J Relig Health DOI 10.1007/s10943-014-9859-6 ORIGINAL PAPER

True Believers? Religion, Physiology, and Perceived Body Weight in Texas Andrea L. Ruiz • Gabriel A. Acevedo

Ó Springer Science+Business Media New York 2014

Abstract This paper examines relationships between body weight, religion, and gender while controlling for relevant covariates and body mass index (BMI), a measure of physical/biological body type. Using data from the 2004 Survey of Texas Adults (n = 1,504), we present results of ordered logistic regression models which indicate that religious factors work distinctly for men and women when controlling for BMI. While church attendance is associated with lower odds of overweight perceptions among women, it is religious salience that is associated with lower odds of self-reported excess weight in men. Implications for research which associates religious and physiological factors are discussed. Keywords

Religion
Catholics
Body
Gender
Texas

Introduction A growing area of research involves the topic of body image, and particularly, the various factors involved with the individual perceptions of body weight (Harris 2006; Koch et al. 2005; Brener et al. 2004; Chang and Christakis 2001; Hunt and Macintyre 2001; Lovejoy 2001; Feingold and Mazella 1998; Levinson et al. 1986). Previous research on self-perceived body weight has produced discordant findings and conflicting viewpoints on the influencing agents of such perceptions. On the one hand, scholars argue that actual body weight does not influence self-perception of size, and typically, individuals experiencing

A. L. Ruiz (&) Department of Sociology, The Pennsylvania State University, 211 Oswald Tower, University Park, PA 16802, USA e-mail: [email protected] G. A. Acevedo Department of Sociology, The University of Texas at San Antonio, San Antonio, TX, USA e-mail: [email protected]

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distortion in body weight perceptions are unable to consistently gauge their size with their weight (Tovee et al. 2000; Strawbridge et al. 1998). On the contrary, other studies maintain that physical weight does influence self-conceptions of weight, but that these individuals are cognitively distorted. Although they accurately perceive their body in accordance to its measurements, they are nevertheless dissatisfied with their looks (Chang and Christakis 2001; Tovee et al. 2000). While some research finds that religion primarily promotes feelings of satisfaction and confidence in self-image, other studies note its influence in fostering body dissatisfaction (Kim et al. 2003; Ferraro 1998). Kim et al. (2003) found that higher levels of religious commitment increase the odds of underestimating body weight. Higher levels of church participation and attendance are found to influence self-acceptance and satisfaction with body weight while controlling for body mass index (BMI) (Kim 2007). While this line of inquiry does demonstrate a robust association between religion and weight perceptions, most of these studies are characterized by sampling limitations (Park 2011; Brener et al. 2004) and a lack of relevant statistical controls (Furnham et al. 2002). Furthermore, few studies highlight the effects of religion and gender on self-conceptions of weight. Our study addresses this important gap in the literature by examining the effects of religion on gender-specific perceptions of body weight. The remaining sections of this paper will proceed as follows. We begin with a review of literature which focuses on the relationship between gender and perceptions of body weight. We then discuss several religious dimensions and their potential links to selfconceptions of body weight. To empirically examine these issues, we draw from the 2004 Survey of Texas Adults (SoTA) (n = 1,504) a statewide sample of adult residents. After presenting results, we discuss the implications of our findings and study limitations. We conclude with suggestions for further inquiry.

Theoretical and Empirical Background Weight Perceptions and Gender Leading medical and public health organizations have emphasized the severity of America’s eating disorder epidemic (APA 2011; NEDA 2012; NIMH 2011). One overarching theme emerging in various scientific disciplines is the distinctive effect of eating disorders on men and women (Cussins 2001; Furnham et al. 2002). Scholars note that negative weight perceptions among females in Western culture often result from unrealistic beauty standards and sexualized evaluative tendencies found in American society (Cussins 2001; Wiederman 2000). This element of contemporary American culture has been linked to deleterious physical and mental health outcomes among females (Cussins 2001). According to one study, women who by national standards are not overweight still report body dissatisfaction during physical intimacy with a partner (Wiederman 2000). Accordingly, scholars conclude that such forms of negative self-evaluation may be attributed to Western values which foster unrealistic standards for female beauty (Frederickson and Roberts 1997; Wiederman 2000). Considering the discussion above, we ask what other elements of Western culture might contribute to this trend. According to one study, consumerism is the ‘‘promotion of commodities’’ which compels individuals to depend heavily on the opinions of others (Lasch 1984:28). This implies that public scrutiny potentially causes feelings of vulnerability and low self-esteem. Media representations may also provide a catalyst for the

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development of negative self-evaluation. While we are sympathetic to the general themes established in these culturalist approaches, we propose that religion may offer both a plausible and empirically verifiable framework from which to better understand the cultural dynamics of body perceptions. Weight Perception and the Religion–Health Connection Empirical research continues to amass a formidable body of evidence suggesting salutatory effects from religion on a host of physical and mental health outcomes. Religious salience has been found to be positively associated with overall health and well-being (Ellison and Levin 1998; Sherkat and Ellison 1999), and other studies affirm that religious social networks and religious involvement enhance overall health and health behaviors by encouraging proactive living habits and abstinence from high-risk activities (Hill et al. 2007; Strawbridge et al. 1998). Finally, religious devotion (e.g., frequency of prayer), frequent church attendance, and sectarian affiliation have also been linked to favorable health outcomes and the abstinence of high-risk lifestyles (Hill et al. 2006; Ellison and Levin 1998; Kim 2007; Krause 1998; Levin 1994; Mason et al. 2013). These robust findings offer compelling evidence concerning religion’s role in impacting individual health and furthermore imply that human behaviors and beliefs are strongly influenced by religious piety. This raises two important questions. First, if religion can influence both physical and mental health, could it also influence self-conceptions of body weight? Secondly, does the influence of religion work distinctively for men and women? One could potentially argue that specific components of physical health, like weight and body size perceptions, might be associated with religion. Theologically, we can look to the Christian tradition and specific doctrinal statements on creationism which describe the human body as ‘‘the temple of the Lord’’ (1 Cor. 6:19, New Oxford Annotated Bible) and emphasize the sacredness of the human form (Gen. 1:26; Rom. 12:1). In their experimental study, Boyatzis et al. (2007) found that for women, reading religious affirmations of the human body improved self perceptions of body image. Additionally, the institution of religion is argued to serve as an ‘‘enclave from the societal norms of thinness’’ (Kim 2007:122), suggesting that higher levels of religiosity are associated with greater body satisfaction. Moreover, Ellison and colleagues explain that having a relationship with a divine being who loves them unconditionally is a source of self-value (Ellison and Levin 1998; Sherkat and Ellison 1999). On the other hand, little empirical evidence exists which contradicts this general pattern. Several notable exceptions claim that religion may confer noxious effects to bodily conceptions of the self. The prevalence of obesity has been found to be greater among those with high levels of religious attendance (Gillum 2006). Cline and Ferraro (2006) find that among women, an affiliation with the Baptist church is associated with an increased risk in obesity and that consumption of religious media is associated with higher BMI. Consistent with these findings, a more recent study finds that higher levels of religious media consumption are associated with higher levels of body weight, accounting for BMI and other covariates (Yeary et al. 2009). Interestingly, while this literature points to a positive association between religion and body weight across various demographic markers, this association is not present among African Americans (Yeary et al. 2009; Reeves et al. 2012). While there is sufficient evidence which suggests a link between religion and the body, few empirical studies have explored how physiology (BMI) and religion can influence body image. According to Kim (2006), women with high levels of religious commitment and men with greater religious application were more likely to underestimate their actual body weight.

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Related to body image, one area of focus relates to the association between religion and eating disorders. While some research suggests that eating disorders are more strongly associated with spirituality rather than with religiosity (Boisvert and Harrell 2012), others point to the role of religious beliefs in the perpetuation of eating disorders among women whom, according to scholars, use their religious beliefs to justify the upkeep of their illness (Joughin et al. 1992; Ford 1992; Banks 1996; Morgan et al. 2000; Jacobs-Pilipski et al. 2005). Despite these findings, a major shortcoming in the aforementioned literature is the virtual absence of studies which explore body image issues among the adult population. Our study addresses these gaps by exploring gender-specific variations in self-reported overweightness among a sample of Texas adults. Furthermore, we contribute to this body of scholarship by assessing the effects of religious factors net of physiological (BMI), demographic, and socioeconomic variables.

Methods Data Results of logistic regression models below are based on data from the 2004 SoTA, a random probability sample of Texas residents ages 18 and older. The data include substantial representation from Hispanic/Latino, African American, and non-Hispanic whites. Additionally, the SoTA permits us to account for citizen versus non-citizen status among our sample. While not representative of the US population as a whole, the data include a rich array of religious, demographic, and health-related measures that are generalizable to a representative and racially diverse sample of respondents. Findings based on analysis using the SoTA have appeared in leading behavioral and public health journals (Burdette and Hill 2008; Hill et al. 2006, 2007). Analytical Strategy As with many cross-sectional studies, missing data are always a potential source of bias in the sample frame. While the number of missing cases in SoTA variables is minimal and generally random, approximately 35 % of the data for the income variable are missing. Following recommendations from Allison (2012), we apply maximum likelihood imputation to handle missing data. This technique shares similar statistical properties with multiple imputation, but is highly efficient and requires less attention to possible violations of mathematical assumptions. All results reported below are based on imputations of missing data using maximum likelihood techniques in JMP 9.0.2 (weighted n = 1,530).1 Dependent Variable The SoTA includes a measure intended to gauge self-perceptions of body weight. The item asks: ‘‘How would you rate your weight? Would you say you are very underweight, somewhat underweight, just about right, somewhat overweight, or very overweight?’’ Since less than 4 % of the overall sample report being underweight, we collapsed the original fivelevel response categories to create a four-level outcome measure, where (0 = very underweight and underweight) (1 = just about right, 2 = somewhat overweight, and 3 = very 1

We removed one outlying case with an excessive measure of BMI [80.

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overweight). With a four-level ordinal dependent variable, we calculate log odds using ordered logistic regression and present odds ratios predicting the odds of perceiving one’s self as overweight. Religious Predictors We include four measures of religiosity and a categorical measure for denominational affiliation. Beginning with religious attendance, we retain the five original response categories to include religious attendance as an ordinal variable, where (0 = never, 1 = less than once a month, 2 = 1–3 times a month, 3 = once a week, and 4 = several times a week). We measure religious salience by including an item which asks: ‘‘How religious would you say you are?’’ For computational purposes, we recode the original variable so that (0 = not at all religious and 6 = very religious) and then enter this item into our models as an ordinal variable. We gauge the impact of prayer frequency on self-reported overweightness and retain possible responses as an ordinal variable coded as follows: (0 = never, 1 = less than once a week, 2 = once or more a week, 3 = once a day and 4 = several times a day). The Biblical inerrancy item asks for level of agreement with the statement, ‘‘The Bible is God’s word and everything happened or will happen exactly as it says.’’ Original responses have been reverse coded so that higher scores indicate stronger beliefs in Biblical inerrancy: (0 = strongly disagree, 1 = disagree, 2 = neutral, 3 = agree, and 4 = strongly agree). Finally, we include denominational affiliation as a dummy coded variable with the following response categories: (0 = Catholic, 1 = Conservative Protestants, 2 = Mainline Protestants, 3 = other, and 4 = none/not affiliated) as the omitted category. Body Mass Index In our view, there are several reasons to include BMI in our models. First, while findings related to the relationship between obesity and mental health are inconsistent (Friedman and Brownell 1995; Onyike et al. 2003), others have shown obesity to foster detrimental mental health functioning (Fontaine et al. 1996, 1997). Second, previous literature has shown the important effects of BMI on body weight perceptions (Brener et al. 2004; de Lanerolle et al. 2009). Additionally, this effect has been shown to impact women to a greater degree than men (Lee et al. 2005; Park 2011). As shown by Fig. 1, SoTA data follow this previously reported pattern. In our data, increased levels of BMI are associated with an increase in the self-perception of excess body weight, r (1,530) = 0.63, p \ .001. In our view, if the effects of religious factors are shown to be consistent while holding BMI constant, this lends considerable and largely unexamined support for the impact of religious measures on self-perceptions of body weight. As such, the present study will treat BMI as a control variable. The SoTA includes measures of body weight and height in kilograms and centimeters. From these measures, we calculate an estimate of BMI by using the standard formula: (weight (kg)/[height (m)]2). Demographic Factors Our analysis includes ‘‘citizenship status’’ for Hispanics in Texas, allowing us to gauge whether acculturation is a factor impacting perceived body weight. The data thus permit us to create a dummy variable to concomitantly control for race/ethnicity and Hispanic citizenship status, where (0 = other, 1 = Hispanic non-citizen, 2 = Hispanic citizen,

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Fig. 1 Association between body mass index and perceived excess body weight SoTA, 2004 (weighted n = 1,530)

3 = African American, and 4 = non-Hispanic white) as the omitted category. We explore the potential for a curvilinear effect of age by comparing younger (0 = 18–36 years) and older respondents (1 = [53 years) with middle age respondents (2 = 37–53 years) as the omitted category. Marital status is a three category, dummy variable coded as follows: (0 = never married, 1 = other, and 2 = married), serving as the omitted category.2 Included in our models as a continuous measure, our final demographic variable captures actual number of children either ‘‘given birth to’’ or ‘‘fathered.’’ Measures of SES The results from full models shown below are net of four indicators of socioeconomic status. Total household income is in actual dollars, and as a result of this variable’s skewed distribution, we take its natural logarithm (base 10) before inclusion into statistical models. Education is a four-level dummy variable, where (0 = some college, 1 = Bachelor’s degree, 2 = [Bachelor’s degree, and 3 = high school or less) as the omitted category. We code gender-specific employment categories, allowing us to explore the effect of selfreported ‘‘homemaker’’ status for females. For women, employment status categories include (0 = homemaker, 1 = unemployed, and 2 = employed) as the omitted category. We measure male employment using two categories: (0 = unemployed, 1 = employed) as the omitted category.

Results Before moving to results from multivariate models, we briefly note several important characteristics from gender-specific descriptive data shown in Table 1. First, while 2

The ‘‘Other’’ category for the marital status variable includes, ‘‘Widowed,’’ ‘‘Separated,’’ ‘‘Partnered but not married,’’ and lastly ‘‘Married but not living with spouse.’’

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J Relig Health Table 1 Descriptive statistics for body image perceptions, BMI, and socio-demographic characteristics for females and males, SoTA (weighted n = 1,530) Females (weighted n = 787)

Males (weighted n = 743)

Mean

SD

Min.

Max.

%

Mean

SD

Min.

Max.

%

Body image

1.71

0.72

0.00

3.00

–

1.46

0.80

0.00

3.00

–

Church attendance

2.16

1.25

0.00

4.00

–

1.96

1.51

0.00

4.00

–

Religious salience

3.99

1.49

0.00

6.00

–

3.51

1.88

0.00

6.00

–

Prayer

3.07

0.93

0.00

4.00

–

2.56

1.34

0.00

4.00

–

Inerrancy

2.98

0.99

0.00

4.00

–

2.70

1.36

0.00

4.00

–

Catholic

–

–

–

–

30.17

–

–

–

–

33.21

Conservative

–

–

–

–

33.94

–

–

–

–

28.15

Mainline

–

–

–

–

10.92

–

–

–

–

9.65

Other

–

–

–

–

17.24

–

–

–

–

17.30

26.94

5.47

15.03

62.76

27.12

5.33

12.91

47.08

Denomination

None BMI

7.73 –

11.70 –

Race/citizenship Hispanic non-citizen

–

–

–

–

14.47

–

–

–

–

17.70

Hispanic citizen

–

–

–

–

21.13

–

–

–

–

21.04

African American

–

–

–

–

12.39

–

–

–

–

9.67

Other

–

–

–

–

2.92

–

–

–

–

3.91

Non-Hispanic whites

–

–

–

–

49.10

–

–

–

–

47.68

18–36

–

–

–

–

42.35

–

–

–

–

46.54

37–53

–

–

–

–

33.74

–

–

–

–

33.83

[54

–

–

–

–

23.92

–

–

–

–

19.62

Married

–

–

–

–

55.22

–

–

–

–

51.98

Never married

–

–

–

–

18.06

–

–

–

–

29.46

Other

–

–

–

–

26.71

–

–

–

–

18.55

Child

2.16

1.21

0.00

10.00

–

1.62

1.93

0.00

10.00

–

Log income

10.13

1.21

0.00

13.35

–

4.56

0.62

0.00

13.46

–

Age

Marital status

Education HS or less

–

–

–

–

77.58

–

–

–

–

72.85

Some college

–

–

–

–

4.86

–

–

–

–

4.46

B.A.

–

–

–

–

12.63

–

–

–

–

14.97

[B.A.

–

–

–

–

4.93

–

–

–

–

7.72

Homemaker

–

–

–

–

23.36

–

–

–

–

–

Unemployed

–

–

–

–

30.52

–

–

–

–

–

Employed

–

–

–

–

46.12

–

–

–

–

–

Female work

Male work Unemployed

–

–

–

–

–

–

–

–

–

32.79

Employed

–

–

–

–

–

–

–

–

–

62.71

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religious measures are consistent with other nationally representative surveys, we do note generally high levels of adherence to Biblical inerrancy, particularly among women. Next, we call attention to the high BMI scores within our sample, with a mean that is above the clinical standard for healthy BMI scores (18.5–25).3 The SoTA data also include a disproportionate percentage of respondents with less than a four-year degree as reflected by our descriptive statistics. We limit our discussion of descriptive data to these points and now turn to results of multivariate models. With the understanding that gender is an important dimension in exploring questions of body image, gender-specific regression models allow us to assess the impact of important religious predictors independently among men and women, net of BMI and other relevant factors. Table 2 presents gender-specific results of logistic regression models predicting women’s self-reports of being overweight. Model 1 includes only religious measures while Model 2 adds a physiological marker (BMI). Model 3 introduces demographic controls, and Model 4 introduces socioeconomic status, creating the full model for this table. As expected, across Models 2, 3 and 4, BMI is the most pronounced and significant predictor of women’s weight perceptions. Each unit increase in BMI is associated with an approximate 52 % higher cumulative log odds of self-reporting overweightness, net of all other factors (Model 4, OR 1.52, p \ .001). In Model 1, we assess the independent effects of religion. Initially, there are significant effects of religious variables among women when controls are excluded. Cumulative odds ratios show that church attendance, religious salience, and prayer are all significant predictors of overweight perceptions among women. Increased church attendance and prayer are associated with lower odds of reporting overweight perceptions, while religious salience is associated with slightly higher odds. However, most religious predictors lose their significance when BMI is introduced into Model 2.4 The only exception is the effect of religious attendance, the most consistent religious predictor among women. Religious attendance lowers the cumulative log odds of feeling overweight by approximately 20 %, net of extensive controls and BMI (Model 4, OR 0.81, p \ .01). It is also evident from the data that religious non-affiliation has a marginal effect on perceived body weight among women. When compared to non-affiliated respondents, Catholics have approximately 77 % higher cumulative log odds of identifying as overweight, net of controls and BMI. However, the effect falls just short of standard levels of statistical significance and consequently, should be interpreted as such (Model 4, OR 1.77, p \ .10). Next, we briefly consider the more noteworthy effects of control variables among women. First, we see that the effects of race/ethnicity and citizenship status are quite pronounced. Coefficients indicate that, compared with non-Hispanic white females, Hispanic non-citizen women have a 60 % lower cumulative odds of identifying as overweight (Model 4, OR 0.40, p \ .001). The effects for African American women are similar but 3

Comparison of BMI scores for men (M = 27.12, SD = 5.33) and women (M = 26.94, SD = 5.47) revealed slightly higher mean scores for men but no significant differences between the groups (t = 0.66, ns). Interestingly however, women report a stronger sense of self-reported overweightness (M = 1.70, SD = .716) when compared to men (M = 1.45, SD = .795, t = -6.49, p \ .001). 4

We estimated additional models that included a composite three-item index of religiousness that took the mean of religious salience, prayer frequency, and Biblical inerrancy. Factor loadings were generally respectable for the index (females Cronbach’s a = .63; males Cronbach’s a = .71). However, the substitution of individual items with a composite index did not result in statistically significant effects from the addition of a religiosity index and did not alter the effects of either attendance or denominational affiliation (results available upon request). Furthermore, the distinct effects of individual religiosity items for men when compared to women leads us to conclude that our models offer more explanatory power when individual religion items are retained.

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J Relig Health Table 2 Estimated net effects of BMI, religious variables and covariates on overweight perceptions among women: logistic regression odds ratios (weighted n = 787) Model 1

Model 2

Model 3

Model 4

Church attendance

0.82***

0.82**

0.83**

0.81**

Religious salience

1.15**

1.02

1.02

1.02

Prayer

0.87 

1.04

1.07

1.09

Inerrancy

1.08

0.98

1.00

1.00

Catholic

1.75 

1.40

1.72

1.77 

Conservative

1.63

1.41

1.36

1.45

Mainline

1.43

1.72

1.53

1.50

Other

1.93*

1.80 

1.96 

2.08*

–

1.48***

1.50***

1.52***

–

0.48

0.40 

Denomination (omitted = none)

BMI

Race/citizenship (omitted = white) Other

–

Hispanic non-citizen

–

–

0.34***

0.40**

Hispanic citizen

–

–

0.70

0.72

African American

–

–

0.48**

0.47**

18–36

–

–

1.07

1.09

[54

–

–

0.55**

0.46**

Age (omitted = 37–53)

Marital status (omitted = married) Never married

–

–

0.56*

0.54*

Others

–

–

0.78

0.77

Birthed children

–

–

1.02

1.04

Log income

–

–

–

1.11 

Education (omitted = \HS) Some college

–

–

–

1.22

B.A.

–

–

–

1.28

[B.A.

–

–

–

1.41

Female work (omitted = employed) Homemaker

–

–

–

0.88

Unemployed

–

–

–

1.51*

Pseudo R2

0.03

0.46

0.48

0.48

-2 log L

1,789.33

1,251.55

1,217.42

1,207.76

Likelihood ratio

24.56**

562.34***

596.47***

606.12***

df

8

9

18

24

 

p \ .10; * p \ .05; ** p \ .01; *** p \ .001

slightly weaker in magnitude. When compared to non-Hispanic white females, African American women have approximately 53 % lower cumulative odds of identifying as overweight (OR 0.47, p \ .01). As we will see below, these race-specific effects are much stronger for women than for males. There is also partial evidence in the data of a curvilinear age effect. While there is no statistically significant difference when comparing women in the older ([54 years) and younger (18–36 years) age categories, women over

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54 years of age have approximately 54 % lower odds of feeling overweight when compared to the women in the ‘‘37–53 years’’ age group (Model 4, OR 0.46, p \ .01). Finally, results indicate that while number of children ‘‘given birth to’’ has no significant association with perceptions of body weight, never-married women do have lower odds of feeling overweight when compared to married women (Model 4, OR 0.54, p \ .05). This implies a specific effect among women that is distinct from physical outcomes associated with childbirth. Realizing our main interest is in the effects of religious variables while holding BMI and other relevant factors constant, we limit our discussion of controls to these brief remarks and move to results of gender-specific models for males. Table 3 presents gender-specific results of logistic regression models predicting men’s perceptions of being overweight. Across models, cumulative odds ratios point to distinct religious effects among men when compared to women. For men, religious salience and prayer are significant predictors of overweight perceptions. On the other hand, religious attendance, unlike the effect for women, fails to predict overweight perceptions among men. Specifically, each unit increase in religious salience is associated with approximately 16 % lower cumulative log odds in men reporting overweightness (Model 4, OR 0.84, p \ .01), while prayer has the opposite effect. Increased frequency of prayer is associated with approximately 20 % higher cumulative odds of men reporting overweightness (Model 4, OR 1.20, p \ .05). Furthermore, coefficients for these religious predictors remain largely unchanged and statistically significant, net of BMI and extensive control variables. Denominational affiliation lacks a consistent pattern in predicting self-reported excess weight by men. However, evidence suggests that among men, Mainline Protestants have slightly higher cumulative log odds of perceiving themselves as overweight when compared to religious ‘‘nones,’’ but the effect just fails to reach the 0.05 level of statistical significance (Model 4, OR 1.98, p \ .10). As with results from female-only models, we briefly consider some of the more noteworthy effects of control variables among men. Unlike the effects of race/ethnicity among women, the effects for men are insignificant. However, there is some evidence of an age effect where younger men in the ‘‘18–36 years’’ age group report lower odds (43 %) of feeling overweight when compared to middle age men (Model 4, OR 0.57, p \ .05). Additionally, men who have never married have approximately 47 % lower odds of perceiving their bodies as overweight when compared to married men (Model 4, OR 0.53, p \ .01). Finally, results indicate that the number of children fathered has highly significant effects on men’s excess body weight perceptions. For each child fathered, odds of men reporting perceived excess body weight decline by approximately 18 % (Model 4, OR 0.82, p \ .001). As previously noted, since our focus is on religious effects in light of BMI and other relevant factors, we limit our discussion of effects from controls and move to a discussion that places our findings within a broader context.

Discussion This article aims to contribute to the literature on body image perceptions by focusing on three key dimensions impacting self-perceived overweightness. First, we highlight the role that religion plays in influencing individual perceptions of body weight. Second, we explore this possible association while holding actual body mass constant. Finally, we assess these effects using gender-specific models, allowing us to gauge distinct effects for women and men. Briefly restated, our results indicate that religious factors work in specific ways depending on gender. Whereas for women, church attendance lowers the odds of self-

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J Relig Health Table 3 Estimated net effects of BMI, religious variables and covariates on self-perceptions of overweightness among men: logistic regression odds ratios (weighted n = 743) Model 1

Model 2

Model 3

Model 4

Church attendance

1.04

1.02

1.03

1.02

Religious salience

0.86**

0.86*

0.83**

0.84**

Prayer

1.21*

1.19*

1.22*

1.20*

Inerrancy

1.03

1.05

1.09

1.10

Denomination Catholic

1.71 

1.15

1.16

1.18

Conservative

1.54

1.52

1.37

1.36

Mainline

2.70**

2.52*

2.07 

1.98 

Other

0.84

1.01

0.95

0.96

–

1.64***

1.65***

1.67***

BMI

Race/citizenship (omitted = white) Other

–

-

1.24

1.10

Hispanic non-citizen

–

-

0.73

0.78

Hispanic citizen

–

-

0.90

0.91

African American

–

-

0.78

0.83

Age (omitted = 37–53) 18–36

–

-

0.54**

0.57*

[54

–

-

1.18

1.00

Marital status (omitted = married) Never married

–

-

0.54**

0.53**

Other

–

-

0.65 

0.66 

Fathered children

–

-

0.81***

0.82***

Log income

–

-

-

1.13

Some college

–

-

-

0.88

B.A.

–

-

-

1.19

[B.A.

–

-

-

1.32 1.51*

Education

Male work (omitted = employed) –

-

-

Pseudo R2

Unemployed

0.06

0.61

0.63

0.63

-2 log L

1,538.04

1,033.71

999.74

993.05

Likelihood ratio

35.50***

539.83***

573.80***

580.49***

df

8

9

18

23

 

p \ .10; * p \ .05; ** p \ .01; *** p \ .001

reported overweightness, this effect among males is absent. Instead, it is religious salience that mitigates men’s propensities to report overweightness, while prayer increases overweight perceptions among men. Finally, although the effects of denominational affiliation are negligible for both genders, the general pattern for both males and females indicates that religious ‘‘nones’’ are less inclined to report overweightness than the religiously affiliated. Below we place our findings within the context of previous scholarship and offer plausible explanatory mechanisms that may shed light on our key findings. We state the

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key contribution our study makes to the religion and health literature, and close with study limitations and possible avenues for future research. We are aware that our results may be incompatible with previous studies that have explored religious variations in actual BMI, which indicate a generally positive association between religiousness and actual body mass. This positive association between religion and body weight has been commonly supported using both individual (Cline and Ferraro 2006; Gillum 2006; Kim et al. 2003; Yeary et al. 2009) and ecological level data (Ferraro 1998). While we find that religious factors are generally associated with perceptions of lower body weight, the aforementioned studies suggest that religion tends to be associated with physical overweightness. Furthermore, our study findings are reinforced by research suggesting that even when highly religious individuals weigh more than those who are less religious, the pious are less likely to perceive themselves as overweight (Kim 2006, 2007; Odoms-Young 2008). So what might explain this apparent contradiction? We suggest two possible explanations. Starting with our results showing a consistent, inverse association between church attendance and overweight perceptions among women; religious participation has been shown to foster social networks that involve like-minded individuals who may impart a positive sense of self-worth (Avalos and Tylka 2006), thus promoting salutatory effects on body image perceptions (Holman 2012). From the context of religious communities, personal relationships within religious settings may promote meaningful attachments that translate to a sense of approval and appreciation from significant others (Homan and Cavanaugh 2013). Consequently, we can expect greater religious attendance and participation within the congregation to foster enhanced body image perceptions. Second, keeping in mind the above-mentioned evidence of increased body size among religious adherents, it is quite possible that regular interactions with individuals whom they share both religious and physical characteristics with may lead to more favorable self-evaluations of body weight. This argument resonates with Merton’s application of reference group theory (Merton 1957: chaps. 8–9), whereby individuals compare their own attributes with those with whom they regularly interact with. Consequently, individuals evaluate their own characteristics based on their immersion within networks of similar, like-minded individuals. Recent applications have applied reference group theory to understand how individual behaviors and beliefs are shaped largely by comparing with other in-group members (Acevedo 2009; Cochran and Beeghley 1991; Cochran et al. 1988; Bock et al. 1983). In sum, while our results showing an inverse association between religious factors and overweight perceptions may contradict patterns indicating religiosity and overweightness to be positively correlated, the expectations of reference group theory might shed light on this inconsistency. Religious individuals, engaging in regular interaction with other congregants, may be expected to compare themselves with those members—persons who share a larger body size than the non-religious. It is possible that future research, particularly qualitative studies, might offer specific explanatory mechanisms that may clarify processes of body weight assessments among religious individuals. The explanations above, however, are only consistent to the extent that we operationalize interaction through church attendance. We are then left having to clarify the inability of church attendance to explain weight perceptions among males in our study. Instead, what might it be about religious salience that among men, substitutes for church attendance as a variable that lessens perceptions of overweightness? Furthermore, why is it that for men, prayer increases these same body weight perceptions? It is to these related questions that we now turn to.

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We begin by considering gendered norms which place a considerable level of importance on female body image, and which socialize women to hold unrealistic expectations for their own body types (Frederickson and Roberts 1997). And while contemporary research suggests that the gender gap is narrowing—with males increasingly showing signs of unrealistic body expectations as well (Christl et al. 2012)—the burden of beauty attainment still rests largely with women (Demarest and Allen 2000; Franzoi et al. 2012; Muth and Cash 1997). Furthermore, empirical research has shown women to be more inclined to compare themselves to other women when evaluating their own bodies, while men tend to self-evaluate their physique based on goals and future body aspirations (Franzoi et al. 2012). In other words, while women tend to draw on comparative and selfcritical appraisals of body weight, men are more individualistic, confident and hopeful in the potential to achieve optimal body standards in the future. In our view, such social-psychological processes may at least partly explain our genderspecific religion effects. It is possible that men, being less reliant on social interactions and reference group processes, may be less impacted by church attendance. If men’s body image perceptions are, in fact, driven more by individual then social interactive mechanisms, as the research alluded to above has shown, we can expect private forms of religiosity to have a greater impact on men’s body weight perceptions than collective experiences, like church participation. In sum, if men are less likely to evaluate themselves in reference to others, then it seems reasonable to suspect that the effects of church attendance would be less pronounced for men when compared to women. Moreover, one theoretical implication of this line of reasoning is that reference group theory, in this instance, has greater explanatory power for women than it does for men. Next we take up the proposition that prayer increases men’s overweight perceptions—a point also requiring brief consideration. Previous studies have shown that prayer often serves as a source of comfort in times of stress and depression (Ai et al. 2006; Pargament et al. 1992) while additional work has shown that prayer may be utilized distinctively by men and women who seek remedies for health-related stressors (Coleman et al. 2006; Levin and Taylor 1997). It has also been shown that prayer may be a particularly potent form of religious coping in times of physical health distress (Ellison and Taylor 1996). With this accumulated scholarship in mind, we suggest that prayer may function as a source of coping for men experiencing overweight perceptions. Consequently, we would expect that men with overweight perceptions might engage in prayer as a form of coping, similar to instances in which prayer is used for health reasons (Gillum and Griffith 2010). That the effect of prayer for women fails to reach a level of statistical significance at either the 0.10 or 0.05 level indicates that their overweight perceptions are impacted to a greater degree by the interactions occurring in religious settings while for men, prayer serves as an individual coping strategy. The links between religion and perceptions of body weight are regrettably understudied, and while a line of research does examine issues of the body, these attempts have significant shortcomings. First, many of these studies are hampered by methodological flaws which hinder the ability to provide conclusive findings. One such error is the fact that many previous studies tend to discount the multidimensional nature of religious factors. Second, low prevalence of eating disorders among the US male population has caused scholarly research to primarily focus on women. Third, most studies concentrate on white and African American females, while overlooking Latina women. Finally, past research has either focused on physiological markers of body type, like BMI, or solely on body weight perceptions. Ours is one of the first studies to explore links between religion and overweight perceptions net of physiological factors. Furthermore, despite extensive controls for

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demographic, socioeconomic and physiological predictors (BMI), many of the religious effects remain. Thus, our results contribute to the ongoing body of empirical work which explores the links between religion and body perceptions (e.g., Brener et al. 2004; Park 2011; Furnham et al. 2002). As with other cross-sectional studies, the current study has several limitations. First, our study design does not allow for specification of direct causal linkages between independent and dependent variables. Instead, our study is largely correlational in nature. Future studies should consider longitudinal data that might shed light on the temporal nature of healthrelated issues. It is also possible that panel data may unearth causal mechanisms that are beyond the scope of cross-sectional data. Qualitative designs may assess possible mechanisms at work which may help shed light on important interpretive processes influencing perceptions of body weight in light of physiological factors. Also, while the SoTA provides some of the most appropriate measures specifically designed around health and religiosity, we are limited in measures of body image perception and include a single-item indicator as our dependent variable. Future work might address this issue in greater detail by expanding questionnaire items to include multiple indicators of body image, thus allowing for the construction of multiple-item indices and scales. Third, future work can focus on important interactions between race/ethnicity and religion. It is possible that specific forms of religiosity moderate the effects of race/ethnicity when explaining body weight perceptions. Furthermore, future work may perhaps consider possible race/ethnicity and religion interactions by drawing from nationally representative samples, allowing for a greater level of generalizability to the larger US population. In closing, there is a need to augment research that links religious and physiological factors. The dearth of scholarship in the sociology of religion—a literature primarily concerned with attitudinal and behavioral outcomes—is symptomatic of a general lack of accumulated scientific research on physiology in the behavioral sciences. It will require a gradual accumulation of empirical research to fully address the possible linkages between physiology, gender, and religion, but we hope our study is a first step in this direction. Acknowledgments We would like to thank Xiaohe Xu, John Bartkowski and Chris Ellison for the helpful comments on an early draft of this paper. Earlier versions were presented at the Department of Sociology Graduate Student Colloquium at the University of Texas at San Antonio and the 2013 Annual Meetings of the American Sociological Association in New York City. The data for this study were acquired via The Inter-University Consortium for Political and Social Research (ICPSR, Study Number 4297) and were made available (in part) by the Population Research Center at the University of Texas at Austin and by funding provided by the RGK Center for Philanthropy and Community Service and the College of Liberal Arts at the University of Texas at Austin. Neither the collector of the data nor any of these entities bears any responsibility for the analyses and interpretations presented here.

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