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Background: An aging population and an increase in the proportion of disabled elderly have brought an unprecedented global challenge, especially in China. Aside lack of professional long-term care facilities, the shortage of human resource for old-age care is also a major threat. Therefore, this study tries to forecast the demand scale of nursing staff for the oldest-old in 2025 in China servicing as a reference for the development plan of human resource for elderly nursing., Methods: Based on CLHLS (Chinese Longitudinal Healthy Longevity Survey) 2011 and 2014, Logit model was used to construct the transition probability matrix of the elderly's health status (health/mild/moderate/severe disability and death). By using the data of the elderly population aged 65 or over in the 2010 national population census, we projected the number of Chinese oldest-old population in different health status by 2025 through Markov model and projected the scale of the demand of nursing staff combined with the human population ratio method., Results: The forecast shows that the Chinese oldest-old population is about 52.6 million, among which 46.9 million are healthy, 3.7 million are mild, 0.8 million are moderate, and 1.2 million are severely disabled in 2025. Concurrently, the demand scale of nursing staff will be 5.6 million according to the low standard and 11.5 million according to the high standard. Thus, human resource supply of long-term care is worrying., Conclusion: In 2025, the population size of the Chinese oldest-old will be further expanded, and the demand of care will increase accordingly, leading to a vast gap in the nursing staff. Therefore, it is urgent to build a professional nursing staff with excellent comprehensive quality and reasonable quantity, to ensure the sustainable development of China's elderly care service industry., (© 2022 The Author(s); Published by Kerman University of Medical Sciences This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)

Background: Currently, there are many studies focusing on the influencing factors of the elderly people’s living arrangements or health status, but little is known about the relationship between living arrangements or health status and long-term care models for the old-age, especially the joint effects. Objective: We aimed to assess the effects of health status and living arrangements on long-term care models (LTCM) among the elderly of Xiamen, China, especially their cumulative joint effects. Methods: A total of 14,373 participants aged ≥ 60 years by multistage sampling in Xiamen of China were enrolled. Multinomial logistic regression was used to estimate the Odds ratios (ORs) regressing LTCM on health status and living arrangements using the Anderson model as theoretical framework. Results: Totally, 14,292 valid questionnaires were obtained, of which 86.37% selected home care. With the increase of disability degree, older people are more likely to choose institutional care, compared to living alone (ORs = 1.75, 2.06, 4.00, 4.01 for the “relatively independent’, “mild disability’, “moderate disability’, and “total disability’, respectively, in comparison with “completely independent’). The elderly living with children and other family members preferred to choose home care. (ORs = 0.50, 0.39, 0.40, and 0.43 for the “living with children’, “living with spouse’, “living with children and spouse’, and “living with others’, respectively, in comparison with “alone’). Additionally, residence, number of children, education level, and feelings of loneliness were the determinants of the choice of social pension. Conclusion: A multitude of older people are trended to choose home care in Xiamen of China. There was an interaction and joint effect between the degree of disability and the living arrangements on LTCM. Therefore, policymakers should pay close attention to care for those living alone, childless, and disabled elders to meet their care needs, especially in home care. In addition, the social construction of facilities for elders in rural areas should be strengthened. [ABSTRACT FROM AUTHOR]

• Healthy ageing is a process of developing or maintaining the functional capability. • Find out linear and non-linear effects of clean air policy on functional capacity. • Long-term exposure PM 2.5 was applied as a proxy of clean air policy. • The subpopulations possibly modify the effects of air pollution. • Different influencing mechanism of air pollutant on outdoor and indoor activities. Since there is limited knowledge about health effects of the clean air policy (CAP, i.e., a series of emission-control actions) on continuum functional capacity (CFC) among the older adults on a large representative data, our research was to fill this gap. We used a continuous variable of airborne fine particulate matter (PM 2.5) particles as a proxy for the CAP to evaluate the linear and non-linear effect of PM 2.5 exposure on CFC of older adults, under the quasi-experimental framework of the temporal contrast between 2011 (before the CAP) and 2015 (after the CAP). Multiple environmental factors were considered and spline function was utilized to fit the spatial autocorrelations. A competing risk model was constructed to qualify the impact of PM 2.5 on multidimensional disability. After adjusting for potential confounders, a J-shaped association was found between PM 2.5 concentration increase on CFC, with a threshold 2μg/m3. We also demonstrated that a 10-µg/m3 increase in PM 2.5 concentration was related to a 14.0% (95% CI :0.00, 19.00%) increment risk in the functional decline. Similarly, the competing risk model presented a hazard ratio of multidimensional disability ranging from 1.707(0.928-4.141) at 40μg/m3 concentration of PM 2.5 to 4.384 (1.970-9.755) over 80μg/m3. Stratified analyses showed that married men less than 80 years old in rural areas are more likely to be affected by PM 2.5 exposure, where the influencing mechanism of air pollutant to outdoor and indoor activities might be the potential cause. Implementing CAP might improve CFC, prevent the occurrence of disability, and update the air policy. [ABSTRACT FROM AUTHOR]