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Summary: Background: Limited data exists on how early-life weight changes relate to metabolic syndrome (MetS) risk in midlife. This study examines the association between long-term trajectories of body mass index (BMI), its variability, and MetS risk in Chinese individuals. Methods: In the Hanzhong Adolescent Hypertension study (March 10, 1987–June 3, 2017), 1824 participants with at least five BMI measurements from 1987 to 2017 were included. Using group-based trajectory modeling, different BMI trajectories were identified. BMI variability was assessed through standard deviation (SD), variability independent of the mean (VIM), and average real variability (ARV). Logistic regression analyzed the relationship between BMI trajectory, BMI variability, and MetS occurrence in midlife (URL: https://www.clinicaltrials.gov; Unique identifier: NCT02734472). Findings: BMI trajectories were categorized as low-increasing (34.4%), moderate-increasing (51.8%), and high-increasing (13.8%). Compared to the low-increasing group, the odds ratios (ORs) [95% CIs] for MetS were significantly higher in moderate (4.27 [2.63–6.91]) and high-increasing groups (13.11 [6.30–27.31]) in fully adjusted models. Additionally, higher BMI variabilities were associated with increased MetS odds (ORs for SDBMI, VIMBMI, and ARVBMI: 2.30 [2.02–2.62], 1.22 [1.19–1.26], and 4.29 [3.38–5.45]). Furthermore, BMI trajectories from childhood to adolescence were predictive of midlife MetS, with ORs in moderate (1.49 [1.00–2.23]) and high-increasing groups (2.45 [1.22–4.91]). Lastly, elevated BMI variability in this period was also linked to higher MetS odds (ORs for SDBMI, VIMBMI, and ARVBMI: 1.24 [1.08–1.42], 1.00 [1.00–1.01], and 1.21 [1.05–1.38]). Interpretation: Our study suggests that both early-life BMI trajectories and BMI variability could be predictive of incident MetS in midlife. Funding: This work was supported by the National Natural Science Foundation of China No. 82070437 (J.-J.M.), the Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University of China (No. XJTU1AF-CRF-2022-002, XJTU1AF2021CRF-021, and XJTU1AF-CRF-2023-004), the Key R&D Projects in Shaanxi Province (Grant No. 2023-ZDLSF-50), the Chinese Academy of Medical Sciences & Peking Union Medical College (2017-CXGC03-2), and the International Joint Research Centre for Cardiovascular Precision Medicine of Shaanxi Province (2020GHJD-14).

Abstract Background Lipid management with a low-density lipoprotein cholesterol (LDL-C) goal of

Abstract Background The new visceral adiposity index (NVAI) was superior to previous obesity indices in predicting cardiovascular diseases among Asians. Nevertheless, the utility of the NVAI for predicting chronic kidney disease is still unclear. The objective of this research was to explore the relationship between the NVAI and subclinical renal damage (SRD) and to investigate whether the NVAI outperforms other common obesity indices in predicting SRD in the Chinese population. Methods Participants in this cross-sectional study were from the Hanzhong Adolescent Hypertension Cohort. The NVAI and seven other common obesity indices were calculated, including body mass index, waist circumference, lipid accumulation product, visceral adiposity index, Chinese visceral adiposity index, a body shape index and metabolic score for visceral fat. Logistic regression models revealed the association between NVAI and SRD. The odds ratio (OR) and the 95% confidence interval (CI) were calculated to show the association between the two variables. The predictive power of eight obesity indices for SRD was evaluated through the receiver operating characteristic curve and area under the curve (AUC). In addition, the net reclassification index (NRI) and integrated discrimination improvement (IDI) were also applied to compare the incremental predictive value for SRD of different obesity indices. Results The median age of the 2358 subjects was 42.00 years. Across NVAI tertiles, the prevalence of SRD was 7.25%, 11.21%, and 21.60%, respectively. After adjusting for confounders, a high level of NVAI remained a risk factor for SRD. The ORs of the middle and top NVAI tertiles for SRD were 1.920 (95% CI: 1.322, 2.787) and 4.129 (95% CI: 2.750, 6.202), respectively. The AUC of the NVAI was 0.666 (95% CI: 0.647, 0.685), which was significantly larger than the AUC of any of the other obesity indicators. Moreover, the NRI and IDI were significantly improved when NVAI was added to the basic model for predicting SRD. Among eight obesity indices, NVAI had the highest NRI (0.392; 95% CI: 0.280, 0.503), and its IDI (0.021; 95% CI: 0.014, 0.027) was second only to that of the body mass index (0.023; 95% CI: 0.014, 0.032). Conclusions NVAI is independently and positively associated with SRD. Among the eight obesity indices, the NVAI shows the strongest predictive power for SRD in the Chinese population. The NVAI may be useful as an effective warning indicator of chronic kidney disease in Chinese adults.