Trajectories of lipid profile during adolescence and risk of subclinical atherosclerosis in early adulthood: a two-decade population-based study

Abstract Background/Introduction Recent studies have shown the highest burdens of premature cardiovascular diseases (CVDs) in the Middle-eastern, and North Africa (MENA) region. The role of dyslipidemia, as a major metabolic disturbance, in the progression of subclinical atherosclerosis and subsequently premature CVDs, indicated by carotid intima-media thickness (cIMT), must not be overlooked, specifically in young adults. Purpose To examine the impact of early-life lipid profile trajectories in adolescence on subclinical atherosclerosis, evidenced by cIMT in adulthood. Methods In this trajectory analysis, with 1006 participants (472 male, mean age=14.72±3.23 years), latent class growth modeling, particularly Group-based multi-trajectory modeling (GBMTM) was used to analyze the heterogeneity in the longitudinal lipid alterations (total cholesterol [TC], triglycerides [TG], high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], and non-HDL-C). The trajectories were named based on direction (rising/decreasing) and slopes of the associated trends in lipid alterations (stable/ slow/ rapid). The association between lipid trajectories, and cIMT values, both as continuous and categorical variables, were evaluated using multivariate regression analysis adjusted for age, sex, body mass index, and systolic blood pressure at the baseline, as well as antihypertensive and lipid-lowering drug use, smoking, physical activity, and desired lipid parameter at the nearest survey to cIMT measurement. Results During a median follow-up of 17.6 years, the "Rising" trajectories of TC, TG, LDL-C, and non-HDL-C were linked to elevated cIMT values (in the fully-adjusted model beta-coefficients [βs]=0.08 [-0.01,0.14], 0.11 [0.05,0.17], 0.13 [0.05,0.21], and 0.12 [0.06,0.18], respectively). The "Rapid-Rising" trajectories of TG, LDL-C, and non-HDL-C notably amplified the risk (in the fully-adjusted model odds ratios (OR)=2.05 [1.46-2.75], 1.99 [1.35-2.92], and 2.02 [1.45-2.77], respectively). Conversely, the "Decreasing" trajectories of TC, LDL-C, and TG were associated with lower cIMT measures (βs =-0.09 [-0.16,-0.03], -0.11 [-0.17,-0.01], and -0.08 [-0.14,-0.02], respectively); also "Decreasing" trajectories of TC and LDL-C lowered the risk by at least 30% in the fully-adjusted model (ORs=0.59 [0.39-0.81] and 0.68 [0.41-1.02], respectively). While HDL-C "Rapid-Decreasing" trajectory doubled the risk of elevated cIMT (OR=1.98 [1.47-2.68]). Conclusion The findings showed the unfavorable trajectory alterations in all lipid parameters were significantly associated with higher cIMT values, underscoring the need for sustained efforts to monitor lipid levels from early adolescence.