[Association between metabolic syndrome, socioeconomic status and quality of life in mexicans]. / Asociación entre síndrome metabólico, nivel socioeconómico y calidad de vida en mexicanos.

Background: In Mexico there is little information regarding the link between metabolic syndrome (MetS), socioeconomic status (SES) and quality of life (QoL). Objective: To assess the association between subjects who are at high risk of developing MetS with SES and QoL. Material and methods: Patients attending UMF-2 IMSS or Centro Urbano-SSA Clínica-1 were asked to participate. Anthropometric measures were collected, the AMAI, SF12, and ESF-I questionnaire where apply for SES, QoL, and MetS, respectively. Association were determined by calculating Spearman's rho and the risk (odds ratio and 95% confidence-interval) was assessed using logistic regression. Results: The difference of SES (193 ± 53 vs. 124 ± 50) and QoL (86.3 ± 14.8 vs. 56.0±25.4) questionnaires were significantly between low-risk and high-risk groups, respectively (p < 0.001). There was a negative correlation between ESF-I and SES (rho = -0.623, p < 0.001) as well as the QoL (rho = -0.719, p < 0.001). MetS risk was augmented by decreasing SES (C+: OR = 6.4, 95%IC: 3.2-13.0; D: OR = 66.1, 95%IC: 23.2-188.3), whereas increasing QoL attenuated it (OR = 0.93, 95%CI: 0.91-0.94). However, QoL mitigated the effect of SES (C+: OR = 4.5, 95%IC: 2.1-9.6; D: OR = 11.9, 95%IC: 3.8-37.6). Conclusions: Lower QoL and SES increased the risk of MetS in Central Mexico; however, improving the QoL can mitigated the effect SES has on developing MetS.

Introducción: en México existe escasa información respecto al vínculo entre el síndrome metabólico (MetS), el nivel socioeconómico (NSE) y la calidad de vida (CdV) de la población. Objetivo: evaluar la asociación entre sujetos que tienen alto riesgo de desarrollar MetS con NSE y CdV. Material y métodos: se invitó a participar a pacientes de la UMF-2 del IMSS y del Centro Urbano-SSA Clínica-1. Se recolectaron medidas antropométricas y se aplicaron los cuestionarios AMAI, SF12 y ESF-I para NSE, CdV y MetS, respectivamente. La asociación se determinó calculando rho de Spearman. El riesgo se evaluó mediante regresión logística (razon de momios e intervalo de confianza del 95%). Resultados: la diferencia entre NSE (193 ± 53 frente a 124 ± 50) y CdV (86.3 ± 14.8 frente a 56.0 ± 25.4) fue significativa entre los grupos de bajo y alto riesgo, respectivamente (p < 0.001). Hubo una fuerte correlación negativa entre las puntuaciones de la ESF-I y NSE (rho = -0.623, p < 0.001) así como con la CdV (rho = -0.719, p < 0.001). El riesgo de MetS aumentó al disminuir el NSE (C+: OR = 6.4, IC95%: 3.2 - 13.0; D: OR = 66.1, IC95%: 23.2 - 188.3), mientras que el aumento de la CdV lo atenuó (OR = 0.93, IC95%: 0.91 - 0.94). Interesantemente, la CdV mitigó el efecto del NSE (C+: OR = 4.5, IC95%: 2.1 - 9.6; D: OR = 11.9, IC95%: 3.8 - 37.6). Conclusión: Una menor CdV y NSE aumentan el riesgo de MetS en la región centro de México; sin embargo, el aumento en la CdV podría disminuir el efecto que tiene el NSE en el desarrollo de MetS.

Asociación entre síndrome metabólico, nivel socioeconómico y calidad de vida en mexicanos / Association between metabolic syndrome, socioeconomic status and quality of life in mexicans

Introducción: en México existe escasa información respecto al vínculo entre el síndrome metabólico (MetS), el nivel socioeconómico (NSE) y la calidad de vida (CdV) de la población. Objetivo: evaluar la asociación entre sujetos que tienen alto riesgo de desarrollar MetS con NSE y CdV. Métodos: se invitó a participar a pacientes de la UMF-2 del IMSS y del Centro Urbano-SSA Clínica-1. Se recolectaron medidas antropométricas y se aplicaron los cuestionarios AMAI, SF12 y ESF-I para NSE, CdV y MetS, respectivamente. La asociación se determinó calculando rho de Spearman. El riesgo se evaluó mediante regresión logística (razon de momios e intervalo de confianza del 95%). Resultados: la diferencia entre NSE (193  53 frente a 124  50) y CdV (86.3  14.8 frente a 56.0  25.4) fue significativa entre los grupos de bajo y alto riesgo, respectivamente (p < 0.001). Hubo una fuerte correlación negativa entre las puntuaciones de la ESF-I y NSE (rho = -0.623, p < 0.001) así como con la CdV (rho = -0.719, p < 0.001). El riesgo de MetS aumentó al disminuir el NSE (C+: OR = 6.4, IC95%: 3.2 - 13.0; D: OR = 66.1, IC95%: 23.2 - 188.3), mientras que el aumento de la CdV lo atenuó (OR = 0.93, IC95%: 0.91 - 0.94). Interesantemente, la CdV mitigó el efecto del NSE (C+: OR = 4.5, IC95%: 2.1 - 9.6; D: OR = 11.9, IC95%: 3.8 - 37.6). Conclusión: Una menor CdV y NSE aumentan el riesgo de MetS en la región centro de México; sin embargo, el aumento en la CdV podría disminuir el efecto que tiene el NSE en el desarrollo de MetS.

Background: In Mexico there is little information regarding the link between metabolic syndrome (MetS), socioeconomic status (SES) and quality of life (QoL) Objective: To assess the association between subjects who are at high risk of developing MetS with SES and QoL. Methods: Patients attending UMF-2 IMSS or Centro Urbano-SSA Clínica-1 were asked to participate. Anthropometric measures were collected, the AMAI, SF12, and ESF-I questionnaire where apply for SES, QoL, and MetS, respectively. Association were determined by calculating Spearman's rho and the risk (odds ratio and 95% confidence-interval) was assessed using logistic regression. Results: The difference of SES (193  53 vs. 124  50) and QoL (86.3  14.8 vs. 56.025.4) questionnaires were significantly between low-risk and high-risk groups, respectively (p < 0.001). There was a negative correlation between ESF-I and SES (rho = -0.623, p < 0.001) as well as the QoL (rho = -0.719, p < 0.001). MetS risk was augmented by decreasing SES (C+: OR = 6.4, 95%IC: 3.2-13.0; D: OR = 66.1, 95%IC: 23.2-188.3), whereas increasing QoL attenuated it (OR = 0.93, 95%CI: 0.91-0.94). However, QoL mitigated the effect of SES (C+: OR = 4.5, 95%IC: 2.1-9.6; D: OR = 11.9, 95%IC: 3.8-37.6).

Metabolic Age, an Index Based on Basal Metabolic Rate, Can Predict Individuals That are High Risk of Developing Metabolic Syndrome.

INTRODUCTION: Every 10 years, an adult's basal metabolic rate (BMR), independent of their BMI, decreases 1-2% due to skeletal muscle loss, thus decreasing an adult's energy requirement and promoting obesity. Increased obesity augments the risk of developing Metabolic Syndrome (MetS); however, an adult's healthy lifestyle, which increases BMR, can mitigate MetS development. To compare different BMRs for certain ages, Metabolic age (Met-age) was developed. AIM: To assess the association between Met-age and MetS and to determine if Met-age is an indicator of high-risk individuals for MetS. METHODS: Four hundred thirty-five attendees at 2 clinics agreed to participate and gave signed informed consent. MetS risk was assessed by the ESF-I questionnaire. Met-age was determined using a TANITA bio-analyzer. Strengthen of association was determined by calculating Spearman's rho and predictability was evaluated by the area-under-a-receiver-operating characteristic curve (AUC). Difference-in-age (DIA) = [chronological age - Met-age]. RESULTS: There was a difference between the low-risk (n = 155) and the high-risk (n = 280) groups' Met-age (37.8±16.7 v. 62.9±17.3) and DIA (1.3±17.4 v. - 10.5±20.8, p < 0.001). There was a positive correlation between the ESF-I questionnaire and Met-age (rho = - 0.624, p < 0.001) and a negative correlation for DIA (rho = - 0.358, p < 0.001). Met-age was strongly predictive (AUC = 0.84, 95% CI 0.80-0.88), suggesting a 45.5 years cutoff (sensitivity = 83.2%, specificity = 72.3%). DIA was a good predictor (AUC = 0.68, 95% CI 0.63-0.74) with a - 11.5 years cutoff (sensitivity = 52.5%, specificity = 82.8%). CONCLUSION: Met-age highly associated with and is an indicator of high-risk individuals for MetS. This would suggest that increases in Met-age are associated with augmented MetS severity, independent of the individual's chronological age.