BACKGROUND: Although scholarly publishing plays a key role in learning, the role of knowledge translation of scholarly publishing with education and income on public health has not been well established. The objective was to describe how knowledge translation of scholarly publishing impacts on public health.
METHODS: The correlations between the input data and the target data were firstly calculated. After the input data that is not correlated to the target have been removed, the principal component analysis will be performed to avoid multicollinearity problems in the input data. Finally, the multivariate regression method is used to fit the relationship between the principal components and the target data. Thus both dimensionality reduction and personalized optimization oriented a target can be done.
RESULTS: After the public health in China is measured by Life expectancy and Death rate, the Pearson correlation coefficient, principal component analysis, and linear regression method have been performed. It proved that some activities of knowledge translation of scholarly publishing with a focus on health and well-being have the highest correlations with the first principal component. Results are also presented on that the first and the second principal component explain 99.3% of the variation (p<0.01) in Life expectancy and 92.8 % of the variation (p<0.01) in Death rate, respectively.
CONCLUSIONS: Scholarly publishing, education, income, health expenditure, nurses, and midwives appear to have a similarly important effect on public health.