1000 resultados para Obesity


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BACKGROUND: Obesity has emerged as a risk factor for the development of asthma and it may also influence asthma control and airways inflammation. However, the role of obesity in severe asthma remains unclear. OBJECTIVE: To explore the association between obesity (defined by BMI) and severe asthma. METHODS: Data from the National Registry for dedicated UK Difficult Asthma Services were used to compare patient demographics, disease characteristics and healthcare utilisation between three body mass index (BMI) categories (normal weight: 18.5 -24.99, overweight: 25 -29.99, obese: =30) in a well characterised group of severe asthmatic adults. RESULTS: The study population consisted of 666 severe asthmatics with a median BMI of 29.8 (interquartile range 22.5 -34.0). The obese group exhibited greater asthma medication requirements in terms of maintenance corticosteroid therapy (48.9% versus 40.4% and 34.5% in the overweight and normal weight groups, respectively), steroid burst therapy and short-acting ß2-agonist (SABA) use per day. Significant differences were seen with gastro-oesophageal reflux disease (GORD) (53.9% versus 48.1% and 39.7% in the overweight and normal weight groups, respectively) and proton pump inhibitor (PPI) use. Bone density scores were higher in the obese group, whilst pulmonary function testing revealed a reduced FVC and raised Kco. Serum IgE levels decreased with increasing BMI and the obese group were more likely to report eczema, but less likely to have a history of nasal polyps. CONCLUSIONS: Severe asthmatics display particular characteristics according to BMI that support the view that obesity associated severe asthma may represent a distinct clinical phenotype.1Royal Brompton Hospital, London, UK;2Department of Computing, Imperial College, UK3Airways Disease, National Heart & Lung Institute, Imperial College, UK;4Centre for infection and immunity, Queen's University of Belfast, UK;5University of Leicester, UK;6The University of Manchester and University Hospital of South Manchester, UK;7Birmingham Heartlands Hospital, University of Birmingham, UK;8Gartnavel General Hospital, University of Glasgow, UK;9Glasgow Royal Infirmary, Glasgow, UKCorrespondence: Dr Andrew N. Menzies-Gow, Royal Brompton Hospital, Fulham Road, London SW3 6HP.

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OBJECTIVES: The aim of this study was to examine the co-occurrence of obesity and sleep problems among employees and workplaces. METHODS: We obtained data from 39 873 men and women working in 3040 workplaces in 2000-2002 (the Finnish Public Sector Study). Individual- and workplace-level characteristics were considered as correlates of obesity and sleep problems, which were modelled simultaneously using a multivariate, multilevel approach. RESULTS: Of the participants, 11% were obese and 23% reported sleep problems. We found a correlation between obesity and sleep problems at both the individual [correlation coefficient 0.048, covariance 0.047, standard error (SE) 0.005) and workplace (correlation coefficient 0.619, covariance 0.068, SE 0.011) level. The latter, but not the former, correlation remained after adjustment for individual- and workplace-level confounders, such as age, sex, socioeconomic status, shift work, alcohol consumption, job strain, and proportion of temporary employees and manual workers at the workplace. CONCLUSIONS: Obese employees and those with sleep problems tend to cluster in the same workplaces, suggesting that, in addition to targeting individuals at risk, interventions to reduce obesity and sleep problems might benefit from identifying "risky" workplaces.

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To determine whether obesity and insulin resistance associate with changes in the protein content of high-density lipoprotein (HDL) in 2 different groups of men by using targeted proteomics.

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Objective: The incidence of oesophageal adenocarcinoma (EAC) has increased rapidly over the past 40 years and accumulating evidence suggests that obesity, as measured by body mass index (BMI), is a major risk factor. It remains unclear whether abdominal obesity is associated with EAC and gastric adenocarcinoma.

Design: Cox proportional hazards regression was used to examine associations between overall and abdominal obesity with EAC and gastric adenocarcinoma among 218 854 participants in the prospective NIHeAARP cohort.

Results: 253 incident EAC, 191 gastric cardia adenocarcinomas and 125 gastric non-cardia adenocarcinomas accrued to the cohort. Overall obesity (BMI) was positively associated with EAC and gastric
cardia adenocarcinoma risk (highest ($35 kg/m2) vs referent (18.5e<25 kg/m2); HR 2.11, 95% CI 1.09 to 4.09 and HR 3.67, 95% CI 2.00 to 6.71, respectively). Waist circumference was also positively associated with EAC and gastric cardia adenocarcinoma risk (highest vs referent; HR 2.01, 95% CI 1.35 to 3.00 and HR 2.22, 95% CI 1.43 to 3.47, respectively), whereas waist-to-hip ratio (WHR) was positively associated with EAC risk only (highest vs referent; HR 1.81, 95% CI 1.24 to 2.64) and persisted in patients with normal BMI (18.5e<25 kg/m2). Mutual adjustment of WHR and BMI attenuated
both, but did not eliminate the positive associations for either with risk of EAC. In contrast, the majority of the anthropometric variables were not associated with adenocarcinomas of the gastric non-cardia.

Conclusion Overall obesity was associated with a higher risk of EAC and gastric cardia adenocarcinoma, whereas abdominal obesity was found to be associated with increased EAC risk; even in people with normal BMI

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Obesity and overweight are suggested to increase the risk of occupational injury but longitudinal evidence to confirm this is rare. We sought to evaluate obesity and overweight as risk factors for occupational injuries.

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Background: Obesity is increasingly prevalent in many countries. Obesity is a major risk factor for the development of type 2 diabetes but its relationship with diabetic kidney disease (DKD) remains unclear. Some studies have suggested that the metabolic syndrome (including obesity) may be associated with DKD in type 1 diabetes. Aim: To investigate the association between obesity and DKD. Design: Retrospective cross-sectional study. Methods: National Diabetes Audit data were available for the 2007–08 cycle. Type 1 and 2 diabetes patients with both a valid serum creatinine and urinary albumin:creatinine ratio were included. DKD was defined as an estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2, albuminuria or both. Logistic regression was used to analyse associations of obesity (body mass index ≥30 kg/m2) and other variables including year of birth, year of diagnosis, ethnicity and stage of kidney disease. Results: A total of 58 791 type 1 and 733 769 type 2 diabetes patients were included in the analysis. After adjustment, when compared with type 1 diabetes patients with normal renal function those with DKD were up to twice as likely to be obese. Type 2 DKD patients were also more likely to be obese. For example, type 2 diabetes patients with an eGFR <15 ml/min/1.73 m2 and normoalbuminuria, microalbuminuria or macroalbuminuria were all more likely to be obese; odds ratios (95% CI) 1.65 (1.3–2.1), 1.56 (1.28–1.92) and 1.27 (1.05–1.54), respectively. Conclusions: This study has highlighted a strong association between obesity and kidney disease in type 1 diabetes and confirmed their association in type 2 diabetes.

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Background: Obesity is a global public health problem. There are a range of treatments available with varying short and long term success rates. One option is the use of anti-obesity medication the prescription of which has increased dramatically in recent years. Despite this, little is known about the individual and GP practice factors that influence the prescription of anti-obesity medication. Methods: Multi-level logistic regression analysis was used to investigate factors associated with the prescription of anti-obesity medication in Northern Ireland using a population primary care prescribing database (~1.5 million people aged 16+ years) during 2009/10. Results: While 25.0% of people are obese, only 1.3% (2.1% of females, 0.6% of males) received anti-obesity medication. The relationship between medication rates and age differed by gender (P < 0.001) with prescriptions higher in younger females and older males. Prescribing of anti-obesity medication reflected obesity prevalence across urban/rural areas and deprivation. There was an unexplained two-fold difference, between the 25th and 75th percentile, in the GP practice prescription of anti-obesity medication. Conclusions: There is evidence of relative under-prescribing in males compared to females despite a similar prevalence of obesity. While the prevalence (and presumably the health consequences) of obesity worsens with age, younger females are more likely to be prescribed anti-obesity medication. This suggests an element of patient demand. Educational material to improve the understanding of the role of anti-obesity medication, for patients and practitioners, is recommended. But further study is needed to understand the factors responsible for the variation in prescribing between GP practices.

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