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The Combined Effect of Individual and Neighborhood Socioeconomic Status on Cancer Survival Rates

BACKGROUND: This population-based study investigated the relationship between individual and neighborhood socioeconomic status (SES) and mortality rates for major cancers in Taiwan. METHODS: A population-based follow-up study was conducted with 20,488 cancer patients diagnosed in 2002. Each patient...

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Detalles Bibliográficos
Autores principales: Chang, Chun-Ming, Su, Yu-Chieh, Lai, Ning-Sheng, Huang, Kuang-Yung, Chien, Sou-Hsin, Chang, Yu-Han, Lian, Wei-Cheng, Hsu, Ta-Wen, Lee, Ching-Chih
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3431308/
https://www.ncbi.nlm.nih.gov/pubmed/22957007
http://dx.doi.org/10.1371/journal.pone.0044325
Descripción
Sumario:BACKGROUND: This population-based study investigated the relationship between individual and neighborhood socioeconomic status (SES) and mortality rates for major cancers in Taiwan. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.