1.Population-attributable risk estimates for breast cancer in Chinese females.
Xiao-feng HU ; Yong JIANG ; Chen-xu QU ; Jian-bing WANG ; Wan-qing CHEN ; Hui LI ; You-lin QIAO
Chinese Journal of Oncology 2013;35(10):796-800
OBJECTIVETo estimate the contribution of known identified risk factors to breast cancer incidence and mortality in China, and provide evidence to support the prevention and control of breast cancer for Chinese females.
METHODSWe calculated the proportion of breast cancer attributable to specific risk factors. Data on exposure prevalence were obtained from Meta-analyses and large-scale national surveys of representative samples of the Chinese population. Data on relative risks were obtained from Meta-analyses and large-scale prospective studies. Cancer mortality and incidence were taken from the Third National Death Survey and from cancer registries in China.
RESULTSThe first 5 risk factors of breast cancer in China were benign breast disease (RR = 2.62), family history of breast cancer (RR = 2.39), smoking (RR = 1.86), overweight (RR = 1.60) and age at menarche (RR = 1.54). The proportion of breast cancer deaths attributable to reproductive factors, lifestyle factors, benign breast disease, the use of external hormone and family history of breast cancer was 27.84%, 23.55%, 15.09%, 3.60% and 2.49%, respectively. The total population attributable fraction (PAF) was 55.95% for risk factors in our study. Overall, we estimated that 79 862 breast cancer cases and 22 456 deaths were attributed to the five risk factors in China in 2005.
CONCLUSIONSThe prevention and control of unhealthy lifestyle factors may significantly reduce the number and death of breast cancer in China.
Breast Diseases ; complications ; Breast Neoplasms ; epidemiology ; etiology ; genetics ; China ; epidemiology ; Female ; Genetic Predisposition to Disease ; Humans ; Menarche ; Meta-Analysis as Topic ; Overweight ; complications ; Risk Factors ; Smoking ; adverse effects
2.Identification of a genetic locus on chromosome 4q34-35 for type 2 diabetes with overweight.
Mi Hyun PARK ; Soo Heon KWAK ; Kwang Joong KIM ; Min Jin GO ; Hye Ja LEE ; Kyung Seon KIM ; Joo Yeon HWANG ; Kuchan KIMM ; Young Min CHO ; Hong Kyu LEE ; Kyong Soo PARK ; Jong Young LEE
Experimental & Molecular Medicine 2013;45(2):e7-
The incidence of type 2 diabetes is rising rapidly because of an increase in the incidence of being overweight and obesity. Identification of genetic determinants for complex diseases, such as type 2 diabetes, may provide insight into disease pathogenesis. The aim of the study was to investigate the shared genetic factors that predispose individuals to being overweight and developing type 2 diabetes. We conducted genome-wide linkage analyses for type 2 diabetes in 386 affected individuals (269 sibpairs) from 171 Korean families and association analyses with single-nucleotide polymorphisms of candidate genes within linkage regions to identify genetic variants that predispose individuals to being overweight and developing type 2 diabetes. Through fine-mapping analysis of chromosome 4q34-35, we detected a locus potentially linked (nonparametric linkage 2.81, logarithm of odds 2.27, P=6 x 10-4) to type 2 diabetes in overweight or obese individuals (body mass index, BMI> or =23 kg m-2). Multiple regression analysis with type 2 diabetes-related phenotypes revealed a significant association (false discovery rate (FDR) P=0.006 for rs13144140; FDR P=0.002 for rs6830266) between GPM6A (rs13144140) and BMI and waist-hip ratio, and between NEIL3 (rs6830266) and insulin level from 1314 normal individuals. Our systematic search of genome-wide linkage and association studies, demonstrate that a linkage peak for type 2 diabetes on chromosome 4q34-35 contains two type 2 diabetes-related genes, GPM6A and NEIL3.
Body Mass Index
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Chromosomes, Human, Pair 4/*genetics
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Diabetes Mellitus, Type 2/*complications/*genetics
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Female
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Genetic Linkage
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*Genetic Loci
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*Genetic Predisposition to Disease
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Genome-Wide Association Study
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Humans
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Male
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Middle Aged
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Overweight/*complications/*genetics
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Phenotype
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Physical Chromosome Mapping
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Statistics, Nonparametric