Study population baseline characteristics
In this study, a total of 20944 participants were recruited, including 12498 men and 8446 women, 5480 participants were excluded who did not meet the inclusion criteria, of whom including 863 people without covariant data, 416 patients with hepatitis B or C virus, 739 people with heavy drinking habits, 2321 people who took drugs at baseline, 323 patients with diabetes, 808 people with baseline fasting blood glucose exceeding 6.1mmol/L, and 10 other patients who did not participate in the study for unknown reasons. Finally, we evaluated 15464 people who met the inclusion and exclusion criteria (8430mens and 7034womens, with an average age of43.71±8.9), including 2741 patients with ectopic fat obesity, we divided them into quartiles according to the quartile of TG(≤0.497,0.497 to≤0.734,0.734 to≤1.118,≥1.118). Table 1 summarizes the clinical baseline characteristics of the study population. We found that in the TG group, male participants and people diagnosed with fatty liver accounted for a higher proportion of the higher TG group, and generally had higher Age, BMI, Body weight, Waist circumference, ALT, AST, GGT, Total cholesterol, HbA1c，Fasting plasma glucose and blood pressure in the group with higher TG level. On the contrary Habit of exercise and HDL cholesterol had more exercise times and HDL cholesterol levels in the groups with lower TG values, and there were statistical differences in all independent variables among different TG groups, p<0.05.
The results of univariate analysis are shown in Table 2. Univariate analysis showed that heavy drinking, smoking, ALT, AST, Total cholesterol, GGT, Triglycerides, HbA1c, Fasting plasma glucose, SBP, DBP: Diastolic blood pressure, Sex, Age, BMI and Waist circumference were positively correlated with the risk of ectopic fat obesity. Nevertheless, HDL cholesterol, Habit of exercise, and Light drinking were negatively correlated with the incidence of ectopic fat obesity. We also found that women had a lower risk of ectopic fat obesity than men.
The results of relationship between TG and incident of Ectopic fat obesity
Before establishing the Logistic regression model, we carried out multiple linear regression tests on all variables, and judged the collinearity between variables according to VIF. Finally, we eliminated three variables: body weight, SBP and Waist circumference. In this research, we used a Logistic regression model to evaluate the relationship between TG and ectopic fat obesity. The unadjusted and adjusted models are shown in Table 3. In the rough model, there was a positive correlation between TG and ectopic fat obesity (OR=4.14,95%CI:3.85-4.44,p<0.00001), but there was no significant change in the fine-tuning model(Model I:adjust for: Sex, Age and BMI) (OR:2.09,95%CI:1.94-2.26,p<0.00001). After adjusting the whole model(Model II: adjust for: Sex, Age, ALT, AST, Habit of exercise, GGT, HDL cholesterol, Total cholesterol, HbA1c. Smoking status, Fasting plasma glucose. SBP and BMI), we can still see that there is a positive correlation between them(OR: 1.55,95%CI:1.41-1.69, p<0.00001). Moreover, we conducted a sensitivity analysis, and we treated TG as a classification variable, and we found that after adjusting the model, the risk of ectopic fat obesity in the group with higher TG(≥1.118) was 3.16 times higher than that in the group with lower TG(≤0.497). In addition, from the change of the effect value (1, 1.41, 2.16, 3.16), it can be seen that the risk of ectopic fat obesity increases gradually with the increase of TG content(P for trend<0.00001), indicating that this trend is significant.
The analyses of non-linear relationship
In this study, due to TG is a continuous variable, we use the GAM to identify the nonlinear relationship between TG and ectopic fat obesity, after adjusting Sex, Age, ALT, AST, Habit of exercise, GGT, HDL cholesterol, Total cholesterol, HbA1c. Smoking status, Fasting plasma glucose. SBP and BMI. we find that there is an inverted U-shaped curve relationship between TG and ectopic fat obesity and there is a curve inflection point in TG within the range of 3.5-4mmol/l, as shown in figure 1. In addition, according to gender as a stratification factor, we fitted the relationship between TG and ectopic fat obesity in different genders. In figure 2, we can observe that there is a similar inverted U-shaped curve relationship between men and women, and after multivariable adjustment, the inverted U-shaped curve relationship still exists. Through Engauge Digitizer software, we identified the inflection point of the curve of the relationship between TG and ectopic fat obesity in the study population was 3.98, while the inflection point was 3.93 in men and 5.18 in women, we used a two-stage linear regression model, calculated the threshold effect of TG on the incidence of ectopic fat obesity according to the smoothing curve and its inflection point, and found that there was a positive correlation between TG and ectopic fat obesity on the left side of the inflection point (OR:1.784,95%CI:1.611-1.975,p<0.0001), and on the right side of the inflection point, there is a negative correlation between them(OR：0.519 ,95%CI:0.333- 0.810,p=0.0039)(Table4).
Through the subgroup, we can further explore other risks in the association between TG and ectopic fat obesity. We transformed variables with p-values <0.05 in univariate analysis (exclude collinearity variable) into categorical variables for hierarchical analysis based on clinical entry points(Sex, Age, ALT, AST, Habit of exercise, GGT, HDL cholesterol, Total cholesterol, HbA1c, Smoking status, Fasting plasma glucose. SBP and BMI), and observed whether the stratified variables interaction with TG, showing on the table 5, we observed significant interactions between TG and gender, HDL, BMI, smoking status, and fasting blood glucose (P for interaction <0.05), while the interaction tests were not statistically significant in Age, Habit of exercise, Total cholesterol, HbA1c, SBP, ALT, AST and GGT. Among other risks associated with ectopic fat obesity and TG, We can see that the correlation between TG and men is higher than that of women, the correlation between TG and TG is higher in people with higher HDL cholesterol (>1.04mmol/l) than in those with lower HDL cholesterol (≤1.04mmol/l), and the correlation between lower fasting blood glucose (≤4.5mmol/l) and TG is higher than that of higher fasting blood glucose (>4.5mmol/l). In people with higher BMI (>28kg/m2), there is a significantly higher risk of ectopic obesity after the increase of TG values. In addition, we also found an interesting phenomenon that the correlation with TG among non-smokers was slightly higher than that among smokers.