Introduction: Americans with diabetes are clinically vulnerable to worse COVID-19 outcomes; thus, insight into how to prevent infection is imperative. Using longitudinal, prospective data from the real-world iNPHORM study, we identify the intrinsic and extrinsic risk factors of confirmed or probable COVID-19 in people with type 1 or 2 diabetes.
Methods: The iNPHORM study recruited 1206 Americans (18-90 years) with insulin- and/or secretagogue-treated type 1 or 2 diabetes from a probability-based internet panel. Online questionnaires (screener, baseline and 12 monthly follow-ups) assessed COVID-19 incidence and various plausible intrinsic and extrinsic factors. Multivariable Cox regression was used to model the rate of COVID-19 (confirmed or probable). Risk factors were selected using a repeated backwards-selection 'voting' procedure.
Results: A sub-sample of 817 iNPHORM participants (type 1 diabetes: 16.9%; age: 52.1 [SD: 14.2] years; female: 50.2%) was analysed between May 2020 and March 2021. During this period, 13.7% reported confirmed or probable COVID-19. Age, body mass index, number of chronic comorbidities, most recent A1C, past severe hypoglycaemia, and employment status were selected in our final model. Body mass index ≥30 kg/m2 versus <30 kg/m2 (HR 1.63 [1.05; 2.52]95% CI ), and increased number of comorbidities (HR 1.16 [1.05; 1.27]95% CI ) independently predicted COVID-19 incidence. Marginally significant effects were observed for overall A1C (p = .06) and employment status (p = .07).
Conclusions: This is the first US-based epidemiologic investigation to characterize community-based COVID-19 susceptibility in diabetes. Our results reveal specific and promising avenues to prevent COVID-19 in this at-risk population.
Clinicaltrials: gov Identifier: NCT04219514.
Keywords: COVID-19; diabetes mellitus; type 1; type 2.
© 2022 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.