To investigate the daily dietary nutrient intake and energy expenditure of university students in Sichuan, in order to understand the levels of dietary nutrient intake and physical activity among college students. To evaluate the adequacy of the students’ nutritional requirements by analyzing the intake and energy contribution of the three major macronutrients, as well as the daily energy expenditure and its composition from physical activities.

A convenient sample of 200 college students in a university of Sichuan were included in the study. Body mass index (BMI) and body fat ratio (BFR) were measured using a body composition analyzer. A three-day 24-hour dietary recall method was used to investigate dietary intake, while the Bouchard Physical Activity Diary and triaxial accelerometer AntiGraph wGT3X-BT were used to investigate subjects’ physical activity and energy expenditure.

The median daily energy intake was 2 237 kcal/d for male students and 1 620 kcal/d for female students. The median daily macronutrient intakes for males were: protein 81 g/d, fat 72 g/d, and carbohydrate 295 g/d,and for females: protein 65 g/d, fat 58 g/d, and carbohydrate 210 g/d. The macronutrient energy ratios were 53∶15∶32 for both genders. The median daily energy expenditure was 473 kcal/d for males and 309 kcal/d for females.

Male college students’ daily energy intake and expenditure are significantly higher than females. College students generally show issues of relatively insufficient energy intake, high fat intake, relatively low carbohydrate intake, and insufficient moderate to high-intensity exercise. College students generally lack moderate-to-vigorous physical activity. Students should be encouraged to actively participate in physical activities to promote balanced diets and a healthy lifestyle.

To investigate the current distribution status and multimorbidity patterns of chronic diseases among the elderly population in China, and provide reference for formulating chronic disease management measures.

Based on the CHARLS database in 2020, a total of 10,635 elderly individuals aged 60 and above were included to investigate the prevalence trends of 15 common chronic diseases. The actual expected ratio (O/E) and agglomerative hierarchical clustering analysis were employed to explore the patterns of comorbidity.

The prevalence of chronic diseases among elderly people in China was 86.39%, with hypertension (48.49%), arthritis (43.12%), and stomach diseases (excluding tumors or cancer) (32.06%) being the main causes. The multimorbidity rate was 66.30%, and the top three coexisting diseases were "hypertension+arthritis" (22.28%, O/E=1.07), "hypertension+dyslipidemia" (20.25%, O/E=1.44), and "stomach disease+arthritis" (18.65%, O/E=1.35). The top three coexisting diseases were "hypertension+arthritis+dyslipidemia" (10.31%, O/E=1.70), "hypertension + dyslipidemia + heart disease" (9.70%, O/E=2.65), and "arthritis + stomach disease + hypertension" (9.49%, O/E=1.42). Agglomeration hierarchical cluster analysis was divided into clusters according to malignant tumors, emotional and mental diseases, " stroke + memory related diseases + Parkinson’s disease", "dyslipidemia + diabetes + hypertension + heart disease", "chronic lung disease + asthma + stomach disease + arthritis + liver disease +kidney disease", forming a multimorbidity model.

The overall prevalence of chronic diseases among elderly people in China is increasing year by year, and there is a clustering trend.

To summarize the performance and implementation status of various randomization methods, and to provide clinical researchers with a guide for choosing an appropriate randomization method and executing it in a standardized manner.

The review elucidated the conceptual and implementation integrity of randomization, and illuminated the developmental history and application of major randomization methods, as well as their performance in the two competitive dimensions of group allocation randomness and group sample balance.

Restricted randomization was frequently used to maintain an appropriate treatment balance in practice. Block randomization was the most widely used, but its allocation sequence lacked sufficient randomness and could be predicted, elevating the risk of selection bias, especially in open-label trials. Methods offering a superior trade-off between randomness and balance included MTI restricted randomization methods like the big stick design and maximal procedure, as well as combinations of multiple randomization methods such as the block urn design and sandwich mixed randomization. Many clinical researchers still had misconceptions about the randomization concept itself and often overlooked its critical methodological rigor and standardized implementation.

Researchers should meticulously choose a suitable randomization method and report implementation details in a standardized manner, allowing peer researchers to evaluate the internal validity and evidence strength of the study. Due to its high predictability, the widely used block randomization method should be substituted by alternative methods with better performance. Future randomization procedures can be explored and developed based on the MTI restrictive methods and the combinations of existing methods.

To analyze the multiple mediating effects of different types of social activities on the relationship between health status and cognitive function, providing insights for mitigating cognitive impairment in older adults.

Using data from the 2018 China Health and Retirement Longitudinal Study, 7 991 individuals aged 65 and older were selected to construct a multiple mediation model examining the mediating effects of physical exercise, cultural and recreational activities, interpersonal interactions, and family life on the relationship between self-rated health and cognitive function.

Self-rated health and the four types of social activities were significantly correlated with cognitive function (P < 0.01). Physical exercise, cultural and recreational activities, interpersonal interactions, and family life exhibited partial mediating effects between self-rated health and cognitive function. Specifically, self-rated health directly influenced cognitive function with an effect size of 0.591 (95%CI: 0.471-0.710). Furthermore, self-rated health mediated cognitive function through the four types of social activities. The mediating effect size was 0.010 (95%CI: 0.002-0.018) for physical exercise, 0.083 (95%CI: 0.055-0.113) for recreational activities, 0.061 (95%CI: 0.042-0.080) for interpersonal interactions, and 0.078 (95%CI: 0.054-0.104) for family life.

Self-rated health can delay cognitive decline in older adults by promoting their participation in social activities.

To investigate the relationship between the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) and new-onset stroke in different glucose metabolism states, and to provide new perspectives on stroke prevention and treatment.

Based on data from the China Health and Retirement Longitudinal Study (CHARLS), a total of 8 567 participants were selected to participate in five surveys in 2011, 2013, 2015, 2018, and 2020. First, the cumulative risk of stroke onset was estimated using the Kaplan-Meier method based on NHHR quartile groupings, and the Log-rank test was used to compare differences between groups. Second, the association between NHHR and new-onset stroke in the total population and in individuals with different glucose metabolic status was analyzed using Cox proportional risk regression models, and interaction analyses were performed.

A total of 745 (8.4%) participants had a new stroke during the 9-year follow-up period. The incidence of stroke in the NHHR quartiles from Q1 to Q4 groups was 6.1%, 8.2%, 9.4%, and 11.1%, respectively. Kaplan-Meier analysis showed a significant difference in cumulative incidence risk of stroke among the different NHHR groups (P<0.05). Cox regression modeling showed that the risk of stroke was increased by 34%, 56%, and 75% in Q2, Q3, and Q4 groups, respectively, compared with Q1 group, with HR and 95% CI of 1.34 (1.07-1.68), 1.56 (1.25-1.95), and 1.75 (1.41-2.18). In prediabetic and diabetic patients, elevated NHHR increased the risk of stroke onset, whereas the association was not observed in the normoglycemic group, and there was a significant interaction between NHHR and glucose metabolic status (P=0.020).

NHHR is positively associated with the risk of new stroke and shows different characteristics in different glycaemic states.

To investigate the relationship between hemoglobin (Hb) levels in early pregnancy and the incidence of gestational diabetes mellitus (GDM).

Following the principle of informed consent, data were collected from pregnant women who underwent prenatal care and delivery at ten hospitals and fifteen community health service centers in Kunshan,Jiangsu Province, from August 2019 to June 2021. This included demographic information, medical and family history, reproductive history, physical examinations, and laboratory test results. GDM was diagnosed based on the results of the oral glucose tolerance test during pregnancy. A restricted cubic spline (RCS) regression analysis was employed to explore the dose-response relationship between Hb levels and the risk of GDM. Based on the RCS results, Hb levels were categorized into two groups: Hb ≤ 138.4 g/L and Hb > 138.4 g/L. Logistic regression was then used to analyze the relationship between early pregnancy Hb levels and the risk of GDM, calculating the odds ratio (OR) and its 95% confidence interval (95%CI) to assess the strength of the association.

Totally 9 045 women with singleton pregnancy were included in this study, with an incidence of GDM of 14.72% (n=1 331). The RCS regression results indicated a linear relationship between early pregnancy Hb levels and the risk of GDM (overall trend test: P=0.013, non-linear test: P=0.396). Multivariable logistic regression revealed that women with Hb > 138.4 g/L had a higher risk of GDM compared to those with Hb ≤ 138.4 g/L, with an adjusted OR of 1.214 (95%CI: 1.021-1.445).

Elevated Hb level in early pregnancy is a risk factor for the development of GDM.

To analyze the trends and characteristics of the number of patients, prevalence, incidence, disability-adjusted life years (DALY), and years lived with disability (YLD) of depressive disorders among the Chinese population from 1990 to 2021, with the hope of providing a theoretical basis for early prevention, intervention, and clinical decision-making regarding depressive disorders.

Depressive disorders data from the GBD 2021 database (Global Burden of Disease Study 2021 Data Resources) were extracted to analyze the number of patients, incidence, prevalence, DALY and YLD in the Chinese population. The software STATA 14.0 and Joinpoint Regression Program 4.8.0.1 were utilized to analyze the incidence, prevalence, DALY, and YLD of depressive disorders across different genders and age groups. Furthermore, the average annual percent change (AAPC) in depressive disorders was calculated.

In 2021, there were 42.3602 million new cases of depressive disorders in China, an increase of 38.9% from 30.4910 million in 1990. The number of patients was 53.1147 million, an increase of 54.0% from 34.4794 million in 1990. Both the standardized incidence and prevalence showed a slow downward trend (the AAPC was -0.57% and -0.44%, respectively, P<0.001). The incidence of depressive disorders in people aged 10 to 24 showed a sudden increase in different years, and the incidence of depressive disorders in people over 65 also showed an accelerating upward trend. The DALY in 1990 and 2021 were 5.4267 million and 7.8659 million person-years, respectively, with a cumulative increase of 44.9%. The DALY rate increased from 461.27 /100 000 to 552.87 /100 000, with an increase of 19.8%. The standardized DALY and YLD rates decreased slowly with each year (the AAPC was -0.53% and -0.53%, respectively, P<0.001).

Depressive disorder is still one of the main causes of global disease burden and a major public health issue facing our country. There is an urgent need to actively explore and implement effective prevention and treatment strategies to reduce the disease burden of depressive disorders.