Affiliation:
1. Faculty of Nursing, Universidad Autónoma de Nuevo León, Monterrey, Mexico
2. Centro de Investigaciones en Materiales Avanzados Unidad Monterrey, Apodaca, Mexico
3. Faculty of Economics, Universidad Autónoma de Nuevo León, Monterrey, Mexico
4. Faculty of Medicine, Universidad Autónoma de Nuevo León, Monterrey, Mexico
Abstract
Objectives: Type 2 diabetes mellitus studies focus on metabolic indicators and different self-reported lifestyle or care behaviors. Self-reported instruments involve conscious process therefore responses might not reflect reality. Meanwhile implicit responses involve automatic, unconscious processes underlying social judgments and behavior. No studies have explored the combined influence of both metabolic indicators and implicit responses on lifestyle practices in type 2 diabetes mellitus patients. The purpose was to investigate the explained variance of socio-demographic, metabolic, anthropometric, clinical, psychosocial, cognitive, and lifestyle variables on glycemic status and on the ability to adapt to changing demands in people with and without type 2 diabetes mellitus in Monterrey, Mexico. Methods: Adults with (n = 30, mean age 46.90 years old, 33.33% male) and without (n = 32, mean age: 41.69 years old, 21.87% male) type 2 diabetes mellitus were studied. Glycemic status was assessed using Bio-Rad D-10 Hemoglobin A1c Program, which uses ion-exchange high-performance chromatography. Stroop 2 test was used to assess the ability to changing demands. Results: In participants with type 2 diabetes mellitus, less years of education, negative self-actualization, and higher levels of cholesterol and triglycerides explained more than 50% of the variance in glycemic status. In participants without type 2 diabetes mellitus, the variance (38.7%) was explained by total cholesterol, metabolic syndrome, high-density lipoprotein, and self-actualization scores; the latter in opposite direction. The ability to adapt to changing demands was explained by total cholesterol, malondialdehyde, insulin resistance, and triglycerides. In participants without type 2 diabetes mellitus, the contributing variables were metabolic syndrome and nutrition scores. Conclusion: Results showed significant effect on at least one of the following variables (socio-demographic, metabolic, or lifestyle subscale) on glycemic status in people with and without type 2 diabetes mellitus. The ability to adapt to changing demands was explained by metabolic variables but only in participants without type 2 diabetes mellitus. Preference for unhealthy behaviors (implicit or automatic responses) outweighs healthy lifestyle practices in people with and without type 2 diabetes mellitus.
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