64 resultados para acute care, body mass index (BMI), clinical outcomes, corrected arm muscle area (CAMA), covariates, dementia, depression, dietitian referral, discharge destination, elderly, functional status, geriatric, hospitalised, length of stay (LOS), malnutrition

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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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Objective: To assess the prevalence of overweight and obesity, and the impact of body mass index (BMI) on maternal and neonatal outcomes, in a UK obstetric population.
Design: Retrospective study.
Setting: A tertiary referral unit in Northern Ireland.
Population: A total of 30 298 singleton pregnancies over an 8-year period, 2004–2011.
Methods: Women were categorised according to World Health Organization classification: underweight (BMI < 18.50 kg/m2); normal weight (BMI 18.50–24.99 kg/m2; reference group); overweight (BMI 25.00–29.99 kg/m2); obese class I (BMI 30.00–34.99 kg/m2); obese class II (BMI 35–39.99 kg/m2); and obese class III (BMI = 40 kg/m2). Maternal and neonatal outcomes were examined using logistic regression, adjusted for confounding variables.
Main outcome measures: Maternal and neonatal outcomes.
Results: Compared with women of normal weight, women who were overweight or obese class I were at significantly increased risk of hypertensive disorders of pregnancy (OR 1.9, 99% CI 1.7–2.3; OR 3.5, 99% CI 2.9–4.2); gestational diabetes mellitus (OR 1.7, 99% CI 1.3–2.3; OR 3.7, 99% CI 2.8–5.0); induction of labour (OR 1.2, 99% CI 1.1–1.3; OR 1.3, 99% CI 1.2–1.5); caesarean section (OR 1.4, 99% CI 1.3–1.5; OR 1.8, 99% CI 1.6–2.0); postpartum haemorrhage (OR 1.4, 99% CI 1.3–1.5; OR 1.8, 1.6–2.0); and macrosomia (OR 1.5, 99% CI 1.3–1.6; OR 1.9, 99% CI 1.6–2.2), with the risks increasing for obese classes II and III. Women in obese class III were at increased risk of preterm delivery (OR 1.6, 99% CI 1.1–2.5), stillbirth (OR 3.0, 99% CI 1.0–9.3), postnatal stay > 5 days (OR 2.1, 99% CI 1.5–3.1), and infant requiring admission to a neonatal unit (OR 1.6, 99% CI 1.0–2.6).
Conclusions: By categorising women into overweight and obesity subclassifications (classes I –III), this study clearly demonstrates an increasing risk of adverse outcomes across BMI categories, with women who are overweight also at significant risk.
Keywords Body mass index, maternal and neonatal outcomes,obesity, pregnancy

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Obesity has consistently been linked to an increased risk of colorectal cancer, particularly among men. Whether body mass index (BMI) differentially influences the risk across the stages of colorectal cancer development remains unclear. We evaluated the associations of BMI with colorectal adenoma incidence, adenoma recurrence, and cancer in the context of a large screening trial, in which cases and controls had an equal chance for disease detection.

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Background: Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries.

Methods: We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m2 [underweight], 18·5 kg/m2 to <20 kg/m2, 20 kg/m2 to <25 kg/m2, 25 kg/m2 to <30 kg/m2, 30 kg/m2 to <35 kg/m2, 35 kg/m2 to <40 kg/m2, ≥40 kg/m2 [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue.
Findings: We used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m2 (95% credible interval 21·3–22·1) in 1975 to 24·2 kg/m2 (24·0–24·4) in 2014 in men, and from 22·1 kg/m2 (21·7–22·5) in 1975 to 24·4 kg/m2 (24·2–24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m2 in central Africa and south Asia to 29·2 kg/m2 (28·6–29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m2 (21·4–22·3) in south Asia to 32·2 kg/m2 (31·5–32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of underweight decreased from 13·8% (10·5–17·4) to 8·8% (7·4–10·3) in men and from 14·6% (11·6–17·9) to 9·7% (8·3–11·1) in women. South Asia had the highest prevalence of underweight in 2014, 23·4% (17·8–29·2) in men and 24·0% (18·9–29·3) in women. Age-standardised prevalence of obesity increased from 3·2% (2·4–4·1) in 1975 to 10·8% (9·7–12·0) in 2014 in men, and from 6·4% (5·1–7·8) to 14·9% (13·6–16·1) in women. 2·3% (2·0–2·7) of the world's men and 5·0% (4·4–5·6) of women were severely obese (ie, have BMI ≥35 kg/m2). Globally, prevalence of morbid obesity was 0·64% (0·46–0·86) in men and 1·6% (1·3–1·9) in women.

Interpretation: If post-2000 trends continue, the probability of meeting the global obesity target is virtually zero. Rather, if these trends continue, by 2025, global obesity prevalence will reach 18% in men and surpass 21% in women; severe obesity will surpass 6% in men and 9% in women. Nonetheless, underweight remains prevalent in the world's poorest regions, especially in south Asia.

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Objectives. We investigated whether exposure to negative aspects of close relationships was associated with subsequent increase in body mass index (BMI) and waist circumference.
Methods. Data came from a prospective cohort study (Whitehall II) of 9425 civil servants aged 35 to 55 years at baseline (phase 1: 1985-1988). We assessed negative aspects of close relationships with the Close Persons Questionnaire (range 0-12) at phases 1 and 2 (1989-1990). We measured BMI and waist circumference at phases 3 (1991-1994) and 5 (1997-1999). Covariates at phase 1 included gender, age, marital status, ethnicity, BMI, employment grade, smoking, physical activity, fruit and vegetable consumption, and common mental disorder.
Results. After adjustment for sociodemographic characteristics and health behaviors, participants with higher exposure to negative aspects of close relationships had a higher likelihood of a 10% or greater increase in BMI and waist circumference (odds ratios per 1-unit increase 1.08 [95% confidence interval (CI)=1.02, 1.14; P=.007] and 1.09 [CI=1.04, 1.14; P <= .001], respectively) as well as a transition from the overweight (25 <= BMI <30) to the obese (BMI >= 30) category.
Conclusions. Adverse social relationships may contribute to weight gain.

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Objective: The proportion of overweight and obese people has grown rapidly, and obesity has now been widely recognized as an important public health problem. At the came time, stress has increased in working life. The 2 problems could be connected if work stress promotes unhealthy eating habits and sedentary behavior and thereby contributes to weight gain. This study explored the association between work stress and body mass index (BMI; kg/m(2)). Methods: We used cross-sectional questionnaire data obtained from 45,810 female and male employees participating in the ongoing Finnish Public Sector Cohort Study. We constructed individual-level scores, as well as occupational- and organizational-level aggregated scores for work stress, as indicated by the demand/control model and the effort-reward imbalance model. Linear regression analyses were stratified by sex and socioeconomic status (SES) and adjusted for age, marital status, job contract, smoking, alcohol consumption, physical activity, and negative affectivity. Results: The results with the aggregated scores showed that lower job control, higher job strain, and higher effort-reward imbalance were associated with a higher BMI. In men, lower job demands were also associated with a higher BMI. These associations were not accounted for by SES, although an additional adjustment for SES attenuated the associations. The results obtained with the individual-level scores were in the same direction, but the relationships were weaker than those obtained with the aggregated scores. Conclusions: This study shows a weak association between work stress and BMI.

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This article investigates to what extent the worldwide increase in body mass index (BMI) has been affected by economic globalization and inequality. We used time-series and longitudinal cross-national analysis of 127 countries from 1980 to 2008. Data on mean adult BMI were obtained from the Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group. Globalization was measured using the Swiss Economic Institute (KOF) index of economic globalization. Economic inequality between countries was measured with the mean difference in gross domestic product per capita purchasing power parity in international dollars. Economic inequality within countries was measured using the Gini index from the Standardized World Income Inequality Database. Other covariates including poverty, population size, urban population, openness to trade and foreign direct investment were taken from the World Development Indicators (WDI) database. Time-series regression analyses showed that the global increase in BMI is positively associated with both the index of economic globalization and inequality between countries, after adjustment for covariates. Longitudinal panel data analyses showed that the association between economic globalization and BMI is robust after controlling for all covariates and using different estimators. The association between economic inequality within countries and BMI, however, was significant only among high-income nations. More research is needed to study the pathways between economic globalization and BMI. These findings, however, contribute to explaining how contemporary globalization can be reformed to promote better health and control the global obesity epidemic. © 2013 Copyright Taylor and Francis Group, LLC.

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Objective
To investigate the effect of fast food consumption on mean population body mass index (BMI) and explore the possible influence of market deregulation on fast food consumption and BMI.

Methods
The within-country association between fast food consumption and BMI in 25 high-income member countries of the Organisation for Economic Co-operation and Development between 1999 and 2008 was explored through multivariate panel regression models, after adjustment for per capita gross domestic product, urbanization, trade openness, lifestyle indicators and other covariates. The possible mediating effect of annual per capita intake of soft drinks, animal fats and total calories on the association between fast food consumption and BMI was also analysed. Two-stage least squares regression models were conducted, using economic freedom as an instrumental variable, to study the causal effect of fast food consumption on BMI.

Findings
After adjustment for covariates, each 1-unit increase in annual fast food transactions per capita was associated with an increase of 0.033 kg/m2 in age-standardized BMI (95% confidence interval, CI: 0.013–0.052). Only the intake of soft drinks – not animal fat or total calories – mediated the observed association (β: 0.030; 95% CI: 0.010–0.050). Economic freedom was an independent predictor of fast food consumption (β: 0.27; 95% CI: 0.16–0.37). When economic freedom was used as an instrumental variable, the association between fast food and BMI weakened but remained significant (β: 0.023; 95% CI: 0.001–0.045).

Conclusion
Fast food consumption is an independent predictor of mean BMI in high-income countries. Market deregulation policies may contribute to the obesity epidemic by facilitating the spread of fast food.

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Obesity has been linked with elevated levels of C-reactive protein (CRP), and both have been associated with increased risk of mortality and cardiovascular disease (CVD). Previous studies have used a single ‘baseline’ measurement and such analyses cannot account for possible changes in these which may lead to a biased estimation of risk. Using four cohorts from CHANCES which had repeated measures in participants 50 years and older, multivariate time-dependent Cox proportional hazards was used to estimate hazard ratios (HR) and 95 % confidence intervals (CI) to examine the relationship between body mass index (BMI) and CRP with all-cause mortality and CVD. Being overweight (≥25–<30 kg/m2) or moderately obese (≥30–<35) tended to be associated with a lower risk of mortality compared to normal (≥18.5–<25): ESTHER, HR (95 % CI) 0.69 (0.58–0.82) and 0.78 (0.63–0.97); Rotterdam, 0.86 (0.79–0.94) and 0.80 (0.72–0.89). A similar relationship was found, but only for overweight in Glostrup, HR (95 % CI) 0.88 (0.76–1.02); and moderately obese in Tromsø, HR (95 % CI) 0.79 (0.62–1.01). Associations were not evident between repeated measures of BMI and CVD. Conversely, increasing CRP concentrations, measured on more than one occasion, were associated with an increasing risk of mortality and CVD. Being overweight or moderately obese is associated with a lower risk of mortality, while CRP, independent of BMI, is positively associated with mortality and CVD risk. If inflammation links CRP and BMI, they may participate in distinct/independent pathways. Accounting for independent changes in risk factors over time may be crucial for unveiling their effects on mortality and disease morbidity.

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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

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The maintenance of normal body weight is disrupted in patients with anorexia nervosa (AN) for prolonged periods of time. Prior to the onset of AN, premorbid body mass index (BMI) spans the entire range from underweight to obese. After recovery, patients have reduced rates of overweight and obesity. As such, loci involved in body weight regulation may also be relevant for AN and vice versa. Our primary analysis comprised a cross-trait analysis of the 1000 single-nucleotide polymorphisms (SNPs) with the lowest P-values in a genome-wide association meta-analysis (GWAMA) of AN (GCAN) for evidence of association in the largest published GWAMA for BMI (GIANT). Subsequently we performed sex-stratified analyses for these 1000 SNPs. Functional ex vivo studies on four genes ensued. Lastly, a look-up of GWAMA-derived BMI-related loci was performed in the AN GWAMA. We detected significant associations (P-values <5 × 10(-5), Bonferroni-corrected P<0.05) for nine SNP alleles at three independent loci. Interestingly, all AN susceptibility alleles were consistently associated with increased BMI. None of the genes (chr. 10: CTBP2, chr. 19: CCNE1, chr. 2: CARF and NBEAL1; the latter is a region with high linkage disequilibrium) nearest to these SNPs has previously been associated with AN or obesity. Sex-stratified analyses revealed that the strongest BMI signal originated predominantly from females (chr. 10 rs1561589; Poverall: 2.47 × 10(-06)/Pfemales: 3.45 × 10(-07)/Pmales: 0.043). Functional ex vivo studies in mice revealed reduced hypothalamic expression of Ctbp2 and Nbeal1 after fasting. Hypothalamic expression of Ctbp2 was increased in diet-induced obese (DIO) mice as compared with age-matched lean controls. We observed no evidence for associations for the look-up of BMI-related loci in the AN GWAMA. A cross-trait analysis of AN and BMI loci revealed variants at three chromosomal loci with potential joint impact. The chromosome 10 locus is particularly promising given that the association with obesity was primarily driven by females. In addition, the detected altered hypothalamic expression patterns of Ctbp2 and Nbeal1 as a result of fasting and DIO implicate these genes in weight regulation.