For each article provide a one paragraph critique addressing the following below: For each article critique the study (how was it a good or bad study)Provide suggestions on how each study could be imp

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September 10, 2018 Original Contribution Associations of Religious Upbringing With Subsequent Health and Well-Being From Adolescence to Young Adulthood: An Outcome-Wide Analysis Ying Chen and Tyler J. VanderWeele* *Correspondence to Dr. Tyler J. VanderWeele, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Kresge Building, 677 Huntington Avenue, Boston, MA 02115 (e-mail: [email protected]).

Initially submitted November 14, 2017; accepted for publication June 29, 2018.

In the present study, we prospectively examined the associations of religious involvement in adolescence (includ- ing religious service attendance and prayer or meditation) with a wide array of psychological well-being, mental health, health behavior, physical health, and character strength outcomes in young adulthood. Longitudinal data from the Growing Up Today Study were analyzed using generalized estimating equations. Sample sizes ranged from 5,681 to 7,458, depending on outcome; the mean baseline age was 14.74 years, and there were 8–14 years of follow-up (1999 to either 2007, 2010, or 2013). Bonferroni correction was used to correct for multiple testing. All models were controlled for sociodemographic characteristics, maternal health, and prior values of the outcome vari- ables whenever data were available. Compared with no attendance, at least weekly attendance of religious services was associated with greater life satisfaction and positive affect, a number of character strengths, lower probabilities of marijuana use and early sexual initiation, and fewer lifetime sexual partners. Analyses of prayer or meditation yielded similar results. Although decisions about religion are not shaped principally by health, encouraging service attendance and private practices in adolescents who already hold religious beliefs may be meaningful avenues of development and support, possibly leading to better health and well-being.

health; lifecourse; outcome-wide analysis; prayer or meditation; religious service attendance; religious upbringing; well-being Abbreviations: GUTS, Growing Up Today Study; NHSII, Nurses’Health Study II; STI, sexually transmitted infection. America is highly religious ( 1,2). Religious beliefs and prac- tices are likely shaped by a number of factors, the most promi- nent of which may be religious upbringing in early life ( 3,4). It is a common practice for parents to raise their children based on their own religious beliefs ( 5). There has, however, been a con- tinuing decline in religiosity for decades, for the most part due to lower rates in younger generations ( 6,7). Despite the general trends of declining religious participation, there is still consider- able intergenerational religiouscontinuity in the United States ( 4). For instance, recent estimates of the rates of intergenera- tional transmission of religious affiliation were 82% in Jews, 85% in Muslims, 62% in Evangelical Protestants, and 43% in Catholics, and 59% of parents who attended religious ser- vices at least weekly had children who reported frequent ser- vice attendance ( 4).

Empirical research suggests that religion is associated with better health and well-being in adults ( 8). For instance, thereis a gradient relationship between frequent religious service attendance and lower mortality risk, even in the most rigorous studies ( 9–14). In other studies, religious involvement has also been linked to a wide range of other outcomes, such as greater psychological well-being, character strengths, reduced mental illness, and healthier behaviors ( 8,15,16). Religious teachings often concern practices related to living a healthy lifestyle and also sometimes explicitly consider character or respect for the body as an integral part of the beliefs ( 15).

Individuals engage in religion in a variety of ways, such as public participation, religious affiliation and identity, private practices, and religious coping ( 15). There have only been a limited number of studies in which investigators have com- pared the health associations of multiple forms of religious participation within the same study. Results from studies in adults generally suggest that religious attendance shows the strongest health associations in community samples, whereas 2355Am J Epidemiol.2018;187(11):2355–2364 religious coping is a prominent predictor for recovery and sur- vival in clinically ill populations ( 13,15,17).

To date, prior studies have mostly been conducted in adults.

However, research has increasingly suggested that religion may confer lifecourse influences and that religion may have even more profound health effects at younger ages ( 18,19). Existing evidence in adolescents suggests that religious involvement may protect against certain behaviors and promote positive practices ( 20–23). These studies are, however, subject to certain limita- tions. Specifically, much of the prior work is cross-sectional.

There is often limited control for baseline characteristics, and reverse causation often cannot be ruled out. For example, an observed inverse association between service attendance and depression may be confounded by prior depression status, because depression may affect subsequent service attendance ( 24). In addition, different aspects of religious involvement are often examined in separate studies and a limited number of outcomes are investigated, so that existing evidence re- mains scattered across studies. It may be important to exam- ine multiple health and well-being outcomes simultaneously within the same study ( 25,26).

To provide additional insights into the role of religious upbring- ing, we used an outcome-wide analytic approach ( 26) to prospec- tively examine the associations of religious involvement in adolescence with a wide array of psychological, mental, behav- ioral, physical health, and character strengths outcomes in young adulthood. The 2 aspects of religious participation that were examined were frequency of religious service atten- dance (a form of public participation) and frequency of prayer or meditation (a form of private practice). The inde- pendent associations of service attendance and prayer or meditation across outcomes were also examined in a second- ary analysis. We hypothesized that both frequent service attendance and prayer or meditation are each associated with greater psychological, mental, behavioral, and physical health and character strengths outcomes. Drawing upon prior literature in adults ( 13,15,17), we expected that service attendance would have stronger associations with various outcomes than would prayer or meditation. METHODS We used longitudinal data from the Nurses’Health Study II (NHSII) and the Growing Up Today Study (GUTS). NHSII was initiated in 1989, and it enrolled 116,430 nurses aged 25–42 years. In 1996, NHSII participants with children between 9 and 14 years of age were invited to have their children participate in another cohort of GUTS. A total of 16,882 children completed the questionnaires about their health. NHSII and GUTS partici- pants continue to be followed up with mailed or Web-based questionnaires annually or biennially ( 27,28). This study was approved by the Brigham and Women’s Hospital Institutional Review Boards.

Religious participation wasfirst assessed in the GUTS 1999 questionnaire wave; therefore, this year was considered as base- line for the present study. The outcome variables were assessed in the most recent waves, either the 2010 wave (for participants aged 23–30 years) or the 2013 or 2007 wave (if data were not availablein the 2010 wave). Of respondents to the 1999 questionnaire (n=12,410), those with missing data on the exposure (n=1,597 on religious service attendance andn=1,621 on prayer or medi- tation) or the outcome variable (nranged from 3,355 to 5,124 for analyses on service attendance and from 3,341 to 5,108 for analy- ses on prayer or meditation, depending on the outcome) were removed from each analysis involving those variables. Missing data on the covariates were imputed from the previous ques- tionnaire year; if no such data were available, the mean values (for continuous variables) or values of the largest category (for categorical variables) of the nonmissing data were used for imputation. This yielded samples of 5,689–7,458 indivi- duals (up to 1,329 were siblings) for analyses on service atten- dance and 5,681–7,448 individuals (up to 1,325 were siblings) for analyses on prayer or meditation, depending on the out- come. Compared with participants who were lost to follow-up in the 2010 questionnaire wave, those who remained in the cohort were older and healthier, had a higher socioeconomic status, and were more likely to report frequent religious partici- pation at baseline; in addition, a higher percentage was female (Web Table 1, available at https://academic.oup.com/aje ).

Web Table 2 shows the timing of the assessment of all vari- ables. The exposure variables (service attendance and prayer or meditation) were assessed in the GUTS 1999 questionnaire wave (participants aged 12–19 years). To reduce the possibil- ity of reverse causation, prior values of the outcome variables assessed in wave 1998 or 1999 were used as a covariate when- ever available. Exposure assessment Religious service attendance. Frequency of religious service attendance (1999 wave) was measured using the question,“How often do you go to religious meetings or services?”Response op- tions ranged from 1 (never) to 5 (more than once per week). Re- sponses were grouped into 3 categories: never, less than once per week, and at least once per week ( 29). Prayer or meditation. Frequency of prayer or meditation (1999 wave) was assessed with the question,“How often do you pray or meditate?”Response categories ranged from 1 (never) to 4 (once per day or more). Outcome assessment A wide array of psychological well-being (life satisfaction, positive affect, self-esteem, emotional processing, and emotional expression), character strengths (frequency of volunteering, sense of mission, forgiveness of others, and being registered to vote), physical health (number of physical health problems and overweight/obesity), mental health (depression, anxiety, and probable posttraumatic stress disorder), and health behavioral (cigarette smoking, frequent binge drinking, marijuana use, other illicit drug use, prescription drug misuse, number of life- time sexual partners, early sexual initiation, history of sexually transmitted Infections (STIs), teen pregnancy, abnormal Pap test results) outcomes were assessed (waves 2010, 2013, or 2007). See Web Table 3 and the Web Appendix for details on each measurement. Am J Epidemiol.2018;187(11):2355–2364 2356Chen and VanderWeele Covariates assessment Sociodemographic characteristics. Sociodemographic co- variates included participant age (in years), sex (female or male), race (white or nonwhite), and geographic region (West, Mid- west, South, or Northeast) (GUTS 1999). Maternal covariates included maternal age (in years; NHSII 1999), race (white or nonwhite; NHSII 1999), marital status (NHSII 1997), subjec- tive socioeconomic status in the United States and in the com- munity (both rated on a scale from 1 to 10), and pretax household income (<$50,000, $50,000–$74,999, $75,000–$99,999, or ≥$100,000; NHSII 2001). We also considered census-tract col- lege education rate (used as a continuous variable) and median income (<$50,000, $50,000–$74,999, $75,000–$99,999, or ≥$100,000; NHSII 2001). Maternal depression. The 5-item Mental Health Index ( 30) was used to measure maternal depressive symptoms over the past 4 weeks (NHSII 1997). As in prior work, a score less than 53 was considered to be an indicator of probable depression ( 31). Maternal smoking. The mothers also reported their current smoking status (NHSII 1997). The response categories were yes and no. Prior values of the outcome variables. To reduce the possi- bility of reverse causation, we adjusted for prior values of the outcome variables whenever data were available. Specifically, adjustments were made for prior depressive symptoms, weight status, smoking, drinking, marijuana use, other drug use, prescrip- tion drug misuse, number of lifetime sexual partners, history of early sexual initiation, history of STIs, and history of pregnancy (GUTS 1998 or 1999). Statistical analyses All statistical analyses were performed using SAS, version 9.4 (SAS Institute, Inc., Cary, North Carolina) (Pvalues were calculated based on 2-sided tests). Distributions of participant characteristics in the full analytic samples werefirst exam- ined. Next,χ 2test and analysis of variance test were used to examine the associations of service attendance and prayer or meditation with covariates separately.

In primary analyses, multiple generalized estimating equa- tions werefirst used to regress each health and well-being outcome on religious service attendance in separate models, with adjustment for clustering by sibling status. Continuous outcomes were standardized (mean=0, standard deviation, 1) to facilitate comparison of effect estimates across outcomes.

Bonferroni correction was used to correct for multiple testing.

For all analyses, we adjusted for sociodemographic character- istics, maternal health, and prior values of the outcome vari- ables whenever available. Next, we reanalyzed the primary sets of models with prayer or meditation as the exposure. Lastly, we included service attendance andprayer or meditation simulta- neously in the models to examine their independent associa- tions across outcomes.

Sensitivity analyses were performed to assess the robust- ness of the observed associations to unmeasured confounding ( 32,33). Specifically, we calculated E-values ( 33), which indi- cate the minimum strength of association that an unmeasured confounder would need to have with both the exposure and the outcome on the risk ratio scale to fully account for anobserved exposure-outcome association, above and beyond the measured covariates. RESULTS Descriptive analyses In the full analytic sample, participants were predominantly white, a higher percentage was female, and most had a high family socioeconomic status (Web Tables 4 and 5). The mean baseline age was 14.74 (standard deviation, 1.66) years. Nearly 60% of the participants attended religious services at least weekly, and 36% reported prayer or meditation at least once per day. Participant characteristics by frequency of service atten- dance are shown in Table 1, and characteristics by frequency of prayer or meditation are shown in Web Table 6. Religious service attendance, health, and well-being Compared with never attendance, at least weekly service attendance was subsequently associated with greater life sat- isfaction and positive affect, greater volunteering, greater sense of mission, more forgiveness, and lower probabilities of drug use and early sexual initiation (Table 2). It was also possibly associated with fewer depressive symptoms and lower probabilities of probable posttraumatic stress disorder, cigarette smoking, prescription drug misuse, history of STIs, and abnormal Pap test results, although the associations did not reachP<0.05 after correction for multiple testing. In comparison, there was little difference between less than weekly and never attendance of ser- vices except for in the character outcomes.

When service attendance and prayer or meditation were simul- taneously included in the model, the associations of service atten- dance with outcomes were mostly attenuated (Web Table 7), which may be due to the correlation between service attendance and prayer or meditation (r=0.60). Nevertheless, the associa- tions of service attendance with volunteering, forgiveness, mari- juana use, early sexual initiation, and the number of lifetime sexual partners remained at the levelP<0.05 even after correc- tion for multiple testing. Prayer or meditation, health, and well-being Compared with never praying or meditating, at least daily practice was associated with greater positive affect, emotional processing, and emotional expression; greater volunteering, greater sense of mission, and more forgiveness; lower likeli- hoods of drug use, early sexual initiation, STIs, and abnormal Pap test results; and fewer lifetime sexual partners (Table 3).

It was also possibly associated with greater life satisfaction and self-esteem, greater likelihood of being registered to vote, fewer depressive symptoms, and a lower risk of cigarette smoking, although the associations did not reach a level ofP<0.05 after correction for multiple testing. Somewhat unexpectedly, com- pared with never praying or meditating, at least daily practice was possibly associated with more, rather than fewer, physical health problems. A comparison of less than daily praying or meditating with never showed little difference, with only a few exceptions. For example, prayer or meditation was positively associated with volunteering, sense of mission, and forgiveness Am J Epidemiol.2018;187(11):2355–2364 Religious Upbringing and Health and Well-Being2357 Table 1.Distribution of Participant Characteristics by Frequency of Religious Service Attendance at Study Baseline (n=10,813), Growing Up Today Study, 1999 Participant CharacteristicFrequency of Religious Service Attendance a PValue Never (n=1,703)Less Than Once per Week (n=2,922)At Least Once per Week (n=6,188) % Mean (SD) % Mean (SD) % Mean (SD) Sociodemographic factors Age, years b 15.03 (1.66) 14.94 (1.67) 14.56 (1.64)<0.001 Male sex 44.86 40.97 40.16 0.002 White race 90.04 93.69 94.07<0.001 Geographic region<0.001 West 27.97 15.31 11.34 Midwest 27.44 32.43 39.23 South 9.25 13.15 16.47 Northeast 35.34 39.11 32.97 Mother’s age, years b 44.91 (3.62) 44.37 (3.53) 43.81 (3.52)<0.001 Mother’s race (white) 95.42 97.53 97.72<0.001 Mother married 87.61 89.32 94.88<0.001 Mother’s subjective SES in the Uniteed States b 7.15 (1.35) 7.13 (1.32) 7.14 (1.28) 0.90 Mother’s subjective SES in the community b 6.87 (1.61) 6.98 (1.56) 7.08 (1.53)<0.001 Pretax household income<0.001 <$50,000 11.74 12.67 13.67 $50,000–$74,999 23.40 21.97 24.83 $75,000–$99,999 20.73 21.43 23.60 ≥$100,000 44.13 43.94 37.90 Census tract college education rate, b% 33.45 (16.77) 32.81 (16.40) 30.33 (15.81)<0.001 Census tract median income<0.001 <$50,000 22.91 23.44 28.18 $50,000–$74,999 45.53 46.34 48.03 $75,000–$99,999 22.39 22.93 18.29 ≥$100,000 9.17 7.29 5.49 Maternal health Maternal depression 11.14 12.14 9.21<0.001 Maternal current smoking 9.87 9.31 5.37<0.001 Prior health status or prior health behaviors Prior depressive symptoms b 1.26 (0.62) 1.24 (0.58) 1.16 (0.57)<0.001 Prior overweight or obesity 21.09 19.18 19.68 0.30 Prior cigarette smoking 24.85 22.59 12.70<0.001 Prior alcohol drinking 13.79 12.16 4.97<0.001 Prior marijuana use 21.97 17.46 7.03<0.001 Prior drug use other than marijuana 8.93 5.50 2.40<0.001 Prior prescription drug misuse 8.83 8.36 5.30<0.001 Prior number of lifetime sexual partners b 0.40 (1.10) 0.27 (0.89) 0.10 (0.55)<0.001 Prior history of early sexual initiation 11.86 8.02 3.24<0.001 Prior history of sexually transmitted infections 0.62 0.40 0.05<0.001 Prior history of teen pregnancy 0.75 0.61 0.26 0.006 Abbreviations: SD, standard deviation; SES, socioeconomic status. aAnalysis of variance orχ 2tests were used to examine the mean (SD) levels of the characteristic or proportion of individuals within each religious service attendance category with that characteristic. bRanges of the participant characteristics were as follows: age, 12–19 years; mother’s age, 35–54 years; mother’s subjective SES in the United States, 1–10; mother’s subjective SES in the community, 1–10; census tract college education rate, 0%–85%; prior depressive symptoms, 0–4; and prior number of lifetime sexual partners, 0–6. Am J Epidemiol.2018;187(11):2355–2364 2358Chen and VanderWeele in a monotonic fashion; compared with never praying or medi- tating, doing so 1–6 times per week was related to greater emo- tional expression, fewer depressive symptoms, and fewer sexualpartners. When prayer or meditation and service attendance were simultaneously included in the model, the associations of at least daily versus never praying or meditating with emotional Table 2.Religious Service Attendance in Adolescence and Health and Well-Being in Young Adulthood (n=5,689–7,458 a), Growing Up Today Study, 1999 to 2007, 2010, or 2013 Health and Well-Being OutcomeReligious Service Attendance Comparison Less Than Once per Week vs. Never At Least Once per Week vs. Never RR b βc 95% CIPValue Threshold RR b βc 95% CIPValue Threshold Psychological well-being Life satisfaction 0.04−0.05, 0.12 0.13 0.05, 0.21<0.0019 d Positive affect 0.09 0.01, 0.17<0.05 0.18 0.10, 0.25<0.0019 d Self-esteem 0.05−0.03, 0.12 0.07−0.00, 0.14 Emotional processing 0.04−0.04, 0.12 0.03−0.05, 0.10 Emotional expression 0.04−0.04, 0.12 0.04−0.03, 0.12 Character strengths Frequency of volunteering 0.13 0.06, 0.20<0.0019 d 0.28 0.21, 0.35<0.0019 d Sense of mission 0.11 0.03, 0.19<0.01 0.28 0.20, 0.35<0.0019 d Forgiveness of others 0.33 0.24, 0.41<0.0019 d 0.69 0.61, 0.77<0.0019 d Registered to vote 1.04 1.01, 1.07<0.01 1.03 1.01, 1.06<0.05 Physical health No. of physical health problems 0.10 0.02, 0.18<0.05 0.02−0.05, 0.09 Overweight/obesity 0.98 0.89, 1.08 1.01 0.92, 1.10 Mental health Depressive symptoms−0.03−0.11, 0.05−0.12−0.19,−0.04<0.01 Depression diagnosis 0.90 0.76, 1.06 0.87 0.75, 1.01 Anxiety symptoms 0.03−0.05, 0.11−0.04−0.11, 0.04 Anxiety diagnosis 1.01 0.84, 1.22 0.89 0.75, 1.07 Probable PTSD 0.87 0.67, 1.13 0.72 0.57, 0.93<0.01 Health behaviors Cigarette smoking 0.99 0.88, 1.11 0.85 0.76, 0.96<0.01 Frequent binge drinking 1.05 0.95, 1.17 0.97 0.87, 1.07 Marijuana use 0.99 0.93, 1.04 0.83 0.78, 0.88<0.0019 d Any other illicit drug use 0.92 0.75, 1.13 0.67 0.55, 0.81<0.0019 d Prescription drug misuse 1.02 0.90, 1.15 0.84 0.74, 0.95<0.01 Number of lifetime sexual partners−0.02−0.09, 0.04−0.28−0.34,−0.21<0.0019 d Early sexual initiation 0.91 0.78, 1.06 0.65 0.55, 0.77<0.0019 d History of STIs 0.99 0.82, 1.20 0.79 0.66, 0.95<0.05 Teen pregnancy 0.81 0.47, 1.37 0.76 0.45, 1.28 Abnormal Pap test results 0.87 0.75, 1.02 0.82 0.71, 0.95<0.01 Abbreviations: CI, confidence interval; PTSD, posttraumatic stress disorder; RR, risk ratio; STIs, sexually transmitted infections.

aThe full analytic sample was restricted to those who had valid data on religious service attendance. The actual sample size for each analysis varied depending on the number of missing values for each outcome under investigation. Missing data on the covariates were imputed from previ- ous questionnaire years; if no such data were available, missing data were imputed as the mean values (continuous variables) or values of the larg- est category (categorical variables) of the nonmissing data. All models were controlled for participants’age, race, sex, geographic region, and prior health status or prior health behaviors (prior depressive symptoms, overweight/obesity, smoking, drinking, marijuana use, other drug use, prescrip- tion drug misuse, number of sexual partners, early sexual initiation, history of sexually transmitted infections, history of teen pregnancy), as well as their mother’s age, race, marital status, socioeconomic status (subjective socioeconomic status, household income, census tract college education rate, and census tract median income), depression, and smoking.

bThe effect estimates for the outcomes of probable PTSD, any other illicit drug use, and teen pregnancy were odds ratios; these outcomes were rare (prevalence<10%), so the odds ratios would approximate the RRs. The effect estimates for other dichotomized outcomes were RRs.

cAll continuous outcomes were standardized (mean=0, standard deviation, 1), andβwas the standardized effect size.dP<0.05 after Bonferroni correction (thePvalue cutoff for Bonferroni correction=0.05/26 outcomes=0.0019). Am J Epidemiol.2018;187(11):2355–2364 Religious Upbringing and Health and Well-Being2359 processing, emotional expression, volunteering, sense of mission, forgiveness, drug use, number of sexual partners, and history of STIs still held (Web Table 7); associations were attenuated, though some remained, when instead controlling for young adult, rather than adolescent, service attendance (Web Table 8).

Sensitivity analyses for unmeasured confounding To assess the robustness of the observed associations to unmeasured confounding, we calculated E-values ( 33) for the associations of religious service attendance (at least weekly vs. never) and prayer or meditation (at least daily vs. never) with various outcomes (Table 4). In the present study, there is evidence suggesting that some of the observed associations were likely robust to unmeasured confounding. This is espe- cially true with the character outcomes, drug use, and sexual behaviors. For example, as noted in Table 4, an unmeasuredconfounder would need to be associated with both service attendance and volunteering by risk ratios of 1.90 each to fully explain away the observed association of at least weekly (vs.

never) attendance of services with volunteering and by 1.72-fold each to shift the lower confidence limit for the estimate to include the null value, above and beyond the measured covariates. DISCUSSION There is growing interest in promoting protective factors that lead to better health, beyond the traditional approach that focuses on reducing risk factors for diseases ( 34). Once risk factors are established, it can be difficult to restore a healthy state. It may be more effective to promote and maintain health and well-being starting in early life ( 35). Results from the pres- ent study suggest that religious involvement in adolescence may Table 3.Prayer or Meditation in Adolescence and Health and Well-Being in Young Adulthood (n=5,689–7,448 a), Growing Up Today Study, 1999 to 2007, 2010, or 2013 Health and Well-Being OutcomePrayer or Meditation Comparison Less Than Once per Week vs. Never 1–6 Times per Week vs. Never Once per Day or More vs. Never RR b βc 95% CIPValue ThresholdRR b βc 95% CIPValue ThresholdRR b βc 95% CIPValue Threshold Psychological well- being Life satisfaction 0.05−0.04, 0.13 0.10 0.02, 0.17<0.05 0.12 0.04, 0.20<0.01 Positive affect 0.07−0.01, 0.15 0.11 0.04, 0.18<0.01 0.16 0.08, 0.23<0.0019 d Self-esteem 0.01−0.07, 0.09 0.10 0.02, 0.18<0.05 0.08 0.00, 0.15<0.05 Emotional processing0.03−0.05, 0.12 0.10 0.02, 0.18<0.05 0.13 0.06, 0.21<0.0019 d Emotional expression0.08 0.00, 0.17<0.05 0.13 0.06, 0.21<0.0019 d 0.15 0.07, 0.22<0.0019 d Character strengths Frequency of volunteering0.14 0.07, 0.22<0.0019 d 0.27 0.20, 0.34<0.0019 d 0.36 0.29, 0.43<0.0019 d Sense of mission 0.14 0.05, 0.22<0.0019 d 0.21 0.13, 0.28<0.0019 d 0.43 0.36, 0.51<0.0019 d Forgiveness of others0.37 0.29, 0.46<0.0019 d 0.60 0.52, 0.68<0.0019 d 0.83 0.75, 0.91<0.0019 d Registered to vote 1.01 0.99, 1.04 1.01 0.99, 1.04 1.03 1.00, 1.05<0.05 Physical health Number of physical health problems0.10 0.02, 0.18<0.05 0.02−0.05, 0.10 0.08 0.01, 0.15<0.05 Overweight/ obesity1.02 0.92, 1.13 0.99 0.90, 1.10 1.00 0.91, 1.10 Mental health Depressive symptoms−0.07−0.16, 0.01−0.15−0.22,−0.07<0.0019 d −0.09−0.16,−0.01<0.05 Depression diagnosis0.93 0.78, 1.10 0.95 0.80, 1.12 0.88 0.74, 1.03 Anxiety symptoms 0.02−0.06, 0.10 0.00−0.08, 0.07 0.04−0.03, 0.11 Anxiety diagnosis 1.00 0.82, 1.23 1.00 0.82, 1.21 0.96 0.79, 1.16 Probable PTSD 0.72 0.53, 0.97<0.05 0.93 0.72, 1.21 0.94 0.73, 1.22 Table continues Am J Epidemiol.2018;187(11):2355–2364 2360Chen and VanderWeele be one such protective factor for a range of health and well- being outcomes ( 20).

Consistent with prior literature, our results suggest associa- tions of frequent religious participation in adolescence with greater subsequent psychological well-being, character strengths, and lower risks of mental illness and several health behaviors ( 36–38). For instance, congruent with prior meta-analyses of mostly cross-sectional adolescent studies on religion and health behaviors ( 37,38), we found reduced probabilities of drug use and several sexual behaviors among religiously observant ado- lescents. Also, consistent with results from a prior meta-analysis of religion and forgiveness ( 39), we found a positive association of religious involvement with forgiveness in early life. Likewise, the effect size between religious involvement and depressive symptoms in the present study is similar to that from a meta- analysis (β=−0.09, 95% confidence interval:−0.11,−0.08) in which investigators integrated evidence across ages ( 40). In our study, there was little association between religious involvement and anxiety, which is in fact consistent with results from other prior longitudinal studies of adult populations ( 15)andcontrasts with results from cross-sectional studies ( 16). Our study adds to prior literature by providing evidence from longitudinal data withconfounding control and also control for baseline values of the outcome variables.

Contrary to our expectation, ourresults suggest that frequent prayer or meditation may be associated with more physical health problems. To our knowledge, the association between religion and adolescent physical health has not been well- studied; we are not aware of any prior longitudinal work in this area using community samples of adolescents ( 41). There is, however, evidence from clinical populations that individuals with chronic conditions are more likely to use private religious practices to cope with illness ( 41,42). Because of the lack of available data, we did not control for baseline physical health.

The inverse association between prayer or meditation and physical health in the present study may in part be due to reverse causation. Those who already have physical health pro- blems may be more likely to pray. It is also conceivable that those with religious beliefs may sometimes avoid medical care because of these beliefs or potentially thinking that the prayer will suffice for healing.

Service attendance is generally the strongest religious/spiritual predictor of health in nonclinical adult samples ( 8,13,17,36). In contrast, we found that compared with service attendance, prayer Table 3.Continued Health and Well-Being OutcomePrayer or Meditation Comparison Less Than Once per Week vs. Never 1–6 Times per Week vs. Never Once per Day or More vs. Never RR b βc 95% CIPValue ThresholdRR b βc 95% CIPValue ThresholdRR b βc 95% CIPValue Threshold Health behaviors Cigarette smoking 0.98 0.86, 1.11 0.99 0.88, 1.12 0.89 0.78, 1.00<0.05 Frequent binge drinking0.97 0.87, 1.09 1.00 0.90, 1.10 0.91 0.82, 1.01 Marijuana use 0.99 0.93, 1.05 0.92 0.87, 0.97<0.01 0.75 0.71, 0.80<0.0019 d Any other illicit drug use0.91 0.74, 1.12 0.75 0.62, 0.92<0.01 0.56 0.46, 0.69<0.0019 d Prescription drug misuse0.90 0.79, 1.02 0.88 0.78, 0.99<0.05 0.72 0.64, 0.82<0.0019 d Number of lifetime sexual partners−0.05−0.12, 0.02−0.13−0.20,−0.07<0.0019 d −0.40−0.46,−0.34<0.0019 d Early sexual initiation1.05 0.89, 1.24 0.84 0.71, 1.00 0.70 0.59, 0.84<0.0019 d History of STIs 0.90 0.68, 1.18 0.83 0.64, 1.08 0.60 0.47, 0.78<0.0019 d Teen pregnancy 0.87 0.50, 1.52 0.64 0.36, 1.15 0.88 0.52, 1.48 Abnormal Pap test results0.82 0.70, 0.98<0.05 0.95 0.81, 1.11 0.74 0.63, 0.88<0.0019 d Abbreviations: CI, confidence interval; PTSD, posttraumatic stress disorder; RR, risk ratio; STIs, sexually transmitted infections.aThe full analytic sample was restricted to those who had valid data on frequency of prayer or meditation. The actual sample size for each analy- sis varied depending on the number of missing values for each outcome under investigation. Missing data on the covariates were imputed from pre- vious questionnaire years; if no such data were available, missing were imputed as the mean values (continuous variables) or values of the largest category (categorical variables) of the nonmissing data. All models were controlled for participants’age, race, sex, geographic region, and prior health status or prior health behaviors (prior depressive symptoms, overweight/obesity, smoking, drinking, marijuana use, other drug use, prescrip- tion drug misuse, number of sexual partners, early sexual initiation, history of sexually transmitted infections, history of teen pregnancy), as well as their mother’s age, race, marital status, socioeconomic status (subjective socioeconomic status, household income, census tract college education rate, and census tract median income), depression, and smoking.

bThe effect estimates for the outcomes of probable PTSD, any other illicit drug use, and teen pregnancy were odds ratios; these outcomes were rare (prevalence<10%), so the odds ratios would approximate the RRs. The effect estimates for other dichotomized outcomes were RRs.

cAll continuous outcomes were standardized (mean=0, standard deviation, 1), andβwas the standardized effect size.dP<0.05 after Bonferroni correction (thePvalue cutoff for Bonferroni correction=0.05/26 outcomes=0.0019). Am J Epidemiol.2018;187(11):2355–2364 Religious Upbringing and Health and Well-Being2361 or meditation had more robust associations with a number of outcomes, including emotional processing, emotional expression, number of physical health problems, prescription drug misuse, his- tory of STIs, and abnormal Pap testresults. The exceptions to this were for life satisfaction, positive affect, probable posttraumatic stress disorder, cigarette smoking, and early sexual initiation,for which the associations with service attendance were stronger.

In adolescent populations, service attendance may be a marker of parental service attendance patterns that may not persist into later life, whereas private religious practices may more closely corre- spond to their own service attendance patterns later in life ( 43).

Adjustment of the prayer or meditation analyses for young adult Table 4.Robustness to Unmeasured Confounding (E-Values a) for Assessing the Causal Associations Between Religious Upbringing in Adolescence and Health and Well-Being in Young Adulthood (n=5,681–7,458 a), Growing Up Today Study, 2007, 2010, or 2013 Health and Well-Being OutcomeReligious Service Attendance Prayer or Meditation For Effect Estimate b For CI Limit c For Effect Estimate b For CI Limit c Life satisfaction 1.50 1.28 1.47 1.25 Positive affect 1.64 1.44 1.58 1.38 Self-esteem 1.33 1.00 1.36 1.07 Emotional processing 1.20 1.00 1.50 1.28 Emotional expression 1.23 1.00 1.56 1.35 Frequency of volunteering 1.90 1.72 2.12 1.93 Sense of mission 1.90 1.71 2.32 2.11 Forgiveness of others 3.15 2.88 3.68 3.37 Registered to vote 1.21 1.11 1.21 1.08 Number of physical health problems 1.16 1.00 1.36 1.10 Overweight/obesity 1.11 1.00 1.00 1.00 Depressive symptoms 1.47 1.25 1.39 1.13 Depression diagnosis 1.56 1.00 1.53 1.00 Anxiety symptoms 1.23 1.00 1.23 1.00 Anxiety diagnosis 1.50 1.00 1.25 1.00 Probable posttraumatic stress disorder 2.12 1.36 1.32 1.00 Cigarette smoking 1.63 1.25 1.50 1.03 Binge drinking 1.21 1.00 1.43 1.00 Marijuana use 1.70 1.53 2.00 1.81 Any other illicit drug use 2.35 1.77 2.97 2.26 Prescription drug misuse 1.67 1.29 2.12 1.74 Number of lifetime sexual partners 1.90 1.73 2.23 2.06 Early sexual initiation 2.45 1.92 2.21 1.67 History of sexually transmitted infections 1.85 1.29 2.72 1.88 Teen pregnancy 1.96 1.00 1.53 1.00 Abnormal Pap test 1.74 1.29 2.04 1.53 Abbreviation: CI, confidence interval.

aSee VanderWeele and Ding ( 33) for the formula for calculating E-values. bThe E-values for effect estimates are the minimum strength of association on the risk ratio scale that an unmea- sured confounder would need to have with both the exposure and the outcome to fully explain away the observed as- sociations of religious service attendance (at least weekly vs. never) and prayer or meditation (at least daily vs. never) with various health outcomes as shown in the last column of Tables 2and 3, conditional on the measured covariates.

For example, an unmeasured confounder would need to be associated with both religious service attendance and for- giveness of others by risk ratios of 3.15 each, above and beyond the measured covariates, to fully explain away the observed association between at least weekly religious service attendance and forgiveness of others. cThe E-values for the limit of the 95% CI closest to the null denote the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the exposure and the outcome to shift the confidence interval to include the null value, conditional on the measured covariates. For example, an unmeasured confounder would need to be associated with both religious service attendance and forgiveness of others by 2.88-fold each, above and beyond the measured covariates, to shift the lower limit of the CI for the observed association between at least weekly service attendance and forgiveness of others to include the null value. Am J Epidemiol.2018;187(11):2355–2364 2362Chen and VanderWeele service attendance only partially attenuated the associations, per- haps suggesting some independent effect.

Adolescents are particularly vulnerable to heightened inter- est in pursuing thrill-seeking behaviors ( 18). The behavioral norms and patterns formed in this period may, in fact, exert profound in- fluences over the lifecourse ( 18). For example, the initiation of smoking is more likely to occur in adolescence than in other stage of life, if it happens at all. Adolescents who have initiated smoking are also likely to continue smoking into adulthood ( 44).

Therefore, if a resilience factor can protect adolescents from initi- ating smoking, it may reduce their lifetime health risk substan- tially ( 18). The present study adds to prior evidence suggesting that religious involvement in adolescence may serve as one such protective factor in not only reducing smoking but also in main- taining psychological well-being,developing character strengths, and reducing certain behaviors, as well as possibly also reducing depression. The beneficial effects of religious involvement in adolescence may function through a number of mechanisms.

For instance, religion provides directives or personal virtue to help maintain self-control and develop negative attitudes toward certain behaviors ( 45). Some religious groups promote beliefs that create meaning and practices that foster active coping, such as practicing forgiveness and meditation, which could help youth actively cope with stress ( 45). Moreover, peer religious youth groups may be an important source of social support and adult role modeling, and they may be an avenue to direct peer influ- ences on behavioral choices. Religious congregations could also connect adolescents to networks and resources in the broader community ( 41,45).

The present study advances beyond prior literature in a number of ways. First, we took an outcome-wide analytic approach to provide a broad picture of the roleof religious participation dur- ing adolescence in relation to a wide range of health and well- being outcomes within the same sample, which helps synthesize previously scattered evidence on individual health outcomes in separate studies. Second, the longitudinal design and the follow- up periods of 8–14 years help establish temporal ordering for as- sessing causality. Third, the longitudinal data along with the adjustment for baseline values of the outcome variables help reduce the possibility of reverse causation, which has been identi- fied as a major threat to assessing causal effects of religious prac- tice ( 8). The present study also used sensitivity analyses to assess the robustness of the associations to unmeasuredconfounding, which provides further evidence for assessing causality.

Our study is, however, subject to certain limitations. First, religious involvement was measured with 2 single items that were widely used in adults. These measures did not consider developmental characteristics of adolescents. For instance, adolescents’decisions on religious participation are likely shaped by both parents and peers. It may, therefore, be important to assess influences from both (e.g., pressure by parents to attend religious services and participation in peer religious youth groups) to facilitate understanding in a developmentally relevant frame- work ( 46). Second, the results may be subject to residual con- founding by parental religiousness(e.g., parental church attendance and parental religious affiliation) for which information was not available. However, we adjusted for baseline maternal depres- sion and smoking status, whichhave both been linked to reli- gious participation and to child outcomes ( 16,47). Results from the sensitivity analysis also suggest that a number of the observedassociations are relatively robust to potential unmeasured con- founding. As a further limitation, GUTS participants were mostly white, and their mothers all worked in the nursingfield. Therefore, results of this study may not be generalizable to other populations.

There is evidence that religion is an important social deter- minant of health over the lifecourse ( 18 ). Religious participa- tion in adulthood is, in many cases, a function of religious upbringing in early life ( 18). Intergenerational transmission of religious values and practices occurs largely through parental modeling and is likely facilitated by close parent-child relation- ships ( 48). Although decisions about religion are not shaped principally by health, for adolescents who already hold reli- gious beliefs, encouraging service attendance and private prac- tices may be meaningful avenues of development and support, possibly leading to better health and well-being. ACKNOWLEDGMENTS Author affiliations: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (Ying Chen, Tyler J. VanderWeele); and Human Flourishing Program, Institute for Quantitative Social Science, Harvard University, Cambridge, Massachusetts (Ying Chen, Tyler J. VanderWeele).

This work was funded by the Templeton Foundation (grant 52125) and the National Institutes of Health (grant ES017876). The National Institutes of Health supports the Nurses’Health Study II (grant UM1CA176726) and the Growing Up Today Study (grants R01HD045763, R01HD057368, R01HD066963, R01DA033974, K01DA023610, and K01DA034753).

We thank the Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School for their support in conducting this study.

The funding agencies had no role in the data collection, analysis, or interpretation, nor were they involved in the writing or submission of this publication.

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