To analyze the epidemic characteristics of rubella in Nanning from 2005 to 2022, providing a reference for rubella prevention and control.

Reported rubella cases in Nanning from 2005 to 2022 were collected, and the Join Point regression model was utilized to analyze the trend of incidence. The spatial autocorrelation analysis and spatiotemporal scanning were employed to assess the clustering of rubella cases.

A total of 4 001 rubella cases were reported in Nanning from 2005 to 2022, with 12 outbreaks and no fatalities. The average annual incidence rate was 3.17 per 100 000, displaying an initial increase followed by a decrease, then another increase and decrease, with significant peaks in 2011 and 2018. Cases were concentrated between March and June, with the incidence rate in urban areas (3.70 per 100 000) being higher than that in rural counties (2.48 per 100 000). Males (3.58 per 100 000) had a higher incidence than females (2.72 per 100 000), and the highest average annual incidence rate was observed in the age group of 10 to 19 years, predominantly among students (73.53%). The proportion of students decreased, while the proportions of farmers, commercial service workers, homemakers, the unemployed, and other professions increased. Spatial autocorrelation analysis indicated significant clustering, with a trend of “high-high” clusters shifting from surrounding counties to the urban center, ultimately shrinking and disappearing, while “low-low” clusters exhibited a merging trend.Spatiotemporal scanning identified two clusters covering seven counties and districts.

Significant progress has been made in rubella prevention and control in Nanning, with the incidence still primarily affecting the 10 to 19 age group and a noted shift in the age of onset. It is recommended to continue strengthening rubella vaccination for age-appropriate children, while also targeting vaccination efforts towards key populations such as middle school students and women of childbearing age.

To understand the status of heart-focused anxiety (HFA) in patients with coronary heart disease and to construct a structural equation model based on the theory of stress processes to analyze the influencing factors and correlations among various variables.

A convenience sampling method was used to select 247 patients with coronary heart disease who visited the Department of Cardiology at the Affiliated Hospital of Yangzhou University from December 2023 to June 2024 for a questionnaire survey. A structural equation model was employed to investigate the influencing factors and path analysis of HFA in these patients.

A total of 247 patients with coronary heart disease were included, with a mean score of (25.77±8.39) on the heart anxiety questionnaire, and the HFA detection rate was 33.2% (82 cases). The structural equation model indicated that positive coping, negative coping, social support, and disease perception had direct effects on HFA, with effect values of -0.226, 0.275, -0.272, and 0.204, respectively (all P < 0.01). Social support had an indirect negative effect value on HFA of-0.187 (95%CI: -0.302 to -0.096), accounting for 40.74% of the total effect. The disease perception had an indirect positive effect value on HFA of 0.335 (95%CI: 0.242 to 0.385), accounting for 62.27% of the total effect.

HFA symptoms are relatively common in patients with coronary heart disease. Healthcare professionals can reduce the level of HFA in patients by guiding them to establish correct disease cognition, adopt positive coping strategies, and actively seek social support.

To identify key influencing factors of non-alcoholic fatty liver disease (NAFLD) and construct a Bayesian network model to explore its pathogenesis.

The study was based on the Beijing Health Management Cohort. The LASSO regression was employed to screen for relevant influencing factors of NAFLD, and 10-fold cross-validation was used to select the optimal penalty parameter λ. Based on the selected variables, structural learning was conducted using the Bayesian network model, and the model fit was evaluated through the Bayesian Information Criterion (BIC) and cross-validation for path analysis.

During the 5-year follow-up period, 22.83% of the 30 001 study participants developed NAFLD (n=6 850), with an incidence density of 45.7 per 1 000 person-years. Six key influencing factors were identified: AGE, BMI, HDL-C, FPG, ALT, and DBP, and a Bayesian network model was constructed based on these factors. The Bayesian network analysis revealed 23 pathways for the development of NAFLD, with the pathway having BMI as the root node being the most frequent (12 pathways), followed by age groups (5 pathways). The pathway AGE→DBP→FPG→NAFLD showed a significantly higher incidence probability in individuals under 45 years compared to those over 45. In cases of low BMI, the pathway BMI→HDL→ALT→NAFLD indicated a higher probability of NAFLD compared to other BMI groups.

The Bayesian network model elucidated the pathways of NAFLD development and clarified the impact of key factors on its onset, providing a theoretical basis for early screening and intervention of NAFLD.

To analyze the trends in the incidence, prevalence, mortality, and disease burden of thalassemia in China from 1990 to 2019, providing a reference for further disease prevention and control.

Data related to the incidence, prevalence, mortality, and Disability-Adjusted Life Years (DALYs) of thalassemia in China were extracted from the Global Burden of Disease Study (GBD) 2019 database. The Join point regression model was utilized to analyze the annual percentage change (APC) and average annual percentage change (AAPC) of the age-standardized incidence rate, prevalence rate, mortality rate, and DALYs rate.

From 1990 to 2019, the number of new thalassemia cases in China decreased from 100 686 to 60 132, with the age-standardized incidence rate declining by 3.88% (AAPC=-0.60%). The number of deaths fell from 6 776 per year to 2 191 per year, leading to a 69.68% reduction in the age-standardized mortality rate (AAPC=-4.04%). DALYs decreased from 541 696 per year to 141 284 per year, with a 71.10% reduction in the age-standardized DALYs rate (AAPC=-4.90%, P < 0.05). The number of individuals with thalassemia decreased from 684 066 to 642 042, although the age-standardized prevalence rate increased by 19.15%(AAPC=0.58%, P < 0.05). Between 1990 and 2019, the disease burden of thalassemia for both males and females showed a declining trend, but the incidence and prevalence rates remained consistently higher in females compared to males, with the male-to-female ratios for age-standardized incidence rate, prevalence rate, DALYs rate, and mortality rate ranging from 0.76 to 0.78, 0.77 to 0.80, 0.94 to 1.07, and 0.97 to 1.12, respectively. The highest mortality and DALYs rates for thalassemia were observed in the age group under 5 years with a notable decline in the 5-to-9-year age group followed by stabilization. Over the last two decades, the mortality and DALYs rates gradually shifted towards older age groups.

The burden of thalassemia in China has alleviated from 1990 to 2019, exhibiting gender and age disparities, along with a trend towards an aging population.

To analyze the trends in coronary heart disease (CHD) mortality in China from 1992 to 2021, providing a basis for adjusting and optimizing CHD prevention and treatment policies.

This study employed the Join point regression model to calculate the annual percentage change in mortality trends, exploring variations in CHD mortality over consecutive time periods. Additionally, an age-period-cohort (APC) model was utilized to compute effect coefficients, assessing the individual impacts of age, period, and birth cohort on CHD mortality risk.

From 1992 to 2021, the overall mortality rates for CHD in both genders showed an upward trend, with average annual percentage changes of 0.584%, 0.979%, and 0.097%, respectively. The APC model estimates revealed that the mortality risk for the age group of 90 to 94 was 614.97 times higher for males and 519.08 times higher for females compared to the age group of 15 to 19. In terms of period effects, the CHD mortality risk for males and females from 2017 to 2021 was 2.58 times and 1.78 times higher, respectively, than that from 1992 to 1996. Regarding cohort effects, individuals born between 1902 and 1906 had a CHD mortality risk 25.07 times and 24.41 times higher for males and females, respectively, compared to those born between 2002 and 2006.

The overall CHD mortality rate in China is on the rise, with a focus on male and elderly populations. Age, period, and birth cohort each have independent effects on CHD mortality risk. Therefore, a multifaceted approach is necessary to advance preventive measures, control risk factors, and reduce mortality risks among residents.

To evaluate the long-term trends in mortality rates attributed to AIDS and sexually transmitted infections (STIs) due to unsafe sexual behavior in China from 1990 to 2019.

Data on AIDS and STI mortality attributed to unsafe sexual behavior were sourced from the Global Burden of Disease Study (GBD) 2019. An age-period-cohort model was employed to assess potential age, period, and cohort effects on long-term trends.

From 1990 to 2019, the overall annual percentage change in mortality rates attributed to unsafe sexual behavior was 3.4% (95%CI: 3.0%-3.7%) for females and 6.4% (95%CI: 6.0%-6.8%) for males in China. Among different age groups, males aged 25 to 79 showed a higher annual percentage change than females (P<0.05). In the reference cohort, male mortality rates increased with age, while female mortality rates declined after the age of 79. The period mortality risk for males exhibited a consistently increasing trend, whereas the period mortality risk for females slightly decreased between 2010 and 2014 but increased thereafter. Mortality risks for both males and females born after 1925-1929 showed an upward trend over time.

Between 1990 and 2019, there was an increase in mortality rates attributed to AIDS and STIs due to unsafe sexual behavior among both males and females in China. Unsafe sexual behavior remains a significant issue in the prevention and control of AIDS and STIs. Strengthening sexual education, promoting condom use during sexual activities, and ensuring cleanliness in sexual behavior are essential.

To investigate the shared genetic structure between six autoimmune diseases (AIDs) and ten psychiatric disorders (PDs) using Genome Structural Equation Modeling (GSEM) and Mendelian randomization (MR).

The research employed linkage disequilibrium score regression to assess the genetic correlations between diseases. GSEM was introduced for exploratory factor analysis on odd-numbered chromosomes and confirmatory factor analysis on even-numbered chromosomes for cross-validation, along with path analysis to establish a three-factor model and hierarchical model.Additionally, a multivariable genome-wide association study was conducted on latent factors to test the bidirectional causal relationships between mediating variables and factors, thereby revealing the complex genetic relationships among the diseases.

GSEM results indicated that the selected 16 diseases could be explained by a three-factor model consisting of three independent factors, which fitted the research data best (χ²=865.291, AIC=929.291, CFI=0.940, SRMR=0.097). In this model, Factor 1 and Factor 3 exhibited characteristics closely related to autoimmune diseases, while Factor 2 primarily encompassed psychiatric disorders, with scleroderma serving as a mediating variable linking the two types of diseases. MR results revealed a bidirectional causal effect between scleroderma and Factor 2 and Factor 3.

GSEM and MR can be utilized to uncover the shared genetic structure and causal effects between AIDs and PDs, thereby highlighting their interactions and providing an important methodological tool for understanding the genetic relationships among complex diseases.

To investigate the impact of changes in the concentrations of major gaseous pollutants in the air of Shijiazhuang on the outpatient visits for neurological disorders in children.

Data on air pollutants, meteorological conditions, and outpatient visits for pediatric neurological disorders from 2013 to 2021 in Shijiazhuang were collected. A case-crossover study based on conditional logistic regression models was employed to assess the effects of changes in NO₂ and SO₂ concentrations on the outpatient visits for neurological disorders in children.

During the study period, for every increase of 10 μg/m³ in NO₂ concentration, the risk of outpatient visits for neurological disorders in children increased by 1.445% (95%CI: 0.980%-1.911%); for every increase of 10 μg/m³ in SO₂ concentration, the risk increased by 0.408% (95%CI: 0.161%-0.655%). Stratified analysis revealed that girls and children aged 7 to 14 years were sensitive populations to SO₂ exposure, and the harmful effects of gaseous pollutants on the neurological system of children were stronger in winter.

Exposure to gaseous pollutants in Shijiazhuang is associated with an increase in outpatient visits for neurological disorders in children, with variations in effects observed based on gender, age, and season.

To investigate the effects of daily average temperature and relative humidity on the incidence of hand, foot, and mouth disease (HFMD) in Qingdao, as well as their lagged effects, providing data support for prevention and control strategies in the city.

Utilizing HFMD case data from 2010 to 2019 provided by the Qingdao Center for Disease Control and Prevention and meteorological data measured by the China National Meteorological Science Data Center, we first employed Pearson correlation analysis to identify key meteorological factors. Subsequently, the Prophet model was used to analyze the periodicity and trends of HFMD incidence in relation to meteorological factors. Finally, a distributed lag nonlinear model was applied to quantify the lagged effects.

The study found that when the daily average temperature in Qingdao ranged from 23°C to 30°C, the relative risk (RR) of HFMD significantly increased, peaking at approximately 2.2 when the temperature reached 30°C. Similarly, when relative humidity was between 70% and 90%, the RR increased notably, peaking at around 2.5 as humidity approached 90%. Additionally, the effects of daily average temperature and relative humidity on HFMD incidence exhibited lagged characteristics, typically with a lag period of about 7 days. When the daily average temperature exceeded 17°C, the risk of HFMD transmission due to lagged effects gradually increased; likewise, when relative humidity surpassed 70%, the lag period was approximately 7 days, resulting in a significant enhancement of transmission risk.

The findings indicate that when the temperature in Qingdao approaches 23°C or humidity nears 70%, there will be a significant impact on HFMD incidence one week later. Therefore, it is recommended that relevant departments in Qingdao implement preventive measures in advance during these meteorological conditions to reduce the risk of HFMD transmission.