Ingesta dietética e índices antropométricos en estudiantes de medicina mexicanos, estratificados por historia familiar de Diabetes Tipo 2

Introduction: Our aim was to evaluate the dietary intake and anthropometric indices in medical students with positive family history of type 2 diabetes (FH-T2D)(+) and without FH-T2D(-).Material and methods: 144 students were analyzed in this cross-sectional, observational study, conducted during the 2017-2018 school year using interviews and 7-day food diary. The participants were characterized anthropometrically. Waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR), corrected mid-arm muscle area (MAMA), fat arm index (FAI), and tricipital skinfold (TSF) were calculated. Results: we found that 79.2% (95%CI: 72.5- 85.8) had FH-T2D. BMI was significantly higher in the participants with FH-T2D than without (23.7±3.8 v 25.0±3.7, respectively, p<0.05). No significant differences were determined in the indices based on central fat distribution (WHtR and WHR), peripheral distribution (FAI and TSF), or muscle mass (MAMA), when stratified by FH-T2D. Regarding dietary intake, when comparing participants with and without FH-T2D, respectively, we observed low/none legume consumption [30% (95%CI: 21.4-38.2) vs 23% (95%CI: 8.2-38.5)], diets high in proteins [38.6% (95%CI: 29.7-47.5) vs 46.7% (95%CI: 28.8-64.5)], low in carbohydrates [84.2% (95%CI: 77.5-90.9) vs 83.3% (95%CI: 70.0-96.7)], and insufficient energy intake [64% (95%CI: 55.2-72.8) vs 56.7% (95%CI: 38.9-74.4)], where the alterations in the dietary pattern were more detrimental for the FH-T2D(+) group. Lastly, the participants with FH-T2D consumed mainly late in the day [60% (95%CI: 50.6-68.6) vs 54% (95%CI: 35.5-71.2)].Conclusions: Even though there were minimal significant differences with the consumption by food categories, those students with FH-T2D presented with a poor, little varied and unbalanced dietary pattern with energy consumption mainly at night. These factors, if prolonged, could increase the risk of developing type 2 diabetes.Introducción: Nuestro objetivo fue evaluar la ingesta dietética y los índices antropométricos en estudiantes de medicina con historia familiar positiva de diabetes tipo 2 (FH-T2D)(+) y sin antecedentes familiares FH-T2D(-).Material y métodos: 144 estudiantes fueron analizados en este estudio transversal y observacional realizado durante el año escolar 2017-2018 mediante entrevistas y un diario de alimentos de 7 días. Los participantes se caracterizaron antropométricamente. Se calculó el ínidce cintura-cadera (WHR) y el índice cintura-altura (WHtR), el área muscular corregida de la mitad del brazo (MAMA), el índice de grasa del brazo (FAI) así como el pliegue cutáneo tricipital (TSF).Resultados:El 79,2% (95%CI: 72,5- 85,8) tenían FH-T2D. El IMC fue significativamente mayor en los participantes con FH-T2D que en aquellos sin FH-T2D (23,7 ± 3,8 v 25,0 ± 3,7, respectivamente, p <0,05). No se determinaron diferencias significativas en los índices basados en la distribución de grasa central (WHtR y WHR), la distribución periférica (FAI y TSF) o la masa muscular (MAMA), cuando se estratificó por FH-T2D. Al comparar la ingesta dietética de participantes con y sin FH-T2D, respectivamente, observamos un consumo bajo / ninguno de leguminosas [30% (95%CI: 21,4-38,2) frente a 23% (95%CI: 8,2-38,5)], dietas altas en proteínas [38,6% (95%CI: 29,7-47,5) frente a 46,7% (95%CI: 28,8-64,5)], bajas en carbohidratos [84,2% (95%CI: 77,5-90,9) frente a 83,3% (95%CI: 70,0-96,7)], y la ingesta de energía insuficiente [64% (95%CI: 55,2-72,8) frente a 56,7% (95%CI: 38,9-74,4)], donde las alteraciones en el patrón de la dieta fueron más perjudiciales para el grupo FH-T2D(+). Los participantes con FH-T2D consumieron al final del día [60% (95%CI: 50,6-68,6) frente a 54% (95%CI: 35,5-71,2)].Conclusiones: Aunque hubo diferencias mínimas significativas con el consumo por categorías de alimentos, aquellos estudiantes con FH-T2D presentaron un patrón dietético deficiente, poco variado y desequilibrado con un consumo de energía principalmente por la noche. Estos factores, si se prolongan, podrían aumentar el riesgo de desarrollar diabetes tipo 2

Ingesta dietética e índices antropométricos en estudiantes de medicina mexicanos, estratificados por historia familiar de diabetes tipo 2

Introduction: Our aim was to evaluate the dietary intake and anthropometric indices in medical students with positive family history of type 2 diabetes (FH-T2D)(+) and without FH-T2D(-). Material and Methods: 144 students were analyzed in this cross-sectional, observational study, conducted during the 2017-2018 school year using interviews and 7-day food diary. The participants were characterized anthropometrically. Waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR), corrected mid-arm muscle area (MAMA), fat arm index (FAI), and tricipital skinfold (TSF) were calculated. Results: We found that 79.2% (95%CI:72.5–85.8) had FH-T2D. BMI was significantly higher in the participants with FH-T2D than without (23.7±3.8 vs. 25.0±3.7, respectively; p<0.05). No significant differences were determined in the indices based on central fat distribution (WHtR and WHR), peripheral distribution (FAI and TSF), or muscle mass (MAMA), when stratified by FH-T2D. Regarding dietary intake, when comparing participants with and without FH-T2D, respectively, we observed low/none legume consumption [30% (95%CI:21.4–38.2) vs. 23% (95%CI:8.2–38.5)], diets high in proteins [38.6% (95%CI:29.7–47.5) vs. 46.7% (95%CI:28.8–64.5)], low in carbohydrates [84.2% (95%CI:77.5–90.9) vs. 83.3% (95%CI:70.0–96.7)], and insufficient energy intake [64% (95%CI:55.2–72.8) vs. 56.7% (95%CI:38.9–74.4)], where the alterations in the dietary pattern were more detrimental for the FH-T2D(+) group. Lastly, the participants with FH-T2D consumed mainly late in the day [60% (95%CI:50.6–68.6) vs. 54% (95%CI:35.5–71.2)]. Conclusions: Even though there were minimal significant differences with the consumption by food categories, those students with FH-T2D presented with a poor, little varied and unbalanced dietary pattern with energy consumption mainly at night. These factors, if prolonged, could increase the risk of developing type 2 diabetes.Introducción: Nuestro objetivo fue evaluar la ingesta dietética y los índices antropométricos en estudiantes de medicina con historia familiar positiva de diabetes tipo 2 (FH-T2D)(+) y sin antecedentes familiares FH-T2D(-). Material y métodos: 144 estudiantes fueron analizados en este estudio transversal y observacional realizado durante el año escolar 2017-2018 mediante entrevistas y un diario de alimentos de 7 días. Los participantes se caracterizaron antropométricamente. Se calculó el ínidce cintura-cadera (WHR) y el índice cintura-altura (WHtR), el área muscular corregida de la mitad del brazo (MAMA), el índice de grasa del brazo (FAI) así como el pliegue cutáneo tricipital (TSF). Resultados:El 79,2% (95%CI: 72,5- 85,8) tenían FH-T2D. El IMC fue significativamente mayor en los participantes con FH-T2D que en aquellos sin FH-T2D (23,7 ± 3,8 v 25,0 ± 3,7, respectivamente, p <0,05). No se determinaron diferencias significativas en los índices basados en la distribución de grasa central (WHtR y WHR), la distribución periférica (FAI y TSF) o la masa muscular (MAMA), cuando se estratificó por FH-T2D. Al comparar la ingesta dietética de participantes con y sin FH-T2D, respectivamente, observamos un consumo bajo / ninguno de leguminosas [30% (95%CI: 21,4-38,2) frente a 23% (95%CI: 8,2-38,5)], dietas altas en proteínas [38,6% (95%CI: 29,7-47,5) frente a 46,7% (95%CI: 28,8-64,5)], bajas en carbohidratos [84,2% (95%CI: 77,5-90,9) frente a 83,3% (95%CI: 70,0-96,7)], y la ingesta de energía insuficiente [64% (95%CI: 55,2-72,8) frente a 56,7% (95%CI: 38,9-74,4)], donde las alteraciones en el patrón de la dieta fueron más perjudiciales para el grupo FH-T2D(+). Los participantes con FH-T2D consumieron al final del día [60% (95%CI: 50,6-68,6) frente a 54% (95%CI: 35,5-71,2)]. Conclusiones: Aunque hubo diferencias mínimas significativas con el consumo por categorías de alimentos, aquellos estudiantes con FH-T2D presentaron un patrón dietético deficiente, poco variado y desequilibrado con un consumo de energía principalmente por la noche. Estos factores, si se prolongan, podrían aumentar el riesgo de desarrollar diabetes tipo 2

The use of insulin-like growth factor 1 improved the parameters of the seminogram in a patient with severe oligoasthenoteratozoospermia

Male patients suffering from oligoasthenoteratozoospermia typically failed to achieve pregnancy, even with assisted reproductive technologies. Growth hormone and insulin-like growth factor 1 have been shown to regulate sperm quality parameters; therefore, the insulin-like growth factor 1 supplement could improve sperm parameters. Here, we determine the effect insulin-like growth factor 1 has on sperm parameters in a patient suffering from oligoasthenoteratozoospermia. A 47-year-old male was administered once a day 1.5 IU of insulin-like growth factor 1 by intradermal injection for 2 months. Seminogram analysis was performed before and after. Treatment with insulin-like growth factor 1 resulted in a 15.5-fold improvement in sperm concentration (1.1 × 10 6 vs 18.3 × 10 6 per mL), 71.4% change in volume (0.7 vs 1.2 mL), increased progressive motility (2% vs 43%), and the total volume of sperm with progressive motility (0% vs 23.6%). Here, we show that administering a daily dose of insulin-like growth factor 1 can improve sperm quality parameters

Visceral and subcutaneous abdominal fat is associated with non-alcoholic fatty liver disease while augmenting Metabolic Syndrome's effect on non-alcoholic fatty liver disease: A cross-sectional study of NHANES 2017-2018.

BackgroundThe aim was to evaluate the effect different types of abdominal fat have on NAFLD development and the effects of abdominal fat has on the association between Metabolic Syndrome (MetS) and NALFD.MethodsData was collected from the cross-sectional NHANES dataset (2017-2018 cycle). Using the controlled attenuation parameter (USG CAP, dB/m), which measures the level of steatosis, the cohort was stratified into two groups: NAFLD(+) (≥274 dB/m) and NAFLD(-). Using complex samples analyses, associations between liver steatosis or NAFLD and types of abdominal fat area [Total abdominal (TAFA), subcutaneous (SAT), and visceral (VAT)] were determined. Pearson's correlation coefficient (r) was calculated to evaluate the associations between adipose tissues and NAFLD. Logistic regression was used to determine the risk [odds ratio (OR) and 95% confidence interval (95%CI)]. Participants were also classified by MetS, using the Harmonizing Definition criteria.ResultsUsing 1,980 participants (96,282,896 weighted), there was a significant (pConclusionTAFA, VAT, and SAT were positively associated with USG CAP values and increased the risk of developing NAFLD. Also, the type of abdominal fat depots did affect the association between MetS and NAFLD

Validation of a non-laboratorial questionnaire to identify Metabolic Syndrome among a population in central Mexico

Objective. To determine the reliability of a non-laboratorial questionnaire, the Encuesta de Identificación de Sujetos Metabólicamente Comprometidos en Fase-I (ESF-I) for identifying Metabolic Syndrome among a population in central Mexico. Methods. Clinical and biochemical parameters were collected for 232 participants from 1 June 2012 – 31 August 2013. Three definitions of Metabolic Syndrome (Harmonizing, National Cholesterol Education Program Expert Panel and Adult Treatment Panel III [ATPIII], and International Diabetes Federation [IDF]) were used to allocate subjects to either the normal or Metabolic Syndrome positive (MetS+) group. The predictability of the questionnaire was determined by the Area-Under-the-Receiver-Operating Characteristic curve (AUC). Youden's index was calculated and the highest score was considered the optimal cutoff value. Cohen´s kappa (κ) was calculated to determine the level of agreement between the ESF-I questionnaire (max score: 15 based on 15 items) and Metabolic Syndrome. Results. From 53.8% – 60.7% of the participants were determined to be MetS+. The average questionnaire score was significantly higher in the MetS+ group for each definition (4.0 vs. 8.0, P < 0.05). The ESF-I questionnaire was predictive for the Harmonizing definition (AUC = 0.841, 95%CI: 0.790 – 0.892), the ATPIII definition (AUC = 0.827, 95%CI: 0.774 – 0.880), and the IDF definition (AUC = 0.836, 95%CI: 0.785 – 0.887). A cutoff value of 7 was determined for each definition; therefore, the cohort was re-categorized based on questionnaire results. There was a strong agreement between the ESF-I questionnaire and MetS (Harmonizing: accuracy = 77.6%, κ = 0.554; ATPIII: accuracy = 74.1%, κ = 0.489; IDF: accuracy = 74.6%, κ = 0.495, P < 0.001). Conclusion. The ESF-I questionnaire can identify MetS+ patients, and therefore, lead to earlier diagnoses, reduced number of consultations, and lower costs with easier application

Flowchart for the selection of study participants.

Flowchart for the selection of study participants.</p

Linear regression between USG CAP and type of abdominal fat depots and BMI.

Linear regression between USG CAP and type of abdominal fat depots and BMI.</p

Univariate and multivariate logistic regression analysis for the presence of NAFLD.

Univariate and multivariate logistic regression analysis for the presence of NAFLD.</p

Linear regression between USG CAP and components of MetS.

Linear regression between USG CAP and components of MetS.</p