Physical Activity–Sedentary Behaviour Profiles and Associated Lifestyle Characteristics in Adolescents: A Cross-Sectional Study

Background/Objectives: Physical activity and sedentary behaviour are related but distinct components of adolescent movement behaviour and may combine into heterogeneous lifestyle profiles. This study aimed to identify empirically derived physical activity–sedentary behaviour profiles and to examine sociodemographic and lifestyle factors associated with profile membership. Methods: This cross-sectional, school-based study included 3307 Polish adolescents aged 15–17 years (52.22% girls; mean age, 15.89 ± 0.71 years). Weekly sedentary time and walking, moderate-intensity, and vigorous-intensity physical activity were assessed using the IPAQ-LF, reprocessed using predefined truncation procedures, standardised using z-scores, and entered into k-means clustering. Two- and three-cluster solutions were evaluated. Separate binary logistic regression models examined crude and sex- and school-type-adjusted associations between candidate lifestyle correlates and profile membership. Results: Although the two-cluster solution had a higher average silhouette coefficient (0.36 vs. 0.28), the three-cluster solution was retained because it provided a more differentiated and substantively interpretable representation of movement-behaviour patterns. The profiles comprised a walking-dominant activity profile (C1; n = 645; 19.50%), a high moderate-to-vigorous activity/lower sedentary profile (C2; n = 354; 10.71%), and a lower physical activity profile (C3; n = 2308; 69.80%). C3 had substantially lower walking, moderate-intensity, and vigorous-intensity activity than C1, while sedentary time was similar in magnitude between these profiles. After adjustment for sex and school type, C2 membership was associated with irregular eating patterns (OR = 1.73, 95% CI: 1.05–2.84), school-day sleep ≥ 9 h/day (OR = 1.98, 95% CI: 1.11–3.54), weekend sleep < 7 h/day (OR = 1.70, 95% CI: 1.02–2.82), and weekend sleep ≥ 9 h/day (OR = 1.59, 95% CI: 1.16–2.16). No lifestyle candidate correlate reached statistical significance in the adjusted C3-versus-C1 analyses. Conclusions: The identified profiles support viewing physical activity and sedentary behaviour as related but non-equivalent dimensions of adolescent movement behaviour. Lower physical activity did not necessarily coincide with higher sedentary time, while selected sleep-duration and eating-regularity characteristics were associated with the high moderate-to-vigorous activity/lower sedentary profile. These findings are exploratory and warrant confirmation in longitudinal studies using objective measures.