Significant indicators and determinants of happiness: evidence from a UK survey and revealed by a data-driven systems modelling approach

Publication type

Journal Article

Published in

Social Sciences


Yuanlin Gu and Hua-Liang Wei

Publication date


This study aims to establish a quantitative relationship between lifestyle and happiness in the UK based on over 10,000 surveyed samples with 63 lifestyle variables from the UK Understanding Society Data. Transparent parametric models are built and a number of significant explanatory variables (lifestyle indicators) have been identified using a systems engineering modelling approach. Specifically; based on the traditional orthogonal forward regression (OFR) algorithm; the study introduces a new metrics; with which the impacts of lifestyle variables (and/or their interactions) can be quantitatively measured and identified one by one. These identified significant indicators provide a meaningful parsimonious representation of the relationship between happiness and lifestyle; revealing how happiness quantitatively depends on lifestyle; and how the lifestyle variables interactively affect happiness. For example; the quantitative results of a linear model indicate that lifestyle variables such as ‘health’; ‘income’; and ‘retirement’; impacts happiness significantly. Furthermore; the results of a bilinear model show that some interaction variables such as ‘retired’ together with ‘elder’; ‘fair health’ together with ‘low-income’ and so on; are significantly related to happiness.







Computing and Well Being


Open Access; This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).