Association between triglyceride glucose index and hyperuricemia: a new evidence from China and the United States.

Background: Hyperuricemia (HUA) is a glo\bal public health problem. The etiology of HUA is complex and efficient and accurate assessment metrics are still lacking when conducting large-scale epidemiologic screening. The aim of this study was to evaluate the association of the triglyceride glucose (TyG) index, TyG-body mass index (BMI), TyG-waist-to-height ratio (WHtR) with the risk of HUA. Methods: Based on data collected from the National Health and Nutrition Examination Survey (NHANES) in the United States and the China Health and Aging Longitudinal Study (CHARLS) in China, a total of 14,286 U.S. adults and 4,620 Chinese adults were included in the analysis. The study examined the levels of TyG, TyG-BMI, TyG-WHtR, and TyG-WC. Multivariate logistic regression was utilized to investigate the relationships between these variables and hyperuricemia (HUA), separately. Additionally, the study used restricted cubic splines (RCS) to explore the linear associations of TyG, TyG-BMI, TyG-WHtR, TyG-WC, and HUA, separately. Results: The NHANES results showed that TyG [Q2, 1.58(1.26, 1.98); Q3, 2.36 (1.94, 2.88); Q4, 3.21 (2.61, 3.94)], TyG-BMI [Q2, 2.14 (1.74, 2.65); Q3, 3.38 (2.74, 4.17); Q4, 6.70 (5.55, 8.02)], TyG-WHtR [Q2, 1.92 (1.56, 2.36); Q3, 3.14 (2.56, 3.85); Q4, 6.28 (5.12, 7.69)], TyG-WC [Q2, 2.32 (1.85, 2.90); Q3, 3.51 (2.84, 4.34); Q4, 7.32 (5.95, 9.02)] were identified as risk factors for hyperuricemia (HUA). Similarly, the CHARLS results, when fully adjusted for covariates, indicated that TyG [Q4, 2.36 (1.08, 5.15)], TyG-BMI [Q3, 2.60 (1.05, 6.41); Q4, 3.70 (1.64, 8.32)], TyG-WHtR (Q4, 2.84 (1.23, 6.55), TyG-WC [Q4, 2.85 (1.23, 6.5)] were also risk factors for HUA. The predictive ability of each indicator for the risk of developing HUA was stronger in women than in men. Furthermore, there was an observed nonlinear relationship between TyG, TyG-BMI, TyG-WHtR, TyG-WC, and HUA in both the NHANES and CHARLS datasets (P-nonlinearity < 0.05). Conclusion: These findings suggest that TyG, TyG-BMI, TyG-WHtR and TyG-WC are associated with an increased risk of HUA. They are potential indicators for screening HUA status in the general population in China and the United States.

The association of platelet to white blood cell ratio with diabetes: a nationwide survey in China.

Background: Inflammation is integral to diabetes pathogenesis. The novel hematological inflammatory biomarker, platelet to white blood cell ratio (PWR), is linked with various conditions such as chronic kidney disease and stroke. However, the association of this novel clinical indicator with diabetes still remains unclear, which is investigated in this study. Materials and Methods: A total of 10,973 Chinese participants were included and grouped according to the tertiles of PWR (T1, T2, and T3 groups). Diagnosis of prediabetes and diabetes adhered to American Diabetes Association criteria. Binary logistic regression was adopted to assess the relationship between PWR and both diabetes and prediabetes. The dose-response relationship of PWR and diabetes was examined using restricted cubic spline regression. Subgroup and interaction analyses were conducted to investigate potential covariate interactions. Results: Individuals with higher PWR had better lifestyles and lipid profiles (all P < 0.05). After adjusting for all the covariates, the T2 group had a 0.83-fold (95% CI: 0.73-0.93, P < 0.01) risk of diabetes and that for the T3 group was 0.68-fold (95% CI: 0.60-0.78. P < 0.001). Dose-response analysis identified non-linear PWR-diabetes associations in the general population and females (both P < 0.05), but absent in males. Participants with prediabetes in the T2 and T3 groups had lower risks of diabetes (OR = 0.80 for the T2 group, P < 0.001 and 0.68 for the T3 group, P < 0.001) in the full models. All the sensitivity analysis support consistent conclusions. Conclusions: An increase in PWR significantly correlates with reduced diabetes risks. A non-linear PWR-diabetes relationship exists in the general population and females, but not in males. The correlation between PWR and diabetes indicates that PWR holds potentials in early identification and prevention of diabetes.

Restricted linear association between night sleep duration and diabetes risk in middle-aged and older adults: a 7-year follow-up analysis from the China health and retirement longitudinal study.

Background: A rapid increase in the prevalence of diabetes is an urgent public health concern among older adults, especially in developing countries such as China. Despite several studies on lifestyle factors causing diabetes, sleep, a key contributor, is understudied. Our study investigates the association between night sleep duration and diabetes onset over a 7-year follow-up to fill information gaps. Method: A population-based cohort study with 5437 respondents used 2011-2018 China Health and Retirement Longitudinal Study data. Using self-reported night sleep duration from the 2011 baseline survey, information on new-onset diabetes was collected in follow-up surveys. Baseline characteristics of participants with vs. without new-onset diabetes were compared using Chi-square and Mann-Whitney U tests. Multivariable Cox regression models estimated the independent relationship between night sleep and new-onset diabetes. The addictive Cox regression model approach and piece-wise regression described the nonlinear relationship between night sleep and new-onset diabetes. Subgroup analysis was also performed by age, gender, body measurement index, dyslipidemia, drinking status, smoking, hypertension, and afternoon napping duration. Result: 549 respondents acquired diabetes during a median follow-up of 84 months. After controlling for confounders, night sleep duration was substantially linked with new-onset diabetes in the multivariable Cox regression model. The risk of diabetes is lower for respondents who sleep longer than 5 hours, except for those who sleep over 8 hours [5.1-6h Hazard ratios (HR) [95% confidence intervals (CI)] = 0.71 (0.55, 0.91); 6.1-7h HR = 0.69 (0.53, 0.89); 7.1-8h HR = 0.58 (0.45, 0.76)]. Nonlinear connections were delineated by significant inflection points at 3.5 and 7.5 hours, with a negative correlation observed only between these thresholds. With one hour more night sleep, the risk of diabetes drops 15%. BMI and dyslipidemia were identified as modifiers when only consider the stand linear effect of sleep duration on diabetes. Conclusion: This study establishes a robust association between night sleep and new-onset diabetes in middle-aged and older Chinese individuals within the 3.5-7.5-hour range, offering a foundation for early glycemic management interventions in this demographic. The findings also underscore the pivotal role of moderate night sleep in preventing diabetes, marking a crucial juncture in community medical research.

Association between sleep duration and possible sarcopenia in middle-aged and elderly Chinese individuals: evidence from the China health and retirement longitudinal study.

BACKGROUND: Sarcopenia is a common cause of disability in the aging population, and managing sarcopenia is an important step in building intrinsic capacity and promoting healthy aging. A growing body of evidence suggests that sleep deprivation may be a mediator of the development of sarcopenia. The purpose of this study was to explore the longitudinal association between sleep duration and possible sarcopenia using data from a national sample. METHODS: Two waves of data from the CHARLS database for 2011 and 2015 were used in this study. All possible sarcopenia participants met the Asia Working Group for Sarcopenia 2019 (AWGS 2019) diagnostic criteria. Sleep duration was assessed using a self-report questionnaire, and sleep duration was categorized as short (≤ 6 h), medium (6-8 h), or long (> 8 h) based on previous studies. Longitudinal associations between sleep duration and possible sarcopenia will be calculated by univariate and multifactorial logistic regression analyses and expressed as odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: A total of 5654 individuals participated in the follow-up study, with a prevalence of possible sarcopenia of 53.72% (578) in the short sleep duration group, 38.29% (412) in the medium sleep duration group, and 7.99% (86) in the long sleep duration group. According to the crude model of the second-wave follow-up study, short sleep durations were significantly more strongly associated with possible sarcopenia than were medium and long sleep durations (OR: 1.35, 95% CI: 1.17-1.55, P = 0.000). The association between short sleep duration and possible sarcopenia was maintained even after adjustment for covariates such as age, gender, residence, education level, BMI, smoking status, alcohol consumption and comorbidities (OR: 1.18, 95% CI: 1.02-1.36, P = 0.029). In the subgroup analysis, short sleep duration was associated with low grip strength (OR: 1.20, 95% CI: 1.02-1.41, P = 0.031). CONCLUSIONS: Sleep deprivation may be closely associated with the development of possible sarcopenia in middle-aged and elderly people, which provides new insights and ideas for sarcopenia intervention, and further studies are needed to reveal the underlying mechanisms involved.

Association between triglyceride glucose-waist height ratio index and cardiovascular disease in middle-aged and older Chinese individuals: a nationwide cohort study.

BACKGROUND: The triglyceride-glucose (TyG) index and its combination with obesity indicators can predict cardiovascular diseases (CVD). However, there is limited research on the relationship between changes in the triglyceride glucose-waist height ratio (TyG-WHtR) and CVD. Our study aims to investigate the relationship between the change in the TyG-WHtR and the risk of CVD. METHODS: Participants were from the China Health and Retirement Longitudinal Study (CHARLS). CVD was defined as self-reporting heart disease and stroke. Participants were divided into three groups based on changes in TyG-WHtR using K-means cluster analysis. Multivariable binary logistic regression analysis was used to examine the association between different groups (based on the change of TyG-WHtR) and CVD. A restricted cubic spline (RCS) regression model was used to explore the potential nonlinear association of the cumulative TyG-WHtR and CVD events. RESULTS: During follow-up between 2015 and 2020, 623 (18.8%) of 3312 participants developed CVD. After adjusting for various potential confounders, compared to the participants with consistently low and stable TyG-WHtR, the risk of CVD was significantly higher in participants with moderate and increasing TyG-WHtR (OR 1.28, 95%CI 1.01-1.63) and participants with high TyG-WHtR with a slowly increasing trend (OR 1.58, 95%CI 1.16-2.15). Higher levels of cumulative TyG-WHtR were independently associated with a higher risk of CVD events (per SD, OR 1.27, 95%CI 1.12-1.43). CONCLUSIONS: For middle-aged and older adults, changes in the TyG-WHtR are independently associated with the risk of CVD. Maintaining a favorable TyG index, effective weight management, and a reasonable waist circumference contribute to preventing CVD.

Association between different triglyceride-glucose index combinations with obesity indicators and arthritis: results from two nationally representative population-based study.

BACKGROUND: Insulin resistance (IR) and arthritis are strongly associated, and the triglyceride-glucose (TyG) index combinations with obesity indicators [including TyG-BMI (glucose triglyceride-body mass index), TyG-WC (glucose triglyceride-waist circumference), and TyG-WHtR (glucose triglyceride-waist height ratio)] has recently been recognized as a more effective indicator for assessing IR. However, there is a lack of research on its association with arthritis, and it is also important to assess in different populations. METHODS: The analysis utilized data from the China Health and Retirement Longitudinal Study (CHARLS) and the National Health and Nutrition Examination Survey (NHANES). Arthritis diagnosis relied on self-reporting confirmed by physicians. The association of TyG-BMI, TyG-WC, and TyG-WHtR with arthritis was analyzed through weighted logistic regression models, and exploring nonlinear effects with restricted cubic spline (RCS) models. Secondary and sensitivity analyses included receiver operating characteristic curve (ROC) analysis, comparisons of z score-related odds ratios, subgroup analyses, and multiple imputation. RESULTS: The study involved 6141 CHARLS participants and 17,091 NHANES participants. Adjusting for confounding variables, TyG-BMI and TyG-WHtR demonstrate a positive correlation with arthritis prevalence in both CHARLS (TyG-BMI: OR = 1.02, 95% CI 1.00-1.04; TyG-WHtR: OR = 1.13, 95% CI 1.03-1.24) and NHANES (TyG-BMI: OR = 1.07, 95% CI 1.06-1.08; TyG-WHtR: OR = 1.50, 95% CI 1.40-1.60). RCS regression analysis demonstrated a significant nonlinear association. ROC analysis indicated that TyG-BMI and TyG-WHtR were superior to TyG for the diagnosis of arthritis in both CHARLS and NHANES. CONCLUSIONS: TyG-BMI and TyG-WHtR demonstrate a positive correlation with arthritis prevalence in both Chinese and the U.S. populations, displaying superior diagnostic relevance compared to TyG.

Longitudinal relationship between weight-adjusted waist index and depressive symptoms in middle-aged and older Chinese adults: A prospective cohort study.

BACKGROUND: The association between obesity and depressive symptoms remains controversial. The Weight-adjusted waist index (WWI) shows advantages in assessing central obesity. This study aimed to investigate the longitudinal relationship between WWI and depressive symptoms. METHOD: This prospective cohort study utilized data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011-2020. Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depressive Symptoms Scale (CESD-10) scores. Linear mixed models were used to examine longitudinal associations. RESULTS: A total of 6835 participants over the age of 45 were included. WWI was positively associated with CESD-10 scores (ß per 1 SD increase = 0.052SD; 95%CI: 0.021 to 0.083SD) and was linked to a faster increase in CESD-10 scores over time (ß = 0.095SD/year; 95%CI: 0.090 to 0.100 SD/year). Conversely, BMI was negatively associated with CESD-10 scores (ß per 1 SD increase = -0.067SD; 95%CI: -0.097 to -0.038SD). However, the negative association between BMI and CESD-10 scores weakened over time (ß per 1 SD increase = 0.008SD/y; 95%CI: 0.003 to 0.013 SD/y). Nonlinear associations were detected between both WWI and BMI with CESD-10 scores. LIMITATIONS: Self-reported depressive symptoms assessments may have introduced information bias. The observational design limits ruling out unobserved confounding factors. CONCLUSIONS: Our findings highlight the association between WWI and the long-term progression of depressive symptoms in middle-aged and older adults. WWI may enhance our understanding of the link between obesity and depressive symptoms and could be superior to BMI in predicting depressive symptom progression.

Association of Air Quality Improvement and Frailty Progression: A National Study across China.

Accumulating evidence strongly suggests that exposure to ambient air pollution is linked with increased frailty. However, little is known about the effect of improved air quality on frailty progression. We aimed to investigate whether improvements in air quality (PM1, PM2.5, PM10, NO2, and O3) can alleviate frailty progression, particularly in the aftermath of implementation of the "Clean Air Action" policy in China. The study involved 12,891 participants with geocoded environmental data from the nationwide China Health and Retirement Longitudinal Study (CHARLS) during the period from May 2011 to August 2015. Multivariate logistic regression models were used to analyze the association of air pollution improvements and frailty progression. The protective effects were noted for PM1, PM2.5, PM10, and NO2 indices, with an aOR (adjusted odds ratio) ranging from 0.72 to 0.79. Air quality improvement in PM1, PM2.5, PM10, and NO2 could alleviate the progression of frailty. The study is the first to examine the association between the improvement of air quality and the progression of frailty, setting a precedent for the importance of a nationwide clean air policy and its impact on healthy ageing.

The association between declining lung function and stroke risk: insights from an observational study and Mendelian randomization.

Background: Stroke, prevalent globally, particularly impacts low- and middle-income countries. Decreased lung function is one of the risk factors for stroke, and there is a lack of sufficient research on the association between the two, especially based on evidence from representative large samples. We aimed to explore the association between lung function and stroke incidence. Methods: We collected data from 13,371 participants from the 2007-2012 U.S. national cross-sectional study and 11,192 participants from the Chinese national cohort study during the 2011-2018 follow-up period. Multivariate logistic regression and Cox proportional hazards regression were used to assess cross-sectional and longitudinal associations of peak expiratory flow with stroke risks. Additionally, we used publicly available GWAS data from a European population to conduct Mendelian randomization analysis, further exploring the potential causal relationship. Results: The results of the cross-sectional study suggest that a decline in peak expiratory flow may be associated with an increased risk of stroke. The cohort study revealed that, compared to the first tertile group, the risk of stroke incidence in the second and third tertile groups of PEF decreased by 19% (hazard ratio (HR) = 0.810, 95%CI = 0.684-0.960) and 21.4% (HR = 0.786, 95%CI = 0.647-0.956), respectively. Mendelian randomization analysis clarified that higher PEF levels are significantly associated with a reduced risk of stroke (OR = 0.852, 95%CI = 0.727-0.997). Conclusion: Decreased lung function is a risk factor for stroke. As a simple and accurate indicator of lung function, PEF can be used to monitor lung function in community populations and patients for primary stroke prevention.

Sleep duration and the risk of new-onset arthritis in middle-aged and older adult population: results from prospective cohort study in China.

Background: The pain and sleep disorders caused by arthritis are health issues that have been re-emphasized with the aging population. However, the majority of research on arthritis and sleep disorders has focused on cases that have already been diagnosed with arthritis. This research aims to explore the correlation between sleep duration and new-onset arthritis in middle-aged and older adult individuals. Methods: Utilizing data from the China Health and Retirement Longitudinal Study from baseline (2011) to the Wave 3 follow-up (2018), we conducted a 7-year longitudinal investigation targeting populations with valid sleep questionnaire records and without arthritis. Sleep duration was assessed from nighttime sleep and daytime nap records. The new-onset of arthritis was determined based on self-reported diagnosis. We employed different logistic regression models to consider the potential impact of sleep duration on arthritis and conducted mediation analyses to assess the involvement of BMI in the association between sleep duration and the new-onset risk of arthritis. Results: Out of the 6,597 individuals analyzed in the cohort, 586 (8.9%) were diagnosed with new-onset arthritis. Median sleep duration was notably shorter in the new-onset arthritis group (6.63 vs. 6.41 h, p < 0.05). There was a notable negative correlation found between new-onset risk of arthritis and sleep duration, with each Interquartile Range (IQR) increment in sleep leading to a 16% risk reduction (OR: 0.864; 95% CI: 0.784-0.954). Stratified analyses revealed BMI as a potential modifier in the sleep-arthritis relationship (P for interaction = 0.05). Mediation analyses further showed that about 3.5% of the association was mediated by BMI. Additionally, the inclusion of sleep duration improved the arthritis predictive power of our model, with an IDI of 0.105 (0.0203, 0.1898) and an NRI of 0.0013 (0.0004, 0.0022) after adding sleep duration to the basic model. Conclusion: In the middle-aged and older adult demographic of China, increased sleep duration is associated with a decreased new-onset risk of arthritis, with BMI potentially playing a role in mediating this connection.

Development and validation of prediction model for fall accidents among chronic kidney disease in the community.

Background: The population with chronic kidney disease (CKD) has significantly heightened risk of fall accidents. The aim of this study was to develop a validated risk prediction model for fall accidents among CKD in the community. Methods: Participants with CKD from the China Health and Retirement Longitudinal Study (CHARLS) were included. The study cohort underwent a random split into a training set and a validation set at a ratio of 70 to 30%. Logistic regression and LASSO regression analyses were applied to screen variables for optimal predictors in the model. A predictive model was then constructed and visually represented in a nomogram. Subsequently, the predictive performance was assessed through ROC curves, calibration curves, and decision curve analysis. Result: A total of 911 participants were included, and the prevalence of fall accidents was 30.0% (242/911). Fall down experience, BMI, mobility, dominant handgrip, and depression were chosen as predictor factors to formulate the predictive model, visually represented in a nomogram. The AUC value of the predictive model was 0.724 (95% CI 0.679-0.769). Calibration curves and DCA indicated that the model exhibited good predictive performance. Conclusion: In this study, we constructed a predictive model to assess the risk of falls among individuals with CKD in the community, demonstrating good predictive capability.

Association of the intergenerational structure with the onset of depressive symptoms among middle-aged and older adults in China.

BACKGROUND: Chinese family structure has undergone tremendous changes over the past few decades. Moreover, the association of the intergenerational structure with depression remains controversial. AIMS: This study aimed to find out the association of the intergenerational structure and the onset of depressive symptoms among Chinese middle-aged and older adults. METHODS: This study included 4,868 participants of the China Health and Retirement Longitudinal Study (CHARLS), who were enrolled in 2011 without depressive symptoms and followed up at least once later in 2013, 2015, 2018, and 2020. Taking the time-varying confounding effect into account, the time-dependent Cox regression models were used to estimate the association of the intergenerational structure and the onset of depressive symptoms. RESULTS: Among the studied middle-aged and older adults, compared to one-generation households, higher hazard ratios (HR) of developing depressive symptoms were found in three-generation households in the study population (HR = 1.21, 95% CI [1.08, 1.36]). Further, for female participants, skipping-generation households (HR = 1.38, 95% CI [1.05, 1.83]) and three-generation lineal households (HR = 1.21, 95% CI [1.02, 1.43]) were found to be significantly associated with new-onset depressive symptoms compared to empty-nest couples. For male participants, living alone (HR = 1.65, 95% CI [1.30, 2.11]), living in standardized nuclear households (HR = 1.27, 95% CI [1.06, 1.54]), impaired nuclear households (HR = 1.80, 95% CI [1.18, 2.76]), or three-generation lineal households (HR = 1.34, 95% CI [1.12, 1.60]) were found to have a significant association with the onset of depressive symptoms. CONCLUSIONS: This study found that males living alone, with unmarried children, or in three-generation lineal households, and females living with grandchildren were more likely to suffer from depressive symptoms. Therefore, special attention should be paid to people in these intergenerational structure subtypes.

Correlation of cardiometabolic index and sarcopenia with cardiometabolic multimorbidity in middle-aged and older adult: a prospective study.

Background: Research has demonstrated that sarcopenia and visceral obesity are significant risk factors for chronic disease in middle-aged and older adults. However, the relationship between sarcopenia, the cardiac metabolic index (CMI), a novel measure of visceral obesity, and cardiometabolic multimorbidity (CMM) remains unclear. In this study, data from the China Longitudinal Study of Health and Retirement (CHARLS) were analyzed to investigate the association between sarcopenia and CMI with CMM in the middle-aged and older adult population. Methods: The study included 4,959 participants aged 45 and over. Sarcopenia was defined using the criteria of the Asian Sarcopenia Working Group 2019. CMM is defined as having two or more of the following conditions: physician-diagnosed heart disease, diabetes, stroke, and/or hypertension. CMI was calculated using the formula: CMI = (TG/HDL-C) × WHtR. To explore the association between CMI and sarcopenia and CMM, cox proportional risk regression models were used. Results: The median age of all participants was 57 years, with 47.1% being male. Over the 8-year follow-up, 1,362 individuals developed CMM. The incidence of CMM was 8.7/1,000 person-years in the group without sarcopenia or high CMI, 17.37/1,000 person-years in those with high CMI, 14.22/1,000 person-years in the sarcopenia group, and 22.34/1,000 person-years in the group with both conditions. After adjusting for covariates, the group with both sarcopenia and high CMI had a significantly increased risk of CMM (HR 2.48, 95% CI 1.12-5.51) and heart disease (HR 2.04, 95% CI 1.05-3.98). Among those over 65 years, sarcopenia was discovered to be associated with an increased risk of CMM [HR (95% CI: 4.83 (1.22, 19.06)]. The risk of CMM was further increased to 7.31-fold (95% CI:1.72, 31.15) when combined with high CMI. Conclusions: The combination of sarcopenia and high CMI is associated with an increased risk of developing CMM. Early identification and intervention of sarcopenia and CMI not only enable the development of targeted therapeutic strategies but also provide potential opportunities to reduce the morbidity and mortality of CMM.

Associations between peak expiratory flow and frailty in olderly individuals: findings from the China health and retirement longitudinal study.

Purpose: Peak Expiratory Flow (PEF) is associated with a variety of adverse health outcomes in older adults; however, the relationship between PEF and frailty remains uncertain, and this study investigated the relationship between PEF and frailty within an olderly Asian demographic. Methods: Data were sourced from the Chinese Health and Retirement Longitudinal Study (CHARLS). Individuals in the study, all 60 years or older, underwent baseline PEF assessments quantified as standardized residual (SR) percentile values. The evaluation of frailty was conducted based on the criteria established by Fried. Participants without frailty at the outset were tracked over a four-year period, during which the relationships between PEF and frailty were examined through logistic regression and discrete-time Cox regression analyses. Results: Among 5,060 participants, cross-sectional analysis revealed that the prevalence of frailty was 2-3 times higher in the lower 10-49th and < 10th SR percentile groups compared to the 80-100th SR percentile group. The longitudinal study corroborated these results, showing an adjusted hazard ratio (HR) of 2.01 (95% CI, 1.15-3.51) for PEF SR percentiles below the 10th, in contrast to those between the 80th and 100th percentiles. Conclusion: PEF independently predicts and determines frailty in older adults. Declines in PEF greater than expected are associated with the development of frailty. Subsequent studies are encouraged to delve deeper into the connection between respiratory function and frailty in diverse contexts.

U-shaped relationship between non-high-density lipoprotein cholesterol and cognitive impairment in Chinese middle-aged and elderly: a cross-sectional study.

BACKGROUND: The relationship between blood lipids and cognitive function has long been a subject of interest, and the association between serum non-high-density lipoprotein cholesterol (non-HDL-C) levels and cognitive impairment remains contentious. METHODS: We utilized data from the 2011 CHARLS national baseline survey, which after screening, included a final sample of 10,982 participants. Cognitive function was assessed using tests of episodic memory and cognitive intactness. We used multiple logistic regression models to estimate the relationship between non-HDL-C and cognitive impairment. Subsequently, utilizing regression analysis results from fully adjusted models, we explored the nonlinear relationship between non-HDL-C as well as cognitive impairment using smooth curve fitting and sought potential inflection points through saturation threshold effect analysis. RESULTS: The results showed that each unit increase in non-HDL-C levels was associated with a 5.5% reduction in the odds of cognitive impairment (OR = 0.945, 95% CI: 0.897-0.996; p < 0.05). When non-HDL-C was used as a categorical variable, the results showed that or each unit increase in non-HDL-C levels, the odds of cognitive impairment were reduced by 14.2%, 20.9%, and 24% in the Q2, Q3, and Q4 groups, respectively, compared with Q1. In addition, in the fully adjusted model, analysis of the potential nonlinear relationship by smoothed curve fitting and saturation threshold effects revealed a U-shaped relationship between non-HDL-C and the risk of cognitive impairment, with an inflection point of 4.83. Before the inflection point, each unit increase in non-HDL-C levels was associated with a 12.3% decrease in the odds of cognitive impairment. After the tipping point, each unit increase in non-HDL-C levels was associated with an 18.8% increase in the odds of cognitive impairment (All p < 0.05). CONCLUSION: There exists a U-shaped relationship between non-HDL-C and the risk of cognitive impairment in Chinese middle-aged and elderly individuals, with statistical significance on both sides of the turning points. This suggests that both lower and higher levels of serum non-high-density lipoprotein cholesterol increase the risk of cognitive impairment in middle-aged and elderly individuals.

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.

Association between remnant cholesterol and the risk of cardiovascular disease in Chinese population.

OBJECTIVES: Previous genetic, observational, and clinical intervention studies reported that circulating levels of remnant cholesterol was associated with cardiovascular disease (CVD). However, whether remnant cholesterol can predict CVD events in Chinese population was not well characterized. STUDY DESIGN: This was a prospective cohort study. METHODS: We used the data of 9456 Chinese adults aged ≥45 years from the China Health and Retirement Longitudinal Study (CHARLS). Estimated remnant cholesterol was calculated as total cholesterol minus high-density lipoprotein cholesterol minus low-density lipoprotein cholesterol. Cox proportional hazard models and restricted cubic spline models were used to assess the relationships between remnant cholesterol levels and CVD, stroke and cardiac events. RESULTS: During 7 years of follow-up, a total of 886 (9.37 %) respondents experienced CVD, 392 (4.15 %) experienced stroke and 544 (5.75 %) experienced cardiac events. In multivariable-adjusted analyses, the adjusted hazard ratios (95 % confidence interval) for the highest versus lowest quartile of remnant cholesterol were 1.14 (1.02-1.32) for CVD and 1.43 (1.12-1.82) for stroke, and each 1-SD increase of log-transformed remnant cholesterol (2.93 mg/dl) was associated with 5 % and 11 % increased risk of the CVD and stroke, respectively. Remnant cholesterol was not associated with increased risk of cardiac events. CONCLUSION: Elevated remnant cholesterol levels were positively associated with CVD and stroke in Chinese adult population, suggesting that remnant cholesterol could be considered as a preferential predictor and treatment target of CVD in Chinese population.

Clean energy consumption, sleep duration, and the association of cancer: findings from the China health and retirement longitudinal study.

Objective: Studies of the association between clean energy consumption, sleep duration, and cancer are still extremely limited. We aim to investigate the individual or joint role of clean energy consumption, and sleep duration in cancer onset. Methods: We used data from the China Health and Retirement Longitudinal Study. Multivariable locally weighted regression (LOESS) models were first used to assess the individual association of daily sleep time with the risk to develop cancer. Multivariate logistic regression models were conducted on the individual and interaction effects of daily sleep time and cooking fuel. Results: We found that short sleep duration (≤6 hours) and non-clean energy consumption were respectively associated with an increased risk of cancer among older Chinese(p<0.05). We assessed daily sleep time in four quartiles, the adjusted odds ratios (AOR), and 95% confidence intervals (95% CI) for participants in the second (5.0 to <6.5 hours), third (6.5 to <8.0 hours), and fourth quartiles (≥8.0 hours) were 0.88 (95% CI: 0.65-1.20), 0.61 (95% CI: 0.40-0.91), and 0.53 (95% CI: 0.37-0.77), respectively. When we set the cutoff point(6.5 hours), participants who slept more than 6 hours had a 39% lower risk of cancer (AOR: 0.61, 95% CI: 0.46-0.79) compared with others. On the other hand, we conducted that exposure to clean fuel from cooking was negatively associated with cancer incidence (AOR: 0.73, 95% CI: 0.54, 0.97). Furthermore, the combination of longer sleep and cleaner fuels showed the lowest OR for cancer (AOR: 0.39, 95% CI: 0.24, 0.65). Conclusion: Our study showed that sleep duration and clean energy consumption were significantly associated with cancer in elderly Chinese people. In addition, the prevalence of cancer was higher among people who slept less than six hours and used non-clean energy sources. Paying greater attention to the effects of sleep duration and clean energy on the risk of cancer may yield practical implications for cancer prevention.

Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health.

Background: EPs pose significant challenges to individual health and quality of life, attracting attention in public health as a risk factor for diminished quality of life and healthy life expectancy in middle-aged and older adult populations. Therefore, in the context of global aging, meticulous exploration of the factors behind emotional issues becomes paramount. Whether ADL can serve as a potential marker for EPs remains unclear. This study aims to provide new evidence for ADL as an early predictor of EPs through statistical analysis and validation using machine learning algorithms. Methods: Data from the 2018 China Health and Retirement Longitudinal Study (CHARLS) national baseline survey, comprising 9,766 samples aged 45 and above, were utilized. ADL was assessed using the BI, while the presence of EPs was evaluated based on the record of "Diagnosed with Emotional Problems by a Doctor" in CHARLS data. Statistical analyses including independent samples t-test, chi-square test, Pearson correlation analysis, and multiple linear regression were conducted using SPSS 25.0. Machine learning algorithms, including Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR), were implemented using Python 3.10.2. Results: Population demographic analysis revealed a significantly lower average BI score of 65.044 in the "Diagnosed with Emotional Problems by a Doctor" group compared to 85.128 in the "Not diagnosed with Emotional Problems by a Doctor" group. Pearson correlation analysis indicated a significant negative correlation between ADL and EPs (r = -0.165, p < 0.001). Iterative analysis using stratified multiple linear regression across three different models demonstrated the persistent statistical significance of the negative correlation between ADL and EPs (B = -0.002, ß = -0.186, t = -16.476, 95% CI = -0.002, -0.001, p = 0.000), confirming its stability. Machine learning algorithms validated our findings from statistical analysis, confirming the predictive accuracy of ADL for EPs. The area under the curve (AUC) for the three models were SVM-AUC = 0.700, DT-AUC = 0.742, and LR-AUC = 0.711. In experiments using other covariates and other covariates + BI, the overall prediction level of machine learning algorithms improved after adding BI, emphasizing the positive effect of ADL on EPs prediction. Conclusion: This study, employing various statistical methods, identified a negative correlation between ADL and EPs, with machine learning algorithms confirming this finding. Impaired ADL increases susceptibility to EPs.

The association between circadian syndrome and chronic kidney disease in an aging population: a 4-year follow-up study.

Introduction: Circadian syndrome (CircS) is proposed as a novel risk cluster based on reduced sleep duration, abdominal obesity, depression, hypertension, dyslipidemia and hyperglycemia. However, the association between CircS and chronic kidney disease (CKD) remains unclear. To investigate the cross-sectional and longitudinal association between CircS and CKD, this study was performed. Methods: A national prospective cohort (China Health and Retirement Longitudinal Study, CHARLS) was used in this study. To define CKD, the estimated glomerular filtration rate (eGFR) was calculated based on the 2012 CKD-EPI creatinine-cystatin C equation. Participants with eGFR <60 mL.min-1/1.73/m2 were diagnosed with CKD. Multivariate binary logistic regression was used to assess the cross-sectional association between CircS and CKD. Subgroup and interactive analyses were performed to determine the interactive effects of covariates. In the sensitivity analysis, the obese population was excluded and another method for calculating the eGFR was used to verify the robustness of previous findings. In addition, participants without CKD at baseline were followed up for four years to investigate the longitudinal relationship between CircS and CKD. Results: A total of 6355 participants were included in this study. In the full model, CircS was positively associated with CKD (OR = 1.28, 95% CI = 1.04-1.59, P < 0.05). As per one increase of CircS components, there was a 1.11-fold (95% CI = 1.04-1.18, P < 0.05) risk of prevalent CKD in the full model. A significant interactive effect of hyperuricemia in the CircS-CKD association (P for interaction < 0.01) was observed. Sensitivity analyses excluding the obese population and using the 2009 CKD-EPI creatinine equation to diagnose CKD supported the positive correlation between CircS and CKD. In the 2011-2015 follow-up cohort, the CircS group had a 2.18-fold risk of incident CKD (95% CI = 1.33-3.58, P < 0.01) in the full model. The OR was 1.29 (95% CI = 1.10-1.51, P < 0.001) with per one increase of CircS components. Conclusion: CircS is a risk factor for CKD and may serve as a predictor of CKD for early identification and intervention.