Dataset Information

Longitudinal associations between post-traumatic stress disorder and metabolic syndrome severity.

ABSTRACT: BACKGROUND:Post-traumatic stress disorder (PTSD) is associated with elevated risk for metabolic syndrome (MetS). However, the direction of this association is not yet established, as most prior studies employed cross-sectional designs. The primary goal of this study was to evaluate bidirectional associations between PTSD and MetS using a longitudinal design. METHOD:A total of 1355 male and female veterans of the conflicts in Iraq and Afghanistan underwent PTSD diagnostic assessments and their biometric profiles pertaining to MetS were extracted from the electronic medical record at two time points (spanning ~2.5 years, n = 971 at time 2). RESULTS:The prevalence of MetS among veterans with PTSD was just under 40% at both time points and was significantly greater than that for veterans without PTSD; the prevalence of MetS among those with PTSD was also elevated relative to age-matched population estimates. Cross-lagged panel models revealed that PTSD severity predicted subsequent increases in MetS severity (? = 0.08, p = 0.002), after controlling for initial MetS severity, but MetS did not predict later PTSD symptoms. Logistic regression results suggested that for every 10 PTSD symptoms endorsed at time 1, the odds of a subsequent MetS diagnosis increased by 56%. CONCLUSIONS:Results highlight the substantial cardiometabolic concerns of young veterans with PTSD and raise the possibility that PTSD may predispose individuals to accelerated aging, in part, manifested clinically as MetS. This demonstrates the need to identify those with PTSD at greatest risk for MetS and to develop interventions that improve both conditions.

SUBMITTER: Wolf EJ

PROVIDER: S-EPMC4925183 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Longitudinal associations between post-traumatic stress disorder and metabolic syndrome severity.

Wolf E J EJ Bovin M J MJ Green J D JD Mitchell K S KS Stoop T B TB Barretto K M KM Jackson C E CE Lee L O LO Fang S C SC Trachtenberg F F Rosen R C RC Keane T M TM Marx B P BP

Psychological medicine 20160418 10

<h4>Background</h4>Post-traumatic stress disorder (PTSD) is associated with elevated risk for metabolic syndrome (MetS). However, the direction of this association is not yet established, as most prior studies employed cross-sectional designs. The primary goal of this study was to evaluate bidirectional associations between PTSD and MetS using a longitudinal design.<h4>Method</h4>A total of 1355 male and female veterans of the conflicts in Iraq and Afghanistan underwent PTSD diagnostic assessmen ...[more]

PMID: 27087657

Similar Datasets

Project description:AimsPrevious studies have reported inconsistent findings regarding the association between post-traumatic stress (PTS) and post-traumatic growth (PTG). Three major issues could account for this inconsistency: (1) the lack of information about mental health problems before the disaster, (2) the concept of PTG is still under scrutiny for potentially being an illusionary perception of personal growth and (3) the overlooking of PTS comorbidities as time-dependent confounding factors. To address these issues, we explored the associations of PTS and PTG with trauma-related diseases and examined the association between PTS and PTG using marginal structural models to address time-dependent confounding, considering pre-disaster covariates, among older survivors of the 2011 Japan Earthquake and Tsunami.MethodsSeven months before the disaster, the baseline survey was implemented to ask older adults about their health in a city located 80 km west of the epicentre. After the disaster, we implemented follow-up surveys approximately every 3 years to collect information about PTS and comorbidities (depressive symptoms, smoking and drinking). We asked respondents about their PTG in the 2022 survey (n = 1,489 in the five-wave panel data).ResultsPTG was protectively associated with functional disability (coefficient -0.47, 95% confidence interval (CI) -0.82, -0.12, P < 0.01) and cognitive decline assessed by trained investigators (coefficient -0.07, 95% CI -0.11, -0.03, P < 0.01) and physicians (coefficient -0.06, 95% CI -0.11, -0.02, P < 0.01), while PTS was not significantly associated with them. Severely affected PTS (binary variable) was associated with higher PTG scores, even after adjusting for depressive symptoms, smoking and drinking as time-dependent confounders (coefficient 0.35, 95% CI 0.24, 0.46, P < 0.01). We also found that an ordinal variable of the PTS score had an inverse U-shaped association with PTG.ConclusionPTG and PTS were differentially associated with functional and cognitive disabilities. Thus, PTG might not simply be a cognitive bias among survivors with severe PTS. The results also indicated that the number of symptoms in PTS had an inverse U-shaped association with PTG. Our findings provided robust support for the theory of PTG, suggesting that moderate levels of psychological struggles (i.e., PTS) are essential for achieving PTG, whereas intense PTS may hinder the attainment of PTG. From a clinical perspective, interventions that encourage social support could be beneficial in achieving PTG by facilitating deliberate rumination.

Project description:Contemporary symptom-based diagnosis of post-traumatic stress disorder (PTSD) largely overlooks related neurobehavioral mechanisms and relies entirely on subjective interpersonal reporting. Previous studies associating biomarkers with PTSD have mostly used symptom-based diagnosis as the main outcome measure, disregarding the wide variability and richness of PTSD phenotypical features. Here, we aimed to computationally derive potential biomarkers that could efficiently differentiate PTSD subtypes among recent trauma survivors. A three-staged semi-unsupervised method ("3C") was used to firstly categorize individuals by current PTSD symptom severity, then derive clusters based on clinical features related to PTSD (e.g. anxiety and depression), and finally to classify participants' cluster membership using objective multi-domain features. A total of 256 features were extracted from psychometrics, cognitive functioning, and both structural and functional MRI data, obtained from 101 adult civilians (age = 34.80 ± 11.95; 51 females) evaluated within 1 month of trauma exposure. The features that best differentiated cluster membership were assessed by importance analysis, classification tree, and ANOVA. Results revealed that entorhinal and rostral anterior cingulate cortices volumes (structural MRI domain), in-task amygdala's functional connectivity with the insula and thalamus (functional MRI domain), executive function and cognitive flexibility (cognitive testing domain) best differentiated between two clusters associated with PTSD severity. Cross-validation established the results' robustness and consistency within this sample. The neural and cognitive potential biomarkers revealed by the 3C analytics offer objective classifiers of post-traumatic morbidity shortly following trauma. They also map onto previously documented neurobehavioral mechanisms associated with PTSD and demonstrate the usefulness of standardized and objective measurements as differentiating clinical sub-classes shortly after trauma.

Dataset Information

Longitudinal associations between post-traumatic stress disorder and metabolic syndrome severity.

Publications

Longitudinal associations between post-traumatic stress disorder and metabolic syndrome severity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets