Contribution of Tobacco SmokeExposure to Learning DisabilitiesLaura Anderko, Joe Braun, and Peggy Auinger

CorrespondenceLaura Anderko, RN, PhD,School of Nursing andHealth Studies, GeorgetownUniversity, 3700 ReservoirRoad NW, Washington, DC20057.la266@georgetown.edu

Keywordstobacco smoke exposurelearning disabilities

ABSTRACT

Objective: To investigate the contribution of exposure to prenatal tobacco smoke (PTS) and environmental tobacco

smoke (ETS) to parent-reported learning disabilities.

Design: A nationally representative, cross-sectional survey conducted in the United States, the National Health and

Nutrition Examination Survey (NHANES) 1999 to 2002, was used to explore the association between reported

learning disability and exposure to PTS and ETS.

Participants: Data were analyzed from 5,420 children ages 4 to 15 years old.

Methods: Secondary data analysis was conducted using logistic regression controlling for a number of potential

confounders and covariates.

Results: Overall, 10.6% of children had a parent-reported learning disability (LD), exceeding previous estimates.

Exposure to PTS (odds ratio [OR] 5 1.6) and ETS (OR 5 1.6) were significantly associated with increased odds for

LD in children, with a greater odds noted (OR 5 2.6) when exposed to PTS and ETS.

Conclusion: Exposure to tobacco smoke significantly increases the odds for children to have a learning disability.

Overall, results indicate that if tobacco exposure is causally associated to LD, eliminating exposures could prevent an

estimated 750,000 of parent-reported learning disabilities in the United States. Results underscore the need for

diligence in the promotion of smoking prevention and cessation efforts.

JOGNN, 39, 111-117; 2010. DOI: 10.1111/j.1552-6909.2009.01093.x

Accepted July 2009

Learning disabilities (LD), de¢ned as disorders

that a¡ect the brain’s ability to receive, pro-

cess, store, and respond to information among

individuals who have average intelligence, are esti-

mated to a¡ect more than 6 million children (ages 6

through 21), almost 9.2% of this population. As

many as one in every ¢ve people in the United

States has a learning disability. More than half of

students receiving special education services

through the public schools are identi¢ed as having

learning disabilities, with many having di⁄culties in

the area of reading (U.S. Department of Education,

2009). The number of children diagnosed with LD

continues to increase, along with the need for spe-

cial education services (Stein, Schettler,Wallinga, &

Valenti, 2002). Despite these trends, little is known

about what underlies these high rates: improved

recognition and reporting, altered diagnostic crite-

ria, or true increases (Hermann, King, & Weitzman,

2008; U.S. Department of Education).

Learning disabilities create enormous emotional

and ¢nancial burdens for individuals, families, and

society (Harpin, 2005; Stein et al., 2002). These dis-

orders have widespread societal impacts including

health and educational costs. Estimated costs of

neurobehavioral disorders in the United States are

staggering, with billions of dollars spent annually

(Landrigan, Schechter, Lipton, Fahs, & Schwartz,

2002). When intellectual and classroom perfor-

mance are impaired due to LD, a child faces

di⁄culty in achieving academic success; more than

31% of children with LD drop out of high school

compared to 11% of the general student population

(U.S. Department of Education, 2009). This adds to

societal costs when children are not able to develop

skills necessary to be gainfully employed.

The causes and risk factors for LD are largely un-

known. There is some evidence that problems

during labor and delivery, low-socioeconomic sta-

tus, and low level of maternal formal education are

associated with LD (U.S. Department of Education,

2009). Still, these factors provide few clues for spe-

ci¢c causal risk factors of LD. Risk factors for LD

need to be evaluated within a more comprehensive

Laura Anderko, RN, PhD,is Robert and KathleenScanlon Endowed Chair forValues Based Health Carein the School of Nursingand Health Studies,Georgetown University,Washington, DC.

Joe Braun, RN, MSPH, isa research assistant inthe Department ofEpidemiology at theUniversity of NorthCarolina, Chapel Hill, NC.

Peggy Auinger, MS, is anassistant in the Departmentof Neurology, University ofRochester School ofMedicine and the AmericanAcademy of PediatricsCenter for Child HealthResearch, Rochester, NY.

JOGNN I N F O C U S

http://jognn.awhonn.org & 2010 AWHONN, the Association of Women’s Health, Obstetric and Neonatal Nurses 111

framework that explores other important maternal,

prenatal, and postnatal characteristics, including

exposure to toxins.

Despite the widespread, increasing prevalence of

LD, the association between them and a variety of

toxic exposures remains an important but largely

unstudied association (Braun, Kahn, Froehlich,

Auinger, & Lanphear, 2006; Linnet et al., 2003). Al-

though exposures to maternal smoking during

pregnancy, prenatal tobacco smoke (PTS) expo-

sure, or having a smoker in the home, environ-

mental tobacco smoke exposure (ETS), have been

linked in varying degrees to children’s ability to rea-

son and learn, this study is the ¢rst to use a

nationally representative sample to explore the as-

sociation between smoking exposures and LD

controlling for lead, a known neurotoxin.

Tobacco smoke, which is composed of more than

3,800 di¡erent chemical compounds, has been as-

sociated with a variety of health problems in

children including neurodevelopmental and/or be-

havioral problems such as reduced intellectual

ability, hyperactivity, decreased attention span, lan-

guage skills, and grade retention (Braun et al., 2006;

Huizink & Mulder, 2005; Kukla, Hruba, & Tyrlik,

2008; U.S. Department of Health and Human Ser-

vices (USDHHS), 2006; Yolton, Auinger, Dietrich,

Lanphear, & Hornung, 2005). Prenatal tobacco

smoke exposure may be a preventable cause of in-

tellectual disability with evidence of a dose-

response relationship (Braun et al.; Linnet et al.,

2003; Rauh et al., 2004). Altered brain development

may occur with tobacco smoke exposure through

fetal hypoxia from the nicotine that reduces blood

£ow or from carbonmonoxide that produces higher

levels of carboxyhemoglobin. Nicotine may also tar-

get neurotransmitter receptors in the fetal brain,

causing abnormalities in cell proliferation and

di¡erentiation (Fried,Watkinson, & Siegel,1997). In-

fant exposure to tobacco smoke can occur through

inhalation or through breast milk (Tyler,White-Scott,

Ekvall, & Abula¢a, 2008).

The purpose of this study was to investigate the im-

pact of PTS and ETS exposure on reported LD in

children using the NHANES 1999 to 2002 data set

and controlling for a variety of potentially important

confounders such as gender and socioeconomic

status.

MethodsA nationally representative, cross-sectional survey

conducted in the United States, the National Health

and Nutrition Examination Survey (NHANES) 1999

to 2002, was the most recent source of data for this

study (National Center for Health Statistics [NCHS],

2004a-2004c). This household survey of the nonin-

stitutionalized, civilian population uses complex,

multistage probability-sampling design (NCHS,

2004a). For this study, data for all children ages 4

to 15 years of age (N 5 5,420) who participated in

NHANES were used to explore the association be-

tween ETS and PTS exposure and LD. Methods for

data collection conducted through NHANES in-

cluded personal interviews, health assessment,

and the collection of biologic samples, such as

blood.

The survey questionnaire included, among other

items, questions on LD, smoking history, and care

received in a neonatal intensive care unit (NICU).

The dependent variable, learning disability, was de-

¢ned as a parent answering yes to the question,

‘‘Has a representative from a school or health pro-

fessional told you that your child had a learning

disability’’?

Independent variables collected via the survey in-

cluded the following: smoker at home (or the

measure of ETS exposure) was de¢ned as answer-

ing yes to the question, ‘‘Does anyone who lives

here smoke cigarettes, cigars or pipes, anywhere

inside this home?’’ and mother smoked while preg-

nant (or the measure of PTS exposure) was de¢ned

as answering yes to the question, ‘‘Did (subject par-

ticipant’s) biological mother smoke at any time

while she was pregnant with (him/her)?’’ Covariates

included in the analysis were age, race, gender,

care in a NICU, attendance at a preschool or day-

care, and socioeconomic status (as measured by

Poverty Income Ratio [PIR]). This variable is de-

¢ned as the total household income divided by the

poverty threshold determined by the government

and based on family size for a particular year

(http://www.census.gov/hhes/www/poverty/de¢ni

tions.html).

Recent declining smoking rates in the United States

and increasing LD prevalence underscore the need

to explore the impact of other environmental toxins.

Because of lead’s impact on intellectual capacity

and the potential role that iron de¢ciency can play

in lead’s ability to damage the neurological system,

several biomarkers were explored in this study, in-

cluding levels of blood lead, serum cotinine, and

ferritin (measure of iron status).

Risk factors for learning disabilities, estimated to affect5% to 10% of U.S. children, are poorly understood.

112 JOGNN, 39, 111-117; 2010. DOI: 10.1111/j.1552-6909.2009.01093.x http://jognn.awhonn.org

I N F O C U S Tobacco Smoke and Learning Disabilities

Due to the high degree of correlation between se-

rum cotinine (a metabolite of nicotine) and self-

reported measures of ETS exposure (Spearman

correlation 5 0.56), these variables were analyzed

separately in logistic regression models to deter-

mine the individual e¡ects on LD based on a

chi-square statistical analysis that was adjusted for

the following variables: age, gender, mother

smoked while pregnant, NICU admission, birth

weight, and ferritin. Once added to the full model,

cotinine, although signi¢cant in the bivariable

analysis (o 0.0001), was no longer signi¢cantly as-

sociated with LD (a large number of serum cotinine

values were missing). Therefore, the primary analy-

sis was performed using self-reported ETS

exposure.

Statistical AnalysisSample weights were applied according to the

National Center for Health Statistics (NCHS) guide-

lines to produce accurate national estimates

adjusting for the oversampling of minority and

young children. Regression diagnostics were con-

ducted to determine outliers, which were excluded

from analyses. Correlation analyses assessed mul-

ticollinearity, in which none was noted. Due to the

high prevalence of parent-reported LD in the sam-

ple population, odds ratios (OR) were adjusted to

better represent the relative risk.

Bivariable analyses were initially conducted to de-

termine associations with parent-reported learning

disability and included potential risk factors based

on previous studies: low birth weight, admission

into an NICU (Avchen, Scott, & Mason, 2001; En-

gland, Kendrick, Gargiullo, Zahniser, & Hannon,

2001); race and income (Coutinho, Oswald, & Best,

2002; U.S. Department of Education, 2009); age

and gender (U.S. Department of Education); and

lead (Lanphear et al., 2005). Variables found to be

associated with a reported learning disability based

on chi-square (p o .2) were included in the logistic

regression analyses and ¢ndings reported as an

OR, which, in this study, is the ratio of the probability

of a learning disability being reported for a child to

the probability of no learning disability being re-

ported for a child. Poverty Income Ratio levels were

presented as quartiles to make the results easier to

interpret and also to illustrate any dose-response

relationships for LD.

Population-attributable risk was calculated for risk

factors independently associated with LD and to-

bacco smoke exposure, including PTS and ETS

exposure separately and combined.

ResultsOverall, 581 (10.6%) of the 5,420 children aged 4 to

15 years who participated in NHANES 1999 to 2002

were reported by a parent to have been diagnosed

with a LD, which translates to an astounding 5.1

million children nationwide. The prevalence of

LD increased signi¢cantly with child’s age, male

gender, decreasing PIR (increasing poverty),

mother smoking during pregnancy, whether any-

one smoked in the home, increasing serum

cotinine levels, low birth weight, and admission into

a NICU (Table 1).

A signi¢cant association of parent-reported LD was

found with the following variables: age (o 0.0001),

gender (0.014), NICU admission (0.036), and birth

weight (0.003). Although PIR was signi¢cant in the

bivariable analysis, it became nonsigni¢cant when

other risk factors were introduced into the model

(Table 2).

Most importantly, ORs were signi¢cantly greater for

LDs in children exposed to PTS (OR 5 1.6, p 5

.044) and ETS (OR 5 1.6, p 5 .024).These ¢ndings

indicate that children exposed to PTS are more than

1 1/2 more likely to experience LD when compared

with non-PTS exposed children, and that children

exposed to ETS are more than11/2 times more likely

to experience LD when compared with non-ETS

exposed childrenThe adjusted OR for LD increased

to 2.6 for children who were exposed to PTS and

ETS (p o .0001), meaning children exposed to both

are almost 3 times more likely to report a learning

disability than children who are not exposed.

Table 3 reports on the attributable risk of LD as a re-

sult of exposure PTS and ETS. Excess cases of LD

were attributable to tobacco exposure in each cat-

egory analyzed and resulted in 750,000 excess

cases for children exposed to one or more tobacco

exposure measure. This number represents the

number of cases that could have been prevented

through interventions such as smoking prevention

or cessation.

DiscussionThis study speci¢cally examines the association

between LD and tobacco smoke exposure using a

Children exposed to prenatal and environmental tobaccosmoke are almost 3 times more likely to have a learning

disability than children who are not exposed.

JOGNN 2010; Vol. 39, Issue 1 113

Anderko, L., Braun, J., and Auinger, P. I N F O C U S

nationally representative sample; tobacco smoke

exposure was signi¢cantly associated with parent-

reported LD in U.S. children after controlling for

potential confounders. Findings support previous

studies that found signi¢cant associations with

tobacco exposure and cognitive de¢cits or be-

havioral problems (Braun et al., 2006; Yolton et al.,

2005).

In this study,10.6% of children had a parent-reported

learning disability. This exceeds previous estimates

from the U.S. Department of Education (2009) that

reported that 9.2% of children in the U.S. population

had a learning disability. However, it should be noted

that estimates of the prevalence for LD may vary by

study for several reasons. For example, criteria for

what it means to have LD vary by state, and the use

of parental self-report may re£ect a range in the un-

derstanding of the actual LD ‘‘diagnosis.’’

Table 1: Prevalence of Self-Reported

Learning Disabilities Among Persons Age

4 to 15 in NHANES 1999 to 2002

According to Demographic and Medical

Factors (N 5 5,420)

Variable

Sample

Size

Weighted

Percent (95%) p Value

Age (in years) .001

4-6 1,097 6.3 (4.4, 8.8)

7-9 1,152 7.4 (5.6, 9.8)

10-12 1,372 12.6 (10.4,15.1)

13-15 1,799 15.9 (12.4, 20.3)

Gender o .0001

Male 2,654 12.8 (11.0,15.0)

Female 2,766 8.2 (7.2, 9.4)

Poverty Income Ratio (PIR) .001

1st quartile (0-1.03) 1,741 15.4 (12.4,18.9)

2nd quartile (1.04-2.08) 1,328 11.8 (9.4,14.6)

3rd quartile (2.09-3.74) 990 8.7 (6.1,12.2)

4th quartile (3.75-5.0) 836 7.3 (5.5, 9.5)

Does anyone smoke in the

home?

o .0001

No 4,198 8.4 (7.2, 9.8)

Yes 1,156 17.8 (15.4, 20.4)

Mother smoked while

pregnant

o .0001

No 4,599 8.5 (7.3, 9.9)

Yes 747 19.4 (15.4, 24.2)

NICU .001

No 4,775 9.4 (8.2,10.8)

Yes 605 17.9 (14.0, 22.5)

Low birth weight .003

� 2,500 g 4,883 9.9 (8.8,11.1)

o2,500 g 476 18.2 (13.8, 23.6)

Note. NHANES 5 National Health and Nutrition Examination Survey.

Table 2: Adjusted ORs for Self-Reported

Learning Disabilities Among Persons 4 to

15 Years of Age, NHANES 1999 to 2002

(Smoker in the Home as Index of Postnatal

Smoke Exposure)

Variable OR (95% CI) p Value

Age (in years) 1.16 (1.08,1.24) o .001

Gender

Female Referent

Male 1.5 (1.1, 2.0) .014

Race

White Referent

Other Hispanic 0.9 (0.4,1.9) .758

Mexican 0.7 (0.4,1.2) .197

Black 0.9 (0.6,1.3) .490

Other-multiracial 0.6 (0.3,1.3) .206

Poverty to income ratio 0.9 (0.7,1.0) .114

Mother smoked while pregnant

No Referent

Yes 1.6 (1.0, 2.6) .044

Smoker at home

No Referent

Yes 1.6 (1.1, 2.3) .024

Birth weight (g) 0.9 (0.9,1.0) .003

NICU

No Referent

Yes 1.6 (1.0, 2.6) .038

Blood lead (log transformed) 1.2 (0.9,1.6) .129

Note. OR 5 odds ratios; CI 5 con¢dence intervals ; NICU 5 neo-

natal intensive care unit.

114 JOGNN, 39, 111-117; 2010. DOI: 10.1111/j.1552-6909.2009.01093.x http://jognn.awhonn.org

I N F O C U S Tobacco Smoke and Learning Disabilities

LimitationsThere were limitations of this analysis. First, the de-

pendent variable, LD, was not medically con¢rmed

for this study speci¢cally but rather de¢ned as a

parent answering yes to the question, ‘‘Has a repre-

sentative from a school or health professional told

you that your child had a learning disability?’’ Al-

though parents can be expected to know their

children better than others, there is the possibility

that they may misunderstand a child’s diagnosed

learning problem.

Second, measures of important variables including

mother’s alcohol habits during pregnancy and ed-

ucational level of the parents were not possible due

to the lack of data in this NHANES data set (Batty,

Der, & Deary, 2006; Gilman, Gardener, & Buka,

2008). Finally, the cross-sectional nature of this

study and the natural history of LD limit the ability

to examine the temporal relationship of exposures

to tobacco smoke on learning abilities.

Comparisons With Previous StudiesLow birth weight and admission into NICU were sig-

ni¢cantly associated with LD, supporting previous

studies that explored developmental disabilities

(Jaddoe et al., 2007). It is clear from previous stud-

ies that maternal smoking during pregnancy can

signi¢cantly a¡ect birth weight; babies born to

mothers who smoke tend to be lower in birth weight

and therefore, more likely to be admitted to an NICU.

Although these associations need further explora-

tion regarding their impact on LD, the logical

health intervention is to eliminate or reduce smok-

ing by the mother during pregnancy.

In contrast with several previous studies, a relation-

ship of race or income with LD was not found

(Coutinho et al., 2002; U.S. Department of Educa-

tion, 2009). Race was not identi¢ed as a risk factor

when PTS and ETS were removed from the model

(p 5 .058). It may be that tobacco exposure, which

has been suggested to be higher in low-income

homes and tend to be more predominate in non-

White families, play a more important role than sim-

ply the socioeconomic status of the children’s

household or race of the child (Coutinho et al.; U.S.

Department of Education).

Males were found to have a signi¢cantly higher

odds of LD in this study, which is consistent with

previous ¢ndings (U.S. Department of Education,

2009). Although a variety of explanations for this

phenomena have been proposed including biases

in the LD identi¢cation process, it is important to

continue to explore the factors that may contribute

to this risk (Coutinho et al., 2002; Rutter et al.,

2004; U.S. Department of Education).

The likelihood for the diagnosis of LD increases

with age; our ¢ndings indicate that older age has a

higher prevalence of LD, which is consistent with

the majority of prior studies. The literature suggests

that the older the child and longer he or she attends

school, the more likely that he or she will be identi-

¢ed as learning disabled by school personnel (U.S.

Department of Education, 2009).

The value of using biomarkers such as serum coti-

nine to validate questionnaire responses related to

exposure to tobacco smoke has been described in

earlier documents; it can o¡set socially desirable

but inaccurate questionnaire responses and add

more precision to the model (Yolton et al., 2005). Still,

in this analysis we found that reported exposure to to-

bacco smoke was signi¢cantly associated with the

outcome of LD. It is likely that biomarkers of tobacco

smoke exposure are better predictors of certain out-

comes but may not accurately re£ect the long-term

e¡ects of lifetime exposures; self-reported exposure

may be as good or better for other outcomes (Cara-

ballo, Giovino, Pechacek, & Mowery, 2001).

Table 3: Population Attributable Risk for Self-Reported Learning Disabilities Among

Persons 4 to 15 years of age, NHANES 1999 to 2002

Exposed (%) Adjusted RR Attributable Fraction (95% CI) Excess Cases

Mother smoked while pregnant 18.2 1.6 6.8 (0.2,11.2) 350,000

Smoker in the home 23.6 1.6 8.9 (2.1,13.3) 450,000

PTS and ETS exposure 11.0 2.6 6.8 (4.7, 8.1) 350,000

� 1 exposure 30.1 1.9 14.8 (7.2,19.7) 750,000

Note. NHANES 5 National Health and Nutrition Examination Survey; RR 5 risk ratio; CI 5 con¢dence interval ; PTS 5 prenatal tobacco

smoke; ETS 5 environmental tobacco smoke.

The risk factors are not mutually exclusive and the estimates of attributable risk are not additive. All odds ratios and attributable risks are

adjusted for variables shown inTable 2.

JOGNN 2010; Vol. 39, Issue 1 115

Anderko, L., Braun, J., and Auinger, P. I N F O C U S

Although recent studies have shown that cogni-

tive de¢cits in children occur below Centers for

Disease Control’s current recommended blood

level, this study found no signi¢cant relationship

between reported LD and lead levels (Lanphear

et al., 2005). Although blood lead levels are rela-

tively stable, they may not accurately measure

lifetime exposure in older children and adolescents

measured in this study. Thus, though lead exposure

may contribute to LD, it was not apparent in this

analysis.

Overall, the results of these analyses indicate that if

tobacco exposure is causally linked to LD, eliminat-

ing exposures to tobacco smoke could prevent an

estimated 750,000 (14.7%) of the 5.1 million cases

of parent-reported LDs. The impact of reducing or

eliminating these exposures would profoundly re-

duce costs spent in remediation, not to mention the

emotional toll of living with a learning disability dur-

ing one’s lifetime.

Implications for PracticePreventing exposure of pregnant women, infants,

and children to tobacco smoke requires a multilevel

approach, including individual, institutional, and

community strategies. At the individual level, ad-

visement by a health care provider can be a simple

yet e¡ective means for supporting smoking cessa-

tion. However, studies indicate that health care

provider advisement is limited, despite evidence

that many mothers and expectant fathers indicate

a readiness to quit smoking (Everett et al., 2005;

USDHHS, 2008).

It is important that nurses not only conduct assess-

ment of smoking behaviors, but also incorporate

stop smoking messages and strategies that sup-

port cessation, such as Quit Lines (1-800-

QUITNOW) and computer- or Web-based smoking

cessation programs that have been very e¡ective.

Studies have also found a strong in£uence of male

partner’s smoking habits on women during and af-

ter pregnancy. Addressing a multiple range of

strategies, including the often-overlooked smoking

habits of the partner, will lead to a more successful

outcome (Albrecht et al., 2003; Fiore, 2008; Myung,

McDonnell, Kazinets, Seo, & Moskowitz, 2009;

USDHHS, 2001).

In the event that cessation proves too di⁄cult, and

because toxic particulate matter from smoke can

remain in upholstery, drapes, and carpeting, nurses

can provide information on measures to reduce in-

door air contamination through simple measures

such as smoking outdoors, not smoking in vehicles,

and never smoking in the presence of children.

At the institutional level, systems interventions such

as educating all personnel in e¡ective smoking

cessation strategies, mandating assessment for

smoking at each visit, and/or o¡ering smoking ces-

sation programs for pregnant women and partners

can increase success (Lumley, Oliver, Chamberlain,

& Oakley, 2004).

At the community level, the importance of smoke-free

ordinances or legislation cannot be underestimated

for improving the overall health of communities, in

particular our children. Almost 9 out of every 10

nonsmoking Americans are exposed to ETS, as

measured by the levels of cotinine in their blood

(USDHHS, 2006). As trusted and respected health

professionals, nurses have the power to act as

change agents, advocating for smoke-free commu-

nities. Examples exist of successful community-

wide approaches, such as smoke-free ordinances

developed, negotiated, and sustained by nurses

(Anderko, 2009).

ConclusionsThe causes and risk factors for LD are poorly un-

derstood. Findings from this study are notable as

they add to the scarce knowledge base on LD and

smoking, using a valid and reliable, population-

based sample. Developmental disabilities can arise

from awide range of exposures and interactions; to-

bacco exposures deserve special attention

because they are widespread and preventable.

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I N F O C U S Tobacco Smoke and Learning Disabilities

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Anderko, L., Braun, J., and Auinger, P. I N F O C U S