Impact of urbanization factors on mortality due to unintentional injuries using panel data regression model and spatial-temporal analysis

Relationships between trauma death, disability, and geographic factors: a systematic review

OBJECTIVE

Trauma is a global health problem. The causes of trauma-related deaths are diverse and may depend in part on socioeconomic and geographical factors; however, there have been few studies addressing such relationships. The aim of this study was to investigate the relationships between trauma and geographical factors in order to support policy recommendations to reduce trauma-related deaths and disability.

METHODS

In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we searched international and Korean databases to retrieve relevant literature published between 2000 and 2020.

RESULTS

Thirty-two studies showed a positive relationship between the outcomes of major trauma and geographical factors. The study investigated regional factors including economic factors such as size of urban areas, gross domestic product, and poverty rate, as well as hospital parameters, such as presence of trauma centers and number of hospital beds. There was a tendency toward higher mortality rates in rural and low-income areas, and most of the studies reported that the presence of trauma centers reduced trauma-related mortality rates.

CONCLUSION

Our study showed that geographic factors influence trauma outcomes. The findings suggest geographical considerations be included in care plans to reduce death and disability caused by trauma.

Statistical modeling to analyze factors affecting the middle-income trap in Indonesia using panel data regression

The Middle-Income Trap (MIT) refers to the situation in which a country's per capita income can reach middle-class levels but remains there for years, making it difficult to move up to a higher income level. Indonesia was declared trapped in MIT in 2014, and in 2019, it was added to the group of upper-middle-income (UM) countries. However, due to COVID-19, it returned to the lower-middle income (UM) group in 2020. Previous studies inspired to see the existence of provinces in MIT Indonesia, so an MIT analysis was carried out for each province. The analysis aims to determine the characteristics of MIT in Indonesia and the factors that influence it and obtain a panel data regression model formed from MIT modeling. Analysis using panel data regression method. The panel data regression model was obtained based on panel data, namely data consisting of a combination of cross-section and time series data. The data used is GRDP per capita for each province in 2010 - 2020 published by the Central Bureau of Statistics (BPS). GRDP per capita data is used as an approach to calculating the MIT index. The results of the study, obtained three variables that have a significant effect on MIT, namely Life Expectancy, Gross Participation Rate, and Gross Fixed Capital Increase with an accuracy model of 97.65 %.

Analysis of the Correlation between Occupational Accidents and Economic Factors in China

One of the important factors affecting the production safety of a country or region is the level of economic development. Avoiding accidents under the condition of ensuring economic development is a problem that needs in-depth research. On the basis of collecting the data of occupational accidents and economic development indicators in China from 2000 to 2020, this paper studies the relationship between occupational accidents and five economic indicators, such as resident consumption, energy consumption, education funds, wage level and research input. The grey working accident model of Gaussian function is established, the occurrence trend of occupational accidents is quantitatively analyzed, and the accident reduction measures are suggested based on the relationship between accidents and economy. The results show that there is a strong correlation between accident and economic indicators, and the comprehensive correlation coefficient among scientific research investment, education funds and accident indicators is significantly higher than that of other economic indicators. Increasing investment in scientific research and education is conducive to improving the quality of workers and training safety professionals and can effectively reduce workplace accidents.