ストレス シャカイ オ ドウ イキヌクカ : サンギョウイ カラ ノ テイゲン

Occupational health deals with all aspects of health and safety in the workplace and has a strong focus on primary prevention of hazards. An influential strategy is occupational risk assessment-the structured and systematic identification and analysis of workplace hazards to assess their potential risks to health and determine appropriate control measures to protect the health and wellbeing of workers. Based on the accumulated evidence using occupational stress models, risk assessment of psychosocial risk factors at workplace, i.e., occupational stress, has become possible. In addition, recent controlled trials indicate that worker participatory organizational interventions have beneficial effects on psychosocial work environment and psychological distress. Occupational risk assessment by workers themselves can provide a cue to survive the current stressful work environment

Clostridium perfringens foodborne outbreak due to braised chop suey supplied by chafing dish.

On February 13, 2002, a public health center in Hiroshima Prefecture, Japan, was notified that many individuals living at the Japan Maritime Self-Defence Force base had symptoms resembling those of food poisoning. Self-administered questionnaires requesting information regarding meal consumption and symptoms were distributed to all 281 members at the base. A case of the illness was defined as a member who had had watery or mucousy stool, or loose stool with abdominal cramps, more than twice a day after consuming dinner on February 12. Control of the illness was defined as a member with no symptoms. The dinner on February 12 was significantly associated with the illness (Mantel-Haenszel odds ratio: 3.59, 95% confidence interval: 1.06-12.20). A case-control study showed that, among the food supplied at dinner on February 12, the braised chop suey was significantly associated with the illness (odds ratio: 12.30, 95% confidence interval: 1.90-521.00). The braised chop suey had been stored in a chafing dish. An environmental investigation indicated that Clostridium perfringens (C. perfringens) in the chafing dish proliferated under an inappropriate heat-retention temperature, and the contaminated braised chop suey could have caused the food poisoning. This study demonstrated that the recommended heat-retention temperature (over 65 degrees C) should be confirmed thoroughly.</p

Broccoli consumption and chronic atrophic gastritis among Japanese males: an epidemiological investigation.

Previous in vitro and animal experiments have shown that sulforaphane, which is abundant in broccoli, inhibits Helicobacter pylori (H. pylori) infection and blocks gastric tumor formation. This suggests that broccoli consumption prevents chronic atrophic gastritis (CAG) introduced by H. pylori infection and, therefore, gastric cancer. For an epidemiological investigation of the relationship between the broccoli consumption and CAG, a cross-sectional study of 438 male employees, aged 39 to 60 years, of a Japanese steel company was conducted. CAG was serologically determined with serum cut-off values set at pepsinogen I &#60; or = 70 ng/ml and a ratio of serum pepsinogen I/pepsinogen II &#60; or = 3.0. Broccoli consumption (weekly frequency) and diet were monitored by using a 31-item food frequency questionnaire. The prevalence of CAG among men who ate broccoli once or more weekly was twice as high as that among men who consumed a negligible amount (P &#60; 0.05). Multiple logistic regression analysis indicated that broccoli consumption once or more weekly significantly increased the risk for CAG (odds ratio, 3.06; 95% confidence interval, 1.12-8.38; P &#60; 0.05), after controlling for age, education, cigarette smoking, and alcohol consumption. The present study failed to show an expected association between frequent broccoli consumption and a low prevalence of CAG.</p

Psychosocial factors at work and inflammatory markers: protocol for a systematic review and meta-analysis

Introduction Chronic inflammation may be a mediator for the development of cardiovascular disease (CVD), metabolic diseases and psychotic and neurodegenerative disorders. Meta-analytic associations between work-related psychosocial factors and inflammatory markers have shown that work-related psychosocial factors could affect the flexibility and balance of the immune system. However, few systematic reviews or meta-analyses have investigated the association between work-related psychosocial factors and inflammatory markers. Based on prospective studies, the present investigation will conduct a comprehensive systematic review and meta-analysis of the association between work-related psychosocial factors and inflammatory markers.Methods and analysis The systematic review and meta-analysis will include published studies identified from electronic databases (PubMed, EMBASE, PsycINFO, PsycARTICLES, Web of Science and Japan Medical Abstracts Society) according to recommendations of the Meta-analysis of Observational Studies in Epidemiology guideline. Inclusion criteria are studies that: examined associations between work-related psychosocial factors and increased inflammatory markers; used longitudinal or prospective cohort designs; were conducted among workers; provided sufficient data for calculating ORs or relative risk with 95% CIs; were published as original articles in English or Japanese; and were published up to the end of 2017. Study selection, data extraction, quality assessment and statistical syntheses will be conducted by 14 investigators. Any inconsistencies or disagreements will be resolved through discussion. The quality of studies will be evaluated using the Risk of Bias Assessment Tool for Non-randomized Studies.Ethics and dissemination The investigation study will be based on published studies, so ethics approval is not required. The results of this study will be submitted for publication in a scientific peer-reviewed journal. The findings may be useful for assessing risk factors for increased inflammatory markers in the workplace and determining future approaches for preventing CVD, metabolic diseases and psychotic and neurodegenerative disorders

Types of psychosocial job demands and adverse events due to dental mismanagement: a cross sectional study

BACKGROUND: A harsh work environment including psychosocial job demands might cause adverse events due to medical mismanagement, but the association has not been explored. The purpose of the study was to investigate whether some types of psychosocial job demands are associated with adverse events due to dental mismanagement experienced by general dental practitioners. METHODS: A self-administered questionnaire was mailed to members of a local branch of the Japan dental association. A total of 261 dental practitioners responded anonymously (response rate 53%). Psychosocial job demands were measured by a Japanese version of the Copenhagen Psychosocial Questionnaire, which comprises five sub-scales: quantitative demands, cognitive demands, emotional demands, demands for hiding emotions, and sensorial demands. The outcome was defined according to whether the respondent's patients experienced one of the following adverse events due to dental mismanagement at least once during the previous one year: dropping of dental instrument or broken injection needle, soft tissue or nerve injury, accidental bleeding, loss of a tooth root into the maxillary sinus, and emphysema. Associations between each demand index and experience of adverse events were examined by logistic regression analyses adjusting for potential confounders. RESULTS: Emotional demands and sensorial demands were significantly associated with the experience of adverse events (odds ratio = 3.9 for each). Other than the indices, male gender, younger age, practice alone, many dental chairs (five or more), and many patients (30 or more per day) were the risks. Working hours per week and number of paramedical staff had no significant associations. CONCLUSION: Emotional and sensorial job demands are a potential target for the reduction of adverse events due to dental mismanagement

Prevention and management of work-related cardiovascular disorders

Cardiovascular disorders (CVDs) constitute a major burden for health of working populations throughout the world with as much as 50% of all causes of death and at least 25% of work disability. There are some changes in CVD risk factors among occupational classes. This is mainly due to the new types of work-related causes of morbidity associated with the recent developments in global work life, particularly in the industrialized countries. Meanwhile, in the developing countries or those in transition (e.g., in Eastern Europe), CVD mortality is increasing due to major socioeconomic changes, the demographic transition and rapid industrialisation and urbanisation, all leading to growing challenges to cardiovascular health. Better control of known risk factors (i.e., smoking, obesity, physical inactivity, high cholesterol, high blood pressure, and high blood glucose) is effective to prevent CVD incidence. But the expected improvement has not been achieved. The obstacles of achieving such impact are due to lack of awareness, lack of policies and their implementation into practice and shortage of infrastructures and human resources. These are needed for wide-scale and long-term programme implementation. Considering the WHO Global Strategy on Occupational Health for All, the WHO Global Action Plan on Workers’ Health, the WHO Programme on Prevention of Non-communicable Diseases and the ILO Decent Work agenda, the 6th ICOH International Conference on Work Environment and Cardiovascular Diseases adopted the Tokyo Declaration

The Passive Monitoring of Depression and Anxiety Among Workers Using Digital Biomarkers Based on Their Physical Activity and Working Conditions: 2-Week Longitudinal Study

BackgroundDigital data on physical activity are useful for self-monitoring and preventing depression and anxiety. Although previous studies have reported machine or deep learning models that use physical activity for passive monitoring of depression and anxiety, there are no models for workers. The working population has different physical activity patterns from other populations, which is based on commuting, holiday patterns, physical demands, occupations, and industries. These working conditions are useful in optimizing the model used in predicting depression and anxiety. Further, recurrent neural networks increase predictive accuracy by using previous inputs on physical activity, depression, and anxiety. ObjectiveThis study evaluated the performance of a deep learning model optimized for predicting depression and anxiety in workers. Psychological distress was considered a depression and anxiety indicator. MethodsA 2-week longitudinal study was conducted with workers in urban areas in Japan. Absent workers were excluded. In a daily survey, psychological distress was measured using a self-reported questionnaire. As features, activity time by intensity was determined using the Google Fit application. Additionally, we measured age, gender, occupations, employment status, work shift types, working hours, and whether the response date was a working or nonworking day. A deep learning model, using long short-term memory, was developed and validated to predict psychological distress the next day, using features of the previous day. Further, a 5-fold cross-validation method was used to evaluate the performance of the aforementioned model. As the primary indicator of performance, classification accuracy for the severity of the psychological distress (light, subthreshold, and severe) was considered. ResultsA total of 1661 days of supervised data were obtained from 236 workers, who were aged between 20 and 69 years. The overall classification accuracy for psychological distress was 76.3% (SD 0.04%). The classification accuracy for severe-, subthreshold-, and light-level psychological distress was 51.1% (SD 0.05%), 60.6% (SD 0.05%), and 81.6% (SD 0.04%), respectively. The model predicted a light-level psychological distress the next day after the participants had been involved in 3 peaks of activity (in the morning, noon, and evening) on the previous day. Lower activity levels were predicted as subthreshold- and severe-level psychological distress. Different predictive results were observed on the basis of occupations and whether the previous day was a working or nonworking day. ConclusionsThe developed deep learning model showed a similar performance as in previous studies and, in particular, high accuracy for light-level psychological distress. Working conditions and long short-term memory were useful in maintaining the model performance for monitoring depression and anxiety, using digitally recorded physical activity in workers. The developed model can be implemented in mobile apps and may further be practically used by workers to self-monitor and maintain their mental health state