Chinese Longitudinal Healthy Longevity Survey Research Articles

Development of a machine learning-based risk assessment model for loneliness among elderly Chinese: a cross-sectional study based on Chinese longitudinal healthy longevity survey.

Loneliness is prevalent among the elderly and has intensified due to global aging trends. It adversely affects both mental and physical health. Traditional scales for measuring loneliness may yield biased results due to varying definitions. The advancements in machine learning offer new opportunities for improving the measurement and assessment of loneliness through the development of risk assessment models. Data from the 2018 Chinese Longitudinal Healthy Longevity Survey, involving about 16,000 participants aged ≥ 65 years, were used. The study examined the relationships between loneliness and factors such as functional limitations, living conditions, environmental influences, age-related health issues, and health behaviors. Using R 4.4.1, seven assessment models were developed: logistic regression, ridge regression, support vector machines, K-nearest neighbors, decision trees, random forests, and multi-layer perceptron. Models were evaluated based on ROC curves, accuracy, precision, recall, F1 scores, and AUC. Loneliness prevalence among elderly Chinese was 23.4%. Analysis identified 15 evaluative factors and evaluated seven models. Multi-layer perceptron stands out for its strong nonlinear mapping capability and adaptability to complex data, making it one of the most effective models for assessing loneliness risk. The study found a 23.4% prevalence of loneliness among elderly individuals in China. SHAP values indicated that marital status has the strongest evaluative value across all forecasting periods. Specifically, elderly individuals who are never married, widowed, divorced, or separated are more likely to experience loneliness compared to their married counterparts.

Association between functional disability and mental health among Chinese older adults: Examining the moderating effects of social participation and physical exercise.

Functional disability significantly burdens healthcare services, negatively affecting older adults' social interaction and quality of life. This study aims to identify the association between functional disability and mental health, and examine the moderating effects of social participation and physical exercise on the association. The data were drawn from 2018 wave of Chinese Longitudinal Healthy Longevity Survey, and ordinary least squares regression model was exploited to explore the association between functional disability and mental health. Activity of daily living (ADL) disability negatively predicted mini-mental state examination (MMSE) score. Furthermore, social participation and physical exercise moderated the association between ADL disability and MMSE score. The results highlight the importance of social participation and physical exercise for the older adults with ADL disability.

Body mass index, waist circumference, hip circumference, abdominal volume index, and cognitive function in older Chinese people: a nationwide study

BackgroundNumerous studies have indicated an obesity paradox in observational research on aging health, where being normal weight or underweight adversely affects cognitive function, while moderate obesity may offer protective benefits. This study aims to investigate the association between body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), abdominal volume index (AVI), and the joint effect of BMI and HC on cognitive impairment in older Chinese people.MethodsA total of 10,579 participants aged 65 years and older from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) were included in this cross-sectional study. BMI, WC, HC, WHtR, WHR, and AVI were calculated from height, weight, WC, and HC measurements, where weight, WC, and HC were obtained by direct measurement. Mini-Mental State Examination was used to assess cognitive impairment. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated using binary logistic regression. Non-linear correlations were investigated using restricted cubic spline curves.ResultsIn multivariate logistic regression models fully adjusted for confounding variables, our analyses showed significant negative associations of WC [OR 0.93 (95%CI 0.88–0.98), P = .012], HC [OR 0.92 (95%CI 0.87–0.97), P = .004], lower WHR (Q2) [OR 0.85 (95%CI 0.72-1.00), P = .044], and AVI [OR 0.93 (95%CI 0.88–0.98), P = .011] with cognitive impairment. Nonlinear curve analysis showed that the risk of cognitive impairment was lowest when the BMI was about 25.5 kg/m², suggesting that the optimal BMI for older Chinese people to maintain good cognitive ability may be in the overweight range. In addition, there was a non-linear “N” shaped relationship between HC and cognitive impairment, with HC having the highest risk of cognitive impairment at about 82 cm and the lowest risk at about 101 cm. The joint effects analysis indicated that the lowest risk was observed among those with normal or higher BMI but higher HC compared with participants with normal BMI levels and lower HC levels.ConclusionIn older Chinese people, a low-waisted and high-hip circumference body figure is favorable for cognitive function in older people. It also found a significant association between AVI and cognitive impairment. The joint analysis of BMI and HC suggests that maintaining a normal or higher BMI with a higher HC may be more conducive to maintaining good cognitive function.

Metrics of physiological network topology are novel biomarkers to capture functional disability and health.

Physiological networks are highly complex, integrating connections among multiple organ systems and their dynamic changes underlying human aging. It is unknown whether individual-level network could serve as robust biomarkers for health and aging. We used personalized network analysis to construct single sample network and examine the associations between network properties and functional disability in the Rugao Longevity and Aging Study (RuLAS), the China Health and Retirement Longitudinal Study (CHARLS), the Chinese Longitudinal Healthy Longevity Survey (CLHLS), and the National Health and Nutrition Examination Survey (NHANES). We observed impairments in interconnected physiological systems among long-lived adults in RuLAS. Single sample network analysis was applied to reflect the co-occurrence of these multi-system impairments at the individual level. The ADL-disabled individuals' networks exhibited notably increased connectivity among various biomarkers. Significant associations were found between network topology and functional disability across RuLAS, CHARLS, CLHLS and NHANES. Additionally, network topology served as novel biomarkers to capture risks of incident ADL disability in CHARLS. Furthermore, these metrics of physiological network topology predicted mortality across four cohorts. Sensitivity analysis demonstrated that prediction performance of network topology remained robust, regardless of the chosen biomarkers and parameters. These findings showed that metrics of network topology were sensitive and robust biomarkers to capture risks of functional disability and mortality, highlighting the role of single sample physiological networks as novel biomarker for health and aging.

Relationship Between Primary Caregiving Type and a Peaceful End-Of-Life Experience Among Older Adults in China

ABSTRACT Few studies have compared pain management provided by informal and formal caregivers of older adults in China at the end of life. This study aims to address this gap by investigating the association between formal and informal care and painfulness at the end of life among older adults in China. Specifically, the study focuses on the influence of various types of informal care. Data were obtained from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) conducted from 2002 to 2018, which is the largest nationally representative study of older adults in China, with a sample size of 21,849 deceased participants. Results from multiple logistic regressions suggest that informal care is associated with a more painful end-of-life experience compared to formal care, with care provided by adult children being a more favorable option within informal care. These findings underscore the urgent need to prioritize education on death and dying, improve the formal care system, and enhance professionalism within informal care.

The relationship between leisure activity participation and cognitive function among older Chinese adults: the differences across gender and age

As population aging increased globally, this study aimed to examine the relationship between leisure activity participation and cognitive function in the older Chinese population and the gender and age differences in this relationship. A total of 12526 individuals aged 60 years and older from the 2018 Chinese Longitudinal Healthy Longevity Survey were obtained for this study. Multiple linear regression analysis was used to explore the relationship. This study found productive, physical, intellectual, recreational and social activities were associated with cognitive function. Males enjoyed extra benefits from recreational activities compared with females. Females enjoyed extra benefits from productive activities and social activities compared with males. Older age enjoyed extra benefits from productive activities, physical activities, intellectual activities, recreational activities, social activities in comparison with younger age. Thus, Chinese older adults need to make efforts to increase the time and variety of leisure activities, especially for the oldest old. Compared with other types of leisure activities, it’s more important for old men to participate in recreational activities, and for old women to participate in productive activities and social activities.

Family care and predictors of the disabled elderly in China: A cross-sectional study based on the Anderson model.

In light of China's progressively aging population, family care with the "warmth of affection" has always been an irreplaceable form of care that meets the wishes of the majority of disabled elderly to enjoy their twilight years comfortably. Data from a follow-up survey on the influencing factors of the Chinese Longitudinal Healthy Longevity Survey from 2018 and the Anderson Model was used as a theoretical framework to analyze the influencing factors using a binary logistic regression model. Children were the main providers of care services among disabled elderly in family care. Family care for disabled elderly was influenced by the combined effects of age (P < 0.01), gender (P < 0.05), marital status (P < 0.01), number of children (P < 0.01), housing ownership (P < 0.05), primary carer preference (P < 0.05), and self-assessed health (P < 0.01) were jointly affected. As a result, it's critical to set up a strong social support network that is focused on family caregiving and includes tailored interventions based on the requirements of disabled elderly and family caregivers.

Development of a Frailty Prediction Model Among Older Adults in China: A Cross-Sectional Analysis Using the Chinese Longitudinal Healthy Longevity Survey.

To identify the risk factors associated with frailty among older adults in China and develop a predictive model for assessing their frailty risk. Secondary cross-sectional analysis. The 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) provided data for this study. A total of 9006 participants were included in the analysis. Their general demographic, socioeconomic status and health behaviour risk factors were collected in the CLHLS. Frailty was assessed using the Frailty Index. A visual nomogram model was constructed based on independent predictors identified using multivariate analysis. The nomogram's discrimination and calibration capabilities were evaluated using the C-statistics and calibration curves. A 1000-times resampling enhanced bootstrap method was performed for internal validation of the nomogram. The results showed that living in rural settings, having a primary education level, having a spouse, having basic living security, smoking, drinking, exercising and social activities were protective factors against frailty. Increasing age, being underweight or obese, adverse self-assessed economic status and poor sleep quality were risk factors of frailty. The AUC values of the internal validation set were 0.830. The calibration curve was close to ideal. The Brier score was 0.122. The above results showed that the nomogram model had a good predictive performance. A simple and fast frailty risk prediction model was developed in this study to help healthcare professionals screen older adults at high risk of frailty in China. The frailty risk prediction model will assist healthcare professionals in risk management and decision-making and provide targeted frailty prevention interventions. Screening high-risk older adults and early intervention can reduce the risk of adverse outcomes and save medical expenses for older adults and society, thereby realising cost-effective planning of health resources and healthy ageing. No patient or public contribution. This study was a cross-sectional, secondary analysis of the CLHLS data.

Household structure and dietary diversity among older adults in rural and urban China: a cross-sectional study

BackgroundHousehold structure can significantly affect older adults’ eating behaviours and diet quality. However, the difference in dietary diversity in various household structures in urban and rural has rarely been investigated. This study aimed to investigate the association between household structure and dietary diversity among older Chinese adults and examine whether the association differed by urban and rural.MethodsThe study used data from the 2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The participants were individuals aged 60 and over with available dietary and household structure data. Dietary diversity was defined as ‘high’ if respondents had a dietary diversity score (DDS) above the mean value. Household structures were classified into four mutually exclusive categories: (1) living alone; (2) spouse only; (3) at least with a great/grandchild(ren); (4) non-empty-nested. Binary logistic regression was applied to investigate the association between household structures and dietary diversity.ResultsNon-empty-nested older adults had the highest probability (OR = 1.64, 95% CI = 1.44–1.87) of having high dietary diversity. People who only lived with their spouse and at least lived with a great/grandchild(ren) were 1.45 (OR = 1.45, 95% CI = 1.23–1.71) and 1.23 (OR = 1.23, 95% CI = 1.08–1.41) times as likely to have diverse diets than older adults who lived alone. The difference in dietary diversity among various household structures is more evident in urban than rural areas. Solo-living older adults were the most disadvantaged regarding dietary diversity in urban and rural areas.ConclusionsHousehold structures are significantly associated with dietary diversity among older Chinese adults aged 60 years and over. The findings emphasise the need to reduce nutritional inequality, encourage dietary diversity, and consider both the household structures and residences when providing health intervention programs to the older population.

Widowhood Shock, Family Reconstruction, and Mild Cognitive Impairment Among Older Adults: A Prospective Cohort Study.

Mild cognitive impairment (MCI), especially among widowed older adults, is increasingly urging public concern. This study aimed to investigate the association of widowhood, remarriage, and widowed life characteristics with the MCI risk among Chinese older adults. With an average age of 86.49 ± 10.20, a sample of 5377 participants aged between 65 and 116 was collected from four waves of the Chinese Longitudinal Healthy Longevity Survey between 2008 and 2018. Cox proportional hazards models and restricted cubic spline models were employed to estimate and plot the associations. Results showed that widowhood is associated with an increasing MCI risk, which could not be alleviated by remarriage. This negative impact was pronounced among women and those at older age. The association of living alone duration after widowhood and MCI onset displayed an inverse U-shape, with a peak risk at the 10th year. These findings have practical implications for pointing out the most vulnerable groups to MCI.

Developmental trajectories and heterogeneity of social engagement among Chinese older adults: a growth mixture model

BackgroundSocial engagement is closely related to well-being among older adults. However, studies on the changing trajectory and influencing factors (especially time-varying factors) of social engagement are limited. This study aimed to examine the social engagement trajectory of older Chinese adults and explore its time-fixed and time-varying factors, thus providing evidence for the development of strategies to promote a rational implementation for healthy aging.MethodsThis study included 2,195 participants from a subset of four surveys from the Chinese Longitudinal Healthy Longevity Survey conducted from 2008 to 2018 (with the latest survey completed in 2018), with follow-ups conducted approximately every three years. Growth mixture modeling was used to explore the social engagement trajectory of older adults and the effects of time-varying variables. In addition, multinomial logistic regression was employed to analyze the association between time-fixed variables and latent classes.ResultsThree distinct trajectories of social engagement among older adults in China were identified: slow declining (n = 204; 9.3%), which meant social engagement score decreased continuously, but social engagement level improved; slow rising (n = 1,039; 47.3%), marked by an increased score of social engagement, but with an depressed engagement level; and middle stabilizing (n = 952; 43.4%), which meant social engagement score and engagement level remained quite stable. A time-fixed analysis indicated that age, marital status, educational level, and annual family income had a significant impact on social engagement (P < 0.05). In contrast, the time-varying analysis showed that a decline in functional ability, insufficient exercise (means no exercise at present), deteriorating self-reported health and quality of life, negative mood, monotonous diet, and reduced community services were closely related to the reduction in social engagement levels (P < 0.05).ConclusionThree trends were observed at the social engagement level. Older adults with initially high levels of social engagement exhibited a continuous upward trend, whereas those with initially low levels experienced a decline in their social engagement, and those with initially intermediate levels remained quite stable. Considering the primary heterogeneous factors, it is imperative for governments to enhance basic services and prioritize the well-being of older adults. Additionally, families should diligently monitor the emotional well-being of older adults and make appropriate arrangements for meals.

The Impact of Social Participation on Frailty among Older Adults: The Mediating Role of Loneliness and Sleep Quality.

Frailty has become a common health issue among older adults, imposing a burden on both society and individuals. The relationship between social participation and frailty has received widespread attention, but the mechanism remains to be explored. The aim of this study is to explore the impact of social participation on frailty among older adults and to analyze the mediating role of loneliness and sleep quality, providing suggestions to alleviate frailty. Data related to social participation, loneliness, sleep quality, and frailty from 7779 older adults were collected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS 2018). The chain mediation model was conducted to explore the relationship between variables, and the Bootstrap method was used to examine the path coefficients. Social participation negatively affected frailty (β = -0.00391049, 95% CI = [-0.042296, -0.035465]); the indirect effect of social participation on frailty mediated by loneliness was -0.0019505 (95% CI = [-0.002551, -0.001371]); the indirect effect of social participation on frailty mediated by sleep quality was -0.0011104 (95%CI = [-0.001692, -0.000557]); the effect mediated by both loneliness and sleep quality was -0.0004263 (95% CI = [-0.000593, -0.000304]). Social participation negatively affected frailty. Loneliness and sleep quality not only mediated independently, but also played a chain mediating role. This suggested that encouraging older adults to engage in more social participation, reducing loneliness, and improving sleep quality are feasible measures to improve frailty.

Were there any missing mediators between visual impairment and anxiety symptoms? Results from Chinese Longitudinal Healthy Longevity Survey.

Visual impairment, encompassing low visual acuity and visual field loss, significantly impacts the older adult population worldwide, leading to increased disability and mortality risks. Recent studies suggest a strong association between visual impairment and anxiety, particularly among older adults. This study aims to explore the relationship between visual impairment and anxiety symptoms in older adult individuals in China, and to investigate potential mediating factors. Data for this study were derived from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), including 11,702 participants aged 65 and older. Visual impairment was assessed through self-reported visual function, while anxiety symptoms were measured using the 7-item Generalized Anxiety Disorder scale (GAD-7). Additional assessments included sleep quality and duration, exercise status, and dietary diversity. Logistic regression models and mediation analysis were employed to explore associations and mediating effects. The findings indicate that visual impairment is significantly associated with increased anxiety symptoms among the older adult (OR = 1.51, 95% CI: 1.32-1.72, p < 0.001). Mediation analysis revealed that sleep quality, dietary diversity score (DDS), and plant-based DDS significantly mediated the relationship between visual impairment and anxiety. In contrast, sleep duration, exercise, and animal-based DDS did not show significant mediating effects. Visual impairment is a crucial predictor of anxiety symptoms in the older adult. Improving sleep quality and promoting a diverse plant-based diet may mitigate anxiety symptoms in this population. Interventions targeting these areas could enhance the mental health and quality of life of older adult individuals with visual impairment.

Social isolation and likelihood of becoming centenarians: evidence from the Chinese longitudinal healthy longevity survey

BackgroundSocial isolation, defined as an individual’s lack of social connections, is particularly prevalent among older adults. However, its association with health outcomes among the oldest-old population (aged 80 and above) was understudied.AimsTo examine the association between social isolation and the likelihood of becoming a centenarian among the oldest-old people in China, aiming to provide novel insights into promoting healthy aging and longevity.MethodsUsing data from The Chinese Longitudinal Healthy Longevity Survey, conducted in 22 provinces in mainland China since 1998, we performed a community-based, prospective nested case-control study. The primary outcome was survival to the age of 100 by 2018 (the end of follow-up). Information on social isolation and other covariates was collected via a questionnaire at baseline. The degree of social isolation was categorized as low, moderate, and high. Included (n = 5,716) were 1,584 identified centenarians and 4,132 controls (deceased before reaching 100 years), matched by age, sex, and year of entry. A conditional logistic regression model was used to evaluate the association between social isolation and the likelihood of becoming a centenarian, adjusting for demographic factors, lifestyle factors, chronic disease, potential disability, optimistic attitude, and perceived loneliness.ResultsIndividuals with the highest social isolation score had lower odds of becoming centenarians (adjusted OR:0.82; 95% CI: 0.68, 0.98), relative to those with the least social isolation (P-value < 0.05), and this association persisted in sensitivity analyses. The association was more pronounced among ever smokers, compared to never smokers (P-value = 0.001). We did not observe significant interactions between social isolation and other covariates (P-value > 0.05 for all).ConclusionsThis study highlights the inverse association between social isolation and the likelihood of becoming a centenarian, emphasizing the need for public health initiatives to combat isolation in the older population.

More cognitive gains from social activity in the oldest-old: evidence from a 10-year longitudinal study.

Previous research has indicated that engagement in social activities has proven advantageous for diminishing the likelihood of cognitive decline. However, no study has examined whether such cognitive benefits were to a similar extent for the young-old, the old-old, and the oldest-old groups. The purpose of this research was to determine whether aging would have an impact on the changes in cognitive function that would occur in older adults with varying degrees of social involvement. The sample for this study comprised 4,481 older adults who participated in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) during the waves spanning from 2008 to 2018. At baseline, participants were classified into the young-old (60-69 years; M age = 66.66; SD = 1.87), the old-old (70-79 years; M age = 74.21; SD = 2.82), and the oldest-old (80 years or older; M age = 86.46; SD = 5.71) groups. The level of cognitive function decreased as participants aged. Importantly, compared to those lacking social activities, individuals who were got involved in social engagement at baseline had slower rates of cognitive decline over time. Furthermore, compared with the young-old group and the old-old group, the impact of social activity engagement on slowing cognitive decline was more salient for the oldest-old group. Active engagement in social activities can slow age-related cognitive decline, particularly for the oldest-old group. To preserve cognitive function with aging, attention and resources should be allocated to encourage social activity engagement.

Projections of Socioeconomic Costs for Individuals with Dementia in China 2020-2050: Modeling Study.

Previous estimates on future socioeconomic costs of dementia in China are inconsistent, and the main drivers of these costs are unclear. This study projected future socioeconomic costs (healthcare, formal social care, and informal care costs) and value of quality adjusted life years (QALYs) lost to dementia in China and assessed drivers of socioeconomic costs. Based on our prior projection on dementia cases to 2050 by a Markov model, we forecasted future socioeconomic costs and the value of QALYs from a societal perspective, utilizing the China Health and Retirement Longitudinal Study and the Chinese Longitudinal Healthy Longevity Survey. In our main analysis, dementia incidence increased by 2.9% annually, while sensitivity analyses considered a flat or 1.0% annual decrease in the temporal trend of dementia incidence. Furthermore, we decomposed socioeconomic costs changes (2018 US$) into population growth, population aging, dementia prevalence and average socioeconomic costs per case. The annual socioeconomic costs and value of QALYs lost to dementia will reach $1,233 billion and $702 billion by 2050. If dementia incidence stays constant or decreases by 1.0% annually, the costs and QALYs would respectively decrease by 34% or 43% in 2050. Informal care is currently, and projected to remain, the largest share of socioeconomic costs. Population aging and rising dementia prevalence will mainly drive the growth in socioeconomic costs through 2050. Dementia casts an increasingly large economic burden on Chinese society, mainly driven by fast aging population and growing dementia prevalence.

Interaction between tea consumption and genes on activities of daily living disability in older adults.

The effects of tea consumption on delaying aging and the onset of age-related disabilities have been reported; however, it is unclear whether these benefits are impacted by genes. This study aimed to examine the associations between tea consumption and activities of daily living (ADL) and explore the role of genetic factors. Data from 46,487 older adults aged 64-105 who participated in at least one data wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) conducted in 2002, 2005, 2008, 2011, 2014, and 2018 were analyzed. Genetic data were produced using the Affymetrix Axiom™myDesign™ (384-format) Human Genotyping Array. The generalized estimation equation and multiple logistic regression models were constructed to examine the effects of tea consumption, polygenic risk score, and their interactions on ADL. Tea consumption was related to reduced ADL decline-the effect was statistically significant among men but not women. A significant interaction between tea consumption and polygenic risk score (PRS) was observed. Tea consumption was associated with a decreased risk of ADL disability only among individuals with a low PRS. These findings indicate that tea consumption plays a role in preventing disability in older adults with low polygenic risk.

The Relationship between Plant-Based Diet Indices and Sleep Health in Older Adults: The Mediating Role of Depressive Symptoms and Anxiety.

The goal of our research was to determine the effects of plant-based dietary patterns on sleep health among older adults and to examine the parallel mediated effects of anxiety and depression. This investigation utilized data obtained from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) and contained 6853 participants. Logistic regression and the restricted cubic splines (RCSs) model were employed to examine how plant-based dietary patterns affect sleep health. Additionally, Amos 26.0 was used to construct a structural equation model to examine the parallel mediated effects of anxiety and depression. A higher plant-based diet index (PDI) was connected to higher odds of better sleep quality (OR = 1.209, 95% CI: 1.039-1.407) and sleep duration (OR = 1.241, 95% CI: 1.072-1.437). Conversely, an elevated unhealthy plant-based diet index (uPDI) was correlated with a lower likelihood of sleep quality (OR = 0.678, 95% CI: 0.574-0.800) and sleep duration (OR = 0.762, 95% CI: 0.647-0.896). The RCSs regression further identified a significant dose-response relationship. Mediation analysis confirmed that anxiety and depression partially mediate the relationship between plant-based diets and sleep health. Our study exhibited significant correlations between plant-based diets and sleep health in the elderly. Depression and anxiety were determined as parallel mediators between plant-based diets and sleep health. Controlling early dietary patterns and affective disorder could help improve sleep quality in older adults.

Enhancing the convenience of frailty index assessment for elderly Chinese people with machine learning methods.

Frailty is a state that is closely associated with adverse health outcomes in the aging process. The frailty index (FI), which measures frailty in terms of cumulative deficits, has been widely used for frailty assessment in elderly people, and its advantage of self-reported information collection makes it applicable to a broader group of elderly people. Our study aims to simplify the Frailty Index Assessment Scale, while maintaining its reliability and accuracy, to easily and quickly assess frailty in elderly people. In this study, participants (age ≥ 65 years) from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which had 13,339, 372 and 1214 participants in 2008, 2011, and 2014, respectively, were used. The 2008 dataset was split into 80% for training and 20% for internal validation, and the data from 2011 to 2014 as external validation. In order to obtain effective predictors, we used Lasso regression, Boruta algorithm and random forest classifier score for feature selection. We used six models for predictive model construction and evaluated the models in the validation dataset. Model performance was measured by area under the curve (AUC), accuracy and F1 score. Logistic regression was found to be the best performing and most interpretable algorithm with AUC, accuracy and F1 of 0.974, 0.932 and 0.880 for the validation dataset, respectively. The AUCs for the external independent validation dataset were 0.963 and 0.977, respectively. Subgroup analysis showed that the model had good predictive power in both males and females. The predictive power was stronger among the elderly people over 80 years old, with AUC, accuracy and F1 of 0.973,0.914, and 0.893, respectively. The model also obtained good predictive power in the case of FI measured by different indicators. The model showed good robustness in the follow-up assessment of frailty status in elderly people, with the AUC remaining above 0.95 and accuracy above 0.9 over the long-term follow-up. Using machine learning techniques, we have successfully developed a simple frailty assessment prediction model based on 10 key features to shorten the frailty assessment scale with near full-scale accuracy. A user-friendly website was created to facilitate the application of this prediction model ( https://healthy-aging.shinyapps.io/Frailty_Assessment/ ).

Risk assessment of PM2.5 from fossil energy consumption on the respiratory health of the elderly

Air pollution mainly comes from fossil energy consumption (FEC), and it brings great threat to public health. The respiratory system of the elderly is highly susceptible to the effects of air pollution due to the decline in body functions. PM2.5 is a major component of air pollution, so the study of the impact of PM2.5 generated by FEC on the respiratory health of the elderly is of great significance. The existing studies have focused more on the effect of PM2.5 on mortality, and this paper is a useful addition to the existing studies by examining the effect of PM2.5 from FEC on the health of the elderly from the perspective of prevalence. In this paper, the binary Logistic regression model was used to calculate the exposure-response relationship coefficient for respiratory health in older adults using the data in 2018 from the Chinese Longitudinal Healthy Longevity Survey. And referring to the Dynamic Projection model for Emissions in China, the changes in the number of older persons suffering from respiratory diseases due to PM2.5 from FEC in the baseline scenario, the clean air scenario, and the on-time peak-clean air scenario were predicted. The results indicated that: (1) PM2.5 from FEC mainly came from coal; (2) PM2.5 from FEC was detrimental to the respiratory health of the elderly, and older seniors were more affected as they age; (3) In the on-time peak-clean air scenario, the number of elderly people suffering from respiratory diseases due to PM2.5 from FEC was growing at the slowest rate. Based on the above results, this paper raised recommendations for reducing the effect of PM2.5 from FEC on the health of the elderly.