What's Behind the “Nones‐sense”? Change Over Time in Factors Predicting Likelihood of Religious Nonaffiliation in the United States

Abstract

The proportion of people in the United States who identify as unaffiliated with any religious tradition (Nones) has risen steadily since the 1990s. Empirical investigations have examined this phenomenon, and point to a range of sociodemographic and associational variables as significant predictors of religious nonaffiliation. To build on these, the research reported here uses nearly five decades of General Social Survey data and binary logistic regression to examine change over time in the direction and size of effect on the likelihood that various factors predict religious nonaffiliation. While some factors (like age and political orientation) behave as expected over time, other factors decrease in their effect on likelihood (e.g., residence in the Far West), lose effect on likelihood (e.g., being college‐educated), or never showed likelihood of effect in the first place (e.g., residence in New England).

Religious Exiting and Social Networks: Computer Simulations of Religious/Secular Pluralism

“…However, recent research has shown that the religiously unaffiliated in the US are becoming more and more representative of the population as a whole (Strawn 2019). The most obvious explanation for this is that the nonreligious are becoming an increasingly large segment of the entire population.…”

“…As the nonreligious expand in size, they must necessarily begin to look like the population in general because they are more of the population. Strawn (2019) shows that several formerly important correlates of disaffiliation are no longer strong correlates, such as age, sex, educational attainment, and income. While atheists -a subset of the nonreligious -remain distinct in a number of ways (Cragun 2014), the growth of the nonreligious in the US has reduced the distinctiveness of the nonreligious, just as it has done in other countries where the nonreligious have seen rapid growth, such as Canada (Thiessen & Wilkins-Laflamme 2017 and the UK (Voas & McAndrew 2012;Voas 2015;Voas & Crockett 2005).…”

“…Despite having ascertained that there are a number of ways in which the nonaffiliated are (or were) distinct from the religious, scholars' ability to predict who would leave religions and who would stay has never been very good. In Strawn's (2019) logistic regression models for various time periods, he is never able to account for more than about 13% of the variation in who is affiliated with a religion and who is not. Uecker et al (2007), who include some additional behavioral variables in their models predicting who affiliates with a religion and who does not (e.g., smoking marijuana, cohabiting), were able to account for just 6% of the variation in who leaves religions.…”

“…Statistical models have consistently found age, sex, educational attainment, income, race, political views, and geographic region (in the US) to be important correlates of religious non-affiliation and atheism (Glenn 1987;Hadaway 1980Hadaway , 1989Altemeyer and Hunsberger 1997;Strawn 2019). However, there are some problems with these variables as an explanation for why people leave religion.…”

“…However, there are some problems with these variables as an explanation for why people leave religion. As Strawn (2019) illustrates, the ability of these variables to predict who will exit religion and who will stay has varied from study to study and from region to region (Norris and Inglehart 2004;Storm 2017Storm , 2009Voas 2003Voas , 2007Voas , 2014Hayes 2000). Not every study has included the same variables despite these being common demographic considerations (Uecker, Regnerus, and Vaaler 2007) and some studies have focused more on people switching religions (Sherkat 2001(Sherkat , 2014Hadaway and Roof 1979) than on people leaving religion altogether Smith 2009, 2015;Cragun 2007).…”