Objective: To investigate the prevalence of hypertension, diabetes and dyslipidemia among physical examination populations at ages of 35 to 75 years in Karamay City of Xinjiang Uygur Autonomous Region, so as to provide insights into the management of chronic disease control. Methods: Residents receiving physical examinations at ages of 35 to 75 years were sampled from 9 communities in Karamay City using the cluster random sampling method. Demographic features and health-related behaviors were collected using questionnaires, and the height, weight, blood pressure, and fasting blood glucose and blood lipid levels were measured. The prevalence of hypertension, diabetes and dyslipidemia was descriptively analyzed, and their risk factors were identified using multivariable logistic regression analysis. Results: A total of 32 556 subjects were sampled, including 12 354 males ( 37.95% ) and 20 202 females ( 62.05% ), with a mean age of ( 56.63±12.78 ) years. The prevalence of hypertension, diabetes and dyslipidemia was 31.72%, 12.18% and 28.69%, and the common comorbidity was dyslipidemia with hypertension ( 2 483 cases, 7.63% ). Multivariable logistic regression analysis identified men ( OR=1.362, 1.823 and 1.130 ), ages of ≥40 years ( OR=3.327-14.019, 2.870-15.337 and 1.530-2.092 ), a family history of chronic diseases ( OR=1.147, 1.249 and 1.200 ), smoking ( OR=1.111, 1.464 and 1.248 ), meat-based diet ( OR=2.081, 2.266 and 1.110 ), vegetable-based diet ( OR=0.479, 0.353 and 0.634 ), underweight ( OR=0.504, 0.298 and 0.546 ), overweight ( OR=1.872, 1.565 and 1.289 ) and obesity ( OR=2.840, 2.177 and 1.230 ) as common influencing factors for hypertension, diabetes and dyslipidemia. Conclusions The prevalence of hypertension is high among physical examination populations at ages of 35 to 75 years in Karamay City. Gender, age, a family history of chronic diseases, smoking, diet habits and body mass index are common factors affecting hypertension, diabetes and dyslipidemia.

Objective: To analyze the characteristics of fine particulate matter (PM2.5) pollution in Urumqi City, Xinjiang Uygur Autonomous Region from 2016 to 2023 and establish a prediction model, so as to provide the reference for air pollution prevention and control. Methods: PM2.5 monitoring data of Urumqi City from 2016 to 2023 were collected through the website of Ministry of Ecology and Environment of China. The changing trend of PM2.5 concentration was analyzed using temporal chart and seasonal index. PM2.5 monthly average concentrations from 2016 to 2023 were used to establish an autoregressive integrated moving average (ARIMA) model, and the data in 2023 was fitted and compared with the actual values, using mean absolute percentage error (MAPE) to evaluate the effectiveness of the model, and PM2.5 monthly average concentration from 2024 to 2025 was predicted. Results: PM2.5 daily average concentration in Urumqi City showed a decreasing trend from 2016 to 2023 (rs=-0.239, P<0.001), with high seasonal indexes in January, February and December, indicating certain seasonal characteristics. The optional model was ARIMA (1, 0, 0) (1, 1, 0)12, with the value of Akaike information criterion, corrected Akaike information criterion, and Bayesian information criterion being 727.38, 727.88 and 737.10, respectively. PM2.5 monthly average concentration in 2023 was fitted and compared with the actual values, with an absolute error range of 0.31-7.45 μg/m3, a relative error range of 0.01-0.53, and MAPE of 14.42%. PM2.5 monthly average concentration in Urumqi City from 2024 to 2025 was predicted to be consistent with the trend from 2016 to 2023. Conclusions PM2.5 concentration in Urumqi City showed a tendency towards a decline from 2016 to 2023, and was relatively high in winter. ARIMA (1, 0, 0) (1, 1, 0)12 can be used for short-term prediction of PM2.5 pollution in Urumqi City.

Objective: To construct a prediction model of non-alcoholic fatty liver disease (NAFLD) in middle-aged and elderly patients with type 2 diabetes mellitus (T2DM), so as to provide basis for early screening and prevention of T2DM complicated with NAFLD. Methods: Patients aged 45 years and above and diagnosed with T2DM in Karamay Hospital of People's Hospital of Xinjiang Uygur Autonomous Region in 2021 were collected as the study subjects. The data of general demographic characteristics and biochemical test results were collected. The patients were randomly divided into training group (n=3 241) and validation group (n=1 389) according to the ratio of 7∶3. LASSO regression and multivariable logistic regression model were used to select predictive factors. The nomograph model for prediction of NAFLD risk in T2DM patients was established. The predictive value of the model was evaluated using the receiver operating characteristic (ROC), adjusted curve and decision clinical analysis. Results: Totally 4 630 T2DM cases were included, including 1 279 cases (27.62%) complicated with NAFLD. LASSO regression and multivariable logistic regression analysis identified gender, age, diastolic blood pressure, body mass index, alanine transaminase, triglycerides, low density lipoprotein cholesterol and platelet count as risk prediction factors for NAFLD in T2DM patients. The area under the ROC curve was 0.823 (95%CI: 0.814-0.832) for the training group and 0.809 (95%CI: 0.799-0.818) for the validation group, and Hosmer-Lemeshow test showed a good fitting effect (P>0.05). Decision curve analysis showed higher net clinical benefit of using the predictive model to predict NAFLD risk when the risk threshold probability was 0.27 to 0.85. Conclusion The nomogram model established has a good predictive value for the risk of NAFLD in T2DM patients aged 45 years and above.

Background Coal workers are inclined to report multi-site work-related musculoskeletal disorders (WMSDs) due to their specific working environment and extensive exposure to occupational hazards, which seriously affect the physical and mental health of coal workers. objective To investigate the prevalence of multi-site WMSDs among workers in coal mining enterprises in Xinjiang, and analyze the related factors influencing multi-site WMSDs. Methods Using stratified cluster random sampling method, Musculoskeletal Disorders Questionnaire, Job Burnout Questionnaire, and Brief Occupational Stress Questionnaire were distributed in six Xinjiang coal mining enterprises to collect data on general information, prevalence of WMSDs in the past year, work-related information, job burnout, and occupational stress among coal miners with a working experience ≥ 1 year. A multiple logistic regression model was used to analyze the influencing factors of multi-site WMSDs. Results A total of 1730 questionnaires were distributed in this survey, 1448 valid questionnaires were recovered, and the valid recovery rate was 83.7%. Among the 1448 coal miners, 93.2% were males and 6.8% were females; 39.2% were aged ≤ 35 years, 31.1% were aged 35-45 years, and 29.6% were aged > 45 years; 58.4% reported ≤ 10 years of working experience, 20.0% reported 10-20 years, and 21.6% reported > 20 years. The total prevalence rate of WMSDs in the coal miners was 75.6% (1095/1448), the prevalence rate of multi-site WMSDs was 58.4% (846/1448), and the prevalence rate of one-site WMSDs was 17.2% (249/1448). The results of multiple logistic regression analysis showed that working experience > 20 years (OR=2.245, 95%CI: 1.655-3.045), severe burnout (OR=2.644, 95%CI: 1.549-4.516), and multiple repetitive operations per minute very often (OR=2.038, 95%CI: 1.339-3.101), often bending at larger angles (OR=1.467, 95%CI: 1.111-1.938), long-time bending the neck forward (OR=1.671, 95%CI: 1.294-2.159), and slipping or falling down (OR=2.459, 95%CI: 1.908-3.168) were positively correlated with multi-site WMSDs; sufficient rest time (OR=0.718, 95%CI: 0.565-0.913) was negatively correlated with multi-site WMSDs. Conclusion Multi-site WMSDs is common among workers in coal mining enterprises, and the prevalence rate of multi-site WMSDs is higher than that of one-site WMSDs. Working experience, job burnout, frequent multiple repetitive operations per minute, often bending at larger angles, long-time bending the neck forward, slipping or falling down, and sufficient rest time are influencing factors of multi-site WMSDs in coal workers.

Background After working in a harsh occupational hazard environment for a long time, open-pit coal mine workers are under tremendous physical and mental pressure, which is prone to presenteeism behavior. objective To identify the relationships between presenteeism, job burnout, and social support of open-pit coal miners, and verify potential mediating effect of job burnout between social support and presenteeism. Methods In 2020—2021, a questionnaire survey was conducted among employees of 6 open-pit coal mining enterprises in Xinjiang by stratified cluster random sampling. Job Burnout Questionnaire, Job Content Questionnaire, and Presenteeism Behavior Scale were used to evaluate burnout, social support, and presenteeism behavior in the study subjects. SPSS 26.0 software was used for t test, F test, correlation analysis, and mediating effect test. Results A total of 1199 questionnaires were distributed and 1083 valid questionnaires were recovered, with an effective recovery rate of 90.3%. The M (P₂₅, P₇₅) scores of presenteeism behavior, social support, and job burnout were 2.0 (2.0, 5.0), 24.0 (23.0, 26.0), and 45.0 (34.0, 51.0), respectively. The Spearman correlation analysis results showed that there was a significant negative correlation between social support and job burnout (\begin{document}$ r $\end{document}=−0.200, P<0.01), a significant negative correlation between presenteeism and social support (\begin{document}$ r $\end{document}=−0.260, P<0.01), and a significant positive correlation between presenteeism and job burnout (\begin{document}$ r $\end{document}=0.304, \begin{document}$ P $\end{document}<0.01). The results of mediating effect test showed that social support had a negative effect on presenteeism (\begin{document}$ \beta $\end{document}=−0.122, \begin{document}$ P $\end{document}<0.001). Social support negatively predicted job burnout (\begin{document}$ \beta $\end{document}=−0.779, \begin{document}$ P $\end{document}<0.001). Job burnout had a partial mediating effect between social support and presenteeism, with an effect value of −0.0294 (95%CI: −0.0394, −0.0201), accounting for 24.18% of the total effect. Conclusion Social support negatively affects the presenteeism behavior of open-pit coal mine workers, and job burnout plays a partial mediating role between social support and presenteeism behavior.