ORCID Profile
0000-0002-6229-1064
Current Organisations
Royal Adelaide Hospital
,
University of Adelaide
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Publisher: Wiley
Date: 17-12-2023
DOI: 10.1111/PHN.13158
Abstract: Previous studies have not fully reported the strength and independency of the correlation of nursing workforce to life expectancy. This study advances that nursing workforce is a major independent contributor to life expectancy at birth (LEB) globally and regionally. A cross‐sectional study was conducted at population level. Ecological data were extracted from the United Nations agencies for 215 populations. Each population is considered a research subject. The correlation between nursing workforce and LEB was analyzed with scatter plots, bivariate correlation, partial correlation, and multiple linear regression analyses, Analysis of Variance post hoc and independent T‐test. Economic affluence, urban lifestyle and obesity were included as the potential confounders in this study. Not applicable Nursing workforce correlated to LEB and this relationship remained regardless of the competition of economic affluence, urbanization, and obesity. Second to economic affluence, nursing workforce showed the greatest influence on LEB. In total, 64.50% of LEB was explained in this study. Nursing workforce was a determinant of regional variations of LEB. Nursing workforce may be a significant contributor to LEB globally and regionally. This contribution was independent of the potential confounding effects of economic affluence, urbanization, and obesity.
Publisher: Scientific Research Publishing, Inc.
Date: 2018
Publisher: Research Square Platform LLC
Date: 16-06-2023
DOI: 10.21203/RS.3.RS-3036260/V1
Abstract: Objective Relaxed natural selection has been indexed with the Biological State Index ( I bs ), which indicates the opportunity for an average member of a population to pass genes to the next generation. This study explores the correlation of I bs to adolescent obesity prevalence. Methods Population level variables (adolescent obesity prevalence, self-calculated I bs , GDP, urbanization and calories) are extracted from or calculated with the United Nations data agencies for the correlation analyses. To examine the I bs -adolescent obesity relationship, the five non-normally distributed variables are analysed in curvilinear regression models with raw data and linear regressions with log-transformed data. Countries are grouped for exploring the regional I bs -adolescent obesity correlations. Results Linear correlation and the first order curvilinear regression identified that I bs -adolescent obesity correlation is significant, and this relationship remains in the third order curvilinear regression and partial correlation when the confounding effects of GDP, urbanization and calories are removed. I bs -adolescent obesity correlation also presents in different country groupings. It is highlighted that I bs -adolescent obesity is significantly stronger in developing countries than developed countries. Stepwise multiple linear regression identified I bs as the second most influential risk factor for adolescent obesity. Caloric intake does not show significant effects on predicting adolescent obesity in both enter and stepwise regression models. Conclusions Reduced natural selection may drive obesity associated genetic background to accumulate in population through allowing people to participate in reproduction. The magnitude of reduced natural selection correlates with adolescent obesity prevalence. This suggests that reduced natural selection is another major risk factor for adolescent obesity.
Publisher: Public Library of Science (PLoS)
Date: 29-09-2023
Publisher: Informa UK Limited
Date: 02-2022
DOI: 10.2147/IJGM.S333004
Publisher: Cold Spring Harbor Laboratory
Date: 03-01-2022
DOI: 10.1101/2022.01.02.22268623
Abstract: Large households/families create more positive psychological well-being which may offer a life course protection against dementia development and deliver more comprehensive healthcare to dementia patients. Dementia specific mortality rates of the 183 member states of World Health Organization were calculated and matched with the respective country data on household size, Gross Domestic Product (GDP), urban and ageing. Scatter plots were produced to explore and visualize the correlations between household size and dementia mortality rates. Pearson’s and nonparametric correlations were used to evaluate the strength and direction of the associations between household size and all other variables. Partial correlation of Pearson’s moment-product approach was used to identify that household size protects against dementia regardless of the competing effects from ageing, GDP and urbanization. Multiple regression identified large household was a significant predictor of dementia mortality. Household size was in a negative and moderately strong correlation (r = -0.6034, p 0.001) with dementia mortality. This relationship was confirmed in both Pearson r (r= - 0.524, p .001) and nonparametric ( rho □=□-0.579, p □ □0.001) analyses. Regardless of the contribution of ageing, SES and urban lifestyle to dementia mortality, large household was an independent predictor of dementia mortality (r = -0.331, p .001) in partial correlation analysis. Stepwise multiple regression analysis selected large household as the variable having the greatest contribution to dementia mortality with R 2 = 0.263 while ageing was placed second increasing R 2 to 0.259. GDP and urbanization were removed as having no statistically significant influence on dementia mortality. Independent of ageing, urbanization and GDP, large household protects against dementia mortality. As part of dementia prevention, healthcare practitioners should encourage people to increase their positive interactions with persons from their neighbourhood or other fields where large household/family size is hard to achieve.
Publisher: Elsevier BV
Date: 09-2022
DOI: 10.1016/J.EJIM.2022.06.006
Abstract: Previous cross-sectional studies generally did not fully consider the potential confounding factors associated with physician impact on overall population health. This ecological study controlled for health, demographic and socioeconomic confounders while using total physician density for predicting overall population health globally and regionally. Ecological data were extracted from the United Nations agencies for 215 populations. Considering the competing effects of economic affluence, urban advantages and obesity, correlations between physician density and life expectancy at birth (LEB) were analysed with scatter plots, bivariate correlation, partial correlation and multiple linear regression analyses. Countries are also grouped for exploring the regional correlations between physician density and LEB. Physician density correlates to LEB and this relationship remains regardless of the competition of the in idual confounders, economic affluence, urbanization and obesity, or their combination. Physician density has the greatest influence on LEB, while economic affluence is second. Physician density explains 64.89% of LEB in this study. Together with constant bivariate correlations in country groupings, power correlation without a plateau or U shape in the trendline of the scatterplots, suggests that a shortage of physicians is a worldwide issue. Physician density is a major independent contributor for LEB both globally and with special regard to the developing world. Telehealth may be an alternative to increase physicians' capacity while funding for increasing physician employment is desirable.
Publisher: BMJ
Date: 03-2016
Publisher: Wiley
Date: 17-09-2023
DOI: 10.1111/INR.12887
Publisher: Springer Science and Business Media LLC
Date: 16-08-2018
Publisher: OMICS Publishing Group
Date: 2016
Publisher: Public Library of Science (PLoS)
Date: 03-03-2022
DOI: 10.1371/JOURNAL.PONE.0263309
Abstract: Large households/families may create more happiness and offer more comprehensive healthcare among the members. We correlated household size to dementia mortality rate at population level for analysing its protecting role against dementia mortality. This is a retrospective cross-sectional study. Dementia specific mortality rates of the 183 member states of World Health Organization were calculated and matched with the respective country data on household size, Gross Domestic Product (GDP), urban population and ageing. Scatter plots were produced to explore and visualize the correlations between household size and dementia mortality rates. Pearson’s and nonparametric correlations were used to evaluate the strength and direction of the associations between household size and all other variables. Partial correlation of Pearson’s approach was used to identify that household size protects against dementia regardless of the competing effects from ageing, GDP and urbanization. Multiple regression was used to identify significant predictors of dementia mortality. Household size was in a negative and moderately strong correlation (r = -0.6034, p 0.001) with dementia mortality. This relationship was confirmed in both Pearson r (r = - 0.524, p .001) and nonparametric (rho = -0.579, p 0.001) analyses. When we controlled for the contribution of ageing, socio-economic status and urban lifestyle in partial correlation analysis, large household was still in inverse and significant correlation to dementia mortality (r = −0.331, p .001). This suggested that, statistically, large household protect against dementia mortality regardless of the contributing effects of ageing, socio-economic status and urban lifestyle. Stepwise multiple regression analysis selected large household as the variable having the greatest contribution to dementia mortality with R 2 = 0.263 while ageing was placed second increasing R 2 to 0.259. GDP and urbanization were removed as having no statistically significant influence on dementia mortality. While acknowledging ageing, urban lifestyle and greater GDP associated with dementia mortality, this study suggested that, at population level, household size was another risk factor for dementia mortality. As part of dementia prevention, healthcare practitioners should encourage people to increase their positive interactions with persons from their neighbourhood or other fields where large household/family size is hard to achieve.
Publisher: Wiley
Date: 17-03-2023
DOI: 10.1002/FSN3.3300
Abstract: Consumption of red meat instead of white meat has typically been associated with cardiovascular diseases (CVDs). Reflecting actual diet patterns, this study explored the role of total meat (red + white) in predicting CVD incidence. Data from 217 countries were extracted from United Nations agencies for the analyses in five steps. Bivariate correlations were applied to examine the relationship between total meat and CVD incidence globally and regionally. Partial correlation was applied to identify that total meat was an independent predictor of CVD incidence while socioeconomic status, obesity, and urbanization were statistically constant. Stepwise linear regression was conducted for selecting the significant predictor of CVD incidence. SPSS 28 and Microsoft Excel were used for correlation analyses. Globally, total meat correlated to CVD incidence strongly and significantly in bivariate correlation models. This relationship remained significant in partial correlation when socioeconomic status, obesity, and urbanization were statistically kept constant. Stepwise multiple regression identified that, second to socioeconomic status, total meat was a significant predictor of CVD incidence. Total meat correlated to CVD incidence in different country groupings. However, the correlations between total meat and CVD incidence were significantly stronger in developing countries than in developed countries. Worldwide, total meat (flesh) consumption correlated to CVD incidence independently, but significantly stronger in developing countries than in developed countries. This correlation is worth exploring further in longitudinal cohort studies.
Publisher: Elsevier BV
Date: 11-2022
DOI: 10.1016/J.PUHE.2022.08.016
Abstract: This article examines the politico-scientific mechanism, which leads nations to declare an epidemic or a pandemic finished, irrespective of the actual epidemiological situation at a given time. A historical comparison is made with the famous behavior of Emperor Justinian I (482-565 CE) during the plague pandemic named after him (part of the first plague pandemic). Finally, a reference to the importance of the multidisciplinary study of the history of medicine and the intersection between pandemics and wars is made.
Publisher: Springer Science and Business Media LLC
Date: 02-06-2016
Publisher: Springer Science and Business Media LLC
Date: 18-04-2016
Publisher: American Institute of Mathematical Sciences (AIMS)
Date: 2016
Publisher: Springer Science and Business Media LLC
Date: 26-09-2018
Publisher: Wiley
Date: 24-08-2018
DOI: 10.1111/EVA.12523
Publisher: Public Library of Science (PLoS)
Date: 18-07-2018
No related grants have been discovered for Wenpeng You.