Endocrinology & Metabolic Syndrome
Open Access
ISSN: 2161-1017
+44 1478 350008
ISSN: 2161-1017
+44 1478 350008
Akshita Narra
Scientific Tracks Abstracts: Endocrinol Metab Synd
Background: A quantifiable assessment of socio-economic status and its bearing on clinical outcome in patients with diabetes is lacking. The social adaptability index (SAI) has previously been validated in the general population and in patients with chronic kidney disease. We hypothesize that SAI could be used in diabetes practice to identify disadvantaged population at risk for inferior outcome. Methods: The NHANES-3 database of patients who have diabetes was analyzed. The association of the SAI (calculated as linear combination of education status, employment, income, marital status and substance abuse) with patient survival was evaluated using a Cox model. Results: The study population consisted of 1,634 subjects with diabetes mellitus with mean age 61.9±15.3 years; 40.9% males; 38.5% White, 27.7% African American, and 31.3% Mexican American. The highest SAI was in Whites (6.9±2.5), followed by Mexican Americans (6.5±2.3), and then African Americans (6.1±2.6) (ANOVA, p<0.001). SAI was higher in subjects living in metropolitan areas (6.8±2.6) compared to the rural population (6.3±2.4) (T-test, p<0.001). Also, SAI was greater in males (7.1±2.4) than in females (6.1±2.4) (T-test, p<0.001). SAI had significant association with survival (HR 0.9, p<0.001) in the entire study population and in most of the subgroups (divided by race, sex, and urban/rural location). Furthermore, SAI divided into tertiles (≤5, 6 to 8, >8) demonstrated a significant and ?dose-dependent? association with survival. Conclusion: Social adaptability index is associated with mortality in the diabetic population and is useful in identifying individuals who are at risk for inferior outcome.
Akshita Narra is a medical graduate from Dr. NTR University of health sciences, India. She is currently pursuing her residency in internal medicine at the University of Connecticut. Her areas of interest include studying the various health care disparities and their impact on outcomes and proposing possibilities to improve them.