Behavior Genetics, Vol. 29, No. 6, 1999

A Twin Study of Drinking and Smoking Onsetand Latencies from First Use to Regular Use

M. C. Stalling,1 J. K. Hewitt,1 T. Beresford,2 A. C. Heath,3 and L. J. Eaves4

Received 7 Sept. 1999—Final 10 Nov. 1999

The early onset of alcohol and tobacco use has been associated with increased risk for later sub-stance abuse and dependence problems. This study investigated genetic and environmental in-fluences on age at onset of alcohol and tobacco use by examining twin resemblance for severalretrospectively reported onset milestones including age at first use, age at first alcohol intoxi-cation experience, and age at regular use. In addition, we also examined the latency betweenage at first use and age at regular use of tobacco and alcohol. The subjects were a volunteersample of older adult twins 50 to 96 years of age. MZ twin correlations for age at first alcoholuse and age at first tobacco use were .57 and .44, respectively, compared to .45 and .37 for DZsame-sex twins. MZ twins correlated .30 and .26 for the latencies between first use and regularuse of alcohol and of tobacco, while DZ correlations were -.01 and .05, respectively. Biomet-rical model-fitting results confirmed that familial resemblance for age at first use for both al-cohol and tobacco was largely the result of shared environmental factors, while the latencies be-tween first use and regular patterns of use were more genetically influenced. These findings addto a growing body of literature suggesting that initiation of substance use is influenced prima-rily by environmental rather than genetic factors.

INTRODUCTION

A number of studies of normal population samples havesuggested that early experimentation with alcohol and/ortobacco is associated with greater severity and persist-ence of subsequent substance use (Barnes et al, 1992;Chou and Pickering, 1992; Clapper et al, 1995; Fer-gusson et al., 1994; Gonzalez, 1989; Grant and Daw-son, 1997; Hawkins et al, 1992,1997; Hays et al, 1986;1987; Jessor and lessor, 1975; 1977; Kandel, 1975; Kan-del and Faust; 1975, Kandel et al, 1992; Newcomb andBentler, 1988; Pedersen and Skrondal, 1998; Robins and

1 Institute for Behavioral Genetics, University of Colorado, Boulder,Colorado 80309.

2 Department of Psychiatry, Department of Veterans Affairs, Denver,Colorado 80220.

3 Department of Psychiatry, Washington University School ofMedicine, St. Louis, Missouri 63110.

4 Department of Human Genetics, Medical College of Virginia, Rich-mond, Virginia 23298.

Przybeck, 1985; Welte and Barnes, 1985; Yamaguchiand Kandel, 1984a, b; Yu and Williford, 1992), and pre-vention efforts have been designed specifically to pre-vent or delay initiation of alcohol and tobacco use (Kan-del et al, 1992; Williams et al, 1995). However, thereis also evidence that substance use normally peaks inlate adolescence and early adulthood (Jessor et al, 1991;Kandel and Raveis, 1989; Labouvie, 1996) and then de-creases without significant negative consequences formost youth (Jessor et al, 1991; Labouvie et al, 1997;Newcomb and Bentler, 1988). Thus, some early sub-stance experimentation is probably normative andresearch efforts have begun to focus more on identi-fying risk factors that may help to distinguish betweenadolescent-limited and life course-persistent patternsof substance involvement.

The fact that age at onset, per se, appears to beonly weakly related to patterns of use and problem sub-stance use in later adulthood may be partly explained

4090001-8244/99/1100-0409$16.00/0 © 1999 Plenum Publishing Corporation

KEY WORDS: Twin study; drinking onset; smoking onset; latency from first to regular use; substanceabuse; genetics.

410 Stallings, Hewitt, Beresford, Heath, and Eaves

by evidence from behavioral genetic studies suggest-ing that environmental factors play an important rolein abstinence versus alcohol use (Han et al., 1999;Heath and Martin, 1988; Heath et al, 1989, 1991a, b;Koopmans and Boomsma, 1996; Prescott et al., 1994a;Rose et al, 1999; but see also Heath, 1999; Kaprio et al,1987; Partanen et al, 1966). In contrast, there is sub-stantial evidence that genetic factors may make agreater contribution to familial resemblance for alco-hol consumption patterns such as frequency and quan-tity of use (Carmelli et al, 1990; Clifford et al, 1984;Gabrielli and Plomin, 1985; Kaprio et al, 1987; Par-tanen et al, 1966; Prescott et al, 1994a) and for prob-lem drinking and alcoholism (Cloninger et al, 1981;1988; Heath et al, 1997a, b; Kaij, 1960; Kaprio et al,1987; Kendler et al, 1992; McGue, 1993; McGue et al,1992; Pickens et al, 1991; Prescott et al, 1994b).

A similar pattern of findings can be noted in thetobacco use literature, although genetic influences onthe initiation versus abstinence of tobacco use may bemore substantial than has been reported for alcohol use.For example, several twin studies have suggested thatthe heritability for smoking initiation is substantial,with estimates ranging between 46 and 84% (Carmelliet al, 1992; Heath and Madden, 1995; Heath and Mar-tin, 1993; True et al, 1997). In terms of regular smok-ing, the data are very consistent with the alcohol con-sumption data in indicating that genetic factors appearto play a more important role than environmental in-fluences in predicting which individuals who becomesmokers progress to long-term persistent smoking(Heath and Madden, 1995; Heath et al, 1998; True et al,1997). Substantial genetic influences underlying twinresemblance for nicotine dependence have also beenreported (True et al, 1999).

Although there is a considerable body of literatureon smoking and drinking patterns in adults, less is knownabout the determinants of age at onset and how quicklyone moves from first use to heavier use or problem use.Studies of substance abuse risk suggest that early prob-lem use, which implies a short latency between first ex-posure and regular use, is an important risk factor forlater adult alcoholism and illicit substance abuse. Fur-ther, one might speculate that sensitivity to the reward-ing properties—and/or insensitivity to the negative as-pects—of tobacco and alcohol might be related to howquickly one makes the transition from initial exposureto regular use, and physiological sensitivity to alcoholhas been proposed as a potential mediator of the geneticinfluence on alcoholism risk (Schuckit, 1980, 1985,1994; Schuckit and Smith, 1997; Pollock, 1992).

In the present study we used retrospective reportsfrom adult twins to examine the genetic and environ-mental determinants of age at onset for first alcohol andtobacco use, as well as the latency in years betweenfirst use and regular use of these substances. We hy-pothesized that environmental influences would beshown to be more important in determining twin re-semblance for age at first use, while genetic factorsmight make a greater contribution to twin resemblancefor the latency between first use and regular use.

METHOD

Subjects

The sample for this study was a subset of twinsfrom a volunteer population-based sample ascertainedfor research on tobacco and alcohol use. The originalsample pool was restricted to Caucasian twins bydesign (for details on sample ascertainment see Heathet al, 1993). Subjects were adult twins 50 to 96 yearsof age, originally recruited between 1985 and 1989through a newsletter published nationally by theAmerican Association of Retired Persons (AARP).Questionnaires were mailed to 12,118 individuals andreturned by 9476 subjects, a response rate of about78%. If either twin responded to this original re-cruitment, both pair members were mailed a follow-up questionnaire between late 1990 and early 1991.Former responders who were known to be deceased,who requested to be removed from the mailing list,or for whom previous mailings were returned withouta forwarding address were excluded from the secondmailing, resulting in a potential subject pool of7622 individuals.

Follow-up questionnaires were returned by4956 subjects representing a response rate of 65% (ap-proximately 41% of the originally ascertained sample).From this sample, 835 subjects younger than age50 and 2 with invalid questionnaires were excluded, re-sulting in a final sample of 4119 individuals. Data forthis study came from this follow-up sample. The sam-ple was 74% female (3049 women and 1070 men) witha mean age of 66.8 (SD=7.9) years. Males were slightlyolder (M=67.3, SD=7.9) than females (M=66.5,SD=7.9) on average, but there was substantial varia-tion in age within gender groups. Males, and particu-larly male DZ twins, were underrepresented in this sam-ple, which is common in volunteer twin samples. Thepreponderance of females probably reflects both theearlier mortality of men and the higher tendency offemales to participate in volunteer studies.

Substance Initiation and Transitions to Regular Use 411

Demographic data were obtained from the initialassessment and are available for 4040 individuals (98%)in the final sample. At the time of original ascertainment,72% of the sample was married or cohabitating, withmales more likely to be married or cohabitating (88%)than females (67%). In addition, respondents were rela-tively well educated, with 52% of the females and 65%of the males having some education beyond high school.The sample was generally of middle-class SES, with ap-proximately 43% reporting an annual income of at least$35,000 (for a more detailed description of this samplesee Prescott et al, 1994a).

Attrition analyses, done previously (Prescott et al,1994a), compared responders to the first assessment onlyto subjects who completed both questionnaires. Resultsindicated that the final sample tended to have higher ed-ucational attainment, higher family income levels, andamong men, were more likely to be retired. The finalsample was not shown to be further selected on currentalcohol consumption, but individuals with a history ofalcohol abuse were probably underrepresented.

Twin Sample

From the full sample (N = 4119), there were 1287twin pairs (2,574 individuals) for whom sufficient in-formation was available to make zygosity judgments.Zygosity determination was made through question-naire procedures assessing the degree of physical sim-ilarity among the twins. The classification scheme wasconservative, with misclassifications most likely to bemonozygotic (MZ) twins incorrectly assigned as dizy-gotic (DZ) twin pairs. Therefore, any biasing effectswould be in the direction of overestimating the simi-larity of DZ twins, which would lead to the underesti-mation of the importance of genetic influences in ouranalyses. The classification of same-sex twins based onsimilar questionnaire items has demonstrated approxi-mately 95% accuracy compared to blood typing (Ced-erlof et al., 1961; Kasriel and Eaves, 1976). For moredetails regarding zygosity determination in this sam-ple, see Prescott et al. (1994a).

Genetic analyses used only twin pairs with com-plete data. Twin pairs where either twin had never triedalcohol or tobacco (complete abstainers)—or for whomage at onset was not reported—were omitted from therelevant genetic analyses. Further, individuals whonever reported regular use of alcohol or tobacco(weekly use of alcohol and daily use of tobacco) wouldnot have transition latency data (latency in years be-tween age at first use and age at regular use). Thus,

twin pairs where one or both of the twins never pro-gressed to regular use were necessarily excluded fromthe relevant transition latency analyses. Analyses wereperformed on the alcohol and tobacco use measuresseparately, however, use of both substances was not re-quired. The numbers of twin pairs utilized for our ge-netic analyses of the substance use milestones and tran-sition latencies are shown in Tables III and IV,respectively.

There is no "correct" method for dealing withmissing data in our analyses, and the omission of sub-jects who have not obtained particular alcohol or to-bacco use milestones can be problematic, particularlyin younger samples where censoring is likely. How-ever, given the age range of our subjects (50 to 96 yearsof age), a strength of our sample is that most of oursubjects have passed through the age of risk for ob-taining these use milestones. That is, it is unlikely thatmany of our participants who have not yet begun usingalcohol or tobacco regularly will do so at some laterpoint in their lives. The omission of complete abstain-ers (i.e., subjects who had never tried alcohol or to-bacco even once) is problematic if abstinence is sim-ply the extreme end of a single liability dimension foralcohol and tobacco consumption. However, existingevidence does not provide strong support for includingabstainers in a single liability dimension for alcoholconsumption (Heath et al., 1991a,b) or cigarette con-sumption (Meyer et al., 1992).

Measures

Alcohol Use. Alcohol use milestones were as-sessed using the following questionnaire items embed-ded within the 16-page follow-up (1990-1991) mail-outsurvey concerning health, habits, and opinions: (1) Atwhat age did you first drink alcohol—first time ever?(2) At what age did you first become intoxicated? and(3) At what age did you start drinking alcohol at leastonce a week? Two transition latency indices were com-puted by subtracting (1) age at first intoxication expe-rience from age at first use ever and (2) age at weeklyalcohol use from age at first use ever. The latency be-tween age at first intoxication and age at weekly usewas not computed because some subjects reported thattheir first intoxication experience occurred after the ageat which they reported weekly use (i.e., this was not a"normative" transition for many subjects).

Tobacco Use. Similar tobacco use milestoneswere assessed using the following questionnaireitems:(l) At what age did you smoke your first ciga-

412 Stallings, Hewitt, Beresford, Heath, and Eaves

rette? (2) At what age did you start smoking at leastone cigarette a day? and (3) At what age did you startsmoking at least a half-pack of cigarettes (10 cigarettes)a day? Two latency scores were computed by sub-tracting age of regular use (at least one cigarette a dayand half a pack or more per day) from age at first use.The latency between smoking at least one cigarette aday and smoking half a pack per day was not computedbecause age at heavier use sometimes preceded age atdaily use of at least one cigarette. This occurred be-cause some subjects responded to the questionnaireitems consistent with their decreased daily use over thelifecourse (i.e., patterns of heavy use sometimes pre-ceded later patterns of reduced use). Since this transi-tion was not normative for all subjects, it was not uti-lized. Further, since our questionnaire surveyspecifically referred to cigarette use only, individualsusing other tobacco products could not be assessed.

Data Transformation. Age at onset for the vari-ous drinking and smoking milestones was positivelycorrelated with age at assessment in our sample (cor-relations ranged between .11 and .16). That is, therewas a modest trend for older individuals to estimatelater ages at onset than younger individuals. This mayrepresent real age cohort differences, but there is alsoevidence from prospective longitudinal data to suggestthat there is a systematic tendency for most individu-als to shift their estimates of age at onset upward asthey get older (Labouvie et al, 1996). Age at onset alsocorrelated negatively with gender (correlations rangedbetween -.15 and -.27), with men reporting earlier agesof onset for all of our smoking and drinking milestonesthan women. Unfortunately, our samples sizes were in-sufficient to examine age and gender effects in our ge-netic analyses, so these effects were partialed from allof our measures prior to genetic analysis. That is, ourgenetic analyses were performed on residual scores foreach of the onset milestones and latency measures, par-tialing out the effects of gender, linear and quadratricage effects, and the interactions between these effectsusing standard regression procedures. In addition, ourage at onset and latency measures all showed signifi-cant positive skewness, so all scores were further trans-formed to approximate normality using a rank normal-izing procedure (Blom, 1958).

Statistical Analyses

We used standard univariate biometrical twinmodels (Neale and Cardon, 1992) to estimate the ge-netic and environmental contributions to population

variance in the age at onset for three alcohol use mile-stones (age at first use ever, age at first intoxication ex-perience, and age at which regular weekly alcohol usebegan), three tobacco use milestones (age at first useever, age at which daily smoking of at least one ciga-rette per day began, and age at which daily smoking ofhalf a pack or more per day began), and the latency inyears between these various use milestones. As notedabove, two of the six possible transition latencies werenot examined in detail because they were not norma-tive transitions (i.e., the ordering of the events was notuniform enough to make use of the data as represent-ing a hard transition from one milestone to the next).

Under the basic twin model, individual differencesin the age at which different use milestones occur, andin the latencies between different use milestones, areassumed to arise from four potential latent sources: ad-ditive genetic effects (A); nonadditive genetic effects(D); shared environmental effects (C), which includeall nongenetic influences that increase the similaritybetween the members of a twin pair; and nonshared en-vironmental effects (E), which include all other non-genetic effects (including measurement error) that con-tribute to within-pair differences among twins. MZtwins are genetically identical, thus they share, or cor-relate perfectly for, all additive and nonadditive geneticeffects. On average, DZ twins share half the additiveeffects of their genes and have a one-in-four chance ofsharing nonadditive genetic effects at any given locus.Thus, the additive and nonadditive genetic effects in-fluencing the members of DZ twin pairs are expectedto correlate .5 and .25, respectively. Given equivalentenvironmental influences on both types of twins, sharedenvironmental influences are expected to correlate 1.0across the members of a twin pair for both zygositygroups. Other implicit assumptions of the basic twinmodel are that genetic and environmental latent effectsare uncorrelated and combine additively and that mat-ing is random in the parent generation of the twins.

Given these theoretical expectations derived fromquantitative genetic theory (Falconer, 1989), a modelfor the expected twin covariance structure can be spec-ified and compared to the observed twin covariancestructure using standard structural equation modelingprocedures. Univariate models were fit directly to theobserved 2x2 twin covariance matrices for each of ourmeasures and model parameters were estimated usingmaximum-likelihood procedures operationalized in thestatistical package MX (Neale, 1998). The fit of alter-native nested models was evaluated using standard X2

difference tests (for details see Neale and Cardon, 1992).

Substance Initiation and Transitions to Regular Use 413

Note that with twins reared together in the samehousehold, as is the case in our sample, not all of thelatent sources of variance described above can be esti-mated simultaneously. Shared environmental influences(C) are confounded with nonadditive genetic influences(D) in such data. Thus, the influence of one source can-not be estimated without assuming the absence of theother. Nevertheless, the plausibility of obtained pa-rameter estimates and the fit of alternative models tothe observed data (though no formal statistical basis forpreferring one model over another is available whencomparing nonnested models) can provide guidelinesfor model selection. To evaluate the relative fit ofnonnested models we used Akaike's (1970) informa-tion criterion (AIC).

RESULTS

Descriptive Analyses

Table I shows the mean ages at onset for the un-transformed alcohol and smoking use milestones forthe full sample and for males and females separately.Untransformed data are shown here for descriptive pur-poses only. All statistical analyses were performed ontransformed scores.

Almost 90% of our subjects had at least tried al-cohol and about half had tried cigarettes (i.e., reportedan age at onset for first use ever). There were no sub-stantial gender differences in the proportions of ourmale and female subsamples who had used alcohol atleast once (93% of the men and 88% of the women),while greater differences are evident regarding ciga-rette use (69% of the males reported at least trying cig-arettes, compared to only 46% of the females). Nearlytwice as many men as women reported regular use ofalcohol and tobacco, and age at onset for all of thedrinking and smoking milestones occurred earlier formen than women. For both men and women first useand regular use of cigarettes occurred earlier, on aver-age, than first use and regular use of alcohol.

Table I also shows mean age-at-onset milestonesfor weekly versus nonweekly alcohol users and fordaily versus nondaily cigarette users. Age at onset forfirst alcohol use in subjects reporting weekly use pre-cedes age at first use in nonweekly alcohol users byabout 2 years. In contrast, when comparing daily cig-arette smokers (defined in the bottom portion of Table Ias smoking at least 10 cigarettes per day) and nondailycigarette users (all others who had tried cigarettes atleast once), age at first use in daily smokers precededthat in nondaily smokers by less than a year. Age at

first use was essentially equivalent between the groupswhen daily smoking was defined as smoking at leastone cigarette per day, so it is not shown. In fact, only17% (N=366) of our subjects who had ever tried ciga-rettes (N=2135) did not progress to smoking at leastone cigarette daily at some point in their lives, and only33% (N-697) did not progress to smoking a half packor more. These data indicate a relatively high level ofregular smoking in our older age cohort, particularlyfor males. In comparison, over half (57%) of our sub-jects who ever tried alcohol did not progress to weeklyalcohol use.

Table II shows the untransformed mean transitionlatencies between the different drinking and smokingmilestones. Mean latencies (defined as the differencein years between milestones) are shown for the fullsample and for males and females separately. Note that,on average, about 6 years elapsed between first alco-hol use and first intoxication experience, and about10 years between age at first use and age at whichweekly alcohol use began for those progressing toweekly use. Latencies for males are about 2 yearsshorter, on average, than for females. For tobacco userswho progressed to smoking at least one cigarette perday, the mean latency was about 2 years between ageat first use and age at daily smoking. About 4 years, onaverage, elapsed between age at first use and age atsmoking a half-pack or more daily for those progressingto that level of smoking. In contrast to the gender dif-ferences in latencies between alcohol use milestones,latencies between smoking milestones were about equalfor men and women.

Twin Correlations

Age-at-Onset Milestones. Twin correlations andcovariance matrices utilized in our genetic analyseswere computed from the transformed measures. Be-cause MZ twins are genetically identical, while DZtwins, on average, share only about half of their seg-regating genes, significantly higher MZ than DZ cor-relations would indicate genetic influences underlyingtwin resemblance. Equivalent MZ/DZ correlationswould connote shared environmental mechanisms.Comparisons of the MZ and DZ twin correlations inTable III suggest that there are substantial shared en-vironmental influences on the age at onset, or age atfirst use ever, for both alcohol and tobacco. MZ twincorrelations also were not substantially higher than DZcorrelations for age at first alcohol intoxication expe-rience or age at daily tobacco use (at least one cigarette

414 Stallings, Hewitt, Beresford, Heath, and Eaves

Table I. Age at Onset for Drinking and Smoking Milestones

Use milestone

AlcoholAge at first use everAge at first intoxicationAge at weekly useb

Among non-weekly users onlyAge at first use everAge at first intoxication

Among weekly users onlyAge at first use everAge at first intoxication

TobaccoAge at first use everAge at daily use (1 cig/day )c

Age at daily use (10 cigs/day)d

Among nondaily users onlyAge at first use ever

Among daily (1 cig/day) usersAge at first use ever

Age at assessmentMedian age at assessment

Full sample(N = 4119)

%a

894637

10034

10078

524335

100

100

M

18.923.127.9

19.823.0

17.623.2

17.519.921.5

17.2

17.566.866

SD

6.57.910.9

7.07.4

5.48.2

5.75.96.0

5.9

5.67.9

Note. M, mean age at use milestone; SD, standard deviation.a Percentage of sample reaching the use milestone.b Weekly alcohol use — drink alcohol at least once per week.c Smoke at least one cigarette per day.d Smoke at least half a pack (10 cigarettes) per day.

Males (N = 1070)

%

936953

10055

10089

696053

100

100

M

17.221.224.2

18.321.9

16.320.8

15.618.419.8

15.2

15.667.367

SD

6.06.18.7

7.25.7

4.75.7

4.74.24.1

5.9

4.57.9

Females (N = 3049)

%

883832

10028

10072

463729

100

100

M

19.624.430.3

20.223.5

18.425.0

18.520.722.6

18.0

18.666.566

SD

6.58.7

11.5

6.97.5

5.69.3

5.96.56.8

5.8

5.97.9

Table II. Mean Ages for Drinking and Smoking Transition Latency Measures

Full sample

Transition latency measurea

AlcoholAge at first use ever to age at first intoxicationAge at first use ever to age at weekly use *

TobaccoAge at first use ever to age at daily use (1 cig/day )c

Age at first use ever to age at daily use (10 cigs/day)d

M

6.110.2

2.44.4

SD

7.49.9

4.55.1

Note. M, mean latency (years); SD, standard deviation.a Latency - difference in years between age at onset for use milestones.b Weekly alcohol use - drink alcohol at least once per week.c Smoke at least one cigarette per day.d Smoke at least half a pack (10 cigarettes) per day.

Males

M

5.07.9

2.74.3

SD

5.98.3

4.04.5

Females

M

6.911.6

2.24.4

SD

8.210.6

4.75.4

per day), and the MZ correlation for age at heavier reg-ular cigarette use (half a pack per day or more) was es-timated to be lower than the corresponding DZ twincorrelation. In general, our pattern of twin correlationsis consistent with substantial shared environmental con-tributions to the timing of these substance use mile-

stones. Only age at weekly alcohol use appears to besubstantially influenced by genetic effects.

Transition Latencies. Table IV shows the MZ andDZ twin correlations for the latency (difference inyears) between first use of alcohol and tobacco and lateruse milestones for these substances. Comparison of the

Substance Initiation and Transitions to Regular Use 415

Table III. MZ and DZ Twin Correlations for Age-at-Onset Milestones

Onset milestone

AlcoholAge at first use everAge at first intoxicationAge at weekly useb

TobaccoAge at first use everAge at daily use (1 cig/day)c

Age at daily use (10 cigs/day )d

rMZ

.57 ± .04

.43 ± .07

.40 ± .08

.44 ± .06

.41 ± .07

.35 ± .08

(NY

(563)(222)(158)

(312)(240)(174)

rDZ

.45 ± .07

.41 ±.10

.18 ±.13

.37 ± .08

.34 ±.10

.50 ±.12

(NY

(240)(96)(62)

(136)(97)(69)

Note. rMZ = MZ twin (product-moment) correlation ± standard error of estimate;rDZ = DZ twin (product-moment) correlation ± standard error of estimate.a N = number of twin pairs with complete data.b Weekly alcohol use — drink alcohol at least once per week.c Smoke at least one cigarette per day.d Smoke at least half a pack (10 cigarettes) per day.

Table IV. MZ and DZ Twin Correlations for Transition Latency Variables

Transition latency variablea

AlcoholAge at first use ever to age at first intoxicationAge at first use ever age at weekly use

TobaccoAge at first use ever to age at daily use (1 cig/day)Age at first use ever to age at daily use (10 cigs/day)

rMZ

.32 ± .07

.30 ± .08

.26 ± .07

.37 ± .08

(N)b

(212)(151)

(235)(170)

rpz

.26 ±.11-.01 ±.14

.05 + .10

.12 ±.12

rMZ = MZ twin (product-moment) correlation ± standard error of estimate;rDZ = DZ twin (product-moment) correlation ± standard error of estimate.a Latency — difference in years between age at onset for use milestones.b N = number of twin pairs with complete data.

(N)b

(89)(58)

(97)(69)

pattern of MZ and DZ twin correlations suggests thatthe latency between age at first alcohol use and age atwhich weekly alcohol use began appears to be morestrongly influenced by genetic factors than the timingor age at which these use milestones occurred (shownin Table III). A similar pattern is also evident for thesmoking latencies as well. Note that the DZ correla-tions for two of the latency measures are lower thanmight be expected given additive genetic influences,suggesting that nonadditive genetic factors may play arole. However, special MZ environmental factors (i.e.,a greater correlation between the environments experi-enced by MZ twin pairs compared to DZ twins) cannotbe ruled out as an alternative explanation. Note that be-cause there are fewer DZ twins than MZ twins, the stan-dard errors around the DZ twin correlations are largerthan for the MZ correlations. Thus, the relatively lowmagnitudes of the DZ correlations may simply reflectchance sampling fluctuations.

Special MZ Environment. To examine the possi-bility that the relevant environments shared by MZ andDZ might not be equivalent, we examined twin simi-larity for twins in frequent contact with each other (atleast weekly) versus those in less frequent contact. Ifthe environmental influences on the transition latenciesare more highly correlated among MZ pairs than DZpairs, one might expect that MZ twins in more frequentcontact with one another would show greater similar-ity than those in less frequent contact. Our question-naire data included two items assessing current (at timeof assessment) frequency of contact (1) How often doyou and your twin see each other? and (2) If you liveapart, how frequently do you and your twin contacteach other by telephone or letter? Responses werecoded by a 6-point Likert scale for the first item (l=welive together; 2=almost everyday; 3=at least once aweek; 4=once or twice a year; 5=a few times a year;6=once a year or less) and a 5-point scale for the sec-

416 Stallings, Hewitt, Beresford, Heath, and Eaves

ond item (omitting the first response category). Becauseof our relatively small samples, we were unable tocompute meaningful twin correlations separately foreach category, so the categories were collapsed intotwo groups: (1) at least weekly contact and (2) less fre-quent contact.

We did observe MZ/DZ differences in contact forthese groups. Most twins were now living apart. Onlyabout 5% of MZ twin pairs and 4% of the same-sex DZpairs reported still living together at the time of as-sessment. Approximately 32% of MZ twins reportedphysically seeing their cotwin at least weekly, com-pared to only 20% of DZ same-sex twin pairs. In termsof contact by phone or letter for those living apart, 53%of MZ twins reported at least weekly contact, comparedto 33% of the DZ twins. However, comparing twin cor-relations for the two frequency of contact groups didnot show a general pattern of greater similarity fortwins in more frequent contact. For the transition la-tency between age at first alcohol use and age at weeklyuse, MZ twins who saw their cotwin at least weekly(N=44 pairs) correlated .33, compared to .29 for MZtwins seeing their cotwin less frequently (N=107 pairs).However, there was a significant difference when ex-amining frequency of contact by phone or letter. HereMZ twins in weekly contact (N=64 pairs) correlated .44for the transition latency, compared to only .10 for MZtwins in less frequent contact (N=71 pairs). A mixedpattern was also found for the two smoking transitionlatency measures. For the transition between first to-bacco use and smoking at least one cigarette per day,the MZ correlations were .15 and .34 (N = 78 and 156pairs) and .26 and .25 (N = 115 and 103) for the high-and low-contact groups for frequency of seeing eachother and for contact by phone or letter, respectively.Regarding the transition from first use to smoking atleast half a pack of cigarettes or more per day, the sameMZ twin correlations were .36 and .37 (N = 52 and118 pairs) and .33 and .42 (N = 84 and 74 pairs). Ingeneral, the patterns among the MZ twins are incon-clusive regarding the potential for special MZ envi-ronment effects. DZ twin sample sizes for the frequencyof contact groups were too small for adequate com-parisons but also showed a mixed pattern. It is impor-tant to point out, however, that our frequency of con-tact data referred to patterns of cotwin contact at thetime of assessment (median age=66), not during the de-velopmental periods when the majority of our twinswere initiating substance use. Because patterns of con-tact are likely to change over the life course, frequencyof contact during adolescence and early adulthood

would have provided a more relevant test for specialMZ environment effects.

Model-Fitting Results

Onset Milestones. Table V shows the results offitting univariate biometrical twin models to each ofthe drinking and smoking milestones. The best-fittingmodels by the AIC are shown in boldface type. Ourmodel-fitting analyses confirm the importance ofshared environmental influences on the age at whichthese substance use milestones occurred. For all of themilestones except age at first alcohol use and age atweekly alcohol use, dropping additive genetic effectsfrom the full ACE model did not result in a significantdecrement in model fit by x2 difference test. Thus, forfour of the six substance use milestones, twin resem-blance could be adequately explained by a model in-cluding only shared environmental influences. Al-though additive genetic effects did contribute to twinresemblance for age at first use of alcohol, the estimateof shared environmental effects wals also substantial—accounting for approximately 35% of the phenotypicvariance in age at first use, compared to 21% attribut-able to additive genetic effects.

No model provided a satisfactory fit to the age atweekly alcohol use data by x2 test, but the best-fittingmodel by AIC suggested the importance of genetic fac-tors and absence of shared environmental influences inexplaining twin resemblance for the onset of weeklyalcohol use. Examination of the expected and observedMZ and DZ covariance matrices for this milestone in-dicated twin 1 and twin 2 differences in variance, andgreater DZ than MZ variances were responsible for thepoor model fit. However, since the DZ sample was rel-atively small (62 pairs) and this pattern was not foundfor any of the other use milestones, alternative ad hocmodels were not explored.

Transition Latencies. Univariate model-fitting re-sults for each of the four transition latencies are shownin Table VI. In contrast to the findings presented inTable V regarding the timing or age at which the dif-ferent substance use milestones occurred, the latencyin years between age at first alcohol use—or first to-bacco use—and the age at which regular weekly drink-ing or daily smoking occurred appears to be moregreatly influenced by genetic factors. A simple addi-tive genetic model was adequate to explain twin re-semblance for three of the four transition latencies.Shared environmental effects made a contribution tothe latency between first alcohol use and first intoxi-

Substance Initiation and Transitions to Regular Use 417

Table V. Model-Fitting Results: Alcohol and Tobacco Use Milestones

Model

AlcoholAge at first use

ACEa

(CI95)AECE

Age at first intoxicationACEAECEa

(CI95)Age at weekly use

ACEAEa

(CI95)CE

TobaccoAge at first use

ACEAECEa

(CI95)Age at daily use (1 cig/day)

ACEAECEa

(C/95)

Age at daily use (10 cigs/day)ACEAECEa

(CI95)

h2

.21(.02-.44)

.58—

.09

.46—

.43

.43(.29-.55)

—

.14

.46

—

.15

.43—

.00

.41—

c2

.35(.14-.53)

—.54

.35—.43

(.33-.51)

.00—

.31

.30—.42

(.34-.49)

.26—.39

(.30-.48)

.40—.40

(.29-.50)

e2

.43(.38-.49)

.42

.46

.56

.54

.57(.49-.67)

.57

.57(.44-.71)

.69

.56

.54

.58(.51-.66)

.59

.57

.61(.52-.70)

.60

.59

.60(.50-.71)

X2

0.35

10.324.91

1.655.311.90

13.3613.36

19.78

1.194.741.90

2.434.233.07

3.029.943.02

df

3

44

344

34

4

344

344

344

P

.95

.04

.30

.65

.26

.76

<.01.01

<.01

.76

.32

.75

.49

.38

.55

.39

.04

.55

AIC

-5.65

2.32-3.09

-4.36-2.69-6.10

7.365.36

11.78

-4.81-3.26-6.10

-3.57-3.77-4.93

-2.981.94

-4.98

Note. (CI95) = 95% confidence intervals for parameter estimates; A = additive genetic effects; C = shared environmental effects; E = nonsharedenvironmental effects; h2 = proportion of variance explained by additive genetic effects; c2 = proportion of variance explained by shared envi-ronmental effects; e2 = proportion of variance explained by nonshared environmental effects.a Best-fitting model by AIC criteria.

cation experience only. Again, the relatively low DZtwin correlations for two of the transition latencies mayindicate the possibility of nonadditive genetic effectsor special MZ environment effects, but given our rel-atively small DZ twin samples, there was insufficientpower to detect these influences.

DISCUSSION

Numerous behavioral genetic studies have inves-tigated the extent to which genetic and environmentalfactors influence tobacco and alcohol abstinence andsmoking and drinking consumption patterns in adult-hood (for a review see Heath, 1999). Much less, how-ever, is known about the determinants of age at onset

and how quickly one makes the transition from initialuse to regular or problem use. In this study we used ret-rospective reports from adult twins to estimate themagnitude of the genetic and environmental sources ofvariance in age at onset for first tobacco and alcoholuse and for the transition latency in years between ageat first use and age at regular use. We hypothesized thattwin resemblance for age at onset would be morestrongly influenced by shared environmental factors,while twin resemblance for the latency between firstuse and regular use might be influenced more by ge-netic factors.

Our data generally support both hypotheses. Forage at first cigarette use estimates of the proportion ofvariance explained by additive genetic effects (h2),

418 Stallings, Hewitt, Beresford, Heath, and Eaves

Table VI. Model-Fitting Results: Latencies from First Use to Regular Alcohol and Tobacco Use

Transition model

Alcohol

h2 c2 d2

Age at first use to age at first intoxicationACEAECEa

(CI95)

.11

.33—

(

.21—.30

.19-.40)

———

Age at first use to age at weekly useADEAEa

(CI95)Tobacco

.00

.28(.13-.43)

——

.31—

Age at first use to age at daily use (I/day)ADEAEa

(CI95)

.00

.24(.12-.35)

——

.25—

Age at first use to age at daily use (10/day)ACEAEa

(CI95)CE

.37

.37(.23-.49)

—

.00—

.30

——

—

e2X2 df P AIC

.68

.67

.70(.60-.81)

0.841.831.07

344

.84

.77

.90

-5.16-6.18-6.93

.69

.72(.57-.87)

5.657.17

34

13.13

-.35-.83

.75

.76(.65-.88)

4.054.60

34

.26

.33-1.95-3.40

.63

.63(.51-.77)

.70

4.284.27

8.25

34

4

.23

.37

.08

-1.72-3.72

.25

Note:(CI95) = 95% confidence intervals for parameter estimates; A = additive genetic effects; C = shared environmental effects; D = nonaddi-tive genetic effects; E = nonshared environmental effects; h2 = proportion of variance explained by additive genetic effects; c2 = proportion ofvariance explained by shared environmental effects; d2 = proportion of variance explained by nonadditive genetic effects; e2 = proportion ofvariance explained by nonshared environmental effects.a Best-fitting model by AIC criteria.

shared environmental effects (c2), and nonshared envi-ronmental effects (e2) obtained from the full ACEmodel were 14, 30, and 56%, respectively. Droppingadditive genetic effects resulted in a minimal and non-significant decrement in model fit (x2 change = .17,p = .40). Dropping shared environmental effects yieldeda poorer fit to the data—though the X2 difference wasalso not significant, at p = .05 (x2 change = 3.55,p = .06).The best-fitting model by AIC required only shared en-vironmental effects to explain twin resemblance for ageat onset of first cigarette use. For age at first alcoholuse, the full ACE model was necessary to obtain an ac-ceptable fit to the data. Shared environmental influ-ences were estimated at 35% and the contribution ofadditive genetic influences on twin resemblance for ageat first alcohol use was estimated as 21%. Our findingsfor onset of alcohol use are similar to those reportedby Prescott and Kendler (1999), though they reportsomewhat stronger evidence for genetic effects, par-ticularly in females (h2 = .36 and c2 = .16 in women,h2 = .22 and c2 = .23 in men).

In general, our results suggest that shared envi-ronmental factors make a substantial contribution totwin resemblance for age at onset for first tobacco and

first alcohol use. Further, this general pattern was foundfor five of the six substance use milestones we exam-ined. That is, not only did shared environment explaina sizable proportion of the variance in age at onset ofuse, but also our data suggest that similar environ-mental processes underlie twin similarity for the tim-ing of the first alcohol intoxication experience, as wellas when daily smoking occurs. Only resemblance forage at regular drinking, defined as at least weekly al-cohol use, appeared to be substantially influenced bygenetic factors. These findings indicate that shared en-vironmental factors may explain most of the differencesbetween families in the timing of many substance usemilestones. They also suggest that early experimenta-tion and even the age at onset for regular tobacco useare likely to be better indicators of familial cultural in-fluences than of biological vulnerability or risk for per-sistent substance use.

In contrast, three of the four transition latencies weexamined showed little evidence for shared environ-mental influences on twin resemblance. Only the tran-sition from first alcohol use to first intoxication expe-rience appeared to be substantially influenced byenvironmental factors. This may reflect, in part, the fact

Substance Initiation and Transitions to Regular Use 419

that for many subjects (20% of those who had used al-cohol) their first experience with alcohol was also theirfirst intoxication experience, but it also suggests that anearly age at onset for first intoxication experience is notlikely to be an important indicator of biological risk formore persistent alcohol use. For the other three transi-tions we examined, a simple additive genetic model wassufficient to explain twin resemblance for the transitionlatencies. These data suggest that how quickly onemakes the transition from first use to regular use of to-bacco and alcohol may be more genetically mediatedthan the timing or onset of the transitions themselves.However, special MZ environment effects could not beruled out as an alternative explanation of the data.

Future research would benefit from prospectivelongitudinal data where transitions could be assessedwithout relying on long-term recall of substance usemilestones or events. Although a number of studieshave examined familial resemblance for substance usetransitions, to our knowledge, no other studies to datehave examined twin resemblance for transition laten-cies between first use and other patterns of use or prob-lem use. How quickly one moves from one stage to an-other may be more predictive of later substance usepatterns than simply whether or not an individual makesa particular transition. Further, physiological sensitiv-ity to alcohol has been proposed as a potential media-tor of the genetic influence on alcoholism risk(Schuckit, 1980,1985, 1994; Schuckit and Smith, 1997;Pollock, 1992). Clearly, sensitivity to the rewardingproperties—and/or insensitivity to the negative as-pects—of tobacco and alcohol would be expected to berelated to how quickly one makes the transition frominitial exposure to regular use.

Limitations

A number of methodological limitations of the cur-rent study should be discussed. First, this study reliedon the retrospective reporting of the age at onset forvarious substance use events or milestones. Particularlyin a sample of older individuals (median age at as-sessment, 66 years), such data are likely to be influ-enced by reporting biases (Brewer, 1988; Henry et al.,1994; Robins et .al, 1985). However, it is unlikely thatsuch biases would be substantially different for MZ andDZ twins; it would simply introduce measurement errorin recall for all participants. Obviously, prospective lon-gitudinal data with shorter recall intervals would bepreferable. However, an important advantage of thissample was that most individuals were past the age of

highest risk for initiating alcohol and tobacco use, andlifetime versus current patterns of use were utilized, socensoring problems would be expected to be minimalcompared to younger samples. Further, although exactages at onset may not be recalled accurately, studiesinvestigating the reliability of retrospectively reportedage at onset suggest that the relative rank ordering ofsubjects is probably fairly stable (Henry et al., 1994;Labouvie et al, 1997).

Second, our samples sizes were relatively small,particularly for examining transition latencies. Al-though our genetic analyses suggested that a simple ad-ditive genetic model underlying twin resemblance forthree of the four transition latencies could not be re-jected, there was relatively low power to test alterna-tive models. The observed pattern of MZ and DZ twincorrelations suggests that the potential for nonadditivegenetic effects and/or special MZ twin environmentalinfluences should be investigated in larger samples.Further, our sample sizes restricted our ability to ex-amine gender differences in our genetic analyses. Heathand Martin (1988) have reported gender differences inthe genetic and environmental factors influencing theonset of alcohol use in a sample of Australian adulttwins. In our analyses, the small number of males pre-cluded tests of gender differences.

It should also be reemphasized that our sample wasan older cohort, born between 1904 and 1937. The en-vironmental culture in the United States regarding smok-ing and drinking practices has changed considerablysince the time when the majority of our subjects passedthrough the period of greatest risk for initiating alcoholor tobacco use. In addition, 75% of our sample werewomen and our subjects were generally of middle-classSES. These sample characteristics should be consideredwhen interpreting our results, particularly with regard tosmoking and drinking behaviors for which gender dif-ferences in prevalence and exposure are known to exist.

Finally, in the basic twin model it is assumed thatmating is random in the parents of the twins for thephenotypes of interest. Evidence suggests that the as-sumption of random mating for drinking and smokingbehaviors is incorrect, thus some proportion of the vari-ance attributable to shared environment in our analy-ses is likely due to assortative mating in the parents ofour twins.

ACKNOWLEDGMENTS

This research was supported in part by NIAAAGrant AA-08672, NIDA Grants DA-11015 and DA-

420 Stallings, Hewitt, Beresford, Heath, and Eaves

10540, and the Research Center for Basic and ClinicalScience Studies of Alcoholism from the Department ofVeterans Affairs (VA Award V554P-3828/3829).

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Edited by Richard J. Rose