scholarly journals Cross-national gender differences in the socioeconomic factors associated with smoking in Australia, the United States of America and South Korea

2012 ◽  
Vol 58 (3) ◽  
pp. 345-353 ◽  
Author(s):  
Davina J. French ◽  
Soong-Nang Jang ◽  
Robert J. Tait ◽  
Kaarin J. Anstey
2011 ◽  
Vol 32 (6) ◽  
pp. 655-670 ◽  
Author(s):  
Thomas Oakland ◽  
Kuldeep Singh ◽  
Camelo Callueng ◽  
Gurmit Singh Puri ◽  
Akiko Goen

Age, gender, and cross-national differences of children ages 8- through 16-years-old in India ( n = 400) and the United States of America ( n = 3,200) are examined on four bipolar temperament styles: extroversion-introversion, practical-imaginative, thinking-feeling, and organized-flexible styles. In general, Indian children prefer extroverted to introverted, practical to imaginative, feeling to thinking, and organized to flexible styles. Gender differences among Indian children are significant only on extroversion-introversion. Age differences are found on thinking-feeling and organized-flexible styles. Cross-national differences are found on only one of the four bipolar styles: practical-imaginative. In contrast to children in the United States of America, those in India are more likely to prefer practical styles. Sample limitations (e.g. non-representativeness and small size relative to the population) limit the generalization of these data.


2020 ◽  
Author(s):  
Fu-Chang Hu

Background: How can we anticipate the progression of the ongoing pandemic of the coronavirus disease 2019 (COVID-19)? As a measure of transmissibility, we aimed to estimate concurrently the time-varying reproduction number, R0(t), over time during the COVID-19 pandemic for each of the following 12 heavily-attacked countries: Singapore, South Korea, Japan, Iran, Italy, Spain, Germany, France, Belgium, United Kingdom, the United States of America, and South Africa. Methods: We downloaded the publicly available COVID-19 pandemic data from the WHO COVID-19 Dashboard website (https://covid19.who.int/) for the duration of January 11, 2020 and May 1, 2020. Then, we specified two plausible distributions of serial interval to apply the novel estimation method implemented in the incidence and EpiEstim packages to the data of daily new confirmed cases for robustly estimating R0(t) in the R software. Results: We plotted the epidemic curves of daily new confirmed cases for the 12 selected countries. A clear peak of the epidemic curve appeared in 10 of the 12 selected countries at various time points, and then the epidemic curve declined gradually. However, the United States of America and South Africa happened to have two or more peaks and their epidemic curves either reached a plateau or still climbed up. Almost all curves of the estimated R0(t) monotonically went down to be less than or close to 1.0 up to April 30, 2020 except Singapore, South Korea, Japan, Iran, and South Africa, of which the curves surprisingly went up and down at various time periods during the COVID-19 pandemic. Finally, the United States of America and South Africa were the two countries with the approximate R0(t) ≥ 1.0 at the end of April, and thus they were now facing the harshest battles against the coronavirus among the 12 selected countries. By contrast, Spain, Germany, and France with smaller values of the estimated R0(t) were relatively better than the other 9 countries. Conclusion: Seeing the estimated R0(t) going downhill speedily is more informative than looking for the drops in the daily number of new confirmed cases during an ongoing epidemic of infectious disease. We urge public health authorities and scientists to estimate R0(t) routinely during an epidemic of infectious disease and to report R0(t) daily to the public until the end of the epidemic.


2016 ◽  
Vol 40 (1) ◽  
pp. 41-51 ◽  
Author(s):  
Philip Young P. Hong ◽  
In Han Song ◽  
Sangmi Choi ◽  
Jang Ho Park

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