PO.PS01.06 · 人群科学

亚洲的可归因癌症:异质性图景

Attributable cancer in Asia: A heterogeneous picture

海报缩略图:亚洲的可归因癌症:异质性图景
编号 5042 展板 15 时间 4/21 09:00–12:00 区域 Section 35 主讲 Paolo Boffetta, MD
分会场 Diet, Alcohol, and Tobacco, and Other Lifestyle Factors
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作者与单位 Authors & Affiliations

Monireh Sadat Seyyedsalehi1, Paolo Boffetta2

1University of Bologna, Bologna, Italy,2Stony Brook University, Stony Brook, NY

摘要 Abstract

中文摘要
已发表的亚洲可改变因素所致癌症负担估计因方法学异质而不可比较。需要一项综合分析来刻画区域差异并为预防策略提供依据。我们估计了将亚洲国家分组为西亚、南亚、东南亚、中亚和选定东亚国家(中国、蒙古和朝鲜;日本和韩国)时主要可避免癌症风险因素的人群归因分数(population attributable fractions, PAFs)。数据来源包括特定区域的暴露估计和来自国际评价的既定相对风险。分析的风险因素包括烟草使用、饮酒、感染、膳食因素、职业因素和超重。PAFs分别针对单个风险因素和癌症类型进行计算。在可改变风险因素对癌症负担的贡献方面,亚洲各地观察到显著的异质性(表1)。烟草、感染和酒精始终位居主要贡献因素之列,尽管其排名因区域而异。膳食和超重在若干国家贡献显著,且区域差异明显。总体而言,许多风险因素的PAFs高于欧洲和美洲报告的水平。归因分数最高的癌症类型分布在各区域间不同,反映了暴露模式和基线发病率的差异。亚洲可改变因素所致的癌症负担巨大,但在各区域间高度异质。需要提高暴露数据的可获得性和质量以进行更准确的评估。在更多亚洲国家推广可比较、方法学协调的PAF估计将强化区域癌症预防策略。未来工作应纳入时间性暴露趋势并扩大所评估风险因素的范围。表1. 以百分比表示的、针对亚洲所有癌症合计的主要可改变癌症风险因素的PAFs。风险因素 性别 西部 中部 南部 东南部 中国+ 朝鲜+ 蒙古 日本+ 韩国 分析中所有因素 两性 30.82 40.54 36.85 38.29 42.44 40.55 分析中所有因素 男性 35.95 48.15 43.25 47.09 55.89 45.87 分析中所有因素 女性 24.45 36.07 34.34 31.78 30.85 28.98 膳食* 两性 8.55 12.07 6.14 9.78 11.12 7.93 膳食* 男性 9.75 15.35 6.51 11.17 12.47 8.47 膳食* 女性 6.54 8.99 5.6 8.08 9.34 6.45 感染** 两性 8.66 18.43 14.11 16.32 15.13 14.11 感染** 男性 8.14 15.24 7.19 13.72 15.71 13.74 感染** 女性 8.01 19.91 20.24 17.53 13.77 11.43 BMI > 25 两性 6.2 6.29 2.63 2.46 3.38 5.5 BMI > 25 男性 3.73 4.05 1.48 1.64 3.71 5.35 BMI > 25 女性 8.01 7.72 3.5 2.8 3.01 4.75 饮酒 两性 0.9 3.66 2.6 2.54 4.11 6.05 饮酒 男性 1.54 7.16 5.59 5.04 7.54 8.63 饮酒 女性 0.44 2.11 1.16 1.09 1.95 3.22 吸烟 两性 11.03 7.42 11.21 12.83 17.25 15.77 吸烟 男性 19.89 21.02 26.13 27.51 33.59 23.97 吸烟 女性 4.04 1.91 3.76 5.03 6.61 7.2 *包括低水果和蔬菜摄入、高红肉和加工肉摄入、乳制品摄入、鱼类摄入 **包括幽门螺杆菌(Helicobacter pylori)、乙型肝炎病毒、丙型肝炎病毒、人乳头瘤病毒
查看英文原文 English abstract
Published estimates of cancer burden attributable to modifiable factors in Asia are not comparable due to heterogeneous methodologies. A comprehensive analysis is needed to characterize regional variations and inform prevention strategies. We estimated population attributable fractions (PAFs) for major avoidable cancer risk factors across Asian countries grouped into West Asia, South Asia, South-East Asia, Central Asia, and selected East Asian countries (China, Mongolia and North Korea; Japan and South Korea). Data sources included region-specific exposure estimates and established relative risks from international evaluations. Risk factors analyzed included tobacco use, alcohol consumption, infections, dietary factors, occupational factors, and excess body weight. PAFs were computed separately for individual risk factors and cancer types. Substantial heterogeneity was observed across Asia in the contribution of modifiable risk factors to cancer burden (table 1). Tobacco, infections, and alcohol were consistently among the leading contributors, although their ranking varied by region. Diet and excess body weight contributed substantially to several countries, with marked regional differences. Overall, PAFs for many risk factors were higher than those reported in Europe and the Americas. The distribution of cancer types with the highest attributable fractions differed across regions, reflecting variations in exposure patterns and baseline incidence. The burden of cancer attributable to modifiable factors in Asia is substantial yet highly heterogeneous across regions. Improving the availability and quality of exposure data is needed for more accurate assessments. Expansion of comparable, methodologically harmonized PAF estimation across additional Asian countries will strengthen regional cancer prevention strategies. Future work should incorporate temporal exposure trends and broaden the range of risk factors evaluated. Table 1. PAFs expressed as percentages, for major modifiable cancer risk factors referring to all cancers combined in Asia. Risk Factor Gender West Center South Southeast China+ North Korea+ Mongolia Japan+ South Korea All factors in the analysis Both 30.82 40.54 36.85 38.29 42.44 40.55 All factors in the analysis Male 35.95 48.15 43.25 47.09 55.89 45.87 All factors in the analysis Female 24.45 36.07 34.34 31.78 30.85 28.98 Diet * Both 8.55 12.07 6.14 9.78 11.12 7.93 Diet * Male 9.75 15.35 6.51 11.17 12.47 8.47 Diet * Female 6.54 8.99 5.6 8.08 9.34 6.45 Infection ** Both 8.66 18.43 14.11 16.32 15.13 14.11 Infection ** Male 8.14 15.24 7.19 13.72 15.71 13.74 Infection ** Female 8.01 19.91 20.24 17.53 13.77 11.43 BMI > 25 Both 6.2 6.29 2.63 2.46 3.38 5.5 BMI > 25 Male 3.73 4.05 1.48 1.64 3.71 5.35 BMI > 25 Female 8.01 7.72 3.5 2.8 3.01 4.75 Alcohol drinking Both 0.9 3.66 2.6 2.54 4.11 6.05 Alcohol drinking Male 1.54 7.16 5.59 5.04 7.54 8.63 Alcohol drinking Female 0.44 2.11 1.16 1.09 1.95 3.22 Tobacco smoking Both 11.03 7.42 11.21 12.83 17.25 15.77 Tobacco smoking Male 19.89 21.02 26.13 27.51 33.59 23.97 Tobacco smoking Female 4.04 1.91 3.76 5.03 6.61 7.2 *Including Low fruit and vegetable intake, high red and processed meat intake, dairy intake, fish intake **Including Helicobacter pylori, Hepatitis B virus, Hepatitis C virus, Human Papillomavirus virus
利益披露 Disclosure
M. Seyyedsalehi, None.. P. Boffetta, None.

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