Design: A cross-sectional study.
Setting: Malaysia.
Participants: A subset of 96 participants aged 18 and above.
Primary and secondary outcomes: Ten facial dimensions were measured using direct measurement and 2D photogrammetry. An assessment of inter-rater reliability was performed using intra-class correlation (ICC) of the 2D images. In addition, ICC and Bland-Altman analyses were used to assess the reliability and agreement of 2D photogrammetry with direct measurement.
Results: Except for head breadth and bigonial breadth, which were also found to have low inter-rater reliability, there was no significant difference in the inter-rater mean value of the 2D photogrammetry. The mean measurements derived from direct measurement and 2D photogrammetry were mostly similar. However, statistical differences were noted for two facial dimensions, i.e., bizygomatic breadth and bigonial breadth, and clinically the magnitude of difference was also significant. There were no statistical differences in respect to the remaining eight facial dimensions, where the smallest mean difference was 0.3 mm and biggest mean difference was 1.0 mm. The ICC showed head breadth had poor reliability, whilst Bland-Altman analyses showed seven out of 10 facial dimensions using 2D photogrammetry were accurate, as compared to direct measurement.
Conclusion: Only certain facial measurements can be reliably and accurately measured using 2D photogrammetry, thus it is important to conduct a reliability and validation study before the use of any measurement methods in anthropometric studies. The results of this study also suggest that 2D photogrammetry can be used to supplement direct measurement for certain facial dimensions.
DESIGN: A cross-sectional study.
SETTING: 11 manufacturing factories in Malaysia.
PARTICIPANTS: 177 night-shift workers aged 40-65 years old were compared with 317 non-night-shift workers.
PRIMARY AND SECONDARY OUTCOMES: Participants completed a self-administered questionnaire on socio-demographics and lifestyle factors, 12-item Short Form Health Survey V.2 (SF-12v2) and the Pittsburgh Sleep Quality Index (PSQI). The Baron and Kenny's method, Sobel test and multiple mediation model with bootstrapping were applied to determine whether PSQI score or its components mediated the association between night-shift work and HRQoL.
RESULTS: Night-shift work was associated with sleep impairment and HRQoL. Night-shift workers had significantly lower mean scores in all the eight SF-12 domains (p<0.001). Compared with non-night-shift workers, night-shift workers were significantly more likely to report poorer sleep quality, longer sleep latency, shorter sleep duration, sleep disturbances and daytime dysfunction (p<0.001). Mediation analyses showed that PSQI global score mediated the association between night-shift work and HRQoL. 'Subjective sleep quality' (indirect effect=-0.24, SE=0.14 and bias corrected (BC) 95% CI -0.58 to -0.01) and 'sleep disturbances' (indirect effect=-0.79, SE=0.22 and BC 95% CI -1.30 to -0.42) were mediators for the association between night-shift work and physical well-being, whereas 'sleep latency' (indirect effect=-0.51, SE=0.21 and BC 95% CI -1.02 to -0.16) and 'daytime dysfunction' (indirect effect=-1.11, SE=0.32 and BC 95% CI -1.86 to -0.58) were mediators with respect to mental well-being.
CONCLUSION: Sleep quality partially explains the association between night-shift work and poorer HRQoL. Organisations should treat the sleep quality of night-shift workers as a top priority area for action to improve their employees' overall wellbeing.
METHODS: A cross-sectional study was conducted among Malaysian manufacturing workers, aged 40-65 years old. They completed a self-administered questionnaire on sociodemographics, lifestyle and family history, and the Pittsburgh Sleep Quality Index (PSQI) questionnaire. Waist circumference, blood pressure, fasting blood sugar, triglycerides and high-density lipoprotein levels were measured. Baron and Kenny's method, Sobel test and multiple mediation models with bootstrapping were used to determine whether the PSQI global score or its components mediated the association between night-shift work and MetS.
RESULTS: Of the 494 participants, 177 (36%) worked night shift and 51% were men. The prevalence of MetS was 37%. Night-shift work was independently associated with a twofold increase in the risk of MetS (adjusted OR: 1.92, 95% CI 1.24 to 2.97). However, the association between night-shift work and MetS did not appear to be modified by sex. Night-shift workers also reported significantly poorer sleep quality, longer sleep latency, shorter sleep duration, sleep disturbances and daytime dysfunction. Robust mediation analysis nonetheless showed that neither PSQI global score nor its components mediated the association between night-shift work and MetS.
CONCLUSION: Early screening and management of MetS and the development of programmes to improve sleep quality should be carried out among night-shift workers. Future research should investigate other modifiable mediators linking night-shift work and MetS.
METHODS: The study was a cross-sectional, web-based survey conducted on primary healthcare workers in Kediri Regency, Indonesia, with the highest Omicron case surge worldwide. It was conducted right after the surge between July and August 2022, the third year of the COVID-19 pandemic hit Indonesia. Under coordination with the local government health officials, primary healthcare workers were invited to participate in an online survey. The respondents were asked to evaluate their sociodemography, work conditions, personal life, and perceived stress (using the Perceived Stress Scale) during the pandemic. Their work-life balance was evaluated using the Work/Non-work Interference and Enhancement Scale. We used several hierarchical linear regression models to determine which variables contribute to work stress among primary healthcare workers.
RESULTS: Sociodemographic characteristics, including gender, age, marital status, years of professional experience, and educational level, were not significantly associated with stress levels among our respondents. Separately, work conditions and personal life variables did not associate with stress levels. However, primary healthcare workers' work and personal lives interfere with each other during the pandemic and are associated with their higher stress.
CONCLUSION: During the pandemic, the work life of primary health workers interferes with their personal life more than the interference of personal life on their work life. At the same time, the work life's enhancement on the personal life and vice versa were lower than its interference. Those conditions are associated with higher perceived stress of primary health workers.