Wanqing Chen1, Changfa Xia2, Rongshou Zheng2, Maigeng Zhou3, Chunqing Lin4, Hongmei Zeng2, Siwei Zhang2, Lijun Wang3, Zhixun Yang2, Kexin Sun2, He Li2, Matthew D Brown5, Farhad Islami6, Freddie Bray7, Ahmedin Jemal6, Jie He8. 1. National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: chenwq@cicams.ac.cn. 2. National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 3. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. 4. International Agency for Research on Cancer, Lyon, France. 5. Center for Global Health, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. 6. Surveillance and Health Services Research, American Cancer Society, Atlanta, GA, USA. 7. Cancer Surveillance Section, International Agency for Research on Cancer, Lyon, France. 8. National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: hejie@cicams.ac.cn.
Abstract
BACKGROUND: Understanding disparities in the burden of cancer attributable to different risk factors is crucial to inform and improve cancer prevention and control. In this report, we estimate the site-specific population-attributable fractions (PAFs) for 23 potentially modifiable risk factors across all provinces in China. METHODS: In this comparative risk assessment study, we used 2014 cancer mortality data for adults from 978 county-level surveillance points in 31 provinces of mainland China. Risk-factor prevalence estimates were obtained from representative surveys. We used summary relative risks obtained from several recent large-scale pooled analyses or high-quality meta-analyses of studies in China. We calculated PAFs using multiple formulae incorporating exposure prevalence and relative risk data stratified by age, sex and province and then combined to create summary PAFs by sex, cancer site, and risk factors. FINDINGS: About 1 036 004 cancer deaths (45·2% of all cancer deaths [95% CI 44·0-46·4]) in China in 2014 in adults aged 20 years or older were attributable to 23 evaluated risk factors. The PAF was higher in men (51·2% [95% CI 50·0-52·4]) than in women (34·9% [33·6-36·2]), with the leading risk factors being active smoking in men and low fruit intake in women. By province, the PAF in both sexes combined ranged from 35·2% in Shanghai to 52·9% in Heilongjiang, while the PAF varied from 40·9% in Shanghai to 56·4% in Guangdong among men and from 26·9% in Shanghai to 48·0% in Heilongjiang among women. The highest PAF among men was smoking in all 31 provinces, whereas among women it varied among low fruit intake (14 provinces), hepatitis B virus infection (seven provinces), smoking (six provinces), excess bodyweight (three provinces), and human papilloma virus infection (one province). INTERPRETATION: The PAFs of cancers attributable to potentially modifiable risk factors vary substantially across provinces in China. Regional adoption of effective primary cancer prevention strategies has a vast potential to reduce the burden of cancer and disparities in China. Smoking, poor diet, and infection warrant particular policy attention as they contributed a large proportion to the total cancer burden. FUNDING: National Science and Technology Basic Research Special Foundation of China.
BACKGROUND: Understanding disparities in the burden of cancer attributable to different risk factors is crucial to inform and improve cancer prevention and control. In this report, we estimate the site-specific population-attributable fractions (PAFs) for 23 potentially modifiable risk factors across all provinces in China. METHODS: In this comparative risk assessment study, we used 2014 cancer mortality data for adults from 978 county-level surveillance points in 31 provinces of mainland China. Risk-factor prevalence estimates were obtained from representative surveys. We used summary relative risks obtained from several recent large-scale pooled analyses or high-quality meta-analyses of studies in China. We calculated PAFs using multiple formulae incorporating exposure prevalence and relative risk data stratified by age, sex and province and then combined to create summary PAFs by sex, cancer site, and risk factors. FINDINGS: About 1 036 004 cancer deaths (45·2% of all cancer deaths [95% CI 44·0-46·4]) in China in 2014 in adults aged 20 years or older were attributable to 23 evaluated risk factors. The PAF was higher in men (51·2% [95% CI 50·0-52·4]) than in women (34·9% [33·6-36·2]), with the leading risk factors being active smoking in men and low fruit intake in women. By province, the PAF in both sexes combined ranged from 35·2% in Shanghai to 52·9% in Heilongjiang, while the PAF varied from 40·9% in Shanghai to 56·4% in Guangdong among men and from 26·9% in Shanghai to 48·0% in Heilongjiang among women. The highest PAF among men was smoking in all 31 provinces, whereas among women it varied among low fruit intake (14 provinces), hepatitis B virus infection (seven provinces), smoking (six provinces), excess bodyweight (three provinces), and human papilloma virus infection (one province). INTERPRETATION: The PAFs of cancers attributable to potentially modifiable risk factors vary substantially across provinces in China. Regional adoption of effective primary cancer prevention strategies has a vast potential to reduce the burden of cancer and disparities in China. Smoking, poor diet, and infection warrant particular policy attention as they contributed a large proportion to the total cancer burden. FUNDING: National Science and Technology Basic Research Special Foundation of China.
Authors: Maomao Cao; He Li; Dianqin Sun; Lin Lei; Jiansong Ren; Jufang Shi; Ni Li; Ji Peng; Wanqing Chen Journal: Chin J Cancer Res Date: 2020-10-31 Impact factor: 5.087
Authors: Shao-Ming Wang; Hormuzd A Katki; Barry I Graubard; Lisa L Kahle; Anil Chaturvedi; Charles E Matthews; Neal D Freedman; Christian C Abnet Journal: Am J Gastroenterol Date: 2021-09-01 Impact factor: 12.045