Dataset Information

Anthropometry, body fat composition and reproductive factors and risk of oesophageal and gastric cancer by subtype and subsite in the UK Biobank cohort.

ABSTRACT: BACKGROUND:Obesity has been positively associated with upper gastrointestinal cancers, but prospective data by subtype/subsite are limited. Obesity influences hormonal factors, which may play a role in these cancers. We examined anthropometry, body fat and reproductive factors in relation to oesophageal and gastric cancer by subtype/subsite in the UK Biobank cohort. METHODS:Among 458,713 UK Biobank participants, 339 oesophageal adenocarcinomas, 124 oesophageal squamous cell carcinomas, 137 gastric cardia and 92 gastric non-cardia cancers were diagnosed during a mean of 6.5 years follow-up. Cox models estimated multivariable hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS:Body mass index (BMI), hip circumference, waist circumference, waist-to-hip ratio, waist-to-height ratio, total body fat and trunk fat were positively associated with oesophageal adenocarcinoma (highest vs lowest category: HR = 2.33, 95%-CI:1.65-3.28; HR = 1.56, 95%-CI:1.15-2.13; HR = 2.30, 95%-CI:1.47-3.57; HR = 1.71, 95%-CI:1.01-2.90; HR = 2.87, 95%-CI:1.88-4.38; HR = 1.96, 95%-CI:1.30-2.96; HR = 2.34, 95%-CI:1.70-3.22, respectively). Although there were no statistically significant associations in combined sex analyses, BMI (HR = 1.83, 95%-CI:1.00-3.37), waist circumference (HR = 2.21, 95%-CI:1.27-3.84) and waist-to-hip ratio (HR = 1.92, 95%-CI:1.11-3.29) were associated with gastric cardia cancer in men; however, mutual adjustment attenuated the associations for BMI and waist-to-hip ratio. For oesophageal squamous cell carcinoma, statistically significant inverse associations were observed among women for BMI, hip circumference, waist circumference, waist-to-height ratio, total body fat and trunk fat, although they were based on small numbers. In addition, older age at first (HR = 0.44, 95%-CI:0.22-0.88) and last live birth (HR = 0.44, 95%-CI:0.22-0.87) were inversely associated with oesophageal squamous cell carcinoma and having a stillbirth/miscarriage/termination was positively associated (HR = 1.84, 95%-CI:1.10-3.07). CONCLUSIONS:Obesity and abdominal obesity specifically may be a risk factor for oesophageal adenocarcinoma and gastric cardia cancer in men. Some reproductive factors may be associated with oesophageal squamous cell carcinoma in women.

SUBMITTER: Sanikini H

PROVIDER: S-EPMC7575071 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Anthropometry, body fat composition and reproductive factors and risk of oesophageal and gastric cancer by subtype and subsite in the UK Biobank cohort.

Sanikini Harinakshi H Muller David C DC Chadeau-Hyam Marc M Murphy Neil N Gunter Marc J MJ Cross Amanda J AJ

PloS one 20201020 10

<h4>Background</h4>Obesity has been positively associated with upper gastrointestinal cancers, but prospective data by subtype/subsite are limited. Obesity influences hormonal factors, which may play a role in these cancers. We examined anthropometry, body fat and reproductive factors in relation to oesophageal and gastric cancer by subtype/subsite in the UK Biobank cohort.<h4>Methods</h4>Among 458,713 UK Biobank participants, 339 oesophageal adenocarcinomas, 124 oesophageal squamous cell carcin ...[more]

PMID: 33079929

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Project description:BackgroundObesity has been related to depression and adhering healthy lifestyle was beneficial to lower the risk of depression; however, little is known about the relationship between body composition and fat distribution with depression risk and the influence of body composition and fat distribution on the association of lifestyle and depression. Therefore, we aimed to investigate whether body composition and fat distribution were associated with the adverse events of depression and the relationship between lifestyle and depression.MethodsWe included 330,131 participants without depression at baseline in the UK Biobank (mean age, 56.9 years; 53.83% females). The assessment of depression was sourced from health outcomes across self-report, primary care, hospital inpatient data, and death data. Body composition was determined by bioelectrical impedance. Seven lifestyles (no current smoking, moderate alcohol consumption, regular physical activity, healthy diet, less sedentary behavior, healthy sleep pattern, and appropriate social connection) were used to generate a lifestyle score.ResultsDuring a median of 11.7 years of follow-up, 7576 incident depression occurred. All the body composition measures were positively associated with depression risk, with the Hazard ratios (HR) for the uppermost tertile (T3) versus the lowest tertile (T1) ranging from 1.26 (95% CI: 1.15-1.39) for trunk fat-free mass (TFFM) to 1.78 (1.62-1.97) for leg fat percentage (LFP). In addition, we found significant interactions between fat mass-related indices, especially leg fat mass (LFM) (p = 1.65 × 10-9), and lifestyle score on the risk of depression, for which the beneficial associations of a healthy lifestyle with the risk of depression were more evident among participants with low body fat measurement.ConclusionsHigh levels of body composition measures were associated with an increased depression risk. Adverse body composition measures may weaken the link between a healthy lifestyle and a reduced risk of depression.

Project description:BackgroundAdverse muscle composition (MC) as measured by magnetic resonance imaging has previously been linked to poor function, comorbidity, and increased hospitalization. The aim of this study was to investigate if adverse MC predicts all-cause mortality using data from UK Biobank.MethodsThere were 40 178 participants scanned using a 6 min magnetic resonance imaging protocol. Images were analysed for thigh fat-tissue free muscle volume and muscle fat infiltration (MFI) using AMRA® Researcher (AMRA Medical, Linköping, Sweden). For each participant, a sex, weight, and height invariant muscle volume z-score was calculated. Participants were partitioned into four MC groups: (i) normal MC, (ii) only low muscle volume [<25th percentile for muscle volume z-score (population wide)], (iii) only high MFI [>75th percentile (population wide, sex-specific)], and (iv) adverse MC (low muscle volume z-score and high MFI). Association of MC groups with mortality was investigated using Cox proportional-hazard modelling with normal MC as referent (unadjusted and adjusted for low hand grip strength, sex, age, body mass index, previous diagnosis of disease (cancer, type 2 diabetes and coronary heart disease), lifestyle, and socioeconomic factors (smoking, alcohol consumption, physical activity, and Townsend deprivation index).ResultsMuscle composition measurements were complete for 39 804 participants [52% female, mean (SD) age 64.2 (7.6) years and body mass index 26.4 (4.4) kg/m2 ]. Three hundred twenty-eight deaths were recorded during a follow-up period of 2.9 (1.4) years after imaging. At imaging, adverse MC was detected in 10.5% of participants. The risk of death from any cause in adverse MC compared with normal MC was 3.71 (95% confidence interval 2.81-4.91, P < 0.001). Only low muscle volume and only high MFI were independently associated with all-cause mortality [1.58 (1.13-2.21), P = 0.007, and 2.02 (1.51-2.71), P < 0.001, respectively]. Adjustment of low hand grip strength [1.77 (1.28-2.44), P < 0.001] did not attenuate the associations with any of the MC groups. In the fully adjusted model, adverse MC and only high MFI remained significant (P < 0.001 and P = 0.020) while the association with only low muscle volume was attenuated to non-significance (P = 0.560). The predictive performance of adverse MC [1.96 (1.42-2.71), P < 0.001] was comparable with that of previous cancer diagnosis [1.93 (1.47-2.53), P < 0.001] and smoking [1.71 (1.02-2.84), P = 0.040]. Low hand grip strength was borderline non-significant [1.34 (0.96-1.88), P = 0.090].ConclusionsAdverse MC was a strong and independent predictor of all-cause mortality. Sarcopenia guidelines can be strengthened by including cut-offs for myosteatosis enabling detection of adverse MC.

Project description:BACKGROUND Pericardial adipose tissue (PAT) is the visceral adipose tissue compartment surrounding the heart. Experimental and observational research has suggested that greater PAT deposition might mediate cardiovascular disease, independent of general or subcutaneous adiposity. We characterize the genetic architecture of adiposity-adjusted PAT and identify causal associations between PAT and adverse cardiac magnetic resonance imaging measures of cardiac structure and function in 28 161 UK Biobank participants. METHODS AND RESULTS The PAT phenotype was extracted from cardiac magnetic resonance images using an automated image analysis tool previously developed and validated in this cohort. A genome-wide association study was performed with PAT area set as the phenotype, adjusting for age, sex, and other measures of obesity. Functional mapping and Bayesian colocalization were used to understand the biologic role of identified variants. Mendelian randomization analysis was used to examine potential causal links between genetically determined PAT and cardiac magnetic resonance-derived measures of left ventricular structure and function. We discovered 12 genome-wide significant variants, with 2 independent sentinel variants (rs6428792, P=4.20×10-9 and rs11992444, P=1.30×10-12) at 2 distinct genomic loci, that were mapped to 3 potentially causal genes: T-box transcription factor 15 (TBX15), tryptophanyl tRNA synthetase 2, mitochondrial (WARS2) and early B-cell factor-2 (EBF2) through functional annotation. Bayesian colocalization additionally suggested a role of RP4-712E4.1. Genetically predicted differences in adiposity-adjusted PAT were causally associated with adverse left ventricular remodeling. CONCLUSIONS This study provides insights into the genetic architecture determining differential PAT deposition, identifies causal links with left structural and functional parameters, and provides novel data about the pathophysiological importance of adiposity distribution.

Project description:BackgroundMagnetic resonance imaging (MRI) is the gold standard for evaluating body composition. However, the reference ranges have not been established.MethodsThree lean tissue and seven adipose tissue parameters based on MRI data from the UK Biobank were used in this study. Participants with European ancestry and data on at least one parameter were screened. Age- and sex-specific percentile curves were generated using the lambda-mu-sigma method. Three levels of reference ranges were provided, which were equivalent to the mean ± 1 standard deviation (SD), 2 SDs and 2.5 SDs.ResultsThe final analysis set for each parameter ranged from 4842 to 14 148 participants (53.4%-56.6% women) with a median age of 61. For lean tissue parameters, compared with those at age 45, the median total lean tissue volume and total thigh fat-free muscle volume at age 70 were 2.83 and 1.73 L, and 3.02 and 1.51 L lower in men and women, respectively. The median weight-to-muscle ratios at age 45 were 0.51 and 0.83 kg/L lower compared with those at age 70 in men and women, respectively. Adipose tissue parameters showed inconsistent differences. In men, the median muscle fat infiltration, visceral adipose tissue (VAT) volume, total abdominal adipose tissue index and abdominal fat ratio were 1.48%, 0.32 L, 0.08 L/m2 and 0.4 higher, and the median abdominal subcutaneous adipose tissue (ASAT) volume and total adipose tissue volume were 0.47 and 0.41 L lower, respectively, at age 70 than at age 45. The median total trunk fat volume was approximately 9.53 L at all ages. In women, the median muscle fat infiltration and VAT volume were 1.68% and 0.76 L higher, respectively, at age 70 than at age 45. The median ASAT volume, total adipose tissue volume, total trunk fat volume, total abdominal adipose tissue index and abdominal fat ratio were 0.35 L, 0.78 L, 1.12 L, 0.49 L/m2 and 0.06 higher, respectively, at age 60 than at age 45. The medians of the former three parameters were 0.33 L, 0.14 L and 0.20 L lower, at age 70 than at age 60. The medians of the latter two parameters were approximately 3.64 L/m2 and 0.55 at ages between 60 and 70.ConclusionsWe have established reference ranges for MRI-measured body composition parameters in a large community-dwelling population. These findings provide a more accurate assessment of abnormal adipose and muscle conditions.

Project description:Non-alcoholic fatty liver disease (NAFLD) has emerged as the most prevalent chronic liver disease worldwide, yet detection has remained largely based on surrogate serum biomarkers, elastography or biopsy. In this study, we used a total of 2959 participants from the UK biobank cohort and established the association of dual-energy X-ray absorptiometry (DXA)-derived body composition parameters and leveraged machine learning models to predict NAFLD. Hepatic steatosis reference was based on MRI-PDFF which has been extensively validated previously. We found several significant associations with traditional measurements such as abdominal obesity, as defined by waist-to-hip ratio (OR = 2.50 (male), 3.35 (female)), android-gynoid ratio (OR = 3.35 (male), 6.39 (female)) and waist circumference (OR = 1.79 (male), 3.80 (female)) with hepatic steatosis. Similarly, A Body Shape Index (Quantile 4 OR = 1.89 (male), 5.81 (female)), and for fat mass index, both overweight (OR = 6.93 (male), 2.83 (female)) and obese (OR = 14.12 (male), 5.32 (female)) categories were likewise significantly associated with hepatic steatosis. DXA parameters were shown to be highly associated such as visceral adipose tissue mass (OR = 8.37 (male), 19.03 (female)), trunk fat mass (OR = 8.64 (male), 25.69 (female)) and android fat mass (OR = 7.93 (male), 21.77 (female)) with NAFLD. We trained machine learning classifiers with logistic regression and two histogram-based gradient boosting ensembles for the prediction of hepatic steatosis using traditional body composition indices and DXA parameters which achieved reasonable performance (AUC = 0.83-0.87). Based on SHapley Additive exPlanations (SHAP) analysis, DXA parameters that had the largest contribution to the classifiers were the features predicted with significant association with NAFLD. Overall, this study underscores the potential utility of DXA as a practical and potentially opportunistic method for the screening of hepatic steatosis.

Project description:Background and aimsExcess energy intake can lead to metabolic dysfunction-associated steatotic liver disease (MASLD), but the relationship between dietary carbohydrate intake and liver fat content remains unclear. This study aimed to examine the associations between types and sources of dietary carbohydrates and liver fat content.MethodsUK Biobank participants with no pre-existing diabetes, liver disease or cardiovascular disease reported dietary intake of types and sources of carbohydrates (total carbohydrates, free sugars, non-free sugars, starch from whole grains, starch from refined grains, and fibre) on at least two 24-h dietary assessments. In cross-sectional analyses, (n = 22,973), odds ratios (OR) of high liver fat content (defined as a score of ≥ 36 in the hepatic steatosis index) by quintiles of carbohydrate intakes were estimated using multivariable logistic regression models. In prospective analyses, a second sample (n = 9268) had liver proton density fat fraction (PDFF) measured by magnetic resonance imaging (2014-2020). Multivariable linear regression models estimated geometric means of PDFF (%) by quintiles of carbohydrate intakes. Models were adjusted for demographic and lifestyle confounders, including total energy intake.ResultsIn the cross-sectional analyses, 6894 cases of high liver fat content were identified. Inverse associations between intakes of fibre (OR of highest vs. lowest quintile 0.46 [95% CI: 0.41-0.52]), non-free sugars (0.63 [0.57-0.70]) and starch from whole grains (0.52 [0.47-0.57]) with liver fat were observed. There were positive associations between starch from refined grains and liver fat (1.33 [1.21-1.46]), but no association with free sugars (p=0.61). In prospective analyses, inverse associations with PDFF (%) were observed for intakes of fibre (- 0.48 geometric mean difference between highest and lowest quintile of intake [- 0.60 to - 0.35]), non-free sugars (- 0.37 [- 0.49 to - 0.25]) and starch from whole grains (- 0.31 [- 0.42 to - 0.19]). Free sugars, but not starch from refined grains, were positively associated with PDFF (0.17 [0.05 to 0.28]).ConclusionThis study suggests that different carbohydrate types and sources have varying associations with liver fat, which may be important for MASLD prevention. Non-free sugars, fibre, and starch from whole grains could be protective, while associations with free sugars and starch from refined grains are less clear.

Dataset Information

Anthropometry, body fat composition and reproductive factors and risk of oesophageal and gastric cancer by subtype and subsite in the UK Biobank cohort.

Publications

Anthropometry, body fat composition and reproductive factors and risk of oesophageal and gastric cancer by subtype and subsite in the UK Biobank cohort.

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