Literature DB >> 27367969

Association Between Socioeconomic Status and Mortality, Cardiovascular Disease, and Cancer in Patients With Type 2 Diabetes.

Araz Rawshani1, Ann-Marie Svensson2, Björn Zethelius3, Björn Eliasson4, Annika Rosengren1, Soffia Gudbjörnsdottir2.   

Abstract

IMPORTANCE: The association between socioeconomic status and survival based on all-cause, cardiovascular (CV), diabetes-related, and cancer mortality in type 2 diabetes has not been examined in a setting of persons with equitable access to health care with adjustment for important confounders.
OBJECTIVE: To determine whether income, educational level, marital status, and country of birth are independently associated with all-cause, CV, diabetes-related, and cancer mortality in persons with type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS: A study including all 217 364 individuals younger than 70 years with type 2 diabetes in the Sweden National Diabetes Register (January 1, 2003, to December 31, 2010) who were monitored through December 31, 2012, was conducted. A Cox proportional hazards regression model with up to 17 covariates was used for analysis. MAIN OUTCOMES AND MEASURES: All-cause, CV, diabetes-related, and cancer mortality.
RESULTS: Of the 217 364 persons included in the study, mean (SD) age was 58.3 (9.3) years and 130 839 of the population (60.2%) was male. There were a total of 19 105 all-cause deaths with 11 423 (59.8%), 6984 (36.6%), and 6438 (33.7%) CV, diabetes-related, or cancer deaths, respectively. Compared with being single, hazard ratios (HRs) for married individuals, determined using fully adjusted models, for all-cause, CV, and diabetes-related mortality were 0.73 (95% CI, 0.70-0.77), 0.67 (95% CI, 0.63-0.71), and 0.62 (95% CI, 0.57-0.67), respectively. Marital status was not associated with overall cancer mortality, but married men had a 33% lower risk of prostate cancer mortality compared with single men, with an HR of 0.67 (95% CI, 0.50-0.90). Comparison of HRs for the lowest vs highest income quintiles for all-cause, CV, diabetes-related, and cancer mortality were 1.71 (95% CI, 1.60-1.83), 1.87 (95% CI, 1.72-2.05), 1.80 (95% CI, 1.61-2.01), and 1.28 (95% CI, 1.14-1.44), respectively. Compared with native Swedes, HRs for all-cause, CV, diabetes-related, and cancer mortality for non-Western immigrants were 0.55 (95% CI, 0.48-0.63), 0.46 (95% CI, 0.38-0.56), 0.38 (95% CI, 0.29-0.49), and 0.72 (95% CI, 0.58-0.88), respectively, and these HRs were virtually unaffected by covariate adjustment. Hazard ratios for those with a college/university degree compared with 9 years or less of education were 0.85 (95% CI, 0.80-0.90), 0.84 (95% CI, 0.78-0.91), and 0.84 (95% CI, 0.76-0.93) for all-cause, CV, and cancer mortality, respectively. CONCLUSIONS AND RELEVANCE: Independent of risk factors, access to health care, and use of health care, socioeconomic status is a powerful predictor of all-cause and CV mortality but was not as strong as a predictor of death from cancer.

Entities:  

Mesh:

Year:  2016        PMID: 27367969     DOI: 10.1001/jamainternmed.2016.2940

Source DB:  PubMed          Journal:  JAMA Intern Med        ISSN: 2168-6106            Impact factor:   21.873


  40 in total

Review 1.  Insights into the relationships between diabetes, prediabetes, and cancer.

Authors:  Lorenzo Scappaticcio; Maria Ida Maiorino; Giuseppe Bellastella; Dario Giugliano; Katherine Esposito
Journal:  Endocrine       Date:  2016-12-31       Impact factor: 3.633

2.  Glioma incidence and survival variations by county-level socioeconomic measures.

Authors:  David J Cote; Quinn T Ostrom; Haley Gittleman; Kelsey R Duncan; Travis S CreveCoeur; Carol Kruchko; Timothy R Smith; Meir J Stampfer; Jill S Barnholtz-Sloan
Journal:  Cancer       Date:  2019-06-17       Impact factor: 6.860

Review 3.  How poverty affects diet to shape the microbiota and chronic disease.

Authors:  Christy A Harrison; Douglas Taren
Journal:  Nat Rev Immunol       Date:  2017-11-07       Impact factor: 53.106

4.  The Hispanic Paradox in Patients With Liver Cirrhosis: Current Evidence From a Large Regional Retrospective Cohort Study.

Authors:  Kofi Atiemo; Nikhilesh R Mazumder; Juan C Caicedo; Daniel Ganger; Elisa Gordon; Samantha Montag; Haripriya Maddur; Lisa B VanWagner; Satyender Goel; Abel Kho; Michael Abecassis; Lihui Zhao; Daniela Ladner
Journal:  Transplantation       Date:  2019-12       Impact factor: 4.939

5.  Long working hours and depressive symptoms: moderating effects of gender, socioeconomic status, and job resources.

Authors:  Kanami Tsuno; Ichiro Kawachi; Akiomi Inoue; Saki Nakai; Takumi Tanigaki; Hikaru Nagatomi; Norito Kawakami
Journal:  Int Arch Occup Environ Health       Date:  2019-03-12       Impact factor: 3.015

6.  Associations of Neighborhood Socioeconomic Disadvantage With Chronic Conditions by Age, Sex, Race, and Ethnicity in a Population-Based Cohort.

Authors:  Alanna M Chamberlain; Jennifer L St Sauver; Lila J Finney Rutten; Chun Fan; Debra J Jacobson; Patrick M Wilson; Cynthia M Boyd; Walter A Rocca
Journal:  Mayo Clin Proc       Date:  2022-01       Impact factor: 7.616

7.  Wealth-Associated Disparities in Death and Disability in the United States and England.

Authors:  Lena K Makaroun; Rebecca T Brown; L Grisell Diaz-Ramirez; Cyrus Ahalt; W John Boscardin; Sean Lang-Brown; Sei Lee
Journal:  JAMA Intern Med       Date:  2017-12-01       Impact factor: 21.873

8.  Opportunities for Improving Population Health in the Post-COVID-19 Era.

Authors:  Utibe R Essien; Giselle Corbie-Smith
Journal:  J Hosp Med       Date:  2021-01       Impact factor: 2.960

9.  Continuous Glucose Monitoring for Underserved and Minority Patients with Type 2 Diabetes in an Interprofessional Internal Medicine Clinic.

Authors:  Arden Bui; Jennifer Kim
Journal:  Innov Pharm       Date:  2020-12-03

10.  Mortality rates and cardiovascular disease burden in type 2 diabetes by occupation, results from all Swedish employees in 2002-2015.

Authors:  Sofia Carlsson; Tomas Andersson; Mats Talbäck; Maria Feychting
Journal:  Cardiovasc Diabetol       Date:  2021-06-26       Impact factor: 9.951

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.