Prevalence of chronic conditions – Diabetes

IPH has estimated and forecast clinical diagnosis rates of diabetes among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007. The data describe the number of people who report that they have experienced doctor-diagnosed diabetes in the previous 12 months (annual clinical diagnosis).  Data are available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. Note that an adjustment was made for diabetes medication use recorded in the SLÁN physical examination sub-group of 45+ year olds. In Northern Ireland, the data is based on the Health and Social Wellbeing Survey 2005/06 . The data describe the number of people who report that they have experienced doctor-diagnosed diabetes at any time in the past (lifetime clinical diagnosis). Data are available by age and sex for each Local Government District in Northern Ireland.Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past. Differences between IPH estimates and reference study estimates: The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.  

Prevalence of chronic conditions – Hypertension

IPH has estimated and forecast clinical diagnosis rates of hypertension among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007. The data describe the number of people who report that they have experienced doctor-diagnosed hypertension in the previous 12 months (annual clinical diagnosis). Data are available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data is based on the Health and Social Wellbeing Survey 2005/06. The data describe the number of people who report that they have experienced doctor/nurse-diagnosed hypertension at any time in the past (lifetime clinical diagnosis). Data are available by age and sex for each Local Government District in Northern Ireland. Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past.   The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Prevalence of chronic conditions – Coronary Heart Disease

IPH has estimated and forecast clinical diagnosis rates of CHD (heart attack and/or angina) among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007 . The data describe the number of people who report that they have experienced doctor-diagnosed heart attack and/or angina in the previous 12 months (annual clinical diagnosis). Data is available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data are based on the Health and Social Wellbeing Survey 2005/06 . The data describe the number of people who report that they have experienced doctor-diagnosed heart attack and/or angina at any time in the past (lifetime clinical diagnosis). Data are available by age and sex for each Local Government District in Northern Ireland. Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past. The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Prevalence of chronic conditions – Chronic Airflow Obstruction

IPH has estimated and forecast clinical diagnosis rates of CAO among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007. The data describe the number of people who report that they have experienced doctor-diagnosed chronic bronchitis, chronic obstructive lung (pulmonary) disease, or emphysema in the previous 12 months (annual clinical diagnosis). Data is available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data are based on the Health and Social Wellbeing Survey 2005/06. The data describe the number of people who report that they have experienced doctor-diagnosed COPD or chronic obstructive pulmonary disease eg chronic bronchitis / emphysema or both disorders at any time in the past (lifetime clinical diagnosis). Data are available by age and sex for each Local Government District in Northern Ireland. Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past.   The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Prevalence of chronic conditions – Musculoskeletal Conditions

IPH has estimated and forecast the number of adults with MSCs for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007 . The data describe the number of people who report that they have experienced doctor-diagnosed MSC in the previous 12 months:     Lower back pain or any other chronic back condition     Rheumatoid arthritis (inflammation of the joints)     Osteoarthritis (arthrosis, joint degradation) Data are  available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data are based on the Health and Social Wellbeing Survey 2005/06 and Understanding Society 2009. The data describe the number of adults who:     Have ever consulted a doctor about back pain     Are currently receiving treatment for musculoskeletal problems (such as arthritis, rheumatism)     Have ever been told by a doctor or other health professional that they had have arthritis? Data are available by age and sex for each Local Government District in Northern Ireland. There are significant differences between the definitions used in RoI and NI and North-South comparisons are not valid. The RoI measures relate to specific MSCs in the previous 12 months that had been diagnosed by a doctor. The NI measures relate to doctor-consultations at any time in the past, doctor-diagnosis at any time in the past and current treatment. The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Multiple imputations applied to the DREAM3 phosphoproteomics challenge: a winning strategy.

DREAM is an initiative that allows researchers to assess how well their methods or approaches can describe and predict networks of interacting molecules [1]. Each year, recently acquired datasets are released to predictors ahead of publication. Researchers typically have about three months to predict the masked data or network of interactions, using any predictive method. Predictions are assessed prior to an annual conference where the best predictions are unveiled and discussed. Here we present the strategy we used to make a winning prediction for the DREAM3 phosphoproteomics challenge. We used Amelia II, a multiple imputation software method developed by Gary King, James Honaker and Matthew Blackwell[2] in the context of social sciences to predict the 476 out of 4624 measurements that had been masked for the challenge. To chose the best possible multiple imputation parameters to apply for the challenge, we evaluated how transforming the data and varying the imputation parameters affected the ability to predict additionally masked data. We discuss the accuracy of our findings and show that multiple imputations applied to this dataset is a powerful method to accurately estimate the missing data. We postulate that multiple imputations methods might become an integral part of experimental design as a mean to achieve cost savings in experimental design or to increase the quantity of samples that could be handled for a given cost.

Challenges of phylogenetic analyses of aDNA sequences

One of the crucial steps of authentication of aDNA sequences is phylogenetic consistency. Amplified sequences should fit into the phylogenetic framework of their supposed origin. An inherent property of aDNA sequences however, is their short sequence length. Additionally, genes for aDNA studies are often chosen by their preservation potential rather than by phylogenetically informative content. This poses potential challenges regarding their analyses, and might result in an inaccurate reflection of the supposed phylogenetic history of the sequence or organism under study. In this paper some fundamental problems of phylogenetic analysis and interpretation of aDNA datasets are discussed. Suggestions for character sampling and treatment of missing data are made. The publication is the result of a talk from the 1st PAMINSA Meeting in Rio de Janeiro, July 2005.

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basicfunctionality has seen some conceptual improvement, containing now some facilitiesto work with and represent ilr bases built from balances, and an elaborated subsys-tem for dealing with several kinds of irregular data: (rounded or structural) zeroes,incomplete observations and outliers. The general approach to these irregularities isbased on subcompositions: for an irregular datum, one can distinguish a “regular” sub-composition (where all parts are actually observed and the datum behaves typically)and a “problematic” subcomposition (with those unobserved, zero or rounded parts, orelse where the datum shows an erratic or atypical behaviour). Systematic classificationschemes are proposed for both outliers and missing values (including zeros) focusing onthe nature of irregularities in the datum subcomposition(s).To compute statistics with values missing at random and structural zeros, a projectionapproach is implemented: a given datum contributes to the estimation of the desiredparameters only on the subcompositon where it was observed. For data sets withvalues below the detection limit, two different approaches are provided: the well-knownimputation technique, and also the projection approach.To compute statistics in the presence of outliers, robust statistics are adapted to thecharacteristics of compositional data, based on the minimum covariance determinantapproach. The outlier classification is based on four different models of outlier occur-rence and Monte-Carlo-based tests for their characterization. Furthermore the packageprovides special plots helping to understand the nature of outliers in the dataset.Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator,robustness, rounded zeros

Rate and predictors of service disengagement in an epidemiological first-episode psychosis cohort.

OBJECTIVES: To assess the prevalence and predictors of service disengagement in a treated epidemiological cohort of first-episode psychosis (FEP) patients. METHODS: The Early Psychosis Prevention and Intervention Centre (EPPIC) in Australia admitted 786 FEP patients from January 1998 to December 2000. Treatment at EPPIC is scheduled for 18 months. Data were collected from patients' files using a standardized questionnaire. Seven hundred four files were available; 44 were excluded, because of a non-psychotic diagnosis at endpoint (n=43) or missing data on service disengagement (n=1). Rate of service disengagement was the outcome of interest, as well as pre-treatment, baseline, and treatment predictors of service disengagement, which were examined via Cox proportional hazards models. RESULTS: 154 patients (23.3%) disengaged from service. A past forensic history (Hazard ratio [HR]=1.69; 95%CI 1.17-2.45), lower severity of illness at baseline (HR=0.59; 95%CI 0.48-0.72), living without family at discharge (HR=1.75; 95%CI 1.22-2.50) and persistence of substance use disorder during treatment (HR=2.30; 95%CI 1.45-3.66) were significant predictors of disengagement from service. CONCLUSIONS: While engagement strategies are a core element in the treatment of first-episode psychosis, particular attention should be paid to these factors associated with disengagement. Involvement of the family in the treatment process, and focusing on reduction of substance use, need to be pursued in early intervention services.

Application of the european customer satisfaction index to postal services. Structural equation models versus partial least squars

Customer satisfaction and retention are key issues for organizations in today’s competitive market place. As such, much research and revenue has been invested in developing accurate ways of assessing consumer satisfaction at both the macro (national) and micro (organizational) level, facilitating comparisons in performance both within and between industries. Since the instigation of the national customer satisfaction indices (CSI), partial least squares (PLS) has been used to estimate the CSI models in preference to structural equation models (SEM) because they do not rely on strict assumptions about the data. However, this choice was based upon some misconceptions about the use of SEM’s and does not take into consideration more recent advances in SEM, including estimation methods that are robust to non-normality and missing data. In this paper, both SEM and PLS approaches were compared by evaluating perceptions of the Isle of Man Post Office Products and Customer service using a CSI format. The new robust SEM procedures were found to be advantageous over PLS. Product quality was found to be the only driver of customer satisfaction, while image and satisfaction were the only predictors of loyalty, thus arguing for the specificity of postal services

Performance assessment and league tables. Comparing like with like.

We formulate performance assessment as a problem of causal analysis and outline an approach based on the missing data principle for its solution. It is particularly relevant in the context of so-called league tables for educational, health-care and other public-service institutions. The proposed solution avoids comparisons of institutions that have substantially different clientele (intake).

Canonical correspondence analysis in social science research

The use of simple and multiple correspondence analysis is well-established in socialscience research for understanding relationships between two or more categorical variables.By contrast, canonical correspondence analysis, which is a correspondence analysis with linearrestrictions on the solution, has become one of the most popular multivariate techniques inecological research. Multivariate ecological data typically consist of frequencies of observedspecies across a set of sampling locations, as well as a set of observed environmental variablesat the same locations. In this context the principal dimensions of the biological variables aresought in a space that is constrained to be related to the environmental variables. Thisrestricted form of correspondence analysis has many uses in social science research as well,as is demonstrated in this paper. We first illustrate the result that canonical correspondenceanalysis of an indicator matrix, restricted to be related an external categorical variable, reducesto a simple correspondence analysis of a set of concatenated (or stacked ) tables. Then weshow how canonical correspondence analysis can be used to focus on, or partial out, aparticular set of response categories in sample survey data. For example, the method can beused to partial out the influence of missing responses, which usually dominate the results of amultiple correspondence analysis.

Performance assessment and league tables. Comparing like with like

We formulate performance assessment as a problem of causal analysis and outline an approach based on the missing data principle for its solution. It is particularly relevant in the context of so-called league tables for educational, health-care and other public-service institutions. The proposed solution avoids comparisons of institutions that have substantially different clientele (intake).

Failure of the surgical treatment in 115 infected hip arthroplasties-­analysis of a 12-­year prosthetic joint cohort study (1999-­2010)

Background:¦Infection after total or partial hip arthroplasty (HA) leads to significant long-­term morbidity and high healthcare cost. We evaluated reasons for treatment failure of different surgical modalities in a 12-­year prosthetic hip joint infection cohort study.¦Method:¦All patients hospitalized at our institution with infected HA were included either retrospectively (1999-­‐2007) or prospectively¦(2008-­‐2010). HA infection was defined as growth of the same microorganism in ≥2 tissues or synovialfluid culture, visible purulence, sinus tract or acute inflammation on tissue histopathology. Outcome analysis was performed at outpatient visits, followed by contacting patients, their relatives and/or treating physicians afterwards.¦Results:¦During the study period, 117 patients with infected HA were identified. We excluded 2 patients due to missing data. The average age was 69 years (range, 33-­‐102 years); 42% were female. HA was mainly performed for osteoarthritis (n=84), followed by trauma (n=22), necrosis (n=4), dysplasia(n=2), rheumatoid arthritis (n=1), osteosarcoma (n=1) and tuberculosis (n=1). 28 infections occurred early(≤3 months), 25 delayed (3-­‐24 months) and 63 late (≥24 months after surgery). Infected HA were¦treated with (i) two-­‐stage exchange in 59 patients (51%, cure rate: 93%), (ii) one-­‐stage exchange in 5 (4.3%, cure rate: 100%), (iii) debridement with change of mobile parts in 18 (17%, cure rate: 83%), (iv) debridement without change of mobile¦parts in 17 (14%, cure rate : 53% ), (v) Girdlestone in 13 (11%, cure rate: 100%), and (vi) two-­‐stage exchange followed by¦removal in 3 (2.6%). Patients were followed for an average of 3.9 years (range, 0.1 to 9 years), 7 patients died unrelated to the infected HA. 15 patients (13%) needed additional operations, 1 for mechanical reasons(dislocation of spacer) and 14 for persistent infection: 11 treated with debridement and retention (8 without change; and 3 with change of mobile parts) and 3 with two-­‐stage exchange. The average number of surgery was 2.2 (range, 1 to 5). The infection was finally eradicated in all patients, but the functional outcome remained unsatisfactory in 20% (persistent pain or impaired mobility due to spacer or Girdlestone situation).¦Conclusions:¦Non-­‐respect of current treatment concept leads to treatment failure with subsequent operations. Precise analysis of each treatment failure can be used for improving the treatment algorithm leading to better results.

Failure of surgical treatment in 115 infected total hip arthroplasties - analysis of a 12-year prosthetic joint cohort study (1999-2010)

Infection of total hip arthroplasties (THA) leads to significant long-termmorbidity and high healthcare costs. We evaluated the differentreasons for treatment failure using different surgical modalities in a12-year prosthetic joint infection cohort study.Method: All patients hospitalized at our institution with infected THAwere included either retrospectively (1999-2007) or prospectively(2008-2010). THA infection was defined as growth of the same microorganismin ≥2 tissue or synovial fluid culture, visible purulence, sinustract or acute inflammation on tissue histopathology. Outcome analysiswas performed at outpatient visits, followed by contacting patients,their relatives and/or treating physicians afterwards.Results: During the study period, 117 patients with THA were identified.We exclude 2 patients due to missing data. The median age was69 years (range, 33-102 years); 42% were women. THA was mainlyperformed for osteoarthritis (n = 84), followed by trauma (n = 22),necrosis (n = 4), dysplasia (n = 2), rheumatoid arthritis (n = 1), osteosarcoma(n = 1) and tuberculosis (n = 1). 28 infections occurred early(≤3 months), 25 delayed (3-24 months) and 63 late (≥24 months aftersurgery). Infected THA were treated with (i) two-stage exchange in59 patients (51%, cure rate: 93%), (ii) one-stage exchange in 5 (4.3%,cure rate: 100%), (iii) debridement with change of mobile parts in18 (17%, cure rate: 83%), (iv) debridement without change of mobileparts in 17 (14%, cure rate: 53% ), (v) Girdlestone in 13 (11%, curerate: 100%), and (vi) two-stage exchange followed by removal in 3(2.6%). Patients were followed for a mean of 3.9 years (range, 0.1 to 9years), 7 patients died unrelated to the infected THA. 15 patients (13%)needed additional operations, 1 for mechanical reasons (dislocationof spacer) and 14 for persistent infection: 11 treated with debridementand retention (8 without change and 3 with change of mobile parts)and 3 with two-stage exchange. The mean number of surgery was 2.2(range, 1 to 5). The infection was finally eradicated in all patients, butthe functional outcome remained unsatisfactory in 20% (persistentpain or impaired mobility due to spacer or Girdlestone situation).Conclusions: Non-respect of current treatment concept leads totreatment failure with subsequent operations. Precise analysis of eachtreatment failures can be used for improving the treatment algorithmleading to better results.