Deaths certified as asthma and use of medical services: A national case-control study

This is an open access publication. The official published version can be accessed from the link below.Background: Studies have linked asthma death to either increased or decreased use of medical services. Methods: A population based case-control study of asthma deaths in 1994–8 was performed in 22 English, six Scottish, and five Welsh health authorities/boards. All 681 subjects who died were under the age of 65 years with asthma in Part I on the death certificates. After exclusions, 532 hospital controls were matched to 532 cases for age, district, and date of asthma admission/death. Data were extracted blind from primary care records. Results: The median age of the subjects who died was 53 years; 60% of cases and 64% of controls were female. There was little difference in outpatient attendance (55% and 55%), hospital admission for asthma (51% and 54%), and median inpatient days (20 days and 15 days) in the previous 5 years. After mutual adjustment and adjustment for sex, using conditional logistic regression, three variables were independently associated with asthma death: fewer general practice contacts (odds ratio 0.82 (95% confidence interval (CI) 0.74 to 0.91) per 5 contacts) in the previous year, more home visits (1.14 (95% CI 1.08 to 1.21) per visit) in the previous year, and fewer peak expiratory flow recordings (0.83 (95% CI 0.74 to 0.92) per occasion) in the previous 3 months. These associations were similar after adjustment for markers of severity, psychosocial factors, systemic steroids, short acting bronchodilators and antibiotics, although the association with peak flow was weakened and just lost significance. Conclusion: Asthma death is associated with less use of primary care services. Both practice and patient factors may be involved and a better understanding of these may offer possibilities for reducing asthma death.This study was funded jointly between the National Research and Development Asthma Management Programme (contract number AM1/ 05/002) and the National Asthma Campaign through a grant from Glaxo Wellcome (now GlaxoSmithKline)

Mainstreaming prevention: Prescribing fruit and vegetables as a brief intervention in primary care

This is the author's PDF version of an article published in Public health© 2005.This articles discusses a project at the Castlefields Health Centre in Halton whereby primary care professionals issue a prescription for discounts on fruit and vegetables. The prescription is explicitly linked to the five-a-day message

Measurement error in a multi-level analysis of air pollution and health: a simulation study.

BACKGROUND: Spatio-temporal models are increasingly being used to predict exposure to ambient outdoor air pollution at high spatial resolution for inclusion in epidemiological analyses of air pollution and health. Measurement error in these predictions can nevertheless have impacts on health effect estimation. Using statistical simulation we aim to investigate the effects of such error within a multi-level model analysis of long and short-term pollutant exposure and health. METHODS: Our study was based on a theoretical sample of 1000 geographical sites within Greater London. Simulations of "true" site-specific daily mean and 5-year mean NO2 and PM10 concentrations, incorporating both temporal variation and spatial covariance, were informed by an analysis of daily measurements over the period 2009-2013 from fixed location urban background monitors in the London area. In the context of a multi-level single-pollutant Poisson regression analysis of mortality, we investigated scenarios in which we specified: the Pearson correlation between modelled and "true" data and the ratio of their variances (model versus "true") and assumed these parameters were the same spatially and temporally. RESULTS: In general, health effect estimates associated with both long and short-term exposure were biased towards the null with the level of bias increasing to over 60% as the correlation coefficient decreased from 0.9 to 0.5 and the variance ratio increased from 0.5 to 2. However, for a combination of high correlation (0.9) and small variance ratio (0.5) non-trivial bias (> 25%) away from the null was observed. Standard errors of health effect estimates, though unaffected by changes in the correlation coefficient, appeared to be attenuated for variance ratios > 1 but inflated for variance ratios < 1. CONCLUSION: While our findings suggest that in most cases modelling errors result in attenuation of the effect estimate towards the null, in some situations a non-trivial bias away from the null may occur. The magnitude and direction of bias appears to depend on the relationship between modelled and "true" data in terms of their correlation and the ratio of their variances. These factors should be taken into account when assessing the validity of modelled air pollution predictions for use in complex epidemiological models

The Bioinformatics Links Directory: a Compilation of Molecular Biology Web Servers

The Bioinformatics Links Directory is an online community resource that contains a directory of freely available tools, databases, and resources for bioinformatics and molecular biology research. The listing of the servers published in this and previous issues of Nucleic Acids Research together with other useful tools and websites represents a rich repository of resources that are openly provided to the research community using internet technologies. The 166 servers highlighted in the 2005 Web Server Issue are included in the more than 700 links to useful online resources that are currently contained within the descriptive biological categories of the Bioinformatics Links Directory. This curated listing of bioinformatics resources is available online at the Bioinformatics Links Directory web site, . A complete listing of the 2005 Nucleic Acids Research Web Server Issue servers is available online at the Nucleic Acids web site, , and on the Bioinformatics Links Directory web site,

Teaching about obesity: Caring, compassion, communication and courage in midwifery education

Teaching innovation can be used to promote the 6Cs in one of the most purportedly stigmatising areas of maternity care: obesity. As rates of maternal obesity continue to rise, getting this area of care right becomes more urgent. Although a great deal has been published about the unsatisfactory and stigmatising impact that staff attitudes can have on those with obesity, there is relatively little on how this problematic area of care should be taught to the next generation of midwives. This article presents a case study of learning about obesity management at the pre-registration, undergraduate level. The case study described is an effort to move away from what is currently largely an academic debate, towards a set of tangible practice recommendations

Childhood intermittent and persistent rhinitis prevalence and climate and vegetation: A global ecologic analysis

Background: The effect of climate change and its effects on vegetation growth, and consequently on rhinitis,are uncertain.Objective: To examine between- and within-country associations of climate measures and the normalizeddifference vegetation index with intermittent and persistent rhinitis symptoms in a global context.Methods: Questionnaire data from 6- to 7-year-olds and 13- to 14-year-olds were collected in phase 3 of theInternational Study of Asthma and Allergies in Childhood. Associations of intermittent (>1 symptom reportbut not for 2 consecutive months) and persistent (symptoms for -2 consecutive months) rhinitis symptomprevalences with temperature, precipitation, vapor pressure, and the normalized difference vegetation indexwere assessed in linear mixed-effects regression models adjusted for gross national income and populationdensity. The mean difference in prevalence per 100 children (with 95% confidence intervals [CIs]) perinterquartile range increase of exposure is reported.Results: The country-level intermittent symptom prevalence was associated with several country-levelclimatic measures, including the country-level mean monthly temperature (6.09-C; 95% CI, 2.06e10.11-C per 10.4-C), precipitation (3.10 mm; 95% CI, 0.46e5.73 mm; per 67.0 mm), and vapor pressure(6.21 hPa; 95% CI, 2.17e10.24 hPa; per 10.4 hPa) among 13- to 14-year-olds (222 center in 94 countries).The center-level persistent symptom prevalence was positively associated with several center-level climaticmeasures. Associations with climate were also found for the 6- to 7-year-olds (132 center in 57countries).Conclusion: Several between- and within-country spatial associations between climatic factors and intermittentand persistent rhinitis symptom prevalences were observed. These results provide suggestive evidencethat climate (and future changes in climate) may influence rhinitis symptom prevalence

Air pollution and the incidence of ischaemic and haemorrhagic stroke in the South London Stroke Register: a case-cross-over analysis.

BACKGROUND: Few European studies investigating associations between short-term exposure to air pollution and incident stroke have considered stroke subtypes. Using information from the South London Stroke Register for 2005-2012, we investigated associations between daily concentrations of gaseous and particulate air pollutants and incident stroke subtypes in an ethnically diverse area of London, UK. METHODS: Modelled daily pollutant concentrations based on a combination of measurements and dispersion modelling were linked at postcode level to incident stroke events stratified by haemorrhagic and ischaemic subtypes. The data were analysed using a time-stratified case-cross-over approach. Conditional logistic regression models included natural cubic splines for daily mean temperature and daily mean relative humidity, a binary term for public holidays and a sine-cosine annual cycle. Of primary interest were same day mean concentrations of particulate matter <2.5 and <10 µm in diameter (PM2.5, PM10), ozone (O3), nitrogen dioxide (NO2) and NO2+nitrogen oxide (NOX). RESULTS: Our analysis was based on 1758 incident strokes (1311 were ischaemic and 256 were haemorrhagic). We found no evidence of an association between all stroke or ischaemic stroke and same day exposure to PM2.5, PM10, O3, NO2 or NOX. For haemorrhagic stroke, we found a negative association with PM10 suggestive of a 14.6% (95% CI 0.7% to 26.5%) fall in risk per 10 µg/m(3) increase in pollutant. CONCLUSIONS: Using data from the South London Stroke Register, we found no evidence of a positive association between outdoor air pollution and incident stroke or its subtypes. These results, though in contrast to recent meta-analyses, are not inconsistent with the mixed findings of other UK studies

A study protocol for a randomised crossover study evaluating the effect of diets differing in carbohydrate quality on ileal content and appetite regulation in healthy humans

A major component of the digesta reaching the colon from the distal ileum is carbohydrate. This carbohydrate is subject to microbial fermentation and can radically change bacterial populations in the colon and the metabolites they produce, particularly short-chain fatty acids (SCFA). However, very little is currently known about the forms and levels of carbohydrate in the ileum and the composition of the ileal microbiota in humans. Most of our current understanding of carbohydrate that is not absorbed by the small intestine comes from ileostomy models, which may not reflect the physiology of an intact gastrointestinal tract. We will investigate how ileal content changes depending on diet using a randomised crossover study in healthy humans. Participants will be inpatients at the research facility for three separate 4-day visits. During each visit, participants will consume one of three diets, which differ in carbohydrate quality: 1) low-fibre refined diet; 2) high-fibre diet with intact cellular structures; 3) high-fibre diet where the cellular structures have been disrupted (e.g. milling, blending). On day 1, a nasoenteric tube will be placed into the distal ileum and its position confirmed under fluoroscopy. Ileal samples will be collected via the nasoenteric tube and metabolically profiled, which will determine the amount and type of carbohydrate present, and the composition of the ileal microbiota will be measured. Blood samples will be collected to assess circulating hormones and metabolites. Stool samples will be collected to assess faecal microbiota composition. Subjective appetite measures will be collected using visual analogue scales. Breath hydrogen will be measured in real-time as a marker of intestinal fermentation. Finally, an continuous fermentation model will be inoculated with ileal fluid in order to understand the shift in microbial composition and SCFA produced in the colon following the different diets. ISRCTN11327221. [Abstract copyright: Copyright: © 2019 Byrne CS et al.

A simulation study of the economic and health impact of a diabetes prevention programme in Ireland.

AIMS: Type 2 diabetes is a major public health issue that has a large effect on society including its health and social services. The aims of this paper are to generate a projection of the number of cases and explore the potential impact of a preventive intervention targeted at people with pre-diabetes on disease prevalence, complications, mortality and cost. METHODS: A Markov simulation model of diabetes and pre-diabetes in Ireland, for the period 1991 to 2036, was generated based on international epidemiological data. The simulation was calibrated with the available Irish data on the prevalence of pre-diabetes, diabetes and diabetic complications. The economic and health impact of a hypothetical nationwide preventive intervention programme, which reduces the incidence by a factor consistent with the international literature, was estimated under three scenarios of alternative effectiveness and uptake. RESULTS: The estimated number of people over 40 years of age with type 2 diabetes in Ireland is projected to increase from 216,000 in 2020 to 414,000 in 2036. A prevention programme, based on the NHS Diabetes Prevention Programme, is estimated to result in a reduction of between 2000 (0.5%) and 19,000 (4.6%) in the number of prevalent cases of diabetes in 2036 resulting in substantial health and quality of life benefits. CONCLUSIONS: A wide range of initiatives with uncertain outcomes will be required to reduce the impact of obesity and type 2 diabetes. A diabetes prevention programme seems likely to be worth pursuing as one element of this set of initiatives

The impact of measurement error in modelled ambient particles exposures on health effect estimates in multi-level analysis: a simulation study.

Background: Various spatiotemporal models have been proposed for predicting ambient particulate exposure for inclusion in epidemiological analyses. We investigated the effect of measurement error in the prediction of particulate matter with diameter <10 µm (PM10) and <2.5 µm (PM2.5) concentrations on the estimation of health effects. Methods: We sampled 1,000 small administrative areas in London, United Kingdom, and simulated the “true” underlying daily exposure surfaces for PM10 and PM2.5 for 2009–2013 incorporating temporal variation and spatial covariance informed by the extensive London monitoring network. We added measurement error assessed by comparing measurements at fixed sites and predictions from spatiotemporal land-use regression (LUR) models; dispersion models; models using satellite data and applying machine learning algorithms; and combinations of these methods through generalized additive models. Two health outcomes were simulated to assess whether the bias varies with the effect size. We applied multilevel Poisson regression to simultaneously model the effect of long- and short-term pollutant exposure. For each scenario, we ran 1,000 simulations to assess measurement error impact on health effect estimation. Results: For long-term exposure to particles, we observed bias toward the null, except for traffic PM2.5 for which only LUR underestimated the effect. For short-term exposure, results were variable between exposure models and bias ranged from −11% (underestimate) to 20% (overestimate) for PM10 and of −20% to 17% for PM2.5. Integration of models performed best in almost all cases. Conclusions: No single exposure model performed optimally across scenarios. In most cases, measurement error resulted in attenuation of the effect estimate