Metabolic syndrome and related disorders · 2025
Lipid Accumulation Product Outperforms BMI and Waist Circumference in Metabolic Disorders.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Elsayed Doha, Al-Kuwari Mohammed, Naeim Janatul, Al-Marri Ali, Al-Thani Noof, Al-Mohannadi Haya, Al-Suliati Haya, Al-Ali Amna, Doi Suhail A
Аннотация
Background and Objective: Obesity is a global health issue intricately linked to metabolic syndrome (MetS), insulin resistance, and dyslipidemia. Anthropometric indices, particularly those measuring central obesity, have emerged as more reliable predictors of these metabolic disorders than general obesity indices such as body mass index (BMI). However, the relative predictive power of these indices remains debated, particularly across sexes. This study aimed to evaluate the discriminative performance of various anthropometric measures, including lipid accumulation product (LAP), BMI, waist circumference (WC), and visceral adiposity index (VAI), in predicting insulin sensitivity, β-cell function, MetS, and dyslipidemia using National Health and Nutritional Evaluation Survey III (NHANES III) data. Methods: A cross-sectional analysis of 3,706 adults from the NHANES III database was conducted. Anthropometric indices were compared against insulin sensitivity Homeostasis Model Assessment (HOMA)-S, β-cell function (HOMA-B), metabolic syndrome (MetS) status, and dyslipidemia. Receiver-operating characteristic (ROC) curves and linear regression models were used to identify thresholds for predicting metabolic abnormalities. Results: LAP emerged as the most discriminative index across all outcomes, outperforming BMI and WC, particularly in predicting insulin sensitivity and β-cell function in males. In females, BMI was superior in predicting β-cell function. VAI demonstrated the strongest association with dyslipidemia but was less effective in predicting insulin resistance. Conclusion: LAP significantly outperforms conventional anthropometric indices in identifying insulin resistance and MetS, highlighting its potential as a screening tool for cardiometabolic risk. Gender differences in the predictive abilities of these measures suggest that BMI may retain value in assessing β-cell function in females. VAI should be considered when screening for dyslipidemia but is less effective for insulin resistance.