Age at Menarche and Adolescent Alcohol Use

Page 1

EMPIRICAL RESEARCH

Age at Menarche and Adolescent Alcohol Use

Melissa Verhoef • Regina J. J. M. van den Eijnden •

Ina M. Koning • Wilma A. M. Vollebergh

Received: 3 September 2013 / Accepted: 2 December 2013

� Springer Science+Business Media New York 2013

Abstract Research has shown that early maturation is

related to problematic alcohol use, yet the differential

effect of early pubertal timing (i.e., younger age at men-

arche) on the onset of alcohol use and subsequent level of

alcohol use has rarely been examined. This distinction is

relevant, as younger age at menarche can have differential

effects on these outcomes, which in turn can have long-

lasting effects. Therefore, the present study examined the

relationship between age at menarche and adolescent

alcohol use among girls, hereby distinguishing between

onset and level of alcohol use. In addition, the moderating

effects of alcohol-specific rules, child disclosure and class

gender composition were examined. Participants were 430

girls from a Dutch four-wave survey, with a mean age of

12.17 years (SD = 0.50) at the beginning of the study.

Results showed that the probability of onset of alcohol use

was increased by younger age at menarche, but only when

girls were younger than 15. Moderation analyses showed

that younger age at menarche increased the risk of alcohol

onset only in low risk girls (with high levels of alcohol-

specific rules and in classes with a high percentage of

girls). Once adolescent girls started drinking alcohol,

younger age at menarche was associated positively with

alcohol consumption only for girls in classes with a mod-

erate to high percentage of girls. These findings confirm

that younger age at menarche is a risk factor for the onset

of alcohol use, but strongly suggest that this effect is

strongest for girls having restrictive alcohol-specific rules

and in classes with a high percentage of girls. Possibly, in

the absence of social factors that ‘‘push’’ to alcohol use,

biological factors (like age at menarche) become more

important. Another possibility is that adolescent girls start

drinking alcohol to oppose their parents if they set too strict

alcohol-specific rules.

Keywords Age at menarche � Adolescent alcohol use �Alcohol-specific rules � Child disclosure � Class gender

composition

Introduction

Younger age at menarche, a commonly used indicator for

early pubertal timing (Belsky et al. 2007), is shown to be

associated with a variety of problem behaviors, such as

alcohol use (Deardorff et al. 2005). The fact that this effect

of early pubertal timing persists into (young) adulthood

(Dick et al. 2000) underscores the significance of analyzing

the effect of early pubertal timing in more detail. The

current study adds to previous research by distinguishing

between the onset and level of alcohol use. This difference

is relevant, as earlier onset of alcohol use is associated with

more negative outcomes such as risky sexual behavior

(Boden and Fergusson 2011) or developing an alcohol-

related disorder (Stolle et al. 2009). In addition, by

examining several moderating variables, we aim to identify

those subgroups of adolescent girls that are at higher risk

for adolescent alcohol use.

Risk Factor for Adolescent Alcohol Use

Research has shown that early pubertal timing in girls is

associated with earlier onset of alcohol use (Deardorff et al.

2005), and higher alcohol use and heavy drinking

M. Verhoef (&) � R. J. J. M. van den Eijnden �I. M. Koning � W. A. M. Vollebergh

Faculty of Social and Behavioral Sciences, Utrecht University,

PO Box 80.140, 3508 TC Utrecht, The Netherlands

e-mail: [email protected]

123

J Youth Adolescence

DOI 10.1007/s10964-013-0075-6

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trajectories (Biehl et al. 2007), although several studies

only found significant results for a subsample of adoles-

cents. For example, Lynne-Landsman et al. (2010) only

found an effect for adolescents in high risk home envi-

ronments, with low levels of resources and high levels of

conflict being related to binge drinking. Heavy adolescent

alcohol use is problematic, as this is a risk factor for

multiple negative short- and long-term outcomes, such as

sexual assault, pregnancy, use of other substances and

traffic accidents (for a review, see Boden and Fergusson

2011). In addition, heavy alcohol use during adolescence is

associated with abnormalities in different areas of the brain

(Medina et al. 2008). The fact that these problem behaviors

continue into adulthood (Hayatbakhsh et al. 2008) under-

scores the significance of analyzing the effect of early

pubertal timing in more detail.

Several hypotheses have been put forward to explain the

effect of early pubertal timing on adolescent alcohol use.

According to the early-timing hypothesis (Stattin and

Magnusson 1990), early-maturing girls (i.e., girls with a

younger age at menarche) are particularly vulnerable to

adjustment difficulties in adolescence, because others

attribute greater maturity to them than warranted by their

chronological age, which is in contrast with their cognitive

and emotional levels of maturity. Consequently, early-

maturing girls may attempt to demonstrate maturity and

independence by displaying deviant behavior. One exam-

ple of such behavior is alcohol use during adolescence.

Drinking during this age period deviates from the basic

norms in society and can be considered as deviant (Goode

2010). Furthermore, adolescent alcohol use generates

negative reactions from others, in particular from parents

(Kristjansson et al. 2010), which also makes this behavior

deviant. In addition, it has been argued that adolescents

initiate or increase alcohol use because they want to display

independence to their parents and peers (Brody and Fore-

hand 1993). Thus, due to the desire of early-maturing girls

to display independence, it is expected that girls with a

younger age at menarche are at an increased risk of getting

involved in deviant behavior, such as alcohol use.

Previous studies investigating the association between

early pubertal timing and adolescent alcohol use rarely

distinguish between the onset and subsequent level of

alcohol use. One notable exception is the study of Costello

et al. (2007), who differentiate between alcohol use and

alcohol use disorder. Their results show that early matu-

ration is related significantly to alcohol use, but not to risk

of alcohol use disorder. However, as earlier onset of

alcohol use is related to more negative outcomes (Boden

and Fergusson 2011), examining the effect of earlier mat-

uration on onset of alcohol use is particularly interesting. It

can be argued that early pubertal timing is indeed of

importance in particular for the onset of alcohol use, as the

need to demonstrate maturity and independence, as

hypothesized by the early-timing hypothesis, decreases

over time (Stattin and Magnusson 1990). This is the case

because the gap between the chronological age and the

cognitive and emotional levels of maturity of early

maturing girls decreases when girls grow older. Therefore,

this study distinguishes between the onset and subsequent

level of adolescent alcohol use, making it possible to

examine whether the impact of early pubertal timing differs

for alcohol onset and subsequent drinking level. Yet, as

early pubertal timing has not constantly been found to be

associated to different graduations of alcohol use (e.g.,

Costello et al. 2007; Lanza and Collins 2002), it is

important to examine factors that contribute to the differ-

ential effect of pubertal timing on alcohol use, i.e.

moderators.

Contextual Amplification of the Effect of Early

Pubertal Timing

Since not every study found significant associations

between early pubertal timing and adolescent girls’ prob-

lem behavior, Ge and colleagues developed the contextual

amplification hypothesis to account for differential effects

of social and personal risk factors (Ge et al. 2011). This

hypothesis states that contextual factors moderate the

negative effects of early pubertal timing on problem

behaviors. Several of these contextual factors are addressed

in this study.

First, concerning the family environment, parenting

behavior is of interest. A lower level of parental monitoring

might give early-maturing girls the opportunity to associate

with older and/or deviant peers, which might lead to the

initiation of risk behaviors, including alcohol use (Westling

et al. 2008). It can be argued that the effect of alcohol-

specific parenting is stronger than that of general parenting

(Schelleman-Offermans et al. 2011), meaning that a lower

level of alcohol-specific rules set by parents might

strengthen the association between early pubertal timing

and adolescent alcohol use. Independent of early pubertal

timing, research has shown that adolescents with permis-

sive parents concerning adolescents’ alcohol use have an

increased risk of early adolescent drinking (Koning et al.

2010a) and heavy drinking trajectories (Van der Vorst et al.

2009). Alcohol-specific rules may work as a protective

factor against the negative association between early

pubertal timing and adolescent alcohol use. Consequently,

it is hypothesized that alcohol-specific rules moderate the

negative effect of younger age at menarche on adolescent

alcohol use.

A second important moderator within the family envi-

ronment is the extent to which the child provides infor-

mation to parents, i.e. children’s disclosure, as this might

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diminish the negative effects of early pubertal timing.

Fletcher et al. (2004) found that parental warmth and

control were positive predictors of perceived parental

knowledge. They argued that children with warm rela-

tionships with their parents are more likely to disclose

information about their personal domains to their parents.

In addition, child disclosure is found to be the primary

means by which parents obtain knowledge about their

children’s whereabouts and is related strongly to better

parent–child relationships (Kerr and Stattin 2000). Thus, a

child’s disclosure can be regarded as a proxy of family

support. It is hypothesized that low children’s disclosure

moderates the relationship between younger age at men-

arche and adolescent alcohol use, with low children’s

disclosure increasing the risk of alcohol use in early-

maturing girls. The relationship is hypothesized because

adolescent girls reporting high disclosure are expected to

have a lower need to demonstrate maturity and indepen-

dence, due to their better relationship with their parents.

Third, regarding school and peers, belonging to a same- or

mixed-sex group of peers influences the risk of deviant

behavior and psychological distress for girls. Prior studies have

shown that early-maturing girls in mixed-sex settings were

more involved in early substance use (Walls and Whitbeck

2011), delinquency (Caspi et al. 1993) and experienced more

psychological distress (Ge et al. 1996) than early-maturing girls

in all-girl settings. Previous research showed that early matu-

ration promotes affiliations with older boys (Caspi et al. 1993).

This may result in the initiation of a more mature lifestyle,

including experimentation with alcohol and tobacco (Stattin

and Magnusson 1990; Dick et al. 2000). In addition, Simmons

and Blyth (1987) have argued that early-maturing girls may

feel vulnerable due to sexual pressure exerted by older boys.

So, it seems that the gender composition or peer groups may

interact with the possible effects of age at menarche. Therefore,

it is hypothesized that there is a moderating effect of sex setting

on the relationship between younger age at menarche and

adolescent alcohol use, with early-maturing girls in classes with

a higher percentage of boys having an increased risk of alcohol

use in comparison with early-maturing girls in classes with a

higher percentage of girls.

These contextual moderators can also have differential

effects on the onset and subsequent level of adolescent

alcohol use. Based on the stronger hypothesized relation-

ship between early pubertal timing and the onset of

drinking (compared to level of alcohol use), we expect that

the contextual moderators also have a stronger effect on the

onset of adolescent alcohol use. So, we not only expect the

effects of early pubertal timing to be more pronounced in

adolescent girls with lower levels of alcohol-specific rules

and child disclosure, and in adolescent girls in classes with

a higher percentage of boys, but we also expect these

moderating effects to be stronger for the onset of

adolescent alcohol use, compared to the effect on the

drinking level of adolescents. The inclusion of these con-

textual factors is a notable contribution to the literature, as

this study appears to be one of the first to examine the

possible differential effects of risk factors on the onset as

well as the level of alcohol use, enabling us to examine the

effect of pubertal timing in more detail.

The Current Study

The primary aim of the present study is to examine the

relationship between younger age at menarche and ado-

lescent alcohol use in more detail by distinguishing the

onset of alcohol use and subsequent drinking level. Based

on previous research, it is expected that younger age at

menarche is of importance in particular for the onset of

alcohol use. In addition, moderating effects of this rela-

tionship by multiple psychosocial factors are examined,

with the expectation that the association between younger

age at menarche and adolescent alcohol use is stronger for

adolescent girls in high risk situations (with lower levels of

alcohol-specific rules and children’s disclosure, and in

classes with a higher percentage of boys). Moreover, we

expect that the moderating effects are stronger for onset of

alcohol use, compared with level of alcohol use.

Method

Design and Procedure

Data of this study are part of a longitudinal randomized clinical

trial called ‘‘Prevention of Alcohol Use in Students’’ (Koning

et al. 2009). Briefly, 80 randomly selected Dutch secondary

schools were invited by letter to participate in the study. Of the

invited schools, 19 were willing to participate. These schools

were randomly assigned to one of the three intervention con-

ditions, or to the control condition. For the present study, only

the female adolescents who were assigned to the control con-

dition were included. Data collection started at the beginning of

the first year in high school (T0; September/October 2006).

After 10 months, the first follow-up (T1) took place in May/

June 2007. The second follow-up (T2) was in May/June 2008

and the last wave (T3) in May/June 2009. Data collection took

place in the classroom, where digital questionnaires were

administered by trained research assistants.

Participants

Participants were 444 female adolescents, from four dif-

ferent schools. Due to initial non-response, either because

of their parents’ refusal or their absence from school on the

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day the questionnaire was administered, data of 14 girls

were missing. This resulted in 430 adolescent girls par-

ticipating in the first wave, with a mean age of 12.17 years

(range 11–14, SD = 0.50). The majority of the sample

(61.6 %) was enrolled in lower secondary vocational edu-

cation and 38.4 % was enrolled in higher general second-

ary and pre-university education. According to the Dutch

Central Bureau of Statistics, this division regarding edu-

cational level is representative for Dutch school-aged

adolescents (Dutch Central Bureau of Statistics 2006).

At the first follow-up, a total of 429 adolescent girls

(99.8 %) completed the follow-up measurement. At the sec-

ond and the third follow-up, there were respectively 379

(88.1 %) and 338 (78.6 %) adolescent girls still enrolled in

the study. Attrition analyses concerning alcohol use and

demographic variables showed firstly that adolescent girls

participating in every wave drank a lower average number of

alcoholic drinks per week at baseline (t(428) = 4.09,

p \ .001) than adolescent girls not participating in every

wave. Furthermore, participating adolescent girls were more

likely to be younger (t(428) = 3.08, p = .002) and were more

often in higher education (v2(1, N = 430) = 9.90, p = .002).

Measures

Alcohol Use

Adolescents’ alcohol use was measured using a quantity-

frequency measure, representing average weekly alcohol

use. Quantity was measured by asking girls how many

glasses of alcohol they usually drank on a weekday

(Monday to Thursday) and on a weekend day (Friday to

Sunday; Engels et al. 1999). Responses for weekdays

ranged from 0 to 11 or more glasses of alcohol, for

weekend days from 0 to 20 or more glasses of alcohol.

Frequency was measured by asking adolescent girls about

the number of days they usually drank alcohol, separately

for weekdays and weekend days (Engels and Knibbe

2000). Quantity-frequency was computed by calculating

the products of the number of glasses and the number of

days, after which the two products for week days and

weekend days were summed (Koning et al. 2011), the

maximum score being 104. A value of 1 or more indicates

that adolescent girls drank at least one glass of alcohol per

week. Onset of alcohol use was defined by dichotomizing

the continuous variable with ‘‘0’’ indicating girls who did

not drink alcohol and ‘‘1’’ indicating those who drank an

average of one or more glasses of alcohol per week.

Age at Menarche

Age at menarche was measured, at each wave, by asking

girls about onset of menarche (yes/no) and, if yes, their age

at first menarche (in year and months). Girls who respon-

ded in years only received the mean month value of girls of

the same age in years (Whincup et al. 2001). Previous

research showed that adolescent girls report their age at

menarche in a reliable and accurate way (Smolak et al.

2007). Still, to prevent any recall errors, we used infor-

mation from the first time girls reported age at menarche

(e.g., if onset of menarche occurred after the data collection

of wave 1, we used the information about age at menarche

from wave 2, not from wave 3). A higher value (age) on

this variable indicates that girls’ onset of menarche

occurred later.

Alcohol-Specific Rules

Alcohol-specific rules refer to the degree of restrictive rule-

setting by parents concerning alcohol use, as perceived by

the adolescent (Van der Vorst et al. 2005). Alcohol-specific

rules were measured by ten items (e.g., ‘‘I am allowed to

drink several glasses of alcohol when my parents are at

home’’ and ‘‘I am allowed to get tipsy when I am out with

friends’’). Items ranged from 1 (never) to 5 (always). These

items were reversely scored, with higher scores indicating

more restrictive rule-setting by parents. To obtain a total

score, the mean of the ten items was calculated, the max-

imum possible score being five. Cronbach’s alphas ranged

from .90 to .94 for the different waves.

Children’s Disclosure

Disclosure towards parents was measured using a five-item

questionnaire developed by Kerr and Stattin (2000; e.g.,

‘‘Do you tell your parents about school (how your courses

go, your relationships with teachers)?’’ and ‘‘Do you keep a

lot of secrets from your parents about what you do during

your free time?’’), ranging from 1 (never) to 5 (always).

Two items were reversely coded, to ensure that higher

scores are indicative of higher disclosure. Cronbach’s

alphas ranged from .71 to .76 for the different waves. For

the total score, the mean of the five items was computed,

the maximum possible score being five. As there were

barely any changes to the reported child disclosure between

the several time points, the mean over the four measure-

ments was used in the analyses.

Class Gender Composition

As for each respondent the gender was known, and each

respondent was assigned a class number, it was possible to

derive the gender distribution for each class at T0. Of this

gender distribution, the class gender composition was

computed, representing the percentage of girls in the class.

Each adolescent received a value, based on the percentage

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of girls in her class, the minimum possible score equals 0

and the maximum possible score equals 100. Classes in

Dutch secondary schools are differentiated by educational

level and, in addition, strongly organized by classrooms.

This means that students spend most of their school time

with the same peers who have a similar educational level.

Of course, contact with students from other classes at the

same grade (graduating class) is possible, but this is mostly

limited to recess, psychical education, and extracurricular

activities (De Bruyn and Cillessen 2006). Just as in the

majority of Western countries, classes in Dutch secondary

schools contain a mix of boys and girls (class gender

composition varied from 0.27 to 0.75). However, there are

some differences in school level, as there are more boys

enrolled in lower secondary vocational education and more

girls in higher general secondary and pre-university edu-

cation (Dutch Central Bureau of Statistics 2006).

Statistical Analyses

Descriptives were computed for the variables included in

the analyses. Both means and SD’s were computed for age

at menarche, the four alcohol quantity-frequency measures,

alcohol-specific rules, child disclosure and class gender

composition (%). In addition, Pearson correlations were

calculated to compute associations between these variables.

Next, onset of adolescent alcohol use was predicted using

separate hierarchical logistic multiple regressions, using

time-varying and time-invariant covariates. To predict onset

at T1, only the adolescent girls who did not start drinking on

T0 were selected. Age at menarche was entered in Step 1. In

Step 2, the time-varying covariate, alcohol-specific rules (at

T0), and the time-invariant covariates, child disclosure and

class gender composition were added. In Step 3, the inter-

actions between centered scores age at menarche and cen-

tered scores of the covariates were entered. These procedures

were repeated for onset of alcohol use at T2 and T3, hereby

using alcohol-specific rules at respectively T0, T1, and T2 as

time-varying covariates and selecting the adolescent girls

who did not start drinking at the previous time point.

Second, to predict the level of adolescent alcohol use, sep-

arate hierarchical linear multiple regressions were used, fol-

lowing the same procedure. For example, level of alcohol use at

T3 was only predicted for adolescent girls reporting alcohol use

at T2, using both time-varying and time-invariant covariates. In

the analyses concerning level of alcohol use, we controlled for

level of alcohol use of the previous time point(s). The model

used for the analyses is presented in Fig. 1.

For both moderation analyses, if an interaction proved to

be significant, simple slope analyses were conducted using

Hayes and Matthes’s (2009) MODPROBE approach. In

this way, regions in the range of the moderator variable can

be identified where the effect of the age at menarche on

adolescent alcohol use is statistically significant, following

the Johnson-Neyman technique. Missing values (varying

between 0.01 and 7.91 % of all values) were imputed using

expectation maximization (Acock 2005). To increase the

accuracy of imputing missing values, other items within the

same scale were used to predict the score of the missing

value. To reduce the influence of outliers (values [ 3 SD

from the mean), outlying cases (n = 15) were assigned the

value of the closest less extreme score (Tabachnick and

Fidell 2007). As we tested multiple models, we used the

Benjamini and Hochberg False Discovery Rate (Benjamini

and Yekutieli 2001) as correction method. All analyses

were performed using SPSS, version 20.0.

Results

Descriptives and Intercorrelations

Intercorrelations and descriptives are reported in Table 1. At

T0, 22.3 % of the adolescent girls had started drinking

Onset alcohol use T1a

Level alcohol use T1b

Onset alcohol use T2a

Level alcohol use T2bYounger age at menarche

Onset alcohol use T3a

Level alcohol use T3b

Alcohol-specific rules (time-varying)Child disclosure (time-invariant)

Class composition (time-invariant)

Fig. 1 Moderation model of the association between age at menarche, alcohol-specific rules, child disclosure, class gender composition and

adolescent girls’ alcohol use. a Only for non-drinking girls. b Only for drinking girls

J Youth Adolescence

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alcohol, increasing to 62.3 % at T3. Average weekly alcohol

use reported by the drinking adolescent girls also increased

from T0 to T3, from 2.45 to 7.04 glasses per week. However,

even though the percentage of drinkers increased from T1 to

T2, from 28.8 to 44.9 %, the average weekly alcohol use of

the drinking adolescent girls remained stable between these

two waves. Alcohol-specific rules decreased over time,

indicating that parents became less restrictive regarding

adolescent alcohol use. In addition, the standard deviation of

alcohol-specific rules increased over the different waves,

showing more variation in parental rules over time. Con-

cerning the intercorrelations, younger age at menarche was

related to less alcohol use only at T1 (r = -.24, p = .035).

Furthermore, alcohol-specific rules were related negatively

to alcohol use at all waves (r = -.22 to -.62).

Predicting Onset of Adolescent Alcohol Use

In Table 2, the main effects of the predictor variable, age at

menarche, and the moderator effects of alcohol-specific

rules, child disclosure and class gender composition are

presented separately for alcohol onset at T1, T2 and T3.

Interactions between age at menarche and the moderating

variables were examined and insignificant interactions

were deleted from the model; significant interactions with

age at menarche are presented in Table 2.

Onset of alcohol use at T1 was increased significantly by

age at menarche (B = -0.45, SE B = 0.17, OR = 0.64,

p = .048), indicating that early-maturing girls had a higher

probability to drink alcohol at T1. Furthermore, onset of

alcohol use at T1 was associated negatively with alcohol-

specific rules at T0 (B = -0.92, SE B = 0.33, OR = 0.40,

p = .006) and with child disclosure (B = -1.39, SE

B = 0.28, OR = 0.25, p \ .001). In addition to these main

effects, a significant interaction effect was found between

age at menarche and class gender composition (B =

-2.73, SE B = 1.38, OR = 0.06, p = .048). Additional

analyses showed that the effect of age at menarche was

only significant for adolescent girls in classes with a

moderate to high percentage of girls (scores [ 0.47,

n = 188). This interaction effect is plotted in Fig. 2. Sep-

arate lines refer to the effect of age at menarche on onset of

alcohol use, for different values of class gender composi-

tion. To determine these values, we used the results of the

MODPROBE approach, namely the lowest value of class

gender composition (0.47) where the effect of age at

menarche on onset of alcohol use is significant, the mean

value (0.58) and the highest value (0.75). This figure shows

that the interaction between age at menarche and class

gender composition is most relevant for predicting onset of

alcohol use in early adolescence, when girls are 13 years or

younger.

Concerning T2, onset of alcohol use was increased

significantly by age at menarche again (B = -0.33, SE

B = 0.15, OR = 0.72, p = .041). Onset of alcohol use at

T2 was related negatively to child disclosure as well

(B = -0.67, SE B = 0.26, OR = 0.51, p = .011). In

addition, one interaction effect proved to be significant,

namely between age at menarche and alcohol-specific rules

at T1 (B = -0.67, SE B = 0.30, OR = 0.51, p = .024).

Additional analyses showed that the effect of age at men-

arche was only significant for adolescent girls with

restrictive parents (scores [ 4.43, n = 212), and not for

adolescent with lenient parents. In Fig. 3 this interaction

effect is presented, with separate lines for the lowest value

of alcohol-specific rules (4.43) where the effect of age at

Table 1 Intercorrelations and descriptive statistics of model variables (N = 430)

Variable 1 2 3 4 5 6 7 8 9 10 11

1. Age at menarche (in years) –

2. Alcohol use T0a (n = 96, 22.3 %) -.12 –

3. Alcohol use T1a (n = 128, 28.8 %) -.24* .44** –

4. Alcohol use T2a (n = 193, 44.9 %) -.16 .21** .54** –

5. Alcohol use T3a (n = 268, 62.3 %) -.03 .23** .55** .58** –

6. Alcohol-specific rules T0 .11* -.61** -.48** -.19* -.22** –

7. Alcohol-specific rules T1 .15** -.20 -.49** -.32** -.26** .56** –

8. Alcohol-specific rules T2 .09 -.26* -.35** -.41** -.28** .48** .65** –

9. Alcohol-specific rules T3 .05 -.16 -.35** -.35** -.35** .42** .55** .68** –

10. Child disclosure T0–T3 .12* -.26* -.22* -.22* -.27** .20** .30** .31** .25** –

11. Class gender composition T0 .03 -.04 -.06 .06 .17** -.03 .06 .01 .03 .01 –

M 12.73 2.45 5.76 5.70 7.04 4.53 4.36 4.10 3.84 4.02 0.50

SD 0.96 2.67 8.09 7.95 8.23 0.56 0.68 0.76 0.95 0.58 0.12

Skewness 0.05 1.37 1.23 1.17 1.08 -1.04 -1.01 -0.95 -0.62 -0.64 0.33

a Calculated using only the drinking adolescent girls at each wave

* p \ .05, ** p \ .01

J Youth Adolescence

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J Youth Adolescence

123

Page 8

menarche on onset of alcohol use is significant, the mean

value (4.83) and the highest value (5.00). This figure shows

that the effect of the interaction between age at menarche

and alcohol-specific rules at T1 changes during adoles-

cence. Strict alcohol-specific rules are related to a higher

probability of onset of alcohol use in early adolescence, but

the opposite seems to be the case in later stages of ado-

lescence. Yet, the differences between the different values

of alcohol-specific rules are quite small.

In contrast with onset of alcohol use at T1 and T2, onset at

T3 was not related significantly to age at menarche. Results

showed that onset of alcohol use at T3 was only related

negatively to alcohol-specific rules at T2 (B = -0.81, SE

B = 0.29, OR = 0.45, p = .005). No further significant

effects were found for onset of alcohol use at T3.

Taken together, results show that the probability of

onset of adolescent alcohol use was increased significantly

by younger age at menarche, but only for onset at T1 and

T2. In addition, alcohol-specific rules were related nega-

tively to onset at T1 and T3, child disclosure to onset at T1

and T2. Moderation analyses showed that a higher risk of

onset of alcohol use in early-maturing girls existed only for

girls with high levels of alcohol-specific rules and for girls

in classes with a moderate to high percentage of girls.

Predicting the Level of Adolescent Alcohol Use

In Table 3, main effects and significant interaction effects

are presented for the variables predicting the level of ado-

lescent alcohol use in girls that are already drinking, sepa-

rately for the level of alcohol use at T1, T2 and T3. In these

analyses, we controlled for previous alcohol consumption.

The level of alcohol use at T1 was associated negatively with

alcohol-specific rules at T0 (B = -2.90, SE B = 1.32,

p = .030, b = -.24) and with previous alcohol use. No

further effects were found for level of alcohol use at T1.

The level of alcohol use at T2 was associated positively

only with previous alcohol use. No significant effects were

found for either age at menarche or the moderator

variables.

The level of adolescent alcohol use at T3 was associated

positively with class gender composition (B = 12.53, SE

B = 3.36, p \ .001, b = .19), with a higher percentage of

girls in classes being related to higher alcohol use. Previous

Fig. 3 Visualization of the

effect of the interaction between

age at menarche and alcohol-

specific rules at T1 on onset of

alcohol use at T2, presented for

different values of the

moderating variable

Fig. 2 Visualization of the

effect of the interaction between

age at menarche and class

gender composition on onset of

alcohol use at T1, presented for

different values of the

moderating variable

J Youth Adolescence

123

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alcohol use was also a significant predictor. Next to these

main effects, the interaction between age at menarche and

class gender composition proved to be significant

(B = 10.57, SE B = 3.71, p = .005, b = .14). Additional

analyses showed that the effect of age at menarche was only

significant for adolescent girls in classes with a moderate to

high percentage of girls (scores [ 0.41, n = 136). In Fig. 4

this interaction effect is presented, with separate lines for the

lowest value of class gender composition (0.41) where the

effect of age at menarche on onset of alcohol use is signifi-

cant, the mean value (0.57) and the highest value (0.75). This

figure shows that the interaction between age at menarche

and class gender composition is particularly of importance in

later stages of adolescence, as the differences between the

separate lines increase with age.

Taken together, the results indicate that younger age at

menarche is not a significant predictor of the level of

alcohol use. Previous alcohol use, however, is related

positively to level of alcohol use. For predicting the level

of alcohol use at T1, a negative association was present

with alcohol-specific rules at T0. Child’s disclosure proved

to be a significant predictor for level of alcohol use at T2,

Table 3 Results of hierarchical linear regression analyses of age at menarche, alcohol-specific rules, behavioral problems, child disclosure and

class gender composition on the level of adolescent alcohol use

Predictor Level alcohol use T1

(n = 96)aLevel alcohol use T2

(n = 128)bLevel alcohol use T3

(n = 193)c

B (SE) b B (SE) b B (SE) b

Step 1

Age at menarche -1.38 (0.69) -.18 -0.37 (0.59) -.05 0.94 (0.47) .02

Level of alcohol use T0 1.46 (0.26)*** .50 0.79 (0.27)** .25 -0.26 (0.38) -.05

Level of alcohol use T1 0.70 (0.09)*** .67 0.46 (0.11)*** .32

Level of alcohol use T2 0.70 (0.08)*** .55

Step 2

Alcohol-specific rules T0 -2.90 (1.32)* -.24 0.10 (1.18) .01 -0.92 (1.05) -.06

Alcohol-specific rules T1 -0.89 (0.91) -.09 -0.01 (0.87) -.00

Alcohol-specific rules T2 0.63 (0.73) .06

Child disclosure T0–T3 -1.45 (0.91) -.14 -1.58 (0.79)* -.15 -0.28 (0.70) -.02

Class gender composition T0 -0.06 (5.17) -0.00 5.46 (4.06) 0.10 12.53 (3.36)*** .19

Step 3

Age at menarche * Class gender composition 10.57 (3.71)** .14

a Step 1 (including age at menarche and prior level alcohol use): adjusted R2 = .28. Step 2 (1 ? main effects): D adjusted R2 = .04, p = .049b Step 1: adjusted R2 = .33. Step 2 (1 ? main effects): D adjusted R2 = .01, p = .192c Step 1: adjusted R2 = .52. Step 2: D adjusted R2 = .04, p = .011. Step 3 (2 ? interaction effects): D adjusted R2 = .02, p = .005

* p \ .05, ** p \ .01

Fig. 4 Visualization of the

effect of the interaction between

age at menarche and class

gender composition on level of

alcohol use at T3, presented for

different values of the

moderating variable

J Youth Adolescence

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class gender composition for level of alcohol use at T3.

Moderation analyses showed that the effect of age at

menarche on level of alcohol use at T3 existed only for

girls in classes with a moderate to high level of girls.

Discussion

Younger age at menarche is associated with a higher risk of

involvement in deviant behaviors, such as alcohol use (e.g.,

Deardorff et al. 2005). However, previous studies rarely

differentiated between the onset and level of drinking, or

investigated the relationship between age at menarche and

alcohol use across different subgroups. The focus of this

study was to examine the relationship between age at

menarche and alcohol use among adolescent girls, while

distinguishing between the onset and subsequent level of

alcohol use. Findings show that, as hypothesized, younger

age at menarche (i.e., earlier pubertal timing) is a risk factor

for the onset of adolescent alcohol use, but not for the

subsequent progress in consumption of alcohol use. Results

further show that younger age at menarche increased the risk

of onset of alcohol use only at T1 and T2, when girls were

aged 13 and 14, indicating that early-maturing girls initiate

alcohol use at a younger age than other girls. However, age

at menarche is not related to onset of alcohol use at T3,

which indicates that the risk factor early pubertal timing is

only manifest at the early stages of adolescence. This is

consistent with previous research (e.g., Kaltiala-Heino et al.

2011). Later in adolescence, when more girls have reached

puberty, the differences between earlier- and later-maturing

girls may disappear when most girls started to mature. At

this point, early-maturing girls are not treated differently by

others anymore, which is in accordance with the early-tim-

ing hypothesis. This might clarify the disappearance of the

effect of age at menarche later in adolescence. Furthermore,

girls were on average 15.32 years old at T3. At this age,

adolescents are reaching late adolescence, a period in which

normative rates of adolescent drinking accelerate quickly

(Chartier et al. 2010). Studies have shown that adolescent

alcohol use is relatively common in this age period (e.g.,

Johnston et al. 2009), in particular in the Netherlands (Si-

mons-Morton et al. 2010). Thus, the fact that alcohol use

becomes more common later in adolescence might also

explain the disappearance of the effect of age at menarche.

As the negative effects of pubertal timing might differ

between individuals, we examined alcohol-specific rules,

children’s disclosure and class gender composition as

additional risk factors. Contrary to our expectations, the

negative effect of age at menarche on onset of alcohol use

exists mainly for girls with a high level of alcohol-specific

parental rules. Apparently, in the presence of additional

risk factors, younger age at menarche does not have any

additional explanatory power. Multiple studies have indeed

demonstrated the strong effects of other risk factors on the

onset of adolescent alcohol use, such as parenting behavior

(Ge et al. 2002; Westling et al. 2008) or adverse childhood

experiences (Rothman et al. 2008). However, future

research is needed to replicate this finding. The fact that

younger age at menarche stands out as a risk factor only in

adolescent girls with a low level of additional risk factors

could be explained by the social push hypothesis, stating

that when children lack social factors that ‘‘push’’ to

problem behavior, biological factors are more likely to

explain this behavior. So, due to the low level of social risk

factors in these girls, younger age at menarche becomes an

important predictor. Another possibility is that there is a

limit to how strict parents can be concerning adolescents’

alcohol use. Previous research showed that authoritarian

parents were less successful in reducing adolescents’

alcohol use than authoritative parents (Adalbjarnardottir

and Hafsteinsson 2001). In the case of too strict alcohol-

specific rules, early-maturing girls could start to oppose

their parents by starting to drink alcohol. However, more

research is needed to examine whether these arguments

could explain the effects found in low risk girls.

Looking at the other outcome examined in the present

study, the level of alcohol use of girls that have started

drinking, results showed that the previous level of alcohol

use was the most important predictor. Only three other

main effects were found, namely of alcohol-specific rules

(T1), children’s disclosure (T2), and class gender compo-

sition (T3), with a lower level of parental rules, a lower

level of children’s disclosure, and a higher percentage of

girls being related to more alcohol use. Apparently, risk

factors have more explanatory power for the onset of

alcohol than for the subsequent alcohol consumption,

which is in line with our hypotheses. One possible expla-

nation could be that, once adolescent girls started drinking

alcohol, and discovered the effects of it, subsequent alcohol

use is internally motivated. For example, girls could con-

tinue their alcohol use because they enjoy the relaxing

effect. Studies have indeed found that adolescents use

alcohol to deal with the stress in their lives (e.g., Bray et al.

2001). However, as no measures concerning stress were

included in this study, future research is needed to examine

this potential explanation.

Lastly, class gender composition appeared to be of

interest. The results show that younger age at menarche

was related to higher levels of alcohol use only for

adolescent girls in classes with a moderate to high per-

centage of girls. This result, however, is not in line with

previous literature, which stated that early-maturing girls

were more at risk when they were surrounded by many

boys. It might be that adolescent girls feel safer to drink

with same-sex peers, which might increase the level of

J Youth Adolescence

123

Page 11

alcohol they consume. Such reasoning was provided by

girls using marijuana in the study of Haines et al. (2009).

It was stated that, in a mixed-sex setting, girls have to be

careful, as boys want to get girls high for sex. This may

also apply to alcohol use: in all-girl settings, such caution

is not necessary and girls feel more secure and thus drink

more alcohol. This might explain why the risk of a higher

level of alcohol use exists only for early-maturing girls in

classes with a moderate to high percentage of girls. These

findings (especially for predicting alcohol use at T3) may

be related to the Dutch school system. This is because

from the first year of secondary school, when most pupils

are 12–13 years of age, the Dutch educational system is

already highly differentiated. Depending on their teacher’s

advice and the results of a test in the last year of primary

education, pupils enter different types of secondary edu-

cation. The educational levels are: pre-vocational educa-

tion, lower general secondary education, upper-general

secondary education and pre-university education. Most

adolescents remain in the same level of education

throughout high school. In addition, classes in Dutch

secondary schools are strongly organized by classrooms,

indicating that students spend most of their school time

with the same peers who have a similar educational level.

As contact with students from other classes is limited, this

might explain the long-lasting effect of class gender

composition. Yet, little is known about the effect of class

gender composition, more research is needed to replicate

these findings and provide additional explanations.

Limitations

This study has several limitations. The results of are based

upon adolescent self-report data. Even though the use of

multiple informants is preferred, self-report measures have

proven to be reliable concerning alcohol use (Koning et al.

2010b) and age at menarche (Smolak et al. 2007) and are

often used in previous studies. Secondly, more detailed

information about peer influences is preferred. This is

because class gender composition was hypothesized to

influence the relationship between age at menarche and

alcohol use, due to the influence of male peers. However,

we were unable to test this hypothesis directly, as no direct

information was available about interactions with peers.

Ideally, one would like to know the proportion of male

peers of the adolescent girls, including information about

their drinking behavior. Furthermore, as peer relationships

can also be formed outside the school environment, more

specific peer related factors should be included in future

research, making it possible to examine the influence of

male peers more directly. Lastly, even though we tried to

incorporate the higher level structure of classes by exam-

ining the effect of class gender composition, future

research might benefit from examining this multilevel

structure more clearly by using multilevel methods.

Implications

The results of this study have various implications. First,

more insight has been provided concerning the relationship

between age at menarche and alcohol use, showing that it is

important to distinguish between onset and subsequent

level of alcohol use. Results indicate that age at menarche

only influences onset during early and middle adolescence;

not during late adolescence when alcohol use becomes

normative. So, when wanting to prevent the initiation of

alcohol use, it is important to look at the age of adolescent

girls. Furthermore, although this study is not the first to

distinguish between the onset and level of alcohol use (e.g.,

Costello et al. 2007; Lanza and Collins 2002), it appears to

be the first to look at the moderating role of several risk

factors. Results indicate that younger age at menarche

increases the risk of onset of alcohol use only in adolescent

girls with a low level of additional risk factors. In addition,

the negative effect of age at menarche on subsequent

drinking behavior is present only in adolescent girls in

classes with a moderate to high percentage of girls. This

indicates that interventions targeting adolescent alcohol use

need to pay attention to these additional risk factors. Lastly,

we showed that the effect of age at menarche on onset of

alcohol use exists only for those adolescent girls reporting

restrictive alcohol-specific rules. Parents should be made

aware of the possible negative side-effects of too strict

rules, hereby reducing the risk of onset of alcohol use for

early-maturing girls.

Conclusions

The current study adds to previous research by distin-

guishing between the onset and subsequent level of ado-

lescent alcohol use, in examining the effect of age at

menarche. In addition, several contextual moderators were

examined. Results indicated that younger age at menarche

was related to the onset of alcohol use only in early and

middle adolescence. This effect was only present in low

risk girls, with high levels of alcohol-specific rules and in

classes with a moderate to high percentage of girls. These

results hold valuable information for interventions aiming

to decrease adolescent alcohol use. For example, taking

into account the role of alcohol-specific rules, the aware-

ness of being too strict as a parent should be increased. In

addition, our results indicate that keeping adolescent girls

away from older boys might also not be the most effective

strategy, as effects were strongest in classes with a mod-

erate to high percentage of girls. In conclusion, our results

J Youth Adolescence

123

Page 12

show that it is necessary to also focus on low risk ado-

lescent girls, as low risk girls, particularly those with a

younger age at menarche, can also become involved in

problematic behavior during adolescence.

Author contributions MV coordinated and drafted the manuscript,

performed the statistical analyses and the interpretation of the data.

RJJME participated in the design of the study and helped with the

interpretation of the data and the draft of the manuscript. IMK

coordinated the study, performed the measurements and helped to

draft the manuscript. WAMV participated in the design and the

coordination of the study and helped to interpret the data and draft the

manuscript. All authors read and approved the final manuscript.

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Author Biographies

Melissa Verhoef is a Ph.D. candidate at the Faculty of Social and

Behavioral Sciences at Utrecht University. Her research interests

include child and adolescent well-being and family relationships.

Regina J. J. M. van den Eijnden is an Assistant Professor at the

Faculty of Social and Behavioral Sciences at Utrecht University. She

received her Ph.D. at the University of Groningen in 1998. Her main

research interests are adolescents’ and young adults’ addiction

behaviours.

Ina M. Koning is a Postdoctoral Researcher at the Faculty of Social

and Behavioral Sciences at Utrecht University where she also

obtained her Ph.D. in 2011. Her research interests include the

prevention of alcohol use in adolescents and the influence of parents

on adolescents’ drinking behavior.

Wilma A. M. Vollebergh is a Professor at the Faculty of Social and

Behavioral Sciences of Utrecht University. She received her Ph.D. at

Utrecht University in 1991. She is the director of research and

program coordinator of ‘‘Youth in Changing Cultural Contexts’’. Her

research focuses on developmental trajectories of mental health and

substance (ab)use in adolescence and early adulthood.

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