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A better understanding of the role of both family- and neighborhood-level socioeconomic characteristics in the development of anxiety disorders is important for identifying salient target populations for intervention efforts. Little research has examined the question of whether associations between anxiety and socioeconomic status (SES) differ depending upon the level at which SES is measured or way in which anxiety manifests. We studied associations between both household- and neighborhood-level income and four different manifestations of anxiety in a community sample of young adolescents.
We conducted a cross-sectional analysis of data on 498 subjects aged 11–13 from a cohort study of Seattle-area middle school students. Generalized estimating equations were used to examine the association between both annual household income and neighborhood median income and each of four anxiety subscale scores from the multidimensional anxiety scale for children (MASC): physical symptoms, harm avoidance, social anxiety, and separation/panic anxiety.
A negative association was found between household income and scores on two of the four MASC subscales—physical symptoms and separation/panic anxiety. In contrast, at equivalent levels of household income, adolescents living in higher income neighborhoods reported higher physical and harm avoidance symptom scores.
The role that SES plays in the development of childhood anxiety appears to be complex and to differ depending on the specific type of anxiety that is manifest and whether income is evaluated at the household or neighborhood level.
The impact of household socioeconomic status (SES) (e.g. family income, education, and poverty status) on internalizing disorders such as anxiety, depression, and somatic problems is well documented in adult populations.[1,2] Although the mechanisms by which SES affects mental health outcomes are not fully understood, persons living in low-SES households suffer increased stress due to the daily strain of experiencing diminished material resources and reduced access to family, social and community supports, as well as from exposure to stressful events such as frequent moves, neighborhood violence, and/or changes in family structure.[1,3] While stress exposure increases risk for some anxiety disorders in adults,[4,5] few studies have focused on associations between SES and anxiety symptoms or disorders in children and adolescents.[6–15] Furthermore, prior studies with children that have examined this association have focused primarily on a broad, inclusive spectrum of anxiety symptoms or score, rather than distinctive manifestations of anxiety.
Childhood anxiety disorders are estimated to affect 4–7% of the U.S. child population.[16, 17] Anxiety symptoms typically first emerge in childhood or adolescence and may persist into adulthood. Like other mental health problems in children, anxiety emerges from a combination of individual characteristics (e.g. temperament, neurocognitive competencies), familial factors (e.g. genetic make-up, parenting style), and environmental factors (e.g. early life adversity, exposure to stressors).[4,5] Anxiety disorders in childhood can have severe emotional and health consequences, including long-term increased risk for other mental health conditions, adverse educational and social outcomes, nicotine dependence, chronic physical health problems, and increased risk of suicide attempts.[17, 19] Knowledge of conditions that place children at increased risk of anxiety disorders is useful for targeting and shaping intervention efforts.
Anxiety is a negative emotional state that is connected to the basic fear or “fight or flight” response that is induced by the presence of a stressor or threat. This normative and adaptive response is universal in nature and involves physiological, neural, cognitive, and behavioral aspects. Anxiety can manifest as fear or worry about a common life event, such as encountering a bully or taking a spelling test, or as more persistent and debilitating symptoms that manifest in response to or anticipation of mildly or severely stressing, isolated or repeated life events. Pathological anxiety results when an individual demonstrates amplified and prolonged reactivity in response to a perceived threat or stressor that exceeds the response warranted by the stimulus. Individuals with pathological anxiety may demonstrate altered patterns of cognitive, physiological, and neural responses to threat, including enhanced attention and processing of threat, elevated psychophysiologic reactivity to fear, and altered amygdala and hypothalamic-pituitary-adrenal axis functioning. The prevalence of pathological anxiety is somewhat stable across life stages; however the manifestation of symptoms and disorders often changes over the developmental course.[22, 23]
Researchers and clinicians measure pathological anxiety using both categorical and dimensional approaches. While work to date on the taxonomy of anxiety in the pediatric population provides limited support for the DSM-IV anxiety diagnostic categories, when a wide spectrum of common anxiety symptoms observed across the developmental span from early childhood through adolescence is subjected to factor analyses, distinctive clusters of emotional, cognitive, physical, and behavioral symptoms emerge. Four subtypes, including physical symptoms, harm avoidance (perfectionism), social anxiety, and separation/panic have been replicated in diverse samples of nonclinical and clinical youth.[26, 27] As Costello et al. note, different types of anxiety have different correlates and predictors over the course of development, as well as distinct peak periods of onset.
Prior research on the association between household or individual SES indicators and childhood anxiety has shown mixed results.[6–8] Miech et al. found that adolescents whose parents had a lower occupational status, education level, income, and composite SES score had a higher likelihood of having an anxiety disorder (overanxious disorder, separation anxiety, simple phobia, or social phobia). Ozer et al. found a significant negative association between maternal educational attainment, but not household income, and anxiety symptoms in a sample of rural Mexican adolescents. Cronk et al. showed low-household income to be associated with increased risk of separation anxiety disorder in a cohort of adolescent girls. This association was explained by parent absence. In contrast, recent results from the 2001–2004 National Health and Nutrition Examination Survey (NHANES) study showed that children from low-income households had a lower prevalence of anxiety disorders “than their wealthier counterparts.” These results are consistent with a comparison of emotional health status of suburban and inner city high school students, which showed affluent adolescents having significantly higher anxiety scores. Follow-up work suggested that high anxiety among affluent youth is related to achievement pressures and isolation from adults.[14, 15] Discrepant study findings may, in part, be attributed to the use of varied approaches for classifying adolescent anxiety and for measuring SES.
While household income reflects available family resources, neighborhood socioeconomic conditions reflect the availability of social and community resources, which have been hypothesized to affect mental well-being in both children and adults. The effects of neighborhood deprivation on depression outcomes have been demonstrated in several studies of adult populations. However, at least one study found no contextual effect of SES on severity of anxiety symptoms. Research exploring this association in children or adolescents is scarce and frequently focused broadly on internalizing disorders rather than anxiety specifically. Two observational studies found a significant positive association between neighborhood disadvantage and internalizing symptoms in community samples of children after adjusting for individual-level factors.[33, 34] Using data from the Moving to Opportunity study, Leventhal and Brooks-Gunn showed that boys, but not girls, in families randomly assigned to receive assistance to move from a high- to a low-poverty neighborhood demonstrated lower levels of anxiety and depression. However, a later analysis showed that girls who moved to low-poverty neighborhoods experienced a greater decline in both depressive and anxious symptoms than boys. To date, there has been little research on the joint or independent effects of family- and neighborhood-level SES on specific forms of anxiety problems in children. Some work suggests that household financial strain negatively affects parenting practices that could result in a conditioned stress response to low income. Youth who are exposed to high levels of stressors in their neighborhoods may demonstrate elevated separation anxiety due to perceptions that protection from danger is inadequate or elevated social anxiety due to poor access to social support from neighbors and access to opportunities and places for socializing. Given the different ways that anxiety is expressed in children and the different ways in which household and neighborhood socioeconomic context might affect children’s perceptions of safety and their levels of distress, we hypothesize that socioeconomic conditions measured at household and neighborhood levels will have differential effects on subtypes of anxiety.
While some previous research has explored how exposure to low household and neighborhood SES affects mental health in children and young adults, a better understanding of these exposures on different forms of childhood anxiety is warranted in light of known variations in predictors and correlates of specific anxiety subtypes. The current study addresses gaps in available literature by simultaneously investigating household and neighborhood income in relation to the occurrence of four subtypes of self-reported anxiety symptoms in young adolescents.
We conducted a cross-sectional secondary analysis of baseline data collected from the Developmental Pathways Project (DPP), a community-based longitudinal study of depression and conduct problems in adolescence. The Institutional Review Board of the University of Washington reviewed and approved the DPP study and the current project.
The DPP study design involved universal depression and conduct problem screening of students entering sixth grade in four Seattle, WA public schools followed by recruitment into the longitudinal study of a sample of students stratified on the basis of risk for mental health problems, with oversampling of those at elevated risk for depression and/or conduct problems. Of 811 eligible students, 521 (64.2%) enrolled, between 60 and 66% of those randomly selected from within each of four risk strata.
The current study sample included the 498 adolescents who completed an anxiety questionnaire and whose parent or guardian reported a King County, WA street address at the time of the baseline interview, conducted between 2002 and 2005.
Two measures of income were employed: (1) Household income (total wages, tips, social security income, unemployment, pension, welfare, and child support for all family members), originally reported by the primary caregiver in 10 income categories; and (2) Neighborhood income, defined as the median household income of a participant’s census tract derived by geocoding the respondent’s residence at the time of the baseline interview to tract-level data from the 2000 U.S. census. Household income is a commonly used indicator of SES that is reflective of accessibility to and availability of material resources that are believed to directly and indirectly influence health outcomes. Neighborhood median income at the census tract level has been found to be highly correlated with other census tract socioeconomic characteristics and also shows a strong gradient with various health indicators. Both income indicators were grouped into three categories, such that within-category sample size was maximized and possible effects of high and low income could be differentiated from those of middle income. Household income was categorized as <$35,000; $35,000–$74,999; and $75,000 or higher. Approximately one third of the sample was in each group. Neighborhood median income categories included less than $40,000, $40,000–59,999, and $60,000 or higher, representing approximately 25, 50, and 25% of the study participants, respectively. On average, 4.2 participants resided in each of 120 census tracts used in this analysis (range = 1–25).
Anxiety symptom subtypes were assessed using the multidimensional anxiety scale for children (MASC) completed by youth at the baseline interview. The MASC is a 39-item, self-report questionnaire, with response options on a 4-point Likert scale ranging from 0 (never true about me) to 3 (often true about me). Responses are summed to derive a total score, with higher scores reflecting higher anxiety. The MASC was developed empirically with the goal of collecting a cross-section of anxiety symptoms that have consistently concerned clinicians and researchers working with anxious children and adolescents. Factor analyses of a wide spectrum of anxiety symptoms yielded four clusters: physical symptoms (e.g. “I get shaky or jittery,” “my heart races or skips beats,” etc.), harm avoidance (e.g. “I try to do everything exactly right,” “I check things out first,” etc.), social anxiety (e.g. “I worry about other people laughing at me,” “I worry about getting called on in class,” etc.), and separation/panic (e.g. “I get scared when my parents go away,” “… the dark, heights, animals, or bugs scare me,” etc.). March and Parker reported that the four-factor model had excellent fit to data collected from both the clinical and nonclinical samples. The MASC has high test–retest reliability (.79 after 3 weeks, .93 after 3 months).[25, 42] Table 1 presents characteristics of the four subscales in this sample. Internal consistency for MASC subscales scores ranged from 0.70 (separation/panic) to 0.85 (social anxiety). Scores for harm avoidance, social anxiety, and separation/panic in the study sample were somewhat higher compared to scores observed in a large normative sample of youth ages of 8–19 years. However, mean physical symptoms score in our sample (7.0) was markedly lower than in the normative sample (11.0). The total anxiety score was not used in this study due to recent research with both adolescent and adult samples that calls into question the validity of anxiety as a unitary construct.[43, 44]
Demographic characteristics were also ascertained at the baseline interview: participant age, race (White, African American, Asian/Other), ethnicity (Hispanic, non-Hispanic), sex (male, female), and household size (<5, ≥5, or more adults and children).
All statistical analyses were conducted using SAS Version 9.2 for Windows (SAS Institute Inc., Cary, NC). To account for oversampling of adolescents who screened high for depression and conduct problems, and to make the sample representative of the general population of Seattle public middle school students, population weights derived for the DPP study were applied in all analysis.
Two-tailed t-tests and analysis of variance (ANOVA) tests were used to compare total MASC scores across sociodemographic groups. To account for possible correlation of observations within neighborhoods, generalized estimating equations (GEE) models with an exchangeable correlation structure were used to examine the association between income and anxiety scales. Separate regression models were estimated for each of the four anxiety subscales as the dependent variable. Each regression model included income measured at the household level and neighborhood level as the primary independent variables. Dummy variables were created for both household and neighborhood income with the highest income categories used as reference. All models were adjusted for the covariates described above, as well as school of attendance. In additional models, tests for trend to examine “dose-response” associations between increments in income level and anxiety scores were assessed by modeling the income variables as grouped linear terms (i.e. ordinal variables treated continuously). Finally, tests for interactions between gender and grouped linear terms for household and neighborhood income were assessed using Wald’s tests.
Table 2 shows MASC anxiety subscale scores across different demographic categories. Of the 498 study participants, approximately half were female (47%). Nearly half (49%) were white, 28% were African American and 23% were Asian or other race; 10% were of Hispanic ethnicity. Most (67%) resided in households of fewer than five members.
Findings from GEE regression models are shown in Table 3. In fully adjusted models, adolescents from low-compared to high-income households had significantly elevated physical anxiety symptom scores (b = 2.03; P = .01). There was no statistically significant difference in physical symptoms score between adolescents residing in medium- and high-income households (b = 0.41; P = .49); however, the test for trend across the income categories was statistically significant (P = .006). Compared to adolescents in high-income households, separation/panic symptom scores were also elevated in both the middle (b = 1.41; P = .01) and low (b = 1.81; P = .01) income groups, and the trend was statistically significant (P = .007). We observe no statistically significant differences among household income groups for either the harm avoidance or social anxiety subscales. There was a statistically significant interaction between gender and household income for the social anxiety subscale (P = .007). When stratifying by gender (Table 4), there was a marginally elevated social anxiety score among females in low-income households compared to those in high-income households (b = 1.65, P = .10), while males in low-income households had a lower, but nonsignificant, social anxiety score compared to males in high-income households (b = −0.73, P = .52). No statistically significant gender × household income interactions were observed for the other three subscales.
A different pattern emerged for neighborhood income, particularly for physical symptoms. In the fully adjusted regression model, physical anxiety symptoms were lower among adolescents in the low compared to those in the high neighborhood income group (b = −2.19; P = .01), with a significant test for trend across the three neighborhood income categories (P = .008). Additionally, adolescents in the middle neighborhood income group had a reduced mean harm avoidance score compared to those in the high neighborhood income group (b = 1.02; P = .03). There were no significant differences in either the social anxiety or separation/panic subscales among the neighborhood income groups. There were no statistically significant interactions between neighborhood income and gender for any of the anxiety subscales.
Our study found that annual household income and average neighborhood income were associated with different types of childhood anxiety and that some associations were positive, while others were negative. Specifically, at equivalent levels of neighborhood income, lower household income was associated with higher levels of physical and separation/panic symptoms. In contrast, at equivalent levels of household income, compared to those living in higher income neighborhoods adolescents living in lower income neighborhoods demonstrated lower physical anxiety, and those living in middle-income neighborhoods demonstrated lower harm avoidance symptoms. A stronger negative association between household income and social anxiety symptoms was observed in girls than in boys.
Our findings regarding associations between low household income and higher physical and separation/panic anxiety subscales scores are consistent with a growing body of evidence suggesting that poor mental and physical health outcomes are more prevalent in children from low-SES families.[3,7–9] Economic hardship is shown to increase risk for a number of family characteristics that are likely to be associated more strongly with certain subtypes of anxiety reactions than others. Consistent with the Family Stress Model outlined by Conger and colleagues, economic distress can lead to parental depression, as well as low parental nurturing, involvement, and supervision, which could, in turn, increase risk for separation/panic anxiety symptoms. Youth exposed to economic strain have been shown to demonstrate impaired coping, suggesting that economic conditions may interfere with the development and or utilization of efficacious management of stress.[47, 48] In our sample, girls living in low-income households demonstrated elevated social anxiety compared to girls living in high-income households. In addition to the general impact of low income on anxiety and social problems, at this developmental stage, girls’ increased sensitivity to peer approval and social comparison[50, 51] could exacerbate the effects of income discrepancies on social anxiety symptoms.
In contrast, significant associations between lower neighborhood income and lower physical anxiety and harm avoidance scores after controlling for household income are not consistent with previous research on this subject.[33, 34] However, these findings may be consistent with “group density” theories that have been proposed to explain the tendency for individuals of disadvantaged economic status to demonstrate better mental and physical health outcomes when living in areas where most residents share similar disadvantaged status.[52, 53] Likewise, within low-income neighborhoods there is generally less income inequality, which has been hypothesized to affect health through invidious comparisons, increased feelings of inadequacy, stress, and anxiety.[54, 55]
The contrasting findings regarding physical anxiety in relation to household versus neighborhood income may be idiosyncratic to this sample but may also suggest that household or familial risk factors such as genetic propensity toward anxiety and/or parental ability to buffer a child from stressors may contribute more to a child’s vulnerability to heightened physiological responses to stress than do neighborhood factors. Future research on possible interactive effects between household and neighborhood income may be informative in determining their influence on mental health. For example, it is possible that effects of household income could be magnified within certain neighborhood contexts. In our sample, we were underpowered to statistically test the household × neighborhood interaction effects. Future studies with larger sample sizes are needed to better understand these potential interactions and the mechanisms through which household and neighborhood factors related to socioeconomic conditions affect the emergence of specific types of childhood anxiety.
It is likely that much of the confusion in the literature about the prevalence and correlates of anxiety disorders has been spawned by the tendency to evaluate anxiety as a unitary construct. Our study may be the first to consider specific anxiety subtypes in association with household income and neighborhood disadvantage. Our findings can help explain some of the discrepancies among prior study findings that used broader measures of anxiety or internalizing problems. A few other researchers have found that different manifestations of anxiety vary in their associations with specific correlates or outcomes. Kaplow et al. demonstrated in the Great Smoky Mountains Study that an apparent lack of association between alcohol use and anxiety disorders, in general, resulted from two contradictory processes. Children with generalized anxiety disorder were more likely, while children with separation anxiety disorder were less likely, than other children to use alcohol. Research on the MASC subtypes per se is limited, but initial findings support the fact that the subtypes of anxiety act independently. Killgore and Yurgelun-Todd found differential amygdala activation corresponding with responses on the social but not the nonsocial anxiety subscales among youth exposed to facial expressions of fear and happiness. Given the lack of specificity with regard to heritability of anxiety, our results suggest hypotheses that, if tested, may add to our current understanding of how biological risk interacts with environmental exposures to contribute to distinct manifestations of anxiety symptoms and disorders in children and adolescents. For example, one hypothesis suggested by our results is that elevations in physical and separation/panic symptoms are conditional on a genetic predisposition for somatic manifestations of anxiety, such as accelerated heart rate and increased cortisol level. It may be that youth with this physiological profile are more likely than peers to have their somatic responses potentiated by stressors characteristic of families with low household income, such as parent absence or low parental involvement.
This study had several limitations. First, the true effect of neighborhood income on childhood anxiety may be of greater magnitude or significance depending on the spatial scale, although a 2002 review of neighborhood research found choice of unit to not significantly affect empirical results. In addition, other neighborhood characteristics such as unemployment or percent poverty may add other information that could provide a fuller characterization of neighborhood socioeconomic conditions beyond neighborhood income alone. Study setting and sample may limit generalizability. Studies conducted in other geographic regions of the United States may yield different results. Also, the emotional health of children at different stages of development may be more or less affected by neighborhood and household economic conditions. Larger study samples would enable finer tuned examination of the effects of disparities between household and neighborhood socioeconomic conditions and children’s mental health status, including interactions among factors. The current study is also limited by its focus on anxiety symptoms in isolation from other forms of psychopathology. Given the common occurrence of comorbid conditions,[61, 62] it will be important for future investigations to consider how household and neighborhood conditions affect co-occurring anxiety disorders, as well as anxiety that is comorbid with depression and substance abuse. Finally, as with other epidemiologic studies of social determinants of health, although broad brushstroke conclusions point to future productive lines of inquiry, zeroing in on the salient causal mechanisms must be left to future work. Consideration of factors, such as parental education, social capital, parental absence, parental mental health status, or neighborhood safety as potential explanatory variables will enable a deeper understanding of mechanisms underlying risk of mental health problems that can guide public health action.
This study capitalized on a unique opportunity to examine associations among a set of individual, family, and neighborhood-level conditions within a fairly large, racially diverse community sample, and offers intriguing clues that set the stage for further research to increase our understanding of how environmental conditions affect the risk of mental health problems. While most prior epidemiologic research on this topic has considered a general “anxiety” outcome, we evaluated four specific anxiety subtypes. The study provides evidence that both household- and neighborhood-level socioeconomic factors may play differing roles in the development of anxiety problems depending on the specific subtype. Future studies should carry forward the practice of examining distinct manifestations of childhood anxiety, recruit larger samples to achieve adequate power for follow-up on potential modification of the effects of household income by neighborhood SES, utilize longitudinal designs to better explicate temporal sequence, and measure additional features of households and neighborhoods to elucidate causal mechanisms.
Contract grant sponsor: National Institutes of Mental Health and Drug Abuse Contract grant number: R01 MH63711. Contract grant sponsor: National Institutes of Health; Contract grant number: T32 HD052462
Conflict of interests: None.