Country Religiosity Declines as Material Security Increases

Abstract

According to the uncertainty hypothesis, religion declines as the quality of life improves. Replicating an earlier study with religious disbelief as the DV, it was predicted that religiosity would decline in developed countries due to greater existential security, including income security (income equality and redistribution via welfare states) and improved health. This study used a uniform data source, improving on the heterogeneous surveys tapped in the earlier work. Predictions were tested by correlation and regression analysis of 114 countries that controlled for Communism and Islamic religion. Religiosity declined with economic and social development (measured by lower agricultural employment and third-level enrollment). income security (low Gini coefficient, high personal taxation tapping the welfare state), and health security (low pathogen prevalence, marginally significant in the regression analysis). Results show that religiosity declines as material security increases, consistent with the uncertainty hypothesis, replicating the earlier study.

Keywords

religiosity uncertainty hypothesis religion as an adaptation economic development existential security pathogen load welfare state Gini coefficient

Religion may be a pan-human adaptation (Sanderson, 2008). Thus, some form of supernatural belief is evidently found in all human societies although some hunter-gatherers are not highly religious (Marlowe, 2010). This adaptationist perspective is bolstered by evidence that religion provides fitness benefits (improved health, increased reproductive success). Religiously active people in modern societies have more children (Blume, 2009; Frejka, & Westoff, 2006; Kaufmann, 2010; Sanderson, 2008), but this may not have been true in ancestral forager communities (Barber, 2012). The possibility that religious involvement reduces stress (Paul-Labrador et al., 2006) and improves health and life expectancy is consistent with a great deal of evidence but remains controversial (Barber, 2004, 2008; Hummer, Rogers, Nam, & Ellison, 1999; Koenig, McCullough, & Larson, 2001; Sloan & Bagiella, 2002).

Evolutionary analysis of religion needs to explain both why religion is observed in most, or all, indigenous societies, and why religious belief is declining in modern societies (Barber, 2011; Zuckerman, 2007). According to the uncertainty hypothesis, religion helps people to deal with uncertainty and anxiety (Li, Cohen, & Kenrick, 2010; Malinowski, 1954; Vail et al., 2010) and it declines in developed countries where residents expect to lead long healthy lives (Barber, 2012). This article tested the hypothesis that religion helps people deal with painful and unpredictable events in their lives and it used cross-national data on the importance attributed to religion (or religiosity, Gallup, 2010). It attempted to replicate an earlier study (Barber, 2011) with disbelief in God as the dependent variable (Zuckerman, 2007) that supported the uncertainty hypothesis.

Although Barber’s (2011) study provided clear evidence for the impact of various dimensions of existential security on religious belief, the data used were heterogeneous being based on varied studies and methodologies thereby introducing a possibility of error despite validation of those data from Zuckerman (2007) against other data types. The present study addressed similar research questions using a uniform source of data (Gallup, 2010) based on the same nationally representative survey conducted globally.

Specific Predictions

The following predictions were tested see (Barber, 2011, for rationale underlying these predictions):

That religiosity would decline with economic development.

That religiosity would decline with the proportion of the population enrolled in third-level education (i.e., all postsecondary programs).

That religiosity would be positively related to income inequality, that is, Gini coefficient (Palani, 2008; Rees, 2009; Solt, Habel, & Grant, 2011).

That societies having an extensive welfare state would be less religious.

That religiosity would increase with the load of infectious diseases and pathogens.

Method

The same method was followed as in Barber (2011), except for modifications and improvements described below.

Sample

The sample of countries consisted of the 114 countries for which Gallup (2010) provided data on religiosity based on nationally representative surveys conducted in 2009 with approximately 1,000 adults sampled for each country. The margin of sampling error averaged about 4% (95% confidence [95% CI] = 2.6%-5.3%). Mean GDP at producer price parity (PPP) was US$10,204 (95% CI = US$8,190-US12,218; Population Reference Bureau, 2006) compared to US$9,500 for the world average, indicating that the countries were representative of the world’s level of economic development.

Dependent Variable

The dependent variable was the proportion of the population reporting that religion was important to them in their daily lives (Gallup, 2010). This measure was validated using Zuckerman’s (2007) data on disbelief in God. Although belief in God is a different dimension from the importance of religion in daily life (or religiosity), one would expect disbelief in God to be negatively correlated with religiosity and this was the case for the 98 countries for which both data types were available, r(96) = –.89, p < .001, indicating a shared variance of 80%, a remarkable level of agreement considering that the Gallup data were for about 5 years later than the Zuckerman data that were also from different surveys.

Control Variables and Independent Variables

See Barber (2011) for detailed description of the independent variables and control variables. These included Islamic religion (Sookhdeo, 2009), Communist state (Anderson, 1994), proportion of labor force in agriculture (a measure of economic development; Central Intelligence Agency [CIA], 2010), enrollment in third-level education (UNESCO, 2010), Gini coefficient of income inequality, personal taxation as a proportion of GDP (Heritage Foundation, 2009), and pathogen load (Fincher & Thornhill, 2008).

A welfare state may shield poor people against economic hardship. Unfortunately there is no good, direct, worldwide measure of how well developed the welfare state is in a particular country although the Organization of Economic Cooperation and Development (OECD) does report welfare expenditure as a proportion of GDP for its members. Welfare states are costly, however, and their cost can be measured indirectly in terms of the level of personal taxation in a country expressed as a proportion of national economic production, or GDP (Heritage Foundation, 2009). I validated this measure against OECD data on welfare expenditure as a proportion of GDP for the 15 countries in the sample for which data were available, r(13) = .84, p < .001 (Adema, Fron, & Ladaique, 2011).

Statistical Procedure

Having ruled out spatial autocorrelation, data were analyzed using OLS (ordinary least squares) regression. All variables were entered using the method of forced entry (see Barber, 2011).

Results

Average religiosity was M = 75.05% ± 2.21 SE (range 16-99). Correlations among religiosity and the predictor variables are presented in Table 1 along with descriptive statistics (means, standard deviations [SDs]) for the predictors. It can be seen that all of the predictors were at least moderately correlated with the dependent variable. Significant negative predictors included Communism, tertiary enrollment, and high personal taxation. Significant positive predictors included Islam religion, agricultural employment, Gini coefficient, and pathogen severity.

Table 1.

Correlations Among Religiosity and Predictors for 114 Countries.

Predictor	1	2	3	4	5	6	7	8
1. Religiosity (%)	-
2. Islam	.41*	-
3. Communist	−.42*	−.10	-
4. Ln agricultural labor (%)	.56*	.36*	.04	-
5. Third-level enrollment (%)	−.70*	−.38*	.30*	−.56*	-
6. Gini coefficient	.44*	−.12	−.44*	.13	−.34*	-
7. Taxation (% GDP)	−.63*	−.45*	.24*	−.36*	.58*	−.42*	-
8. Pathogen load	.61*	.22*	−.44*	.50*	−.61*	.49*	−.41*	-
Mean	75.05	0.37	0.22	2.83	25.03	39.76	21.56	33.32
±SD	23.62	0.48	0.41	1.52	18.44	8.38	11.49	7.09

p < .05; Ln = natural logarithm.

Regression analysis results are presented in Table 2. Religiosity was related to each of the predictor variables in the expected direction, and all of the effects were statistically significant with the exception of parasite prevalence that was marginally significant. Religiosity was higher in Islamic countries and lower in Communist (or former Soviet) countries. Religiosity declined as economic security increased based on more equal distribution of income (low Gini coefficient) and higher taxation rates. Religiosity declined with economic development as assessed by low levels of agricultural labor and with social development as indexed by enrolment in third-level education. Finally, the effect of health security (i.e., reduced pathogen load) was only marginally significant (p < .10) despite having a strong simple correlation with the dependent variable. The fact that the effect of the pathogen load was so much weaker in the regression analysis (Table 2) than in the correlational analysis could be due to shared variance with other predictors, particularly those tapping economic development, social development, and economic security (Table 1).

Table 2.

Effects of Existential Security on Religiosity for 114 Countries (Standardized Regression Coefficients in Parentheses).

Predictor	B	SE B	t	Variance inflation factor
Islam	4.85 (.10)	2.69	1.80*	1.26
Communist	−11.91 (.21)	3.13	3.81**	1.26
Ln agricultural labor (%)	4.13 (.26)	0 .85	4.86**	1.39
Third-level enrollment (%)	−0.30 (.23)	0.070	4.29**	1.51
Gini coefficient	0.31 (.11)	0.15	2.07*	1.39
Taxation (% GDP)	−0.45 (.22)	0.11	4.09**	1.41
Pathogen load	0.28 (.08)	0.18	1.56	1.49
Constant	57.94	9.64	—	—
r ²	0.68
F(6, 106)	32.26**

p < .05. **p < .001; Ln = natural logarithm.

Discussion

All five predictions received some support. Results thus confirm the uncertainty hypothesis for Gallup religiosity data, thereby replicating Barber’s (2011) results using disbelief in God as a dependent variable (see Tables 1 and 2) and supporting earlier research (Gill & Lundsgaarde, 2004; Hollinger, Haller, & Valle-Hollinger, 2007; Norris & Inglehart, 2004; Paul, 2005, 2009; Rees, 2009; Zuckerman, 2007, 2008) .

Results show that the religiosity of a country is predicted by economic development, by favorable health conditions, and by a more equal distribution of income as well as a well-developed welfare state (insofar as this is measured by high levels of personal taxation relative to GDP). These results are consistent with those of Barber for disbelief in God and much other evidence linking existential security with declining religiosity (Norris & Inglehart, 2004; Paul, 2005, 2009; Rees, 2009; Zuckerman, 2007, 2008). Consistency of the present findings with those of Barber is not surprising given that Gallup religiosity was strongly correlated with disbelief in God. Even so, there were intriguing differences. Thus, Islamic religion was a strong negative predictor of disbelief in God (Barber, 2011; Table 2) but had a comparatively weak effect on Gallup religiosity (standardized regression coefficients of .25 vs. .10, respectively, Table 2).

Predictions from the uncertainty hypothesis were supported by the data. This conclusion bolsters the argument that one evolutionary function of religion is to help people cope with uncertainty in their lives, whether it is inability to control the physical ecology (where technological development has a key impact), economic uncertainty associated with income inequality (Palani, 2008; Rees, 2009; Solt et al., 2011), a weak social welfare system (Barber, 2011; Norris & Inglehart, 2004; Paul, 2005, 2009; Zuckerman, 2007, 2008), or epidemic diseases (Barber, 2011) that shorten life expectancy.

The contemporary decline in the importance of religion in developed countries is understandable as an adaptive response to increasing existential security. Perhaps interest in the supernatural is merely diverted away from organized religion to other forms of expression, such as science fiction, television soap operas, and so forth (Barber, 2012). It would also be interesting to investigate whether the social advantages of religious participation are replaced by secular pursuits, such as sports, as Wann, Melznick, Russell, and Pease (2001, pp. 198-200) suggest. Perhaps the stress management role of religion is replaced by increased use of antianxiety medications, recreational drugs, and secular practices such as exercise and psychotherapy. Whatever about the future of religion, this study finds that the current global distribution of religiosity is strongly predicted by varying levels of material security.

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

Author Biography

Nigel Barber hails from Ireland. He received his PhD in biopsychology from Hunter College, CUNY, and taught psychology at Bemidji State University and Birmingham Southern College. A prolific cross-national researcher, he accounts for societal differences in sexual and reproductive behavior using an innovative approach, known as Evolutionary Social Science. Books include Why Parents Matter, The Science of Romance, Kindness in a Cruel World, The Myth of Culture: Why We Need a Genuine Natural Science of Societies, and Why Atheism Will Replace Religion: The Triumph of Earthly Pleasures Over Pie in the Sky. The author blogs at Psychology Today () and the Huffington Post http://blogs.psychologytoday.com/blog/the-human-beast

References

Adema

Fron

Ladaique

(2011). Is the European welfare state really more expensive? (OECD Social Employment, and Migration Working Papers, No. 124). Retrieved from https://dx-doi-org.web.bisu.edu.cn/10.1787/5kg2d2d4pbf0-enon11/21/2011

Anderson

(1994). Religion, state and politics in the Soviet Union. Cambridge, UK: Cambridge University Press.

Barber

(2004). Kindness in a cruel world: The evolution of altruism. Amherst, NY: Prometheus.

Barber

(2008). The myth of culture: Why we need a genuine natural science of societies. Cambridge, UK: Cambridge Scholars Press.

Barber

(2011). A cross-national test of the uncertainty hypothesis of religious belief. Cross-Cultural Research, 45, 318-333.

Barber

(2012). Why atheism will replace religion: The triumph of earthly pleasures over pie in the sky. Retrieved from http://www.amazon.com/Atheism-Will-Replace-Religion-ebook/dp/B00886ZSJ6/

Blume

(2009). The reproductive benefits of religious affiliation. In Voland

Schiefenhovel

(Eds.), The biological evolution of religious mind and behavior (pp. 117-126). New York, NY: Springer.

Central Intelligence Agency. (2010). The world factbook. Washington, DC: Author.

Fincher

C. L.

Thornhill

(2008). Assortative sociality, limited dispersal, infectious disease and the genesis of the global pattern of religious diversity. Proceedings of the Royal Society of London, 275, 2587-2594.

10.

Frejka

Westoff

C. S.

(2006). Religion, religiousness, and fertility in the U.S. and Europe. Working Paper WP 2006-013. Rostock, Germany: Max Planck Institute for Demographic Research.

11.

Gallup. (2010). Religiosity highest in world’s poorest nations. Retrieved from http://www.gallup.com

12.

Gill

Lundsgaarde

(2004). State welfare spending and religiosity. Rationality and Society, 16, 399-436.

13.

Heritage Foundation. (2009). Index of economic freedom. Retrieved from http://wwww.heritage.org/index/ranking.aspx

14.

Hollinger

Haller

Valle-Hollinger

(2007). Christian religion, society and the state in the modern world. Innovation: The Journal of Social Science Research, 20, 133-157.

15.

Hummer

R. A.

Rogers

R. G.

Nam

C. B.

Ellison

C. G.

(1999). Religious involvement and U.S. adult mortality. Demography, 36, 273-285.

16.

Kaufmann

(2010). Shall the religious inherit the earth? London: Profile books.

17.

Koenig

H. G.

McCullough

M. E.

Larson

D. B.

(2001). Handbook of religion and health. New York, NY: Oxford University Press.

18.

Y. J.

Cohen

A. B.

Kenrick

D. T.

(2010). Mating competitors increase religious beliefs. Journal of Experimental Social Psychology, 46, 428-431.

19.

Malinowski

(1954). Magic, science and religion, and other essays. Garden City, NY: Doubleday.

20.

Marlowe

(2010). The Hadza hunter-gatherers of Tanzania. Berkeley: University of California Press.

21.

Norris

Inglehart

(2004). Sacred and secular: Religion and politics worldwide. Cambridge, UK: Cambridge University Press.

22.

Palani

(2008). The effect of religiosity on income inequality. Journal of Political and International Affairs, 61-70.

23.

Paul

(2005). Cross-national correlations of quantifiable societal health with popular religiosity and secularism in the prosperous democracies. Journal of Religion and Society, 7. Retrieved from http://www.moses.creighton.edu/JRS/2005/2005-11.html.

24.

Paul

(2009). The chronic dependence of popular religiosity upon dysfunctional psychological conditions. Evolutionary Psychology, 7, 398-441.

25.

Paul-Labrador

M. D.

Polk

J. H.

Dwyer

Velasquez

Nidich

Rainforth

(2006). Effects of a randomized controlled trial of transcendental meditation on components of the metabolic syndrome in subjects with coronary heart disease. Archives of Internal Medicine, 166, 1218-1224.

26.

Population Reference Bureau. (2006). World population datasheet. Washington, DC: Author.

27.

Rees

T. J.

(2009). Is personal insecurity a cause of cross-national differences in the intensity of religious belief? Journal of Religion and Society, 11, 1-24.

28.

Sanderson

S. K.

(2008). Adaptation, evolution, and religion. Religion, 38, 141-156.

29.

Sloan

R. P.

Bagiella

(2002). Claims about religious involvement and health outcomes. Annals of Behavioral Medicine, 24, 14-21.

30.

Solt

Habel

Grant

J. T.

(2011). Economic inequality, relative power, and religiosity. Social Science Quarterly, 92, 447-465.

31.

Sookhdeo

(2009). Freedom to believe: Challenging Islam’s apostasy law. Three Rivers, MI: Isaac Publishing.

32.

UNESCO. (2010). Retrieved from http://www.nationmaster.com/graph/edu_ter_enr-education-tertiary-enrollment

33.

Vail

K. E.

Rothschild

Z. K.

Weise

D. R.

Solomon

Pysczynski

Greenberg

(2010). A terror management analysis of the psychological functions of religion. Personality and Social Psychology Review, 14, 84-94.

34.

Wann

D. L.

Melznick

M. J.

Russell

G. W.

Pease

D. G.

(2001). Sport fans: The psychology and social impact of spectators .New York, NY: Routledge.

35.

Zuckerman

(2007). Atheism: contemporary numbers and patterns. In Martin

(Ed.), The Cambridge companion to atheism (pp. 47-68). Cambridge, UK: Cambridge University Press.

36.

Zuckerman

(2008). Society without God: What the least religious nations can tell us about contentment. New York, NY: New York University Press.