Association between dynapenic abdominal obesity and arthritis among the middle-aged and older Chinese: a longitudinal study.

BACKGROUND: This study aimed to assess the longitudinal association between dynapenic abdominal obesity and new-onset arthritis among the middle-aged and older Chinese population. METHODS: We included 6863 participants from the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS). Dynapenia was defined as handgrip strength < 28 kg for males, and < 18 kg for females. Abdominal obesity was defined as a waist circumference ≥ 90 cm for males and ≥ 85 cm for females. Based on the definitions, all participants were divided into four groups: no dynapenia and no abdominal obesity (ND/NAO), abdominal obesity alone (ND/AO), dynapenia alone (D/NAO), and dynapenia and abdominal obesity (D/AO). The association between dynapenic abdominal obesity and new-onset arthritis was assessed by sex using the Poisson regression models. RESULTS: After a four-year follow-up, 1272 (18.53%) participants reported new-onset arthritis. Those in the D/AO group had a significantly increased risk of new-onset arthritis compared to those in the ND/NAO group (adjusted relative risk (RR): 1.34, 95% confidence interval (CI): 1.01-1.77). In females, the ND/AO (RR: 1.21, 95% CI: 1.03-1.43) and D/AO (RR: 1.39, 95% CI: 1.01-1.93) groups were associated with a higher risk of arthritis. This significant association was not observed in males. CONCLUSIONS: Our results indicated that the combined effect of dynapenia and abdominal obesity significantly increased the risk of new-onset arthritis in females, but this association was not observed in males.

The impact of physical activity on the prevalence of edentulism: an analysis of the relationships between active lifestyle and dental health.

BACKGROUND: Edentulism is considered the ultimate sign of oral health disease burden. It is a common and frequent clinical disease, mostly seen in the elderly, which has been reported to be closely associated with many diseases. While physical activity is known to benefit many chronic diseases, the relationship between the volume of physical activity and edentulism remains unclear. MATERIALS AND METHODS: The CHARLS provided the data for this study. A total of 6,480 participants were enrolled in this study, of whom 46.02% were male and 53.98% were female. The edentulism was defined according to self-report and physical activity volume can be represented by metabolic equivalents. Multiple logistic regression, smooth curve fitting, threshold effects analysis, and Cox regression models were used to explore the relationship between physical activity volume and edentulism. RESULTS: In the fully adjusted model, physically active participants had a 24% lower risk of edentulism compared to those who were physically inactive. Then, we subdivided participants with adequate physical activity into four levels: 600 ≤ PAV < 1200; 1200 ≤ PAV < 1800; 1800 ≤ PAV < 3000; and PAV ≥ 3000. We found that the risk of developing edentulism was lowest and statistically significant at the level of 1,800-3,000 MET-minutes/week physical activity volume (OR = 0.41; 95% CI, 0.24-0.69, p < 0.001). A U-shaped relationship between physical activity volume and edentulism with an inflection point of 2514 (MET-minutes/week) was observed. The results of the longitudinal study also confirm the benefits of physical activity volume with edentulism, participants with adequate physical activity volume had a 21% lower risk of developing edentulism than participants with inadequate physical activity volume (HR = 0.79; 95% CI, 0.67-0.94, p = 0.008). CONCLUSIONS: This study reveals a U-shaped relationship between physical activity volume and edentulism. Physical activity reduces the risk of developing edentulism in middle-aged and older populations, but it is important to control the appropriate volume of physical activity.

Atherogenic index of plasma and obesity-related risk of stroke in middle-aged and older Chinese adults: a national prospective cohort study.

BACKGROUD: The association between the atherogenic index of plasma (AIP) and stroke risk is uncertain. Overweight and obese individuals frequently develop atherosclerosis, suggesting AIP may mediate the relationship between body mass index (BMI) and stroke risk. This study investigates whether AIP mediates the BMI-stroke association and evaluates the interaction effects of AIP and BMI on stroke risk in middle-aged and older Chinese adults. METHOD: This study analyzes data from the China Health and Retirement Longitudinal Study (CHARLS), an ongoing nationally representative prospective cohort study that began in 2011. It includes 8 598 middle-aged and older Chinese adults without stroke at baseline. A mediation analysis, employing a novel two-stage regression method, was conducted to evaluate the indirect effect of BMI on stroke through AIP. RESULTS: During a median follow-up of 7.1 years, 615 (7.2%) participants developed a stroke. After adjusting for confounders, AIP was significantly associated with stroke risk (hazard ratio [HR] per 1-SD increase, 1.24; 95% CI 1.14-1.35). Mediation analysis indicated that compared to normal weight, obesity similarly raised stroke risk by 78.0% (HR 1.78, 95% CI 1.40-2.27), with 29.67% (95% CI 14.27-45.08%) of the association mediated through AIP (HR 1.15, 95% CI 1.08-1.23). No significant multiplicative or additive interactions were observed between BMI and AIP on stroke. CONCLUSIONS: This study found that the AIP appeared to be associated with stroke risk and mediates the association between obesity and stroke among middle-aged and older Chinese adults.

Association between nighttime sleep duration and quality with low back pain in middle-aged and older Chinese adults.

BACKGROUND: This study aims to investigate the association between sleep duration, sleep quality, and the risk of low back pain (LBP) among middle-aged and elderly individuals in China. METHODS: Utilizing data from the China Health and Retirement Longitudinal Study spanning 2011 to 2020, we categorized sleep duration into long, medium, and short categories, and sleep quality into good, fair, and poor levels. LBP status was determined based on self-reported information by participants. Multivariable logistic regression analysis was employed to assess the relationship between sleep duration, sleep quality, with the risk of LBP. RESULTS: A total of 6750 individuals were included in the longitudinal study. After 9 years of follow-up, the prevalence of LBP was 25.69 %. In the fully adjusted model, compared to individuals with medium sleep duration, those with short sleep duration had a 28 % increased risk of developing LBP (OR = 1.28, 95%CI: 1.12, 1.46). Additionally, when compared to individuals with good sleep quality, those with fair and poor sleep quality had a 35 % (OR = 1.35, 95%CI: 1.19, 1.54) and 33 % (OR = 1.33, 95%CI: 1.12, 1.58) increased risk of LBP, respectively. Joint analysis of both factors revealed that individuals with poor sleep quality and short sleep duration had the highest risk of LBP. CONCLUSION: Among middle-aged and elderly individuals in China, short sleep duration and poor sleep quality were associated with an increased risk of LBP. Future studies should further explore the mechanisms underlying this association and validate the findings through randomized controlled trials.

Association of changes and cumulative measures of triglyceride-glucose index-body mass index with hypertension risk: a prospective cohort study.

BACKGROUND: To investigate the relationships of the dynamic changes in triglyceride glucose index-body mass index (TyG­BMI) and cumulative TyG-BMI with the risk of hypertension among middle-aged and elderly Chinese. METHODS: Data were used from the China Health and Retirement Longitudinal Study (CHARLS). Participants who participated in the baseline study (2011-2012) and in subsequent surveys (2015-2018) were included in this study. The primary exposures were changes in TyG-BMI and cumulative TyG-BMI from 2012 to 2015. Changes in TyG-BMI were categorized using k-means clustering methods, while cumulative TyG-BMI was categorized into quartiles. Cox proportional hazards regression models were performed to examine the association between changes in TyG-BMI and cumulative TyG-BMI with the incidence of hypertension. Linear regression analyzes were performed to examine the association between changes in TyG-BMI and cumulative TyG-BMI with cumulative systolic blood pressure (SBP) and cumulative diastolic blood pressure (DBP). RESULTS: Of a total of 2,561 participants aged 56.93 ± 8.08 years old at baseline, 253 individuals (9.9%) developed hypertension during the 7-year follow-up period. The hazard ratios (HR) and 95% confidence interval (CI) for hypertension were 1.50 (1.10-2.03) for class 2 (persistently medium class) and 2.35 (1.61-3.42) for class 3 (persistently high class), compared to class 1 (persistently low class). Additionally, class 2 showed increases of 7.70 mmHg (95% CI: 5.18-10.21) in cumulative SBP and 6.53 mmHg (95% CI: 4.68-8.38) in cumulative DBP, while class 3 exhibited increases of 14.10 mmHg (95% CI: 10.56-17.64) in cumulative SBP and 12.64 mmHg (95% CI: 10.03-15.25) in cumulative DBP, compared with class 1. Regarding cumulative TyG-BMI, the HR for hypertension were 1.75 (95% CI: 1.18-2.59) for quartile 3 and 2.15 (95% CI: 1.43-3.23) for quartile 4, compared with quartile 1. In quartile 2, cumulative SBP increased by 3.99 mmHg (95% CI: 0.88-7.11) and cumulative DBP by 2.74 mmHg (95% CI: 0.45-5.02). Quartile 3 showed increases of 8.32 mmHg (95% CI: 5.09-11.54) in cumulative SBP and 7.13 mmHg (95% CI: 4.76-9.49) in cumulative DBP. Quartile 4 exhibited the highest increases, with cumulative SBP rising by 13.15 mmHg (95% CI: 9.70-16.60) and cumulative DBP by 12.20 mmHg (95% CI: 9.67-14.74). Furthermore, a linear relationship was observed between cumulative TyG-BMI and the risk of hypertension. CONCLUSIONS: Changes in TyG-BMI and cumulative TyG-BMI were associated with an increased risk of hypertension, as well as higher cumulative SBP and DBP in Chinese middle-aged and elderly population.

Construction and evaluation of sarcopenia risk prediction model for patients with diabetes: a study based on the China health and retirement longitudinal study (CHARLS).

PURPOSE: Sarcopenia is a common complication of diabetes. Nevertheless, precise evaluation of sarcopenia risk among patients with diabetes is still a big challenge. The objective of this study was to develop a nomogram model which could serve as a practical tool to diagnose sarcopenia in patients with diabetes. METHODS: A total of 783 participants with diabetes from China Health and Retirement Longitudinal Study (CHARLS) 2015 were included in this study. After oversampling process, 1,000 samples were randomly divided into the training set and internal validation set. To mitigate the overfitting effect caused by oversampling, data of CHARLS 2011 were utilized as the external validation set. Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate logistic regression analysis were employed to explore predictors. Subsequently, a nomogram was developed based on the 9 selected predictors. The model was assessed by area under receiver operating characteristic (ROC) curves (AUC) for discrimination, calibration curves for calibration, and decision curve analysis (DCA) for clinical efficacy. In addition, machine learning models were constructed to enhance the robustness of our findings and evaluate the importance of the predictors. RESULTS: 9 factors were selected as predictors of sarcopenia for patients with diabetes. The nomogram model exhibited good discrimination in training, internal validation and external validation sets, with AUC of 0.808, 0.811 and 0.794. machine learning models revealed that age and hemoglobin were the most significant predictors. Calibration curves and DCA illustrated excellent calibration and clinical applicability of this model. CONCLUSION: This comprehensive nomogram presented high clinical predictability, which was a promising tool to evaluate the risk of sarcopenia in patients with diabetes.

Association between persistent musculoskeletal pain and incident sarcopenia in China: the mediating effect of depressive symptoms.

Objective: To evaluate the association between musculoskeletal pain and incident sarcopenia and further explore the mediating effect of depressive symptoms among middle-aged and older Chinese adults. Methods: Using the data from the China Health and Retirement Longitudinal Study 2011 and 2015, we included 12,788 participants in the cross-sectional analysis and 8,322 for the longitudinal analysis. Musculoskeletal pains located in the neck, back, waist, shoulder, arm, wrist, leg, knee, and ankle were self-reported at baseline and follow-up. The diagnosis criteria of sarcopenia was based on the Asian Working Group for Sarcopenia 2019. Multivariable logistic regression models were used to evaluate the association between musculoskeletal pain, and the Karlson-Holm-Breen (KHB) method was used to explore the mediating effect of depressive symptoms. Results: Over the 4-year follow-up, 445 participants were identified with incident sarcopenia. In the longitudinal analysis, participants with baseline musculoskeletal pain (adjusted odds ratio (OR): 1.37, 95% confidence interval (CI): 1.07-1.76), persistent musculoskeletal pain (OR:1.68, 95%CI: 1.28-2.24), and persistent waist pain (OR:1.46, 95%CI: 1.04-2.03) were significantly associated with increased the risk of incident sarcopenia. Furthermore, depressive symptoms were found to partially mediate the association between musculoskeletal pain and incident sarcopenia. Conclusion: Persistent musculoskeletal pain, especially in waist area, was positively associated with a higher risk of sarcopenia among the middle-aged and older Chinese. Depressive symptoms played a partial mediating role in this association.

Mediation analysis of cognitive function in the relationship between pulmonary function and depression among middle-aged and older adults.

AIM: This study aims to explore the association between declining lung function and depression in middle-aged and older adults, with a special focus on the mediating role of cognitive function. METHODS: This study utilizes self-reported and physical examination data from 5345 individuals participating in the 2015 cycle of the China Health and Retirement Longitudinal Study (CHARLS) to explore the role of cognitive function changes in mediating the effects of diminished lung function on depression among middle-aged and older adults. RESULTS: Multivariate linear regression analysis revealed a positive correlation between pulmonary and cognitive functions (ß = 0.003, 95% CI: 0.002∼0.003, P < 0.01) and a negative correlation between cognitive function and depression (ß = -0.279, 95% CI: -0.330-0.228, P < 0.01). Cognitive function plays a mediating role in linking pulmonary function with depression, exhibiting a mediation effect of -0.0007 and a total effect of -0.0046, wherein the mediation effect contributes to 15.22% of the total effect. For females, the mediating effect of cognitive function was stronger (ß = -0.0013, 95% CI: -0.0018∼-0.0008, P < 0.01) than it was for males (ß = -0.0006, 95% CI: -0.0009∼-0.0003, P < 0.01). CONCLUSIONS: The study underscores the importance of monitoring lung and cognitive functions as interconnected factors contributing to the mental health of middle-aged and older adults. It suggests that interventions aimed at improving pulmonary health and cognitive function may help mitigate depressive symptoms among middle-aged and older adults. Further research is warranted to validate these findings across diverse cultural and demographic settings. Geriatr Gerontol Int 2024; ••: ••-••.

The Interplay between nighttime/midday sleep duration and the number of new-onset chronic diseases: A decade-long prospective study in China.

OBJECTIVE: To investigate the interplay between individual nighttime and midday sleep duration and the number of new-onset chronic diseases and determine the optimal sleep duration associated with lowest number of new-onset chronic diseases. METHODS: We used data from the China Health and Retirement Longitudinal Study (CHARLS) covering a decade and involving 10,828 participants. A random intercept cross-lagged model was used to explore the interplay between nighttime/midday sleep durations and new-onset chronic diseases at both the within-individual and between-individual levels, followed by a dose-response analysis at the between-individual level to determine the optimal sleep duration. New-onset chronic diseases include 14 types of self-reported diseases diagnosed by doctors. RESULTS: Within-individual analysis revealed that increased nighttime/midday sleep duration led to a higher number of new-onset chronic diseases, and an increased number of new-onset chronic diseases resulted in decreased nighttime sleep duration. Between nighttime and midday sleep, one type of sleep duration increase was likely to lead to an increase in another type. Between-individual analysis found a nonlinear relationship between the number of new-onset chronic diseases and nighttime sleep duration, identifying the optimal nighttime sleep duration as 7.46 h. CONCLUSIONS: These findings elucidate the interplay between sleep duration and number of new-onset chronic diseases and underscore the need for public awareness and comprehensive interventions. Future studies should focus on refining sleep monitoring and exploring the sleep-chronic diseases nexus in greater depth.

Age-related differences in the number of chronic diseases in association with trajectories of depressive symptoms: a population-based cohort study.

BACKGROUND: The number of chronic diseases has been associated with changes in depressive symptoms over time among middle-aged and older adults. This study aimed to explore the association between the number of chronic diseases and trajectories of depressive symptoms and the role of age in this association. METHODS: A total of 12,974 middle-aged and older Chinese adults (≥ 45 years) participated in the China Health and Retirement Longitudinal Study (CHARLS) in waves 2011, 2013, 2015, 2018, and 2020. The number of chronic diseases was determined by self-reported hospital diagnosis of hypertension, dyslipidemia, diabetes, cancer, chronic lung diseases, liver disease, heart diseases, stroke, kidney diseases, digestive diseases, emotional, nervous, or psychiatric problems, memory-related disease, arthritis or rheumatism, asthma, and then obtaining the total number of chronic diseases. Depressive symptoms were measured by the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10). Group-based trajectory modeling (GBTM) was adopted to capture the trajectories of depressive symptoms over time. Multinomial logistic regressions were conducted to examine the association between the number of chronic diseases and trajectories of depressive symptoms and the role of age in this association. RESULTS: Four distinct trajectories of depressive symptoms were observed in 34.68% individuals in mild, 40.76% in moderate, 19.41% in increasing, and 5.15% in severe group. Compared to participants without chronic diseases, those with one, two, three or more chronic diseases had a 1.81, 3, and 7.49-fold higher risk of developing severe depressive symptom trajectory, respectively. Moreover, the association between the number of chronic diseases and severe depressive symptoms trajectory differed by age (45-59 and ≥ 60 years) (P for interaction < 0.05). CONCLUSION: Participants with middle age may play a promoting role in the association between the number of chronic disease and severe depressive symptoms. The severe depressive symptoms intervention may be more beneficial for middle-aged adults.

LUTS/BPH increases the risk of depressive symptoms among elderly adults: A 5-year longitudinal evidence from CHARLS.

OBJECTIVE: The prevalence of Lower Urinary Tract Symptoms suggestive of Benign Prostatic Hyperplasia (LUTS/BPH) is notably high and potentially elevates the likelihood of depressive symptoms. This study was designed to employ both cross-sectional and longitudinal methodologies to explore the correlation between LUTS/BPH and depressive symptoms among middle-aged and elderly men in China. METHODS: This investigation utilized data from the China Health and Retirement Longitudinal Study (CHARLS), with the initial dataset from 2015 serving as the baseline and subsequent data from 2018 and 2020 facilitating longitudinal analysis. The study encompassed a baseline cohort of 5156 men aged 45 years and above, and an expansive longitudinal analytical sample of 23,530 participants spanning from 2015 to 2020. The assessment of depressive symptoms was conducted using the 10-item Center for Epidemiological Studies Depressive Symptoms Scale (CESD-10). To investigate the factors associated with LUTS/BPH, the relationship between LUTS/BPH and depressive symptoms, and to evaluate the incidence rate of depressive symptoms onset based on LUTS/BPH status, multivariate logistic analyses and logistic regression models were employed. RESULTS: Our results reveal a markedly higher incidence of depressive symptoms among individuals with LUTS/BPH, at 30.16 %, compared to 22.94 % in those without LUTS/BPH. This pattern was consistent in both mild and moderate depressive symptoms categories. However, the prevalence of severe depressive symptoms did not exhibit a significant disparity between the two groups. Longitudinal analysis spanning from 2015 through 2018 and 2020 further corroborated these observations. Individuals with LUTS/BPH showed a substantially higher incidence of depressive symptoms across all severity levels compared to those without LUTS/BPH. Specifically, the presence of LUTS/BPH was linked to a 53 % heightened risk of mild depressive symptoms, a 45 % increase in moderate depressive symptoms, and an alarming 229 % surge in severe depressive symptoms risk between 2015 and 2018. Additionally, from 2015 to 2020, there was a 30 % increased risk for mild depressive symptoms, a 41 % rise for moderate depressive symptoms, and a 106 % escalation in the risk of severe depressive symptoms among those with LUTS/BPH. CONCLUSION: In middle-aged and older Chinese adults, LUTS/BPH were correlated with an elevated risk of depressive symptoms.

Machine learning algorithms to predict mild cognitive impairment in older adults in China: A cross-sectional study.

OBJECTIVE: This study aimed to explore the predictive value of machine learning (ML) in mild cognitive impairment (MCI) among older adults in China and to identify important factors causing MCI. METHODS: In this study, 6434 older adults were selected based on the data of the China Health and Elderly Care Longitudinal Survey (CHARLS) in 2020, and the dataset was subsequently divided into the training set and the test set, with a ratio of 6:4. To construct a prediction model for MCI in older adults, six ML algorithms were used, including logistic regression, KNN, SVM, decision tree (DT), LightGBM, and random forest (RF). The Delong test was used to compare the differences of ROC curves of different models, while decision curve analysis (DCA) was used to evaluate the model performance. The important contributions of the prediction results were then used to explain the model by the SHAP value.The Matthews correlation coefficient (MCC) was calculated to evaluate the performance of the models on imbalanced datasets. Additionally, causal analysis and counterfactual analysis were conducted to understand the feature importance and variable effects. RESULTS: The area under the ROC curve of each model range from 0.71 to 0.77, indicating significant difference (P < 0.01). The DCA results show that the net benefits of LightGBM is the largest within various probability thresholds. Among all the models, the LightGBM model demonstrated the highest performance and stability. The five most important characteristics for predicting MCI were educational level, social events, gender, relationship with children, and age. Causal analysis revealed that these variables had a significant impact on MCI, with an average treatment effect of -0.144. Counterfactual analysis further validated these findings by simulating different scenarios, such as improving educational level, increasing age, and increasing social events. CONCLUSION: The ML algorithm can effectively predict the MCI of older adults in China and identify the important factors causing MCI.

Associations between sensory impairment and functional limitations among older Chinese adults: mediating roles of social isolation and cognition.

BACKGROUND: The high prevalence of sensory impairment and functional limitations in older adults is a significant concern, yet there is limited understanding of the relationship between these two conditions. Therefore, the objective of this study was to investigate the pathways connecting sensory impairment and functional limitations by examining serial multiple mediating effects of social isolation and cognition in older adults. METHODS: Using the China Health and Retirement Longitudinal Study dataset, a sample of 4871 older adults was selected. The study variables included sensory impairment, functional limitations, social isolation and cognition, and other covariates. A hierarchical multiple linear regression model was used to assess the association between sensory impairment and functional limitations. Mediation analysis was conducted to explore the sequential multiple mediating effects of social isolation and cognitive function in the relationship between sensory impairment and functional limitations. RESULTS: Our findings revealed a significant and positive association between sensory impairment and functional limitations (B = 0.615, 95% CI: 0.397, 0.834). After adjusting for social isolation and cognitive function, the impact of sensory impairment on functional limitations accounted for 87.19% of the total effect. Additionally, approximately 12.81% of the significant relationship between dual sensory impairment and functional limitations was mediated by social isolation and cognitive function. A serial multiple mediating pathway (sensory impairment → social isolation → cognition → functional limitations) was identified, with a coefficient of 0.013 (95% CI: 0.006, 0.020). CONCLUSIONS: Our study provides evidence for the mediating effects of social isolation and cognition in the relationship between sensory impairment and functional limitations. Given the prevalence of functional limitations among older adults with sensory impairment, it is crucial to consider social isolation and cognitive function in efforts to reduce the burden of disability care. Future validation of these findings through longitudinal studies is necessary.

Body Roundness Index Trajectories and the Incidence of Cardiovascular Disease: Evidence From the China Health and Retirement Longitudinal Study.

BACKGROUND: Several previous cross-sectional studies suggested that body roundness index (BRI) may be associated with cardiovascular disease (CVD). However, the association should be further validated. Our study aimed to assess the association of the BRI trajectories with CVD among middle-aged and older Chinese people in a longitudinal cohort. METHODS AND RESULTS: A total of 9935 participants from the CHARLS (China Health and Retirement Longitudinal Study) with repeated BRI measurements from 2011 to 2016 were included. The BRI trajectories were identified by group-based trajectory modeling. The primary outcome was incident CVD (stroke or cardiac events), which occurred in 2017 to 2020. Cox proportional hazards regression models were used to examine the association of BRI trajectories with CVD risk. Participants were divided into 3 BRI trajectories, named the low-stable BRI trajectory, moderate-stable BRI trajectory and high-stable BRI trajectory, accounting for 49.81%, 42.35%, and 7.84% of the study population, respectively. Compared with participants in the low-stable BRI trajectory group, those in the moderate-stable and high-stable BRI trajectory groups had an increased risk of CVD, with multivariable adjusted hazard ratios of 1.22 (95% CI, 1.09-1.37) and 1.55 (95% CI, 1.26-1.90), respectively. Furthermore, simultaneously adding the BRI trajectory to the conventional risk model improved CVD risk reclassification (all P<0.05). CONCLUSIONS: A higher BRI trajectory was associated with an increased risk of CVD. The BRI can be included as a predictive factor for CVD incidence.

A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly.

BACKGROUND: With the continuous advancement of age in China, attention should be paid to the mental well-being of the elderly population. The present study uses a novel machine learning (ML) method on a large representative elderly database in China as a sample to predict the risk factors of depression in the elderly population from both holistic and individual level. METHODS: A total of participants met the inclusion criteria from the fourth waves of the China Health and Retirement Longitudinal Study (CHARLS) were analyzed with ML algorithms. The level of depression was assessed by the 10-item Center for Epidemiological Studies Depression Scale (CESD-10). RESULTS: The current study found top 5 factors that were important for predicting depression in the elderly population in China, including average sleep time, gender, age, social activities and nap time during the day. The results also provide reliable diagnostic likelihood at the individual level to support clinicians identify the most impactful factors contributing to patient depression. Our findings also suggested that activities such as interacting with friends and play ma-Jong, chess or join community clubs may have a positive collaborative effect for elderly's mental health. CONCLUSIONS: Holistic approaches are an effective method of deriving and interpreting sophisticated models of mental health in elderly populations. More detailed information about a patient's demographics, medical history, sleeping patterns and social/leisure activities can help to inform policy and treatment interventions on a population and individual level. Large scale surveys such as CHARLS are effective methods for testing the most accurate models, however, further research using professional clinical input could further advance the field.

Role of intergenerational connections in cognitive aging: Evidence from a Chinese longitudinal study.

Objective: To explore the impact of intergenerational connections on cognitive function in middle-aged and older adults (45-60 years and over 60 years, respectively) and analyze the urban-rural and sex differences in the effects of intergenerational connections on cognitive function. Method: Based on China Health and Retirement Longitudinal Study data (CHARLS), this study conducted ID matching for four waves of data from 2011, 2013, 2015, and 2018. Cognitive function was measured via Telephone Interview for Cognitive Status-modified (TICS-m), word recall, and imitation drawing. Using a combination of cross-sectional and longitudinal research, we constructed the cross-lagged panel model (CLPM) with a sample of 1,480 participants to explore the relationship between intergenerational connections and cognitive function. Results: This study examines the impact of intergenerational connections on cognitive function in middle-aged (45-60 years) and older adults (over 60 years) using data from the CHARLS. It identifies urban-rural and sex differences, with notable effects among rural female participants. The frequency of meeting with one child negatively predicts cognitive function (ß = -0.040, p = 0.041), and the frequency of communication with one child positively predicts cognitive function (ß = 0.102, 0.068, 0.041, p < 0.001, p = 0.001, 0.045). Meanwhile, intergenerational connections with multiple children positively predicts cognitive function (ß = 0.044, p = 0.031), (ß = 0.128, 0.084, and 0.056, p < 0.001, 0.001, p = 0.008). There are urban-rural and sex differences in the effects of intergenerational connections on cognitive function; additionally, the effects of intergenerational connections on cognitive function are significant in rural female middle-aged and older adults. Discussion: This study proposes the theory of skewed intergenerational support, which suggests that as middle-aged and older adults age, the responsibility for intergenerational support is skewed toward one child. This leads to conflicts between middle-aged and older parents and the child, which further affects cognitive function. In addition, this study put forward the boat-carrying theory of intergenerational relations and "to hold a bowl of water level" is the art of dealing with intergenerational relationships.

Association between nighttime sleep duration, nap time, and mild cognitive impairment in Chinese older adults: a cross-sectional study.

OBJECTIVE: This study aims to investigate the relationship between midday nap time, nighttime sleep duration, and mild cognitive impairment (MCI) in Chinese older adults and determine the recommended sleep duration to provide a scientific basis for preventing and managing MCI in this population. METHODS: Utilizing the 2020 China Health and Retirement Longitudinal Study database, the demographic data, health status, and lifestyle information of the study participants were collected. A total of 5,314 valid samples were included in the analysis. Logistic regression and restricted cubic spline plots were employed to explore the relationship between sleep patterns and MCI. RESULTS: In the cross-sectional analysis, a linear relationship was observed between midday nap duration and MCI among Chinese elderly. The probability of MCI was lowest among those who napped for less than 30 min at noon. Compared with individuals who napped for30-90 min, those who did not nap were more likely to have MCI (OR = 1.30, 95% CI: 1.05-1.60). Older adults with napping duration < 30 min (OR = 0.73, 95% CI:0.56-0.95) also exhibited lower probability of MCI when compared those without napping habit, Nighttime sleep duration exhibited a U-shaped relationship with MCI. Individuals with less than approximately 6 h of nighttime sleep showed a gradual decrease in the probability of MCI with increasing sleep duration, whereas those with more than 7.5 h demonstrated an increase in the probability of MCI with longer sleep duration. Older adults who slept less than 6 h at night (OR = 1.22, 95% CI: 1.01 ~ 1.46) or more than 8 h (OR = 1.78, 95% CI: 1.35-2.33) were more likely to develop MCI compared with those who slept 6 to 8 h. CONCLUSION: After controlling for potential confounding variables, both nighttime sleep duration and midday nap duration exhibited a nonlinear "U"-shaped relationship with MCI among the elderly. The probability of depression was lower with a nap duration of approximately 60 min, and the optimal nighttime sleep duration was 6-8 h, with around 7 h providing the greatest cognitive benefits.

Estimating the impact of metabolic syndrome on low back pain and the joint effects of metabolic syndrome and depressive symptoms on low back pain: insights from the China Health and Retirement Longitudinal Study.

BACKGROUND: Although metabolic syndrome (MetS) and depressive symptoms (DS) are predictors of low back pain (LBP), their combined effects and relative contributions to LBP have not been well studied. Using the nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), this study conducted cross-sectional and longitudinal analyses to investigate the impact of MetS on LBP, and the joint effects of MetS and DS on LBP. METHODS: This study included a cross-sectional analysis of 8957 participants aged at least 45 years from the CHARLS 2011 dataset and a longitudinal follow-up of 3468 participants without LBP from the CHARLS 2011, tracked over 9.25 years (from June 2011 to September 2020) with 4 times LBP assessment in CHARLS 2013, 2015, 2018, and 2020. To explore the association between MetS on LBP and the joint effects of MetS and DS on LBP, multivariable-adjusted multinomial logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Multivariable-adjusted COX proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95% CIs. All statistical analyses were conducted using STATA (version SE16). RESULTS: In the cross-sectional analysis, MetS was associated with a lower risk of LBP (adjusted OR = 0.85, 95% CI = 0.74-0.97), while there was no significance for this association in the longitudinal analysis. In the joint association of MetS and DS with LBP, participants with NoMetS + DS (adjusted OR = 2.31, 95% CI = 1.94-2.75), and MetS + DS (adjusted OR = 2.16, 95% CI = 1.81-2.59) were risk factors for LBP events, while those with MetS + NoDS (adjusted OR = 0.75, 95% CI = 0.62-0.90) was a protective factor for LBP events than those with NoMetS + NoDS. During the 9.25 years of follow-up, 1708 cases (49.25%) experienced incident LBP events. In the longitudinal analysis, a significantly negative association was not found in MetS + NoDS for LBP events. Three sensitivity analyses identified the robustness of the associations. Moreover, the nature of cross-sectional associations differed by age (45-64 and 65 + years). CONCLUSIONS: Our study found that MetS was linked to a lower incidence of LBP, but this effect does not persist over time. Importantly, the combination of MetS and DS significantly increased LBP risk, a joint effect not extensively studied before. These findings underscore the novel contribution of our research, advocating for the joint assessment of MetS and DS to enhance LBP risk stratification and inform prevention strategies.

Post-COVID social engagement and depression among Chinese older adults: exploring rural/urban and gender differences.

PURPOSE: This study investigates the impact of post-COVID social engagement on depression levels among Chinese older adults, with a focus on rural/urban and gender differences. METHODS: Using the year 2018 and year 2020 data from the China Health and Retirement Longitudinal Study (CHARLS), this study analyzed pre- and post-COVID depression levels and social engagement indicators, including going-out, activities and networking among Chinese older adults (N = 8,793). RESULTS: Results showed a significant increase in depression levels across all demographic groups post-COVID, with rural females exhibiting the highest levels of depression. Reduced social engagement was associated with increased depression, particularly among rural males and females. Subgroup analyses highlighted nuanced patterns: rural males suffered from decreased intense activities and online contacts, while urban males experienced heightened depression with reduced visiting and light activities. Rural females reported increased depression with decreased moderate activities and dancing outdoors but decreased levels with reduced online contacts. Conversely, urban females experience decreased depression with reduced social engagements, suggesting areevaluation of priorities amidst pandemic challenges. CONCLUSION: This study has underscored the importance of considering individual, cultural, and contextual factors in understanding mental health outcomes among Chinese older adults. Findings inform targeted interventions aimed at promoting psychological well-being and resilience among Chinese older adults in the post-COVID era, including community-based programs and mental health screenings, to foster social connection and emotional support.

Association between physical activity level and diabetes incidence among Chinese middle-aged and older adults: a cross-sectional study from the China health and retirement longitudinal study.

Background: It has been shown that diabetes is associated with insufficient physical activity among middle-aged and older adults, but the association between different physical activity levels (PAL) and diabetes incidence needs to be further explored. Objective: This study aims to explore the correlation and dose-response relationship between different PAL and the diabetes incidence in middle-aged and older adults. Methods: Utilizing data from the 2018 China Health and Retirement Longitudinal Study (CHARLS), this cross-sectional analysis included 17,226 middle-aged and older adults aged 45 and above. Binary logistic regression models and restricted cubic spline (RCS) were used to explore the correlation and dose-response relationship between different PAL and the incidence of diabetes in the total middle-aged and older adults population as well as in subgroups. Sensitivity analyses were also performed to verify the robustness of the findings. Results: In the entire study population, compared with the lowest PAL, participants in the third and fourth quartiles PAL saw diabetes incidence significantly reduced by 16% (p = 0.005) and 33% (p < 0.001), respectively (p for trend < 0.001). In subgroup analyses, the fourth quartile PAL significantly reduced the diabetes incidence among females, individuals aged 60-69, and rural residents by 25% (p = 0.011), 38% (p < 0.001) and 28% (p < 0.001), respectively. For males, middle-aged (45-59 years), and urban residents, the third quartile PAL reduced diabetes incidence by 22% (p = 0.004), 24% (p = 0.012), 21% (p = 0.013), respectively. When the fourth quartile PAL was reached, the diabetes incidence was significantly reduced in these populations by 41% (p < 0.001), 39% (p < 0.001), and 41% (p < 0.001), respectively. There was a negative dose-response relationship between physical activity and diabetes incidence in specific Chinese middle-aged and older adults population. In addition, sensitivity analyses indicated the robustness of the findings. Conclusion: Higher PAL was associated with lower diabetes incidence in specific Chinese middle-aged and older adults population. It is feasible to use physical activity to predict diabetes incidence in this demographic, and high PAL may be an effective means of preventing and controlling diabetes.