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Gender differences in multiple underlying dimensions of health-related quality of life are associated with sociodemographic and socioeconomic status.

ABSTRACT: The purpose of the study was to examine whether gender differences in summary health-related quality of life (HRQoL) are due to differences in specific dimensions of health, and whether they are explained by sociodemographic and socioeconomic (SES) variation.The National Health Measurement Study collected cross-sectional data on a national sample of 3648 black and white noninstitutionalized adults ages 35 to 89 years. Data included the Short Form 36-Item survey, which yielded separate Mental and Physical Component Summary scores (MCS and PCS, respectively), and five HRQoL indexes: Short Form 6 dimension, EuroQol 5 dimension, the Health Utilities Indexes Mark 2 and 3, and the Quality of Well-Being Scale Self-Administered form. Structural equation models were used to explore gender differences in physical, psychosocial, and pain latent dimensions of the 5 indexes, adjusting for sociodemographic and SES indicators. Observed MCS and PCS scores were examined in regression models to judge robustness of latent results.Men had better estimated physical and psychosocial health and less pain than women with similar trends on the MCS and PCS scores. Adjustments for marital status or income reduced gender differences more than did other indicators. Adjusting results for partial factorial invariance of HRQoL attributes supported the presence of gender differentials, but also indicated that these differences are impacted by dimensions being related to some HRQoL attributes differently by gender.Men have better estimated health on 3 latent dimensions of HRQoL-physical, psychosocial, and pain-comparable to gender differences on the observed MCS and PCS scores. Gender differences are partly explained by sociodemographic and SES factors, highlighting the role of socioeconomic inequalities in perpetuating gender differences in health outcomes across multiple domains. These results also emphasize the importance of accounting for measurement invariance for meaningful comparison of group differences in estimated means of self-reported measures of health.

SUBMITTER: Cherepanov D

PROVIDER: S-EPMC3687080 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

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Gender differences in multiple underlying dimensions of health-related quality of life are associated with sociodemographic and socioeconomic status.

Cherepanov Dasha D Palta Mari M Fryback Dennis G DG Robert Stephanie A SA Hays Ron D RD Kaplan Robert M RM

Medical care 20111101 11

<h4>Purpose</h4>The purpose of the study was to examine whether gender differences in summary health-related quality of life (HRQoL) are due to differences in specific dimensions of health, and whether they are explained by sociodemographic and socioeconomic (SES) variation.<h4>Methods</h4>The National Health Measurement Study collected cross-sectional data on a national sample of 3648 black and white noninstitutionalized adults ages 35 to 89 years. Data included the Short Form 36-Item survey, w ...[more]

PMID: 21945974

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Project description:The Adult Strabismus Quality of Life Questionnaire (AS-20) and the Amblyopia & Strabismus Questionnaire (A&SQ) both measure health-related quality of life in strabismus patients. We evaluated to what extent these instruments cover similar domains by identifying the underlying quality-of-life factors of the combined questionnaires.Participants were adults from a historic cohort with available orthoptic childhood data documenting strabismus and/or amblyopia. They had previously completed the A&SQ and were now asked to complete the AS-20. Factor analysis was performed on the correlation-matrix of the combined AS-20 and A&SQ data to identify common underlying factors. The identified factors were correlated with the clinical variables of angle of strabismus, degree of binocular vision, and visual acuity of the worse eye.One hundred ten patients completed both questionnaires (mean age, 44 years; range, 38-51 years). Six factors were found that together explained 78% of the total variance. The factor structure was dominated by the first four factors. One factor contained psychosocial and social-contact items, and another factor depth-perception items from both questionnaires. A third factor contained seven items-only from the AS-20-on eye strain, stress, and difficulties with reading and with concentrating. A fourth factor contained seven items-only from the A&SQ-on fear of losing the better eye and visual disorientation, specific for amblyopia. Current visual acuity of the worse eye correlated with depth-perception items and vision-related items, whereas current binocular vision correlated with psychosocial and social-contact items, in 93 patients.Factor analysis suggests that the AS-20 and A&SQ measure a similar psychosocial quality-of-life domain. However, functional problems like avoidance of reading, difficulty in concentrating, eye stress, reading problems, inability to enjoy hobbies, and need for frequent breaks when reading are represented only in the AS-20. During the development of the A&SQ, asthenopia items were considered insufficiently specific for strabismus and were excluded a priori. The patients who generated the items for the AS-20 had, in majority, adulthood-onset strabismus and diplopia and were, hence, more likely to develop such complaints than our adult patients with childhood-onset strabismus and/or amblyopia.

Project description:ObjectiveThis study aimed to determine the association between adolescent socioeconomic status (father's education and adolescent subjective socioeconomic status) and adult quality of life and the mediation roles of adult socioeconomic status, social capital and lifestyle (physical activity and exposure to smoke) among the "Tehran University of Medical Sciences Employees Cohort (TEC) Study" participants.MethodData of 4455 participants were derived from the Tehran University of Medical Sciences Employees Cohort (TEC) Study. In this study, the World Health Organization quality of life-BREF, the World Bank's Integrated and the International Physical Activity Questionnaire were used. Data were analyzed with structural equation modeling using SPSS Amos 24.0 program.ResultsThe mean age of the participants was 42.31 years (SD: 8.37) and most of the subjects were female (60.7%). Correlation analysis results revealed that, quality of life had a significant and positive association with adolescent subjective socioeconomic status (r = 0.169, p < 0.01) and father's education (r = 0.091, p < 0.01). A mediation model testing the direct relationship between adolescent socioeconomic status and adult socioeconomic status and quality of life, showed a positive relationship between adolescent subjective socioeconomic status (β = 0.229, p < 0.001) and father's education (β = 0.443, p < 0.001) with adult socioeconomic status. Adult socioeconomic status was positively related to quality of life (β = 0.205, p < 0.001). Adult socioeconomic status mediated the relationship between adolescent subjective socioeconomic status (β = 0.047, p < 0.01) and father's education (β = 0.091, p < 0.01) with quality of life. While adult socioeconomic status fully mediated the relationship between the father's education and quality of life, it partially mediated the adolescent subjective socioeconomic status-quality of life association. Other variables such as social capital and lifestyle did not have mediator role in a mediation model.ConclusionThis study provides the evidence for the role of adult socioeconomic status as a partial mediator between adolescent subjective socioeconomic status and quality of life. Therefore, there are several unknown mediators other than adult socioeconomic status that need to be explored in future studies.

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Project description:BACKGROUND:Myasthenia gravis (MG), a chronic neuromuscular disorder, can adversely affect patients' health-related quality of life (HRQoL), especially in women. The study aimed to evaluate the difference in HRQoL of women and men MG patients and explore the factors that mediate the relationship between gender and HRQoL. METHODS:A cross-sectional study was conducted among 1815 patients with MG in China. The revised 15-item MG quality of life scale (MG-QOL15r) was used to access patients' HRQoL in overall, physical, social and emotional domains. Socio-demographic information, diagnosis and treatment history, comorbidities, social support, active lifestyle and the MG activities of daily living scale (MG-ADL) were recorded and compared between women and men using the Student's t-test and Pearson's Chi-square test. Multivariable regression analyses were conducted to identify independent contributors to HRQoL, especially those affecting different gender. RESULTS:On average, female patients with MG reported a lower MG-QOL15r score than the males (44.49?±?29.10 vs 49.32?±?29.18). The association between gender and patients' HRQoL interacted with the number of comorbidities across the overall, physical and social domains of patients. As the number of comorbidities increased, the scores of HRQoL decreased and it was faster among females than the males (p?<?0.05). Moreover, unemployment, exacerbation of the disease, and active lifestyle contributed to the patients' HRQoL across all domains. Unemployment (??=?-?4.99 [95%CI, -?7.80 to -?2.18], p?<?0.001) and exacerbations (??=?-?8.49 [95%CI, -?11.43 to -?5.54], p?<?0.001) were correlated with poorer HRQoL; while an active lifestyle had a positive impact on HRQoL (??=?0.28 [95%CI, 0.16 to 0.40], p?<?0.001). CONCLUSIONS:The results indicate that the HRQoL of women MG patients was lower than that of men. The relationship between gender and HRQoL is modulated by the number of comorbidities. Thus, to improve the HRQoL of women MG patients, symptomatic treatments might not be enough, their comorbid conditions should be considered as well. Additionally, employment status, MG exacerbations, and an active lifestyle have been found as determining factors of the patients' HRQoL, which suggests future interventions should cope with these factors to improve their quality of life.

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Gender differences in multiple underlying dimensions of health-related quality of life are associated with sociodemographic and socioeconomic status.

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Gender differences in multiple underlying dimensions of health-related quality of life are associated with sociodemographic and socioeconomic status.

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