for perfecto

Loading... citation_instruction

Accessibility Information and Tools

Accessibility Information and Tips Revised Date: 07/2015

Prenatal substance exposure: What predicts behavioral resilience by early adolescence?

Detailed Record

Title:

Prenatal substance exposure: What predicts behavioral resilience by early adolescence?

Authors:

Liebschutz, Jane M.. Clinical Addiction Research and Education Unit, Boston Medical Center, Boston, MA, US, [email protected]  Crooks, Denise. Department of Family Medicine, Boston Medical Center, Boston, MA, US Rose-Jacobs, Ruth, ORCID 0000-0003-4498-9570 . Department of Pediatrics, Boston Medical Center, Boston, MA, US Cabral, Howard J.. Department of Biostatistics, Boston University School of Public Health, Boston, MA, US Heeren, Timothy C.. Data Coordinating Center, Boston University School of Public Health, Boston, MA, US Gerteis, Jessie. Abt Associates, Inc., Cambridge, MA, US Appugliese, Danielle P.. Data Coordinating Center, Boston University School of Public Health, Boston, MA, US Heymann, Orlaith D.. Clinical Addiction Research and Education Unit, Boston Medical Center, Boston, MA, US Lange, Allison V.. Clinical Addiction Research and Education Unit, Boston Medical Center, Boston, MA, US Frank, Deborah A.. Department of Family Medicine, Boston Medical Center, Boston, MA, US

Address:

Liebschutz, Jane M., Boston Medical Center, 801 Massachusetts Avenue, Second Floor, Boston, MA, US, 02118, [email protected] 

Source:

Psychology of Addictive Behaviors, Vol 29(2), Jun, 2015. pp. 329-337.

NLM Title Abbreviation:

Psychol Addict Behav

Publisher:

US : American Psychological Association

Other Journal Titles:

Bulletin of the Society of Psychologists in Addictive Behaviors; Bulletin of the Society of Psychologists in Substance Abuse

Other Publishers:

US : Educational Publishing Foundation Society of Psychologists in Addictive Behaviors

ISSN:

0893-164X (Print) 1939-1501 (Electronic)

Language:

English

Keywords:

resilience, violence, adolescence, intrauterine substance exposure

Abstract:

Understanding behavioral resilience among at-risk adolescents may guide public policy decisions and future programs. We examined factors predicting behavioral resilience following intrauterine substance exposure in a prospective longitudinal birth-cohort study of 136 early adolescents (ages 12.4–15.9 years) at risk for poor behavioral outcomes. We defined behavioral resilience as a composite measure of lack of early substance use initiation (before age 14), lack of risky sexual behavior, or lack of delinquency. Intrauterine substance exposures included in this analysis were cocaine, tobacco, alcohol, and marijuana. We recruited participants from Boston Medical Center as mother–infant dyads between 1990 and 1993. The majority of the sample was African American/Caribbean (88%) and 49% female. In bivariate analyses, none and lower intrauterine cocaine exposure level predicted resilience compared with higher cocaine exposure, but this effect was not found in an adjusted model. Instead, strict caregiver supervision (adjusted odds ratio [AOR] = 6.02, 95% confidence interval (CI) [1.90, 19.00], p = .002), lower violence exposure (AOR = 4.07, 95% CI [1.77, 9.38], p < .001), and absence of intrauterine tobacco exposure (AOR = 3.71, 95% CI [1.28, 10.74], p = .02) predicted behavioral resilience. In conclusion, caregiver supervision in early adolescence, lower violence exposure in childhood, and lack of intrauterine tobacco exposure predicted behavioral resilience among a cohort of early adolescents with significant social and environmental risk. Future interventions should work to enhance parental supervision as a way to mitigate the effects of adversity on high-risk groups of adolescents. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

Document Type:

Journal Article

Subjects:

*At Risk Populations; *Drug Usage; *Prediction; *Prenatal Exposure; *Resilience (Psychological); Early Adolescence

Medical Subject Headings (MeSH):

Adolescent;  Adolescent Behavior;  Cannabis;  Child;  Cocaine;  Ethanol;  Female;  Humans;  Longitudinal Studies;  Male;  Parenting;  Pregnancy;  Prenatal Exposure Delayed Effects;  Resilience, Psychological;  Tobacco;  Violence 

PsycINFO Classification:

Psychosocial & Personality Development (2840)

Population:

Human Male Female

Location:

US

Age Group:

Childhood (birth-12 yrs) School Age (6-12 yrs) Adolescence (13-17 yrs) Adulthood (18 yrs & older)

Tests & Measures:

Youth Risk Behavior Surveillance System Wisconsin Youth Risk Behavior Surveillance Middle School Questionnaire Wisconsin Youth Risk Behavior Surveillance High School Questionnaire Violence Exposure Scale for Children—Revised Hooked on Nicotine Checklist   DOI: 10.1037/t01779-000

Grant Sponsorship:

Sponsor: National Institutes of Health, National Institute on Drug Abuse Grant Number: DA 06532 Recipients: Frank, Deborah A. (Prin Inv) Sponsor: National Institutes of Health, National Center for Research Resources Grant Number: RR000533 and RR025771 Recipients: No recipient indicated

Conference:

Pediatric Academic Societies Conference, May, 2009, Baltimore, MD, US

Conference Notes:

Portions of this article were presented at the aforementioned conference and the College of Problems on Drug Dependence Annual Meeting, June 24, 2009, Reno, Nevada.

Methodology:

Empirical Study; Longitudinal Study; Prospective Study; Quantitative Study

Format Covered:

Electronic

Publication Type:

Journal; Peer Reviewed Journal

Publication History:

Accepted: Mar 9, 2015; Revised: Mar 6, 2015; First Submitted: Aug 15, 2014

Release Date:

20150615

Correction Date:

20190211

Copyright:

American Psychological Association. 2015

Digital Object Identifier:

http://dx.doi.org.ezproxy.snhu.edu/10.1037/adb0000082 

PMID:

26076097

PsycARTICLES Identifier:

adb-29-2-329

Accession Number:

2015-26085-002

Number of Citations in Source:

70

Translate Full Text:  Choose Language الإنجليزية/العربية английски език/български 英语/简体中文 英語/繁體中文 angličtina/čeština Engelsk/dansk Engels/Nederlands Anglais/Français Englisch/Deutsch Αγγλικά/Ελληνικά English/Hausa אנגלית/עברית अंग्रेज़ी/हिंदी angol/magyar Inggris/bahasa Indonesia Inglese/Italiano 英語/日本語 영어/한국어 Engelsk/Norsk انگليسی/فارسی angielski/polski Inglés/Português English/Pashto Engleză/română Английский/Русский Inglés/Español English/Serbian Angleški/Slovenski Angličtina/Slovenčina Engelska/svenska อังกฤษ/ไทย İngilizce/Türk Англійська/Українська انگریزی/اردو   Translation in Progress: Translations powered by Language Weaver Service

Prenatal Substance Exposure: What Predicts Behavioral Resilience by Early Adolescence?

Contents

1. Method
2. Study Design
3. Sample Selection
4. Data Collection
5. Dependent Variable
6. Independent Variables
7. Analysis
8. Results
9. Discussion
10. Strengths and Limitations
11. Public Health Implications
12. Conclusion
13. References

Full Text

Listen Pause Stop Select: American Accent Australian Accent British Accent Volume   Settings Download mp3 Close Player Speech-enabled by ReadSpeaker By: Jane M. Liebschutz Clinical Addiction Research and Education Unit, Boston Medical Center, Boston, Massachusetts, and Department of Medicine, Boston University School of Medicine; Denise Crooks Department of Family Medicine, Boston Medical Center Ruth Rose-Jacobs Department of Pediatrics, Boston Medical Center, and Boston University School of Medicine Howard J. Cabral Department of Biostatistics, Boston University School of Public Health Timothy C. Heeren Data Coordinating Center, Boston University School of Public Health Jessie Gerteis Abt Associates, Inc., Cambridge, Massachusetts Danielle P. Appugliese Data Coordinating Center, Boston University School of Public Health Orlaith D. Heymann Clinical Addiction Research and Education Unit, Boston Medical Center Allison V. Lange Clinical Addiction Research and Education Unit, Boston Medical Center Deborah A. Frank Department of Family Medicine, Boston Medical Center, and Department of Pediatrics, Boston University School of Medicine

Acknowledgement: The analyses presented here and preparation of this article were supported in part by National Institute on Drug Abuse, National Institutes of Health Grant DA 06532 (Deborah A. Frank, PI), and National Center for Research Resources, National Institutes of Health Grants RR000533 and RR025771. Its contents are solely the responsibility of the authors and do not represent the official view of National Center for Research Resources, National Institute of Drug Abuse, or the National Institutes of Health. Portions of this article were presented at the Pediatric Academic Societies Conference, Baltimore, Maryland, May 2009, and the College of Problems on Drug Dependence Annual Meeting, June 24, 2009, Reno, Nevada. We gratefully acknowledge analytic assistance from Brett Martin, data collection assistance from Shayna Soenksen and Laura Anatale, manuscript formatting and submission assistance from Shernaz Dossabhoy, and as always, the participants and their families.

Resilience is a dynamic process, influenced by multiple factors encompassing genetics, biology, environment, psychology, and exposure to adversity (Rutter, 2006). Resilience can be defined as positive adaptation or recovery in the context of adversity. An individual may display resilience in one functional domain at one period of development, but not necessarily in multiple domains or over different developmental epochs (Luthar & Brown, 2007). Of particular interest for policy and scientific inquiry is understanding behavioral resilience among children, adolescents, and young adults who grow up with the most extreme adversity, such as witnessed parental violence, parental addiction, and poverty. In this study, we focused specifically on a cluster of multiple problem behaviors in a high-risk cohort, as problem behaviors tend to co-occur and are also negatively related to prosocial behaviors (e.g., school attendance) and positive health behaviors (e.g., exercise, diet; Jessor, Donovan, & Costa, 1991).

There are known links between intrauterine substance exposure (IUSE) and indicators of poorer behavioral and health outcomes in adolescence. In this study, we focused on intrauterine cocaine exposure (IUCE), intrauterine tobacco exposure (IUTE), intrauterine alcohol exposure (IUAE), and intrauterine marijuana exposure (IUME) because there is substantial literature linking these exposures to negative developmental and health outcomes in children and adolescents. IUCE has been linked to adolescent substance use (Delaney-Black et al., 2011; Frank et al., 2011; Richardson, Larkby, Goldschmidt, & Day, 2013), childhood externalizing behavior problems (Bennett, Marini, Berzenski, Carmody, & Lewis, 2013), inattention, and impulsivity (Richardson, Goldschmidt, Leech, & Willford, 2011). IUTE has been associated with childhood and adolescent conduct disorder, externalizing behavior (Cornelius, Goldschmidt, De Genna, & Larkby, 2012; Piper, Gray, & Birkett, 2012; Stene-Larsen, Borge, & Vollrath, 2009), adolescent delinquent behaviors, and adult criminal behavior (Paradis, Fitzmaurice, Koenen, & Buka, 2011; Rantakallio, Läärä, Isohanni, & Moilanen, 1992). IUAE has been correlated with attention difficulties (Mattson, Crocker, & Nguyen, 2011; Underbjerg et al., 2012), delinquent behaviors (Schonfeld, Mattson, & Riley, 2005), and higher rates of attention-deficit/hyperactivity disorder (Mattson et al., 2011). IUME in the context of environmental disadvantage has been linked to increased attention problems and aggression in 18-month-old girls (El Marroun et al., 2011), future substance use (Frank et al., 2011), delinquency in late childhood (Goldschmidt, Day, & Richardson, 2000) and adolescence (Day, Leech, & Goldschmidt, 2011), and poor academic performance (Goldschmidt, Richardson, Willford, Severtson, & Day, 2012). Given this well-established literature on intrauterine exposure to individual substances and adolescent outcomes, we examined multiple forms of IUSE simultaneously to see whether some exposures are more detrimental than others and to avoid mistakenly attributing the effects of one substance on outcomes to another.

A prospective study design and biological markers to confirm IUSE are of particular importance when studying resilience because of the temporal relationship of the predictors of resilience and the markers of resilience over the lifetime of children and adolescents and to avoid ascertainment bias. For this reason, it is inappropriate to examine predictors of resilience and markers of resilience in a cross-sectional survey. Like many other research teams that have examined resilience (Bennett et al., 2013; Delaney-Black et al., 2011; Frank et al., 2011), we employed a prospective design. We also confirmed IUSE with at least one biological marker from each mother–infant dyad, including either maternal or neonatal urine drug tests or meconium radioimmunoassays.

To gain a clearer understanding of what contributes to resilience, it is essential to examine the effects of IUSE in the context of other components that influence resilience. Other factors that influence adolescent resilience that we examined in this study included parental supervision, exposure to violence, and sex. Population-based studies in the United States have found that social support, including parental support and monitoring, increases healthy resilient behaviors in adolescents (Goldstein, Faulkner, & Wekerle, 2013; Mistry, McCarthy, Yancey, Lu, & Patel, 2009; Tiet, Huizinga, & Byrnes, 2010). In previous work, we found that parental incarceration correlated with depressive symptoms and externalizing behaviors (Wilbur et al., 2007), and others have found that it appears to increase not only antisocial behaviors but also mental health problems, drug use, or educational underperformance (Murray, Farrington, & Sekol, 2012). Thus, it is not clear how parental incarceration impacts long-term resilience. In violent neighborhoods and among high-risk populations, close parental supervision and monitoring increase adolescent resilience (Burlew et al., 2009; Li, Feigelman, & Stanton, 2000; Stanton et al., 2002). Macrosystem community influences, particularly exposure to violence and neighborhood safety, can strongly impact coping skills (Benzies & Mychasiuk, 2009; Li, Nussbaum, & Richards, 2007). Li et al. (2007) found that neighborhood hassles and violence exposure increased internalizing and externalizing symptoms in adolescents. Neighborhood cohesion may lead to positive behavioral outcomes for adolescents, whereas neighborhood disorganization may be related to delinquency (Cantillon, 2006; Chung & Steinberg, 2006). In addition, exposure to violence, either as victim or witness, correlates with increased suicidal ideation in 9- and 10-year-olds and delinquent behavior in early adolescence, irrespective of IUCE or parental distress (Gerteis et al., 2011; O’Leary et al., 2006).

The relationship between sex and resilience is complex and not consistent across studies. Females show increased likelihood of behavioral resilience in young adulthood in some samples (Ackerman, Riggins, & Black, 2010; Skinner, Haggerty, Fleming, & Catalano, 2009). This may be the result of increased parental monitoring among female adolescents (Li et al., 2000). However, other samples have shown that female sex correlates with less resilience (Tusaie, Puskar, & Sereika, 2007). The interactions between sex and IUSE effects are also inconsistent (Bennett et al., 2013; Bridgett & Mayes, 2011; Dennis, Bendersky, Ramsay, & Lewis, 2006; Dixon, Kurtz, & Chin, 2008; El Marroun, et al., 2011). Non-White race has been associated with decreased resilience (Dumont, Widom, & Czaja, 2007; Fantuzzo, LeBoeuf, Rouse, & Chen, 2012; Mistry et al., 2009), not as a biologic factor but as a marker for discrimination and material deprivation, low socioeconomic status, or lack of supportive social networks (Brown, 2008; Li et al., 2007; Tusaie et al., 2007). In contrast, a sample of 489 rural African American youth developed psychosocial competence under conditions of high risk, even as they displayed lower health resilience outcomes (Brody et al., 2013).

An ecological model, which takes into account the individual, family, community, environment, and larger social context, can facilitate understanding of contributing factors toward behavioral resilience in adolescents who have experienced violence and IUSE. Using an ecological model, this exploratory study examined selected predictors of components of resilience among high-risk adolescents. We hypothesized that both IUSE and the family and social environment during childhood and adolescence would predict presence or absence of behavioral resilience in adolescence. Specifically, we hypothesized that lower levels of intrauterine exposure to substances, lower household substance use, lower exposure to violence, lower rates of parental incarceration, greater parental supervision, and greater neighborhood cohesion would be associated with greater adolescent behavioral resilience.

Method

Study Design

This was a masked prospective longitudinal cohort study of adolescents recruited at birth to examine the effects of levels of IUCE on behavior and development. Participants and their caregivers were repeatedly assessed from birth, using interviews and urine assays, as well as neuropsychological and behavioral assessments that have been reported elsewhere (Frank et al., 2011; Gerteis et al., 2011).

Sample Selection

Sample recruitment took place at the postpartum unit of Boston City Hospital (now Boston Medical Center) from 1990 to 1993. Mother–infant dyads met the following eligibility criteria: maternal age ≥18 years; infant gestational age ≥36 weeks; no need for neonatal intensive care; no diagnosis of fetal alcohol syndrome; and no indication (either by neonatal or maternal urine toxic screen or meconium assay or by history in medical record) of intrauterine exposure to illegal opiates, methadone, amphetamines, phencyclidine, barbiturates, or hallucinogens; and no history of HIV seropositivity in the infant or mother. Further information about recruitment procedures and sample characteristics has been previously described (Tronick, Frank, Cabral, Mirochnick, & Zuckerman, 1996). Boston Medical Center Institutional Review Board approval was obtained yearly. Mothers or primary caregivers also provided ongoing informed consent. Beginning at 8 years, study participants provided assent.

Of the original 252 cohort members, we analyzed data from the 136 participants examined at early adolescence, targeted for ages 12.5–14.5 years. Due to challenges in getting participants for interviews in the target range, the actual age range was 12.4–15.9 years. These participants did not differ significantly from the nonparticipants in terms of sex, ethnicity, maternal age at birth, or intrauterine exposure to alcohol, tobacco, marijuana, or cocaine.

Data Collection

This study used data collected at birth and ages 8.5 years, 9.5 years, 11 years, and early adolescence (12.4–15.9 years). The primary outcomes were obtained during early adolescence. Primary caregivers were interviewed in parallel with the participants at each time point. Children’s evaluators were masked to participants’ IUCE status and to all information furnished by their caregivers. Questions about delinquent behavior, substance use, and sexual activity were asked as part of an audio computer-assisted self-interview (ACASI) in which the participant read and listened via headphones to written and audio text of the questions and answers. The participant answered questions by clicking the computer mouse. Using the ACASI is thought to promote more truthful answers to questions on potentially sensitive subjects than would be obtained via face-to-face interview (Riley et al., 2001). ACASI questions included items from the Hooked on Nicotine Checklist (DiFranza et al., 2002), parts of the Centers for Disease Control and Prevention’s 2005 Youth Risk Behavior Surveillance System (Eaton et al., 2006), the Wisconsin Youth Risk Behavior Surveillance Middle School Questionnaire and the Wisconsin Youth Risk Behavior Surveillance High School Questionnaire. In addition, urine samples were tested for cotinine, marijuana, and other illicit drugs (Frank et al., 2011).

Dependent Variable

Resilience was defined as the absence of three outcomes: HIV risk behavior, early initiation of substance use, and delinquency. Each of these was measured at the early adolescent interview at ages 12.4–15.9 years. The latter two outcomes have been examined individually in previous publications from this study (Frank et al., 2011; Gerteis et al., 2011). Any of these three behaviors was considered an indicator that the participant was not showing resilience. Absence of these risk factors was analyzed cumulatively as a better indicator of resilience (Jessor, 1987). HIV risk behavior was defined as endorsement of one or more of the following behaviors: lack of condom use during first intercourse or most recent intercourse, injection drug use, or pregnancy (self or partner). Early initiation of substances was defined as use of substances (tobacco, alcohol, marijuana, or other illicit substances) before age 14 years. Specific questions included “How old were you when you smoked a whole cigarette for the first time?” and “How old were you when you had your first drink of alcohol other than a few sips?” It was specified that “a drink of alcohol is equal to having a can of beer (the same size as a soda can), a glass of wine, a wine cooler, or a shot of liquor such as rum, gin, vodka, or whiskey.” For misuse of prescription medications (e.g., amphetamines, steroids, oxycodone and other pain killers, or benzodiazepines), the question was “How old were you when you first tried taking [substance of interest] without a doctor or nurse telling you to take them?” In the case of illicit substances (marijuana, heroin, cocaine, “club drugs”), a quantity was not specified, with the question framed as “How old were you when you first tried [substance] for the first time?” Delinquency was defined as self-report of at least three delinquent activities in response to seven questions on minor criminal behavior from the National Longitudinal Study of Adolescent Health (Gerteis et al., 2011; Udry, 2003).

Independent Variables

We identified a priori a set of caregiver and adolescent variables to be tested as predictors of behavioral resilience in the context of an ecological model: (a) no IUSE, (b) lack of household substance use during participants’ early adolescence, (c) lower exposure to violence, (d) higher neighborhood cohesion, (e) strict supervision during adolescence, (f) no history of parental incarceration, (g) female sex, and (h) birth mother’s race/ethnicity (African American/African Caribbean vs. other).

IUSE

Levels of IUSE were determined by infant urine and meconium assays as well as urine assays and postpartum interviews of the mothers using an adaptation of the Addiction Severity Index (5th ed.; McLellan et al., 1992). IUCE was classified as heavier, lighter, or none, where heavier was defined as the top quartile of self-reported days of maternal cocaine use during the index pregnancy and/or the top quartile of cocaine metabolites in the infant’s meconium. All other intrauterine cocaine use was defined as lighter. Self-reported IUTE was coded as yes/no and none, <[1/2] pack per day, and ≥[1/2] pack of cigarettes per day. IUTE was initially coded in a three-level variable, but both levels of tobacco exposure had similar results. To conserve degrees of freedom in the analysis, we chose to combine them into a single variable (exposed or not) for the multivariable analyses. Self-reported IUAE was coded as none versus any drinking by the mother during last 30 days of the index pregnancy. IUME was determined by a positive result on any one of the following: mothers’ self-report and urine and meconium assays (any detection was considered positive), obtained from the mothers and newborns. A third of the marijuana users in this cohort who denied marijuana use were identified solely on the basis of meconium or urine assay.

Household substance use

At each study visit, household substance use was determined by the caregivers’ responses to questions asking whether any member of the household where the child was living or spent considerable time used individual substances (marijuana, cocaine, tobacco, heroin, prescription medications not taken as prescribed, methadone) or had a drinking problem. Household tobacco use (yes/no) was analyzed separately from other household substance use because it was thought that it might have unique effects separate from other substances (Weitzman, Gortmaker, & Sobol, 1992). Of note, because caregiver’s own substance use was too highly correlated with prenatal exposure to give an independent effect, substance use by members other than the caregiver was used for this variable.

Exposure to violence

Children’s self-reported exposure to violence (as either a witness or a victim) was measured using the Violence Exposure Scale for Children—Revised (Fox & Leavitt, 1995). This measure was used in its original cartoon format accompanying the questionnaire at ages 8.5, 9.5, and 11 years, and then as a modified questionnaire without cartoons in early adolescence. Scores at each age were grouped in quartiles, with the fourth quartile being the highest level of exposure and the first quartile being the lowest level of exposure. Quartiles were chosen because the scale total score is not weighted for severity (Frank et al., 2011; Gerteis et al., 2011). Others have used rank order in quartiles as a mode of analysis (Shahinfar, Fox, & Leavitt, 2000). Never being in the highest quartile of self-reported violence exposure at any study assessment was used as a predictor of resilience.

Neighborhood cohesion

Caregiver-reported neighborhood cohesion during early adolescence was a composite variable of caregivers’ responses to three questions drawn from the National Survey of Children’s Health (U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, & National Center for Health Statistics, 2003) on perceived aspects of the neighborhood (e.g., “We watch out for each other’s children,” “People in my neighborhood help each other out,” and “There are people I can count on in this neighborhood”). The instrument uses a 7-point Likert scale that ranges from very strongly disagree to very strongly agree, with a composite score ranging from 3 to 21 (low to high cohesion).

Supervision during adolescence

Participants reported on their perceptions of caregivers’ parenting during adolescence with relation to strictness/supervision (Eaton et al., 2006). The supervision scale consisted of questions that asked specifically about parental strictness about the adolescent’s activities (e.g., “In a typical week, what is the latest you can stay out on school nights?”) and parental knowledge about the adolescent’s activities (e.g., “My parents know exactly where I am most afternoons after school” [yes/no]; “How much do your parents really know what you do with your free time?” [don’t know/know a little/know a lot]). For each of these scale scores, we divided the continuous scores into quartiles and created a dichotomous variable of the highest quartile versus others in our sample.

Parental incarceration

Parental incarceration at any time was determined by any positive caregiver response during childhood or adolescent interviews to the following questions: “In [child’s] lifetime, has his or her father been in jail or prison?” and “How many times since [the child] was born, have you been in jail or prison (either because you were serving a sentence or because you were detained before a trial)?”

Caregiver type

Caregiver type in early adolescence was defined as birth mother, kin, or unrelated as identified by the adult accompanying the participant who gave informed consent at each study visit. This was measured at each study visit.

Analysis

Bivariate analyses using logistic regression models unadjusted for covariates were performed to determine associations with resilience for the seven theoretical predictor variables. A multivariable logistic regression analysis included all independent variables that were associated with resilience at p < .10, age, and all IUSEs, which were a main focus of the construction of the source sample. Multicollinearity was not found in the multivariable regression. Odds ratios (ORs) and 95% confidence intervals (CIs) were computed from the logistic regression models. Statistically significant results had two-tailed p values less than .05. All analyses were conducted using SAS, Version 9.3.

Results

Of the 136 participants, the mean age = 14.2 years (SD = 0.7, range 12.4–15.9 years); 72 (53%) were classified as behaviorally resilient. Specifically, 94% of the cohort exhibited no HIV risk behaviors, 76% reported two or fewer delinquent acts, and 59% had not initiated alcohol, tobacco, or other substance use (see Table 1). Behavioral Resilience by Maternal and Adolescent Characteristics: Bivariate Analyses (N = 136)

In bivariate analyses, a number of variables were found to be significantly (p < .05) associated with resilience, including lower levels of violence exposure between ages 8.5–11.5 years, strict parental supervision, lack of substance use in the home during adolescence, no IUCE compared with heavy IUCE, and lack of IUAE and IUTE. Sex and race/ethnicity were not correlated with behavioral resilience (see Table 1). Scores on acceptance/involvement, psychological autonomy, parental incarceration, neighborhood cohesion, and caregiver type during early adolescence were not related to resilience and are not presented here.

In multivariable logistic regression analysis, strictest supervision (adjusted odds ratio [AOR] = 6.02, 95% CI [1.90, 19.00], p = .002), lower violence exposure (AOR = 4.07, 95% CI [1.77, 9.38], p = .001), and lack of IUTE (AOR = 3.71, 95% CI [1.28, 10.74], p = .02) were statistically significant protective factors associated with behavioral resilience (see Table 2). Older age appeared protective, with results just above statistical significance (AOR = 0.52, 95 CI% [0.27, 1.02], p = .06). No statistically significant interactions were found with IUCE and other salient independent variables. Predictors of Resilience: Multivariable Logistic Regression

To further explore the tobacco results, we conducted a (post hoc) multivariable analysis limited to those with both lighter and heavier IUCE to test whether the intrauterine tobacco effects found were due to high prevalence of IUTE in participants with heavy cocaine exposure. The results showed no difference by low versus high IUCE (results not shown).

Discussion

Strict caregiver supervision in early adolescence, lower violence exposure from ages 8–14 years, and lack of IUTE were predictors of behavioral resilience in this exploratory analysis among a cohort of early adolescents with significant social and environmental risk regardless of IUCE status. In contrast to our hypothesis, although heavy IUCE was associated with decreased odds of resilience when compared with no IUCE in bivariate analyses, this effect was not identified after controlling for other factors. Viewed from an ecological stance, the biologic factor of IUTE, the microsystem factor of parental supervision, and the combined micro-/macrosystem factors of lower violence exposure each contributed significantly to behavioral resilience.

The findings from this current study also support growing understanding of the potent effect of violence on development and behavior. Adverse childhood experiences, including exposure to violence, have been associated in retrospective studies with a number of lifelong problems, including depression, substance abuse, and high-risk health behaviors (Felitti et al., 1998). The proposed mechanism for this relationship is that violence exposure disrupts the normal stress response of the hypothalamic–pituitary–adrenal axis (Neigh, Gillespie, & Nemeroff, 2009), so that cortisol does not appropriately increase in response to stress. This blunted cortisol response is highly associated with depression and other mental health problems (Neigh et al., 2009). Lester and Padbury (2009) found an exaggerated blunting of the cortisol response in 11-year-olds who had both childhood exposure to domestic violence and IUCE, compared with those without IUCE, without violence, or without either. In our study, the impact of not experiencing high levels of violence on behavioral resilience points to an urgent need to prevent violence exposure.

Our findings on parental supervision are consistent with work conducted in other studies that did not account for documented IUSE (Steinberg, Lamborn, Darling, Mounts, & Dornbusch, 1994). Chilcoat and Anthony (1996) reported that lower parental supervision increased the risk for early initiation of substances in a sample of largely minority children from an urban setting. Burlew et al. (2009) noted that parental supervision buffered the impact of increased neighborhood risk for early substance initiation in a sample of African American youth living in low-income neighborhoods. In intergenerational longitudinal studies, decreased parental monitoring was associated with externalizing behaviors (e.g., precursors of delinquency; Bailey, Hill, Oesterle, & Hawkins, 2009). Lahey, Van Hulle, D’Onofrio, Rodgers, and Waldman (2008) reported that parental knowledge of children’s peers and limit setting influenced risk of adolescent delinquency, particularly in adolescents in high-risk neighborhoods. Similarly, parental monitoring and supervision have been shown to decrease early sexual activity among high-risk adolescents (Boislard & Poulin, 2011; Browning, Leventhanl, & Brooks-Gunn, 2005).

The continued impact of IUTE into adolescence confirms other studies that have shown that such exposure has been associated with conduct disorder and behavioral problems in childhood and adolescence in samples without IUCE (Brook, Zhang, Rosenberg, & Brook, 2006; Desrosiers et al., 2013; Gaysina et al., 2013; Rantakallio et al., 1992). Furthermore, the findings on IUTE expose misconceptions about relative impact of intrauterine exposure to legal compared with illegal substances on long-term behavioral outcomes. The fact that tobacco is legal and cocaine is not is often misinterpreted to suggest that IUTE is less harmful than intrauterine exposure to illicit substances. However, as our study has demonstrated, IUTE can have long-lasting behavioral consequences identifiable even when such use co-occurs with IUCE. Smoking cessation programs should focus on women of childbearing age (Chamberlain et al., 2013; Lumley et al., 2009; Valanis et al., 2001).

Strengths and Limitations

The strengths of this study include the prospective longitudinal cohort design and the detailed biological information on intrauterine exposures, as well as frequent prospective data collection on predictors and outcomes of interest. We acknowledge that this study has several limitations. First, the sample size may have affected the statistical power to detect a significant association of IUCE and resilience or lack of resilience. Although we may have failed to identify all factors associated with resilience because of lack of power, we did find three factors, one at each level predicted by the ecological model, which significantly influenced resilience. Furthermore, we constructed multiple models to test our predetermined hypothesis, which used a limited number of variables in order to diminish the impact of sample size on statistical power. Second, use of a dichotomous outcome (i.e., resilient vs. not resilient) may have obscured more subtle findings that relate to this complex developmental process. Third, the model in this study predicting resilience in early adolescence may not have predicted resilience in other developmental periods. In particular, this sample had a low rate of risky sexual behavior, which may have been due to the age itself. Prevalence of sexual behavior itself is low in this age group as compared with older age groups. The risky sexual behavior measure of resiliency likely played a minor role in this study, but in older age groups, resiliency to risky sexual behaviors may be more common. Lastly, our findings may be generalized only to urban, low-income, predominantly African American/African Caribbean populations. Further research needs to be conducted in other samples, including cohorts that are of higher socioeconomic status, rural, or of other ethnicities.

Public Health Implications

Family practices and environmental factors, particularly stricter caregiver supervision and less exposure to violence, may buffer the negative behavioral impact of IUSE for at-risk urban youth. While IUTE remains a risk for negative behavioral outcomes, this study points also to potential postnatal points of modifiable environmental experiences that can moderate early life disadvantages. Because this is an observational study, it was not known whether an intervention to reduce violence and increase parental supervision will enhance behavioral resilience.

Conclusion

Lower exposure to violence in childhood, close parental supervision in adolescence, and lack of IUTE predicted increased behavioral resilience in high-risk urban adolescents, half of whom had IUCE. Despite the presumed increased risk for adolescent maladaptive behaviors associated with IUCE, level of IUCE was not related to lower odds of behavioral resilience after covariate control. Interventions to enhance parental supervision in adolescence should be tested as a method to mitigate the effects of harmful exposures for high-risk youth.

References

Ackerman, J. P., Riggins, T., & Black, M. M. (2010). A review of the effects of prenatal cocaine exposure among school-aged children. Pediatrics, 125, 554–565.

Bailey, J. A., Hill, K. G., Oesterle, S., & Hawkins, J. D. (2009). Parenting practices and problem behavior across three generations: Monitoring, harsh discipline, and drug use in the intergenerational transmission of externalizing behavior. Developmental Psychology, 45, 1214–1226. 10.1037/a0016129

Bennett, D. S., Marini, V. A., Berzenski, S. R., Carmody, D. P., & Lewis, M. (2013). Externalizing problems in late childhood as a function of prenatal cocaine exposure and environmental risk. Journal of Pediatric Psychology, 38, 296–308. 10.1093/jpepsy/jss117

Benzies, K., & Mychasiuk, R. (2009). Fostering family resiliency: A review of the key protective factors. Child & Family Social Work, 14, 103–114. 10.1111/j.1365-2206.2008.00586.x

Boislard, P. M.-A., & Poulin, F. (2011). Individual, familial, friends-related and contextual predictors of early sexual intercourse. Journal of Adolescence, 34, 289–300. 10.1016/j.adolescence.2010.05.002

Bridgett, D. J., & Mayes, L. C. (2011). Development of inhibitory control among prenatally cocaine exposed and non-cocaine exposed youths from late childhood to early adolescence: The effects of gender and risk and subsequent aggressive behavior. Neurotoxicology and Teratology, 33, 47–60. 10.1016/j.ntt.2010.08.002

Brody, G. H., Yu, T., Chen, E., Miller, G. E., Kogan, S. M., & Beach, S. R. (2013). Is resilience only skin deep? Rural African Americans’ socioeconomic status-related risk and competence in preadolescence and psychological adjustment and allostatic load at age 19. Psychological Science, 24, 1285–1293. 10.1177/0956797612471954

Brook, D. W., Zhang, C., Rosenberg, G., & Brook, J. S. (2006). Maternal cigarette smoking during pregnancy and child aggressive behavior. The American Journal on Addictions, 15, 450–456. 10.1080/10550490600998559

Brown, D. (2008). African American resiliency: Examining racial socialization and social support as protective factors. Journal of Black Psychology, 34, 32–48.

Browning, C. R., Leventhanl, T., & Brooks-Gunn, J. (2005). Sexual initiation in early adolescence: The nexus of parental and community control. American Sociological Review, 70, 758–778.

Burlew, K. A., Johnson, C. S., Flowers, A. M., Peteet, B. J., Griffith-Henry, K. D., & Buchanan, N. D. (2009). Neighborhood risk, parental supervision and the onset of substance use among African American adolescents. Journal of Child and Family Studies, 18, 680–689.

Cantillon, D. (2006). Community social organization, parents, and peers as mediators of perceived neighborhood block characteristics on delinquent and prosocial activities. American Journal of Community Psychology, 37, 111–127. 10.1007/s10464-005-9000-9

Chamberlain, C., O’Mara-Eves, A., Oliver, S., Caird, J. R., Perlen, S. M., Eades, S. J., & Thomas, J. (2013). Psychosocial interventions for supporting women to stop smoking in pregnancy. Cochrane Database of Systematic Reviews, 10, CD001055.

Chilcoat, H. D., & Anthony, J. C. (1996). Impact of parent monitoring on initiation of drug use through late childhood. Journal of the American Academy of Child & Adolescent Psychiatry, 35, 91–100. 10.1097/00004583-199601000-00017

Chung, H. L., & Steinberg, L. (2006). Relations between neighborhood factors, parenting behaviors, peer deviance, and delinquency among serious juvenile offenders. Developmental Psychology, 42, 319–331. 10.1037/0012-1649.42.2.319

Cornelius, M. D., Goldschmidt, L., De Genna, N. M., & Larkby, C. (2012). Long-term effects of prenatal cigarette smoke exposure on behavior dysregulation among 14-year-old offspring of teenage mothers. Maternal and Child Health Journal, 16, 694–705. 10.1007/s10995-011-0766-0

Day, N. L., Leech, S. L., & Goldschmidt, L. (2011). The effects of prenatal marijuana exposure on delinquent behaviors are mediated by measures of neurocognitive functioning. Neurotoxicology and Teratology, 33, 129–136. 10.1016/j.ntt.2010.07.006

Delaney-Black, V., Chiodo, L. M., Hannigan, J. H., Greenwald, M. K., Janisse, J., Patterson, G., . . .Sokol, R. J. (2011). Prenatal and postnatal cocaine exposure predict teen cocaine use. Neurotoxicology and Teratology, 33, 110–119. 10.1016/j.ntt.2010.06.011

Dennis, T., Bendersky, M., Ramsay, D., & Lewis, M. (2006). Reactivity and regulation in children prenatally exposed to cocaine. Developmental Psychology, 42, 688–697. 10.1037/0012-1649.42.4.688

Desrosiers, C., Boucher, O., Forget-Dubois, N., Dewailly, E., Ayotte, P., Jacobson, S. W., . . .Muckle, G. (2013). Associations between prenatal cigarette smoke exposure and externalized behaviors at school age among Inuit children exposed to environmental contaminants. Neurotoxicology and Teratology, 39, 84–90. 10.1016/j.ntt.2013.07.010

DiFranza, J. R., Savageau, J. A., Fletcher, K., Ockene, J. K., Rigotti, N. A., McNeill, A. D., . . .Wood, C. (2002). Measuring the loss of autonomy over nicotine use in adolescents: The DANDY (Development and Assessment of Nicotine Dependence in Youths) study. Archives of Pediatrics & Adolescent Medicine, 156, 397–403. 10.1001/archpedi.156.4.397

Dixon, D. R., Kurtz, P. F., & Chin, M. D. (2008). A systematic review of challenging behaviors in children exposed prenatally to substances of abuse. Research in Developmental Disabilities, 29, 483–502.

Dumont, K. A., Widom, C. S., & Czaja, S. J. (2007). Predictors of resilience in abused and neglected children grown-up: The role of individual and neighborhood characteristics. Child Abuse & Neglect, 31, 255–274.

Eaton, D. K., Kann, L., Kinchen, S., Ross, J., Hawkins, J., Harris, W. A., . . .Wechsler, H. (2006). Youth risk behavior surveillance—United States, 2005. MMWR Surveillance Summaries. Retrieved from http://www.cdc.gov.ezproxy.snhu.edu/mmwr/preview/mmwrhtml/ss5505a1.htm

El Marroun, H., Hudziak, J. J., Tiemeier, H., Creemers, H., Steegers, E. A., Jaddoe, V. W., . . .Huizink, A. C. (2011). Intrauterine cannabis exposure leads to more aggressive behavior and attention problems in 18-month-old girls. Drug and Alcohol Dependence, 118, 470–474. 10.1016/j.drugalcdep.2011.03.004

Fantuzzo, J., LeBoeuf, W., Rouse, H., & Chen, C. C. (2012). Academic achievement of African American boys: A city-wide, community-based investigation of risk and resilience. Journal of School Psychology, 50, 559–579. 10.1016/j.jsp.2012.04.004

Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., . . .Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) study. American Journal of Preventive Medicine, 14, 245–258. 10.1016/S0749-3797(98)00017-8

Fox, N. A., & Leavitt, L. A. (1995). VEX-R: The Violence Exposure Scale for Children—Revised. College Park, MD: Department of Human Development, University of Maryland.

Frank, D. A., Rose-Jacobs, R., Crooks, D., Cabral, H., Gerteis, J., Hacker, K., . . .Heeren, T. (2011). Adolescent initiation of licit and illicit substance use: Impact of intrauterine exposures and post-natal exposure to violence. Neurotoxicology and Teratology, 33, 100–109.

Gaysina, D., Fergusson, D. M., Leve, L. D., Horwood, J., Reiss, D., Shaw, D. S., . . .Harold, G. T. (2013). Maternal smoking during pregnancy and offspring conduct problems: Evidence from 3 independent genetically sensitive research designs. Journal of the American Medical Association Psychiatry, 70, 956–963. 10.1001/jamapsychiatry.2013.127

Gerteis, J., Chartrand, M., Martin, B., Cabral, H. J., Rose-Jacobs, R., Crooks, D., & Frank, D. A. (2011). Are there effects of intrauterine cocaine exposure on delinquency during early adolescence? A preliminary report. Journal of Developmental and Behavioral Pediatrics, 32, 393–401. 10.1097/DBP.0b013e318218d9f2

Goldschmidt, L., Day, N. L., & Richardson, G. A. (2000). Effects of prenatal marijuana exposure on child behavior problems at age 10. Neurotoxicology and Teratology, 22, 325–336. 10.1016/S0892-0362(00)00066-0

Goldschmidt, L., Richardson, G. A., Willford, J. A., Severtson, S. G., & Day, N. L. (2012). School achievement in 14-year-old youths prenatally exposed to marijuana. Neurotoxicology and Teratology, 34, 161–167. 10.1016/j.ntt.2011.08.009

Goldstein, A. L., Faulkner, B., & Wekerle, C. (2013). The relationship among internal resilience, smoking, alcohol use, and depression symptoms in emerging adults transitioning out of child welfare. Child Abuse & Neglect, 37, 22–32. 10.1016/j.chiabu.2012.08.007

Jessor, R. (1987). Problem-behavior theory, psychosocial development, and adolescent problem drinking. British Journal of Addiction, 82, 331–342. 10.1111/j.1360-0443.1987.tb01490.x

Jessor, R., Donovan, J. E., & Costa, F. M. (1991). Beyond adolescence: Problem behavior and young adult development. New York, NY: Cambridge University Press.

Lahey, B. B., Van Hulle, C. A., D’Onofrio, B. M., Rodgers, J. L., & Waldman, I. D. (2008). Is parental knowledge of their adolescent offspring’s whereabouts and peer associations spuriously associated with offspring delinquency?Journal of Abnormal Child Psychology, 36, 807–823.

Lester, B. M., & Padbury, J. F. (2009). Third pathophysiology of prenatal cocaine exposure. Developmental Neuroscience, 31, 23–35. 10.1159/000207491

Li, S. T., Nussbaum, K. M., & Richards, M. H. (2007). Risk and protective factors for urban African-American youth. American Journal of Community Psychology, 39, 21–35.

Li, X., Feigelman, S., & Stanton, B. (2000). Perceived parental monitoring and health risk behaviors among urban low-income African-American children and adolescents. Journal of Adolescent Health, 27, 43–48. 10.1016/S1054-139X(99)00077-4

Lumley, J., Chamberlain, C., Dowswell, T., Oliver, S., Oakley, L., & Watson, L. (2009). Interventions for promoting smoking cessation during pregnancy. Cochrane Database of Systematic Reviews, 8, CD001055.

Luthar, S. S., & Brown, P. J. (2007). Maximizing resilience through diverse levels of inquiry: Prevailing paradigms, possibilities, and priorities for the future. Development and Psychopathology, 19, 931–955. 10.1017/S0954579407000454

Mattson, S. N., Crocker, N., & Nguyen, T. T. (2011). Fetal alcohol spectrum disorders: Neuropsychological and behavioral features. Neuropsychology Review, 21, 81–101. 10.1007/s11065-011-9167-9

McLellan, A. T., Kushner, H., Metzger, D., Peters, R., Smith, I., & Grissom, G. (1992). The fifth edition of the Addiction Severity Index. Journal of Substance Abuse Treatment, 9, 199–213.

Mistry, R., McCarthy, W. J., Yancey, A. K., Lu, Y., & Patel, M. (2009). Resilience and patterns of health risk behaviors in California adolescents. Preventive Medicine, 48, 291–297.

Murray, J., Farrington, D. P., & Sekol, I. (2012). Children’s antisocial behavior, mental health, drug use, and educational performance after parental incarceration: A systematic review and meta-analysis. Psychological Bulletin, 138, 175–210. 10.1037/a0026407

Neigh, G. N., Gillespie, C. F., & Nemeroff, C. B. (2009). The neurobiological toll of child abuse and neglect. Trauma, Violence, & Abuse, 10, 389–410. 10.1177/1524838009339758

O’Leary, C. C., Frank, D. A., Grant-Knight, W., Beeghly, M., Augustyn, M., Rose-Jacobs, R., . . .Gannon, K. (2006). Suicidal ideation among urban nine and ten year olds. Journal of Developmental and Behavioral Pediatrics, 27, 33–39. 10.1097/00004703-200602000-00005

Paradis, A. D., Fitzmaurice, G. M., Koenen, K. C., & Buka, S. L. (2011). Maternal smoking during pregnancy and criminal offending among adult offspring. Journal of Epidemiology and Community Health, 65, 1145–1150. 10.1136/jech.2009.095802

Piper, B. J., Gray, H. M., & Birkett, M. A. (2012). Maternal smoking cessation and reduced academic and behavioral problems in offspring. Drug and Alcohol Dependence, 121, 62–67. 10.1016/j.drugalcdep.2011.08.004

Rantakallio, P., Läärä, E., Isohanni, M., & Moilanen, I. (1992). Maternal smoking during pregnancy and delinquency of the offspring: An association without causation?International Journal of Epidemiology, 21, 1106–1113. 10.1093/ije/21.6.1106

Richardson, G. A., Goldschmidt, L., Leech, S., & Willford, J. (2011). Prenatal cocaine exposure: Effects on mother- and teacher-rated behavior problems and growth in school-age children. Neurotoxicology and Teratology, 33, 69–77. 10.1016/j.ntt.2010.06.003

Richardson, G. A., Larkby, C., Goldschmidt, L., & Day, N. L. (2013). Adolescent initiation of drug use: Effects of prenatal cocaine exposure. Journal of the American Academy of Child & Adolescent Psychiatry, 52, 37–46. 10.1016/j.jaac.2012.10.011

Riley, E. D., Chaisson, R. E., Robnett, T. J., Vertefeuille, J., Strathdee, S. A., & Vlahov, D. (2001). Use of audio computer-assisted self-interviews to assess tuberculosis-related risk behaviors. American Journal of Respiratory and Critical Care Medicine, 164, 82–85. 10.1164/ajrccm.164.1.2101091

Rutter, M. (2006). Implications of resilience concepts for scientific understanding. Annals of the New York Academy of Sciences, 1094, 1–12.

Schonfeld, A. M., Mattson, S. N., & Riley, E. P. (2005). Moral maturity and delinquency after prenatal alcohol exposure. Journal of Studies on Alcohol, 66, 545–554.

Shahinfar, A., Fox, N. A., & Leavitt, L. A. (2000). Preschool children’s exposure to violence: Relation of behavior problems to parent and child reports. American Journal of Orthopsychiatry, 70, 115–125. 10.1037/h0087690

Skinner, M. L., Haggerty, K. P., Fleming, C. B., & Catalano, R. F. (2009). Predicting functional resilience among young-adult children of opiate-dependent parents. Journal of Adolescent Health, 44, 283–290. 10.1016/j.jadohealth.2008.07.020

Stanton, B., Li, X., Pack, R., Cottrell, L., Harris, C., & Burns, J. M. (2002). Longitudinal influence of perceptions of peer and parental factors on African American adolescent risk involvement. Journal of Urban Health, 79, 536–548. 10.1093/jurban/79.4.536

Steinberg, L., Lamborn, S. D., Darling, N., Mounts, N. S., & Dornbusch, S. M. (1994). Over-time changes in adjustment and competence among adolescents from authoritative, authoritarian, indulgent, and neglectful families. Child Development, 65, 754–770. 10.2307/1131416

Stene-Larsen, K., Borge, A. I., & Vollrath, M. E. (2009). Maternal smoking in pregnancy and externalizing behavior in 18-month-old children: Results from a population-based prospective study. Journal of the American Academy of Child & Adolescent Psychiatry, 48, 283–289. 10.1097/CHI.0b013e318195bcfb

Tiet, Q. Q., Huizinga, D., & Byrnes, H. F. (2010). Predictors of resilience among inner city youth. Journal of Child and Family Studies, 19, 360–378.

Tronick, E. Z., Frank, D. A., Cabral, H., Mirochnick, M., & Zuckerman, B. (1996). Late dose–response effects of prenatal cocaine exposure on newborn neurobehavioral performance. Pediatrics, 98, 76–83.

Tusaie, K., Puskar, K., & Sereika, S. M. (2007). A predictive and moderating model of psychosocial resilience in adolescents. Journal of Nursing Scholarship, 39, 54–60.

Udry, J. R. (2003). The National Longitudinal Study of Adolescent Health (Add Health), Waves I, II, and III, 1994–1996, 2000–2002 [Data set]. Retrieved from http://www.cpc.unc.edu/projects/addhealth

Underbjerg, M., Kesmodel, U. S., Landrø, N. I., Bakketeig, L., Grove, J., Wimberley, T., . . .Mortensen, E. L. (2012). The effects of low to moderate alcohol consumption and binge drinking in early pregnancy on selective and sustained attention in 5-year-old children. BJOG, 119, 1211–1221. 10.1111/j.1471-0528.2012.03396.x

U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, & National Center for Health Statistics. (2003). National Survey of Children’s Health, 2003 (ICPSR04691-v1). http://doi.org.ezproxy.snhu.edu/10.3886/ICPSR04691.v1

Valanis, B., Lichtenstein, E., Mullooly, J. P., Labuhn, K., Brody, K., Severson, H. H., & Stevens, N. (2001). Maternal smoking cessation and relapse prevention during health care visits. American Journal of Preventive Medicine, 20, 1–8. 10.1016/S0749-3797(00)00266-X

Weitzman, M., Gortmaker, S., & Sobol, A. (1992). Maternal smoking and behavior problems of children. Pediatrics, 90, 342–349.

Wilbur, M. B., Marani, J. E., Appugliese, D., Woods, R., Siegel, J. A., Cabral, H. J., & Frank, D. A. (2007). Socioemotional effects of fathers’ incarceration on low-income, urban, school-aged children. Pediatrics, 120, e678–e685. 10.1542/peds.2006-2166

Submitted: August 15, 2014 Revised: March 6, 2015 Accepted: March 9, 2015

This publication is protected by US and international copyright laws and its content may not be copied without the copyright holders express written permission except for the print or download capabilities of the retrieval software used for access. This content is intended solely for the use of the individual user. Source: Psychology of Addictive Behaviors. Vol. 29. (2), Jun, 2015 pp. 329-337) Accession Number: 2015-26085-002 Digital Object Identifier: 10.1037/adb0000082

Hide Left Column

Document Viewing Options:

• Detailed Record
• HTML Full Text
• This PDF document opens in a frame, to view the document outside of a frame, please change your Adobe Reader settings. To do this, open Adobe Reader, go to Help Menu and select Accessibility Setup Assistant option then select Use Recommend Settings and Skip Setup. You only need to do this once with the current computer you are using. PDF Full Text (128KB)

Cited References

• Cited References (2)

Hide Right Column

Tools

• Google Drive
• Print
• E-mail
• Save
• Cite
• Export
• Permalink
• Share
• Listen
• Translate