Prenatal alcohol and marijuana exposure

Neurotoxicology and Teratology 24 (2002) 309 – 320 www.elsevier.com/locate/neutera

Prenatal alcohol and marijuana exposure: Effects on neuropsychological outcomes at 10 years Gale A. Richardsona,*, Christopher Ryana, Jennifer Willforda, Nancy L. Daya, Lidush Goldschmidtb a

Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, 3811 O’Hara Street, Pittsburgh, PA 15213, USA b Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA Received 15 August 2001; received in revised form 13 December 2001; accepted 19 December 2001

Abstract This report from a longitudinal study of the effects of prenatal alcohol and marijuana exposure investigates whether these drugs affect neuropsychological development at 10 years of age. Women were recruited from a medical assistance prenatal clinic and interviewed about their substance use at the end of each trimester of pregnancy, at 8 and 18 months, and at 3, 6, 10, 14, and 16 years. Half of the women were African American, and half were Caucasian. The women were generally from lower socioeconomic status families and had obtained high school degrees. At the 10-year follow-up, 593 children completed a neuropsychological battery, which focused on problem solving, learning and memory, mental flexibility, psychomotor speed, attention, and impulsivity. Prenatal alcohol use was found to have a significant negative impact on learning and memory skills, as measured by the WRAML. Prenatal marijuana exposure also had an effect on learning and memory, as well as on impulsivity, as measured by a continuous performance task. The effects of prenatal alcohol and marijuana exposure persisted when other predictors of learning and memory were controlled. We continue to follow these offspring into the adolescent years when further neuropsychological deficits may become evident. D 2002 Elsevier Science Inc. All rights reserved. Keywords: Prenatal alcohol exposure; Prenatal marijuana exposure; Learning and memory; Impulsivity; Executive function

1. Introduction Prenatal alcohol and marijuana use affect many aspects of child and adolescent development. Prenatal alcohol exposure has been reported to be associated with deficits in the following domains: overall intellectual development and school achievement [6,23,42,61], memory [6,41,43,47,56,63,66], visual/spatial abilities [25,40,47,55], attention [6,32,47, 56,62,66], impulsivity [25,56,62,64], and problem-solving skills [7,39,47,56,60,65]. Deficits in executive functioning, a construct that includes the ability to plan, focus attention, solve problems, and use goal-directed behaviors [37,70], have also been found both in individuals with Fetal Alcohol Syndrome (FAS) and in individuals who were exposed to lower levels of drinking [7,8,30,31,39,57,66].

* Corresponding author. Tel.: +1-412-681-3482; fax: +1-412-6811261. E-mail address: [email protected] (G.A. Richardson).

Thus, prenatal alcohol exposure has detrimental effects on numerous aspects of neuropsychological development, although the specific abnormalities that have been reported are inconsistent. In addition, questions remain about the effects of the pattern of the exposure. Streissguth et al. [61,63] found that binge drinking (  5 drinks/occasion) and the number of drinks per occasion were better predictors of some deficits, while average ounces of absolute alcohol per day was a better predictor of other deficits [64]. One of our previous reports showed that average daily use of alcohol was a better predictor of growth at 18 months than was frequent heavy drinking [10]. It remains to be explored whether this is true for other outcomes. Compared to the amount of research concerning the effects of prenatal alcohol exposure, there is limited research on the long-term effects of prenatal marijuana exposure. In the Ottawa Prenatal Prospective Study (OPPS), prenatal marijuana use was associated with significantly lower scores on the verbal and memory domains of the McCarthy Scales of Children’s Abilities at 4 years of age [15]. At 5 and 6 years

0892-0362/02/$ – see front matter D 2002 Elsevier Science Inc. All rights reserved. PII: S 0 8 9 2 - 0 3 6 2 ( 0 2 ) 0 0 1 9 3 - 9

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of age, however, there were no effects of prenatal marijuana use on the overall cognitive, verbal, or memory domains of the McCarthy Scales [14]. At ages six to nine, after controlling for the home environment and personality variables, there were no effects of prenatal marijuana exposure on IQ, visual– motor tracking, visual discrimination, or visual memory tasks in a subsample of the OPPS [46]. There were also no prenatal marijuana effects on overall IQ and basic visuoperceptual skills at the 9- to 12-year follow-up, but tasks thought to reflect executive functioning, such as visual – motor integration, nonverbal concept formation, and problem solving, were affected [16,19]. At 13 – 16 years of age, however, prenatal marijuana exposure was not associated with aspects of attention, such as flexibility, encoding, and focusing [17]. In a report from our Maternal Health Practices and Child Development Project (MHPCD), prenatal marijuana exposure had a negative effect on short-term memory at 3 years of age [11]. At our 6-year follow-up, prenatal marijuana use was associated with more errors of commission, an indication of impulsivity, and with fewer omission errors, an indication of better attention [34]. By contrast, Fried et al. [18] found an association between prenatal marijuana exposure and increased omission errors at 6 years and at 13– 16 years [17], but found no relation at 9 –12 years of age [19]. The inconsistencies in these results could be due to differences in sociodemographic characteristics, drug use patterns, or different assessment instruments between the two samples. The purpose of this report is to investigate whether prenatal exposures to alcohol and marijuana affect neuropsychological development at 10 years of age. The effects of prenatal tobacco exposure on neuropsychological performance at 10 years in this cohort have been reported separately [9]. Other factors also affect neuropsychological performance and must be considered, such as the child’s age, gender, intelligence level, and anxiety, as well as the parent’s socioeconomic level and intellectual ability [37]. We hypothesized that prenatal alcohol exposure would be associated with deficits in the areas of memory, attention and impulsivity, problem solving, and psychomotor skills. We also hypothesized that prenatal marijuana use would be associated with deficits in problem solving and with increased impulsivity. We predicted that these deficits would persist after controlling for other factors associated with the outcomes.

2. Methods 2.1. Sample selection and study design The study sample consists of women and their offspring who are participants in the MHPCD Project. The study was approved by the Institutional Review Boards of the MageeWomens Hospital and the University of Pittsburgh. Women attending the prenatal clinic at the Magee-Womens Hospital were interviewed when they came in for their fourth or fifth

prenatal month examination. A total of 1360 women who were 18 years of age or older were interviewed. Two samples were selected from the initial interview to study the effects of prenatal alcohol and marijuana exposure on the offspring. All women who drank three or more drinks per week and a random sample of women who drank less than this amount were selected into the alcohol cohort. All women who used two or more joints of marijuana per month during the first trimester and a random sample of women who used less than this amount were selected for the marijuana cohort. Women could be in either or both cohorts. For this report, the two cohorts were combined. Information about alcohol, marijuana, and other substance use during the first, second, and third trimesters of pregnancy was collected at the initial interview, at the seventh prenatal month, and at 24 – 48 h postdelivery, respectively. The women were interviewed again at 8 and 18 months, and at 3, 6, 10, 14, and 16 years postpartum. All interviews included questions about maternal substance use, social and psychological status, and the environment of the study child. At each phase, the growth, cognitive development, temperament, and behavioral characteristics of the offspring were assessed using age-appropriate measurements. The 10-year follow-up was conducted from 1994 through 1997. 2.2. Sample characteristics At birth, 763 live singleton infants and their mothers participated in the study. From birth to the 10-year phase, five children died and three children were placed for adoption. At the 10-year phase, 8 mothers lost custody and the children could not be traced, 40 mothers refused to participate, 46 families moved out of state, and 25 were lost to follow-up. The 636 subjects interviewed at the 10-year follow-up represented 91% of the eligible subjects and 83% of the birth cohort. Seven percent of the children were not in the custody of their biological mother. In these cases, the current caretaker was interviewed. Children with conditions that interfered with testing were excluded from these analyses. These included: cerebral palsy (n = 3), mental retardation/severe developmental disability (n = 5), color blindness or severe visual impairment (n = 8), and deafness (n = 1). Three children were excluded because the examiners rated the testing conditions as detrimental or seriously detrimental due to the impact of the child’s medication on performance and 23 children did not complete any of the neuropsychological assessments for a variety of reasons including refusal, time constraints, or home visits. Thus, the final cohort for this analysis included 593 caregivers and children. The children who did not complete the 10-year assessment (n = 43) were older (10.9 vs. 10.5 years, P < .01) and had fewer illnesses (0.6 vs. 1.0 illnesses, P < .05) than those who did complete the assessment (n = 593). The mothers who did not complete the 10-year assessment used less alcohol currently (0.7 vs.

G.A. Richardson et al. / Neurotoxicology and Teratology 24 (2002) 309–320

1.1 drinks/day, P < .05) and less marijuana in the first trimester (0.2 vs. 0.4 joints/day, P < .01) than did those who completed the 10-year follow-up phase. There were no other significant differences in prenatal or current substance use or sociodemographic characteristics between children who were included in this analysis and those who were not. The subjects in the study were of low socioeconomic status. Forty-seven percent of the women were Caucasian and 53% were African American. At 10 years postpartum, the median family income was US$1200 per month, and 63% of the women worked and/or studied outside of home. On average, at 10 years postpartum, the women were 35.3 years old (range = 28 – 69) and they had 12.3 years of education (range = 7 –18). Fifty-three percent of the women reported having an adult male living in the household, while 40% of the women were married. The mean estimated maternal IQ was 88 (range = 58 – 122), as measured by the two-subtest version of the WAIS-R [4]. The children were, on average, 10.5 years old (S.D. = 0.5, range = 10 – 13) at the assessment. Fifty percent of the children were male. The mean number of siblings was 1.6 (range = 0– 6). Forty-five percent of the children were in the fifth grade (range = 2 –8). Twenty-three percent of the children had repeated one or more grades. The mean Stanford – Binet Intelligence Scale [69] Composite Score was 91.5 (range = 59– 130). 2.3. Measures

Table 1 Descriptive statistics for outcome variables Mean

Standard deviation

Range

Wisconsin Categories completed No. of errors No. of perseverative errors

3.8 50.5 23.8

1.6 19.0 9.8

1–6 12 – 99 5 – 56

WRAML Picture memorya Design memorya Verbal learninga Story memorya Screening index

9.1 7.1 9.7 7.6 88.3

2.7 2.8 3.1 3.0 13.9

2 – 18 1 – 15 1 – 18 1 – 16 48 – 134

Trail Making Trails A time (s) Trails B time (s)

37.9 102.8

12.8 42.6

16 – 79 31 – 236

Stroop Word T score Color T score Color/Word T score

47.4 45.0 46.7

6.2 6.6 6.1

26 – 67 24 – 64 21 – 65

Grooved Pegboard DHb: time to insert (s) NDHc: time to insert (s)

80.5 93.2

14.6 19.1

54 – 127 54 – 159

1.5 3.7 1.7 3.6

1.2 4.6 1.4 6.2

0 – 7.3 0 – 39.7 0–8 0 – 45

CPT-2 Mean omission errors Mean commission errors Trial 3 omission errors Trial 3 commission errors a

2.3.1. Child assessments The neuropsychological test battery examined five cognitive domains. The domains were chosen based on previous findings in the literature and on hypothesized mechanisms of the effects of prenatal alcohol and marijuana exposure. Each of the instruments is psychometrically sound, sensitive to subtle brain dysfunction, and appropriate for 10-year-old children of average or low average intelligence. Table 1 presents the descriptive statistics for each instrument. The first domain, problem solving and abstract reasoning, was measured by a computerized version of the Wisconsin Card Sorting Test [5]. Subjects were required to match stimulus cards on the basis of color, shape, or number. When the performance criterion was reached (10 successive correct responses), the sorting rule changed and the subject had to deduce the new rule, using feedback about the correctness of each response. This test provides a measure of deductive reasoning and an estimate of the subject’s ability to shift to a new strategy (or response set) when reinforcement contingencies change. Further, it provides measures of perseverative responding and impulsivity. The number of categories completed, the total number of errors, and the number of perseverative errors were used for the analyses. Norms have been published for children [5]. There were four cases where the number of perseverative errors was greater than three standard deviations from the mean. These were recoded to the next lowest value in the distribution.

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b c

Scaled score. Dominant hand. Nondominant hand.

The second domain was learning and memory, measured by the Wide Range Assessment of Memory and Learning (WRAML) [58]. The screening version of this test consisted of four subtests that examine picture, design, and story memory, and verbal learning (mean = 10; S.D. = 3). A composite screening index was also obtained (mean = 100; S.D. = 15). The third domain was mental flexibility, measured by Trail Making, Parts A and B [49]. This test of attention, visuomotor tracking, and problem solving is sensitive to subtle brain dysfunction. In Trails A, the subject was presented with a sheet of paper on which circled numbers were randomly arrayed across the page. The task was to connect the numbers in consecutive order as rapidly as possible. In Trails B, the sheet contained both numbers and letters; the task was to rapidly alternate between the two in sequence. Response measures chosen for analysis were the number of seconds to complete each sequence, which were log-transformed. The Adult Version of Trail Making was used because it is more challenging and more sensitive to mild cognitive dysfunction than the briefer Child’s Version. There were seven and eight cases where the times to complete Trails A and B, respectively, were greater than

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three standard deviations from the mean. These cases were recoded to the next lowest value. The Stroop Color/Word Interference Test was also used to measure mental flexibility, specifically the ability of the subject to shift a perceptual set to conform to changing demands. On the word page, the subject read the names of colors printed in black ink. On the color page, the subject named the color of the ink in which X’s were printed. On the color/word page, the name of the color and the color of the ink in which it was printed did not match; the subject was required to read the color of the ink and ignore the name of the color. The Golden [21] version of this test was used, and 45 s were allowed for each subtest. The variable used for this analysis was the color/word t score (mean = 50, S.D. = 10). The four color/word scores, which were greater than three standard deviations from the mean, were recoded to the next lowest value. The fourth domain was psychomotor speed and eye – hand coordination, as measured by the Grooved Pegboard [54]. This is a test of eye– hand coordination, which requires the subject to rapidly place notched pegs into a board of 25 holes. Response measures used for analysis were the time to insert the pegs with the dominant hand and with the nondominant hand. These variables were log-transformed. There were eight cases for the dominant hand and eight for the nondominant hand where the time to insert the pegs was greater than three standard deviations from the mean. These cases were recoded to the next lowest value. The fifth domain was attention and general mental efficiency, measured by the Continuous Performance Test. The Pediatric Assessment of Cognitive Efficiency (PACE) [38] is designed to measure the child’s attention, impulsivity, information processing efficiency, and motor control. The Continuous Performance Test-Letters (CPT-2) presented a series of colored letters and the child responded to a target stimulus when it was preceded by a specific letter. Three trials were presented, each with 100 stimuli, 10 of which were correct. Errors of omission were defined as the number of times the subject missed the target and errors of commission were the number of times the subject made an incorrect response. Variables used for analysis were the mean errors of omission and commission across the three trials. The performance on the last of the three trials was also used to assess whether children who were prenatally exposed to drugs would be more affected by fatigue than those who were not exposed. 2.3.2. Substance use Alcohol and marijuana use were assessed using the methods developed by the MHPCD Project [12]. The women were asked about the usual, minimum, and maximum quantity and frequency of beer, wine, liquor, beer cooler, and wine cooler use. They were also asked about their usual, maximum, and minimum amount and frequency of marijuana, hashish, and sinsemilla use. Hashish and sinsemilla were translated into joints of marijuana based

on the relative amounts of D-9-THC in each substance [20,27]. A bowl or a joint of hashish was counted as three joints of marijuana, and sinsemilla was coded as two joints of marijuana. Alcohol and marijuana use were assessed for each month of the first trimester and across the entire trimester for the second and third trimesters of pregnancy. At the 10-year follow-up, the women reported their substance use over the past year. Several alcohol variables were used for this analysis. The prevalence of prenatal and current alcohol use is presented in Table 2. Average daily volume (ADV) was a summary measure of the total amount of alcohol consumed, averaged to represent the number of drinks per day. This variable was used for each trimester. The distribution of alcohol use was positively skewed. Therefore, log – linear transformation was used to reduce its skewness. In addition, two variables were constructed to represent binge drinking. Although binge drinking has typically been defined as five or more drinks per occasion [61,63], recent reports have argued that a level of four or more drinks per occasion is more useful in defining problematic intake for women [72]. Therefore, a dichotomous variable was constructed using this definition for each trimester. In addition, the frequency (e.g., once/month, once/week, etc.) with which a woman drank four or more drinks per day was calculated for each trimester. The correlations between ADV and the dichotomous binge variable were .48, .59, and .34 for the first, second, and third trimesters, respectively. The correlations between ADV and the frequency of binge drinking variable were .88, .92, and .88 for the first, second, and third trimesters, respectively. Table 3 presents the prevalence of prenatal and current marijuana use. Marijuana use was expressed as the average number of joints per day (ADJ = average daily joints) for each trimester. Since the distribution of marijuana use was positively skewed, log – linear transformation was used to reduce its skewness. We also investigated the effect of Table 2 Prevalence of alcohol use during pregnancy and at 10 years postpartum (%)

Nonea Lightb Moderatec Heavyd Binge4e Frequency4f (mean) a b c d e f g h

First trimester (n = 593)

Second trimester (n = 533)

Third trimester (n = 593)

10 years (n = 592)

35.3 30.9 14.7 19.2 35.0 0.06g

63.0 30.0 4.1 2.8 4.0 0.01h

68.0 25.5 2.9 3.7 4.0 0.01h

20.6 36.0 13.7 29.7 49.0 0.11g

None: no use. Light: 0 < ADV  0.4 drinks/day. Moderate: 0.4 < ADV  0.89 drinks/day. Heavy: ADV > 0.89 drinks/day. Four or more drinks/occasion (yes/no). Frequency of four or more drinks/day. Two to three times per month. One time per 3 months.

G.A. Richardson et al. / Neurotoxicology and Teratology 24 (2002) 309–320 Table 3 Prevalence of marijuana use during pregnancy and at 10 years postpartum

Nonea Lightb Moderatec Heavyd a b c d

First trimester (n = 593)

Second trimester (n = 534)

Third trimester (n = 593)

10 years (n = 592)

58.2 19.4 8.1 14.3

76.8 14.4 3.6 5.2

80.9 10.8 3.2 5.1

77.9 17.2 1.7 3.2

None: no use. Light: 0 < ADJ  0.4 joints/day. Moderate: 0.4 < ADJ  0.89 joints/day. Heavy: ADJ > 0.89 joints/day.

heavy marijuana use by constructing a dichotomous variable ( < 0.89 vs.  0.89 joints/day). Tobacco use was expressed as the average number of cigarettes smoked per day during each trimester and at each follow-up phase. Cocaine use was defined, for these analyses, as a dichotomous variable indicating use/no use. For descriptive analyses, alcohol and marijuana users were categorized into four groups: abstainers, light users (  0.4 joints or drinks/day), moderate users ( > 0.4 and  0.89 joints or drinks/day), and heavy users ( > 0.89 joints or drinks/day). The cutpoint of 0.89 was chosen to define heavy use because it is equivalent to one or more joints or drinks/day. This is calculated using the following formula: (7 joints or drinks/week  4 weeks/month)/31 days/month. 2.3.3. Maternal demographic and socioeconomic status Demographic and socioeconomic status at 10 years was defined by: maternal age, number of years of education, monthly family income, presence of husband or boyfriend in the household (yes/no), race (African American/Caucasian), and working/studying outside of the home (yes/no). 2.3.4. Maternal psychosocial characteristics Maternal depression, hostility, and the number of reported life events were used to assess psychological status at the 10-year phase. Maternal depression was assessed using the Center for Epidemiological Studies-Depression Scale (CES-D) [48], hostility was measured by the Spielberger State – Trait Anxiety Inventory [59], and life events were measured by questions adapted from Dohrenwend et al. [13]. An estimate of maternal IQ was obtained at the 10-year phase by administering the two-subtest version (vocabulary and block design) of the WAIS-R [4]. The WAIS-R was obtained only on the biological parent. 2.3.5. Child characteristics and environment The child’s age, gender, and number of siblings were recorded. Information on the child’s hospitalizations, injuries, illnesses, and uncorrected vision problems (i.e., prescribed glasses were not worn the day of the assessment) was obtained from the caregiver. The Home Observation for Measurement of the Environment-Short Form (HOME-SF) [1] was used to assess the quality of the cognitive simulation

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and emotional support provided by the child’s family. The Stanford – Binet Intelligence Scale-4th Edition [69] was used to assess the child’s intellectual development. The child also completed the Revised Children’s Manifest Anxiety Scale [51], a 37-item scale, which assesses anxietyrelated symptoms. 2.4. Data analysis A general structural equation model (SEM) was used to analyze the effects of prenatal alcohol and marijuana exposure on the domains of neuropsychological outcomes. This method not only allows us to test the effects of prenatal substance use on all neuropsychological domains simultaneously, but it also takes into account measurement error and allows us to consider the correlations within the endogenous or outcome variables and within the exogenous factors such as substance use. This analysis was used to determine which domains of neuropsychological development were affected by either prenatal alcohol or marijuana exposure.

Table 4 Variables considered for inclusion in the analyses Current maternal demographics/socioeconomic status Age Educationa Monthly family incomea Presence of male in the household Racea Work/school status Current maternal psychosocial characteristics Depression Estimated IQ Hostility Life events Current child characteristics/home environment Agea (not included for WRAML) Anxietya Gendera HOME-SFa Number of hospitalizations Number of illnesses Number of injuries Number of siblings Stanford – Binet Intelligence Scale Composite Score Uncorrected vision problemsa Current maternal substance use Alcohol Cocaine Marijuana Tobacco Prenatal substance use Alcohola Cocaine Marijuanaa Tobaccoa a

Variable retained in final, SEM model.

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The SEM was carried out in three steps, using the software package LISREL 8 [26]. First, a confirmatory factor analysis was conducted to test whether the grouping of the outcome variables into the five domains, as outlined in Section 2.3.1., fit the observed data. The confirmatory factor analysis indicated that this theoretical organization was a good fit with the observed data, with one exception. In the learning and memory domain, a better fit was obtained if the picture memory subscale was omitted. Second, significant covariates were selected for inclusion in the model. Variables reported in the literature to be related either to neuropsychological outcomes or to alcohol or marijuana use were considered for inclusion in the model as covariates (Table 4). The variables that were retained for the final models are indicated in

Table 4. Third, prenatal marijuana and alcohol use were added to the model to test whether they were significantly associated with any of the five domains of neuropsychological outcomes. Two latent variables were created to represent the effects of alcohol and marijuana. The alcohol latent variable included ADV, binge drinking, and frequency of binge drinking. The marijuana latent variable consisted of average daily joints and heavy marijuana use, as defined in Section 2.3.2. A single observed variable, the number of cigarettes per day, represented tobacco use. The adjusted goodness-offit, comparative fit, and parsimony goodness-of-fit indices were used to test the goodness of fit of the models and evaluate the parsimoniousness of the model. Adjusted goodness-of-fit and comparative fit values greater than 0.90 are

Table 5 Maternal characteristics associated with alcohol use By level of first trimester use Age (years) Education (years) Married (%) Work/school (%) Family income (% < US$400/month) Race (% White) Depression Hostility % Marijuana users % Tobacco users % Cocaine users

No use (n = 209)

Light/moderatea (n = 270)

Heavyb (n = 114c)

23.3 11.7 36 23 57 43 40.4 17.6 27 39 1

23.0 11.9 30 30 64 46 41.5 19.0 45 56 4

n = 403

n = 168

22.9 11.8 34 17 69 47 40.0 17.3 15 46

23.4 12.0 36 17 65 51 41.4 18.4 24 66

By level of current use

n = 122

n = 294

n = 176

Age (years) Education (years) Married (%) Work/school (%) Family income (US$/month) Race (% White) Depression Hostility IQ % Marijuana users % Tobacco users % Cocaine users Home environment

38.1 12.0 43 64 1555 44 37.3 15.5 88.4 8 49 0 12.8

34.7 12.4 47 69 1659 53 37.5 15.8 89.3 16 57 4 12.6

34.6*** 12.2* 27*** 52*** 1201*** 39* 39.3 16.7* 86.4* 41*** 73*** 15*** 12.6

By level of third trimester use Age (years) Education (years) Married (%) Work/school (%) Family income (% < US$400/mo) Race (% White) Depression Hostility % Marijuana users % Tobacco users

a b c d

Light/moderate: 0 < ADV  0.89 drinks/day. Heavy: ADV > 0.89 drinks/day. Overall significance: * P < .05; ** P < .01; *** P < .001. Significant at a = .05 using Bonferroni Inequality for multiple comparisons.

22.6 11.8 25 25 65 57 * 41.4 19.2** 61*** 78*** 7*

Significant group differencesd

1 and 3 1 1 1 1

and and and and

2, 1 and 3 3, 2 and 3,1 and 2 3, 2 and 3,1 and 2 3

n = 22 23.2 11.4 18 9 81 18* 40.7 19.3* 50** 54**

1 and 3, 2 and 3 1 and 2 1 and 3, 2 and 3 1 and 2

1 1 1 1 1 2

and and and and and and

2, 2 3, 3, 3, 3

1 and 3

1 2 1 1 1

and and and and and

3 3 3, 2 and 3 3, 2 and 3 3, 2 and 3

2 and 3 2 and 3 2 and 3

G.A. Richardson et al. / Neurotoxicology and Teratology 24 (2002) 309–320

considered acceptable. Parsimony goodness-of-fit values greater than 0.50 are considered acceptable. Based on the significant findings from the SEM, stepwise multiple regression analyses were then used to investigate in more detail the effects of prenatal alcohol and marijuana exposure on the separate measures that defined the neuropsychological domains, while controlling for other predictors. The residuals from the regression analyses were screened to identify outliers and influential points to ensure that the results were not influenced by only a few cases. SEM does not have this capability. The tolerances of the variables in the final models were examined to ascertain that the stability of the coefficients was not affected by multi-

315

collinearity. Three outliers/influential points were removed from the first trimester WRAML analyses and one each was removed from the second and third trimester analyses. One outlier was removed from the CPT regression analyses. There were moderate correlations, ranging from .5 to .7, between trimesters in the rates of alcohol and marijuana use. However, the use of alcohol and marijuana was not constant throughout pregnancy, as shown in Tables 2 and 3. The majority of women reduced their use as their pregnancies progressed. Separate regression analyses were conducted for each trimester of pregnancy to assess the effects of exposure at the different time periods. Separate regressions were also run for the various measures of alcohol and marijuana.

Table 6 Maternal characteristics associated with marijuana use By level of first trimester use Age (years) Education (years) Married (%) Work/school (%) Family income (% < US$400/mo) Race (% White) Depression Hostility % Heavy alcohol userse % Tobacco users % Cocaine users By level of third trimester use Age (years) Education (years) Married (%) Work/school (%) Family income (% < US$400/mo) Race (% White) Depression Hostility % Heavy alcohol userse % Tobacco users

No use (n = 345) 23.2 11.9 37 27 58 54 40.7 18.1 13 47 1 n = 480

Light/moderatea (n = 163) 22.7 11.8 26 29 64 45 41.2 18.9 28 63 5 n = 83

Heavyb (n = 85c) 23.0 11.8 18*** 19 70 21*** 42.0 19.9* 29*** 67*** 8 **

23.4 11.9 25 21 75 37 41.0 18.0 5 70

By level of current use

n = 461

n = 112

n = 19

Age (years) Education (years) Married (%) Work/school (%) Family income (US$/month) Race (% White) Depression Hostility IQ % Heavy alcohol userse % Tobacco users % Cocaine users Home environment

35.6 12.3 43 67 1628 50 37.3 15.8 88.9 22 56 3 12.8

34.7 12.0 32 48 1070 37 40.7 16.7 86.3 58 76 20 12.2

33.0 12.1 16.0 ** 42*** 989*** 16*** 38.9 ** 18.2 ** 84.5* 42*** 68*** 26*** 11.6*

b c d e

Light/moderate: up to 0.89 joints/day. Heavy: more than 0.89 joints/day. Overall significance: * P < .05; ** P < .01; *** P < .001. Significant at a = .05 using Bonferroni Inequality for multiple comparisons.  1 drink/day.

1 and 2, 1 and 3

1 and 3, 2 and 3 1 1 1 1

and and and and

3 2, 1 and 3 2, 1 and 3 3

n = 30

23.0 11.9 36 17 66 50 40.1 17.5 2 47

a

Significant group differencesd

22.8 11.3 20 10 82 23 ** 43.6 19.9 23*** 77***

1 and 3

1 and 3, 2 and 3 1 and 2, 1 and 3

1 1 1 1 1 1 1 1 1 1 1

and and and and and and and and and and and

3 2, 2, 2, 2 3 2 2 2 2, 2

1 and 3 1 and 3 1 and 3

1 and 3

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3. Results 3.1. Correlates of substance use Women who drank one or more drinks per day during their first trimester of pregnancy were significantly more likely to use marijuana, tobacco, and cocaine, to be Caucasian, and to report more hostility than the abstainers. In the third trimester, women who drank one or more drinks per day were more likely to be African American and to use marijuana compared to the women who abstained (Table 5). Women who drank at least a drink a day at the 10-year follow-up were more likely to report the current use of marijuana, tobacco, and cocaine than were the nondrinkers. Current heavy alcohol users were more likely to be younger, single, to have lower family incomes, to report more hostility, and to be less likely to work and/or go to school, in comparison to the abstainers. As shown in Table 6, the use of one or more joints of marijuana per day during the first trimester was significantly associated with being single, African American, and hostile. These women also had an increased rate of heavy alcohol use and tobacco and cocaine use compared with the women who did not use marijuana in the first trimester. Women who used one or more joints of marijuana per day during the third trimester of pregnancy were significantly more likely to be African American, to drink one or more drinks/day,

and to smoke cigarettes than were women who did not use marijuana during the third trimester. These same factors characterized women who were heavy marijuana users at 10 years postpartum. 3.2. SEM analyses Fig. 1 shows the results of the SEM analysis for first trimester substance use. First trimester alcohol and tobacco use were significant predictors of the learning and memory factor. There were no significant associations between prenatal marijuana and alcohol use and any of the other four neuropsychological domains. Poorer performance on the learning and memory domain was associated with being African American, male, and having a lower family income. The adjusted goodness-of-fit, comparative fit, and parsimony goodness-of-fit indices for the model were 0.92, 0.96, and 0.63, respectively. Second trimester alcohol use also significantly predicted performance on the learning and memory domain. The adjusted goodness-of-fit, comparative fit, and parsimony goodness-of-fit indices were 0.92, 0.95, and 0.63, respectively. There were no other relationships between second trimester substance use and the neuropsychological domains. Third trimester alcohol and marijuana use were not significant predictors of any of the neuropsychological domains. 3.3. Regression analyses

Fig. 1. Structural equation model illustrating relations between first trimester substance use and neuropsychological outcomes. aIncludes average daily joints and heavy marijuana use. bIncludes average daily volume, binge drinking, and frequency of binge drinking. c0 = Female; 1 = Male. d0 = African American; 1 = Caucasian.

Stepwise multiple regressions were conducted on the separate measures that comprised the learning and memory domain to identify which aspects of learning and memory were affected. Prenatal alcohol exposure significantly predicted scores on three of the four WRAML subscales at 10 years (Table 7). ADV of alcohol use in the first trimester predicted lower scores on the verbal learning subscale. The frequency of binge drinking (four or more drinks per day) during the first trimester predicted lower scores on the design memory, story memory, and verbal learning scales. Second trimester ADV of alcohol was associated with lower scores on the verbal learning and story memory scales, and second trimester binge drinking was associated with lower scores on the verbal learning scale. Third trimester ADV of alcohol predicted lower scores on the story memory scale. We compared the adjusted variances for ADV and the binge drinking variable to determine which had a greater effect on the WRAML scores. The total variance explained was nearly identical for the two variables, indicating that neither measure was more predictive than the other. Prenatal exposure to marijuana was also significantly related to adverse effects on the WRAML. The dichotomous variable that defined heavy use of marijuana during the first trimester predicted lower scores on the design memory subscale and on the screening index of the WRAML. In our assessment at 6 years of age, we found that second trimester marijuana use was associated with increased com-

G.A. Richardson et al. / Neurotoxicology and Teratology 24 (2002) 309–320 Table 7 Regression analysesa Outcome variable WRAML Design memoryb

Verbal learningb

Story memoryb

Screening index

CPT-2 Trial 3 commission errors

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4. Discussion Significant predictors Family income Race Gender First trimester frequency binge alcohol First trimester heavy marijuana Family income Race Child anxiety Gender First trimester alcohol First trimester frequency binge alcohol Second trimester alcohol Second trimester binge alcohol First trimester tobacco Second trimester tobacco Race Gender HOME score First trimester frequency binge alcohol Second trimester alcohol Third trimester alcohol Family income Race Gender First trimester heavy marijuana First trimester tobacco

Child anxiety Gender Second trimester marijuana

R2

b 0.00 0.43 0.49 1.51

0.01 0.01 0.01 0.01

0.83

0.02

0.001 0.95 0.06 0.52 0.51

0.03 0.01 0.02 0.01 0.01

1.55

0.01

1.86

0.01

1.53

0.01

0.03

0.01

0.02

0.01

0.86 0.52 0.11 1.25

0.02 0.01 0.01 0.01

1.03

0.01

0.91

0.01

0.001 5.94 2.69 3.34

0.01 0.05 0.01 0.01

0.10

0.01

0.10 1.90 1.86

0.01 0.02 0.01

a Analyses are presented only for those outcomes where prenatal alcohol or marijuana was significant. Analyses were run separately by trimester but are shown together for ease of presentation. b Scaled score.

mission errors, a measure of impulsivity [34]. At 10 years, we again found that second trimester marijuana use, expressed as average daily joints, predicted more commission errors on Trial 3 of the CPT. The regression analyses were repeated with the child’s Stanford– Binet Intelligence Scale composite score in the model and the effects of prenatal substance exposure on learning and memory were unchanged.

A SEM was used to identify the relations between prenatal exposures and neuropsychological domains. This analysis was followed by regression analyses to explore the specific measures in the learning and memory factor that were associated with prenatal exposure. Prenatal exposure to alcohol had a significant deleterious effect on the children’s learning and memory score at 10 years of age. The regression analyses showed that average daily alcohol use and frequency of drinking four or more drinks/day both predicted poorer performance on verbal learning and verbal and visual memory tasks. In general, these were effects of alcohol exposure during the first and second trimesters. Both measures of alcohol use predicted learning and memory equally well. These findings persisted when other factors that predicted learning and memory, such as race, gender, and family sociodemographic characteristics, were controlled. Our findings of an effect of prenatal alcohol exposure on learning and memory are consistent with many other reports in the literature in which prenatal alcohol use was found to affect auditory, verbal, and visual memory skills [6,30,41, 43,47,56,63,66]. However, this report adds to the literature in that it is the only study of women who received prenatal care, who drank light to moderate amounts of alcohol, and whose offspring were 10– 11 years old at the time of assessment. The period of middle childhood is an important period in development because it represents a period of rapid change in behavior [68] and in the development of cognitive abilities [35]. The fact that these findings are replicated in a light to moderately exposed sample is also significant in demonstrating a relation at levels lower than previously reported. These findings are consistent with the results from animal research, which have shown that prenatal alcohol exposure leads to deficits in spatial and operant learning and memory tasks. For example, deficits in serial pattern, discrimination, and reversal learning, as well as spatial and delay-dependent memory performance have been demonstrated in animals following prenatal alcohol exposure [3,24,33,45,50,52]. Prenatal alcohol exposure may affect learning and memory skills through its effect on the hippocampus [3,28,71,74]. Research has demonstrated that the behavioral correlates, neurotransmitter function, and structural development of the hippocampus are temporally vulnerable to the effects of prenatal alcohol exposure [3,29,44,75]. The development of the hippocampus occurs during the later part of the first trimester and into the second trimester, although the dentate granule cells of the hippocampus do not develop until later in the second trimester and into the third trimester [2]. Our findings are consistent with this pattern of fetal development given that deficits in cognitive function were associated with exposure during the first and second trimesters of pregnancy. However, it is difficult to specify that prenatal alcohol use acts solely on one brain region because of the interconnectedness of

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different regions of the brain, such as the hippocampus and the prefrontal cortex [3,28]. In comparing the results from the ADV and the frequency of binge drinking measures, both predicted negative effects on learning and memory. Given the high correlations between ADV and the frequency of binge drinking, it is not possible to identify which measure of drinking is more predictive. Indeed, the utility of the measures may vary with the outcome and with the age of the child. For example, in the Seattle Longitudinal Study, binge alcohol use was found to be a better predictor of outcomes at 7 1/2 years of age [56,63], while at the 14-year follow-up, the average number of drinks was a better predictor of a variety of outcomes [25,55,60,64]. We did not find support for our hypotheses of effects of prenatal alcohol exposure on problem solving, abstract reasoning, or mental flexibility, which are considered to be aspects of executive functions. Most of the previous research that has reported that prenatal alcohol use affects executive function has been conducted with older children and with children who were more heavily exposed [8,30,31,39,57,66]. Some executive function and attention skills do not develop until at least 12 years of age [36,67,73], which could explain the lack of effects at 10 years of age. In fact, in preliminary analyses from our 14-year follow-up, prenatal alcohol exposure significantly predicted deficits in several domains of executive function, including planning, cognitive flexibility, and concept formation [77]. We also did not find effects of prenatal alcohol exposure on performance on the CPT measures of attention and impulsivity. The CPT used in this study had different task requirements from those used in other studies and did not include a measure of reaction time, which Streissguth et al. [62,65] found was associated with prenatal alcohol exposure. Prenatal marijuana use during the first trimester of pregnancy predicted poorer performance on the design memory and the screening index on the WRAML at 10 years of age. Second trimester marijuana use was associated with increased errors of commission on a computerized attention task, an indication of impulsivity. These results persisted when other predictors of neuropsychological performance were controlled. The effects on errors of commission appeared only toward the end of the task when the children were fatigued. The magnitude of the marijuana effects was small and limited to only a few aspects of functioning. One conclusion to be drawn from these results is that prenatal marijuana exposure has limited effects on cognitive and neuropsychological functions at this age, although it may have an impact on behavior, as evidenced by the greater level of impulsivity associated with marijuana exposure. The same relationship between increased impulsivity and second trimester marijuana use was found when these children were 6 years of age [34]. We have also previously reported that prenatal marijuana use predicted increased

attention problems and impulsivity at 10 years, as reported by the mothers [22]. We did not find any relationship with attention problems on the CPT measures used for this report. However, it is difficult to compare the CPT measure of inattention to parental reports of inattention, which include behaviors such as failure to listen and failure to finish things. As with the findings for alcohol exposure, it is possible that prenatal marijuana effects on these and additional domains may be found when the children reach 14 years of age. For example, executive function skills continue to develop into adolescence [36,67,73]. Preliminary analyses from the 14-year phase showed that prenatal marijuana exposure was associated with the WISC Mazes and Coding subtests, suggesting deficits in cognitive flexibility and planning [76]. There are several neuropsychological tasks that both the MHPCD and OPPS have administered in their protocols. The lack of marijuana effects on some of the tasks that are thought to reflect executive function is consistent between the two projects. For example, we found no effects on the Stroop and Trail Making tests, in agreement with the results from the OPPS [16,17,46]. We found limited effects on memory at 10 years of age. In the OPPS, prenatal marijuana exposure was found to affect memory at 4 years [15], but not at 5 – 6 years [14], 6 –9 years [46], or 9 –12 years [19]. By contrast, although we found effects on the CPT at ages 6 [34] and 10 that reflect impulsivity, Fried reported increased omission errors, which reflect inattention, at 6 years [18] and at 13 –16 years [17], but no effects on CPT performance at 9 –12 years of age [19]. Thus, although in both studies here appear to be significant effects of prenatal marijuana exposure on neuropsychological function, the specific findings differ. The strengths of this study include the detailed assessment of alcohol, marijuana, tobacco, and other drug use during each trimester of pregnancy and at each follow-up phase, a comprehensive neuropsychological battery, the assessment of sociodemographic, environmental, and psychological factors that can influence neuropsychological task performance, a large sample size, and excellent follow-up rates. In addition, predictors of performance on the neuropsychological tasks, such as gender, race, and intellectual level, were the same as other researchers have reported [36,53,73], which supports the validity of our results. In summary, we found that prenatal alcohol and marijuana exposure specifically affected learning and memory. Prenatal marijuana exposure also predicted increased impulsivity, consistent with our findings at 6 years [34]. Prenatal tobacco use was also found to affect learning and memory, consistent with an earlier report from this project [9]. Thus, in this population, we have demonstrated effects of substance exposure on the development of children exposed during gestation. This is particularly notable as this cohort represents children who have been exposed to light to moderate levels of drugs.

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