This was a longitudinal retrospective cohort study that included subjects 20 years or older who underwent comprehensive health examinations including echocardiography between January 2008 and July 2016, at the Health Promotion Center at Samsung Medical Center (SMC, Seoul, Republic of Korea). The study population consisted of employees of various organizations and companies and subjects who voluntarily took part in annual or biennial comprehensive health screening examinations at the center. Of 9,809 patients who had two or more echocardiograms, those with fewer than three lipid measurements during the 5 years preceding the first echocardiogram and those who had missing data were excluded from the analyses (n=5,801). We also excluded subjects with indicators of early diastolic dysfunction that met the criteria of the primary endpoint, moderate to severe heart valve disease, and left ventricular ejection fraction (LVEF) less than 50% on the first echocardiogram (n=852). Subjects with a clinical diagnosis of heart failure, a history of ischemic heart disease, cardiomyopathy, valvulopathy, and chronic atrial fibrillation at baseline were excluded (n=144). We also excluded subjects with estimated glomerular filtration rate less than 60 mL/min/1.73 m² at the time of the first echocardiography (n=38), as calculated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula, and those with any history of cancer (n=157). A total of 2,817 subjects was included in the final study population (Fig. 1). The study protocol was approved by the Institutional Review Board (IRB) of SMC (no. 2020-06-076), and the informed consent requirement was waived by the IRB because the study information was de-identified. The protocol for the study was in accordance with the guidelines of the Declaration of Helsinki.

Medical history, smoking status, alcohol status, exercise status, medication, anthropometric data, and laboratory data were collected during routine health examinations. Subjects completed self-administered questionnaires that covered their prior medical history, prescribed medications, smoking, and exercise history. Smoking status was categorized as never, past smoker, or current smoker. Exercise status was assessed as none or regular exercise (≥3 days/week). Body mass index (BMI) was calculated as body weight divided by height squared (kg/m²). Blood pressure was measured using a mercury sphygmomanometer after at least 5 minutes of rest in a sitting position. Blood samples were collected after a 12-hour overnight fast. Plasma TC, TG, HDL-C, and LDL-C were measured using a Modular D2400 analyzer (Roche Diagnostics, Basel, Switzerland). ApoB level was measured by the immunoturbidimetric method using a Roche/Hitachi Modular P analyzer (Roche Diagnostics). Non-HDL-C was calculated by subtracting HDL-C from TC. Fasting plasma glucose (FPG) and insulin levels were measured using the hexokinase method with Bayer Reagent Packs on an automated chemistry analyzer (Advia 1650 Autoanalyzer, Bayer Diagnostics, Leverkusen, Germany) and an immunoradiometric assay (DIAsource Co., Louvain-la-Neuve, Belgium), respectively. The N-terminal fragment of pro-brain natriuretic peptide was determined using an Elecsys proBNP reagent kit and an Elecsys 2010 chemistry analyzer (Roche Diagnostics, Indianapolis, IN, USA). Glycosylated hemoglobin (HbA1c) level was determined by high-performance liquid chromatography on an HLC-723G8 automated glycohemoglobin analyzer (TOSOH, Yokkaichi, Japan). Hypertension was defined as blood pressure ≥140/90 mm Hg or use of antihypertensive medication [12]. Diabetes mellitus (DM) was defined as FPG of 126 mg/dL or greater, HbA1c of 6.5% or greater, or current use of diabetes medication [13].

The mean, standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV) of each lipid parameter were calculated from three to six consecutive measurements of LDL-C, TC, HDL-C, TG, and non-HDL-C during the 5 years preceding the first echocardiogram (three measurements, n=1,183; four measurements, n=679; five measurements, n=752; six measurements, n=203). Only the measurements during the 5 years preceding the first echocardiogram, but not those during the follow-up period, were included in the calculation of variability parameters. CV was defined as SD divided by the mean ×100, as described previously [14,15], VIM was calculated as SD divided by mean to the power χ (SD/mean^χ), where χ is derived from curve fitting via nonlinear regression analysis as implemented in the PROC NLIN procedure of the SAS package (SAS Institute Inc., Cary, NC, USA). ARV was the average of the absolute differences between consecutive values and was calculated using the following formula, where N denotes the number of measurements of the lipid profile [1].

For 1,061 of 2,817 subjects in whom three or more apoB measurements during the 5 years preceding the first echocardiogram were available (three measurements, n=582; four measurements, n=147; five measurements, n=224; six measurements, n=108), the mean, SD, CV, VIM, and ARV of apoB level were calculated in the same manner as in other lipid measurements. Only the measurements during the 5 years preceding the first echocardiogram, but not during the follow-up period, were included in the calculation of variability parameters.

Standard two-dimensional transthoracic echocardiography and Doppler echocardiography using multiple windows were conducted as part of a health promotion program using commercially available equipment (Vivid7, GE Medical Systems, Horten, Norway; and SC2000, Siemens Medical Solution, Mountain View, CA, USA). Image acquisition and measurements were performed according to the 2003 American Society of Echocardiography (ASE) guidelines and 2009 European Association of Echocardiography/ASE guidelines [16]. Echocardiographic parameters of LVEF, left atrial volume index (LAVI), left ventricular mass index (LVMI), transmitral early diastolic velocity (E), and mitral annulus early diastolic velocity (e’) were assessed. LVEF was evaluated using biplane Simpson’s rule by way of a manual tracing of digital images.

LVDD was defined as preserved LVEF (≥50%) and one or more of the following findings on screening echocardiography: (1) E/e’ >15; (2) 8<E/e’≤15 and e’ <7 cm/sec; or (3) 8<E/e’≤ 15 and left atrial enlargement (LAVI >34 mL/m²) and left ventricular hypertrophy (LVMI >115 g/m² in males, >95 g/m² in females) [16,17]. The rate of change in E/e’ over time was determined by subtracting baseline E/e’ from E/e’ measured at the last follow-up, divided by duration of follow-up in months.

Subjects were classified into three groups according to tertile of the mean and variability of each lipid parameter. The Kaplan-Meier analysis and log-rank test were used to compare survival between the three groups. The hazard ratio (HR) and 95% confidence interval (CI) for LVDD were calculated by multivariable Cox proportional hazard regression analysis. In multivariable analyses, a non-adjusted model (model 1); a model adjusted for age and sex (model 2); a model further adjusted for the presence of hypertension and DM, BMI, and mean of lipid measurements (model 3); and a model further adjusted for E/e’ and HbA1c (model 4) were constructed. To determine the relative contributions of CV-HDL-C, CV-LDL-C, and CV-TG to the significant association in the fully adjusted models, we sequentially added the tertile of mean TG, CV-TG, and mean LDL-C and CV-LDL-C to a multivariable analysis model including mean HDL-C, CV-HDL-C, and other covariates.

Two separate subgroup analyses were conducted according to (1) statin therapy and (2) statin therapy and/or use of any lipid-modifying agents as identified by self-reported questionnaires. Statin therapy was confirmed by searching the institutional clinical data warehouse (CDW). However, as searching the institutional CDW is reliable for prescriptions inside the institution but can miss statin therapy outside the institution, we supplemented the analysis by including questionnaire-confirmed cases using any lipid-modifying agents. Statin therapy and use of lipid-modifying agent were defined as one or more prescriptions or positive responses to the questionnaire during the same period as used in the determination of the variability of lipid measurements prior to the first echocardiograph.

Subgroup analyses were conducted according to sex and the trend of each lipid parameter before study entry. An increasing or decreasing trend before study entry was determined by beta-estimate of the regression line generated from the consecutive measurements included in the calculation of variability parameters at baseline [18]. An increasing or decreasing trend was defined as slope ≥0 and <0, respectively.

All data are presented as mean±SD for continuous variables or as number with percentage for categorical ones. All P values were two-tailed, and P values <0.05 were considered statistically significant. All statistical analyses were performed using STATA version 16.0 (StataCorp., College Station, TX, USA) and SAS version 9.4.

Of the 2,817 participants included in this study, 2,336 were male and 481 were female. The mean age was 55 years (interquartile range, 50 to 60). Among these participants, 371 (13.2%) had diabetes at baseline. Clinical and echocardiographic characteristics of the study population are summarized in Table 1. The cut-off values for tertiles of mean, SD, and CV of lipid measurements are summarized in Supplementary Table 1.

Five hundred and sixty subjects (19.9%) developed LVDD during a median follow-up of 3.7 years (interquartile range, 2.1 to 4.9), comprising 459 of 2,336 male subjects and 101 of 481 female subjects (19.6% and 21.0%, respectively). Among the 560 patients who developed LVDD, three had regional wall motion abnormality consistent with ischemic heart disease in echocardiogram, and the remaining 557 patients had no sign of ischemic heart disease in echocardiogram.

Among the mean parameters, only the tertile of TG level was associated with incident LVDD in the unadjusted model and the age- and sex-adjusted model (Table 2, Fig. 2). However, the association between tertile of mean TG level and risk of LVDD was not significant in the fully adjusted model (Table 2). An incrementally higher risk of LVDD was observed with higher CV tertile for LDL-C and TC compared with the lowest tertile group in the unadjusted model (P for trend; CV-LDL-C 0.002, CV-HDL-C 0.108, CV-TC 0.009, CV-TG 0.083) (Fig. 2). In the fully-adjusted model, higher CV-LDL-C, CV-HDL-C, and CV-TG were associated with elevated risk for LVDD (for tertile 3 vs. tertile 1: CV-LDL-C [HR, 1.35; 95% CI, 1.10 to 1.67], CV-HDL-C [HR, 1.24; 95% CI, 1.01 to 1.52], CV-TG [HR, 1.25; 95% CI, 1.01 to 1.54]) (Table 2). Tertile 2 but not tertile 3 of CV-TC was associated with LVDD (for tertile 2 vs. tertile 1; HR, 1.28; 95% CI, 1.03 to 1.58) (Table 2).

Because the highest tertiles of CV-TG, CV-HDL-C, and CV-LDL-C were associated with risk of LVDD, we conducted an additional multivariable Cox regression analysis including CV-TG, CV-HDL-C, and CV-LDL-C as covariates. When tertile of mean TG, CV-TG, and mean LDL-C and CV-LDL-C were added sequentially to the fully adjusted model including tertiles of mean HDL-C and CV-HDL-C along with other covariates, the association between CV-LDL-C and LVDD remained significant (for tertile 3 vs. tertile 1 [HR, 1.30, 95% CI, 1.05 to 1.62]; for tertile 2 vs. tertile 1 [HR, 1.26; 95% CI, 1.01 to 1.56]) (Supplementary Table 2).

Although the highest tertiles of SD and VIM of all lipid measurements were associated with LVDD in unadjusted multivariate Cox analysis, only SD-LDL-C and VIM-LDL-C were associated with LVDD in fully adjusted Cox analysis (Table 2, Supplementary Table 3). ARV of LDL-C and of TC were associated with LVDD in unadjusted multivariate analysis. However, its significant association was lost in fully adjusted multivariate analysis (Supplementary Table 3).

Two separate analyses were conducted according to use of statin therapy and to use of statin and/or any dyslipidemia medications. In these analyses, there was no significant interaction with statin therapy in the association between mean LDL-C, SD-LDL-C, and CV-LDL-C and risk of LVDD. Significant associations between SD-LDL-C and CV-LDL-C and risk of LVDD were observed in the group without statin therapy (Table 3). A similar trend was observed when the group was defined based on use of statin and/or any dyslipidemia medications, with no significant interaction with use of statin and/or any dyslipidemia medications in the associations between mean LDL-C, SD-LDL-C, and CV-LDL-C and risk of LVDD (Table 3).

When we explored if there was significant interaction with increasing and decreasing trend of each lipid parameter at baseline in the association between variability of each lipid parameter and risk of LVDD, there was a significant interaction with increasing and decreasing trend only in the association between CV-HDL-C and risk of LVDD, but not in the association between CV-LDL-C or CV-TC and risk of LVDD (Supplementary Table 4). The association between CV-HDL-C and risk of LVDD was significant only in the subgroup with increasing trend of HDL-C at baseline (Supplementary Table 4).

When stratified by sex, the association between highest tertile of CV-LDL-C and LVDD was significant in both male and female subjects (for males, P=0.048; for females, P=0.047) (Supplementary Table 5). The association between the highest tertile of CV-TC and LVDD was significant only in females. However, there was no significant interaction with sex in the association between each lipid parameter and risk of LVDD.

Mean apoB was not associated with development of LVDD. However, SD-apoB, CV-apoB, VIM-apoB, and ARV-apoB were all significantly associated with LVDD even in the fully adjusted multivariable model (Supplementary Table 6). Both mean and variability of non-HDL-C were not associated with development of LVDD in the fully adjusted multivariable model (Supplementary Table 6).

The rate of change in E/e’ during the follow-up period according to tertile of mean, SD, and CV of lipid measurements is presented in Supplementary Table 7. An incrementally higher risk of LVDD was observed with higher tertiles of SD-LDL-C (P for trend=0.045) and CV-LDL-C (P for trend=0.036).