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Background The disease burden of ischemic heart disease is becoming heavier, and the influence of metabolic factors is gradually increasing, and there is still insufficient research in exploring the disease burden caused by metabolic factors and its change trend. Objective To analyzes the long-term impact and trend of the disease burden of ischemic heart disease caused by metabolic factors in China from 1990 to 2019, so as to provide solid and powerful scientific support and basis for the prevention and control of ischemic heart disease. Methods Based on the data of the Global Burden of Disease Study in 2019, the mortality rate, disability adjusted life year (DALY) and corresponding normalized indicators attributed to metabolic factors in ischemic heart disease of different ages and sexes in China from 1990 to 2019 were obtained. The Joinpoint model was used to systematically evaluate the temporal trend of disease changes. Results The mortality rate and DALY rate of ischemic heart disease attributed to metabolic factors in the whole population of China increased from 38.01/100 000 and 944.68/100 000 in 1990 to 103.34/100 000 and 1 972.50/100 000 in 2019, respectively. Compared with 1990, in 2019, the mortality rate of ischemic heart disease, DALY rate and corresponding standardized indicators attributed to metabolic factors were significantly higher in males than in females, and higher in the older age group than in the lower age group. In terms of gender, during the period of 1990—2019, the standardized mortality rate of men with IHD attributed to metabolic factors in China was gradually higher than the global level, while the standardized mortality rate of the whole population and women was always lower than the global level. The standardized DALY rates of all three are significantly lower than the global level. In terms of age, the DALY rate attributed to high body mass index in 1990—2019 showed an upward trend and dominated the population, and renal insufficiency gradually became prominent in the elderly population. Conclusion Since 1990, the overall burden of ischemic heart disease in China has shown an upward trend. The burden of ischemic heart disease caused by metabolic factors is increasing, and it is necessary to continue to increase the publicity of ischemic heart disease prevention and control, especially for key groups such as men and the elderly, carry out targeted health management, better guide the formulation of health policies, improve the utilization efficiency of health resources, and optimize the layout and structure of medical services, so as to better meet the public health needs, reduce the burden of ischemic heart disease in China to a greater extent, and help achieve the goal of healthy China.

Background: The global aging population has raised concerns about the fair distribution of elderly care resources. China, as the largest developing country, has made efforts to address population aging challenges. However, equitable distribution of elderly care resources remains a concern. This study analyzed the spatial layout and accessibility of elderly care service facilities (ECSFs) in Xiamen City to improve resource allocation and enhance the elderly care system in China. The findings provide valuable insights for other developing countries and regions seeking to improve their own elderly care resource allocation. Methods: Xiamen City was chosen as the research area due to its unique geographical location and advanced information technology infrastructure. The study examined the spatial distribution, accessibility, and equity of ECSFs. Using Python, point of interest (POI) data were collected and evaluated using the kernel density method and two‐step floating catchment area method. Spatial autocorrelation analysis identified areas of aggregation and dispersion in ECSF accessibility. Results: Xiamen currently has 660 ECSFs, including nursing homes, adult day care centers, home care agencies, and rural elderly care homes. The analysis revealed spatial disparities, with ECSFs clustering primarily in the central area of Xiamen Island. Significant differences in accessibility were found among the four types of ECSFs. Spatial autocorrelation analysis identified cold and hot spot areas, indicating variations in accessibility across regions. Conclusion: Xiamen City has made progress in allocating elderly care resources and constructing service facilities. However, equity in resource allocation remains a concern. Areas with limited accessibility were identified, leading to unequal access to elderly care resources and timely physical care. To address these challenges, decision‐making departments should consider increasing facilities, improving transportation, enhancing macro planning, and improving facility service quality and accessibility. These measures will optimize ECSF accessibility and promote equitable distribution of elderly care resources. [ABSTRACT FROM AUTHOR]

Background: Forecasting the intensity, source, and cost of informal care for older adults in China is essential to establish and enhance policy support systems for informal care within the context of East Asian traditional culture that emphasizes filial piety. This study aims to analyze the current situation and influencing factors for the informal care needs and predict the trends of informal care needs for older adults in China from 2020 to 2040. Methods: Using the CHARLS database from 2015 to 2018, this study first combined a two-part model and a multinomial logit to analyze the influencing factors for the informal care needs of urban-rural older adults in China. Secondly, a multi-state Markov model was constructed to forecast the number of urban-rural older populations in each health state from 2020 to 2040. Finally, based on a microsimulation model, this study predicted the trends of informal care intensity, source, and cost for older adults in urban and rural areas from 2020 to 2040. Results: In 2040, the size of the disabled older population in China will expand further. In rural areas, the total number of disabled people in 2040 (39.77 million) is 1.50 times higher than that in 2020; In urban areas, the total number of disabled people in 2040 (56.01 million) is 2.51 times higher than that in 2020. Compared with 2020, older adults population with mild, moderate and severe disability in 2040 would increase by 87.60%, 101.70%, and 115.08%, respectively. In 2040, the number of older adults receiving low-, medium-, and high-intensity care in China will be 38.60 million, 22.89 million, and 41.69 million, respectively, and older people will still rely on informal care provided by spouses and children (from spouses only: 39.26 million, from children only: 36.74 million, from spouses and children only: 16.79 million, other: 10.39 million). The total cost of informal care in 2040 will be 1,086.65 billion yuan, 2.22 times that of 2020 (490.31 billion yuan), which grows faster than the economic growth rate. Conclusion: From 2020 to 2040, the informal care needs of older people in rural areas will increase first and then decrease due to the demographic structure and rapid urbanization. In contrast, the informal care needs of older people in urban areas will continuously increase from 2020 to 2040, with the growth rate gradually slowing down. This study provides an evidence-based rationale for scientifically measuring the economic value of informal care and reasonably allocating care resources. [ABSTRACT FROM AUTHOR]

Background: With an intensified aging population and an associated upsurge of informal care need in China, there is an ongoing discussion around what factors influence this need among older adults. Most existing studies are cross-sectional and do not focus on older people living in the community. Conversely, this study empirically explores the factors that affect informal care need of Chinese community-dwelling older individuals based on longitudinal data. Methods: This study constructed panel data using the China Health and Retirement Longitudinal Research Study (CHARLS) from 2011 to 2018 for analysis. Generalized linear mixed models were used to analyze the factors affecting reception of informal care, and linear mixed models were used to analyze the factors affecting informal care sources and intensity. Results: During the follow-up period, 7542, 6386, 5087, and 4052 older adults were included in 2011–2018, respectively. The proportion receiving informal care increased from 19.92 to 30.78%, and the proportion receiving high-intensity care increased from 6.42 to 8.42% during this period. Disability (estimate = 4.27, P < 0.001) and living arrangement (estimate = 0.42, P < 0.001) were the critical determinants of informal care need. The rural older adults reported a greater tendency to receive informal care (estimate = 0.14, P < 0.001). However, financial support from children did not affect informal care need (P > 0.05). Conclusions: At present, there is a great demand for the manpower and intensity of informal care, and the cost of informal care is on the rise. There are differences in informal care needs of special older groups, such as the oldest-old, living alone and severely disabled. In the future, the region should promote the balance of urban and rural care service resources, rationally tilt economic support resources to rural areas, reduce the inequality of long-term care resources, improve the informal care support system, and provide a strong community guarantee for the local aging of the older adults. [ABSTRACT FROM AUTHOR]

Objective: This study describes regional differences and dynamic changes in the prevalence of comorbidities among middle-aged and elderly people with chronic diseases (PCMC) in China from 2011–2018, and explores distribution patterns and the relationship between PM2.5 and PCMC, aiming to provide data support for regional prevention and control measures for chronic disease comorbidities in China. Methods: This study utilized CHARLS follow-up data for ≥ 45-year-old individuals from 2011, 2013, 2015, and 2018 as research subjects. Missing values were filled using the random forest machine learning method. PCMC spatial clustering investigated using spatial autocorrelation methods. The relationship between macro factors and PCMC was examined using Geographically and Temporally Weighted Regression, Ordinary Linear Regression, and Geographically Weighted Regression. Results: PCMC in China showing a decreasing trend. Hotspots of PCMC appeared mainly in western and northern provinces, while cold spots were in southeastern coastal provinces. PM2.5 content was a risk factor for PCMC, the range of influence expanded from the southeastern coastal areas to inland areas, and the magnitude of influence decreased from the southeastern coastal areas to inland areas. Conclusion: PM2.5 content, as a risk factor, should be given special attention, taking into account regional factors. In the future, policy-makers should develop stricter air pollution control policies based on different regional economic, demographic, and geographic factors, while promoting public education, increasing public transportation, and urban green coverage. [ABSTRACT FROM AUTHOR]

Objective: This study describes regional differences and dynamic changes in the prevalence of comorbidities among middle-aged and elderly people with chronic diseases (PCMC) in China from 2011–2018, and explores distribution patterns and the relationship between PM2.5 and PCMC, aiming to provide data support for regional prevention and control measures for chronic disease comorbidities in China. Methods: This study utilized CHARLS follow-up data for ≥ 45-year-old individuals from 2011, 2013, 2015, and 2018 as research subjects. Missing values were filled using the random forest machine learning method. PCMC spatial clustering investigated using spatial autocorrelation methods. The relationship between macro factors and PCMC was examined using Geographically and Temporally Weighted Regression, Ordinary Linear Regression, and Geographically Weighted Regression. Results: PCMC in China showing a decreasing trend. Hotspots of PCMC appeared mainly in western and northern provinces, while cold spots were in southeastern coastal provinces. PM2.5 content was a risk factor for PCMC, the range of influence expanded from the southeastern coastal areas to inland areas, and the magnitude of influence decreased from the southeastern coastal areas to inland areas. Conclusion: PM2.5 content, as a risk factor, should be given special attention, taking into account regional factors. In the future, policy-makers should develop stricter air pollution control policies based on different regional economic, demographic, and geographic factors, while promoting public education, increasing public transportation, and urban green coverage. [ABSTRACT FROM AUTHOR]

Objective: This study describes regional differences and dynamic changes in the prevalence of comorbidities among middle-aged and elderly people with chronic diseases (PCMC) in China from 2011-2018, and explores distribution patterns and the relationship between PM 2.5 and PCMC, aiming to provide data support for regional prevention and control measures for chronic disease comorbidities in China., Methods: This study utilized CHARLS follow-up data for ≥ 45-year-old individuals from 2011, 2013, 2015, and 2018 as research subjects. Missing values were filled using the random forest machine learning method. PCMC spatial clustering investigated using spatial autocorrelation methods. The relationship between macro factors and PCMC was examined using Geographically and Temporally Weighted Regression, Ordinary Linear Regression, and Geographically Weighted Regression., Results: PCMC in China showing a decreasing trend. Hotspots of PCMC appeared mainly in western and northern provinces, while cold spots were in southeastern coastal provinces. PM 2.5 content was a risk factor for PCMC, the range of influence expanded from the southeastern coastal areas to inland areas, and the magnitude of influence decreased from the southeastern coastal areas to inland areas., Conclusion: PM 2.5 content, as a risk factor, should be given special attention, taking into account regional factors. In the future, policy-makers should develop stricter air pollution control policies based on different regional economic, demographic, and geographic factors, while promoting public education, increasing public transportation, and urban green coverage., (© 2024. The Author(s).)