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Sleep Duration and Cancer Risk: a Systematic Review and Meta-analysis of Prospective Studies
Zhao, Hao,Yin, Jie-Yun,Yang, Wan-Shui,Qin, Qin,Li, Ting-Ting,Shi, Yun,Deng, Qin,Wei, Sheng,Liu, Li,Wang, Xin,Nie, Shao-Fa Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.12
To assess the risk of cancers associated with sleep duration using meta-analysis of published cohort studies, we performed a comprehensive search using PubMed, Embase and Web of Science through October 2013. We combined hazard ratios (HRs) from individual studies using meta-analysis approaches. A random effect dose-response analysis was used to evaluate the relationship between sleep duration and cancer risk. Subgroup analyses and sensitivity analyses were also performed. Publication bias was evaluated using Funnel plots and Begg's test. A total of 13 cohorts from 12 studies were included in this meta-analysis, which included 723, 337 participants with 15, 156 reported cancer outcomes during a follow-up period ranging from 7.5 to 22 years. The pooled adjusted HRs were 1.06 (95% CI: 0.92, 1.23; P for heterogeneity =0.003) for short sleep duration, 0.91 (95% CI: 0.78, 1.07; P for heterogeneity <0.0001) for long sleep duration. In subgroup analyses stratified by cancer type, long duration of sleep showed an inverse relation with hormone-related cancer (HR=0.79; 95% CI: 0.65, 0.97; P for heterogeneity =0.009) and a greater risk of colorectal cancer (HR=1.29; 95% CI: 1.09, 1.52; P for heterogeneity =0.346). Further meta-analysis on dose-response relationships showed that the relative risks of cancer were 1.00 (95% CI: 0.99, 1.01; P for linear trend=0.9151) for one hour of sleep increment per day, and 1.00 (95% CI: 0.98, 1.01; P for linear trend=0.7749) for one hour of sleep increment per night. No significant dose-response relationship between sleep duration and cancer was found on non-linearity testing (P=0.5053). Our meta-analysis suggests a positive association between long sleep duration and colorectal cancer, and an inverse association with incidence of hormone related cancers like those in the breast. Studies with larger sample size, longer follow-up times, more cancer types and detailed measure of sleep duration are warranted to confirm these results.
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Comprehensive assessment method for multi-attribute decision making
Liqiong Chen,Zhaohao Wang 원광대학교 기초자연과학연구소 2017 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS Vol.14 No.4
There are lots of methods for multi-attribute decision making problems. However, there is no standard to judge which is more reasonable. This paper proposes a comprehensive assessment method based on the existing methods for multi-attribute decision making problems. First, we introduce the ranking vector and the transformation function to make different methods in one dimension. Then, we give the reliability degree of different methods and discuss its several desirable properties. Next, we propose a comprehensive assessment method. Further more, an example is illustrated to demonstrate the validity and feasibility of the proposed method.
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Feng Zhang,Zhaohao Wang 원광대학교 기초자연과학연구소 2017 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS Vol.14 No.4
Inclusion measure of hesitant fuzzy sets is an important subject in the theory of hesitant fuzzy set, and it has been studied and widely used in clustering analysis and decision making. In this paper, we aim at constructing inclusion measure for hesitant fuzzy sets based on fuzzy sets. The axiomatical definition of inclusion measure for hesitant fuzzy sets is firstly proposed, and we construct a new inclusion relation for hesitant fuzzy sets. Based on this new inclusion relation, different inclusion measures based on the inclusion measures of fuzzy sets for hesitant fuzzy sets are further constructed. In addition, in order to describe the fuzziness degree of HFSs, information energy for HFSs is introduced. Finally, a real example about hesitant fuzzy multi-attribute decision making is used to illustrate the validity and applicability of the proposed inclusion measures and information energies.
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