**Evaluation of the E** ff**ect of CYP2D6 Genotypes on Tramadol and** *O***-Desmethyltramadol Pharmacokinetic Profiles in a Korean Population Using Physiologically-Based Pharmacokinetic Modeling**

**Hyeon-Cheol Jeong 1, Soo Hyeon Bae 2, Jung-Woo Bae 3, Sooyeun Lee 3, Anhye Kim 4, Yoojeong Jang 1 and Kwang-Hee Shin 1,\***

Received: 6 October 2019; Accepted: 15 November 2019; Published: 17 November 2019

**Abstract:** Tramadol is a μ-opioid receptor agonist and a monoamine reuptake inhibitor. *O*-desmethyltramadol (M1), the major active metabolite of tramadol, is produced by CYP2D6. A physiologically-based pharmacokinetic model was developed to predict changes in time-concentration profiles for tramadol and M1 according to dosage and CYP2D6 genotypes in the Korean population. Parallel artificial membrane permeation assay was performed to determine tramadol permeability, and the metabolic clearance of M1 was determined using human liver microsomes. Clinical study data were used to develop the model. Other physicochemical and pharmacokinetic parameters were obtained from the literature. Simulations for plasma concentrations of tramadol and M1 (after 100 mg tramadol was administered five times at 12-h intervals) were based on a total of 1000 virtual healthy Koreans using SimCYP ® simulator. Geometric mean ratios (90% confidence intervals) (predicted/observed) for maximum plasma concentration at steady-state (Cmax,ss) and area under the curve at steady-state (AUClast,ss) were 0.79 (0.69–0.91) and 1.04 (0.85–1.28) for tramadol, and 0.63 (0.51–0.79) and 0.67 (0.54–0.84) for M1, respectively. The predicted time–concentration profiles of tramadol fitted well to observed profiles and those of M1 showed under-prediction. The developed model could be applied to predict concentration-dependent toxicities according to CYP2D6 genotypes and also, CYP2D6-related drug interactions.

**Keywords:** CYP2D6; *O*-desmethyltramadol; pharmacokinetics; physiologically-based pharmacokinetics; tramadol


*Study Limitations*

The current study focused solely on community pharmacies in North Carolina that had 50% or more of their prescriptions enrolled in a Med Sync program. More knowledge could be gained by broadening the participant sample to include community pharmacies in other states. Despite the small sample, the current study does include both urban and rural community pharmacies and a range of prescription volume per week indicating technicians can support Med Sync utilization in a variety of contexts. Furthermore, expanding this research to determine how technicians' roles a ffect patients' outcomes may be beneficial and is warranted.


*2.4. Data Collection: Muscle Activation Measurement*

After taking a break for 30 min after the *MVC* measurement, dental work simulations were performed on a dental mannequin (Simple Manikin III, NISSIN, Kyoto, Japan) installed in the dental UCS, and muscle activity was recorded in eight EMG channels. The participants performed simulations for intraoral scanning and tooth preparation tasks for two days at intervals of one week to prevent fatigue accumulation between tasks, and the work order was randomly selected by listing all orders (Figure 2).

**Figure 2.** Electromyography measurements during dental simulations. (**A**) Tooth preparation simulation; (**B**) Intraoral scanning simulation.

 (µV) The digital integrated dental UCS (MEGAGEN, Daegu, Korea) used an intraoral scanner (i500; MEDIT, Seoul, Korea) and monitored the dental UCS, and the conventional dental UCS (Maxpert; SHINHUNG, Seoul, Korea) showed the scanning process on a separate monitor, other than that of the dental UCS, connected to an intraoral scanner. The participants performed all work procedures after adjusting the dentist's chair and the patient's chair to fit their posture and body.

 (%) = × 100 The intraoral scanning task was performed by consecutively scanning the maxillary and mandibular models for dental education (D85DP-500B.1; Nissin Dental, Kyoto, Japan) three times using an intraoral scanner (i500; MEDIT, Seoul, Korea; Figure 2). The scanning strategy was to scan the complete arch in the order of occlusal, buccal, and lingual, and all participants performed a scan so that there were no empty spaces in any of the teeth (Figure 2). The weight of an intraoral scanner used in the present study was 280 g.

ℎ 60 − ℎ 60

ℎ 60 × 100

(%) =

The tooth preparation task was performed by preparing the maxillary right first molar (D85DP-500B.1; Nissin Dental, Kyoto, Japan) for a single ceramic crown and chamfer margin using a high-speed dental handpiece (TG-98; W&H, Bürmoos, Austria; Figure 2). Participants performed the tooth preparation task without a magnification system (Figure 2).

One investigator (J.M.L.) recorded the muscle activity in real time only when the participant performed any action for the tasks and did not record the muscle activity unless the participant performed the simulation. In addition, all working times were recorded.

#### *2.5. Data Collection: Muscle Activation Analysis*

Muscle activation and muscle fatigue were calculated from the data measured using *EMG* measurement software (TeleScan ver 3.29; LAXTHA, Daejeon, Korea). *EMG* data from dental work were normalized and expressed as percentages, and the activation of each muscle was calculated as follows [9,12] (1):

$$\text{RMS\\_EMG}(\%MV\text{C}) = \frac{\text{Muscle activation during tasks (\mu\text{V})}}{\text{MVC}} \times 100\tag{1}$$

*RMS EMG* (%*MVC*) indicates muscle activation that occurs during dental work compared to MVC. As the *RMS EMG* (%*MVC*) increased, the risk of MSDs increased, and the ergonomic risk level according to the activation level of each muscle was evaluated according to previous literature: *MVC* in the range of 0–10% means "low risk"; 11–20% means "moderate risk," and more than 21% means "high risk" [9,12,13].

Muscle fatigue can be identified by increasing and decreasing median edge frequency (*MEF*) values, and as *MEF* decreases, muscle fatigue increases [22–25]. The *MEF* value can be obtained in the frequency range of 1–400 Hz after applying the fast Fourier transform, which transforms the *EMG* signal that changes with time into a frequency. Among the total working time, *MEF* in the first 60 s and next 60 s were calculated, and muscle fatigue was calculated according to the following formula [23,24] (2):

$$\text{Muscle\\_fatigue(\%)} = \frac{\text{MEF in the second 60 s} - \text{MEF in the first 60 s}}{\text{MEF in the first 60 s}} \times 100 \tag{2}$$

When *MEF* in the first 60 s of dental work was compared with *MEF* in the next 60 s, a negative value was obtained when the value of *MEF* in the second 60 s was low, indicating the increase in muscle fatigue [23,24].


This study employs a racial stereotyping measure used in several prior studies of neighborhood racial preferences [8-13]. It is scaled from −6 to +6 and is constructed from five survey items in which respondents were asked to rate each of the four major racial or ethnic groups (white, black, Asian, Hispanic) on a given characteristic (intelligence, laziness, violence-prone, committed to strong families, committed to fairness and equality for all). High (positive) scores indicate unfavorable ratings of out-groups relative to one's own group; low (negative) scores indicate favorable ratings of out-groups; 0 indicates no perceived difference. Cronbach's alpha for the scale is 0.62.

Social isolation from racial and ethnic minorities is measured by three separate survey items in which respondents were asked: "Do you personally know any" "Hispanics or Latin Americans," "Blacks," and "Asian Americans?" Each item is coded such that "0" indicates that the respondent reports not personally knowing anyone from the group, while a score of "1" indicates that the respondent reports knows a member of the group. The current study also employs a measure of racial homogeneity in respondents' communities. Studies have indicated that the racial composition of individuals' current communities affects their neighborhood racial preferences [59]. Furthermore, spatial and social isolation from ethnic outgroups is associated with more negative outgroup perceptions [38]. Respondents were asked to estimate the "percentage of the people who live in your local community" that are white.

Socio-demographic variables include sex, age (in years), total family income, and years of education. Dichotomous variables indicate whether the respondent is married, is a homeowner, has children in the home, or lives in the South. In addition, this study uses the variable XNORCSIZ, which is a measure of the size of a respondent's place of residence, ranging from 1 (open country) to 10 (city greater than 250,000).

### **4. Results**

Table 2 compares non-Hispanic white evangelical Protestants to whites in other religious categories on key socio-demographic variables. Several significant differences are worth noting. Evangelical Protestants are most different from the non-Christian groups—Jews, adherents of "other" faiths, and the unaffiliated. Compared with these groups evangelicals are older, less educated, live in less populated areas, and are more likely to live in the South. Evangelicals tend to be older than Catholics and far more likely to live in the South. Compared with mainline Protestants, they are less educated and more likely to live in the South. The religiously unaffiliated are less likely than evangelical Protestants to be married or own their home.

**Table 2.** Comparison of Evangelical Protestants to Other Groups on Key Socio-Demographic Variables.

Source: 2000 General Social Survey; N = 878; \* Difference from evangelical Protestants statistically significant (p < 0.05, 2-tailed); \*\* p < 0.01, 2-tailed

Table 3 compares evangelical Protestants to the other religious categories on the focal independent variables in the current study: social isolation from minorities and racial stereotyping. Again, differences between evangelical Protestants and the three non-Christian groups are most notable. Compared with these whites, evangelical Protestants are significantly less likely to report personally knowing Hispanics or Asian Americans, and more likely to hold negative stereotypes about minorities. Evangelical Protestants show little distinctiveness from Catholics and mainline Protestant, however. The only significant difference is evangelicals' greater likelihood of knowing blacks compared with Catholics.

**Table 3.** Comparison of Evangelical Protestants to Other Groups on Key Independent Variables.

Source: 2000 General Social Survey; N = 878; \* Difference from evangelical Protestants statistically significant (p < 0.05, 2-tailed); \*\* p < 0.01, 2-tailed.

Table 4 shows the neighborhood racial-composition preferences of non-Hispanic whites by religious tradition. Evangelical Protestants prefer the most racially homogeneous neighborhood, with an average of roughly 60 percent white [67]. Mainline Protestants prefer only slightly more diverse neighborhoods, with an average of 57.7 percent. Catholics (53.5%) and Jews (53.7%) both prefer neighborhoods in which slightly over half of all households are white. Only those of "other" faiths and the unaffiliated prefer, on average, a neighborhood in which whites do not make a majority. Those of "other" faiths have the weakest preference for same-race neighbors with an average of 42.8 percent. The religiously unaffiliated prefer a neighborhood in which about 49 percent of households are white [68]. All groups except for the "other" faith group prefer a neighborhood that is between 15 and 17 percent black. Differences in percent Asian and Hispanic are a bit more noticeable. Evangelical Protestants prefer the lowest percentage of both Asians and Hispanics, followed by mainline Protestants. Those of "other" faiths and the unaffiliated prefer the highest percentage of Asians and Hispanics.

Table 5 contains results from an OLS regression analysis of the percentage of households that respondents filled in as white. Model 1 compares non-Hispanic white evangelical Protestants to whites in each other religious tradition [69]. Results reveal that, before accounting for socio-demographic characteristics, evangelical Protestants' preference for same-race neighbors is significantly greater than that of every religious group but mainline Protestants. Model 2 introduces socio-demographic variables. Results indicate that group differences in socio-demographic characteristics largely explain the distinctiveness of white evangelical Protestants' neighborhood preferences [70]. Net of these controls, evangelical Protestants' preference for same-race neighbors is significantly greater than only those in the "other" faith category.

**Table 4.** Neighborhood Racial Preferences among Non-Hispanic Whites, by Religious Tradition.

Source: 2000 General Social Survey; N = 878

**Table 5.** Preference for Same-Race Neighbors Among Other White Religious Groups Compared to White Evangelical Protestants.

**Table 5.** *Cont.*

Source: 2000 General Social Survey;

Unstandardized coefficients reported, standard errors in parentheses.

† p < 0.10; \* p < 0.05; \*\* p < 0.01

a Reference group is evangelical Protestants

*Note*: Models 2 and 5 also control for family income, sex, marital status, home ownership, and the presence of children aged 0–6 or 7–12 in the household. None of these variables approach significance, so for simplicity they are not reported.

Models 3 and 4 introduce measures of social isolation from racial and ethnic minorities, as well as negative stereotyping, in the absence of socio-demographic variables. Model 3 demonstrates that the measures of social isolation from minorities used in the current study only partly explain group differences in preferences. While differences between groups are diminished somewhat, evangelical Protestants still prefer a significantly higher percentage of white neighbors than do Catholics, those of "other" faiths, and the unaffiliated.

Likewise, Model 4 indicates that white evangelical Protestants' stronger preference for same-race neighbors is not well explained by a greater propensity to hold negative stereotypes about minorities. Again, differences between evangelicals and other groups shrink somewhat, particularly for the "other" faith category and the unaffiliated, but remain statistically significant. Model 5 presents results from the full model, which includes socio-demographic variables. The pattern of group differences in Model 5 is highly similar to the one in Model 2. While stereotyping and isolation from minorities partially explain evangelical Protestants' distinctiveness, Model 2 demonstrates that socio-demographic characteristics alone render insignificant the differences between evangelicals and all other groups but the "other" faith category. Overall, these results suggest that while socio-demographic characteristics explain white evangelical Protestants' stronger preference for same-race neighbors, racial stereotyping and racial isolation do not.

As other studies have found, several socio-demographic characteristics are significant predictors of neighborhood racial-composition preferences. Birth cohort is a strong predictor for non-Hispanic whites. In Model 2, each additional year of age is associated with a .4 percentage point increase in same-race households. Compared with non-Southerners, whites living in the South prefer a neighborhood with a significantly higher percentage of whites. Respondents from more populous areas have a weaker preference for same-race neighbors, as do more educated whites. Each additional year of education is associated with a nearly 2 percent decrease in preferred same-race neighbors. Household composition has an effect on preferences. In Model 2, those with children between 13 and 17 prefer fewer white neighbors. In the final model, however, residing in the South and having children between 13 and 17 are the only significant socio-demographic variables.

Generally speaking, non-Hispanic whites that report personally knowing members of minority groups have a weaker preference for same-race neighbors. However, compared with personally knowing African Americans, knowing Hispanics or Asian Americans has a stronger effect on neighborhood preferences. Net of controls for stereotyping and socio-demographic characteristics, only knowing Hispanics or Asian Americans is predictive of a weaker preference for same-race neighbors. Respondent's estimates of racial homogeneity in their current communities matter as well. The estimated percentage of whites in the respondents' community is significantly positively associated with a preference for same-race neighbors. Finally, like numerous other studies [9-13], this analysis finds that holding negative stereotypes about minorities is a strong predictor of neighborhood racial preferences for non-Hispanic whites. A one-unit increase on the stereotyping scale is associated with a roughly ten percent increase in percent white.

### **5. Discussion and Conclusions**

Prior research on the causes of racial residential segregation has focused on the role of economic and financial institutions and on the preferences of individuals regarding the racial composition of their neighborhoods. The role that social institutions, such as religion, might play in influencing intergroup relations and either isolating or integrating racial and ethnic groups has gone largely unexplored. Emerson and Smith [20] have argued that the segregation of American religion along racial lines contributes to the racialization of American society. This study examines the relationship between religious affiliation and neighborhood racial-composition preferences among non-Hispanic whites. Evangelical and mainline Protestants have the strongest preference for same-race neighbors, while those of various "other" faiths and the unaffiliated have the weakest. This finding closely mirrors the general pattern observed for a range of whites' racial attitudes, in which Protestants have the most conservative attitudes, religious minorities (Jews, other faiths, and the unaffiliated) have the most progressive, and Catholics are somewhere in between [55,56]. Interestingly, it also mirrors the racial diversity within each of these traditions, as Protestant congregations are the most racially homogeneous, followed by Catholic and non-Christian congregations [27,28]. Furthermore, this study finds that while socio-demographic characteristics largely account for white evangelicals' stronger preference for same-race neighbors, negative stereotyping and social isolation from minorities do not.

Emerson and Smith [20] have suggested that religion contributes to the racialization of American society by creating racially distinct social networks, thereby limiting opportunities for interracial bridging ties. In the current study, however, the extent to which respondents personally know members of minority groups only partly explained religious group differences in preferences. Furthermore, evangelical Protestants' concentration in the South and in less populated areas likely accounts for their lower likelihood of knowing Hispanics or Asian Americans, especially compared with Jews, those of "other" faiths, and the unaffiliated. It is possible that more detailed measures of interracial contact and social network composition may better explain religious differences in neighborhood preferences. Examining the role of interracial contact at places of worship may be a worthwhile strategy. There is evidence that such contact may be especially effective at improving racial attitudes [21].

Emerson and Smith argue that religion endows individuals with cultural tools that they use to interpret the social world. When applied to race, these cultural tools influence individuals' racial attitudes. However, in the current study, a measure of racial stereotyping did not account for white evangelical Protestants' stronger preference for same-race neighbors. Instead, controls for socio-demographic characteristics, particularly region and education, explained much of the distinctiveness of evangelical Protestants' preferences. It is possible that other measures of racial attitudes would better explain the religious gap in preferences. Additional research is necessary to determine how religious affiliation may affect racial attitudes, including preferences about neighborhood racial and ethnic diversity.

While Blanchard's study [23] found that the presence of mainline Protestant congregations is associated with lower levels of black-white residential segregation, the current study finds that mainline Protestants themselves are indistinguishable from evangelical Protestants in their neighborhood racial-composition preferences. Notably, Blanchard makes an *institutional* argument about the relationship between local congregations and interracial relations. Evangelical Protestant congregations tend to be less involved in providing community service and outreach than mainline congregations, thus missing opportunities to foster bridging social capital [35-37]. In addition, mainline clergy tend to be more liberal than the laity, which may be a contributing factor to the level and type of community involvement displayed by mainline congregations [71]. Despite the relatively conservative racial attitudes of their members, mainline congregations may nonetheless have a positive effect on community racial integration by fostering civic engagement and bridging social capital [72].

Emerson and colleagues' provocative publications [20,27,30] have spurred an important line of research about race and religion in the United States. However, their conclusions have not been universally echoed in other social science research [49,51,52]. This study and recent work by Taylor and Merino [55,56] indicate the need for important qualification to claims about the influence of religion on racial attitudes. Individuals whose denominational preference is evangelical Protestant have significantly more conservative racial attitudes than other white Americans and prefer more racially homogeneous neighborhoods. However, after accounting for their socio-demographic characteristics, this group loses much of its distinctiveness. This pattern of findings makes it less clear how religion influences whites' racial attitudes.

Why is it difficult to identify religious influences on racial attitudes? Perhaps because, as Bartkowski and Matthews suggest, "the very same constellation of religious beliefs and practices that can be used to eradicate racial stratification also can be enlisted to reinforce it" ([73], p. 164). For example, an evangelical theology that has been said to blind its adherents to structural racism and reinforce segregated churches and social networks also drives efforts at 'racial healing' and 'Christ-centered' race-bridging [74,75]. Such ambivalence is on display in Brown's [76] study using Detroit Area Studies data from the 1970s and 1990s. He reports that, despite their stronger denial of racial housing discrimination, white evangelical Protestants actually expressed significantly greater openness than other white Christians to living in racially integrated neighborhoods. Brown situates these interesting findings within Detroit's own history of race relations and religious activism. His study also highlights the need to be attentive to the differing religious dynamics within local communities.

Additional research is needed to determine how religion works to either inhibit or foster bridging ties across racial and ethnic boundaries. Blanchard's [23] 'closed community thesis,' posited as an explanation for higher levels of black-white residential segregation in evangelical-rich communities, warrants further testing. Blanchard's thesis draws on two important areas of inquiry in the sociology of religion. First, several studies have suggested that religious traditions vary in the extent to which their congregations facilitate civic engagement and the development of bridging social capital in the broader community [15,37,72,77,78]. Second, there is growing interest in how religious involvement and beliefs structure individuals' social networks and their opportunities for intergroup contact [29,32,34,79,80]. Future research should examine how involvement in congregations and their religious subcultures shapes both opportunities for and preferences regarding social connections across racial and ethnic lines, particularly when religious culture contributes to racial identity [81]. As Edgell and Tranby suggest, "if religious subcultures are shaped in the context of highly salient racial boundaries, they may in fact be about race" ([51], p. 284). In addition, the cultural tools individuals acquire through participation in religious subcultures color their experiences with racial and ethnic diversity [51,75,82,83]. The task of researchers will be to better understand how individuals draw on those cultural tools to bridge racial divides in their communities.

### **References and Notes**

### **Religion and Marriage Timing: A Replication and Extension**

### **Joshua J. Rendon, Xiaohe Xu, Melinda Lundquist Denton and John P. Bartkowski**

**Abstract:** Previous studies have revealed denominational subculture variations in marriage timing in the U.S. with conservative Protestants marrying at a much younger age than Catholics and the unaffiliated. However, the effects of other religious factors, such as worship service attendance and religious salience, remain overlooked. Informed by a theoretical framework that integrates the denominational subculture variation thesis and the gendered religiosity thesis, this study replicates, updates, and extends previous research by examining the effects of religiosity on the timing of first marriage among 10,403 men and 12,279 women using pooled cross-sectional data from the National Survey of Family Growth, 2006–2010. Our survival regression models indicate that: (1) consistent with previous research, Protestants in general, and conservative Protestants in particular, marry earlier than the religiously unaffiliated; (2) irrespective of denominational affiliation, increased frequency of worship service attendance decreases age at first marriage for both men and women, whereas religious salience is associated with earlier marriage only for women; (3) among Catholics, as worship service attendance increases, the waiting time to first marriage decreases; and (4) among Protestants, however, worship service attendance decreases age at first marriage for men who are affiliated with mainline and non-denominational Protestant churches, while for women the decrease in age at first marriage associated with worship service attendance is found for those who report a conservative Protestant affiliation. The complex intersections of denominational affiliation, frequency of worship service attendance, religious salience, and gender are discussed. Results suggest that religion continues to exert influences on marriage timing among recent birth cohorts of young Americans.

Reprinted from *Religions*. Cite as: Rendon, J.J.; Xu, X.; Denton, M.L.; Bartkowski, J.P. Religion and Marriage Timing: A Replication and Extension. *Religions* **2014**, *5*, 834–851.

### **1. Introduction**

The past several decades have witnessed a remarkable growth in scholarly research on marriage timing [1,2]. A particular stream of this burgeoning body of research has focused on the role of religion and documented denominational subculture variations in marriage timing in the U.S., with conservative Protestants marrying at a much younger age than Catholics and the unaffiliated [3–5]. Though previous studies have revealed notable religious subculture variations in marriage timing in the U.S., the effects of other religious factors such as worship service attendance and religious salience are understudied. Informed by a theoretical framework that integrates the denominational subculture variation thesis and the gendered religiosity thesis, this study replicates and extends previous research by examining the effects of religiosity on the timing of first marriage among recent birth cohorts of American young adults using pooled cross-sectional data from the National Survey of Family Growth, 2006–2010. In particular, this study addresses the following research questions: (1) Does religion continue to exert influences on marriage timing among recent birth cohorts of young Americans? (2) If so, are there denominational subculture variations as exhibited in previous research net of other religious factors? (3) Are worship service attendance (*i.e.*, religious network integration) and religious salience (*i.e.*, the internalization of religious norms and values) associated with marriage timing? (4) If so, do these associations vary across diverse faith traditions as expected by the denominational subculture variation thesis? (5) And finally, do these religious effects on marriage timing, if uncovered, vary by gender?

This study makes significant contributions to family and religious studies in several important ways. First, denominational subculture variations in marriage timing as reported by previous studies are largely based on survey data collected in the late 1980s and early 1990s. The present study explores whether these denominational subculture variations are still present among young Americans who were surveyed in the 21st century. This replication effort is warranted in light of recent social trends. Young Americans are increasingly experiencing multiple life course transitions in union formation, especially pre-marital cohabitation, which is known to delay entry into first marriage [6]. In addition, religiosity in terms of worship service attendance, prayer, belief in afterlife, and scriptural literalism (or scriptural inerrancy) among American adults has steadily declined across birth cohorts [7]. Given the trends toward delayed marriage and away from religious involvement, it is important to examine whether or not previously documented relationships between religion and marriage timing are still at work in the population.

Second, there is a lack of critical and rigorous validity checks in previous studies on denominational subculture variations in marriage timing. Previous studies examining the influence of denominational affiliation on marriage timing used a measure of denominational affiliation during adolescence [3]. While the use of denominational affiliation in adolescence meets the criterion of causal reasoning, adolescent religious affiliation may not truly reflect individuals' religiosity at the time of first marriage. In effect, it may reflect individuals' parental expectations and/or family religious traditions [8,9]. Given these oversights, this study extends the denominational subculture variation thesis by using denominational affiliation in both adolescence and adulthood. This comparative and fuller approach provides an ideal test for the robustness of the denominational subculture variation thesis in the context of change and continuity in religiosity across the individuals' life course.

Third, the effects of worship service attendance and religious salience on marriage timing have been understudied. In fact, one of the frequently cited studies even overlooked other religious factors including worship service attendance and religious salience [5]. The current study fills this research void by investigating: (1) denominational subculture variations in marriage timing net of worship service attendance and religious salience; (2) independent or net effects of worship service attendance and religious salience on marriage timing after controlling for denominational affiliation; and (3) intersectional or multiplicative effects of worship service attendance and/or religious salience and denominational affiliation on marriage timing.

Finally, the current study explores the effects of religiosity on marriage timing by gender. Though previous studies have examined the links between religion and marriage timing separately by gender [3,5], no explicit and systematic efforts have been made to understand gender differences in marriage patterns. Informed by previous scholarship that deems both religion and family as gendered institutions [10–12], this study examines the gendered effects of religious denominational affiliation, worship service attendance, and religious salience on marriage timing.

### **2. Review of Literature and Research Hypotheses**

The denominational subculture thesis was initially developed by religion scholars to: (1) rank-order religious denominations along a liberal-moderate-conservative continuum; and (2) assess the consistency of these rankings across a range of "pro-family" issues, with special attention to both between-denominational differences and within-denominational homo/heterogeneity [13]. Utilizing this theoretical perspective, recent scholarship has highlighted distinctive denominational subculture variations in marriage timing. Mormons (the Latter-day Saints), moderate Protestants, and conservative Protestants marry earlier than Jews or their unaffiliated counterparts. Catholics fall right in the middle of this marriage-timing spectrum by differentiating themselves from the early marrying Latter-day Saints and conservative Protestants and the late marrying unaffiliated and Jews [3,5].

These denominational differences in marriage timing are often accounted for by their distinctive subculture variations in theological beliefs and religious norms pertaining to pro-family attitudes, fertility patterns, gender differences in educational attainment and labor force participation, as well as gender ideologies [3,5]. Mormons and conservative Protestants, for example, place a primacy on marriage and family life and emphasize family roles as a source of sanctification and fulfillment. The subcultural emphasis on traditional family life encourages and supports marriage at younger ages [3,5]. The average age of first marriage for Catholics falls between Protestants and Mormons on one end and Jews and the unaffiliated on the other. Like Protestants, Catholics also espouse a pro-family theology that might lead to earlier marriage. However, the fact that the average age of first marriage among Catholics is later than that of Protestants may be related to the contours of the Catholic respondents. Catholicism is viewed by many as an integral part of their cultural and family identity. These individuals may identify themselves as Catholic on a survey even if they are not religiously engaged, thereby being called "cultural Catholics." Individuals who were raised in a Protestant tradition but are no longer religious are less likely to maintain their Protestant identity and therefore more likely to move into the unaffiliated category. As a result, the Catholic category of respondents includes larger numbers of nominally religious respondents as compared to Protestants, and therefore Catholics may be less distinct from the religiously unaffiliated than Protestants [8].

Though the denominational subculture variation thesis is informative in identifying and explicating the multifaceted linkages between religion and marriage timing, this line of research is not without limitations. After carefully reviewing this body of literature, several weaknesses are noteworthy. First, previous studies relied heavily on respondents' denominational affiliation during adolescence [3,5]. This operationalization practice makes sense in temporal order but can be problematic and misleading. It has been argued that adolescent denominational affiliation may not accurately reflect individuals' religious identities and commitment as their religious identities and beliefs continue to be shaped and reshaped by their own discoveries as they age [8,9]. Therefore, denominational affiliation during one's upbringing or adolescence can result in inconsistent and inaccurate measures of the subcultural contexts that influence the marriage timing of young adults. To rectify this research limitation, current denominational affiliation or, more ideally, denominational affiliation at first marriage should be used to serve as a critical check.

Second, by default, the denominational subculture thesis is predicated on the theological beliefs and religious norms of the religious traditions. As such, it overlooks possible denominational variations in other measures that gauge either public or private religiosity. Two such measures that can potentially affect marriage timing across various denominational families are worship service attendance and religious salience. As a measure of public religiosity, frequency of worship service attendance can shorten marriage timing in three significant ways: (1) those who attend worship services frequently can regularly receive a moral proclamation of the importance of marriage and other pro-family, pronuptial, and pronatal messages and teachings; (2) frequent attendance at worship services can provide opportunities to cultivate religious capital or networks through which one can interact with co-religionists to enhance their views of marriage and/or to dissuade or sanction those who stray from the religious teachings; and (3) frequent attendance at worship services can also serve as an indication of religious commitment, particularly commitment to marriage and family life. In a similar fashion, religious salience, as a measure of private religiosity, can affect marriage timing as well. Religious salience is a subjective measure of how important religion is to a person and the extent to which they have internalized the religious norms, values, and teachings of their religious community [14]. Individuals who report high levels of religious salience are more likely to internalize and adopt their religion's norms and values pertaining specifically to marriage and family life. They may also be more inclined to consult or use religious teachings to inform major life decisions. Religious salience is less tangible than worship service attendance in terms of religious commitment and the sacrifice of time, energy, or income. However, religious salience represents similar commitment based on subjective assessment of internalized importance of religion. There are good reasons to believe that both frequent worship service attendance and heightened religious salience can affect marriage timing directly. The mechanism of influence for each factor, however, is dependent upon the religious context where the individual is interacting with co-religionists or internalizing religious teachings. As such, attendance and salience may affect marriage timing differentially across denominational families because of different levels of strictness in religious ideologies, expectations, and practices. For example, these religious effects can be stronger for conservative Protestant denominations for their higher levels of biblical literalism, theological conservatism, and more frequent religious service attendance [13].

A third limitation of previous research is that in spite of the widely recognized gender differences in marriage timing and religiosity [5,10–12,15], prior studies on marriage timing have taken these differences for granted. Little, if any, attention has been given to the gendered effects of religion on marriage timing. This oversight is unfortunate because both marriage and religion have long been viewed as gendered institutions [10–12]. With reference to gendered marriage, the most widely canvassed explanation offered by Jessie Bernard is that there are two different marital realities, his and hers, such that marriage benefits husbands more than wives [16]. Recent scholarship continues to document gendered boundaries, segregated roles, and gender-differentiated meanings in marriage [10]. Turning to the gendered character of religion or religiosity, scholars of religion have concluded that women are more religious than men on a wide range of measures [11,12]. Scholars of religion offer three types of explanations for this gendered religiosity: (1) women are psychologically or naturally more inclined towards religion (psychological explanation); (2) women are predisposed to such religious values as nurturance, submission, and gentleness during their childhood socialization (socialization explanation); and (3) women's structural locations in society, such as childrearing roles, lack of labor force participation experiences, and their prioritization of family life, lead to a stronger religious orientation than their male counterparts (social location explanation). These two bodies of literature jointly suggest that denominational subculture differences and other religious variations in marriage timing can be different across the two gender groups.

Guided by the literatures reviewed above, the following hypotheses are formulated:

Hypothesis 1: Those who are affiliated with a faith tradition are more likely to marry at a younger age than those who are unaffiliated (Hypothesis 1A). Moreover, among Protestants, conservative Protestants will display the earliest entrance into marriage, followed by mainline Protestants (Hypothesis 1B). Catholics, on the other hand, are expected to be between the early marrying conservative Protestants and the late marrying religiously unaffiliated (Hypothesis 1C). Finally, denominational affiliation in adolescence will exhibit weaker and inconsistent subculture influences on marriage timing than denominational affiliation at young adulthood (Hypothesis 1D).

Hypothesis 2: Regardless of denominational affiliation, there will be a negative relationship between frequency of service attendance and marriage timing such that more frequent worship service attendance will be significantly associated with a younger age at first marriage (shorter waiting time to first marriage).

Hypothesis 3: Regardless of denominational affiliation, those who deem religion important in their lives will marry earlier than those for whom religion is viewed as unimportant.

Hypothesis 4: Worship service attendance and religious salience will affect marriage timing differently across faith traditions, with the strongest effects being observed for conservative Protestants.

Hypothesis 5: Given women's higher levels of religiosity and a stronger orientation towards family life, the religious effects on marriage timing will be stronger for women than for men.

### **3. Research Methods**

### *3.1. Data*

To test the hypotheses delineated above, this study used data from the 2006–2010 cycles of the National Survey of Family Growth (NSFG 2006–2010). These surveys were designed to provide reliable national data on cohabitation, marriage, divorce, remarriage, contraception, infertility, and the health of women and infants in the United States. The pooled NSFG 2006–2010 sample was nationally representative of the civilian, non-institutionalized population, consisting of 10,403 men and 12,279 women ages 15–44. The NSFG has consistently surveyed young Americans aged 44 or younger because of its focus on reproductive health. This age truncation may limit the estimation of the religious effects on marriage timing due to its disproportionate inclusion of unmarried young respondents, thus hampering the potential to generalize the study findings to other populations (e.g., older populations). In spite of this limitation, however, the NSFG contains excellent life course transition questions pertaining to cohabitation and marriage, making the data suitable for the current study. In addition, given the analytical focus of this study on early marriage among young Americans, especially those who are religious, the pooled NSFG data are well suited for this purpose.

The NSFG 2006–2010 used a complex survey design and oversampled underrepresented groups, including African Americans and Hispanics. The survey was conducted by the Institute for Social Research (ISR) at the University of Michigan, from June 2006 through June 2010 under contract from the National Center of Health Statistics. The merged public-use data and the codebook were downloaded from the Centers for Disease Control and Prevention by the first author.

### *3.2. Dependent Variable: Waiting Time to First Marriage*

Taking a cue from previous research, this study used an event history approach to analyze the survey data [5]. Within this analytical framework, the dependent variable was conceptualized and operationalized as the waiting time to first marriage, which was constructed via two different procedures. First, for respondents who were ever married, the waiting time to first marriage was calculated by subtracting date of birth from date of first marriage (in century month = year × 12 + month). Second, for respondents who were unmarried, their waiting time was calculated by subtracting date of birth from date of interview (in century month calculated similarly as before). Respondents who were unmarried at the time of interview represent censoring cases in this study, which is one of the major advantages of using event history methods for data analysis. In other words, those who were not married at the time of interview will not be excluded from the current study because they may marry at a later time. As displayed in Table 1, the average waiting time for women is 24.4 years and for men 25.2 years, respectively, a year older for women and 3 years younger for men compared to Xu *et al.*'s study [5]. It is worth noting that one of the striking differences in this sample from Xu *et al.*'s study is the larger number of individuals who reported never being married at the time of interview. In this sample, approximately 55% of women and 64% of men reported never being married as opposed to 21% of women and 27% of men in their study based on the first wave of the National Survey of Families and Households.

**Table 1.** Sample Characteristics by Gender.

**Table 1.** *Cont.*

**Table 1.** *Cont.*

### *3.3. Key Covariates: Religious Variables*

In the current study, religious denominational affiliation, frequency of worship service attendance, and religious salience were used as covariates to replicate, update, and extend previous research on marriage timing. Consistent with previous research, denominational affiliation reported by respondents was employed to operationalize denominational subculture variations [5,13]. But due to possible changes in religiosity over the life course of respondents [8,9], two versions of the religious denominational affiliation variables were used: (1) respondents' denominational affiliation as an adolescent and (2) respondents' current (at the time of study) denominational affiliation. Because the National Center of Health Statistics did not release the original denominational affiliation variables with detailed denominational membership, the denominational affiliation variables available in the public use data filewere pre-collapsed, thus incongruent with previous studies that utilized detailed denominational membership. These variables were dummy-coded into five broader faith traditions: Catholic, conservative Protestant (Baptists and other fundamentalist Protestants), mainline Protestant (Methodists, Lutherans, Presbyterians, and Episcopal groups), other Protestant (non-denominational or Protestant groups not listed in the survey), and other religions (Muslims, Jews, Latter-day Saints and Jehovah Witnesses) with the unaffiliated serving as the reference group.

The NSFG 2006–2010 also included frequency of worship service attendance and religious salience. Worship service attendance was recorded as an ordinal variable to indicate respondents' public religiosity, with seven response categories ranging from 1 = "never attend" to 7 = "attend more than once a week." For ease of interpretation in the models, worship service attendance was treated as a continuous measure (a categorical version of the variable was experimented but no difference surfaced). While previous research used frequency of worship service attendance at age 14 [3], this study made use of current worship service attendance instead because of excessive missing data in the adolescent worship service attendance variable (missing data were observed for the vast majority of respondents).

Finally, the NSFG 2006–2010 included religious salience. This measure was used to gauge respondents' private religiosity. The NSFG 2006–2010 asked how important religion was in respondents' daily life, which was dummy-coded with 1 = salient ("very important" and "somewhat important") and 0 = not salient ("not important"). The category of "not salient" was used as the reference.

### *3.4. Other Covariates: Control Variables*

To conduct the statistical analysis, the following control variables (covariates) were included to avoid possible spurious effects of religiosity on marriage timing. Race/ethnicity was dummy-coded into Black, Hispanic, and other race/ethnicity, with white serving as the reference category. Premarital cohabitation was also dummy-coded into 1 = "ever had premarital cohabitation" and 0 = "never had premarital cohabitation" (the reference category). Current educational attainment, in actual years, was dummy-coded into two variables: high school and more than high school with less than high school serving as the reference group. Because respondents' employment status at time of marriage was unavailable, current employment status was used and dummy-coded with 1 = employed and 0 = otherwise. Family structure at age 14 was used and dummy-coded into 1 = biological two-parent family and 0 = other family arrangement. Current family resources were measured by whether the family received public assistance, which was dummy-coded into 1 = "yes" and 0 = "no". Since region of residence was not provided in the public use data, metro statistical area was used and dummy-coded into 1 = urban and 0 = rural to control for marriage market differences. Finally, years of survey were dummy-coded into three variables: 2007, 2008, and 2010, with 2006 serving as the reference category.

### *3.5. Analytic Strategies*

Following previous studies, the effects of the religious variables on marriage timing were analyzed by using a series of log-logistic parametric survival models (selected as the best fitting model among five different types of parametric survival models; not shown but available upon request). This modeling strategy has several advantages, including but not limited to: (1) censored observations for those who were not married at the time of study were incorporated into the analysis; (2) the waiting time to first marriage with flexible distributions was accounted for; and (3) fuller information was used for statistical modeling; and (4) a direct comparison with previous studies, such as Xu *et al.*'s study published in 2005, was possible.

To test study hypotheses, a nested modeling technique was used such that Model 1 was a replication model that included denominational affiliation and all of the control variables. Each model was run once with the adolescent affiliation variables and once with the current affiliation variables in order to allow a comparison of the two different measures of denominational affiliation. Models 2 and 3 were extension models that included worship service attendance and religious salience, respectively, while controlling for denominational affiliation and other covariates. Model 4 was the full model that combined all religious variables. It is important to note that these models were estimated separately for men and women in order to explore gender differences. In addition, the effects of worship service attendance and religious salience, along with statistical controls, were estimated separately for each of the five denominational families by gender. In essence, these models assessed complex moderating or intersectional effects of denominational subculture, worship service attendance or religious salience, and gender on marriage timing. It should be noted that all of these models were estimated by using the complex survey and multiple imputation procedures in Stata 13 to adjust for design effects and missing values [17,18].

### **4. Results**

### *4.1. Denominational Subculture Variations in Marriage Timing*

Model 1 of Tables 2 and 3 show general support for Hypothesis 1A. Consistent with previous studies, the negative and significant regression coefficients displayed in survival regressions indicate that the waiting time until first marriage was shorter for those who were affiliated with any faith tradition than for those who were unaffiliated. In other words, religiously affiliated respondents were more likely to marry at a younger age. This pattern generally holds for both denominational affiliation during adolescence and adulthood as shown in Tables 2 and 3.

While all religious groups marry younger than the unaffiliated, Hypothesis 1B suggests that conservative and mainline Protestants will report the earliest entries into marriage, respectively. As shown in the tables (Models 2–4), net of worship service attendance, religious salience, and other statistical controls, conservative Protestants exhibit the most consistent and early marrying effects (the negative and significant regression coefficients are observed across both versions of the denominational affiliation variables). These findings offer partial support for Hypothesis 1B pertaining to distinctive conservative Protestantism. However, in contrast to Hypothesis 1B, mainline Protestants do not marry significantly earlier than the unaffiliated once all of the covariates are controlled for in the models. Hypothesis 1C statesthat Catholics will fall between the early marrying conservative Protestants and late marrying unaffiliated in marriage timing. As it turns out, Hypothesis 1C is supported only for current denominational affiliation but rejected for adolescent denominational affiliation (no statistical differences between Catholics and the unaffiliated are observed) if other religious factors are not considered (Model 1). Once additional religious factors are added to the models, however, there is no longer a significant difference in the marriage timing of Catholics and the religiously unaffiliated.

Hypotheses 1A–1D examined the denominational subculture variations in marriage timing. The results show that both adolescent and current religious affiliations are related to marriage timing, but as was expected, current religious affiliation is a stronger measure of the subcultural influences on marriage timing (somewhat consistent with Hypothesis 1D). In addition, the subcultural context that appears to have the most consistent and significant influence on early entry into marriage is that of conservative Protestantism.

Although we found some support for denominational subculture variation, some of these variations in marriage timing are mediated by both worship service attendance and religious salience (the ancillary regression analyses indicating significant mediating effects are not shown here but available upon request). In the case of current denominational affiliation for women, denominational subculture variations in marriage timing are completely mediated (or explained) away by religious salience (see Models 3–4 of Table 2). That is, after controlling for either worship service attendance or religious salience, denominational subculture variations in marriage timing become considerably weaker or even completely nullified as compared to one of the earlier studies [5] (once again, the ancillary regression analyses confirmed these significant mediating effects).

**Table 2.** Maximum Likelihood Parameter Estimates from Log-Logistic Survival (AFT) Regressions of Waiting Time on Religious Variables for Women.

Note: \* *p* < .05; \*\* *p* < .01; \*\*\* *p* < .001. Race/ethnicity, premarital cohabitation, education, employment, family structure at age 14, poverty, urban-rural residence, and year of study are statistically controlled.

### *4.2. Worship Service Attendance, Religious Salience and Marriage Timing*

Hypothesis 2 predicts that worship service attendance will be related to a shorter waiting time to first marriage. Models 2 and 4 in Tables 2 and 3 provide the opportunity to test this hypothesis as an extension of previous studies. As expected, the negative and statistically significant survival regression coefficients show that after controlling for denominational affiliation and other covariates, every unit increase in frequency of worship service attendance is associated with a younger age at first marriage (a shorter waiting time to first marriage). This robust pattern holds for both men and women, which strongly supports Hypothesis 2. Turning to religious salience as addressed in Hypothesis 3, Models 3 and 4 in Tables 2 and 3 suggest that those for whom religion was deemed salient married earlier than those who viewed religion as unimportant in their lives. The effects of religious salience are far more robust for women than for men. In Model 4, for example, religious salience is no longer statistically significant for men when worship service attendance is included in the model, but it continues to be significant for women. In light of these results, Hypothesis 3 is partially supported.

**Table 3.** Maximum Likelihood Parameter Estimates from Log-Logistic Survival (AFT) Regressions of Waiting Time on Religious Variables for Men.

Note: \* *p* < .05; \*\* *p* < .01; \*\*\* *p* < .001. Race/ethnicity, premarital cohabitation, education, employment, family structure at age 14, poverty, urban-rural residence, and year of study are statistically controlled.

Turning to Hypothesis 4, we examine whether worship service attendance and religious salience operate differently across the different religious traditions in the study. Table 4 shows the coefficients for each of these two religious variables when the models are run separately by denomination and gender. The frequency of worship service attendance is systematically and negatively associated with time to first marriage for both male and female Catholics. Among Protestant groups, on the other hand, the negative association between worship service attendance and length of time to first marriage is not consistent across all of the models. Among conservative Protestants, there is a significant coefficient for attendance for females who were conservative Protestants in adolescence and those who are currently conservative Protestants. For the men, however, the relationship between attendance and marriage timing is only significant for those men who were conservative Protestant during adolescence. Among mainline Protestants, it is only the men for whom more frequent worship service attendance is significantly related to earlier marriage. Religious salience is significantly related to a shorter time to first marriage only for female mainline Protestants and male Catholics. Thus, the moderating effects involving religious salience are minimal and not systematic. Taken together, the survival models featured in Table 4 lend some credence to Hypothesis 4 pertaining to worship service attendance. It appears that the way in which worship service attendance influences marriage timing does vary across religious traditions. And while the effect of attendance for conservative Protestants was expected, we also found that attendance has a strong influence on marriage timing among Catholics. The support for Hypothesis 4 related to religious salience is generally weak and in most cases, statistically trivial.

**Table 4.** Maximum Likelihood Parameter Estimates from Log-Logistic Survival (AFT) Regressions of Waiting Time on Religious Variables By Denomination and Gender.

Note: \* *p* < .05; \*\* *p* < .01; \*\*\* *p* < .001. Race/ethnicity, premarital cohabitation, education, employment, family structure at age 14, poverty, urban-rural residence, and year of study are statistically controlled.

### *4.3. Gender Differences*

As was predicted in Hypothesis 5, several gendered religious effects on marriage timing emerged from this study. The noteworthy results can be stated as follows: (1) denominational subculture variations in marriage timing (especially conservative Protestant affiliation) are more prominent and systematic for men than for women after controlling for worship service attendance and religious salience; (2) religious salience, a measure of private religiosity, is more robust in affecting marriage timing for women than for men; and (3) for each of the five denominational families as depicted in Table 4, the early marrying effects of worship service attendance are more pronounced for men than for women. Based on these findings, there are noticeable gender differences in religious effects on marriage timing as was expected in Hypothesis 5. It appears, however, that private religious salience is more of an influence for women, while marriage timing among men is more consistently influenced by public religious practice (worship service attendance).

### **5. Discussion and Conclusions**

This study was designed to replicate, update, and extend previous research on the relationship between religion and marriage timing using the National Survey of Family Growth, 2006–2010, a nationally representative sample of young American men and women. As anticipated, a series of multivariate survival regression models revealed important religious effects on the waiting time to first marriage. In the pages that follow, these findings are summarized and highlighted.

First, consistent with Hypothesis 1A, respondents who were affiliated with all faith traditions exhibited shorter waiting time to first marriage than those who were unaffiliated. This finding undergirds the notion that pro-family and pro-marriage values that characterize virtually all faith traditions continue to play an important role in marriage timing. As pointed out by Uecker and Stokes [19], religion is responsible in part for much of the early marriages in recent birth cohorts. However, it is worth noting that denominational subculture variations documented in this study are less robust than previously reported, especially after other religious factors are simultaneously considered.

In support of Hypothesis 1B, conservative Protestants showed the most robust and consistent early marrying effects compared to the unaffiliated, which was followed by other Protestants (men). Given conservative Protestants' enthusiasm for pro-family values, traditional gender ideologies, and family life, these findings are highly anticipated. They underscore the subcultural uniqueness associated with conservative Protestantism that is highlighted by their distinctive biblical literalism and theological conservatism. On the other hand, inconsistent with Hypothesis 1C, those who were affiliated with the Catholic faith tradition were not statistically different from the late marrying unaffiliated once other religiosity measures (worship service attendance and religious salience) were included in the analysis. This result is consistent with the earlier discussion regarding the cultural identity of many Catholics who may identify as Catholic even thought their religious engagement more closely resembles the religiously unaffiliated. This conclusion is further supported by the findings regarding worship service attendance in Table 4. In the model for Catholics we found that those who did attend regularly were more likely to reflect the pro-family and pro-marriage stance of the Catholic Church with a shorter waiting time to marriage. Furthermore, it was difficult to conclude firmly if Hypothesis 1D was supported or rejected because the two versions of denominational affiliation exhibited different patterns in their effects on marriage timing across the two gender groups. But it seems safe to conclude that the results derived from current denominational affiliation tell "more interesting" stories.

Second, this study concluded that irrespective of denominational affiliation, as worship service attendance increased, the waiting time to first marriage became shortened, which lent strong credence to Hypothesis 2. In fact, attendance at religious services emerged as the most robust predictor of marriage timing. Moreover, worship service attendance also acted as a mediator, explaining away not only some of the denominational affiliation effects but also the effects of religious salience, which was particularly pronounced for men. These mediating effects are theoretically important for two reasons: (1) religious denominational affiliation can be nominal such that its effects on marriage timing will not matter unless it is manifested through religious practice, such as worship service attendance; and (2) in line with previous research on the linkages between religion and family life, public religiosity often exerts more pronounced net effects on marital dynamics, relationship quality, and other dimensions of marital well-being [20].

Partially consistent with Hypothesis 3, religious salience was also found to shorten the waiting time to first marriage. However, there were striking gender differences. For men, religious salience lost its statistical significance when worship service attendance was introduced, whereas for women religious salience was statistically important throughout the analysis. So why does the internalization of the religious pro-family and pro-marriage orientations and teachings matter for women but not for men? On the one hand, religious institutions tend to be gender-stratified, such that women have fewer opportunities to exhibit their religiosity publicly other than attendance at religious services. As a result, women tend to internalize their faith through such private acts as prayers and scripture studies. On the other hand, men have abundant opportunities to externalize their religious faith by serving as leaders or teachers, thus private religiosity seems to matter less for men than for women.

In partial support of Hypothesis 4, this study indicated that worship service attendance and religious salience affected the waiting time to first marriage differently across denominational families with the effects of religious salience being far less systematic than worship service attendance. Attendance at worship services mattered more consistently for Catholics than for various Protestant groups even though Catholics were not that different from the unaffiliated in marriage timing as reported above. So while Catholics as a group are not significantly different from the religiously unaffiliated, Catholics who attend regularly do in fact marry at a younger age than their less-attending or non-attending counterparts. This within-group heterogeneity was also noted for conservative Protestant women and mainline or other Protestant men. These patterns of within-group religious heterogeneity complement nicely the denominational subculture variations observed in marriage timing.

In general, this study found some evidence to support Hypothesis 5. The gendered effects of religious salience as a predictor and mediator for women, and the denominational specific effects of worship service attendance for men, supported the contention that like the institution of family or marriage, religious institutions are also gendered. In the context of marriage timing, these results echo broader forms of gender segregation in society by the well-known differentiation between the public (worship service attendance for men) and private (religious salience for women) spheres of life for both sexes.

While this study yielded some interesting and important findings, several research limitations and directions for future research need to be addressed and discussed. As noted previously, future research should utilize more refined religious denominational groups, which are less likely to be available in the public use data. Failure to separate denominational groups, such as the Latter-day Saints and Jews, from other faith traditions can make the interpretations difficult. As such, access to the original data is essential to use an appropriate classification scheme to group denominational families. In addition, with a growing number of Americans being self-classified as unaffiliated [21], further distinction of the unaffiliated group becomes necessary in order to examine properly the effects of this group on marriage timing. It is important to note that the unaffiliated group can consist of atheists, agnostics, and others who may classify themselves as unaffiliated because they tend to come from an inter-faith home, thus embracing different beliefs, values or norms. Furthermore, due to a large amount of missing data, the variable of worship service attendance in adolescence could not be used in this study. Attention is needed in future research to better record respondents' retrospective responses. An event history calendar can be very helpful in probing and recording respondents' past religious practices. Likewise, in this study many covariates serving as statistical controls were not measured at first marriage. Instead, they were measured at the time of interview. As a result, no causal relationships and implications are suggested.

Additionally, as noted previously, the National Survey of Family Growth focuses on a young population with a narrow age range from 15 to 44. Given the increasing age at first marriage across the population [22], the current data include significant numbers of respondents who are not yet married. While these factors limit our ability to measure the eventual marriage patterns of these respondents, the data do allow us to examine the marriage patterns of young adults and the prevalence of early marriage within the population. Finally, we suggest that future research incorporate qualitative studies, which can help better understand the nuanced motivations or desires for earlier or later entrance into marriage.

In closing, this study makes several noteworthy contributions to family and religious studies. In spite of the declining religiosity across birth cohorts in the U.S. and the increasing age at first marriage in recent decades [7,22], this study documented continued and important impacts of religion on marriage timing among young Americans. Echoing previous research, the present study observed persistent denominational subculture variations in marriage timing, especially for conservative Protestants compared to other denominational groups. In addition to these notable religious subculture variations, this study also revealed accelerating effects of religious attendance and salience on marriage timing. While the impacts of religious attendance were noted for both men and women, the effects of religious salience were particularly pronounced for women. This finding pertaining to private religiosity underscores the gendered nature of both family and religious life in contemporary America. This gendered finding is also nicely complemented by the complex intersection of gender, denominational affiliation, worship service attendance, and religious salience, suggesting that future research should move beyond the denominational subculture variation thesis and bring gender into the study on religion and family life in general and religion and marriage timing in particular. Finally, it is recommended that similar theoretical and methodological approaches used here be considered to examine additional life course transitions such as the timing of premarital and post-divorce cohabitation, divorce, and/or remarriage.

### **Author Contributions**

JJR and XX conceived of the study and preformed the statistical analyses. MLD and JPB provided theoretical guidance and helped to draft the manuscript. The authors jointly edited and approved the final manuscript.

### **Conflicts of Interest**

The authors declare no conflict of interest.

### **References**


**2. Methods**

Patent data for this study were extracted from the Lens online database using different keyword searches in patent titles, abstracts, and claims [17]. Title, abstract, and claim keyword searches are common tools for patent extraction [9–12]. The search was then filtered to include only patent documents (i.e., patent applications, granted patents, and three limited patents) until 2022, and the information was extracted according to patent document type, patent family, publication date, patent applicant, patent owner, patent jurisdiction, legal status of patents, and patent classification [13–16].

### **3. Results and Discussion**

### *3.1. Documents Type and Patent Families*

A total of 81 patent documents were collected between 1985 and 2022 that concern the use of hydrogels for seawater desalination processes. The selection includes 66 patent applications, 12 granted patents, and 3 limited patents. With 57 simple families and 57 extended families, it was confirmed that 57 patent documents covering the same technical subject were published at different times in the same country or in different countries or regions.

#### *3.2. Publication Date of Patent Documents*

Based on the earliest priority date, it is possible to precisely assume that 1985 is considered the starting year of patenting of hydrogels for seawater desalination [18]. Thirtyone patent documents were published between 1985 and 2019; however, 62% of all patent documents have been published during the last three years. Furthermore, 2022 was the year with the maximum recorded number of patent documents and patent applications, with 16 and 15, respectively, while 2011 was the year with the maximum number of granted patents, with a total of five (Figure 1).

**Figure 1.** Publication dates of patent documents related to the use of hydrogels for seawater desalination processes.

### *3.3. Patent Applicants and Owners*

The patent applicant is the person or organization that has filed a patent application. On the other hand, the patent owner is the organization with rights to the property of the granted patent [15].

The top 10 applicants for patent documents related to the use of hydrogels for seawater desalination processes until 2022 are displayed in Figure 2. The list includes natural persons and organizations (i.e., companies and academic institutions). The companies "Kraton Polymers US LLC" (Houston, TX, United States) and "Baoshan Iron & Steel CO LTD" (Shanghai, China) are the most prolific patenting companies, with nine and four patent documents, respectively, while William Marsh Rice University (Houston, TX, United States) and Tianjin Polytechnic University (Tianjin, China) are the academic institutions leading the way, with four patent documents each. On the other hand, different natural people are the lead applicants, with four or three patent documents.

**Figure 2.** Applicants (top 10) of patent documents related to the use of hydrogels for seawater desalination processes.

Table 1 presents the owners of patent documents related to the use of hydrogels for seawater desalination processes until 2022. The ownership of the rights to the property of the patent concerns eight owners: four companies and four academic institutions. Three of them are, at the same time, already applicants according to the top 10 applicants.

**Table 1.** Owners of patent documents related to the use of hydrogels for seawater desalination processes.

#### *3.4. Jurisdictions and Legal Status of Patents*

Patent jurisdictions correspond to the countries in which the patent is protected through the appropriate patent office at which the patent application is filed. When a patent application is filed, it is examined by the appropriate patent office (e.g., the China National Intellectual Property Administration (CNIPA), the Moroccan Office of Industrial and Commercial Property (OMPIC), the United States Patent and Trademark Office (USPTO), and so on), and a decision is delivered according to the specific patentability criteria that an invention must meet. Finally, a claimed invention through a patent application becomes a granted patent in one or more designated countries if it is qualified for patent protection [13].

For patent documents related to the use of hydrogels for seawater desalination processes, the jurisdictions of patent documents until 2022 are presented in Figure 3. China, through the CNIPA, encompasses 45 patent documents, with a patent contribution per document total of 55.56%. The United States, through the USPTO, encompasses 23 patent documents, with a patent contribution per document total of 28.4%. On the other hand, the global system for filing patent applications, known as the Patent Cooperation Treaty (PCT) and administered by the World Intellectual Property Organization (WIPO), encompasses seven patent documents, with a patent contribution per document total of 8.64%.

**Figure 3.** Jurisdictions of patent documents related to the use of hydrogels for seawater desalination processes.

Moreover, these jurisdictions of patent documents related to the use of hydrogels for seawater desalination processes ensure the following five legal statuses:

### *3.5. Patent Classifications*

As a technology indicator in a specific area, the patent classifications help inventors and researchers to categorize claimed inventions and retrieve different patent documents. The International Patent Classification (IPC) is the most widely used hierarchical system in the form of codes. It divides all technology areas into a range of sections, classes, subclasses, groups, and subgroups [13].

For patent documents related to the use of hydrogels for seawater desalination processes, the top 10 IPC codes until 2022 are presented in Table 2. The patent classifications reveal that most IPC code corresponds to C02F103/08, with 29 patent documents. It concerns the treatment of seawater using the desalination process. The IPC codes related to hydrogels and presented into these top 10 correspond to B01J13/00 and C08J3/075, which are categorized for colloid chemistry and macromolecular gels, respectively.

**Table 2.** IPC codes (top 10) of patent documents related to the use of hydrogels for seawater desalination processes.

### **4. Conclusions**

The novel approach for seawater desalination using hydrogels was successfully explored by researchers around the world. Inventors proposed various claimed inventions through this innovation. In this study, a patent landscape report was proposed regarding patent document types, patent families, publication dates, patent applicants, patent owners, patent jurisdictions, the legal status of patents, and patent classifications. Therefore, this research reveals that China and the United States are leading the way in innovation, and the most prolific patenting organizations are companies and universities. On the other hand, most inventions are intended for the treatment of seawater using desalination processes specially adapted for manufacturing semi-permeable membranes for separation processes, and the research and development are based on macromolecular gels and synthetic macromolecular compounds.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable. **Data Availability Statement:** The data presented in this study are available within this article content.

**Acknowledgments:** The author acknowledges the Cambia Institute for the Lens patent dataset used in this study.

**Conflicts of Interest:** The author declares no conflict of interest.


4. LECS with crown method

5. "After resecting the tumor, the incision line was closed using laparoscopic stapling devices."

Figure 13. Operation device was inserted into the perforation hole, and seromuscular dissection began by laparoscopy.

Although modified LECS techniques are used, the Hiki procedure is a basic concept that is employed throughout low invasive surgery for GISTs. By minimizing the resected region,

(Figures 14 and 15). Figures 10–15 are excerpted from Hiki's report.

Figure 12. Endoscopic submucosal resection around the tumor and artificial perforation was performed.

30 Gastric Cancer - An Update

In order to reduce the transmural communication during the operation, Nunobe et al. reported the crown method and inverted LECS [25]. By pulling up the incision line of the stomach with several stitches, abdominal cavity contamination is prevented. This technique was named crown method because pulled-up stomach wall looks like a crown (Figure 16). Using the traction of the stitch, the resected specimen is inverted to the intragastric cavity. This technique

to remove the tumor without the contamination of abdominal cavity. Figures 16 and 17

Laparoscopic Endoscopic Cooperative Surgery: Current Status and Perspective

http://dx.doi.org/10.5772/intechopen.76983

33

Classical LECS with crown method is an improved technique that reduces the risk of cancer cell dissemination. However, it can be difficult to completely prevent the contamination because of transmural communication during the procedure. Nonexposed endoscopic wallinversion surgery (NEWS) was first reported by Goto et al. in 2011 with the goal of minimizing transmural communication during the operation [26]. They performed NEWS in an ex vivo porcine model and described the usefulness of this procedure. By inverting the tumor into the inside of the stomach without opening the gastric lumen, complete resection with nonexposure

1. "Markings around a model lesion are made with electrocautery knife."

2. "A circumferential seromuscular incision is made from the outside."

are excerpted from Nunobe's report.

was achieved. The procedure is as follows:

5. NEWS

Figure 16. Surgeons pull up the incision line of the stomach with several stitches and pulled up stomach wall looks like a crown.

Figure 17. The stitches are also used as a supporting tool when the incision line is closed with a laparoscopic stapling device. The Figures 16 and 17 are excerpted from Nunobe's report.

was named inverted LECS. Inverted LECS with crown method is not only useful for preventing tumor seeding into peritoneal cavity, but also for securing the visual field during the operation. The stitches are also used as a supporting tool when the incision line is closed with a laparoscopic stapling device (Figure 17). Although nonexposed endoscopic wallinversion surgery (NEWS) [26] and a combination of laparoscopic endoscopic approaches to neoplasia with a nonexposure technique (CLEAN-NET) [27] are described later as nonexposure procedures, inverted LECS with crown method has few limitations such as tumor size or tumor location in comparison with NEWS or CLEAN-NET. As such, it can make it possible to remove the tumor without the contamination of abdominal cavity. Figures 16 and 17 are excerpted from Nunobe's report.


*Article* **Precautionary Behavior and Depression in Older Adults during the COVID-19 Pandemic: An Online Cross-Sectional Study in Hubei, China**

**Wei Liang 1,2, Yanping Duan 1,2,3,\*, Borui Shang 4, Chun Hu 5, Julien Steven Baker 1,2, Zhihua Lin 6, Jiali He 3 and Yanping Wang 7**

**Abstract:** The large-scale COVID-19 pandemic has not only resulted in the risk of death but also augmented the levels of depression in community-dwelling older adults. The present study aimed to investigate the characteristics of depression in Chinese older adults during the COVID-19 pandemic, to examine the association of individual precautionary behavior with older adults' depression levels, and to identify the moderating role of socioeconomic indicators in the aforementioned association. Five hundred and sixteen older adults were recruited from five cities of Hubei province in China. They were asked to complete an online questionnaire survey. Results showed that 30.8% of participants indicated a significant depressive symptom during the pandemic. Older adults' depression levels differed significantly in marital status, living situation, education level, household income, subjective health status, and infected cases of acquaintances. Precautionary behavior change showed significant inverse associations with older adults' depression levels, where household income moderated this relationship. This is the first study to investigate the characteristics, behavioral correlates, and moderators of depression among Chinese older adults during the COVID-19 pandemic. Research findings may provide new insights into interventions and policy-making on individual precautionary behavior and mental health among older adults for future pandemics.

**Keywords:** COVID-19; older adults; depression; precautionary behavior; socioeconomic status; online survey; mental health


**5.2 Nutrient absorption**

The developed biofilm regularly contains voids and water channels that give an expanded surface zone to nutrient trade. As the water channels are interconnected and dive deep into the biofilm, it guarantees supplement accessibility to microbial networks dwelling somewhere inside the biofilm. The biofilm traps the follow component and supplement from outside condition through physical trapping or electrostatic interaction. The complex biofilm design additionally gives the chance to metabolic cooperation, and specialties are framed inside these spatially composed structures. The microcolonies created in these specialties vary in their structure removal and redistribution of metabolic end product. As these microcolonies are orchestrated one next to the other, it gives a great chance to the trading of substrate, evacuation, and redistribution of metabolic finished result [23].

#### **5.3 Gene transfer**

Biofilm offer an appropriate niche during which bacterium of various microbial community will grow in shut proximity to every possible vicinity. This provides associate in nursing area for the exchange of extrachromosomal genetic parts like plasmid inclusion body. Indeed, the transfer of inclusion body deoxyribonucleic acid via conjugation occurs at higher frequency within the biofilm cells as compared to their planktonic counterparts. The horizontal transfer of conjugative plasmid adds to the event and stabilization of biofilm. Since inclusion body could have genes that provide resistance to several antimicrobials agents, biofilm formation also offers a mechanism for the unfolding of microorganism resistance to antimicrobial agents [24]. Conjugal transfer of deoxyribonucleic acid (plasmid) is not the sole mechanism of factor transfer in a very microbial biofilm; another mechanism like transformation also can be expected, as an amount of deoxyribonucleic acid is additionally found in the biofilm structure. This deoxyribonucleic acid is assumed to be discharged within the biofilm matrix by the lysis of microorganism cells as found within the case of *Streptococcus pneumonia* and *Acinetobacter calcoaceticus*. The dense population within the microcolonies of biofilm conjointly provides a wonderful chance for the uptake of this extracellular matrix deoxyribonucleic acid [25]. Researchers observed a high frequency transformation within the young and actively growing biofilms of *Acinetobacter sp.* BD413 and correlative enlarged transformation frequency with the deoxyribonucleic acid concentration and located no saturation [26].

#### **5.4 Disease**

The role of biofilm forming microorganism in mediating numerous infectious diseases is changing into rather more necessary with an increasing numbers of infections in humans. Biofilm infection in human includes microorganism endocarditis (infection of heart valves), otitis (infection of the middle ear), chronic microorganism inflammation (infection of the prostate gland), cystic fibrosis (infection of lower metabolic process system), dentistry diseases, and most medical device-connected infections [27]. These diseases are well reviewed by researchers. *Vibrion* infectious disease which is the causative agent of infectious disease has been famous to endure transition to conditionally viable environmental cells, once discharged into the environment. Recently, researchers showed that this process involves assemblage sensing dependent biofilm formation, the factors that enhances the waterborne unfold of infectious disease epidemic [28]. In *Acinetobacter baumannii*, a medical building pathogen, biofilm formation on abiotic and biological surfaces is understood to influence its virulence. Biofilm microorganisms are consistently resistant to the antimicrobial stress, and so their demolition with antibiotic treatment could be a prime concern of medical analysis [29, 30].

### **6. Conclusion**

The nature of biofilm structure and therefore the physiological attributes of biofilm organisms have inherent resistance to antimicrobial agents, no matter these antimicrobial agents are antibiotics or disinfectants. From the results obtained from the study, it can be concluded that the microbial strains that have the ability to produce biofilms become methicillin resistant. This supports the argument that biofilms play major role in providing the antibiotic resistance to bacteria.

**11**

**Author details**

Asma Bashir, Neha Farid\*, Kashif Ali and Kiran Fatima

\*Address all correspondence to<EMAIL_ADDRESS>
Technology (SZABIST), Karachi, Pakistan

provided the original work is properly cited.

Department of Biosciences, Shaheed Zulfikar Ali Bhutto Institute of Science and

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*Development of Biofilms for Antimicrobial Resistance DOI: http://dx.doi.org/10.5772/intechopen.90062*

There is no conflict of interest.

**Conflict of interest**

*Development of Biofilms for Antimicrobial Resistance DOI: http://dx.doi.org/10.5772/intechopen.90062*