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Xu X, Li Y, Mi H. Life expectancy, long-term care demand and dynamic financing mechanism simulation: an empirical study of Zhejiang Pilot, China. BMC Health Serv Res 2024; 24:469. [PMID: 38622660 PMCID: PMC11017606 DOI: 10.1186/s12913-024-10875-7] [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: 08/26/2023] [Accepted: 03/18/2024] [Indexed: 04/17/2024] Open
Abstract
BACKGROUND China has piloted Long-Term Care Insurance (LTCI) to address increasing care demand. However, many cities neglected adjusting LTCI premiums since the pilot, risking the long-term sustainability of LTCI. Therefore, using Zhejiang Province as a case, this study simulated mortality-adjusted long-term care demand and the balance of LTCI funds through dynamic financing mechanism under diverse life expectancy and disability scenarios. METHODS Three-parameter log-quadratic model was used to estimate the mortality from 1990 to 2020. Mortality with predicted interval from 2020 to 2080 was projected by Lee-Carter method extended with rotation. Cohort-component projection model was used to simulate the number of older population with different degrees of disability. Disability data of the older people is sourced from China Health and Retirement Longitudinal Study 2018. The balance of LTCI fund was simulated by dynamic financing actuarial model. RESULTS Life expectancy of Zhejiang for male (female) is from 80.46 (84.66) years in 2020 to 89.39 [86.61, 91.74] (91.24 [88.90, 93.25]) years in 2080. The number of long-term care demand with severe disability in Zhejiang demonstrates an increasing trend from 285 [276, 295] thousand in 2023 to 1027 [634, 1657] thousand in 2080 under predicted mean of life expectancy. LTCI fund in Zhejiang will become accumulated surplus from 2024 to 2080 when annual premium growth rate is 5.25% [4.20%, 6.25%] under various disability scenarios, which is much higher than the annual growth of unit cost of long-term care services (2.25%). The accumulated balance of LTCI fund is sensitive with life expectancy. CONCLUSIONS Dynamic growth of LTCI premium is essential in dealing with current deficit around 2050 and realizing Zhejiang's LTCI sustainability in the long-run. The importance of dynamic monitoring disability and mortality information is emphasized to respond immediately to the increase of premiums. LTCI should strike a balance between expanding coverage and controlling financing scale. This study provides implications for developing countries to establish or pilot LTCI schemes.
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Affiliation(s)
- Xueying Xu
- School of International Studies, Zhejiang University, Hangzhou, China
| | - Yichao Li
- School of Public Affairs, Zhejiang University, Hangzhou, China.
| | - Hong Mi
- School of Public Affairs, Zhejiang University, Hangzhou, China
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Dhafari TB, Pate A, Azadbakht N, Bailey R, Rafferty J, Jalali-Najafabadi F, Martin GP, Hassaine A, Akbari A, Lyons J, Watkins A, Lyons RA, Peek N. A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods. J Clin Epidemiol 2024; 165:111214. [PMID: 37952700 DOI: 10.1016/j.jclinepi.2023.11.004] [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] [Received: 05/17/2023] [Revised: 10/14/2023] [Accepted: 11/05/2023] [Indexed: 11/14/2023]
Abstract
OBJECTIVES Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns. STUDY DESIGN AND SETTING We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns. RESULTS Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation. CONCLUSION The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.
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Affiliation(s)
- Thamer Ba Dhafari
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Alexander Pate
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Narges Azadbakht
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Rowena Bailey
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - James Rafferty
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Farideh Jalali-Najafabadi
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, M13 9PL Manchester, UK
| | - Glen P Martin
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Abdelaali Hassaine
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Jane Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Alan Watkins
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Niels Peek
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK; NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
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Fang S, Liang H, Liang Y. Typologies of dependency, household characteristics, and disparity in formal and informal care use: analysis of community-dwelling long-term care insurance claimants in an urban municipality of China. Int J Equity Health 2023; 22:235. [PMID: 37950244 PMCID: PMC10636834 DOI: 10.1186/s12939-023-02048-5] [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: 04/30/2023] [Accepted: 10/30/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND A comprehensive understanding of subgroups of community-dwelling older adults and their long-term care (LTC) utilization can help to promote equality in the long-term services and support system. Dependency and household characteristics were found to affect the LTC utilization of homebound older adults. However, few studies considered the typologies of dependency of older populations according to co-occurring limitations, and little is known about differences in LTC use among elderly of typologies of dependency under distinct household conditions. METHODS We aimed to identify typologies of dependency of older adults living at home and explore the disparities in formal care and informal care use among typologies of dependency by income and living situation. In this cross-sectional study, we used the public long-term care insurance (LTCI) database of Yiwu, Zhejiang Province, China, and included 1675 individuals aged ≥ 60 years living at home. Cluster analysis was conducted to determine typologies of dependency among older adults. A two-step multilevel analysis was used to examine disparities in formal and informal care use related to household income and living status among typologies of dependency. RESULTS Seven dependency clusters were identified. Pro-wealthy inequalities in both formal and informal care use were found in the least dependent cluster and the limited-locomotion cluster. Pro-poor inequalities in formal care use were found in the fully dependent cluster without impaired vision and the cluster with intact continence and vision. Living with family members was positively associated with receiving formal care for the fully dependent cluster. Older adults in most clusters were more likely to use informal care when living with family members, except for the least dependent cluster and the limited-locomotion cluster. CONCLUSIONS Our findings suggest that household inequalities in LTC use varied among typologies of dependency of older adults, which may provide insights for researchers and policymakers to develop tailored LTC and targeted LTCI programs for older adults living at home and their family caregivers, considering both typologies of dependency and household characteristics.
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Affiliation(s)
- Shuai Fang
- Institute of Sociology, Shanghai Academy of Social Sciences, 622 Huaihai Middle Rd., Huangpu District, Shanghai, 200020, China
| | - Hong Liang
- School of Social Development and Public Policy, Fudan University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China
| | - Yan Liang
- School of Nursing, Fudan University, 305 Fenglin Rd., Xuhui District, Shanghai, 200032, China.
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Fang S, Liang H, Liang Y. Relationship between person, environmental factors, and activities of daily living performance among physically disabled older adults living at home: a structural equation model. BMC Geriatr 2023; 23:285. [PMID: 37170103 PMCID: PMC10176859 DOI: 10.1186/s12877-023-04000-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 04/25/2023] [Indexed: 05/13/2023] Open
Abstract
BACKGROUND Older adults with physical disability need long-term services and support, which incur enormous costs. However, supportive environments may reduce disability and promote aging in place. It is unclear how the physical and social environment affect different types of functional impairments and influence the performance of activities of daily living (ADL) in physically disabled older adults. OBJECTIVE The purpose of this study was to examine the relationship between person, environmental factors, and ADL performance among physically disabled older adults living at home. METHODS This was a cross-sectional study. Using long-term care insurance claims data from a pilot city in China, we used a structural equation model to assess the potential paths among person, environmental factors, and ADL performance. RESULTS Education and income had different influences on the social environment and physical environment. The functional impairments had significant effects on ADL performance, either directly or through physical environment (with handrails) and social environment (family support). CONCLUSIONS The present findings offer crucial evidence for understanding the interactions between a person and the environment, as well as their influence on physical ADLs, suggesting the importance of a supportive environment and a subpopulation-targeting strategy for disabled older adults.
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Affiliation(s)
- Shuai Fang
- Institute of Sociology, Shanghai Academy of Social Sciences, 622 Huaihai Middle Rd., Huangpu District, Shanghai, 200020, China
| | - Hong Liang
- School of Social Development and Public Policy, Fudan University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China
| | - Yan Liang
- School of Nursing, Fudan University, 305 Fenglin Rd., Xuhui District, Shanghai, 200032, China.
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