Objective: To investigate the association between medium to long term PM 2.5 exposure around school areas and overweight/obesity among primary and secondary school students in Guangxi, providing data support and theoretical foundations for scientifically addressing overweight and obesity in primary and secondary school students. Methods: From September to November 2023, a stratified cluster random sampling method was employed to select 251 183 students aged 7-18 years (grade 1 to grade 12) from 14 prefecture level cities (111 districts and counties) in Guangxi. PM 2.5 mass concentration data were obtained from the Tracking Air Pollution in China (TAP) dataset. Preliminary comparative analysis was conducted using the Mann-Whitney U test, while binary Logistic regression models were applied to quantify the relationship between PM 2.5 exposure and overweight/obesity. Restricted cubic spline analysis was further utilized to examine the nonlinear association between PM 2.5 concentration and overweight/obesity risk. Results: The detection rate of overweight/obesity among Guangxi students in 2023 was 19.5%. The median PM 2.5 concentration in the year prior to the study was higher in the overweight/obesity group (23.22 μg/m 3) compared to the non overweight/obesity group (22.63 μg/m 3) ( Z=-15.66, P <0.01), and consistent trends were observed across gender (male/female) and educational stage (primary/junior/senior high school) subgroups (all P <0.01). Binary Logistic regression revealed that for every 10 μg/m 3 increase in the annual average PM 2.5 concentration, the risk of overweight/obesity increased by 12% ( OR=1.12, 95%CI=1.09- 1.15 , P <0.01). Restricted cubic spline analysis indicated a nonlinear relationship between monthly PM 2.5 levels and overweight/obesity risk ( P trend <0.01). Below 22.68 μg/m 3, PM 2.5 exposure showed no significant association with obesity risk; above the threshold, the risk increased with rising PM 2.5 levels. Conclusion Medium to long term PM 2.5 exposure around school environments is significantly associated with overweight/obesity among primary and secondary school students.

Objective: To explore the bidirectional associations among body mass index Z scores (BMI Z scores) and weight stigma with depressive symptoms in adolescents, thereby providing evidence for targeted intervention strategies. Methods: A stratified cluster random sampling method was employed to select 18 301 adolescents aged 12-18 years from all 12 prefectures (103 counties) in the Inner Mongolia Autonomous Region, and two waves of longitudinal surveys were conducted in September 2023 (T1) and September 2024 (T2) among the adolescents. Weight stigma was assessed by using a self developed questionnaire, depressive symptom was measured with the Center for Epidemiologic Studies Depression Scale (CES-D), and BMI Z scores were calculated according to the World Health Organization standards. Pearson correlation analysis was used to examine associations among variables, and cross lagged panel models were constructed to investigate the dynamic bidirectional relationships among the three variables. Results: Adolescents BMI Z scores and weight stigma with depressive symptoms all exhibited autoregressive stability across the two time points (autoregressive paths, all P <0.01). Cross lagged model comparisons indicated that the bidirectional path model achieved the best fit ( χ 2=12.65, RMSEA =0.017, CFI =1.000; △ χ 2=193.39, P <0.01), supporting dynamic bidirectional associations among the three variables. After adjusting for gender, age, subjective social status and only child status, T1 BMI Z scores among adolescents positively predicted T2 weight stigma ( β =0.061), and T1 weight stigma positively predicted T2 depressive symptoms ( β =0.608); in the reverse direction, T1 depressive symptoms predicted T2 weight stigma ( β =0.003), and T1 weight stigma predicted T2 BMI Z scores ( β =0.081) (all P <0.01). Conclusions There is a bidirectional cross lagged relationship among adolescents BMI Z scores and weight stigma with depressive symptoms, suggesting that weight stigma may serve as a key psychological variable linking obesity and depressive symptoms. Greater attention should be paid to the potential threat of weight stigma to adolescents mental health, with intervention strategies expanded from a solely physiological focus to encompass psychosocial dimensions.

Objective: To evaluate the intervention effectiveness of co-occurrence and prevention for myopia and obesity among primary and secondary school students, so as to provide a scientific basis for the development of comprehensive intervention measures in myopia and obesity. Methods: From September 2022 to September 2023, a cluster random sampling method was used to select 6 primary schools and 6 junior high schools from Tongzhou District, Beijing. Participants were randomly assigned to an intervention group (914 before intervention and 754 after intervention) and a control group (868 before intervention and 652 after intervention), with an expected duration of one academic year. Based on the RE-AIM framework, integrate resources from families, schools, communities, and medical institutions to develop a school-based intervention technology packagefor the co-occurrence and prevention of myopia and obesity in children. The intervention group received intervention according to the comprehensive intervention technology package, while the control group did not receive any intervention measures. Relevant health indicators during the baseline period and after intervention were measured and collected, and groups were compared by Chi quest test, t-test and Wilcoxon rank sum test. Results: After intervention, the uncorrected visual acuity of primary and secondary school students in the intervention group (4.79±0.30) and the control group (4.77±0.33) both decreased compared to those before intervention (4.80±0.30, 4.90±0.32) ( t =-7.00,-5.24); the decrease in uncorrected visual acuity in the intervention group was smaller than that in the control group( t =5.33)( P <0.01). After intervention, body mass index, waist circumference, hip circumference, and body fat percentage of primary and secondary school students in the intervention group decreased compared to those before intervention. However, the changes in these indicators were not statistically significant ( t/Z =-0.03, - 0.36，- 0.30，- 0.01, P >0.05); the above indicators in the control group increased compared to those before intervention, but only hip circumference and body fat percentage showed statistically significant changes ( t/Z =2.17, 2.62, P <0.05). After intervention, both the intervention group and the control group showed increases in systolic and diastolic blood pressure compared to those before intervention(intervention group: t =2.16,5.29; control group: t =6.84,5.07); the intervention group had lower systolic and diastolic blood pressure than the control group( t = -5.27 , -2.08)( P <0.05). After intervention, the intervention and the control groups had statistically significant differences in cognitive accuracy(92.48%, 69.33%) in terms of "outdoor exercise can prevent myopia" and "having 5 servings of adult fist sized vegetables and fruits every day" ( χ 2=6.30, 7.86, P <0.05). There was a statistically significant difference in the proportion of primary and secondary school students in the intervention group (40.98%) and the control group (35.43%) for "who did not drink sugary drinks for every day in the past 7 days" ( χ 2=4.32, P <0.05). After intervention, the intervention group and the control group showed increases in "school outdoor activity duration on school days" and "outdoor activity duration on rest days" compared to those before intervention ( t/Z =-13.32,-9.71;- 2.59，-2.69）；the behavior rate of "visual acuity measurement frequency at least once every 3 months" in the intervention group (46.68%) and the control group (52.76%) increased compared to those before intervention (36.43%, 44.01%), and the increases in the intervention group were greater than that in the control group ( χ 2=17.52,11.08) ( P <0.05). Conclusions Comprehensive intervention measures have significant intervention effects on controlling the occurrence and development of comorbidity of myopia and obesity in children. It could actively promote collaboration and cooperation among families, schools, communities and medical institutions to reduce the occurrence of myopia and obesity among primary and secondary school students.

Background Thyroid hormones are crucial for development and proper functioning of human physiological systems. Current research on the thyroid mainly focuses on the impacts of lifestyle factors on thyroid dysfunction, while less attention is paid to the factors affecting thyroid hormone levels, especially occupational hazards, which warrants further investigation. Objective To investigate the associations between occupational hazard exposure and thyroid-stimulating hormone (TSH) and thyroid hormone levels in male coal mine workers. Methods A cross-sectional study design was adopted. A total of 12564 workers who participated in the occupational health check-ups at the Xishan Coal Electricity (Group) Corporation Occupational Disease Prevention and Control Institute in 2023 and met the inclusion and exclusion criteria were selected as research subjects. A self-designed electronic questionnaire was used to collect basic information, occupational history, and lifestyle habits of all study subjects. Height, weight, thyroid function test results, and occupational hazard exposure of the study subjects were obtained through occupational health examinations and routine workplace occupational hazard detection records. Generalized linear regression was used to analyze the associations between occupational hazard exposure and the levels of TSH and thyroid hormones. Results The median (P₂₅, P₇₅) levels of triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), and TSH in the included 12564 male coal mine workers were 1.16 (1.03, 1.29) ng·mL⁻¹, 7.70 (6.70, 8.90) μg·dL⁻¹, 3.63 (3.40, 3.84) pg·mL⁻¹, 1.19 (1.08, 1.30) ng·dL⁻¹, and 1.93 (1.36, 2.78) μIU·mL⁻¹, respectively. The overall abnormality rate of thyroid hormones was 2.83%, with the highest rate for subclinical hypothyroidism (1.83%), followed by hyperthyroidism (0.37%), hypothyroidism (0.32%), and subclinical hyperthyroidism (0.31%). After adjustment for confounding factors, the generalized linear regression model showed that long working hours were associated with higher levels of T3 and FT3, with β (95%CI) values of 0.011 (0.003, 0.019) and 0.038 (0.019, 0.057) respectively. Night shift work was linked to increased TSH levels and decreased FT4 levels, with β (95%CI) values of 0.171 (0.016, 0.326) and −0.012 (−0.019, −0.006) respectively. Coal dust exposure was associated with decreased levels of T3 and T4, with β (95%CI) values of −0.022 (−0.037, −0.008) and −0.320 (−0.434, −0.207) respectively. Noise exposure was related to decreased levels of T4 and FT4, with β (95%CI) values of −0.102 (−0.166, −0.038) and −0.020 (−0.027, −0.013) respectively. Conclusion The TSH and thyroid hormone levels of coal miners are mostly within the normal reference ranges, with a low abnormality rate. Long work hours, night shift work, coal dust, and noise are associated with the levels of TSH and thyroid hormone levels in the male miners. Coal companies should reasonably arrange working hours, optimize the night shift scheduling system, and enhance protection against coal dust and noise to promote occupational health and safeguard the physical health of miners.

Abstract The COVID-19 pandemic has posed a series of complex challenges. COVID-19 in children and adolescents is generally less severe than in adults and the elderly; however, some children and adolescents may experience severe complications and adverse health effects even after mild or asymptomatic COVID-19 infections. The article focuses on gathering the epidemic characteristics, health impact, risk factors, prevention and control measures, and vaccination status of children and adolescents with COVID-19 infection to provide recommendations for protecting children and adolescents in the post COVID-19 era.

Objective To explore the CT imaging features and independent risk factors for cystic pulmonary nodules and establish a malignant probability prediction model. Methods The patients with cystic pulmonary nodules admitted to the Department of Thoracic Surgery of the First People's Hospital of Neijiang from January 2017 to February 2022 were retrospectively enrolled. They were divided into a malignant group and a benign group according to the pathological results. The clinical data and preoperative chest CT imaging features of the two groups were collected, and the independent risk factors for malignant cystic pulmonary nodules were screened out by logistic regression analysis, so as to establish a prediction model for benign and malignant cystic pulmonary nodules. Results A total of 107 patients were enrolled. There were 76 patients in the malignant group, including 36 males and 40 females, with an average age of 59.65±11.74 years. There were 31 patients in the benign group, including 16 males and 15 females, with an average age of 58.96±13.91 years. Multivariate logistic analysis showed that the special CT imaging features such as cystic wall nodules [OR=3.538, 95%CI (1.231, 10.164), P=0.019], short burrs [OR=4.106, 95%CI (1.454, 11.598), P=0.008], cystic wall morphology [OR=6.978, 95%CI (2.374, 20.505), P<0.001], and the number of cysts [OR=4.179, 95%CI (1.438, 12.146), P=0.009] were independent risk factors for cystic lung cancer. A prediction model was established: P=ex/(1+ex), X=–2.453+1.264×cystic wall nodules+1.412×short burrs+1.943×cystic wall morphology+1.430×the number of cysts. The area under the receiver operating charateristic curve was 0.830, the sensitivity was 82.9%, and the specificity was 74.2%. Conclusion Cystic wall nodules, short burrs, cystic wall morphology, and the number of cysts are the independent risk factors for cystic lung cancer, and the established prediction model can be used as a screening method for cystic pulmonary nodules.

Objective To understand the molecular epidemiological characteristics of Norovirus outbreaks and the genome evolution of Norovirus epidemic strains in Hainan Province from 2020 to 2022.Methods The information and samples have been collected from the norovirus outbreaks from 2020 to 2022.Norovirus was detected by using the real-time PCR in these samples,then the detected sequences were amplified the analyzed.The Norovirus se-quences of 8 strains had been amplified and analyzed.Results From 2020 to 2022,39 gastroenteritis outbreaks were reported,and 25 outbreaks caused by Norovirus which mainly occurred in childcare institutions and schools(20/25,80％).The Norovirus outbreaks were mainly concentrated in counties around Haikou(northeast),which including Ding'an(5 cases),Wenchang(4 cases),Chengmai(4 cases),and Lingao(3 cases);following by western regions which included Baisha(2 cases),Ledong(2 cases),and Dongfang(3 cases).1 case was in Wanning in the southeast.Among individuals aged 2-17,the positive proportion of Norovirus in males was higher than that in females.Among individuals aged over 55,the proportion of Norovirus positive in females was higher than that in males.The gender of positive samples among individuals aged 18-40 was related to their profession.According to RT-PCR typing and sequencing,GⅡ group Norovirus were classified in13 outbreaks.There were 4 genotypes detected.GⅡ.2[P1 6]was the main epidemic strain with 60％(9/13),and the other three genotypes were GⅡ.4 Sydney[P31](15.4％,2/13)GⅡ.4 Sydney[P16](7.7％,1/13)and GⅡ.3[P12](7.7％,1/13).Further genic analysis of 8 Norovirus strains showed that all of them were still in the same branch as the previ-ous strain,and all exhibited a certain amount of amino acid variation.Conclusion Norovirus is the main pathogen of gastroenteritis outbreaks in Hainan province,and the main epidemic strain is GⅡ.2[P16].It is necessary to continue to strengthen the monitoring that provides scientific evidence for the prevention and control of norovirus out-breaks in Hainan region.