Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta‐analysis

OBJECTIVES: A previous individual participant data meta-analysis (IPDMA) identified differences in major depression classification rates between different diagnostic interviews, controlling for depressive symptoms on the basis of the Patient Health Questionnaire-9. We aimed to determine whether similar results would be seen in a different population, using studies that administered the Edinburgh Postnatal Depression Scale (EPDS) in pregnancy or postpartum. METHODS: Data accrued for an EPDS diagnostic accuracy IPDMA were analysed. Binomial generalised linear mixed models were fit to compare depression classification odds for the Mini International Neuropsychiatric Interview (MINI), Composite International Diagnostic Interview (CIDI), and Structured Clinical Interview for DSM (SCID), controlling for EPDS scores and participant characteristics. RESULTS: Among fully structured interviews, the MINI (15 studies, 2,532 participants, 342 major depression cases) classified depression more often than the CIDI (3 studies, 2,948 participants, 194 major depression cases; adjusted odds ratio [aOR] = 3.72, 95% confidence interval [CI] [1.21, 11.43]). Compared with the semistructured SCID (28 studies, 7,403 participants, 1,027 major depression cases), odds with the CIDI (interaction aOR = 0.88, 95% CI [0.85, 0.92]) and MINI (interaction aOR = 0.95, 95% CI [0.92, 0.99]) increased less as EPDS scores increased. CONCLUSION: Different interviews may not classify major depression equivalently

Post-disaster Recovery in Industrial Sectors: A Markov Process Analysis of Multiple Lifeline Disruptions

Lifeline disruptions can represent a serious economic threat at various scales. However, firm-level empirical evidence regarding the consequences and reliability of lifeline services, and how lifeline service disruptions impact on economic losses after disasters, is still lacking. This study applies a temporal, non-homogeneous, Markov process approach that explicitly considers multiple lifeline service disruptions. This approach is used to quantitatively estimate the impacts of multiple lifeline disruptions on business production capacity losses. The model is illustrated based on the 2011 Great East Japan Earthquake case study with detailed information obtained from individual business recovery data. The result indicates that the restoration of lifeline systems during disruptions should consider each business service given that it significantly affects business production capacity recovery. For example, the case study results indicate that if electrical power, water and gas are disrupted, restoration of electrical power supply yields the highest influence on production capacity improvement, amounting to 15% per day on average, compared with 10% per day for gas restorations, and 8% per day for water restoration. The proposed model can provide information to business managers and policymakers on the optimum recovery strategy and on how to mitigate economic losses in disruption event cases

Analysis of the industrial solid wastes from the boat building sector in Marche region (Italy): parametrical and chemical-physical characterisation

This paper deals with a qualitative and quantitative analysis of the particular industrial solid wastes generated from the renowned manufacturing sector of motor and sailing pleasure-crafts in Marche Region (Central Italy, Adriatic Sea side). Three case-study boat-builder companies, located in the Marche regional district and selected for their representative production in glass-fibre or carbon fibre reinforced composite materials, were examined. Specific waste production coefficient values per employee were derived on a four-year temporal range (2006-2009) and also two original waste production coefficients (per boat-area unit and per boat-weight unit) were proposed. Furthermore, a chemical-physical characterisation was carried out for two representative composite waste typologies of the boat manufacturing sector, namely a carbon-fibre reinforced plastic residue and a glass-fibre reinforced plastic residue