Associations of six adiposity-related markers with incidence and mortality from 24 cancers—findings from the UK Biobank prospective cohort study

Abstract Background Adiposity is a strong risk factor for cancer incidence and mortality. However, most of the evidence available has focused on body mass index (BMI) as a marker of adiposity. There is limited evidence on relationships of cancer with other adiposity markers, and if these associations are linear or not. The aim of this study was to investigate the associations of six adiposity markers with incidence and mortality from 24 cancers by accounting for potential non-linear associations. Methods A total of 437,393 participants (53.8% women; mean age 56.3 years) from the UK Biobank prospective cohort study were included in this study. The median follow-up was 8.8 years (interquartile range 7.9 to 9.6) for mortality and 9.3 years (IQR 8.6 to 9.9) for cancer incidence. Adiposity-related exposures were BMI, body fat percentage, waist-hip ratio, waist-height ratio, and waist and hip circumference. Incidence and mortality of 24 cancers sites were the outcomes. Cox proportional hazard models were used with each of the exposure variables fitted separately on penalised cubic splines. Results During follow-up, 47,882 individuals developed cancer and 11,265 died due to cancer during the follow-up period. All adiposity markers had similar associations with overall cancer incidence. BMI was associated with a higher incidence of 10 cancers (stomach cardia (hazard ratio per 1 SD increment 1.35, (95% CI 1.23; 1.47)), gallbladder (1.33 (1.12; 1.58)), liver (1.27 (1.19; 1.36)), kidney (1.26 (1.20; 1.33)), pancreas (1.12 (1.06; 1.19)), bladder (1.09 (1.04; 1.14)), colorectal (1.10 (1.06; 1.13)), endometrial (1.73 (1.65; 1.82)), uterine (1.68 (1.60; 1.75)), and breast cancer (1.08 (1.05; 1.11))) and overall cancer (1.03 (1.02; 1.04)). All these associations were linear except for breast cancer in postmenopausal women. Similar results were observed when other markers of central and overall adiposity were used. For mortality, nine cancer sites were linearly associated with BMI and eight with waist circumference and body fat percentage. Conclusion Adiposity, regardless of the marker used, was associated with an increased risk in 10 cancer sites.

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Associations of air pollution with obesity and body fat percentage, and modification by polygenic risk score for BMI in the UK Biobank

Environmental Research ◽

10.1016/j.envres.2020.109364 ◽

2020 ◽

Vol 185 ◽

pp. 109364 ◽

Cited By ~ 1

Author(s):

Melissa A. Furlong ◽

Yann C. Klimentidis

Keyword(s):

Air Pollution ◽

Body Fat ◽

Risk Score ◽

Polygenic Risk Score ◽

Body Fat Percentage ◽

Uk Biobank ◽

Fat Percentage ◽

Polygenic Risk ◽

The Uk

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Comparing CISNET Breast Cancer Incidence and Mortality Predictions to Observed Clinical Trial Results of Mammography Screening from Ages 40 to 49

Medical Decision Making ◽

10.1177/0272989x17718168 ◽

2018 ◽

Vol 38 (1_suppl) ◽

pp. 140S-150S ◽

Cited By ~ 4

Author(s):

Jeroen J. van den Broek ◽

Nicolien T. van Ravesteyn ◽

Jeanne S. Mandelblatt ◽

Hui Huang ◽

Mehmet Ali Ergun ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Incidence ◽

Cancer Mortality ◽

Mammography Screening ◽

Breast Cancer Mortality ◽

Breast Cancer Incidence ◽

Mortality Reduction ◽

Incidence And Mortality ◽

The Uk

Background. The UK Age trial compared annual mammography screening of women ages 40 to 49 years with no screening and found a statistically significant breast cancer mortality reduction at the 10-year follow-up but not at the 17-year follow-up. The objective of this study was to compare the observed Age trial results with the Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer model predicted results. Methods. Five established CISNET breast cancer models used data on population demographics, screening attendance, and mammography performance from the Age trial together with extant natural history parameters to project breast cancer incidence and mortality in the control and intervention arm of the trial. Results. The models closely reproduced the effect of annual screening from ages 40 to 49 years on breast cancer incidence. Restricted to breast cancer deaths originating from cancers diagnosed during the intervention phase, the models estimated an average 15% (range across models, 13% to 17%) breast cancer mortality reduction at the 10-year follow-up compared with 25% (95% CI, 3% to 42%) observed in the trial. At the 17-year follow-up, the models predicted 13% (range, 10% to 17%) reduction in breast cancer mortality compared with the non-significant 12% (95% CI, -4% to 26%) in the trial. Conclusions. The models underestimated the effect of screening on breast cancer mortality at the 10-year follow-up. Overall, the models captured the observed long-term effect of screening from age 40 to 49 years on breast cancer incidence and mortality in the UK Age trial, suggesting that the model structures, input parameters, and assumptions about breast cancer natural history are reasonable for estimating the impact of screening on mortality in this age group.

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Probiotics for the Treatment of Docetaxel-Related Weight Gain of Breast Cancer Patients—A Single-Center, Randomized, Double-Blind, and Placebo-Controlled Trial

Frontiers in Nutrition ◽

10.3389/fnut.2021.762929 ◽

2021 ◽

Vol 8 ◽

Author(s):

Zhang Juan ◽

Zhang Qing ◽

Liang Yongping ◽

Liyuan Qian ◽

Wei Wu ◽

...

Keyword(s):

Breast Cancer ◽

Body Weight ◽

Weight Gain ◽

Cancer Treatment ◽

Cancer Patients ◽

Body Fat ◽

Breast Cancer Treatment ◽

Body Fat Percentage ◽

Breast Cancer Patients ◽

Fat Percentage

Background: Docetaxel is an important chemotherapy-agent for breast cancer treatment. One of its side-effects is weight gain, which increases the all-cause mortality rate. Considering gut microbiota is one important factor for weight regulation, we hypothesized that probiotics could be potentially used to reduce the docetaxel-related weight gain in breast cancer patients.Methods: From 10/8/2018 to 10/17/2019, 100 breast cancer (Stage I-III) patients underwent four cycles of docetaxel-based chemotherapy were enrolled and randomly assigned to receive probiotics (Bifidobacterium longum, Lactobacillus acidophilus, and Enterococcus faecalis) or placebo (supplementary material of the probiotics capsule) treatment for 84 days with three capsules per time, twice/day. The primary outcome: the changes in body weight and body-fat percentage of the patients were measured by a designated physician using a fat analyzer, and the secondary outcomes: the fasting insulin, plasma glucose, and lipids were directly obtained from the Hospital Information System (HIS); The metabolites were measured using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS); The fecal microbiome was analyzed using bacterial 16S ribosomal RNA (rRNA) gene sequence. All indicators were measured 1 day before the first cycle of docetaxel-based chemotherapy and 21 days after the last cycle of docetaxel-based chemotherapy.Results: Compared with the placebo group, the probiotic group showed significantly smaller changes in body weight (Mean [SD] 0.77 [2.58] vs. 2.70 [3.08], P = 0.03), body-fat percentage (Mean [SD] 0.04 [1.14] vs. 3.86 [11.09], P = 0.02), and low density lipoprotein (LDL) (Mean [SD]−0.05[0.68] vs. 0.39 [0.58], P = 0.002). Moreover, five of the 340 detected plasma metabolites showed significant differences between the two groups. The change of biliverdin dihydrochloride (B = −0.724, P = 0.02) was inverse correlated with weight gain. One strain of the phylum and three strains of the genus were detected to be significantly different between the two groups. Also, the changes of Bacteroides (B = −0.917, P < 0.001) and Anaerostipes (B = −0.894, P < 0.001) were inverse correlated with the change of LDL.Conclusions: Probiotics supplement during docetaxel-based chemotherapy for breast cancer treatment may help to reduce the increase in body weight, body-fat percentage, plasma LDL, and minimize the metabolic changes and gut dysbacteriosis.Clinical Trial Registration:http://www.chictr.org.cn/showproj.aspx?proj=24294, ChiCTR-INQ-17014181.

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Assessment of Age-Induced Changes in Body Fat Percentage and BMI Aided by Bayesian Modelling: A Cross-Sectional Cohort Study in Middle-Aged and Older Adults

Clinical Interventions in Aging ◽

10.2147/cia.s277171 ◽

2020 ◽

Vol Volume 15 ◽

pp. 2301-2311

Author(s):

Pawel Macek ◽

Malgorzata Terek-Derszniak ◽

Malgorzata Biskup ◽

Halina Krol ◽

Jolanta Smok-Kalwat ◽

...

Keyword(s):

Older Adults ◽

Cohort Study ◽

Body Fat ◽

Body Fat Percentage ◽

Bayesian Modelling ◽

Middle Aged ◽

Fat Percentage ◽

Cross Sectional ◽

Induced Changes

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Associations of BMI and Serum Urate with Developing Dementia: A Prospective Cohort Study

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgaa638 ◽

2020 ◽

Vol 105 (12) ◽

pp. e4688-e4698

Author(s):

Zhi Cao ◽

Chenjie Xu ◽

Hongxi Yang ◽

Shu Li ◽

Fusheng Xu ◽

...

Keyword(s):

Body Mass Index ◽

Cohort Study ◽

Lower Risk ◽

Serum Urate ◽

Healthy Weight ◽

Uk Biobank ◽

Health Records ◽

Increased Risk ◽

The Uk

Abstract Context Recent studies have suggested that a higher body mass index (BMI) and serum urate levels were associated with a lower risk of developing dementia. However, these reverse relationships remain controversial, and whether serum urate and BMI confound each other is not well established. Objectives To investigate the independent associations of BMI and urate, as well as their interaction with the risk of developing dementia. Design and Settings We analyzed a cohort of 502 528 individuals derived from the UK Biobank that included people aged 37–73 years for whom BMI and urate were recorded between 2006 and 2010. Dementia was ascertained at follow-up using electronic health records. Results During a median of 8.1 years of follow-up, a total of 2138 participants developed dementia. People who were underweight had an increased risk of dementia (hazard ratio [HR] = 1.91, 95% confidence interval [CI]: 1.24–2.97) compared with people of a healthy weight. However, the risk of dementia continued to fall as weight increased, as those who were overweight and obese were 19% (HR = 0.81, 95%: 0.73–0.90) and 22% (HR = 0.78, 95% CI: 0.68–0.88) were less likely to develop dementia than people of a healthy weight. People in the highest quintile of urate were also associated with a 25% (HR = 0.75, 95% CI: 0.64–0.87) reduction in the risk of developing dementia compared with those who were in the lowest quintile. There was a significant multiplicative interaction between BMI and urate in relation to dementia (P for interaction = 0.004), and obesity strengthens the protective effect of serum urate on the risk of dementia. Conclusion Both BMI and urate are independent predictors of dementia, and there are inverse monotonic and dose-response associations of BMI and urate with dementia.

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