No abstract available.
Socioeconomic Factors

No abstract available.
Socioeconomic Factors*

No abstract available.
Korea ; Socioeconomic Factors

No abstract available.
Atrial Fibrillation ; Socioeconomic Factors

No abstract available.
Mass Screening ; Socioeconomic Factors

The third observation of a longitudinal study on the food and nutrition security of two different socio-economic groups of households in Bai Say commune, An Thi district, Hung Yen province in November 1998. One month after, the harvest showed: there is a significant difference in main occupation, additional job, education level, family size/dependent number of household's member, asset and income sources between the rich high and poor-very poor level. Food shortage is still has occurred by households during pre-harvest period, of which 57.8% of poor and very poor households suffered more than 3 months/year from food shortage.
Family Characteristics ; Food ; Socioeconomic Factors

OBJECTIVEThe human socio-economic development depends on the planet's natural capital. Humans have had a considerable impact on the earth, such as resources depression and environment deterioration. The objective of this study was to assess the impact of socio-economic development on the ecological environment of Wuhan, Hubei Province, China, during the general planning period 2006-2020.

METHODSSupport vector machine (SVM) model was constructed to simulate the process of eco-economic system of Wuhan. Socio-economic factors of urban total ecological footprint (TEF) were selected by partial least squares (PLS) and leave-one-out cross validation (LOOCV). Historical data of socio-economic factors as inputs, and corresponding historical data of TEF as target outputs, were presented to identify and validate the SVM model. When predicted input data after 2005 were presented to trained model as generalization sets, TEFs of 2005, 2006,..., till 2020 were simulated as output in succession.

RESULTSUp to 2020, the district would have suffered an accumulative TEF of 28.374 million gha, which was over 1.5 times that of 2004 and nearly 3 times that of 1988. The per capita EF would be up to 3.019 gha in 2020.

CONCLUSIONSThe simulation indicated that although the increase rate of GDP would be restricted in a lower level during the general planning period, urban ecological environment burden could not respond to the socio-economic circumstances promptly. SVM provides tools for dynamic assessment of regional eco-environment. However, there still exist limitations and disadvantages in the model. We believe that the next logical step in deriving better dynamic models of ecosystem is to integrate SVM and other algorithms or technologies.

The Philippines has been the leading country in Southeast Asia in terms of infections (both in terms of total and active cases) brought forth by the SARS-COV-2 virus, known as the COVID-19 pandemic. We highlight the historical underpinnings of pandemic responses that are related to the Philippines, both globally and locally. We also present some counterfactuals in an economic recession that the pandemic caused. Arguing for fast-track rehabilitation and improvement of digital infrastructure, this development is essential in promoting ecommerce, quality education through remote learning, and the quality of health data generation and analysis. As the world is reminded of the Balmis expedition while the world still grapples to obtain a cure for the pandemic, we look at these tenets of the “new normal” to address issues of social justice in the Philippine setting.
COVID-19 ; Pandemics ; Socioeconomic Factors

Calculating the sample size is a vital step during the planning of a study in order to ensure the desired power for detecting clinically meaningful differences. However, estimating the sample size is not always straightforward. A number of key components should be considered to calculate a suitable sample size. In this paper, general considerations for conducting sample size calculations for inequality tests are summarized.
Clinical Study ; Sample Size* ; Socioeconomic Factors*

Growth acceleration following femoral shaft fracture occasionally results in a significant leg-length inequality with limp. The ability to predict subsequent overgrowth would enable the surgeon to compensate for growth acceleration by providing the appropriate overriding of the fragments before the time union. The purpose of this study was to establish principles which would aid in predicting over growth. Between 1972 May and 1983 September, 115 inward patients who were 16 years old or the younger were treated in the Department of Orthopaedic Surgery of Hanyang University Hospital. In these cases, we analysed the causes of fractures, associated injury and methods of treatment. And also, by use of mentgenogram, evaluated on site, shape and degree of overriding of fractures. And then, the degree of overgrowth of bone was compared with unaffected site and analized by Bell Tompson's split orthoroentgenogram. 1. The average tibial overgrowth after fracture of femoral shaft is 2.2 mm in length. 2. The average femoral overgrowth after fracture of femoral shaft is 9.4 mm in length.
Acceleration ; Child ; Extremities ; Humans ; Socioeconomic Factors