Global human obesity and political globalization; asymmetric relationship through world human development levels.
Mubbasher MunirZahrahtul Amani ZakariaReda AlhajjMumtazimah Binti MohamadAtif Amin BaigNoman ArshedPublished in: Nutrition and health (2022)
Purpose - Political globalization is a crucial and distinct component of strengthening global organizations. Obesity is a global epidemic in a few nations, and it is on the verge of becoming a pandemic that would bring plenty of diseases. This research aims to see how the political globalization index affects worldwide human obesity concerning global human development levels. Methods- To assess any cross-sectional dependence among observed 109 nations, the yearly period from 1990 to 2017 is analyzed using second generation panel data methods. KAO panel cointegration test and Fully Modified Least Square model were used to meet our objectives. Finding- Low level of political globalization tends to increase global human obesity because countries cannot sway international decisions and resources towards them. While the high level of political globalization tends to reduce obesity because it can control and amends international decisions. For the regression model, a fully modified Least Square model was utilized. The study observed that the R squared values for all models are healthy, with a minimum of 87 percent variables explaining differences in global obesity at the country level. Originality: There is very important to tackle the globalization issue to reduce global human obesity. With the simplicity of dietary options and the amount of physical labour they undergo in their agricultural duties, an increase in rural population percentage tends to lower the average national obesity value.
Keyphrases
- insulin resistance
- metabolic syndrome
- endothelial cells
- weight loss
- type diabetes
- high fat diet induced
- weight gain
- induced pluripotent stem cells
- pluripotent stem cells
- cross sectional
- sars cov
- body mass index
- south africa
- risk assessment
- physical activity
- deep learning
- electronic health record
- machine learning
- artificial intelligence