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Takahiko Yoshimoto,1,2 Hiroyuki Oka,2 Hirotaka Ochiai,1 Shuhei Ishikawa,3 Akatsuki Kokaze,1 Shingo Muranaga,3 Ko Matsudaira2 1Department of Hygiene, Public Health and Preventive Medicine, Showa University School of Medicine, Shinagawa-ku, Tokyo, Japan; 2Department of Medical Research and Management for Musculoskeletal Pain, 22nd Century Medical & Research Center, Faculty of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan; 3Department of Rehabilitation, Kameda Medical Center, Kamogawa, Chiba, JapanCorrespondence: Takahiko YoshimotoDepartment of Hygiene, Public Health and Preventive Medicine, Showa University School of Medicine, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8555, JapanTel +81 (3)3784-8134Fax +81 (3)3784-7733Email yoshimotot@med.showa-u.ac.jpBackground: A decrease in work productivity due to presenteeism among healthcare workers with low back pain (LBP) is a major problem in the workplace. It is important to determine the factors associated with presenteeism to successfully manage work productivity among nursing staff with LBP. This study aimed to identify the factors associated with presenteeism among nursing personnel with LBP through the evaluation of several aspects, including individual, occupational, and psychological factors.Methods: We conducted a cross-sectional study with 668 nursing personnel who had experienced LBP within the 4 weeks before study enrollment at a tertiary hospital in Japan. Information on demographics (eg, sex, age, height, weight, etc.), LBP intensity (Numerical Rating Scale, NRS), kinesiophobia (Tampa Scale for Kinesiophobia-11, TSK-11), depressive condition (K6), workaholism, overworking hours, frequency of shift work, sleep problem, work-related stress, and presenteeism (Work Productivity and Activity Impairment-General Health) were collected using a self-administered questionnaire. Multiple linear regressions were applied to examine the factors related to presenteeism. We further used a multiple imputation by chained equations for missing data in the model.Results: Multiple linear regression analysis after adjusting for covariates showed that NRS (regression coefficient β = 2.275), TSK-11 (1.112), K6 (0.616), and sleep duration (− 1.990) were significantly associated with presenteeism. These results with complete-case analyses were similar to those with multiple imputation analyses.Conclusion: Psychological factors, such as kinesiophobia and depressive symptoms, were associated with presenteeism independently of LBP intensity among nursing staff with LBP. Our findings suggest that the above-mentioned factors may need to be considered for the development of strategies to increase work productivity among nursing staff with LBP.Keywords: low back pain, presenteeism, productivity, nurse, psychological factor

Takahiko Yoshimoto,1 Hirotaka Ochiai,1 Takako Shirasawa,1 Satsue Nagahama,2 Akihito Uehara,1 Jun Muramatsu,1 Akatsuki Kokaze1 1Department of Hygiene, Public Health and Preventive Medicine, Showa University School of Medicine, Shinagawa-Ku, Tokyo, Japan; 2All Japan Labor Welfare Foundation, Shinagawa-Ku, Tokyo, JapanCorrespondence: Takahiko Yoshimoto Email yoshimotot@med.showa-u.ac.jpPurpose: Although many studies have indicated the association between low back pain (LBP) and lifestyle factors, the combined effect of lifestyle factors on LBP has not been adequately investigated. We aimed to investigate the association between a cluster of unhealthy lifestyle behaviors and LBP using a large cohort of Japanese adults.Methods: We included 419,003 adults aged over 20 years who underwent an annual health checkup between April 2013 and March 2014 in Japan. Information on the following lifestyle factors was collected using the standardized questionnaire: smoking, alcohol intake, exercise, physical activity, walking speed, weight control, eating habits, and sleep. Each factor was evaluated as a dichotomous variable (1: health risk, 0: no health risk). A lifestyle risk score was calculated by summing the score of each lifestyle factor (range: 0– 12) and was categorized into three groups (low, moderate, high). LBP was defined as self-reported LBP under treatment. Logistic regression analysis was conducted to calculate the odds ratio (OR) and 95% confidence interval (CI) for LBP.Results: In multivariable logistic regression analysis, the OR for LBP was significantly higher in the moderate-risk score group (adjusted OR: 1.33 [95% CI: 1.23– 1.44] in men; 1.40 [95% CI: 1.27– 1.54] in women) and the high-risk score group (adjusted OR: 1.54 [95% CI: 1.43– 1.67] in men; 1.83 [95% CI: 1.64– 2.03] in women) than in the low-risk score group. A trend of higher risk of LBP associated with higher lifestyle risk score was observed in both sexes (p for trend < 0.001). These results were similar even in subgroup analysis by age and body mass index (BMI).Conclusion: Clustering of unhealthy lifestyles was associated with increased risk of LBP regardless of age and BMI. These results may provide implications for better prevention and management of LBP, considering modifiable lifestyle factors.Keywords: lifestyle, low back pain, clustering, health checkup