Association Between Nonalcoholic Fatty Liver Disease and the Risk of Cardiovascular Disease in the Middle-Age and Elderly Population of Northern China: A Cross-Sectional Study.

Background: Nonalcoholic fatty liver disease (NAFLD) has become a major global health burden, which increases the risk of extra-hepatic complications such as type 2 diabetes mellitus (T2DM), dyslipidemia, metabolic syndrome (MetS), and cardiovascular disease (CVD). However, NAFLD remains underappreciated and underdiagnosed. Our study aimed to explore the prevalence of NAFLD and the association between NAFLD and CVD events among adults aged 40 and older in Northern China. Methods: This study was conducted in the Shijingshan district of Beijing, China from November 2011 to August 2012. A total of 18891 subjects were recruited in the study. The information including demographical information, lifestyle, previous history of diabetes, hypertension, dyslipidemia, CVD, and liver disease were gathered. Data on physical examination, blood lipid profile, fasting blood glucose, and 2-hour blood glucose were recorded. Determination of MetS was according to T2DM guideline of Chinese Diabetes Society (2020 edition). The association between CVD and NAFLD was evaluated by multivariate logistic regression. Results: The prevalence of NAFLD was 15.2%. After adjustment for age, smoking status, alcohol intake, WC, hypertension, dyslipidemia and hyperglycemia, the odds ratios (ORs) of CVD in men were 1.622 (95%CI: 1.345-1.957) and 1.990 (95%CI: 1.709-2.316) in women with NAFLD, compared with the subjects without NAFLD. Conclusions: NAFLD is independently associated with increased risk of CVD development.

Higher triglyceride­glucose index is associated with increased risk of stroke among middle-aged and elderly Chinese: a national longitudinal study.

Stroke is a severe cerebrovascular disease. This study aimed to determine the association between triglyceride­glucose (TyG) index and stroke among middle-aged and elderly Chinese. Data was extracted from China Health and Retirement Longitudinal Study survey 2015 and survey 2018. Logistic regression, trend test and subgroup analysis were conducted to assess the association. Possible nonlinear relationships were explored with restricted cubic spline (RCS). Propensity score matching (PSM) was conducted to attenuate the effect of confounding factors. ORs of stroke was positively associated with TyG index. The ORs in RCS analysis also increased with the rising TyG, though p for non-linearity was bigger than 0.05. After PSM, the ORs in the full adjusted models were 1.28 (1.01, 1.62). TyG was suggested as an independent risk factor for stroke in the middle aged and elderly Chinese.

Urban resilience reduces depressive symptoms among middle-aged and elderly adults: A multidimensional analysis based on China longitudinal healthy longevity survey.

With the rapid urbanization and aging population, depression has become a severe public health issue globally, affecting millions of individuals and significantly impacting their quality of life and healthcare costs. Urban resilience refers to a city's ability to absorb, recover, and prepare for future shocks, ensuring sustainable development despite challenges. This study aims to explore the impact of urban resilience on depressive symptoms among middle-aged and elderly adults. Using data from the China Health and Retirement Longitudinal Study (CHARLS), we analyzed five dimensions of urban resilience: economic, social, ecological, institutional, and infrastructural resilience. The results of cox proportional hazards model indicate that high levels of urban resilience significantly reduce the risk of depressive symptoms (HR = 0.875, 95% CI: 0.832-0.920, P < 0.001). Specifically, economic resilience (HR = 0.883, 95% CI: 0.846-0.921, P < 0.001), social resilience (HR = 0.916, 95% CI: 0.876-0.958, P < 0.001), ecological resilience (HR = 0.670, 95% CI: 0.516-0.869, P = 0.003), institutional resilience (HR = 0.922, 95% CI: 0.886-0.960, P < 0.001), and infrastructural resilience (HR = 0.875, 95% CI: 0.826-0.926, P < 0.001) all show significant negative correlations with depressive symptoms. Furthermore, the mitigation of depressive symptoms risk resulting from improved urban resilience disproportionately benefits vulnerable groups and those with healthy living habits. These findings provide scientific evidence for urban planning and policy formulation, contributing to the promotion of mental health and healthy aging among middle-aged and elderly populations.

Exploring the effects of combining health qigong and dance on working memory in middle-aged and elderly women: A preliminary investigation.

OBJECTIVE: Cognitive decline represents a critical clinical and public health issue that adversely affects the quality of life for older patients and their families. This concern was exacerbated by the reduced engagement in outdoor activities among seniors during the COVID-19 pandemic, presenting substantial challenges to aging societies. The objective of this study was to investigate the impact of health qigong combined with Tibetan dance on working memory in middle-aged and elderly women, and to determine its potential as a preventive strategy against cognitive disorders. METHODS: A pilot study was conducted to compare the effects of a Health Qigong exercise intervention with those of everyday life and sports routines. The primary outcome measure was working memory assessed using a 2-Back working memory task research paradigm. Between July and September 2021, a total of 33 women were divided into four groups: two middle-aged groups (N = 18, with 8 women in the experimental group and 10 in the control group) and two elderly groups (N = 15, with 7 in the experimental group and 8 in the control group). Participants in the experimental groups underwent a 10-week intervention, consisting of three 60-min sessions per week. Each session included a warm-up, Health Qigong combined with Tibetan dance, and a cool-down. Throughout the study, all participants continued their daily routines. Response times and error rates were analyzed using a mixed-design repeated-measures analysis of variance. RESULTS: A simple effects analysis revealed that Health Qigong combined with Tibetan dance significantly enhanced 2-Back response time and error rate in the middle-aged group. In contrast, the 2-Back error rate significantly increased in the elderly control group that did not receive the intervention (p < 0.05). CONCLUSION: Health Qigong demonstrates beneficial effects on middle-aged and elderly women. Combining Health Qigong with dance may serve as a preventive measure against cognitive disorders. This pioneering study conducted during the COVID-19 pandemic, assesses the new possibility of Health Qigong and dance, with the objective to offer more diverse indoor exercise options for middle-aged and elderly women.

An application of the Bayesian network model based on the EN-ESL-GA algorithm: Exploring the predictors of heart disease in middle-aged and elderly people in China.

BACKGROUND: The morbidity and mortality of heart disease are increasing in middle-aged and elderly people in China. It is necessary to explore relationships and interactive associations between heart disease and its risk factors in order to prevent heart disease. OBJECTIVE: To establish a Bayesian network model of heart disease and its influencing factors in middle-aged and elderly people in China, and explore the applicability of the elite-based structure learner using genetic algorithm based on ensemble learning (EN-ESL-GA) algorithm in etiology analysis and disease prediction. METHODS: Based on the 2013 national tracking survey data from China Health and Retirement Longitudinal Study (CHARLS) database, EN-ESL-GA algorithm was used to learn the Bayesian network structure. Then we input the data and the learned network structure into the Netica software for parameter learning and inference analysis. RESULTS: The Bayesian network model based on the EN-ESL-GAalgorithm can effectively excavate the complex network relationships and interactive associations between heart disease and its risk factors in middle-aged and elderly people in China. CONCLUSIONS: The Bayesian network model based on the EN-ESL-GA algorithm has good applicability and application prospect in the prediction of diseases prevalence risk.

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Objective: To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2 (T2DM) in the middle-aged and elderly populations based on the results of a Meta-analysis, and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service. Methods: Cohort studies evaluating T2DM risks were identified in Chinese and English databases. The logistic model utilized Meta-combined effect values such as the odds ratio (OR) to derive ß, the partial regression coefficient, of the logistic model. The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model. Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service. The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7602 individuals who did not have T2DM at their baseline medical checkups done at the community health center. This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people. Results: A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM, including age, central obesity, smoking, physical inactivity, impaired fasting glucose, a reduced level of high-density lipoprotein cholesterol (HDL-C), hypertension, body mass index (BMI), triglyceride glucose (TYG) index, and a family history of diabetes, with the OR values and 95% confidence interval (CI) being 1.04 (1.03, 1.05), 1.55 (1.29, 1.88), 1.36 (1.11, 1.66), 1.26 (1.07, 1.49), 3.93 (2.94, 5.24), 1.14 (1.06, 1.23), 1.47 (1.34, 1.61), 1.11 (1.05, 1.18), 2.15 (1.75, 2.62), and 1.66 (1.55, 1.78), respectively, and the combined ß values being 0.039, 0.438, 0.307, 0.231, 1.369, 0.131, 0.385, 0.104, 0.765, and 0.507, respectively. A total of 37 studies reported the incidence rate, with the combined incidence being 0.08 (0.07, 0.09) and the parameter α being -2.442 for the logistic model. The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7602 individuals who had medical checkups and were followed up for at least once. External validation results showed that the predictive model had an area under curve (AUC) of 0.794 (0.771, 0.816), accuracy of 74.5%, sensitivity of 71.0%, and specificity of 74.7% in the 7602 individuals. Conclusion: The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.

Effects of Different Aerobic Exercises on Blood Lipid Levels in Middle-Aged and Elderly People: A Systematic Review and Bayesian Network Meta-Analysis Based on Randomized Controlled Trials.

With increasing age, dyslipidemia becomes a common health problem in the middle-aged and elderly population, posing a significant risk of cardiovascular disease. Aerobic exercise, as a non-pharmacological intervention, is considered to be effective in improving blood lipid levels, but the extent to which different types of aerobic exercise affect blood lipids is not clear. This study aims to investigate the effects of 12 different aerobic exercises on total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol in middle-aged and elderly people aged 45 years and over through systematic review and Bayesian network Meta-analysis of randomized controlled trials. We systematically searched relevant databases and included eligible randomized controlled trials. Bayesian network meta-analysis was used to compare the effects of 12 types of aerobic exercise on lipid levels. A total of 487 randomized controlled trials involving middle-aged and elderly people over 45 years old were included. The results of the network meta-analysis showed that all types of aerobic exercise could reduce blood lipid levels compared with no intervention in middle-aged and elderly people. In terms of total cholesterol, triglyceride, and low-density lipoprotein cholesterol, swimming had the most significant effect. For HDL cholesterol, dance showed a better effect. Studies have shown that swimming and dancing have a positive effect on improving blood lipid levels in middle-aged and elderly people. It is recommended to choose the appropriate type of exercise according to personal preference and physical condition.

Exploring the association between sleep duration and cancer risk in middle-aged and older Chinese adults: observations from a representative cohort study (2011-2020).

BACKGROUND: This prospective cohort study aimed to investigate the relationship between sleep duration and cancer incidence among 9996 participants over a median follow-up period of 9 years. METHODS: Participants without cancer at baseline were followed for over 88,790 person-years. The incidence of cancer and sleep duration was self-reported. The relationship between sleep duration and cancer incidence was analyzed using Cox proportional hazards models adjusted for various confounding factors, including age, gender, lifestyle factors, and comorbidities. RESULTS: During the follow-up, 325 participants were diagnosed with incident cancer, resulting in an incidence rate of 20.49 per 1000 person-years. After adjusting for confounders, a total sleep duration of less than 6 h was significantly associated with an increased risk of cancer (HR: 1.27; 95% CI: 1.01-1.61). This association was particularly strong for cancers in the digestive and respiratory systems (HR: 1.41; 95% CI: 1.03-1.93). Longer sleep durations (> 9 h) showed a potential increase in cancer risk, but results were not consistently significant. Age-stratified analyses revealed a similar significant increase in cancer incidence among individuals aged 60 years or younger with less than 6 h of sleep per day, showing a 35% increase in overall cancer risk and an 83% increase in digestive and respiratory system cancer. No significant association was found between nocturnal sleep durations or daytime naps and cancer incidence. However, a significant interaction was observed between daytime naps longer than 30 min and cancer incidence in women (p = 0.041). CONCLUSIONS: We observed that short sleep duration may increase the risk of cancer, particularly cancers in the digestive and respiratory systems. Additionally, while longer sleep durations might also increase cancer risk, this finding requires validation with larger sample sizes.

Dose-response relationship between weekly physical activity level and the frequency of colds in Chinese middle-aged and elderly individuals.

Background: Engaging in appropriate physical activity can significantly lower the risk of various diseases among middle-aged and older adults. Investigating optimal levels of physical activity (PA) is crucial for enhancing the health of this demographic. This study aims to explore the dose-response relationship between weekly PA levels and the frequency of colds among Chinese middle-aged and elderly individuals, identifying the necessary PA level to effectively diminish the risk of colds. Methods: We conducted a cross-sectional study using a web-based survey targeting individuals aged 40 and older (n = 1, 683) in China. The survey collected information on PA and the frequency of colds. Data was analyzed using Kruskal-Wallis test and the χ2 test. We explored the dose-response relationship between weekly PA and cold frequency over the past year through an ordered multivariate logistic regression model and a restricted cubic spline model. Results: (1) Brisk walking emerged as the preferred physical exercise for those over 40. The findings suggest that engaging in moderate (odds ratio (OR) = 0.64, P < 0.001, 95% confidence interval (CI) [0.50-0.81]) and high (OR = 0.64, P < 0.001, 95% CI [0.51-0.79]) levels of PA weekly significantly reduces the risk of catching a cold. Individuals with one (OR = 1.47, P < 0.001, 95% CI [1.20-1.80]) or multiple chronic diseases (OR = 1.56, P < 0.001, 95% CI [1.21-2.00]) were at increased risk. Those residing in central (OR = 1.64, P < 0.001, 95% CI [1.33-02.01]) and western China (OR = 1.49, P = 0.008, 95% CI [1.11-02.00]) faced a higher risk compared to their counterparts in eastern China. (2) According to the restricted cubic spline model, adults who experienced one cold in the past year had a weekly PA level of 537.29 metabolic equivalent-minutes per week (MET-min/wk) with an OR value of 1. For those reporting two or more colds, the PA level was 537.76 MET-min/wk with an OR of 1. Conclusions: (1) Brisk walking is the most favored exercise among the Chinese middle-aged and elderly, with the prevalence of colds being affected by the number of chronic diseases and the geographic location. (2) Regular, moderate exercise is linked to a lower risk of colds. To effectively reduce cold frequency, it is recommended that middle-aged and elderly Chinese individuals engage in a minimum of 538 MET-min/wk of exercise.

The relationship between stigma and quality of life in hospitalized middle-aged and elderly patients with chronic diseases: the mediating role of depression and the moderating role of psychological resilience.

Objective: Patients with chronic diseases may have some psychological problems due to their own or surrounding environmental factors, which can adversely affect the patient's illness and life. Given that the number of chronically ill patients in China is currently increasing every year, more research is needed to determine the best ways to manage changes in psychological status and psychological stress responses in chronically ill patients. The researchers constructed a mediated moderation model to explore the impact of stigma on the quality of life of chronically ill patients, as well as the mediating role of depression and the moderating role of psychological resilience. Methods: A stratified sampling method was used to select 363 middle-aged and old-aged patients with chronic diseases aged 45 years and older from the Affiliated Hospital of Zhejiang University for the study. Data were collected from patients with chronic diseases such as cardiac, respiratory, renal, and other chronic diseases using the Cumulative Illness Rating Scale for Geriatrics (CIRS-G), the Stigma Scale for Patients with Chronic Diseases (SSCI), the Patient Health Questionaire-9 (PHQ-9), the Quality of Life Inventory (SF-12), and the Conner-Davidson Resilience Scale (CD-RISC) were collected from patients with cardiac, respiratory, renal, and other chronic diseases. A descriptive analysis was used to describe the sample. Linear regression was used to evaluate the relationship between the variables. Mediation and moderation analyses were used to explore the mediating role of depression and the moderating role of psychological resilience. Results: There was a moderate negative correlation between stigma and quality of life (r = -0.378, P < 0.01). There was a moderate negative correlation between depression and quality of life (r = -0.497, P < 0.01). There was a moderately positive correlation between psychological resilience and quality of life (r = 0.382, P < 0.01). There was a moderate negative correlation between psychological resilience and depression (r = -0.348, P < 0.01). There was a weak negative correlation between psychological resilience and stigma (r = -0.166, P < 0.01). There was a strong positive correlation between stigma and depression (r = 0.607, P < 0.01) The mediation study showed that stigma was a significant predictor of quality of life and that stigma and quality of life were mediated to some extent by depression, with the mediating effect accounting for 67.55% of the total effect. The direct path from stigma to depression is moderated by psychological resilience (ß = -0.0018, P < 0.01). Conclusions: Depression mediates the relationship between stigma and quality of life, while psychological elasticity plays a moderating role between stigma and depression, and when the level of psychological elasticity increases, the more significant the role of stigma on depression. As a physiologically and psychologically vulnerable group, patients with chronic diseases' overall quality of life and mental health should be taken more seriously, and clinical workers should pay timely attention to the psychological and mental conditions of patients with chronic diseases and provide timely and appropriate interventions and therapeutic measures. The relevant results of this study also provide a new perspective for clinical work on psychological intervention for patients with chronic diseases.

Effect of resistance training on inflammatory markers in middle-aged and older adults: A meta-analysis.

BACKGROUND AND OBJECTIVE: A meta-analysis was conducted to evaluate the impact of resistance training on pro-inflammatory cytokines c-reactive protein (CRP), interleukin 6 (IL 6), and tumor necrosis factor- α (TNF- α) in middle-aged and elderly individuals. METHODS: The retrieval period for the Web of Science and other large electronic databases is set by default to March 2022. Both included and excluded researchers are independent examination literature on the impact of resistance exercise on markers of inflammation in the elderly. The physical medical care Evidence Database scale (Physical Therapy Evidence Database, PEDro) was used to evaluate the research quality, and Revmen 5.3 was used to end the index analysis. RESULTS: After a total of four rounds of elimination, 12 items were eventually included. The total sample size for the research was 388 persons. Resistance training substantially reduced CRP levels in middle-aged and older individuals, with SMD = -0.56 and 95 % confidence interval ([-0.78, -0.34], P < 0.00001, correspondingly. Resistance training can successfully lower IL6 concentrations in middle-aged and older adults, although the combined impact is not substantial. SMD = -0.25, 95 % CI [-0.54, 0.04]; P = 0.09. TNF- concentrations did not alter significantly following resistance exercise in middle-aged and older adults. The overall effect was SMD = -0.07, with a 95 % confidence interval [-0.37, 0.23], while P = 0.64. CONCLUSION: Resistance training reduces CRP, IL6, and TNF-α levels among middle-aged and elderly people. However, it has no significant anti-inflammatory effects on TNF-α. Resistance exercise at a moderate level for 3 times / week with a duration of 6-12 weeks or 16-32 weeks, significantly reduced CRP levels. This work contributing to exploring the resistance training program for the elderly to reduce inflammatory markers, and further, providing suggestions for the elderly to participate in resistance training and reduce the concentration of inflammatory markers.

Relationship between Life's Essential 8 and metabolic syndrome among older Americans (NHANES, 2007-2010): navigating biological aging and inflammation.

Background: Metabolic syndrome (MetS) is a global health concern, and it is particularly harmful to middle-aged and elderly individuals. Life Element Eight (LE8), a measure to improve cardiovascular health, may offer benefits for MetS. Herein, we examined the relationship between LE8 and MetS among middle-aged and elderly individuals, and elucidated the role of biological aging and inflammation in this process. Methods: We obtained the LE8 scores of 2,901 Americans, along with their biological aging indicators (Biological age, Phenotypic age, Serum Klotho), and computed their inflammatory indicators SII, DII. Using logistic regression model, we assessed the association among inflammatory markers, Biological aging, LE8 and MetS. Additionally, we generated restricted cubic spline (RCS) plots to display trends in significant variables in logistic regression. Using parallel mediation analysis, we evaluated the possible mediating role of various factors in the risk relationship between LE8 and MetS. Results: Our examination revealed that higher LE8 scores were associated with a lower incidence of MetS in a fully adjusted model. The high LE8 subgroup had a 79.73% reduction in the risk of MetS compared to the low subgroup with an OR = 0.2027 (95% Cl 0.0871, 0.4714), with similar correlations between health factor scores and MetS risk. Biological aging mediated the associations between LE8, health behaviors and health factor scores and MetS risk. Conclusion: A rise in the LE8 score among middle-aged and elderly individuals is a protective factor for MetS, and this association may be partially mediated by biological aging, suggesting that LE8 may reduce the risk of MetS by ameliorating aging.

Association of estimated cardiorespiratory fitness in middle-aged and elderly people with cardiovascular disease: Evidence from the China health and retirement longitudinal study.

BACKGROUND AND AIM: Cardiovascular diseases (CVD) is a major threat to public health, while cardiorespiratory fitness (CRF) is a key predictor of chronic disease. Given this, the purpose of this study was to investigate the relationship between estimated CRF (eCRF) and CVD in middle-aged and elderly Chinese people. METHODS AND RESULTS: The China Health and Retirement Longitudinal Study (CHARLS) with 4761 individuals were included in analysis. Participants were divided into three groups according to eCRF quantile in sex subgroups. Cox proportional hazards regression models were used to explore the correlation of eCRF with CVD (stroke or cardiac events). In total, 4761 participants were included in this cohort study (2500 [52.51%] women). During a 7-year follow-up from 2011 to 2018, 796 CVDs (268 Strokes and 588 cardiac events) were recorded. In multivariable-adjusted analyses, for per 1 SD increase of eCRF, the age-adjusted risk of CVD was reduced by about 18% (HR = 0.82; 95% CI, 0.72-0.93) in men, and was reduced by about 29% (HR = 0.71; 95% CI, 0.62-0.81) in women. Similar associations were also found between eCRF and stroke and cardiac events. Both subgroup and interaction analyses showed that the interaction of age had a statistically significant effect on CVD risk. CONCLUSION: ECRF was inversely associated with CVD risk (stroke or cardiac events) in both men and women. Remarkable sex and age differences exist in the effectiveness of increasing eCRF to reduce the risk of CVD. As a potential, efficient and cost-effective risk prediction tool, eCRF deserves further attention and wide application.

Effects of mobile Internet use on the health of middle-aged and older adults: evidences from China health and retirement longitudinal study.

The rapid development of digital technology has radically changed people's lives. Simultaneously, as the population is rapidly aging, academic research is focusing on the use of Internet technology to improve middle-aged and older people's health, particularly owing to the popularity of mobile networks, which has further increased the population's accessibility to the Internet. However, related studies have not yet reached a consensus. Herein, empirical analysis of the influence of mobile Internet use on the subjective health and chronic disease status of individuals in their Middle Ages and above was conducted utilizing ordered logit, propensity score matching (PSM), and ordered probit models with data from the 2020 China Health and Retirement Longitudinal Study. The study aimed to provide a theoretical basis and reference for exploring technological advances to empower the development of a healthy Chinese population and to advance the process of healthy aging. The health of middle-aged and older adults mobile Internet users was greatly improved, according to our findings. Further, the use of mobile Internet by these persons resulted in improvements to both their self-assessed health and the state of their chronic diseases. As per the findings of the heterogeneity analysis, the impact of mobile Internet use was shown to be more pronounced on the well-being of middle-aged persons aged 45-60 years compared to those aged ≥ 60 years. Further, the endogeneity test revealed that the PSM model could better eliminate bias in sample selection. The results suggest that the estimates are more robust after eliminating endogeneity, and that failure to disentangle sample selectivity bias would overestimate not only the facilitating effect of mobile Internet use on the self-assessed health impacts of middle-aged and older adults, but also the ameliorating effect of mobile Internet use on the chronic diseases of middle-aged and older adults. The results of the mechanistic analysis suggest that social engagement is an important mediating mechanism between mobile Internet use and the health of middle-aged and older adults. This implies that mobile Internet use increases opportunities for social participation among middle-aged and older adults, thereby improving their health.

Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly hypertensive people in China: a longitudinal study.

Background: Hypertension is a common chronic disease that can trigger symptoms such as anxiety and depression. Therefore, it is essential to predict their risk of depression. The aim of this study is to find the best prediction model and provide effective intervention strategies for health professionals. Methods: The study subjects were 2733 middle-aged and older adults who participated in the China Health and Retirement Longitudinal Study (CHARLS) between 2018 and 2020. R software was used for Lasso regression analysis to screen the best predictor variables, and logistic regression, random forest and XGBoost models were constructed. Finally, the prediction efficiency of the three models was compared. Results: In this study, 18 variables were included, and LASSO regression screened out 10 variables that were important for the establishment of the model. Among the three models, Logistic Regression model showed the best performance in various evaluation indicators. Conclusion: The prediction model based on machine learning can accurately assess the likelihood of depression in middle-aged and elderly patients with hypertension in the next three years. And by combining Logistic regression and nomograms, we were able to provide a clear interpretation of personalized risk predictions.

Development and validation of a novel sleep health score in the sleep heart health study.

BACKGROUND: There is a lack of consensus in evaluating multidimensional sleep health, especially concerning its implication for mortality. A validated multidimensional sleep health score is the foundation of effective interventions. METHODS: We obtained data from 5706 participants in the Sleep Heart Health Study. First, random forest-recursive feature elimination algorithm was used to select potential predictive variables. Second, a sleep composite score was developed based on the regression coefficients from a Cox proportional hazards model evaluating the associations between selected sleep-related variables and mortality. Last, we validated the score by constructing Cox proportional hazards models to assess its association with mortality. RESULTS: The mean age of participants was 63.2 years old, and 47.6% (2715/5706) were male. Six sleep variables, including average oxygen saturation (%), spindle density (C3), sleep efficiency (%), spindle density (C4), percentage of fast spindles (%) and percentage of rapid eye movement (%) were selected to construct this multidimensional sleep health score. The average sleep composite score in participants was 6.8 of 22 (lower is better). Participants with a one-point increase in sleep composite score had an 10% higher risk of death (hazard ratio = 1.10, 95% confidence interval: 1.08-1.12). CONCLUSIONS: This study constructed and validated a novel multidimensional sleep health score to better predict death based on sleep, with significant associations between sleep composite score and all-cause mortality. Integrating questionnaire information and sleep microstructures, our sleep composite score is more appropriately applied for mortality risk stratification.

Optimal obesity- and lipid-related indices for predicting type 2 diabetes in middle-aged and elderly Chinese.

To investigate the screening and predicting functions of obesity- and lipid-related indices for type 2 diabetes (T2D) in middle-aged and elderly Chinese, as well as the ideal predicted cut-off value. This study's data comes from the 2011 China Health and Retirement Longitudinal Study (CHARLS). A cross-sectional study design was used to investigate the relationship of T2D and 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride- glucose index (TyG index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The unadjusted and adjusted correlations between 13 indices and T2D were assessed using binary logistic regression analysis. The receiver operating characteristic curve (ROC) was used to determine the usefulness of anthropometric indices for screening for T2D and determining their cut­off value, sensitivity, specificity, and area under the curve (AUC). The study comprised 9488 people aged 45 years or above in total, of whom 4354 (45.89%) were males and 5134 (54.11%) were females. Among them were 716 male cases of T2D (16.44%) and 870 female cases of T2D (16.95%). A total of 13 obesity- and lipid-related indices were independently associated with T2D risk after adjusted for confounding factors (P < 0.05). According to ROC analysis, the TyG index was the best predictor of T2D among males (AUC = 0.780, 95% CI 0.761, 0.799) and females (AUC = 0.782, 95% CI 0.764, 0.799). The AUC values of the 13 indicators were higher than 0.5, indicating that they have predictive values for T2D in middle-aged and elderly Chinese. The 13 obesity- and lipid-related indices can predict the risk of T2D in middle­aged and elderly Chinese. Among 13 indicators, the TyG index is the best predictor of T2D in both males and females. TyG-WC, TyG-BMI, TyG-WHtR, LAP, and CVAI all outperformed BMI, WC, and WHtR in predicting T2D.

The combined effect of handgrip strength and obesity phenotype on the risk of stroke in Chinese middle-aged and elderly: A cohort study.

OBJECTIVE: The aim of this study was to investigate the combined effect of handgrip strength (HGS) and obesity phenotype on the risk of stroke in Chinese middle-aged and elderly people. METHODS: The data was used from the China Health and Retirement Longitudinal Study (CHARLS). Middle-aged and older adults who participated in surveys between 2011 and 2018 were included in the study. They were divided into 4 different types of obesity phenotypes based on obesity and metabolic status: metabolically healthy non-overweight/obesity (MHNO), metabolically healthy overweight/obesity (MHO), metabolically abnormal non-overweight/obesity (MANO), and metabolically abnormal overweight/obesity (MAO). The HGS level was divided into low and high groups according to the median values. Cox proportional risk regression model was used to analyze the joint effect of HGS and obesity phenotype on the risk of stroke among participants. RESULTS: A total of 7904 participants aged 58.89±9.08 years were included in this study. After adjusting for potential confounders, high HGS&MHO (HR=1.86, 95 % CI=1.12-3.09), high HGS&MANO (HR=2.01, 95 %CI=1.42-2.86), high HGS&MAO (HR=2.01, 95 % CI=1.37-2.93), low HGS&MHNO (HR=1.57, 95 % CI=1.00-2.46), low HGS&MHO (HR=2.09, 95 % CI=1.29-3.38), low HGS&MANO (HR=2.02, 95 % CI=1.35-3.03), and low HGS&MAO (HR=2.48, 95 % CI=1.72-3.58) group had significantly higher risks of stroke than the high HGS&MHNO group. CONCLUSION: The coexistence of metabolically unhealthy and low HGS can synergistically increase the risk of stroke in Chinese middle-aged and elderly people.

Obesity and lipid indices as predictors of depressive symptoms in middle-aged and elderly Chinese: insights from a nationwide cohort study.

BACKGROUND: Depressive symptoms are one of the most common psychiatric disorders, with a high lifetime prevalence rate among middle-aged and elderly Chinese. Obesity may be one of the risk factors for depressive symptoms, but there is currently no consensus on this view. Therefore, we investigate the relationship and predictive ability of 13 obesity- and lipid-related indices with depressive symptoms among middle-aged and elderly Chinese. METHODS: The data were obtained from The China Health and Retirement Longitudinal Study (CHARLS). Our analysis includes individuals who did not have depressive symptoms at the baseline of the CHARLS Wave 2011 study and were successfully follow-up in 2013 and 2015. Finally, 3790 participants were included in the short-term (from 2011 to 2013), and 3660 participants were included in the long-term (from 2011 to 2015). The average age of participants in short-term and long-term was 58.47 years and 57.88 years. The anthropometric indicators used in this analysis included non-invasive [e.g. waist circumference (WC), body mass index (BMI), and a body mass index (ABSI)], and invasive anthropometric indicators [e.g. lipid accumulation product (LAP), triglyceride glucose index (TyG index), and its-related indices (e.g. TyG-BMI, and TyG-WC)]. Receiver operating characteristic (ROC) analysis was used to examine the predictive ability of various indicators for depressive symptoms. The association of depressive symptoms with various indicators was calculated using binary logistic regression. RESULTS: The overall incidence of depressive symptoms was 20.79% in the short-term and 27.43% in the long-term. In males, WC [AUC = 0.452], LAP [AUC = 0.450], and TyG-WC [AUC = 0.451] were weak predictors of depressive symptoms during the short-term (P < 0.05). In females, BMI [AUC = 0.468], LAP [AUC = 0.468], and TyG index [AUC = 0.466] were weak predictors of depressive symptoms during the long-term (P < 0.05). However, ABSI cannot predict depressive symptoms in males and females during both periods (P > 0.05). CONCLUSION: The research indicates that in the middle-aged and elderly Chinese, most obesity- and lipid-related indices have statistical significance in predicting depressive symptoms, but the accuracy of these indicators in prediction is relatively low and may not be practical predictors.

Four-years change of BMI and waist circumference are associated with metabolic syndrome in middle-aged and elderly Chinese.

The purpose of the study was to determine whether changes in body mass index (BMI) and waist circumference (WC) in middle-aged and elderly Chinese are associated with metabolic syndrome. In this cohort investigation, 3697 middle-aged and elderly people aged 45 or over were recruited from the China Health and Retirement Longitudinal Study (CHARLS). The National Cholesterol Education Program Adult Treatment Panel III (2005) defined metabolic syndrome (MetS). With Cox regression analysis, we calculated hazard ratio (HR) and 95% confidence intervals (CIs) for MetS based on BMI-WC change categories. To assess the prevalence of MetS, the changes in BMI and WC levels were classified into four quartiles based on their relative and absolute changes. In subjects whose BMI and WC decreased (HR = 0.338; 95% CIs 0.264, 0.433) as well as those whose BMI increased and their WC decreased (HR = 0.375; 95% CIs 0.228, 0.499), metabolic syndrome risk was significantly lower compared with those with increases in both BMI and WC. Regarding the absolute changes in BMI, the lowest percentile of BMI was significantly lower in both males (HR = 0.302; 95% CIs 0.204, 0.448) and females (HR = 0.486; 95% CIs 0.354, 0.667) for the risk of metabolic syndrome. Similar results were observed in the absolute changes in WC, with the lowest quantile of WC having a significant impact on MetS risk in males (HR = 0.170; 95% CIs 0.107, 0.270) and females (HR = 0.303; 95% CIs 0.217, 0.424). The risk of metabolic syndrome was significantly associated with changes in BMI and WC in middle-aged and elderly Chinese. A reduced BMI and WC are associated with lower metabolic syndrome risks in middle-aged and elderly people.