV-infected women

Discussion

List of abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Sebastian Shepherd

Roles

Author response to Decision Letter 0

Decision Letter 1

Jerome T Galea

Roles

Acceptance letter

Jerome T Galea

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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