The combined effect of individual and neighborhood socioeconomic status on cancer survival rates.

The combined effect of individual and neighborhood socioeconomic status on cancer survival rates.
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DOI:
10.1371/journal.pone.0044325
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发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Lee CC
Lee CC
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Chang CM;Su YC;Lai NS;Huang KY;Chien SH;Chang YH;Lian WC;Hsu TW;Lee CC

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本研究以人口为基础,探讨台湾地区个人及社区社经地位与主要癌症死亡率的关系。一项以人群为基础的随访研究对2002年确诊的20,488名癌症患者进行了研究。每位患者被追踪至死亡或持续5年。个人收入相关保险支付金额作为个体SES患者的代理度量。社会经济地位是由收入来定义的,社区被分为生活在有利地区和不利地区。在调整了可能的混杂因素和危险因素后,采用Cox比例风险模型比较不同SES组之间的无死亡生存率。在调整患者特征(年龄、性别、Charlson共病指数评分、城市化、居住地区)、肿瘤范围、治疗方式(手术和辅助治疗)、医院特征(所有制和教学水平)后,弱势社区65岁以下个体社会经济地位低的结直肠癌和头颈癌患者的死亡风险高1.5 ~ 2倍。与优势社区的高个体SES患者相比。在肺癌和乳腺癌中发现了交叉水平的相互作用效应。65岁以下、社会经济地位低的肺癌和乳腺癌患者在优势社区的死亡风险最高。弱势社区65岁及以上社会经济地位低的前列腺癌患者死亡风险最高。SES与宫颈癌和胰腺癌的死亡率之间没有关联。我们的研究结果表明,即使在全民医疗保健制度下,个体社会经济地位低的癌症患者的死亡率也最高。公共卫生战略和福利政策必须继续关注这一弱势群体。
This population-based study investigated the relationship between individual and neighborhood socioeconomic status (SES) and mortality rates for major cancers in Taiwan. A population-based follow-up study was conducted with 20,488 cancer patients diagnosed in 2002. Each patient was traced to death or for 5 years. The individual income-related insurance payment amount was used as a proxy measure of individual SES for patients. Neighborhood SES was defined by income, and neighborhoods were grouped as living in advantaged or disadvantaged areas. The Cox proportional hazards model was used to compare the death-free survival rates between the different SES groups after adjusting for possible confounding and risk factors. After adjusting for patient characteristics (age, gender, Charlson Comorbidity Index Score, urbanization, and area of residence), tumor extent, treatment modalities (operation and adjuvant therapy), and hospital characteristics (ownership and teaching level), colorectal cancer, and head and neck cancer patients under 65 years old with low individual SES in disadvantaged neighborhoods conferred a 1.5 to 2-fold higher risk of mortality, compared with patients with high individual SES in advantaged neighborhoods. A cross-level interaction effect was found in lung cancer and breast cancer. Lung cancer and breast cancer patients less than 65 years old with low SES in advantaged neighborhoods carried the highest risk of mortality. Prostate cancer patients aged 65 and above with low SES in disadvantaged neighborhoods incurred the highest risk of mortality. There was no association between SES and mortality for cervical cancer and pancreatic cancer. Our findings indicate that cancer patients with low individual SES have the highest risk of mortality even under a universal health-care system. Public health strategies and welfare policies must continue to focus on this vulnerable group.
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