Shankuan Zhu

Objective: To examine the association between sleep quality and psychological resilience in a Chinese community-based cohort and assess the consistency of this association across two sleep measures. Design: Cross-sectional analysis of baseline data. Setting: Community-based cohort in Hangzhou, China (2016–2019). Participants: 10 268 adults aged 18–80 years enrolled via quota sampling stratified by sex and age group. After excluding participants with missing data, analytic samples were 9781 (single-item measure) and 9780 (Pittsburgh Sleep Quality Index (PSQI)), owing to one additional missing response. Primary outcome measure: Low psychological resilience, defined by a median split on a 9-item scale adapted from the Brief Resilience Scale and Connor–Davidson Resilience Scale. Results: Poor sleep quality was associated with higher odds of low resilience across both measures (single-item measure, adjusted OR=1.5, 95% CI 1.3 to 1.6; PSQI, adjusted OR=1.5, 95% CI 1.4 to 1.7), after adjustment for demographic factors, socio-economic factors, mental health indicators and health behaviours. Interaction tests showed no evidence of effect modification by sex, age group, loneliness or depression history for the single-item measure (p>0.05). For the PSQI, the association differed by loneliness (p<0.05), with a larger magnitude of association among lonely participants (adjusted OR=2.1, 95% CI 1.6 to 2.7) than non-lonely participants (adjusted OR=1.5, 95% CI 1.3 to 1.6). Conclusions: Poor sleep quality was consistently associated with low resilience across both measures. Because the design was cross-sectional, temporal direction cannot be established. Longitudinal and interventional studies are needed to establish temporal ordering, and intervention studies are needed to determine whether improving sleep increases resilience.

Background/Objective: Maternal diet is an important determinant of gut microbiota composition in dams and offspring. This study investigated whether HDCA supplementation during maternal high-fat diet (HFD) exposure was associated with gut microbiota composition in dams and offspring and with selected obesity-related phenotypes. Methods: Nineteen C57BL/6J female mice were assigned to a control diet group (CON), a high-fat diet group (HFD), and a high-fat diet supplemented with 0.5% hyodeoxycholic acid group (HFD+HDCA). Fecal samples were collected from the dams before mating, following 8 weeks of dietary intervention, and from the offspring at weaning. All samples were analyzed using 5R 16S rRNA gene sequencing. Body weight was monitored in both dams and offspring, and liver histology was assessed by hematoxylin and eosin staining. Results: HFD exposure was associated with obesity-related phenotypes in dams and offspring, including increased maternal body weight and greater hepatic lipid accumulation and visceral adiposity in offspring. LEfSe and ANCOM-BC2 analyses identified concordant microbial changes between dams and offspring under corresponding dietary conditions. Lachnospiraceae_Unknown_genus3261 and Coprococcus increased with HFD exposure in both dams and offspring, whereas Bifidobacterium, Coprococcus, and Allobaculum decreased following HDCA supplementation. These findings indicate maternal–offspring concordance in microbiota responses to HFD and HDCA, without establishing direct vertical transmission. PICRUSt2 analysis suggested group association differences in predicted functional potential for pathways annotated to propionate, pyruvate, and β-alanine metabolism. Conclusions: HDCA supplementation during maternal HFD exposure was associated with differences in offspring gut microbiota at weaning and with attenuation of selected obesity-related phenotypes. These findings suggest a potential role of the gut microbiota–bile acid axis in mediating intergenerational dietary effects. However, the study does not establish direct microbial transmission, altered metabolic activity, or causality; these findings require confirmation in litter-aware and mechanistic studies.

Background: Cross-sectional metabolomic studies of diabetes are prone to reverse causation, and longitudinal studies cannot distinguish causal metabolites from early markers. Transition analysis, tracking bidirectional glycemic changes in prediabetes, may identify more causal signatures. We compared three designs in one cohort and validated predictive performance. Methods: In the Lanxi Urban Cohort (discovery), we applied cross‑sectional (n=3182), longitudinal (n=2826), and transition (n=791 prediabetic; 224 reverted, 481 stable, 86 progressed) analyses to 2033 plasma metabolites using PLS‑DA and LASSO to select differential metabolites and build composite indices. Indices were validated in WELL‑China (n=8715; median follow‑up 7.8y) and Lanxi Rural (n=1573; 8.5y). Cox models adjusted for sociodemographic, lifestyle, and clinical covariates estimated HRs per SD; incident diabetes from ICD‑10 E11. Results: Cross‑sectional identified 43 metabolites; pooled validation index HR=1.73 (95%CI 1.63–1.85), AUC=78.59% (76.88–80.30), replication 23% (10/43). Longitudinal identified 24 metabolites: HR=1.92 (1.79–2.06), AUC=81.73% (80.11–83.35), replication 54% (13/24). Transition identified 9 metabolites: HR=2.11 (1.98–2.24), AUC=82.92% (81.31–84.52), replication 89% (8/9). After mutual adjustment, transition index retained independent effect (HR=1.44). Conclusion: Transition analysis in prediabetes identified fewer but more replicable metabolites with better prediction, supporting its use for risk stratification and early prevention.

Although substantial evidence links sweetened beverage (SB) intake to chronic diseases, its association with biological aging and underlying mechanisms remains unclear. This population‐based study included 9104 adults aged 18–80 years from the WELL‐China cohort. SB consumption was assessed using a validated food frequency questionnaire. Biological age and biological age acceleration (BAacc) were estimated using the Klemera and Doubal method (KDM). After multivariable adjustment, frequent SB consumption was significantly associated with accelerated KDM‐derived BAacc, compared with non‐consumers (β = 0.29 years, 95% CI: 0.06–0.52). This association was stronger among participants younger than 55 years ( P for interaction < 0.05). Gut microbiota was profiled using 16S rRNA gene sequencing. We identified 10 genera significantly associated with the frequent SB consumption, and 56 genera significantly associated with BAacc. Notably, five genera ( Allisonella , Lactobacillus , Weissella , Lactococcus , and Bacilli_unclassified ) were shared between the two analyses and enriched in both frequent SB consumers and individuals with higher BAacc. Frequent SB consumption is associated with accelerated biological aging, especially among adults younger than 55 years. Shared gut microbial signatures associated with both SB intake and BAacc suggest a potential microbiota‐related pathway. These findings support reducing SB consumption as a potential strategy for promoting healthy aging.

Background: The role of overall dietary diversity in type 2 diabetes (T2D) risk remains uncertain, and the potential associations involving the gut microbiota and metabolism are poorly understood. We therefore aimed to elucidate the associations between dietary diversity and T2D development and to explore the roles of gut microbiota and metabolism in two large-scale Chinese cohorts. Methods: This study included 8103 participants aged 18–80 years from the WELL-China cohort as the discovery cohort and 2020 from the Lanxi cohort as the validation cohort. Dietary diversity score (DDS) was calculated using a validated food frequency questionnaire and categorized as high-, medium-, or low-DDS groups. The primary outcome was incident T2D during a median follow-up period of 6.2 years. 16S rRNA sequencing was used to analyze the gut microbiota, while untargeted metabolomics was employed for plasma metabolite profiling. Cox regression was applied in all analyses. Results: High DDS was associated with a lower risk of T2D, with a hazard ratio of 0.71 [p = 0.039; 95% CI: 0.50 to 0.98] compared with low DDS. Eleven bacterial genera and 15 metabolites were identified between the high- and low- DDS groups. Among them, two genera (e.g., Blautia) and four metabolites, such as L-pipecolic acid, enriched in the high-DDS group were negatively correlated with incident T2D, whereas two genera and two metabolites depleted in the high-DDS group showed positive associations. Furthermore, most metabolites enriched in the high-DDS group were positively associated with high-DDS-enriched genera and linked to protective pathways (e.g., vitamin B6 metabolism); opposite associations were observed for depleted metabolites, which were linked to steroid hormone biosynthesis, a pathway whose dysregulation is closely linked to insulin resistance. Conclusions: Higher dietary diversity was associated with a lower risk of T2D, which might be partially due to the combined effects and interactions of beneficial bacteria and anti-inflammatory metabolites. Our findings position DDS as an easily modifiable lifestyle factor for T2D prevention, supporting its integration into public health guidelines.

Aim: Cardiovascular disease (CVD) is the leading cause of death worldwide, with higher risks in diabetes and prediabetes. We aim to investigate how dietary fibre affects cardiovascular disease (CVD) risk across different diabetes statuses and explore the role of gut microbiota. Methods and Materials: We analysed 207 413 participants from four cohorts in three countries, including 7951 with gut microbiota data from two Chinese cohorts. Dietary fibre intake was assessed via validated food frequency questionnaires. Major adverse cardiovascular events (MACE) included non‐fatal ischaemic heart disease, heart failure, stroke and cardiovascular deaths. Cox regression examined associations between dietary fibre, CVD mortality and MACE risk, while multivariable analyses evaluated fibre‐related microbiota and MACE. Results: Higher dietary fibre intake was associated with reduced CVD mortality (11% per SD) and MACE risk (6%–12% per SD) in individuals with normoglycaemia or prediabetes, but not in those with diabetes ( p for interaction = 0.009). An exploratory fibre‐related microbiota index, reflecting beneficial microbial genera (e.g., Lachnospiraceae) and reduced pro‐inflammatory genera (e.g., Desulfovibrio), was inversely associated with MACE risk across all diabetes statuses (17%–23% risk reduction per SD). However, the exploratory microbiota index correlated with energy‐adjusted dietary fibre intake only in non‐diabetic individuals. Conclusions: The varying impact of dietary fibre based on diabetes status underscores the need for personalised nutrition. The exploratory microbiota index reflects the interplay between fibre, gut health and cardiovascular outcomes, suggesting that microbiota‐related markers may help identify populations who could potentially benefit from tailored dietary strategies.

This study aimed to examine the association between an overall healthy lifestyle and periodontitis in a Chinese population. We further sought to explore the features of lifestyle-related oral microbiota, gut microbiota and plasma metabolome in relation to periodontitis. This cross-sectional study included 2,182 Chinese adults from the Lanxi cohort. The overall lifestyle assessment included waist circumference, smoking status, drinking status, physical activity and diet. Periodontitis was diagnosed in accordance with the criteria of the American Academy of Periodontology. 16S rRNA sequencing was used to analyze the oral and gut microbiota, while an untargeted metabolome was employed for plasma metabolite profiling. Participants with a healthy lifestyle had a lower prevalence of periodontitis than those with an unhealthy lifestyle (adjusted OR = 0.75, 95% CI: 0.59–0.96). Significant differences were observed in oral microbiota, gut microbiota and plasma metabolome between participants in the healthy and unhealthy lifestyle groups. Further analysis identified 12 lifestyle-related oral microbial genera, 12 gut microbial genera and 10 plasma metabolites, suggesting potential biological links between lifestyle and periodontal health. These findings suggest a potential association between a healthy lifestyle and periodontitis, with the oral and gut microbiota and plasma metabolome potentially involved.

The dietary habits from eastern coastal China have recently garnered widespread attention for their potential health benefits; however, empirical evidence remains limited. Here we applied unsupervised clustering to dietary data from 8,931 participants in the WELL-China cohort from the eastern coastal region and identified a healthful dietary pattern, designated as the ‘EastDiet’. This EastDiet comprised both well-recognized healthy foods (higher intakes of vegetables, fruits, seafood, whole grains, dairy, nuts and eggs; lower intakes of refined rice, red meat and fried foods) and distinctive Chinese dietary elements (greater consumption of freshwater fish, starchy tubers and roots, soy products and edible fungi). Three key aspects of the EastDiet were highlighted in our analysis: (1) approximately 46% of participants adhered to the EastDiet, and these individuals were more likely to be female and older and prefer lighter flavours; (2) adherence to the EastDiet was associated with lower odds of central obesity (odds ratio, 0.83; 95% confidence intervals, 0.75–0.92) and a 22% lower risk of incident major adverse cardiovascular events (hazard ratio, 0.78; 95% confidence intervals, 0.64–0.96); and (3) omics profiling revealed favourable metabolomic and gut microbial signatures associated with the EastDiet, which were linked to reduced risks of central obesity and major adverse cardiovascular events. This dietary pattern and its association with central obesity was successfully replicated in an independent cohort. In conclusion, the EastDiet identified in this study represents an evidence-based dietary pattern rooted in Chinese food traditions, which may serve as a framework for promoting healthy eating in China.

Background: Studies have shown that obesity contributes to colorectal tumors (CRC). Hyodeoxycholic acid (HDCA) has been found to have a therapeutic effect on obesity-related diseases such as nonalcoholic fatty liver (NAFLD). However, there are still no studies revealing whether HDCA has effects on CRC, which may suggest new uses for HDCA. Methods: C57BL/6 mice fed with high-fat diet supplemented with 0.5% HDCA were injected with MC38 cells subcutaneously to construct the subcutaneous metastasis model of CRC. The trend of body weight and tumor volume were evaluated, and blood metabolites and gut microbiota sequencing were analyzed. Results: Compared with HFD-fed mice, HDCA-treated mice had higher fecal and serum HDCA levels. After tumor inoculation, the HDCA mice had smaller subcutaneous tumor volumes, as well as higher HDCA and THDCA levels in feces and blood. Blood metabolomics revealed significant enrichment in pathways of bile secretion, arachidonic acid metabolism, primary bile acid metabolism, and taurine and hypotaurine metabolism. Analysis of gut microbiota at the completion of obesity modeling revealed the Chao1 index of the feces being lower in the HDCA mice. The relative abundance of a total of nine genera were significantly higher and eighteen genera were lower. The KEGG results indicated significant upregulation of nine metabolic pathways and downregulation of sixteen metabolic pathways. Conclusions: HDCA intake ameliorates HFD-induced obesity phenotype, inhibiting colorectal tumor growth in mice, and decreases the abundance of gut microbiota. Gut microbiota affected by HDCA may participate in metabolism-related effects through circulation, which might be one way that HDCA affects colorectal tumors.

Study Objectives: To investigate the relationships between Traditional Chinese Medicine (TCM) body constitution and sleep quality in a large population-based cohort. Methods: This cross-sectional study included 8517 participants from the WELL China cohort. We used the Wang Qi Nine Body Constitution Questionnaire (WQ-9BC) to assess TCM body constitution and the Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality. We used multivariable logistic regression analyses to estimate odds ratios (ORs) for the association between body constitution and poor sleep quality (PSQI score > 5), adjusting for demographics, lifestyle factors, and comorbidities. Results: Compared with a balanced body constitution (1898; 22%), individuals with an unbalanced constitution had a 2.6-fold risk (95% CI = 2.3 to 3.0), and those with an unbalanced tendency had a 1.5-fold risk of poor sleep quality (95% CI = 1.3 to 1.8). All eight unbalanced constitutions were associated with a higher risk of poor sleep quality, with Qi stagnation (OR 4.0 [95% CI = 3.0 to 5.5]) and blood stasis (OR 3.8 [95% CI = 2.3 to 6.2]) having the highest ORs. About 52% of participants had multiple unbalanced constitutions and/or tendencies. The OR for poor sleep quality increased with the composite number of Yang deficiency, Yin deficiency, Qi deficiency, heat dampness, blood stasis, and Qi stagnation constitutions and/or tendencies. Conclusions: All eight unbalanced constitutions are associated with poor sleep quality in a dose-dependent manner, with Qi stagnation and blood stasis displaying the strongest associations. Multiple unbalanced constitutions and/or tendencies are cumulatively associated with poor sleep quality. Identifying TCM body constitution could help in detecting high-risk groups and designing targeted interventions. Statement of Significance Poor sleep is a global public health concern with high prevalence and many adverse effects. Traditional Chinese medicine (TCM) body constitution has been widely used to personalize health care in China. Our study is the first to discover a dose–response relationship between the degree of imbalance in constitution and sleep quality, and a cumulative relationship between multiple unbalanced constitutions and/or tendencies and sleep quality. Considering that a large percentage of the population has unbalanced constitutions and/or tendencies, our findings have significant public health implications. Identifying TCM body constitutions may help target populations with an increased risk of poor sleep quality and guide the design of personalized interventions to improve sleep.