Abstract

Undergraduate nursing students are trained to promote health in clinical and community settings, but their own health-promoting behaviors occur in the context of academic demands, clinical training, work responsibilities, and limited time for self-care. The primary objective of this cross-sectional analytic study was to estimate the adjusted association between health-professional advice seeking and global Health-Promoting Lifestyle Profile II (HPLP-II) scores among 506 undergraduate nursing students at the Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara. Secondary analyses described HPLP-II scores, stress ratings, information sources, subscale-specific associations, and propensity-score sensitivity analyses; exploratory analyses evaluated HPLP-II psychometrics, level-based lifestyle profiles, and stress-by-advice-seeking interaction. The overall median HPLP-II score was 2.40 (IQR: 2.06, 2.79). Internal consistency was high for the global scale (Cronbach’s alpha = 0.961) and ranged from acceptable to high across subscales (alpha = 0.812–0.900). Ordinal exploratory factor analysis using polychoric correlations supported exploratory use of the theoretical six-domain structure but did not provide confirmatory validation; parallel analysis suggested eight factors. Two level-based lifestyle profiles were identified: Low HPLP (58.1%) and High HPLP (41.9%), reflecting broad score-level separation rather than distinct validated phenotypes. In the primary HC3 robust model, health-professional advice seeking was associated with higher global HPLP-II scores (b = 0.242, 95% CI: 0.140, 0.344; p < 0.001), whereas academic stress and vacation-period stress showed small inverse adjusted associations with HPLP-II scores. Sensitivity analyses, including IPTW, a modified HPLP-II score excluding Health Responsibility, and a model excluding willingness to improve lifestyle, showed advice-seeking coefficients in the same positive direction. The exploratory stress-by-advice-seeking interaction was not statistically significant. Findings should be interpreted as associations rather than causal effects.

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