RESUMO
Objective: The present study examines the network structure and, using Bayesian network analysis, estimates the directional pathways among symptoms of posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and levels of alcohol and cannabis use. Method: A sample of 1471 adults in the United States, who reported at least one potentially traumatic event, completed the PTSD Checklist (PCL-5), Patient Health Questionnaire (PHQ-9), and the Alcohol/Cannabis Use Disorders Identification Test (AUDIT/CUDIT). A regularized partial correlation network provided estimates of symptoms clusters and connections. Directional pathways within the network were then estimated using a directed acyclic graph (DAG). Results: Symptoms clustered in theoretically consistent ways. Risky behavior demonstrated the highest strength centrality and bridge strength. Neither alcohol nor cannabis use appeared central in the network, and DAG results suggested that MDD and PTSD symptoms are more likely to lead to substance use than the other way around. Conclusions: Results suggest that cannabis use is largely connected to alcohol use. Consistent with prior research, risky behavior appeared to be the primary bridge between substance use and PTSD. The direction of associations between substance use and psychological symptoms requires further attention.
RESUMO
Overconsumption of energy-rich foods that disrupt caloric balance is a fundamental cause of overweight, obesity and diabetes. Dysglycemia and the resulting cardiovascular disease cause substantial morbidity and mortality worldwide, as well as high societal cost. The prevalence of obesity in childhood and adolescence is increasing, leading to younger diabetes diagnosis, and higher severity of microvascular and macrovascular complications. An important goal is to identify early life conditions that increase future metabolic risk, toward the goal of preventing diabetes and cardiovascular disease. An ample body of evidence implicates prenatal and postnatal childhood growth trajectories in the programming of adult metabolic disease. Human epidemiological data show that accelerated childhood growth increases risk of type 2 diabetes in adulthood. Type 2 diabetes results from the combination of insulin resistance and pancreatic ß-cell failure, but specific mechanisms by which accelerated postnatal growth impact one or both of these processes remain uncertain. This review explores the metabolic impact of overnutrition during postnatal life in humans and in rodent models, with specific attention to the connection between accelerated childhood growth and future adiposity, insulin resistance, ß-cell mass and ß-cell dysfunction. With improved knowledge in this area, we might one day be able to modulate nutrition and growth in the critical postnatal window to maximize lifelong metabolic health.