Health, Security and Participation: A Structural Relationship Modeling among the Three Pillars of Active Ageing in China

Yang, Yinan; Meng, Ying‐Ying; Dong, Peng

doi:10.3390/ijerph17197255

Cited by 9 publications

(7 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The larger number of indicators available in the SHARE survey matches the areas of greatest scientific development within AA, namely Health and Participation, with a lower presence of questions related to the Lifelong Learning and Security pillars, despite their proven relevance in positive ageing trajectories [ 14 , 103 , 137 ].…”

Section: Discussionmentioning

confidence: 99%

“…An optimal combination of the Health, Lifelong Learning, Participation and Security pillars will be key to achieving AA. Most authors hold this assumption and there have been attempts to build it into empirical models [101][102][103], yet few have succeeded in showing the interdependence between some pillars and others to show profiles of older adults ageing along diverse trajectories. This paper has demonstrated the interdependence of the pillars, giving five main profiles, which in turn were related to personal and contextual factors as well as to measures of well-being and quality of life.…”

Section: Plos Onementioning

confidence: 99%

See 1 more Smart Citation

Active ageing profiles among older adults in Spain: A Multivariate analysis based on SHARE study

et al. 2022

View full text Add to dashboard Cite

Background Following the active ageing model based on the Health, Lifelong Learning, Participation and Security pillars, this research has a twofold objective: i) to classify older adults according to active ageing profiles, taking into account the four pillars, and ii) to ascertain the relationship between the profiles and personal and contextual factors, as well as well-being and quality of life in old age. Methods A study sample of 5,566 Spanish older adults who participated in wave 6 of the Survey of Health, Ageing and Retirement in Europe (SHARE) was included. Data were analysed in different steps applying several statistical analyses (Principal Component, Cluster, Discriminant, Multiple Correspondence and bivariate analysis with Pearson chi-square and ANOVA). Results Five older adult profiles were obtained (I: with moderate activity; II: quasi-dependents; III: with active ageing-limiting conditions; IV: with diverse and balanced activity; V: with excellent active ageing conditions). The first three profiles were characterised by subjects with a high average age, low educational level, who were retired or housewives, and who perceived a moderate level of loneliness, satisfaction with the social network and quality of life, as well as having a larger family network, but living in small households or alone. In contrast, the latter two profiles showed better personal and contextual conditions, well-being and quality of life. Discussion and conclusions The multidimensional approach to active ageing followed in this article has revealed the presence of several older adult profiles, which are confined to groups with better or worse active ageing conditions. In this context, if ageing is a process that reflects the previous way of life, intervention priorities will have to consider actions that promote better conditions during the life cycle.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

Active ageing profiles among older adults in Spain: A Multivariate analysis based on SHARE study

et al. 2022

View full text Add to dashboard Cite

show abstract

“…We analyze the relationships among the variables with the help of SEM in the statistical analysis software Mplus 8.0, and the maximum likelihood estimation method (ML) is used due to its robust estimation even if the measured indicators do not obey normal distribution under the premise of large samples [ 44 ]. On the measurement models, the coefficients of all measurement indicators explaining the latent variables are significant at the 1% level, indicating that the indicators measured the latent variables better.…”

Section: Resultsmentioning

confidence: 99%

Childhood Circumstances and Mental Health in Old Age: A Life Course Survey in China

Zhu

Liao

2021

IJERPH

View full text Add to dashboard Cite

Current evidence and research of the life course approach on the association between life experiences and health in old age are fragmentary. This paper empirically examines the “long arm” effect of the childhood circumstances on mental health in later life using a large longitudinal dataset (CHARLS) conducted in 2014 and 2015. We operationalize the childhood circumstances as family economic conditions, community environment, and peer network to include the meaningful content and understand their interaction. The SEM results indicate that effects of those factors contributing to older people’s mental health are unequal and vary among age groups and genders. Of those, peer network in childhood determines to a large extent the mental health through the whole life course, while economic conditions and community environment are weakly associated with mental health. Furthermore, we find a distinct interaction mechanism linking those variables. The peer network completely mediates the effect of the community environment on the mental health of older adults and has a partial mediating effect on the economic conditions. Those findings suggest that social policies aimed at promoting older people’s mental health in the context of the active ageing and health ageing strategy should go beyond the old age stage and target social conditions early in childhood.

show abstract

“…It is mainly due to two reasons, one is that urban women have better social security resources, they can get access to better social security services and benefits (54). In addition, the three-child policy is currently being advocated in China (55), due to China's strong traditional intergenerational ties and the inadequacy of the current childcare system (56, 57), more and more women prefer to retire to care for their grandchildren to reduce the pressure on their children (58,59). In the absence of social support, many women are physically and psychologically exhausted by family (60).…”

Section: Discussionmentioning

confidence: 99%

How long can Chinese women work after retirement based on health level: Evidence from the CHARLS

Cheng

Fang

Zeng

2023

Front. Public Health

View full text Add to dashboard Cite

ObjectiveTo further enhance the understanding of factors impacting female participation in the workforce based on health levels and to measure the excess work capacity of middle-aged and older female groups by residence and educational level.MethodsData of women aged 45–74 were accessed from the China Health and Retirement Longitudinal Study (CHARLS) from 2011, 2013, 2015, to 2018. The health status of women was comprehensively evaluated by single health variables and frailty index. A Probit model was used to measure the excess working capacity of women by region (rural/urban) and educational level, taking all women aged 45–49, rural women aged 45–49, and rural (illiterate) women in all age groups as the benchmark, respectively.ResultsThe excess capacity of all Chinese women aged 50–64 is 1.9 years, and that of women aged 50–74 is 5.1 years. The excess work capacity of women in urban and rural areas and with different educational levels is heterogeneous. The excess working capacity of urban women aged 50–64 is 6.1–7.8 years, and that of urban women aged 50–74 is 9.8–14.9 years. The excess working capacity of urban women aged 50–64 is about 6 times that of rural women. The excess work capacity of highly educated women was 3 times higher than that of illiterate women.ConclusionThe potential work capacity of Chinese women remains to be exploited, especially for urban and highly educated middle-aged and older women with better conditions of health, whose potential is more significant. A rational retirement policy for women and the progressive implementation of an equal retirement age for men and women will contribute to further advancement of gender equality and healthy aging in the workplace in China.

show abstract

Health, Security and Participation: A Structural Relationship Modeling among the Three Pillars of Active Ageing in China

Cited by 9 publications

References 11 publications

Active ageing profiles among older adults in Spain: A Multivariate analysis based on SHARE study

Active ageing profiles among older adults in Spain: A Multivariate analysis based on SHARE study

Childhood Circumstances and Mental Health in Old Age: A Life Course Survey in China

How long can Chinese women work after retirement based on health level: Evidence from the CHARLS

Contact Info

Product

Resources

About