Social inequalities in health-related quality of life among people aging with HIV/AIDS: the role of comorbidities and disease severity

Abstract

Purpose While socioeconomic inequalities in health-related quality of life are well documented in the scientific literature, research has neglected to look into the reasons for these inequalities. The purpose of this study is to determine in what way social inequalities in health-related quality of life among patients with the same chronic disease could be explained by variations in disease severity. Methods We used the data of 748 people aging with HIV in Germany who took part in the nationwide study 50plushiv and provided self-report data on socioeconomic status, health-related quality of life (SF-12) and various markers of disease severity (comorbidity, falls, late presentation and AIDS diagnosis). Regression analyses were applied to determine the impact of SES on HRQOL after adjusting for disease severity variables. Results The mental and physical subscales of the SF-12, comorbidity burden and falls were significantly related to SES. SES explained 7% of the variance in PCS scores and 3% of the variance in MCS scores after adjusting for age and time since diagnosis. Markers of disease severity explained 33% of the variance in PCS scores and 14% of the variance in MCS scores. After adjusting for disease severity SES was still significantly related to PCS and MCS scores. Conclusions The diverse sample of people aging with HIV showed social inequalities regarding HRQOL and most of the disease severity markers. SES was significantly related to mental and physical HRQOL after adjusting for disease severity. Possible explanations for this phenomenon are discussed.

Sociodemographic, HIV-Related Characteristics, and Health Care Factors as Predictors of Self-Reported Vaccination Coverage in a Nationwide Sample of People Aging with HIV in Germany

“…Eligible participants were all people diagnosed with HIV, 50 years old or older. The questionnaire was provided as an online questionnaire and as a paper pencil questionnaire (for more information, see [ 18 ]). All information obtained from the participants is self-reported.…”

“…We used various sociodemographic variables for descriptive purposes and as predictors of vaccination and cancer screening coverage, as age, gender (male vs. female), sexual orientation (heterosexual vs. not heterosexual), size of place of residence (less than 500,000 vs. more than 500,000), relationship status (single vs. in relationship), education (10 years and less vs. more than 10 years), and socioeconomic status (SES; combined metric variable; see [ 18 , 19 ] for details). We further used HIV-related variables such as duration of HIV infection, CD4 count (less than 200 vs. more than 200) and HIV RNA level (viral load; undetectable vs. detectable), an AIDS diagnosis, and late HIV diagnosis (see [ 18 ] for details), and health care variables such as type of HIV specialist provider (private practice vs. hospital/clinic), distance to HIV specialist (less than 10 km vs. more than 10 km), last visit to HIV specialist (within 3 months vs. longer than 3 months), type of insurance (public vs. private), and whether the patient was regularly consulting a general practitioner apart from the HIV specialist (no vs. yes).…”

Estimation of Health-State Utility Values and Factors Driving Health-Related Quality of Life in People Living with HIV and AIDS and Receiving cART in Germany: Baseline Analysis of a Cohort Study

“…Further, to our knowledge, there are no available estimates of utilities which can be used in health economic evaluations of HIV-mitigation strategies. Two recent studies (Drewes et al, 2020;Sabranski et al, 2020) investigate aspects of HRQoL in German HIV-patient using SF-12 instrument. They showed the overall negative impact of HIV infection on mental and physical health and found impairing effects of age, depression and unemployment (Sabranski et al, 2020) and impact of different comorbidities (Drewes et al, 2020) on health-related quality of life.…”

Physical activity among women of low socioeconomic status living with HIV in two major cities of Brazil and Mozambique: A cross-sectional comparative study

“…Moreover, HIV/AIDS is a disease embedded in social inequity, affecting those of lower socioeconomic status (SES) at a disproportionately high rate ( 5 , 6 ). Although the universalization of cART allowed greater access to treatment, the exposure of PLHIV with low SES to risk factors, predisposing to disability and chronic diseases is greater in comparison with the wealthier groups ( 5 - 7 ). Therefore, multiple physiological symptoms associated with the HIV and cART are majorly due to poverty ( 6 , 7 ).…”