Objective: To estimate the occurrence and to assess the determinants of posttraumatic stress disorder (PTSD) in flood victims. Method:We carried out a retrospective study to examine the occurrence and the determinants of PTSD in victims of flood in 1998 and 1999 in Hunan, China. We used multistage sampling to select the subjects from the flood areas, and we ascertained PTSD according to DSM-IV criteria. Data were collected in face-to-face interviews carried out by experienced research assistants using a preconstructed questionnaire. We used a multiple logistic regression model to analyze the data.Results: A total of 33 340 subjects (86.0% of the selected subjects, aged 7 years or over) in the study villages were interviewed. Among them, 2875 (8.6%) had symptoms that met the diagnostic criteria for PTSD. Conclusions: PTSD is a common mental disorder in flood victims, which implies the need for improved health services, especially mental health services, for this population. (Can J Psychiatry 2006;51:350-354) Information on funding and support and author affiliations appears at the end of the article. Clinical Implications· PTSD is common in flood-affected populations. · It is important to provide psychological support, in addition to physical support, for flood-affected populations. · Particular attention should be paid to female victims and senior victims in the flood-affected areas. Limitations· The study findings were based on observations in a Chinese population in Hunan province; they may not be applicable to other populations. · The severity and type of flood were arbitrarily defined and may not necessarily reflect the nature of the flood. · We were not able to study modifiable PTSD risk factors (for example, lack of family or social support).
BackgroundPost-traumatic stress disorder (PTSD) is one of the most prevalent long-term psychiatric disorders among survivors of traumatic events. It is well established that social support has been related to the onset of PTSD after natural disasters. However, very little is known whether or not social support has had an influence on the recovery from the PTSD that was diagnosed after floods. This study, therefore, made a follow-up assessment of PTSD in flood victims 13–14 years after they were diagnosed with PTSD in 2000 to measure the prevalence rate of PTSD among them and identify the association between social support and their recovery from PTSD.MethodsVictims who had experienced Dongting Lake flood in 1998 and had been diagnosed as having PTSD in 2000 were enrolled in this study. A follow-up survey was done between the years 2013 and 2014 to diagnose the victims again of PTSD using the DSM-IV criteria. Social support and its three dimensions were measured using the Chinese version of Social Support Rating Scale (SSRS), including objective support, subjective support and support utilization. Data were collected through face-to-face interviews using a structured questionnaire. Bivariate and multivariate logistic regression analyses were used to examine the relationship between social support and the recovery from PTSD after flood.ResultsOut of 321 subjects with prior PTSD, 51 (15.89 %) were diagnosed as still having PTSD. Logistic regression analyses indicated that the recovery from prior PTSD was significantly associated with social support (odds ratio (OR) =0.202, 95 % confidence interval (95 % CI): 0.047–0.878), subjective support (OR = 0.236, 95 % CI: 0.080–0.694) and support utilization (OR = 0.245, 95 % CI: 0.071–0.844).ConclusionsThe prevalence rate of current PTSD indicates that natural disasters, such as floods, may affect the mental health of victims for a long time. Social support was significantly associated with the recovery from prior PTSD, especially subjective support and support utilization.
Background: Dysbiosis of human gut microbiota is associated with a wide range of metabolic disorders, including gestational diabetes mellitus (GDM). Yet whether gut microbiota dysbiosis participates in the etiology of GDM remains largely unknown.Objectives: Our study was initiated to determine whether the alternations in gut microbial composition during early pregnancy linked to the later development of GDM, and explore the feasibility of microbial biomarkers for the early prediction of GDM. Study design:This nested case-control study was based upon an early pregnancy follow-up cohort (ChiCTR1900020652). Gut microbiota profiles of 98 subjects with GDM and 98 matched healthy controls during the early pregnancy (10-15 weeks) were assessed via 16S rRNA gene amplicon sequencing of V4 region. The data set was randomly split into a discovery set and a validation set, the former was used to analyze the differences between GDM cases and controls in gut microbial composition and functional annotation, and to establish an early identification model of GDM, then the performance of the model was verified by the external validation set.Results: Bioinformatic analyses revealed changes to gut microbial composition with significant differences in relative abundance between the groups. Specifically, Eisenbergiella, Tyzzerella 4, and Lachnospiraceae NK4A136 were enriched in the GDM group, whereas Parabacteroides, Megasphaera, Eubacterium eligens group, etc. remained dominant in the controls. Correlation analysis revealed that GDM-enriched genera Eisenbergiella and Tyzzerella 4 were positively correlated with fasting blood glucose levels, while three control-enriched genera (Parabacteroides, Parasutterella, and Ruminococcaceae UCG 002) were the opposite. Further, GDM functional annotation modules revealed enrichment of modules for sphingolipid metabolism, starch and sucrose metabolism, etc., while lysine biosynthesis and nitrogen metabolism were reduced. Finally, five genera and two clinical indices were included in the linear discriminant analysis model for the prediction of GDM; the areas under receiver operating characteristic curves of the training and validation sets were 0.736 (95% confidence interval: 0.663-0.808) and 0.696 (0.575-0.818), respectively. Ma et al. Gut Bacterial Dysbiosis Before GDMConclusions: Gut bacterial dysbiosis in early pregnancy was found to be associated with the later development of GDM, and gut microbiota-targeted biomarkers might be utilized as potential predictors of GDM.
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