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1.
Cardiovasc Diabetol ; 21(1): 225, 2022 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-36320060

RESUMO

BACKGROUND: Waist circumference (WC), visceral adiposity index (VAI), lipid accumulation product (LAP), and Chinese visceral adiposity index (CVAI) are considered surrogate indicators of abdominal fat deposition, but the longitudinal association of these indices with cardiovascular (CV) events in adults with type 2 diabetes (T2D) remains unclear. Our study aimed to examine the associations between abdominal obesity indices and incident CV events among people with T2D and to compare their predictive performance in risk assessment. METHODS: The present study included 2328 individuals with T2D from the Xinjiang Multi-Ethnic Cohort. Multivariable Cox regression analyses were applied to assess the associations between abdominal obesity indices and CV events. Harrell's concordance statistic (C-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index were utilized to evaluate the predictive performance of each abdominal obesity index. RESULTS: At a median follow-up period of 59 months, 289 participants experienced CV events. After multivariable adjustment, each 1-SD increase in WC, VAI, LAP, and CVAI was associated with a higher risk of CV events in people with T2D, with adjusted hazard ratios (HRs) being 1.57 [95% CI (confidence interval): 1.39-1.78], 1.11 (95% CI 1.06-1.16), 1.46 (95% CI 1.36-1.57), and 1.78 (95% CI 1.57-2.01), respectively. In subgroup analyses, these positive associations appeared to be stronger among participants with body mass index (BMI) < 25 kg/m2 compared to overweight/obese participants. As for the predictive performance, CVAI had the largest C-statistic (0.700, 95% CI 0.672-0.728) compared to VAI, LAP, WC, and BMI (C-statistic: 0.535 to 0.670, all P for comparison < 0.05). When the abdominal obesity index was added to the basic risk model, the CVAI index also showed the greatest incremental risk stratification (C-statistic: 0.751 vs. 0.701, P < 0.001; IDI: 4.3%, P < 0.001; NRI: 26.6%, P < 0.001). CONCLUSIONS: This study provided additional evidence that all abdominal obesity indices were associated with the risk of CV events and highlighted that CVAI might be a valuable abdominal obesity indicator for identifying the high risk of CV events in Chinese populations with T2D. These results suggest that proactive assessment of abdominal obesity could be helpful for the effective clinical management of the diabetic population.


Assuntos
Doenças Cardiovasculares , Diabetes Mellitus Tipo 2 , Adulto , Humanos , Obesidade Abdominal , Diabetes Mellitus Tipo 2/epidemiologia , Estudos Prospectivos , Adiposidade , Obesidade , Índice de Massa Corporal , Estudos de Coortes , Doenças Cardiovasculares/complicações , China/epidemiologia , Fatores de Risco
2.
Artigo em Inglês | MEDLINE | ID: mdl-35983006

RESUMO

Background: There are few reports on the relationship between dietary patterns and cardiovascular disease (CVD) risk in patients with type 2 diabetes (T2D). This study aimed to explore relationships between dietary patterns and CVD risk in the T2D population using multiple statistical analysis methods. Methods: A total of 2,984 patients with T2D from the Xinjiang Multi-Ethnic Cohort, 555 of whom were suffering from CVD, were enrolled in this study. Participants' dietary intake was measured by the semiquantitative food frequency questionnaire (FFQ). Three statistical methods were used to construct dietary patterns, including principal component analysis (PCA) method, reduced-rank regressions (RRR) method, and partial least-squares regression (PLS) method. Then, the association between dietary patterns and CVD risk in T2D patients was analyzed by logistic regression. After excluding participants with CVD, the associations between dietary patterns and 10-year CVD risk scores were subsequently evaluated to reduce reverse causality. Results: In this study, four dietary patterns were identified by three methods. Adjustment for confounding factors, subjects with the highest scores on the "high-protein and high-carbohydrate" patterns derived from PCA, RRR, and PLS had higher odds of CVD than those with the lowest scores (OR: 2.89, 95% CI: 2.11-3.96, P trend < 0.001; OR: 2.96, 95% CI: 2.17-4.03, P trend < 0.001; OR: 2.01, 95% CI: 1.50-2.70, P trend < 0.001, respectively). However, the dietary pattern of PCA-prudent was not significantly related to the odds of having CVD in T2D patients (adjusted ORQ4vsQ1: 0.93, 95% CI: 0.70-1.24, P trend =0.474). Interestingly, we also found significant associations between "high-protein and high-carbohydrate" patterns and the elevated predicted 10-year CVD risk in T2D patients (all P trend < 0.05). Conclusion: The positive correlation between "high-protein and high-carbohydrate" patterns and CVD risk in T2D patients was robust across all three data-driven approaches. These findings may have public health significance, encouraging an emphasis on food choices in the usual diet and promoting nutritional interventions for patients with T2D to prevent CVD.

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