Evidence of a Gene × Environment Interaction Between Birth Weight and Genetic Risk in the Prediction of Criminogenic Outcomes Among Adolescent Males

Abstract

A number of studies have revealed that low birth weight children have a heightened risk of various maladaptive outcomes, including academic challenges and delinquent involvement. However, very little research to date has examined whether the relationship between low birth weight, poor academic performance, and delinquent peer affiliation is moderated by genetic risk. Using data from the National Longitudinal study of Adolescent Health, the present study examines whether male adolescents born at very low birth weights are significantly predisposed to poor academic performance and delinquent peer affiliation. Moreover, we test whether the effect of birth weight on these outcomes is conditioned by level of genetic risk. We find no evidence that very low birth weight males are more likely to affiliate with delinquent peers or perform poorly in school during adolescence. However, upon examining gene–environment interactions, we find that being born at a very low birth weight does significantly increase the odds of poor academic performance and delinquent peer affiliation among males who possess a higher level of genetic risk. Limitations are noted and the implications of the findings are discussed.

Keywords

birth weight delinquent peer affiliation poor academic performance genetic risk moderating effects gender

Each year, approximately 8.3% of infants born in the United States are low birth weight (<2,500 g; Hamilton, Martin, & Ventura, 2007). In the past few decades, a number of perinatal and neonatal interventions (e.g., antenatal steroids) have been developed to improve the survival rate of infants born with dangerously low birth weights (Saigal & Doyle, 2008; Schwartz, Luby, Scanlon, & Kellogg, 1994). As a result, a greater number of very low birth weight infants are surviving past infancy (Horbar et al., 2002). Researchers and health care professionals alike have raised concerns over how the recent improvement in the survival rate of very low birth weight infants might lead to a greater prevalence and/or severity of developmental challenges as these children age (Hack, Friedman, & Fanaroff, 1996; Lorenz, Wooliever, Jetton, & Paneth, 1998). Several studies have validated such concerns, showing that the increased survival rate of some of the lowest birth weight infants has been accompanied by a spike in the absolute number of children with various health and developmental challenges (Lorenz et al., 1998; Taylor, Minich, Klein, & Hack, 2004).

Some of the health problems that individuals born low birth weight are prone to (particularly those weighing <1,000 g) include anxiety and other psychiatric symptoms (Indredavik, Vik, Heyerdahl, Kulseng, & Brubakk, 2005), chronic lung disease (Marshall et al., 1999), and severe intracranial hemorrhage (Lemons et al., 2001). Nevertheless, the incidence of severe disability (e.g., deafness, mental retardation, cerebral palsy) among low birth weight infants appears to be quite low. A related line of research, however, has demonstrated that low birth weight survivors may face more subtle developmental challenges that may be undetectable at birth (for a meta-analysis, see Aarnoudse-Moens, Weisglas-Kuperus, van Goudoever, & Oosterlaan, 2009). Specifically, studies suggest that low birth weight infants are more likely to incur a number of challenges across neuropsychological, social, and behavioral dimensions of development. Research has shown, for example, that children with the lowest birth weights are particularly predisposed to school failure due to impaired executive functioning, even when they possess average levels of intelligence (Anderson & Doyle, 2004; Saigal, Hoult, Streiner, Stoskopf, & Rosenbaum, 2000). In addition to impaired executive functions, children born with abnormally low birth weights appear to be at an increased risk of behavioral problems, including aggressive and externalizing behavior (Vaske, Newsome, & Boisvert, 2013) and early-onset delinquency (Gibson, Piquero, & Tibbetts, 2001; Tibbetts & Piquero, 1999).

Much of the work on birth weight has been limited to outcomes measured during infancy and childhood, with relatively few studies exploring the longevity of effects into later life stages (for exceptions, see Dahl et al., 2006; Gibson et al., 2001; Tibbetts & Piquero, 1999). Perhaps more importantly, the literature has generally failed to examine the role of gene–environment interplay in the development of low birth weight infants. To be precise, only a handful of studies have examined whether the developmental delays that are associated with being born low birth weight are conditioned by indicators of genetic risk (for exceptions, see Keltikangas-Järvinen et al., 2007; Tharpar et al., 2005). In an effort to address these voids in the literature, the goal of the present study is twofold. First, we seek to explore whether very low birth weight males are at an increased risk of two criminogenic outcomes during adolescence: poor academic performance and delinquent peer affiliation. Second, we aim to test whether the relationship between birth weight, poor academic performance, and delinquent peer affiliation among males is moderated by genetic risk.

The Link Between Low Birth Weight, Poor Academic Performance, and Delinquent Peer Affiliation

Research linking low birth weight to academic challenges is extensive (Botting, Powls, Cooke, & Marlow, 1998; Dahl et al., 2006; Hack et al., 2002). Studies comprising this body of research converge to reveal that low birth weight children tend to perform significantly worse in core school subjects relative to their normal birth weight counterparts (Botting et al., 1998; Weindrich, Laucht, & Schmidt, 2003). To illustrate, Weindrich and colleagues (2003) examined a sample of 215 11-year-old German children with no sign of severe neurological disability and found that both low birth weight and very low birth weight children performed less well on measures of vocabulary and arithmetic relative to normal birth weight children. Research by Botting et al. (1998) found that significantly more children weighing less than 1,500 g at birth (3.3 lb) were failing in one or more subjects relative to controls. No evidence of academic “catch up” among low birth weight children was detected between the ages of 6 and 12 years, suggesting that the scholastic difficulties of low birth weight children may extend into early adolescence (Botting et al., 1998).

Although studies exploring the academic competency of low birth weight individuals during late adolescence and early adulthood are less common, the research conducted thus far is inconsistent in its findings (Breslau, Paneth, & Lucia, 2004; Dahl et al., 2006; Samuelsson et al., 2006). For example, a study by Dahl and colleagues (2006) revealed that both males and females who were born very low birth weight exhibited less school competence between the ages of 13 and 18 years. Similar research suggests little evidence of improvement in academic achievement between childhood and late adolescence (see Breslau et al., 2004). Nevertheless, some studies do provide evidence of academic “catch-up” by late childhood/early adolescence (Samuelsson et al., 2006; Taylor et al., 2004), whereas others detect significant differences between low birth weight and normal birth weight individuals in academic achievement through early adulthood (Hack, 2006; Hack et al., 2002). In light of these mixed findings, it is not entirely clear whether the risk of childhood academic disadvantage incurred by low birth weight individuals persists into adolescence and adulthood.

An important correlate of poor academic performance is delinquent peers associations (Chang & Le, 2005; Dishion, Patterson, Stoolmiller, & Skinner, 1991). Findings from research have suggested that the failure to adequately perform in school might compel an adolescent to seek out and engage in delinquent behaviors with other academically challenged youth (Dishion et al., 1991). Conversely, association with delinquent peers might diminish one’s interest in and dedication to school work, and thereby impair scholastic success (Chang & Le, 2005). Research has also highlighted how various dimensions of social adjustment during childhood and adolescence can be influenced by social information processing (e.g., hostile attribution bias; Crick & Dodge, 1994). Whereas skillful processing leads to social competence, deficiencies in processing increase the likelihood of an aggressive temperament and, consequently, poor social and academic adjustment (Dodge & Crick, 1990). Thus, adolescents with deficits in social information processing are likely at an increased risk of both delinquent peer affiliation and poor academic performance.

As birth weight seems to be an important predictor of scholastic achievement, it is therefore possible that it might also influence the likelihood of delinquent peer affiliation. Although no research to date has specifically examined the effect of birth weight on the likelihood of involvement with delinquent peers during adolescence, a related line of research suggests that low birth weight individuals possess a higher risk of outcomes closely associated with delinquent peer affiliation, including an earlier onset of delinquent involvement (Gibson et al., 2001; Tibbetts & Piquero, 1999), conduct problems (Indredavik et al., 2005), and an aggressive personality (Vaske et al., 2013). In light of the findings linking birth weight to various criminogenic outcomes, we explore the possibility that birth weight may have important implications for both academic performance and delinquent peer involvement during adolescence.

Genetic Risk, Involvement With Delinquent Peers, and Poor Academic Performance

In addition to the body of research linking low birth weight to maladaptive academic and behavioral outcomes, another body of research has revealed that genetic factors significantly impact these outcomes as well (Beaver et al., 2009; Beaver, Wright, & DeLisi, 2008; Johnson, McGue, & Iacono, 2005). For instance, Beaver and colleagues (2009) examined a sample of twins and found that as much as 62% of the variation in delinquent peer affiliation among adolescents can be accounted for by genetic factors. Additional research has shown that DAT1, a dopamine transporter polymorphism, is associated with greater delinquent peer affiliation among males (see Beaver et al., 2008). Other genes, including monoamine oxidase A (MAOA), have also been linked to various antisocial phenotypes (Caspi et al., 2002; Kim-Cohen et al., 2006), including an increased likelihood of weapon use and gang affiliation (Beaver, DeLisi, Vaughn, & Barnes, 2010). To be precise, research suggests that adolescent males possessing a low activity MAOA allele (i.e., the 2-repeat or 3-repeat allele) are significantly more likely to join a gang and use a weapon in a fight than their high-activity MAOA counterparts (Beaver, DeLisi, et al., 2010). Both behavioral and molecular genetic studies, therefore, highlight the role of genetic factors in involvement with delinquent peers.

Research has also indicated that a substantial proportion of the variation in academic performance is the result of genetic factors (Haworth, Dale, & Plomin, 2008) and that such effects are especially pronounced for subjects with economically disadvantaged backgrounds (Tucker-Drob & Harden, 2012). For example, a study by Haworth and colleagues (2008) revealed that genetic factors accounted for more than 60% of the variance in scientific achievement of school-aged children. Molecular genetic research has also linked risk alleles on several genetic polymorphisms to poor academic achievement (Beaver, Vaughn, Wright, DeLisi, & Howard, 2010; Beaver, Wright, DeLisi, & Vaughn, 2012). One study, for instance, found a significant association between genetic risk on three dopaminergic genes (DRD2, DRD4, and DAT1) and academic achievement during middle and high school (Beaver, Vaughn, et al., 2010). Another body of research has linked specific genetic markers, such as MAOA, to factors that often underpin academic difficulties, such as poor executive functioning (Kim-Cohen et al., 2006; Liu et al., 2011), deficits in self-regulation (Kim-Cohen et al., 2006), and attentional problems (Liu et al., 2011). Consequently, possession of one or more risk alleles may play a direct, indirect, or interactive role in impeding the scholastic achievement of adolescents.

Could the Effects of Low Birth Weight on Poor Academic Performance and Delinquent Affiliation Be Conditional?

As demonstrated above, research has indicated that both low birth weight and indicators of genetic risk appear to increase the likelihood of delinquent affiliation, poor academic performance, and other associated outcomes. What has been neglected in the literature, however, is whether birth weight and genetic risk interact to predict poor academic performance and delinquent peer affiliation. In light of prior findings, it is reasonable to expect that the effects of low birth weight and genetic factors on these outcomes may indeed be conditioned by other factors (Beeghly et al., 2006; Greenley, Taylor, Drotar, & Minich, 2007; Keltikangas-Järvinen et al., 2007; Laucht, Esser, & Schmidt, 2001). For instance, research has found the effects of low birth weight on maladaptive traits and behaviors to be especially potent among individuals exposed to other environmental risks, such as cocaine in the womb (Beeghly et al., 2006), family dysfunction (Greenley et al., 2007), and low maternal responsivity (Laucht et al., 2001).

Very few studies to date, however, have examined whether allelic variation on relevant polymorphisms might condition the relationship between birth weight, academic achievement, and antisocial outcomes (for a notable exception, see Keltikangas-Järvinen et al., 2007). Additional exploration of the conditioning role of genetic factors is therefore warranted, especially because genes such as DRD2, DRD4, and MAOA have been independently linked to adjustment problems for adolescent males (see Beaver, DeLisi, et al., 2010; Beaver et al., 2008). Moreover, a wealth of research has shown that the effects of genetic factors are most pronounced in the presence of other environmental insults (e.g., abuse), including occurrences at the earliest stages of the life course (Beaver, 2008; Caspi et al., 2002). It stands to reason, therefore, that an abnormally low birth weight may be especially likely to heighten the risk of maladjustment for subjects who already possess a high level of genetic risk. We proceed, therefore, with an empirical exploration of a potential gene–environment interaction between birth weight and a high-risk genotype in predicting poor academic performance and delinquent peer affiliation during adolescence.

Method

Sample

Data for this study are derived from the National Longitudinal Study of Adolescent Health (Add Health), a prospective, nationally representative study of more than 90,000 American adolescents (Harris et al., 2003; Udry, 1998). The study consists of 4 waves of data that span 14 to 15 years of development across adolescence and adulthood. Importantly, the Add Health included a large number of siblings in the study. At Wave 1, respondents were asked if they had a sibling, half sibling, unrelated sibling, co-twin, or cousin between the ages of 11 and 20 years. If the respondent answered yes, then their sibling was asked to participate in the study. In addition, a probability sample of full siblings was selected for inclusion in the sibling sample (Jacobson & Rowe, 1999). Approximately 5,500 siblings were ultimately included in the Add Health study at Wave 1, and a subsample of these siblings (approximately 2,500) were also asked to submit samples of the DNA for genotyping at Wave 3. Paternal and maternal alleles on a number of candidate genes (e.g., DRD2, DRD4) were identified for each subject through buccal swabbing (Cohen et al., n.d.).

In the current study, we follow the lead of prior research (Beaver, Wright, DeLisi, Walsh, et al., 2007; Haberstick et al., 2005) and only use the genetically informative data that were available for males. As previous studies have indicated, measures of antisocial behavior for females (including delinquent peer affiliation) appear to be unrelated to a number of genetic markers that are included in our measure of genetic risk (i.e., DRD2, DRD4, MAOA; see Beaver, Sak, Vaske, & Nilsson, 2010; Beaver et al., 2008). In addition, research has indicated that birth weight may be especially relevant to the offending behavior of males (see Tibbetts & Piquero, 1999). As a result, females were excluded from our analytical sample.¹ Using these selection criteria (i.e., genotyped, male), we were left with a final analytical sample of approximately 1,300 males.

Measures

Outcome Measures

Poor academic performance

A number of studies have detected significant associations between low birth weight and poor academic performance (Breslau, Johnson, & Lucia, 2001; Grunau, Whitfield, & Fay, 2004; Hack et al., 2002) as well as poor academic performance and adolescent delinquency (Maguin & Loeber, 1996). In the current study, we assessed the degree of each youth’s academic success using items commonly employed in the literature (Crosnoe & Muller, 2004). During the in-home interviews at Wave 1, adolescents were asked about their grades during the most recent grading period in the spring. Youths were specifically asked to provide their most recent grade in English, mathematics, history/social studies, and science. Response items ranged from 1 (A) to 4 (D or lower). Items were coded so that higher scores were indicative of lower grades. Ultimately, scores on the four items were standardized and summed to create an index of poor academic performance (α = .73). Table 1 includes the descriptive statistics of the poor academic performance measure as well as all other variables and scales included in the analysis.

Table 1.

Descriptive Statistics for the Add Health Genotyped Subsample of Males.

Variable	M	SD	Range
Poor academic performance	0.00	0.78	−1.32-1.77
Delinquent peer affiliation	0.00	0.81	−0.84-2.37
Very low birth weight	0.05	0.21	0-1
Genetic risk	3.78	1.34	0-9
Race (non-White = 1)	0.34	0.47	0-1
Age Wave 1	16.11	1.68	12.12-20.86
Low SES	0.22	0.41	0-1
Low self-control	00	0.65	−1.50-2.92
Neighborhood disadvantage	0.00	0.61	−0.73-2.34
Low maternal attachment	0.00	0.87	−0.41-7.37
Maternal disengagement	0.00	0.74	−0.95-3.97
Low maternal involvement	0.03	0.17	0-1

Note. Add Health = National Longitudinal Study of Adolescent Health; SES = socioeconomic status.

Delinquent peer affiliation

In addition to our measure of poor academic performance, we also employed a measure of delinquent peer affiliation as a dependent variable in the current study. Following the lead of prior research (Beaver et al., 2009; Beaver et al., 2008), we created a delinquent peer affiliation measure using three items that were available at Wave 1. Respondents were asked to report how many of their closest friends smoke cigarettes at least once a day, drink alcohol at least once a month, and smoke marijuana at least once a month. Responses ranged from 0 (no friends) to 3 (3 or more friends). The three items were subsequently standardized and summed to create the Wave 1 delinquent peer affiliation scale (α = .74).

Early Childhood and Genetic Measures

Very low birth weight

Studies examining the relationship between birth weight and various developmental outcomes often use different criteria to classify the at-risk group (see Anderson & Doyle, 2004; Botting et al., 1998; Breslau et al., 2001; Dahl et al., 2006). To be precise, researchers may examine cognitive and/or behavioral outcomes for individuals who are low birth weight (Breslau et al., 2001; Tibbetts & Piquero, 1999), very low birth weight (Botting et al., 1998; Dahl et al., 2006; Hack et al., 2002), or extremely low birth weight (Anderson & Doyle, 2004; Grunau et al., 2004). The general pattern in the literature is that the more extreme the weight deficit at birth, the more adverse the subsequent health, cognitive, and behavioral outcomes of the child (see Breslau et al., 2001; Hack et al., 1994; Taylor, Hack, & Klein, 1998). Research also suggests that, when comparing low birth weight subjects by severity, relatively higher birth weights are more likely to make significant age-related progress by adolescence and even “catch up” on some measures (see Taylor et al., 2004). In the current study, we employed a measure of very low birth weight to ensure that we do not overlook the role of birth weight in adolescent functioning by only examining subjects whose risk may be less persistent and/or severe (see Hack et al., 1994).

At the first wave of data collection, caregivers (usually the mother) were asked about their child’s weight at the time of birth. Although caregivers typically provided their child’s birth weight in units of pounds and ounces (e.g., 8 lbs., 3 oz.), mothers who reported that their child weighed less than 4 lbs. at birth were not permitted to do so. Due to this limitation in the data, we were obliged to classify individuals as very low birth weight (1) or other birth weight (0) based on whether their caregiver reported their weight to be less than 4 lbs. (or roughly 1,800 g) at birth. We should note that researchers do not consistently categorize subjects by birth weight across studies, despite common cutoff points (e.g., 1,500 g). Extremely low birth weight classification can range from 750 to 1,000 g (Anderson & Doyle, 2004; Grunau et al., 2004; Hack et al., 1994), whereas low birth weight has been determined using the criteria of 5.5 lbs. (Breslau et al., 1994; Vaske et al., 2013) as well as 6 lbs. (Gibson et al., 2001; Tibbetts & Piquero, 1999). Regardless of measurement, concordant findings tend to emerge for studies that use similar, though not identical, criteria to create their measures (see Anderson & Doyle, 2004; Grunau et al., 2004). Thus, there is little reason to believe that a slight difference in our classification of very low birth weight subjects would substantially alter the results of our study.²

Genetic risk

As scholastic achievement and delinquent peer affiliation have been found to be influenced by a number of genes (Beaver et al., 2008; Beaver et al., 2012), we opted to include a measure of genetic risk in the present study. At Wave 3, roughly 1,300 male subjects were genotyped for polymorphisms found in the following five genes: the monoamine oxidase A gene (MAOA), the serotonin transporter gene (5HTT), the dopamine D4 receptor gene (DRD4), the dopamine D2 receptor gene (DRD2), and the dopamine transporter gene (DAT1). Notably, these polymorphisms have been associated with various maladaptive traits and behaviors during adolescence, including delinquent involvement (Beaver, Sak, et al., 2010) and academic achievement (Beaver, Vaughn, et al., 2010; Beaver et al., 2012). The genotyping protocol concerning the primer sequences and the amplification process has been thoroughly described in previous publications (Cohen et al., n.d.).

To create our measure, we first identified the number of risk alleles possessed by each subject on the five examined polymorphisms. To summarize, a 30 base pair variable number tandem repeat (VNTR) in the promoter region of MAOA was genotyped. Because MAOA is an X-lined gene, male subjects only possessed one MAOA allele. Subjects who possessed a 2-repeat or 3-repeat allele were designated as “low activity” and were assigned a value of 1, whereas subjects who possessed higher repeat alleles were coded as a 0 (see Haberstick et al., 2005).

Participants were also genotyped for the 44 base pair VNTR in 5HTTLPR. Short alleles (484 base pairs) were assigned a value of 1 and long alleles (528 base pairs) were assigned a value of 0. Because each participant possesses 2 alleles for this polymorphism, scores range from 0 (no risk alleles) to 2 (2 risk alleles).

The 48 base pair VNTR in the DRD4 gene may be repeated between 2 and 11 times. Prior research has grouped alleles exhibiting between 2 and 6 repeats together and has designated them as low risk. Conversely, the 7-, 8-, 9-, and 10-repeat alleles have been identified as the risk alleles. Therefore, subjects possessing 2 risk alleles in this polymorphism were assigned a value or 2, subjects possessing 1 risk allele were assigned a value or 1, and subjects possessing no risk alleles were assigned a value of 0.

In a similar fashion, the Taq1A polymorphism, located in the 3’ untranslated region of DRD2, was genotyped for two different alleles: the A1 allele and the A2 allele. As previous research has designated the A1 allele as the risk allele, subjects were assigned a value on this gene corresponding to the number of A1 alleles they possessed (ranging from 0 to 2).

Finally, the 40 base pair VNTR in the DAT1 polymorphism was genotyped. In line with prior research (Hopfer et al., 2005), participants who did not possess a 9- or 10-repeat allele were excluded from the analysis. The 10-repeat allele was designated as the risk allele and was therefore assigned a value or 1, whereas the 9-repeat allele was assigned a value of 0. Therefore, participants were assigned a value on this polymorphism based on the number of 10-repeat alleles they possessed (ranging from 0 to 2).

We followed the lead of prior research (Beaver, Sak, et al., 2010) and created a composite measure of genetic risk using the information obtained from the five different genetic polymorphisms described above. In particular, the composite measure of risk was ultimately formed by summing the number of risk alleles together across the five polymorphisms. The summation resulted in a genetic risk scale ranging from 0 to 9, with higher scores reflecting greater genetic risk toward maladaptive outcomes during adolescence.

Adolescent Traits

Low self-control

We also included a measure of low self-control in the current study. At Wave 1, adolescents were asked whether they go with their gut feeling when making a decision, think about the consequences of their decision, gather ample facts to solve a problem, try to think of alternative solutions to a problem, and analyze what went right or wrong after taking a particular course of action. These questions are noteworthy in that they adequately reflect Hirschi’s (2004) recent conceptualization of low self-control, which he describes as “the tendency to consider the full range of potential costs [and long-term implications] of a particular act” (p. 543). Furthermore, literature linking impulsivity to poor scholastic achievement often finds that self-regulated learning strategies, such as self-evaluation and future orientation, are predictive of academic performance (see Nota, Soresi, & Zimmerman, 2004). Additional research has revealed a close nexus between executive dysfunction, poor decision making, and low self-control (see Wikström & Treiber, 2007). Ultimately, we coded the responses to the five questions listed above so that individuals with lower levels of self-control received higher scores. An index was then created by standardizing and summing the recoded items (α = .66).

Neighborhood and Parent Socialization Measures

Neighborhood disadvantage

We also included various measures of the subjects’ neighborhood and family context during their youth. First, we created an index of neighborhood disadvantage using six items that asks the respondents if they feel their neighborhood is safe and desirable (for a similar measure, see Beaver, Wright, DeLisi, Daigle, et al., 2007). At Wave 1, youths were asked whether they felt safe in their neighborhood, whether they were happy in their neighborhood, whether they knew most of their neighbors, and whether they wanted to move. Items were recoded so that respondents who expressed greater dissatisfaction with the neighborhood scored higher on each item. Subsequently, items were standardized and added together to create an index of neighborhood disadvantage (α = .66).

Low maternal attachment

We also created an index of maternal attachment at Wave 1. Following the lead of prior research (Haynie & Piquero, 2006), we utilized two items in which adolescents were asked how close they felt to their mother and how much they thought their mother cared about them. Response options ranged from 1 (not very close/much) to 5 (very close/much). Responses were reverse coded, standardized, and summed to create our index of low maternal attachment (α = .67).

Maternal disengagement

We followed the lead of prior research (Beaver et al., 2009) and created an index designed to tap the extent to which the mother was withdrawn, cold, and removed from her child’s life. During the first wave of data collection, adolescents were asked to report on whether they were satisfied with their relationship with their mother and with the way she communicates with them, whether she calmly corrects their mistakes and misbehaviors, and whether their mother is warm or loving toward them. Response options ranged from 1 (strongly agree) to 5 (strongly disagree). Items were then standardized and added together to form an index in which higher scores reflect a greater degree of maternal disengagement (α = .79).

Low maternal involvement

Finally, we developed an item assessing low maternal involvement. At the first wave of data collection, adolescents were asked if they had engaged in a number of activities with their mother during the past 4 weeks, including shopping, going to a movie or special event, talking about a personal problem, playing a sport, attending church, and talking about school. Adolescents who did not report engaging in any of the activities with their mother during the 4 weeks prior to the interview were assigned a value of 1, whereas adolescents who reported engaging in at least one of these activities with their mother were assigned a value of 0. Importantly, prior research has also used these measures to tap the extent of maternal involvement (see Haynie & Piquero, 2006).

Control Variables

Age

In an effort to rule out the possibility that any significant findings are spurious due to the age of the respondent, we included a continuous variable in the analysis measuring the age of each respondent (in years) at Wave 1.

Sex

Similarly, we included a dichotomous measure of the respondents’ sex (1 = male; 0 = female) to help rule out the possibility of confounding.

Race

A measure of race (1 = non-White; 0 = White) was also included in the analysis, as birth weight, academic performance, and delinquent outcomes have all been found to vary by race (Noguera, 2003; Peeples & Loeber, 1994; Rawlings, Rawlings, & Read, 1995).

Low socioeconomic status (SES)

We followed the lead of prior research (Jackson, 2012) and created a measure of low SES using four items that asked caregiver respondents about the extent to which they received financial assistance at Wave 1. Specifically, respondents reported whether in the last month they had received food stamps, unemployment compensation, Aid to Families With Dependent Children, or public housing/housing subsidy. Subjects were assigned a value of 1 on the low SES item if their caregiver reported having received any assistance within the previous month. Otherwise, they were assigned a value of 0 on this variable.

Plan of Analysis

In the present study, we estimate a series of ordinary least squares (OLS) regression models to explore the link between very low birth weight status, genetic risk, poor academic performance, and delinquent peer affiliation.³ As the genotyped subsample included a number of sibling pairs, we estimated Huber/White standard errors to correct for the artificial deflation of standard errors due to the nonindependence of cases (Williams, 2000). We also implemented a correction for multiple testing and used Bonferroni-adjusted p values when determining the significance of our results (i.e., the critical p value was divided by the number of hypotheses tested). First, we examine whether male subjects who weighed less than 4 lbs. at birth (i.e., very low birth weight subjects) perform significantly worse in school during their adolescent years, net of individual, genetic, social, and demographic controls. We also explore whether very low birth weight subjects are significantly more likely to associate with delinquent peers during adolescence, net of controls. In addition to examining the direct effects of very low birth weight on poor academic performance and delinquent peer affiliation, we estimate two regression equations exploring the interactive effects of very low birth weight and genetic risk in the prediction of these outcomes. In particular, we test whether the statistical interaction between very low birth weight and genetic risk is significantly predictive of poor academic performance and delinquent peer affiliation among adolescent males. Multiplicative interaction terms were created to examine the moderating effects of genetic risk. To reduce collinearity, covariates in the analysis were mean centered prior to creating the interaction term (Jaccard, Wan, & Turrisi, 1990).

Results

Table 2 contains the results from all four regression equations estimated in the present study. Models 1 and 3 examine the direct effects of very low birth weight on poor academic performance and delinquent peer affiliation, whereas Models 2 and 4 examine the interactive effects of very low birth weight and genetic risk on these outcomes. The analysis begins with our first model, which estimates the effects of very low birth weight on poor academic performance. The results of Model 1 reveal that very low birth weight status did not significantly influence the likelihood of poor academic performance among male adolescents, controlling for various individual, social, and demographic variables. Similarly, Model 1 indicates that our measure of genetic risk was not significantly predictive of poor academic performance. Subjects with a greater number of risk alleles, therefore, were not significantly more likely than subjects with fewer risk alleles to be scholastically challenged during their adolescent years.

Table 2.

The Direct and Interactive Effects of Very Low Birth Weight and Genetic Risk on Poor Academic Performance and Delinquent Peer Affiliation Among Males.

	Poor academic performance		Delinquent peer affiliation
	Model 1	Model 2	Model 3	Model 4
	b/β	b/β	b/β	b/β
Very low birth weight	−.01 −.01	−.01 −.02	.01 .01	.00 .00
	(.03)	(.03)	(.02)	(.02)
Genetic risk	(.03) (.03)	(.03) (.03)	−.01 −.01	−.01 −.01
Genetic risk	(.02)	(.02)	(.02)	(.02)
Very low birth weight × Genetic risk	NA	.07* .09	NA	.07* .09
Very low birth weight × Genetic risk		(.02)		(.02)
Age	.06* .12	.05* .11	.14* .27	.13* .27
Age	(.01)	(.01)	(.02)	(.02)
Race (non-White)	.13* .09	.13* .08	−.08 −.05	−.09 −.05
Race (non-White)	(.05)	(.05)	(.05)	(.05)
Low SES	.37* .20	.36* .19	.14* .07	.13* .07
Low SES	(.07)	(.06)	(.06)	(.06)
Low self-control	.17* .15	.17* .15	.12* .10	.12* .10
Low self-control	(.04)	(.04)	(.04)	(.04)
Neighborhood disadvantage	.01 .01	.01 .01	−.04 −.03	−.04 −.03
Neighborhood disadvantage	(.04)	(.04)	(.04)	(.04)
Low maternal attachment	.07* .08	.06* .07	.07* .07	.06 .06
Low maternal attachment	(.03)	(.03)	(.03)	(.03)
Maternal disengagement	.00 .00	.00 .00	.14* .12	.14* .12
Maternal disengagement	(.04)	(.04)	(.04)	(.04)
Low maternal involvement	.27 .06	.27 .06	−.09 −.02	−.08 −.02
Low maternal involvement	(.14)	(.14)	(.15)	(.14)
Intercept	−1.01	−2.17	−.97	2.12
Intercept	(.23)	(.24)	(.23)	(.24)
n	1,022	1,022	1,041	1,041
R ²	.10	.11	.13	.14

Note. SES = socioeconomic status.

The values in parentheses are the standard errors.

p ≤ .05 (two-tailed).

Model 3 of Table 2 examines the direct effect of very low birth weight on delinquent peer affiliation among males. Net of indicators of genetic, individual, and social risk, very low birth weight was not significantly associated with greater delinquent peer affiliation among adolescent males. Our measure of genetic risk was also unrelated to delinquent peer affiliation among males during their adolescent years. The results of Models 1 and 3 therefore reveal null direct relationships between both very low birth weight status and genetic risk and our outcomes of interest (i.e., poor academic performance and delinquent peer affiliation).

Next, we explore whether very low birth weight is differentially predictive of poor academic performance and delinquent peer affiliation for males at distinct levels of genetic risk. In other words, we test whether the impact of birth weight on academic performance and delinquent associations is significantly moderated by genetic risk. Models 2 and 4 provide evidence for significant, positive biosocial interactions between very low birth weight and genetic risk. Model 2 specifically demonstrates that the influence of very low birth weight on poor academic performance is significantly more potent as an individual’s level of genetic risk increases. The significant interaction detected in Model 2 is depicted in Figure 1. Importantly, although Model 2 estimates are based on standardized measures of low birth weight and genetic risk, Figure 1 was created by splitting the sample by birth weight status and then plotting the predicted standardized score on poor academic performance by the unstandardized level of genetic risk, adjusting for model covariates. Figure 1 indicates that very low birth weight males who possess the highest level of genetic risk score approximately .80 standard deviations higher on our measure of poor academic performance than very low birth weight males who possess the lowest level of genetic risk. Conversely, academic performance hovers around the average for individuals with other birth weights, regardless of their level of genetic risk. Very low birth weight and genetic risk, therefore, become relevant to academic performance when examined in conjunction, despite both being nonsignificant when examined in isolation.

Figure 1.

Differential effects of genetic risk on poor academic performance among males by birth weight.

When testing the interactive model predicting delinquent peer affiliation, we garnered similar results. Model 4 indicates that the effect of very low birth weight on delinquent peer affiliation is significantly heightened as an individual’s level of genetic risk increases. This significant interaction is depicted in Figure 2. Similar to Figure 1, Figure 2 was created by splitting the sample by birth weight status and then plotting the predicted standardized score on delinquent peer affiliation by the unstandardized level of genetic risk, adjusting for model covariates. As displayed in Figure 2, the difference in delinquent peer affiliation among very low birth weight males who are at high and low levels of genetic risk is sizeable. To be precise, very low birth weight males at the highest level of genetic risk score more than 3 standard deviations higher on our indicator of delinquent peer affiliation than very low birth weight males who exhibit no genetic risk. In contrast, individuals of other birth weights show average levels of delinquent affiliation, regardless of their level of genetic risk.⁴

Figure 2.

Differential effects of genetic risk on delinquent peer affiliation among males by birth weight.

Discussion

A long line of research has revealed that low birth weight is significantly associated with a number of negative health outcomes in children (Indredavik et al., 2005; Lemons et al., 2001; Marshall et al., 1999). Additional research has linked lower birth weights to a variety of maladaptive traits and behaviors, including poor executive functioning (Anderson & Doyle, 2004), aggressive temperament (Vaske et al., 2013), and early-onset offending (Gibson et al., 2001; Tibbetts & Piquero, 1999). Notwithstanding these bodies of research, few studies have examined the effect of birth weight on these outcomes during adolescence and/or adulthood (except see Dahl et al., 2006; Tibbetts & Piquero, 1999) and even fewer have explored whether the influence of low birth weight on negative health and behavioral outcomes is moderated by genetic factors (except see Keltikangas-Järvinen et al., 2007). The present study sought to address these voids in the literature by exploring whether very low birth weight status is predictive of poor academic performance and delinquent peer affiliation among adolescent males. We also tested the possible moderating role of genetic risk in the relationship between very low birth weight and these criminogenic outcomes. The results of our statistical models revealed three important findings.

First, the results indicated that subjects with very low birth weights were not significantly more likely to exhibit poorer academic performance or greater delinquent peer affiliation. The results for our measure of genetic risk were also nonsignificant. The null findings are somewhat surprising, as a number of studies have found birth weight to influence academic achievement (Botting et al., 1998; Breslau et al., 2001; Dahl et al., 2006) and genetic factors to influence both academic achievement and delinquent peer affiliation (Beaver et al., 2009; Johnson et al., 2005). Nevertheless, research has repeatedly indicated that early environmental insults may be more or less influential on later life outcomes depending on one’s level of genetic risk on one or more candidate genes (for a seminal study, see Caspi et al., 2002). The lack of significant direct effects, therefore, may speak to the need for greater attention to the role of gene–environment interplay in the prediction of poor academic performance and delinquent peer affiliation. Our subsequent findings confirm this hypothesis.

Second, on examining the interactive models, we found that very low birth weight emerged as a significant predictor of poor academic performance under conditions of higher genetic risk. In particular, although genetic risk and very low birth weight did not significantly influence academic performance independently, very low birth weight males who exhibited relatively high levels of genetic risk were especially likely to perform poorly in school during their adolescent years (see Figure 2). Finally, we found that a gene–environment interaction between birth weight and genetic risk significantly predicted delinquent peer affiliation. Whereas adolescent males who were not born very low birth weight exhibited average levels of delinquent peer affiliation regardless of genetic risk, those who were born very low birth weight exhibited significant increases in delinquent peer affiliation as their level of genetic risk increased.

The findings of the present study suggest a pattern consistent with the diathesis-stress model. The diathesis-stress model argues that an individual’s vulnerability to environmental risk factors is contingent on his or her level of genetic risk. To be precise, the model suggests that subjects with high-risk genotypes are especially likely to respond negatively to environmental adversity. When both genetic and environmental risk factors are present, therefore, the hypothesized result is an increased likelihood of antisocial traits and behaviors.

Our study also builds on the work of Keltikangas-Järvinen and colleagues (2007), which indicated that being born low birth weight resulted in particularly low educational attainment for men with one or more A1 alleles on the Taq1 polymorphism of DRD2. Still, our findings indicate that gene–environment interactions between birth weight and genetic risk may be relevant not only to poor academic outcomes but also to another important correlate of crime: delinquent peer affiliation. The results of the current study also highlight the utility of employing more comprehensive indicators of genetic risk that take into account the risk on a number of genes (see also Beaver, Sak, et al., 2010). Although examining single genetic markers as moderators is useful, potentially important gene–environment interactions may go undetected when genetic risk is measured using a single gene.

Despite the important contribution of the current study to the literature, we would be remiss if we did not point out the limitations of the study. First, as mentioned previously, we were unable to use the conventional cutoff for very low birth weight due to limitations in the data. Nevertheless, other work examining the negative effects of lower birth weights has converged to reveal similar results, despite using slightly different classifications (see Anderson & Doyle, 2004; Hack et al., 1994). Second, because our genotyped sample of males included siblings, we cannot guarantee that the results of the current study are generalizable to the nonsibling population. It is worthwhile to note, however, that recent research by Barnes and Boutwell (2013) suggests that research using sibling samples is likely more generalizable to the nonsibling population than previously thought, as twin siblings did not appear to systematically differ from singletons in terms of their development and behavior.

Third, although we did examine the role of birth weight and genetic risk in predicting two potentially important correlates of crime (i.e., poor academic performance and delinquent peer affiliation), we did not explore other potentially relevant correlates of crime, such as negative emotionality or indicators of family strain. A recent review suggests that gene–environment interplay may indeed play a role in the development and stability of negative temperament, which appears to be predictive of an array of behavioral problems over the life course (see Delisi & Vaughn, 2014). Future research would benefit from additional exploration of potential gene–environment interactions between genetic risk and birth weight in predicting these and other related outcomes. Finally, recent work by Keller (2014) suggests that researchers who study gene-environment interactions (GxEs) more adequately control for confounders by implementing a fully interacted model in which each component of the GxE is interacted with all covariates in the model. Although this approach may result in problems with overfitting and multicollinearity, future GxE studies should consider its utility.

In conclusion, being born very low birth weight appears to increase the probability of poor academic performance and delinquent peer affiliation during adolescence for males, but only for subjects with relatively high levels of genetic risk. Despite these conditional effects, neither very low birth weight nor genetic risk appears to heighten the risk of these outcomes independently. Future research should seek to uncover the role of gene–environment interplay between birth weight and genetic risk in predicting additional criminogenic outcomes during later life stages (e.g., adulthood). Moving forward, scholars should also expand their analyses to include additional candidate genes and to explore broader populations, including nonsiblings. Hopefully, additional research on the topic can lead to more effective prenatal interventions that take both genetic risk and prenatal risk into account.

Footnotes

Acknowledgements

Special acknowledgment is due to Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by Grant No. P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. No direct support was received from Grant P01-HD31921 for this analysis. Information on how to obtain the Add Health data files is available on the Add Health website ().

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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