To analyze the relationship between obstructive sleep apnea (OSA) and nocturnal blood pressure, and to evaluate the possible effect of obesity in this association, so as to provide reference for further exploring the mechanism of OSA-related hypertension.

A total of 753 adult patients diagnosed with OSA were randomly selected from August 2021 to December 2022 in the Sleep Medicine Center of the Fourth West China Hospital of Sichuan University because of snoring, apnea, and other reasons. After polysomnography (PSG) was completed, 753 adult patients diagnosed with OSA were selected as research subjects. The general data of patients, PSG related data, nocturnal blood pressure and related indicators were collected. Correlation analysis and structural equation model were used to analyze the effects of OSA and obesity on nocturnal blood pressure.

In patients with OSA, Apnea Hyponea Index (AHI) was positively correlated with systolic blood pressure (SBP), diastolic blood pressure (DBP) (r=0.297 and 0.222, P < 0.001), and BMI (r=0.443, P < 0.001), and BMI was positively correlated with SBP and DBP (r=0.313 and 0.260, P < 0.001). The results of structural equation model suggested that obesity played an intermediary role in the effect of OSA on nocturnal SBP and DBP. The standardized intermediary effect values were 0.063 (95%CI: 0.035-0.090) and 0.059 (95%CI: 0.032-0.087), respectively, and the proportion of intermediary effect was 21.72% and 26.22%, respectively.

OSA can directly affect the blood pressure of patients. At the same time, obesity plays an intermediary role in the effect of OSA on SBP and DBP.

To analyze the changes in lung cancer mortality and DALY attributed to tobacco in China from 1990 to 2019, providing scientific basis for formulating lung cancer prevention and control strategies attributed to tobacco.

Extract lung cancer mortality and DALY rates attributed to tobacco in China from the 2019 Global Burden of Disease database from 1990 to 2019, use Joinpoint software to analyze the trends in mortality and DALY rates, and use an age period cohort (APC) model to analyze age, period, and cohort effects.

The number of lung cancer deaths attributed to tobacco in China increased from 16 500 in 1990 to 51 800 in 2019, and the standardized mortality rate increased from 20.22/100 000 in 1990 to 26.27/100 000 in 2019, with an average annual increase of 0.92% (95% CI: 0.72%-1.11%). The DALY caused by lung cancer attributed to tobacco in China increased from 42.40 million person-years in 1990 to 113.90 million person-years in 2019. The standardized DALY rate increased from 474.81/100 000 in 1990 to 547.54/100 000 in 2019, with an average annual increase of 0.51% (95% CI: 0.27%-0.74%). Compared with the global and different SDI regions, China’s lung cancer standardized mortality rate and standardized DALY rate attributed to tobacco showed the largest increase from 1990 to 2019, reaching 29.93% and 15.32% respectively. The lung cancer mortality rate attributed to tobacco in China from 1990 to 2019 showed an increasing trend with age, with a period effect showing a first decreasing, then increasing, and then decreasing trend. The cohort effect showed a first increasing, then decreasing trend. The prediction model shows that from 2020 to 2030, the standardized mortality rate and standardized DALY rate caused by lung cancer attributed to tobacco in China are both showing a slow upward trend, and may reach 26.96/100 000 and 554.20/100 000 respectively by 2030.

The burden of lung cancer attributed to tobacco in China remained on the rise from 1990 to 2019. Further attention should be paid to the elderly male population, health education, popularization of cancer core knowledge, and early screening, diagnosis, and treatment of lung cancer.

This study aimed to analyze the prevalence of three types of cardiovascular diseases (hypertension, coronary heart disease, and stroke) and their relationships with depression symptoms among rural residents of Yiliang County, Yunnan Province.

A health interview and examination survey was conducted on 2 506 rural residents aged ≥35 years in Yiliang County, Yunnan province by utilizing a multistage stratified random sampling method. A binary logistic regression model was employed to analyze the relationships between depression symptoms and three types of cardiovascular diseases (CVDs): hypertension, coronary heart disease(CHD), and stroke.

The prevalence of hypertension, CHD, stroke, and depression symptoms in the surveyed population was 64.2%, 4.3%, 3.3%, and 5%, respectively. Prevalence of hypertension, CHD, stroke, and depression symptoms increased with age (χ²=106.237,χ²=21.084,χ²=27.135,χ²=43.556,P<0.001). Females exhibited a higher prevalence of both hypertension (67.6% vs. 60.8%,χ²=12.677,P<0.001) and depression symptoms (6.3% vs. 3.8%,χ²=8.080,P<0.05) compared to males. Individuals with lower educational levels and household per capita income had a higher prevalence of hypertension (χ²=23.362,χ²=9.249,P<0.05)and depression symptoms (χ²=16.191,χ²=6.665,P<0.05). The prevalence of depression symptoms were higher in the Han majority than in ethnic minority groups (χ²=14.231, P<0.001). Individuals with good access to medical services had a higher prevalence of depression symptoms than their counterparts (χ²=5.220, P<0.05). The results of logistic regression analysis revealed that individuals with CHD (OR=3.462, 95% CI:1.962-6.108), and stroke (OR=3.683, 95% CI:2.001-6.781) had a higher risk of developing depression symptoms.

The Prevalence of three types of CVDs higher among rural residents in Yiliang County of Yunnan Province compared to other regions. Targeted prevention and intervention efforts are warranted, particularly among females, individuals with lower educational levels, and those with lower incomes. Implementing effective strategies to mitigate the prevalence of CVDs will contribute to improverural residents’ mental health.

To analyze the effects of diabetes distress (DD) and depressive symptoms (DS) on self-efficacy in community patients with type 2 diabetes mellitus (T2DM), and to explore the mediating effect of DD on DS and self-efficacy.

A total of 648 community patients with T2DM in Nanjing were selected by convenience sampling method and investigated with the general information questionnaire, Diabetes Distress Scale, 9-item Patient Health Questionnaire and Diabetes self-efficacy Scale. A multiple linear regression model was used to analyze the influencing factors of self-efficacy, and mediating effect analysis was used to explore the mediating role of DD.

The prevalence of DD and DS was 27.5% and 40.4%, respectively, and the self-efficacy score was 3.82±0.60. DD and DS were significantly positively correlated (r=0.56, P<0.01), and both were negatively correlated with self-efficacy. DD (β=-0.34, P<0.01) and DS (β=-0.16, P<0.01) were the influencing factors of self-efficacy, and DD had a partial mediating effect between DS and self-efficacy, Bootstrap 95%confidence interval was -0.28--0.16 (P<0.01).

Community health workers need to conduct early screening and treatment of DD and DS in T2DM patients, which can help improve patients’ self-efficacy inmanaging the disease.

Toanalyze the application of CNN-BiLSTM combination model and intelligent algorithm optimization in the prediction and early warning of HFMD incidence and to discussthe optimization model for predicting the incidence of HFMD, so as to provide reference for relevant departments to formulate prevention and control measures.

The monthly incidence data of hand, foot and mouth disease in Shanxi Province from January 2009 to December 2019 and the year-end resident population data released by the Shanxi Statistical Yearbook 2008-2020 were collected from January 2009 to December 2019.The monthly incidence data of hand, foot and mouth disease in Shanxi Province from January 2009 to December 2019 were used as sample modeling data to construct the corresponding models in MATLAB 7.6 software, and the prediction effect of each model was compared, and the optimal model was selected according to the principle that the smaller the error value and the higher the accuracy.

By comparing the root mean square error and mean absolute error obtained by predicting the monthly incidence of foot and mouth disease of hand with different models, it can be seen that the CNN-BiLSTM model optimized based on intelligent algorithm is significantly better than the unoptimized CNN-BiLSTM combination model, that is, the values of RMSE and MAE of CNN-BiLSTM-PSO/GAPSO/SSA (1.943 3,1.309 7; 1.879 2, 1.240 2; 1.419 5, 1.169 1) is smaller than the corresponding CNN-BiLSTM model (2.066 3, 1.390 8), among which the CNN-BiLSTM-SSA combination model performs best.

The CNN-LSTM-SSA model has good predictive performance and accuracy in predicting the monthly incidence trend of HFMD, which can be used to predict the future incidence of HFMD in Shanxi Province.

To analyze the mortality trend of lung cancer in Sichuan Province from 2007 to 2021, and provide evidence for formulating lung cancer prevention and control policies in the new period.

Lung cancer mortality was obtained from Health Statistics Yearbook of Sichuan Province. A cohort age-period model was used to estimate the effect of age, period and birth cohort on lung cancer mortality in residents aged 20-84.

The mortality rates of lung cancer in male and female increased from 59.68/100 000 and 16.48/100 000 in 2007 to 75.14/100 000 and 30.49/100 000 in 2021 respectively. Compared with residents aged 20-24, male and female residents aged 75-79 were 101 times and 121 times higher than those aged 20-24 respectively; male and female lung cancer mortality risks from 2017 to 2021 were 1.29 times and 1.31 times higher than those from 2012 to 2016 respectively; male and female lung cancer mortality risks born in 1927—1931 were 73.42 times and 38.49 times higher than those born in 1992—1996 respectively.

Lung cancer mortality in Sichuan Province fluctuates from 2007 to 2021, and male mortality is higher. There were differences in lung cancer mortality risk by age, period, and birth cohort.

To analyze the change of disease burden of injury in China from 1990 to 2019, and to predict the change trend from 2020 to 2034, so as to provide basis for the formulation of injury prevention and control strategies.

Using the global disease burden research database in 2019, the change trends of age-standardized incidence, prevalence, mortality and disability-adjusted life expectancy rate of injuries in China were analyzed, and the average annual change percentage was calculated.The grey prediction model GM (1) was used to predict the annual DALY change trend from 2020 to 2034.

From 1990 to 2019, the incidence, prevalence, mortality and Daly rate of self-injury and interpersonal violence showed a downward trend, with the largest decrease among people aged 0-9 (AAPC=-2.27%,-0.26%,-4.72%,-6.00%). The incidence and prevalence of traffic injuries showed an upward trend, while mortality and DALY rates generally showed a downward trend, but those over 70 years old showed an upward trend (AAPC=0.26%, 0.88%). The incidence of accidental injuries showed an overall downward trend (AAPC=-0.08%), but showed an upward trend in 2006—2019 (AAPC=2.69%), and the mortality and DALY rates showed an overall downward trend, among which the morbidity, prevalence, mortality and Daly rates of people ≥ 70 years old showed an upward trend (AAPC=1.84%, 1.15%, 0.66%, 0.51%). The grey prediction model showed that the DALY of the three kinds of injuries will show a downward trend from 2020 to 2034. It is estimated that by 2035, the Daly rate will decrease to 166.304 / 100 000, 862.338 / 100 000 and 715.27 / 100 000 respectively.

The mortality rate and DALY rate of three kinds of injuries in China show a general downward trend from 1990 to 2019, but the incidence rate of traffic injuries and accidental injuries are still rising, and the disease burden of the elderly is still increasing.

To analyze the epidemiological characteristics and spatiotemporal clustering of hepatitis B virus (HBV)infection in China from 2011 to 2021, to provide a foundation for future HBV prevention and control initiatives.

Data on HBV incidence from 2011 to 2021 across different regions of China were gathered from the "China Health Statistical Yearbook" and the Chinese Center for Disease Control and Prevention. A descriptive analysis was performed to investigate the trends of HBV. Spatial autocorrelation analysis was utilized to explore both global and local spatial clustering of HBV incidence, while spatiotemporal scan analysis was employed to investigate the spatiotemporal clustering of HBV incidence.

Between 2011 and 2021, a total of 10 838 518 cases of HBV were reported in China, with an annual average incidence rate of 71.78 per 100,000 population. There was no statistically significant difference in the decreasing trend of hepatitis B incidence during this period (Z=-1.557, P=0.120). Spatial autocorrelation results identified 7 high-high clustering areas of HBV incidence, primarily in Guangdong, and 3 low-low clustering areas, mainly in Shanghai and Jiangsu. Spatiotemporal scan results revealed 2 high-incidence clusters in the northwest region from 2011 to 2015, shifting to 6 clusters in the south and its northern areas from 2017 to 2021. There were 14 low-incidence clusters from 2016 to 2021, mainly in the east and northeast regions.

From 2011 to 2021, HBV incidence in China displays spatial and spatiotemporal clustering, with a nonsignificant decreasing trend. Future efforts should enhance HBV monitoring and resource allocation for prevention and control in high-prevalence areas.

To investigate the relationship between Dietary Inflammatory Index (DII) and sarcopenia in older adults and to provide a scientific basis for the prevention and treatment of sarcopenia.

From January 2022 to January 2023, 253 older adults over 60 years old were recruited in Chengdu. DII were calculated according to the semi-quantitative food frequency questionnaire, and the groups were divided into Q1-Q4 according to the DII from low to high, sarcopenia was diagnosed according to Asian Working Group for sarcopenia 2019. The relationship between DII and sarcopenia was estimated by logistic regression analysis.

After controlling confounding factors, compared with the Q1 group, the risk of sarcopenia in the Q3 group and Q4 group was 3.94 times and 7.02 times higher than that in the Q1 group (P<0.05), and the risk of sarcopenia increases in older adults with higher DII.

Higher DII increases the risk of sarcopenia, and it is recommended to provide dietary guidance for older adults to reduce the risk of sarcopenia affected by DII.