English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Context and Objective. The purpose of this study was to determine optimal waist circumference (WC) cut-off values for the detection of multiple risk factor aggregation in individuals from Maracaibo, Venezuela. Participants and Methods. A total of 1,902 adult individuals of both genders belonging to MMSPS were included. Complete physical, laboratory, and anthropometric examination were done to evaluate Metabolic Syndrome (MS) components and insulin resistance. ROC curves were plotted for risk factor aggregation in order to assess WC cut-off point. Logistic regression models were constructed to assess risk factors associated with the WC. Results. There were 52.2% females and 47.8% males, with WC of  cm and  cm, respectively. ROC curves exhibited a WC cut-off point for women of 90.25 cm (68.4% sensitivity, 65.8% specificity) and 95.15 cm (71.1% sensitivity, 67.4% specificity) for men. HOMA2-IR and high blood pressure were associated with a WC over these cut-off points, as well as 2.5-fold risk increase for multiple risk factor aggregation (OR 2.56; CI 95%: 2.05–3.20; ). Conclusions. These population-specific WC cut-offs are readily applicable tools for detection of risk factor aggregation. Insulin resistance is closely associated with this definition of abdominal obesity, which may serve as a surrogate for its assessment.

Optimal Waist Circumference Cut-Off Point for Multiple Risk Factor Aggregation: Results from the Maracaibo City Metabolic Syndrome Prevalence Study