• Safety and Health at Work
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• v.15 no.1
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• pp.102-109
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• 2024

Background: In today's modern world, longer working hours, shift work, and working at night have become major causes of the disruption of our natural circadian rhythms. This study aimed to investigate the effects of the type of shift work (rotating vs. fixed day), duty period (on-duty vs. off-duty), and working period within each shift (nighttime vs. daytime) on the circadian rhythm characteristics of nurses who provide direct patient care. Methods: This cross-sectional study used a purposive sampling method. Cosinor analysis was applied to analyze the actigraphy data of nurses providing direct patient care for seven consecutive days. The linear mixed effects model was then used to determine any variances between shift type, duty period, and working period within each shift for the nurses. Results: The mesor value did not differ according to nurses' shift type, duty period, and working period within each shift. The amplitude was statistically higher in on-duty nurses and in daytime working hours. The acrophase was significantly delayed in nighttime working hours. As well as nurses in rotating shift had experience. Conclusion: Our findings revealed that the peak activity of nurses occurs significantly later at night while working and nurses working during nighttime hours may have a weaker or less distinct circadian rhythm. Thus, this study suggests that limits be placed on the number of rotating nighttime shifts for nurses.

• Health Policy and Management
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• v.27 no.3
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• pp.241-246
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• 2017

Background: The purpose of this study is to investigate the trends on the induced abortion in Korea using social big-data and confirm whether there was time series trends and seasonal characteristics in induced abortion. Methods: From October 1, 2007 to October 24, 2016, we used Naver's data lab query, and the search word was 'induced abortion' in Korean. The average trend of each year was analyzed and the seasonality was analyzed using the cosinor model. Results: There was no significant changes in search volume of abortion during that period. Monthly search volume was the highest in May followed by the order of June and April. On the other hand, the lowest month was December followed by the order of January, and September. The cosinor analysis showed statistically significant seasonal variations (amplitude, 4.46; confidence interval, 1.46-7.47; p< 0.0036). The search volume for induced abortion gradually increased to the lowest point at the end of November and was the highest at the end of May and declined again from June. Conclusion: There has been no significant changes in induced abortion for the past nine years, and seasonal changes in induced abortion have been identified. Therefore, considering the seasonality of the intervention program for the prevention of induced abortion, it will be effective to concentrate on the induced abortion from March to May.

• Journal of Korean Foot and Ankle Society
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• v.25 no.3
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• pp.126-132
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• 2021

Purpose: This study examined whether there are seasonal variations in the number of plantar fasciitis cases from the database of the Korean Health Insurance Review & Assessment Service and an internet search of the volume data related to plantar fasciitis and whether there are correlations between variations. Materials and Methods: The number of plantar fasciitis cases per month was acquired from the Korean Health Insurance Review & Assessment Service from January 2016 to December 2019. The monthly internet relative search volumes for the keywords "plantar fasciitis" and "heel pain" were collected during the same period from DataLab, an internet search query trend service provided by the Korean portal website, Naver. Cosinor analysis was performed to confirm the seasonality of the monthly number of cases and relative search volumes, and Pearson and Spearman correlation analysis was conducted to assess the correlation between them. Results: The number of cases with plantar fasciitis and the relative search volume for the keywords "plantar fasciitis" and "heel pain" all showed significant seasonality (p<0.001), with the highest in the summer and the lowest in the winter. The number of cases with plantar fasciitis was correlated significantly with the relative search volumes of the keywords "plantar fasciitis" (r=0.632; p<0.001) and "heel pain" (r=0.791; p<0.001), respectively. Conclusion: Both the number of cases with plantar fasciitis and the internet search data for related keywords showed seasonality, which was the highest in summer. The number of cases showed a significant correlation with the internet search data for the seasonality of plantar fasciitis. Internet big data could be a complementary resource for researching and monitoring plantar fasciitis.