JOURNAL OF SEX RESEARCH, 52(1), 43–54, 2015 Copyright # The Society for the Scientific Study of Sexuality ISSN: 0022-4499 print=1559-8519 online DOI: 10.1080/00224499.2013.821443

Risky Sexual Behavior Among Young Adult Latinas: Are Acculturation and Religiosity Protective? Scott James Smith Department of Sociology, Anthropology, Social Work, and Criminal Justice, Oakland University A sexual health disparity exists among U.S. Latinas, who have rates of sexually transmitted infections (STIs) that are more than double their peers. Previous research has identified acculturation and religiosity as key social determinants of sexual health, but such findings have been inconsistent, with some researchers identifying protective benefits and other researchers noting increased risk. The purpose of this study was to explain how intrinsic and extrinsic religiosity as well as acculturation predict risky sexual behavior using Structural Equation Modeling of a nationally representative sample of self-identified Latinas (N ¼ 1,168) from the National Longitudinal Survey of Adolescent Health. Results indicated that intrinsic religiosity and acculturation assert protective effects while extrinsic religiosity increases risk. Recommendations for policy, intervention, and future research are offered.

The Hispanic population in the United States is the largest non-White subpopulation among adolescents (U.S. Census Bureau, 2012), and epidemiological data reveal a sexual health disparity, with rates of sexually transmitted infections (STIs) among Latinas between two and four times the rates of non-Hispanic Whites (Centers for Disease Control and Prevention [CDC], 2012). The differences between Latinas’ sexual health outcomes and those of their peers are partially explainable by the fact that Latinas engage in risky behavior at higher rates (Frost & Driscoll, 2006). Previous researchers on Latina sexual behavior have identified acculturation and religiosity as determinants of risky sexual behavior. Acculturation refers to the process of replacing culture of origin with culture of residence (Cuellar, Arnold, & Maldonado, 1995), while religiosity generally refers to the influence of varying aspects of religion (Rohrbaugh & Jessor, 1975). The This research used data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due to Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health Web site (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis. Correspondence should be addressed to Scott James Smith, Oakland University, Department of Sociology, Anthropology, Social Work, and Criminal Justice, Rochester, MI 48309. E-mail: [email protected]

findings have been inconsistent in terms of their conclusions about the risk or protective nature of these factors, and the results are in both directions for acculturation and religiosity. Explanations for this inconsistency have focused on methodological issues, citing myriad concerns about the conceptualization and measurement of religiosity and acculturation (Abraı´do-Lanza, Armbrister, Flo´rez, & Aguirre, 2006; Hill & Pargament, 2003; Hunt, Schneider, & Comer, 2004; Steensland et al., 2000). Previous research where these two constructs have been modelled together is sparse, despite traditional Hispanic culture’s orientation to religion. As such, there is a substantial gap in the current understanding of how acculturation and religiosity operate together as determinants of sexual behavior. This study sought to address this gap with the goal of informing interventions and policy that aim to reduce the incidence of risky sexual behavior in Latinas. Background Latina Sexual Risk Behavior In terms of sexual activity, Latinas are more likely to have had sex and be currently sexually active than their White peers (CDC, 2012). These sexual encounters do not appear to be protected, evidenced by data that demonstrate Latinas are the least likely subpopulation to use condoms (CDC, 2012). Further, Latinas are slightly more likely than their White peers to sexually debut before age 13 (CDC, 2012) as well as more likely than

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both Black and White peers to debut before age 17 (Driscoll, Biggs, Brindis, & Yankah, 2001). The result is a longer period of sexual activity that explains why Latinas have been more likely to report four or more lifetime sexual partners than their White peers (CDC, 2012). Latinas are less likely to have sex while under the influence of alcohol or other drugs than their Black or White peers, but they are also more likely to get human immunodeficiency virus (HIV) testing than Whites (CDC, 2012). To understand why Latinas enjoy certain protections and incur certain risks, it is necessary to understand the determinants of their sexual health behavior. Latina Sexual Risk in Context Ecological systems theory (Bronfenbrenner, 1979) asserts that behavior is the product of the interaction between person and environment. The interaction is altered by the presence of risk and protective factors that explain the variance in outcomes within a population (Coie et al., 1993) and therefore act as determinants of health (Phelan & Link, 2005); for Latinas, acculturation and religiosity are two such determinants. Acculturation and Risky Sexual Behavior Numerous researchers have suggested that the risks and protections related to Latina risky sexual behavior are located in traditional Hispanic cultural values, and the process of acculturating alters their risk profile (Abraı´do-Lanza, Chao, & Flo´rez, 2005). However, the findings in these studies are inconsistent regarding the effect of acculturation on Latina’s sexual behavior. Acculturation as risk. The process of acculturating appears to remove some of the protections offered by many traditional Hispanic cultural values. Epidemiological data shows rates of risk behavior and STIs at significantly lower rates in many South and Central American countries than in the United States (AfableMunsuz & Brindis, 2006). Researchers have identified several values that may be replaced during acculturation, leading to decreased protection. One value, familismo (the high value placed on family cohesion), has been identified as protective because it increases the level of parental monitoring, thereby reducing opportunity to engage in risky behavior (Gil, Wagner, & Vega, 2000; Romero & Ruiz, 2007). Even when direct parental monitoring is absent, the traditional value of respect for authority (respeto) is associated with increased prosocial behavior (Ramirez et al., 2004), potentially reducing risk. Together, familismo and respeto increase communication between parents and children, which appears protective against risky sexual behavior (Holtzman & Rubinson, 1995). This is most pronounced in communication between 44

mother and daughter (Dutra, Miller, & Forehand, 1999), with evidence that Hispanic girls who have frequent, positive communication about sex with their mothers delay sexual debut and report fewer lifetime partners (Rojas-Guyler, Ellis, & Sanders, 2005). This mother-daughter protection may be strong because of the transmission of marianismo, the value of purity and femininity implicated in delayed sexual initiation (Wood & Price, 1997). However, many of these cultural values have also been identified as a source of risk. Acculturation as protection. Evidence suggests the process of acculturation may increase Latinas’ protection against certain sexual risk behaviors because they move away from cultural traditions that limit their sexual knowledge, decision-making abilities, and selfefficacy. For instance, despite close family relationships, Latina teens report talking to their parents about sex less than their White peers do (Guzma´n, SchlehoferSutton, & Villanueva, 2003). For those girls who do talk to their parents, the potential exists to receive inaccurate information, especially if their parents have low levels of acculturation (Miller, Guarnaccia, & Fasina, 2002). The reduced effect of marianismo in its subservience to the men’s message may increase the sexual self-efficacy of Latinas, especially with a Latino partner who has been reared to embody machismo (strength, virility, and dominance; Marin, 2003). Acculturation’s overall effect on Latinas’ risky sexual behavior. Because Latinas’ culture provides risk and protection, the cultural change resulting from acculturation may not result in substantial change to their overall risk profile; rather, acculturation may simply alter the mechanism responsible for certain risk behaviors. Whereas low-acculturated Latinas may engage in risky behavior due to their submission to their male partner’s wishes, high-acculturated Latinas might engage in risky behavior because they have acquired more permissive sexual attitudes (Ahrold & Meston, 2010). The higher levels of acculturation buffer the permissive attitudes with increased condom negotiation (Rojas-Guyler et al., 2005) and use (Norris & Ford, 1994). However, as Latinas acculturate they begin using substances at a higher rate, and there is evidence of increased incidence of sex under the influence of a substance with greater acculturation (Cintron, Owens, & Cintron, 2007), potentially decreasing condom use (Hingson, Strunin, Berlin, & Heeren, 1990). Religion is one additional level of cultural influence relevant to Latinas. Hispanic culture places a high value on religion (Williams & Davidson, 1996); in turn, religious values support and maintain their culture (Geertz, 2002). Campesino and Schwartz (2006) suggested that such values as simpa´tia (harmony in relationships) and personalismo (closeness and cooperation with others) appear to both encourage and support higher levels of religious

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value among Latinas. As such, it is necessary to understand the influence of religion on risky sexual behavior. Religiosity and Risky Sexual Behavior Religiosity refers to the extent an individual or group employs religious ideology in their value formation and decision making (Nonnemaker, McNeely, & Blum, 2003). Because religion is both a component and determinant of culture, it is not surprising that religiosity appears to alter risk and protection much as acculturation does (Nonnemaker et al., 2003). Specific to Latinas, religiosity appears to be mostly protective; however, there are relatively few studies investigating religiosity on Latina sexual behavior, and among these studies there are contradictory findings. Religiosity as protection. Generally, religiosity is a protective influence on adolescent sexual health (Elifson, Klein, & Sterk, 2003). One explanation for religiosity’s protective effects is that many risky sexual behaviors (e.g., promiscuity, multiple partners) are forbidden by religion (Rowatt & Schmitt, 2003). Further, religiosity provides an internalized belief system that increases behavioral consistency as well as an externalized belief system that encourages compliance with behavioral standards to maintain group membership, all resulting in reduced risk exposure (Rowatt & Schmitt, 2003). Researchers have also identified increased religiosity as protective against several sexual risk behaviors. Liebowitz, Castellano, and Cuellar (1999) found that high levels of religiosity predicted later sexual debut for Hispanic youth, a result confirmed by SchlehoferSutton and Guzman (2001), who noted that the effect of religiosity was stronger than the effects of parental conversations about sex. Higher religiosity among Latinas is also associated with fewer lifetime sexual partners than their less religious peers (Edwards, Fehring, Jarrett, & Haglund, 2008). Despite these protections, there is evidence that religiosity can increase risk. Religion as risk. Similar to acculturation, religiosity appears to function as a risk factor in some cases, especially for women and members of racial=ethnic minority communities. Miller and Gur (2002) observed that highly religious girls had lower avoidance and refusal skills compared to less religious and nonreligious peers, possibly explaining Latinas’ higher rate of sexual activity. The Catholic Church’s prohibition of birth control (Fuller, 1996) may help explain low rates of condom use among Latinas (Martin et al., 2011), although several researchers exploring religiosity and condom use found either no direct effect (Baumeister, Flores, & Marı´n, 1995; Peragallo, 1996; Unger & Molina, 1999) or found religiosity benefited males but not females (Villarruel, Jemmott, Jemmott, & Ronis, 2007).

Religiosity also appears to impair transmission of sexual health knowledge (Bersamin, Fisher, Walker, Hill, & Grube, 2007). Adolescents whose parents have high levels of religiosity report less communication about sex than their peers with less religious parents (Regnerus, 2005). This problem is compounded by the effects of religiosity on school-based sex education, specifically in the expansion of abstinence-only education (AOE) in U.S. states with a large number of Hispanics (Perrin & DeJoy, 2003). Taken together, this reduction in communication may suggest that religiosity and acculturation interact in a way that alters risk. The Combined Effects of Acculturation and Religiosity Although there is a well-established relationship between religiosity and acculturation, few researchers have utilized both components. Not surprisingly, those that have explored both have found each component alters the risk or protective effect of the other (Raffaelli, Zamboanga, & Carlo, 2005). In terms of how acculturation and religiosity may alter each other’s risk or protection toward risky sexual behavior among Latinas, researchers suggested lower sexual self-efficacy (Marin, 2003), the lack of visibility of STIs in their communities (Prado et al., 2006), and high fertility values (Driscoll et al., 2001) as areas where the two constructs strongly influence each other. There appears to have been only one study in which the researchers addressed sexual health behaviors of Latinas using religiosity and level of acculturation as independent variables. Edwards and colleagues (2008) found that the combination of high traditional sexual attitudes and high levels of both religious involvement and importance predicted fewer partners for Latinas over the course of their lives. This study’s cross-sectional design limits causal assumptions but does provide evidence that a viable relationship exists. Research Gaps The inconsistency in findings regarding the influence of acculturation and religiosity on sexual health behavior among Latinas creates a substantial gap in understanding the determinants of sexual behavior. This is compounded by the lack of research, particularly using longitudinal designs, that have integrated both predictors. There is also a gap created by methodological problems common to studies where researchers have investigated acculturation (Hunt et al., 2004) and religiosity (Campesino & Schwartz, 2006), and these problems have been implicated in the inconsistent research findings. Hypotheses The purpose of this study was to evaluate the effects of acculturation and religiosity on Latinas’ sexual 45

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risk behaviors. The aims were to determine whether controlling for socioeconomic factors, intrinsic religiosity, extrinsic religiosity, and acculturation significantly explained the variance in risky sexual behaviors. The following hypotheses were proposed: H1: Latinas with lower levels of acculturation and higher levels of intrinsic religiosity are less likely to engage in risky sexual behavior. H2: Latinas with higher levels of extrinsic religiosity are more likely to engage in risky sexual behavior. H3: The risk or protective effects are present despite statistically significant, positive covariance between each construct.

Methods Analytic Strategy A longitudinal design was used in this study, with Wave 1 independent variables predicting Wave 3 outcomes. To capture the extraneous influence the predictors exert on each other and the dependent variable, confirmatory factor analysis (CFA) was performed to measure the underlying latent constructs of the independent variables instead of their observed form. Structural equation modeling (SEM) was then used to evaluate the relationship between predictor and outcome variables. Data The National Longitudinal Study of Adolescent Health. This researcher used data from Waves 1 and 3 of the National Longitudinal Study of Adolescent Health (Add Health). Presently, there are four waves of data available to the public, but Wave 3 was used in this study because Wave 4 did not include necessary measures for the outcome variable. The in-home Wave 1 data were collected between April and December 1995 using a school-based sampling frame comprised of 80 high schools and 52 middle schools across the United States, selected with unequal probability of selection and implicit stratification to allow national estimates of seventh- through twelfth-grade students representative of the United States in regard to geography, population density, type of school, size of school, and ethnicity (N ¼ 20,745) (Harris et al., 2009).1 To reduce response bias to sensitive questions about health behaviors included in the survey, audio computerassisted self-interviewing (ACASI) was utilized, whereby respondents listened to questions through headphones and entered their responses directly into a laptop. Wave 3 was collected between August 2001 and April 2002, and it included every Wave 1 respondent who could be 1 Additional details about the sample and design of Add Health are available online at http://www.cpc.unc.edu/projects/addhealth/ design.

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located and was in the United States (N ¼ 15,197). For the current study, the sample was restricted to self-identified Hispanic females in Wave 1 who participated in Wave 3 and answered all of the questions used to create the outcome variable (n ¼ 1,168). Table 1 presents the demographic characteristics of the sample. The average Latina in the sample was in

Table 1. Sample Characteristics of Self-Identified Hispanic Females in Wave I of the Add Health Survey (N ¼ 1,168) Demographic Age (M ¼ 15.81, SD ¼ 1.70) 12 13 14 15 16 17 18 19 20 Grade (M ¼ 10.00, SD ¼ 1.62) 7 8 9 10 11 12 Graduated Not in school but should be Race Other White American Indian=Native American Black=African American Asian=Pacific Islander Hispanic identification Mexican=Mexican American Other Hispanic Central=South American Puerto Rican Cuban=Cuban American Chicano=Chicana Born in the United States Yes No Speak English at home Yes No Religion Catholic Evangelical Protestant Mainline Protestant No religion Other Black Protestant Jewish Household income (M ¼ $35,057, SD ¼ $37,992) 1.5  poverty line 1.5–2.5  poverty line 2.5–4  poverty line 4  poverty line–Top 5% of households Top 5% of households

Percentage

4.10 14.50 17.20 18.10 16.40 14.60 12.10 2.70 0.20 16.50 16.60 18.00 16.40 15.70 14.40 0.50 1.90 47.50 42.20 6.20 2.70 1.50 51.00 15.20 12.90 11.20 6.00 3.70 75.42 24.58 54.20 45.80 58.70 12.10 11.60 9.30 8.00 0.20 0.20 49.70 22.30 18.40 7.70 1.90

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high school during the Wave I interviews, and was between 15 and 16 years old. The sample was racially diverse, with most (48%) choosing the label ‘‘other’’ for their race, and the majority (51%) ethnically identified as Mexican or Mexican American. Most were born in the United States (62%), but the sample was almost evenly split concerning speaking English at home. The sample was predominantly Catholic (59%), though this number is almost 10% lower than other estimates of religious affiliation (Perl, Greely, & Gray, 2006). Poverty rates were high, with just under half (49%) living below 1.5 times the poverty threshold. Measures Independent variables. The questions used to measure acculturation and religiosity were based on earlier studies that used Add Health data (Gordon-Larsen, Harris, Ward, & Popkin, 2003; Nonnemaker et al., 2003) as well as other researchers’ measurement recommendations (Abraı´do-Lanza et al., 2006; Cabassa, 2003; Steensland et al., 2000). Acculturation. Two items measured linguistic acculturation: (1) ‘‘What language do you speak at home?’’ and (2) the interviewer’s report of the language the respondent used for the survey. Reverse coding was used on these two measures, transforming them into binary responses with 1 representing English and 0 representing non-English. Three questions measured generational status: (1) ‘‘Was your father born in the United States?’’; (2) ‘‘Was your mother born in the United States?’’; and (3) ‘‘Were you born in the United States?’’ Those born in the United States scored a 1, and those born outside the United States scored 0. Religiosity. Religiosity was conceptualized to be comprised of two components: intrinsic and extrinsic. Extrinsic religiosity was measured from two questions: ‘‘In the past 12 months, how often did you attend religious services?’’ and ‘‘Many churches, synagogues, and other places of worship have special activities for teenagers, such as youth groups, Bible classes, or choir. In the past 12 months, how often did you attend such youth activities?’’ The items were originally 4-point scales ranging from 4 ¼ Never to 1 ¼ Every week. The scale was reverse-coded and was altered to range from 0 to 3, so that Never had a value of 0. Three questions measured intrinsic religiosity: (1) ‘‘How important is religion to you?’’; (2) ‘‘How frequently do you pray?’’; and (3) ‘‘Do you believe the scriptures of your religion are the word of God, without any error?’’ All items were coded so that higher scores reflected higher levels of religiosity. Religious importance had four possible responses ranging from Not at all to Very, while frequency of prayer originally had five

categories from Never to Once a day or more. The question about belief in divine inspiration of scripture was a yes=no question with a third option: ‘‘My religion doesn’t have a sacred scripture.’’ To capture the influence of religion despite the lack of scripture, this third response was recoded as 1; a yes or no response scored 2 or 0, respectively. The distribution of prayer scores in two categories, Less than once a month and At least once a month, were substantially lower than for other categories so they were collapsed into one category, leaving the final variable with four categories. Socioeconomic status (SES). The effect of SES was controlled for by modeling it with a direct path to the dependent variable and allowing it to covary with the independent variables. Three measures of economic status were utilized to form a composite of SES: household income, mother’s educational level, and father’s education level. Household income was computed by taking the reported household income (0 income was coded as missing) and family size (the reports of all family members living in the home were summed) and classifying each household into one of five categories relative to the 1994 poverty threshold (adjusted for family size). To account for the inaccurate assessment of the existing poverty level, Goodman’s (1999) model was used; the poverty level was multiplied by 1.5 to determine the lowest level. The remaining levels are 1.5 to less than 2.5 times the poverty threshold; 2.5 to less than 4 times the poverty threshold; 4 times the poverty threshold but not in the top 5% of household incomes; and top 5% of household incomes. Parent education level was derived from parents’ report of their educational attainment on 10-point scale, ranging from Never went to school to Professional training beyond a four-year degree. This scheme was recoded into the following five levels: (0) less than a high school degree, (1) high school degree, GED, or vocational training instead of high school, (2) some college or trade school, (3) college graduate, and (4) professional training beyond college. Missing data. Bennett’s (2001) determination that variables with 10% or more missing data may result in biased statistical estimates led to the utilization of multiple imputation for four variables: household income (26.2% missing), mother’s education level (14.5% missing), father’s education level (14.6% missing), and father’s country of birth (26.8% missing). Following the recommendation of Graham (2009), who noted that more imputations are necessary as the amount of missing data increases, 20 imputations were performed for each of these variables. Dependent variable. Risky sexual behavior was created to be a scale variable comprised of seven items 47

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Figure 1.

Initial path model of religiosity and acculturation model predicting risky sexual behavior.

(measured in Wave 3) that are strongly related to poor sexual health outcomes: sexual debut before the age of 17; four or more lifetime sex partners; more than one sex partner in the past year; nonuse or inconsistent use of condoms; having sex with an intravenous (IV) drug user; failure to be tested for STIs; and having sex under the influence of alcohol and=or other drugs. The questions were dichotomized and summed to create the outcome scale. The outcome variable was treated as a censored variable (from below) to correct for zero inflation, which also enables conclusions about individuals who have

no risk behavior. In addition, because the measurement component of the model involved categorical data, WLSMV (weighted least squares estimation method robust to multivariate nonnormality) was used as the estimator for all analyses because it is robust to violations of normality assumptions and produces estimates comparable to maximum likelihood estimation (Beauducel & Herzberg, 2006). Model specification and modification. The initial model tested was a simple model where religiosity and acculturation predicted risky sexual behavior (Figure 1).

Figure 2. Final path model with standardized coefficients for the religiosity and acculturation model predicting risky sexual behavior. Standardized coefficients reported in diagram.  p < .05.  p < .01.  p < .001.

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SES. Because SES was comprised of three variables, it is presumed to be just identified, so model fit was not assessed (Kline, 2005). All items had standardized loadings greater than .62.

The model was modified after the model modification index suggested the overall model fit would improve substantially by allowing a direct path from extrinsic religiosity to intrinsic religiosity (Figure 2). In the initial model, the factors were allowed to covary, which accounts for the close relationship between the two factors. The direct path is theoretically sound, given that for many people the corporate practice of their religion helps strengthen their personal, internal religious practices (Donahue, 1985). Accordingly, the modification was adopted and retained as the final model.

Acculturation. Acculturation was hypothesized to be a two-factor structure, one factor measuring linguistic acculturation and the other factor measuring generational status. CFA results indicated a one-factor model was a better fit than the two-factor model because the two factors had a correlation of .90, indicating poor discriminant validity. The one-factor model, v2 ¼ 7.76 (5 df), had standardized factor loadings greater than .74.

Results Due to the complex sampling used in Add Health, Stata 12 (StataCorp, 2011) was utilized for the univariate analysis and MPlus 6.12 (Muthen & Muthen, 2011) for the multivariate analysis. Table 2 presents the factor fit indices, interitem correlations, factor loadings, and descriptive statistics for each factor.

Religiosity. CFA confirmed the hypothesized twofactor model of religiosity (measuring intrinsic and extrinsic religiosity), v2 ¼ 1.57 (4 df). Religiosity’s factors had a correlation of .78, so a model comparison was performed (comparing the two-factor model to an H0 nested one-factor model). Because WLSMV estimation does not produce a chi-square difference score distributed as a chi-square, a second analysis testing a one-factor model using the residuals from the first model was necessary to produce the appropriate chi-square. The chi-square difference was significant (v2diff ¼ 18:53, p < .001) indicating the fit worsened, so the two-factor model was retained. Standardized factor loadings were all greater than .66.

Measurement Model Results CFA was performed to construct the independent variables used in all three models, and model fit was assessed based on Hu and Bentler’s (1999) joint criteria of a CFI greater than .95 and RMSEA less than .06. For the latent variables that were theorized to be two-factor models, the factor correlations were examined to look for discriminant validity and then a model comparison was performed if necessary.

Dependent variable. common among the

Risky sexual behavior was sample, with the average

Table 2. Fit Indices, Chi-Square Difference Tests, Factor Loadings, Interitem Correlations for Factors Used as Independent Variables With Means and Standard Deviations for Each Item Factor Loadings Factor Socioeconomic Statusa 1. Household income 2. Father’s level of education 3. Mother’s level of education Acculturation 1. Mother born in the United States 2. Father born in the United States 3. Respondent born in the United States 4. Home language 5. Survey language

M

SD B

SE

b

SE

0.90 1.07 1.00 — 0.62 0.06 0.82 1.12 1.22 0.14 0.76 0.06 1.03 1.09 1.15 0.12 0.72 0.05

0.55 0.59 0.24 0.46 0.12

0.50 0.49 0.43 0.50 0.32

Religiosityb 1. Importance of religion 2.17 0.96 2. Prayer frequency 2.13 1.07 3. Belief that scriptures are the word of God 1.40 0.90 4. Religious service attendance 1.89 1.15 5. Youth activities attendance 0.94 1.24

1.00 0.90 0.86 0.93 0.75

— 0.04 0.04 0.04 0.05

0.98 0.89 0.84 0.91 0.74

0.02 0.03 0.03 0.03 0.05

1.00 — 0.92 0.03 0.80 0.05 0.73 0.04 0.77 0.05 0.70 0.03 1.00 — 0.92 0.06 0.71 0.08 0.66 0.05

Interitem Correlations 1

2

3

4

— .48 .45

— .54

NA NA NA

NA NA NA

— .89 .84 .87 .65

— .67 .66 .65 .48

— .70 .80 .55

— .50 .54 .38

— .78 .58

— .51 .34

v2 (df)

CFI RMSEA

v2diff

—

—

—

—

7.76 (5)

.999

0.022

7.67 (1 df)

1.57 (4) 1.000

0.000

— .76

— .60 18.53

a

Factors with three items are just identified and fit is not assessed. Items 1 through 3 measure intrinsic religiosity; Items 4 and 5 measure extrinsic religiosity.  p < .01.  p < .001. b

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Table 3. Mean, Standard Deviation, and Measures of Distribution for Outcome Variable Along With Questions Used to Construct Variable and the Percentages of Risky Sexual Behavior Participation Question From Survey How old were you the first time you had vaginal intercourse? With how many partners have you ever had vaginal intercourse, even if only once? With how many different partners have you had vaginal intercourse in the past 12 months? Did you always use a condom when you had vaginal intercourse in the past 12 months? Have you had sex with an IV [intravenous] drug user in the past 12 months? Have you been tested for STDs [sexually transmitted diseases] in the past 12 months? Have you been in a sexual situation you regretted because of alcohol and=or drugs in the past 12 months?a Number of Risk Behaviors Reportedb

Risk Behavior

% Reporting

Under age 17 Four or more More than 1 Did not always use Had sex with IV drug user Not tested Regretted sexual activity

38.53 34.16 16.41 61.01 1.58 71.87 8.60

%

0 1 2 3 4 5 6 7

3.73 28.96 25.52 22.37 13.27 5.04 0.99 0.12

Note. Questions reworded to account for their removal from the context of the survey. a Two separate questions. b M ¼ 2.32; SD ¼ 1.32.

model, and it was allowed to covary with all other factors, given the known influence of SES on religiosity (Bock, Beeghley, & Mixon, 1983) and acculturation (Cabassa, 2003). Table 4 presents the model implied correlations and Table 5 presents the SEM results. Intrinsic religiosity was protective against risky sexual behavior. A one-unit increase in intrinsic religiosity resulted in a Z-score decrease of .35 (p < .001). SES also provided protection, with a one-unit increase resulting in a .21 decrease in the dependent variable Z-score (p < .05). Higher levels of extrinsic religiosity and acculturation were associated with increased risky sexual behavior. Extrinsic religiosity increased the likelihood of engaging in risky sexual behavior by .24 units for every 1 unit increase

respondent reporting two out of seven behaviors (Table 3). At the extremes, 0.12% reported engaging in all risk behaviors, and 3.73% reported engaging in none of the risk activities. The most common risk behavior was not having an STD screening in the past year (72%), followed by not using a condom during every sexual encounter in the past year (61%). The least likely risk behavior was having sex with an IV drug user, with 1.58% reporting this experience. Structural Model Results In the final stage of analysis, a structural component was added to the measurement model (Figure 2). SES was controlled for on the dependent variable in the Table 4.

Correlations for the Structural Model Predicting Risky Sexual Behavior

Item 1 2 3 4 5 6 7 8 9 10 11 12 13 14

50

Family income Father’s education level Mother’s education level Mother born in United States Father born in United States Born in United States Language at home Language of interview Importance of religion Prayer frequency Scriptures are ‘‘word of God’’ Church attendance Youth activities attendance Risky sexual behavior

1

2

3

4

5

6

7

8

9

10

11

12

13

— 0.51 0.50 0.42 0.39 0.42 0.54 0.56 0.10 0.03 0.03 0.05 0.03 0.06

— 0.54 0.28 0.35 0.26 0.43 0.24 0.02 0.02 0.09 0.10 0.05 0.02

— 0.36 0.36 0.11 0.40 0.14 0.09 0.09 0.17 0.04 0.02 0.07

— 0.92 0.84 0.87 0.65 0.23 0.19 0.22 0.12 0.00 0.22

— 0.76 0.83 0.60 0.13 0.14 0.24 0.01 0.04 0.23

— 0.78 0.58 0.16 0.06 0.18 0.07 0.05 0.10

— 0.76 0.28 0.16 0.26 0.15 0.05 0.26

— 0.01 0.02 0.00 0.07 0.09 0.29

— 0.67 0.66 0.65 0.48 0.16

— 0.50 0.54 0.38 0.12

— 0.51 0.34 0.17

— 0.60 0.09

— 0.05

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Table 5. Model Fit Indices, Unstandardized Coefficients, and Standardized Coefficients for the Structural Model v2 (df) Model fit indices

122.87 (50 df)

CFI

RMSEA

.98

.03

Factor Outcome B b Intrinsic religiosity ! Risky sexual behaviors 0.51y 0.35 Extrinsic religiosity 0.32 0.24 Acculturation 0.50 0.37 Socioeconomic status 0.32 0.21 Note. MPlus computes the mean for model fit indices when using multiple imputation.  p < .05.  p < .01.  p < .001. y p ¼ .001.

in extrinsic religiosity (p < .05). Similarly, every 1 unit increase in acculturation increased the likelihood of engaging in risky sexual behavior by .37 units (p < .001).

Discussion Hypothesis 1 Findings Hypothesis 1 stated that Latinas with lower levels of acculturation and higher levels of intrinsic religiosity are less likely to engage in risky sexual behavior. The findings supported the first hypothesis and bolster the findings of other researchers who noted the protective nature of these constructs against risky sexual behavior. The findings also support the theory that measurement issues are a leading culprit in the previous inconsistent findings. The protective nature of low acculturation supports most previous health research, though it diverges from some studies that have suggested low acculturation levels increase risk. It is possible that the studies noting risk were not capturing the full effect of acculturation. For example, Trejos-Castillo & Vazsonyi (2009) reported no effect from acculturation on maternal-child communication about sex and reduced risk behavior. They used generational status as their acculturation measure, which assumes a linear assimilation process and excludes bicultural expression. As such, their findings do not disconfirm the association between acculturation and maternal communication, only the lack of a relationship between generation status and communication. Hypothesis 2 Findings Hypothesis 2 stated that Latinas with higher levels of extrinsic religiosity would be more likely to engage in risky sexual behavior. As predicted, extrinsic religiosity functioned as a risk factor, increasing the likelihood of engaging in risky sexual behavior. The most obvious explanation for extrinsic religiosity’s risk effect, especially compared with the protection from intrinsic religiosity, is that high levels of extrinsic religiosity may have

no bearing on an individual’s sexual behavior because the adolescent may be compelled by family to attend church. Accordingly, the measure of church attendance is not a measure of personal religious values but of family values (Thornton & Camburn, 1989). However, researchers have reason to suspect that the effects of extrinsic religiosity are more complex. Because most religions have restrictions on sexual behavior, it is likely the church exerts structural barriers that increase risk by controlling the information that is provided to adherents (Bersamin et al., 2007; Santelli, 2006). For example, if the message about sexual health is limited to abstinence, then the broader conversation about risk is neglected (Fortenberry, 2005; Santelli, 2006). In addition, many adolescents hear the morality in abstinence messages as meaning only vaginal intercourse is considered sex (Sanders & Reinisch, 1999), resulting in participation in oral or anal intercourse with the belief they are safe activities (Bru¨ckner & Bearman, 2005). The influence may occur indirectly through the adolescent’s parents, as suggested by Regnerus (2005), who found highly religious parents were likely to reduce the amount of conversation about sex with their children or limit the discussion to the same message their religious institution provides. Pragmatically, the church setting is a large social network that increases access to potential partners (Bearman, Moody, & Stovel, 2004). Jensen, Newell, and Holman (1990) found that men who attended church regularly and had permissive attitudes toward sex were more likely to be sexually active than less frequent attendees, suggesting some men may use religious services to find sexual partners. Because individuals from these environments may be equally ignorant of safer-sex practices (Bersamin et al., 2007) or the risks associated with different sexual behaviors (Lindberg, Jones, & Santelli, 2008), the normative behavior of the group is unchanged, perpetuating risk (Fishbein & Ajzen, 1975). In addition, moral objections to sex may result in unplanned and therefore unprotected sex (Bearman & Bru¨ckner, 2001; Rostosky, Wilcox, Wright, & Randall, 2004). Hypothesis 3 Findings Hypothesis 3 stated that risk effects or protective effects are present despite statistically significant, positive covariance between each construct. The results mostly supported hypothesis 3, though there were several interesting findings. The first was the relationship between intrinsic and extrinsic religiosity. The model modification allowing a direct path from extrinsic religiosity to intrinsic religiosity explains some of the inconsistency in the literature on the role of religiosity as it relates to sexual behavior. If researchers use only one domain of religiosity, they likely will fail to capture the collective influence of religiosity on risky sexual behavior (Hill & Pargament, 2003). 51

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Of additional interest is the relationship between intrinsic religiosity, extrinsic religiosity, and acculturation. While intrinsic religiosity was bolstered by extrinsic religiosity, the opposite effects on risky sexual behavior suggests some independence of the two variables, validating their unique attributes (Donahue, 1985; Reed & Meyers, 1991). The same is true when considering the positive covariance between extrinsic religiosity and acculturation, which is not surprising because of the church’s role for many Hispanics and the likelihood that Hispanic parents will require church attendance of their children (Flores, Eyre, & Millstein, 1998; Romo, Berenson, & Segars, 2004). When all three variables are considered together, there is a strong relationship between religiosity and acculturation, and that measurement of religiosity among Latinas without regard to culture may yield incomplete results (Campesino & Schwartz, 2006). Research on parental monitoring supports this finding, noting that Hispanic immigrant parents may decrease supervision of their children at religious events because they assume the institution is performing the supervision task as was the case in their country of origin (Romero & Ruiz, 2007). Accordingly, future research on Latinas should strongly consider incorporation of both constructs rather than relying on any single measure. The role of SES was also interesting, specifically the negative covariance between SES and intrinsic religiosity. One explanation may be that lower SES presents greater life challenges, and intrinsic religious practices such as prayer may be utilized for coping (Ross, 1990). Acculturation and extrinsic religiosity were also negatively correlated, which reinforces the idea that as a Latina acculturates, part of the cultural values she replaces are those associated with her religious practices (Campesino & Schwartz, 2006). Study Limitations The current study has several limitations. First, using secondary data creates limits on variable selection. Although Add Health data have good measures of all study variables, the current use is obviously outside the original intent of the study. Second, the lack of homogeny among Latinas means generalization of these findings is premature. Finally, as with any use of SEM, this is merely one possible way the data are related, and other theoretically relevant models may exist that require equal consideration. Despite these limitations, the finding in this research fills several gaps in the understanding of the risk=protective effects of religiosity and acculturation. Future Research Future research examining how different elements of acculturation and intrinsic religiosity relate to one another is necessary to identify the actual protective 52

mechanisms offered and how they relate to extrinsic religiosity. In addition, the difference in socialization between Hispanic males and females may alter the way religiosity and acculturation affect Latinos; therefore, further research applying this model to Latinos is necessary. Finally, examining subpopulations is vital because there is great diversity within the Hispanic population. The most urgent research needs are for Hispanics identifying racially as Black and those affiliated with institutional sects of Protestantism because of the competing risk and protections they experience as members of their respective communities. Intervention Implications The findings from this study suggest that religious organizations are strong influences on sexual health for Latinas for myriad reasons, and accordingly, community partnerships with these organizations could reduce risky sexual behavior. However, because collaboration is less likely with organizations that have stronger historic prohibitions against sexual health initiatives, a more effective approach may be through indirect means. This could include supporting existing programs that target behaviors related to risky sexual behavior, such as anti–substance use campaigns that are prolific among religious organizations (Chatters, Levin, & Ellison, 1998) or providing access to STI screening at health screening events commonly offered in conjunction with religious organizations (Davis et al., 1994). In addition to the public health interventions, the protective benefits of intrinsic religiosity and low acculturation suggest efforts to preserve these qualities will improve sexual health. As mentioned, Campesino and Schwartz (2006) suggest the Hispanic values of personalismo and familismo are the vehicles of spirituality for Latinas. As such, interventions that strengthen the family and help preserve the family’s cultural identity will likely have a multiplicative effect on preventing risky sexual behavior. References Abraı´do-Lanza, A. F., Armbrister, A. N., Flo´rez, K. R., & Aguirre, A. N. (2006). Toward a theory-driven model of acculturation in public health research. American Journal of Public Health, 96(8), 1342–1346. doi:10.2105=AJPH.2005.064980 Abraı´do-Lanza, A. F., Chao, M. T., & Flo´rez, K. R. (2005). Do healthy behaviors decline with greater acculturation? Implications for the Latino mortality paradox. Social Science and Medicine, 61(6), 1243–1255. doi:10.1016=j.socscimed.2005.01.016 Afable-Munsuz, A., & Brindis, C. D. (2006). Acculturation and the sexual and reproductive health of Latino youth in the United States: A literature review. Perspectives on Sexual and Reproductive Health, 38(4), 208–219. doi:10.1363=3820806 Ahrold, T. K., & Meston, C. M. (2010). Ethnic differences in sexual attitudes of U.S. college students: Gender, acculturation, and religiosity factors. Archives of Sexual Behavior, 39(1), 190–202. doi:10.1007=s10508-008-9406-1

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