Low clusterin levels in high-density lipoprotein associate with insulin resistance, obesity, and dyslipoproteinemia

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.

A prospective cohort study of obesity and risk of oesophageal and gastric adenocarcinoma in the NIH-AARP Diet and Health Study

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

Obesity and occupational injury:a prospective cohort study of 69,515 public sector employees

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.

Obesity and kidney disease in type 1 and 2 diabetes: an analysis of the National Diabetes Audit

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.

The relationship between BMI and the prescription of anti-obesity medication according to social factors: a population cross sectional study

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.

Visual attention to food cues in obesity: An eye‐tracking study.

Objective
Based on the theory of incentive sensitization, the aim of this study was to investigate differences in attentional processing of food-related visual cues between normal-weight and overweight/obese males and females.

Methods
Twenty-six normal-weight (14M, 12F) and 26 overweight/obese (14M, 12F) adults completed a visual probe task and an eye-tracking paradigm. Reaction times and eye movements to food and control images were collected during both a fasted and fed condition in a counterbalanced design.

Results
Participants had greater visual attention towards high-energy-density food images compared to low-energy-density food images regardless of hunger condition. This was most pronounced in overweight/obese males who had significantly greater maintained attention towards high-energy-density food images when compared with their normal-weight counterparts however no between weight group differences were observed for female participants.

Conclusions
High-energy-density food images appear to capture visual attention more readily than low-energy-density food images. Results also suggest the possibility of an altered visual food cue-associated reward system in overweight/obese males. Attentional processing of food cues may play a role in eating behaviors thus should be taken into consideration as part of an integrated approach to curbing obesity.

Attentional bias to food-related visual cues: is there a role in obesity?

The incentive sensitisation model of obesity suggests that modification of the dopaminergic associated reward systems in the brain may result in increased awareness of food-related visual cues present in the current food environment. Having a heightened awareness of these visual food cues may impact on food choices and eating behaviours with those being most aware of or demonstrating greater attention to food-related stimuli potentially being at greater risk of overeating and subsequent weight gain. To date, research related to attentional responses to visual food cues has been both limited and conflicting. Such inconsistent findings may in part be explained by the use of different methodological approaches to measure attentional bias and the impact of other factors such as hunger levels, energy density of visual food cues and individual eating style traits that may influence visual attention to food-related cues outside of weight status alone. This review examines the various methodologies employed to measure attentional bias with a particular focus on the role that attentional processing of food-related visual cues may have in obesity. Based on the findings of this review, it appears that it may be too early to clarify the role visual attention to food-related cues may have in obesity. Results however highlight the importance of considering the most appropriate methodology to use when measuring attentional bias and the characteristics of the study populations targeted while interpreting results to date and in designing future studies.

Genetic studies of body mass index yield new insights for obesity biology

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.