Clustering characteristics of upper gastrointestinal cancer risk behaviours and their association with social determinants of health: a latent class analysis
摘要
Research on risk behaviours (RBs) clustering linked to upper gastrointestinal cancer (UGC) is scarce. This study focused on rural residents aged 40–69 years in high-risk areas of UGC, and sought to identify clustering patterns among 11 RBs related to UGC and their associations with social determinants of health (SDOH). Using data from the rural UGC screening in Jiangsu Province, latent class analysis was used to identify distinct RB classes, and multinomial logistic regression was applied to assess their associations with SDOH. Among the 45,036 participants, 58.56% had two or more RBs, with overweight/obesity being the most prevalent RB. Four distinct RB latent classes were identified: overall healthy behaviour (55.39%), smoking-alcohol dominant (7.91%), unhealthy diet-dominant (9.37%), and nutrient insufficiency (27.33%) clusters. Men, those with advanced age, and those with lower educational attainment were more likely to belong to the smoking-alcohol dominant, unhealthy diet-dominant, and nutrient insufficiency clusters compared to the overall healthy behaviour cluster. Married individuals and those from households with 4–6 members were less likely to be classified into the smoking-alcohol dominant cluster, whereas individuals from such households were more likely to be in the nutrient insufficiency cluster. Individuals from households with an annual income of Chinese Yuan (CNY) ≥ 60,000 were more likely to be classified into the smoking-alcohol dominant and unhealthy diet-dominant clusters, whereas those with an income of CNY 30,000–59,999 had lower odds of being in the nutrient insufficiency cluster but higher odds of being in the unhealthy diet-dominant cluster. This study indicates that RBs for UGC are highly co-occurring and exhibit distinct clustering within the target screening population. Tailored health intervention strategies based on RB clustering patterns during UGC screening may effectively reduce the UGC burden.