Abstract
ObjectiveThe purposes of the study were to investigate the detailed association of serum uric acid (SUA) with visceral fat area (VFA) and body fat percentage (BFP) as calculated by bioelectrical impedance analysis (BIA) and build non-invasive diagnosis models of hyperuricaemia by combining obesity-related indicators, age and sex.MethodA total of 19 343 adults were included. Multivariable regression analysis models were employed to analyse the association of SUA with VFA and BFP. Receiver operating characteristic curves were generated to diagnose hyperuricaemia in adults.ResultsAfter fully adjusting for covariates, SUA was positively associated with VFA, BFP and body mass index (BMI) with βs of 0.447, 2.522 and 4.630 (95% CI= (0.412 to 0.482), (2.321 to 2.723) and (4.266 to 4.994)). After stratification by gender, this association persists (p<0.001). Fitted smoothing curves identified non-linear relationships between SUA and both VFA and BMI after full adjustment in males (inflection points: 93.9 cm2and 30.9 kg/m2). A non-linear relationship also exists between SUA and BFP in females (inflection point: 34.5%). A combined model incorporating BFP, BMI, age and sex exhibited the best ability to diagnose hyperuricaemia (AUC (area under the curve) =0.805, specificity=0.602, sensitivity=0.878). For normal-weight and lean populations, individuals with hyperuricaemia tended to have higher levels of VFA and BFP in females and males, respectively (p<0.001). The combination of VFA, BFP, BMI, age and sex exhibited the best ability to diagnose hyperuricaemia in normal-weight and lean populations (AUC=0.803, specificity=0.671, sensitivity=0.836).ConclusionVFA and BFP are independent factors associated with SUA. In males, SUA shows a non-linear relationship with VFA and BMI. In females, SUA and BFP exhibit a non-linear relationship. In normal-weight and lean individuals, the accumulation of VFA and BFP may be involved in hyperuricaemia. VFA and BFP were helpful in diagnosing hyperuricaemia in adults, especially for normal-weight and lean populations.
Funder
the Health Science and Technology Development Major Project of Nanjing