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Prenatal cocaine exposure and school-age intelligence
Drug and Alcohol Dependence 50 (1998) 203 – 210
Prenatal cocaine exposure and school-age intelligence Gail A. Wasserman a,b,*, Jennie K. Kline b,c,d, David A. Bateman e,f, Claudia Chiriboga f,g, Lambert H. Lumey c,h, Helen Friedlander i, Laura Melton b, Margaret C. Heagarty e,f b
a Department of Child Psychiatry, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA New York State Psychiatric Institute, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA c Sergie6sky Center, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA d School of Public Health, Columbia Uni6ersity, New York, NY, USA e Department of Pediatrics, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA f Harlem Hospital Center, New York, NY, USA g Di6ision of Pediatric Neurology, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA h American Health Foundation, New York, NY, USA i New York City Board of Education, New York, NY, USA
Accepted 1 January 1998
Abstract Assessments of the possible consequences of prenatal exposure to cocaine have been limited by lack of control for socio-demographic confounders and lack of follow-up into the school years. We evaluated intelligence at ages 6 – 9 years in 88 children from a cohort of 280 born between September 1, 1985 and August 31, 1986 and identified at birth as cocaine-exposed, and in a group of unexposed (n=96) births of comparable gender and birthweight. IQ scores did not differ between children with and without prenatal exposure to cocaine (mean 82.9 vs. 82.4, difference =0.5 points, 95% CI-3.1, 4.1); results were unchanged with adjustment for child height, head circumference and prior residence in a shelter or on the street, and for caregiver IQ and home environment (mean difference =2.2 points, 95% CI-1.5, 5.8). © 1998 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Cocaine; Intelligence; Child development; Prenatal exposure
1. Introduction Early reports, soon after cocaine use reached epidemic proportions in the late 1980s, stimulated widespread concern that prenatal exposure might lead to serious developmental deficits. Concerns have abated as few systematic studies have shown developmental effects, at least at very young ages (Mayes et al., 1992; Olson et al., 1995) Among other factors, inconsistencies across earlier studies may reflect the small numbers of subjects, and insufficient control for socio-demographic confounders likely to co-occur with both maternal cocaine use and adverse developmental outcomes
* Corresponding author.
(Richardson and Day, 1994; Neuspiel, 1995). Study of the association between prenatal cocaine exposure and developmental deficits, specifically poorer performance on intelligence (IQ) tests, is complicated by the fact that in urban settings, prenatal use of cocaine is associated with a constellation of other factors (Woods et al., 1993, 1995) that influence child development (McLoyd, 1990). These include poverty, abandonment, inadequate parenting, and prenatal exposure to other drugs. While only a few studies have controlled for socio-demographic confounders, almost none has assessed additional other important contributors to child intelligence, such as maternal intelligence, or the quality of the child rearing environment. Further, because of the social circumstances in which cocaine use occurs, follow-up rates for exposed women
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and children are likely to be poor, yielding unrepresentative samples of cocaine-exposed children. Most previous studies draw on infants, with only a few (Chasnoff et al., 1992; Griffith et al., 1994; Hurt et al., 1995) investigating children as old as 2 or 3 years. In this later age group prenatal cocaine exposure shows no consistent association with child development. For example, in a series of reports (Chasnoff et al., 1992; Azuma and Chasnoff, 1993; Griffith et al., 1994) Chasnoff et al. reported on outcomes at ages 2 and 3 years in children born to mothers participating in a drug treatment program during the course of the study. Approximately 50% of the cohort was retained through age 3 years (Azuma and Chasnoff, 1993). It is difficult to summarize these findings because sample sizes and group definitions differ across reports; only one analysis controlled for child rearing quality and none controlled for other potentially confounding variables such as gender or maternal education. This series of reports suggests that cocaine-exposed children generally did not do as well as unexposed children, but findings are inconsistent across ages and measures and there were few effects specific to cocaine. In another larger prospective study of about 125 children (55% of the original cohort) followed to age 30 months, there were no differences between exposed and unexposed children in Bayley developmental scores at any assessment point (Hurt et al., 1995). Although analyses did not control for potential social confounders, it is unlikely that this null result is confounded by demographic or other factors since exposed and unexposed children were comparable in race and gender and no other factors (e.g. head circumference and foster care residence) were associated with developmental scores. Age 2 developmental tests correlate only weakly with school age IQ (McCall, 1979). While the above reports suggest that prenatal cocaine exposure has little or no effect on early development, the rather low predictive utility of 2-year developmental scores means that existing studies offer little information as to the long-term developmental consequences of prenatal cocaine use. In order to examine whether in utero cocaine exposure is associated with intellectual functioning in the school years, the present investigation located and assessed intelligence in a sample of prenatally exposed and unexposed children at ages 6 – 9 years.
2. Methods All aspects of data collection, including recruitment, assessment, and data cleaning, were conducted blind to child exposure status.
2.1. Subjects The medical records of all singleton live births (n= 2810) born at Harlem Hospital in New York City between September 1, 1985 and August 31, 1986 were screened for evidence of prenatal exposure to cocaine, based on indication in the chart of either a positive history of cocaine use during pregnancy or a positive toxicology report of cocaine metabolites present in the infant’s urine (Bateman et al., 1993). During that time period, universal toxicology screening was performed for cocaine, opiates, methadone and amphetamines. During that time period, 94% (n =2644) of singleton births had urine tests. By these procedures, 363 infants were identified as ‘cocaine exposed’, including two additional children not previously (Bateman et al., 1993) identified.
2.1.1. Exclusionary criteria Harlem Hospital serves an almost exclusively African-American population. For this reason and because tests of child intelligence and achievement used in this report have been standardized only in English, we excluded from study children whose surname was Spanish (n= 47), under the assumption that these children and/or their caregivers were less likely to speak English in the home. Additional exclusionary criteria included birthweight B 2000 g (n=21), neonatal death (n=3), and the presence of significant congenital anomalies such as Down’s syndrome (n= 3). In addition, we excluded two infants who were initially incorrectly coded as single births, but were found on review to be twins; additional clerical errors resulted in the exclusion of six infants. In sum, then, 281 prenatally exposed infants were selected. 2.1.2. Exposure history Of the 281 exposed infants, 41 had a positive history of cocaine exposure only (including one child with a missing toxicology report), 61 had a positive urine screen only (including one with unknown maternal history), and 179 had both a positive history and a positive urine screen. Besides exposure to prentatal cocaine, many mothers were using other drugs as well, including methadone. Excluding tobacco, alcohol and marijuana, based on either history or toxicology report of non-cocaine substances, 229 (82%) mothers used only cocaine and 52 mothers used other substances in addition to cocaine. Of these 52, 21 used cocaine and heroin only, 12 used cocaine and PCP only, and 19 used more than one other drug. No mother tested for, or reported, methadone and cocaine use in combination, unless she also used heroin. 2.1.3. Unexposed comparison group We chose an unexposed (based on chart indication of
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negative history and negative toxicology screen) comparison group from singleton births within the same time period, using the same exclusion criteria. In order to obtain a sample of comparable birthweight and sex, for each exposed child, we selected the closest-born, same-sexed child with a birthweight that was within 200 g of the exposed child’s birthweight. For four exposed infants, birthweight was matched within 201– 500 g. One exposed infant was not matched for birthweight and was therefore excluded from the sample. Five exposed infants, matched with infants of the opposite sex, were retained in the sample. Thus the final sample consists of 280 prenatally exposed children and their 280 unexposed matches. One unexposed child was noted during the home interview to have Down’s syndrome, although this was not recorded in his chart; this child was excluded from the analysis.
2.1.4. Comparisons between mothers using and not using cocaine Comparisons of data from birth certificates (available for 273 exposed and 272 unexposed children, Lumey et al., 1996) showed that mothers who used cocaine were significantly older, less likely to be married, more likely to have been born in the USA, and less likely to be primiparous. Mothers using cocaine were somewhat, although not significantly so, more likely to be receiving Medicaid. Cocaine users and non-users did not differ in maternal education, gestational age, type of delivery, or infant APGAR score. 2.2. Procedure 2.2.1. Sample retrie6al We attempted to locate the 560 children beginning in December 1992. Several data sources were searched in an effort to locate subjects. For the 2 years that sample retrieval was taking place, the New York City Board of Education repeatedly scanned its records for children who matched subjects on name, sex, and date of birth. Once they located a child in a given school, that school’s principal was contacted to ask for release of an address so that the family could be contacted. Subjects not located through the Board of Education records were sought through other databases, including the Visiting Nurse Service of NYC, medical records of the study hospital and its affiliates, NYC Department of Health Child Health Stations records, records of the School Health Program at the study hospital, and telephone directories. We were unable to obtain permission to trace families through Medicaid information. Families for whom we obtained addresses were sent a letter describing the study, and were asked to return a ‘Do not contact’ stamped postcard if they did not wish to participate. Families whose letters were not
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returned by the post office, and who had not responded within 2 weeks, and who had an available telephone number, were contacted by field staff in order to arrange a visit to discuss the study. Families without telephones were visited at home. In a number of cases, the field interviewer arrived at an apartment only to determine that the family had moved. If this happened, a team of ‘trackers’ familiar with neighborhoods near the study hospital and with experience at a local mental health outreach program, returned to the neighborhood to ask neighbors if they had any forwarding information. Altogether we were able to locate and assess 206 families (37% of the sample), 98 exposed and 108 unexposed (Table 1). Of those located but not assessed, seven children were reported dead and 39 were reported to have moved out of state according to family members or neighbors. Families of 99 children (18%) refused participation, either actively or passively. Active refusals included seven exposed and one unexposed child in foster care settings where we were unable to obtain access to the child (although other foster parents did permit access). Passive refusals included repeated broken appointments and repeated ‘no-shows’. Rates of assessing children and families did not differ between exposed and unexposed groups (x 2 (1, n6 = 559)= 0.41, ns). Drawing on birth certificate information, we examined whether assessed children differed from those located but not assessed (primarily refusers) and from those not found (Lumey et al., 1996), separately for the exposed and unexposed groups. Among exposed and unexposed children separately, there were no significant differences across these three groups in marital status, Table 1 Subject retrieval for children with and without prenatal exposure to cocaine Exposed n =280
Unexposed n = 280
Assessed IQ test completedb IQ test not completed
98 88 10
108a 97 11
Refused Active refusal Passive refusalc
48 45 3
51 48 3
Child reported dead Child reported to have moved out of state Not found
6 18
1 21
110
99
a Includes one assessed comparison child found, at assessment, to have Down’s syndrome. Child is excluded from analyses. b Includes two exposed and three unexposed children with IQ tests administered in the homes and two children whose parents refuse home interviews. c Repeated broken appointments.
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Medicaid status, maternal age, the proportion primiparous, birthweight, or gender. In both exposure groups, the mothers of children who were not located were more likely to be foreign-born than were the mothers of children who were located.
2.2.2. Home inter6iew Once families were located, a home interview was arranged, wherein study procedures were explained and consent was obtained. The 3-hour home interview gathered information from the caregiver on parental academic/occupational history, family structure, and the childrearing qualities of the home environment. Caregivers were interviewed regarding their own histories and, if known, the histories of the biological mothers. 2.2.3. Clinic assessment The caregiver and child came to the study clinic for a medical and neurologic examination, and a psychological assessment, provided by a pediatrician and a Master’s-level psychologist, respectively. Most children were tested within 6 weeks of their home visit; 2% were tested more than 6 months after the visit. During the testing session, the caregiver’s intelligence was assessed. In seven instances (five exposed and two unexposed), the caregiver interviewed in the home was not the person who accompanied the child to the clinic. Unless indicated otherwise, below we use the term ‘caregiver’ to refer to the adult who accompanied the child to the clinic and whose intelligence was tested. 2.3. Measures 2.3.1. WISC-III (Wechsler, 1991) Child intelligence was measured with the WISC-III. This measure of child intelligence has outstanding reliability and predictive validity for its three summary scales (verbal, performance and full scale). 2.3.2. Demographic information Demographic information, obtained during the home interview, included, as noted, information regarding occupational/educational history of the caretaker, and residential history of the child. 2.3.3. HOME The elementary-age version of the Home Observation for Measurement of the Environment (HOME: Caldwell and Bradley, 1984) provided an index of the quality of the home environment. The instrument combines observational and interview information on different aspects of the home environment, such as parental warmth and acceptance towards the child, physical punishment, and provision of opportunities for learning. The instrument is reliable over time and predicts
childrens’ subsequent cognitive development (Bradley et al., 1989).
2.3.4. Ra6en’s Standard Progressi6e Matrices (Ra6en et al., 1983) Caretaker intelligence was assessed by the Standard Progressive Matrices. There are 60 problems of increasing difficulty; for each, the subject is asked to make sense of the relations among visually-presented material. Both short-term stability and associations with individually-administered tests of intelligence are good. 2.3.5. Height and head circumference The child’s height was measured in centimeters using a stadiometer. The child was instructed to stand as tall as possible with feet flat on the ground, heels and shoulders against the back board and the chin parallel to the floor. Head circumference was determined using a millimetered measuring tape placed above the supraorbital ridges over the most prominent part of the forehead and over the most prominent occipital region to yield the maximum circumference. Head circumference was measured twice; analyses were performed using the average of the two measures. 2.4. Statistical methods Ordinary least squares regression analysis was used to estimate associations between prenatal exposure to cocaine and full scale, verbal, and performance IQ scores, adjusting for potential confounders. We defined as a potential confounder any variable independently associated (at PB 0.10 or less) with full scale IQ in the total sample in a regression model that did not include a term for prenatal cocaine exposure. Potential confounders were identified in two steps: (i) by inspection of full scale IQ scores across strata of selected covariates; (ii) in a series of regression analyses to identify, from among those covariates screened in the first step, those with independent associations with full scale IQ. Variables screened for associations with full scale WISC-III score included both child and caretaker characteristics. Child characteristics included sex, age, birthweight, place of origin of the biological mother, head circumference, height, whether the child was ever in foster care, if the child had lived in three or more different apartments, whether the child had ever resided on the street or in a shelter, the number of children in the home, and whether the child lived with all biological siblings. Caretaker characteristics included: IQ, relationship to the child, sex, age, education, current support on public assistance, reported use of cocaine since 1985 (reflecting postnatal exposure for the target child), quality of the home environment, and whether the caretaker was currently employed. The child’s current head circumference and height were defined as
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z-scores, based on age- and sex-specific norms available from the Fels and National Center for Health Statistics surveys (Hamill et al., 1979; Roche et al., 1987. Although these norms are based primarily on white children, they permitted us to rank our sample on head circumference and height without inadvertent control of cocaine exposure. Such inadvertent control would occur with the use of sample-based, rather than survey-based, z-scores if cocaine were associated with either decreased head circumference or growth. Among the covariates screened, five were associated with full scale IQ score. Full scale IQ increased with increasing caretaker IQ, increasing HOME score, and with increasing head circumference. IQ decreased with increasing height, and was lower in children who had lived in the street or a shelter. The primary regression analyses adjust for these five potential confounders; all except ‘lived in street or shelter’ were analyzed as continuous variables. Estimated associations between prenatal cocaine exposure and IQ were nearly identical when analyses were repeated without adjustment for head circumference and height (which might be viewed as potentially intervening between exposure and IQ); they were also unchanged when we adjusted for child age, sex, and the logarithm of blood lead level (collected on 151 children). In a secondary analysis, we further classified cocaine-exposed children into those with (n= 16) and without (n = 72) evidence of prentatal exposure to heroin, methadone, or PCP, based on either maternal medical record or infant toxicology test.
3. Results
3.1. Sample characteristics Tables 2 and 3 present sample characteristics for exposed and unexposed children and their caretakers. The sample as a whole demonstrates considerable economic impoverishment. While most children (64%) were living with their biological mothers, a large proportion resided with someone else, usually a grandmother (18%). Many caregivers had not gone beyond high school (44%), and 3% had completed less than 8 years of schooling. Most families (63%) received public assistance, and most caregivers (66%) were not employed outside the home. Almost all (91%) biological mothers had been born in the US. At some time prior to assessment, 17% of children had been placed in foster care, 30% did not live together with all their siblings, 16% had spent some time living in the street or in a shelter, and 22% had already lived in three or more apartments at the time of testing. Compared with caregivers of unexposed children, caregivers of exposed children were less likely to be their biological parents [x 2(2, n = 179) =14.18, P B 0.001],
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Table 2 Selected characteristics of caregivers of childrena with and without prenatal exposure to cocaine Cocaine exposedb n =88
Unexposedb n =96
Relationship to child** Biological parent Grandparent Other
54.7% 26.7% 18.6%
80.6% 12.9% 6.5%
Sex (female) Mean age (years)**
94.2% 44.0 (13.0)
96.7% 35.7 (10.4)
51.2% 30.2%
37.4% 37.4%
Caregiver characteristics
Education completed BHigh school High school graduate/ GED Beyond high school No household public assistance Postnatal cocaine use** IQc,* Currently employed
18.6%
25.3%
36.5%
37.0%
33.7% 30.1 (10.2) 27.9%
9.5% 34.4 (9.4) 39.6%
a
SD, where applicable, in parentheses. Includes all children with IQ assessments; n varies slightly because of missing data; unexposed group does not include child found to have Down’s Syndrome. c Percentile score on Raven’s Progressive Matrices. *PB0.01, **PB0.001 b
and were older [t(163.22)= 4.63, PB 0.0001], as would be expected for grandparents. Caregivers of exposed children were somewhat less likely to be currently employed [x 2(1, n=177)= 2.68, PB 0.10], received lower scores on the Raven’s Progressive Matrices [t(176)= 2.96, PB 0.01], and were more likely to report postnatal cocaine use (i.e. after 1985) [x 2 (1, n=181)= 16.00, PB0.0001] than those of unexposed children. Exposed and unexposed children were similar in age, sex, and birthweight, as would be expected from study selection procedures (Table 3). Compared with unexposed children, exposed children were somewhat more likely to have a biological mother who was born in the USA [x 2 (2, n= 176)=5.73, P= 0.06], and were shorter [t(174)= 1.19, P B0.05]. Exposed and unexposed children did not differ in head circumference. Exposed and unexposed children differed in a number of markers of the social environment (Table 3), with exposed children more likely to have spent time in foster care [x 2 (1, n= 181)= 7.96, P= 0.005] and less likely to reside with all their siblings [x 2 (2, n= 181)=5.36, P= 0.07].
3.2. Cocaine and IQ Unadjusted full scale IQ was similar in exposed and unexposed children (mean IQs 82.9 and 82.4, respec-
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tively; difference=0.5 points, 95% CI − 3.1, 4.1). Table 4 presents the results of regression analyses, predicting full scale IQ from the set of covariates, with and without consideration of exposure status. As noted, estimated associations between prenatal cocaine exposure and IQ were nearly identical when analyses were repeated with adjustment for head circumference, height, caregiver’s intelligence, HOME score, and whether or not the child had ever lived in a shelter or on the street. With adjustment for covariates, the estimated difference in IQ between exposed and unexposed children was 2.2 points (95% CI − 1.5, 5.8). Altogether, the five covariates accounted for 24% of the variance in full scale IQ; the addition of exposure status to the
Table 4 Regression coefficients relating prenatal cocaine exposure and sociodemographic factors to changes in full scale IQa
Head circumference z-score Height z-score Caregiver IQ HOME score Child ever lived in shelter or on street Cocaine exposure Cumulative R 2
Model without exposure status
Model with exposure status
B
B
3.76*** −2.25* 0.34*** 0.38** −4.43*
3.78*** −2.18* 0.37*** 0.38** −3.93
— R 2 =0.24
2.19 R 2 =0.25
a
Table 3 Child and social characteristics for childrena with and without prenatal exposure to cocaine Child characteristics
Child characteristics Mean age (months)* Sex (% boy) Mean birthweight (g) Mean head circumference (cm) Mean head circumference z-scorec Mean height (cm)** Mean height z-scorec Family origin* Biological mother USAborn African-American Biological mother foreign-born AfricanAmerican Other Social characteristics Residence history Ever placed in foster care*** Lived in 3+apartments Ever lived in street/shelter Number of other children in home Mean HOME Score Sibship composition* No siblings Has siblings, but not all living with study child All siblings living with study child a
Cocaine exposedb n= 88
Unexposedb n= 96
93.5 (7.7) 53.4% 2804 (457) 51.8 (1.4)
95.6 (7.6) 50.0% 2851 (424) 52.0 (1.4)
−0.41 (1.0)
−0.24 (0.96)
127.0 (6.5) 0.69 (1.1)
129.0 (7.0) 0.92 (1.1)
96.3%
86.2%
1.2%
7.4%
2.4%
6.4%
26.7%
10.5%
18.8% 10.8%
23.4% 17.9%
model explained a further 1% of the variance in IQ. Results were unchanged when we adjusted for only caregiver IQ, HOME, and living in street/shelter (B= 1.8, 95% CI − 1.8, 5.4) and when we added child age and sex to the model (B= 2.6, 95% CI − 1.1, 6.3). Similarly, with adjustment for log blood lead level, associations between cocaine exposure and IQ were unchanged; the estimated difference between exposed and unexposed children was 2.7 points (95% CI= − 1.2, 6.5). Concurrent blood lead level had a small adverse association with full scale IQ, explaining 2% of the variance in full scale IQ [B per unit log blood lead= − 3.2, 95% CI − 6.5, 0.15, PB 0.06].
3.3. Polydrug use Results were also unchanged when exposed children were further classified by whether or not there was evidence of prenatal exposure to heroin, methadone or PCP. Compared with unexposed children, full scale IQ was higher by an estimated 1.9 points (95% CI −1.9, 5.7) in the 61 children with exposure to cocaine only and higher by an estimated 3.6 points (95% CI −3.0, 10.2) in the 14 children with exposure to cocaine plus other drugs.
2.0 (1.8)
1.9 (1.8)
41.0 (8.0)
41.4 (7.6)
12.8% 36.0%
12.6% 21.1%
3.4. Verbal and performance IQ
51.2%
66.3%
Results were similar when analyses were conducted to examine associations with verbal and performance IQ. With adjustment for the five covariates, verbal and performance IQs were an estimated 1.3 (95% CI −2.5, 5.1) and 2.7 (95% CI −1.1, 6.6) points higher, respectively, in exposed children compared with those who were unexposed.
SD, where applicable, in parentheses. Includes all children with IQ assessments; n varies slightly because of missing data. c Based on age- and sex-specific norms. See Section 2.4. *PB0.10, **PB0.05, ***PB0.01. b
Regression analyses based on 75 exposed and 88 unexposed children with complete data on all covariates. *PB0.10, ** PB0.01, ***PB0.001.
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4. Discussion We found no association between prenatal cocaine exposure and intelligence in 6 – 9-year-old children. These results are consistent with other systematic studies at earlier ages. This study represents the largest follow-up of such children to date that extends into the school years. In contrast to the lack of adverse associations with prenatal cocaine exposure, we observed the expected associations between social factors and school-age intelligence. Mean IQ was low in both exposed and unexposed children relative to test norms; this was expectable considering the social adversity common to many children in this study. Measures of growth (head circumference and height), and of the social environment (caregiver’s intelligence, HOME score, and residence in shelter/street) explained 24% of the variance in school-age intelligence. The strength of associations between covariates and intelligence was the same for exposed and unexposed children. Although our findings are consistent with the few existing studies, inferences are limited by the low retrieval rate (37%), which leaves open the possibility that either group of children (exposed or unexposed) may not be representative of their respective cohorts. On the other hand, we found that families located and assessed did not differ from the target cohort in several socioeconomic variables, including marital status, Medicaid status, maternal age, the proportion primiparous, birthweight, or gender, so that our results may not be vulnerable to selection bias. However, data available at birth, on which comparisons were possible, included few variables with known strong associations with intelligence. Our low follow-up rate reflects the challenges of attempting to locate an impoverished inner-city sample 7 years after birth. In a number of cases, we had minimal perinatal information. Some children were listed only by surname, not having been given a first name before they left the hospital. Some mothers had changed their surnames or the child’s surname or first name in the 7 years since birth, due to marriage or to the father’s acknowledging paternity. Many children were not being reared by their biological mothers. Some mothers, it was discovered, had given inaccurate personal information at the time of birth, and some had listed their address at the time of birth at what turned out, 7 years later, to be a vacant lot. Despite Board of Education cooperation, many of the addresses provided were incorrect; many children had been transferred to another school in between our locating them in the Board data files and contacting the school. Some school principals declined co-operation. Many letters were returned by the post office indicating that the family had moved or that the address did not exist.
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Due to the problems in locating and assessing a difficult sample population over time, future studies of the effects of prenatal cocaine exposure might consider following well-defined samples prospectively from birth. On the other hand, given that studies to date have not noted significant adverse outcomes in cocaine-exposed children at follow-up, it may well be that the considerable resources necessary to conduct a definitive followup study would best be spent on some other issue. A further limitation of the study is the possibility that some of the unexposed children were, in fact, exposed prenatally. The urine test used to define exposure is sensitive to maternal cocaine use within the 2–3 days preceding the test (Hamilton et al., 1977); maternal report has been shown to be invalid in several urban settings (Zuckerman et al., 1989; Sackoff et al., 1992; Grant et al., 1994; Kline et al., 1997). Caregivers in the present study were asked whether the child’s biological mother had ever used cocaine; 15% (n =74) of the biological mothers of unexposed children reported that they had previously used cocaine and 52% (n= 21) of the non-maternal caregivers of unexposed children reported that the child’s biological mother had used cocaine at some time. These data most likely underestimate the likelihood of maternal cocaine use. While we are not able to determine the timing of maternal cocaine use relative to the pregnancy, these reports raise the possibility that some of the children in the unexposed group were exposed prenatally to cocaine. Misclassification of exposure status would ordinarily lead to an underestimate of the true association between exposure and IQ. However, in light of our results, which show essentially no differences between exposed and unexposed children, we cannot predict the direction of the true association, if any, between prenatal cocaine and children’s IQ. In summary, in this sample, cocaine use during pregnancy occurred in a context of multiple risks for child developmental outcome; to a large extent, these risks are common to families raising children in urban poverty. Within this environment, prenatal cocaine exposure does not seem to confer an additional risk for adverse developmental outcome.
Acknowledgements This research was supported by grants from the National Institute on Drug Abuse (R01-DA07612; Margaret C. Heagarty, MD, Principal Investigator) and from the Leon Lowenstein Foundation (Gail Wasserman, Ph.D. , Principal Investigator). We acknowledge Dr Stephen K. Ng for his central contributions to the design and initiation of this study. We are grateful to Aida Musabegovic and Tracy Unger, who conducted the assessments of children’s intelligence.
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References Azuma, S.D., Chasnoff, I.J., 1993. Outcome of children prenatally exposed to cocaine and other drugs: a path analysis of 3-year data. Pediatrics 92, 396–402. Bateman, D.A., Ng, S.K., Hansen, C.A., Heagarty, M.C., 1993. The effects of intrauterine cocaine exposure in newborns. Am. J. Public Health 83, 190–193. Bradley, R.H., Caldwell, B.M., Rock, S.L., Barnard, K.E., Gray, C., Hammond, M.A., Mitchell, S., Siegel, L., Gottfried, A., Johnson, D.L., 1989. Home environment and cognitive development in the first 3 years of life: a collaborative study involving six sites and three ethnic groups in North America. Dev. Psychol. 25, 217 – 235. Caldwell, B.M., Bradley, R.H., 1984. Home Observation for Measurement of the Environment. University of Arkansas at Little Rock, Little Rock, AR. Chasnoff, I.J., Griffith, D.R., Freier, C., Murray, J., 1992. Cocaine/ polydrug use in pregnancy: 2-year follow up. Pediatrics 89, 284 – 289. Grant, T., Brown, Z., Callahan, C., Barr, H., Streissguth, A.P., 1994. Cocaine exposure during pregnancy: improving assessment with radioimmunoassay of maternal hair. Obstet. Gynecol. 83, 524 – 531. Griffith, D.R., Azuma, S.D., Chasnoff, I.J., 1994. Three-year outcome of children exposed prenatally to drugs. J. Am. Acad. Child Adolesc. Psychiatry 33, 20–27. Hamill, P.V., Drizd, T.A., Johnson, C.L., Reed, R.B., Roche, A.F., Moore, W.M., 1979. Physical growth: National Center for Health Statistics percentiles. Am. J. Clin. Nutr. 32, 607–629. Hamilton, H.E., Wallace, J.E., Shimek, E.L., Land, P., Harris, S.C., Christenson, J.G., 1977. Cocaine and benzolecgonine excretion in humans. J. Forensic Sci. 22, 697–707. Hurt, H., Brodsky, N.L., Betancourt, L., Braitman, L.E., Malmud, E., Giannetta, J., 1995. Cocaine-exposed children: follow-up through 30 months. Dev. Behav. Pediatr. 16, 29–35. Kline, J., Ng, S.K., Schittini, M., Levin, B., Susser, M., 1997. Cocaine use during pregnancy: sensitive detection by hair assay. Am. J. Public Health 87, 352–358. Lumey, L.H., Bateman, D.A., Kline, J.K., Wasserman, G.A., Chiriboga, C., Friedlander, H., Melton, L., Heagarty M.C., 1996. Newborn Follow-up in an Inner-City Population with Pregnancy Cocaine Use. Paper presented at the 1996 MICHEP Workshop, Centers for Disease Control, Atlanta, GA, December, 1996.
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Mayes, L.C., Granger, R.H., Bornstein, M.H., Zuckerman, B., 1992. The problem of prenatal cocaine exposure: a rush to judgement. J. Am. Med. Assoc. 267, 406 – 408. McCall, R.B., 1979. The development of intellectual functioning in infancy and the prediction of later IQ. In: Osofsky, J.D. (Ed.), Handbook of Infant Development. Wiley, New York, pp. 707– 741. McLoyd, V.C., 1990. The impact of economic hardship on black families and children. Psychological distress, parenting, and socioemotional development. Child Dev. 61, 311 – 346. Neuspiel, D.R., 1995. The problem of confounding in research on prenatal cocaine effects on behavior and development. In: Lewis, M., Bendersky, M. (Eds.), Mothers, Babies and Cocaine: The Role of Toxins in Development. Lawrence Erlbaum, Hillsdale, NJ, pp. 95 – 109. Olson, H.C., Grant, T.M., Martin, J.C., Streissguth, A.P., 1995. A cohort study of prenatal cocaine exposure: addressing methodological concerns. In: Lewis, M., Bendersky, M. (Eds.), Mothers, Babies and Cocaine: The Role of Toxins in Development. Lawrence Erlbaum, Hillsdale, NJ, pp. 129 – 162. Raven, J.C., Court, J.H., Raven, J., 1983. Manual for Raven’s Progressive Matrices and Vocabulary Scales (Section 3) –Standard Progressive Matrices, Lewis, London. Richardson, G.A., Day, N.L., 1994. Detrimental effects of prenatal cocaine exposure: illusion or reality? J. Am. Acad. Child Adolesc. Psychiatry 33, 28 – 34. Roche, A.F., Mukherjee, D., Guo, S.M., Moore, W.M., 1987. Head circumference reference data: birth to 18 years. Pediatrics 79, 706 – 712. Sackoff, J., Kline, J., Kinney, A., Grunebaum, A., 1992. Cocaine use in patients under-reported. Am. J. Public Health 82, 1043. Wechsler, D., 1991. Manual for the WISC-III. Psychological Corporation, San Antonio, TX. Woods, N.S., Behnke, M., Eyler, F.D., Conlon, M., Wobie, K., 1995. Cocaine use among pregnant women: socioeconomic, obstetrical and psychological issues. In: Lewis, M., Bendersky, M. (Eds.), Mothers, Babies, and Cocaine: The Role of Toxins in Development. Lawrence Erlbaum, Hillsdale, NJ, pp. 305 – 332. Woods, N.S., Eyler, F.D., Behnke, M., Conlon, M., 1993. Cocaine use during pregnancy: maternal depressive symptoms and infant neurobehavior over the first month. Infant Behav. Dev. 116, 83 – 98. Zuckerman, B., Frank, D.A., Hingson, R., Amaro, H., Levenson, S.M., Kayne, H., Parker, S., Vinci, R., Aboagye, K., Fried, L.E., 1989. Effects of maternal marijuana and cocaine use on fetal growth. New Engl. J. Med. 320, 762 – 768.
Prenatal cocaine exposure and school-age intelligence Gail A. Wasserman a,b,*, Jennie K. Kline b,c,d, David A. Bateman e,f, Claudia Chiriboga f,g, Lambert H. Lumey c,h, Helen Friedlander i, Laura Melton b, Margaret C. Heagarty e,f b
a Department of Child Psychiatry, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA New York State Psychiatric Institute, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA c Sergie6sky Center, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA d School of Public Health, Columbia Uni6ersity, New York, NY, USA e Department of Pediatrics, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA f Harlem Hospital Center, New York, NY, USA g Di6ision of Pediatric Neurology, College of Physicians and Surgeons, Columbia Uni6ersity, New York, NY, USA h American Health Foundation, New York, NY, USA i New York City Board of Education, New York, NY, USA
Accepted 1 January 1998
Abstract Assessments of the possible consequences of prenatal exposure to cocaine have been limited by lack of control for socio-demographic confounders and lack of follow-up into the school years. We evaluated intelligence at ages 6 – 9 years in 88 children from a cohort of 280 born between September 1, 1985 and August 31, 1986 and identified at birth as cocaine-exposed, and in a group of unexposed (n=96) births of comparable gender and birthweight. IQ scores did not differ between children with and without prenatal exposure to cocaine (mean 82.9 vs. 82.4, difference =0.5 points, 95% CI-3.1, 4.1); results were unchanged with adjustment for child height, head circumference and prior residence in a shelter or on the street, and for caregiver IQ and home environment (mean difference =2.2 points, 95% CI-1.5, 5.8). © 1998 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Cocaine; Intelligence; Child development; Prenatal exposure
1. Introduction Early reports, soon after cocaine use reached epidemic proportions in the late 1980s, stimulated widespread concern that prenatal exposure might lead to serious developmental deficits. Concerns have abated as few systematic studies have shown developmental effects, at least at very young ages (Mayes et al., 1992; Olson et al., 1995) Among other factors, inconsistencies across earlier studies may reflect the small numbers of subjects, and insufficient control for socio-demographic confounders likely to co-occur with both maternal cocaine use and adverse developmental outcomes
* Corresponding author.
(Richardson and Day, 1994; Neuspiel, 1995). Study of the association between prenatal cocaine exposure and developmental deficits, specifically poorer performance on intelligence (IQ) tests, is complicated by the fact that in urban settings, prenatal use of cocaine is associated with a constellation of other factors (Woods et al., 1993, 1995) that influence child development (McLoyd, 1990). These include poverty, abandonment, inadequate parenting, and prenatal exposure to other drugs. While only a few studies have controlled for socio-demographic confounders, almost none has assessed additional other important contributors to child intelligence, such as maternal intelligence, or the quality of the child rearing environment. Further, because of the social circumstances in which cocaine use occurs, follow-up rates for exposed women
0376-8716/98/$19.00 © 1998 Elsevier Science Ireland Ltd. All rights reserved. PII S0376-8716(98)00037-4
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and children are likely to be poor, yielding unrepresentative samples of cocaine-exposed children. Most previous studies draw on infants, with only a few (Chasnoff et al., 1992; Griffith et al., 1994; Hurt et al., 1995) investigating children as old as 2 or 3 years. In this later age group prenatal cocaine exposure shows no consistent association with child development. For example, in a series of reports (Chasnoff et al., 1992; Azuma and Chasnoff, 1993; Griffith et al., 1994) Chasnoff et al. reported on outcomes at ages 2 and 3 years in children born to mothers participating in a drug treatment program during the course of the study. Approximately 50% of the cohort was retained through age 3 years (Azuma and Chasnoff, 1993). It is difficult to summarize these findings because sample sizes and group definitions differ across reports; only one analysis controlled for child rearing quality and none controlled for other potentially confounding variables such as gender or maternal education. This series of reports suggests that cocaine-exposed children generally did not do as well as unexposed children, but findings are inconsistent across ages and measures and there were few effects specific to cocaine. In another larger prospective study of about 125 children (55% of the original cohort) followed to age 30 months, there were no differences between exposed and unexposed children in Bayley developmental scores at any assessment point (Hurt et al., 1995). Although analyses did not control for potential social confounders, it is unlikely that this null result is confounded by demographic or other factors since exposed and unexposed children were comparable in race and gender and no other factors (e.g. head circumference and foster care residence) were associated with developmental scores. Age 2 developmental tests correlate only weakly with school age IQ (McCall, 1979). While the above reports suggest that prenatal cocaine exposure has little or no effect on early development, the rather low predictive utility of 2-year developmental scores means that existing studies offer little information as to the long-term developmental consequences of prenatal cocaine use. In order to examine whether in utero cocaine exposure is associated with intellectual functioning in the school years, the present investigation located and assessed intelligence in a sample of prenatally exposed and unexposed children at ages 6 – 9 years.
2. Methods All aspects of data collection, including recruitment, assessment, and data cleaning, were conducted blind to child exposure status.
2.1. Subjects The medical records of all singleton live births (n= 2810) born at Harlem Hospital in New York City between September 1, 1985 and August 31, 1986 were screened for evidence of prenatal exposure to cocaine, based on indication in the chart of either a positive history of cocaine use during pregnancy or a positive toxicology report of cocaine metabolites present in the infant’s urine (Bateman et al., 1993). During that time period, universal toxicology screening was performed for cocaine, opiates, methadone and amphetamines. During that time period, 94% (n =2644) of singleton births had urine tests. By these procedures, 363 infants were identified as ‘cocaine exposed’, including two additional children not previously (Bateman et al., 1993) identified.
2.1.1. Exclusionary criteria Harlem Hospital serves an almost exclusively African-American population. For this reason and because tests of child intelligence and achievement used in this report have been standardized only in English, we excluded from study children whose surname was Spanish (n= 47), under the assumption that these children and/or their caregivers were less likely to speak English in the home. Additional exclusionary criteria included birthweight B 2000 g (n=21), neonatal death (n=3), and the presence of significant congenital anomalies such as Down’s syndrome (n= 3). In addition, we excluded two infants who were initially incorrectly coded as single births, but were found on review to be twins; additional clerical errors resulted in the exclusion of six infants. In sum, then, 281 prenatally exposed infants were selected. 2.1.2. Exposure history Of the 281 exposed infants, 41 had a positive history of cocaine exposure only (including one child with a missing toxicology report), 61 had a positive urine screen only (including one with unknown maternal history), and 179 had both a positive history and a positive urine screen. Besides exposure to prentatal cocaine, many mothers were using other drugs as well, including methadone. Excluding tobacco, alcohol and marijuana, based on either history or toxicology report of non-cocaine substances, 229 (82%) mothers used only cocaine and 52 mothers used other substances in addition to cocaine. Of these 52, 21 used cocaine and heroin only, 12 used cocaine and PCP only, and 19 used more than one other drug. No mother tested for, or reported, methadone and cocaine use in combination, unless she also used heroin. 2.1.3. Unexposed comparison group We chose an unexposed (based on chart indication of
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negative history and negative toxicology screen) comparison group from singleton births within the same time period, using the same exclusion criteria. In order to obtain a sample of comparable birthweight and sex, for each exposed child, we selected the closest-born, same-sexed child with a birthweight that was within 200 g of the exposed child’s birthweight. For four exposed infants, birthweight was matched within 201– 500 g. One exposed infant was not matched for birthweight and was therefore excluded from the sample. Five exposed infants, matched with infants of the opposite sex, were retained in the sample. Thus the final sample consists of 280 prenatally exposed children and their 280 unexposed matches. One unexposed child was noted during the home interview to have Down’s syndrome, although this was not recorded in his chart; this child was excluded from the analysis.
2.1.4. Comparisons between mothers using and not using cocaine Comparisons of data from birth certificates (available for 273 exposed and 272 unexposed children, Lumey et al., 1996) showed that mothers who used cocaine were significantly older, less likely to be married, more likely to have been born in the USA, and less likely to be primiparous. Mothers using cocaine were somewhat, although not significantly so, more likely to be receiving Medicaid. Cocaine users and non-users did not differ in maternal education, gestational age, type of delivery, or infant APGAR score. 2.2. Procedure 2.2.1. Sample retrie6al We attempted to locate the 560 children beginning in December 1992. Several data sources were searched in an effort to locate subjects. For the 2 years that sample retrieval was taking place, the New York City Board of Education repeatedly scanned its records for children who matched subjects on name, sex, and date of birth. Once they located a child in a given school, that school’s principal was contacted to ask for release of an address so that the family could be contacted. Subjects not located through the Board of Education records were sought through other databases, including the Visiting Nurse Service of NYC, medical records of the study hospital and its affiliates, NYC Department of Health Child Health Stations records, records of the School Health Program at the study hospital, and telephone directories. We were unable to obtain permission to trace families through Medicaid information. Families for whom we obtained addresses were sent a letter describing the study, and were asked to return a ‘Do not contact’ stamped postcard if they did not wish to participate. Families whose letters were not
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returned by the post office, and who had not responded within 2 weeks, and who had an available telephone number, were contacted by field staff in order to arrange a visit to discuss the study. Families without telephones were visited at home. In a number of cases, the field interviewer arrived at an apartment only to determine that the family had moved. If this happened, a team of ‘trackers’ familiar with neighborhoods near the study hospital and with experience at a local mental health outreach program, returned to the neighborhood to ask neighbors if they had any forwarding information. Altogether we were able to locate and assess 206 families (37% of the sample), 98 exposed and 108 unexposed (Table 1). Of those located but not assessed, seven children were reported dead and 39 were reported to have moved out of state according to family members or neighbors. Families of 99 children (18%) refused participation, either actively or passively. Active refusals included seven exposed and one unexposed child in foster care settings where we were unable to obtain access to the child (although other foster parents did permit access). Passive refusals included repeated broken appointments and repeated ‘no-shows’. Rates of assessing children and families did not differ between exposed and unexposed groups (x 2 (1, n6 = 559)= 0.41, ns). Drawing on birth certificate information, we examined whether assessed children differed from those located but not assessed (primarily refusers) and from those not found (Lumey et al., 1996), separately for the exposed and unexposed groups. Among exposed and unexposed children separately, there were no significant differences across these three groups in marital status, Table 1 Subject retrieval for children with and without prenatal exposure to cocaine Exposed n =280
Unexposed n = 280
Assessed IQ test completedb IQ test not completed
98 88 10
108a 97 11
Refused Active refusal Passive refusalc
48 45 3
51 48 3
Child reported dead Child reported to have moved out of state Not found
6 18
1 21
110
99
a Includes one assessed comparison child found, at assessment, to have Down’s syndrome. Child is excluded from analyses. b Includes two exposed and three unexposed children with IQ tests administered in the homes and two children whose parents refuse home interviews. c Repeated broken appointments.
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Medicaid status, maternal age, the proportion primiparous, birthweight, or gender. In both exposure groups, the mothers of children who were not located were more likely to be foreign-born than were the mothers of children who were located.
2.2.2. Home inter6iew Once families were located, a home interview was arranged, wherein study procedures were explained and consent was obtained. The 3-hour home interview gathered information from the caregiver on parental academic/occupational history, family structure, and the childrearing qualities of the home environment. Caregivers were interviewed regarding their own histories and, if known, the histories of the biological mothers. 2.2.3. Clinic assessment The caregiver and child came to the study clinic for a medical and neurologic examination, and a psychological assessment, provided by a pediatrician and a Master’s-level psychologist, respectively. Most children were tested within 6 weeks of their home visit; 2% were tested more than 6 months after the visit. During the testing session, the caregiver’s intelligence was assessed. In seven instances (five exposed and two unexposed), the caregiver interviewed in the home was not the person who accompanied the child to the clinic. Unless indicated otherwise, below we use the term ‘caregiver’ to refer to the adult who accompanied the child to the clinic and whose intelligence was tested. 2.3. Measures 2.3.1. WISC-III (Wechsler, 1991) Child intelligence was measured with the WISC-III. This measure of child intelligence has outstanding reliability and predictive validity for its three summary scales (verbal, performance and full scale). 2.3.2. Demographic information Demographic information, obtained during the home interview, included, as noted, information regarding occupational/educational history of the caretaker, and residential history of the child. 2.3.3. HOME The elementary-age version of the Home Observation for Measurement of the Environment (HOME: Caldwell and Bradley, 1984) provided an index of the quality of the home environment. The instrument combines observational and interview information on different aspects of the home environment, such as parental warmth and acceptance towards the child, physical punishment, and provision of opportunities for learning. The instrument is reliable over time and predicts
childrens’ subsequent cognitive development (Bradley et al., 1989).
2.3.4. Ra6en’s Standard Progressi6e Matrices (Ra6en et al., 1983) Caretaker intelligence was assessed by the Standard Progressive Matrices. There are 60 problems of increasing difficulty; for each, the subject is asked to make sense of the relations among visually-presented material. Both short-term stability and associations with individually-administered tests of intelligence are good. 2.3.5. Height and head circumference The child’s height was measured in centimeters using a stadiometer. The child was instructed to stand as tall as possible with feet flat on the ground, heels and shoulders against the back board and the chin parallel to the floor. Head circumference was determined using a millimetered measuring tape placed above the supraorbital ridges over the most prominent part of the forehead and over the most prominent occipital region to yield the maximum circumference. Head circumference was measured twice; analyses were performed using the average of the two measures. 2.4. Statistical methods Ordinary least squares regression analysis was used to estimate associations between prenatal exposure to cocaine and full scale, verbal, and performance IQ scores, adjusting for potential confounders. We defined as a potential confounder any variable independently associated (at PB 0.10 or less) with full scale IQ in the total sample in a regression model that did not include a term for prenatal cocaine exposure. Potential confounders were identified in two steps: (i) by inspection of full scale IQ scores across strata of selected covariates; (ii) in a series of regression analyses to identify, from among those covariates screened in the first step, those with independent associations with full scale IQ. Variables screened for associations with full scale WISC-III score included both child and caretaker characteristics. Child characteristics included sex, age, birthweight, place of origin of the biological mother, head circumference, height, whether the child was ever in foster care, if the child had lived in three or more different apartments, whether the child had ever resided on the street or in a shelter, the number of children in the home, and whether the child lived with all biological siblings. Caretaker characteristics included: IQ, relationship to the child, sex, age, education, current support on public assistance, reported use of cocaine since 1985 (reflecting postnatal exposure for the target child), quality of the home environment, and whether the caretaker was currently employed. The child’s current head circumference and height were defined as
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z-scores, based on age- and sex-specific norms available from the Fels and National Center for Health Statistics surveys (Hamill et al., 1979; Roche et al., 1987. Although these norms are based primarily on white children, they permitted us to rank our sample on head circumference and height without inadvertent control of cocaine exposure. Such inadvertent control would occur with the use of sample-based, rather than survey-based, z-scores if cocaine were associated with either decreased head circumference or growth. Among the covariates screened, five were associated with full scale IQ score. Full scale IQ increased with increasing caretaker IQ, increasing HOME score, and with increasing head circumference. IQ decreased with increasing height, and was lower in children who had lived in the street or a shelter. The primary regression analyses adjust for these five potential confounders; all except ‘lived in street or shelter’ were analyzed as continuous variables. Estimated associations between prenatal cocaine exposure and IQ were nearly identical when analyses were repeated without adjustment for head circumference and height (which might be viewed as potentially intervening between exposure and IQ); they were also unchanged when we adjusted for child age, sex, and the logarithm of blood lead level (collected on 151 children). In a secondary analysis, we further classified cocaine-exposed children into those with (n= 16) and without (n = 72) evidence of prentatal exposure to heroin, methadone, or PCP, based on either maternal medical record or infant toxicology test.
3. Results
3.1. Sample characteristics Tables 2 and 3 present sample characteristics for exposed and unexposed children and their caretakers. The sample as a whole demonstrates considerable economic impoverishment. While most children (64%) were living with their biological mothers, a large proportion resided with someone else, usually a grandmother (18%). Many caregivers had not gone beyond high school (44%), and 3% had completed less than 8 years of schooling. Most families (63%) received public assistance, and most caregivers (66%) were not employed outside the home. Almost all (91%) biological mothers had been born in the US. At some time prior to assessment, 17% of children had been placed in foster care, 30% did not live together with all their siblings, 16% had spent some time living in the street or in a shelter, and 22% had already lived in three or more apartments at the time of testing. Compared with caregivers of unexposed children, caregivers of exposed children were less likely to be their biological parents [x 2(2, n = 179) =14.18, P B 0.001],
207
Table 2 Selected characteristics of caregivers of childrena with and without prenatal exposure to cocaine Cocaine exposedb n =88
Unexposedb n =96
Relationship to child** Biological parent Grandparent Other
54.7% 26.7% 18.6%
80.6% 12.9% 6.5%
Sex (female) Mean age (years)**
94.2% 44.0 (13.0)
96.7% 35.7 (10.4)
51.2% 30.2%
37.4% 37.4%
Caregiver characteristics
Education completed BHigh school High school graduate/ GED Beyond high school No household public assistance Postnatal cocaine use** IQc,* Currently employed
18.6%
25.3%
36.5%
37.0%
33.7% 30.1 (10.2) 27.9%
9.5% 34.4 (9.4) 39.6%
a
SD, where applicable, in parentheses. Includes all children with IQ assessments; n varies slightly because of missing data; unexposed group does not include child found to have Down’s Syndrome. c Percentile score on Raven’s Progressive Matrices. *PB0.01, **PB0.001 b
and were older [t(163.22)= 4.63, PB 0.0001], as would be expected for grandparents. Caregivers of exposed children were somewhat less likely to be currently employed [x 2(1, n=177)= 2.68, PB 0.10], received lower scores on the Raven’s Progressive Matrices [t(176)= 2.96, PB 0.01], and were more likely to report postnatal cocaine use (i.e. after 1985) [x 2 (1, n=181)= 16.00, PB0.0001] than those of unexposed children. Exposed and unexposed children were similar in age, sex, and birthweight, as would be expected from study selection procedures (Table 3). Compared with unexposed children, exposed children were somewhat more likely to have a biological mother who was born in the USA [x 2 (2, n= 176)=5.73, P= 0.06], and were shorter [t(174)= 1.19, P B0.05]. Exposed and unexposed children did not differ in head circumference. Exposed and unexposed children differed in a number of markers of the social environment (Table 3), with exposed children more likely to have spent time in foster care [x 2 (1, n= 181)= 7.96, P= 0.005] and less likely to reside with all their siblings [x 2 (2, n= 181)=5.36, P= 0.07].
3.2. Cocaine and IQ Unadjusted full scale IQ was similar in exposed and unexposed children (mean IQs 82.9 and 82.4, respec-
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tively; difference=0.5 points, 95% CI − 3.1, 4.1). Table 4 presents the results of regression analyses, predicting full scale IQ from the set of covariates, with and without consideration of exposure status. As noted, estimated associations between prenatal cocaine exposure and IQ were nearly identical when analyses were repeated with adjustment for head circumference, height, caregiver’s intelligence, HOME score, and whether or not the child had ever lived in a shelter or on the street. With adjustment for covariates, the estimated difference in IQ between exposed and unexposed children was 2.2 points (95% CI − 1.5, 5.8). Altogether, the five covariates accounted for 24% of the variance in full scale IQ; the addition of exposure status to the
Table 4 Regression coefficients relating prenatal cocaine exposure and sociodemographic factors to changes in full scale IQa
Head circumference z-score Height z-score Caregiver IQ HOME score Child ever lived in shelter or on street Cocaine exposure Cumulative R 2
Model without exposure status
Model with exposure status
B
B
3.76*** −2.25* 0.34*** 0.38** −4.43*
3.78*** −2.18* 0.37*** 0.38** −3.93
— R 2 =0.24
2.19 R 2 =0.25
a
Table 3 Child and social characteristics for childrena with and without prenatal exposure to cocaine Child characteristics
Child characteristics Mean age (months)* Sex (% boy) Mean birthweight (g) Mean head circumference (cm) Mean head circumference z-scorec Mean height (cm)** Mean height z-scorec Family origin* Biological mother USAborn African-American Biological mother foreign-born AfricanAmerican Other Social characteristics Residence history Ever placed in foster care*** Lived in 3+apartments Ever lived in street/shelter Number of other children in home Mean HOME Score Sibship composition* No siblings Has siblings, but not all living with study child All siblings living with study child a
Cocaine exposedb n= 88
Unexposedb n= 96
93.5 (7.7) 53.4% 2804 (457) 51.8 (1.4)
95.6 (7.6) 50.0% 2851 (424) 52.0 (1.4)
−0.41 (1.0)
−0.24 (0.96)
127.0 (6.5) 0.69 (1.1)
129.0 (7.0) 0.92 (1.1)
96.3%
86.2%
1.2%
7.4%
2.4%
6.4%
26.7%
10.5%
18.8% 10.8%
23.4% 17.9%
model explained a further 1% of the variance in IQ. Results were unchanged when we adjusted for only caregiver IQ, HOME, and living in street/shelter (B= 1.8, 95% CI − 1.8, 5.4) and when we added child age and sex to the model (B= 2.6, 95% CI − 1.1, 6.3). Similarly, with adjustment for log blood lead level, associations between cocaine exposure and IQ were unchanged; the estimated difference between exposed and unexposed children was 2.7 points (95% CI= − 1.2, 6.5). Concurrent blood lead level had a small adverse association with full scale IQ, explaining 2% of the variance in full scale IQ [B per unit log blood lead= − 3.2, 95% CI − 6.5, 0.15, PB 0.06].
3.3. Polydrug use Results were also unchanged when exposed children were further classified by whether or not there was evidence of prenatal exposure to heroin, methadone or PCP. Compared with unexposed children, full scale IQ was higher by an estimated 1.9 points (95% CI −1.9, 5.7) in the 61 children with exposure to cocaine only and higher by an estimated 3.6 points (95% CI −3.0, 10.2) in the 14 children with exposure to cocaine plus other drugs.
2.0 (1.8)
1.9 (1.8)
41.0 (8.0)
41.4 (7.6)
12.8% 36.0%
12.6% 21.1%
3.4. Verbal and performance IQ
51.2%
66.3%
Results were similar when analyses were conducted to examine associations with verbal and performance IQ. With adjustment for the five covariates, verbal and performance IQs were an estimated 1.3 (95% CI −2.5, 5.1) and 2.7 (95% CI −1.1, 6.6) points higher, respectively, in exposed children compared with those who were unexposed.
SD, where applicable, in parentheses. Includes all children with IQ assessments; n varies slightly because of missing data. c Based on age- and sex-specific norms. See Section 2.4. *PB0.10, **PB0.05, ***PB0.01. b
Regression analyses based on 75 exposed and 88 unexposed children with complete data on all covariates. *PB0.10, ** PB0.01, ***PB0.001.
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4. Discussion We found no association between prenatal cocaine exposure and intelligence in 6 – 9-year-old children. These results are consistent with other systematic studies at earlier ages. This study represents the largest follow-up of such children to date that extends into the school years. In contrast to the lack of adverse associations with prenatal cocaine exposure, we observed the expected associations between social factors and school-age intelligence. Mean IQ was low in both exposed and unexposed children relative to test norms; this was expectable considering the social adversity common to many children in this study. Measures of growth (head circumference and height), and of the social environment (caregiver’s intelligence, HOME score, and residence in shelter/street) explained 24% of the variance in school-age intelligence. The strength of associations between covariates and intelligence was the same for exposed and unexposed children. Although our findings are consistent with the few existing studies, inferences are limited by the low retrieval rate (37%), which leaves open the possibility that either group of children (exposed or unexposed) may not be representative of their respective cohorts. On the other hand, we found that families located and assessed did not differ from the target cohort in several socioeconomic variables, including marital status, Medicaid status, maternal age, the proportion primiparous, birthweight, or gender, so that our results may not be vulnerable to selection bias. However, data available at birth, on which comparisons were possible, included few variables with known strong associations with intelligence. Our low follow-up rate reflects the challenges of attempting to locate an impoverished inner-city sample 7 years after birth. In a number of cases, we had minimal perinatal information. Some children were listed only by surname, not having been given a first name before they left the hospital. Some mothers had changed their surnames or the child’s surname or first name in the 7 years since birth, due to marriage or to the father’s acknowledging paternity. Many children were not being reared by their biological mothers. Some mothers, it was discovered, had given inaccurate personal information at the time of birth, and some had listed their address at the time of birth at what turned out, 7 years later, to be a vacant lot. Despite Board of Education cooperation, many of the addresses provided were incorrect; many children had been transferred to another school in between our locating them in the Board data files and contacting the school. Some school principals declined co-operation. Many letters were returned by the post office indicating that the family had moved or that the address did not exist.
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Due to the problems in locating and assessing a difficult sample population over time, future studies of the effects of prenatal cocaine exposure might consider following well-defined samples prospectively from birth. On the other hand, given that studies to date have not noted significant adverse outcomes in cocaine-exposed children at follow-up, it may well be that the considerable resources necessary to conduct a definitive followup study would best be spent on some other issue. A further limitation of the study is the possibility that some of the unexposed children were, in fact, exposed prenatally. The urine test used to define exposure is sensitive to maternal cocaine use within the 2–3 days preceding the test (Hamilton et al., 1977); maternal report has been shown to be invalid in several urban settings (Zuckerman et al., 1989; Sackoff et al., 1992; Grant et al., 1994; Kline et al., 1997). Caregivers in the present study were asked whether the child’s biological mother had ever used cocaine; 15% (n =74) of the biological mothers of unexposed children reported that they had previously used cocaine and 52% (n= 21) of the non-maternal caregivers of unexposed children reported that the child’s biological mother had used cocaine at some time. These data most likely underestimate the likelihood of maternal cocaine use. While we are not able to determine the timing of maternal cocaine use relative to the pregnancy, these reports raise the possibility that some of the children in the unexposed group were exposed prenatally to cocaine. Misclassification of exposure status would ordinarily lead to an underestimate of the true association between exposure and IQ. However, in light of our results, which show essentially no differences between exposed and unexposed children, we cannot predict the direction of the true association, if any, between prenatal cocaine and children’s IQ. In summary, in this sample, cocaine use during pregnancy occurred in a context of multiple risks for child developmental outcome; to a large extent, these risks are common to families raising children in urban poverty. Within this environment, prenatal cocaine exposure does not seem to confer an additional risk for adverse developmental outcome.
Acknowledgements This research was supported by grants from the National Institute on Drug Abuse (R01-DA07612; Margaret C. Heagarty, MD, Principal Investigator) and from the Leon Lowenstein Foundation (Gail Wasserman, Ph.D. , Principal Investigator). We acknowledge Dr Stephen K. Ng for his central contributions to the design and initiation of this study. We are grateful to Aida Musabegovic and Tracy Unger, who conducted the assessments of children’s intelligence.
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