[Association between metabolic syndrome, socioeconomic status and quality of life in mexicans]

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.

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.