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research-article2014
JADXXX10.1177/1087054714542002Journal of Attention DisordersRazani et al.
Current Perspectives
Neighborhood Characteristics and ADHD: Results of a National Study
Journal of Attention Disorders 2015, Vol. 19(9) 731–740 © 2014 SAGE Publications Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1087054714542002 jad.sagepub.com
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. 2015; 19(9) 731-740) Keywords ADD/ADHD, childhood, parks, physical activity, neighborhood characteristics, parental functioning
Objective ADHD is the most commonly diagnosed psychiatric condition 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 interventional 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 prevalence of ADHD, and interestingly, correlated with sun exposure (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 neighborhood 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 perceived stress, anxiety, and depression (Lovell, Moss, & 1
University of California at San Francisco, CA, USA
Corresponding Author: Nooshin Razani, UCSF Benioff Children’s Hospital Oakland, 5220 Claremont Ave., Oakland, CA 94609, USA. Email: [email protected]
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Wetherell, 2012). Is it possible that improved social support at the neighborhood level will buffer the stresses associated with ADHD? Curtis et al. (2013) create a conceptual framework linking neighborhood conditions to mental health. This framework shows interplay between neighborhood physical characteristics and social factors that influence causal pathways in mental health. These neighborhood or communitylevel 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 characteristics and ADHD, while accounting for individual and family 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 support), plus physical characteristics such as sidewalks, libraries, recreation centers, parks, and disorder, are associated with ADHD prevalence. 2. These neighborhood social characteristics and physical characteristics are associated with ADHD severity. 3. These findings hold true after controlling for individual and family characteristics. We hypothesized that greater neighborhood social support 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 survey 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 conducted 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 children 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 following 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 environment were chosen based on previously recognized associations with ADHD, including race/ethnicity (non-Hispanic White, Hispanic, non-Hispanic Black, and Other; Merikangas 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 household, and other family structures), maternal education (greater than high school, high school, less than high school), and self-reported maternal mental health (excellent/very good, good, or fair/poor; Blackwell, 2010; Johnston & 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 several 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. 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.
categories are also consistent with scales of support, amenities, 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,” comprised four questions (Figure 1), with yes (1) or no (0) answers each. Nonmissing responses were summed to generate 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 generated, 1% had a missing value because one or more questions were missing.
Statistical Analysis We present the overall distributions of each of the neighborhood and family characteristics, as well as the distributions
of the family characteristics within each of the neighborhood characteristics (Table 1). We performed descriptive statistics on family characteristics and neighborhood characteristics 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 multivariate 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 logistic 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 conducted 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.
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Table 1. U.S. NSCH 2007 Results: Distributions of Family Characteristics, Overall and Within Level of Neighborhood Characteristics. Neighborhood characteristics Family characteristics
Support (%)
Amenities (%)
Full sample N = 64,076 (%) Low Medium High
Race/ethnicity White Hispanic Black Other Income as percentage of federal poverty level Greater than 400 200-400 Less than 200 Maternal education Greater than high school High school or equivalent Less than high school Maternal mental health Very good/excellent Good Poor/fair Family structure Two parent, biological or adoptive One parent Two parent, at least one step All others
None Some
Disorder (%) All
None Some All
57 19 15 8
29 33 31 7
56 20 16 9
69 13 10 8
64 18 12 6
60 19 13 7
55 18 17 10
61 18 13 8
50 23 17 10
34 24 32 9
30 33 37
8 19 74
29 33 38
40 34 26
18 33 49
28 33 39
34 32 33
35 33 31
18 32 50
10 25 66
62 26 12
35 39 26
62 26 12
68 23 9
49 34 17
59 27 14
67 25 9
66 24 10
54 31 15
40 38 23
71 21 8
43 27 29
69 22 8
82 15 4
62 27 11
69 22 9
74 19 7
74 20 6
64 24 12
54 27 19
63 20 10 7
37 44 11 8
62 20 10 7
71 14 10 6
62 18 10 10
63 20 10 7
62 20 10 7
66 18 10 7
57 24 11 7
42 36 14 8
Note. NSCH = National Survey of Children’s Health.
Neighborhood characteristics varied by socioeconomic status (Table 1). A higher proportion of White respondents reported higher Neighborhood Support (69%) than the proportion 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 caregivers 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 prevalence after adjusting for child, family, and other neighborhood variables (odds ratio [OR] = 1.66; 95% confidence intervals [CI] = [1.05, 2.63]). Neighborhood Disorder and Amenities were not associated with higher ADHD prevalence. 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 structures 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% moderate symptoms, and 13% were described as severe. Lower Neighborhood Support was associated with higher ADHD
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Razani et al. 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
Full sample Neighborhood characteristics Neighborhood support High Medium Low Neighborhood amenities All (4 of 4) Some (1-3 of 4) None (zero of 4) Neighborhood disorder None (zero of 3) Some (1-2 of 3) All (3 of 3) Family characteristics Race/ethnicity White (non-Hispanic) Hispanic Black (non-Hispanic) Other (non-Hispanic) Income as percentage of federal poverty level Greater than 400 200-400 Less than 200 Maternal education Greater than high school High school or equivalent Less than high school Maternal mental health Very good/excellent Good Poor/fair Family structure Two parent, biological/ adoptive One parent Two parents, step-parent All other family structures
Unadjusted
Adjusted
8
7 8 15
Ref 1.21 [1.03, 1.43] 2.28 [1.50, 3.48]
Ref 1.13 [0.94, 1.37] 1.66 [1.05, 2.63]
8 9 8
Ref 1.13 [0.98, 1.38] 1.06 [0.83, 1.36]
Ref 1.12 [0.96, 1.30] 0.90 [0.66, 1.24]
8 9 13
Ref 1.12 [0.95, 1.30] 1.78 [1.29, 2.47]
Ref 0.96 [0.81, 1.14] 1.43 [0.96, 2.15]
9 5 9 8
Ref 0.51 [0.39, 0.67] 1.00 [0.82, 1.21] 0.88 [0.69, 1.12]
Ref 0.44 [0.30, 0.65] 0.62 [0.48, 0.80] 0.81 [0.62, 1.07]
7 8 10
Ref 1.01 [0.84, 1.21] 1.36 [1.13, 1.63]
Ref 0.89 [0.73, 1.09] 1.09 [0.87, 1.38]
8 9 7
Ref 1.15 [0.98, 1.36] 0.91 [0.70, 1.16]
Ref 0.96 [0.80, 1.15] 0.69 [0.51, 0.93]
6 10 19
Ref 1.59 [1.34, 1.87] 3.42 [2.69, 4.35]
Ref 1.61 [1.34, 1.93] 3.03 [2.35, 3.91]
6
Ref
Ref
11 13 12
2.29 [1.93, 2.71] 1.99 [1.63, 2.43] 2.15 [1.72, 2.68]
1.93 [1.58, 2.36] 1.76 [1.42, 2.17] 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.
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 associated with higher odds of ADHD diagnosis and higher ADHD severity, even after taking into consideration age, sex, family, income, and other neighborhood characteristics. Neighborhood amenities and disorder were not statistically associated with ADHD prevalence or severity.
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Table 3. U.S. NSCH 2007 Results: ADHD Severity and Neighborhood, Family Characteristics (n = 4,290). Odds for increased ADHD severity OR (95% CI) Neighborhood characteristics Neighborhood support High Medium Low Neighborhood amenities All (4 of 4) Some (1-3 of 4) None (0 of 4) Neighborhood disorder None (zero of 3) Some (1-2 of 3) All (3 of 3) Family characteristics Race/ethnicity White (non-Hispanic) Hispanic Black (non-Hispanic) Other (non-Hispanic) Income as percentage of federal poverty level Greater than 400 200-400 Less than 200 Maternal education Greater than high school High school or equivalent Less than high school Maternal mental health Very good/excellent Good Poor/fair Family structure Two parent, biological/adoptive One parent Two parents, step-parent All other family structures
Unadjusted
Adjusted
Ref 1.37 [1.03, 1.83] 4.60 [2.76, 7.66]
Ref 1.22 [0.89, 1.66] 3.74 [1.71, 8.15]
Ref 1.73 [1.23, 2.45] 1.39 [1.07, 1.80]
Ref 1.27 [0.94, 1.70] 1.56 [0.91, 2.68]
Ref 1.38 [1.02, 1.86] 1.56 [0.81, 3.01]
Ref 1.05 [0.75, 1.48] 0.84 [0.42, 1.68]
Ref 0.69 [0.40, 1.18] 1.12 [0.77, 1.65] 1.40 [1.00, 1.94]
Ref 0.60 [0.34, 1.05] 0.74 [0.46, 1.18] 1.67 [0.96, 2.90]
Ref 1.77 [1.27, 2.47] 2.44 [1.74, 3.43]
Ref 1.77 [1.26, 2.49] 1.81 [1.15, 2.83]
Ref 1.48 [1.12, 1.97] 1.31 [0.75, 2.28]
Ref 0.99 [0.71, 1.38] 0.79 [0.42, 1.50]
Ref 1.66 [1.24, 2.24] 2.91 [1.90, 4.48]
Ref 1.33 [0.95, 1.87] 2.04 [1.22, 3.42]
Ref 1.69 [1.25, 2.29] 1.34 [0.91, 1.97] 1.13 [0.75, 1.68]
Ref 1.14 [0.77, 1.69] 0.95 [0.62, 1.45] 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.
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 neighborhood 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 networks have been associated with mood disorders, such that
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Razani et al. low social capital is associated with depression, anxiety, and schizophrenia (Whitley & McKenzie, 2005). The associations between neighborhood social conditions 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 comorbidities in this study, future research should investigate how depression, anxiety, and misconduct may mediate the relationship between neighborhood and ADHD. Modesto-Lowe et al. (2011) present a resilience framework 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, academic achievement, or classroom behavior, but peer relationships. 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 neighborhood 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 resilience 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, families 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 available 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 neighborhood 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 parents 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 children 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 follows, 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 neighborhood physical characteristics as surveyed in the NSCH. This finding dovetails with a variety of other work showing more pronounced effect for neighborhood social than physical 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 discounting the importance of physical characteristics in the neighborhood. 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 methodology did not ask parents to distinguish whether ADHD diagnoses 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 developmental pediatrician evaluation. Future investigations are needed to determine how parent, child, and investigator report of ADHD symptoms in a range of neighborhood environments would be useful in
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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 representative sample of noninstitutionalized children in the United States. This is the first nationally representative study of ADHD and neighborhood, family, and sociodemographic 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 perspective to ADHD, as finding neighborhood level correlates implies there are multiple levels of opportunity for intervention. 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.
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Razani et al. recommendation for the social capital initiative. Washington, DC: The World Bank. Hayton, J. C., Allen, D. G., & Scarpello, V. (2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel 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 recommendations 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.psyneuen.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 corollaries 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 guidelines 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, 4958. 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 mental 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 symptoms. 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 geneby-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). Attentiondeficit/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/hyperactivity disorder: Relationship among parenting stress, parental practices and child behaviour. Attention Deficit and Hyperactivity Disorders, 3, 61-68. doi:10.1007/s12402-0110053-3 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, 603651. doi:10.1086/210356 Taylor, A. F. (2001). Coping with ADD: The surprising connection 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 neighborhood 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 psychiatry: 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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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 adolescent and young adult health, risk behavior, risk perceptions, decision making, and risk communication. 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. Holly E. Morrell, PhD, is a clinical psychologist and is currently an assistant professor in School of Behavioral Health, Department of Psychology at Loma Linda University. Her interests are in health psychology and advanced statistics and methodology. 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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research-article2014
JADXXX10.1177/1087054714542002Journal of Attention DisordersRazani et al.
Current Perspectives
Neighborhood Characteristics and ADHD: Results of a National Study
Journal of Attention Disorders 2015, Vol. 19(9) 731–740 © 2014 SAGE Publications Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1087054714542002 jad.sagepub.com
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. 2015; 19(9) 731-740) Keywords ADD/ADHD, childhood, parks, physical activity, neighborhood characteristics, parental functioning
Objective ADHD is the most commonly diagnosed psychiatric condition 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 interventional 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 prevalence of ADHD, and interestingly, correlated with sun exposure (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 neighborhood 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 perceived stress, anxiety, and depression (Lovell, Moss, & 1
University of California at San Francisco, CA, USA
Corresponding Author: Nooshin Razani, UCSF Benioff Children’s Hospital Oakland, 5220 Claremont Ave., Oakland, CA 94609, USA. Email: [email protected]
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Wetherell, 2012). Is it possible that improved social support at the neighborhood level will buffer the stresses associated with ADHD? Curtis et al. (2013) create a conceptual framework linking neighborhood conditions to mental health. This framework shows interplay between neighborhood physical characteristics and social factors that influence causal pathways in mental health. These neighborhood or communitylevel 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 characteristics and ADHD, while accounting for individual and family 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 support), plus physical characteristics such as sidewalks, libraries, recreation centers, parks, and disorder, are associated with ADHD prevalence. 2. These neighborhood social characteristics and physical characteristics are associated with ADHD severity. 3. These findings hold true after controlling for individual and family characteristics. We hypothesized that greater neighborhood social support 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 survey 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 conducted 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 children 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 following 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 environment were chosen based on previously recognized associations with ADHD, including race/ethnicity (non-Hispanic White, Hispanic, non-Hispanic Black, and Other; Merikangas 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 household, and other family structures), maternal education (greater than high school, high school, less than high school), and self-reported maternal mental health (excellent/very good, good, or fair/poor; Blackwell, 2010; Johnston & 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 several 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. 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.
categories are also consistent with scales of support, amenities, 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,” comprised four questions (Figure 1), with yes (1) or no (0) answers each. Nonmissing responses were summed to generate 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 generated, 1% had a missing value because one or more questions were missing.
Statistical Analysis We present the overall distributions of each of the neighborhood and family characteristics, as well as the distributions
of the family characteristics within each of the neighborhood characteristics (Table 1). We performed descriptive statistics on family characteristics and neighborhood characteristics 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 multivariate 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 logistic 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 conducted 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.
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Table 1. U.S. NSCH 2007 Results: Distributions of Family Characteristics, Overall and Within Level of Neighborhood Characteristics. Neighborhood characteristics Family characteristics
Support (%)
Amenities (%)
Full sample N = 64,076 (%) Low Medium High
Race/ethnicity White Hispanic Black Other Income as percentage of federal poverty level Greater than 400 200-400 Less than 200 Maternal education Greater than high school High school or equivalent Less than high school Maternal mental health Very good/excellent Good Poor/fair Family structure Two parent, biological or adoptive One parent Two parent, at least one step All others
None Some
Disorder (%) All
None Some All
57 19 15 8
29 33 31 7
56 20 16 9
69 13 10 8
64 18 12 6
60 19 13 7
55 18 17 10
61 18 13 8
50 23 17 10
34 24 32 9
30 33 37
8 19 74
29 33 38
40 34 26
18 33 49
28 33 39
34 32 33
35 33 31
18 32 50
10 25 66
62 26 12
35 39 26
62 26 12
68 23 9
49 34 17
59 27 14
67 25 9
66 24 10
54 31 15
40 38 23
71 21 8
43 27 29
69 22 8
82 15 4
62 27 11
69 22 9
74 19 7
74 20 6
64 24 12
54 27 19
63 20 10 7
37 44 11 8
62 20 10 7
71 14 10 6
62 18 10 10
63 20 10 7
62 20 10 7
66 18 10 7
57 24 11 7
42 36 14 8
Note. NSCH = National Survey of Children’s Health.
Neighborhood characteristics varied by socioeconomic status (Table 1). A higher proportion of White respondents reported higher Neighborhood Support (69%) than the proportion 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 caregivers 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 prevalence after adjusting for child, family, and other neighborhood variables (odds ratio [OR] = 1.66; 95% confidence intervals [CI] = [1.05, 2.63]). Neighborhood Disorder and Amenities were not associated with higher ADHD prevalence. 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 structures 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% moderate symptoms, and 13% were described as severe. Lower Neighborhood Support was associated with higher ADHD
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Razani et al. 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
Full sample Neighborhood characteristics Neighborhood support High Medium Low Neighborhood amenities All (4 of 4) Some (1-3 of 4) None (zero of 4) Neighborhood disorder None (zero of 3) Some (1-2 of 3) All (3 of 3) Family characteristics Race/ethnicity White (non-Hispanic) Hispanic Black (non-Hispanic) Other (non-Hispanic) Income as percentage of federal poverty level Greater than 400 200-400 Less than 200 Maternal education Greater than high school High school or equivalent Less than high school Maternal mental health Very good/excellent Good Poor/fair Family structure Two parent, biological/ adoptive One parent Two parents, step-parent All other family structures
Unadjusted
Adjusted
8
7 8 15
Ref 1.21 [1.03, 1.43] 2.28 [1.50, 3.48]
Ref 1.13 [0.94, 1.37] 1.66 [1.05, 2.63]
8 9 8
Ref 1.13 [0.98, 1.38] 1.06 [0.83, 1.36]
Ref 1.12 [0.96, 1.30] 0.90 [0.66, 1.24]
8 9 13
Ref 1.12 [0.95, 1.30] 1.78 [1.29, 2.47]
Ref 0.96 [0.81, 1.14] 1.43 [0.96, 2.15]
9 5 9 8
Ref 0.51 [0.39, 0.67] 1.00 [0.82, 1.21] 0.88 [0.69, 1.12]
Ref 0.44 [0.30, 0.65] 0.62 [0.48, 0.80] 0.81 [0.62, 1.07]
7 8 10
Ref 1.01 [0.84, 1.21] 1.36 [1.13, 1.63]
Ref 0.89 [0.73, 1.09] 1.09 [0.87, 1.38]
8 9 7
Ref 1.15 [0.98, 1.36] 0.91 [0.70, 1.16]
Ref 0.96 [0.80, 1.15] 0.69 [0.51, 0.93]
6 10 19
Ref 1.59 [1.34, 1.87] 3.42 [2.69, 4.35]
Ref 1.61 [1.34, 1.93] 3.03 [2.35, 3.91]
6
Ref
Ref
11 13 12
2.29 [1.93, 2.71] 1.99 [1.63, 2.43] 2.15 [1.72, 2.68]
1.93 [1.58, 2.36] 1.76 [1.42, 2.17] 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.
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 associated with higher odds of ADHD diagnosis and higher ADHD severity, even after taking into consideration age, sex, family, income, and other neighborhood characteristics. Neighborhood amenities and disorder were not statistically associated with ADHD prevalence or severity.
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Table 3. U.S. NSCH 2007 Results: ADHD Severity and Neighborhood, Family Characteristics (n = 4,290). Odds for increased ADHD severity OR (95% CI) Neighborhood characteristics Neighborhood support High Medium Low Neighborhood amenities All (4 of 4) Some (1-3 of 4) None (0 of 4) Neighborhood disorder None (zero of 3) Some (1-2 of 3) All (3 of 3) Family characteristics Race/ethnicity White (non-Hispanic) Hispanic Black (non-Hispanic) Other (non-Hispanic) Income as percentage of federal poverty level Greater than 400 200-400 Less than 200 Maternal education Greater than high school High school or equivalent Less than high school Maternal mental health Very good/excellent Good Poor/fair Family structure Two parent, biological/adoptive One parent Two parents, step-parent All other family structures
Unadjusted
Adjusted
Ref 1.37 [1.03, 1.83] 4.60 [2.76, 7.66]
Ref 1.22 [0.89, 1.66] 3.74 [1.71, 8.15]
Ref 1.73 [1.23, 2.45] 1.39 [1.07, 1.80]
Ref 1.27 [0.94, 1.70] 1.56 [0.91, 2.68]
Ref 1.38 [1.02, 1.86] 1.56 [0.81, 3.01]
Ref 1.05 [0.75, 1.48] 0.84 [0.42, 1.68]
Ref 0.69 [0.40, 1.18] 1.12 [0.77, 1.65] 1.40 [1.00, 1.94]
Ref 0.60 [0.34, 1.05] 0.74 [0.46, 1.18] 1.67 [0.96, 2.90]
Ref 1.77 [1.27, 2.47] 2.44 [1.74, 3.43]
Ref 1.77 [1.26, 2.49] 1.81 [1.15, 2.83]
Ref 1.48 [1.12, 1.97] 1.31 [0.75, 2.28]
Ref 0.99 [0.71, 1.38] 0.79 [0.42, 1.50]
Ref 1.66 [1.24, 2.24] 2.91 [1.90, 4.48]
Ref 1.33 [0.95, 1.87] 2.04 [1.22, 3.42]
Ref 1.69 [1.25, 2.29] 1.34 [0.91, 1.97] 1.13 [0.75, 1.68]
Ref 1.14 [0.77, 1.69] 0.95 [0.62, 1.45] 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.
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 neighborhood 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 networks have been associated with mood disorders, such that
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Razani et al. low social capital is associated with depression, anxiety, and schizophrenia (Whitley & McKenzie, 2005). The associations between neighborhood social conditions 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 comorbidities in this study, future research should investigate how depression, anxiety, and misconduct may mediate the relationship between neighborhood and ADHD. Modesto-Lowe et al. (2011) present a resilience framework 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, academic achievement, or classroom behavior, but peer relationships. 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 neighborhood 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 resilience 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, families 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 available 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 neighborhood 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 parents 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 children 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 follows, 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 neighborhood physical characteristics as surveyed in the NSCH. This finding dovetails with a variety of other work showing more pronounced effect for neighborhood social than physical 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 discounting the importance of physical characteristics in the neighborhood. 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 methodology did not ask parents to distinguish whether ADHD diagnoses 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 developmental pediatrician evaluation. Future investigations are needed to determine how parent, child, and investigator report of ADHD symptoms in a range of neighborhood environments would be useful in
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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 representative sample of noninstitutionalized children in the United States. This is the first nationally representative study of ADHD and neighborhood, family, and sociodemographic 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 perspective to ADHD, as finding neighborhood level correlates implies there are multiple levels of opportunity for intervention. 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.
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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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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 adolescent and young adult health, risk behavior, risk perceptions, decision making, and risk communication. 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. Holly E. Morrell, PhD, is a clinical psychologist and is currently an assistant professor in School of Behavioral Health, Department of Psychology at Loma Linda University. Her interests are in health psychology and advanced statistics and methodology. 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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