The final analysis included 196515 subjects. The socio-demographic and lifestyle characteristics of the male and female samples are presented separately in Table 1. Males accounted for 54.92% of the sample, whereas females comprised 45.08%. The proportion of middle-aged and elderly people aged ≥45 years is 45.55%, and the proportion of young people aged <45 years old is 54.45%. A total of 77,172 cases of MAFLD (39.27%) were identified between 2016 and 2020, and men had a prevalence of 54.37%, which was higher than women (20.88%, p<0.001).
The defined lifestyle scoring system, including optimal cut points for options of the lifestyle items, is presented as Appendix Table 1 in Supplementary materials. The factors extracted by the PCA method corresponded to dietary factors and mental models. The factor loadings for each dietary factor are shown in Appendix Table 2 in Supplementary materials.
Based on the results of the silhouette coefficient and elbow method, we identified nine clusters for males and four clusters for females. A relatively high agreement is found between the cluster solution derived from the full sample and the random subsample (males: Cohen’s kappa= 0.55, p < 0.01; females: Cohen’s kappa = 0.89, p < 0.01). The specific characteristics of each cluster are presented in Figure 3 and Table 2.
For males, the largest cluster (C1, n=21494,19.91%) was referred to as a “healthy” lifestyle pattern. It excludes all risky health behaviors and is characterized by being physically active, not smoking, not drinking, having low levels of sedentary, having moderate physical intensity at work, sleeping well, and having a healthy mind and diet. Cluster 2 (C2, n=10790, 10.00%) was characterized by physical inactivity, an unhealthy diet, not smoking, not drinking, being sedentary, and having poor mental status. Cluster 3 (C3, n=10092,9.35%) was characterized by “heavy smoking” but maintaining other healthy lifestyle behaviors. Cluster 4 (C4, n=16160,14.97%) was significantly characterized by heavily consuming alcohol, smoking in small quantities, being physically active, and having irrational dietary behaviors. Cluster 5 (C5, n=3917,3.63%) was described as having the “most physically intense work,” being physically active, having a healthy mentality, and having high fat and high cholesterol diet. Cluster 6 (C6, n=7656,7.09%) was almost the exact opposite to Cluster 4 and was characterized by “heavy smoking,” being physically inactive, having “poor sleep quality,” and having an unhealthy diet but no drinking. Cluster 7 (C7, n=17,723,16.42%) is the opposite of cluster 2 and characterized by “heavy smoking,” and “heavy drinking” but being physically active. Cluster 8 (C8, n=1865,1.73%) likes cluster 5, was characterized by performing the “most physically intense work,” “heavy drinking,” “heavy smoking,” being physically inactive, being highly sedentary, and having “unhealthy mentality and diet.” Lastly, cluster 9 (C9, n=18234,16.89%), known as the “unhealthiest” lifestyle pattern, was characterized by heavy drinking and smoking, being physically inactive, being sedentary, having poor sleep quality, and having unhealthy mental status and diet.
The largest cluster of females (CF1, n=80551,90.93%), known as the “relatively healthy” lifestyle pattern, differed from the largest cluster of males in that they lacked physical activity. Cluster 2 (CF2, n=1040,1.17%) was characterized by heavy smoking, being highly sedentary, having poor mental status, and having unhealthy diet. Cluster 3 (CF3, n=718,0.81%), known as the “least healthy” lifestyle pattern, had similar characteristics to cluster 2 except for heavy drinking. Cluster 4 (CF4, n=6275, 7.08%) was characterized by heavy alcohol consumption but was the most active in exercise and had relatively healthy dietary behaviors.
In men, C4, C7, and C9 had the highest prevalence of MAFLD (58.36%, 58.63%, and 58.06%, respectively), whereas the lowest prevalence was observed for C1 (48.07%). The prevalence of MAFLD was lower in women than that in men (20.88% vs 54.37%, p<0.001). In women, a very similar prevalence of MAFLD was found in CF1, CF3, and CF4, whereas CF2 had the highest prevalence of MAFLD (26.92%).
The results of the binary logistic regression models are presented in Table 3, stratified by gender. C1 and CF1 were chosen as the reference clusters for males and females because they had the largest populations and showed a lower prevalence of MAFLD compared with the other clusters. After adjusting for confounding variables, C2, C6, C8, and C9 among males were significantly associated with a higher risk of MAFLD. C3, C4, and C7 had significantly lower odds of belonging to the MAFLD group. In the female clusters, the odds of CF2 belonging to MAFLD were higher (AOR=1.370, 95% CI=1.168–1.607).