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. 2024 Jan 6;23(1):16.
doi: 10.1186/s12933-023-02114-w.

Association between the cumulative average triglyceride glucose-body mass index and cardiovascular disease incidence among the middle-aged and older population: a prospective nationwide cohort study in China

Affiliations

Association between the cumulative average triglyceride glucose-body mass index and cardiovascular disease incidence among the middle-aged and older population: a prospective nationwide cohort study in China

Fadong Li et al. Cardiovasc Diabetol. .

Abstract

Background: Findings from earlier research have established that insulin resistance (IR) is implicated in atherosclerosis progression, representing a noteworthy risk factor for cardiovascular disease (CVD). Recently, the triglyceride glucose-body mass index (TyG-BMI) has been introduced as a straightforward and robust alternative indicator for early detection of IR. Nevertheless, there is a scarcity of studies that have examined the capability of TyG-BMI for predicting incident CVD. Consequently, the core objective of this study was to determine whether the cumulative average TyG-BMI correlated with CVD incidence.

Methods: All data was sourced from the China Health and Retirement Longitudinal Study (CHARLS). The exposure was the cumulative average TyG-BMI, determined by the average of TyG-BMI values for the baseline and follow-up investigations (Wave 1 in 2011, Wave 3 in 2015, respectively). The calculation of TyG-BMI involved a combination of triglyceride, fasting blood glucose, and body mass index. The primary outcome was incident CVD. Logistic regression analyses as well as restricted cubic spline (RCS) regression analyses were performed for examining the association between the cumulative average TyG-BMI and CVD incidence.

Results: In all, 5,418 participants were enrolled in our analysis, with 2,904 (53.6%) being female, and a mean (standard deviation, SD) age of 59.6 (8.8) years. The mean (SD) cumulative average TyG-BMI among all participants was 204.9 (35.7). Totally, during a 4-year follow-up, 543 (10.0%) participants developed CVD. The fully adjusted logistic regression analysis revealed a significant association between the cumulative average TyG-BMI and incident CVD [odds ratio (OR), 95% confidence interval (CI): 1.168, 1.040-1.310, per 1 SD increase]. The RCS regression analysis displayed a positive, linear association of the cumulative average TyG-BMI with CVD incidence (P for overall = 0.038, P for nonlinear = 0.436).

Conclusions: Our study revealed a noteworthy correlation between the cumulative average TyG-BMI and incident CVD among the middle-aged and older population. The cumulative average TyG-BMI emerges as a valuable tool that may enhance the primary prevention and treatment of CVD.

Keywords: CHARLS; Cardiovascular disease; Insulin resistance; Prospective cohort study; TyG-BMI.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of the study population. BMI, body mass index; TG, triglyceride; FBG, fasting blood glucose; TyG-BMI, triglyceride glucose-body mass index
Fig. 2
Fig. 2
Incidence rates of CVD categorized by quartiles of the cumulative average TyG-BMI. Q1, Quartile 1; Q2, Quartile 2; Q3, Quartile 3; Q4, Quartile 4; TyG-BMI, triglyceride glucose-body mass index
Fig. 3
Fig. 3
Association between the cumulative average TyG-BMI and incident CVD. The model was adjusted for age, gender, smoking status, drinking status, SBP, DBP, HbA1c, TC, HDL-c, LDL-c, residence (hukou), education level, marital status, hypertension, dyslipidemia, diabetes, liver disease, kidney disease, antihypertensive treatment, lipid-lowering treatment and hypoglycaemic treatment. SBP, systolic blood pressure; DBP, diastolic blood pressure; HbA1c, glycosylated hemoglobin A1c; TC, total cholesterol; HDL‐c, high‐density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; TyG-BMI, triglyceride glucose-body mass index; OR, odds ratio; CI, confidence interval
Fig. 4
Fig. 4
Association between the cumulative average TyG-BMI and incident heart condition (A) and incident stroke (B). The model was adjusted for age, gender, smoking status, drinking status, SBP, DBP, HbA1c, TC, HDL-c, LDL-c, residence (hukou), education level, marital status, hypertension, dyslipidemia, diabetes, liver disease, kidney disease, antihypertensive treatment, lipid-lowering treatment and hypoglycaemic treatment. SBP, systolic blood pressure; DBP, diastolic blood pressure; HbA1c, glycosylated hemoglobin A1c; TC, total cholesterol; HDL‐c, high‐density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; TyG-BMI, triglyceride glucose-body mass index; OR, odds ratio; CI, confidence interval
Fig. 5
Fig. 5
Subgroup analyses of the association between the cumulative average TyG-BMI and CVD incidence. The model was adjusted for age, gender, smoking status, drinking status, SBP, DBP, HbA1c, TC, HDL-c, LDL-c, residence (hukou), education level, marital status, hypertension, dyslipidemia, diabetes, liver disease, kidney disease, antihypertensive treatment, lipid-lowering treatment and hypoglycaemic treatment (excluding the variable for subgroup stratification). SBP, systolic blood pressure; DBP, diastolic blood pressure; HbA1c, glycosylated hemoglobin A1c; TC, total cholesterol; HDL‐c, high‐density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; OR, odds ratio; CI, confidence interval

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