Are Stressful Developmental Processes of Youths Leading to Health Problems Amplified by Genetic...

EMPIRICAL RESEARCH

Are Stressful Developmental Processes of Youths Leadingto Health Problems Amplified by Genetic Polymorphisms? TheCase of Body Mass Index

Kandauda (K.A.S.) Wickrama • Catherine Walker O’Neal •

Assaf Oshri

Received: 11 December 2013 / Accepted: 27 February 2014 / Published online: 8 March 2014

� Springer Science+Business Media New York 2014

Abstract Although previous research has documented

the adverse influence of early socioeconomic disadvantage

on youths’ physical health outcomes and the increase in

health inequalities over the early life course, little is known

about genetically informed sequential life course devel-

opmental processes leading to health outcomes. Consistent

with the life course-stress process perspective, we

hypothesized that early socioeconomic adversity initiates a

stress process over the early life course. This process

involves the disrupted transition from adolescence to

young adulthood, which increases the risk of health prob-

lems during young adulthood. Behavioral, psychosocial,

and genetic data were collected from 12,424 adolescents

(53 % female) over a period of 13 years participating in the

nationally representative National Longitudinal Study of

Adolescent Health (Add Health). Early cumulative socio-

economic adversity and the polygenic influence were

measured using composite indices. The study provided

evidence for stressful developmental processes of adoles-

cents, involving parental rejection, depressive symptoms,

and adolescents’ precocious transition. This longitudinal

process was initiated by early cumulative socioeconomic

adversity and eventuated with young adults’ increased

body mass index (BMI). Furthermore, the study provided

evidence for the influence of life context–gene interactions

(G 9 E) on adolescents’ precocious development and

young adult BMI (after controlling for the lagged measure)

amplifying the stress process over the early life course.

These findings emphasize the need for incorporating indi-

vidual genetic characteristics in a longitudinal context into

life course stress research. Furthermore, policies focused

on eradicating childhood/adolescent adversities are neces-

sary as well as youth programs and policies that promote

youth competencies that aid in their successful transition to

young adulthood.

Keywords Early life adversity � Genes � Obesity

Introduction

Early socioeconomic adversity during childhood and early

adolescence (hereafter, referred to as early adversity) is

linked to stressful developmental processes leading to

health problems in adulthood (O’Rand and Hamil-Luker

2005; Wickrama and O’Neal 2013). Some youths are

capable of avoiding the damaging influence of early

adversities, while others may experience detrimental

developmental processes involving a sequence of age-

graded stressful life experiences and negative outcomes

(Oshri et al. 2013; Wheaton and Gotlib 1997; Wickrama

et al. 2008). These prolonged stress effects are consistent

with the life course-stress process perspective (Pearlin et al.

2005). In the present study, we hypothesize that early

socioeconomic conditions and parental rejection/

K. Wickrama

Department of Human Development and Family Science, 103

Family Science Center I, University of Georgia, Athens, GA,

USA

e-mail: [email protected]

C. W. O’Neal (&)


Dawson Hall, University of Georgia, Athens, GA, USA


A. Oshri


Family Science Center I, University of Georgia, Athens, GA,

USA


123

J Youth Adolescence (2014) 43:1096–1109

DOI 10.1007/s10964-014-0109-8

negligence (hereafter, parental rejection) set a process in

motion that disrupts the successful transition of adolescents

to adulthood by accelerating the acquisition of adult roles

(i.e., precocious development), such as parenthood, mar-

riage or cohabitation, truncated education, and independent

living. These precocious transitional events create a

stressful life context, which increases adolescents’ risk of

declining physical health during the transition to adulthood

(Foster et al. 2008; Wickrama et al. 2008). However, less is

known empirically about the longitudinal processes that

lead to these unfavorable health risks as research taking a

‘‘long-view’’ to examine an extended period of the early

life course is less common.

Obesity and being overweight are major public health

problem in the United States (Finucane et al. 2011).

Approximately 30 % of adolescents and 69 % of adults in

the United States are overweight or obese (Centers for

Disease Control and Prevention 2012). Obesity has been

shown to be associated with both contemporaneous and

long-term physical health (e.g., heart disease, diabetes,

certain cancers, and orthopedic and endocrine problems)

and mental health problems (e.g., depression) (WHO

2002). Recent research has also linked obesity to other

dimensions of wellbeing, such as the quality of romantic

relationship, socioeconomic attainment, and social func-

tioning (Crosnoe 2007; Merten et al. 2008). Obesity,

especially when experienced early in the life course, is

strongly associated with negative consequences in adult-

hood (Ferraro and Kelley-Moore 2003).

We hypothesize that variations in multiple candidate

genes involved in regulating the serotonergic and dopa-

minergic neurotransmitter systems accelerate (or impede)

stressful developmental processes by influencing age-gra-

ded developmental outcomes directly (G) and interactively

with the life contexts (G 9 E; Belsky and Beaver 2011;

Wickrama et al. 2013a, b; Wickrama and O’Neal 2013).

Researchers suggest that the impact of context–gene

interplay on an individual’s behavior (i.e., phenotypes)

may not appear until later in life because environment

salience and susceptibility may increase from childhood to

young adulthood (Shanahan and Boardman 2009). Fur-

thermore, recent studies have shown that multiple genes

may cumulatively influence developmental outcomes of

youth (i.e., a polygenic effect) (Belsky and Beaver 2011;

Simons et al. 2012; Wickrama et al. 2013a, b; Wickrama

and O’Neal 2013). To our knowledge, no previous study

has examined cumulative genetic influences on develop-

mental processes over the early life course leading to adult

health outcomes.

The current study investigates body mass index (BMI)

as a marker of poor health in young adults. As depicted in

Fig. 1, the present study will examine if early adversities

are associated with developmental processes implicated in

young adults’ BMI. The present study will also examine if

these adverse processes are strengthened through additive

genetic influences on age-graded developmental outcomes

(G) and amplified (or impeded) by genetic polymorphisms

through interactions with age-graded social contexts

(G 9 E).

We expect that early cumulative socioeconomic adver-

sity will be associated with parents’ rejection of their

children (Path A). In turn, parental rejection will increase

the likelihood of adolescents’ depressive symptoms (Path

B), which has implications for their precocious acquisition

of adult roles (Path C). Consistent with the life course

perspective, we expect that adolescents experiencing a

precocious transition will encounter adverse health conse-

quences, in particular the development of higher levels of

BMI (obesity) in young adulthood, because it creates a

chronically stressful life context for emerging adults (Path

D). Paths A, B, C, and D will form a stressful develop-

mental pathway through adolescence, emerging adulthood,

and young adulthood indicating a ‘‘chain of risks’’ begin-

ning with early adversity and resulting in sequential neg-

ative developmental outcomes.

Stressful Developmental Processes

Research has shown that the health risk of cumulative

socioeconomic adversity is considerably stronger than the

independent effect of individual dimensions of socioeco-

nomic adversity (Bauman et al. 2006). Consistent with the

family stress model, we hypothesize that cumulative

socioeconomic adversity increases emotional problems of

parents because they are more likely to experience multiple

stressful circumstances, including family economic pres-

sure, adverse work conditions, lack of social support,

community stress, and marital problems. Distressed par-

ents, in turn, are more irritable, authoritarian, rejecting,

neglecting, and hostile toward their children (Conger et al.

2010). Furthermore, parents with a lack of resources and

income may not find adequate time to spend with their

children, contributing to parent–child distancing and child

negligence. Thus, in the present investigation, we will

investigate the influence of early cumulative socioeco-

nomic adversity by generating a composite index of dif-

ferent dimensions of adversity.

Parental rejection is implicated in adolescents’ feelings

of worthlessness, unhappiness, and their pessimistic out-

look on the future (Benoit et al. 2013). For example, early

adverse socioeconomic characteristics, such as family

economic hardship, low parental education, and parents’

marital instability, may influence depressive symptoms

through its impact on family stressful events (e.g., having

to move to a different home in order to live within the

confines of low-family income) (Brooks-Gunn and

J Youth Adolescence (2014) 43:1096–1109 1097

123

Peterson 1991; Ge et al. 1994; Wickrama et al. 2008),

extra-familial stressful conditions (e.g., threatening and

dangerous communities; Ross and Mirowsky 2001). Par-

ticularly, resource deprivation (lack of school materials,

food, clothing, and leisure) generates depressive feelings in

youths. These stressful experiences are expected to

increase adaptive challenges for and depressive symptoms

in adolescents already dealing with the rapid biological,

cognitive, and social changes that occur during this period

of life. In addition, as shown in Fig. 1, early socioeconomic

adversity may also be directly associated with adolescent

depressive symptoms.

Depressed youth with weak family ties due to parental

rejection are more at risk for a disrupted transition to

adulthood, particularly, the precocious acquisition of adult

roles (rushed to adulthood; Foster et al. 2008; Scaramella

et al. 1998; Wickrama et al. 2008). Consistent with the life

course perspective, adolescents’ precocious life events

during the transition to adulthood include off-time events,

such as the birth of a child at an early age and truncated

education, that deviate from normative timing, especially

in terms of assuming adult roles or responsibilities while

still an adolescent (Elder et al. 1996). We propose that the

detrimental effect of parental rejection in this chain of risks

experienced by adolescents is stronger than other dimen-

sions of parenting, such as parental management, because

parental rejection operates as a chronic stressor, in addition

to other stressors such as personality and unsafe neigh-

borhoods, and is a source of ‘‘identity disruption’’ with

implications for generating negative feelings (Thoits 1995).

As shown in Fig. 1, regardless of parental rejection and

depressive symptoms, we expect that early cumulative

socioeconomic disadvantage, characterized by a disad-

vantaged family and community, will also contribute to the

occurrence of precocious life events (Bernhardt et al. 2005;

Wickrama et al. 2005). The processes accounting for this

‘‘direct influence’’ may include parental marital problems

(Amato and Booth 2001), parents’ employment problems

(Hagan and Wheaton 1993), family resource limitations

(Lynch et al. 1997), and residential adversity (Wickrama

et al. 2005). Moreover, adolescents from disadvantaged

and troubled families are more likely to form weak bonds

to normative social institutions, such as schools, churches,

and community organizations, due to poor social skills and

low social acceptance, and they also curtail or abandon

conventional aspirations. Consequently, there is less social

deterrence for precocious entry into adult roles (Wickrama

et al. 2008).

The life course perspective suggests that the timing and

sequence of transition events, such as completing one’s

education, beginning a career, and entry into family

responsibilities, gives structure to the life course. Some

studies document that youth benefit from following nor-

mative sequences of major life events (Jackson 2004), but

numerous other studies (Schoen et al. 2007; Shanahan

2000) have shown that youth take a variety of divergent

paths from adolescence to adulthood. We hypothesize that

regardless of this heterogeneity in the timing and sequence

of life events, in general, the early occurrence of major life

transition events may increase the likelihood of negative

consequences for individual well-being because it creates a

chronically stressful life context that places excessive

demands on ill-equipped adolescents (Foster et al. 2008;

Oshri et al. 2011; Wickrama et al. 2008).

Chronic stressful circumstances are thought to lead to

stress responses that may exacerbate metabolic processes

resulting in increased BMI (Dowd et al. 2009). Exposure to

chronic stressors results in a two-stage stress response

(Burdette and Needham 2012). First, adrenaline is released

from the ‘‘fight or flight response,’’ which triggers the

release of stored energy and fat reserves. Second, the

hypothalamic–pituitary–adrenal (HPA) axis is activated to

Fig. 1 The theoretical model: stressful developmental processes

leading to young adult obesity and genetic amplification. Double

arrows signify gene–environment interactions whereby genetic

influences are moderated by early experiences of socioeconomic

adversity and/or parental rejection

1098 J Youth Adolescence (2014) 43:1096–1109

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release cortisol into the bloodstream in order to restore the

energy reserves by prompting hunger and transforming

food into fat reserves. In addition, psychological distress

may also increase cortisol levels throughout the day lead-

ing to chronically high cortisol levels, which is associated

with central obesity (Burdette and Needham 2012). Psy-

chological distress also contributes to physical inactivity

and the sedentary life style of youth (Katon et al. 2010).

Furthermore, unhealthy eating behaviors are often a way to

cope with stressful life circumstances (Ng and Jeffery

2003; Wickrama et al. 2011). Thus, we expect that cumu-

lative early life socioeconomic adversity will initiate a

‘‘chain of risks’’ including parental rejection, depressive

symptoms, precocious development, and, consequently,

BMI as young adults.

Do Genetic Polymorphisms Amplify Stressful

Developmental Processes?

Additive Genetic Influence (G)

Genetic make-up of an individual represents segments of

the genome that contribute to his/her particular behaviors

(phenotypes) or functions (in this study, acquisition of

precious life events and lifestyle factors, as reflected by

obesity). Polymorphisms are variations in the structure of

genes, and each variant of a gene is called an ‘‘allele.’’

Most molecular genetics research on behavior has focused

on variations in candidate genes that regulate neurotrans-

mitter systems, such as serotonergic and dopaminergic

neurotransmitter systems. Repeat polymorphisms in the

promoter region of SLC6A4 gene produce two variants (or

5-HTTLPR alleles)—a short and long allele—with the

short allele resulting in lower serotonin transporter avail-

ability than the long allele. Research shows that individuals

with one or two copies of the 5-HTTPR ‘‘short’’ allele

display more behavioral, psychological, and health prob-

lems (Caspi and Moffitt 2006). In addition to other relevant

influences on youths’ behavior, serotonin transporter genes

may also play a role in the lifestyle behaviors of young

adults because they are linked to reward sensitivity (Hariri

et al. 2003; 2006; Zhong et al. 2009), which has implica-

tions for precocious life events, such as early sex, early

pregnancy, and early cohabitation, as well as for obesity.

Like serotonin transporter genes, key regulators of the

dopaminergic system (DAT1 and DRD4 genetic variants)

are also linked to reward sensitivity, which has been

hypothesized to serve as the mechanism connecting these

neurotransmitter systems to a host of life processes

including human romantic relations, sexual behaviors,

emotional problems, educational failure, and obesity rela-

ted behaviors (Beaver et al. 2007; Emanuele et al. 2007;

Pederson et al. 2005). Similarly, individuals who have

specific DAT1 and DRD4 allele variants are likely to

engage in novelty seeking behaviors and develop addictive

behaviors, ADHD, and behavioral problems, which may

explain the association between these genetic variants and

precocious development and obesity (Beaver et al. 2007;

Kim-Cohen et al. 2006; Simons et al. 2012). In addition, on

average, individuals with a DRD4 allele variant have been

found to have higher body mass than individuals without

this specific genetic variant (Stice et al. 2010). Thus, we

expect that these genetic variants implicated in both

dopamine and serotonin neurotransmission (5HTTP,

DAT1, and DRD4) may be associated with behaviors

leading to precocious life events (e.g., early sexual inter-

course, teenage pregnancy) as well as to obesity (e.g.,

unhealthy eating and sedentary behavior). More impor-

tantly, recent research indicates that multiple genes may

combine to exert a cumulative influence on individual

behaviors or phenotypes (Belsky and Beaver 2011; Simons

et al. 2012; Wickrama and O’Neal 2013). Thus, we expect

that these genetic polymorphisms will increase the likeli-

hood of youths’ precocious development and high BMI

levels.

Life Contexts–Gene Interactions (G 9 E)

Numerous studies have found that genes, or their variants,

interact with environmental contexts to shape youth

developmental outcomes, such as educational success,

sense of mastery, and health outcomes (e.g., Caspi and

Moffitt 2006; Wickrama and O’Neal 2013). The environ-

ment–gene interaction (G 9 E) has been interpreted

according to a genetic modification approach. From this

approach, the environment is thought to set the stage for a

certain outcome to occur, but whether the outcome mate-

rializes, or to what extent, may be dependent on the pre-

sence of certain genetic variants. That is, genes buffer the

influence of the environment on outcomes or change its

susceptibility to the environment (Belsky and Beaver

2011).

Numerous genetic studies have found that variants of

genes often interact with environmental contexts (G 9 E)

to shape individuals’ psychological vulnerability and aca-

demic and cognitive competency (e.g., Caspi and Moffitt

2006). These findings are often interpreted according to the

stress—diathesis hypothesis, which posits that ‘‘risk

alleles’’ or ‘‘vulnerability genes’’ make individuals more

susceptible to stressful environments (e.g., early socio-

economic adversity) and operate as ‘‘triggers’’ (Shanahan

and Boardman 2009) for negative adolescent develop-

mental outcomes. But the differential susceptibility

hypothesis, or plasticity hypothesis, has emphasized that

positive environmental contexts (e.g., affluent environ-

mental conditions or warm/nurturing parenting) operate as


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‘‘social enhancements’’ or ‘‘compensations’’ (Shanahan

and Boardman 2009) leading the same genetic variants to

exert positive influences (Belsky et al. 2009; Belsky and

Beaver 2011). In other words, certain alleles may be more

appropriately viewed as ‘‘plasticity genes’’ that merely

amplify the effect of a positive or negative environment.

Although recent studies provide promising evidence for the

plasticity hypothesis (Belsky and Beaver 2011; Simons

et al. 2012; Wickrama and O’Neal 2013), in the present

study, we do not expect to find evidence of such differ-

ential susceptibility because our measures of the contexts

do not capture the full continuum of environmental con-

texts—from positive to negative (e.g., adverse environment

to affluent environmental, warm and caring parenting to

rejecting and neglecting parenting). Rather, our measures

primarily assess environmental adversity and parental

rejection/negligence (i.e., the negative side of the contin-

uum). Thus, in the present study, we expect evidence to

support the stress—diathesis hypothesis because, as shown

in Fig. 1, we expect that genetic polymorphisms will

amplify the influence of age-graded stressful life contexts

on youths’ developmental outcomes (precocious develop-

ment and BMI).

Current Study

Understanding the life course developmental processes

stemming from early socioeconomic context leading to

young adult health outcomes through adolescents’ dis-

rupted transition experiences is a pertinent topic for social

science research. Additionally, investigating genetic influ-

ences on life course developmental processes broadens our

understanding about how biology and environment com-

bine to influence youth development over the early life

course. Previous research has documented the adverse

influence of early socioeconomic disadvantage on adoles-

cent emotional health, the occurrence of youth’s precocious

transition events, as well as their physical health outcomes

(Bernhardt et al. 2005; O’Rand and Hamil-Luker 2005;

Wickrama and Noh 2010; Wickrama et al. 2005, 2008).

However, these studies are often focused on a single pro-

cess and health outcome. Drawing from the life course

perspective, and consistent with the notion of a ‘‘chain of

risks,’’ the present study proposes to examine life course

developmental processes stemming from early socioeco-

nomic adversity leading to young adults’ BMI through

adolescent depression and precocious development.

Because little is known about how genes interact with

social contexts to influence subsequent developmental

outcomes, the present study sought to examine the additive

(G) and interactive (G 9 E) genetic influences on this

process within a single analytical framework (see Fig. 1).

Based on the life course perspective and previous

genetic research, we hypothesized that cumulative early

life socioeconomic adversity will initiate a ‘‘chain of risks’’

including parental rejection, depressive symptoms, preco-

cious development, and, consequently, BMI as young

adults. That is, early socioeconomic adversity will be

associated with increases in adolescents’ depressive

symptoms, adolescents’ depressive symptoms will be

associated with increases in adolescents’ precocious

events, and precocious development will be associated with

increases in young adults’ BMI. In addition, we hypothe-

sized that individuals with certain genetic polymorphisms

(variants of DRD2, DRD4, and 5HTTPR) will engage in

more precocious development and have higher BMI levels

as young adults compared to individuals without these

genetic variants. Finally, we hypothesized that genetic

polymorphisms will amplify the influence of early socio-

economic adversity and parental rejection on youths’

developmental outcomes (precocious development and

BMI).

Methods

Sample

Data for this study were drawn from a nationally repre-

sentative sample of adolescents participating in the

National Longitudinal Study of Adolescent Health (Add

Health). In 1995, baseline (Wave 1) data were derived from

a complex cluster-sampling of middle and high school

students, yielding 20,745 respondents of 12–19 years of

age (average age was 15.5 years), from 134 middle and

high schools. To ensure diversity, the sample was stratified

by region, urbanicity, school type (public vs. private),

racial composition, and size. Second and third wave data

were collected in 1996 and 2001 (N2 = 14,738 and

N3 = 15,100). We used in-home interview data from par-

ents who responded to family demographic, socioeco-

nomic, and parenting questions in Wave 1 and adolescents

who participated in all four waves and provided a genetic

sample. Thus, the final study sample was 12,424. We used

Wave 1 sample weights in the analyses. In most instances,

the adolescent’s mother served as the responding parent

because Add Health investigators rationalized that,

according to the results of previous studies, mothers are

generally more familiar than fathers with the schooling,

health status, and health behaviors of their children. If the

mother was unavailable, the interviewer was instructed to

choose the first person who lives with the respondent from

the following list: stepmother, other female guardian,

father, stepfather, other male guardian. Over 95 % of the

responding parent figures in the final sample were


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biological, step, adopted, or foster parents (rather than

another relative or unrelated guardian). More information

about Add Health is available at http://www.cpc.unc.edu/

projects/AddHealth. The final sample consisted of

approximately 53 % women, and 39 % of respondents

reported a minority racial/ethnic status with the largest

percentages reported for African American, Hispanic,

Asian, and Native American, respectively. At W3 or W4

respondents were asked to provide a saliva sample for

genotyping.

Measures

Body Mass Index

At W4 (2008), trained interviewers measured respondents’

height and weight. From these measurements, BMI, the

ratio of weight to height squared ([lbs 9 703]/in.2), was

calculated. Height and weight measurements were also

obtained by trained interviewers at Wave 2 (1996). This

information was used to calculate adolescent BMI, the ratio

of weight to height squared ([lbs 9 703]/in.2), which was

included in the model as a control variable.

Cumulative Socioeconomic Adversity

Following existing research (Brody et al. 2013), we con-

structed an index assessing cumulative socioeconomic

adversity by adding dichotomous indicators capturing dif-

ferent dimensions of adversity. These indicators included

low parental education, high family economic hardship,

low parental marital stability, and high community adver-

sity. Except for marital stability (initially computed as a

dichotomous variable), dichotomous indicators were cre-

ated by conducting a mean split for each of the following

measures.

Parental Education The responding parent reported both

parents’ highest level of education obtained at W1 (1995).

Responses ranged from: 1 = never went to school to

10 = professional training beyond 4-year college or uni-

versity degree. Mothers’ and fathers’ educational levels

were summed to create an index of parental education. For

single-headed families with no available data from fathers

(n = 79), maternal education served as the indicator of

parental education.

Economic Hardship Five dichotomous items (0 = no,

1 = yes) assessed whether any member of the household

received the following social service benefits: social

security, supplemental security income, aid to families with

dependent children, food stamps, or housing subsidies at

W1 (1995). Responses to these five items were summed to

create an index of economic hardship with a range of 0–5.

Parents’ Marital Stability A binary variable was com-

puted to differentiate parents who had been consistently

married to their spouse (or in a marriage-like relationship)

for at least 15 years (1) from other parents (0).

Community Adversity The community adversity measure

was generated by summing four indicators corresponding

to their census tract information from the 1990 US Census.

Those indicators included the proportion of families living

in poverty, the proportion of single-parent families, the

proportion of adults employed in service occupations, and

the proportion of unemployed men (adapted from Sucoff

and Upchurch 1998). This index had an internal consis-

tency of .78.

Parental Rejection and Negligence

Mothers responded to five items assessing their relationship

with the target adolescent. All items were rated on a scale

ranging from 1 = strongly agree to 5 = strongly disagree.

Sample items include whether they ‘‘got along well with

the adolescent’’ and ‘‘felt this child interferes with his/her

activities.’’ When necessary, responses were reverse-scored

before summing the items so that higher scores indicate

greater parental rejection. This index had an internal con-

sistency of .96.

Depressive Symptoms

From Wave 1 (1995) data, eight of the ten items from the

Center for Epidemiological Studies Depression Scale

(Radloff 1977) were used to assess adolescent respondents’

frequency of distress feelings (e.g., ‘‘felt depressed and

sad’’) in the past week. The two positive affect items were

removed to assess the frequency of negative affect only.

Scale responses ranged from 0 (never or rarely) to 3 (most

of the time or all of the time). This resulted in an index of

depressive symptoms ranging from 0 to 24, with adequate

internal reliability (a = .78).

Precocious Transitions

We used both Wave 3 and Wave 4 data to identify

respondents who experienced precocious events. In this

classification, we ensured that all respondents had aged

enough to have experienced risks defined as precocious

events. We operationalized most of the youth’s precocious

life events (e.g., early sexual activities, early marriage,

early cohabitation, early leaving home, and truncated

education) based on US national norm ages, and the events


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http://www.cpc.unc.edu/projects/AddHealth

http://www.cpc.unc.edu/projects/AddHealth

that occurred before the normative ages were considered to

be precocious (Wickrama et al. 2005). A sum score was

then computed indicating the total number of precocious

transitions the adolescent experienced. The individual

indicators used in this index are described below.

Early Sexual Activities (Early Sex) In the United States,

the average age of first sexual intercourse was 16 years old

among American males and female (Centers for Disease

Control and Prevention 2010). The onset of sex intercourse

before 16 years of age was categorized as ‘‘early sex.’’

Retrospective reports of respondents’ (Wave 3, 2001) year

of first sexual intercourse and their age were used for this

classification.

Early Marriage Marriage before 24 years of age was

categorized as ‘‘early marriage.’’ Retrospective reports

(Wave 4, 2008) on marital status (married once or more),

duration of marriage, and the respondents’ age were used to

identify young adults who married before 24 years of age.

We also identified and added respondents who reported

their marital experience before 24 years of age in Wave 3,

but did not report it in Wave 4.

Early Leaving Home Previous studies have documented

that the average age of leaving home is 21 years for young

adults (Kreiter 2003). Reports (Wave 3, 2001) on the res-

idential status (living in a separate house, apartment, trailer

home, or group quarters) and the retrospective reports on

the year of moving were used for this classification (these

reports were not available in Wave 4). Full-time college/

university students were not categorized as ‘‘early leavers.’’

Because the youngest respondents were 19 years old in

2001, the cutoff for this classification was 19 years of age.

Thus, our measure corresponds to ‘‘early leaving home’’

during adolescent years.

Early Pregnancy Teenage pregnancy (during adoles-

cence) was considered early pregnancy. Thus, early preg-

nancy (females becoming pregnant or males impregnating/

fathering) before 19 years of age was classified as ‘‘early

pregnancy.’’ Retrospective reports (Wave 3, 2001) on the

year of first pregnancy or ‘‘fathering’’ were used for this

classification.

Joining the Workforce Prematurely Retrospective reports

(Wave 3, 2001) on the year of ‘‘first full-time paid work’’

and respondent’s age were used to identify youths who

worked full-time during the high school attending years.

Truncated Education Adolescents who did not complete

high school or an equivalent level of education (early

termination of education) were classified as having low

education compared to other youth using Wave 3 data.

Composite Genetic Index

The Institute for Behavioral Genetics at the University of

Colorado conducted the genotyping of Add Health DNA

samples using previously established methods (Harris et al.

2006). Three genetic polymorphisms were examined in the

current study because of existing research suggesting spe-

cific alleles of these polymorphisms are related to genetic

risk (Belsky et al. 2009). Specifically, subjects were gen-

otyped for: a 40 bp variable number of tandem repeats

(VNTR) in the 30 untranslated region of the gene (DAT1), a

48 bp VNTR in the third exon of the dopamine D4 receptor

gene (DRD4), and a 43 bp addition/deletion in the 50 reg-

ulatory region of the serotonin transporter gene (SLC6A4).

The specific alleles include the 10R allele of DAT1, the 7R

allele of DRD4, and the short (S) 5HTTLPR allele of

SLC6A4 (12 bp repeat). Following existing research (e.g.,

Belsky and Beaver 2011; Simons et al. 2012), each of the

three genetic polymorphisms was coded dichotomously

(1 = at least one allele, 0 = no copies of the allele), and a

sum score was computed with values ranging from 0 to 3.

Higher scores indicated the presence of more genetic risk

alleles.

Control Variables

Race/Ethnicity At W1 adolescents reported their race/

ethnicity. Dichotomous variables were then created to

assess African American, Hispanic, Asian, Native Ameri-

can, and White racial/ethnic statuses. The dichotomous

variables for each of the minority statuses were included as

independent variables in the regression equation resulting

in regression coefficients that can be interpreted with ref-

erence to Whites (reference group = Whites). For multi-

racial respondents, only their first choice of race/ethnicity

category was considered. The majority of respondents were

White (63.9 %) followed by African American (15.9 %),

Hispanic (13.2 %), Asian (6.0 %), and Native American

(1.0 %) races/ethnicities. Of the Hispanics in the sample,

48.1 % indicated that they were Mexican–American,

15.5 % indicated Cuban American, 15.8 % indicated

Puerto Rican American, and 20.6 % indicated a different

Hispanic race/ethnicity origin.

Gender Gender was coded as male (0) or female (1).

Analysis

We conducted structural equation modeling (SEM) using

Mplus statistical software (version 6) to test our


123

hypothesized models. The Mplus COMPLEX command

was used to account for the nested structure of the school-

based design within the Add Health study. Full information

maximum likelihood (FIML) procedures were used to

account for missing data. FIML does not impute missing

values; instead, it estimates model parameters and standard

errors directly from all available data. FIML has been

shown to provide more accurate parameter estimates than

other procedures for handling missing data (Enders 2001).

An attrition and missing data analysis showed that ado-

lescents who participated in all four waves were slightly

younger but otherwise confirmed that there was little dif-

ference between adolescents with missing data in our study

sample and those with complete data. Preliminary analyses

revealed no statistically significant rGE correlations

between our cumulative genetic index variable and the

early cumulative adversity index we examined. This sug-

gests that results indicating a G 9 E interaction between

these variables are not reflective of a gene–environment

correlation. The cumulative genetic index also did not vary

significantly by respondents’ gender. Furthermore,

although the cumulative genetic index was not correlated

with race/ethnicity, we incorporated race/ethnicity within

the model to minimize the possibility of population strat-

ification influencing the results. Gene–environment inter-

actions were tested using the product terms of centered

variables. Model fit was evaluated using the comparative fit

index (CFI) and the root mean square error of approxi-

mation (RMSEA).

Results

Table 1 presents descriptive statistics of the study vari-

ables. Young adults’ BMI (W4, 2008) varied from 15.40 to

68.50. Overall, early socioeconomic adversity was not

severe with respondents’ experiencing an average of 1.58

socioeconomic hardships in early adolescence (Wave 1,

1995). Most parents disagreed with statements indicating

parental rejection (M = 9.45, SD = 2.75). Adolescents, on

average, reported few depressive symptoms (M = 5.40,

SD = 3.57). Generally respondents reported few preco-

cious life transition events (M = .67, SD = .83). The

approximate percentages for each precocious transition

event were: 23.8 % for early sex, 9.3 % for early preg-

nancy, 28 % for early marriage, 27 % for leaving home

early, 11 % for joining the work force prematurely, and

13.2 % for high school drop outs. Figure 2 illustrates the

full model assessing early socioeconomic adversities,

subsequent adverse developmental processes, and amplifi-

cation of these effects by genetic polymorphisms as well as

the interactions of these genes with age-graded social

contexts (G 9 E).

Developmental Processes Influencing Young Adult

BMI

As shown in Fig. 2, we found evidence that cumulative

socioeconomic adversity at Wave 1 (1995) may create a

‘‘chain of risks’’ influencing young adults’ BMI (Wave 4,

2008) after controlling for race/ethnicity, gender, and lag-

ged BMI (Wave 2, 1995). More specifically, cumulative

socioeconomic adversity was associated with parental

rejection (B = .16), which, in turn, was implicated in the

occurrence of depressive symptoms (B = 1.15) and later

precocious transition events during adolescence (B = .21).

Also, precocious transition events were more prevalent

among adolescents reporting depressive symptoms

(B = 1.15). As expected, the stressful nature of precocious

transition events was associated with the increased likeli-

hood of having a high BMI in young adulthood (Wave 4)

(B = .15). Thus, cumulative socioeconomic adversity

created a chain of risks resulting in higher BMI in young

adulthood. However, cumulative socioeconomic adversity

at Wave 1 (1995) also continued to exert direct effects on

adolescents’ depressive symptoms (B = 1.50), their pre-

cocious transition to adulthood (B = .83), and their BMI in

young adulthood (B = 1.03) after accounting for this life

course chain of insults.

Statistically significant findings also existed for adoles-

cent BMI. More specifically, on average, adolescents

experiencing greater cumulative socioeconomic adversity

had higher BMI than individuals experiencing less socio-

economic adversity (B = 1.54, p \ .001). Furthermore,

adolescents with more depressive symptoms and those with

more genetic risk alleles generally had higher BMI values

Table 1 Descriptive statistics of study variables (N = 12,424)

Variables Mean (or

proportion)

SD Range

Cumulative socioeconomic

adversity

1.58 1.11 0.00–4.00

Parental rejection 9.45 2.75 2.00–24.00

Depressive symptoms 5.40 3.57 0.00–24.00

Precocious life transition

events

.67 .83 0.00–6.00

Cumulative genetic

sensitivity (G)

1.85 .12 0.00–3.00

Body mass index (W4,

2008)

29.15 7.53 15.40–68.50

Body mass index (W2,

1996)

23.29 4.58 11.63–51.43

Gender (female) 54.5 %

African American 15.9 %

Hispanic 13.2 %

Asian 6.0 %


123

at Wave 2 (1996) than adolescents with few depressive

symptoms and risk alleles (B = .07, p \ .001 and B = .12,

p \ .05 for depressive symptoms and risk alleles, respec-

tively). As expected, lagged BMI was a strong predictor of

subsequent BMI in young adulthood (B = 1.13, p \ .001).

Race/ethnicity and gender were also included in the

model as control variables, and some notable demographic

differences were also found. For instance, compared to

Whites, African Americans generally reported higher BMI

as adolescents (B = .86, p \ .001). Similarly, Hispanics

also reported higher BMI during adolescence and young

adulthood (B = .62 and .30, p \ .05, respectively) than

Whites. But Hispanics, as a minority race/ethnicity, were

unique in that they reported less parental rejection than

their White counterparts (B = -.09, p \ .01). All minority

racial/ethnic groups reported more depressive symptoms

than Whites (B = .28, .72, and 1.15, p \ .01 for African

Americans, Hispanics, and Asians, respectively), whereas

African Americans and Asians reported fewer precocious

life transitions than Whites (B = -.09, p \ .05 for African

Americans and B = -.20, p \ .001 for Asians). Females

experienced slightly more socioeconomic adversity

(r = .01, p \ .01), more parental rejection (B = .03,

p \ .05), and higher young adult BMI (B = .40, p \ .001)

but fewer precocious life transitions (r = -.07, p \ .05)

than males.

Furthermore, we also examined potential race/ethnicity

and gender moderation, particularly in regards to differ-

ences in the effect of cumulative socioeconomic adversity

on adolescent and young adult BMI. There were no sta-

tistically significant racial/ethnic differences. Regarding

gender differences, the paths from early adversity to BMI

were statistically significant for females (B = 1.138 and

1.134 for BMI in adolescence and young adulthood) but

not for males (B = .578 and .576 for BMI in adolescence

and young adulthood).

Direct and Interactive Polygenic Effects

After controlling for developmental processes, the cumu-

lative genetic index for genetic variants implicated in

serotonin and dopamine neurotransmission did not directly

influence young adults’ BMI (B = .10) or precocious life

transitions (b = .01). However, individuals with more risk

alleles generally reported more depressive symptoms in

adolescence (B = .09). Furthermore, multiplicative inter-

action terms assessing context–gene interplay (G 9 E)

indicated two statistically significant G 9 E effects. The

index of genetic variants interacted with socioeconomic

adversity to influence young adults’ BMI (b = .13). Fur-

thermore, the genetic index also interacted with parental

rejection to influence the occurrence of precocious life

transition events (b = .04). For both interaction effects, the

presence of risk alleles was associated with the amplifica-

tion of the negative influence stressful contexts (more

specifically, socioeconomic adversity and parental rejec-

tion) exert on BMI. Overall, the structural equation model

including developmental processes, control variables, and

genetic factors explained 49.9 % of the variance in young

adults’ BMI. Model fit indices indicated that the model

provided a good fit to the data [v2(55) = 4,638.466;

CFI = .955, RMSEA = .029].

Fig. 2 Developmental processes leading to young adult obesity and genetic amplifications. Unstandardized coefficients are shown with

standardized coefficients in parentheses. Only statistically significant paths are included. *p \ .05; **p \ .01; ***p \ .001


123

Discussion

Although previous research has documented the adverse

influence of early socioeconomic disadvantage on youths’

physical health outcomes and the increase in health

inequalities over the early life course (Bauman et al. 2006;

O’Rand and Hamil-Luker 2005; Wickrama and O’Neal

2013), little is known about life course developmental

processes that explain this cumulative process. Particularly,

little is known about sequential life course processes

leading to health outcomes. Moreover, most previous

studies are fragmented and focused on single develop-

mental outcomes. Thus, the present study partly fills this

gap by providing evidence for the persistent influence of

early adversity on young adult BMI through sequentially-

linked adolescent developmental failures. More impor-

tantly, to our knowledge, previous research has not inves-

tigated genetic influences on life course processes, and the

simultaneous gene and environment influences, leading to

health outcomes. Consistent with the stress—diathesis

hypothesis, the present study provides evidence for the

additive and interactive genetic influences on this life

course developmental process leading young adults’ BMI.

Specifically, the present study addressed two main

objectives. First, it examined the disrupted developmental

processes of adolescents following early adversities and

leading to young adults’ high BMI. Consistent with our

expectations, the results showed that children who have

experienced adverse socioeconomic conditions, parental

rejection, and depressive symptoms showed higher levels

of precocious development compared to children who have

experienced less adverse conditions. In turn, precocious

development was associated with high BMI in early

adulthood. These findings are consistent with the life

course notion of a chain of risks over the life course

(O’Rand and Hamil-Luker 2005).

We utilized a composite index of early socioeconomic

adversity to capture various dimensions of adversity. As

expected, this multi-dimensional operationalization of

early adversity provided an effective measure with high

predictive validity in relation to youth developmental

processes, explaining variation not only in parental rejec-

tion but also explaining variation in depressive symptoms,

precocious development, and BMI. Moreover, consistent

with previous studies, our preliminary analysis has also

shown that the developmental risk of cumulative socio-

economic adversity is stronger than the independent effect

of individual dimensions of socioeconomic adversity

(Bauman et al. 2006).

In past research, parental rejection has been found to

inflict psychological vulnerability in youth, resulting in the

precocious development of adolescents (Foster et al. 2008;

Scaramella et al. 1998; Wickrama et al. 2008). In line with

previous findings, adolescents’ precocious development

explained variation in young adults’ BMI (Wickrama and

Noh 2010). Although, we did not elucidate the mediating

mechanisms for this association, behavioral and physio-

logical mechanisms may link stressful precocious devel-

opment to young adult BMI. The behavioral mechanisms

may include substance use, poor eating, inadequate sleep,

and lack of exercise (Knutson 2005; Needham and Crosnoe

2005). The physiological mechanisms likely include stress-

related inflammatory and metabolic dysregulations (Ap-

pelhans et al. 2010; Fagundes et al. 2013). Future studies

should elucidate these mechanisms.

Addressing our second study objective, the results pro-

vided evidence for the possible amplification of adverse

development processes of youth by genetic polymorphisms

through interactions with age-graded life contexts (G 9 E).

The results suggest that genetic polymorphisms may

interact with early socioeconomic adversity and with

parental rejection to explain variability in youth develop-

mental outcomes: young adults’ BMI and adolescents’

precocious development, respectively. These findings are

consistent with the notion that the impact of specific

environments and context–gene interplay on an individual

phenotype may be observed only in a later life stage as

G 9 E effects are salient at different ages and also likely

increase from childhood to young adulthood (Shanahan and

Boardman 2009). Thus, the present study examined these

G 9 E influences by locating them in a comprehensive life

course model that allows environments and genes to ‘‘act in

concert’’ over the life course rather than examining gene–

environment interactions in an isolated manner. Hence,

although genetic influences are small in magnitude, the

statistically significant results of the present study suggest

that genetic polymorphism may both accelerate (G effect)

and amplify (G 9 E effect) disrupted developmental pro-

cesses over the early life course.

Candidate gene studies often provide evidence of small

genetic effects (as indicated by effect sizes). For example, a

recent study by Rietveld et al. (2013) published in Science,

found three alleles (single nucleotide polymorphisms) were

associated with educational attainment with small esti-

mated effect sizes (R2 & 0.02 % per allele). A linear

polygenic score from all measured alleles accounted for

&2 % of the variance in both educational attainment and

cognitive function. These researchers argue that these

findings provide promising alleles for examination in

future research, and their effect size estimates can anchor

power analyses in social science genetics. Similarly, we

believe that the genetic variants investigated in the present

study, and their small but statistically significant influ-

ences, are also useful information for future developmental

studies. In combination, the polymorphisms had a small,

but noteworthy, effect on susceptibility to developmental


123

risks. When a youth inherits several, or numerous, sus-

ceptibility variants together, they may have a sizable

influence on developmental risk (Falconer and McKay

1995). In the present study, we investigated only three

genetic variants, which have been shown to influence

outcomes, due to data availability. Moreover, social epi-

demiologists have pointed out that a small shift in the

distribution of risk throughout the population or small

effects of a risk can make large differences in the wellbe-

ing/health status of that population (Berkman and Kawachi

2000; Mirowsky and Ross 1992). Thus, the results of

present study suggest that future studies should incorporate

more variants in investigations of cumulative genetic

effects. We believe that the evidence for genetic influences

provided by the present study are substantially important

and also suggests that developmental life course research

should be informed by genetics.

To our knowledge, no previous study has examined such

cumulative genetic influences on developmental processes

over the early life course leading to adult health outcomes.

Because multiple genes can cumulatively influence indi-

vidual behaviors by exerting a shared genetic influence, we

followed existing research using a composite genetic

measure to capture this potential polygenic influence

(Belsky and Beaver 2011). Our findings suggest that mul-

tiple genes, rather than individual genes, additively and

interactively with the environment influence youth devel-

opmental outcomes (Belsky and Beaver 2011). Further-

more, the results of our comprehensive model showed that

the association between two life contexts (parental rejec-

tion and precocious development) was not spurious due to

the common influence of the alleles we measured in the

cumulative genetic index. Similarly, the influence of ado-

lescent precocious development on young adult BMI is not

due either to the common influence of early adversity or to

the common genetic influence captured by our index of

genetic variants implicated in neurotransmission.

We argue that the findings of the present study do not

contradict the life course-stress process perspective (Pear-

lin et al. 2005), rather these findings provide extended

support for this perspective. Like the current research, life

course perspective is largely concerned with the effect of

life context on youth developmental outcomes. Also, one

important tenant of the life course perspective (Elder and

Giele 2009) is that individual characteristics (e.g., indi-

vidual agency) operate as moderators of the influence of

life context over the life course. The current research

incorporates biological characteristics as important indi-

vidual characteristics. Particularly, we argue that individual

genetic make-up can be considered as an individual bio-

logical characteristic that moderates the life course stress

process. Accordingly, the significant G 9 E interactions in

the current findings reflect the moderating (or amplifying)

influence of stressful life contexts thereby accelerating the

life course-stress process. Because of the increased avail-

ability of genetic data in psychosocial research, life course-

stress researchers should extend this line of research to

enhance our understanding of life course-stress process.

Several factors potentially limit the scope and the gen-

eralizability of the results. First, our results may be subject

to false positive associations and a lack of statistical power,

which is often a possibility in candidate gene association

studies. Thus, future studies should attempt to replicate

these findings with larger samples. Second, we did not

examine potential moderating effects of youth academic

and cognitive competencies or psychological vulnerabili-

ties, which can protect youth from the negative influence of

early socioeconomic adversity on young adults’ health

outcomes (Wheaton and Gotlib 1997). Third, our measure

of parental rejection and negligence was limited to the

questions asked of parents at Wave 1, the same time point

used to examine cumulative socioeconomic adversity.

Although these items have been used in previous studies

utilizing the Add Health data and have predicted variation

in numerous subsequent physical and mental health out-

comes (Wickrama et al. 2009, 2013a, b; Wickrama and

Noh 2010), the validity of these items has not been spe-

cifically examined and their internal consistency was

higher than typical (.96). Thus, these limitations should be

taken into consideration when interpreting the present

findings.

Conclusion

The present study makes a valuable contribution to existing

research by providing evidence for an adverse develop-

mental process over the early life course stemming from

early adversity as well as for the additive and interactive

influence of genotype on this process. Adverse socioeco-

nomic conditions appeared to initiate an adverse ‘‘chain of

risks’’ including parental rejection, depressive symptoms,

and precocious transition events. In turn, precocious

development was associated with high BMI in early

adulthood. Furthermore, the results suggest that genetic

polymorphisms may interact with early socioeconomic

adversity and parental rejection to influence life course

developmental processes.

In addition to advancing scientific research, these find-

ings have key policy and program implications as they

indicate numerous leverage points for intervention and

prevention work. For instance, it is imperative that policies

are enacted to improve the economic conditions of families

with young children because early socioeconomic adver-

sity initiates a chain of risks that increase the likelihood of

poor health later in life and across multiple domains. The


123

findings also highlight adolescent depression as a key

leverage point for improving the health of young adults as

depressive symptoms in adolescence are often a gateway to

more severe hardships in later life, including social diffi-

culties, lack of employment opportunities, and poor mental

and physical health (Fombonne et al. 2001; Richardson

et al. 2003). Youth programs and policies should promote

youth psychological competencies that aid in their suc-

cessful transition to young adulthood. In addition, these

findings linking precocious development to young adults’

BMI illustrate the far-reaching positive health conse-

quences of policy and program initiatives aimed at

enhancing successful adolescents’ transition to adulthood

avoiding precocious life events (including early sexual

activity, teenage pregnancy, and school dropout). Particu-

larly, programs and interventions aimed at improving the

life conditions of youth experiencing precocious life

events, such as GED classes or parenting classes for

teenage parents, may be successful turning points whereby

interventions can improve the resilience of these individ-

uals who are at high risk of subsequent poor health, par-

ticularly obesity.

Acknowledgments 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 P01-

HD31921 from the Eunice Kennedy Shriver National Institute of

Child Health and Human Development, with cooperative funding

from 23 other federal agencies and foundations. Special acknowl-

edgment is due Ronald R. Rindfuss and Barbara Entwisle for assis-

tance in the original design. Information on how to obtain the Add

Health data files is available on the Add Health website (http://www.

cpc.unc.edu/addhealth). No direct support was received from grant

P01-HD31921 for this analysis.

Author contributions K.A.S.W. conceived of the study, conducted

the preliminary analyses, and drafted the manuscript; C.W.O. par-

ticipated in the interpretation of the data and manuscript writing and

preparation; A.O. helped to draft the manuscript. All authors read and

approved the final manuscript.

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Kandauda A. S. Wickrama is a Professor at the University of

Georgia in Human Development and Family Science. He received his

doctorate in Sociology from Iowa State University. His major

research interests include social determinants of health and health

inequality across the life course and the application of advanced

statistical methods to social epidemiology.

Catherine Walker O’Neal is a Postdoctoral Research Fellow at the

University of Georgia in Human Development and Family Science.

She received her doctorate in Child and Family Development from

the University of Georgia. Her major research interests include

development over the life course and family and social factors that are

influential in health and well-being outcomes.

Assaf Oshri is an Assistant Professor at the University of Georgia in

Human Development and Family Science. He received his doctorate

in Developmental Psychology from Florida International University.

His major research interests include the study of developmental

processes that underlie the link between early stress and risk

behaviors among youth using a developmental psychopathology

theoretical framework.


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