Santiago Rodriguez-Segade1,2, Javier Rodriguez3,4, Félix Camiña3, Luís Sanmartín-Portas5, Josefa Gerpe-Jamardo5, Marcos Pazos-Couselo6, Jose M García-López6, Manuela Alonso-Sampedro7,8, Arturo González-Quintela8, Francisco Gude7. 1. Department of Biochemistry and Molecular Biology, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain. ssegade@telefonica.net. 2. Clinical Biochemistry Laboratory, Complejo Hospitalario Universitario de Santiago, Travesía de la Choupana s/n, 15706, Santiago de Compostela, Spain. ssegade@telefonica.net. 3. Department of Biochemistry and Molecular Biology, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain. 4. Clinical Biochemistry Laboratory, Complejo Hospitalario Universitario de Santiago, Travesía de la Choupana s/n, 15706, Santiago de Compostela, Spain. 5. Primary Care Center, 36800, A-Estrada, Pontevedra, Spain. 6. Division of Endocrinology, Complejo Hospitalario Universitario de Santiago, Travesía de Conxo s/n, 15706, Santiago de Compostela, Spain. 7. Clinical Epidemiology Unit, Complejo Hospitalario Universitario de Santiago, Travesía de la Choupana s/n, 15706, Santiago de Compostela, Spain. 8. Division of Internal Medicine, School of Medicine, University of Santiago de Compostela, c/San Francisco n-1, 15782, Santiago de Compostela, Spain.
Abstract
AIMS: To investigate, in a sample of nondiabetic adults from a Spanish community, the differences between prediabetes as defined by HbA1c ("H-prediabetes") and by fasting plasma glucose (FPG) ("F-prediabetes") in regard to prevalence and the influence of potential risk factors, adjusting the latter for confounders. METHODS: A total of 1328 nondiabetic participants aged ≥ 18 years were classified as normoglycemic, H-prediabetic [HbA1c 5.7-6.4% (39-47 mmol/mol)] or F-prediabetic (FPG 5.6-6.9 mmol/L). Multivariable analyses were used to compare the impacts of risk factors on the prevalence of H-prediabetes, F-prediabetes and their conjunctive and disjunctive combinations ("HaF-prediabetes" and "HoF-prediabetes," respectively). RESULTS: Some 29.9% of participants were HoF-prediabetic, 21.7% H-prediabetic, 16.3% F-prediabetic and only 8.1% HaF-prediabetic. Whatever the definition of prediabetes, increasing age, fasting insulin and LDL cholesterol were each a risk factor after adjustment for all other variables. Increasing BMI and decreasing mean corpuscular hemoglobin (MCH) were additional risk factors for H-prediabetes; male sex and increasing uric acid for F-prediabetes and increasing BMI for HaF-prediabetes. The participants satisfying the compound condition "hypertension or hyperlipidemia or obesity or hyperuricemia" (59.9% of the whole study group) included 83.1% of all subjects with HoF-prediabetes. CONCLUSIONS: In this population, the most sensitive risk factor for detection of prediabetes was age, followed by fasting insulin, LDL cholesterol, BMI, MCH, male sex and uric acid, with differences depending on the definition of prediabetes. MCH, an indirect measure of erythrocyte survival, significantly influences the prevalence of HbA1c-defined prediabetes. This study suggests that screening of individuals with selected risk factors may identify a high proportion of prediabetic persons.
AIMS: To investigate, in a sample of nondiabetic adults from a Spanish community, the differences between prediabetes as defined by HbA1c ("H-prediabetes") and by fasting plasma glucose (FPG) ("F-prediabetes") in regard to prevalence and the influence of potential risk factors, adjusting the latter for confounders. METHODS: A total of 1328 nondiabetic participants aged ≥ 18 years were classified as normoglycemic, H-prediabetic [HbA1c 5.7-6.4% (39-47 mmol/mol)] or F-prediabetic (FPG 5.6-6.9 mmol/L). Multivariable analyses were used to compare the impacts of risk factors on the prevalence of H-prediabetes, F-prediabetes and their conjunctive and disjunctive combinations ("HaF-prediabetes" and "HoF-prediabetes," respectively). RESULTS: Some 29.9% of participants were HoF-prediabetic, 21.7% H-prediabetic, 16.3% F-prediabetic and only 8.1% HaF-prediabetic. Whatever the definition of prediabetes, increasing age, fasting insulin and LDL cholesterol were each a risk factor after adjustment for all other variables. Increasing BMI and decreasing mean corpuscular hemoglobin (MCH) were additional risk factors for H-prediabetes; male sex and increasing uric acid for F-prediabetes and increasing BMI for HaF-prediabetes. The participants satisfying the compound condition "hypertension or hyperlipidemia or obesity or hyperuricemia" (59.9% of the whole study group) included 83.1% of all subjects with HoF-prediabetes. CONCLUSIONS: In this population, the most sensitive risk factor for detection of prediabetes was age, followed by fasting insulin, LDL cholesterol, BMI, MCH, male sex and uric acid, with differences depending on the definition of prediabetes. MCH, an indirect measure of erythrocyte survival, significantly influences the prevalence of HbA1c-defined prediabetes. This study suggests that screening of individuals with selected risk factors may identify a high proportion of prediabetic persons.
Entities:
Keywords:
Community screening; FPG; HbA1c; Prediabetic phenotype; Prevention; Risk factors
Authors: Kate Junker; Claire M Buckley; Seán R Millar; Sinéad Flynn; Janas M Harrington; Patricia M Kearney; Ivan J Perry Journal: PLoS One Date: 2021-06-25 Impact factor: 3.240