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Associations Between Socioeconomic Status and Major Complications in Type 1 Diabetes: The Pittsburgh Epidemiology of Diabetes Complication (EDC) Study
Open accessAbstract
Purpose To understand the effect of socioeconomic status (SES) on the risk of complications in type 1 diabetes (T1D), we explored the relationship between SES and major diabetes complications in a prospective, observational T1D cohort study.Methods Complete data were available for 317 T1D persons within 4 years of age 28 (ages 24-32) in the Pittsburgh Epidemiology of Diabetes Complications Study. Age 28 was selected to maximize income, education, and occupation potential and to minimize the effect of advanced diabetes complications on SES.Results The incidences over 1 to 20 years' follow-up of end-stage renal disease and coronary artery disease were two to three times greater for T1D individuals without, compared with those with a college degree (p < .05 for both), whereas the incidence of autonomic neuropathy was significantly greater for low-income and/or nonprofessional participants (p < .05 for both). HbA(1c) was inversely associated only with income level. In sex- and diabetes duration-adjusted Cox models, lower education predicted end-stage renal disease (hazard ratio [HR], 2.9; 95% confidence interval [95% CI], 1.1-7.7) and coronary artery disease (HR, 2.5, 95% CI, 1.3-4.9), whereas lower income predicted autonomic neuropathy (HR, 1.7; 95% CI, 1.0-2.9) and lower-extremity arterial disease (HR, 3.7; 95% CI, 1.1-11.9).Conclusions These associations, partially mediated by clinical risk factors, suggest that lower SES T1D individuals may have poorer self-management and, thus, greater complications from diabetes.
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“Several studies127–130 have identified additional non-glycaemic risk factors for the development of complications.”
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“Low levels of education and income have been associated with high risks of both micro-vascular and macrovascular complications.127”
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Citations
Cites
Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes
(2005) · New England Journal of Medicine · doi:10.1056/nejmoa052187 · Cited by 5,138
Cardiovascular Survey Methods.
Rose, G., & Blackburn, H. (1968) · Annals of Internal Medicine · doi:10.7326/0003-4819-69-6-1335_2 · Cited by 3,090
Winkleby, M. A., Jatulis, D. E., Frank, E., & Fortmann, S. P. (1992) · American Journal of Public Health · doi:10.2105/ajph.82.6.816 · Cited by 2,048
Socioeconomic factors and cardiovascular disease: a review of the literature.
Kaplan, G. A., & Keil, J. E. (1993) · Circulation · doi:10.1161/01.cir.88.4.1973 · Cited by 1,845
NATIONAL TRENDS IN EDUCATIONAL DIFFERENTIALS IN MORTALITY
Feldman, J. J., Makuc, D. M., Kleinman, J. C., & Cornoni‐Huntley, J. C. (1989) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a115225 · Cited by 610
Measuring Socioeconomic Status
Cirino, P. T., Chin, C. E., Sevcik, R. A., Wolf, M., Lovett, M. W., & Morris, R. D. (2002) · Assessment · doi:10.1177/10791102009002005 · Cited by 394
The hypertension detection and follow-up program
Hypertension detection and follow-up program cooperative group (1976) · Preventive Medicine · doi:10.1016/0091-7435(76)90039-6 · Cited by 348
Risk Factors for Development of Incipient and Overt Diabetic Nephropathy in Type 1 Diabetic Patients
Rossing, P. R., Hougaard, P., & Parving, H. (2002) · Diabetes Care · doi:10.2337/diacare.25.5.859 · Cited by 243
Warnick, G. R., & Albers, J. J. (1978) · Clinical Chemistry · doi:10.1093/clinchem/24.6.900 · Cited by 179
The combat exposure scale: A systematic assessment of trauma in the vietnam war
Lund, M., Foy, D. W., Sipprelle, C. N., & STRACHAN, A. M. (1984) · Journal of Clinical Psychology · doi:10.1002/1097-4679(198411)40:6 · Cited by 150
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Sorted by citations
Items 101–144 of 144
Uddin, J., Uddin, H., Rahman, M., Saha, P., Hossin, M. Z., Hajizadeh, M., & Kirkland, S. (2023) · Public Health · doi:10.1016/j.puhe.2023.06.041 · Cited by 4
Ray, M. K., Fleming, J., Aschenbrenner, A. J., Hassenstab, J. J., Redwine, B., Burns, C., Arbeláez, A. M., Vajravelu, M. E., & Hershey, T. G. (2024) · JMIR Formative Research · doi:10.2196/60275 · Cited by 3
Zuijdwijk, C., Pendsey, S., Ron, J., Williams, K., Akiki, S., Chalkhore, S., Ogle, G. D., & Ahmet, A. H. (2017) · Journal of Diabetology · doi:10.4103/jod.jod_3_17 · Cited by 3
Schmitt, V. H., Hobohm, L., Hahad, O., Sivanathan, V., Schmidt, F. P., Münzel, T. F., Lurz, P. C., Gori, T., & Keller, K. (2025) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2025.103201 · Cited by 3
Omigbile, O., Adebayo, O., Emmanuel, A., Eyitayo, L., Beatrice, O., & Mayaki, T. B. (2023) · IntechOpen eBooks · doi:10.5772/intechopen.108180 · Cited by 3
Glycemic control and sponsor rank of military dependents with type 1 diabetes mellitus
Paz, R., Rouhanian, M., & Vogt, K. S. (2015) · Pediatric Diabetes · doi:10.1111/pedi.12306 · Cited by 3
Walker, A. F., Schatz, D., Silverstein, J. H., Parker, K. A., Aponick, A. U., & Rohrs, H. J. (2013) · ICAN Infant Child & Adolescent Nutrition · doi:10.1177/1941406413500526 · Cited by 4
Diabetic Nephropathy Determinant Factor in Diabetes Mellitus at RSUD Dr. M. Soewandhie Surabaya
Putri, R. I. (2015) · Jurnal Berkala Epidemiologi · doi:10.20473/jbe.v3i1.2015.109-121 · Cited by 2
Gianvecchio, C., Cabas, J., Perez, D., & Semidey, K. (2023) · Cureus · doi:10.7759/cureus.39306 · Cited by 2
Soliman, Y., Everett, K., Shulman, R. M., Austin, P. C., Lipscombe, L. L., Booth, G. L., & Weisman, A. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16547 · Cited by 2
Physical Problems among Children and Adolescents Complain of Diabetes Type I in Erbil City.
Ahmed, K., Saleem, S., & Tofeeq, R. (2017) · kufa journal for nursing sciences · doi:10.36321/kjns.vi20163.2675 · Cited by 2
¿Qué variables se asocian con un buen control metabólico en pacientes con diabetes tipo 1?
Laureano, F. C. S., Gutierrez‐Manzanedo, J. V., Ortega, C. A., & Aguilar‐Diosdado, M. (2013) · Avances en Diabetología · doi:10.1016/j.avdiab.2013.02.002 · Cited by 2
Lord, J., & Odoi, A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0298182 · Cited by 3
Devaraj, S. M., Miller, R. G., Orchard, T. J., Kriska, A. M., Gary‐Webb, T. L., & Costacou, T. (2021) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2021.108016 · Cited by 3
Self-citationAssociation Between Psychosocial Acuity and Glycemic Control in a Pediatric Type 1 Diabetes Clinic
Wardell, J., Albright, D. K., Chang, C., Plegue, M. A., Lee, J. E., Hirschfeld, E., Garrity, A. N., Lee, J. M., & DeJonckheere, M. J. (2024) · The Science of Diabetes Self-Management and Care · doi:10.1177/26350106241232634 · Cited by 1
Yassin, M. M., Laqqan, M. M., Mwafy, S. N., & El-qreenawy, S. I. (2024) · Middle East Fertility Society Journal · doi:10.1186/s43043-023-00150-w · Cited by 1
Demographic Predictors of Elevated LDL Cholesterol in Type 1 Diabetes: A Cross-Sectional Study
Dart, M. E., Patrie, J. T., & Love, K. M. (2024) · Clinical Diabetes · doi:10.2337/cd24-0051 · Cited by 1
Pierre-Jerome, C. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-99352-4.00009-7 · Cited by 1
Nasir, D., Hatim, A., Bourkha, M. E. A., Bеid, S. Е., & Ez-ziymy, S. (2024) · Procedia Computer Science · doi:10.1016/j.procs.2024.05.052 · Cited by 1
Miller, F. G., Anderson, M., Tucker, D. R., Vaz, K., Brown, J. G., Anderson-Jackson, L., & McGrowder, D. A. (2020) · Advances in medical diagnosis, treatment, and care (AMDTC) book series · doi:10.4018/978-1-7998-2139-7.ch007 · Cited by 1
Rochmah, N., Faizi, M., Hisbiyah, Y., Triastuti, I. W., Wicaksono, G., Endaryanto, A., & Soetjipto, S. (2021) · Indian Journal of Forensic Medicine & Toxicology · doi:10.37506/ijfmt.v15i4.17006 · Cited by 1
Ambler, G. R., Cameron, F. J., Joshi, K., & Wherrett, D. K. (2019) · Wiley eBooks · doi:10.1002/9781119152712.ch15 · Cited by 1
Epidemiology of Type 1 Diabetes Complications in African-Americans
Washington, R. (2012) · D-Scholarship@Pitt (University of Pittsburgh)
Epidemiological studies of childhood diabetes and important health complications to the disease
Berhan, Y. T. (2014) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Experiential Learning and Sports Bring Self-Management Skills Alive for Kids with Diabetes
Beebe, C., Joyce, M., Alesia, T., Aschkenasy, J. R., & Davis, V. (2017) · AADE in Practice · doi:10.1177/2325160317729188
Lohiya, N. N., Khadilkar, V. V., Chiplonkar, S. A., & Khadilkar, A. V. (2019) · Indian Journal of Child Health · doi:10.32677/ijch.2019.v06.i08.005
de Oliveira, L. I. M., Salamaia, E. M., dos Santos, G. T., & Kohara, S. K. (2021) · Arquivos Catarinenses de Medicina · doi:10.63845/54bcsg41
Healthcare utilization & disparities in pediatric diabetes care during COVID-19
Dimentstein, K., Valenzuela, J. M., Yee, S. T., Pan, B., Snyder, M. C. N., & Wolf, R. M. (2024) · Children s Health Care · doi:10.1080/02739615.2024.2317325
Onwukwe, O., & Lundgrin, E. L. (2024) · Frontiers in Clinical Diabetes and Healthcare · doi:10.3389/fcdhc.2024.1304577
Bell, M. J., & Neff, O. T. (2024) · Sociology of Health & Illness · doi:10.1111/1467-9566.13814 · Cited by 1
The peripheral nervous system: peripheral neuropathies in the diabetic foot
Pierre-Jerome, C. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13328-2.00022-2
Razon, A. H., Biswas, S., Hossain, S., Khatun, A., Sagufta, J. F., Barsha, T. S., & Zohra, F. (2025) · Public Health and Toxicology · doi:10.18332/pht/205877
Nationwide study of income-based disparities in diabetic limb preservation in South Korea
Lee, Y. J., Han, K., & Kim, J. H. (2025) · Scientific Reports · doi:10.1038/s41598-025-27511-x · Cited by 1
Building a Foundation for Diabetes Clinical Behavioral Research with Incarcerated Persons
Reagan, L. (2014) · OpenCommons at University of Connecticut (University of Connecticut)
Vo, U. G., Gilfillan, M., Hamilton, E. J., Manning, L., Munshi, B., Hiew, J., Norman, P. E., & Ritter, J. C. (2021) · Figshare · doi:10.6084/m9.figshare.14385525
Vo, U. G., Gilfillan, M., Hamilton, E. J., Manning, L., Munshi, B., Hiew, J., Norman, P. E., & Ritter, J. C. (2021) · Figshare · doi:10.6084/m9.figshare.14385528
Saeed, M., Stene, L. C., Ariansen, I., Tell, G. S., Tapia, G., Joner, G., & Skrivarhaug, T. (2022) · Figshare · doi:10.6084/m9.figshare.19670198
Effectiveness of Using Patient-Defined Meal Sizes to Determine Bolus Doses of Insulin
Davidson, M. B., Scarlett, L., Duran, P. A., JENNE, K. W., Shinn, P., & Woodcock, E. (2026) · Diabetes Obesity and Cardiometabolic CARE · doi:10.2337/doc25-0018
Yu, Q., Kong, Z., Shi, Q., Cheng, C. K., Zhang, J., & Nie, J. (2026) · Journal of Diabetes Investigation · doi:10.1111/jdi.70322
Palermo, L., Senga, J., Fakembe, P., Zhu, X., Walsh, C., Leslie, B., Shulman, R. M., Presseau, J., Dogba, M. J., Banerjee, A., et al. (2026) · Diabetes Obesity and Metabolism · doi:10.1111/dom.70819
Implementing a Social Needs Screening and Intervention Program at a Pediatric Diabetes Center
Relan, S., DeWit, E., EVANS, K., Manaskie, M., Roghair, J., Feingold, H., JACOB, S. N., Winterer, C. M., Colvin, J. D., Clements, M. A., et al. (2026) · Quality Management in Health Care · doi:10.1097/qmh.0000000000000577
Metadata
- Authors
- Secrest, A. M., Costacou, T., Gutelius, B., Miller, R. G., Songer, T. J., & Orchard, T. J.
- Affiliations
- University of Pittsburgh (US)
- New York City Department of Health and Mental Hygiene (US)
- Corresponding author
- Orchard, Trevor J.
- Venue
- Annals of Epidemiology
- Publisher
- Elsevier BV
- Published
- 2011-05
- Volume
- 21
- Issue
- 5
- Pages
- 374-381
- ISSN
- 1047-2797 (ISSN-L)
- PMC
- PMC3079455
- OpenAlex
- W2148414695
- Cited by
- 144
- References
- 27
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 12 · 2023: 7 · 2022: 11 · 2021: 15 · 2020: 13 · 2019: 12 · 2018: 13 · 2017: 9 · 2016: 7 · 2015: 12 · 2014: 7 · 2013: 7 · 2012: 9
- FWCI
- 6.03
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annals of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (R37DK034818, R01DK034818, F30DK082137)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Social Sciences › Health › Health disparities and outcomes
- Keywords
- type 1 diabetes, socioeconomic status, diabetes complications, end-stage renal disease, coronary artery disease, autonomic neuropathy, lower extremity arterial disease, educational attainment, income, HbA1c, diabetes self-management, Pittsburgh Epidemiology of Diabetes Complications Study
- MeSH terms
- Adolescent, Adult, Diabetes Mellitus, Type 1, Employment, Female, Humans, Male, Pennsylvania, Prospective Studies, Social Class, Cohort Studies, Confidence Intervals, Diabetes Complications, Young Adult
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