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 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

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.

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

Eliciting and reconstructing programme theory: an exercise in translating theory into practice

The importance of evaluation to demonstrate the effectiveness of policies, programmes and interventions is widely recognised. Evaluation in the context of public health and healthcare is viewed as a complicated exercise, particularly when dealing with complex interventions involving multiple partners, multiple components and multiple outcomes. Eliciting the programme theory is an important starting point of an evaluation process to enable the link between theory and action to be articulated. This article gives a pragmatic account of the practicalities of working with stakeholders as they embark on a formative evaluation of a complex public health initiative, using a using a theory-based approach. Drawing on the principles of Leeuw’s strategic assessment, we planned a workshop to reflect the four stages of this approach–group formation, assumption surfacing, dialectical debate and synthesis. Stakeholders took part in four activities–Free Listing, Sphere of Influence, Beattie’s Theoretical Framework and Programme Concept Mapping. We found that our elicitation approach was particularly suited to reconstructing the programme theory in a non-threatening and playful environment, bringing about an alignment of programme theories by consensus and reducing anxiety

Healthy obesity as an intermediate state of risk: a critical review

This is an Accepted Manuscript of an article published by Taylor & Francis in Expert Review of Endocrinology and Metabolism on 12 Aug 2016, available online: http://dx.doi.org/10.1080/17446651.2016.1220298Introduction: Obesity is a top public health priority but interventions to reverse the condition have had limited success. About 1-in-3 obese adults are free of metabolic risk factor clustering and are considered ‘healthy', and much attention has focused on the implications of this state for obesity management. Areas covered: We searched for individual studies, systematic reviews, and meta-analyses which examined correlates and outcomes of metabolically healthy obesity. We discuss the key roles of fat distribution and physical activity in determining healthy vs. unhealthy obesity and report a greatly increased risk of incident type 2 diabetes associated with healthy obesity vs. healthy normal-weight, among other outcomes. We argue that despite inconsistencies in the definition, patterns across studies clearly show that healthy obesity is a state of intermediate disease risk. Expert commentary: Given the current state of population-level evidence, we conclude that obesity and metabolic dysfunction are inseparable and that healthy obesity is best viewed only as a state of relative health but not of absolute health. We recommend that weight loss through energy restriction be a stand-alone target in addition to increased physical activity for minimising risk of future disease

Ambient air pollution and the prevalence of rhinoconjunctivitis in adolescents: A worldwide ecological analysis

Whether exposure to outdoor air pollution increases the prevalence of rhinoconjunctivitis in children is unclear. Using data from Phase Three of the International Study of Asthma and Allergies in childhood (ISAAC), we investigated associations of rhinoconjunctivitis prevalence in adolescents with model-based estimates of ozone, and satellite-based estimates of fine (diameter < 2.5 μm) particulate matter (PM2.5) and nitrogen dioxide (NO2). Information on rhinoconjunctivitis (defined as self-reported nose symptoms without a cold or flu accompanied by itchy watery eyes in the past 12 months) was available on 505,400 children aged 13–14 years, in 183 centres in 83 countries. Centre-level prevalence estimates were calculated and linked geographically with estimates of long-term average concentrations of NO2, ozone and PM2.5. Multi-level models were fitted adjusting for population density, climate, sex and gross national income. Information on parental smoking, truck traffic and cooking fuel was available for a restricted set of centres (77 in 36 countries). Between centres within countries, the estimated change in rhinoconjunctivitis prevalence per 100 children was 0.171 (95% confidence interval: − 0.013, 0.354) per 10% increase in PM2.5, 0.096 (− 0.003, 0.195) per 10% increase in NO2 and − 0.186 (− 0.390, 0.018) per 1 ppbV increase in ozone. Between countries, rhinoconjunctivitis prevalence was significantly negatively associated with both ozone and PM2.5. In the restricted dataset, the latter association became less negative following adjustment for parental smoking and open fires for cooking. In conclusion, there were no significant within-country associations of rhinoconjunctivitis prevalence with study pollutants. Negative between-country associations with PM2.5 and ozone require further investigation

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

Protein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.TU Berlin, Open-Access-Mittel – 2021DFG, 390540038, EXC 2008: Unifying Systems in Catalysis "UniSysCat"DFG, 392923329, GRK 2473: Bioaktive Peptide - Innovative Aspekte zur Synthese und BiosyntheseDFG, 426290502, Erfassung der strukturellen Organisation des Mycoplasma pneumoniae Proteoms mittels in-Zell Crosslinking-Massenspektrometri

Healthcare practitioners' views and experiences of barriers and facilitators to weight management interventions for adults with intellectual disabilities

Background Obesity is common in adults with intellectual disabilities, yet little is known about how weight management interventions are provided for this population. Methods Semi‐structured interviews were held with 14 healthcare practitioners involved in weight management interventions in an English county. A study topic guide was developed to elicit practitioners' views and experiences of barriers and facilitators to weight management for adults with intellectual disabilities. Responses were analysed using thematic analysis. Results Several barriers are involved in weight management for people with intellectual disabilities including communication challenges, general practitioners' lack of knowledge and awareness of weight management services, inconsistencies in caring support, resource constraints, wider external circumstances surrounding the individuals and motivational issues. Facilitators include reasonable adjustments to existing weight management services. However, there is a need for specialist weight management provision for people with intellectual disabilities. Conclusions This study provides suggestions for future research, policy and practice consideration