8765 Assessment of the Social Vulnerability Index of a 10-Year Retrospective Cohort of Youth with Prediabetes
Authors: Somerville Danielle , Kolagani Ramya H , McCrory Courtney E , Budakoti Shreshty , Chinchilli Vernon M , Joseph Joshua , Hale Daniel E , Raja-Khan Nazia , Saenz Lina Paola Huerta 
Published: October 2024

Disclosure: D. Somerville: None. R.H. Kolagani, MHS: None. C.E. McCrory: None. S. Budakoti: None. V.M. Chinchilli, PhD: None. J. Joseph: None. D.E. Hale: None. N. Raja-Khan: None. L.P. Huerta Saenz: None.

Background: The incidence of prediabetes (preD) is rising among youth in the US. While there are known metabolic risk factors linked to preD development, we were interested in exploring the role of social determinants of health (SDoH) in the development of pediatric preD. The social vulnerability index (SVI) is a tool developed by the CDC to stratify SDoH risk for communities based on 14 factors such socioeconomic status (SES), household composition, race and transportation access. By understanding the role of SVI in the development of preD in youth, we may be able to plan interventions to prevent progression to Type 2 Diabetes (T2D). Objective: Our study goal was to determine the relationship between SVI and preD in youth receiving care at our institution, a large pediatric referral center in Central Pennsylvania. Methods: We conducted a 10-year retrospective chart review of electronic medical records (EMRs) to identify children/youth aged 6-17 years old diagnosed with preD at our pediatric health system between 01/2010 and 01/2020. We used the American Diabetes Association definitions of preD (one or more sub-type): 1) Impaired fasting glucose (IFG), 2) Impaired glucose tolerance (IGT), and 3) Elevated hemoglobin A1c (HA1C). ICD10 codes were used for initial chart identification (R73.01, R73.02, R73.03 and R73.09). The second phase of identification of youth with preD included the review of biological measures of glycemia of the initial identified charts to support the reported ICD10 diagnosis (either isolated subtypes or combinations). Social, demographic characteristics, and residence setting (urban vs. rural) were also investigated. SVI was assessed on a 0-1 scale, with high SVI (0.5-1) indicating greater social vulnerability and low SVI (0-0.49) indicating lower social vulnerability. Rurality was determined per the Health Resources and Services Administration Tool (HRSA). SAS frequencies were calculated. Fisher’s exact tests were applied to compare the frequencies of the aforementioned groups with respect to IFG, IGT, and HA1C. Results: We identified 2700 charts of youth with preD per ICD10 codes search, but only 552 had confirmed preD diagnosis supported by biological data registered in EMRs. The most common preD isolated subtype was HA1C (87.3%), while 12% and 4% had isolated IFG and IGT, respectively. Most youth had high SVI (66.9%) and only 5.8% were rural (p &gt; 0.05). Neither SVI or rurality were associated with isolated preD subtypes, but 8.2% of low-SVI youth had composite [IFG +HA1C] subtypes compared to 3.5% of high-SVI youth (p=0.02). Conclusions: SVI was not significantly associated with any isolated preD subtype. However, youth with the combined preD subtypes [IFG + HA1C] had lower SVI. As T2D is more prevalent in youth from low SES, addressing SDoH at earlier stages of T2D (preD phase) is needed in the effort to prevent the progression of the disease.

Presentation: 6/1/2024