Hypertension Briefing

Blood pressure is the force exerted on artery walls as the heart pumps blood through the body. Hypertension, or high blood pressure, occurs when blood pressure is constantly higher than the pressure needed to carry blood through the body. The Chronic Conditions Hub is a website that brings together information on chronic health conditions. It allows you to easily access, manage and share relevant information resources. The Chronic Conditions Hub includes the Institute of Public Health in Ireland’s (IPH) estimates and forecasts of the number of people living with chronic conditions. On the Chronic Conditions Hub you will find:- A Briefing for each condition - Detailed technical documentation - Detailed national and sub-national data that can be downloaded or explored using online data tools - A prevalence tool that allows you to calculate prevalence figures for your population data

Musculoskeletal Conditions Briefing: Technical Documentation

Musculoskeletal conditions (MSCs) are a group of diseases that affect the body’s bones, joints, muscles and the tissues that connect them. Common MSCs include back pain, rheumatoid arthritis, osteoarthritis, osteoporosis, and spinal disorders. MSCs are the most common cause of severe long term pain and physical disability in developed countries. They significantly affect the psychosocial wellbeing of individuals as well as their families and carers. They are responsible for substantial costs to the health and social care system and the economy. They are a leading cause of absence from work and lost productivity at work. MSCs comprise a diverse group of conditions. Some have a specific medical diagnosis (eg rheumatoid arthritis) but others have no clear medical diagnosis (eg back pain). Risk factors for the development and progression of MSCs include age, sex, family history, obesity, physical inactivity, injury and biomechanical occupational health issues. This document details the methods used to calculate the estimates and forecasts.

Stroke Briefing

The Chronic Conditions Hub is a website that brings together information on chronic health conditions. It allows you to easily access, manage and share relevant information resources. The Chronic Conditions Hub includes the Institute of Public Health in Ireland’s (IPH) estimates and forecasts of the number of people living with chronic conditions. On the Chronic Conditions Hub you will find: - A Briefing for each condition - Detailed technical documentation - Detailed national and sub-national data that can be downloaded or explored using online data tools - A prevalence tool that allows you to calculate prevalence figures for your population data A stroke happens when blood flow to a part of the brain is interrupted by a blocked or burst blood vessel. A lack of blood supply can damage brain cells and affect body functions. IPH has systematically estimated and forecast the prevalence of stroke on the island of Ireland.   Epidemiology Age, family history, diabetes, high blood pressure, high cholesterol, smoking, unhealthy diet, physical inactivity and alcohol are the main risk factors for stroke. The World Health Organization estimates that stroke and cerebrovascular disease is responsible for 10% of all world deaths and is the second most common cause of death worldwide. Cerebrovascular diseases (ICD 10 codes I60-I69) were responsible for 7.2% of all deaths in the Republic of Ireland in 2009 and for 8.6% of all deaths in Northern Ireland in 2010.

Stroke Briefing: Technical Documentation

A stroke happens when blood flow to a part of the brain is interrupted by a blocked or burst blood vessel. A lack of blood supply can damage brain cells and affect body functions. IPH has systematically estimated and forecast the prevalence of stroke on the island of Ireland. This document details the methods used to calculate these estimates and forecasts. Technical documentation      

Comparison of IPH prevalence estimates with other survey-based estimates

The Institute of Public Health in Ireland publishes estimates and forecasts of the prevalence of chronic health conditions for national and subnational areas on the island of Ireland. The estimates and forecasts are based on statistical models of nationally representative health survey data that estimate the risk of having the condition. The risks of having the condition are then applied to population estimates and projections. The purpose of this document is to: 1. Compare IPH prevalence estimates with prevalence estimates from other health surveys on the island. 2. Highlight the methodological issues in comparing prevalence estimates from different surveys.

Longstanding health conditions among three-year-old children in the Republic of Ireland in 2011

Access audio, video and slides from the launch of the report The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to longstanding health conditions among young children across the island of Ireland. This report, based on a systematic analysis of data from the Growing Up in Ireland National Longitudinal Study of Children in the Republic of Ireland, is the first comprehensive look at longstanding health conditions among young children in Ireland. Estimated prevalence (per cent and number of cases) of longstanding health conditions among three-year-olds in the Republic of Ireland in 2011 by administrative counties/cities. The conditions are carer-reported: - "Longstanding illness, condition or disability” (where longstanding was defined as “anything that has troubled him/her over a period of time or that is likely to affect him/her over a period of time”) - Diagnosed asthma or asthma symptoms - Diagnosed eczema/any kind of skin allergy - Sight problem that required correction - Hearing problem that required correction - The estimates are based on data from the Growing Up in Ireland National Longitudinal Study of Children (www.growingup.ie) and population data. See the Chronic Conditions Hub for more details.  

Longstanding health conditions among three-year-old children in the Republic of Ireland in 2011: Executive Summary

Access audio, video and slides from the launch of the report The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to longstanding health conditions among young children across the island of Ireland. This report, based on a systematic analysis of data from the Growing Up in Ireland National Longitudinal Study of Children in the Republic of Ireland, is the first comprehensive look at longstanding health conditions among young children in Ireland. Estimated prevalence (per cent and number of cases) of longstanding health conditions among three-year-olds in the Republic of Ireland in 2011 by administrative counties/cities. The conditions are carer-reported: - "Longstanding illness, condition or disability” (where longstanding was defined as “anything that has troubled him/her over a period of time or that is likely to affect him/her over a period of time”) - Diagnosed asthma or asthma symptoms - Diagnosed eczema/any kind of skin allergy - Sight problem that required correction - Hearing problem that required correction - The estimates are based on data from the Growing Up in Ireland National Longitudinal Study of Children (www.growingup.ie) and population data. See the Chronic Conditions Hub for more details.    

Longstanding health conditions among three-year-old children in the Republic of Ireland in 2011: Factsheet

Access audio, video and slides from the launch of the report The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to longstanding health conditions among young children across the island of Ireland. This report, based on a systematic analysis of data from the Growing Up in Ireland National Longitudinal Study of Children in the Republic of Ireland, is the first comprehensive look at longstanding health conditions among young children in Ireland. Estimated prevalence (per cent and number of cases) of longstanding health conditions among three-year-olds in the Republic of Ireland in 2011 by administrative counties/cities. The conditions are carer-reported: - "Longstanding illness, condition or disability” (where longstanding was defined as “anything that has troubled him/her over a period of time or that is likely to affect him/her over a period of time”) - Diagnosed asthma or asthma symptoms - Diagnosed eczema/any kind of skin allergy - Sight problem that required correction - Hearing problem that required correction - The estimates are based on data from the Growing Up in Ireland National Longitudinal Study of Children (www.growingup.ie) and population data. See the Chronic Conditions Hub for more details.    

Seguiment de l'evolució de la recuperació del bosc de ribera en la zona afectada per l'incendi del riu Canaletes del 20/07/2009. Proposta de campanya de voluntariat ambiental en rius per la custòdia i recuperació fluvial

El riu Canaletes va resultar afectat per l’ incendi que es va produir a Horta de Sant Joan el juliol de l’any 2009. El foc va malmetre bona part de la flora i fauna de la zona, però un dels ecosistemes que en va sortir més perjudicat va ser el del bosc de ribera, ecosistema molt fràgil en front de pertorbacions d’aquest tipus, ja que la seva capacitat de regeneració no és tant senzilla ni ràpida com en altres ecosistemes mediterranis com podrien ser els boscos de pi blanc. No obstant, si que existeixen algunes espècies de ribera que presenten una ràpida resposta als incendis com és el cas dels salzes o alguns pollancres o àlbers, que en aquest cas, poc temps després del foc ja presentaven rebrots, segons observacions realitzades al camp. Per comprovar l’evolució de la recuperació del bosc de ribera en la zona afectada per l’incendi, es van realitzar diverses sortides de camp. D’aquestes observacions, es va poder deduir que actualment el bosc de ribera de la zona estudiada, evoluciona segons les previsions realitzades en estudis immediatament posteriors al foc, de manera que hi estan proliferant de manera ràpida bardisses amb esbarzer, gavarrera, roldor i sanguinyol, en aquells llocs que abans de l’incendi eren ocupats per arbres caducifolis.

Prevalence of injuries among three-year-old children in the Republic of Ireland in 2011

The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to examine health conditions and injuries among young children across the island of Ireland.This short report is a supplement to a previous IPH report that examines health conditions among three-year-olds in the Republic of Ireland. It provides estimates of the prevalence of injuries that required hospital admission or treatment among three-year-olds in the Republic of Ireland in 2011. The analysis identifies risk factors associated with child injuries and provides estimates of the prevalence of these conditions for each of the 34 administrative cities and counties.

Carer-reported health conditions among seven-year-old children in Northern Ireland in 2011: A report based on data from the Millennium Cohort Study

The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to examine health conditions among young children across the island of Ireland.This report uses information collected from parents in the Millennium Cohort Study (MCS) along with population data collected in the 2011 Northern Ireland Census to estimate the prevalence of any longstanding condition, asthma, eczema, sight problems and hearing problems among seven-year-olds in Northern Ireland in 2011. The analysis identifies risk factors associated with each condition and provides estimates of the prevalence of these conditions for each of the 11 Local Government Districts.A report on health conditions among three-year-olds in the Republic of Ireland has previously been published by the IPH.See the Chronic Conditions Hub for more details.

Apprenticeship Review - Background Issues Paper

The Government’s Action Plan for Jobs contained the following commitment regarding a review of apprenticeship: “Initiate a review of the apprenticeship training model, including costs, duration and demand with a view to providing an updated model of training that delivers the necessary skilled workforce to service the needs of a rapidly changing economy and ensures appropriate balance between supply and demand.” The first stage of the review process involves the preparation of this background issues paper which, inter alia, provides a factual description of the current system of apprenticeship, including the governance arrangements, trends and forecasts in relation to recruitment and identified strengths and weaknesses of the model and proposes a range of possible options for change.

Coherent forecasting of multiple-decrement life tables: a test using Japanese cause of death data

Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult toachieve because the relative values of the forecast components often fail to behave ina way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It hasbeen shown that cause-specic mortality forecasts are pessimistic when compared withall-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approachof using log mortality rates and forecasts the density of deaths in the life table. Sincethese values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbingstate), they are intrinsically relative rather than absolute values across decrements aswell as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison(1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that theunit sum constraint is honoured. The structure of the best-known, single-decrementmortality-rate forecasting model, devised by Lee and Carter (1992), is expressed incompositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortalityby cause of death for Japan

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.