Prevalence of Suboptimal Health Status and Its Influencing Fac-tors among Chinese Software Programmers

Minmin  Tian; Qiong  Zhang; Zhigang  Zhang; Juanjuan  Meng; Longzhu  Liu

doi:10.18502/ijph.v50i7.6625

Minmin Tian Department of Experimental Center for Preventive Medicine, School of Public Health, Shaanxi University of Chinese Medicine, Shaanxi, China
Qiong Zhang Department of Experimental Center for Preventive Medicine, School of Public Health, Shaanxi University of Chinese Medicine, Shaanxi, China
Zhigang Zhang Department of Toxicology, School of Public Health, Shaanxi University of Chinese Medicine, Shaanxi, China
Juanjuan Meng Department of Experimental Center for Preventive Medicine, School of Public Health, Shaanxi University of Chinese Medicine, Shaanxi, China
Longzhu Liu Department of Toxicology, School of Public Health, Shaanxi University of Chinese Medicine, Shaanxi, China

DOI: https://doi.org/10.18502/ijph.v50i7.6625

Keywords: Software programmers; Suboptimal health status; Prevalence; Influencing factors

Abstract

Background: There is a lack of specific study of the suboptimal health status (SHS) in software programmers. The aims of the present study were to investigate the prevalence of SHS and analyze the influencing factors among Chinese software programmers.

Methods: A cross-sectional survey using a programmer SHS scale was conducted to evaluate the prevalence of SHS, as well chi-square test and multi-factor logistic regression were applied to analyze the relationship between suboptimal health and personal basic information, living and work habits in software programmers.

Results: The prevalence of SHS was 18.67% in software programmers. Single factor analysis found that there were differences in suboptimal health prevalence among different work cities (P = 0.031), hours of sleep per day (P = 0.046), overtime days per month (P = 0.010) and exercise frequency per week (P = 0.015). The factors for suboptimal health such as hours of sleep per day (OR = 0.307, 95% CI = 0.096~0.984) and exercise frequency per week (OR = 0.190, 95% CI = 0.054~0.671) significantly affected subjects of SHS via multi-factor logistic regression analysis, indicating that adequate sleep and exercise decreased the chance of SHS up to 30.70% and 19.00%, respectively.

Conclusion: Suboptimal health had become a serious public health challenge in Chinese software programmers. Whilst, the health status of the programmers could be effectively elevated by improving lifestyles.