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Jia H, Lubetkin EI. Relative importance of selected predictors of health-related quality-of-life (HRQOL) among U.S. adults. Qual Life Res 2024; 33:1633-1645. [PMID: 38514600 DOI: 10.1007/s11136-024-03632-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/10/2024] [Indexed: 03/23/2024]
Abstract
PURPOSE Many factors have been associated with health-related quality of life (HRQOL), and researchers often have tried to rank these contributing factors. Variable importance quantifies the net independent contribution of each individual predictor in a set of predictors to the prediction accuracy of the outcome. This study assessed relative importance (RI) of selected contributing factors to respondents' physically unhealthy days (PUD), mentally unhealthy days (MUD), activity limitation days (ALD), and EuroQol EQ-5D index derived from the Healthy Days measures (dEQ-5D). METHODS Using data from the 2021 Behavioral Risk Factor Surveillance Systems (BRFSS), we estimated the RI of seven socio-demographics and seventeen chronic conditions and risk behaviors. A variable's importance was measured as the average increase in the coefficient of determination after adding the variable to all possible sub-models. RESULTS After controlling for socio-demographics, arthritis and no physical activity were the most important variables for PUD with a RI of 10.5 and 10.4, respectively, followed by depression (RI = 8.5) and COPD (RI = 8.3). Depression was the most important variable for MUD with RI = 23.0 while all other 16 predictors had a RI < 7.0. Similar results were observed for ALD and dEQ-5D: depression was the most important predictor (RI = 16.3 and 15.2, respectively), followed by no physical activity, arthritis, and COPD (RI ranging from 7.1 to 9.2). CONCLUSION This study quantified and ranked selected contributing factors of HRQOL. Results of this analysis also can be used to validate HRQOL measures based on domain knowledge of HRQOL.
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Affiliation(s)
- Haomiao Jia
- Department of Biostatistics, Mailman School of Public Health and School of Nursing, Columbia University, 560 West 168th Street, New York, NY, 10032, USA.
| | - Erica I Lubetkin
- Department of Community Health and Social Medicine, CUNY School of Medicine, New York, NY, USA
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Kajos LF, Molics B, Than P, Gőbel G, Elmer D, Pónusz-Kovács D, Csákvári T, Kovács B, Horváth L, Bódis J, Boncz I. Comparative analysis of the quality of life regarding patients who underwent hip replacement in public versus private hospitals in Hungary. Sci Rep 2024; 14:10031. [PMID: 38693216 PMCID: PMC11063203 DOI: 10.1038/s41598-024-60720-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 04/26/2024] [Indexed: 05/03/2024] Open
Abstract
The study aimed to investigate the impact of hip replacement surgery on the quality of life and to compare the outcomes by sociodemographic and surgical data in Hungarian public and private hospitals. Patients were selected at the Department of Orthopaedics (Clinical Centre, University of Pécs) and at the Da Vinci Private Clinic in Pécs. Patients completed the SF-36 and Oxford Hip Score (OHS) questionnaires before the surgery, 6 weeks and 3 months later. We also evaluated socio-demographic data, disease and surgical conditions. The research involved 128 patients, 60 patients in public, 68 patients in private hospital. Despite the different sociodemographic characteristics and surgical outcomes of public and private healthcare patients, both groups had significantly improved the quality of life 3 months after hip replacement surgery measured by OHS and SF-36 physical health scores (p < 0.001). In the mental health score, only the patients of the private health sector showed a significant improvement (p < 0.001). The extent of improvement did not differ between the two healthcare sectors according to the OHS questionnaire (p = 0.985). While the SF-36 physical health score showed a higher improvement for public patients (p = 0.027), the mental health score showed a higher improvement for private patients (p = 0.015).
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Affiliation(s)
- Luca Fanni Kajos
- Institute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary.
- Doctoral School of Health Sciences, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary.
- National Laboratory on Human Reproduction, Pécs, 7624, Hungary.
| | - Bálint Molics
- Institute of Physiotherapy and Sport Science, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
| | - Péter Than
- Department of Orthopaedics, Clinical Centre, Medical School, University of Pécs, Pécs, 7632, Hungary
| | - Gyula Gőbel
- Da Vinci Private Clinic, Pécs, 7635, Hungary
| | - Diána Elmer
- Institute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
- National Laboratory on Human Reproduction, Pécs, 7624, Hungary
| | - Dalma Pónusz-Kovács
- Institute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
- Doctoral School of Health Sciences, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
- National Laboratory on Human Reproduction, Pécs, 7624, Hungary
| | - Tímea Csákvári
- Institute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
| | - Bettina Kovács
- Institute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
| | - Lilla Horváth
- Institute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
| | - József Bódis
- Institute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
- National Laboratory on Human Reproduction, Pécs, 7624, Hungary
- Department of Obstetrics and Gynaecology, Clinical Centre, Medical School, University of Pécs, Pécs, 7624, Hungary
| | - Imre Boncz
- Institute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, 7621, Hungary
- National Laboratory on Human Reproduction, Pécs, 7624, Hungary
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Chen J, Wu Y, Li L, He F, Zou B, Zhuang Y, Tuersun Y, Yang J, Wu F, Kan Y, Lyu K, Lu Y, Ming WK, Sun X, Wang D. How is family health related to health-related quality of life among middle-aged and older adults in rural China? A cross-sectional study. Int J Older People Nurs 2024; 19:e12605. [PMID: 38374792 DOI: 10.1111/opn.12605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 12/30/2023] [Accepted: 01/12/2024] [Indexed: 02/21/2024]
Abstract
BACKGROUND Health-related quality of life (HRQOL) is unequal between countries and regions, and the emphasis on HRQOL of populations of low-income countries and regions is unprecedented. OBJECTIVES To examine the association between family health and HRQOL among middle-aged and older adults in rural China, and determine whether this association differs by age, gender and chronic disease subgroup. METHODS Cross-sectional survey carried out from July to September 2021. The participants were 1059 people aged 46 and over living in rural China. We used the European Quality of Life Five Dimension Five Level (EQ-5D-5L) and Family Health Scale-Short Form (FHS-SF) to assess health-related quality of life (HRQOL) and family health, respectively. RESULTS The mean EQ-VAS was 75.66, the mean EQ index score was 0.92, and the mean FHS was 37.90 in rural middle-aged and older adults. After Bonferroni correction, generalised linear regression models showed that FHS was significantly associated with the EQ-VAS (β = 0.829; 95% confidence interval [CI]: 0.660 to 0.997; p < .001) and the EQ index score (β = 0.003; 95%CI: 0.001 to 0.004; p < .001). Binary logistic regression models showed that FHS was associated with three dimensions of HRQOL (mobility, self-care and usual activities) (p < .01). Based on subgroup analyses, the effect of FHS on EQ-VAS and the EQ index score was significant in three subgroups after Bonferroni correction (p < .01), but the association between FHS and the dimensions of HRQOL differed by age, gender and chronic disease group (p > .01). CONCLUSIONS This study is the first to explore that family health and its dimensions are significant positive predictors of HRQOL among middle-aged and older adults in rural China. Family-based measures may have more potential and value because better family health significantly improves HRQOL. IMPLICATIONS FOR PRACTICE In the health strategy, the government and primary health care workers should include family health as an indicator and assess it before and after the implementation of the strategy.
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Affiliation(s)
- Jiangyun Chen
- School of Health Management, Southern Medical University, Guangzhou, China
- Institute of Health Management, Southern Medical University, Guangzhou, China
| | - Yibo Wu
- School of Public Health, Peking University, Beijing, China
| | - Lehuan Li
- School of Health Management, Southern Medical University, Guangzhou, China
| | - Feiying He
- Southern Medical University, Guangzhou, China
| | - Biqing Zou
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Yishan Zhuang
- School of Public Health, Southern Medical University, Guangzhou, China
| | | | - Jiao Yang
- School of Public Health, Capital Medical University, Beijing, China
| | - Fangjing Wu
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Yifan Kan
- School of Public Health, Southern Medical University, Guangzhou, China
| | - Ke Lyu
- School of Public Health, China Medical University, Shenyang, China
| | - Yefeng Lu
- Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wai-Kit Ming
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China
| | - Xinying Sun
- School of Public Health, Peking University, Beijing, China
| | - Dong Wang
- School of Health Management, Southern Medical University, Guangzhou, China
- Institute of Health Management, Southern Medical University, Guangzhou, China
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