Clinical Cancer Prevention: 188 (Recent Results in Cancer Research)
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All Cox regression models were stratified by age to prevent violation of the proportional hazards assumption and adjusted for smoking status, education, nationality, marital status, language region, and study MONICA wave 1—3; NRP1A.
Nationality was included as being Swiss or foreign. Marital status was composed of 4 categories: single, married, widowed, and divorced or separated.
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A trend test was used to examine whether the potential increase in risk for the outcome under investigation was linear. Multiplicative likelihood ratio test interaction was considered for sex and smoking. We used the original data set to test for trend and interaction, because in Stata those methods are not implemented for imputed data Stata: mi.
The relative importance of the score components was analyzed for those causes of death being statistically significant in the Cox regression models with the use of the imputed data set and the continuous score. For this purpose, one component was removed from the score, followed by our checking whether the reduced score was still significant.
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Rate advancement periods RAPs were calculated for all-cause mortality only because of a lack of power for cause-specific mortality. Based on an age dimension, the RAP estimates how much earlier death occurred in those being exposed than in those being unexposed In addition, we estimated population-attributable fractions PAFs for all-cause and total cancer mortality.
We also performed sensitivity analyses to investigate reverse causation. For this purpose, the first 2 y of follow-up were excluded from the analysis. Another sensitivity analysis was performed to evaluate whether the results of the Cox regression were similar, when the original rather than the imputed data set continuous or categorical score was used.
For the Cox regression models performed with the original data set, an additional category was created for confounding variables with missing values. All analyses were performed with the use of Stata The study included 16, participants men and women with a mean follow-up of The mean age at baseline was Participants within the highest lifestyle score category, i.
In addition, the proportion of participants with a high lifestyle score was greater in the NRP1A. Adherence to the recommendations was rather low for physical activity, sedentary behavior, and processed meat consumption Table 1. In total, deaths occurred, of which were caused by cancer and by CVD Table 3. Cox regression with the use of the imputed data set; models were adjusted for education, marital status, study, language region, nationality, and smoking status.
P -trend test for linearity and likelihood ratio test for multiplicative interaction, with the use of the original data set. Both the categorical and the continuous lifestyle scores were inversely associated with all-cause and total cancer mortality, but not with CVD mortality Table 3. Sex-stratified analyses of the categorical score showed that the association with all-cause mortality was stronger in men than in women men, HR: 0. In men, the risk of dying was even statistically significant when comparing low and moderate levels of the lifestyle score HR: 0.
The risk of dying from cancer all sites was inversely associated with the lifestyle score in men HR: 0.
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Lung, UADT, stomach, and prostate cancer mortality also were inversely associated when comparing lowest and highest levels of the lifestyle score HR: 0. Results were similar for the continuous score. No statistically significant associations were observed when physical activity and sedentary behavior all-cause mortality in women, and lung, and UADT cancer mortality or BMI all-cause mortality in women, and stomach, and prostate cancer mortality were excluded from the score.
Removing nutritional score components led to nonsignificant results with regard to lung and UADT cancer mortality intake of fruits and vegetables, alcohol, and grains; salt in UADT only data not shown. For the calculation of RAPs and PAFs, we used the original data set, which included 11, participants men and women. In men, additional gain of lifetime was greatest in those having low compared with moderate or high lifestyle score levels 1.
In women, RAPs were not statistically significant low compared with moderate and high, 0. For total cancer mortality, the estimated PAF was even higher. In women, PAFs were not statistically significant all-cause mortality, 4. The sensitivity analysis on reverse causation, i. Results of the Cox regression were consistent for all-cause, total cancer, lung cancer, prostate cancer, and CVD mortality: use of the imputed or the original data set did not change the results appreciably.
UADT and stomach cancer mortality results were comparable in the imputed data set for the categorical and the continuous lifestyle scores. But for the original data set, no significant associations were observed, which most likely was because of the small number of UADT and stomach cancer deaths.
However, the association with cancer mortality was statistically significant in men only. Our results strengthen the existing evidence that adherence to a healthy lifestyle is associated with all-cause and total cancer mortality 15 — Others showed the relevance of a general healthy lifestyle to prevent cancer and reduce all-cause mortality by building a lifestyle score based on the recommendations of the AICR only 26 or the American Cancer Society ACS 27 — However, in our study, the association was considerably weaker for women than for men.
We assume that this was due to an overall healthier behavior in women. In line with our results, Romaguera et al. Although our estimates were larger, the greatest association was also shown for stomach cancer, followed by UADT and lung cancers. Romaguera et al. Kabat et al. The strongest associations were observed for gallbladder, endometrial, liver, and colon cancer.
Most studies focused on breast cancer 30 — 34 , but also colorectal 35 and pancreatic 36 cancer risk were investigated. This is in contrast to several previous studies and might be due to a small number of cases. Similar to us, Cerhan et al. But in our sensitivity analysis, the exclusion of the first 2 y of follow-up yielded a significant association of the lifestyle score with CVD mortality. This may indicate reverse causation, i. McCullough et al. Similar to others, we observed that removing one component of the lifestyle score did not appreciably change the association observed for total cancer mortality men and women combined 17 , but the relative importance of individual score components differed with respect to their relevance for specific cancer types For example, for lung and UADT cancer mortality, physical activity, sedentary behavior, and nutrition seemed to be of greater importance than the other lifestyle score components.
We observed statistically significant RAPs for all-cause mortality in men, but not in women. For fruit and vegetable consumption, the estimated RAP was comparable with the 1. In relation to smoking, these estimates for all-cause mortality were smaller. In the third NHANES, the RAP for the combination of 4 lifestyle factors all compared with none: never smoking, healthy diet, adequate physical activity, and moderate alcohol consumption was estimated to be Our study had strengths and limitations.
The whole range of the lifestyle score was represented in our study, and participants were followed for up to 32 y, with low loss to follow-up. The exposure was assessed only once at baseline by self-report, which might have biased the results toward the null. This might be especially true for the NRP1A, designed as a primary prevention intervention in which participants were educated on behaviors defined as healthy and therefore might have even more strongly overreported or overestimated healthy behaviors. The assessment of the lifestyle score components was similar for the 2 cohorts pooled, and the bias introduced by pooling is expected to be minor.
The available data on dietary intake was limited, given that only the h recall has been assessed. Equal weights were given to the risk factors included in the lifestyle score and an overall estimate was calculated, not taking into account differences between specific cancer types.
By performing data imputation, we were able to present more precise estimates of the association under investigation without changing the association, as shown by the sensitivity analysis. Nevertheless, the number of cases was relatively low for some cancer-specific—type mortalities, especially stomach, urinary tract, and liver cancers; therefore, the results have to be interpreted with caution. Concerning generalizability, we assume that the results of our analysis tend to underestimate the real association between mortality and healthy lifestyle. In conclusion, our results support the importance of a general healthy lifestyle with regard to all-cause and cancer mortality.
To reduce the burden of cancer in the population, preventive measures should stress the potential of low-risk health behavior and communicate the diverse opportunities for improvement, rather than focusing on specific risk factors only. To deepen our understanding of the association between cancer and lifestyle, future research should consider a life course approach. None of the authors reported a conflict of interest related to the study. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.
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Citation Impact 5. Skip to main content Advertisement. Aims and scope Breast Cancer Research is an international, peer-reviewed online journal, publishing original research, reviews, editorials and reports. Open access research articles of exceptional interest are published in all areas of biology and medicine relevant to breast cancer, including normal mammary gland biology, with special emphasis on the genetic, biochemical, and cellular basis of breast cancer.
In addition to basic research, the journal publishes preclinical, translational and clinical studies with a biological basis, including Phase I and Phase II trials.