No abstract available.
Socioeconomic Factors

No abstract available.
Socioeconomic Factors*

No abstract available.
Atrial Fibrillation ; Socioeconomic Factors

No abstract available.
Korea ; 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*

OBJECTIVES: This study was conducted to implement Health Plus Happiness Plus projects in Gyeongsangnam-Do and assess the policy implications of initiatives to address regional health inequalities. METHODS: Health Plus Happiness Plus projects were started as strategies to address regional health inequalities in Gyeongsangnam-Do. The principles of these projects are taken from the Health Action Zones initiatives in England: participation, partnership, resource concentration in project areas. The time period for these projects is from 2010 to 2017, and the total budget is 5.6 billion won. In 2010, a 6.8 hundred million won total budget was invested in 17 project areas. Such investments fell into four broad categories: establishment of the means and local framework; survey development to analyze the health determinants; development of an education and training center; and establishment of a technical support center. RESULTS: Education and training programs for practitioners and coordinators were provided, and project teams and project promotion committees were established in project areas. Health survey result briefing meetings were held, and 17 health committees were established in project areas. CONCLUSIONS: Health Plus Happiness Plus projects have some problems in relation to participation and partnerships, however, if these principled projects are performed continuously, they will contribute to a reduction of standardized mortality rate and regional health inequalities in Gyeongsangnam-Do and the improvement of residents' well-being in project areas.
Budgets ; Happiness ; Health Surveys ; Investments ; Socioeconomic Factors