Thursday, June 06, 2013

What matters most to well-being?

Throughout 2011-2012 the UK Annual Population Survey included four questions assessing personal well-being.

Overall, how satisfied are you with your life nowadays?

Overall, to what extent do you feel the things you do in your life are worthwhile?

Overall, how happy did you feel yesterday?

Overall, how anxious did you feel yesterday?

Those taking part in the survey are asked to give their answers on a scale of 0 to 10 where 0 is ‘not at all’ and 10 is ‘completely’.

About 165,000 people were surveyed making this the largest survey of population well-being that has been undertaken  in the UK. The results have been published in the report linked below.

The findings and their presentation certainly throw up some important issues regarding how we prioritize factors which contribute to well-being and how the conceptualization, measurement and analysis of well-being data affects this.

As mentioned above the survey examined subjective reports of well-being covering the evaluative component (life-satisfaction), hedonic component (happiness, anxiety) and eudaimonic aspect (life is worthwhile). If you feel quality of life should incorporate a broader suite of measures the ONS well-being site includes reference to an array of metrics that could be considered to gauge the well-being of society including environmental, financial, work-related and relationship-based factors. These are displayed in an interactive format here and a .pdf summary of the National Well-Being wheel of measures is provided here. However, the point of the current paper was to take many of the factors believed to be important to welfare and to evaluate their unique contribution to reports of subjective well-being. In this sense it captures many of the determinants of quality of life and aims to rank them using the unique variance they explain in regression and following the ranking system below:

Large = contribution of 1.0 percentage point or more to R-square;
Moderate= contribution of .05 < 1.0 percentage point to R-square;
Small= contribution of 0.1 < 0.5 percentage point to R-square;
Very small= contribution of less tthan 0.10 percentage point to R-square.

The authors find that self-rated health is the variable most closely linked to well-being. This is potentially unsurprising considering that there is common method variance in self-report measures asked via questionnaire. Marriage and employment are the next important. Surprisingly disability shows a 'very small' unique contributions to well-being though it is possible that disability is captured through the contribution of the self-rated health variable. Similarly, measures of social status show little relationship to well-being as do other established predictors of well-being such as gender, age, age-squared, and religion (particularly hedonic aspects like happiness and anxiety rather than more evaluative components like life-satisfaction). These findings are important as they demonstrate the relatively small portion of variance in well-being explained by 'key' variables. They also demonstrate the relatively large discrepancies between the contribution of variables and open up questions regarding the level of attention that should be paid to each. Given the sample size, sample representativeness, and reasonably good well-being measures this is particularly the case. A final point, the regression methodology used to evaluate the 'unique contribution' of variables to well-being cannot separate out the causal steps and stages from which individual components lead to changes in well-being. For instance, the contribution of social class to well-being was identified to be small but it could be mediated by health so that when health is included in the regression the effect of social class is largely diminished. Similar arguments could be provided for many of the other factors.

Author Name(s):
Sebnem Oguz, Salah Merad, Dawn Snape, Office for National Statistics

This article uses data from the Annual Population Survey collected between April 2011 and March 2012 which includes measures of personal well-being. It describes the results of regression analysis
– a statistical technique which analyses variation in well-being outcomes by specific characteristics and circumstances of individuals while holding all other characteristics equal. This allows for a better understanding of what matters most to personal well-being than when different factors are considered separately

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