Relationship Between Satisfaction In Life, Income, And Religiosity In The UK

Conceptual Framework

‘Happiness’ and ‘Life Satisfaction’ are subjective yet well researched concepts. Literature reveals that these terms are often interchangeable and is defined by different aspects of life which concludes in subjective wellbeing. They concept may be viewed in two-folds. First material wellbeing or wellness in standard of living which is related to material comfort and privilege or perception of wellbeing or perception of contentment which may or may not be related to actual material success but with other factors such as resilience, faith and acceptance.

Many have argued and established that happiness and satisfaction in life corroborates with religion and spirituality and that they are associated positively. There exists a wide range of academic literature which asserts positive linear relationship between the degree religiosity of a person and their perception or state of well-being and therefore by extension satisfaction in life (such as, Stavrova, Fetchenhauer and Schlosser, 2013). Anand, Jones and Gill (2015) in their paper had concluded that spirituality and life satisfaction score have weakly but positively associated relationship among graduate level students in UK.

Generally, it is perceived that wealthier people being more capable of satisfying their basic needs , are happier that those deprived of it or struggle to meet ends (Ruberton, Gladstone and Lyubomirsky, 2016). Many thus assert that wellbeing depends on economic and financial wellbeing and as such it is driven primarily through materialistic satisfaction through financial prosperity (DeJonge et al., 2016).

This paper has as its aim, the intent to explore and establish the relationship between satisfaction in life of an individual with religiousness and income. It tries to capture whether and how these two aspects affect the satisfaction that a person feels in his or her life, among the residents of the United Kingdom.

Aim of the Research: The relationship of satisfaction in life with that of income and religiosity.

The paper is first introduced by discussing a brief background that is relevant to the topic under study. A conceptual framework is then presented followed by the methodology of the research, relevant analysis of the data and corresponding discussion of the results of the analysis along with the conclusion.

The institution of religion primarily offers to its followers a set of guidelines or moral guidance and social identity. Therefore it is believed to aid its subscribers by playing the role of a support framework of coping with life and feeling a sense of social support and belonging as well as in terms of providing basis of invoking emotional resilience through the concept of “faith” in a higher power. It has been reported to have helped victims of fatal diseases and trauma patients (Jim 2015). It has also been reported that it plays a role in stunting substance abuse and psychological distress (Ivtzan et al. 2013).This all suggests its positive impact towards people’s general attitude towards life and by extension their feelings of satisfaction in life even in the face of the multitudes of problems that life may throw towards them.  Therefore a person who is religious or actively participates in the practices of their religious community are expected to be on a broader scale have a tendency to be better equipped to be satisfied with life.  These two are therefore hypothesized to have positive association.

Methodology

In this regard, the following research hypothesis can be framed:

Hypothesis 1: Religion has a positive influence on how satisfied a person feels in Life.

Poverty or lack of ability to satisfy basic necessities in life naturally hampers the standard of living and ability for a person to enjoy life. Financial worry can be related to stress on many counts, such as standard of health care that can be availed, standard or education to be availed, quality of material possessions and recreational outlets in general. Material bliss or contentment is thus dependent on one’s capital worth and hence income which then is expected to influence the level of difficulties, from at least the material aspects that one may face in life and by extension their level of satisfaction in life (Ruberton, Gladstone and Lyubomirsky 2016). It has been observed from a cross-sectional point of view, that people aim to earn higher in their lives to achieve better life standards and it is presumed that richest people in a nation and across nations are more satisfied with life rather than those who are poor (Diener and Oishi 2013). Therefore income of a person is theorised to have a positive relationship with their level of satisfaction in life.

Hypothesis 2: Income has a positive relationship with Life Satisfaction.

The study follows a quantitative methodology. The two hypothesis are tested by means of data collected from the secondary source, ‘world value survey wave 5’. The analysis in the study is exploratory and deductive. The tentative relationship between religiosity and income with reported satisfaction in life will be addressed and analysed using suitable exploratory and deductive approach.

The data on income, strength of religious belief and perceived satisfaction in life was obtained from the secondary source, world value survey data wave 5 for the United Kingdom. The data consisted of observations from 1041 individuals residing in the United Kingdom covering a wide range of attributes including the ones we are interested in.

The data variables were categorical in nature. The variable representing the feeling of satisfaction in life for each individual had 10 valid scales from 1 being dissatisfied to 10 being satisfied in increasing order of satisfaction. The data consisted of 1008 valid observations of this variable. The variable income too was scaled or categorical, having ten valid categories of income with 1 being the lowest income group and 10 the highest. The data consisted of 814 valid data observations from this variable. The data variable signifying whether the person is religious or not had three valid categories, where 1 stood for being religious, 2 being not religious and 3 stood for being a convinced atheist. Therefore the scale measure religiousness in a descending scale, where increase in level corresponds to decrease in religious commitment.

The study aims to investigate and determine the relationship between the feeling of satisfaction in life and income and satisfaction in life and religiosity. The study then aims to scrutinize the effect of religious adherence and income with that of the level of satisfaction that one experiences in life. The study tries to identify the presence and nature of any tentative linear relationship. Life satisfaction is taken to be the variable that is to be explained or in other words the dependent variable while income and religiosity serve as the explanatory or independent variables.

Data Analysis and Results

The data is analysed using statistical techniques. It makes uses of descriptive and graphical methods to explore the dataset and then makes use of correlation test and regression analysis to deduce about the validity of the hypotheses. The data is assumed to be normally distributed.

The distribution of the level of satisfaction among the participants of the study showed that 10.66% reported to be completely satisfied and 48.32% rated that their level of life satisfaction is between 8 and 9.

The data consisted of 40% people who reported to earn less than the fifth step of income or less than and equal to moderate income group out of the valid observations that are not missing. 21.81% of the observations were missing.

The participants in the dataset consisted of 46.97% religious individuals, 40.15% non-religious individuals and 9.70% who were convinced atheists. 

The mean level of life satisfaction among all the participants was found to be 7.55 with standard error 0.051. The median was 7.55, that is , at least 50% of the individuals rated themselves as being at 7.55 level of satisfaction. The mode was 8. The standard deviation of the life satisfaction rating was 1.644. The skewness coefficient was -0.973 which implies mild negative skewness and kurtosis was observed as 1.738 which is moderately leptokortic. The mean religion was 1.62, median was 1.57 and mode was 1. The standard deviation of religiosity ratings was 0.622, with skewness 0.613 and kurtosis -0.658 that is mildly platykurtic. The income scale had a mean of 6.30 with median 6.47 and mode 7. The standard deviation was 2.583. The measure of skewness was -0.255 and kurtosis -0.955. Therefore income is mildly negatively skewed, almost symmetric and mildly platykurtic, almost mesokurtic.

Statistics
	How satisfied are you with your life	Religious person	Scale of incomes
N	Valid	1038	1008	814
Missing	3	33	227
Mean	7.55	1.62	6.30
Std. Error of Mean	.051	.021	.091
Median	7.72a	1.57a	6.47a
Mode	8	1	7
Std. Deviation	1.644	.662	2.583
Variance	2.703	.438	6.674
Skewness	-.973	.613	-.255
Std. Error of Skewness	.076	.077	.086
Kurtosis	1.738	-.658	-.955
Std. Error of Kurtosis	.152	.154	.171
Percentiles	25	6.61b	1.02b	4.27b
50	7.72	1.57	6.47
75	8.72	2.22	8.51
a. Calculated from grouped data.
b. Percentiles are calculated from grouped data.

Table 1: Descriptive Statistics 

The relationship between life satisfaction and religiosity was then measured using Kendall’s tau for tied cases for ordinal data. The measure was found to be -0.055 and the p-value was found to be 0.041. This was therefore found to be significant at 5% level of significance. Therefore the two variables have mild negative correlation. The correlation implies that higher abhorrence to religion corresponds to lesser satisfaction in life since low value of this variable for religiosity implies higher adherence to religious practices. Spearman’s rho was also found to be significant and equal to -0.064. Therefore the two are found to be negatively related or higher religiosity is suggested to be positively related to life satisfaction. 

Correlations
	How satisfied are you with your life	Religious person
Kendall’s tau_b	How satisfied are you with your life	Correlation Coefficient	1.000	-.055*
Sig. (2-tailed)	.	.041
N	1038	1006
Religious person	Correlation Coefficient	-.055*	1.000
Sig. (2-tailed)	.041	.
N	1006	1008
Spearman’s rho	How satisfied are you with your life	Correlation Coefficient	1.000	-.064*
Sig. (2-tailed)	.	.041
N	1038	1006
Religious person	Correlation Coefficient	-.064*	1.000
Sig. (2-tailed)	.041	.
N	1006	1008
*. Correlation is significant at the 0.05 level (2-tailed).

Table 2: Correlation between Religiousness and Life Satisfaction

The relationship between life satisfaction and income scale was then measured using Kendall’s tau for tied cases for ordinal data. The measure was found to be 0.131 and the p-value was found to be less than 0.0001. This was therefore found to be significant at 5% level of significance. Therefore the two variables have mild positive correlation. The correlation implies that higher income corresponds to higher satisfaction in life. Spearman’s rho was also found to be significant and equal to 0.169. Therefore the two are found to be positively related or higher income is suggested to be positively related to life satisfaction. 

Correlations
	How satisfied are you with your life	Scale of incomes
Kendall’s tau_b	How satisfied are you with your life	Correlation Coefficient	1.000	.131**
Sig. (2-tailed)	.	.000
N	1038	813
Scale of incomes	Correlation Coefficient	.131**	1.000
Sig. (2-tailed)	.000	.
N	813	814
Spearman’s rho	How satisfied are you with your life	Correlation Coefficient	1.000	.169**
Sig. (2-tailed)	.	.000
N	1038	813
Scale of incomes	Correlation Coefficient	.169**	1.000
Sig. (2-tailed)	.000	.
N	813	814
**. Correlation is significant at the 0.01 level (2-tailed).

Conclusion

Table 3: Correlation between Income and Life Satisfaction

Finally, the effects of each covariate that is religiosity and income on the life satisfaction levels were analyzed by means of regression analysis. The VIF values were found to be approximately 1 for both the independent variables therefore the data can be said to be devoid of multi-collinearity. The regression model that was fitted was found to be significant at 5% level of significance, that is, the model significantly explained variation in satisfaction levels. The unit increase in ‘religious person’ variable corresponded with a 0.277 unit decrease in lie satisfaction ratings. That is a person who is non-religious is expected to have decreased ratings by 0.277 as compared to one who is religious and one who is a convinced atheist will experience decreased ratings by 0.277 units as compared to one who is just non-religious. Again, a unit increase in income scale corresponds to an increase in 0.122 units of satisfaction ratings. Both the independent variables were found to be significant at 5% level of significance. The goodness of fit was however found to be 0.042 which is very low. 

Model Summaryb
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
R Square Change	F Change	df1	df2	Sig. F Change
1	.205a	.042	.039	1.611	.042	17.226	2	788	.000
a. Predictors: (Constant), Scale of incomes, Religious person
b. Dependent Variable: How satisfied are you with your life

Table 4: Model Summary 

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	89.440	2	44.720	17.226	.000b
Residual	2045.683	788	2.596
Total	2135.123	790
a. Dependent Variable: How satisfied are you with your life
b. Predictors: (Constant), Scale of incomes, Religious person

Table 5: Regression ANOVA

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.	Collinearity Statistics
B	Std. Error	Beta	Tolerance	VIF
1	(Constant)	7.172	.198		36.273	.000
Religious person	-.227	.087	-.091	-2.596	.010	.992	1.008
Scale of incomes	.122	.022	.192	5.480	.000	.992	1.008
a. Dependent Variable: How satisfied are you with your life

Table 6: Regression Coefficients and VIF

Discussion and Conclusion

The results show that the relationship between the life satisfaction ratings and the religious variable is negative. Here the variable measures degree of religiousness in descending order thus the negative correlation actually implies a positive relationship between the increasing religiosity and life satisfaction. Furthermore the effect of religiosity in the regression model also suggest that for a person who is religious the life satisfaction rating is expected be greater than one who is non-religious or a convinced atheist. This supports the conjecture of the first hypothesis that religiosity has a positive relationship with life satisfaction.

Again it was seen that increase in income corroborates with increase in life satisfaction ratings. The relationship is mildly positive but significant. Furthermore the effect of income was found to influence the life satisfaction ratings in the regression model significantly in a positive way, such that increase in income corresponded with increase in ratings. Therefore this supports the second conjecture that income is positively associated with life satisfaction.

The goodness of fit measure was found to be however low and this implies that the model might not be able to be a very good predictor of the life satisfaction. This is however expected since life satisfaction is complex and there are a lot of factors that may influence it in several ways aside from the two we have studied. Nonetheless, the study concludes that increasing income and religiosity do have some significant positive influence on it.

References

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