scholarly journals Addressing Factors Associated with Arab Women's Socioeconomic Status May Reduce Breast Cancer Mortality: Report from a Well Resourced Middle Eastern Country

2015 ◽  
Vol 16 (15) ◽  
pp. 6303-6309 ◽  
Author(s):  
Tam Truong Donnelly ◽  
Al-Hareth Al Khater ◽  
Mohamed Ghaith Al Kuwari ◽  
Salha Bujassoum Al-Bader ◽  
Mariam Abdulmalik ◽  
...  
Medicine ◽  
2016 ◽  
Vol 95 (31) ◽  
pp. e4335 ◽  
Author(s):  
Theodora M. Ripping ◽  
Danielle van der Waal ◽  
André L.M. Verbeek ◽  
Mireille J.M. Broeders

2018 ◽  
Vol 8 (2) ◽  
pp. 75-98 ◽  
Author(s):  
Diana Prieto ◽  
Milton Soto-Ferrari ◽  
Rindy Tija ◽  
Lorena Peña ◽  
Leandra Burke ◽  
...  

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yazmin San Miguel ◽  
Scarlett Lin Gomez ◽  
James D. Murphy ◽  
Richard B. Schwab ◽  
Corinne McDaniels-Davidson ◽  
...  

2019 ◽  
Author(s):  
Yazmin San Miguel ◽  
Scarlett Lin Gomez ◽  
James D. Murphy ◽  
Richard B. Schwab ◽  
Corinne McDaniels-Davidson ◽  
...  

Abstract Purpose We assessed breast cancer mortality in older versus younger women according to race/ethnicity, neighborhood socioeconomic status (nSES), and health insurance status. Methods The study included female breast cancer cases 18 years of age and older, diagnosed between 2005 and 2015 in the California Cancer Registry. Multivariable Cox proportional hazards modeling was used to generate hazard ratios (HR) of breast cancer specific deaths and 95% confidence intervals (CI) for older (60+ years) versus younger (<60 years) patients separately by race/ethnicity, nSES, and health insurance status. Results Risk of dying from breast cancer was higher in older than younger patients after multivariable adjustment, which varied in magnitude by race/ethnicity (P-interaction<0.0001). Comparing older to younger patients, higher mortality differences were shown for non-Hispanic white (HR=1.43; 95% CI, 1.36-1.51) and Hispanic women (HR=1.37; 95% CI, 1.26-1.50) and lower differences for non-Hispanic blacks (HR=1.17; 95% CI, 1.04-1.31) and Asians/Pacific Islanders (HR=1.15; 95% CI, 1.02-1.31). HRs comparing older to younger patients varied by insurance status (P-interaction<0.0001), with largest mortality differences observed for privately insured women (HR=1.51; 95% CI, 1.43-1.59) and lowest in Medicaid/military/other public insurance (HR=1.18; 95% CI, 1.10-1.26). No age differences were shown for uninsured women. HRs comparing older to younger patients were similar across nSES strata. Conclusion Our results provide evidence for the continued disparity in black-white breast cancer mortality, which is magnified in younger women. Moreover, insurance status continues to play a role in breast cancer mortality, with uninsured women having the highest risk for breast cancer death, regardless of age.


2021 ◽  
Vol 4 (10) ◽  
pp. e2131020
Author(s):  
Timothy J. Robinson ◽  
Lauren E. Wilson ◽  
P. Kelly Marcom ◽  
Melissa Troester ◽  
Charles F. Lynch ◽  
...  

2014 ◽  
Vol 21 (3) ◽  
pp. 418 ◽  
Author(s):  
R. Dent ◽  
A. Valentini ◽  
W. Hanna ◽  
E. Rawlinson ◽  
E. Rakovitch ◽  
...  

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 1566-1566 ◽  
Author(s):  
Anees B. Chagpar ◽  
Mario Coccia

1566 Background: Reducing breast cancer mortality is a key healthcare challenge worldwide. We sought to determine the impact of macro-socioeconomic factors on breast cancer age-standardized incidence (ASI) and mortality-per-incident case (MPI) in LMICs. Methods: Data regarding breast cancer ASI and mortality in 78 LMICs were obtained from IARC/WHO. MPI was defined as the age standardized mortality divided by the ASI. Country-level socioeconomic data were obtained from World Bank, UN Development Project, and WHO data sources. Results: In 2018, the median ASI for breast cancer was 26.5 (range; 5-67.3) per 100,000 population in LMICs, with a median MPI of 50.6% (range 27-70%). ASI and MPI were inversely correlated (Spearman rho = -0.236, p = 0.044). Factors associated with ASI and MPI are shown in the table below. We found no factor could discriminate between the highest and lowest quartile in terms of ASI. However, all (except health expenditure as a % of GDP) were significantly different between the highest and lowest quartile in terms of MPI. Conclusions: Results suggest considerable variation in terms of breast cancer MPI within LMICs. Improved rates are seen with increasing GDP, literacy, contraceptive use, and provision of doctors and mammography, but overall % GDP expended on public health does not seem to significantly influence breast cancer MPI. [Table: see text]


Sign in / Sign up

Export Citation Format

Share Document