|Year : 2018 | Volume
| Issue : 1 | Page : 8-17
Secondhand smoke exposure is associated with autism spectrum disorder in US males but not in females: Results from the National Survey on Children's Health
Naila Khalil1, Bhupinder Kaur2, Alexandra Lawson3, James Ebert4, Ramzi Nahhas5
1 Department of Population and Public Health Sciences, Boonshoft School of Medicine, Wright State University, Dayton, OH, USA
2 Child and Adolescent Psychiatry Fellow, Kobacker Center, University of Toledo Medical Center, Toledo, OH, USA
3 Medical Student, Boonshoft School of Medicine, Wright State University, Dayton, OH, USA
4 Director, The Pediatric Lipid Clinic, Dayton Children's Hospital, Dayton, OH, USA
5 Department of Population and Public Health Sciences; Department of Psychiatry, Boonshoft School of Medicine, Wright State University, Dayton, OH, USA
|Date of Submission||05-Feb-2018|
|Date of Acceptance||13-Mar-2018|
|Date of Web Publication||11-Apr-2018|
Dr. Naila Khalil
3123 Research Blvd, Suite #200, Department of Population and Public Health Sciences, Boonshoft School of Medicine, Wright State University, Dayton, OH
Source of Support: None, Conflict of Interest: None
Background: Secondhand smoke (SHS) exposure is linked with neurobehavioral disorders in children. This study evaluated the SHS exposure and autism spectrum disorders (ASD) in children in the United States.
Materials and Methods: Parent-reported postnatal SHS exposure and ASD diagnosis were examined in children age 2 to 12 years using the 2011–2012 National Survey on Children's Health. The physician diagnosis of current ASD as reported by the parents was used as the outcome. Logistic regression analysis was used to evaluate the association of ASD with SHS after adjusting for risk factors.
Results: Of the 56,710 children, 24% had SHS exposure, 2% had ASD, and the mean age was 7 years. SHS exposure was associated with 47% greater odds of ASD in male children (adjusted odds ratio [OR] = 1.47; 95% confidence interval [CI] =1.05, 2.07; P = 0.025). In contrast, SHS was not significantly associated with ASD in female children (adjusted OR = 0.72; 95% CI = 0.40, 1.29; P = 0.266). Other significant factors associated with ASD diagnosis in male children were age, income, mother's education, and mental health status.
Conclusions: SHS is significantly associated with ASD in male children. Sociodemographic factors, natal and prenatal characteristics are important etiologic influences for ASD. Targeted efforts to change the smoking behavior of parents and caregivers of children could reduce ASD.
Keywords: Autism, children, gender, secondhand smoke
|How to cite this article:|
Khalil N, Kaur B, Lawson A, Ebert J, Nahhas R. Secondhand smoke exposure is associated with autism spectrum disorder in US males but not in females: Results from the National Survey on Children's Health. Environ Dis 2018;3:8-17
|How to cite this URL:|
Khalil N, Kaur B, Lawson A, Ebert J, Nahhas R. Secondhand smoke exposure is associated with autism spectrum disorder in US males but not in females: Results from the National Survey on Children's Health. Environ Dis [serial online] 2018 [cited 2023 Mar 30];3:8-17. Available from: http://www.environmentmed.org/text.asp?2018/3/1/8/229882
| Introduction|| |
Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by deficits in social communication, social interaction, and repetitive behaviors. According to Centers for Disease Control and Preventions (CDC's) Autism and Developmental Disabilities Monitoring Network report in 2012, 1 in 68 children suffers from ASD, higher than the previously reported 1 in 150 children in 2000. In 2012, the prevalence of ASD in the United States (US) was 14.6/1000 children, compared to 6.7/1000 children in 2000.
The exact cause of autism is unclear; both genes and environment are thought to play an important role. ASDs are highly heritable disorders, but there is only about 70% concordance in monozygotic twins which suggests that nongenetic factors like environmental factors (prenatal and perinatal) might also play a major role. Sociodemographic factors that may be associated with ASD include advanced parental ages, parents' socioeconomic status (SES), prematurity, low birth weight (LBW), parents' educational status, immigrant status, and race/ethnicity.,,,,,,,,,, Some of these risk factors have been previously studied.,,, A few risk factors were consistently associated with ASD, while others have shown inconsistent conclusions.
Recent research demonstrates that environmental exposures may have a role in ASD development. As evaluated in recent comprehensive reviews of existing literature from US, Canada, and Europe, the associations have been reported between ASD and multiple chemicals and toxins. These associations included air pollutants, phthalates, polychlorinated biphenyls (PCBs), solvents, pesticides, phthalates, heavy metals, fragrances, and volatile organic compounds ,,, to name a few. Strongest evidence was noted for air pollutants and pesticides., Such research proposed exposure to these chemicals and toxins during gestation affects the neurodevelopment of the fetus, including disruption of neurotransmitters and receptor pathways. It has even been suggested that increasing use and exposure of these toxins and chemicals contribute to the increasing rate of ASD diagnoses over the last three decades. Included in this list of chemicals and toxins was tobacco smoke. In fact, ASD has found to be associated with both maternal smoking and maternal secondhand smoke (SHS) exposure during pregnancy, understandably as both tobacco smoke and SHS contain thousands of chemicals. However, this relationship is still contended due to potential confounding factors like SES.
According to the 2007–2008 National Health and Nutrition Examination Survey, 40% of children aged 3 years or older in the US experienced SHS exposure. In this survey, SHS exposure was more common among males (43.5%) than females (37.4%) and in younger age groups than older: 3–11 years (53.6%); 12–19 years (46.5%).
SHS exposure predisposes these children to many adverse health outcomes including respiratory tract infections, asthma exacerbation, sudden infant death syndrome, middle ear problems, reduced hearing and language development, cognitive, behavioral, and developmental disorders, and reduced IQ scores. In addition, children exposed to SHS have a higher prevalence of emotional and behavioral problems than children without SHS exposure. Since younger children tend to have greater exposure to SHS than older children, there is ample opportunity for toxins from SHS to impact the neurodevelopment of young children. Although prenatal tobacco exposure is associated with behavioral problems, there is some evidence that SHS exposure during early childhood may be more hazardous to developing brain than prenatal exposure. However, it is difficult to distinguish prenatal active smoking by the mother, her SHS exposure and the postnatal SHS exposure due to collinearity and co-occurrence of these exposures., The home environments tend to be similar during both prenatal and postnatal phases. In a review, Eskenazi and Castorina have reported adverse neurocognitive development in children exposed to postnatal SHS compared to those only exposed to prenatal SHS. Furthermore, postnatal SHS may be more hazardous to developing brain as compared to SHS in utero. The fetus is exposed to SHS through the placental barrier which may provide some protection; however, postnatal SHS exposure is through direct inhalation. In addition, the postnatal SHS smoke and primary smoke differ in chemical composition and their concentration levels. Early childhood and adolescence are critical phases of neurodevelopment. SHS exposure in childhood is a relatively common exposure and may continue for longer periods than the relatively shorter 9 months exposure to SHS in utero.
In the US, approximately 1 in 6 pregnant women aged 15–44 years smoke, though smoking prevalence is lower in pregnant women than nonpregnant women of the same age. According to the 2011 Pregnancy Risk Assessment and Monitoring System data of women who smoked before pregnancy, 55% quit during pregnancy. However, 40% of these women started smoking again within 6 months after delivery. In another National smoking survey for pregnant women between 2000 and 2010, the prevalence of smoking before pregnancy remained unchanged, with approximately one in five women reporting smoking before pregnancy (23.6% in 2000–24.7% in 2010). The prevalence of smoking during pregnancy decreased from 13.3% in 2000 to 12.3% in 2010, and the prevalence of smoking after delivery decreased from 18.6% in 2000 to 17.2% in 2010. The results highlight the fact that one in five women and their children are exposed to tobacco smoke. Further, as almost 50% of women are not able to quit smoking, hence prenatal exposure continues as SHS exposure for young children.
In the current analysis, we tested the hypotheses that SHS exposure is associated with the increased prevalence of ASD in children between 2 and 12 years of age and that this association differs by sex.
| Materials and Methods|| |
The data for this study were taken from 2011 to 2012 National Survey of Children's Health (NSCH). This survey was conducted by the US CDC Data Resource Center (a project of the Child and Adolescent Health Measurement Initiative at Oregon Health and Science University), sponsored by the Maternal and Child Health Bureau, Health Resources and Services Administration. The purpose of the survey was to provide national and state-specific prevalence estimates for a range of children's health indicators. Out of 95,677 children included in the survey, 56,710 children between 2 and 12 years of age were selected for this analysis for which information regarding ASD, SHS, and other demographic variables were complete. Analyses were restricted to this age range because, according to the CDC, starting at age 2 years ASD diagnosis can be reliable, valid, and stable. Further, children older than 12 years were excluded to minimize any effect of current smoking by the children themselves.
NSCH data were collected through questionnaire by random telephone dialing to identify households with one or more children <18 years of age. Within the household, the parent or guardian who was most well informed about the child's health was interviewed. Questions included demographic characteristics, child's health and functional status, family functioning, parental health, and neighborhood and additional demographics. Multiple languages in addition to English were used to conduct the interviews. These languages included Spanish, Mandarin, Cantonese, Vietnamese, and Korean. Out of total 95,677 interviews conducted in children, 4905 (5%) interviews were completed by a Spanish language interviewer and 229 (0.2%) interviews were completed by an Asian language interviewer.
Primary outcome and exposure variables
ASD diagnosis (yes/no) was outcome variable and derived from the question “Does the child currently have autism, Asperger's disorder, childhood pervasive development disorder, or other ASD?” The exposure variable SHS tobacco exposure was derived from the question “Does anyone living in your household use cigarettes, cigars, or pipe tobacco?” The reply to this question was coded as 0: No SHS (referent); 1: Yes SHS exposure. This information is available at the NSCH website (PDF also attached). Please see page 1–2, “SECTION 2: Child's Health and Functional Status” among children ages 2–17, as response to question #13: “For each condition, please tell me if a doctor or other health care provider ever told you that (CHILD'S NAME) had the condition, even if (he/she) does not have the condition now. Has a doctor or health professional ever told you that (CHILD'S NAME) has any of the following conditions?:” Autism, Asperger's Disorder, pervasive development disorder, or other ASD (K2Q35A)” ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/slaits/nsch_2011_2012/01_Frequently_asked_questions/NSCH_2011_2012_FAQs. Pdf.
Covariates included in the analysis, some of which may confound the relationship between SHS and ASD, were mother's mental health status (good [referent] vs. poor), sex of the child, child's age (continuous), mother's age (continuous), primary language (English vs. other [referent]), birth weight (normal [referent], vs. LBW [LBW, birth weight <2500 g]), prematurity (full term delivery [referent] vs. premature), SES (measured by how hard it was to meet basic needs of food and housing; not hard/never [referent] vs. often hard), race and ethnicity (non-Hispanic [NH] white vs. other [referent]), mother's educational level (high school or less [referent], vs. greater), family structure (single mother vs. other [referent]) generational status of household to determine the foreign status of mother and/or father (first- or second-generation household [referent] vs. third- or higher generation household).,,,
All analyses were adjusted to account for the complex survey design, sampling weights, and strata as suggested by the NSCH. The weighted NSCH sample is representative of the US civilian noninstitutionalized population. Population characteristics were summarized as the mean ± standard error (SE) or number and proportion of observations unless indicated otherwise. As decided a priori, analyses were conducted to examine the relationships between sociodemographic characteristics associated with ASD status as reported in the literature.,,, Descriptive analyses were carried out for the overall sample and repeated by sex and by ASD, SHS status. Differences in means were tested using Student's two-tailed t-tests and differences in proportions were tested using Rao–Scott Chi-square analysis as recommended by the NSCH. SAS survey procedures were used (SAS Institute Inc., Version 9.3), with the Taylor series linearization method for calculation of SEs. All analyses were conducted using two-tailed tests at the 5% significance level.
Logistic regression (univariate and multivariate adjusted) was performed to determine the independent association between SHS exposure and ASD after adjusting for the covariates mentioned above. All risk factors were entered together in the model. The analysis was repeated after stratifying by sex.
| Results|| |
Description of study population
In the sample of 56,710 children between 2 and 12 years of age, 2.3% had been diagnosed with ASD and 24.2% had SHS exposure [Table 1]. The mean age of children was 7.08 ± 0.03 years. The mean age of mothers was 35.7 ± 0.07 years. NH white race/ethnicity was predominant (51%) and the majority (58%) of these families found it hard to pay for basic needs. An estimated 9.8% of children were LBW babies and 12% were premature. English was the predominant primary language (84%). Nearly 64% of mothers were educated beyond high school, <1% had poor mental health status, and 8.7% of households were led by a single mother. A majority of households were third generation or higher families (73%). As shown in [Table 1], males had higher prevalence of ASD compared to females (3.5% vs. 0.95%; P < 0.001); however, LBW was more common in female births (10.9%) than males (8.8%); (P < 0.001). No other variables were significantly different between genders.
|Table 1: Weighted characteristics of 2011-2012 National Survey of Children's Health study participants, overall, and by sex|
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Description of study population by autism spectrum disorders status
[Table 2] shows the descriptive information of the study population by ASD status overall, and by sex. Children with ASD had higher SHS exposure (30% vs. 24%, respectively; P = 0.023). With the exception of family structure, all variables were significantly different between those with and without ASD. Specifically, children in the sample diagnosed with ASD were more likely than those not diagnosed with ASD to (a) be older (mean difference 0.9 years; P < 0.001), (b) have an older mother (mean difference 1.5 years; P = 0.001), (c) be male (80% vs. 51%, P < 0.001), (d) belong to “other ethnicity” (Hispanic and/or nonwhite) (59% vs. 49%; P = 0.029), (e) have difficulty paying for basics (71% vs. 58%; P < 0.001), (f) have been LBW (14% vs. 10%; P = 0.022), (g) have been premature (19% vs. 12%; P < 0.001), (h) have English as the primary language of their household (93% vs. 83%; P = 0.006), (i) have a mother with at least a high school education (72% vs. 64%; P = 0.002), (j) have a mother with poor mental health status (4.3% vs. 0.9%; P < 0.001), and (j) be part of a third generation or higher family (82% vs. 71%; P = 0.006).
|Table 2: Weighted characteristics of 2011-2012 National Survey of Children's Health study participants, overall, and by autism spectrum disorders status|
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Description of study population by autism spectrum disorders status
[Table 3] shows the descriptive characteristics of the study population overall (for ease in comparison) and by SHS status overall. Children with SHS had higher prevalence of ASD (2.8% vs. 2.1%, respectively; P = 0.023). With the exception of age and sex, all variables were significantly different between those with and without SHS. Specifically, children exposed to SHS in the sample were more likely than those not exposed to SHS to (a) have an younger mother (mean difference 2.5 years; P = 0.001), (b) belong to NH White race/ethnicity (56% vs. 50%; P < 0.001), (c) have difficulty paying for basics (74% vs. 53%; P < 0.001), (d) have been LBW (11% vs. 9%; P < 0.001), (e) have been premature (14% vs. 11%; P < 0.001), (f) have English as the primary language of their household (91% vs. 81%; P < 0.001), (g) have a mother with less than, or a high school education (49% vs. 32%; P < 0.001), (h) have a mother with poor mental health status (2.2% vs. 0.6%; P < 0.001), and (i) be part of a third generation or higher family (84% vs. 70%; P < 0.001).
|Table 3: Weighted characteristics of 2011-2012 National Survey of Children's Health study participants, overall, and by secondhand smoke status|
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Univariate logistic regression results for autism spectrum disorders
Based on univariate logistic regression analyses [Table 4], sexual dimorphism was noted in the direction and magnitude of significant associations between risk factors and the odds of ASD, in particular, SHS exposure. In sex-stratified univariate logistic regression, SHS exposure was related to 48% higher odds of ASD in male children but not related to ASD in females (odds ratio [OR] = 0.98). Similarly, mother's higher education and poor mental status were associated with significantly greater odds of ASD in males but not in females. Race/ethnicity was not associated with ASD in either males or females. LBW was associated with increased odds of ASD only in females. In both sexes, mother's age, prematurity, English as a primary language, difficulty paying for basics, and third or higher household generational status were significant predictors of ASD.
|Table 4: Weighted unadjusted odds ratio for autism spectrum disorders, 2011-2012 National Survey of Children's Health study participants, aged 2-12 years, overall, and by sex|
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Multivariable logistic regression results for autism spectrum disorders
In multivariable models [Table 5], after adjusting for other ASD risk factors, sex-stratified analysis showed that male children exposed to SHS had 47% greater odds of ASD diagnosis (adjusted OR = 1.47; 95% confidence interval [CI] = 1.05, 2.07; P = 0.025) compared to males not exposed to SHS. In contrast, SHS was not significantly associated with ASD diagnosis in female children (adjusted OR = 0.72; 95% CI = 0.40, 1.29; P = 0.266). In male children, older age, difficulty paying for basics, mother's education greater than high school, and mother's poor mental health were significant risk factors for ASD diagnosis. However, in female children, only older mother's age and difficulty paying for basics were significantly related to ASD diagnosis.
|Table 5: Weighted multivariable* adjusted odds ratio 95% confidence interval of autism spectrum disorders, 2011-2012 National Survey of Children's Health study participants, aged 2-12 years, overall, and by sex|
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| Discussion|| |
SHS exposure was significantly associated with ASD in male children. In addition, after controlling for SHS, in male children, increasing age, older maternal age, poor maternal mental status, mother's greater than high school education, and difficulty paying for basics were significantly related to ASD in multivariable analysis. The findings of this study show association and not causality. However, they highlight health burden of childhood neurodevelopmental disorders attributable to SHS exposure.
Researchers have previously reported the association of ASD with maternal smoking and tobacco use during pregnancy;, however, the current study only showed this association for male children, which will be explained below. Although the mechanism of SHS on neurodevelopment is not completely understood, current literature proposes that prenatal tobacco exposure causes fetal hypoxia and modulation of neurotransmitter systems through nicotinic acetylcholine receptors and may result in the development of autism and related disorders. Cigarette smoke includes polycyclic aromatic hydrocarbons, metals, and other chemicals with known adverse health effects, which may cause fetal hypoxia and affect fetal brain development.
This study suggests that SHS exposure in childhood is also associated with ASD. Research has shown that SHS exposure in childhood can impact neurodevelopment, as children with greater SHS exposure have associated decreased verbal IQ, increased rates of attention-deficit/hyperactivity disorder, increased rates of learning disability, and behavioral problems., The mechanism of postnatal SHS exposure on neurodevelopment is still unknown, but, according to rodent studies, it is believed the toxins in SHS affect the brain in postnatal children in a similar manner as they do in prenatal children.
ASD was also found to be associated with male sex, which is consistent with previous literature that shows males have a 4:1 or 3:1 ratio of ASD diagnoses as compared to females. Furthermore, we found a significant association between SHS and ASD in males but not in females. However, a male preponderance is not unique to ASD. The prevalence of ADHD is three times greater among males than among females (reviewed in Lanphear et al., 2006).,, Gender differences have been documented in studies investigating the effect of environmental exposures on neurobehavioral outcomes. In mice, environmental exposure to atrazine, perfluorooctanoic acid, bisphenol A, 2, 3, 7, 8-tetrachlorodibenzo-p-dioxin, and a mixture of these chemicals showed statistically significant sex difference with enhanced behavioral effects of mixtures in males. There is some evidence that as compared to female children, male children exposed to lead and PM2.5 air pollutants  have poorer cognitive performance.,, In other studies, male SHS exposed children had significantly higher prevalence of learning disabilities and conduct disorders compared to SHS exposed female children. Further maternal smoking during pregnancy was associated with increased risks of psychiatric symptoms in late adolescence for male children compared to female children.,
Sexually dimorphic characteristics are found in nearly every region of the brain and are fundamental for sex-dependent behaviors and can be seen in related neurodevelopmental disorders. These anatomic and functional differences evolve during prenatal, postnatal growth, and early adolescence. Nicotine is considered an endocrine disruptor  and is documented to increase estrogen, testosterone, and thyroid hormone levels with chronic exposure., Endocrine disrupting compounds including nicotine in smoke interfere with hormone-mediated development and sex differences and contribute to neuropsychiatric disorders that present with a sex bias. For example, microglia, the immune cells of the brain play an important role in the synaptic organization. Microglial programming of developing brain is sexually dimorphic in some region of the brain including brain area for social behavior, suggesting sex hormones dependence. Microglial growth colonization may be susceptible to endocrine disruption and may manifest as altered brain development and behavior. The fact that ASDs and Asperger's are four and nine times more prevalent in males than females, respectively, is postulated to be linked with sex hormone androgens or their estrogenic metabolites. An “extreme male” brain theory of autism has been proposed to explain ASD male preponderance due to higher prenatal androgens in ASD cases.
Nicotine is considered an endocrine disruptor  and is documented to increase estrogen, testosterone, and thyroid hormone levels with chronic exposure., Thyroid hormones are essential for neurodevelopment in prenatal and postnatal life and have been considered for their possible links to autism and ASDs., As reviewed by Flouris et al., (2009) SHS effects are more pronounced in men compared with women including SHS-induced changes in thyroid hormone secretion. Further studies are needed to better understand the SHS effect in males versus females.
In addition to being male, children with ASD were more likely to be older. This association concurs with previous studies of ASD. It is standard to screen for ASD between 18 and 24 months of a child's life. However, this screening is best suited for children on the more extreme end of the spectrum, namely, those with more severe autism or with intellectual disability. Children who have milder forms of ASD are more likely to remain undiagnosed until an older age. For instance, Asperger's syndrome was on average diagnosed at age seven.,
In the current analysis, greater maternal age was significantly associated with ASD. Multiple studies have shown increased maternal age is associated with ASD, and it has also been associated with chromosomal abnormalities and obstetric complications.,, Poor mental status of the mother was also found to be a risk factor for the development of ASD which is in accordance with prior research studies that concluded that poor mental health status of the mother is a predisposing factor for ASD in children., The increase in levels of stress hormones (such as adrenaline) in the mother leads to maternal vasoconstriction that in turn leads to placental vasoconstriction affecting fetal blood flow or directly affect fetal hormone levels leading to abnormal brain development.
Finally, maternal education greater than high school (for male children) and difficulty paying for basics (for both male and female children), a surrogate indicator for SES, were also significant risk factors for ASD. Previous research demonstrates that children belonging to the lower sociodemographic strata have higher risk of ASD., The stressors related to lower SES of the mother during the prenatal and perinatal period may predispose children to development of ASD. Previously, it was believed that higher SES was a risk factor for ASD in the US; however, it is believed that this is actually due to an SES disparity, as people of higher SES are more likely to receive health care and subsequently more likely to have their child diagnosed., Regarding maternal education specifically, in this analysis, male children whose mothers had higher education had 79% higher odds of ASD as compared to male children whose mothers had lower education. This could be explained by the fact that highly educated mothers have more access to the health-care services and hence children are diagnosed at an earlier age; however, this would not explain why the association was not seen in female children (OR = 0.98). Children with ASD are also more likely to have an individualized education program if their mother is more educated, not if they have more severe ASD.
Limitations of the study include the fact that the results could be impacted by recall bias since the data were taken from a survey. Furthermore, the association between SHS and ASD only shows association and not causality; longitudinal studies that could control for prenatal maternal smoking and mother's exposure to SHS could provide a better understanding. Furthermore, even though many confounding variables were taken into consideration, there might have been some that were not addressed such as mother's smoking during pregnancy. Previous research evaluating the relationship between ASD and maternal smoking during pregnancy did not find a significant association, and thus the differentiation between perinatal and postnatal SHS may warrant further study. The strengths of the study are that the data were from a nationally representative sample. Future studies with longitudinal follow-up assessing prenatal exposure and controlling for maternal smoking will provide more insight.
| Conclusions|| |
We conclude that SHS is significantly associated with ASD in male children. In addition, sociodemographic characteristics and natal and prenatal factors are important etiologic influences for ASD. Targeted efforts to change the smoking behavior of parents and caregivers of children could reduce ASD.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
CDC. (Centers for Disease Control and Prevention). Division of Birth Defects, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention; 2016. Available from: http://www.cdc.gov/ncbddd/autism/data.html
. [Last accessed on 2016 May 17].
Ben Itzchak E, Lahat E, Zachor DA. Advanced parental ages and low birth weight in autism spectrum disorders – Rates and effect on functioning. Res Dev Disabil 2011;32:1776-81.
Sandin S, Hultman CM, Kolevzon A, Gross R, MacCabe JH, Reichenberg A, et al.
Advancing maternal age is associated with increasing risk for autism: A review and meta-analysis. J Am Acad Child Adolesc Psychiatry 2012;51:477-860.
Schieve LA, Boulet SL, Blumberg SJ, Kogan MD, Yeargin-Allsopp M, Boyle CA, et al.
Association between parental nativity and autism spectrum disorder among US-born non-hispanic white and Hispanic children, 2007 National Survey of Children's Health. Disabil Health J 2012;5:18-25.
Leavey A, Zwaigenbaum L, Heavner K, Burstyn I. Gestational age at birth and risk of autism spectrum disorders in Alberta, Canada. J Pediatr 2013;162:361-8.
Quinlan CA, McVeigh KH, Driver CR, Govind P, Karpati A. Parental age and autism spectrum disorders among New York city children 0-36 months of age. Matern Child Health J 2015;19:1783-90.
Rai D, Lewis G, Lundberg M, Araya R, Svensson A, Dalman C, et al.
Parental socioeconomic status and risk of offspring autism spectrum disorders in a Swedish population-based study. J Am Acad Child Adolesc Psychiatry 2012;51:467-76.e6.
Williams K, Helmer M, Duncan GW, Peat JK, Mellis CM. Perinatal and maternal risk factors for autism spectrum disorders in New South Wales, Australia. Child Care Health Dev 2008;34:249-56.
Burd L, Severud R, Kerbeshian J, Klug MG. Prenatal and perinatal risk factors for autism. J Perinat Med 1999;27:441-50.
Zhang X, Lv CC, Tian J, Miao RJ, Xi W, Hertz-Picciotto I, et al.
Prenatal and perinatal risk factors for autism in China. J Autism Dev Disord 2010;40:1311-21.
Larsson HJ, Eaton WW, Madsen KM, Vestergaard M, Olesen AV, Agerbo E, et al.
Risk factors for autism: Perinatal factors, parental psychiatric history, and socioeconomic status. Am J Epidemiol 2005;161:916-25.
Grether JK, Anderson MC, Croen LA, Smith D, Windham GC. Risk of autism and increasing maternal and paternal age in a large north American population. Am J Epidemiol 2009;170:1118-26.
Chaste P, Leboyer M. Autism risk factors: Genes, environment, and gene-environment interactions. Dialogues Clin Neurosci 2012;14:281-92.
Delobel-Ayoub M, Ehlinger V, Klapouszczak D, Maffre T, Raynaud JP, Delpierre C, et al.
Socioeconomic disparities and prevalence of autism spectrum disorders and intellectual disability. PLoS One 2015;10:e0141964.
Ronald A, Happé F, Dworzynski K, Bolton P, Plomin R. Exploring the relation between prenatal and neonatal complications and later autistic-like features in a representative community sample of twins. Child Dev 2010;81:166-82.
Sealey LA, Hughes BW, Sriskanda AN, Guest JR, Gibson AD, Johnson-Williams L, et al.
Environmental factors in the development of autism spectrum disorders. Environ Int 2016;88:288-98.
Rossignol DA, Genuis SJ, Frye RE. Environmental toxicants and autism spectrum disorders: A systematic review. Transl Psychiatry 2014;4:e360.
Ming X. Environmental toxicants and autism spectrum disorders. Autism 2012;2:e108.
Centers for Disease Control and Prevention (CDC). Vital signs: Nonsmokers' exposure to secondhand smoke – United States, 1999-2008. MMWR Morb Mortal Wkly Rep 2010;59:1141-6.
Kabir Z, Connolly GN, Alpert HR. Secondhand smoke exposure and neurobehavioral disorders among children in the United States. Pediatrics 2011;128:263-70.
Marano C, Schober SE, Brody DJ, Zhang C. Secondhand tobacco smoke exposure among children and adolescents: United States, 2003-2006. Pediatrics 2009;124:1299-305.
Eskenazi B, Trupin LS. Passive and active maternal smoking during pregnancy, as measured by serum cotinine, and postnatal smoke exposure. II. Effects on neurodevelopment at age 5 years. Am J Epidemiol 1995;142:S19-29.
Eskenazi B, Castorina R. Association of prenatal maternal or postnatal child environmental tobacco smoke exposure and neurodevelopmental and behavioral problems in children. Environ Health Perspect 1999;107:991-1000.
Chen R, Clifford A, Lang L, Anstey KJ. Is exposure to secondhand smoke associated with cognitive parameters of children and adolescents? – A systematic literature review. Ann Epidemiol 2013;23:652-61.
Park S, Cho SC, Hong YC, Kim JW, Shin MS, Yoo HJ, et al.
Environmental tobacco smoke exposure and children's intelligence at 8-11 years of age. Environ Health Perspect 2014;122:1123-8.
Kalkbrenner AE, Schmidt RJ, Penlesky AC. Environmental chemical exposures and autism spectrum disorders: A review of the epidemiological evidence. Curr Probl Pediatr Adolesc Health Care 2014;44:277-318.
U.S. Department of Health and Human Services. The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Coordinating Center for Health Promotion, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2006.
Rice D, Barone S Jr. Critical periods of vulnerability for the developing nervous system: Evidence from humans and animal models. Environ Health Perspect 2000;108 Suppl 3:511-33.
NSDUH. Center for Behavioral Health Statistics and Quality. Behavioral Health Trends in the United States: Results from the 2014 National Survey on Drug Use and Health (HHS Publication No. SMA 15-4927, NSDUH Series H-50); 2015. Available from: http://www.samhsa.gov/data/
. [Last accessed on 2016 Dec 26].
Tong VT, Dietz PM, Morrow B, D'Angelo DV, Farr SL, Rockhill KM, et al.
Trends in smoking before, during, and after pregnancy – Pregnancy Risk Assessment Monitoring System, United States, 40 sites, 2000-2010. MMWR Surveill Summ 2013;62:1-9.
CDC. (Centers for Disease Control and Prevention) 2011-2012 National Survey of Children's Health, 2016; 2011-2012. Available from: http://www.cdc.gov/nchs/slaits/nsch.htm
. [Last accessed on 2016 May 17].
CDC. (Centers for Disease Control and Prevention). National Center for Health Statistics. National Health and Nutrition Examination Survey: Reference Manuals and Reports. Survey Methods and Analytic Guidelines. Estimation and Weighting Procedures; 2016. Available from: http://www.cdc.gov/nchs/nhanes/search/nhanes09_10.aspx
. [Last accessed on 2016 May 17].
Kalkbrenner AE, Braun JM, Durkin MS, Maenner MJ, Cunniff C, Lee LC, et al.
Maternal smoking during pregnancy and the prevalence of autism spectrum disorders, using data from the autism and developmental disabilities monitoring network. Environ Health Perspect 2012;120:1042-8.
Tran PL, Lehti V, Lampi KM, Helenius H, Suominen A, Gissler M, et al.
Smoking during pregnancy and risk of autism spectrum disorder in a finnish national birth cohort. Paediatr Perinat Epidemiol 2013;27:266-74.
Williams GM, O'Callaghan M, Najman JM, Bor W, Andersen MJ, Richards D, et al.
Maternal cigarette smoking and child psychiatric morbidity: A longitudinal study. Pediatrics 1998;102:e11.
Halladay AK, Bishop S, Constantino JN, Daniels AM, Koenig K, Palmer K, et al.
Sex and gender differences in autism spectrum disorder: Summarizing evidence gaps and identifying emerging areas of priority. Mol Autism 2015;6:36.
Pinborough-Zimmerman J, Satterfield R, Miller J, Bilder D, Hossain S, McMahon W, et al.
Communication disorders: Prevalence and comorbid intellectual disability, autism, and emotional/behavioral disorders. Am J Speech Lang Pathol 2007;16:359-67.
Willcutt EG. The prevalence of DSM-IV attention-deficit/hyperactivity disorder: A meta-analytic review. Neurotherapeutics 2012;9:490-9.
Lanphear BP, Auinger P, Froehlich T, Kahn RS, Braun J. Exposures to environmental toxicants and attention deficit hyperactivity disorder in US children. Environ Health Perspect 2006;114:1904-9.
Sobolewski M, Conrad K, Allen JL, Weston H, Martin K, Lawrence BP, et al.
Sex-specific enhanced behavioral toxicity induced by maternal exposure to a mixture of low dose endocrine-disrupting chemicals. Neurotoxicology 2014;45:121-30.
Jedrychowski W, Perera F, Mrozek-Budzyn D, Mroz E, Flak E, Spengler JD, et al.
Gender differences in fetal growth of newborns exposed prenatally to airborne fine particulate matter. Environ Res 2009;109:447-56.
Bellinger D, Leviton A, Waternaux C, Needleman H, Rabinowitz M. Longitudinal analyses of prenatal and postnatal lead exposure and early cognitive development. N Engl J Med 1987;316:1037-43.
Bellinger DC, Needleman HL. Intellectual impairment and blood lead levels. N Engl J Med 2003;349:500-2.
Jedrychowski W, Perera F, Jankowski J, Mrozek-Budzyn D, Mroz E, Flak E, et al.
Gender specific differences in neurodevelopmental effects of prenatal exposure to very low-lead levels: The prospective cohort study in three-year olds. Early Hum Dev 2009;85:503-10.
Fergusson DM, Woodward LJ, Horwood LJ. Maternal smoking during pregnancy and psychiatric adjustment in late adolescence. Arch Gen Psychiatry 1998;55:721-7.
Weissman MM, Warner V, Wickramaratne PJ, Kandel DB. Maternal smoking during pregnancy and psychopathology in offspring followed to adulthood. J Am Acad Child Adolesc Psychiatry 1999;38:892-9.
Rebuli ME, Patisaul HB. Assessment of sex specific endocrine disrupting effects in the prenatal and pre-pubertal rodent brain. J Steroid Biochem Mol Biol 2016;160:148-59.
Bergman Š, Heindel JJ, Jobling S, Kidd KA, Zoeller RT, Jobling SK. State of the Science of Endocrine Disrupting Chemicals 2012: An Assessment of the State of the Science of Endocrine Disruptors Prepared by a Group of Experts for the United Nations Environment Programme and World Health Organization: World Health Organization; 2013.
Tweed JO, Hsia SH, Lutfy K, Friedman TC. The endocrine effects of nicotine and cigarette smoke. Trends Endocrinol Metab 2012;23:334-42.
Flouris AD, Vardavas CI, Metsios GS, Tsatsakis AM, Koutedakis Y. Biological evidence for the acute health effects of secondhand smoke exposure. American Journal of Physiology-Lung Cellular and Molecular Physiology. 2009;298:L3-12.
Gore AC, Martien KM, Gagnidze K, Pfaff D. Implications of prenatal steroid perturbations for neurodevelopment, behavior, and autism. Endocr Rev 2014;35:961-91.
Rebuli ME, Gibson P, Rhodes CL, Cushing BS, Patisaul HB. Sex differences in microglial colonization and vulnerabilities to endocrine disruption in the social brain. Gen Comp Endocrinol 2016;238:39-46.
Knickmeyer RC, Baron-Cohen S. Fetal testosterone and sex differences in typical social development and in autism. J Child Neurol 2006;21:825-45.
Khan A, Harney JW, Zavacki AM, Sajdel-Sulkowska EM. Disrupted brain thyroid hormone homeostasis and altered thyroid hormone-dependent brain gene expression in autism spectrum disorders. J Physiol Pharmacol 2014;65:257-72.
Andersen SL, Laurberg P, Wu CS, Olsen J. Attention deficit hyperactivity disorder and autism spectrum disorder in children born to mothers with thyroid dysfunction: A Danish nationwide cohort study. BJOG 2014;121:1365-74.
Fairthorne J, Jacoby P, Bourke J, de Klerk N, Leonard H. Onset of maternal psychiatric disorders after the birth of a child with autism spectrum disorder: A retrospective cohort study. Autism 2016;20:37-44.
Harstad E, Huntington N, Bacic J, Barbaresi W. Disparity of care for children with parent-reported autism spectrum disorders. Acad Pediatr 2013;13:334-9.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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