In total, 44.3% of particle matter 10 (PM10) is fugitive dust, and one of the main sources of fugitive dust generation in Korea is construction work (22%). Construction sites account for 84% of the total business places that have reported fugitive dust generation. Currently, the concentration of fine dust at construction sites is being remotely monitored by government inspection agencies through IoT sensors, but it is difficult to trust that appropriate fine dust reduction measures are being taken, because contractors can avoid taking these measures by submitting false reports or photos. In addition, since the fine dust monitoring system under government management is not an open platform and centralized system, residents near construction sites encounter difficulties in accessing information about fine dust. Therefore, in this study, we designed and constructed a blockchain network model to transparently and reliably provide network participants with the information associated with IoT data and fine dust reduction measures. To operate the blockchain network, we designed the chaincode, DApp, and network architecture. In addition, information on fine dust concentration and reduction measure photos were shared with the participants via the blockchain search tool (Hyperledger Explorer). The proposed blockchain network is expected to form a trust protocol among contractors, government inspection agencies, and citizens.
Objective: In this study, we investigate the effect of depressive symptoms in elderly on general and cancer health screening participation using the large epidemiological study data in South Korea.
Methods: This study was conducted on 1,977 people who responded to a health examination questionnaire among 2,360 adults aged 60 or older who participated in the Korea National Health and Nutrition Examination Survey (KNHANES) in 2020. Depressive symptoms were measured by the Patient Health Questionnaire-9 and classified as minimal (0-4), mild (5-9), and moderate and severe (10-27). To investigate the relationship between depressive symptoms and health screening participation, a multiple logistic regression model controlling covariates was used.
Results: Compared to the group with minimal depressive symptoms, the mild group did not show a significant difference (odd ratio [OR]=0.71, 95% confidence interval [95% CI]=0.45-1.13), but the moderate to severe group showed a significant negative relationship with general health screening participation (OR=0.59, 95% CI=0.35-0.99). There was a significant negative relationship between depressive symptoms and cancer health screening participation (mild group OR=0.77, 95% CI=0.48-1.23; moderate to severe group OR=0.50, 95% CI=0.28-0.87).
Conclusion: This study showed that people with depressive symptoms are less likely to get a general and cancer health screening. In order to promote health screening participation, policies that consider health behavior promotion programs and psychiatric interventions targeting moderate to severe depressive symptom groups are necessary
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