Latent profile analysis identified five distinct quality of life profiles among Chinese adolescents, with sleep duration, physical activity, screen time, and dietary behaviors showing distinct and heterogeneous associations across profiles relative to a Moderate QoL reference class.
Five distinct latent quality of life profiles were identified among Chinese adolescents.
Longer sleep duration was associated with lower odds of Low QoL and Health-advantaged profiles, but higher odds of Low Physical and Psychological Health and High QoL profiles.
Higher physical activity was associated with lower odds of the Health-advantaged profile and higher odds of the Low Physical and Psychological Health and High QoL profiles.
Screen time was associated with lower odds of the Health-advantaged profile and higher odds of the Low Physical and Psychological Health profile.
Greater minimally processed food (MPF) intake was associated with lower odds of Low QoL and Health-advantaged profiles, and higher odds of Low Physical and Psychological Health and High QoL profiles.
Higher ultra-processed food (UPF) intake was inversely associated with Low QoL, Health-advantaged, and High QoL profiles, and positively associated with the Low Physical and Psychological Health profile.
Adolescent quality of life is heterogeneous and lifestyle behaviors show distinct, profile-specific associations rather than uniform effects across all QoL groups.
This research suggests that adolescent quality of life (QoL) is not one-size-fits-all — among over 7,000 Chinese adolescents, researchers identified five meaningfully different groups with distinct QoL patterns, ranging from Low QoL to High QoL, with one notable group characterized specifically by low physical and psychological health. This heterogeneity means that looking at QoL as a single average score across all teens can mask important differences between subgroups. The study also found that lifestyle behaviors like sleep, physical activity, screen time, and diet were associated with QoL in complex and sometimes counterintuitive ways. For example, longer sleep duration and higher physical activity were linked to higher odds of being in both the High QoL group and the Low Physical and Psychological Health group, compared to the moderate group. Similarly, eating more ultra-processed foods was paradoxically associated with lower odds of being in the Low QoL group, while also being linked to higher odds of the Low Physical and Psychological Health group. These mixed patterns suggest that lifestyle behaviors interact with QoL in nuanced ways that differ across subgroups of adolescents. This research suggests that public health programs aimed at improving adolescent wellbeing should not take a blanket approach. Because different groups of teens have different QoL profiles and respond differently to the same lifestyle factors, tailored interventions — ones designed with a specific subgroup's profile in mind — may be more effective than universal programs. The findings also underscore the value of using statistical techniques like latent profile analysis to uncover hidden subgroups within large populations rather than treating all adolescents as a homogeneous group.
Upload your bloodwork. We'll cross-reference your results against this study and 4,700 others.
Upload Your LabsSong X, Yang Z. (2026). Latent profile analysis of adolescent quality of life and its associations with lifestyle behaviors.. Frontiers in public health. https://doi.org/10.3389/fpubh.2026.1910401