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Institute
INTRODUCTION:
We investigated the impact of changes in lifestyle habits on colorectal cancer (CRC) risk in a multicountry European cohort.
METHODS:
We used baseline and follow-up questionnaire data from the European Prospective Investigation into Cancer cohort to assess changes in lifestyle habits and their associations with CRC development. We calculated a healthy lifestyle index (HLI) score based on smoking status, alcohol consumption, body mass index, and physical activity collected at the 2 time points. HLI ranged from 0 (most unfavorable) to 16 (most favorable). We estimated the association between HLI changes and CRC risk using Cox regression models and reported hazard ratios (HR) with 95% confidence intervals (CI).
RESULTS:
Among 295,865 participants, 2,799 CRC cases were observed over a median of 7.8 years. The median time between questionnaires was 5.7 years. Each unit increase in HLI from the baseline to the follow-up assessment was associated with a statistically significant 3% lower CRC risk. Among participants in the top tertile at baseline (HLI > 11), those in the bottom tertile at follow-up (HLI <= 9) had a higher CRC risk (HR 1.34; 95% CI 1.02-1.75) than those remaining in the top tertile. Among individuals in the bottom tertile at baseline, those in the top tertile at follow-up had a lower risk (HR 0.77; 95% CI 0.59-1.00) than those remaining in the bottom tertile.
DISCUSSION:
Improving adherence to a healthy lifestyle was inversely associated with CRC risk, while worsening adherence was positively associated with CRC risk. These results justify and support recommendations for healthy lifestyle changes and healthy lifestyle maintenance for CRC prevention.
Obesity is a risk factor for several major cancers. Associations of weight change in middle adulthood with cancer risk, however, are less clear. We examined the association of change in weight and body mass index (BMI) category during middle adulthood with 42 cancers, using multivariable Cox proportional hazards models in the European Prospective Investigation into Cancer and Nutrition cohort. Of 241 323 participants (31% men), 20% lost and 32% gained weight (>0.4 to 5.0 kg/year) during 6.9 years (average). During 8.0 years of follow-up after the second weight assessment, 20 960 incident cancers were ascertained. Independent of baseline BMI, weight gain (per one kg/year increment) was positively associated with cancer of the corpus uteri (hazard ratio [HR] = 1.14; 95% confidence interval: 1.05-1.23). Compared to stable weight (+/- 0.4 kg/year), weight gain (>0.4 to 5.0 kg/year) was positively associated with cancers of the gallbladder and bile ducts (HR = 1.41; 1.01-1.96), postmenopausal breast (HR = 1.08; 1.00-1.16) and thyroid (HR = 1.40; 1.04-1.90). Compared to maintaining normal weight, maintaining overweight or obese BMI (World Health Organisation categories) was positively associated with most obesity-related cancers. Compared to maintaining the baseline BMI category, weight gain to a higher BMI category was positively associated with cancers of the postmenopausal breast (HR = 1.19; 1.06-1.33), ovary (HR = 1.40; 1.04-1.91), corpus uteri (HR = 1.42; 1.06-1.91), kidney (HR = 1.80; 1.20-2.68) and pancreas in men (HR = 1.81; 1.11-2.95). Losing weight to a lower BMI category, however, was inversely associated with cancers of the corpus uteri (HR = 0.40; 0.23-0.69) and colon (HR = 0.69; 0.52-0.92). Our findings support avoiding weight gain and encouraging weight loss in middle adulthood.
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.
Metabolic signatures of healthy lifestyle patterns and colorectal cancer risk in a European cohort
(2020)
BACKGROUND & AIMS: Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort.
METHODS: Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1-5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer and Nutrition participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression.
RESULTS: Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29-0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50-0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86-1.00) overall. Signature associations were stronger in male compared with female participants.
CONCLUSIONS: Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer.
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.
Obesity is a risk factor for several major cancers. Associations of weight change in middle adulthood with cancer risk, however, are less clear. We examined the association of change in weight and body mass index (BMI) category during middle adulthood with 42 cancers, using multivariable Cox proportional hazards models in the European Prospective Investigation into Cancer and Nutrition cohort. Of 241 323 participants (31% men), 20% lost and 32% gained weight (>0.4 to 5.0 kg/year) during 6.9 years (average). During 8.0 years of follow-up after the second weight assessment, 20 960 incident cancers were ascertained. Independent of baseline BMI, weight gain (per one kg/year increment) was positively associated with cancer of the corpus uteri (hazard ratio [HR] = 1.14; 95% confidence interval: 1.05-1.23). Compared to stable weight (+/- 0.4 kg/year), weight gain (>0.4 to 5.0 kg/year) was positively associated with cancers of the gallbladder and bile ducts (HR = 1.41; 1.01-1.96), postmenopausal breast (HR = 1.08; 1.00-1.16) and thyroid (HR = 1.40; 1.04-1.90). Compared to maintaining normal weight, maintaining overweight or obese BMI (World Health Organisation categories) was positively associated with most obesity-related cancers. Compared to maintaining the baseline BMI category, weight gain to a higher BMI category was positively associated with cancers of the postmenopausal breast (HR = 1.19; 1.06-1.33), ovary (HR = 1.40; 1.04-1.91), corpus uteri (HR = 1.42; 1.06-1.91), kidney (HR = 1.80; 1.20-2.68) and pancreas in men (HR = 1.81; 1.11-2.95). Losing weight to a lower BMI category, however, was inversely associated with cancers of the corpus uteri (HR = 0.40; 0.23-0.69) and colon (HR = 0.69; 0.52-0.92). Our findings support avoiding weight gain and encouraging weight loss in middle adulthood.
Fetuin-A, a hepatic-origin protein, is strongly positively associated with risk of type 2 diabetes in human observational studies, but it is unknown whether this association is causal. Weaimed to study the potential causal relation of circulating fetuin-A to risk of type 2 diabetes in a Mendelian randomization study with single nucleotide polymorphisms located in the fetuin-A-encoding AHSG gene. We used data from eight European countries of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study including 10,020 incident cases. Plasma fetuin-A concentration was measured in a subset of 965 subcohort participants and 654 case subjects. A genetic score of the AHSG single nucleotide polymorphisms was strongly associated with fetuin-A (28% explained variation). Using the genetic score as instrumental variable of fetuin-A, we observed no significant association of a 50 mu g/mL higher fetuin-A concentration with diabetes risk (hazard ratio 1.02 [95% CI 0.97, 1.07]). Combining our results with those from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium (12,171 case subjects) also did not suggest a clear significant relation of fetuin-A with diabetes risk. In conclusion, although there is mechanistic evidence for an effect of fetuin-A on insulin sensitivity and secretion, this study does not support a strong, relevant relationship between circulating fetuin-A and diabetes risk in the general population.
Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI<18.5 kg/m(2)) or obese (BMI30 kg/m(2)) categories, while the highest quartile of ABSI separated 18-39% of the individuals within each BMI category, which had 22-55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.
Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI<18.5 kg/m(2)) or obese (BMI30 kg/m(2)) categories, while the highest quartile of ABSI separated 18-39% of the individuals within each BMI category, which had 22-55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.
Background: Population-specificity of exploratory dietary patterns limits their generalizability in investigations with type 2 diabetes incidence.
Objective: The aim of this study was to derive country-specific exploratory dietary patterns, investigate their association with type 2 diabetes incidence, and replicate diabetes-associated dietary patterns in other countries.
Methods: Dietary intake data were used, assessed by country-specific questionnaires at baseline of 11,183 incident diabetes cases and 14,694 subcohort members (mean age 52.9 y) from 8 countries, nested within the European Prospective Investigation into Cancer and Nutrition study (mean follow-up time 6.9 y). Exploratory dietary patterns were derived by principal component analysis. HRs for incident type 2 diabetes were calculated by Prentice-weighted Cox proportional hazard regression models. Diabetes-associated dietary patterns were simplified or replicated to be applicable in other countries. A meta-analysis across all countries evaluated the generalizability of the diabetes-association.
Results: Two dietary patterns per country/UK-center, of which overall 3 dietary patterns were diabetes-associated, were identified. A risk-lowering French dietary pattern was not confirmed across other countries: pooled HRFrance per 1 SD: 1.00; 95% CI: 0.90, 1.10. Risk-increasing dietary patterns, derived in Spain and UK-Norfolk, were confirmed, but only the latter statistically significantly: HRSpain: 1.09; 95% CI: 0.97, 1.22 and HRUK-Norfolk: 1.12; 95% CI: 1.04, 1.20. Respectively, this dietary pattern was characterized by relatively high intakes of potatoes, processed meat, vegetable oils, sugar, cake and cookies, and tea. Conclusions: Only few country/center-specific dietary patterns (3 of 18) were statistically significantly associated with diabetes incidence in this multicountry European study population. One pattern, whose association with diabetes was confirmed across other countries, showed overlaps in the food groups potatoes and processed meat with identified diabetes-associated dietary patterns from other studies. The study demonstrates that replication of associations of exploratory patterns with health outcomes is feasible and a necessary step to overcome population-specificity in associations from such analyses.