Background: Many studies have reported on the causes of chronic lower back pain (CLBP). The aim of this study is to identify if the hierarchical neural network (HNN) is superior to a conventional statistical model for CLBP prediction. Linear models, which included multiple regression analysis, were executed for the analysis of the survey data because of the ease of interpretation. The problem with such linear models was that we could not fully consider the influence of interactions caused by a combination of nonlinear relationships and independent variables. Materials and Methods: The subjects in our study were 96 people (30 men aged 72.3 ± 5.6 years and 66 women aged 71.9 ± 5.4 years) who participated at a college health club from 20 July 2016 to 20 March 2017. The HNN and the logistic regression analysis (LR) were used for the prediction of CLBP and the accuracy of each analysis was compared and examined by using our previously reported data. The LR verified the fit using the Hosmer–Lemeshow test. The efficiencies of the two models were compared using receiver performance analysis (ROC), the root mean square error (RMSE), and the deviance (−2 log likelihood). Results: The area under the ROC curve, the RMSE, and the −2 log likelihood for the LR were 0.7163, 0.2581, and 105.065, respectively. The area under the ROC curve, the RMSE, and the log likelihood for the HNN were 0.7650, 0.2483, and 102.787, respectively (the correct answer rates were HNN = 73.3% and LR = 70.8%). Conclusions: On the basis of the ROC curve, the RMSE, and the −2 log likelihood, the performance of the HNN for the prediction probability of CLBP is equal to or higher than the LR. In the future, the HNN may be useful as an index to judge the risk of CLBP for individual patients.

Background and objectives: It is well-known that lifestyle is closely associated with psychological distress in many elderly subjects. However, the effect of intervention with physical activity and/or sleeping on psychological distress has not been fully discussed. The purpose of this cross-sectional study was to investigate the relationships between physical activity, sleeping time, and psychological distress in community-dwelling elderly Japanese subjects. Materials and Methods: A total of 108 elderly Japanese (31 men and 77 women) subjects were enrolled in this cross-sectional study. Psychological distress was evaluated using the K6 questionnaire. Physical activity, including sedentary behavior, was measured using a tri-accelerometer. Sleeping time was evaluated using a self-reported questionnaire. Results: The median of the K6 scores was 1.0 (0–18), and the sedentary behavior (%) and walking time (minutes/day) were 57.2 ± 10.7 and 80.7 (17.9–222.4), respectively. Sleeping time was negatively correlated with psychological distress. In addition, multiple linear regression showed that walking time and sleeping time were important factors for psychological distress, even after adjusting for confounding factors. Conclusions: These results suggest that increased walking time and sleeping time may be beneficial for reducing psychological distress in community-dwelling elderly Japanese subjects.

Background and objectives: The aim of this study was to examine the relationship between nicotine dependence and food dependence in smokers. Smoking and obesity are both serious public health problems that give rise to diseases and increased medical expenses. Nicotine dependence is one of the sources of difficulty in smoking cessation, while food dependence is one of the causes of obesity. Materials and Methods: We examined the data of 72 (smoking vs. nonsmoking) and 62 (nicotine dependence vs. no nicotine dependence) subjects among 321 staff and students at medical colleges in Kagawa and Okayama prefectures in Japan. Results: There was a significant difference in food dependence (except women) between the smoking and nonsmoking groups (total: smoking 4.7 ± 6.1, nonsmoking 2.1 ± 2.0, p = 0.0411; men: smoking 4.0 ± 4.7, nonsmoking 2.0 ± 2.1, p = 0.0490). There was also a significant difference in food dependence (except women) between the nicotine dependence and no nicotine dependence groups (total: nicotine dependence 4.6 ± 6.3, no nicotine dependence 2.0 ± 2.1, p = 0.0370; men: nicotine dependence 3.6 ± 4.8, no nicotine dependence 1.6 ± 1.8, p = 0.0489). Conclusion: The findings showed that the smoking group (and nicotine dependence group) had higher food dependence than the nonsmoking group (and no nicotine dependence group). Our results indicate an interdependence between nicotine and food dependences.

Background: Our purpose is to clarify whether psychological distress (PD) affects the rate of continuous sedentary behavior (CSB). Materials and Methods: In this secondary analysis, a sample population of 80 healthy older adults aged 65 years or older participated in a health club of college A from 2016 to 2017. We conducted Structural Equation Modeling (SEM) using the cross-lagged and synchronous effects models. We adopted the following as proxy variables: CSB (based on the ratio of 1.5 METs sessions or more continuing for over 30 min) CSB and PD (based on the Kessler psychological distress scale: K6). Results: “2016 K6” had a significant influence on “2017 CSB” (standardization factor (β) = 0.136, p = 0.020) using the cross-lagged effects model, and “2017 K6” significantly influenced “2017 CSB” (β = 0.166, p = 0.039) using the synchronous effects model. Fit indices were Adjusted Goodness-of-Fit Index (AGFI) = 0.990, Confirmatory Fit Index (CFI) = 1.000, and Root Mean Square Error of Approximation (RMSEA) = 0.000. Conclusion: The results suggest that PD may affect the ratio of CSB one year later.

Background and objectives: Psychological distress (PD) is associated with continuous sedentary behaviors (CSB; based on the ratio of 1.5 metabolic equivalents (METs) sessions or more continuing for over 30 min) in older adults, but the long-term relation is not sufficiently clarified. This study aims to clarify the long-term relationship between PD and the rate of CSB. Materials and Methods: In this secondary analysis, a sample population of 72 healthy elderly people aged 65 years or older participated in a health club of college A from 2016 to 2018. We conducted structural equation modeling (SEM) using the cross-lagged and synchronous effects models. We adopted the following as proxy variables: CSB and PD (based on the Kessler 6 scale (K6) scores). Results: “2016 K6” to“2017 CSB” (standardization factor (β = 0.141, p = 0.025), “2017 K6” to “2018 CSB” (β = 0.187, p < 0.001) and “2016 CSB” to “2018 CSB” (β = 0.188, p < 0.001) were all statistically significant using the cross-lagged effects models. Fit indices were adjusted goodness of fit index (AGFI) = 0.961, comparative fit index (CFI) = 1.000, and root mean square error of approximation (RMSEA) = 0.000. Conclusion: The results suggest that PD may affect the ratio of CSB one year later, and CSB may affect the ratio of PD two year later.