ARTICLE |
Departments of a Pediatrics
b Psychology
c General Medical Sciences, Case Western Reserve University, Cleveland, Ohio
| ABSTRACT |
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METHODS. Children who were exposed to cocaine in utero (n = 209) and nonexposed children (n = 189) were followed prospectively at birth and at 1, 2, 4, and 6 years of age and were compared on receptive, expressive, and total language scores across time using random coefficient models, controlling for confounders.
RESULTS. A significant, stable effect of cocaine exposure on language development was observed over time for all language domains, with cocaine exposure related to poorer language performance. Cigarette exposure was related to lower receptive language scores. Environmental influences on language scores were also observed. Both the cocaine-exposed and nonexposed children declined in language performance over time.
CONCLUSIONS. Prenatal cocaine exposure has a stable negative effect on language skills during the first 6 years of life. Both cocaine-exposed and nonexposed children showed decreased language growth over time; however, cocaine-exposed children demonstrated linguistic deficits compared with nonexposed peers and did not catch up. Cigarette and environmental influences were also noted.
Key Words: cocaine longitudinal language outcomes home environment gender tobacco teratology
Abbreviations: CE—cocaine exposed NCE—non–cocaine exposed BZE—benzoylecgonine M-OH-BZE—meta-hydroxybenzoylecgonine PPVT-R—Peabody Picture Vocabulary Test, Revised WAIS-R—Wechsler Adult Intelligence Scale, Revised HOME—Home Observation for Measurement of the Environment SES—socioeconomic status
Children who are exposed to cocaine in utero are at risk for a variety of developmental delays as a result of both biological risk and postnatal environmental influences. Biological risks include a disruption in arousal and attention.1–5 The environmental risks are threefold: inadequate stimulation provided by a drug-using mother,6,7 insecure child attachment,8 and poverty.9 These risk factors may have an impact on the language development of children who are exposed to cocaine.
Outcome studies of language development of children who were exposed to cocaine in utero have been equivocal,4,10–20 possibly as a result of methodologic differences such as age at assessment, instruments used, and variability in selection of confounding factors considered.15 Although most studies have reported language outcomes at a single time point, one of the few longitudinal prospective studies of children who were exposed to cocaine found stable cocaine-specific effects on total language scores, even after control for multiple medical and demographic covariates.11,21 Children with cocaine exposure performed on average 15% of a SD lower on a standardized language test than nonexposed children, with the strongest effects at 18 months and 3 years. This study extended these findings with a larger developmental age span, examining also receptive and expressive language and using biological markers (meconium) of cocaine exposure.
This investigation examined the effects of cocaine exposure in utero on language development in a longitudinal sample of children who were enrolled prospectively at birth and followed to 1, 2, 4, and 6 years of age. Children who were exposed to cocaine in utero were hypothesized to perform more poorly than nonexposed children on standardized measures of receptive and expressive language across all time points. Careful delineation of environmental factors that are known to relate to child language skills was conducted, particularly maternal education/vocabulary, depressive symptoms, and use of other substances.
| METHODS |
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The sample size for the original cohort was 415. The number of children who participated in the language testing at each follow-up time point varied; however,
85% of the cohort participated in 3 or more of the 4 visits. At 1 year, the sample size consisted of 405 children, with 371 assessed and 265 children receiving the language measures. At 2 years, 404 children from the original sample were available (1 death), with 381 assessed and 339 completing language measures. At 4 years, 404 children were available, with 394 completing the language test, 12 (8 CE) not coming to the visit, 16 (12 CE) dropouts, and 2 (1 CE) moving out of state. Attrition was greater for the CE group (P = .04) than for the NCE group. At 6 years of age, 377 received assessments, with 371 children completing the language test battery.
Procedures
At 1 and 2 years of age, the Preschool Language Scale, Third Edition22 was administered. At 4 years, the Clinical Evaluation of Language Fundamentals–Preschool23 was given. At 6 years, the Comprehensive Assessment of Spoken Language24 was administered. At all ages, examiners were unaware of infant cocaine status.
For assessment of prenatal drug exposure, infants and their biological mothers were seen immediately after birth, at which time the biological mother was interviewed regarding drug use. Biological mothers were asked to recall the frequency and the amount of drug use for the month before pregnancy and each trimester of her pregnancy. More specific, for tobacco, the number of cigarettes smoked per day was recorded; for marijuana, the number of joints smoked per day was recorded; for alcohol, the number of drinks of beer, wine, or hard liquor per day was computed; and for cocaine, the number of rocks consumed and amount of money spent per day were noted. This drug assessment was updated at each follow-up visit to provide a similar measure of current drug use, with the assessments also administered to the foster or relative caregiver to provide a measure of postnatal environmental exposure for children who were placed out of maternal care.
Birth, demographic, and medical characteristics were taken from hospital records and included maternal race, age, parity, number of prenatal care visits, and type of medical insurance, infant Apgar scores, birth weight, length, and head circumference. At enrollment, maternal socioeconomic status (SES; A.B. Hollingshead, PhD, Four-Factor Index of Social Status, unpublished manual, 1975) and educational level were calculated. Maternal vocabulary score was measured using the Peabody Picture Vocabulary Test, Revised (PPVT-R).25 Two subtests of the Wechsler Adult Intelligence Scale, Revised26 (WAIS-R) were administered: The Block Design and Picture Completion subtests from the WAIS-R enabled an estimation of nonverbal intelligence. The Brief Symptom Inventory27 is a standardized self-report scale that was administered at birth and at all visits to obtain a measure of severity of psychological distress. The General Severity Index, a summary score of the Brief Symptom Inventory, was used as an indicator of overall distress. The Hobel Neonatal Risk Index28 was computed to obtain a measure of neonatal medical complications. Also at the visit, the child's placement (either biological mother/relative or foster/adoptive caregiver) was noted, and data on the current caregiver were updated. When the child had been placed with a new caregiver, intellectual measures of the caregiver were also updated. The Home Observation of the Environment (HOME), Preschool version was administered to the caregiver in an interview format as a measure of the quality of the caregiving environment.29
Statistical Analysis
Baseline maternal and child characteristics and prenatal drug exposure were summarized using means and SDs for continuous variables and frequencies and percentages for categorical variables. Comparisons between CE and NCE groups were performed using t tests, Wilcoxon rank sum tests, and Pearson
2 tests. All positively skewed data, including drug self-report measures and General Severity Index, were transformed using the natural logarithm of (x + 1) to achieve a distribution that approximates normality. Correlations between drug exposure data and language outcomes were estimated using Spearman correlation coefficients.
For examination of language performance across time, each measurement was internally standardized to create z scores at each visit using all available children. Standardization of scores at each time point allowed modeling to be performed across language measures despite that different age-appropriate tests were used. Analyses of the z scores were accomplished using random coefficient models with restricted maximum likelihood estimation. The intercept and the slope for child age were treated as random effects to capture the variability and correlation in the data. The actual age of the child was used instead of visit age to capture trends over time better. These models were used to estimate and test relationships between cocaine exposure groups at the follow-up visits (ages 1, 2, 4, and 6 years). Initially, child age, cocaine exposure, and the interaction between age and exposure were included in the model to test for changing effects over time. Because the interaction term was not significant for any of the language measures, main effects models were fit. The developmental trajectories were allowed to be nonlinear (eg, quadratic) using polynomials of time. The lowest order polynomial of time was retained. In all models, the trajectories were found to be linear. The effects of cocaine are presented with and without consideration of possible confounding variables.
For each measure, the model-building strategy of Bandstra et al11 was followed to achieve a final model that controlled for possible confounding and moderating variables to estimate an unbiased effect of prenatal cocaine exposure on language development. The following variables were considered for each outcome: child's age, prenatal cocaine exposure (yes versus no), and the interaction between age and cocaine exposure; maternal age at child's birth, current caregiver's PPVT-R and WAIS-R block design; child's race and child's gender; prenatal drug variables (alcohol, cigarettes, and marijuana), prenatal care, parity, SES, and marital status; current HOME scale; and adoptive/foster care. Adjusted least squares means and SEs were calculated from the final models and compared between treatment groups at each follow-up visit age. Plots of the adjusted group means (±SE) for each language measure over time are provided. Analyses were performed using SAS 9 (SAS Institute, Cary, NC).
| RESULTS |
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From birth to 6 years, there were 11 deaths (8 CE and 3 NCE;
2 = 1.9, P < .17). Causes of death for the CE children were sudden infant death syndrome (n = 4), cardiopulmonary arrest (n = 1), pneumonia (n = 1), accidental asphyxia (n = 1), and respiratory distress syndrome (n = 1). Causes of death for the NCE children were sudden infant death syndrome (n = 2) and respiratory distress syndrome (n = 1). From enrollment at birth, the retention rate was 93% (377) at 6 years for surviving children.
Meconium Assays and Outcomes
Several significant relationships were found between the concentration (ng/g) of cocaine metabolites and child language outcomes. At 1 year, the concentrations of BZE (r = –0.16, P < .02) and M-OH-BZE (r = –0.14, P < .04) were negatively related to the expressive language score; and at 2 years, the concentration of BZE was negatively related to receptive (r = –0.14, P < .02), expressive (r = –0.12, P < .05), and total language scores (r = –0.11, P < .02). At 4 years, the concentration of cocaethylene, the metabolite formed through the combination of cocaine and alcohol, was negatively related to expressive language (r = –0.12, P < .03) and marginally related to total language score (r = –0.11, P < .06). By 6 years of age, there were no significant relationships.
Longitudinal Analyses
Table 4 presents the mean unadjusted receptive, expressive, and total language scores by group for each of the 4 time points. Table 5 presents the adjusted mean language scores at each visit for the CE and NCE groups.
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0.15 SD (±0.08) lower than NCE children. No effects of marijuana or alcohol exposure were found. However, cigarette exposure was negatively associated with receptive language (P = .0168). Marital status and adoptive/foster care were not significantly related to receptive language.
Expressive Language
The interaction between child age and cocaine exposure was not significant for expressive language scores. Significant main effects for race and gender were found. Black children scored approximately one third of a SD lower than nonblack children, and boys performed one third of a SD lower than girls. The expressive language trajectory also varied by current HOME score (P = .0002). Higher HOME scores were associated with higher expressive language scores at 2 and 4 years of age (P < .0001). Controlling for these covariates, a significant and constant effect of cocaine exposure was found (P = .048). CE children perform
0.15 SD (±0.08) lower than NCE children. Marijuana, alcohol, or cigarette exposure was not a significant confounder. Marital status and adoptive/foster care were not related to expressive language development. On average, all children declined in their expressive language scores at 4 years compared with the 1-year visit (P = .03).
Associations of the PPVT-R, HOME, and Cigarette Exposure to Language
The effect of current caregivers' PPVT-R was significant at 4 years of age, such that as the PPVT-R scores increased, so did the child's scores on receptive (P = .0066) and total language (P = .0025) measures. This effect was also observed for the total language score at 6 years of age (P < .001).
The HOME scale showed significant effects across the ages. At 1 year of age, the receptive language score was negatively related to the HOME scale, such that as the HOME score increased, the receptive language score decreased (P = .04). At 2 years of age, the HOME score was positively related to expressive language, such that as the HOME score increased, so did the child's expressive language score (P = .037). At 4 years of age, the HOME score was positively related to all language scores (receptive, P < .0001; expressive, P < .0001; and total, P = .005 scores). This effect remained at 6 years of age (P = .001).
Children who were exposed to any cigarette smoking in utero had a lower mean standardized receptive language score by 0.21 ± 0.09 SD (95% confidence interval: –0.38 to –0.04). Children who were exposed to cigarette smoking also had a lower mean standardized total language score by 0.17 ± 0.09 SD (95% confidence interval: –0.35 to 0.01). Exposure to cigarette smoking did not have a significant effect on expressive language at any time point and was therefore not included in the final model for expressive language.
| DISCUSSION |
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Of note is that language scores in both the CE and NCE groups declined over time, suggesting that factors that are common to both groups, such as low SES, education, and poverty, have a negative impact on the developmental trajectory of language, a finding that is in agreement with the longitudinal studies of the Miami Prenatal Cocaine study21 that also report a decline in scores on standard language measures with time. Cigarette smoking during pregnancy also had a negative impact on receptive language skills.
These findings are consistent with previous research by Fried and Watkinson32 that showed reduced auditory processing skills in children who were exposed prenatally to tobacco. In the neonatal period, those infants demonstrated decreased rates of auditory habituation.33 At 12 to 24 months, infants showed poorer responses to auditory-related items on the Bayley Scales of Infant Development.34 Follow-up at 3 and 4 years of age revealed deficits in language skills and at 6 years in auditory processing skills.32,35 At 9 to 12 years, these children presented with lower language and reading scores, particularly related to the auditory aspects of these skills.36 The present findings indicate that tobacco exposure is additive to the risk of CE children for language deficits.
Environmental Effects
Our data also support the notion that environmental variables can affect language skills to a considerable extent. That current caregiver's vocabulary score and the HOME score both seem to have an impact on language performance underscores the environmental modifiability of language. Bandstra et al11 also found a relationship between language outcomes and the HOME scale. Previous reports of delay in semantic representation in children who were exposed to cocaine37 may relate to the caregiver's vocabulary rather than to the cocaine exposure itself. The current caregiver's vocabulary score was significant only at the 4-year and 6-year testing times but not at the younger ages. At a young age, the child's language development may not be as influenced by the caregiver's vocabulary because the child is acquiring basic vocabulary and syntactic structures. However, as language development proceeds, the child is required to master complex syntax, and vocabulary growth is extremely rapid. That a caregiver's verbal skills played an important role in the child's language growth is interesting. As reported previously,3 the foster/adoptive caregiver's vocabulary, depression, and HOME scores mediate the adoptive-care effect on language at 4 years of age.
Limitations of Study
Several limitations of this study should be noted. First, not all children were assessed at each time point, with the fewest number of children completing the language test at 1 year of age. However, 85% of the enrolled sample are represented in at least 3 time points. A second limitation was the use of different language measures at different time points. The preschool years are a time of rapid language acquisition, and few measures can adequately assess language skills from 1 year to 6 years of age. Ceiling and floor effects are problematic. Despite that different assessments were used at each time point, the magnitude of language deficit between the CE and NCE children remained constant at each time. This finding suggests that the different measures were assessing similar language constructs.
| CONCLUSIONS |
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| ACKNOWLEDGMENTS |
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We thank Terri Lotz-Ganley for manuscript preparation; Kristen Weigand, Laurie Ellison, Selena Cook, Julia Noland, Martin Manuel, Astrida Seja Kaugars, and Teresa Linares for research and data analytic assistance; and the Cuyahoga County Department of Children and Family Services.
| FOOTNOTES |
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Address correspondence to Barbara A. Lewis, PhD, Department of Pediatrics, Case Western Reserve University, Cleveland, OH 44106. E-mail: bxl{at}case.edu
The authors have indicated they have no financial relationships relevant to this article to disclose.
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