North South Survey of Children's Height, Weight and Body Mass Index, 2002.

North South Survey of Children’s Height, Weight and Body Mass Index, 2002. As part of a North South Survey of Childrenâ?Ts Oral Health conducted in Ireland in 2001/â?T02 [1], the heights and weights of a representative sample of children and adolescents age 4-16 years was measured. Data were collected by 34 teams of trained and calibrated dentists and dental nurses for 17,518 children aged 4-16 in the Republic of Ireland (RoI) and 2,099 in Northern Ireland (NI). Click here to download PDF 379kb

Mortality risk of obesity and underweight is overestimated with self-reported body mass index.

Obese persons (those with a body mass index [BMI] ≥30 kg/m2) tend to underestimate their weight, leading to an underestimation of their true (measured) BMI and obesity prevalence.1,2 In contrast, underweight people (BMI <18.5 kg/m2) tend to report themselves heavier, resulting in a higher BMI compared with measured BMI and an underestimation of underweight prevalence.

The inter-rater reliability of the Pulmonary Embolism Severity Index.

The Pulmonary Embolism Severity Index (PESI) is a validated clinical prognostic model for patients with acute pulmonary embolism (PE). Our goal was to assess the PESI's inter-rater reliability in patients diagnosed with PE. We prospectively identified consecutive patients diagnosed with PE in the emergency department of a Swiss teaching hospital. For all patients, resident and attending physician raters independently collected the 11 PESI variables. The raters then calculated the PESI total point score and classified patients into one of five PESI risk classes (I-V) and as low (risk classes I/II) versus higher-risk (risk classes III-V). We examined the inter-rater reliability for each of the 11 PESI variables, the PESI total point score, assignment to each of the five PESI risk classes, and classification of patients as low versus higher-risk using kappa (κ) and intra-class correlation coefficients (ICC). Among 48 consecutive patients with an objective diagnosis of PE, reliability coefficients between resident and attending physician raters were > 0.60 for 10 of the 11 variables comprising the PESI. The inter-rater reliability for the PESI total point score (ICC: 0.89, 95% CI: 0.81-0.94), PESI risk class assignment (κ: 0.81, 95% CI: 0.66-0.94), and the classification of patients as low versus higher-risk (κ: 0.92, 95% CI: 0.72-0.98) was near perfect. Our results demonstrate the high reproducibility of the PESI, supporting the use of the PESI for risk stratification of patients with PE.

North South Survey of Children's Height, Weight and Body Mass Index, 2002

As part of a North South Survey of Childrens Oral Health conducted in Ireland in 2001/’02 [1], the heights and weights of a representative sample of children and adolescents age 4-16 years was measured. Data were collected by 34 teams of trained and calibrated dentists and dental nurses for 17,518 children aged 4-16 in the Republic of Ireland (RoI) and 2,099 in Northern Ireland (NI). This report presents the results of the study which provide a baseline measurement of Childrens height and weight against which future change can be measured. By comparing these data with international norms we can estimate the current prevalence of overweight and obesity among children and adolescents in Ireland.

Epidemiology of Chagas disease in Jaguaruana, Ceará, Brazil. I. Presence of triatomines and index of Trypanosoma cruzi infection in four localities of a rural area

In order to assay the triatomine infestation and domiciliation in the rural area of Jaguaruana district, state of Ceará, Brazil, we studied, from November 2000 to April 2002, 4 localities comprising 158 domiciles as a whole, with an average of 4 inhabitants/house, who are dwelling in there for more than 7 years. Most houses have tile-covered roofs and the walls built with plaster-covered bricks (57%), followed by bricks without plaster (33%), and mud walls (7.5%). A total of 3082 triatomines were captured from different locations, according to the following capture plan: (a) intradomiciles: 238 Triatoma brasiliensis, 6 T. pseudomaculata, 9 Rhodnius nasutus, and 2 Panstrongylus lutzi; (b) peridomiciles (annexes): 2069 T. brasiliensis, 223 T. pseudomaculata, 121 R. nasutus, and 1 P. lutzi; (c) wild, in carnauba palms (Copernicia prunifera): 413 R. nasutus. From the captured triatomines, 1773 (57.5%) were examined. The natural index of Trypanosoma cruzi infection ranged from 10.8% to 30.2% (average of 17%), depending on the species and the location from where the triatomines were captured.

Inequality and the stereotyping of young people

Recent research published by the Equality Authority highlights the ways in which a selection of teenagers believe they are negatively perceived and treated by adults across Irish society. The report is based on focus group discussions with 90 teenagers during May and June 2005 and includes the views of young asylum seekers, travellers, people with disabilities and lesbian, gay, bisexual and transgender youth. Contact with the young people was facilitated through the National Youth Council of Ireland (NYCI). The report also includes findings from a case study of stereotyping of young people in the Irish media.This resource was contributed by The National Documentation Centre on Drug Use.

Does income inequality cause health and social problems?

Key points• The literature shows general agreement about a correlation between income inequality and health/social problems. • There is less agreement about whether income inequality causes health and social problems independently of other factors, but some rigorous studies have found evidence of this. • The independent effect of income inequality on health/social problems shown in some studies looks small in statistical terms. But these studies cover whole populations, and hence a significant number of lives. • Some research suggests that inequality is particularly harmful beyond a certain threshold. Britain was below this threshold in the 1960s, 1970s and early 1980s, but rose past it in 1986–7 and has settled well above it since 1998–9. If the threshold is significant it could provide a target for policy. • Anxiety about status might explain income inequality’s effect on health and social problems. If so, inequality is harmful because it places people in a hierarchy which increases competition for status, causing stress and leading to poor health and other negative outcomes. • Not all research shows an independent effect of income inequality on health/social problems. Some highlights the role of individual income (poverty/material circumstances), culture/history, ethnicity and welfare state institutions/social policies. • The author concludes that there is a strong case for further research on income inequality and discussion of the policy implications.This resource was contributed by The National Documentation Centre on Drug Use.

Poverty, inequality and policy since 1997

This study examines the impact of policy on poverty and inequality in Britain since 1997This research shows what effect policies introduced since 1997 have had on reducing poverty and inequality. It offers a considered assessment of impacts over a decade:How did policies change, before 1997 and since then?What evidence is there of impacts on key outcomes?What gaps or problems remain or emerged?The study covers a range of subjects, including public attitudes to poverty and inequality, children and early years, education, health, employment, pensions, and migrants. It measures the extent of progress and also considers future direction and pressures, particularly in the light of recession and an ageing society.The research draws on extensive analysis of policy documents, analysis by government departments and research bodies, published statistics and evaluations, analysis of large-scale datasets, micro-simulation modelling and a long-running qualitative study with residents of low-income neighbourhoods.��

Trends in world inequality in life span since 1970

The trends in the variance of length of life, and in the variance of length of adult life in particular, are not well understood, while world inequality in length of adult life has remained stagnant. This��research��from the National Bureau of Economic Research (US)��examines life-span inequality in a broad, balanced panel of 180 rich and poor countries observed in 1970 and 2000. While the share of inequality within countries has decreased over time, inequalities between different countries have unambiguously increased. �� ��

Policy Brief: Introducing Active Ageing Index

The Active Ageing Index (AAI) is a new analytical tool that aims to help policy makers in developing policies for active and healthy ageing. Its aim is to point to the untapped potential of older people for more active participation in employment, in social life and for independent living. Mobilising the potential of both older women and men is crucial to ensure prosperity for all generations in ageing societies. This policy brief introduces the Active Ageing Index to the policy makers. ��

Health Inequality Profiles 2008 - MSOA level data (v2)

Using mortality and population data from 2001 to 2007 DSRs and life expectancy were calculated for all Middle Layer Super Output Areas in the East of England.

Health Inequality Profiles 2008 - All age, all cause standardised vs. EoE

DSRs (with CIs) for All age, all cause mortality 2001-03 to 2005-07, by gender, for Counties/UAs, County quintiles, County 80/20 standardises - as in previous years - against East of England Census 2001 population.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

Measuring health inequalities II

Exploring and using summary measures of inequality often used in economics such as Gini Coefficients and Theil Index to summarise and compare intra-PCT health inequalities