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Perspective from NHANES Data: Synergistic Effects of Visceral Adiposity Index and Lipid Accumulation Products on Diabetes Risk

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Journal Sci Rep
Specialty Science
Date 2025 Jan 2
PMID 39747273
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Abstract

This study aimed to explore the synergistic effect of lipid accumulation product (LAP) and visceral adiposity index (VAI) on diabetes risk, and to evaluate the potential associations of these novel metabolic markers with diabetes. The current cross-sectional survey utilised data from the 2015-2018 National Health and Nutrition Examination Survey (NHANES). The relationship between LAP and VAI levels and diabetes was examined using multiple logistic regression analysis. Moreover, threshold effects analysis and smoothed curve fitting were used as analytical techniques. The diabetes group exhibited significantly higher LAP (90.1 ± 84.1) and VAI (2.8 ± 2.8) levels compared to the non-diabetes group (p < 0.0001).After adjusting for confounding factors, LAP (OR = 1.01, 95% CI: 1.00-1.01, p < 0.0001) and VAI (OR = 1.22, 95% CI: 1.16-1.28, p < 0.0001) were independently associated with diabetes risk. The interaction term (LAP x VAI) showed a significant synergistic effect (OR = 1.01, 95% CI: 1.00-1.07, p = 0.0042).Diabetes risk significantly increased when LAP was below 97.70 (OR = 1.03, 95% CI: 1.02-1.03, p < 0.0001) and when VAI was below 3.76 (OR = 1.88, 95% CI: 1.69-2.08, p < 0.0001). According to this study, LAP and VAI are independent predictors of diabetes risk and exhibit a significant synergistic effect. Combining these indices may improve the accuracy of diabetes screening.

References
1.
Al-Qudah S, Kasabri V, Saleh M, Suyagh M, AlAlawi S, Yasin N . Cross-sectional correlates of nesfatin and lipopolysaccharide binding protein in metabolic syndrome patients with and without prediabetes. Horm Mol Biol Clin Investig. 2018; 36(3). DOI: 10.1515/hmbci-2018-0035. View

2.
Al-Batsh M, Albsoul-Younes A, Kasabri V, Suyagh M, AlAlawi S, Yasin N . Proportional correlates of cystatin-C with pentraxin-3, visceral adiposity index and atherogenicity index of plasma but not blood indices in metabolic syndrome patients with and without prediabetes. Horm Mol Biol Clin Investig. 2018; 36(3). DOI: 10.1515/hmbci-2018-0058. View

3.
Acheampong E, Adua E, Obirikorang C, Anto E, Peprah-Yamoah E, Obirikorang Y . Predictive modelling of metabolic syndrome in Ghanaian diabetic patients: an ensemble machine learning approach. J Diabetes Metab Disord. 2024; 23(2):2233-2249. PMC: 11599523. DOI: 10.1007/s40200-024-01491-7. View

4.
Rattanatham R, Tangpong J, Chatatikun M, Sun D, Kawakami F, Imai M . Assessment of eight insulin resistance surrogate indexes for predicting metabolic syndrome and hypertension in Thai law enforcement officers. PeerJ. 2023; 11:e15463. PMC: 10234272. DOI: 10.7717/peerj.15463. View

5.
Deng H, Hu P, Li H, Zhou H, Wu X, Yuan M . Novel lipid indicators and the risk of type 2 diabetes mellitus among Chinese hypertensive patients: findings from the Guangzhou Heart Study. Cardiovasc Diabetol. 2022; 21(1):212. PMC: 9571423. DOI: 10.1186/s12933-022-01660-z. View