Search

To better understand the role of individual and lifestyle factors in human disease, an exposome-wide association study was performed to investigate within a single-study anthropometry measures and lifestyle factors previously associated with B-cell lymphoma (BCL). Within the European Prospective Investigation into Cancer and nutrition study, 2402 incident BCL cases were diagnosed from 475 426 participants that were followed-up on average 14 years. Standard and penalized Cox regression models as well as principal component analysis (PCA) were used to evaluate 84 exposures in relation to BCL risk. Standard and penalized Cox regression models showed a positive association between anthropometric measures and BCL and multiple myeloma/plasma cell neoplasm (MM). The penalized Cox models additionally showed the association between several exposures from categories of physical activity, smoking status, medical history, socioeconomic position, diet and BCL and/or the subtypes. PCAs confirmed the individual associations but also showed additional observations. The PC5 including anthropometry, was positively associated with BCL, diffuse large B-cell lymphoma (DLBCL) and MM. There was a significant positive association between consumption of sugar and confectionary (PC11) and follicular lymphoma risk, and an inverse association between fish and shellfish and Vitamin D (PC15) and DLBCL risk. The PC1 including features of the Mediterranean diet and diet with lower inflammatory score showed an inverse association with BCL risk, while the PC7, including dairy, was positively associated with BCL and DLBCL risk. Physical activity (PC10) was positively associated with DLBCL risk among women. This study provided informative insights on the etiology of BCL.

Additional file 1: Supplementary information. Table S1. Number of metabolites included in each study population; Table S2. Metabolites associated with each anthropometric variable in the replication set; Table S3. Metabolites with the greatest contribution for each metabolic signature; Table S4. Correlations between the metabolic signatures and their corresponding anthropometric measure; Table S5. Metabolites that changed significantly from baseline to follow-up in the Intercept; Table S6. Metabolites significantly associated with weight loss in the Intercept; Table S7. Metabolites significantly associated with weight loss in the Intercept; Figure S1. Overall Rpartial2 and weighted Rpartial2 for each covariate and BMI in the discovery set; Figure S2. Overall Rpartial2 and weighted Rpartial2 for each covariate and WC in the discovery set; Figure S3. Overall Rpartial2 and weighted Rpartial2 for each covariate and WHR in the discovery set; Figure S4. Overall Rpartial2 and weighted Rpartial2 for each covariate and weight loss in the Intercept; Figure S5. Association of colorectal and endometrial cancers with the metabolic signatures further adjusted to C-peptide; Figure S6. Association of colorectal and endometrial cancers with the anthropometric measures of obesity; Figure S7. Smile plot of the associations between metabolites with weight loss in the Intercept.

Additional file 2: Table S2. Gene expression studies used as input for gene set analyses.

Additional file 1: Table S1. Translation of the question on physical activity, as it appears in the NOWAC questionnaires.

Published version, also at http://dx.doi.org/10.1186/s12885-015-1971-9 Background: The main aim of this study was to investigate pre- and post-diagnostic physical activity (PA) levels, as well as changes in pre- and post-diagnostic PA levels, and their association with all-cause and breast cancer-specific mortality in women with breast cancer. Our study will add to the knowledge on whether a modifiable behavior such as PA can improve survival. Methods: We included 1,327 women with breast cancer from the population-based Norwegian Women and Cancer study, which enrolled women from 1991 to 2003. Breast cancer cases were identified through linkage to the Cancer Registry of Norway; date and cause of death were obtained from the National Register for Causes of Death through 31 December 2012. Self-reported pre- and post-diagnostic PA levels were assessed, and Cox proportional hazard regression and spline regression were used to evaluate the associations. Results: Pre-diagnostic PA levels were not associated with all-cause or breast cancer-specific mortality. Post-diagnostic PA levels were associated with a significant trend (P < 0.001) of decreased all-cause and breast cancer-specific mortality, which was stronger among older women (aged 50–74 years) and did not differ across categories of body mass index. All-cause mortality (hazard ratio [HR] = 1.76, 95 % confidence interval [CI] 1.21–2.56) and breast cancer-specific mortality (HR = 2.05, 95 % CI 1.35–3.10) increased among women who reduced their post-diagnostic PA level. These values were similar among women whose maintained an inactive PA level pre- and post-diagnosis. Conclusion: Overall, we observed a dose–response trend, with an inverse association between increased postdiagnostic PA level and all-cause and breast cancer-specific mortality, as well as a higher mortality risk among women who reduced their post-diagnostic PA levels. Our results are very promising for women with breast cancer, and indicate that health care professionals should consider adding PA as a part of primary cancer treatment.

Background: Body mass index (BMI) based on self-reported height and weight has been criticized as being biased because of an observed tendency for overweight and obese people to overestimate height and underestimate weight, resulting in higher misclassification for these groups. We examined the validity of BMI based on self-reported values in a sample of Norwegian women aged 44–64 years. Methods: The study sample of 1,837 participants in the Norwegian Women and Cancer study self-reported height and weight, and then, within 1 year, either self-reported anthropometric again, or were measured by medical staff. Demographic and anthropometric were compared using t-tests and chi-square tests of independence. Misclassification of BMI categories was assessed by weighted Cohen’s kappa and Bland–Altman plot. Results: On average, the two measurements were taken 8 months apart, and self-reported weight increased by 0.6 kg (P,0.05), and BMI by 0.2 kg/m2 (P,0.05). The distribution of BMI categories did not differ between self-reported and measured values. There was substantial agreement between self-reported values and those measured by medical staff (weighted kappa 0.73). Under-reporting resulting in misclassification of BMI category was most common among overweight women (36%), but the highest proportion of extreme under-reporting was found in obese women (18% outside the 95% limits of agreement). The cumulative distribution curves for the measured and self-reported values closely followed each other, but measurements by medical staff were shifted slightly toward higher BMI values. Conclusion: While there was substantial agreement between self-reported and measured BMI values, there was small but statistically significant under-reporting of weight and thus self-reported BMI. The tendency to under-report was largest among overweight women, while the largest degree of under-reporting was found in the obese group. Self-reported weight and height provide a valid ranking of BMI for middle-aged Norwegian women. Keywords: body mass index, Norway, repeated measurements, self-report, validity, women © 2015 Skeie et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License. The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. Permissions beyond the scope of the License are administered by Dove Medical Press Limited. Information on how to request permission may be found at: http://www.dovepress.com/permissions.php

Background: Excess body weight, physical activity, smoking, alcohol consumption and certain dietary factors are individually related to colorectal cancer (CRC) risk; however, little is known about their joint effects. The aim of this study was to develop a healthy lifestyle index (HLI) composed of five potentially modifiable lifestyle factors healthy weight, physical activity, non-smoking, limited alcohol consumption and a healthy diet, and to explore the association of this index with CRC incidence using data collected within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods: In the EPIC cohort, a total of 347,237 men and women, 25- to 70-years old, provided dietary and lifestyle information at study baseline (1992 to 2000). Over a median follow-up time of 12 years, 3,759 incident CRC cases were identified. The association between a HLI and CRC risk was evaluated using Cox proportional hazards regression models and population attributable risks (PARs) have been calculated. Results: After accounting for study centre, age, sex and education, compared with 0 or 1 healthy lifestyle factors, the hazard ratio (HR) for CRC was 0.87 (95% confidence interval (CI): 0.44 to 0.77) for two factors, 0.79 (95% CI: 0.70 to 0.89) for three factors, 0.66 (95% CI: 0.58 to 0.75) for four factors and 0.63 (95% CI: 0.54 to 0.74) for five factors; P-trend

Objective: To quantify the independent associations between objectively measured physical activity (PA), cardiorespiratory fitness (CRF), and anthropometry in European men and women. Methods: 2,056 volunteers from 12 centers across Europe were fitted with a heart rate and movement sensor at 2 visits 4 months apart for a total of 8 days. CRF (ml/kg/min) was estimated from an 8 minute ramped step test. A cross-sectional analysis of the independent associations between objectively measured PA (m/s(2)/d), moderate and vigorous physical activity (MVPA) (% time/d), sedentary time (% time/d), CRF, and anthropometry using sex stratified multiple linear regression was performed. Results: In mutually adjusted models, CRF, PA, and MVPA were inversely associated with all anthropometric markers in women. In men, CRF, PA, and MVPA were inversely associated with BMI, whereas only CRF was significantly associated with the other anthropometric markers. Sedentary time was positively associated with all anthropometric markers, however, after adjustment for CRF significant in women only. Conclusion: CRF, PA, MVPA, and sedentary time are differently associated with anthropometric markers in men and women. CRF appears to attenuate associations between PA, MVPA, and sedentary time. These observations may have implications for prevention of obesity.

Long-term weight gain (i.e., weight gain since age 20) has been related to higher risk of postmenopausal breast cancer, but a lower risk of premenopausal breast cancer. The effect of weight change in middle adulthood is unclear. We investigated the association between weight change in middle adulthood (i.e., women aged 40-50 years) and the risk of breast cancer before and after the age of 50. We included female participants of the European Prospective Investigation into Cancer and Nutrition cohort, with information on anthropometric measures at recruitment and after a median follow-up of 4.3 years. Annual weight change was categorized using quintiles taking quintile 2 and 3 as the reference category (-0.44 to 0.36 kg/year). Multivariable Cox proportional hazards regression analysis was used to examine the association. 205,723 women were included and 4,663 incident breast cancer cases were diagnosed during a median follow-up of 7.5 years (from second weight assessment onward). High weight gain (Q5: 0.83-4.98 kg/year) was related to a slightly, but significantly higher breast cancer risk (HRQ5_versus_Q2/3: 1.09, 95% CI: 1.01-1.18). The association was more pronounced for breast cancer diagnosed before or at age 50 (HRQ5_versus_Q2/3: 1.37, 95% CI: 1.02-1.85). Weight loss was not associated with breast cancer risk. There was no evidence for heterogeneity by hormone receptor status. In conclusion, high weight gain in middle adulthood increases the risk of breast cancer. The association seems to be more pronounced for breast cancer diagnosed before or at age 50. Our results illustrate the importance of avoiding weight gain in middle adulthood.

Paper 3 of this thesis is not available in Munin: 3. Borch KB, Lund E, Braaten T and Weiderpass E.: 'Physical activity and risk of postmenopausal breast cancer by hormonal receptor status - the Norwegian Women and Cancer Study' (manuscript) 4. Avhandlingen tar for seg effekten av fysisk aktivitet i forhold til total dødelighet, hjerte-kar og kreft dødelighet og risiko for brystkreft, samt validerer selv-rapportert fysisk aktivitet i Kvinner – og Kreft studien. Vi sammenlignet en fysisk aktivitetsskala fra 1 til 10, der deltagerne ble bedt om å krysse av fysisk aktivitetsnivå, med en sensor som målte puls og bevegelse over 4 døgn. Resultatene viste at skalaen var tilstrekkelig til å rangere deltagernes fysisk aktivitetsnivå. Kvinner med veldig lave fysiske aktivitetsnivå hadde høyere risiko for total dødelighet, hjerte-kar og kreft død enn kvinner som rapporterte et moderat aktivitetsnivå. Hvis fysisk inaktivitet som risiko faktor for død ikke eksisterte hos kvinner i Norge ville 11,5 % av alle dødsfall vært utsatt. Vi fant inkonsistent sammenheng mellom fysisk aktivitet og postmenopausal brystkreft med en økt risiko for brystkreft karakterisert med positiv østrogen/progesteron status hos kvinner som rapporterte lavt fysisk aktivitetsnivå sammenlignet med moderat fysisk aktivitetsnivå ved 30 års alder, mens lave fysiske aktivitetsnivåer fra 14 års alderen og til voksen viste en beskyttende effekt for brystkreft.

BACKGROUND & AIMS: Colorectal cancer located at different anatomical subsites may have distinct etiologies and risk factors. Previous studies that have examined this hypothesis have yielded inconsistent results, possibly because most studies have been of insufficient size to identify heterogeneous associations with precision. METHODS: In the European Prospective Investigation into Cancer and Nutrition study, we used multivariable joint Cox proportional hazards models, which accounted for tumors at different anatomical sites (proximal colon, distal colon, and rectum) as competing risks, to examine the relationships between 14 established/suspected lifestyle, anthropometric, and reproductive/menstrual risk factors with colorectal cancer risk. Heterogeneity across sites was tested using Wald tests. RESULTS: After a median of 14.9 years of follow-up of 521,330 men and women, 6291 colorectal cancer cases occurred. Physical activity was related inversely to proximal colon and distal colon cancer, but not to rectal cancer (P heterogeneity = .03). Height was associated positively with proximal and distal colon cancer only, but not rectal cancer (P heterogeneity = .0001). For men, but not women, heterogeneous relationships were observed for body mass index (P heterogeneity = .008) and waist circumference (P heterogeneity = .03), with weaker positive associations found for rectal cancer, compared with proximal and distal colon cancer. Current smoking was associated with a greater risk of rectal and proximal colon cancer, but not distal colon cancer (P heterogeneity = .05). No heterogeneity by anatomical site was found for alcohol consumption, diabetes, nonsteroidal anti-inflammatory drug use, and reproductive/menstrual factors. CONCLUSIONS: The relationships between physical activity, anthropometry, and smoking with colorectal cancer risk differed by subsite, supporting the hypothesis that tumors in different anatomical regions may have distinct etiologies.

It is unclear if body weight in early life affects cancer risk independently of adult body weight. To investigate this question for six obesity-related cancers, we performed univariable and multivariable analyses using i) Mendelian randomization (MR) analysis and ii) longitudinal analyses in prospective cohorts. Both the MR and longitudinal analyses indicated that larger body size at age 10 was associated with higher risk of endometrial (ORMR=1.61, 95%CI = 1.23-2.11) and kidney cancer (ORMR=1.40, 95%CI = 1.09-1.80). These associations were attenuated after accounting for adult body size in both the MR and cohort analyses. Early life BMI was not consistently associated with the other investigated cancers. The lack of clear independent risk associations suggests that early life BMI influences endometrial and kidney cancer risk mainly through pathways that are common with adult BMI.