The relationship between late-life depression, poverty, social network, and perceived health is little studied in Africa; the magnitude of the problem remains largely unknown and there is an urgent need to research into this area. We interviewed community dwelling elderly persons of two rural areas in Nigeria using Mini-Mental State Examination (MMSE) and Geriatric Depression Scale (GDS-30). Those who scored 11 and above on the GDS-30 were further interviewed using Geriatric Mental State Schedule (GMSS). Diagnosis of depression was based on the International Classification of Diseases 10th edition (ICD-10) and GMSS-Automated Geriatric Examination for Computer Assisted Taxonomy (GMMS-AGECAT). A total of 458 community dwelling elderly persons participated in the study of which 57% were females. Mean age of the participants was 73.65(7.8) years (95% CI 72.93-74.37). The mean GDS-30 and MMSE scores were 4.15(4.80) and 21.73(4.67), respectively. A total of 59 and 58 participants had depression based on ICD-10 criteria and GMSS-AGECAT, respectively. Agreement between ICD-10 and AGECAT diagnoses was κ = 0.931. By multiple logistic regression analysis, late-life depression was significantly associated with financial difficulties (Odds ratio 4.52 and bereavement Odds ratio 2.70). Late-life depression in this cohort is associated with health and socio-economic factors that are worth paying attention to, in a region of economic deprivation and inadequate healthcare.
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Discrete dynamical systems are used to model various realistic systems in network science, from social unrest in human populations to regulation in biological networks. A common approach is to model the agents of a system as vertices of a graph, and the pairwise interactions between agents as edges. Agents are in one of a finite set of states at each discrete time step and are assigned functions that describe how their states change based on neighborhood relations. Full characterization of state transitions of one system can give insights into fundamental behaviors of other dynamical systems. In this paper, we describe a discrete graph dynamical systems (GDSs) application called GDSCalc for computing and characterizing system dynamics. It is an open access system that is used through a web interface. We provide an overview of GDS theory. This theory is the basis of the web application; i.e., an understanding of GDS provides an understanding of the software features, while abstracting away implementation details. We present a set of illustrative examples to demonstrate its use in education and research. Finally, we compare GDSCalc with other discrete dynamical system software tools. Our perspective is that no single software tool will perform all computations that may be required by all users; tools typically have particular features that are more suitable for some tasks. We situate GDSCalc within this space of software tools. PMID:26263006
Discrete dynamical systems are used to model various realistic systems in network science, from social unrest in human populations to regulation in biological networks. A common approach is to model the agents of a system as vertices of a graph, and the pairwise interactions between agents as edges. Agents are in one of a finite set of states at each discrete time step and are assigned functions that describe how their states change based on neighborhood relations. Full characterization of state transitions of one system can give insights into fundamental behaviors of other dynamical systems. In this paper, we describe a discrete graph dynamical systems (GDSs) application called GDSCalc for computing and characterizing system dynamics. It is an open access system that is used through a web interface. We provide an overview of GDS theory. This theory is the basis of the web application; i.e., an understanding of GDS provides an understanding of the software features, while abstracting away implementation details. We present a set of illustrative examples to demonstrate its use in education and research. Finally, we compare GDSCalc with other discrete dynamical system software tools. Our perspective is that no single software tool will perform all computations that may be required by all users; tools typically have particular features that are more suitable for some tasks. We situate GDSCalc within this space of software tools. 2ff7e9595c
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