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.

Obesity-and lipid-related indices as a risk factor of hypertension in mid-aged and elderly Chinese: a cross-sectional study.

OBJECTIVE: Hypertension refers to the persistent elevation of blood pressure above the established normal range, resulting in increased pressure exerted by blood on the walls of blood vessels during its circulation. Recent studies have identified significant associations between obesity and lipid-related indices, as well as hypertension. Nevertheless, these studies have yet to comprehensively examine the correlation between the two variables. Our objective is to identify the fat and lipid-related indices that have the strongest correlation with hypertension. METHOD: There was a total of 9488 elderly and middle-aged Chinese citizens who participated in this investigation. The participants in this research were separated into distinct gender cohorts. The participants were classified into normal and hypertensive categories according to their gender, with hypertension defined as a blood pressure level of 140/90 mmHg or higher, or a history of hypertension. Through the utilization of binary logistic regression analyses and the receiver operator curve (ROC), the optimal among fourteen indicators associated with obesity and lipids were identified. RESULTS: After adjusting for variables, statistical analysis showed that all 14 measures of obesity and lipid were risk factors for hypertension. The receiver operating characteristic (ROC) curve analysis reveals that the Chinese visceral adiposity index (CVAI) has the highest degree of relationship to hypertension. Simultaneously, a statistically significant association between hypertension and these 14 variables was observed in both males and females. CONCLUSION: There was a significant independent association between various parameters related to obesity and lipid-related index and the presence of hypertension, indicating that these factors can be considered risk factors for hypertension. CVAI and WHtR (waist height ratio) can be used to screen the high-risk groups of hypertensions in middle-aged and elderly people in China, and then take individualized health care measures to reduce the harm of hypertension.

Multidimensional Internet Use, Social Participation, and Depression Among Middle-Aged and Elderly Chinese Individuals: Nationwide Cross-Sectional Study.

BACKGROUND: There is growing evidence that the internet has beneficial effects on the mental health of middle-aged and older people (≥45 years), but the evidence is inconclusive, and the underlying mechanisms are less known. OBJECTIVE: This study aims to explore the relationship between multidimensional (devices, frequency, and purpose) internet use and depression in middle-aged and elderly Chinese, as well as the mediating effect of social participation. Moreover, this study will explore the moderating effect of the regional informatization development level (RIDL) on the relationships between individual internet use, social participation, and depression. METHODS: Data on 17,676 participants aged 45 years or older were obtained from the China Health and Retirement Longitudinal Study (CHARLS) 2018 data set. The 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10) was used to identify the presence of depression. Logistic regression was used to explore the relationship between each dimension of internet use and depression. Multiple linear regression was used to explore the mediating effect of social participation and the moderating effect of the RIDL. RESULTS: The results showed that 28.33% (5008/17,676) of the total population had depression. In terms of regional subgroups, respondents living in the western region exhibited the highest proportion of depression (2041/5884, 34.69%). Internet use was negatively associated with depression (odds ratio 0.613, 95% CI 0.542-0.692; P<.001). Various dimensions of internet use positively contributed to individual social participation and reduced individual depression (devices: ß=-.170, 95% CI -0.209 to -0.127; frequency: ß=-.065, 95% CI -0.081 to -0.047; and purpose: ß=-.043, 95% CI -0.053 to -0.031). In addition, the RIDL weakened the relationship between individual-level internet use and social participation (internet use: F74.12,9.82=7.55, P<.001; devices: F51.65/9.88=5.23, P=.005; frequency: F66.74/10.08=6.62, P=.001; and purpose: F66.52/9.78=6.80, P=.001), and negatively moderated the relationship between the frequency of internet use and depression (frequency: F662.67/188.79=3.51, P=.03). CONCLUSIONS: This study found that different dimensions of internet use are associated with lower levels of depression. Social participation partially mediates the association between multidimensional internet use and depression in the eastern, central, and western regions, respectively. Additionally, the RIDL helps individuals further their internet use and social participation, reducing the impact of depression. However, this effect weakens sequentially from the western region to the central region and then to the eastern region.

Obesity-and lipid-related indices as a predictor of hypertension in Mid-aged and Elderly Chinese: A Cross-sectional Study.

Objective: Middle-aged and elderly people in China probably suffer from hypertension. There is a close relationship between obesity-and lipid-related index and hypertension, which is recognized by recent studies. However, these studies have not systematically compared the relationship between the two. We aim to find the most effective obesity-and lipid-related index for predicting hypertension. Method: A total of 9488 middle-aged and elderly people in China participated in this study. In this study, the subjects were divided into male and female groups by the definition of the 2018 Chinese Guidelines for Prevention and Treatment of Hypertension. Searching for the best predictors among 13 obesity-and lipid-related indicators through binary logistic regression analyses and receiver operator curve (ROC). These 13 indicators are body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), conicity index (CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). Results: After adjusting bias, all 13 indexes are risk factors for hypertension. In ROC curve analysis, thirteen obesity-and lipid-related factors can predict the occurrence of hypertension. Among them, CVAI has the best prediction effect (male: AUC = 0.660, female: AUC = 0.699). AUC for WHtR was equal to that for BRI and TyG - WHtR in identifying hypertension in male. Similarly, AUC of TyG-BMI and BMI were the same. In females, AUC for WHtR and BRI were the same when predicting hypertension. AUC of ABSI was much lower than other test indexes. Conclusion: In predicting hypertension, thirteen obesity-and lipid-related factors are effective. In addition, in males and females, CVAI is the best indicator to indicate hypertension. TyG-WHtR, WHtR, and BRI performed well in predicting metabolic syndrome in both males and females. ABSI has a poor ability to predict hypertension.

Obesity- and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study.

Objective: Metabolic syndrome is a common condition among middle-aged and elderly people. Recent studies have reported the association between obesity- and lipid-related indices and metabolic syndrome, but whether those conditions could predict metabolic syndrome is still inconsistent in a few longitudinal studies. In our study, we aimed to predict metabolic syndrome by obesity- and lipid-related indices in middle-aged and elderly Chinese adults. Method: A national cohort study that consisted of 3,640 adults (≥45 years) was conducted. A total of 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), conicity index (CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), and triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, and TyG-WHtR), were recorded. Metabolic syndrome (MetS) was defined based on the criteria of the National Cholesterol Education Program Adult Treatment Panel III (2005). Participants were categorized into two groups according to the different sex. Binary logistic regression analyses were used to evaluate the associations between the 13 obesity- and lipid-related indices and MetS. Receiver operating characteristic (ROC) curve studies were used to identify the best predictor of MetS. Results: A total of 13 obesity- and lipid-related indices were independently associated with MetS risk, even after adjustment for age, sex, educational status, marital status, current residence, history of drinking, history of smoking, taking activities, having regular exercises, and chronic diseases. The ROC analysis revealed that the 12 obesity- and lipid-related indices included in the study were able to discriminate MetS [area under the ROC curves (AUC > 0.6, P < 0.05)] and ABSI was not able to discriminate MetS [area under the ROC curves (AUC < 0.6, P > 0.05)]. The AUC of TyG-BMI was the highest in men, and that of CVAI was the highest in women. The cutoff values for men and women were 187.919 and 86.785, respectively. The AUCs of TyG-BMI, CVAI, TyG-WC, LAP, TyG-WHtR, BMI, WC, WHtR, BRI, VAI, TyG index, CI, and ABSI were 0.755, 0.752, 0.749, 0.745, 0.735, 0.732, 0.730, 0.710, 0.710, 0.674, 0.646, 0.622, and 0.537 for men, respectively. The AUCs of CVAI, LAP, TyG-WC, TyG-WHtR, TyG-BMI, WC, WHtR, BRI, BMI, VAI, TyG-index, CI, and ABSI were 0.687, 0.674, 0.674, 0.663, 0.656, 0.654, 0.645, 0.645, 0.638, 0.632, 0.607, 0.596, and 0.543 for women, respectively. The AUC value for WHtR was equal to that for BRI in predicting MetS. The AUC value for LAP was equal to that for TyG-WC in predicting MetS for women. Conclusion: Among middle-aged and older adults, all obesity- and lipid-related indices, except ABSI, were able to predict MetS. In addition, in men, TyG-BMI is the best indicator to indicate MetS, and in women, CVAI is considered the best hand to indicate MetS. At the same time, TyG-BMI, TyG-WC, and TyG-WHtR performed better than BMI, WC, and WHtR in predicting MetS in both men and women. Therefore, the lipid-related index outperforms the obesity-related index in predicting MetS. In addition to CVAI, LAP showed a good predictive correlation, even more closely than lipid-related factors in predicting MetS in women. It is worth noting that ABSI performed poorly, was not statistically significant in either men or women, and was not predictive of MetS.

Association between Different Types of Plant-Based Diets and Dyslipidemia in Middle-Aged and Elderly Chinese Participants.

Plant-based dietary patterns may reduce the risk of dyslipidemia. However, not all plant-based foods are beneficial, and limited data exist for the Chinese population. We investigated the association between different plant-based dietary indices and the risk of dyslipidemia in a Chinese middle-aged and elderly population. The study participants (n = 4096) consisted of adults between 35 and 74 years of age from Xinjiang, China. Dietary consumption of the study participants was evaluated using a semi-quantitative food-frequency questionnaire (FFQ). Three different plant-based dietary indices were calculated using data from dietary surveys, including overall plant-based diet index (PDI), healthy plant-based diet index (hPDI), and unhealthy plant-based diet index (uPDI). Based on these indices, we created an adjusted plant-based diet index (aPDI) based on the Xinjiang population actual dietary behavior and health effects of food. We measured the levels of total cholesterol, triglyceride, LDL-C, and HDL-C in the blood of the study participants. We used multivariable logistic regression and restricted cubic spline to analyze the relationship between plant-based diets and dyslipidemia. The findings showed that 36.6% of the participants had dyslipidemia. Higher PDI adherence was related to lower odds of dyslipidemia (Q3 vs. Q1, OR: 0.780, 95% CI: 0.641-0.949; Q4 vs. Q1, OR: 0.799, 95% CI: 0.659-0.970). High aPDI was related to lower odds of dyslipidemia (Q4 vs. Q1, OR: 0.770, 95% CI: 0.628-0.945; Q5 vs. Q1, OR: 0.748, 95% CI: 0.607-0.921). High scores for PDI, hPDI, and aPDI were all related to a reduced risk of low HDL-C (OR: 0.638, 95% CI: 0.491-0.823; OR: 0.661, 95% CI: 0.502-0.870; OR: 0.580, 95% CI: 0.443-0.758). Conversely, a high uPDI score was associated with an increased risk of low HDL-C (OR: 1.349, 95% CI: 1.046-1.740). There was no non-linear relationship between PDI, hPDI, uPDI, and aPDI and the risk of different types of dyslipidemia. Plant-based dietary indices are related to specific types of dyslipidemia risk. Appropriately increasing the consumption of plant-based foods while improving the quality of plant-based dietary patterns is critical for the prevention of dyslipidemia, especially low HDL-C, in the population.

The Influence of Alcohol Consumption, Depressive Symptoms and Sleep Duration on Cognition: Results from the China Health and Retirement Longitudinal Study.

AIM: Healthy cognition-related factors include alcohol consumption, depressive symptoms, and sleep duration. However, less is known about the role of these factors in the dyad or tripartite relationships. In this study, we examined whether there were potential mediation effects, moderation effects, and interactions between these factors in the longitudinal study. METHODS: Both cross-sectional data analysis and a longitudinal study were performed using baseline and 2018 data from the China Health and Retirement Longitudinal Study (CHARLS) cohort. CHARLS is a nationwide survey program covering 450 villages and 150 counties in 28 provinces that aims to investigate comprehensive demographic information. After selecting participants from the CHARLS cohort, 15,414 were included in the study. Non-drinkers, those who drink more than once a month, and those who drink less than once a month were defined by their alcohol consumption. Depressive symptoms were defined as nondepressed (less than or equal to 12) and depressed (more than 12). Sleep duration was defined as 7-8 h per night, ≤6 h per night, and ≥9 h per night. The total cognitive scores were calculated from memory, orientation, and executive tests. The PROCESS macro in SPSS was used to analyze all mediations and moderating mediations. RESULTS: Alcohol consumption has a positive correlation with cognition. The global cognition z scores of participants with depressive symptoms were significantly lower than those of the control (all p's < 0.001), in different models. The memory score (ß: -0.148; 95% CI: -0.240 to -0.056; p = 0.002), the executive score (ß: -0.082; 95% CI: -0.157 to -0.006; p = 0.033), and the global cognition score (ß: -0.105; 95% CI: -0.187 to -0.023; p = 0.012) of participants defined as ≤6 h per night were, obviously, less than the control (7-8 h per night). An association between depression and alcohol consumption has been found, and the protective effects have been reversed by depression, which caused the cognition decline. Sleep duration was identified as a moderator, influencing the relationship between depressive symptoms and cognitive function. Besides, there was an interaction causing cognition decline among alcohol consumption, depressive symptoms, and sleep duration. Cognitive function showed a marked downward trend with increasing age. CONCLUSIONS: In this model, depression primarily mediates the relationship between alcohol consumption and cognition, and sleep duration changes the mediation effect. Furthermore, there is a significant interaction between alcohol consumption, depressive symptoms, and sleep duration, which are significantly associated with cognitive function.

The association between social engagement and depressive symptoms in middle-aged and elderly Chinese: A longitudinal subgroup identification analysis under causal inference frame.

Background: Studies have suggested that there is a significant association between social engagement and depression symptoms. However, this association may differ in people with different features such as different sociodemographic characteristics and health conditions. Methods: Research data were obtained from the CHARLS database. The causal inference was performed with the propensity score. We used the linear mixed-effects model tree algorithm under the causal inference frame for subgroup identification analysis. Results: We included 13,521 participants, and the median follow-up time is 4 years. Under the casual inference frame, the association between social engagement and depression symptoms is confirmed for all included individuals (OR = 0.957, P = 0.016; 95%CI: 0.923-0.992). Using the linear mixed-effects model tree, we found two subgroups, including middle-aged and elderly residents who live in rural areas with <6 h of sleep and those living in urban areas, could benefit more from social engagement. After using the propensity score method, all the two subgroups selected are statistically significant (P = 0.007; P = 0.013) and have a larger effect size (OR = 0.897, 95%CI: 0.830-0.971; OR = 0.916, 95%CI: 0.854-0.981) than the whole participants. As for sex difference, this associations are statistically significant in male (OR: 0.935, P = 0.011, 95%CI: 0.888-0.985) but not in female (OR: 0.979, P = 0.399, 95%CI: 0.931-1.029). Conclusions: Our findings indicate that social engagement may reduce the risks of depressive symptoms among all individuals. The identified subgroups of middle-aged and elderly residents who live in rural areas with <6 h of sleep and those who live in urban areas may benefit more from the social engagement than the whole participants.

Association of dietary fiber intake with newly-diagnosed type 2 diabetes mellitus in middle-aged Chinese population.

BACKGROUND: Epidemiological evidence concerning dietary fiber on newly-diagnosed type 2 diabetes mellitus (T2DM) is sparse. Therefore, the purpose of this study was to investigate the relationship between dietary fiber intake and newly-diagnosed T2DM in a middle-aged Chinese population. METHODS: Using data from the Hangzhou Nutrition and Health Survey collected between June 2015 and December 2016, we investigated the associations between dietary patterns and the risk of chronic non- communicable diseases. Anthropometric measurements and samples collection for biochemical assays are conducted by the well-trained staff and nurse, respectively. Multivariable logistic regression analysis was used to analyze the effect of dietary fiber intake on the risk of newly-diagnosed T2DM in crude and adjusted models. RESULTS: Among 3250 participants, 182 (5.6%) people were identified as newly-diagnosed T2DM. Pearson correlation coefficients revealed a significant inverse association of total dietary fiber with BMI, SBP, DBP, HbA1c and LDL-C in all participants, participants with and without T2DM (P < 0.05). Compared with the study participants in the first quartile (Q1, the lowest consumption)of dietary fiber intake, participants in the fourth quartile (Q4) had a lower prevalence of newly-diagnosed T2DM(OR = 0.70; 95%CI:0.49-1.00; P < 0.05), after adjustment for potential confounders. CONCLUSIONS: In this middle-aged Chinese population, higher intake of dietary fiber was significantly associated with lower risk of newly-diagnosed T2DM. However, our findings need to be confirmed in future large-scale prospective studies.

The major causes and risk factors of total and cause-specific mortality during 5.4-year follow-up: the Shanghai Changfeng Study.

To investigate the major causes and predictive factors of death in a middle-aged and elderly Chinese population. A total of 6591 residents aged ≥ 45 years from Shanghai Changfeng community were followed up for an average of 5.4 years. The causes of death were coded according to the 10th Revision of International Classification of Diseases. The mortality rate was calculated by person-years of follow up and age-standardized according to the 2010 Chinese census data. Multivariable-adjusted Cox proportional hazards model was performed to investigate the predictors of all-cause and cause-specific mortality. During the total follow-up of 35,739 person-years, 370 deaths were documented (157 from malignant neoplasms, 70 from heart diseases, 68 from cerebrovascular diseases, 75 from other causes). The age-standardized all-cause mortality rate was 798.2 per 100,000 person-years (927.9 among men and 716.7 among women). Results from multivariable analyses showed that aging, diabetes, and osteoporosis at baseline were independent predictors of all-cause mortality, with hazard ratios (HR) of 1.11 (95% CI 1.10-1.13), 1.91 (1.51-2.42), and 1.71 (1.24-2.35), respectively. The population attributable risk percent of diabetes and osteoporosis was 19.7% and 11.7%, respectively. Cigarette smoking was associated with a higher risk of all-cause mortality in men (HR and 95%CI 1.44, 1.01-2.06). In women, diabetes and osteoporosis were related to a higher risk of cardiovascular mortality (3.27, 1.82-5.88 and 1.89, 1.04-3.46, respectively). While in men, osteoporosis was related to a higher risk of malignant neoplasms mortality (2.39, 1.07-5.33). Malignant neoplasms, heart diseases, and cerebrovascular diseases are the leading causes of death. Aging, smoking, underweight, diabetes, and osteoporosis are independent predictors of premature death among middle-aged and elderly Chinese community population. Moreover, there may have been some differences in the causes and predictors of premature death between men and women.

Gender Difference on the Association between Dietary Patterns and Obesity in Chinese Middle-Aged and Elderly Populations.

Dietary patterns are linked to obesity, but the gender difference in the association between dietary patterns and obesity remains unclear. We explored this gender difference in a middle-aged and elderly populations in Shanghai. Residents (n = 2046; aged ≥45 years; 968 men and 1078 women) who participated in the Shanghai Food Consumption Survey were studied. Factor analysis of data from four periods of 24-h dietary recalls (across 2012-2014) identified dietary patterns. Height, body weight, and waist circumference were measured to calculate the body mass index. A log binominal model examined the association between dietary patterns and obesity, stratified by gender. Four dietary patterns were identified for both genders: rice staple, wheat staple, snacks, and prudent patterns. The rice staple pattern was associated positively with abdominal obesity in men (prevalence ratio (PR) = 1.358; 95% confidence interval (CI) 1.132-1.639; p = 0.001), but was associated negatively with general obesity in women (PR = 0.745; 95% CI: 0.673-0.807; p = 0.031). Men in the highest quartile of the wheat staple pattern had significantly greater risk of central obesity (PR = 1.331; 95% CI: 1.094-1.627; p = 0.005). There may be gender differences in the association between dietary patterns and obesity in middle-aged and elderly populations in Shanghai, China.