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1.
PLoS One ; 19(2): e0298662, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38394065

RESUMEN

BACKGROUND: The 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. METHODS: Data 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. RESULTS: Using 1,980 participants (96,282,896 weighted), there was a significant (p<0.001) correlation between USG CAP and TAFA (r = 0.569), VAT (r = 0.645), and SAT (r = 0.479). Additionally, the risk of developing NAFLD was observed for total abdominal obesity (OR = 19.9, 95%CI: 5.1-77.8, p<0.001), visceral obesity (OR = 9.1, 95%CI: 6.2-13.5, p<0.001) and subcutaneous obesity (OR = 4.8, 95%CI: 3.2-6.9, p<0.001). Using 866 participants (44,399,696 weighted), for visceral obesity, participants with MetS and visceral obesity (OR = 18.1, 95%CI: 8.0-41.3, p<0.001) were shown to have a greater risk than participants with MetS only (OR = 6.3, 95%CI: 2.6-15.2, p<0.001). For subcutaneous obesity, again, participants with MetS and subcutaneous obesity (OR = 18.3, 95%CI: 8.0-41.9, p<0.001) were shown to have a greater risk than the MetS-only group (OR = 10.3, 95%CI: 4.8-22.4, p<0.001). CONCLUSION: TAFA, 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.


Asunto(s)
Síndrome Metabólico , Enfermedad del Hígado Graso no Alcohólico , Humanos , Enfermedad del Hígado Graso no Alcohólico/complicaciones , Enfermedad del Hígado Graso no Alcohólico/epidemiología , Enfermedad del Hígado Graso no Alcohólico/metabolismo , Síndrome Metabólico/complicaciones , Síndrome Metabólico/epidemiología , Síndrome Metabólico/metabolismo , Estudios Transversales , Obesidad Abdominal/complicaciones , Obesidad Abdominal/epidemiología , Obesidad Abdominal/metabolismo , Encuestas Nutricionales , Obesidad/complicaciones , Grasa Abdominal/metabolismo , Grasa Intraabdominal/metabolismo
2.
Nutr Metab Cardiovasc Dis ; 33(9): 1725-1732, 2023 09.
Artículo en Inglés | MEDLINE | ID: mdl-37407310

RESUMEN

BACKGROUND AND AIMS: Hyperinsulinemia and hyperuricemia are known to increase the risk of mortality due to certain complications, such as Type 2 Diabetes and cardiovascular disease. However, despite their common comorbidities, their combined effect has not been evaluated. The study's aim was to evaluate the combine effect of hyperinsulinemia and hyperuricemia on all-cause mortality. METHODS AND RESULTS: NHANES datasets (cycles 2003-2018) were examined. Differences between groups were evaluated using Rao-Scott Chi-square and General Linear Model for categorical and continuous data, respectively. Hazard Ratios (HR) were calculated using Cox regression with 95% confidence intervals (95%CI). There was significant difference (p < 0.05) in the mortality rate between the control group (2.3 ± 0.2%), the hyperinsulinemia only group (3.1 ± 0.3%), the hyperuricemia only group (4.0 ± 0.8%), and both conditions (5.1 ± 0.8%). Individually, when compared to the control group, there was a significant increase in mortality risk for hyperinsulinemia (HR: 1.50, 95%CI: 1.12-2.01, p = 0.007) and hyperuricemia (HR: 1.80, 95%CI:1.18-2.75, p = 0.006). However, when both conditions were present, there appeared an additive effect in the mortality risk (HR: 2.32, 95%CI: 1.66-3.25, p < 0.001). When stratified by BMI class, only normal weight participants presented with a significant risk (HR: 7.00, 95%CI: 2.50-20.30, p < 0.001). Also, when stratified by age, only participants older than 40 years presented a risk (HR: 2.22, 95%CI: 1.56-3.16, p < 0.001). CONCLUSION: Alone, hyperuricemia and hyperinsulinemia significantly increased the mortality rate; however, the combined presence of both pathologies was associated with a significantly augmented mortality rate. Normal weight participant or that were >40 years old had a greater risk for mortality.


Asunto(s)
Enfermedades Cardiovasculares , Diabetes Mellitus Tipo 2 , Hiperinsulinismo , Hiperuricemia , Humanos , Adulto , Hiperuricemia/diagnóstico , Hiperuricemia/complicaciones , Diabetes Mellitus Tipo 2/complicaciones , Encuestas Nutricionales , Hiperinsulinismo/diagnóstico , Factores de Riesgo
3.
J Drug Assess ; 10(1): 97-105, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34676131

RESUMEN

OBJECTIVE: Receptor activator of NF-κß ligand (RANKL) is crucial for the development of hepatic insulin resistance and poor glucose uptake; therefore, inhibiting RANKL with Denosumab could improve fasting plasma glucose (FPG) and insulin (FPI). METHODS: A systematic review was conducted to evaluate the effects of Denosumab on glycemic parameters. PubMed, SCOPUS, EBSCO, and LILACS databases were searched for studies that investigated the effect of Denosumab on FPG, glycated hemoglobin (HbA1c), FPI, and Homeostatic Model Assessment for Insulin Resistance (HOMA1-IR). The pooled standard difference in means (SDM) and 95% confidence intervals (95%CI) were calculated. The results were stratified into (1) Normal Glucose Tolerance (NGT) and (2) Impaired Glucose Tolerance (IGT). RESULTS: Six publications (1203 participants) were included. There was a significant association between Denosumab and FPG (SDM = -0.388, 95%CI: -0.705 to -0.070, p = .017) and with HOMA1-IR (SDM = -0.223, 95%CI: -0.388 to -0.058, p = .008), but not for HbA1c and FPI. When stratified by glucose tolerance, the association between Denosumab and FPG, HbA1c, and HOMA1-IR was present for the IGT group. Lastly, Denosumab had a time-dependent effect on HbA1c (slope = -0.037, 95%CI: -0.059 to -0.015, p < .005). CONCLUSIONS: Denosumab significantly improved glycemic parameters. This outcome was more prominent for subjects with compromised glucose tolerance, positing that Denosumab can be used as a treatment to improve glucose metabolism for persons with pre-diabetes and diabetes.

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