Diabetes, a spectrum of metabolic diseases caused by deficits in insulin secretion, insulin action, or both, is one of the most common chronic diseases among adults, effecting over 30 million people in the United States in 2017. Using data from the National Health Interview Survey (NHIS), the CDC estimated that young adults ages 18-44 years account for ~ 3 million diagnosed diabetes cases and 1.6 million undiagnosed cases in the US in 2015, with 3.1/1,000 individuals in this age group developing diabetes each year. NHIS results are based on self-report of diagnosis date, insulin use, and diabetes type, which may not accurately assess diabetes status and type. In 2017, the Diabetes in Young Adult (DiYA) study estimated that the age- and sex- standardized diabetes incidence rate was 3.8/1,000 using information in electronic health records (EHR) of a racially/ethnically diverse population of over 2.1 million health plan members 18-44 years in California. Given that the incidence and prevalence of diabetes in US children and adolescents < 18 years continues to increase and there is minimal mortality among this age group, these increases will in part drive increases in prevalence of diabetes in young adults. A major challenge of diabetes surveillance in this age group is that most reported estimates of incidence and prevalence are not type-specific. Use of electronic health records (EHRs) allow for the assessment of type based on clinicians' determination and provides other clinical and demographic information such as pharmacological treatment, body mass index, age and race/ethnicity.
The Aims of this study are:
Aim 1 : To ascertain prevalent diabetes cases in calendar years 2020-2024 among young adults ages 18-44 years at diagnosis, using cost-efficient approaches that maximize use of information in the electronic health records (EHRs) and administrative databases.
Aim 2 : To ascertain newly diagnosed (incident 2020-2024) diabetes cases in young adults ages 18-44 years, using cost-efficient approaches that maximize use of EHRs and administrative data.
Aim 3 : To describe selected clinical characteristics at diagnosis and determine if these characteristics have changed over time. This study will be conducted in Kaiser Permanente Southern California (KPSC), an integrated health care system that has ~1.4 million members age 18-44 years in an 8-county area including Los Angeles county, the largest county in California. The racial/ethnic diversity of the membership, the wealth of clinical information in the EHR including diagnosis codes from inpatient, outpatient, and virtual care encounters; laboratory test results including diabetes autoantibodies (when ordered); dispensed prescriptions, height, weight, blood pressure, and patient reported outcomes that can be linked to demographic and membership data including health plan enrollment start and end dates, creates a robust platform for diabetes surveillance activities.
Diabetes is one of the most common chronic diseases among adults, effecting over 30 million people in the United States in 2017, with young adults ages 18-44 years accounting for ~ 3 million cases with limited information on diabetes type. Ongoing, efficient surveillance is essential to inform health care delivery systems and generate testable hypotheses related to the natural history of diabetes in this age group. The current study seeks to assess the long-term trends of the prevalence, incidence and early clinical characteristics of young adults with diabetes in our racially and ethnically diverse population to assist in the identification of sub- populations for focused efforts on diabetes prevention and reduction in co-morbidities.
