Racial and Ethnic Variation in Health-Related Quality of Life Scores Prior to Prostate Cancer Treatment

Reading, Stephanie R.; Porter, Kimberly R.; Slezak, Jeffrey M.; Harrison, Teresa N.; Gelfond, Joy; Chien, Gary W.; Jacobsen, Steven J.

doi:10.1016/j.esxm.2017.07.002

Cited by 2 publications

(1 citation statement)

References 32 publications

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“…Still, most of the studies are on a particular sample with a chronic condition or disease [19,33]. As most of this research has used disease specific HRQoL which is not generalizable to all general population [34]. More research is needed on the intersections of age, gender, and race on HRQoL of populations.…”

Section: Introductionmentioning

confidence: 99%

Health-Related Quality of Life of Economically Disadvantaged African American Older Adults: Age and Gender Differences

Assari

Smith

Bazargan

2019

IJERPH

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Background: The association between age and health-related quality of life (HRQoL) is still under debate. While some research shows older age is associated with better HRQoL, other studies show no or negative association between age and HRQoL. In addition, while the association between age and HRQoL may depend on race, ethnicity, gender, and their intersections, most previous research on this link has been performed in predominantly White Middle Class. Objective: To explore gender differences in the association between age and mental and physical HRQoL in a sample of economically disadvantaged African American (AA) older adults. Methods: This cross-sectional survey was conducted in South Los Angeles between 2015 to 2018. A total number of 740 economically disadvantaged AA older adults (age ≥ 55 years) were enrolled in this study, using non-random sampling. This includes 266 AA men and 474 AA women. The independent variable of interest was age. Dependent variables of interest were physical component scores (PCS) and mental component scores (MCS), two main summary scores of the HRQoL, measured using Short Form-12 (SF-12). Gender was the moderator. Socioeconomic status (educational attainment and financial difficulty) were covariates. Linear regression models were used to analyze the data. Results: AA women reported worse PCS; however, gender did not impact MCS. In the pooled sample, high age was associated with better PCS and MCS. In the pooled sample, a significant interaction was found between gender and age on PCS, suggesting a stronger effect of age on PCS for AA men than AA women. In gender-stratified models, older age was associated with better PCS for AA men but not AA women. Older age was similarly and positively associated with better MCS for AA men and women. Conclusions: There may be some gender differences in the implications of ageing for the physical HRQoL of AA older adults. It is unclear how old age may have a boosting effect on physical HRQoL for AA men but not AA women. Future research should test gender differences in the effect of age on physical health indicators such as chronic disease as well as cognitive processes involved in the evaluation of own’s health in AA men and women.

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Section: Introductionmentioning

confidence: 99%