BMC Nursing (Nov 2021)

Health promoting lifestyle behaviors and associated predictors among clinical nurses in China: a cross-sectional study

  • Wen Zeng,
  • Shaomei Shang,
  • Qian Fang,
  • Shan He,
  • Juan Li,
  • Yuanrong Yao

DOI
https://doi.org/10.1186/s12912-021-00752-7
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 11

Abstract

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Abstract Background Nurses play a core role and encompass the main workforce in health care systems. Their role model of health promoting lifestyle behaviors (HPLB) would directly or indirectly affect their clients’ beliefs or attitudes of health promotion. There is limited evidence on HPLB in clinical registered nurses. The current study aimed to explore the HPLB and associated influencing factors among clinical registered nurses in China. Methods A multi-center cross-sectional anonymous online survey was conducted in 2020. Participants were asked to complete social demographic information as well as the revised Chinese edition of Health Promoting Lifestyle Profile (HPLP). Independent-Sample T-Test, One-Way ANOVA, and categorical regression (optimal scaling regression) were the main methods to analyze the relationship between demographic data and the score of HPLB. Results 19,422 nurses were included in the study. The mean score of self-actualization, health responsibility/physical activity, nutrition, job safety, interpersonal support, and overall Health Promoting Lifestyle Profile were, 27.61(5.42) out of a score of 36, 22.71(7.77) out of a score of 44, 10.43(2.97) out of a score of 16, 22.05(3.97) out of a score of 28, 20.19(4.67) out of a score of 28, and 102.99 (19.93) out of a score of 144, respectively. There was a significant relationship among Hospital levels, working years, nightshift status, and monthly income per person, and mean score of all subscales and the overall HPLP (P < 0.05). Conclusions Nurses who participated in the study presented a moderate level of health promoting lifestyle behaviors. Hospital levels, working years, nightshift status, and monthly income per person were predictors for all subscales and overall HPLP.

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