The association of long-term trajectories of BMI, its variability, and metabolic syndrome: a 30-year prospective cohort study

Tongshuai Guo; Sirui Zheng; Tao Chen; Chao Chu; Jie Ren; Yue Sun; Yang Wang; Mingjun He; Yu Yan; Hao Jia; Yueyuan Liao; Yumeng Cao; Mingfei Du; Dan Wang; Zuyi Yuan; Duolao Wang; Jianjun Mu

doi:10.1016/j.eclinm.2024.102486

The association of long-term trajectories of BMI, its variability, and metabolic syndrome: a 30-year prospective cohort study

EClinicalMedicine. 2024 Feb 12:69:102486. doi: 10.1016/j.eclinm.2024.102486. eCollection 2024 Mar.

Authors

Tongshuai Guo¹, Sirui Zheng², Tao Chen³, Chao Chu¹, Jie Ren¹, Yue Sun¹, Yang Wang¹, Mingjun He¹, Yu Yan¹, Hao Jia¹, Yueyuan Liao¹, Yumeng Cao¹, Mingfei Du¹, Dan Wang¹, Zuyi Yuan¹, Duolao Wang², Jianjun Mu¹

Affiliations

¹ Department of Cardiology, First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, 710061, China.
² Biostatistics Unit, Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.
³ Centre for Health Economics, University of York, Heslington, York, YO10 5DD, UK.

Abstract

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 SD_BMI, VIM_BMI, and ARV_BMI: 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 SD_BMI, VIM_BMI, and ARV_BMI: 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).

Keywords: Body mass index; Body mass index trajectory; Body mass index variability; Central obesity; Metabolic syndrome.

Associated data

ClinicalTrials.gov/NCT02734472