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Objective: To examine the prevalence of suicide-related behaviors among junior middle school students, and to explore the mediating role of depression in the relationship between suicide-related behaviors and family function., Methods: A total of 2572 junior middle school students from three middle schools in Chengdu were interviewed face-to-face by using suicide-related items from Youth Risk Behavior Surveillance System (YRBSS), Chinese Family Assessment Instrument (C-FAI), and Center for Epidemiologic Studies Depression Scale for Children (CES-DC). The mediating role of depression was analyzed with structural equation model., Results: The prevalence of suicide-related behaviors was 26.01% among the respondents. The prevalence of suicide ideation, suicide plan and suicide attempt were 24.38%, 13.49% and 10.77%, respectively. Depression played a partial mediating role in how family function impacted on suicide-related behaviors, presenting a direct effect value of 0.170 (95% CI : 0.117-0.218, P <0.001) and an indirect effect value of 0.205 (95% CI : 0.176-0.234, P <0.001), with the mediating effect accounting for 54.67% of the total effect., Conclusion: Poor family function may increase the risk of suicide-related behaviors, and this effect is produced mostly through the impact on children's mental health. Improving family function will not only improve children's psychological status, but also reduce suicide-related behaviors., (Copyright© by Editorial Board of Journal of Sichuan University (Medical Sciences).)

The main purpose of this paper is to explore the applicability of multivariate multilevel models for bioequivalence evaluation. Using an example of a 4 x 4 cross-over test design in evaluating bioequivalence of homemade and imported rosiglitazone maleate tablets, this paper illustrated the multivariate-model-based method for partitioning total variances of ln(AUC) and ln(C(max)) in the framework of multilevel models. It examined the feasibility of multivariate multilevel models in directly evaluating average bioequivalence (ABE), population bioequivalence (PBE) and individual bioequivalence (IBE). Taking into account the correlation between ln(AUC) and ln(C(max)) of rosiglitazone maleate tablets, the proposed models suggested no statistical difference between the two effect measures in their ABE bioequivalence via joint tests, whilst a contradictive conclusion was derived based on univariate multilevel models. Furthermore, the PBE and IBE for both ln(AUC) and ln(C(max)) of the two types of tablets were assessed with no statistical difference based on estimates of variance components from the proposed models. Multivariate multilevel models could be used to analyze bioequivalence of multiple effect measures simultaneously and they provided a new way of statistical analysis to evaluate bioequivalence.

This study aims to explore the application value of multilevel models for bioequivalence evaluation. Using a real example of 2 x 4 cross-over experimental design in evaluating bioequivalence of antihypertensive drug, this paper explores complex variance components corresponding to criteria statistics in existing methods recommended by FDA but obtained in multilevel models analysis. Results are compared with those from FDA standard Method of Moments, specifically on the feasibility and applicability of multilevel models in directly assessing the bioequivalence (ABE), the population bioequivalence (PBE) and the individual bioequivalence (IBE). When measuring ln (AUC), results from all variance components of the test and reference groups such as total variance (sigma(TT)(2) and sigma(TR)(2)), between-subject variance (sigma(BT)(2) and sigma(BR)(2)) and within-subject variance (sigma(WT)(2) and sigma(WR)(2)) estimated by simple 2-level models are very close to those that using the FDA Method of Moments. In practice, bioequivalence evaluation can be carried out directly by multilevel models, or by FDA criteria, based on variance components estimated from multilevel models. Both approaches produce consistent results. Multilevel models can be used to evaluate bioequivalence in cross-over test design. Compared to FDA methods, this one is more flexible in decomposing total variance into sub components in order to evaluate the ABE, PBE and IBE. Multilevel model provides a new way into the practice of bioequivalence evaluation.

Objective: To investigate the quality of life of heroin dependent patients with methadone maintenance therapy and its influencing factors., Methods: A total of 216 heroin dependent patients who were receiving methadone maintenance therapy in Zigong of Sichuan Province were surveyed with the WHOQOL-BREF., Results: The patients had a score of 12.06 +/- 3.73 for total quality of life and wellbeing and a score of, 13.14 +/- 2.79, 12.17 +/- 3.38, 12.20 +/- 3.17, 11.94 +/- 3.31, for physical, psychological, social relationships, and environmental function respectively. Age, length of drug addiction, job status, family relationship, arrested in last three months, frequency of sex activity, taking tranquilizer, confidence of treatment, duration of treatment, ways of using drugs had an impact on quality of life (P<0.05). Age, length of drug addiction, job status, family relationships, frequency of sex activity, arrested last three months, taking tranquilizer, and confidence of treatment entered into the multiple regression model., Conclusion: It is vital to take measures to improve quality of life of the drug addicted patients according to their different individual and family status.

Application of Rogerson Spatial Pattern Surveillance Method was discussed in real-time surveillance and early monitoring for infectious diseases. Theory of Rogerson Spatial Pattern Surveillance Method was introduced in detail. Data from the program on 'Monitoring epidemic cerebrospinal meningitis with Rogerson Spatial Pattern Surveillance Method' by the Chinese Center for Disease Control and Prevention provided evidence as how to choose crucial parameters such as K, H, n0 and tau, how to simulate surveillance process and how to interpret results. Rogerson Spatial Pattern Surveillance Method seemed to be able to continuously monitor the changes of infectious diseases. New cases could be added to this model at any moment and this model could provide early warning information in time when the excess of cases occurred. Simultaneously it could provide the time and site of the extra cases. Rogerson Spatial Pattern Surveillance Method could implement dynamic and real-time surveillance for infectious diseases. Simultaneously it could avoid the problem of multiple tests that causing large type I error. It greatly helped in providing reliable information for controlling infectious diseases in early epidemic period. Hence,it had important value of application in early warning on infectious diseases.

Objective: Application of Knox method was discussed in exploring temporal-spatial cluster for infectious diseases., Methods: The theory of Knox method was introduced in detail. As an example, the temporal-spatial cluster of epidemic cerebrospinal meningitis cases from April to May in 2005 was explored in Beijing and the statistical process of Knox method was clearly demonstrated with related results well interpreted., Results: Only when time and distance threshold values were set as 13 days and 29.67 km, potential temporal-spatial cluster could be detected in epidemic cerebrospinal meningitis cases., Conclusion: According to the characteristics of the epidemics, under Knox method, if appropriate threshold values of time and distance were chosen, information on temporal-spatial cluster of infectious diseases could be obtained. According to the records of different time and distance threshold values, the nature of an infectious disease might be explored. Thus Knox method could help us to strengthen the early warning system on infectious disease control strategy.