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Journal of Attention Disorders
http://jad.sagepub.com/content/early/2014/07/11/1087054714542002
The online version of this article can be found at:
DOI: 10.1177/1087054714542002
published online 15 July 2014Journal of Attention Disorders
Nooshin Razani, Joan F. Hilton, Bonnie L. Halpern-Felsher, Megumi J. Okumura, Holly E. Morrell and Irene H. Yen
Neighborhood Characteristics and ADHD: Results of a National Study
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Journal of Attention Disorders
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© 2014 SAGE Publications
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DOI: 10.1177/1087054714542002
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Article
Objective
ADHD is the most commonly diagnosed psychiatric condi-
tion in childhood: National estimates of prevalence range
from 8% to 10% of U.S. children (Bloom, Cohen, &
Freeman, 2011; Centers for Disease Control and Prevention
[CDC], 2010). ADHD is a highly heritable condition
(Faraone et al., 2005). Nongenetic factors such as preterm
birth, low birth weight, prenatal tobacco exposure, and
socioeconomic status have also been associated with ADHD
(Nigg, Nikolas, & Burt, 2010; Russell, Ford, Rosenberg, &
Kelly, 2014). We are interested in whether neighborhood, in
other words, the social and physical environment where
young people spend their time, is associated with ADHD.
Previous research suggests that children with ADHD are
sensitive to place. A series of cross-sectional and interven-
tional studies show that natural settings are associated with
better impulse control and attention span in children with
ADHD (Kuo & Taylor, 2004; Taylor, 2001; Taylor & Kuo,
2009). Geographic variation has been shown in the preva-
lence of ADHD, and interestingly, correlated with sun expo-
sure (Arns, van der Heijden, Arnold, & Kenemans, 2013).
Children with ADHD may also benefit from living in
neighborhoods that promote physical activity. Physical
activity has been associated with improved cognition and
behavior in the general population (Archer & Kostrzewa,
2012; Gapin, Labban, & Etnier, 2011) and improved
symptoms in children with ADHD (Medina et al., 2010).
Neighborhood amenities that increase physical activity
include the presence of recreation centers, sidewalks, mixed
land use providing a variety of walking destinations (such
as a library), and nearby parks and playgrounds (Ding,
Sallis, Kerr, Lee, & Rosenberg, 2011; Mota, Almeida,
Santos, & Ribeiro, 2005; Veitch et al., 2012). Other neigh-
borhood factors such as a lack of safety, or neighborhood
disorder in the form of vandalism and graffiti detract from
physical activity.
A neighborhoods’ social environment, the presence of
social networks, trust, cooperation, and sense of safety
among neighbors has been protective for a variety of
health outcomes including other mental health conditions
(Chung & Docherty, 2011; Evans, 2003; Leventhal &
Brooks-Gunn, 2000). There is reason to believe that these
associations would apply to ADHD as well. Improved
support for mothers of children with ADHD has been
shown to improve psychological measures such as per-
ceived stress, anxiety, and depression (Lovell, Moss, &
542002JADXXX10.1177/1087054714542002Journal of Attention DisordersRazani et al.
research-article2014
1University of California at San Francisco, USA
Corresponding Author:
Nooshin Razani, UCSF Benioff Children’s Hospital Oakland, 5220
Claremont Ave., Oakland, CA 94609, USA.
Email: nrazani@mail.cho.org
Neighborhood Characteristics and ADHD:
Results of a National Study
Nooshin Razani1, Joan F. Hilton1, Bonnie L. Halpern-Felsher1,
Megumi J. Okumura1, Holly E. Morrell1, and Irene H. Yen1
Abstract
Objective: We examined the association of neighborhood social and physical characteristics with ADHD, accounting
for individual and family factors. Method: The 2007 National Survey of Child Health, a nationally representative data set,
was used (N = 64,076). Three neighborhood scales were generated: social support, amenities, and disorder. Logistic and
ordinal logistic regressions were conducted to examine the association of these scales with ADHD diagnosis and severity
while adjusting for individual and family characteristics. Results: Eight percent had a child with ADHD: 47% described
as mild, 40% moderate, and 13% severe. In adjusted models, lower neighborhood support was associated with increased
ADHD diagnosis (odds ratio [OR] = 1.66 [1.05, 2.63]) and severity (OR = 3.74 [1.71, 8.15]); neighborhood amenities
or disorder were not significantly associated. Poor parental mental health was associated with ADHD prevalence and
severity. Conclusion: Neighborhood social support is a potential area of intervention for children with ADHD and their
caregivers. Research challenges and opportunities are discussed. (J. of Att. Dis. XXXX; XX(X) XX-XX)
Keywords
ADD/ADHD, childhood, parks, physical activity, neighborhood characteristics, parental functioning
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2 Journal of Attention Disorders
Wetherell, 2012). Is it possible that improved social sup-
port at the neighborhood level will buffer the stresses
associated with ADHD?
Curtis et al. (2013) create a conceptual framework link-
ing neighborhood conditions to mental health. This frame-
work shows interplay between neighborhood physical
characteristics and social factors that influence causal path-
ways in mental health. These neighborhood or community-
level factors interact with individual and family attributes
that may put the person at risk of mental health
dysfunction.
While there is a theoretic association of ADHD and
neighborhood physical and social characteristics suggested
by these studies, we are not aware at studies looking at the
potential and compared relationship. Using a nationally
representative survey of children in the United States, we
examine the relationship between neighborhood character-
istics and ADHD, while accounting for individual and fam-
ily level factors. The aims of the present study were to
determine whether:
1. Neighborhood social characteristics such as trust
among neighbors and perceived safety (social sup-
port), plus physical characteristics such as side-
walks, libraries, recreation centers, parks, and
disorder, are associated with ADHD prevalence.
2. These neighborhood social characteristics and phys-
ical characteristics are associated with ADHD
severity.
3. These findings hold true after controlling for indi-
vidual and family characteristics.
We hypothesized that greater neighborhood social sup-
port and amenities, and that less neighborhood disorder
would be associated with lower ADHD prevalence and
severity.
Method
Data Set
This is a secondary data analysis of the 2007 National
Survey of Children’s Health (NSCH). This telephone sur-
vey was conducted as part of the State and Local Area
Integrated Telephone Survey Program (http://www.cdc.
gov/nchs/slaits/nsch.htm#2007nsch) by the National Center
for Health Statistics with funding from the Maternal Child
Health Bureau and CDC. Telephone interviews were con-
ducted in English, Spanish, Mandarin, Cantonese,
Vietnamese, or Korean. Sampling weights were provided
by the NSCH to represent the entire noninstitutionalized
child population in the United States. Further description of
the sampling methodology is described elsewhere
(Blumberg et al., 2012).
Participants
The study participant was the adult in eligible families who
knew the most about the sample child’s health. (In 94% of
cases, this was the mother or father; hence, we will refer to
the respondent as the parent.) We limited the sample to chil-
dren of age 6 and above, which was the age range specified
by the Diagnostic and Statistical Manual of Mental
Disorders (4th ed.; DSM-IV; American Psychiatric
Association, 1994) definition of ADHD in place when the
data were collected (N = 64,076, 70% of 91,642 total
surveys).
Measures
ADHD prevalence and severity. Children were identified as
having ADHD if the parent answered yes to both of the fol-
lowing questions: “Has a doctor or health care provider ever
told you that [sample child] has ADHD or ADD?” followed
by, “Does [sample child] currently have [ADHD or ADD]?”
Parents were asked, “Would you describe [sample child’s]
illness as mild, moderate, or severe?” For analysis, severity
was limited to children with ADHD and scored as: mild (1),
moderate (2), and severe (3).
Family characteristics. Characteristics of the family environ-
ment were chosen based on previously recognized associa-
tions with ADHD, including race/ethnicity (non-Hispanic
White, Hispanic, non-Hispanic Black, and Other; Merikan-
gas et al., 2010), income as percentage of federal poverty
level (greater than 400% federal poverty level, 200%-400%
federal poverty level, and less than 200% federal poverty
level), family structure (two biological or adoptive parents,
two parents with at least one step-parent, one parent house-
hold, and other family structures), maternal education
(greater than high school, high school, less than high
school), and self-reported maternal mental health (excel-
lent/very good, good, or fair/poor; Blackwell, 2010; John-
ston & Mash, 2001; Nigg et al., 2010).
Neighborhood characteristics. Twelve questions survey
neighborhood social and physical characteristics. Initial
analysis was run using each variable independently. As sev-
eral of the variables were correlated, the analysis was
repeated using a collapsed set of categories.
To create categories, principal components analysis was
conducted using a polychoric correlation matrix to account
for the combination of ordinal and binary variables
(Kolenikov & Angeles, 2004). Three unique components
were chosen based on the results of a parallel analysis
(Hayton, Allen, & Scarpello, 2004). The component-based
scales described below were created by using variables with
loading scores greater than 0.3. Internal consistency of
these scales was confirmed using Cronbach’s alpha. These
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Razani et al. 3
categories are also consistent with scales of support, ameni-
ties, and disorder used by others (Ding et al., 2011; Grootaert
& van Bastelaer, 2001; Sampson & Raudenbush, 1999).
The first scale, “Neighborhood Support,” comprised five
questions (Figure 1), with four-point Likert-type scale
responses. The nonmissing values for each respondent were
averaged to generate a four-point scale. We converted the
resulting scale, ranging from 1 to 4, to a categorical scale, with
“low” (1.0-1.9), “medium” (2.0-3.9), and “high” (4) levels of
support. After generating the scale, 3% had a missing value.
The second scale, “Neighborhood Amenities,” com-
prised four questions (Figure 1), with yes (1) or no (0)
answers each. Nonmissing responses were summed to gen-
erate a scale that ranges from 0 to 4. The data are presented
as “none” (zero amenities), “some” (1-3 amenities), and
“all” (4 amenities). After generating the scale, 2% had a
missing value because one or more questions were
missing.
The final scale, “Neighborhood Disorder,” comprised
three questions (Figure 1) with yes/no answers. Nonmissing
responses were summed to create a scale that ranged from 0
to 3. We present the data in three categories: “none” (zero
markers for disorder), “some” (1-2 markers of disorder),
and “all” (3 markers of disorder). After the scales were gen-
erated, 1% had a missing value because one or more ques-
tions were missing.
Statistical Analysis
We present the overall distributions of each of the neighbor-
hood and family characteristics, as well as the distributions
of the family characteristics within each of the neighbor-
hood characteristics (Table 1). We performed descriptive
statistics on family characteristics and neighborhood char-
acteristics using the Cochran–Mantel–Haenszel chi-square
tests.
We conducted a series of unadjusted logistic regression
analyses predicting odds of reported ADHD diagnosis with
individual, family, and neighborhood characteristics, a mul-
tivariate logistic regression analysis predicting odds of
ADHD prevalence with neighborhood characteristics after
controlling for individual and family—covariates, and an
analogous set of unadjusted and multivariate ordinal logis-
tic regression analyses to examine the influence of family—
and neighborhood characteristics on three levels of ADHD
severity. Given that a child’s age and sex are recognized
covariates of ADHD prevalence, we controlled for them in
the final multivariable models (Mick, Faraone, &
Biederman, 2004; Rucklidge, 2010). All analyses were con-
ducted using Stata 11 (College Station, TX), accounting for
the complex sampling design.
Results
Sample Characteristics
Most respondents reported medium to high Neighborhood
Support, medium to high Neighborhood Amenities, and low
Neighborhood Disorder. Four percent of parents reported
feeling low Support, 5% reported having no Amenities, and
4% reported having all three markers of Neighborhood
Disorder.
Neighborhood Support
How much do you agree or disagree with each of these statements about your neighborhood or community:
“People in this neighborhood help each other out”
“We watch out for each other’s children in this neighborhood”
“There are people I can count on in this neighborhood”
“If my child were outside playing and got hurt or scared, there are adults nearby who I trust to help my child”
How often do you feel your child is safe in your neighborhood?
Neighborhood Amenities
Which of the following are available in your neighborhood, even if your child does not use them?
A park or playground area
Sidewalks or walking paths
A library or bookmobile
A recreation center, community center, boys’ or girls’ club
Neighborhood Disorder
Which of the following exist in your neighborhood?
Litter or garbage on the street or sidewalks
Poorly kept or delapidated housing
Vandalism such as broken windows or graffiti.
Figure 1. 2007 National Survey of Child Health Neighborhood Scales.
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4 Journal of Attention Disorders
Neighborhood characteristics varied by socioeconomic
status (Table 1). A higher proportion of White respondents
reported higher Neighborhood Support (69%) than the pro-
portion of Hispanic (13%) or African American (10%)
respondents. Higher income, maternal education, parental
mental health levels, and two parent (biological or adoptive)
households are represented at higher proportions in the
higher Neighborhood Support categories, as well as with
more Amenities and less Disorder. Of note, only 4% of care-
givers who stated they had high Neighborhood Support
reported poor mental health, whereas 26% of those with low
Neighborhood Support reported poor mental health. Each of
these associations was statistically significant at p < .01.
ADHD Diagnosis, Controlling for Neighborhood,
and Family Factors
Eight percent of participants reported having a child with
ADHD. ADHD prevalence among children with low
Neighborhood Support was 15%, as compared with 7% to
8% in those with more Social Support (Table 2). The
prevalence of ADHD was also higher among individuals
reporting high Neighborhood Disorder, low incomes,
lower maternal mental health, and households not headed
by two biological or adoptive parents. Low Neighborhood
Support remained associated with higher ADHD preva-
lence after adjusting for child, family, and other neighbor-
hood variables (odds ratio [OR] = 1.66; 95% confidence
intervals [CI] = [1.05, 2.63]). Neighborhood Disorder and
Amenities were not associated with higher ADHD preva-
lence. Lower levels of reported maternal mental health
were associated with higher ADHD prevalence with an
odds ratio of 3.03 (95% CI = [2.35, 3.91]), family struc-
tures other than two biological or adoptive parents were
also associated with higher ADHD, while non-White
race/ethnicity and lower maternal education had lower
odds.
ADHD Severity, Controlling for Neighborhood,
and Family Factors
Of those with ADHD, 47% have mild symptoms, 40% mod-
erate symptoms, and 13% were described as severe. Lower
Neighborhood Support was associated with higher ADHD
Table 1. U.S. NSCH 2007 Results: Distributions of Family Characteristics, Overall and Within Level of Neighborhood
Characteristics.
Neighborhood characteristics
Support (%) Amenities (%) Disorder (%)
Family characteristics Full sample N = 64,076 (%) Low Medium High None Some All None Some All
Race/ethnicity
White 57 29 56 69 64 60 55 61 50 34
Hispanic 19 33 20 13 18 19 18 18 23 24
Black 15 31 16 10 12 13 17 13 17 32
Other 8 7 9 8 6 7 10 8 10 9
Income as percentage of federal poverty level
Greater than 400 30 8 29 40 18 28 34 35 18 10
200-400 33 19 33 34 33 33 32 33 32 25
Less than 200 37 74 38 26 49 39 33 31 50 66
Maternal education
Greater than high school 62 35 62 68 49 59 67 66 54 40
High school or equivalent 26 39 26 23 34 27 25 24 31 38
Less than high school 12 26 12 9 17 14 9 10 15 23
Maternal mental health
Very good/excellent 71 43 69 82 62 69 74 74 64 54
Good 21 27 22 15 27 22 19 20 24 27
Poor/fair 8 29 8 4 11 9 7 6 12 19
Family structure
Two parent, biological or adoptive 63 37 62 71 62 63 62 66 57 42
One parent 20 44 20 14 18 20 20 18 24 36
Two parent, at least one step 10 11 10 10 10 10 10 10 11 14
All others 7 8 7 6 10 7 7 7 7 8
Note. NSCH = National Survey of Children’s Health.
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Razani et al. 5
severity, after controlling for age, sex, other family and
neighborhood factors (Table 3; OR = 3.74; 95% CI = [1.71,
8.15]). The presence of Neighborhood Amenities was not
significantly associated with decreased reported ADHD
severity (OR = 1.56; 95% CI = [0.91, 2.68]), although the
increasing odds with decreasing amenities score suggests a
potential relationship. Reported poor parental mental health
and lower income were associated with increased ADHD
severity.
Conclusion
In this nationally representative sample of U.S. children, we
found that lower neighborhood social support was associ-
ated with higher odds of ADHD diagnosis and higher
ADHD severity, even after taking into consideration age,
sex, family, income, and other neighborhood characteris-
tics. Neighborhood amenities and disorder were not statisti-
cally associated with ADHD prevalence or severity.
Table 2. U.S. NSCH 2007 Results: Neighborhood and Family Level Associations With Odds of ADHD Diagnosis (n = 52,084).
OR of ADHD (95% CI)
% ADHD prevalence Unadjusted Adjusted
Full sample 8
Neighborhood characteristics
Neighborhood support
High 7 Ref Ref
Medium 8 1.21 [1.03, 1.43] 1.13 [0.94, 1.37]
Low 15 2.28 [1.50, 3.48] 1.66 [1.05, 2.63]
Neighborhood amenities
All (4 of 4) 8 Ref Ref
Some (1-3 of 4) 9 1.13 [0.98, 1.38] 1.12 [0.96, 1.30]
None (zero of 4) 8 1.06 [0.83, 1.36] 0.90 [0.66, 1.24]
Neighborhood disorder
None (zero of 3) 8 Ref Ref
Some (1-2 of 3) 9 1.12 [0.95, 1.30] 0.96 [0.81, 1.14]
All (3 of 3) 13 1.78 [1.29, 2.47] 1.43 [0.96, 2.15]
Family characteristics
Race/ethnicity
White (non-Hispanic) 9 Ref Ref
Hispanic 5 0.51 [0.39, 0.67] 0.44 [0.30, 0.65]
Black (non-Hispanic) 9 1.00 [0.82, 1.21] 0.62 [0.48, 0.80]
Other (non-Hispanic) 8 0.88 [0.69, 1.12] 0.81 [0.62, 1.07]
Income as percentage of federal poverty level
Greater than 400 7 Ref Ref
200-400 8 1.01 [0.84, 1.21] 0.89 [0.73, 1.09]
Less than 200 10 1.36 [1.13, 1.63] 1.09 [0.87, 1.38]
Maternal education
Greater than high school 8 Ref Ref
High school or equivalent 9 1.15 [0.98, 1.36] 0.96 [0.80, 1.15]
Less than high school 7 0.91 [0.70, 1.16] 0.69 [0.51, 0.93]
Maternal mental health
Very good/excellent 6 Ref Ref
Good 10 1.59 [1.34, 1.87] 1.61 [1.34, 1.93]
Poor/fair 19 3.42 [2.69, 4.35] 3.03 [2.35, 3.91]
Family structure
Two parent, biological/
adoptive
6 Ref Ref
One parent 11 2.29 [1.93, 2.71] 1.93 [1.58, 2.36]
Two parents, step-parent 13 1.99 [1.63, 2.43] 1.76 [1.42, 2.17]
All other family structures 12 2.15 [1.72, 2.68] 2.31 [1.34, 3.99]
Note. Adjusted model included age and sex. NSCH = National Survey of Children’s Health; OR = odds ratio; CI = confidence interval.
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6 Journal of Attention Disorders
Individuals with ADHD have elevated stress levels and
poorer recovery from stress than control groups
(Lackschewitz, Huther, & Kroner-Herwig, 2008). Families
living with ADHD have been shown to have increased
stresses such conflict compared with controls (Russell et
al., 2014). One explanation for our findings is that neigh-
borhood social support serves as buffer for these stressors, a
potential added factor in creating resiliency, and that its
absence exacerbates ADHD in those at genetic risk
(Modesto-Lowe, Yelunina, & Hanjan, 2011). For children
with ADHD, who often have social dysfunction because of
inattention, hyperactivity, and impulsivity (Nijmeijer et al.,
2008), a neighborhood with social support may provide
added opportunity to create social bonds beyond those from
school or home environments.
Neighborhood social conditions have been associated
with other mental health conditions. Perceived or actual
poor neighborhood safety increases the risk of externalizing
problems such as generalized misconduct, delinquency,
hostility, and violent behaviors as well as greater risk of
internalizing problems such as depression, distress, and
anxiety (Curtis et al., 2013). Social capital, defined as trust,
community participation, and community/individual net-
works have been associated with mood disorders, such that
Table 3. U.S. NSCH 2007 Results: ADHD Severity and Neighborhood, Family Characteristics (n = 4,290).
Odds for increased ADHD severity OR (95% CI)
Unadjusted Adjusted
Neighborhood characteristics
Neighborhood support
High Ref Ref
Medium 1.37 [1.03, 1.83] 1.22 [0.89, 1.66]
Low 4.60 [2.76, 7.66] 3.74 [1.71, 8.15]
Neighborhood amenities
All (4 of 4) Ref Ref
Some (1-3 of 4) 1.73 [1.23, 2.45] 1.27 [0.94, 1.70]
None (0 of 4) 1.39 [1.07, 1.80] 1.56 [0.91, 2.68]
Neighborhood disorder
None (zero of 3) Ref Ref
Some (1-2 of 3) 1.38 [1.02, 1.86] 1.05 [0.75, 1.48]
All (3 of 3) 1.56 [0.81, 3.01] 0.84 [0.42, 1.68]
Family characteristics
Race/ethnicity
White (non-Hispanic) Ref Ref
Hispanic 0.69 [0.40, 1.18] 0.60 [0.34, 1.05]
Black (non-Hispanic) 1.12 [0.77, 1.65] 0.74 [0.46, 1.18]
Other (non-Hispanic) 1.40 [1.00, 1.94] 1.67 [0.96, 2.90]
Income as percentage of federal poverty level
Greater than 400 Ref Ref
200-400 1.77 [1.27, 2.47] 1.77 [1.26, 2.49]
Less than 200 2.44 [1.74, 3.43] 1.81 [1.15, 2.83]
Maternal education
Greater than high school Ref Ref
High school or equivalent 1.48 [1.12, 1.97] 0.99 [0.71, 1.38]
Less than high school 1.31 [0.75, 2.28] 0.79 [0.42, 1.50]
Maternal mental health
Very good/excellent Ref Ref
Good 1.66 [1.24, 2.24] 1.33 [0.95, 1.87]
Poor/fair 2.91 [1.90, 4.48] 2.04 [1.22, 3.42]
Family structure
Two parent, biological/adoptive Ref Ref
One parent 1.69 [1.25, 2.29] 1.14 [0.77, 1.69]
Two parents, step-parent 1.34 [0.91, 1.97] 0.95 [0.62, 1.45]
All other family structures 1.13 [0.75, 1.68] 1.35 [0.50, 3.64]
Note. Adjusted model included age and sex. NSCH = National Survey of Children’s Health; OR = odds ratio; CI = confidence interval.
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Razani et al. 7
low social capital is associated with depression, anxiety,
and schizophrenia (Whitley & McKenzie, 2005).
The associations between neighborhood social condi-
tions and mental health may be applied to ADHD. In the
presence of externalizing or internalizing comorbidities
(such as anxiety or depression), having poor neighborhood
conditions may lead to increased diagnosis, or reported
severity of ADHD. While we did not adjust for comorbidi-
ties in this study, future research should investigate how
depression, anxiety, and misconduct may mediate the rela-
tionship between neighborhood and ADHD.
Modesto-Lowe et al. (2011) present a resilience frame-
work to explain the variability in the clinical, academic, and
social course of ADHD: In teen studies, 20% do well, 20%
do poorly, and 60% are somewhere in between. A resilient
life trajectory is one where individuals have tools to adapt
to adversity throughout their life span. In Modesto-Lowe’s
review they find that the best predictor of success with
ADHD (defined as being an adapted adult) is not IQ, aca-
demic achievement, or classroom behavior, but peer rela-
tionships. Modesto-Lowe et al. (2011) argue that there is a
need to find strategies for social competence in children
with ADHD. We propose that interventions at the neighbor-
hood level, which create opportunities to socialize, and a
feeling of support and trust at home, may be helpful for
families with ADHD.
Secure attachment, experiencing positive emotions, and
having a purpose in life are three important aspects of resil-
ience in mental health in general. For families with a child
with ADHD, social support at the neighborhood level may
improve parental mental health and therefore opportunities
for secure attachment for children. As reviewed above, fam-
ilies dealing with ADHD may need even more support than
other families. Parents may feel overwhelmed, depressed,
or in need of support. Neighborhood social support may
also help resilience in that a decrease in the child’s ADHD
may improve the child’s behavior, and therefore parental
mental health. Neighborhood support as we defined it—
perceived neighborhood trust and perceived safety—has
been associated with parents’ willingness to allow their
children to play in outdoor public places and to use avail-
able amenities (Evans, 2006; Rosenberg et al., 2009). In
supportive settings even where there are amenities such as
parks, children may be able to experience neighborhood
nature or to be physical active.
An important area of future research is how neighbor-
hood characteristics may be associated with mental health
outcomes for caregivers of children with ADHD. The
respondents in our study with low neighborhood support,
low amenities, and high disorder reported poor mental
health in the parent. In addition, poor maternal mental
health remained associated with ADHD in the final model.
Prior research has attributed poor mental health among par-
ents of children with ADHD with behavior problems or
oppositional behavior that can accompany ADHD
(Pimentel, Vieira-Santos, Santos, & Vale, 2011). It is easy to
imagine that these issues may be exacerbated in families
with ADHD where there is low neighborhood support, low
amenities, and high disorder. In Bartlett’s qualitative study
of families living in high-rises located in a neighborhood
with low perceived trust and safety, he describes how chil-
dren are kept indoors for much of the day, and mothers and
children had fewer opportunities to be outdoors to meet and
create social networks with neighbors. In the cases he fol-
lows, the missed opportunities for creating a safety net
among neighbors and restlessness among children kept
indoors all day contributed to family conflict and stress
(Bartlett, 1998). Cooper-Marcus’s observation of public
housing showed that the arrangement of public spaces is
related to when and how tenants have the opportunity to
socialize with each other, and how supported parents felt in
child care and in allowing their children to play outdoors
(Marcus, 2001; Marcus & Francis, 1998).
We did not find significant associations with neighbor-
hood physical characteristics as surveyed in the NSCH.
This finding dovetails with a variety of other work showing
more pronounced effect for neighborhood social than phys-
ical characteristics for mental health (Gidlow, Cochrane,
Davey, Smith, & Fairburn, 2010). Given the evidence that
children with ADHD benefit from time in nature, sunshine,
and from physical activity, it will be important to create
valid measures of neighborhood exposure before discount-
ing the importance of physical characteristics in the neigh-
borhood. The NSCH survey used in this study assessed for
the presence of a variety of neighborhood amenities and
detractors, but does not establish how often children were
exposed to amenities such as parks, and how often they
were outside in their neighborhood. In our case, it is of note
that the linear relationship between neighborhood amenities
and ADHD suggests that there may be a potential
relationship.
There are several limitations to this study. Relying on
parental report to measure ADHD severity in a child may
introduce measurement bias. The total prevalence of ADHD
in this sample may be overreported as the survey methodol-
ogy did not ask parents to distinguish whether ADHD diag-
noses were made by primary care providers or psychiatrists.
Inattentive children with mood disorders, anxiety disorders,
learning disabilities, or even autism may be misdiagnosed
as having ADHD. These misdiagnoses may have increased
the number of children who were diagnosed as having
ADHD or having “severe ADHD” as maternal depression,
mood disorders, and anxiety can show up in children whose
parents have mood and anxiety disorders. In future research
looking at ADHD and neighborhood conditions, parental
report should be corroborated by psychiatrist or develop-
mental pediatrician evaluation.
Future investigations are needed to determine how par-
ent, child, and investigator report of ADHD symptoms in a
range of neighborhood environments would be useful in
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8 Journal of Attention Disorders
assessing potential bias. Future analysis should look at the
potential role for mental health comorbidities which may be
on the causal pathway between neighborhood support and
ADHD. As this is a cross-sectional study, longitudinal
research will be necessary to tease out the potential causal
relationship between neighborhood social support and
ADHD. How the social and physical characteristics of a
neighborhood may interact in the context of ADHD is an
important area or further research.
Despite these limitations, the strengths of this study
include a large sample size and random survey sampling
design that create a unique opportunity to study ADHD in
the context of neighborhood characteristics across a repre-
sentative sample of noninstitutionalized children in the
United States. This is the first nationally representative
study of ADHD and neighborhood, family, and sociodemo-
graphic associations. Although ADHD is known to have a
strong genetic component, national studies such as this one
remind us of the importance of applying a public health per-
spective to ADHD, as finding neighborhood level correlates
implies there are multiple levels of opportunity for inter-
vention. Our study suggests that increasing neighborhood
social support—in the form of trust among neighbors, and
perceived safety—could positively affect the prevalence
and severity of ADHD.
Acknowledgment
We would like to thank Dr. Michael Cabana, Dr. Mark Miller, and
Rebecca Scherzer for their assistance in preparing this
manuscript.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
Funding
The author(s) received no financial support for the research,
authorship, and/or publication of this article.
References
American Psychiatric Association. (1994). Diagnostic and statis-
tical manual of mental disorders (4th ed.). Washington, DC:
Author.
Archer, T., & Kostrzewa, R. M. (2012). Physical exercise alle-
viates ADHD symptoms: Regional deficits and development
trajectory. Neurotoxicity Research, 21, 195-209. doi:10.1007/
s12640-011-9260-0
Arns, M., van der Heijden, K. B., Arnold, L. E., & Kenemans,
J. L. (2013). Geographic variation in the prevalence of
attention-deficit/hyperactivity disorder: The sunny perspec-
tive. Biological Psychiatry, 74, 585-590. doi:10.1016/j.bio-
psych.2013.02.010
Bartlett, S. (1998). Does inadequate housing perpetuate children’s
poverty? Childhood, 5, 403-420.
Blackwell, D. L. (2010). Family structure and children’s health
in the United States: Findings from the National Health
Interview Survey, 2001-2007 (Vital and Health Statistics,
Series 10, No. 246, pp. 1-166). Retrieved from http://www.
ncbi.nlm.nih.gov/pubmed/21388047
Bloom, B., Cohen, R. A., & Freeman, G. (2011). Summary
health statistics for U.S. children: National Health Interview
Survey, 2010 (Vital and Health Statistics, Series 10, No.
250, pp. 1-80). Retrieved from http://www.ncbi.nlm.nih.gov/
pubmed/22338334
Blumberg, S. J., Foster, E. B., Frasier, A. M., Satorius, J., Skalland,
B. J., Nysse-Carris, K. L., . . .O’Connor, K. S. (2012). Design
and operation of the National Survey of Children’s Health,
2007 (Vital and Health Statistics, Series 1, No. 55, pp. 1-149).
Retrieved from http://www.cdc.gov/nchs/data/series/sr_01/
sr01_055.pdf
Centers for Disease Control and Prevention. (2010). Increasing
prevalence of parent-reported attention-deficit/hyperac-
tivity disorder among children—United States, 2003 and
2007. Morbidity and Mortality Weekly Report, 59, 1439-
1443. Retrieved from http://www.cdc.gov/mmwr/preview/
mmwrhtml/mm5944a3.htm
Chung, H. L., & Docherty, M. (2011). The protective function of
neighborhood social ties on psychological health. American
Journal of Health Behavior, 35, 785-796.
Curtis, S., Pain, R., Fuller, S., Khatib, Y., Rothon, C., Stansfeld, S.
A., & Daya, S. (2013). Neighbourhood risk factors for com-
mon mental disorders among young people aged 10-20 years:
A structured review of quantitative research. Health Place,
20, 81-90. doi:10.1016/j.healthplace.2012.10.010
Ding, D., Sallis, J. F., Kerr, J., Lee, S., & Rosenberg, D. E. (2011).
Neighborhood environment and physical activity among
youth a review. American Journal of Preventive Medicine,
41, 442-455. doi:10.1016/j.amepre.2011.06.036
Evans, G. W. (2003). The built environment and mental health.
Journal of Urban Health, 80, 536-555. doi:10.1093/jurban/
jtg063
Evans, G. W. (2006). Child development and the physical envi-
ronment. Annual Review of Psychology, 57, 423-451.
doi:10.1146/annurev.psych.57.102904.190057
Faraone, S. V., Perlis, R. H., Doyle, A. E., Smoller, J. W.,
Goralnick, J. J., Holmgren, M. A., & Sklar, P. (2005).
Molecular genetics of attention-deficit/hyperactivity disor-
der. Biological Psychiatry, 57, 1313-1323. doi:10.1016/j.bio-
psych.2004.11.024
Gapin, J. I., Labban, J. D., & Etnier, J. L. (2011). The effects of
physical activity on attention deficit hyperactivity disorder
symptoms: The evidence. Preventive Medicine, 52(Suppl. 1),
S70-S74. doi:10.1016/j.ypmed.2011.01.022
Gidlow, C., Cochrane, T., Davey, R. C., Smith, G., & Fairburn,
J. (2010). Relative importance of physical and social aspects
of perceived neighbourhood environment for self-reported
health. Preventive Medicine, 51, 157-163. doi:10.1016/j.
ypmed.2010.05.006
Grootaert, C., & van Bastelaer, T. (Eds.). (2001). Understanding
and measuring social capital: A synthesis of findings and
at LOMA LINDA UNIV LIBRARY on July 17, 2014jad.sagepub.comDownloaded from
Razani et al. 9
recommendation for the social capital initiative. Washington,
DC: The World Bank.
Hayton, J. C., Allen, D. G., & Scarpello, V. (2004). Factor reten-
tion decisions in exploratory factor analysis: A tutorial on par-
allel analysis. Organizational Research Methods, 7, 191-205.
doi:10.1177/10944281094428104263675
Johnston, C., & Mash, E. J. (2001). Families of children with
attention-deficit/hyperactivity disorder: Review and recom-
mendations for future research. Clinical Child and Family
Psychology Review, 4, 183-207.
Kolenikov, S., & Angeles, G. (2004). The use of discrete data in
PCA: Theory, simulations, and applications to socioeconomic
indices. Retrieved from http://www.cpc.unc.edu/measure/
publications/wp-04-85
Kuo, F. E., & Taylor, A. F. (2004). A potential natural treatment
for attention-deficit/hyperactivity disorder: Evidence from
a national study. American Journal of Public Health, 94,
1580-1586.
Lackschewitz, H., Huther, G., & Kroner-Herwig, B. (2008).
Physiological and psychological stress responses in adults
with attention-deficit/hyperactivity disorder (ADHD).
Psychoneuroendocrinology, 33, 612-624. doi:10.1016/j.psy-
neuen.2008.01.016
Leventhal, T., & Brooks-Gunn, J. (2000). The neighborhoods they
live in: The effects of neighborhood residence on child and
adolescent outcomes. Psychological Bulletin, 126, 309-337.
Lovell, B., Moss, M., & Wetherell, M. A. (2012). With a little help
from my friends: Psychological, endocrine and health corol-
laries of social support in parental caregivers of children with
autism or ADHD. Research in Developmental Disabilities,
33, 682-687. doi:10.1016/j.ridd.2011.11.014
Marcus, C. C. (2001, March). The neighborhood approach to
building community: Different perspectives on smart growth.
Western City Magazine.
Marcus, C. C., & Francis, C. (1998). People places: Design guide-
lines for Urban Open Spaces (2nd ed.). Danvers, MA: John
Wiley.
Medina, J. A., Netto, T. L., Muszkat, M., Medina, A. C., Botter,
D., Orbetelli, R., . . .Miranda, M. C. (2010). Exercise impact
on sustained attention of ADHD children, methylphenidate
effects. Attention Deficit and Hyperactivity Disorders, 2, 49-
58. doi:10.1007/s12402-009-0018-y
Merikangas, K. R., He, J. P., Brody, D., Fisher, P. W., Bourdon,
K., & Koretz, D. S. (2010). Prevalence and treatment of men-
tal disorders among US children in the 2001-2004 NHANES.
Pediatrics, 125, 75-81. doi:10.1542/peds.2008-2598
Mick, E., Faraone, S. V., & Biederman, J. (2004). Age-dependent
expression of attention-deficit/hyperactivity disorder symp-
toms. Psychiatric Clinics of North America, 27, 215-224.
doi:10.1016/j.psc.2004.01.003
Modesto-Lowe, V., Yelunina, L., & Hanjan, K. (2011).
Attention-deficit/hyperactivity disorder: A shift
toward resilience? Clinical Pediatrics, 50, 518-524.
doi:10.1177/0009922810394836
Mota, J., Almeida, M., Santos, P., & Ribeiro, J. C. (2005).
Perceived neighborhood environments and physical activity in
adolescents. Preventive Medicine, 41, 834-836. doi:10.1016/j.
ypmed.2005.07.012
Nigg, J., Nikolas, M., & Burt, S. A. (2010). Measured gene-
by-environment interaction in relation to attention-deficit/
hyperactivity disorder. Journal of the American Academy of
Child & Adolescent Psychiatry, 49, 863-873. doi:10.1016/j.
jaac.2010.01.025
Nijmeijer, J. S., Minderaa, R. B., Buitelaar, J. K., Mulligan,
A., Hartman, C. A., & Hoekstra, P. J. (2008). Attention-
deficit/hyperactivity disorder and social dysfunctioning.
Clinical Psychology Review, 28, 692-708. doi:10.1016/j.
cpr.2007.10.003
Pimentel, M. J., Vieira-Santos, S., Santos, V., & Vale, M. C.
(2011). Mothers of children with attention deficit/hyperac-
tivity disorder: Relationship among parenting stress, paren-
tal practices and child behaviour. Attention Deficit and
Hyperactivity Disorders, 3, 61-68. doi:10.1007/s12402-011-
0053-3
Rosenberg, D., Ding, D., Sallis, J. F., Kerr, J., Norman, G.
J., Durant, N., . . .Saelens, B. E. (2009). Neighborhood
Environment Walkability Scale for Youth (NEWS-Y):
Reliability and relationship with physical activity. Preventive
Medicine, 49, 213-218. doi:10.1016/j.ypmed.2009.07.011
Rucklidge, J. J. (2010). Gender differences in attention-deficit/
hyperactivity disorder. Psychiatric Clinics of North America,
33, 357-373. doi:10.1016/j.psc.2010.01.006
Russell, G., Ford, T., Rosenberg, R., & Kelly, S. (2014). The
association of attention deficit hyperactivity disorder with
socioeconomic disadvantage: Alternative explanations and
evidence. Journal of Child Psychology and Psychiatry, 55,
436-445. doi:10.1111/jcpp.12170
Sampson, R. J., & Raudenbush, S. W. (1999). Systematic social
observation of public spaces: A new look at disorder in urban
neighborhoods. American Journal of Sociology, 105, 603-
651. doi:10.1086/210356
Taylor, A. F. (2001). Coping with ADD: The surprising connec-
tion to green play settings. Environment & Behavior, 33,
54-77.
Taylor, A. F., & Kuo, F. E. (2009). Children with attention deficits
concentrate better after walk in the park. Journal of Attention
Disorders, 12, 402-409. doi:10.1177/108705-4708323000
Veitch, J., van Stralen, M. M., Chinapaw, M. J., te Velde, S. J.,
Crawford, D., Salmon, J., & Timperio, A. (2012). The neigh-
borhood social environment and body mass index among
youth: A mediation analysis. The International Journal of
Behavioral Nutrition and Physical Activity, 9, Article 31.
doi:10.1186/1479-5868-9-31
Whitley, R., & McKenzie, K. (2005). Social capital and psychia-
try: Review of the literature. Harvard Review of Psychiatry,
13, 71-84. doi:10.1080/10673220590956474
Author Biographies
Nooshin Razani, MD MPH, is a pediatrician practicing at
UCSF Benioff Children’s Hospital Oakland. She currently
serves as senior health fellow for the Institute at the Golden
Gate, a program of the Golden Gate National Parks
Conservancy in partnership with the National Park Service.
She completed this study while a general pediatrics fellow at
UCSF.
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10 Journal of Attention Disorders
Joan F. Hilton, ScD, MPH, is a biostatistician and professor in the
Department of Epidemiology and Biostatistics at UCSF. Professor
Hilton researches methods for exact inference, teaches clinical
trial methods, and collaborates on a wide range of biomedical
topics.
Bonnie L. Halpern-Felsher is a developmental psychologist and
is currently a professor in adolescent medicine in the Department
of Pediatrics at Stanford University. Her research interests include
child, adolescent, and emerging adult development, as well as ado-
lescent and young adult health, risk behavior, risk perceptions,
decision making, and risk communication.
Holly E. Morrell, PhD, is a clinical psychologist and is cur-
rently an assistant professor in School of Behavioral Health,
Department of Psychology at Loma Linda University. Her inter-
ests are in health psychology and advanced statistics and
methodology.
Megumi J. Okumura, MD, is a combined internal medicine and
pediatrics physician, and assistant professor of pediatrics at UCSF.
Her research interests include children with special health care
needs, health care transitions from pediatrics to adult health care,
and chronic illness management.
Irene H. Yen, PhD MPH, is a social epidemiologist and associate
professor in the Department of Medicine at UCSF. Her research
expertise is in survey design and research methods. Her research
interests include social determinants of health, and neighborhood
influences on health behaviors and health status.
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