RT Journal Article
SR Electronic
T1 Relationships between black tea consumption and key health indicators in the world: an ecological study
JF BMJ Open
JO BMJ Open
FD British Medical Journal Publishing Group
SP e000648
DO 10.1136/bmjopen-2011-000648
VO 2
IS 6
A1 Ariel Beresniak
A1 Gerard Duru
A1 Genevieve Berger
A1 Dominique Bremond-Gignac
YR 2012
UL http://bmjopen.bmj.com/content/2/6/e000648.abstract
AB Objectives The aim of this study was to investigate potential statistical relationships between black tea consumption and key health indicators in the world. The research question is: Does tea consumption is correlated with one or more epidemiological indicators? Design Ecological study using a systematic data-mining approach in which the unit of the analysis is a population of one country. Setting Six variables, black tea consumption data and prevalence data of respiratory diseases, infectious diseases, cancer, cardiovascular diseases and diabetes, have been studied at a global level. Participants Data from 50 participating countries in the World Health Survey were investigated. Primary and secondary outcomes measures Level of statistical relationships between variables. Results Principal component analysis established a very high contribution of the black tea consumption parameter on the third axis (81%). The correlation circle confirmed that the ‘black tea’ vector was negatively correlated with the diabetes vector and was not correlated with any of the other four health indicators. A linear correlation model then confirmed a significant statistical correlation between high black tea consumption and low diabetes prevalence. Conclusions This innovative study establishes a linear statistical correlation between high black tea consumption and low diabetes prevalence in the world. These results are consistent with biological and physiological studies conducted on the effect of black tea on diabetes and confirm the results of a previous ecological study in Europe. Further epidemiological research and randomised studies are necessary to investigate the causality.