To investigate the differences in gut microbiota and energy metabolism among individuals with varying body mass index (BMI) levels, and to provide insights for the prevention and treatment of overweight and obesity.

A total of 98 healthy adults were recruited from Chengdu, categorized into four groups based on BMI: overweight (n=16), obesity (n=15), underweight (n=16), and normal weight (n=51). Participants underwent questionnaire surveys, physical examinations, body composition analysis, biochemical tests, and energy expenditure measurements. Fecal samples were collected for 16S rDNA sequencing and gas chromatography-mass spectrometry (GC-MS) metabolomics analysis. Univariate analysis of variance and chi-square tests were performed to compare differences in gut microbiota structure and energy metabolism among the four groups.

Gut microbiota structure analysis: Significant differences were observed in the gut microbiota structure among the four groups, with statistical significance in ACE and Chao1 indices (P=0.003, P=0.003). The normal weight group exhibited higher ACE and Chao1 indices compared to other groups, indicating a higher species richness. The relative abundance of different bacteria varied across groups. Compared to the normal weight group, the overweight, obese, and underweight groups showed reduced species richness and lower relative abundance of beneficial bacteria such as Bifidobacterium. Functional metabolic pathways of the gut microbiota were altered in these groups, with significant differences in the synthesis and metabolism of various amino acids, including glycine, in the overweight and obese groups (P=0.009, P=0.032).Correlation with BMI and energy expenditure indicators: The gut microbiota structure was associated with different levels of energy metabolism indicators. Bifidobacterium was positively correlated with cold-induced thermogenesis (CIT) (P=0.011), while Bifidobacterium animalis was negatively correlated with BMI and basal energy expenditure (BEE) (P<0.001), and positively correlated with CIT (P=0.029).

There are differences in gut microbiota structure and functional metabolic pathways among individuals with different BMI levels. The gut microbiota structure is associated with various energy metabolism indicators at different levels. These findings suggest that gut microbiota may play a role in energy metabolism and could be a potential target for interventions aimed at preventing and treating overweight and obesity.

To analyze theassociation and interactionof night shift work and unhealthy lifestyle on hyperhomocysteinemia(HHcy), and to provide basis for theHHcy preventionamong railway workers.

Total of 6 926 railway workers who received physical examination in a hospital in Guangzhou from September to December 2021 were selected as study objects. Binary logistic was performed to analyze correlation, the restricted cubic spline (RCS) model was used to assess the dose-response relationship, and the interaction of night shift work and unhealthy lifestyle with HHcy were analyzed.

The prevalence rate of HHcy among railway workers was 23.3%. Logistic regression showed that night shift work lasted 0-2.9 years (OR=1.340, 95% CI:1.120-1.603), night shift work frequency ≤ 1 d/w (OR=1.302, 95% CI:1.029-1.646) or ≥ 4 d/w (OR=1.516, 95% CI:1.248-1.841), smoking (OR=1.516, 95% CI:1.248-1.841), overweight (OR=1.173, 95% CI: 1.030-1.335) were positively correlated with HHcy. Sleep duration > 7 h/d and exercise were negatively correlated with HHcy (P<0.05). RCS model found a nonlinear relationship of night shift work with HHcy (P_total <0.001,P_non-linear=0.001). No multiplicative and additive interaction of night shift work and any unhealthylifestyle with HHcy were found(P> 0.05). Among different night shift conditions, smoking, almost inactive, overweight/obesity, and ≤ 7 h/d sleep had a higher risk of HHcy (P<0.05).

Night shift work and unhealthy lifestyle are risk factors for HHcy. In different night shift work conditions, smoking, almost inactive, overweight/obesity, sleep duration ≤ 7 h/d can increase HHcy risk.

To explore the changes in the quality of life and its influencing factors of elderly people in rural areas of Sichuan province from 2018 to 2023, and to provide a basis for timely adjustment of health intervention measures.

Data from the sixth and seventh health service surveys in Sichuan province in 2018 and 2023 were summarized, and the EQ-5D questionnaire health utility value and visual analogue scale (VAS) score were used to evaluate quality of life.Survey time interaction items were includedin a weighted two-level random intercept model to explore the differences in the effects of influencing factors.

The utility value of elderly people in rural areas of Sichuan province was 0.83±0.22, and the VAS score was 65.53±17.81, both lower than the national average. Analysis showedthat survey year, individual characteristics, lifestyle, chronic disease prevalence, and family medical factors wereinfluencing factors for utility value and VAS score. In addition, in the utility score, the interaction items of over 80 years old (β=0.046, P<0.001), 1-2 times of weekly exercise (β=-0.035, P=0.045), diabetes (β=0.032, P=0.031), and annual family income of over 50 000 (β=0.029, P=0.048) with time were statistically significant; In VAS score, the interaction between time and age of over 80 years old (β=4.647, P<0.001), primary and junior high school education (β=-3.301, P<0.001), alcohol consumption (β=-2.262, P=0.004), diabetes (β=4.946, P<0.001), hypertension (β=2.992, P<0.001), annual family income of more than 50 000 (β=4.322, P<0.001), physical examination in the past year (β=2.925, P<0.001) had statistical significance.

The quality of life of elderly people in rural areas of Sichuan province is relatively low and requires attention. When formulating health intervention measures, full consideration should be given to the changes in the above factors and effects.

To evaluate the epidemic intensity of scarlet fever in Xinjiang using the Moving Epidemic Method (MEM), and to provide evidences for the classification of early warning of scarlet fever.

Monitoring data on scarlet fever in Xinjiang from 2014 to 2023 were collected, with the weekly incidence rate serving as the research object. The δ value corresponding to the maximum Youden index was selected to establish the MEM model. The epidemic thresholds for the two epidemic seasons of scarlet fever were estimated separately. The effectiveness of the MEM was evaluated through a cross-validation procedure. The epidemic level of scarlet fever in Xinjiang from 2014 to 2023 was assessed, and predictions were made for the spring epidemic season in 2024.

The optimal δ value for the spring epidemic peak of scarlet fever in Xinjiang was 2.5. The sensitivity of the model fitting was 0.83, the specificity was 0.91, and the Youden index was 0.74. For the autumn epidemic peak model, the optimal δ value was 2.6, with a sensitivity of 0.90, a specificity of 0.93, and a Youden index of 0.83. In the spring of 2024, the epidemic season entered the low-epidemic level in the 13th week and rose to the medium-epidemic level in the 23rd week, after which it maintained the low-epidemic level. By the 28th week, the epidemic level had fallen below the epidemic threshold, and there were no high or very high epidemic levels observed.

For the bimodal epidemic characteristics of scarlet fever in Xinjiang, the MEM model can be used to determine the epidemic intensity thresholds of different epidemic seasons by splitting the epidemic season, which is proved to be feasible. The model can be used to establish a scarlet fever early warning system, which provides a scientific basis for guiding the classification and early warning of scarlet fever.

To analyze the spatial and temporal distribution characteristics and changing trends of newly reported HIV / AIDS cases aged 50 years and over in Guizhou Province from 2018 to 2023, and to provide scientific basis for ≥50 years old AIDS prevention and control.

Using the database of the AIDS comprehensive prevention and control data information system, the newly reported cases aged 50 years and over from 2018 to 2023 were screened out, and their demographic characteristics were analyzed. Then use ArcGIS software for spatial autocorrelation analysis.

From 2018 to 2023, the proportion of HIV/AIDS cases aged 50 and above in Guizhou Province increased from 46.91% in 2018 to 56.99% in 2023, and the proportion increased year by year(trend χ²=249.968, P<0.001),and the distribution of local areas was concentrated.The global Moran ’s I was between 0.336 3 and 0.395 0(P<0.001). It showed that there was a global spatial autocorrelation in 2018-2023. SatScan showed six clusters, among which Puding, Xixiu, Zhenning, Liuzhi, Zhijin and Guanling were the most likely to gather (RR=2.990, LLR=1 222.719), which was also highly consistent with the results of spatial autocorrelation analysis.

The newly-discovered HIV / AIDS patients aged 50 and above in Guizhou Province in recent years have spatial clustering, mainly concentrated in the central and western and southern regions of Guizhou Province. It is recommended to strengthen the comprehensive prevention and control of AIDS in areas with high incidence of epidemic, especially to carry out targeted preventive measures in time in areas with a trend of spread.

To assess Hantaan virus infection risk across districts in Sichuan Province, providing a scientific basis for prevention and intervention measures for Hemorrhagic Fever with Renal Syndrome (HFRS) and data for evaluating their effectiveness.

This study utilized open-source databases and mathematical modeling. HFRS case report data were collected to analyze epidemic status and spatial distribution using traditional epidemiological methods, while a Bayesian spatiotemporal model examined temporal effects, spatial effects, spatiotemporal interactions, and the impact of meteorological, socioeconomic, and healthcare factors on regional risk levels.

From 2015 to 2021, HFRS incidence in Sichuan showed temporal variation and seasonality, with Yanyuan County reporting the highest cases. Spatial analysis indicated that most districts had risk values consistent with the provincial average, with high-risk areas in the southern, northeastern and central regions. Relative risk declined overall from 2015 to 2020, with a 41.7% decrease in 2020 compared to 2015, although a slight increase occurred in 2021 (0.22 per 100 000). Yanyuan County had the highest relative risk (2.66 [1.64, 4.57]), while other regions aligned with the provincial average. Urbanization rate and humidity affected HFRS incidence negatively, and precipitation affected HFRS incidence positively.

HFRS incidence in Sichuan Province is generally low, with higher rates in specific districts, highlighting spatial risk variability. Meteorological, socioeconomic, and healthcare factors influence infection risk. Monitoring relevant indicators and implementing timely interventions are essential to prevent increased human infection risk.

To analyze the compensation for adverse events following immunization from vaccination under Anhui Province’s National Immunization Program (NIP) from 2012 to 2024.

Data from cases compensated for adverse events following immunization from vaccination in Anhui Province from 2012 to 2024 were collected and analyzed using descriptive NIP demiological methods.

From 2012 to 2024, there were a total of 80 AEFI compensation cases in Anhui Province for NIP vaccines, with the lowest compensation amount being 13 200 yuan and the highest compensation amount being 1.54 million yuan. The total compensation amounted to 35.49 million yuan, with an average compensation of 443 600 yuan per case (ranging from 13 200 yuan to 1.54 million yuan). The number of cases and compensation amount for those under 1 year old were the highest, with 64 cases (80.00%) and 25.29 million yuan (71.26%) respectively. In the vaccine distribution, BCG vaccine had the highest number of AEFI compensation cases and compensation amount, with 33 cases (41.25%) and 1.05 million yuan (29.64%), respectively. In terms of clinical diagnoses, neurological diseases had the highest number of cases and total compensation amount, with 33 cases (41.25%) and 2.03 million yuan (57.26%). In the damage severity classification, Grade IV had the most compensation cases, with 20 cases (25.00%), while Grade II-B had the highest total compensation amount, totaling 7.49 million yuan(21.09%). The average payment time after the investigation and diagnosis conclusion was 252.28 days.

The overall implementation of compensation for adverse events following immunization from vaccination under Anhui Province’s NIP is good, but there is a need for further improvement in compensation procedures and mechanisms.

To evaluate the efficacy of three treatment modalities, preoperative, postoperative, and combined preoperative and postoperative systemic therapy, in elderly patients with rectal cancer (RC), and to analyze the prognostic factors for elderly RC patients.

Data from 4612 RC patients aged 60 and above were used, sourced from the SEER database between 2011 and 2015. The Overlap Weighting (OW) method based on XGBoost was employed to balance covariate differences between treatment groups and assess the impact of different treatment regimens on the survival prognosis of RC patients. Survival curves were plotted using the Kaplan-Meier method, and Log-rank tests were conducted. Cox regression analysis was utilized to evaluate independent risk factors affecting the survival of RC patients.

After OW weighting, the three treatment groups achieved balance across all covariates. The survival rates among different treatment groups were statistically significant (P<0.001). The 1-year, 3-year, and 5-year survival rates were 94.6%, 82.2%, and 71.6% for the preoperative systemic therapy group, 95.0%, 79.0%, and 67.8% for the postoperative systemic therapy group, and 97.3%, 85.5%, and 73.4% for the combined preoperative and postoperative systemic therapy group, respectively. Multivariate Cox regression analysis revealed that, compared to the preoperative systemic therapy group, the specific death hazard ratio for the postoperative systemic therapy group was 1.216(95% CI: 1.072-1.381). Patients with liver metastasis had a specific death hazard ratio of 1.719(95% CI: 1.253-2.358) compared to those without liver metastasis.

The sequence of systematic treatment has a significant impact on the survival prognosis of elderly RC patients. After controlling for factors such as age and gender, preoperative systemic treatment had a better survival prognosis among the three treatment methods; Liver metastasis may be an independent factor affecting the prognosis of RC patients.

To explore the relationship between the carbohydrate to fiber ratio (CF) and the risk of type 2 diabetes mellitus (T2DM) among residents in the Ili region of Xinjiang, with the goal of providing a scientific basis for the prevention and control of type 2 diabetes.

The data from the the Xinjiang Multi-Ethnic Cohort in the Ili region was utilized, selecting participants who took part in the baseline survey in 2019 and were followed up in 2020, 2021, and 2022. We calculated the CF for study participants based on dietary survey data. A Cox proportional hazards model was employed to investigate the association between CF and the risk of T2DM. Additionally, restricted cubic splines were used to analyze the dose-response relationship between CF and T2DM risk.

A total of 6 879 participants were included in the study, with a median follow-up time of 37.4 months, during which 543 new cases of type 2 diabetes (T2DM) were identified. Participants were categorized into quartiles based on CF (Cumulative Frequency). After adjusting for potential confounding factors, the risk of developing T2DM in the Q2 and Q3 groups was reduced by 30.0%(HR=0.700, 95% CI: 0.547-0.896) and 29.3% (HR=0.707, 95% CI: 0.553-0.904), respectively, compared to the Q1 group. The use of restricted cubic splines indicated a non-linear U-shaped relationship between CF and the risk of developing T2DM (P<0.05). Stratified analysis revealed that in overweight and obese individuals (BMI≥24 kg/m²), the risk of T2DM in the Q2 and Q3 groups was reduced by 35.7% and 35.4%, respectively, compared to the Q1 group. Among males, the risk of T2DM in the Q2 group was reduced by 31.6% compared to the Q1 group, while in females, the Q3 group showed a reduction of 36.7% compared to the Q1 group. Additionally, in individuals aged under 65 years, the risk of T2DM in the Q2 group was also reduced by 34.5% compared to the Q1 group. No associations were observed in other stratified populations.

A U-shaped relationship exists between CF and the risk of T2DM. Attention should be paid to the CF levels in individuals who are overweight or obese and those under 65 years of age, as there are significant implications for the prevention and management of type 2 diabetes.