Decomposing the change in labour force indicators over time

In this paper we study changes in the size and the composition of the labour force in five OECD countries from 1983 through 2000. We apply a recent decomposition method to quantify the components of the change over time in the crude labour force rate and the mean age of the labour force. Our results show that the change in the crude labour force rate was dominated by the change in age-specific labour force participation rates. For the mean age of the labour force we find that for males the change in the age composition of the population predominately explains the overall change while the results for females are less clear-cut.decomposition method, labor force, labor force indicators, population aging

A comparison of Italians and resident foreigners

Objective: In this paper, we study the determinants of internal migration in Italy from 1995 to 2006. Methods: To conduct this investigation, we applied an augmented version of the gravity model to the migratory flows of Italians and resident foreigners. In addition to the classic deter-minants of migration—i.e., the sizes of populations and the distance between places—the model considered a possible autocorrelation of flows and a set of socio-economic and demographic explanatory variables that may influence migratory flows. Results: Different results were obtained for the two subpopulations. Among the Italians studied, both the economic conditions and the demographic features of regions were found to have operated as both push and pull determinants of migratory flows, although the demographic characteristics were shown to have affected migratory flows to a lesser extent. Among the resident foreigners studied, the demographic characteristics of the regions did not appear to have acted as push factors, but they were found to have had an effect as a pull determinant. While the economic conditions of the destination regions were shown to have been particularly important in attracting the resident foreigners, the economic conditions of the sending regions were not found to have had a clear-cut effect on the decision to leave

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice