Objective To investigate the effects of joint function screening and correction on intervention efficacy of prevention and assessment score of training injuries in new recruits.Methods A randomized controlled study was conducted on 265 new recruits subjected from two organizational units of an army unit with cluster sampling.Based on entire organizational unit,the participants were randomly divided into a control group(n=132)and an experimental group(n=133).The experimental group received joint function screening and corrective movement training,which was subsequently applied in the new recruit training,while the control group underwent training according to conventional methods.Joint function were collected before and after training.The demographic data,assessment score of training,and incidence of training injuries were collected through the participant's own organizational unit.Receiver operating characteristic(ROC)curve was plotted to evaluate the efficacy of joint function screening in predicting training injuries,and binary logistic regression and general linear regression analyses were applied to verify the correlation of joint function screening score with training injuries and assessment score of training.Results After new training,the score of joint function screening was significantly higher in the experimental group than the control group(16.62±1.87 vs 14.92±2.58,P<0.001).And the score was obviously increased in the experimental group(16.62±1.87 vs 12.82±1.98,P<0.001)and the control group(14.92±2.58 vs 12.95±1.81,P<0.001)when compared with the corresponding score before training.The area under the ROC curve(AUC)of joint function screening in predicting training injuries was 0.762(95%CI:0.694～0.830),indicating good predictive efficacy.During the new training process,the incidence of training injuries in the experimental group(13.53%)was significantly lower than that in the control group(24.24%,Chi-square=4.963,P=0.026).Binary logistic regression analysis showed that the pre-training assessment score of joint function screening was an important influencing factor for training injuries in new recruits(OR=0.552,95%CI:0.413～0.660,P<0.001).The experimental group obtained notably higher mean assessment score than the control group[733.00(716.00,752.75)vs 728.79(710.46,744.28),P=0.027].Linear regression analysis revealed a correlation between post-training score of joint function screening and the assessment score of newly trained personnel(P<0.001).Conclusion Joint function screening and correction for newly trained personnel can effectively prevent training-related injuries during the new training period,and correcting joint function through training can effectively improve the assessment score of newly trained personnel.

Objective To investigate the status quo of health literacy among military personnel stationing on plateau and analyze its influencing factors.Methods National Health Literacy Monitoring Questionnaire(2015),self-made questionnaire for demographic data based on literature,Connor-Davidson Resilience Scale,Simplified Coping Style Questionnaire,and Positive and Negative Affect Scale were employed to survey 2 516 officers and soldiers stationing on plateau with aid of a WeChat APP Questionnaire Star.Their current status of health literacy and its influencing factors were analyzed.Results The survey results showed that the overall health literacy level was 20.03％among the 2 516 participants.The literacy levels of basic knowledge and concepts,healthy lifestyles and behaviors,and health skills were 31.08％,26.23％,and 26.63％,respectively,and the health literacy levels of scientific health concepts,infectious disease prevention and treatment,chronic disease prevention and treatment,safety and first aid,basic medical care,and health information were 40.58％,19.36％,9.62％,82.75％,29.61％,and 45.03％,respectively.Multivariate unconditional logistic regression analysis indicated that the influencing factors of health literacy level were years of working(OR=1.857,95％CI:1.391～2.479;OR=4.657,95％CI:3.297～6.578),ethnicity(OR=0.394,95％CI:0.251～0.620),marriage(OR=0.609,95％CI:0.430～0.861),only-child family(OR=0.759,95％CI:0.585～0.985),home location(OR=0.545,95％CI:0.359～0.827),smoking(OR=1.579,95％CI:1.254～1.988),education level(OR=3.638,95％CI:1.500～8.822),weekly online game time(OR=0.517,95％CI:0.365～0.731;OR=0.351,95％CI:0.172～0.716),number of physical checkups per year(OR=3.251,95％CI:1.359～7.778;OR=4.545,95％CI:1.841～11.221),father's occupation(OR=5.185,95％CI:1.800～14.933;OR=3.229,95％CI:1.261～8.270),mother's occupation(OR=0.221,95％CI:0.086～0.568;OR=0.218,95％CI:0.081～0.587;OR=0.046,95％CI:0.018～0.118),positive coping(OR=1.052,95％CI:1.033～1.072),and negative coping(OR=0.950,95％CI:0.929～0.972).Conclusion The overall health literacy level is quite low among the plateau military personnel in this ministry,and the relevant departments should actively explore effective interventions to comprehensively improve their health literacy based on the influencing factors.

Military vocational education has become one of the strategies to strengthen the military in the new era. The army urgently needs to build a number of featured online courses of military vocational education. Therefore, taking the course "Knowledge and Skills of Health Education for the Army" as an example, this paper discusses the overall construction objectives, construction ideas, teaching content, curriculum and test question bank construction of the course. In addition, this paper analyzes and summarizes the problems existing in the teaching organization, implementation, and preliminary application, so as to provide ideas and construction strategies for the construction of online open courses in other military vocational education.

Objective: To investigate the association between aflatoxin exposure and primary hepatocellular carcinoma (PHC) development. Methods: From December 2013 to May 2016, we selected 214 patients newly diagnosed with PHC as cases, and 214 patients as controls from three hospitals in Chongqing. Cases were confirmed with PHC diagnosis standard. And cases caused by clear reasons such as drug-induced liver injury, alcoholic liver damage, fatty liver and gallstones etiology, were excluded. Controls were included with no cancer and no digestive system disease, and recruited simultaneously with cases. Cases and controls were frequency-matched (1∶1) by same gender and age (±3 years). Peripheral blood and random urine samples were collected and analyzed for serum HBsAg status by biochemistry analyzer, and serum AFB₁-ALB adduct and urinary AFB₁-N⁷-GUA adduct by ELISA. Basic information, living habits and history of disease for patients were obtained by questionnaires. We used wilcoxon rank sum test to compare the median of serum AFB₁-ALB adduct and urinary AFB₁-N⁷-GUA adduct in cases and controls. Logistic regression analyses were performed to assess risk factors for PHC, and synergism index (S) of aflatoxin with other factors was estimated by the method of Andersson. Results: There was no significant difference in age between PHC cases (50.74±9.67) years and controls (51.15±9.90) years. Logistic regression showed that the odds ratio of HBV infection for PHC development was 46.3 (95% CI: 23.3-88.0). There was a significant difference in median concentrations of serum AFB₁-ALB adduct (cases vs controls: 146.23 vs 74.42 ng/g albumin, P<0.001), but no difference in median concentrations of urinary AFB₁-N⁷-GUA adduct was observed (cases vs controls: 0.17 vs 0.14 ng/mg creatinine, P<0.210). The odd ratios for PHC risk after adjustment were 1.9 (95%CI: 1.1-3.4) for AFB₁-ALB adduct, and 2.1 (95%CI: 1.0-4.2) for AFB₁-N⁷-GUA adduct. Moreover, we observed a positive interaction of aflatoxin exposure with HBV, alcohol drinking, and diabetes. The S was 4.7 (95%CI: 2.8-7.9), 3.5 (95%CI: 1.0-12.0), and 12.4 (95%CI: 1.8-84.2), respectively for serum AFB₁-ALB adduct with each of the three factors mentioned, and was 1.9 (95%CI:1.1-3.1), 2.0 (95%CI: 1.1-3.6), and 2.0 (95%CI: 1.1-3.6), respectively for urinary AFB₁-N⁷-GUA adduct with each of the three factors mentioned. Conclusion HBV was still the main risk factor, and AFB₁ exposure was also an independent risk factor for PHC in Chongqing. There was a positive interaction of aflatoxin with HBV, alcohol drinking, and diabetes.